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overflow: hidden; text-overflow: ellipsis; -webkit-line-clamp: 3; -webkit-box-orient: vertical; }</style><div class="col-xs-12 clearfix"><div class="u-floatLeft"><h1 class="PageHeader-title u-m0x u-fs30">Fractal Analysis</h1><div class="u-tcGrayDark">1,648 Followers</div><div class="u-tcGrayDark u-mt2x">Recent papers in <b>Fractal Analysis</b></div></div></div></div></div></div><div class="TabbedNavigation"><div class="container"><div class="row"><div class="col-xs-12 clearfix"><ul class="nav u-m0x u-p0x list-inline u-displayFlex"><li class="active"><a href="https://www.academia.edu/Documents/in/Fractal_Analysis">Top Papers</a></li><li><a href="https://www.academia.edu/Documents/in/Fractal_Analysis/MostCited">Most Cited Papers</a></li><li><a href="https://www.academia.edu/Documents/in/Fractal_Analysis/MostDownloaded">Most Downloaded Papers</a></li><li><a href="https://www.academia.edu/Documents/in/Fractal_Analysis/MostRecent">Newest Papers</a></li><li><a class="" href="https://www.academia.edu/People/Fractal_Analysis">People</a></li></ul></div><style type="text/css">ul.nav{flex-direction:row}@media(max-width: 567px){ul.nav{flex-direction:column}.TabbedNavigation li{max-width:100%}.TabbedNavigation li.active{background-color:var(--background-grey, #dddde2)}.TabbedNavigation li.active:before,.TabbedNavigation li.active:after{display:none}}</style></div></div></div><div class="container"><div class="row"><div class="col-xs-12"><div class="u-displayFlex"><div class="u-flexGrow1"><div class="works"><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_70207328" data-work_id="70207328" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/70207328/Reconstruction_of_satellite_images_based_on_fractal_filters">Reconstruction of satellite images based on fractal filters</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Receiving of remote sensed data&amp;#39;s signals in urban space information reception centers is usually difficult, because of complex electromagnetic situation in cities and insufficient EMC. Traditional methods for digital... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_70207328" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Receiving of remote sensed data&amp;#39;s signals in urban space information reception centers is usually difficult, because of complex electromagnetic situation in cities and insufficient EMC. Traditional methods for digital reconstruction of images use smoothing and autoregressive forecasting. In this case anomalous spikes on the image are lost. Alternative method based on Kolmogorov-Wiener&amp;#39;s filters and fractal properties of satellite images is</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/70207328" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="213594000" href="https://independent.academia.edu/MeshkovI">Ivan Meshkov</a><script data-card-contents-for-user="213594000" type="text/json">{"id":213594000,"first_name":"Ivan","last_name":"Meshkov","domain_name":"independent","page_name":"MeshkovI","display_name":"Ivan Meshkov","profile_url":"https://independent.academia.edu/MeshkovI?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_70207328 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="70207328"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 70207328, container: ".js-paper-rank-work_70207328", }); 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Traditional methods for digital reconstruction of images use smoothing and autoregressive forecasting. In this case anomalous spikes on the image are lost. Alternative method based on Kolmogorov-Wiener\u0026amp;#39;s filters and fractal properties of satellite images is","downloadable_attachments":[],"ordered_authors":[{"id":213594000,"first_name":"Ivan","last_name":"Meshkov","domain_name":"independent","page_name":"MeshkovI","display_name":"Ivan Meshkov","profile_url":"https://independent.academia.edu/MeshkovI?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":507,"name":"Electromagnetism","url":"https://www.academia.edu/Documents/in/Electromagnetism?f_ri=160248","nofollow":false},{"id":1252,"name":"Remote Sensing","url":"https://www.academia.edu/Documents/in/Remote_Sensing?f_ri=160248","nofollow":false},{"id":5560,"name":"Electromagnetic Compatibility","url":"https://www.academia.edu/Documents/in/Electromagnetic_Compatibility?f_ri=160248","nofollow":false},{"id":12115,"name":"Optical Communication","url":"https://www.academia.edu/Documents/in/Optical_Communication?f_ri=160248","nofollow":false},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248"},{"id":157036,"name":"Urban Space","url":"https://www.academia.edu/Documents/in/Urban_Space?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":172625,"name":"Fractal","url":"https://www.academia.edu/Documents/in/Fractal?f_ri=160248"},{"id":225304,"name":"Smoothing","url":"https://www.academia.edu/Documents/in/Smoothing?f_ri=160248"},{"id":1707689,"name":"Pixel","url":"https://www.academia.edu/Documents/in/Pixel?f_ri=160248"},{"id":4041490,"name":"Satellite Image","url":"https://www.academia.edu/Documents/in/Satellite_Image?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_63498377" data-work_id="63498377" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/63498377/An_efficient_one_dimensional_fractal_analysis_for_iris_recognition">An efficient one-dimensional fractal analysis for iris recognition</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">An iris recognition system is proposed in this paper. This system implements (a) the combination of proposed black hole search method and integro-differential operators for iris localization,(b) one-dimensional fractal analysis for... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_63498377" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">An iris recognition system is proposed in this paper. This system implements (a) the combination of proposed black hole search method and integro-differential operators for iris localization,(b) one-dimensional fractal analysis for feature extraction and (c) dissimilarity operator for matching. The black hole search method achieves 100% accuracy of pupil detection for both CASIA and MMU Iris databases. Experiment results show that the proposed system has an encouraging result with low EER to 4.63% in CASIA iris ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/63498377" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="db7d7c406053ac537d7b98982b055fb7" rel="nofollow" data-download="{"attachment_id":75910582,"asset_id":63498377,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/75910582/download_file?st=MTczMjY4MTg0Nyw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="125496595" href="https://mmu-my.academia.edu/ChuanChinTeo">Chuan Chin Teo</a><script data-card-contents-for-user="125496595" type="text/json">{"id":125496595,"first_name":"Chuan Chin","last_name":"Teo","domain_name":"mmu-my","page_name":"ChuanChinTeo","display_name":"Chuan Chin Teo","profile_url":"https://mmu-my.academia.edu/ChuanChinTeo?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_63498377 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="63498377"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 63498377, container: ".js-paper-rank-work_63498377", }); 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This system implements (a) the combination of proposed black hole search method and integro-differential operators for iris localization,(b) one-dimensional fractal analysis for feature extraction and (c) dissimilarity operator for matching. The black hole search method achieves 100% accuracy of pupil detection for both CASIA and MMU Iris databases. Experiment results show that the proposed system has an encouraging result with low EER to 4.63% in CASIA iris ...","downloadable_attachments":[{"id":75910582,"asset_id":63498377,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":125496595,"first_name":"Chuan Chin","last_name":"Teo","domain_name":"mmu-my","page_name":"ChuanChinTeo","display_name":"Chuan Chin Teo","profile_url":"https://mmu-my.academia.edu/ChuanChinTeo?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics?f_ri=160248","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=160248","nofollow":false},{"id":160144,"name":"Feature Extraction","url":"https://www.academia.edu/Documents/in/Feature_Extraction?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":235060,"name":"Black Hole","url":"https://www.academia.edu/Documents/in/Black_Hole?f_ri=160248"},{"id":871638,"name":"IRIS RECOGNITION","url":"https://www.academia.edu/Documents/in/IRIS_RECOGNITION?f_ri=160248"},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_9927209 coauthored" data-work_id="9927209" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/9927209/Metabolism_and_cell_shape_in_cancer_A_fractal_analysis">Metabolism and cell shape in cancer: A fractal analysis</a></div></div><div 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Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="10866" href="https://www.academia.edu/Documents/in/Morphology">Morphology</a>, <script data-card-contents-for-ri="10866" type="text/json">{"id":10866,"name":"Morphology","url":"https://www.academia.edu/Documents/in/Morphology?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="12597" href="https://www.academia.edu/Documents/in/Crystallization">Crystallization</a><script data-card-contents-for-ri="12597" type="text/json">{"id":12597,"name":"Crystallization","url":"https://www.academia.edu/Documents/in/Crystallization?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=27908106]'), work: {"id":27908106,"title":"Fractal Analysis of Ice Crystals in Frozen 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Chemistry","url":"https://www.academia.edu/Documents/in/Agricultural_and_Food_Chemistry?f_ri=160248"},{"id":1029221,"name":"Freezing","url":"https://www.academia.edu/Documents/in/Freezing?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_31800241" data-work_id="31800241" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/31800241/Fractal_patterns_of_fractures_in_granites">Fractal patterns of fractures in granites</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Fractal measurements using the Cantor's dust method in a linear one-dimensional analysis mode were made on the fracture patterns revealed on two-dimensional, planar surfaces in four granites. This method allows one to conclude that: (1)... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_31800241" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Fractal measurements using the Cantor's dust method in a linear one-dimensional analysis mode were made on the fracture patterns revealed on two-dimensional, planar surfaces in four granites. This method allows one to conclude that: (1) The fracture systems seen on two-dimensional surfaces in granites are consistent with the part of fractal theory that predicts a repetition of patterns on different scales of observation, self similarity. Fractal analysis gives essentially the same values of D on the scale of kilometres, metres and centimetres (five orders of magnitude) using mapped, surface fracture patterns in a Sierra Nevada granite batholith (Mt. Abbot quadrangle, Calif.). (2) Fractures show the same fractal values at different depths in a given batholith. Mapped fractures (main stage ore veins) at three mining levels (over a 700 m depth interval) of the Boulder batholith, Butte, Mont. show the same fractal values although the fracture disposition appears to be different at different levels. (3) Different sets of fracture planes in a granite batholith, Central France, and in experimental deformation can have different fractal values. In these examples shear and tension modes have the same fractal values while compressional fractures follow a different fractal mode of failure. The composite fracture patterns are also fractal but with a different, median, fractal value compared to the individual values for the fracture plane sets. These observations indicate that the fractal method can possibly be used to distinguish fractures of different origins in a complex system. It is concluded that granites fracture in a fractal manner which can be followed at many scales. It appears that fracture planes of different origins can be characterized using linear fractal analysis.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/31800241" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="63d62fba5251220048ee4c1bc86ff6ed" rel="nofollow" data-download="{"attachment_id":52099526,"asset_id":31800241,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/52099526/download_file?st=MTczMjY4MTg0Nyw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="61297720" href="https://independent.academia.edu/BruceVelde">Bruce Velde</a><script data-card-contents-for-user="61297720" type="text/json">{"id":61297720,"first_name":"Bruce","last_name":"Velde","domain_name":"independent","page_name":"BruceVelde","display_name":"Bruce Velde","profile_url":"https://independent.academia.edu/BruceVelde?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_31800241 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="31800241"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 31800241, container: ".js-paper-rank-work_31800241", }); 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This method allows one to conclude that: (1) The fracture systems seen on two-dimensional surfaces in granites are consistent with the part of fractal theory that predicts a repetition of patterns on different scales of observation, self similarity. Fractal analysis gives essentially the same values of D on the scale of kilometres, metres and centimetres (five orders of magnitude) using mapped, surface fracture patterns in a Sierra Nevada granite batholith (Mt. Abbot quadrangle, Calif.). (2) Fractures show the same fractal values at different depths in a given batholith. Mapped fractures (main stage ore veins) at three mining levels (over a 700 m depth interval) of the Boulder batholith, Butte, Mont. show the same fractal values although the fracture disposition appears to be different at different levels. (3) Different sets of fracture planes in a granite batholith, Central France, and in experimental deformation can have different fractal values. In these examples shear and tension modes have the same fractal values while compressional fractures follow a different fractal mode of failure. The composite fracture patterns are also fractal but with a different, median, fractal value compared to the individual values for the fracture plane sets. These observations indicate that the fractal method can possibly be used to distinguish fractures of different origins in a complex system. It is concluded that granites fracture in a fractal manner which can be followed at many scales. It appears that fracture planes of different origins can be characterized using linear fractal analysis.","downloadable_attachments":[{"id":52099526,"asset_id":31800241,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":61297720,"first_name":"Bruce","last_name":"Velde","domain_name":"independent","page_name":"BruceVelde","display_name":"Bruce Velde","profile_url":"https://independent.academia.edu/BruceVelde?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":400,"name":"Earth Sciences","url":"https://www.academia.edu/Documents/in/Earth_Sciences?f_ri=160248","nofollow":false},{"id":2923,"name":"Methodology","url":"https://www.academia.edu/Documents/in/Methodology?f_ri=160248","nofollow":false},{"id":6637,"name":"Fracture","url":"https://www.academia.edu/Documents/in/Fracture?f_ri=160248","nofollow":false},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false},{"id":54501,"name":"Complex System","url":"https://www.academia.edu/Documents/in/Complex_System?f_ri=160248"},{"id":59579,"name":"Dimensional Analysis","url":"https://www.academia.edu/Documents/in/Dimensional_Analysis?f_ri=160248"},{"id":76052,"name":"Depth","url":"https://www.academia.edu/Documents/in/Depth?f_ri=160248"},{"id":118582,"name":"Physical sciences","url":"https://www.academia.edu/Documents/in/Physical_sciences?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":172625,"name":"Fractal","url":"https://www.academia.edu/Documents/in/Fractal?f_ri=160248"},{"id":588515,"name":"Sierra Nevada","url":"https://www.academia.edu/Documents/in/Sierra_Nevada?f_ri=160248"},{"id":775583,"name":"Shear","url":"https://www.academia.edu/Documents/in/Shear?f_ri=160248"},{"id":965094,"name":"Origin","url":"https://www.academia.edu/Documents/in/Origin?f_ri=160248"},{"id":976618,"name":"Igneous Rocks","url":"https://www.academia.edu/Documents/in/Igneous_Rocks?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_11855281" data-work_id="11855281" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/11855281/Nonlinear_dynamics_of_EEG_signal_reveals_influence_of_magnetic_field_on_the_brain">Nonlinear dynamics of EEG-signal reveals influence of magnetic field on the brain</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/11855281" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="e049ba2290d4c019ffb6207fa1d132e2" rel="nofollow" data-download="{"attachment_id":37249913,"asset_id":11855281,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/37249913/download_file?st=MTczMjY4MTg0Nyw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="29268562" href="https://sgh-pl.academia.edu/WlodzimierzKlonowski">Wlodzimierz Klonowski</a><script data-card-contents-for-user="29268562" type="text/json">{"id":29268562,"first_name":"Wlodzimierz","last_name":"Klonowski","domain_name":"sgh-pl","page_name":"WlodzimierzKlonowski","display_name":"Wlodzimierz Klonowski","profile_url":"https://sgh-pl.academia.edu/WlodzimierzKlonowski?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_11855281 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="11855281"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 11855281, container: ".js-paper-rank-work_11855281", }); 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To better understand microglia function in neurological disease, it is important to identify and quantify microglia... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_47130372" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In pathological brain, a variety of morphological forms exist that reflect differences in functional requirements. To better understand microglia function in neurological disease, it is important to identify and quantify microglia morphology associated with specific neuropathologies. Traditional feature parameters such as area or cell diameter are not sufficient. In this study microglia were quantified by the box-counting fractal dimension (DB). One hundred and four cells from post-mortem tissue were analyzed comprising cells of controls, Alzheimer&#39;s disease, schizophrenia and affective disorder. The DB was significantly different from the control (1.36) compared to schizophrenia (1.41), Alzheimer&#39;s disease (1.41) and affective disorder (1.43) with p &lt; 0.01. Thus fractal analysis provides a useful quantitative and objective measure of microglial form associated with normal function and diverse neuropathology. The distribution of fractal dimensions associated with microgli...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/47130372" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="394e7dab49e5d4a6e67f17ba5a345f32" rel="nofollow" data-download="{"attachment_id":66386448,"asset_id":47130372,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/66386448/download_file?st=MTczMjY4MTg0Nyw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32292318" href="https://oxford.academia.edu/AlastairBuchan">Alastair Buchan</a><script data-card-contents-for-user="32292318" type="text/json">{"id":32292318,"first_name":"Alastair","last_name":"Buchan","domain_name":"oxford","page_name":"AlastairBuchan","display_name":"Alastair Buchan","profile_url":"https://oxford.academia.edu/AlastairBuchan?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_47130372 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="47130372"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 47130372, container: ".js-paper-rank-work_47130372", }); 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To better understand microglia function in neurological disease, it is important to identify and quantify microglia morphology associated with specific neuropathologies. Traditional feature parameters such as area or cell diameter are not sufficient. In this study microglia were quantified by the box-counting fractal dimension (DB). One hundred and four cells from post-mortem tissue were analyzed comprising cells of controls, Alzheimer\u0026#39;s disease, schizophrenia and affective disorder. The DB was significantly different from the control (1.36) compared to schizophrenia (1.41), Alzheimer\u0026#39;s disease (1.41) and affective disorder (1.43) with p \u0026lt; 0.01. Thus fractal analysis provides a useful quantitative and objective measure of microglial form associated with normal function and diverse neuropathology. The distribution of fractal dimensions associated with microgli...","downloadable_attachments":[{"id":66386448,"asset_id":47130372,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":32292318,"first_name":"Alastair","last_name":"Buchan","domain_name":"oxford","page_name":"AlastairBuchan","display_name":"Alastair Buchan","profile_url":"https://oxford.academia.edu/AlastairBuchan?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":305,"name":"Applied Mathematics","url":"https://www.academia.edu/Documents/in/Applied_Mathematics?f_ri=160248","nofollow":false},{"id":318,"name":"Mathematical 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class="InlineList-item-text" data-has-card-for-ri="357230" href="https://www.academia.edu/Documents/in/Quantum_Interference">Quantum Interference</a>, <script data-card-contents-for-ri="357230" type="text/json">{"id":357230,"name":"Quantum Interference","url":"https://www.academia.edu/Documents/in/Quantum_Interference?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="421049" href="https://www.academia.edu/Documents/in/Classical_Limit">Classical Limit</a><script data-card-contents-for-ri="421049" type="text/json">{"id":421049,"name":"Classical Limit","url":"https://www.academia.edu/Documents/in/Classical_Limit?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17957412]'), work: {"id":17957412,"title":"Fractal Magneto-conductance Fluctuations in Mesoscopic Semiconductor Billiards","created_at":"2015-11-08T07:39:30.165-08:00","url":"https://www.academia.edu/17957412/Fractal_Magneto_conductance_Fluctuations_in_Mesoscopic_Semiconductor_Billiards?f_ri=160248","dom_id":"work_17957412","summary":null,"downloadable_attachments":[{"id":39799124,"asset_id":17957412,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37878759,"first_name":"Adam","last_name":"Micolich","domain_name":"independent","page_name":"AdamMicolich","display_name":"Adam Micolich","profile_url":"https://independent.academia.edu/AdamMicolich?f_ri=160248","photo":"https://gravatar.com/avatar/e3ebc704f12570e926eb2660d594af0c?s=65"}],"research_interests":[{"id":115917,"name":"Chaotic Dynamics","url":"https://www.academia.edu/Documents/in/Chaotic_Dynamics?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":357230,"name":"Quantum Interference","url":"https://www.academia.edu/Documents/in/Quantum_Interference?f_ri=160248","nofollow":false},{"id":421049,"name":"Classical Limit","url":"https://www.academia.edu/Documents/in/Classical_Limit?f_ri=160248","nofollow":false},{"id":424714,"name":"Quantum Hall Effect","url":"https://www.academia.edu/Documents/in/Quantum_Hall_Effect?f_ri=160248"},{"id":510924,"name":"Ballistic Transport","url":"https://www.academia.edu/Documents/in/Ballistic_Transport?f_ri=160248"},{"id":616972,"name":"Low Temperature","url":"https://www.academia.edu/Documents/in/Low_Temperature?f_ri=160248"},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248"},{"id":1237922,"name":"Energy Levels","url":"https://www.academia.edu/Documents/in/Energy_Levels?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17792070" data-work_id="17792070" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17792070/Synthesis_for_handwriting_analysis">Synthesis for handwriting analysis</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17792070" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8569f37e027f0856c8c692f2b20f1f93" rel="nofollow" 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type="text/json">{"id":37716280,"first_name":"Nicole","last_name":"Vincent","domain_name":"independent","page_name":"NicoleVincent","display_name":"Nicole Vincent","profile_url":"https://independent.academia.edu/NicoleVincent?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_17792070 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="17792070"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 17792070, container: ".js-paper-rank-work_17792070", }); });</script></li><li class="js-percentile-work_17792070 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 17792070; 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Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="43619" href="https://www.academia.edu/Documents/in/Feature_Selection">Feature Selection</a>, <script data-card-contents-for-ri="43619" type="text/json">{"id":43619,"name":"Feature Selection","url":"https://www.academia.edu/Documents/in/Feature_Selection?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="155958" href="https://www.academia.edu/Documents/in/Pattern_Matching">Pattern Matching</a><script data-card-contents-for-ri="155958" type="text/json">{"id":155958,"name":"Pattern Matching","url":"https://www.academia.edu/Documents/in/Pattern_Matching?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17792070]'), work: {"id":17792070,"title":"Synthesis for handwriting analysis","created_at":"2015-11-05T06:18:42.773-08:00","url":"https://www.academia.edu/17792070/Synthesis_for_handwriting_analysis?f_ri=160248","dom_id":"work_17792070","summary":null,"downloadable_attachments":[{"id":39713852,"asset_id":17792070,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37716280,"first_name":"Nicole","last_name":"Vincent","domain_name":"independent","page_name":"NicoleVincent","display_name":"Nicole Vincent","profile_url":"https://independent.academia.edu/NicoleVincent?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science?f_ri=160248","nofollow":false},{"id":5109,"name":"Pattern Recognition","url":"https://www.academia.edu/Documents/in/Pattern_Recognition?f_ri=160248","nofollow":false},{"id":43619,"name":"Feature Selection","url":"https://www.academia.edu/Documents/in/Feature_Selection?f_ri=160248","nofollow":false},{"id":155958,"name":"Pattern Matching","url":"https://www.academia.edu/Documents/in/Pattern_Matching?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":403149,"name":"Iterated Function System","url":"https://www.academia.edu/Documents/in/Iterated_Function_System?f_ri=160248"},{"id":1237788,"name":"Electrical And Electronic Engineering","url":"https://www.academia.edu/Documents/in/Electrical_And_Electronic_Engineering?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_71234092" data-work_id="71234092" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/71234092/The_Broken_Past_Fractals_in_Archaeology">The Broken Past: Fractals in Archaeology</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/71234092" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="bf6c040b810da4a0bf219ae7bc664a9e" rel="nofollow" data-download="{"attachment_id":80667822,"asset_id":71234092,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/80667822/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="135319" href="https://longwood.academia.edu/WalterWitschey">Walter R T Witschey, Sr.</a><script data-card-contents-for-user="135319" type="text/json">{"id":135319,"first_name":"Walter R T","last_name":"Witschey, Sr.","domain_name":"longwood","page_name":"WalterWitschey","display_name":"Walter R T Witschey, Sr.","profile_url":"https://longwood.academia.edu/WalterWitschey?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_71234092 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="71234092"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 71234092, container: ".js-paper-rank-work_71234092", }); });</script></li><li class="js-percentile-work_71234092 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 71234092; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_71234092"); 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class="u-positionAbsolute" data-has-card-for-ri-list="71234092"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">13</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="300" href="https://www.academia.edu/Documents/in/Mathematics">Mathematics</a>, <script data-card-contents-for-ri="300" type="text/json">{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="317" href="https://www.academia.edu/Documents/in/Fractal_Geometry">Fractal Geometry</a>, <script data-card-contents-for-ri="317" type="text/json">{"id":317,"name":"Fractal Geometry","url":"https://www.academia.edu/Documents/in/Fractal_Geometry?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="392" href="https://www.academia.edu/Documents/in/Archaeology">Archaeology</a>, <script data-card-contents-for-ri="392" type="text/json">{"id":392,"name":"Archaeology","url":"https://www.academia.edu/Documents/in/Archaeology?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="5063" href="https://www.academia.edu/Documents/in/Settlement_Patterns">Settlement Patterns</a><script data-card-contents-for-ri="5063" type="text/json">{"id":5063,"name":"Settlement Patterns","url":"https://www.academia.edu/Documents/in/Settlement_Patterns?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=71234092]'), work: {"id":71234092,"title":"The Broken Past: Fractals in 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Geometry","url":"https://www.academia.edu/Documents/in/Fractal_Geometry?f_ri=160248","nofollow":false},{"id":392,"name":"Archaeology","url":"https://www.academia.edu/Documents/in/Archaeology?f_ri=160248","nofollow":false},{"id":5063,"name":"Settlement Patterns","url":"https://www.academia.edu/Documents/in/Settlement_Patterns?f_ri=160248","nofollow":false},{"id":5493,"name":"Nonlinear dynamics","url":"https://www.academia.edu/Documents/in/Nonlinear_dynamics?f_ri=160248"},{"id":12222,"name":"Survey (Archaeological Method \u0026 Theory)","url":"https://www.academia.edu/Documents/in/Survey_Archaeological_Method_and_Theory_?f_ri=160248"},{"id":19728,"name":"Lithic Technology","url":"https://www.academia.edu/Documents/in/Lithic_Technology?f_ri=160248"},{"id":24827,"name":"Ceramics (Archaeology)","url":"https://www.academia.edu/Documents/in/Ceramics_Archaeology_?f_ri=160248"},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248"},{"id":105778,"name":"Debitage Analysis","url":"https://www.academia.edu/Documents/in/Debitage_Analysis?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":476803,"name":"Nonlinear Dynamic System","url":"https://www.academia.edu/Documents/in/Nonlinear_Dynamic_System?f_ri=160248"},{"id":506858,"name":"Nonlinear system","url":"https://www.academia.edu/Documents/in/Nonlinear_system?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_5940474" data-work_id="5940474" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/5940474/The_fractal_geometry_of_tidal_channel_systems_in_the_Dutch_Wadden_Sea">The fractal geometry of tidal-channel systems in the Dutch Wadden Sea</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Horton's hierarchical and fractal analysis of channel circumference reveals that tidal-channel systems in the Dutch Wadden Sea have similar branching patterns. Channel systems have the same characteristics as three- to four-times... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_5940474" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Horton's hierarchical and fractal analysis of channel circumference reveals that tidal-channel systems in the Dutch Wadden Sea have similar branching patterns. Channel systems have the same characteristics as three- to four-times branching networks. The branch lengths of these channels decrease logarithmically. The channel systems can be regarded as ‘statistical self-similar fractal’ networks, considering the natural variability in branch lengths and channel positions. Branching of channels does not continue below the 500 m scale. The channel-system circumference length is logarithmically related to the tidal prism and drainage area. The similarity of the channel systems, regardless of their size, relative amount of intertidal flats, and tidal amplitude, points to a self-organising nature. All processes depend on the feedback between morphology and hydrodynamics. At first sight, the channel systems can be regarded as an ebb-driven drainage network, governed by erosion. However, flood-dominated net sedimentation occurs in large parts of the drainage basins and modifies the ebb-driven network. The complex interaction of hydrodynamic and morphodynamic processes in tidal basins limits the applicability of process-based models. Behaviour-oriented modelling has a wide applicability and can be improved using the fractal geometry as the dynamical equilibrium morphology. The fractal-network geometry can also be used for stochastic reconstructions of fossil tidal-channel systems, when only limited observations are available.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/5940474" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="306dcbc7d204773796477cc3f66d825a" rel="nofollow" data-download="{"attachment_id":49082778,"asset_id":5940474,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49082778/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8835397" href="https://independent.academia.edu/AlbertOost">Albert Oost</a><script data-card-contents-for-user="8835397" type="text/json">{"id":8835397,"first_name":"Albert","last_name":"Oost","domain_name":"independent","page_name":"AlbertOost","display_name":"Albert Oost","profile_url":"https://independent.academia.edu/AlbertOost?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_5940474 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="5940474"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 5940474, container: ".js-paper-rank-work_5940474", }); 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Channel systems have the same characteristics as three- to four-times branching networks. The branch lengths of these channels decrease logarithmically. The channel systems can be regarded as ‘statistical self-similar fractal’ networks, considering the natural variability in branch lengths and channel positions. Branching of channels does not continue below the 500 m scale. The channel-system circumference length is logarithmically related to the tidal prism and drainage area. The similarity of the channel systems, regardless of their size, relative amount of intertidal flats, and tidal amplitude, points to a self-organising nature. All processes depend on the feedback between morphology and hydrodynamics. At first sight, the channel systems can be regarded as an ebb-driven drainage network, governed by erosion. However, flood-dominated net sedimentation occurs in large parts of the drainage basins and modifies the ebb-driven network. The complex interaction of hydrodynamic and morphodynamic processes in tidal basins limits the applicability of process-based models. Behaviour-oriented modelling has a wide applicability and can be improved using the fractal geometry as the dynamical equilibrium morphology. The fractal-network geometry can also be used for stochastic reconstructions of fossil tidal-channel systems, when only limited observations are available.","downloadable_attachments":[{"id":49082778,"asset_id":5940474,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":8835397,"first_name":"Albert","last_name":"Oost","domain_name":"independent","page_name":"AlbertOost","display_name":"Albert Oost","profile_url":"https://independent.academia.edu/AlbertOost?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":317,"name":"Fractal Geometry","url":"https://www.academia.edu/Documents/in/Fractal_Geometry?f_ri=160248","nofollow":false},{"id":406,"name":"Geology","url":"https://www.academia.edu/Documents/in/Geology?f_ri=160248","nofollow":false},{"id":135283,"name":"Barrier Island","url":"https://www.academia.edu/Documents/in/Barrier_Island?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":299563,"name":"Self Organization","url":"https://www.academia.edu/Documents/in/Self_Organization?f_ri=160248"},{"id":1551329,"name":"Dynamic equilibrium","url":"https://www.academia.edu/Documents/in/Dynamic_equilibrium?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_72532259 coauthored" data-work_id="72532259" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/72532259/Fractal_Analysis_In_the_Detection_of_Colonic_Cancer_Images">Fractal Analysis In the Detection of Colonic Cancer Images</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">AbstractThe aim of this study was to investigate the value of fractal dimension in separating normal and cancerous images, and to examine the relationship between fractal dimension and traditional texture analysis features. Forty-four... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_72532259" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">AbstractThe aim of this study was to investigate the value of fractal dimension in separating normal and cancerous images, and to examine the relationship between fractal dimension and traditional texture analysis features. Forty-four normal images and 58 cancer images from ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/72532259" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="00f4ac42bc0c32944e899df759d0903c" rel="nofollow" data-download="{"attachment_id":81423707,"asset_id":72532259,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/81423707/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="216802943" href="https://independent.academia.edu/AlanMurray51">Alan Murray</a><script data-card-contents-for-user="216802943" type="text/json">{"id":216802943,"first_name":"Alan","last_name":"Murray","domain_name":"independent","page_name":"AlanMurray51","display_name":"Alan Murray","profile_url":"https://independent.academia.edu/AlanMurray51?f_ri=160248","photo":"https://0.academia-photos.com/216802943/75179247/63686362/s65_alan.murray.jpeg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-72532259">+1</span><div class="hidden js-additional-users-72532259"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/AbdelrahimEsgiar">Abdelrahim Esgiar</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-72532259'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-72532259').html(); 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Forty-four normal images and 58 cancer images from ...","downloadable_attachments":[{"id":81423707,"asset_id":72532259,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":216802943,"first_name":"Alan","last_name":"Murray","domain_name":"independent","page_name":"AlanMurray51","display_name":"Alan Murray","profile_url":"https://independent.academia.edu/AlanMurray51?f_ri=160248","photo":"https://0.academia-photos.com/216802943/75179247/63686362/s65_alan.murray.jpeg"},{"id":13909435,"first_name":"Abdelrahim","last_name":"Esgiar","domain_name":"independent","page_name":"AbdelrahimEsgiar","display_name":"Abdelrahim Esgiar","profile_url":"https://independent.academia.edu/AbdelrahimEsgiar?f_ri=160248","photo":"https://0.academia-photos.com/13909435/59250962/47493325/s65_abdelrahim.esgiar.jpeg"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=160248","nofollow":false},{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics?f_ri=160248","nofollow":false},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=160248","nofollow":false},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer?f_ri=160248","nofollow":false},{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=160248"},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248"},{"id":36265,"name":"Entropy","url":"https://www.academia.edu/Documents/in/Entropy?f_ri=160248"},{"id":48999,"name":"Information","url":"https://www.academia.edu/Documents/in/Information?f_ri=160248"},{"id":56368,"name":"Image Classification","url":"https://www.academia.edu/Documents/in/Image_Classification?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":372699,"name":"Information Analysis","url":"https://www.academia.edu/Documents/in/Information_Analysis?f_ri=160248"},{"id":375328,"name":"Cancer Classification","url":"https://www.academia.edu/Documents/in/Cancer_Classification?f_ri=160248"},{"id":420802,"name":"Colon cancer","url":"https://www.academia.edu/Documents/in/Colon_cancer?f_ri=160248"},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248"},{"id":998885,"name":"Feature Analysis","url":"https://www.academia.edu/Documents/in/Feature_Analysis?f_ri=160248"},{"id":1819399,"name":"Case Control Studies","url":"https://www.academia.edu/Documents/in/Case_Control_Studies?f_ri=160248"},{"id":3286327,"name":"Image Texture","url":"https://www.academia.edu/Documents/in/Image_Texture?f_ri=160248"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences?f_ri=160248"},{"id":3793278,"name":"Colonic Neoplasms","url":"https://www.academia.edu/Documents/in/Colonic_Neoplasms?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_15062876 coauthored" data-work_id="15062876" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/15062876/Resumo_Expandido_Encontro_Anual_de_Inicia%C3%A7%C3%A3o_Cient%C3%ADfica_Tema_Mec%C3%A2nica_Fractal">Resumo Expandido - Encontro Anual de Iniciação Científica. 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Проанализированы инструменты... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_6496461" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">В статье рассмотрены основные положения теорий динамики рынков, в частности, гипотезы эффективного рынка, гипотезы когерентного рынка, гипотезы фрактального рынка и гипотезы синергетического рынка. Проанализированы инструменты фрактального рынка для принятия на их основе обоснованных инвестиционных решений. Приведены и обоснованы инструменты технического анализа, основанного на игре за трендом для прогнозирования динамики рынка, согласно гипотезе фрактального рынка, в частности, волновую модель Эллиотта и применения нейро-нечетких моделей. <br />Ключевые слова: эффективный рынок, когерентный рынок, фрактальный рынок, синергетический рынок, технический анализ</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/6496461" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="3a79b42a246279837e09bbb80caf7127" rel="nofollow" data-download="{"attachment_id":33330705,"asset_id":6496461,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/33330705/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4675555" href="https://nmetau.academia.edu/OleksiiNykytenko">Oleksii Nykytenko</a><script data-card-contents-for-user="4675555" type="text/json">{"id":4675555,"first_name":"Oleksii","last_name":"Nykytenko","domain_name":"nmetau","page_name":"OleksiiNykytenko","display_name":"Oleksii Nykytenko","profile_url":"https://nmetau.academia.edu/OleksiiNykytenko?f_ri=160248","photo":"https://0.academia-photos.com/4675555/1965776/2802971/s65_oleksii.nykytenko.jpg"}</script></span></span></li><li class="js-paper-rank-work_6496461 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="6496461"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 6496461, container: ".js-paper-rank-work_6496461", }); 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$(".js-view-count[data-work-id=6496461]").text(description); $(".js-view-count-work_6496461").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_6496461").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="6496461"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">13</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="47" href="https://www.academia.edu/Documents/in/Finance">Finance</a>, <script data-card-contents-for-ri="47" type="text/json">{"id":47,"name":"Finance","url":"https://www.academia.edu/Documents/in/Finance?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="748" href="https://www.academia.edu/Documents/in/Financial_Economics">Financial Economics</a>, <script data-card-contents-for-ri="748" type="text/json">{"id":748,"name":"Financial Economics","url":"https://www.academia.edu/Documents/in/Financial_Economics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="15066" href="https://www.academia.edu/Documents/in/Financial_mathematics">Financial mathematics</a>, <script data-card-contents-for-ri="15066" type="text/json">{"id":15066,"name":"Financial mathematics","url":"https://www.academia.edu/Documents/in/Financial_mathematics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="24831" href="https://www.academia.edu/Documents/in/Fractals">Fractals</a><script data-card-contents-for-ri="24831" type="text/json">{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=6496461]'), work: {"id":6496461,"title":"Анализ теорий динамики рынков","created_at":"2014-03-21T07:17:26.859-07:00","url":"https://www.academia.edu/6496461/%D0%90%D0%BD%D0%B0%D0%BB%D0%B8%D0%B7_%D1%82%D0%B5%D0%BE%D1%80%D0%B8%D0%B9_%D0%B4%D0%B8%D0%BD%D0%B0%D0%BC%D0%B8%D0%BA%D0%B8_%D1%80%D1%8B%D0%BD%D0%BA%D0%BE%D0%B2?f_ri=160248","dom_id":"work_6496461","summary":"В статье рассмотрены основные положения теорий динамики рынков, в частности, гипотезы эффективного рынка, гипотезы когерентного рынка, гипотезы фрактального рынка и гипотезы синергетического рынка. Проанализированы инструменты фрактального рынка для принятия на их основе обоснованных инвестиционных решений. Приведены и обоснованы инструменты технического анализа, основанного на игре за трендом для прогнозирования динамики рынка, согласно гипотезе фрактального рынка, в частности, волновую модель Эллиотта и применения нейро-нечетких моделей.\r\nКлючевые слова: эффективный рынок, когерентный рынок, фрактальный рынок, синергетический рынок, технический анализ","downloadable_attachments":[{"id":33330705,"asset_id":6496461,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4675555,"first_name":"Oleksii","last_name":"Nykytenko","domain_name":"nmetau","page_name":"OleksiiNykytenko","display_name":"Oleksii Nykytenko","profile_url":"https://nmetau.academia.edu/OleksiiNykytenko?f_ri=160248","photo":"https://0.academia-photos.com/4675555/1965776/2802971/s65_oleksii.nykytenko.jpg"}],"research_interests":[{"id":47,"name":"Finance","url":"https://www.academia.edu/Documents/in/Finance?f_ri=160248","nofollow":false},{"id":748,"name":"Financial Economics","url":"https://www.academia.edu/Documents/in/Financial_Economics?f_ri=160248","nofollow":false},{"id":15066,"name":"Financial mathematics","url":"https://www.academia.edu/Documents/in/Financial_mathematics?f_ri=160248","nofollow":false},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false},{"id":25112,"name":"Financial Markets","url":"https://www.academia.edu/Documents/in/Financial_Markets?f_ri=160248"},{"id":45591,"name":"Financial Derivatives","url":"https://www.academia.edu/Documents/in/Financial_Derivatives?f_ri=160248"},{"id":67762,"name":"Efficient Market Hypothesis","url":"https://www.academia.edu/Documents/in/Efficient_Market_Hypothesis?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":172625,"name":"Fractal","url":"https://www.academia.edu/Documents/in/Fractal?f_ri=160248"},{"id":419222,"name":"Market Efficiency Hypothesis","url":"https://www.academia.edu/Documents/in/Market_Efficiency_Hypothesis?f_ri=160248"},{"id":730238,"name":"Fractals and Chaos","url":"https://www.academia.edu/Documents/in/Fractals_and_Chaos?f_ri=160248"},{"id":971930,"name":"Efficient Market Hypothesis Capital Structures and Earnings Management","url":"https://www.academia.edu/Documents/in/Efficient_Market_Hypothesis_Capital_Structures_and_Earnings_Management?f_ri=160248"},{"id":1335000,"name":"Fractal Market Hypothesis","url":"https://www.academia.edu/Documents/in/Fractal_Market_Hypothesis?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_11033702" data-work_id="11033702" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/11033702/Fractal_Dimensions_of_Blocks_Using_a_Box_counting_Technique_for_the_2001_Bhuj_Earthquake_Gujarat_India">Fractal Dimensions of Blocks Using a Box-counting Technique for the 2001 Bhuj Earthquake, Gujarat, India</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Several destructive earthquakes have occurred in the Kachchh region of Gujarat during the past two centuries, among them Allah Bund earthquake (M7.8) in 1819, Anjar earthquake (M6) in 1956 and the recent Bhuj earthquake (M7.6) in 2001.... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_11033702" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Several destructive earthquakes have occurred in the Kachchh region of Gujarat during the past two centuries, among them Allah Bund earthquake (M7.8) in 1819, Anjar earthquake (M6) in 1956 and the recent Bhuj earthquake (M7.6) in 2001. The Anjar earthquake was on KMF (Kachchh Mainland Fault) and the recent Bhuj events were caused by a hidden fault north of KMF. The present study discusses the fractal analysis of tectonics governing seismic activity in the region. The region has been divided into five blocks and the fractal dimension of each block has been calculated using the box-counting technique. The results show significantly low value of fractal dimension of the Kachchh rift block consisting of the KMF compared to the other surrounding blocks, which also contain faults and rifts of higher fractal dimension. This indicates that the cause of earthquakes in this block may be asperities and barriers. However, the predominance of aftershocks over foreshocks signifies that barriers may be the main cause. The other results, such as the lower value of dimension of fault clustering show that the Kachchh rift block has faults which are distributed in a clustered manner. In this context, the seismicity of this block seems to be high.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/11033702" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="863d25433ab3ba3586482208aaeaf292" rel="nofollow" data-download="{"attachment_id":46955442,"asset_id":11033702,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/46955442/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26696715" href="https://bhu-in.academia.edu/AVADHRAM">AVADH RAM</a><script data-card-contents-for-user="26696715" type="text/json">{"id":26696715,"first_name":"AVADH","last_name":"RAM","domain_name":"bhu-in","page_name":"AVADHRAM","display_name":"AVADH RAM","profile_url":"https://bhu-in.academia.edu/AVADHRAM?f_ri=160248","photo":"https://0.academia-photos.com/26696715/7439038/8360369/s65_avadh.ram.jpg"}</script></span></span></li><li class="js-paper-rank-work_11033702 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="11033702"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 11033702, container: ".js-paper-rank-work_11033702", }); });</script></li><li class="js-percentile-work_11033702 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 11033702; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_11033702"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_11033702 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="11033702"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 11033702; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=11033702]").text(description); $(".js-view-count-work_11033702").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_11033702").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="11033702"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="409" href="https://www.academia.edu/Documents/in/Geophysics">Geophysics</a>, <script data-card-contents-for-ri="409" type="text/json">{"id":409,"name":"Geophysics","url":"https://www.academia.edu/Documents/in/Geophysics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="890611" href="https://www.academia.edu/Documents/in/Fractal_Dimension">Fractal Dimension</a><script data-card-contents-for-ri="890611" type="text/json">{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=11033702]'), work: {"id":11033702,"title":"Fractal Dimensions of Blocks Using a Box-counting Technique for the 2001 Bhuj Earthquake, Gujarat, India","created_at":"2015-02-23T21:58:41.197-08:00","url":"https://www.academia.edu/11033702/Fractal_Dimensions_of_Blocks_Using_a_Box_counting_Technique_for_the_2001_Bhuj_Earthquake_Gujarat_India?f_ri=160248","dom_id":"work_11033702","summary":"Several destructive earthquakes have occurred in the Kachchh region of Gujarat during the past two centuries, among them Allah Bund earthquake (M7.8) in 1819, Anjar earthquake (M6) in 1956 and the recent Bhuj earthquake (M7.6) in 2001. The Anjar earthquake was on KMF (Kachchh Mainland Fault) and the recent Bhuj events were caused by a hidden fault north of KMF. The present study discusses the fractal analysis of tectonics governing seismic activity in the region. The region has been divided into five blocks and the fractal dimension of each block has been calculated using the box-counting technique. The results show significantly low value of fractal dimension of the Kachchh rift block consisting of the KMF compared to the other surrounding blocks, which also contain faults and rifts of higher fractal dimension. This indicates that the cause of earthquakes in this block may be asperities and barriers. However, the predominance of aftershocks over foreshocks signifies that barriers may be the main cause. The other results, such as the lower value of dimension of fault clustering show that the Kachchh rift block has faults which are distributed in a clustered manner. In this context, the seismicity of this block seems to be high.","downloadable_attachments":[{"id":46955442,"asset_id":11033702,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26696715,"first_name":"AVADH","last_name":"RAM","domain_name":"bhu-in","page_name":"AVADHRAM","display_name":"AVADH RAM","profile_url":"https://bhu-in.academia.edu/AVADHRAM?f_ri=160248","photo":"https://0.academia-photos.com/26696715/7439038/8360369/s65_avadh.ram.jpg"}],"research_interests":[{"id":409,"name":"Geophysics","url":"https://www.academia.edu/Documents/in/Geophysics?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_43250419" data-work_id="43250419" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/43250419/Stochastic_differential_equations_on_fractal_sets">Stochastic differential equations on fractal sets</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this manuscript, we review fractal calculus and random processes. Random variables and processes on totally disconnected fractal sets are defined. Random walks on fractal middle-ξ Cantor sets are suggested and corresponding variances... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_43250419" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this manuscript, we review fractal calculus and random processes. Random variables and processes on totally disconnected fractal sets are defined. Random walks on fractal middle-ξ Cantor sets are suggested and corresponding variances are given which are power laws. The mean square stochastic calculus is generalized on fractal sets, which can lead to the standard case by setting dimension α = 1. Furthermore , we solve a fractal stochastic differential equation using the Frobenius method. Graphs are presented to give more details. ARTICLE HISTORY</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/43250419" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="b699cd5690a9a2d0c758a43aa0e5e970" rel="nofollow" data-download="{"attachment_id":63521566,"asset_id":43250419,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/63521566/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5903423" href="https://iaurmia.academia.edu/KhaliliGolmankhaneh">Alireza Khalili Golmankhaneh</a><script data-card-contents-for-user="5903423" type="text/json">{"id":5903423,"first_name":"Alireza","last_name":"Khalili Golmankhaneh","domain_name":"iaurmia","page_name":"KhaliliGolmankhaneh","display_name":"Alireza Khalili Golmankhaneh","profile_url":"https://iaurmia.academia.edu/KhaliliGolmankhaneh?f_ri=160248","photo":"https://0.academia-photos.com/5903423/2520645/77834941/s65_alireza.khalili_golmankhaneh.png"}</script></span></span></li><li class="js-paper-rank-work_43250419 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="43250419"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 43250419, container: ".js-paper-rank-work_43250419", }); });</script></li><li class="js-percentile-work_43250419 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 43250419; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_43250419"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_43250419 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="43250419"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 43250419; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=43250419]").text(description); $(".js-view-count-work_43250419").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_43250419").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="43250419"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i></div><span class="InlineList-item-text u-textTruncate u-pl6x"><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a><script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (false) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=43250419]'), work: {"id":43250419,"title":"Stochastic differential equations on fractal sets","created_at":"2020-06-03T20:07:28.224-07:00","url":"https://www.academia.edu/43250419/Stochastic_differential_equations_on_fractal_sets?f_ri=160248","dom_id":"work_43250419","summary":"In this manuscript, we review fractal calculus and random processes. Random variables and processes on totally disconnected fractal sets are defined. Random walks on fractal middle-ξ Cantor sets are suggested and corresponding variances are given which are power laws. The mean square stochastic calculus is generalized on fractal sets, which can lead to the standard case by setting dimension α = 1. Furthermore , we solve a fractal stochastic differential equation using the Frobenius method. Graphs are presented to give more details. ARTICLE HISTORY","downloadable_attachments":[{"id":63521566,"asset_id":43250419,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5903423,"first_name":"Alireza","last_name":"Khalili Golmankhaneh","domain_name":"iaurmia","page_name":"KhaliliGolmankhaneh","display_name":"Alireza Khalili Golmankhaneh","profile_url":"https://iaurmia.academia.edu/KhaliliGolmankhaneh?f_ri=160248","photo":"https://0.academia-photos.com/5903423/2520645/77834941/s65_alireza.khalili_golmankhaneh.png"}],"research_interests":[{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_13388757" data-work_id="13388757" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/13388757/Space_charge_limited_currents_An_E_infinity_Cantorian_approach">Space-charge-limited currents: An E-infinity Cantorian approach</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/13388757" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="41627a9e73ea9c1b0b48ae66c966b04f" rel="nofollow" data-download="{"attachment_id":45395791,"asset_id":13388757,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button 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href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="890611" href="https://www.academia.edu/Documents/in/Fractal_Dimension">Fractal Dimension</a><script data-card-contents-for-ri="890611" type="text/json">{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=13388757]'), work: {"id":13388757,"title":"Space-charge-limited currents: An E-infinity Cantorian 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Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248","nofollow":false},{"id":2162050,"name":"Current-Voltage Characteristic","url":"https://www.academia.edu/Documents/in/Current-Voltage_Characteristic?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17096067 coauthored" data-work_id="17096067" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17096067/Fractal_Analysis_in_Human_Pathology">Fractal Analysis in Human Pathology</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17096067" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c6471280f9bee1840e1f49dd1fe9cfdd" rel="nofollow" data-download="{"attachment_id":42323297,"asset_id":17096067,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/42323297/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="36668079" href="https://unisi.academia.edu/GiorgioBianciardi">Giorgio Bianciardi</a><script data-card-contents-for-user="36668079" type="text/json">{"id":36668079,"first_name":"Giorgio","last_name":"Bianciardi","domain_name":"unisi","page_name":"GiorgioBianciardi","display_name":"Giorgio Bianciardi","profile_url":"https://unisi.academia.edu/GiorgioBianciardi?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-17096067">+1</span><div class="hidden js-additional-users-17096067"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/LutfiAlia">Lutfi Alia</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-17096067'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-17096067').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_17096067 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="17096067"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 17096067, container: ".js-paper-rank-work_17096067", }); });</script></li><li class="js-percentile-work_17096067 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget 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$(".js-view-count[data-work-id=17096067]").text(description); $(".js-view-count-work_17096067").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_17096067").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="17096067"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2184" href="https://www.academia.edu/Documents/in/Electron_Microscopy">Electron Microscopy</a>, <script data-card-contents-for-ri="2184" type="text/json">{"id":2184,"name":"Electron Microscopy","url":"https://www.academia.edu/Documents/in/Electron_Microscopy?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="24831" href="https://www.academia.edu/Documents/in/Fractals">Fractals</a>, <script data-card-contents-for-ri="24831" type="text/json">{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="28235" href="https://www.academia.edu/Documents/in/Multidisciplinary">Multidisciplinary</a>, <script data-card-contents-for-ri="28235" type="text/json">{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a><script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=17096067]'), work: {"id":17096067,"title":"Fractal Analysis in Human Pathology","created_at":"2015-10-21T04:39:25.041-07:00","url":"https://www.academia.edu/17096067/Fractal_Analysis_in_Human_Pathology?f_ri=160248","dom_id":"work_17096067","summary":null,"downloadable_attachments":[{"id":42323297,"asset_id":17096067,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":36668079,"first_name":"Giorgio","last_name":"Bianciardi","domain_name":"unisi","page_name":"GiorgioBianciardi","display_name":"Giorgio Bianciardi","profile_url":"https://unisi.academia.edu/GiorgioBianciardi?f_ri=160248","photo":"/images/s65_no_pic.png"},{"id":5087402,"first_name":"Lutfi","last_name":"Alia","domain_name":"independent","page_name":"LutfiAlia","display_name":"Lutfi Alia","profile_url":"https://independent.academia.edu/LutfiAlia?f_ri=160248","photo":"https://0.academia-photos.com/5087402/2223012/2602271/s65_lutfi.alia.jpg"}],"research_interests":[{"id":2184,"name":"Electron Microscopy","url":"https://www.academia.edu/Documents/in/Electron_Microscopy?f_ri=160248","nofollow":false},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false},{"id":28235,"name":"Multidisciplinary","url":"https://www.academia.edu/Documents/in/Multidisciplinary?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":413194,"name":"Analysis of Variance","url":"https://www.academia.edu/Documents/in/Analysis_of_Variance?f_ri=160248"},{"id":518963,"name":"Basal cell carcinoma","url":"https://www.academia.edu/Documents/in/Basal_cell_carcinoma?f_ri=160248"},{"id":2177223,"name":"Skin Neoplasms","url":"https://www.academia.edu/Documents/in/Skin_Neoplasms?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_1772433" data-work_id="1772433" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/1772433/Rheological_study_and_fractal_analysis_of_flaxseed_gum_gels">Rheological study and fractal analysis of flaxseed gum gels</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The rheological properties and fractal dimensions of flaxseed gum gels were analyzed in various ionic strength values ranging between 0 and 1000 mM. The rheological properties of flaxseed gum were significantly influenced by the ionic... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_1772433" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The rheological properties and fractal dimensions of flaxseed gum gels were analyzed in various ionic strength values ranging between 0 and 1000 mM. The rheological properties of flaxseed gum were significantly influenced by the ionic strength. The gel strength first increased then decreased with the increasing of ionic strength and the strongest gel was obtained when the ionic strength was 400 mM. The calculated fractal dimensions of the flaxseed gum gels were 2.06–2.49 or 1.42–2.18, based on the model selected and the ionic strength applied. These results would help to understand the microstructure of the flaxseed gum gels and the influence of ionic strength on that. However, the difference in results between the two models implied that further study is needed to find suitable model for flaxseed gum gels.► The fractal structure of flaxseed gum was analyzed using two Rheological model. ► The fractal dimension of flaxseed gum was calculated to be 2.06–2.49 or 1.42–2.18. ► Ionic strength has significant effect on the fractal dimension of flaxseed gum.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/1772433" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ca75c2c6df7fc8eed34d0967e2d37301" rel="nofollow" data-download="{"attachment_id":50870659,"asset_id":1772433,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50870659/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2081841" href="https://cau-cn.academia.edu/YongWang">Yong Wang</a><script data-card-contents-for-user="2081841" type="text/json">{"id":2081841,"first_name":"Yong","last_name":"Wang","domain_name":"cau-cn","page_name":"YongWang","display_name":"Yong Wang","profile_url":"https://cau-cn.academia.edu/YongWang?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_1772433 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="1772433"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 1772433, container: ".js-paper-rank-work_1772433", }); 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$(".js-view-count[data-work-id=1772433]").text(description); $(".js-view-count-work_1772433").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_1772433").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="1772433"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="531" href="https://www.academia.edu/Documents/in/Organic_Chemistry">Organic Chemistry</a>, <script data-card-contents-for-ri="531" type="text/json">{"id":531,"name":"Organic Chemistry","url":"https://www.academia.edu/Documents/in/Organic_Chemistry?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="7598" href="https://www.academia.edu/Documents/in/Rheology">Rheology</a>, <script data-card-contents-for-ri="7598" type="text/json">{"id":7598,"name":"Rheology","url":"https://www.academia.edu/Documents/in/Rheology?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="85344" href="https://www.academia.edu/Documents/in/Model_Selection">Model Selection</a>, <script data-card-contents-for-ri="85344" type="text/json">{"id":85344,"name":"Model Selection","url":"https://www.academia.edu/Documents/in/Model_Selection?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a><script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=1772433]'), work: {"id":1772433,"title":"Rheological study and fractal analysis of flaxseed gum gels","created_at":"2012-07-07T12:32:14.211-07:00","url":"https://www.academia.edu/1772433/Rheological_study_and_fractal_analysis_of_flaxseed_gum_gels?f_ri=160248","dom_id":"work_1772433","summary":"The rheological properties and fractal dimensions of flaxseed gum gels were analyzed in various ionic strength values ranging between 0 and 1000 mM. The rheological properties of flaxseed gum were significantly influenced by the ionic strength. The gel strength first increased then decreased with the increasing of ionic strength and the strongest gel was obtained when the ionic strength was 400 mM. The calculated fractal dimensions of the flaxseed gum gels were 2.06–2.49 or 1.42–2.18, based on the model selected and the ionic strength applied. These results would help to understand the microstructure of the flaxseed gum gels and the influence of ionic strength on that. However, the difference in results between the two models implied that further study is needed to find suitable model for flaxseed gum gels.► The fractal structure of flaxseed gum was analyzed using two Rheological model. ► The fractal dimension of flaxseed gum was calculated to be 2.06–2.49 or 1.42–2.18. ► Ionic strength has significant effect on the fractal dimension of flaxseed gum.","downloadable_attachments":[{"id":50870659,"asset_id":1772433,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":2081841,"first_name":"Yong","last_name":"Wang","domain_name":"cau-cn","page_name":"YongWang","display_name":"Yong Wang","profile_url":"https://cau-cn.academia.edu/YongWang?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":531,"name":"Organic Chemistry","url":"https://www.academia.edu/Documents/in/Organic_Chemistry?f_ri=160248","nofollow":false},{"id":7598,"name":"Rheology","url":"https://www.academia.edu/Documents/in/Rheology?f_ri=160248","nofollow":false},{"id":85344,"name":"Model Selection","url":"https://www.academia.edu/Documents/in/Model_Selection?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":335749,"name":"Medical Bioengineering","url":"https://www.academia.edu/Documents/in/Medical_Bioengineering?f_ri=160248"},{"id":473797,"name":"Microstructures","url":"https://www.academia.edu/Documents/in/Microstructures?f_ri=160248"},{"id":494469,"name":"Gel","url":"https://www.academia.edu/Documents/in/Gel?f_ri=160248"},{"id":573653,"name":"Food Sciences","url":"https://www.academia.edu/Documents/in/Food_Sciences?f_ri=160248"},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248"},{"id":970774,"name":"Ionic Strength","url":"https://www.academia.edu/Documents/in/Ionic_Strength?f_ri=160248"},{"id":1323439,"name":"Carbohydrate Polymers","url":"https://www.academia.edu/Documents/in/Carbohydrate_Polymers?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_8124542" data-work_id="8124542" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/8124542/Fractal_analysis_and_modeling_of_VoIP_traffic">Fractal analysis and modeling of VoIP traffic</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div 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class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="15789824" href="https://independent.academia.edu/trangdinh4">trang dinh</a><script data-card-contents-for-user="15789824" type="text/json">{"id":15789824,"first_name":"trang","last_name":"dinh","domain_name":"independent","page_name":"trangdinh4","display_name":"trang dinh","profile_url":"https://independent.academia.edu/trangdinh4?f_ri=160248","photo":"https://0.academia-photos.com/15789824/9675755/10776450/s65_trang.dinh.jpg"}</script></span></span></li><li class="js-paper-rank-work_8124542 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="8124542"><i class="u-m1x fa fa-bar-chart"></i><strong 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data-card-contents-for-ri="24831" type="text/json">{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="169392" href="https://www.academia.edu/Documents/in/Detectors">Detectors</a>, <script data-card-contents-for-ri="169392" type="text/json">{"id":169392,"name":"Detectors","url":"https://www.academia.edu/Documents/in/Detectors?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="411912" href="https://www.academia.edu/Documents/in/Poisson_Process">Poisson Process</a><script data-card-contents-for-ri="411912" type="text/json">{"id":411912,"name":"Poisson Process","url":"https://www.academia.edu/Documents/in/Poisson_Process?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=8124542]'), work: {"id":8124542,"title":"Fractal analysis and modeling of VoIP traffic","created_at":"2014-08-29T02:08:39.699-07:00","url":"https://www.academia.edu/8124542/Fractal_analysis_and_modeling_of_VoIP_traffic?f_ri=160248","dom_id":"work_8124542","summary":null,"downloadable_attachments":[{"id":48207832,"asset_id":8124542,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":15789824,"first_name":"trang","last_name":"dinh","domain_name":"independent","page_name":"trangdinh4","display_name":"trang dinh","profile_url":"https://independent.academia.edu/trangdinh4?f_ri=160248","photo":"https://0.academia-photos.com/15789824/9675755/10776450/s65_trang.dinh.jpg"}],"research_interests":[{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":169392,"name":"Detectors","url":"https://www.academia.edu/Documents/in/Detectors?f_ri=160248","nofollow":false},{"id":411912,"name":"Poisson Process","url":"https://www.academia.edu/Documents/in/Poisson_Process?f_ri=160248","nofollow":false},{"id":543432,"name":"Exponential distribution","url":"https://www.academia.edu/Documents/in/Exponential_distribution?f_ri=160248"},{"id":582384,"name":"Gaussian noise","url":"https://www.academia.edu/Documents/in/Gaussian_noise?f_ri=160248"},{"id":963313,"name":"Pareto Distribution","url":"https://www.academia.edu/Documents/in/Pareto_Distribution?f_ri=160248"},{"id":1151837,"name":"Transport Protocols","url":"https://www.academia.edu/Documents/in/Transport_Protocols?f_ri=160248"},{"id":2272349,"name":"Generalized Pareto Distribution","url":"https://www.academia.edu/Documents/in/Generalized_Pareto_Distribution?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3782296" data-work_id="3782296" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3782296/Analiza_fraktalna_obraz%C3%B3w_radiologicznych_%C5%BCuchwy_w_obszarze_z%C4%99b%C3%B3w_reinkludowanych_Fractal_analysis_of_mandibular_radiographic_images_in_the_region_of_reincluded_teeth">Analiza fraktalna obrazów radiologicznych żuchwy w obszarze zębów reinkludowanych* Fractal analysis of mandibular radiographic images in the region of reincluded teeth</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3782296" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d9c53c3c8494b0ce7ee76781bd6fb2e6" rel="nofollow" data-download="{"attachment_id":31445756,"asset_id":3782296,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" 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u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="457608" href="https://www.academia.edu/Documents/in/Czas">Czas</a><script data-card-contents-for-ri="457608" type="text/json">{"id":457608,"name":"Czas","url":"https://www.academia.edu/Documents/in/Czas?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=3782296]'), work: {"id":3782296,"title":"Analiza fraktalna obrazów radiologicznych żuchwy w obszarze zębów reinkludowanych* Fractal analysis of mandibular radiographic images in the region of reincluded teeth","created_at":"2013-06-24T20:37:33.740-07:00","url":"https://www.academia.edu/3782296/Analiza_fraktalna_obraz%C3%B3w_radiologicznych_%C5%BCuchwy_w_obszarze_z%C4%99b%C3%B3w_reinkludowanych_Fractal_analysis_of_mandibular_radiographic_images_in_the_region_of_reincluded_teeth?f_ri=160248","dom_id":"work_3782296","summary":null,"downloadable_attachments":[{"id":31445756,"asset_id":3782296,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4648810,"first_name":"Marta","last_name":"Borowska","domain_name":"uwb","page_name":"MartaBorowska","display_name":"Marta Borowska","profile_url":"https://uwb.academia.edu/MartaBorowska?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":457608,"name":"Czas","url":"https://www.academia.edu/Documents/in/Czas?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_30244825" data-work_id="30244825" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/30244825/%D0%9C%D0%B5%D1%82%D0%BE%D0%B4%D0%B8%D0%BA%D0%B0_%D0%BF%D0%B5%D1%80%D0%B5%D0%B4%D0%BF%D1%80%D0%BE%D0%B3%D0%BD%D0%BE%D0%B7%D0%BD%D0%BE%D0%B3%D0%BE_%D1%84%D1%80%D0%B0%D0%BA%D1%82%D0%B0%D0%BB%D1%8C%D0%BD%D0%BE%D0%B3%D0%BE_%D0%B0%D0%BD%D0%B0%D0%BB%D1%96%D0%B7%D1%83_%D1%87%D0%B0%D1%81%D0%BE%D0%B2%D0%B8%D1%85_%D1%80%D1%8F%D0%B4%D1%96%D0%B2">Методика передпрогнозного фрактального аналізу часових рядів</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Запропоновано методику передпрогнозного фрактального аналізу часових рядів, яка базується на послідовному R/S-аналізі. На основі цієї методики можна визначати рівень персистентності, розраховувати середню величину неперіодичного циклу... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_30244825" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Запропоновано методику передпрогнозного фрактального аналізу часових рядів, яка базується на послідовному R/S-аналізі. На основі цієї методики можна визначати рівень персистентності, розраховувати середню величину неперіодичного циклу часових рядів, а також встановлювати інвестиційну якість (дохідність) активів, які представляються фінансовими часовими рядами. В рамках цієї методики запропоновано критерій визначення середньої довжини періодичного і неперіодичного циклів, на основі згладжування V-статистики за допомогою звичайних плинних середніх та адаптивної плинної Кауфмана. <br /><br />Ключові слова: послідовний R/S-аналіз, показник Херста, часовий ряд, середня довжина неперіодичного циклу, інвестиційна якість фінансових активів <br /><br />Предложена методика предпрогнозного фрактального анализа временных рядов, основанная на последовательном R/S-анализе. На основе этой методики можно определять уровень персистентности, рассчитывать среднюю длину непериодического цикла временных рядов, а также определять инвестиционное качество (доходность) активов, которые задаются финансовыми временными рядами. В рамках этой методики предложен критерий определения средней длины периодического и непериодического циклов на основе сглаживания V-статистики с помощью обычных скользящих средних и адаптивной средней Кауфмана. <br /><br />Ключевые слова: последовательный R/S-анализ, показатель Херста, временной ряд, средняя длина непериодического цикла, инвестиционное качество финансовых активов.<br /><br />The method of pre-forecasting fractal time series analysis, based on the sequential R/S-analysis is offered. Based on this technique it is possible to determine to the level of persistence, to calculate the average length of non-time series periodic cycle, and to establish investment quality (yield) of assets which are represented by financial time series. Under this method the criterion for the average length of periodic and non-periodic cycles determining, based on smoothing the V-statistics using simple moving average and Kaufman adaptive moving average is proposed. <br /><br />Keywords: sequential R/S-analysis, Hurst index, time series, average length of non-time series periodic cycle, investment quality of assets</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/30244825" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="31b19773cb4275f321ff793fc270cad6" rel="nofollow" data-download="{"attachment_id":50710428,"asset_id":30244825,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50710428/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="57383713" href="https://knuba.academia.edu/AlexanderKuchansky">Alexander Kuchansky</a><script data-card-contents-for-user="57383713" type="text/json">{"id":57383713,"first_name":"Alexander","last_name":"Kuchansky","domain_name":"knuba","page_name":"AlexanderKuchansky","display_name":"Alexander Kuchansky","profile_url":"https://knuba.academia.edu/AlexanderKuchansky?f_ri=160248","photo":"https://0.academia-photos.com/57383713/15059432/15795857/s65_alexander.kuchansky.jpg"}</script></span></span></li><li class="js-paper-rank-work_30244825 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="30244825"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 30244825, container: ".js-paper-rank-work_30244825", }); 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$(".js-view-count[data-work-id=30244825]").text(description); $(".js-view-count-work_30244825").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_30244825").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="30244825"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="30485" href="https://www.academia.edu/Documents/in/Time_series_analysis">Time series analysis</a>, <script data-card-contents-for-ri="30485" type="text/json">{"id":30485,"name":"Time series analysis","url":"https://www.academia.edu/Documents/in/Time_series_analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="366369" href="https://www.academia.edu/Documents/in/Time_Series_Forecasting">Time Series Forecasting</a><script data-card-contents-for-ri="366369" type="text/json">{"id":366369,"name":"Time Series Forecasting","url":"https://www.academia.edu/Documents/in/Time_Series_Forecasting?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=30244825]'), work: {"id":30244825,"title":"Методика передпрогнозного фрактального аналізу часових рядів","created_at":"2016-12-04T12:19:11.214-08:00","url":"https://www.academia.edu/30244825/%D0%9C%D0%B5%D1%82%D0%BE%D0%B4%D0%B8%D0%BA%D0%B0_%D0%BF%D0%B5%D1%80%D0%B5%D0%B4%D0%BF%D1%80%D0%BE%D0%B3%D0%BD%D0%BE%D0%B7%D0%BD%D0%BE%D0%B3%D0%BE_%D1%84%D1%80%D0%B0%D0%BA%D1%82%D0%B0%D0%BB%D1%8C%D0%BD%D0%BE%D0%B3%D0%BE_%D0%B0%D0%BD%D0%B0%D0%BB%D1%96%D0%B7%D1%83_%D1%87%D0%B0%D1%81%D0%BE%D0%B2%D0%B8%D1%85_%D1%80%D1%8F%D0%B4%D1%96%D0%B2?f_ri=160248","dom_id":"work_30244825","summary":"Запропоновано методику передпрогнозного фрактального аналізу часових рядів, яка базується на послідовному R/S-аналізі. На основі цієї методики можна визначати рівень персистентності, розраховувати середню величину неперіодичного циклу часових рядів, а також встановлювати інвестиційну якість (дохідність) активів, які представляються фінансовими часовими рядами. В рамках цієї методики запропоновано критерій визначення середньої довжини періодичного і неперіодичного циклів, на основі згладжування V-статистики за допомогою звичайних плинних середніх та адаптивної плинної Кауфмана. \n\nКлючові слова: послідовний R/S-аналіз, показник Херста, часовий ряд, середня довжина неперіодичного циклу, інвестиційна якість фінансових активів \n\nПредложена методика предпрогнозного фрактального анализа временных рядов, основанная на последовательном R/S-анализе. На основе этой методики можно определять уровень персистентности, рассчитывать среднюю длину непериодического цикла временных рядов, а также определять инвестиционное качество (доходность) активов, которые задаются финансовыми временными рядами. В рамках этой методики предложен критерий определения средней длины периодического и непериодического циклов на основе сглаживания V-статистики с помощью обычных скользящих средних и адаптивной средней Кауфмана. \n\nКлючевые слова: последовательный R/S-анализ, показатель Херста, временной ряд, средняя длина непериодического цикла, инвестиционное качество финансовых активов.\n\nThe method of pre-forecasting fractal time series analysis, based on the sequential R/S-analysis is offered. Based on this technique it is possible to determine to the level of persistence, to calculate the average length of non-time series periodic cycle, and to establish investment quality (yield) of assets which are represented by financial time series. Under this method the criterion for the average length of periodic and non-periodic cycles determining, based on smoothing the V-statistics using simple moving average and Kaufman adaptive moving average is proposed. \n\nKeywords: sequential R/S-analysis, Hurst index, time series, average length of non-time series periodic cycle, investment quality of assets","downloadable_attachments":[{"id":50710428,"asset_id":30244825,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":57383713,"first_name":"Alexander","last_name":"Kuchansky","domain_name":"knuba","page_name":"AlexanderKuchansky","display_name":"Alexander Kuchansky","profile_url":"https://knuba.academia.edu/AlexanderKuchansky?f_ri=160248","photo":"https://0.academia-photos.com/57383713/15059432/15795857/s65_alexander.kuchansky.jpg"}],"research_interests":[{"id":30485,"name":"Time series analysis","url":"https://www.academia.edu/Documents/in/Time_series_analysis?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":366369,"name":"Time Series Forecasting","url":"https://www.academia.edu/Documents/in/Time_Series_Forecasting?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_17550018 coauthored" data-work_id="17550018" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/17550018/Surface_EMG_based_muscle_fatigue_evaluation_in_biomechanics">Surface EMG based muscle fatigue evaluation in biomechanics</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/17550018" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="4dca03318428cab6ff87e60fca4b312d" rel="nofollow" data-download="{"attachment_id":41974289,"asset_id":17550018,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/41974289/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37342815" href="https://unizg.academia.edu/STonkovic">S. 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Tonkovic","profile_url":"https://unizg.academia.edu/STonkovic?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-17550018">+2</span><div class="hidden js-additional-users-17550018"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/VladimirMedved">Vladimir Medved</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://unizg.academia.edu/MarioCifrek">Mario Cifrek</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-17550018'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-17550018').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_17550018 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="17550018"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 17550018, container: ".js-paper-rank-work_17550018", }); 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number of undiscovered prospects for lode gold, southwestern Ashanti Belt, Ghana</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/32294864" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="270cc658e80b9dcb952617800aa2f3e7" rel="nofollow" data-download="{"attachment_id":52510856,"asset_id":32294864,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" 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autocorrelation","url":"https://www.academia.edu/Documents/in/Spatial_autocorrelation?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":444165,"name":"Prospectivity Analysis","url":"https://www.academia.edu/Documents/in/Prospectivity_Analysis?f_ri=160248"},{"id":727191,"name":"Fry Analysis","url":"https://www.academia.edu/Documents/in/Fry_Analysis?f_ri=160248"},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248"},{"id":2513107,"name":"parameter space","url":"https://www.academia.edu/Documents/in/parameter_space?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_33771754 coauthored" data-work_id="33771754" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/33771754/Fractal_Aesthetics_in_Architecture">Fractal Aesthetics in Architecture</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper deals with fractal aesthetics and proposes a new fractal analysis method for the perceptual study of architecture. The authors believe in the universality of formulas and aim to complement the architectural description in terms... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_33771754" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper deals with fractal aesthetics and proposes a new fractal analysis method for the perceptual study of architecture. The authors believe in the universality of formulas and aim to complement the architectural description in terms of proportion. Although a well established fractal analysis method to describe the complexity of facades across different scales already exists, box-counting is imprecise because of too many inﬂuences coming along with the method itself. The authors consider the self-similarity as an important part of aesthetic quality in architecture. This is due to the fact that it describes a concept of consistency that holds everything together from the whole to the smallest detail which refers to the classical meaning of the word symmetry. Hence, a new fractal analysis method is introduced which so far has been applied to quantitative linguistics. Basically, elements of different order, called construct/constituent pairs, are counted and related in a formula. In architecture the pairing consists of likewise elements belonging to different orders, from the overview, the fundamental elements to the smaller details. As a conjecture, some preferable fractal dimensions (from the aesthetical point of view) are proposed for architectural structures.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/33771754" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="472c5c4aa1f6fa5f1a8b54cc6f8de336" rel="nofollow" data-download="{"attachment_id":53760450,"asset_id":33771754,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/53760450/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="13002532" href="https://tuwien.academia.edu/WolfgangELorenz">Wolfgang E Lorenz</a><script data-card-contents-for-user="13002532" type="text/json">{"id":13002532,"first_name":"Wolfgang","last_name":"Lorenz","domain_name":"tuwien","page_name":"WolfgangELorenz","display_name":"Wolfgang E Lorenz","profile_url":"https://tuwien.academia.edu/WolfgangELorenz?f_ri=160248","photo":"https://0.academia-photos.com/13002532/11055891/59585805/s65_wolfgang.lorenz.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-33771754">+1</span><div class="hidden js-additional-users-33771754"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://tuwien.academia.edu/GeorgFranck">Georg Franck</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-33771754'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-33771754').html(); 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The authors believe in the universality of formulas and aim to complement the architectural description in terms of proportion. Although a well established fractal analysis method to describe the complexity of facades across different scales already exists, box-counting is imprecise because of too many inﬂuences coming along with the method itself. The authors consider the self-similarity as an important part of aesthetic quality in architecture. This is due to the fact that it describes a concept of consistency that holds everything together from the whole to the smallest detail which refers to the classical meaning of the word symmetry. Hence, a new fractal analysis method is introduced which so far has been applied to quantitative linguistics. Basically, elements of different order, called construct/constituent pairs, are counted and related in a formula. In architecture the pairing consists of likewise elements belonging to different orders, from the overview, the fundamental elements to the smaller details. As a conjecture, some preferable fractal dimensions (from the aesthetical point of view) are proposed for architectural structures.","downloadable_attachments":[{"id":53760450,"asset_id":33771754,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":13002532,"first_name":"Wolfgang","last_name":"Lorenz","domain_name":"tuwien","page_name":"WolfgangELorenz","display_name":"Wolfgang E Lorenz","profile_url":"https://tuwien.academia.edu/WolfgangELorenz?f_ri=160248","photo":"https://0.academia-photos.com/13002532/11055891/59585805/s65_wolfgang.lorenz.jpg"},{"id":19989835,"first_name":"Georg","last_name":"Franck","domain_name":"tuwien","page_name":"GeorgFranck","display_name":"Georg Franck","profile_url":"https://tuwien.academia.edu/GeorgFranck?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":317,"name":"Fractal Geometry","url":"https://www.academia.edu/Documents/in/Fractal_Geometry?f_ri=160248","nofollow":false},{"id":8367,"name":"Complexity","url":"https://www.academia.edu/Documents/in/Complexity?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":837716,"name":"Architectural Analysis","url":"https://www.academia.edu/Documents/in/Architectural_Analysis?f_ri=160248","nofollow":false},{"id":1274468,"name":"Harmonic Proportion","url":"https://www.academia.edu/Documents/in/Harmonic_Proportion?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_27637766" data-work_id="27637766" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/27637766/Fractal_and_nonfractal_properties_of_triadic_Koch_curve">Fractal and nonfractal properties of triadic Koch curve</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/27637766" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="82c78ced18ddc5ee87e84b5ff0df476c" rel="nofollow" data-download="{"attachment_id":47904297,"asset_id":27637766,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/47904297/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="51849852" href="https://independent.academia.edu/NebojsaMilosevi%C4%87">Nebojsa Milosević</a><script data-card-contents-for-user="51849852" type="text/json">{"id":51849852,"first_name":"Nebojsa","last_name":"Milosević","domain_name":"independent","page_name":"NebojsaMilosević","display_name":"Nebojsa Milosević","profile_url":"https://independent.academia.edu/NebojsaMilosevi%C4%87?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_27637766 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="27637766"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 27637766, container: ".js-paper-rank-work_27637766", }); 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On one hand, the objects built by humans become – more and more each day... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_21905285" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The impact that progress in information technology has on the entire activity of humans has proportions and a complexity that are difficult to describe or summarize. On one hand, the objects built by humans become – more and more each day – “smart”, or at least capable of collecting, processing and transmitting information.  However, these objects are increasingly capable of making decisions, based on pre-programmed algorithms or based on heuristic “learning” techniques – through progressive exposure to the environment and the preferences and options of the user. On the other hand, all of the intellectual and even emotional activity of modern man is increasingly assisted and dependent on instruments developed through information technology: databases, search engines, communication devices, operational models, heuristic models.  <br /><br />This progress in information technology has submitted the actual paradigm of scientific knowledge to revision pressures unprecedented from Karl Popper to the present day. The new debate has coagulated like a show around the confrontation between Noam Chomski, the illustrious American linguist and political scientist and Peter Norvig, the leader of the research department in Google company. This confrontation of ideas began in 2011, at the Brains, Minds, and Machines symposium hosted by the Massachusetts Institute of Technology, from „how one can obtain artificial intelligence” and, in a few months, through articles and relatively elaborate interventions [Norvig, 2012] became about „what human knowledge is”. Essentially, it is about knowledge understood as an explicative model, simple enough for every link to be logically comprehensible (Chomski) and, alternatively, knowledge as an informational model, a „black box”, capable of offering increasingly better predictions based on historical data and internal statistical search algorithms (Norvig). The question is: does the progress of knowledge still depend on models that are elegant in their simplicity, logically accessible – in integrity and in detail, models that are continually reviewed to approximate the available data as well as possible? Or are we entering a new era of statistical informational models, capable of continuously processing enormous quantities of data – historical or real time data and providing classifications, predictions, etc. – but without subjacent explanations: we find out how much, when, with associated probabilities, but the question „why?” loses its relevance.<br /><br />In the applied medical sciences, the most significant reflection of this pressure to change the relationship paradigm between historical data – formalized knowledge – the practice of decisions and predictions is Evidence Based Medicine, EBM. It is not a new concept – its origins can be traced (at least) to the comparative clinical study on six groups of patients, through which the British physician James Lind, of the Royal Navy, established in 1747 what the foods than can prevent and treat scurvy – lemons and oranges – were. Isolating vitamin C and clarifying the pathogenesis of scurvy came about almost 200 years later, in 1932, but the prophylactic treatment had already been generalized by the Royal Navy as early as 1787, based on the evidence collected by Lind. The reference definition of EBM was settled in 1996: <br />„the conscious, explicit and judicious use of the best evidence in order to formulate decisions with regard to the treatment of individual patients” [Sackett, 1996]. Best evidence meaning proof (as certain as possible), not explanations (as plausible as possible). In the last few decades, the scope of medical research and the increasing pressure for the maximum but responsible use of the results of this research imposed EBM as a dominant technique for collecting, organizing, evaluating and using medical information; EBM procedures are now standardized at a national and international level, with specialized associations and regulation and certification organizations facilitating the development of work methods [Mayer, 2010].<br /><br />In a good correlation with EBM, a direction of accelerated progress in applying new information techniques in medicine is that of prediction models capable of continuous development, through what is suggestively known as „learning” or „training”. Artificial neural networks are one of the forms that were intensely studied and tested in this context, as part of the research surrounding „artificial intelligence”. Promising results have been reported more and more frequently in applying neural networks to diagnosis [Ganesan, 2010], [Jiang, 2010], [Barwad, 2012], [Amato, 2013], but also to evaluating prognosis and prediction factors [Lundin, 1999]. The number of such factors under evaluation has risen exponentially lately, especially due to the progress in genomics and molecular biology, which gave rise to a necessity for new information instruments, capable of processing such a large data volume.  Prediction based on such information models supplied with huge databases is already transitioning into the current medical practice [Silva, 2015], [Prigg, 2015]: at Beth Israel Deaconess Hospital in Boston USA, Dr. Steven Horng recently announced the operational phase for of an information instrument that allows the formulation of a diagnosis, indicates recommended therapeutic procedures and estimates the prognosis for every patient in intensive therapy.  Dr. Horng, a physician specializing in both emergency medicine and biomedical IT, believes that the accuracy with which the program formulates, for example, the prediction for the imminence of the patient’s death in the next 30 days is over 96%.  The recent and historical clinical and paraclinical data of the patient are introduced into the information model based on similar historical data collected in the last 30 years from over 250000 patients. The database is augmented continuously through the regular collection of information, every 3 minutes, from the physiological data monitors installed for all the patients admitted into the ICU of the hospital.  <br /><br />In the last 30 years, technological progress has brought about a true revolution in medical imagery [Dougherty, 2009]. On one hand, minimally invasive investigation techniques have become accessible for a very large number of patients, both in human and veterinary medicine: MRIs, computerized tomography, nuclear magnetic resonance, confocal reflection microscopy. On the other hand, the increased performance of information instruments facilitates new approaches in distinguishing useful information in medical images [Bubnov, 2014], [Lennon, 2015]. The digital format, practically generalized both for the results in new investigation techniques, as well as for classical microscopy and radiology, now facilitates processing for the extraction of useful information, storing and accessing images, as well as the comparison, morphometric and statistical analysis, identification of regions of interest/lesions etc. [Rangayyan, 2005].<br /><br />The road towards semi-automated and even automated procedures that can be used directly in research, screening, pre-diagnosis or diagnosis is open and is beginning to be intensely exploited, including by the commercial component of medical activity. Using automated and semi-automated procedures also leads to an exponential increase in the volume of collected data which, in turn, reclaims information approaches such as neural networks for processes or such as EBM for testing and application. It is a progress spiral that is presently accelerating and in which man, the professional, the expert, can be centrifugally marginalized towards positions in which he only contributes punctually to ample, interdependent processes that he does not control anymore. It is possible that we are witnessing the dawn of a new historical era, in which the virtual reality created continuously by humans becomes as significant and autonomous as objective reality. Our attempt to know and change reality in its entirety for our own purposes shall inevitably adapt to the new situation.  <br /> <br />Simon Rosenfeld, from the National Cancer Institute – USA, considers that oncology and oncological research are at a critical crossroads with the dynamics of nonlinear systems and research regarding swarm intelligence in the contemporary attempt to offer a new, unifying vision with regard to the way in which systems as diverse as „biological networks, communities of social insects, robotic communities, microbial communities, communities of somatic cells, (…) social networks, and (…) many other systems” [Rosenfeld, 2015] appear and function. Rosenfeld’s unifying vision marks an essential link between carcinogenesis, fractal analysis – that was mainly developed as a modeling instrument for nonlinear dynamic systems and artificial neural networks – that are one of the best documented examples of man-made swarm intelligence.<br /><br />Fractal analysis facilitates the obtaining of measurements, of numbers that quantify the non-periodical complexity that is so characteristic of biological structures, on all size scales in which life is manifested.  This research has investigated the possibility of including fractal analysis applied to histopathological or cytopathological microscopic images amongst the instruments used for diagnosing tumours in animals. I then tested the introduction of the fractal dimension amongst oncological prognostic factors. For this purpose, I developed statistical models and artificial neural network-type models for the survival duration, including the fractal dimension in the set of predictors based on which these models estimate the prognostic for cancer patients.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/21905285" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="753d659e8efbfb3589f6122d8d888b2f" rel="nofollow" data-download="{"attachment_id":42639592,"asset_id":21905285,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/42639592/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5436618" href="https://fmvb.academia.edu/LiviuGaita">Liviu Gaita</a><script data-card-contents-for-user="5436618" type="text/json">{"id":5436618,"first_name":"Liviu","last_name":"Gaita","domain_name":"fmvb","page_name":"LiviuGaita","display_name":"Liviu Gaita","profile_url":"https://fmvb.academia.edu/LiviuGaita?f_ri=160248","photo":"https://0.academia-photos.com/5436618/2388269/2780830/s65_liviu.gaita.jpg"}</script></span></span></li><li class="js-paper-rank-work_21905285 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="21905285"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 21905285, container: ".js-paper-rank-work_21905285", }); 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On one hand, the objects built by humans become – more and more each day – “smart”, or at least capable of collecting, processing and transmitting information. However, these objects are increasingly capable of making decisions, based on pre-programmed algorithms or based on heuristic “learning” techniques – through progressive exposure to the environment and the preferences and options of the user. On the other hand, all of the intellectual and even emotional activity of modern man is increasingly assisted and dependent on instruments developed through information technology: databases, search engines, communication devices, operational models, heuristic models. \n\nThis progress in information technology has submitted the actual paradigm of scientific knowledge to revision pressures unprecedented from Karl Popper to the present day. The new debate has coagulated like a show around the confrontation between Noam Chomski, the illustrious American linguist and political scientist and Peter Norvig, the leader of the research department in Google company. This confrontation of ideas began in 2011, at the Brains, Minds, and Machines symposium hosted by the Massachusetts Institute of Technology, from „how one can obtain artificial intelligence” and, in a few months, through articles and relatively elaborate interventions [Norvig, 2012] became about „what human knowledge is”. Essentially, it is about knowledge understood as an explicative model, simple enough for every link to be logically comprehensible (Chomski) and, alternatively, knowledge as an informational model, a „black box”, capable of offering increasingly better predictions based on historical data and internal statistical search algorithms (Norvig). The question is: does the progress of knowledge still depend on models that are elegant in their simplicity, logically accessible – in integrity and in detail, models that are continually reviewed to approximate the available data as well as possible? Or are we entering a new era of statistical informational models, capable of continuously processing enormous quantities of data – historical or real time data and providing classifications, predictions, etc. – but without subjacent explanations: we find out how much, when, with associated probabilities, but the question „why?” loses its relevance.\n\nIn the applied medical sciences, the most significant reflection of this pressure to change the relationship paradigm between historical data – formalized knowledge – the practice of decisions and predictions is Evidence Based Medicine, EBM. It is not a new concept – its origins can be traced (at least) to the comparative clinical study on six groups of patients, through which the British physician James Lind, of the Royal Navy, established in 1747 what the foods than can prevent and treat scurvy – lemons and oranges – were. Isolating vitamin C and clarifying the pathogenesis of scurvy came about almost 200 years later, in 1932, but the prophylactic treatment had already been generalized by the Royal Navy as early as 1787, based on the evidence collected by Lind. The reference definition of EBM was settled in 1996: \n„the conscious, explicit and judicious use of the best evidence in order to formulate decisions with regard to the treatment of individual patients” [Sackett, 1996]. Best evidence meaning proof (as certain as possible), not explanations (as plausible as possible). In the last few decades, the scope of medical research and the increasing pressure for the maximum but responsible use of the results of this research imposed EBM as a dominant technique for collecting, organizing, evaluating and using medical information; EBM procedures are now standardized at a national and international level, with specialized associations and regulation and certification organizations facilitating the development of work methods [Mayer, 2010].\n\nIn a good correlation with EBM, a direction of accelerated progress in applying new information techniques in medicine is that of prediction models capable of continuous development, through what is suggestively known as „learning” or „training”. Artificial neural networks are one of the forms that were intensely studied and tested in this context, as part of the research surrounding „artificial intelligence”. Promising results have been reported more and more frequently in applying neural networks to diagnosis [Ganesan, 2010], [Jiang, 2010], [Barwad, 2012], [Amato, 2013], but also to evaluating prognosis and prediction factors [Lundin, 1999]. The number of such factors under evaluation has risen exponentially lately, especially due to the progress in genomics and molecular biology, which gave rise to a necessity for new information instruments, capable of processing such a large data volume. Prediction based on such information models supplied with huge databases is already transitioning into the current medical practice [Silva, 2015], [Prigg, 2015]: at Beth Israel Deaconess Hospital in Boston USA, Dr. Steven Horng recently announced the operational phase for of an information instrument that allows the formulation of a diagnosis, indicates recommended therapeutic procedures and estimates the prognosis for every patient in intensive therapy. Dr. Horng, a physician specializing in both emergency medicine and biomedical IT, believes that the accuracy with which the program formulates, for example, the prediction for the imminence of the patient’s death in the next 30 days is over 96%. The recent and historical clinical and paraclinical data of the patient are introduced into the information model based on similar historical data collected in the last 30 years from over 250000 patients. The database is augmented continuously through the regular collection of information, every 3 minutes, from the physiological data monitors installed for all the patients admitted into the ICU of the hospital. \n\nIn the last 30 years, technological progress has brought about a true revolution in medical imagery [Dougherty, 2009]. On one hand, minimally invasive investigation techniques have become accessible for a very large number of patients, both in human and veterinary medicine: MRIs, computerized tomography, nuclear magnetic resonance, confocal reflection microscopy. On the other hand, the increased performance of information instruments facilitates new approaches in distinguishing useful information in medical images [Bubnov, 2014], [Lennon, 2015]. The digital format, practically generalized both for the results in new investigation techniques, as well as for classical microscopy and radiology, now facilitates processing for the extraction of useful information, storing and accessing images, as well as the comparison, morphometric and statistical analysis, identification of regions of interest/lesions etc. [Rangayyan, 2005].\n\nThe road towards semi-automated and even automated procedures that can be used directly in research, screening, pre-diagnosis or diagnosis is open and is beginning to be intensely exploited, including by the commercial component of medical activity. Using automated and semi-automated procedures also leads to an exponential increase in the volume of collected data which, in turn, reclaims information approaches such as neural networks for processes or such as EBM for testing and application. It is a progress spiral that is presently accelerating and in which man, the professional, the expert, can be centrifugally marginalized towards positions in which he only contributes punctually to ample, interdependent processes that he does not control anymore. It is possible that we are witnessing the dawn of a new historical era, in which the virtual reality created continuously by humans becomes as significant and autonomous as objective reality. Our attempt to know and change reality in its entirety for our own purposes shall inevitably adapt to the new situation. \n \nSimon Rosenfeld, from the National Cancer Institute – USA, considers that oncology and oncological research are at a critical crossroads with the dynamics of nonlinear systems and research regarding swarm intelligence in the contemporary attempt to offer a new, unifying vision with regard to the way in which systems as diverse as „biological networks, communities of social insects, robotic communities, microbial communities, communities of somatic cells, (…) social networks, and (…) many other systems” [Rosenfeld, 2015] appear and function. Rosenfeld’s unifying vision marks an essential link between carcinogenesis, fractal analysis – that was mainly developed as a modeling instrument for nonlinear dynamic systems and artificial neural networks – that are one of the best documented examples of man-made swarm intelligence.\n\nFractal analysis facilitates the obtaining of measurements, of numbers that quantify the non-periodical complexity that is so characteristic of biological structures, on all size scales in which life is manifested. This research has investigated the possibility of including fractal analysis applied to histopathological or cytopathological microscopic images amongst the instruments used for diagnosing tumours in animals. I then tested the introduction of the fractal dimension amongst oncological prognostic factors. For this purpose, I developed statistical models and artificial neural network-type models for the survival duration, including the fractal dimension in the set of predictors based on which these models estimate the prognostic for cancer patients. \n","downloadable_attachments":[{"id":42639592,"asset_id":21905285,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5436618,"first_name":"Liviu","last_name":"Gaita","domain_name":"fmvb","page_name":"LiviuGaita","display_name":"Liviu Gaita","profile_url":"https://fmvb.academia.edu/LiviuGaita?f_ri=160248","photo":"https://0.academia-photos.com/5436618/2388269/2780830/s65_liviu.gaita.jpg"}],"research_interests":[{"id":165,"name":"Pathology","url":"https://www.academia.edu/Documents/in/Pathology?f_ri=160248","nofollow":false},{"id":657,"name":"Veterinary Medicine","url":"https://www.academia.edu/Documents/in/Veterinary_Medicine?f_ri=160248","nofollow":false},{"id":6021,"name":"Cancer","url":"https://www.academia.edu/Documents/in/Cancer?f_ri=160248","nofollow":false},{"id":35938,"name":"Digital Image Processing","url":"https://www.academia.edu/Documents/in/Digital_Image_Processing?f_ri=160248","nofollow":false},{"id":51165,"name":"Prognosis and health management","url":"https://www.academia.edu/Documents/in/Prognosis_and_health_management?f_ri=160248"},{"id":54123,"name":"Artificial Neural Networks","url":"https://www.academia.edu/Documents/in/Artificial_Neural_Networks?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":478925,"name":"Virtual Microscopes and Student Learning","url":"https://www.academia.edu/Documents/in/Virtual_Microscopes_and_Student_Learning?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 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end","downloadable_attachments":[{"id":55939434,"asset_id":36053728,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":70433502,"first_name":"Ex","last_name":"Condate","domain_name":"unive","page_name":"excondate","display_name":"Ex Condate","profile_url":"https://unive.academia.edu/excondate?f_ri=160248","photo":"https://0.academia-photos.com/70433502/19134380/86890744/s65_ex.condate.png"}],"research_interests":[{"id":128,"name":"History","url":"https://www.academia.edu/Documents/in/History?f_ri=160248","nofollow":false},{"id":131,"name":"European 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Revolution","url":"https://www.academia.edu/Documents/in/The_Industrial_Revolution?f_ri=160248"},{"id":63804,"name":"Institutions","url":"https://www.academia.edu/Documents/in/Institutions?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":801690,"name":"The Great Divergence","url":"https://www.academia.edu/Documents/in/The_Great_Divergence?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_19020238" data-work_id="19020238" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/19020238/The_Simplest_Ever_Unified_Field_Theory">The Simplest Ever Unified Field Theory</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Regarding the foundations of matter as energy fields in a fractal gearing structure can redefine the foundations of quantum physics in a unique new way, while remaining consistent with modern probabilisitic theories. Further, working... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_19020238" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Regarding the foundations of matter as energy fields in a fractal gearing structure can redefine the foundations of quantum physics in a unique new way, while remaining consistent with modern probabilisitic theories.  Further, working experimental models of fractal gear arrays have created effects that cannot be explained with current theories, and they are described here in detail.  This theory is the only way to explain the experimental phenomenon, and it is an explanation to phenomenon which I have been able to create in the lab for the first time in physics history.  Fractal gear theory is a deterministic model of quantum fields that can be used simultaneously with the current standard model and they both can borrow concepts from each other without breaking the logical consistency.  An example is the double-slit experiment; fractal gear theory states that a harmonic field structure is created by the geometry of the matter (the slits) and the electron or photon rides on it in an oscillatory manner so it does not matter if one or many particles enter simultaneously through the slits.  Many of the modern theories provide quantitative answers to the questions that arise from this new deterministic unified field theory. A prime example is that strings from string theory can be understood as a line of contact thru time within a fractal gear field array.  Physicists today have obfuscated theories with statistical data , whereas most of the real advances in physics have arisen from thought experiments and theoretical and geometric analysis. This theory was devised with very little mathematics and a whole lot of 3D geometry and analysis with almost zero experimental data or references beyond the foundations of modern quantum physics.  It is a grass roots endeavor to start from scratch and rebuild quantum physics with a correct picture that almost any mechanically inclined person can understand; a picture that has eluded physicists for over 100 years.  I believe that if a picture is worth 1000 words, then a geometry is worth 1000 formulas, but geometry is much easier to work with.<br /><br />Fractal gear fields are a quantum foam theory and provides means for transmitting information and by its explanation of emergent space time, it is directly implied that information is able to travel faster than the speed of light within a bound domain.  The speed of transmission dissipates at a rate proportional to the total energy within the domain.  Fractal gear theory is a geometrical foundation for a pilot-wave theory in the spirit of DeBroglie -Bohm theory.  Further, the 3D geometric form of fractal gear fields shows clearly that all bell inequality measurements using photon polarization is biased and in error, due to angular variations in density of the field structure.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/19020238" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="538afdb3cf8451bf14d92c8b6f7e45e0" rel="nofollow" data-download="{"attachment_id":40385293,"asset_id":19020238,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40385293/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37760580" href="https://independent.academia.edu/shareeffahmy">shareef fahmy</a><script data-card-contents-for-user="37760580" type="text/json">{"id":37760580,"first_name":"shareef","last_name":"fahmy","domain_name":"independent","page_name":"shareeffahmy","display_name":"shareef fahmy","profile_url":"https://independent.academia.edu/shareeffahmy?f_ri=160248","photo":"https://0.academia-photos.com/37760580/21164566/29175577/s65_shareef.fahmy.jpg"}</script></span></span></li><li class="js-paper-rank-work_19020238 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="19020238"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 19020238, container: ".js-paper-rank-work_19020238", }); 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$(".js-view-count[data-work-id=19020238]").text(description); $(".js-view-count-work_19020238").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_19020238").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="19020238"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">30</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="317" href="https://www.academia.edu/Documents/in/Fractal_Geometry">Fractal Geometry</a>, <script data-card-contents-for-ri="317" type="text/json">{"id":317,"name":"Fractal Geometry","url":"https://www.academia.edu/Documents/in/Fractal_Geometry?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="518" href="https://www.academia.edu/Documents/in/Quantum_Physics">Quantum Physics</a>, <script data-card-contents-for-ri="518" type="text/json">{"id":518,"name":"Quantum Physics","url":"https://www.academia.edu/Documents/in/Quantum_Physics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1247" href="https://www.academia.edu/Documents/in/Quantum_Gravity">Quantum Gravity</a>, <script data-card-contents-for-ri="1247" type="text/json">{"id":1247,"name":"Quantum Gravity","url":"https://www.academia.edu/Documents/in/Quantum_Gravity?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="3396" href="https://www.academia.edu/Documents/in/Foundations_of_Quantum_Mechanics">Foundations of Quantum Mechanics</a><script data-card-contents-for-ri="3396" type="text/json">{"id":3396,"name":"Foundations of Quantum Mechanics","url":"https://www.academia.edu/Documents/in/Foundations_of_Quantum_Mechanics?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=19020238]'), work: {"id":19020238,"title":"The Simplest Ever Unified Field Theory","created_at":"2015-11-25T18:23:14.305-08:00","url":"https://www.academia.edu/19020238/The_Simplest_Ever_Unified_Field_Theory?f_ri=160248","dom_id":"work_19020238","summary":"Regarding the foundations of matter as energy fields in a fractal gearing structure can redefine the foundations of quantum physics in a unique new way, while remaining consistent with modern probabilisitic theories. Further, working experimental models of fractal gear arrays have created effects that cannot be explained with current theories, and they are described here in detail. This theory is the only way to explain the experimental phenomenon, and it is an explanation to phenomenon which I have been able to create in the lab for the first time in physics history. Fractal gear theory is a deterministic model of quantum fields that can be used simultaneously with the current standard model and they both can borrow concepts from each other without breaking the logical consistency. An example is the double-slit experiment; fractal gear theory states that a harmonic field structure is created by the geometry of the matter (the slits) and the electron or photon rides on it in an oscillatory manner so it does not matter if one or many particles enter simultaneously through the slits. Many of the modern theories provide quantitative answers to the questions that arise from this new deterministic unified field theory. A prime example is that strings from string theory can be understood as a line of contact thru time within a fractal gear field array. Physicists today have obfuscated theories with statistical data , whereas most of the real advances in physics have arisen from thought experiments and theoretical and geometric analysis. This theory was devised with very little mathematics and a whole lot of 3D geometry and analysis with almost zero experimental data or references beyond the foundations of modern quantum physics. It is a grass roots endeavor to start from scratch and rebuild quantum physics with a correct picture that almost any mechanically inclined person can understand; a picture that has eluded physicists for over 100 years. I believe that if a picture is worth 1000 words, then a geometry is worth 1000 formulas, but geometry is much easier to work with.\n\nFractal gear fields are a quantum foam theory and provides means for transmitting information and by its explanation of emergent space time, it is directly implied that information is able to travel faster than the speed of light within a bound domain. The speed of transmission dissipates at a rate proportional to the total energy within the domain. Fractal gear theory is a geometrical foundation for a pilot-wave theory in the spirit of DeBroglie -Bohm theory. Further, the 3D geometric form of fractal gear fields shows clearly that all bell inequality measurements using photon polarization is biased and in error, due to angular variations in density of the field structure.","downloadable_attachments":[{"id":40385293,"asset_id":19020238,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37760580,"first_name":"shareef","last_name":"fahmy","domain_name":"independent","page_name":"shareeffahmy","display_name":"shareef fahmy","profile_url":"https://independent.academia.edu/shareeffahmy?f_ri=160248","photo":"https://0.academia-photos.com/37760580/21164566/29175577/s65_shareef.fahmy.jpg"}],"research_interests":[{"id":317,"name":"Fractal Geometry","url":"https://www.academia.edu/Documents/in/Fractal_Geometry?f_ri=160248","nofollow":false},{"id":518,"name":"Quantum Physics","url":"https://www.academia.edu/Documents/in/Quantum_Physics?f_ri=160248","nofollow":false},{"id":1247,"name":"Quantum Gravity","url":"https://www.academia.edu/Documents/in/Quantum_Gravity?f_ri=160248","nofollow":false},{"id":3396,"name":"Foundations of Quantum Mechanics","url":"https://www.academia.edu/Documents/in/Foundations_of_Quantum_Mechanics?f_ri=160248","nofollow":false},{"id":3504,"name":"General Relativity","url":"https://www.academia.edu/Documents/in/General_Relativity?f_ri=160248"},{"id":4751,"name":"Black Holes","url":"https://www.academia.edu/Documents/in/Black_Holes?f_ri=160248"},{"id":6813,"name":"Quantum Cosmology","url":"https://www.academia.edu/Documents/in/Quantum_Cosmology?f_ri=160248"},{"id":7936,"name":"Quantum Mechanics","url":"https://www.academia.edu/Documents/in/Quantum_Mechanics?f_ri=160248"},{"id":10092,"name":"Quantum Field Theory","url":"https://www.academia.edu/Documents/in/Quantum_Field_Theory?f_ri=160248"},{"id":10598,"name":"String Theory","url":"https://www.academia.edu/Documents/in/String_Theory?f_ri=160248"},{"id":19656,"name":"Special Relativity","url":"https://www.academia.edu/Documents/in/Special_Relativity?f_ri=160248"},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248"},{"id":25955,"name":"Emergent Quantum Gravity","url":"https://www.academia.edu/Documents/in/Emergent_Quantum_Gravity?f_ri=160248"},{"id":28545,"name":"Loop Quantum Gravity","url":"https://www.academia.edu/Documents/in/Loop_Quantum_Gravity?f_ri=160248"},{"id":32764,"name":"String theory (Physics)","url":"https://www.academia.edu/Documents/in/String_theory_Physics_?f_ri=160248"},{"id":39224,"name":"Natural Fractals","url":"https://www.academia.edu/Documents/in/Natural_Fractals?f_ri=160248"},{"id":73135,"name":"Fractals and Waves","url":"https://www.academia.edu/Documents/in/Fractals_and_Waves?f_ri=160248"},{"id":82659,"name":"Space-time","url":"https://www.academia.edu/Documents/in/Space-time?f_ri=160248"},{"id":123242,"name":"String Theory, Quantum Field Theory, Black Holes","url":"https://www.academia.edu/Documents/in/String_Theory_Quantum_Field_Theory_Black_Holes?f_ri=160248"},{"id":156510,"name":"Fractals and multifractals","url":"https://www.academia.edu/Documents/in/Fractals_and_multifractals?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":172625,"name":"Fractal","url":"https://www.academia.edu/Documents/in/Fractal?f_ri=160248"},{"id":252021,"name":"Fractal Dual-Band Monopole Antenna","url":"https://www.academia.edu/Documents/in/Fractal_Dual-Band_Monopole_Antenna?f_ri=160248"},{"id":377788,"name":"FRACTAL COSMOS","url":"https://www.academia.edu/Documents/in/FRACTAL_COSMOS?f_ri=160248"},{"id":550664,"name":"Fractals and Geometry of Nature","url":"https://www.academia.edu/Documents/in/Fractals_and_Geometry_of_Nature-1?f_ri=160248"},{"id":561727,"name":"Twistor Theory","url":"https://www.academia.edu/Documents/in/Twistor_Theory?f_ri=160248"},{"id":730238,"name":"Fractals and Chaos","url":"https://www.academia.edu/Documents/in/Fractals_and_Chaos?f_ri=160248"},{"id":890611,"name":"Fractal Dimension","url":"https://www.academia.edu/Documents/in/Fractal_Dimension?f_ri=160248"},{"id":977414,"name":"Fractal Organization of Nature","url":"https://www.academia.edu/Documents/in/Fractal_Organization_of_Nature?f_ri=160248"},{"id":1029421,"name":"Fractales","url":"https://www.academia.edu/Documents/in/Fractales?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_40388938" data-work_id="40388938" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/40388938/CARACTERIZACI%C3%93N_DE_LA_PASTA_CER%C3%81MICA_ARQUEOL%C3%93GICA_POR_MEDIO_DE_AN%C3%81LISIS_FRACTAL">CARACTERIZACIÓN DE LA PASTA CERÁMICA ARQUEOLÓGICA POR MEDIO DE ANÁLISIS FRACTAL</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">La presente investigación sigue la línea de los estudios tecnológicos de la fabricación cerámica. No se pretende desarrollar un análisis de cadenas operatorias, pero se parte de la idea que una secuencia específica de acciones y gestos... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_40388938" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">La presente investigación sigue la línea de los estudios tecnológicos de la fabricación cerámica. No se pretende desarrollar un análisis de cadenas operatorias, pero se parte de la idea que una secuencia específica de acciones y gestos deja una huella en los materiales arqueológicos y que esa huella puede ser identificada y caracterizada. El proceso de producción de la cerámica es complejo y abarca un número considerable de etapas, desde la selección de la materia prima hasta la decoración posterior a la cocción. En este proceso se anidan varias cadenas operatorias que van a dejar rastro en la pasta cerámica, que es el objeto de esta investigación.  No es la intención identificar los gestos o acciones específicas que dieron como resultado una pasta particular. El objetivo es más modesto. Se trata simplemente de identificar sistemáticamente las distintas pastas presentes en una colección de tiestos arqueológicos.  En esta investigación se propone un método para hacer una caracterización sistemática de la pasta de la cerámica arqueológica que no se base primordialmente en aspectos naturales de la materia prima, sino que se desprenda de las huellas que dejaron los procesos de manufactura. El método que se propone es el análisis fractal del patrón de la pasta.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/40388938" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="fc8f29344ba045f558ab9ed1c5bc3b87" rel="nofollow" data-download="{"attachment_id":60640032,"asset_id":40388938,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/60640032/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5263647" href="https://enah.academia.edu/AGarc%C3%ADa">Alejandro García</a><script data-card-contents-for-user="5263647" type="text/json">{"id":5263647,"first_name":"Alejandro","last_name":"García","domain_name":"enah","page_name":"AGarcía","display_name":"Alejandro García","profile_url":"https://enah.academia.edu/AGarc%C3%ADa?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_40388938 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="40388938"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 40388938, container: ".js-paper-rank-work_40388938", }); 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$(".js-view-count[data-work-id=40388938]").text(description); $(".js-view-count-work_40388938").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_40388938").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="40388938"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">7</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="2213" href="https://www.academia.edu/Documents/in/Pottery_Archaeology_">Pottery (Archaeology)</a>, <script data-card-contents-for-ri="2213" type="text/json">{"id":2213,"name":"Pottery (Archaeology)","url":"https://www.academia.edu/Documents/in/Pottery_Archaeology_?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4651" href="https://www.academia.edu/Documents/in/Mesoamerican_Archaeology">Mesoamerican Archaeology</a>, <script data-card-contents-for-ri="4651" type="text/json">{"id":4651,"name":"Mesoamerican Archaeology","url":"https://www.academia.edu/Documents/in/Mesoamerican_Archaeology?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="16007" href="https://www.academia.edu/Documents/in/Ceramic_Analysis_Archaeology_">Ceramic Analysis (Archaeology)</a>, <script data-card-contents-for-ri="16007" type="text/json">{"id":16007,"name":"Ceramic Analysis (Archaeology)","url":"https://www.academia.edu/Documents/in/Ceramic_Analysis_Archaeology_?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="24829" href="https://www.academia.edu/Documents/in/Mesoamerica">Mesoamerica</a><script data-card-contents-for-ri="24829" type="text/json">{"id":24829,"name":"Mesoamerica","url":"https://www.academia.edu/Documents/in/Mesoamerica?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=40388938]'), work: {"id":40388938,"title":"CARACTERIZACIÓN DE LA PASTA CERÁMICA ARQUEOLÓGICA POR MEDIO DE ANÁLISIS FRACTAL","created_at":"2019-09-18T22:30:33.006-07:00","url":"https://www.academia.edu/40388938/CARACTERIZACI%C3%93N_DE_LA_PASTA_CER%C3%81MICA_ARQUEOL%C3%93GICA_POR_MEDIO_DE_AN%C3%81LISIS_FRACTAL?f_ri=160248","dom_id":"work_40388938","summary":"La presente investigación sigue la línea de los estudios tecnológicos de la fabricación cerámica. No se pretende desarrollar un análisis de cadenas operatorias, pero se parte de la idea que una secuencia específica de acciones y gestos deja una huella en los materiales arqueológicos y que esa huella puede ser identificada y caracterizada. El proceso de producción de la cerámica es complejo y abarca un número considerable de etapas, desde la selección de la materia prima hasta la decoración posterior a la cocción. En este proceso se anidan varias cadenas operatorias que van a dejar rastro en la pasta cerámica, que es el objeto de esta investigación. No es la intención identificar los gestos o acciones específicas que dieron como resultado una pasta particular. El objetivo es más modesto. Se trata simplemente de identificar sistemáticamente las distintas pastas presentes en una colección de tiestos arqueológicos. En esta investigación se propone un método para hacer una caracterización sistemática de la pasta de la cerámica arqueológica que no se base primordialmente en aspectos naturales de la materia prima, sino que se desprenda de las huellas que dejaron los procesos de manufactura. El método que se propone es el análisis fractal del patrón de la pasta.","downloadable_attachments":[{"id":60640032,"asset_id":40388938,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5263647,"first_name":"Alejandro","last_name":"García","domain_name":"enah","page_name":"AGarcía","display_name":"Alejandro García","profile_url":"https://enah.academia.edu/AGarc%C3%ADa?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":2213,"name":"Pottery (Archaeology)","url":"https://www.academia.edu/Documents/in/Pottery_Archaeology_?f_ri=160248","nofollow":false},{"id":4651,"name":"Mesoamerican Archaeology","url":"https://www.academia.edu/Documents/in/Mesoamerican_Archaeology?f_ri=160248","nofollow":false},{"id":16007,"name":"Ceramic Analysis (Archaeology)","url":"https://www.academia.edu/Documents/in/Ceramic_Analysis_Archaeology_?f_ri=160248","nofollow":false},{"id":24829,"name":"Mesoamerica","url":"https://www.academia.edu/Documents/in/Mesoamerica?f_ri=160248","nofollow":false},{"id":66901,"name":"Epiclassic Mesoamerica","url":"https://www.academia.edu/Documents/in/Epiclassic_Mesoamerica?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":2535784,"name":"Xajay","url":"https://www.academia.edu/Documents/in/Xajay?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_8091380" data-work_id="8091380" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/8091380/Fractal_and_multifractal_analysis_A_review">Fractal and multifractal analysis: A review</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/8091380" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="5581da198ed6726c61128e8f786a43f5" rel="nofollow" data-download="{"attachment_id":48216972,"asset_id":8091380,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" 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href="https://www.academia.edu/32294871/Predictive_mapping_of_prospectivity_and_quantitative_estimation_of_undiscovered_VMS_deposits_in_Skellefte_district_Sweden_">Predictive mapping of prospectivity and quantitative estimation of undiscovered VMS deposits in Skellefte district (Sweden)</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/32294871" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="973f85641cb474ac2a47fd0496f7565a" rel="nofollow" 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Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":278386,"name":"JPEG","url":"https://www.academia.edu/Documents/in/JPEG?f_ri=160248"},{"id":322735,"name":"GNSS receivers","url":"https://www.academia.edu/Documents/in/GNSS_receivers?f_ri=160248"},{"id":893719,"name":"Electronic Imaging","url":"https://www.academia.edu/Documents/in/Electronic_Imaging?f_ri=160248"},{"id":924170,"name":"Matrices","url":"https://www.academia.edu/Documents/in/Matrices?f_ri=160248"},{"id":1191356,"name":"Internet","url":"https://www.academia.edu/Documents/in/Internet?f_ri=160248"},{"id":1957069,"name":"Lossless Compression","url":"https://www.academia.edu/Documents/in/Lossless_Compression?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_29775070 coauthored" data-work_id="29775070" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/29775070/Delineation_of_geochemical_anomalies_based_on_stream_sediment_data_utilizing_fractal_modeling_and_staged_factor_analysis">Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_29775070" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/29775070" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ddd9e8749d3999a89d94f566b5a8bf05" rel="nofollow" data-download="{"attachment_id":50226808,"asset_id":29775070,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50226808/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="170622" href="https://feazad.academia.edu/PeymanAfzal">Peyman Afzal</a><script data-card-contents-for-user="170622" type="text/json">{"id":170622,"first_name":"Peyman","last_name":"Afzal","domain_name":"feazad","page_name":"PeymanAfzal","display_name":"Peyman Afzal","profile_url":"https://feazad.academia.edu/PeymanAfzal?f_ri=160248","photo":"https://0.academia-photos.com/170622/42886/7440301/s65_peyman.afzal.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-29775070">+2</span><div class="hidden js-additional-users-29775070"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/MisaghMirzaei">Misagh Mirzaei</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/MahyarYousefi">Mahyar Yousefi</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-29775070'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-29775070').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_29775070 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="29775070"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 29775070; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=29775070]").text(description); $(".js-view-count-work_29775070").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_29775070").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="29775070"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="60585" href="https://www.academia.edu/Documents/in/Factor_analysis">Factor analysis</a>, <script data-card-contents-for-ri="60585" type="text/json">{"id":60585,"name":"Factor analysis","url":"https://www.academia.edu/Documents/in/Factor_analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="801388" href="https://www.academia.edu/Documents/in/Spatial_Analysis_for_Mineral_Prospectivity">Spatial Analysis for Mineral Prospectivity</a>, <script data-card-contents-for-ri="801388" type="text/json">{"id":801388,"name":"Spatial Analysis for Mineral Prospectivity","url":"https://www.academia.edu/Documents/in/Spatial_Analysis_for_Mineral_Prospectivity?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1009312" href="https://www.academia.edu/Documents/in/Geographic_Information_Systems_GIS_">Geographic Information Systems (GIS)</a><script data-card-contents-for-ri="1009312" type="text/json">{"id":1009312,"name":"Geographic Information Systems (GIS)","url":"https://www.academia.edu/Documents/in/Geographic_Information_Systems_GIS_?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=29775070]'), work: {"id":29775070,"title":"Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis","created_at":"2016-11-10T01:10:34.599-08:00","url":"https://www.academia.edu/29775070/Delineation_of_geochemical_anomalies_based_on_stream_sediment_data_utilizing_fractal_modeling_and_staged_factor_analysis?f_ri=160248","dom_id":"work_29775070","summary":"Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.","downloadable_attachments":[{"id":50226808,"asset_id":29775070,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":170622,"first_name":"Peyman","last_name":"Afzal","domain_name":"feazad","page_name":"PeymanAfzal","display_name":"Peyman Afzal","profile_url":"https://feazad.academia.edu/PeymanAfzal?f_ri=160248","photo":"https://0.academia-photos.com/170622/42886/7440301/s65_peyman.afzal.jpg"},{"id":56889868,"first_name":"Misagh","last_name":"Mirzaei","domain_name":"independent","page_name":"MisaghMirzaei","display_name":"Misagh Mirzaei","profile_url":"https://independent.academia.edu/MisaghMirzaei?f_ri=160248","photo":"/images/s65_no_pic.png"},{"id":56694798,"first_name":"Mahyar","last_name":"Yousefi","domain_name":"independent","page_name":"MahyarYousefi","display_name":"Mahyar Yousefi","profile_url":"https://independent.academia.edu/MahyarYousefi?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":60585,"name":"Factor analysis","url":"https://www.academia.edu/Documents/in/Factor_analysis?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":801388,"name":"Spatial Analysis for Mineral Prospectivity","url":"https://www.academia.edu/Documents/in/Spatial_Analysis_for_Mineral_Prospectivity?f_ri=160248","nofollow":false},{"id":1009312,"name":"Geographic Information Systems (GIS)","url":"https://www.academia.edu/Documents/in/Geographic_Information_Systems_GIS_?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_31824813" data-work_id="31824813" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/31824813/A_mathematical_model_of_fluid_flow_in_tight_porous_media_based_on_fractal_assumptions">A mathematical model of fluid flow in tight porous media based on fractal assumptions</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Natural tight reservoirs are networks with high connectivity but low porosity, in which fractal behaviors have been widely observed and proven to affect the transport property significantly. The objective of this study is to establish a... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_31824813" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Natural tight reservoirs are networks with high connectivity but low porosity, in which fractal behaviors have been widely observed and proven to affect the transport property significantly. The objective of this study is to establish a mathematical model to describe fluid flow in fractal tight porous media. To address this problem, four fractal dimensions were used: the pore size fractal dimension D f , geometrical and hydraulic tortuosity fractal dimensions D sg and D s , and the fractal dimension D k characterizing the hydraulic diameter-number distribution. The relationship among these fractal dimensions was analyzed and D f was found equal to D k þ D sg. Then a unified model connecting the porosity and D f is deduced for arbitrary fractal tight porous media. Based on the scaling-invariant behaviors assumed, a fractal mathematical model is developed for the permeability estimation, which is fabricated only by fundamental and well-defined physical properties of D f ; D s , the scaling lacunarity P k , the range of the pore sizes, and the porosity of the fractal generator u 0. To validate the permeability model, we developed an algorithm to model fractal tight porous media according to the scaling-invariant topography of fractal objects based on Voronoi tessellations, and to simulate fluid flow in these complex networks by Lattice Boltzmann method (LBM) at pore scale. Numerical experiments indicate that the hydraulic tortuosity fractal dimension D s is approximately equal to 1.1. Consequently, the fractal mathematical model was quantitatively determined and its performance was verified by the LBM simulations. Finally, the fractal mathematical model was rearranged into a permeability-porosity form for practical applications.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/31824813" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0fe50124c19b44d37ae06deff97c3c0d" rel="nofollow" data-download="{"attachment_id":52119646,"asset_id":31824813,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/52119646/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="17238727" href="https://henanpu.academia.edu/yiJin">yi Jin</a><script data-card-contents-for-user="17238727" type="text/json">{"id":17238727,"first_name":"yi","last_name":"Jin","domain_name":"henanpu","page_name":"yiJin","display_name":"yi Jin","profile_url":"https://henanpu.academia.edu/yiJin?f_ri=160248","photo":"https://0.academia-photos.com/17238727/5176201/89171765/s65_yi.jin.jpg"}</script></span></span></li><li class="js-paper-rank-work_31824813 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="31824813"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 31824813, container: ".js-paper-rank-work_31824813", }); 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$(".js-view-count[data-work-id=31824813]").text(description); $(".js-view-count-work_31824813").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_31824813").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="31824813"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="231216" href="https://www.academia.edu/Documents/in/Tight_Gas_Reserviors">Tight Gas Reserviors</a>, <script data-card-contents-for-ri="231216" type="text/json">{"id":231216,"name":"Tight Gas Reserviors","url":"https://www.academia.edu/Documents/in/Tight_Gas_Reserviors?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1580515" href="https://www.academia.edu/Documents/in/3D_porosity_and_mineralogy_characterization_in_tight_gas_sandstones">3D porosity and mineralogy characterization in tight gas sandstones</a>, <script data-card-contents-for-ri="1580515" type="text/json">{"id":1580515,"name":"3D porosity and mineralogy characterization in tight gas sandstones","url":"https://www.academia.edu/Documents/in/3D_porosity_and_mineralogy_characterization_in_tight_gas_sandstones?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2657126" href="https://www.academia.edu/Documents/in/fractal_topography">fractal topography</a><script data-card-contents-for-ri="2657126" type="text/json">{"id":2657126,"name":"fractal topography","url":"https://www.academia.edu/Documents/in/fractal_topography?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=31824813]'), work: {"id":31824813,"title":"A mathematical model of fluid flow in tight porous media based on fractal assumptions","created_at":"2017-03-11T20:25:55.512-08:00","url":"https://www.academia.edu/31824813/A_mathematical_model_of_fluid_flow_in_tight_porous_media_based_on_fractal_assumptions?f_ri=160248","dom_id":"work_31824813","summary":"Natural tight reservoirs are networks with high connectivity but low porosity, in which fractal behaviors have been widely observed and proven to affect the transport property significantly. The objective of this study is to establish a mathematical model to describe fluid flow in fractal tight porous media. To address this problem, four fractal dimensions were used: the pore size fractal dimension D f , geometrical and hydraulic tortuosity fractal dimensions D sg and D s , and the fractal dimension D k characterizing the hydraulic diameter-number distribution. The relationship among these fractal dimensions was analyzed and D f was found equal to D k þ D sg. Then a unified model connecting the porosity and D f is deduced for arbitrary fractal tight porous media. Based on the scaling-invariant behaviors assumed, a fractal mathematical model is developed for the permeability estimation, which is fabricated only by fundamental and well-defined physical properties of D f ; D s , the scaling lacunarity P k , the range of the pore sizes, and the porosity of the fractal generator u 0. To validate the permeability model, we developed an algorithm to model fractal tight porous media according to the scaling-invariant topography of fractal objects based on Voronoi tessellations, and to simulate fluid flow in these complex networks by Lattice Boltzmann method (LBM) at pore scale. Numerical experiments indicate that the hydraulic tortuosity fractal dimension D s is approximately equal to 1.1. Consequently, the fractal mathematical model was quantitatively determined and its performance was verified by the LBM simulations. Finally, the fractal mathematical model was rearranged into a permeability-porosity form for practical applications.","downloadable_attachments":[{"id":52119646,"asset_id":31824813,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":17238727,"first_name":"yi","last_name":"Jin","domain_name":"henanpu","page_name":"yiJin","display_name":"yi Jin","profile_url":"https://henanpu.academia.edu/yiJin?f_ri=160248","photo":"https://0.academia-photos.com/17238727/5176201/89171765/s65_yi.jin.jpg"}],"research_interests":[{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":231216,"name":"Tight Gas Reserviors","url":"https://www.academia.edu/Documents/in/Tight_Gas_Reserviors?f_ri=160248","nofollow":false},{"id":1580515,"name":"3D porosity and mineralogy characterization in tight gas sandstones","url":"https://www.academia.edu/Documents/in/3D_porosity_and_mineralogy_characterization_in_tight_gas_sandstones?f_ri=160248","nofollow":false},{"id":2657126,"name":"fractal topography","url":"https://www.academia.edu/Documents/in/fractal_topography?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_15398208 coauthored" data-work_id="15398208" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/15398208/OROGENIC_GOLD_PROSPECTIVITY_MAPPING_USING_GEOSPATIAL_DATA_INTEGRATION_REGION_OF_SAQEZ_NW_OF_IRAN">OROGENIC GOLD PROSPECTIVITY MAPPING USING GEOSPATIAL DATA INTEGRATION, REGION OF SAQEZ, NW OF IRAN</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x 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type="text/json">{"id":4165,"name":"Fuzzy Logic","url":"https://www.academia.edu/Documents/in/Fuzzy_Logic?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="275013" href="https://www.academia.edu/Documents/in/Geophysical_Exploration">Geophysical Exploration</a>, <script data-card-contents-for-ri="275013" type="text/json">{"id":275013,"name":"Geophysical Exploration","url":"https://www.academia.edu/Documents/in/Geophysical_Exploration?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="282633" href="https://www.academia.edu/Documents/in/Geochemical_exploration">Geochemical exploration</a><script data-card-contents-for-ri="282633" type="text/json">{"id":282633,"name":"Geochemical exploration","url":"https://www.academia.edu/Documents/in/Geochemical_exploration?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=15398208]'), work: {"id":15398208,"title":"OROGENIC GOLD PROSPECTIVITY MAPPING USING GEOSPATIAL DATA INTEGRATION, REGION OF SAQEZ, NW OF 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Afzal","profile_url":"https://feazad.academia.edu/PeymanAfzal?f_ri=160248","photo":"https://0.academia-photos.com/170622/42886/7440301/s65_peyman.afzal.jpg"},{"id":21869489,"first_name":"Mana","last_name":"Rahimi","domain_name":"independent","page_name":"ManaRahimi","display_name":"Mana Rahimi","profile_url":"https://independent.academia.edu/ManaRahimi?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":4165,"name":"Fuzzy Logic","url":"https://www.academia.edu/Documents/in/Fuzzy_Logic?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":275013,"name":"Geophysical Exploration","url":"https://www.academia.edu/Documents/in/Geophysical_Exploration?f_ri=160248","nofollow":false},{"id":282633,"name":"Geochemical exploration","url":"https://www.academia.edu/Documents/in/Geochemical_exploration?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_29837589" data-work_id="29837589" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/29837589/Visual_Analysis_of_Nonlinear_Dynamical_Systems_Chaos_Fractals_Self_Similarity_and_the_Limits_of_Prediction">Visual Analysis of Nonlinear Dynamical Systems: Chaos, Fractals, Self-Similarity and the Limits of Prediction</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Nearly all nontrivial real-world systems are nonlinear dynamical systems. Chaos describes certain nonlinear dynamical systems that have a very sensitive dependence on initial conditions. Chaotic systems are always deterministic and may be... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_29837589" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Nearly all nontrivial real-world systems are nonlinear dynamical systems. Chaos describes certain nonlinear dynamical systems that have a very sensitive dependence on initial conditions. Chaotic systems are always deterministic and may be very simple, yet they produce completely unpredictable and divergent behavior. Systems of nonlinear equations are difficult to solve analytically, and scientists have relied heavily on visual and qualitative approaches to discover and analyze the dynamics of nonlinearity. Indeed, few fields have drawn as heavily from visualization methods for their seminal innovations: from strange attractors, to bifurcation diagrams, to cobweb plots, to phase diagrams and embedding. Although the social sciences are increasingly studying these types of systems, seminal concepts remain murky or loosely adopted. This article has three aims. First, it argues for several visualization methods to critically analyze and understand the behavior of nonlinear dynamical systems. Second, it uses these visualizations to introduce the foundations of nonlinear dynamics, chaos, fractals, self-similarity and the limits of prediction. Finally, it presents Pynamical, an open-source Python package to easily visualize and explore nonlinear dynamical systems' behavior.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/29837589" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="4dcdb437a1f8dcebd08d3de29f5eaaea" rel="nofollow" data-download="{"attachment_id":50311529,"asset_id":29837589,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50311529/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26869573" href="https://usc.academia.edu/GeoffBoeing">Geoff Boeing</a><script data-card-contents-for-user="26869573" type="text/json">{"id":26869573,"first_name":"Geoff","last_name":"Boeing","domain_name":"usc","page_name":"GeoffBoeing","display_name":"Geoff Boeing","profile_url":"https://usc.academia.edu/GeoffBoeing?f_ri=160248","photo":"https://0.academia-photos.com/26869573/7564380/15674607/s65_geoff.boeing.jpg"}</script></span></span></li><li class="js-paper-rank-work_29837589 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="29837589"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 29837589, container: ".js-paper-rank-work_29837589", }); 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Chaos describes certain nonlinear dynamical systems that have a very sensitive dependence on initial conditions. Chaotic systems are always deterministic and may be very simple, yet they produce completely unpredictable and divergent behavior. Systems of nonlinear equations are difficult to solve analytically, and scientists have relied heavily on visual and qualitative approaches to discover and analyze the dynamics of nonlinearity. Indeed, few fields have drawn as heavily from visualization methods for their seminal innovations: from strange attractors, to bifurcation diagrams, to cobweb plots, to phase diagrams and embedding. Although the social sciences are increasingly studying these types of systems, seminal concepts remain murky or loosely adopted. This article has three aims. First, it argues for several visualization methods to critically analyze and understand the behavior of nonlinear dynamical systems. Second, it uses these visualizations to introduce the foundations of nonlinear dynamics, chaos, fractals, self-similarity and the limits of prediction. Finally, it presents Pynamical, an open-source Python package to easily visualize and explore nonlinear dynamical systems' behavior.","downloadable_attachments":[{"id":50311529,"asset_id":29837589,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26869573,"first_name":"Geoff","last_name":"Boeing","domain_name":"usc","page_name":"GeoffBoeing","display_name":"Geoff Boeing","profile_url":"https://usc.academia.edu/GeoffBoeing?f_ri=160248","photo":"https://0.academia-photos.com/26869573/7564380/15674607/s65_geoff.boeing.jpg"}],"research_interests":[{"id":78,"name":"Control Systems Engineering","url":"https://www.academia.edu/Documents/in/Control_Systems_Engineering?f_ri=160248","nofollow":false},{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics?f_ri=160248","nofollow":false},{"id":317,"name":"Fractal 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Physics","url":"https://www.academia.edu/Documents/in/Quantum_Physics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4456" href="https://www.academia.edu/Documents/in/Time_Series">Time Series</a>, <script data-card-contents-for-ri="4456" type="text/json">{"id":4456,"name":"Time Series","url":"https://www.academia.edu/Documents/in/Time_Series?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="57433" href="https://www.academia.edu/Documents/in/Seasonality">Seasonality</a><script data-card-contents-for-ri="57433" type="text/json">{"id":57433,"name":"Seasonality","url":"https://www.academia.edu/Documents/in/Seasonality?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=5368274]'), work: {"id":5368274,"title":"Fractal analysis of river flow 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class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/6547536/A_practical_implementation_of_the_box_counting_algorithm">A practical implementation of the box counting algorithm</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/6547536" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="94a053b1b10ed20d26770cb3d05c3999" rel="nofollow" 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Gonzato","profile_url":"https://independent.academia.edu/GuidoGonzato?f_ri=160248","photo":"https://0.academia-photos.com/5274608/3131841/8904622/s65_guido.gonzato.jpg"}],"research_interests":[{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":550664,"name":"Fractals and Geometry of Nature","url":"https://www.academia.edu/Documents/in/Fractals_and_Geometry_of_Nature-1?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_27004390 coauthored" data-work_id="27004390" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/27004390/A_study_on_Improvisation_in_a_Musical_performance_using_Multifractal_Detrended_Cross_Correlation_Analysis">A study on Improvisation in a Musical performance using Multifractal Detrended Cross Correlation Analysis</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">MFDFA (the most rigorous technique to assess multifractality) was performed on four Hindustani music samples played on same ‘raga’ sung by the same performer. Each music sample was divided into six parts and ‘multifractal spectral width’... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_27004390" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">MFDFA (the most rigorous technique to assess multifractality) was performed on four Hindustani music samples played on same ‘raga’ sung by the same performer. Each music sample was divided into six parts and ‘multifractal spectral width’ was determined for each part corresponding to the four samples. The results obtained reveal that different parts of all the four sound signals possess spectral width of widely varying values. This gives a cue of the so called ‘musical improvisation’ in all music samples, keeping in mind they belong to the bandish part of the same raga. Formal compositions in Hindustani raga<br />are juxtaposed with the improvised portions, where an artist manoeuvers his/her own creativity to bring out a mood that is specific for that particular performance, which is known as ‘improvisation’. Further, this observation hints at the association of different emotions even in the same bandish of the same raga performed by the same artist, this<br />interesting observation cannot be revealed unless rigorous non-linear technique explores the nature of musical structure. In the second part, we applied MFDXA technique to explore more in-depth about ‘improvisation’ and association with emotion. This technique is applied to find the degree of cross-correlation (γx) between the different parts of the samples. Pronounced correlation has been observed in the middle parts of the all the four samples evident from higher values of γx whereas the other parts show weak correlation. This gets further support from the values of spectral width from different parts of the<br />sample — width of those parts is significantly different from other parts. This observation is extremely new both in respect of musical structure of so called improvisation and associated emotion. The importance of this study in application area of cognitive music therapy is immense.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/27004390" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="067c983eb7faf621745936044e12f666" rel="nofollow" data-download="{"attachment_id":47264791,"asset_id":27004390,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/47264791/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2057266" href="https://jadavpur.academia.edu/ShankhaSanyal">Shankha Sanyal</a><script data-card-contents-for-user="2057266" type="text/json">{"id":2057266,"first_name":"Shankha","last_name":"Sanyal","domain_name":"jadavpur","page_name":"ShankhaSanyal","display_name":"Shankha Sanyal","profile_url":"https://jadavpur.academia.edu/ShankhaSanyal?f_ri=160248","photo":"https://0.academia-photos.com/2057266/674578/837182/s65_shankha.sanyal.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-27004390">+1</span><div class="hidden js-additional-users-27004390"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://jadavpur.academia.edu/ArchiBanerjee">Archi Banerjee</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-27004390'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-27004390').html(); 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container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_27004390 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="27004390"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 27004390; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=27004390]").text(description); $(".js-view-count-work_27004390").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_27004390").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="27004390"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="5493" href="https://www.academia.edu/Documents/in/Nonlinear_dynamics">Nonlinear dynamics</a>, <script data-card-contents-for-ri="5493" type="text/json">{"id":5493,"name":"Nonlinear dynamics","url":"https://www.academia.edu/Documents/in/Nonlinear_dynamics?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="21548" href="https://www.academia.edu/Documents/in/Cognitive_Neuroscience">Cognitive Neuroscience</a>, <script data-card-contents-for-ri="21548" type="text/json">{"id":21548,"name":"Cognitive Neuroscience","url":"https://www.academia.edu/Documents/in/Cognitive_Neuroscience?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a><script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=27004390]'), work: {"id":27004390,"title":"A study on Improvisation in a Musical performance using Multifractal Detrended Cross Correlation Analysis","created_at":"2016-07-15T03:06:22.616-07:00","url":"https://www.academia.edu/27004390/A_study_on_Improvisation_in_a_Musical_performance_using_Multifractal_Detrended_Cross_Correlation_Analysis?f_ri=160248","dom_id":"work_27004390","summary":"MFDFA (the most rigorous technique to assess multifractality) was performed on four Hindustani music samples played on same ‘raga’ sung by the same performer. Each music sample was divided into six parts and ‘multifractal spectral width’ was determined for each part corresponding to the four samples. The results obtained reveal that different parts of all the four sound signals possess spectral width of widely varying values. This gives a cue of the so called ‘musical improvisation’ in all music samples, keeping in mind they belong to the bandish part of the same raga. Formal compositions in Hindustani raga\nare juxtaposed with the improvised portions, where an artist manoeuvers his/her own creativity to bring out a mood that is specific for that particular performance, which is known as ‘improvisation’. Further, this observation hints at the association of different emotions even in the same bandish of the same raga performed by the same artist, this\ninteresting observation cannot be revealed unless rigorous non-linear technique explores the nature of musical structure. In the second part, we applied MFDXA technique to explore more in-depth about ‘improvisation’ and association with emotion. This technique is applied to find the degree of cross-correlation (γx) between the different parts of the samples. Pronounced correlation has been observed in the middle parts of the all the four samples evident from higher values of γx whereas the other parts show weak correlation. This gets further support from the values of spectral width from different parts of the\nsample — width of those parts is significantly different from other parts. This observation is extremely new both in respect of musical structure of so called improvisation and associated emotion. The importance of this study in application area of cognitive music therapy is immense.\n","downloadable_attachments":[{"id":47264791,"asset_id":27004390,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":2057266,"first_name":"Shankha","last_name":"Sanyal","domain_name":"jadavpur","page_name":"ShankhaSanyal","display_name":"Shankha Sanyal","profile_url":"https://jadavpur.academia.edu/ShankhaSanyal?f_ri=160248","photo":"https://0.academia-photos.com/2057266/674578/837182/s65_shankha.sanyal.jpg"},{"id":12362104,"first_name":"Archi","last_name":"Banerjee","domain_name":"jadavpur","page_name":"ArchiBanerjee","display_name":"Archi Banerjee","profile_url":"https://jadavpur.academia.edu/ArchiBanerjee?f_ri=160248","photo":"https://0.academia-photos.com/12362104/3744499/4386205/s65_archi.banerjee.jpg"}],"research_interests":[{"id":5493,"name":"Nonlinear dynamics","url":"https://www.academia.edu/Documents/in/Nonlinear_dynamics?f_ri=160248","nofollow":false},{"id":21548,"name":"Cognitive Neuroscience","url":"https://www.academia.edu/Documents/in/Cognitive_Neuroscience?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_20847555" data-work_id="20847555" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/20847555/CO2_addition_and_pressure_effects_on_laminar_and_turbulent_lean_premixed_CH4_air_flames">CO2 addition and pressure effects on laminar and turbulent lean premixed CH4 air flames</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/20847555" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="df5cdd2c4cb68cd7f07855313739780f" rel="nofollow" data-download="{"attachment_id":41595759,"asset_id":20847555,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/41595759/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa 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class="js-view-count-work_20847555 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="20847555"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 20847555; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=20847555]").text(description); $(".js-view-count-work_20847555").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_20847555").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="20847555"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="60" href="https://www.academia.edu/Documents/in/Mechanical_Engineering">Mechanical Engineering</a>, <script data-card-contents-for-ri="60" type="text/json">{"id":60,"name":"Mechanical Engineering","url":"https://www.academia.edu/Documents/in/Mechanical_Engineering?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="72" href="https://www.academia.edu/Documents/in/Chemical_Engineering">Chemical Engineering</a>, <script data-card-contents-for-ri="72" type="text/json">{"id":72,"name":"Chemical Engineering","url":"https://www.academia.edu/Documents/in/Chemical_Engineering?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="4594" href="https://www.academia.edu/Documents/in/Carbon_Dioxide">Carbon Dioxide</a>, <script data-card-contents-for-ri="4594" type="text/json">{"id":4594,"name":"Carbon Dioxide","url":"https://www.academia.edu/Documents/in/Carbon_Dioxide?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9351" href="https://www.academia.edu/Documents/in/Image_Analysis">Image Analysis</a><script data-card-contents-for-ri="9351" type="text/json">{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=20847555]'), work: {"id":20847555,"title":"CO2 addition and pressure effects on laminar and turbulent lean premixed CH4 air flames","created_at":"2016-01-26T12:27:20.441-08:00","url":"https://www.academia.edu/20847555/CO2_addition_and_pressure_effects_on_laminar_and_turbulent_lean_premixed_CH4_air_flames?f_ri=160248","dom_id":"work_20847555","summary":null,"downloadable_attachments":[{"id":41595759,"asset_id":20847555,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":42152728,"first_name":"Christian","last_name":"Chauveau","domain_name":"independent","page_name":"ChristianChauveau","display_name":"Christian Chauveau","profile_url":"https://independent.academia.edu/ChristianChauveau?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":60,"name":"Mechanical Engineering","url":"https://www.academia.edu/Documents/in/Mechanical_Engineering?f_ri=160248","nofollow":false},{"id":72,"name":"Chemical Engineering","url":"https://www.academia.edu/Documents/in/Chemical_Engineering?f_ri=160248","nofollow":false},{"id":4594,"name":"Carbon Dioxide","url":"https://www.academia.edu/Documents/in/Carbon_Dioxide?f_ri=160248","nofollow":false},{"id":9351,"name":"Image Analysis","url":"https://www.academia.edu/Documents/in/Image_Analysis?f_ri=160248","nofollow":false},{"id":47297,"name":"Automotive Engineering","url":"https://www.academia.edu/Documents/in/Automotive_Engineering?f_ri=160248"},{"id":156347,"name":"Methane","url":"https://www.academia.edu/Documents/in/Methane?f_ri=160248"},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":215075,"name":"Experimental Study","url":"https://www.academia.edu/Documents/in/Experimental_Study?f_ri=160248"},{"id":431154,"name":"Fuel Consumption","url":"https://www.academia.edu/Documents/in/Fuel_Consumption?f_ri=160248"},{"id":1205279,"name":"Mie Scattering","url":"https://www.academia.edu/Documents/in/Mie_Scattering?f_ri=160248"},{"id":1231269,"name":"Pressure Effect","url":"https://www.academia.edu/Documents/in/Pressure_Effect?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_214427" data-work_id="214427" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/214427/The_Fractal_Dimensions_of_Lithic_Reduction">The Fractal Dimensions of Lithic Reduction</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/214427" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="fe03920358df7607c6ac77f9d070eb92" rel="nofollow" data-download="{"attachment_id":31545581,"asset_id":214427,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/31545581/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="129957" href="https://fau.academia.edu/CliffordBrown">Clifford Brown</a><script data-card-contents-for-user="129957" type="text/json">{"id":129957,"first_name":"Clifford","last_name":"Brown","domain_name":"fau","page_name":"CliffordBrown","display_name":"Clifford Brown","profile_url":"https://fau.academia.edu/CliffordBrown?f_ri=160248","photo":"https://0.academia-photos.com/129957/34635/31819/s65_clifford.brown.jpg"}</script></span></span></li><li class="js-paper-rank-work_214427 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="214427"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 214427, container: ".js-paper-rank-work_214427", }); });</script></li><li class="js-percentile-work_214427 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 214427; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_214427"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_214427 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="214427"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 214427; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=214427]").text(description); $(".js-view-count-work_214427").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_214427").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="214427"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="392" href="https://www.academia.edu/Documents/in/Archaeology">Archaeology</a>, <script data-card-contents-for-ri="392" type="text/json">{"id":392,"name":"Archaeology","url":"https://www.academia.edu/Documents/in/Archaeology?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="19728" href="https://www.academia.edu/Documents/in/Lithic_Technology">Lithic Technology</a>, <script data-card-contents-for-ri="19728" type="text/json">{"id":19728,"name":"Lithic Technology","url":"https://www.academia.edu/Documents/in/Lithic_Technology?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="24831" href="https://www.academia.edu/Documents/in/Fractals">Fractals</a>, <script data-card-contents-for-ri="24831" type="text/json">{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="105778" href="https://www.academia.edu/Documents/in/Debitage_Analysis">Debitage Analysis</a><script data-card-contents-for-ri="105778" type="text/json">{"id":105778,"name":"Debitage Analysis","url":"https://www.academia.edu/Documents/in/Debitage_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=214427]'), work: {"id":214427,"title":"The Fractal Dimensions of Lithic Reduction","created_at":"2010-02-11T22:27:03.154-08:00","url":"https://www.academia.edu/214427/The_Fractal_Dimensions_of_Lithic_Reduction?f_ri=160248","dom_id":"work_214427","summary":null,"downloadable_attachments":[{"id":31545581,"asset_id":214427,"asset_type":"Work","always_allow_download":false},{"id":708871,"asset_id":214427,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":129957,"first_name":"Clifford","last_name":"Brown","domain_name":"fau","page_name":"CliffordBrown","display_name":"Clifford Brown","profile_url":"https://fau.academia.edu/CliffordBrown?f_ri=160248","photo":"https://0.academia-photos.com/129957/34635/31819/s65_clifford.brown.jpg"}],"research_interests":[{"id":392,"name":"Archaeology","url":"https://www.academia.edu/Documents/in/Archaeology?f_ri=160248","nofollow":false},{"id":19728,"name":"Lithic Technology","url":"https://www.academia.edu/Documents/in/Lithic_Technology?f_ri=160248","nofollow":false},{"id":24831,"name":"Fractals","url":"https://www.academia.edu/Documents/in/Fractals?f_ri=160248","nofollow":false},{"id":105778,"name":"Debitage Analysis","url":"https://www.academia.edu/Documents/in/Debitage_Analysis?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248"},{"id":390335,"name":"Lithic Reduction","url":"https://www.academia.edu/Documents/in/Lithic_Reduction?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_14973761 coauthored" data-work_id="14973761" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/14973761/Using_fractal_image_analysis_to_characterize_microstructure_of_low_fat_stirred_yoghurt_manufactured_with_microparticulated_whey_protein">Using fractal image analysis to characterize microstructure of low-fat stirred yoghurt manufactured with microparticulated whey protein</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/14973761" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="68f51cac3df6941f075d6d11dacbfec4" rel="nofollow" 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type="text/json">{"id":33968931,"first_name":"Richard","last_name":"Ipsen","domain_name":"ku-dk","page_name":"RIpsen","display_name":"Richard Ipsen","profile_url":"https://ku-dk.academia.edu/RIpsen?f_ri=160248","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-14973761">+1</span><div class="hidden js-additional-users-14973761"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/Jos%C3%A9ManuelAmigoRubio">José Manuel Amigo Rubio</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-14973761'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-14973761').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_14973761 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="14973761"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 14973761, container: ".js-paper-rank-work_14973761", }); });</script></li><li class="js-percentile-work_14973761 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 14973761; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_14973761"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_14973761 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="14973761"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 14973761; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=14973761]").text(description); $(".js-view-count-work_14973761").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_14973761").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="14973761"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">6</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="4468" href="https://www.academia.edu/Documents/in/Food_Engineering">Food Engineering</a>, <script data-card-contents-for-ri="4468" type="text/json">{"id":4468,"name":"Food Engineering","url":"https://www.academia.edu/Documents/in/Food_Engineering?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="43974" href="https://www.academia.edu/Documents/in/Wavelets">Wavelets</a>, <script data-card-contents-for-ri="43974" type="text/json">{"id":43974,"name":"Wavelets","url":"https://www.academia.edu/Documents/in/Wavelets?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="174778" href="https://www.academia.edu/Documents/in/Principal_Components_Analysis">Principal Components Analysis</a><script data-card-contents-for-ri="174778" type="text/json">{"id":174778,"name":"Principal Components Analysis","url":"https://www.academia.edu/Documents/in/Principal_Components_Analysis?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=14973761]'), work: {"id":14973761,"title":"Using fractal image analysis to characterize microstructure of low-fat stirred yoghurt manufactured with microparticulated whey protein","created_at":"2015-08-17T00:32:21.780-07:00","url":"https://www.academia.edu/14973761/Using_fractal_image_analysis_to_characterize_microstructure_of_low_fat_stirred_yoghurt_manufactured_with_microparticulated_whey_protein?f_ri=160248","dom_id":"work_14973761","summary":null,"downloadable_attachments":[{"id":43684821,"asset_id":14973761,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":33968931,"first_name":"Richard","last_name":"Ipsen","domain_name":"ku-dk","page_name":"RIpsen","display_name":"Richard Ipsen","profile_url":"https://ku-dk.academia.edu/RIpsen?f_ri=160248","photo":"/images/s65_no_pic.png"},{"id":49175213,"first_name":"José Manuel Amigo","last_name":"Rubio","domain_name":"independent","page_name":"JoséManuelAmigoRubio","display_name":"José Manuel Amigo Rubio","profile_url":"https://independent.academia.edu/Jos%C3%A9ManuelAmigoRubio?f_ri=160248","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":4468,"name":"Food Engineering","url":"https://www.academia.edu/Documents/in/Food_Engineering?f_ri=160248","nofollow":false},{"id":43974,"name":"Wavelets","url":"https://www.academia.edu/Documents/in/Wavelets?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":174778,"name":"Principal Components Analysis","url":"https://www.academia.edu/Documents/in/Principal_Components_Analysis?f_ri=160248","nofollow":false},{"id":549122,"name":"Confocal Laser Scanning Microscopy","url":"https://www.academia.edu/Documents/in/Confocal_Laser_Scanning_Microscopy?f_ri=160248"},{"id":573653,"name":"Food Sciences","url":"https://www.academia.edu/Documents/in/Food_Sciences?f_ri=160248"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_25102001 coauthored" data-work_id="25102001" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25102001/Application_of_fractal_modeling_and_PCA_method_for_hydrothermal_alteration_mapping_in_the_Saveh_area_Central_Iran_based_on_ASTER_multispectral_data">Application of fractal modeling and PCA method for hydrothermal alteration mapping in the Saveh area (Central Iran) based on ASTER multispectral data</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The aim of this study is determination and separation of alteration zones using Concentration-Area (C-A) fractal model based on remote sensing data which has been extracted from Advanced Spaceborne Thermal Emission and Reflection... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_25102001" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The aim of this study is determination and separation of alteration zones using Concentration-Area (C-A) fractal model based on remote sensing data which has been extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The studied area is on the SW part of Saveh, 1:250,000 geological map, which is located in Urumieh-Dokhtar magmatic belt, Central Iran. The pixel values were computed by Principal Component Analysis (PCA) method used to determine phyllic, argillic, and propylitic alteration zones. The C-A fractal model is utilized for separation of different parts of alteration zones due to their intensity. The log-log C-A plots reveal multifractal nature for phyllic, argillic, and propylitic alteration zones. The obtained results based on fractal model show that the main trend of the alteration zones is in NW-SE direction. Compared to the geological map of the study area and copper mineralizations, the alteration zones have been detected properly and correlate with the mineral occurrences, intrusive rock, and faults.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25102001" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="7b9a440d37603e577ad6f0f3c7ea991c" rel="nofollow" data-download="{"attachment_id":45423004,"asset_id":25102001,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45423004/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="170622" href="https://feazad.academia.edu/PeymanAfzal">Peyman Afzal</a><script data-card-contents-for-user="170622" type="text/json">{"id":170622,"first_name":"Peyman","last_name":"Afzal","domain_name":"feazad","page_name":"PeymanAfzal","display_name":"Peyman Afzal","profile_url":"https://feazad.academia.edu/PeymanAfzal?f_ri=160248","photo":"https://0.academia-photos.com/170622/42886/7440301/s65_peyman.afzal.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-25102001">+2</span><div class="hidden js-additional-users-25102001"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/mirsalehmirmohammadi">mirsaleh mirmohammadi</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://tehran.academia.edu/MirkoAhmadfaraj">Mirko Ahmadfaraj</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-25102001'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-25102001').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_25102001 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="25102001"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 25102001, container: ".js-paper-rank-work_25102001", }); });</script></li><li class="js-percentile-work_25102001 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 25102001; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_25102001"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_25102001 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="25102001"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 25102001; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=25102001]").text(description); $(".js-view-count-work_25102001").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_25102001").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="25102001"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="23408" href="https://www.academia.edu/Documents/in/Remote_sensing_and_GIS">Remote sensing and GIS</a>, <script data-card-contents-for-ri="23408" type="text/json">{"id":23408,"name":"Remote sensing and GIS","url":"https://www.academia.edu/Documents/in/Remote_sensing_and_GIS?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="160248" href="https://www.academia.edu/Documents/in/Fractal_Analysis">Fractal Analysis</a>, <script data-card-contents-for-ri="160248" type="text/json">{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="517313" href="https://www.academia.edu/Documents/in/Mineral_Prospecting_Mineral_Exploration_Field_Geology_Ore_mineralogy_Petrography_Ore_Deposits_Modeli">Mineral Prospecting/Mineral Exploration/Field Geology/Ore mineralogy/Petrography/Ore Deposits Modeling</a><script data-card-contents-for-ri="517313" type="text/json">{"id":517313,"name":"Mineral Prospecting/Mineral Exploration/Field Geology/Ore mineralogy/Petrography/Ore Deposits Modeling","url":"https://www.academia.edu/Documents/in/Mineral_Prospecting_Mineral_Exploration_Field_Geology_Ore_mineralogy_Petrography_Ore_Deposits_Modeli?f_ri=160248","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=25102001]'), work: {"id":25102001,"title":"Application of fractal modeling and PCA method for hydrothermal alteration mapping in the Saveh area (Central Iran) based on ASTER multispectral data","created_at":"2016-05-07T00:54:31.793-07:00","url":"https://www.academia.edu/25102001/Application_of_fractal_modeling_and_PCA_method_for_hydrothermal_alteration_mapping_in_the_Saveh_area_Central_Iran_based_on_ASTER_multispectral_data?f_ri=160248","dom_id":"work_25102001","summary":"The aim of this study is determination and separation of alteration zones using Concentration-Area (C-A) fractal model based on remote sensing data which has been extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. The studied area is on the SW part of Saveh, 1:250,000 geological map, which is located in Urumieh-Dokhtar magmatic belt, Central Iran. The pixel values were computed by Principal Component Analysis (PCA) method used to determine phyllic, argillic, and propylitic alteration zones. The C-A fractal model is utilized for separation of different parts of alteration zones due to their intensity. The log-log C-A plots reveal multifractal nature for phyllic, argillic, and propylitic alteration zones. The obtained results based on fractal model show that the main trend of the alteration zones is in NW-SE direction. Compared to the geological map of the study area and copper mineralizations, the alteration zones have been detected properly and correlate with the mineral occurrences, intrusive rock, and faults.","downloadable_attachments":[{"id":45423004,"asset_id":25102001,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":170622,"first_name":"Peyman","last_name":"Afzal","domain_name":"feazad","page_name":"PeymanAfzal","display_name":"Peyman Afzal","profile_url":"https://feazad.academia.edu/PeymanAfzal?f_ri=160248","photo":"https://0.academia-photos.com/170622/42886/7440301/s65_peyman.afzal.jpg"},{"id":32139824,"first_name":"mirsaleh","last_name":"mirmohammadi","domain_name":"independent","page_name":"mirsalehmirmohammadi","display_name":"mirsaleh mirmohammadi","profile_url":"https://independent.academia.edu/mirsalehmirmohammadi?f_ri=160248","photo":"https://0.academia-photos.com/32139824/9805548/10925989/s65_mirsaleh.mirmohammadi.jpg"},{"id":28939540,"first_name":"Mirko","last_name":"Ahmadfaraj","domain_name":"tehran","page_name":"MirkoAhmadfaraj","display_name":"Mirko Ahmadfaraj","profile_url":"https://tehran.academia.edu/MirkoAhmadfaraj?f_ri=160248","photo":"https://0.academia-photos.com/28939540/12734182/14163534/s65_mirko.ahmad_faraj.jpg"}],"research_interests":[{"id":23408,"name":"Remote sensing and GIS","url":"https://www.academia.edu/Documents/in/Remote_sensing_and_GIS?f_ri=160248","nofollow":false},{"id":160248,"name":"Fractal Analysis","url":"https://www.academia.edu/Documents/in/Fractal_Analysis?f_ri=160248","nofollow":false},{"id":517313,"name":"Mineral Prospecting/Mineral Exploration/Field Geology/Ore mineralogy/Petrography/Ore Deposits Modeling","url":"https://www.academia.edu/Documents/in/Mineral_Prospecting_Mineral_Exploration_Field_Geology_Ore_mineralogy_Petrography_Ore_Deposits_Modeli?f_ri=160248","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_3820802" data-work_id="3820802" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/3820802/Habitat_structure_and_vegetation_relationships_in_central_Argentina_salt_marsh_landscapes">Habitat structure and vegetation relationships in central Argentina salt marsh landscapes</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Relationships between habitat structure and spatial variations in vegetation composition were determined in catenas of central Argentina salt marsh landscapes. Vegetation was classified following a multi-technique strategy. An analysis of... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3820802" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Relationships between habitat structure and spatial variations in vegetation composition were determined in catenas of central Argentina salt marsh landscapes. Vegetation was classified following a multi-technique strategy. An analysis of species distributions along an environmental gradient was made and a redundancy analysis was used to relate the environmental variables to vegetation data. The spatial covariation was evaluated through fractal analysis. The vegetation can be divided into four discrete noda that correspond to different topographic positions (summit, backslope, footslope and toeslope, respectively): nodum of Stipa trichotoma + St. tenuissima, nodum of Distichlis scoparia, nodum of Distichlis spicata and nodum of Spartina densiflora. Each of these nodum is characterized by a definite combination of floristic groups. Symmetric aggregation of vegetation borders was observed in all three sites. The existence of vegetation discontinuities along the catenas depended largely on water table depth and salinity which in turn controlled the edaphic salinity. The arrangement of sites by multivariate analysis reflected the influence of a complex gradient representing halomorphic and hydromorphic factors. β-diversity was associated with abrupt changes in the physical structure of the catena for a reduced spatial dimension (300-m scale). Absolute diversity and evenness were higher on the summit and declined progressively toward the toeslope. The rate of change was higher on the backslope and the dominant species have different ecological amplitudes overlapping along the gradient. The main operational factors associated with the floristic differences are: (i) the variations in the chemical composition and the seasonal dynamics of the soil solution in the aerated layer of soils, (ii) the salinity and dynamics of groundwater, and (iii) the length of time that the soil is flooded during the rainy season (summer). The fractal dimension was close to 2, implying weak spatial dependence. Fractal dimension varied as a function of scale. The fractogram only revealed a significant spatial dependence on the summit. This spatial dependence was associated with short distances of gradient showing that the organizational pattern of Distichlis spp.- Spartina was related to combinations of underlying environmental factors rather than to a specific position in the catena. The catenas are highly structured spatially, floristic compositions are inextricably linked to this structure. Habitat complexity may directly affect associated vegetation by regulating the hydrohalomorphic conditions in the aerated layer of the soils. The relationships of the habitat-floristic groups are not simple, hydromorphism interacts in a complex way with halomorphism.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3820802" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c7754f7424b39d1632ab2caefa652c58" rel="nofollow" data-download="{"attachment_id":50125741,"asset_id":3820802,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50125741/download_file?st=MTczMjY4MTg0OCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4701085" href="https://utjp.academia.edu/RolandoLeon">Rolando Leon</a><script data-card-contents-for-user="4701085" type="text/json">{"id":4701085,"first_name":"Rolando","last_name":"Leon","domain_name":"utjp","page_name":"RolandoLeon","display_name":"Rolando Leon","profile_url":"https://utjp.academia.edu/RolandoLeon?f_ri=160248","photo":"https://0.academia-photos.com/4701085/1982512/2341191/s65_rolando.leon.jpg"}</script></span></span></li><li class="js-paper-rank-work_3820802 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3820802"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3820802, container: ".js-paper-rank-work_3820802", }); 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Vegetation was classified following a multi-technique strategy. An analysis of species distributions along an environmental gradient was made and a redundancy analysis was used to relate the environmental variables to vegetation data. The spatial covariation was evaluated through fractal analysis. The vegetation can be divided into four discrete noda that correspond to different topographic positions (summit, backslope, footslope and toeslope, respectively): nodum of Stipa trichotoma + St. tenuissima, nodum of Distichlis scoparia, nodum of Distichlis spicata and nodum of Spartina densiflora. Each of these nodum is characterized by a definite combination of floristic groups. Symmetric aggregation of vegetation borders was observed in all three sites. The existence of vegetation discontinuities along the catenas depended largely on water table depth and salinity which in turn controlled the edaphic salinity. The arrangement of sites by multivariate analysis reflected the influence of a complex gradient representing halomorphic and hydromorphic factors. β-diversity was associated with abrupt changes in the physical structure of the catena for a reduced spatial dimension (300-m scale). Absolute diversity and evenness were higher on the summit and declined progressively toward the toeslope. The rate of change was higher on the backslope and the dominant species have different ecological amplitudes overlapping along the gradient. The main operational factors associated with the floristic differences are: (i) the variations in the chemical composition and the seasonal dynamics of the soil solution in the aerated layer of soils, (ii) the salinity and dynamics of groundwater, and (iii) the length of time that the soil is flooded during the rainy season (summer). The fractal dimension was close to 2, implying weak spatial dependence. Fractal dimension varied as a function of scale. 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