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collocation</title> <meta name="description" content="Search results for: wavelet collocation"> <meta name="keywords" content="wavelet collocation"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="wavelet collocation"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 295</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: wavelet collocation</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25</span> Subsurface Structures Related to the Hydrocarbon Migration and Accumulation in the Afghan Tajik Basin, Northern Afghanistan: Insights from Seismic Attribute Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samim%20Khair%20Mohammad">Samim Khair Mohammad</a>, <a href="https://publications.waset.org/abstracts/search?q=Takeshi%20Tsuji"> Takeshi Tsuji</a>, <a href="https://publications.waset.org/abstracts/search?q=Chanmaly%20Chhun"> Chanmaly Chhun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Afghan Tajik (foreland) basin, located in the depression zone between mountain axes, is under compression and deformation during the collision of India with the Eurasian plate. The southern part of the Afghan Tajik basin in the Northern part of Afghanistan has not been well studied and explored, but considered for the significant potential for oil and gas resources. The Afghan Tajik basin depositional environments (< 8km) resulted from mixing terrestrial and marine systems, which has potential prospects of Jurrasic (deep) and Tertiary (shallow) petroleum systems. We used 2D regional seismic profiles with a total length of 674.8 km (or over an area of 2500 km²) in the southern part of the basin. To characterize hydrocarbon systems and structures in this study area, we applied advanced seismic attributes such as spectral decomposition (10 - 60Hz) based on time-frequency analysis with continuous wavelet transform. The spectral decomposition results yield the (averaging 20 - 30Hz group) spectral amplitude anomaly. Based on this anomaly result, seismic, and structural interpretation, the potential hydrocarbon accumulations were inferred around the main thrust folds in the tertiary (Paleogene+Neogene) petroleum systems, which appeared to be accumulated around the central study area. Furthermore, it seems that hydrocarbons dominantly migrated along the main thrusts and then concentrated around anticline fold systems which could be sealed by mudstone/carbonate rocks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=The%20Afghan%20Tajik%20basin" title="The Afghan Tajik basin">The Afghan Tajik basin</a>, <a href="https://publications.waset.org/abstracts/search?q=seismic%20lines" title=" seismic lines"> seismic lines</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20decomposition" title=" spectral decomposition"> spectral decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=thrust%20folds" title=" thrust folds"> thrust folds</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrocarbon%20reservoirs" title=" hydrocarbon reservoirs"> hydrocarbon reservoirs</a> </p> <a href="https://publications.waset.org/abstracts/168361/subsurface-structures-related-to-the-hydrocarbon-migration-and-accumulation-in-the-afghan-tajik-basin-northern-afghanistan-insights-from-seismic-attribute-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168361.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">114</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">24</span> Applying Image Schemas and Cognitive Metaphors to Teaching/Learning Italian Preposition a in Foreign/Second Language Context</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andrea%20Fiorista">Andrea Fiorista</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The learning of prepositions is a quite problematic aspect in foreign language instruction, and Italian is certainly not an exception. In their prototypical function, prepositions express schematic relations of two entities in a highly abstract, typically image-schematic way. In other terms, prepositions assume concepts such as directionality, collocation of objects in space and time and, in Cognitive Linguistics’ terms, the position of a trajector with respect to a landmark. Learners of different native languages may conceptualize them differently, implying that they are supposed to operate a recategorization (or create new categories) fitting with the target language. However, most current Italian Foreign/Second Language handbooks and didactic grammars do not facilitate learners in carrying out the task, as they tend to provide partial and idiosyncratic descriptions, with the consequent learner’s effort to memorize them, most of the time without success. In their prototypical meaning, prepositions are used to specify precise topographical positions in the physical environment which become less and less accurate as they radiate out from what might be termed a concrete prototype. According to that, the present study aims to elaborate a cognitive and conceptually well-grounded analysis of some extensive uses of the Italian preposition a, in order to propose effective pedagogical solutions in the Teaching/Learning process. Image schemas, cognitive metaphors and embodiment represent efficient cognitive tools in a task like this. Actually, while learning the merely spatial use of the preposition a (e.g. Sono a Roma = I am in Rome; vado a Roma = I am going to Rome,…) is quite straightforward, it is more complex when a appears in constructions such as verbs of motion +a + infinitive (e.g. Vado a studiare = I am going to study), inchoative periphrasis (e.g. Tra poco mi metto a leggere = In a moment I will read), causative construction (e.g. Lui mi ha mandato a lavorare = He sent me to work). The study reports data from a teaching intervention of Focus on Form, in which a basic cognitive schema is used to facilitate both teachers and students to respectively explain/understand the extensive uses of a. The educational material employed translates Cognitive Linguistics’ theoretical assumptions, such as image schemas and cognitive metaphors, into simple images or proto-scenes easily comprehensible for learners. Illustrative material, indeed, is supposed to make metalinguistic contents more accessible. Moreover, the concept of embodiment is pedagogically applied through activities including motion and learners’ bodily involvement. It is expected that replacing rote learning with a methodology that gives grammatical elements a proper meaning, makes learning process more effective both in the short and long term. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20approaches%20to%20language%20teaching" title="cognitive approaches to language teaching">cognitive approaches to language teaching</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20schemas" title=" image schemas"> image schemas</a>, <a href="https://publications.waset.org/abstracts/search?q=embodiment" title=" embodiment"> embodiment</a>, <a href="https://publications.waset.org/abstracts/search?q=Italian%20as%20FL%2FSL" title=" Italian as FL/SL"> Italian as FL/SL</a> </p> <a href="https://publications.waset.org/abstracts/165956/applying-image-schemas-and-cognitive-metaphors-to-teachinglearning-italian-preposition-a-in-foreignsecond-language-context" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165956.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">88</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">23</span> Linear Decoding Applied to V5/MT Neuronal Activity on Past Trials Predicts Current Sensory Choices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ben%20Hadj%20Hassen%20Sameh">Ben Hadj Hassen Sameh</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaillard%20Corentin"> Gaillard Corentin</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Parker"> Andrew Parker</a>, <a href="https://publications.waset.org/abstracts/search?q=Kristine%20Krug"> Kristine Krug</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=perception" title="perception">perception</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20making" title=" decision making"> decision making</a>, <a href="https://publications.waset.org/abstracts/search?q=attention" title=" attention"> attention</a>, <a href="https://publications.waset.org/abstracts/search?q=decoding" title=" decoding"> decoding</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20system" title=" visual system"> visual system</a> </p> <a href="https://publications.waset.org/abstracts/154327/linear-decoding-applied-to-v5mt-neuronal-activity-on-past-trials-predicts-current-sensory-choices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154327.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">141</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22</span> Visualization Tool for EEG Signal Segmentation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sweeti">Sweeti</a>, <a href="https://publications.waset.org/abstracts/search?q=Anoop%20Kant%20Godiyal"> Anoop Kant Godiyal</a>, <a href="https://publications.waset.org/abstracts/search?q=Neha%20Singh"> Neha Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Sneh%20Anand"> Sneh Anand</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20K.%20Panigrahi"> B. K. Panigrahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jayasree%20Santhosh"> Jayasree Santhosh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=de-noising" title="de-noising">de-noising</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-channel%20data" title=" multi-channel data"> multi-channel data</a>, <a href="https://publications.waset.org/abstracts/search?q=PCA" title=" PCA"> PCA</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20spectra" title=" power spectra"> power spectra</a>, <a href="https://publications.waset.org/abstracts/search?q=segmentation" title=" segmentation"> segmentation</a> </p> <a href="https://publications.waset.org/abstracts/37186/visualization-tool-for-eeg-signal-segmentation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37186.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">401</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">21</span> Quantitative Evaluation of Supported Catalysts Key Properties from Electron Tomography Studies: Assessing Accuracy Using Material-Realistic 3D-Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ainouna%20Bouziane">Ainouna Bouziane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ability of Electron Tomography to recover the 3D structure of catalysts, with spatial resolution in the subnanometer scale, has been widely explored and reviewed in the last decades. A variety of experimental techniques, based either on Transmission Electron Microscopy (TEM) or Scanning Transmission Electron Microscopy (STEM) have been used to reveal different features of nanostructured catalysts in 3D, but High Angle Annular Dark Field imaging in STEM mode (HAADF-STEM) stands out as the most frequently used, given its chemical sensitivity and avoidance of imaging artifacts related to diffraction phenomena when dealing with crystalline materials. In this regard, our group has developed a methodology that combines image denoising by undecimated wavelet transforms (UWT) with automated, advanced segmentation procedures and parameter selection methods using CS-TVM (Compressed Sensing-total variation minimization) algorithms to reveal more reliable quantitative information out of the 3D characterization studies. However, evaluating the accuracy of the magnitudes estimated from the segmented volumes is also an important issue that has not been properly addressed yet, because a perfectly known reference is needed. The problem particularly complicates in the case of multicomponent material systems. To tackle this key question, we have developed a methodology that incorporates volume reconstruction/segmentation methods. In particular, we have established an approach to evaluate, in quantitative terms, the accuracy of TVM reconstructions, which considers the influence of relevant experimental parameters like the range of tilt angles, image noise level or object orientation. The approach is based on the analysis of material-realistic, 3D phantoms, which include the most relevant features of the system under analysis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electron%20tomography" title="electron tomography">electron tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=supported%20catalysts" title=" supported catalysts"> supported catalysts</a>, <a href="https://publications.waset.org/abstracts/search?q=nanometrology" title=" nanometrology"> nanometrology</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20assessment" title=" error assessment"> error assessment</a> </p> <a href="https://publications.waset.org/abstracts/170855/quantitative-evaluation-of-supported-catalysts-key-properties-from-electron-tomography-studies-assessing-accuracy-using-material-realistic-3d-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170855.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">88</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20</span> Identification of Text Domains and Register Variation through the Analysis of Lexical Distribution in a Bangla Mass Media Text Corpus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahul%20Bhattacharyya">Mahul Bhattacharyya</a>, <a href="https://publications.waset.org/abstracts/search?q=Niladri%20Sekhar%20Dash"> Niladri Sekhar Dash</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present research paper is an experimental attempt to investigate the nature of variation in the register in three major text domains, namely, social, cultural, and political texts collected from the corpus of Bangla printed mass media texts. This present study uses a corpus of a moderate amount of Bangla mass media text that contains nearly one million words collected from different media sources like newspapers, magazines, advertisements, periodicals, etc. The analysis of corpus data reveals that each text has certain lexical properties that not only control their identity but also mark their uniqueness across the domains. At first, the subject domains of the texts are classified into two parameters namely, ‘Genre' and 'Text Type'. Next, some empirical investigations are made to understand how the domains vary from each other in terms of lexical properties like both function and content words. Here the method of comparative-cum-contrastive matching of lexical load across domains is invoked through word frequency count to track how domain-specific words and terms may be marked as decisive indicators in the act of specifying the textual contexts and subject domains. The study shows that the common lexical stock that percolates across all text domains are quite dicey in nature as their lexicological identity does not have any bearing in the act of specifying subject domains. Therefore, it becomes necessary for language users to anchor upon certain domain-specific lexical items to recognize a text that belongs to a specific text domain. The eventual findings of this study confirm that texts belonging to different subject domains in Bangla news text corpus clearly differ on the parameters of lexical load, lexical choice, lexical clustering, lexical collocation. In fact, based on these parameters, along with some statistical calculations, it is possible to classify mass media texts into different types to mark their relation with regard to the domains they should actually belong. The advantage of this analysis lies in the proper identification of the linguistic factors which will give language users a better insight into the method they employ in text comprehension, as well as construct a systemic frame for designing text identification strategy for language learners. The availability of huge amount of Bangla media text data is useful for achieving accurate conclusions with a certain amount of reliability and authenticity. This kind of corpus-based analysis is quite relevant for a resource-poor language like Bangla, as no attempt has ever been made to understand how the structure and texture of Bangla mass media texts vary due to certain linguistic and extra-linguistic constraints that are actively operational to specific text domains. Since mass media language is assumed to be the most 'recent representation' of the actual use of the language, this study is expected to show how the Bangla news texts reflect the thoughts of the society and how they leave a strong impact on the thought process of the speech community. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bangla" title="Bangla">Bangla</a>, <a href="https://publications.waset.org/abstracts/search?q=corpus" title=" corpus"> corpus</a>, <a href="https://publications.waset.org/abstracts/search?q=discourse" title=" discourse"> discourse</a>, <a href="https://publications.waset.org/abstracts/search?q=domains" title=" domains"> domains</a>, <a href="https://publications.waset.org/abstracts/search?q=lexical%20choice" title=" lexical choice"> lexical choice</a>, <a href="https://publications.waset.org/abstracts/search?q=mass%20media" title=" mass media"> mass media</a>, <a href="https://publications.waset.org/abstracts/search?q=register" title=" register"> register</a>, <a href="https://publications.waset.org/abstracts/search?q=variation" title=" variation"> variation</a> </p> <a href="https://publications.waset.org/abstracts/82473/identification-of-text-domains-and-register-variation-through-the-analysis-of-lexical-distribution-in-a-bangla-mass-media-text-corpus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82473.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">174</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19</span> Impact of Geomagnetic Storm on Ionosphere</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Affan%20Ahmed">Affan Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research investigates the impact of the geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=geomagnetic%20storms" title="geomagnetic storms">geomagnetic storms</a>, <a href="https://publications.waset.org/abstracts/search?q=ionospheric%20disturbances" title=" ionospheric disturbances"> ionospheric disturbances</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20weather%20effects" title=" space weather effects"> space weather effects</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetosphere-ionosphere%20coupling" title=" magnetosphere-ionosphere coupling"> magnetosphere-ionosphere coupling</a> </p> <a href="https://publications.waset.org/abstracts/195423/impact-of-geomagnetic-storm-on-ionosphere" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/195423.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">13</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18</span> Multiscale Simulation of Absolute Permeability in Carbonate Samples Using 3D X-Ray Micro Computed Tomography Images Textures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20S.%20Jouini">M. S. Jouini</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Al-Sumaiti"> A. Al-Sumaiti</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Tembely"> M. Tembely</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Rahimov"> K. Rahimov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Characterizing rock properties of carbonate reservoirs is highly challenging because of rock heterogeneities revealed at several length scales. In the last two decades, the Digital Rock Physics (DRP) approach was implemented successfully in sandstone rocks reservoirs in order to understand rock properties behaviour at the pore scale. This approach uses 3D X-ray Microtomography images to characterize pore network and also simulate rock properties from these images. Even though, DRP is able to predict realistic rock properties results in sandstone reservoirs it is still suffering from a lack of clear workflow in carbonate rocks. The main challenge is the integration of properties simulated at different scales in order to obtain the effective rock property of core plugs. In this paper, we propose several approaches to characterize absolute permeability in some carbonate core plugs samples using multi-scale numerical simulation workflow. In this study, we propose a procedure to simulate porosity and absolute permeability of a carbonate rock sample using textures of Micro-Computed Tomography images. First, we discretize X-Ray Micro-CT image into a regular grid. Then, we use a textural parametric model to classify each cell of the grid using supervised classification. The main parameters are first and second order statistics such as mean, variance, range and autocorrelations computed from sub-bands obtained after wavelet decomposition. Furthermore, we fill permeability property in each cell using two strategies based on numerical simulation values obtained locally on subsets. Finally, we simulate numerically the effective permeability using Darcy’s law simulator. Results obtained for studied carbonate sample shows good agreement with the experimental property. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiscale%20modeling" title="multiscale modeling">multiscale modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=permeability" title=" permeability"> permeability</a>, <a href="https://publications.waset.org/abstracts/search?q=texture" title=" texture"> texture</a>, <a href="https://publications.waset.org/abstracts/search?q=micro-tomography%20images" title=" micro-tomography images"> micro-tomography images</a> </p> <a href="https://publications.waset.org/abstracts/76794/multiscale-simulation-of-absolute-permeability-in-carbonate-samples-using-3d-x-ray-micro-computed-tomography-images-textures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76794.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">183</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17</span> Influence of Geomagnetic Storms on Ionospheric Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Affan%20Ahmed">Affan Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research investigates the Influence of geomagnetic storm occurring from April 22 to April 26, 2023, on the Earth’s ionosphere, with a focus on analyzing specific ionospheric parameters to understand the storm's effects on ionospheric stability and GNSS signal propagation. Geomagnetic storms, caused by intensified solar wind-magnetosphere interactions, can significantly disturb ionospheric conditions, impacting electron density, Total Electron Content (TEC), and thermospheric composition. Such disturbances are particularly relevant to satellite-based navigation and communication systems, as fluctuations in ionospheric parameters can degrade signal integrity and reliability. In this study, data were obtained from multiple sources, including OMNIWeb for parameters like Dst, Kp, Bz, Electric Field, and solar wind pressure, GUVI for O/N₂ ratio maps, and TEC data from low-, mid-, and high-latitude stations available on the IONOLAB website. Additional Equatorial Electrojet (EEJ) and geomagnetic data were acquired from INTERMAGNET. The methodology involved comparing storm-affected data from April 22 to April 26 with quiet days in April 2023, using statistical and wavelet analysis to assess variations in parameters like TEC, O/N₂ ratio, and geomagnetic indices. The results show pronounced fluctuations in TEC and other ionospheric parameters during the main phase of the storm, with spatial variations observed across latitudes, highlighting the global response of the ionosphere to geomagnetic disturbances. The findings underline the storm’s significant impact on ionospheric composition, particularly in mid- and high-latitude regions, which correlates with increased GNSS signal interference in these areas. This study contributes to understanding the ionosphere’s response to geomagnetic activity, emphasizing the need for robust models to predict and mitigate space weather effects on GNSS-dependent technologies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=geomagnetic%20storms" title="geomagnetic storms">geomagnetic storms</a>, <a href="https://publications.waset.org/abstracts/search?q=ionospheric%20disturbances" title=" ionospheric disturbances"> ionospheric disturbances</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20weather%20effects" title=" space weather effects"> space weather effects</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetosphere-ionopheric%20coupling" title=" magnetosphere-ionopheric coupling"> magnetosphere-ionopheric coupling</a> </p> <a href="https://publications.waset.org/abstracts/195427/influence-of-geomagnetic-storms-on-ionospheric-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/195427.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">13</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">16</span> Development of a Computer Aided Diagnosis Tool for Brain Tumor Extraction and Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fathi%20Kallel">Fathi Kallel</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulelah%20Alabd%20Uljabbar"> Abdulelah Alabd Uljabbar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulrahman%20Aldukhail"> Abdulrahman Aldukhail</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulaziz%20Alomran"> Abdulaziz Alomran</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MRI" title="MRI">MRI</a>, <a href="https://publications.waset.org/abstracts/search?q=brain%20tumor" title=" brain tumor"> brain tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=CAD" title=" CAD"> CAD</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=DWT" title=" DWT"> DWT</a>, <a href="https://publications.waset.org/abstracts/search?q=PCA" title=" PCA"> PCA</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/81523/development-of-a-computer-aided-diagnosis-tool-for-brain-tumor-extraction-and-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81523.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">251</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">15</span> Discovery of Exoplanets in Kepler Data Using a Graphics Processing Unit Fast Folding Method and a Deep Learning Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kevin%20Wang">Kevin Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jian%20Ge"> Jian Ge</a>, <a href="https://publications.waset.org/abstracts/search?q=Yinan%20Zhao"> Yinan Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Kevin%20Willis"> Kevin Willis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Kepler has discovered over 4000 exoplanets and candidates. However, current transit planet detection techniques based on the wavelet analysis and the Box Least Squares (BLS) algorithm have limited sensitivity in detecting minor planets with a low signal-to-noise ratio (SNR) and long periods with only 3-4 repeated signals over the mission lifetime of 4 years. This paper presents a novel precise-period transit signal detection methodology based on a new Graphics Processing Unit (GPU) Fast Folding algorithm in conjunction with a Convolutional Neural Network (CNN) to detect low SNR and/or long-period transit planet signals. A comparison with BLS is conducted on both simulated light curves and real data, demonstrating that the new method has higher speed, sensitivity, and reliability. For instance, the new system can detect transits with SNR as low as three while the performance of BLS drops off quickly around SNR of 7. Meanwhile, the GPU Fast Folding method folds light curves 25 times faster than BLS, a significant gain that allows exoplanet detection to occur at unprecedented period precision. This new method has been tested with all known transit signals with 100% confirmation. In addition, this new method has been successfully applied to the Kepler of Interest (KOI) data and identified a few new Earth-sized Ultra-short period (USP) exoplanet candidates and habitable planet candidates. The results highlight the promise for GPU Fast Folding as a replacement to the traditional BLS algorithm for finding small and/or long-period habitable and Earth-sized planet candidates in-transit data taken with Kepler and other space transit missions such as TESS(Transiting Exoplanet Survey Satellite) and PLATO(PLAnetary Transits and Oscillations of stars). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithms" title="algorithms">algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=astronomy%20data%20analysis" title=" astronomy data analysis"> astronomy data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=exoplanet%20detection%20methods" title=" exoplanet detection methods"> exoplanet detection methods</a>, <a href="https://publications.waset.org/abstracts/search?q=small%20planets" title=" small planets"> small planets</a>, <a href="https://publications.waset.org/abstracts/search?q=habitable%20planets" title=" habitable planets"> habitable planets</a>, <a href="https://publications.waset.org/abstracts/search?q=transit%20%20photometry" title=" transit photometry"> transit photometry</a> </p> <a href="https://publications.waset.org/abstracts/140507/discovery-of-exoplanets-in-kepler-data-using-a-graphics-processing-unit-fast-folding-method-and-a-deep-learning-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140507.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">225</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">14</span> An ANOVA-based Sequential Forward Channel Selection Framework for Brain-Computer Interface Application based on EEG Signals Driven by Motor Imagery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Forouzan%20Salehi%20Fergeni">Forouzan Salehi Fergeni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain-computer%20interface" title="brain-computer interface">brain-computer interface</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20selection" title=" channel selection"> channel selection</a>, <a href="https://publications.waset.org/abstracts/search?q=motor%20imagery" title=" motor imagery"> motor imagery</a>, <a href="https://publications.waset.org/abstracts/search?q=support-vector-machine" title=" support-vector-machine"> support-vector-machine</a> </p> <a href="https://publications.waset.org/abstracts/186038/an-anova-based-sequential-forward-channel-selection-framework-for-brain-computer-interface-application-based-on-eeg-signals-driven-by-motor-imagery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186038.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">52</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">13</span> Wearable Antenna for Diagnosis of Parkinson’s Disease Using a Deep Learning Pipeline on Accelerated Hardware</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Subham%20Ghosh">Subham Ghosh</a>, <a href="https://publications.waset.org/abstracts/search?q=Banani%20Basu"> Banani Basu</a>, <a href="https://publications.waset.org/abstracts/search?q=Marami%20Das"> Marami Das</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The development of compact, low-power antenna sensors has resulted in hardware restructuring, allowing for wireless ubiquitous sensing. The antenna sensors can create wireless body-area networks (WBAN) by linking various wireless nodes across the human body. WBAN and IoT applications, such as remote health and fitness monitoring and rehabilitation, are becoming increasingly important. In particular, Parkinson’s disease (PD), a common neurodegenerative disorder, presents clinical features that can be easily misdiagnosed. As a mobility disease, it may greatly benefit from the antenna’s nearfield approach with a variety of activities that can use WBAN and IoT technologies to increase diagnosis accuracy and patient monitoring. Methodology: This study investigates the feasibility of leveraging a single patch antenna mounted (using cloth) on the wrist dorsal to differentiate actual Parkinson's disease (PD) from false PD using a small hardware platform. The semi-flexible antenna operates at the 2.4 GHz ISM band and collects reflection coefficient (Γ) data from patients performing five exercises designed for the classification of PD and other disorders such as essential tremor (ET) or those physiological disorders caused by anxiety or stress. The obtained data is normalized and converted into 2-D representations using the Gabor wavelet transform (GWT). Data augmentation is then used to expand the dataset size. A lightweight deep-learning (DL) model is developed to run on the GPU-enabled NVIDIA Jetson Nano platform. The DL model processes the 2-D images for feature extraction and classification. Findings: The DL model was trained and tested on both the original and augmented datasets, thus doubling the dataset size. To ensure robustness, a 5-fold stratified cross-validation (5-FSCV) method was used. The proposed framework, utilizing a DL model with 1.356 million parameters on the NVIDIA Jetson Nano, achieved optimal performance in terms of accuracy of 88.64%, F1-score of 88.54, and recall of 90.46%, with a latency of 33 seconds per epoch. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antenna" title="antenna">antenna</a>, <a href="https://publications.waset.org/abstracts/search?q=deep-learning" title=" deep-learning"> deep-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=GPU-hardware" title=" GPU-hardware"> GPU-hardware</a>, <a href="https://publications.waset.org/abstracts/search?q=Parkinson%E2%80%99s%20disease" title=" Parkinson’s disease"> Parkinson’s disease</a> </p> <a href="https://publications.waset.org/abstracts/194610/wearable-antenna-for-diagnosis-of-parkinsons-disease-using-a-deep-learning-pipeline-on-accelerated-hardware" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194610.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">11</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">12</span> Ischemic Stroke Detection in Computed Tomography Examinations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Allan%20F.%20F.%20Alves">Allan F. F. Alves</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernando%20A.%20Bacchim%20Neto"> Fernando A. Bacchim Neto</a>, <a href="https://publications.waset.org/abstracts/search?q=Guilherme%20Giacomini"> Guilherme Giacomini</a>, <a href="https://publications.waset.org/abstracts/search?q=Marcela%20de%20Oliveira"> Marcela de Oliveira</a>, <a href="https://publications.waset.org/abstracts/search?q=Ana%20L.%20M.%20Pavan"> Ana L. M. Pavan</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20E.%20D.%20Rosa"> Maria E. D. Rosa</a>, <a href="https://publications.waset.org/abstracts/search?q=Diana%20R.%20Pina"> Diana R. Pina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ischemic%20stroke" title="ischemic stroke">ischemic stroke</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a>, <a href="https://publications.waset.org/abstracts/search?q=CT%20scans" title=" CT scans"> CT scans</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuzzy%20C-means" title=" Fuzzy C-means "> Fuzzy C-means </a> </p> <a href="https://publications.waset.org/abstracts/39714/ischemic-stroke-detection-in-computed-tomography-examinations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39714.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11</span> Gestalt in Music and Brain: A Non-Linear Chaos Based Study with Detrended/Adaptive Fractal Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shankha%20Sanyal">Shankha Sanyal</a>, <a href="https://publications.waset.org/abstracts/search?q=Archi%20Banerjee"> Archi Banerjee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sayan%20Biswas"> Sayan Biswas</a>, <a href="https://publications.waset.org/abstracts/search?q=Sourya%20Sengupta"> Sourya Sengupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Sayan%20Nag"> Sayan Nag</a>, <a href="https://publications.waset.org/abstracts/search?q=Ranjan%20Sengupta"> Ranjan Sengupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Dipak%20Ghosh"> Dipak Ghosh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AFA" title="AFA">AFA</a>, <a href="https://publications.waset.org/abstracts/search?q=DFA" title=" DFA"> DFA</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=gestalt%20in%20music" title=" gestalt in music"> gestalt in music</a>, <a href="https://publications.waset.org/abstracts/search?q=Hurst%20exponent" title=" Hurst exponent"> Hurst exponent</a> </p> <a href="https://publications.waset.org/abstracts/71039/gestalt-in-music-and-brain-a-non-linear-chaos-based-study-with-detrendedadaptive-fractal-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/71039.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">332</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10</span> Comprehensive Analysis of Electrohysterography Signal Features in Term and Preterm Labor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhihui%20Liu">Zhihui Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Dongmei%20Hao"> Dongmei Hao</a>, <a href="https://publications.waset.org/abstracts/search?q=Qian%20Qiu"> Qian Qiu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang%20An"> Yang An</a>, <a href="https://publications.waset.org/abstracts/search?q=Lin%20Yang"> Lin Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Song%20Zhang"> Song Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yimin%20Yang"> Yimin Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xuwen%20Li"> Xuwen Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Dingchang%20Zheng"> Dingchang Zheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrohysterogram" title="electrohysterogram">electrohysterogram</a>, <a href="https://publications.waset.org/abstracts/search?q=feature" title=" feature"> feature</a>, <a href="https://publications.waset.org/abstracts/search?q=preterm%20labor" title=" preterm labor"> preterm labor</a>, <a href="https://publications.waset.org/abstracts/search?q=term%20labor" title=" term labor "> term labor </a> </p> <a href="https://publications.waset.org/abstracts/68367/comprehensive-analysis-of-electrohysterography-signal-features-in-term-and-preterm-labor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68367.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">572</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9</span> Facies Sedimentology and Astronomic Calibration of the Reinech Member (Lutetian)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jihede%20Haj%20Messaoud">Jihede Haj Messaoud</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamdi%20Omar"> Hamdi Omar</a>, <a href="https://publications.waset.org/abstracts/search?q=Hela%20Fakhfakh%20Ben%20Jemia"> Hela Fakhfakh Ben Jemia</a>, <a href="https://publications.waset.org/abstracts/search?q=Chokri%20Yaich"> Chokri Yaich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Upper Lutetian alternating marl–limestone succession of Reineche Member was deposited over a warm shallow carbonate platform that permits Nummulites proliferation. High-resolution studies of 30 meters thick Nummulites-bearing Reineche Member, cropping out in Central Tunisia (Jebel Siouf), have been undertaken, regarding pronounced cyclical sedimentary sequences, in order to investigate the periodicity of cycles and their related orbital-scale oceanic and climatic changes. The palaeoenvironmental and palaeoclimatic data are preserved in several proxies obtainable through high-resolution sampling and laboratories measurement and analysis as magnetic susceptibility (MS) and carbonates contents in conjunction with a wireline logging tools. The time series analysis of proxies permits to establish cyclicity orders present in the studied intervals which could be linked to the orbital cycles. MS records provide high-resolution proxies for relative sea level change in Late Lutetian strata. The spectral analysis of MS fluctuations confirmed the orbital forcing by the presence of the complete suite of orbital frequencies in the precession of 23 ka, the obliquity of 41 ka, and notably the two modes of eccentricity of 100 and 405 ka. Regarding the two periodic sedimentary cycles detected by wavelet analysis of proxy fluctuations which coincide with the long-term 405 ka eccentricity cycle, the Reineche Member spanned 0,8 Myr. Wireline logging tools as gamma ray and sonic were used as a proxies to decipher cyclicity and trends in sedimentation and contribute to identifying and correlate units. There are used to constraint the highest frequency cyclicity modulated by a long term wavelength cycling apparently controlled by clay content. Interpreted as a result of variations in carbonate productivity, it has been suggested that the marl-limestone couplets, represent the sedimentary response to the orbital forcing. The calculation of cycle durations through Reineche Member, is used as a geochronometer and permit the astronomical calibration of the geologic time scale. Furthermore, MS coupled with carbonate contents, and fossil occurrences provide strong evidence for combined detrital inputs and marine surface carbonate productivity cycles. These two synchronous processes were driven by the precession index and ‘fingerprinted’ in the basic marl–limestone couplets, modulated by orbital eccentricity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=magnetic%20susceptibility" title="magnetic susceptibility">magnetic susceptibility</a>, <a href="https://publications.waset.org/abstracts/search?q=cyclostratigraphy" title=" cyclostratigraphy"> cyclostratigraphy</a>, <a href="https://publications.waset.org/abstracts/search?q=orbital%20forcing" title=" orbital forcing"> orbital forcing</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20analysis" title=" spectral analysis"> spectral analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=Lutetian" title=" Lutetian"> Lutetian</a> </p> <a href="https://publications.waset.org/abstracts/54761/facies-sedimentology-and-astronomic-calibration-of-the-reinech-member-lutetian" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54761.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">294</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> Comparison of the Effectiveness of Tree Algorithms in Classification of Spongy Tissue Texture</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Roza%20Dzierzak">Roza Dzierzak</a>, <a href="https://publications.waset.org/abstracts/search?q=Waldemar%20Wojcik"> Waldemar Wojcik</a>, <a href="https://publications.waset.org/abstracts/search?q=Piotr%20Kacejko"> Piotr Kacejko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=texture%20analysis" title=" texture analysis"> texture analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=tree%20algorithms" title=" tree algorithms"> tree algorithms</a> </p> <a href="https://publications.waset.org/abstracts/107923/comparison-of-the-effectiveness-of-tree-algorithms-in-classification-of-spongy-tissue-texture" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107923.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">180</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> Factors Affecting Air Surface Temperature Variations in the Philippines </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=John%20Christian%20Lequiron">John Christian Lequiron</a>, <a href="https://publications.waset.org/abstracts/search?q=Gerry%20Bagtasa"> Gerry Bagtasa</a>, <a href="https://publications.waset.org/abstracts/search?q=Olivia%20Cabrera"> Olivia Cabrera</a>, <a href="https://publications.waset.org/abstracts/search?q=Leoncio%20Amadore"> Leoncio Amadore</a>, <a href="https://publications.waset.org/abstracts/search?q=Tolentino%20Moya"> Tolentino Moya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Changes in air surface temperature play an important role in the Philippine’s economy, industry, health, and food production. While increasing global mean temperature in the recent several decades has prompted a number of climate change and variability studies in the Philippines, most studies still focus on rainfall and tropical cyclones. This study aims to investigate the trend and variability of observed air surface temperature and determine its major influencing factor/s in the Philippines. A non-parametric Mann-Kendall trend test was applied to monthly mean temperature of 17 synoptic stations covering 56 years from 1960 to 2015 and a mean change of 0.58 °C or a positive trend of 0.0105 °C/year (p < 0.05) was found. In addition, wavelet decomposition was used to determine the frequency of temperature variability show a 12-month, 30-80-month and more than 120-month cycles. This indicates strong annual variations, interannual variations that coincide with ENSO events, and interdecadal variations that are attributed to PDO and CO2 concentrations. Air surface temperature was also correlated with smoothed sunspot number and galactic cosmic rays, the results show a low to no effect. The influence of ENSO teleconnection on temperature, wind pattern, cloud cover, and outgoing longwave radiation on different ENSO phases had significant effects on regional temperature variability. Particularly, an anomalous anticyclonic (cyclonic) flow east of the Philippines during the peak and decay phase of El Niño (La Niña) events leads to the advection of warm southeasterly (cold northeasterly) air mass over the country. Furthermore, an apparent increasing cloud cover trend is observed over the West Philippine Sea including portions of the Philippines, and this is believed to lessen the effect of the increasing air surface temperature. However, relative humidity was also found to be increasing especially on the central part of the country, which results in a high positive trend of heat index, exacerbating the effects on human discomfort. Finally, an assessment of gridded temperature datasets was done to look at the viability of using three high-resolution datasets in future climate analysis and model calibration and verification. Several error statistics (i.e. Pearson correlation, Bias, MAE, and RMSE) were used for this validation. Results show that gridded temperature datasets generally follows the observed surface temperature change and anomalies. In addition, it is more representative of regional temperature rather than a substitute to station-observed air temperature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=air%20surface%20temperature" title="air surface temperature">air surface temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=carbon%20dioxide" title=" carbon dioxide"> carbon dioxide</a>, <a href="https://publications.waset.org/abstracts/search?q=ENSO" title=" ENSO"> ENSO</a>, <a href="https://publications.waset.org/abstracts/search?q=galactic%20cosmic%20rays" title=" galactic cosmic rays"> galactic cosmic rays</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothed%20sunspot%20number" title=" smoothed sunspot number"> smoothed sunspot number</a> </p> <a href="https://publications.waset.org/abstracts/58180/factors-affecting-air-surface-temperature-variations-in-the-philippines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58180.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">324</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> A Machine Learning Approach for Assessment of Tremor: A Neurological Movement Disorder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rajesh%20Ranjan">Rajesh Ranjan</a>, <a href="https://publications.waset.org/abstracts/search?q=Marimuthu%20Palaniswami"> Marimuthu Palaniswami</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20A.%20Hashmi"> A. A. Hashmi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20approach%20for%20neurological%20disorder%20assessment" title="machine learning approach for neurological disorder assessment">machine learning approach for neurological disorder assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic%20classification%20of%20tremor%20types" title=" automatic classification of tremor types"> automatic classification of tremor types</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction%20method%20for%20tremor%20classification" title=" feature extraction method for tremor classification"> feature extraction method for tremor classification</a>, <a href="https://publications.waset.org/abstracts/search?q=neurological%20movement%20disorder" title=" neurological movement disorder"> neurological movement disorder</a>, <a href="https://publications.waset.org/abstracts/search?q=parkinsonian%20tremor" title=" parkinsonian tremor"> parkinsonian tremor</a>, <a href="https://publications.waset.org/abstracts/search?q=essential%20tremor" title=" essential tremor"> essential tremor</a> </p> <a href="https://publications.waset.org/abstracts/100383/a-machine-learning-approach-for-assessment-of-tremor-a-neurological-movement-disorder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/100383.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">154</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> Potential of Aerodynamic Feature on Monitoring Multilayer Rough Surfaces</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ibtissem%20Hosni">Ibtissem Hosni</a>, <a href="https://publications.waset.org/abstracts/search?q=Lilia%20Bennaceur%20Farah"> Lilia Bennaceur Farah</a>, <a href="https://publications.waset.org/abstracts/search?q=Saber%20Mohamed%20Naceur"> Saber Mohamed Naceur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aerodynamic" title="aerodynamic">aerodynamic</a>, <a href="https://publications.waset.org/abstracts/search?q=bi-dimensional" title=" bi-dimensional"> bi-dimensional</a>, <a href="https://publications.waset.org/abstracts/search?q=vegetation" title=" vegetation"> vegetation</a>, <a href="https://publications.waset.org/abstracts/search?q=synergistic" title=" synergistic"> synergistic</a> </p> <a href="https://publications.waset.org/abstracts/55360/potential-of-aerodynamic-feature-on-monitoring-multilayer-rough-surfaces" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55360.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Assessment of DNA Sequence Encoding Techniques for Machine Learning Algorithms Using a Universal Bacterial Marker</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diego%20Santiba%C3%B1ez%20Oyarce">Diego Santibañez Oyarce</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernanda%20Bravo%20Cornejo"> Fernanda Bravo Cornejo</a>, <a href="https://publications.waset.org/abstracts/search?q=Camilo%20Cerda%20Sarabia"> Camilo Cerda Sarabia</a>, <a href="https://publications.waset.org/abstracts/search?q=Bel%C3%A9n%20D%C3%ADaz%20D%C3%ADaz"> Belén Díaz Díaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Esteban%20G%C3%B3mez%20Ter%C3%A1n"> Esteban Gómez Terán</a>, <a href="https://publications.waset.org/abstracts/search?q=Hugo%20Osses%20Prado"> Hugo Osses Prado</a>, <a href="https://publications.waset.org/abstracts/search?q=Ra%C3%BAl%20Caulier-Cisterna"> Raúl Caulier-Cisterna</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorge%20Vergara-Quezada"> Jorge Vergara-Quezada</a>, <a href="https://publications.waset.org/abstracts/search?q=Ana%20Moya-Beltr%C3%A1n"> Ana Moya-Beltrán</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DNA%20encoding" title="DNA encoding">DNA encoding</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=Fourier%20transform" title=" Fourier transform"> Fourier transform</a>, <a href="https://publications.waset.org/abstracts/search?q=Fourier%20transformation" title=" Fourier transformation"> Fourier transformation</a> </p> <a href="https://publications.waset.org/abstracts/190369/assessment-of-dna-sequence-encoding-techniques-for-machine-learning-algorithms-using-a-universal-bacterial-marker" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190369.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">28</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> The Touch Sensation: Ageing and Gender Influences </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Abdouni">A. Abdouni</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Thieulin"> C. Thieulin</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Djaghloul"> M. Djaghloul</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Vargiolu"> R. Vargiolu</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Zahouani"> H. Zahouani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A decline in the main sensory modalities (vision, hearing, taste, and smell) is well reported to occur with advancing age, it is expected a similar change to occur with touch sensation and perception. In this study, we have focused on the touch sensations highlighting ageing and gender influences with in vivo systems. The touch process can be divided into two main phases: The first phase is the first contact between the finger and the object, during this contact, an adhesive force has been created which is the needed force to permit an initial movement of the finger. In the second phase, the finger mechanical properties with their surface topography play an important role in the obtained sensation. In order to understand the age and gender effects on the touch sense, we develop different ideas and systems for each phase. To better characterize the contact, the mechanical properties and the surface topography of human finger, in vivo studies on the pulp of 40 subjects (20 of each gender) of four age groups of 26±3, 35+-3, 45+-2 and 58±6 have been performed. To understand the first touch phase a classical indentation system has been adapted to measure the finger contact properties. The normal force load, the indentation speed, the contact time, the penetration depth and the indenter geometry have been optimized. The penetration depth of a glass indenter is recorded as a function of the applied normal force. Main assessed parameter is the adhesive force F_ad. For the second phase, first, an innovative approach is proposed to characterize the dynamic finger mechanical properties. A contactless indentation test inspired from the techniques used in ophthalmology has been used. The test principle is to blow an air blast to the finger and measure the caused deformation by a linear laser. The advantage of this test is the real observation of the skin free return without any outside influence. Main obtained parameters are the wave propagation speed and the Young's modulus E. Second, negative silicon replicas of subject’s fingerprint have been analyzed by a probe laser defocusing. A laser diode transmits a light beam on the surface to be measured, and the reflected signal is returned to a set of four photodiodes. This technology allows reconstructing three-dimensional images. In order to study the age and gender effects on the roughness properties, a multi-scale characterization of roughness has been realized by applying continuous wavelet transform. After determining the decomposition of the surface, the method consists of quantifying the arithmetic mean of surface topographic at each scale SMA. Significant differences of the main parameters are shown with ageing and gender. The comparison between men and women groups reveals that the adhesive force is higher for women. The results of mechanical properties show a Young’s modulus higher for women and also increasing with age. The roughness analysis shows a significant difference in function of age and gender. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ageing" title="ageing">ageing</a>, <a href="https://publications.waset.org/abstracts/search?q=finger" title=" finger"> finger</a>, <a href="https://publications.waset.org/abstracts/search?q=gender" title=" gender"> gender</a>, <a href="https://publications.waset.org/abstracts/search?q=touch" title=" touch"> touch</a> </p> <a href="https://publications.waset.org/abstracts/50180/the-touch-sensation-ageing-and-gender-influences" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50180.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">265</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Decoding Kinematic Characteristics of Finger Movement from Electrocorticography Using Classical Methods and Deep Convolutional Neural Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ksenia%20Volkova">Ksenia Volkova</a>, <a href="https://publications.waset.org/abstracts/search?q=Artur%20Petrosyan"> Artur Petrosyan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ignatii%20Dubyshkin"> Ignatii Dubyshkin</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexei%20Ossadtchi"> Alexei Ossadtchi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain-computer%20interface" title="brain-computer interface">brain-computer interface</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ECoG" title=" ECoG"> ECoG</a>, <a href="https://publications.waset.org/abstracts/search?q=movement%20decoding" title=" movement decoding"> movement decoding</a>, <a href="https://publications.waset.org/abstracts/search?q=sensorimotor%20cortex" title=" sensorimotor cortex"> sensorimotor cortex</a> </p> <a href="https://publications.waset.org/abstracts/88212/decoding-kinematic-characteristics-of-finger-movement-from-electrocorticography-using-classical-methods-and-deep-convolutional-neural-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88212.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">178</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> The Roots of Amazonia’s Droughts and Floods: Complex Interactions of Pacific and Atlantic Sea-Surface Temperatures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rosimeire%20Ara%C3%BAjo%20Silva">Rosimeire Araújo Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=Philip%20Martin%20Fearnside"> Philip Martin Fearnside</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Extreme droughts and floods in the Amazon have serious consequences for natural ecosystems and the human population in the region. The frequency of these events has increased in recent years, and projections of climate change predict greater frequency and intensity of these events. Understanding the links between these extreme events and different patterns of sea surface temperature in the Atlantic and Pacific Oceans is essential, both to improve the modeling of climate change and its consequences and to support efforts of adaptation in the region. The relationship between sea temperatures and events in the Amazon is much more complex than is usually assumed in climatic models. Warming and cooling of different parts of the oceans, as well as the interaction between simultaneous temperature changes in different parts of each ocean and between the two oceans, have specific consequences for the Amazon, with effects on precipitation that vary in different parts of the region. Simplistic generalities, such as the association between El Niño events and droughts in the Amazon, do not capture this complexity. We investigated the variability of Sea Surface Temperature (SST) in the Tropical Pacific Ocean during the period 1950-2022, using Empirical Orthogonal Functions (FOE), spectral analysis coherence and wavelet phase. The two were identified as the main modes of variability, which explain about 53,9% and 13,3%, respectively, of the total variance of the data. The spectral and coherence analysis and wavelets phase showed that the first selected mode represents the warming in the central part of the Pacific Ocean (the “Central El Niño”), while the second mode represents warming in the eastern part of the Pacific (the “Eastern El Niño The effects of the 1982-1983 and 1976-1977 El Niño events in the Amazon, although both events were characterized by an increase in sea surface temperatures in the Equatorial Pacific, the impact on rainfall in the Amazon was distinct. In the rainy season, from December to March, the sub-basins of the Japurá, Jutaí, Jatapu, Tapajós, Trombetas and Xingu rivers were the regions that showed the greatest reductions in rainfall associated with El Niño Central (1982-1983), while the sub-basins of the Javari, Purus, Negro and Madeira rivers had the most pronounced reductions in the year of Eastern El Niño (1976-1977). In the transition to the dry season, in April, the greatest reductions were associated with the Eastern El Niño year for the majority of the study region, with the exception only of the sub-basins of the Madeira, Trombetas and Xingu rivers, which had their associated reductions to Central El Niño. In the dry season from July to September, the sub-basins of the Japurá Jutaí Jatapu Javari Trombetas and Madeira rivers were the rivers that showed the greatest reductions in rainfall associated with El Niño Central, while the sub-basins of the Tapajós Purus Negro and Xingu rivers had the most pronounced reductions. In the Eastern El Niño year this season. In this way, it is possible to conclude that the Central (Eastern) El Niño controlled the reductions in soil moisture in the dry (rainy) season for all sub-basins shown in this study. Extreme drought events associated with these meteorological phenomena can lead to a significant increase in the occurrence of forest fires. These fires have a devastating impact on Amazonian vegetation, resulting in the irreparable loss of biodiversity and the release of large amounts of carbon stored in the forest, contributing to the increase in the greenhouse effect and global climate change. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sea%20surface%20temperature" title="sea surface temperature">sea surface temperature</a>, <a href="https://publications.waset.org/abstracts/search?q=variability" title=" variability"> variability</a>, <a href="https://publications.waset.org/abstracts/search?q=climate" title=" climate"> climate</a>, <a href="https://publications.waset.org/abstracts/search?q=Amazon" title=" Amazon"> Amazon</a> </p> <a href="https://publications.waset.org/abstracts/175407/the-roots-of-amazonias-droughts-and-floods-complex-interactions-of-pacific-and-atlantic-sea-surface-temperatures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175407.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">64</span> </span> </div> </div> <ul class="pagination"> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wavelet%20collocation&page=9" rel="prev">&lsaquo;</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wavelet%20collocation&page=1">1</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wavelet%20collocation&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wavelet%20collocation&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=wavelet%20collocation&page=4">4</a></li> <li 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