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if ($a.is_logged_in() && $viewedUser.is_current_user()) { $('body').addClass('profile-viewed-by-owner'); } $socialProfiles = []</script><div id="js-react-on-rails-context" style="display:none" data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://independent.academia.edu/LiChungsheng","location":"/LiChungsheng","scheme":"https","host":"independent.academia.edu","port":null,"pathname":"/LiChungsheng","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" data-component-name="ProfileCheckPaperUpdate" data-props="{}" data-trace="false" data-dom-id="ProfileCheckPaperUpdate-react-component-a94a1865-91a7-48ff-a1f9-a8a948946875"></div> <div id="ProfileCheckPaperUpdate-react-component-a94a1865-91a7-48ff-a1f9-a8a948946875"></div> <div class="DesignSystem"><div class="onsite-ping" id="onsite-ping"></div></div><div class="profile-user-info DesignSystem"><div class="social-profile-container"><div class="left-panel-container"><div class="user-info-component-wrapper"><div class="user-summary-cta-container"><div class="user-summary-container"><div class="social-profile-avatar-container"><img class="profile-avatar u-positionAbsolute" alt="Chung-sheng Li" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/38280282/17936797/17950019/s200_chung-sheng.li.jpg" /></div><div class="title-container"><h1 class="ds2-5-heading-sans-serif-sm">Chung-sheng Li</h1><div class="affiliations-container fake-truncate js-profile-affiliations"></div></div></div><div class="sidebar-cta-container"><button class="ds2-5-button hidden profile-cta-button grow js-profile-follow-button" data-broccoli-component="user-info.follow-button" data-click-track="profile-user-info-follow-button" data-follow-user-fname="Chung-sheng" data-follow-user-id="38280282" data-follow-user-source="profile_button" data-has-google="false"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">add</span>Follow</button><button class="ds2-5-button hidden profile-cta-button grow js-profile-unfollow-button" data-broccoli-component="user-info.unfollow-button" data-click-track="profile-user-info-unfollow-button" data-unfollow-user-id="38280282"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">done</span>Following</button></div></div><div class="user-stats-container"><a><div class="stat-container js-profile-followers"><p class="label">Followers</p><p class="data">49</p></div></a><a><div class="stat-container js-profile-followees" data-broccoli-component="user-info.followees-count" data-click-track="profile-expand-user-info-following"><p class="label">Following</p><p class="data">20</p></div></a><a><div class="stat-container js-profile-coauthors" data-broccoli-component="user-info.coauthors-count" data-click-track="profile-expand-user-info-coauthors"><p class="label">Co-authors</p><p class="data">9</p></div></a><span><div class="stat-container"><p class="label"><span class="js-profile-total-view-text">Public Views</span></p><p class="data"><span class="js-profile-view-count"></span></p></div></span></div><div class="user-bio-container"><div class="profile-bio fake-truncate js-profile-about" style="margin: 0px;">Chung-Sheng Li is currently the Global Research Managing Director of Artificial Intelligence for Accenture Operations, with a focus on driving the development of new AI-enabled service offerings for Accenture Business Process Services.  Previously, he has been with IBM Research between 1990 and 2016.    His career includes driving research and development initiatives spanning cognitive computing, cloud computing, smarter planet, cybersecurity, and cognitive regulatory compliance. He has authored or coauthored more than 100 patents and 170 journal and conference papers (and received the best paper award from IEEE Transactions on Multimedia in 2003). He is a Fellow of the IEEE.  He received BSEE from National Taiwan University, Taiwan, R.O.C., in 1984, and the MS and PhD degrees in electrical engineering and computer science from the University of California, Berkeley, in 1989 and 1991, respectively.<br /><div class="js-profile-less-about u-linkUnstyled u-tcGrayDarker u-textDecorationUnderline u-displayNone">less</div></div></div><div class="ri-section"><div class="ri-section-header"><span>Interests</span></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="38280282" href="https://www.academia.edu/Documents/in/Digital_Communications"><div id="js-react-on-rails-context" style="display:none" 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ANALYSIS"]}" data-trace="false" data-dom-id="Pill-react-component-7d769910-69c4-4369-9ed4-f85c41454925"></div> <div id="Pill-react-component-7d769910-69c4-4369-9ed4-f85c41454925"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="38280282" href="https://www.academia.edu/Documents/in/Electrical_Engineering_and_Computer_Science"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Electrical Engineering and Computer Science"]}" data-trace="false" data-dom-id="Pill-react-component-5057cf00-2635-47e0-839d-4350f505efb7"></div> <div id="Pill-react-component-5057cf00-2635-47e0-839d-4350f505efb7"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="38280282" href="https://www.academia.edu/Documents/in/Bit_Error_Rate"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Bit Error Rate"]}" data-trace="false" data-dom-id="Pill-react-component-d2c0d505-2c66-4599-92d6-88c9b013bcdc"></div> <div id="Pill-react-component-d2c0d505-2c66-4599-92d6-88c9b013bcdc"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="38280282" href="https://www.academia.edu/Documents/in/Statistical_Genetics"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Statistical Genetics"]}" data-trace="false" data-dom-id="Pill-react-component-04722406-3d05-4ef8-8e76-d298f7f2785d"></div> <div id="Pill-react-component-04722406-3d05-4ef8-8e76-d298f7f2785d"></div> </a></div></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Chung-sheng Li</h3></div><div class="js-work-strip profile--work_container" data-work-id="112039365"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/112039365/Site_Based_Biosurveillance"><img alt="Research paper thumbnail of Site-Based Biosurveillance" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/112039365/Site_Based_Biosurveillance">Site-Based Biosurveillance</a></div><div class="wp-workCard_item"><span>PsycEXTRA Dataset</span><span>, 2004</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="112039365"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="112039365"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 112039365; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=112039365]").text(description); $(".js-view-count[data-work-id=112039365]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 112039365; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='112039365']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 112039365, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=112039365]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":112039365,"title":"Site-Based Biosurveillance","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":2004,"errors":{}},"publication_name":"PsycEXTRA Dataset"},"translated_abstract":null,"internal_url":"https://www.academia.edu/112039365/Site_Based_Biosurveillance","translated_internal_url":"","created_at":"2023-12-21T20:23:49.773-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38280282,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Site_Based_Biosurveillance","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38280282,"first_name":"Chung-sheng","middle_initials":null,"last_name":"Li","page_name":"LiChungsheng","domain_name":"independent","created_at":"2015-11-13T12:05:34.460-08:00","display_name":"Chung-sheng Li","url":"https://independent.academia.edu/LiChungsheng"},"attachments":[],"research_interests":[],"urls":[{"id":37546912,"url":"https://doi.org/10.1037/e307182005-059"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="89460770"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/89460770/PetroSPIRE_Indexing_and_retrieval_of_seismic_data_for_oil_and_gas_exploration"><img alt="Research paper thumbnail of PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/89460770/PetroSPIRE_Indexing_and_retrieval_of_seismic_data_for_oil_and_gas_exploration">PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration</a></div><div class="wp-workCard_item"><span>SEG Technical Program Expanded Abstracts 2003</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We describe a novel approach to index a seismic data archive as a database in order to provide su...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We describe a novel approach to index a seismic data archive as a database in order to provide sufficient precision and recall in specific tasks such as retrieving seismic data containing faults and strong horizons, which commonly arise in oil and gas exploration scenarios. The results show that 70% recall with 80% precision can be achieved using this methodology. This technology could be deployed as a significant aid to geologists working to interpret or explore seismic data. Seismic data archives present one of the most difficult challenges for search and retrieval from 3D archives due to the requirements of domain specific knowledge and large data volumes for the retrieval tasks.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="89460770"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="89460770"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 89460770; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=89460770]").text(description); $(".js-view-count[data-work-id=89460770]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 89460770; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='89460770']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 89460770, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=89460770]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":89460770,"title":"PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration","translated_title":"","metadata":{"abstract":"We describe a novel approach to index a seismic data archive as a database in order to provide sufficient precision and recall in specific tasks such as retrieving seismic data containing faults and strong horizons, which commonly arise in oil and gas exploration scenarios. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="85269371"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/85269371/Toward_Business_Integrity_Modeling_and_Analysis_Framework_for_Risk_Measurement_and_Analysis"><img alt="Research paper thumbnail of Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/90019216/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/85269371/Toward_Business_Integrity_Modeling_and_Analysis_Framework_for_Risk_Measurement_and_Analysis">Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis</a></div><div class="wp-workCard_item"><span>Applied Sciences</span><span>, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Financialization has contributed to economic growth but has caused scandals, misselling, rogue tr...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, ope...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="eab27754da043c8f4622b53e081a1d43" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":90019216,"asset_id":85269371,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/90019216/download_file?st=MTczMjM3ODQ3Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85269371"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="85269371"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 85269371; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=85269371]").text(description); $(".js-view-count[data-work-id=85269371]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 85269371; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='85269371']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 85269371, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "eab27754da043c8f4622b53e081a1d43" } } $('.js-work-strip[data-work-id=85269371]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":85269371,"title":"Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis","translated_title":"","metadata":{"abstract":"Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, ope...","publisher":"MDPI AG","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"publication_name":"Applied Sciences"},"translated_abstract":"Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. 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However, inappropriate user-generated content in the form of violent, disturbing, infringing or fraudulent materials has become a serious challenge for public safety, law enforcement, and business integrity. It has also become increasingly difficult for end users to locate the most relevant content from the huge amount and variety of potentially interesting content selections. Therefore, content moderation and curation serve the two key purposes of protection and promotion to ensure compliance to site policy, local tastes or norms, or even the law, as well as the creation of an entertaining and compelling user experience via high-quality content. In this paper, we survey the governance, processes, standards, and technologies developed and deployed within the industry. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69664097"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/69664097/Supporting_Incremental_Join_Queries_on_Ranked_Inputs"><img alt="Research paper thumbnail of Supporting Incremental Join Queries on Ranked Inputs" class="work-thumbnail" src="https://attachments.academia-assets.com/79671919/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/69664097/Supporting_Incremental_Join_Queries_on_Ranked_Inputs">Supporting Incremental Join Queries on Ranked Inputs</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper investigates the problem of incremental joins of multiple ranked data sets when the jo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper investigates the problem of incremental joins of multiple ranked data sets when the join condition is a list of arbitrary user-defined predicates on the input tuples. This problem arises in many important applications dealing with ordered inputs and multiple ranked data sets, and requiring the top solutions. We use multimedia applications as the motivating examples but the problem is equally applicable to traditional database applications involving optimal resource allocation, scheduling, decision making, ranking, etc. We propose an algorithm that enables querying of ordered data sets by imposing arbitrary userdefined join predicates. The basic version of the algorithm does not use any random access but a variation can exploit available indexes for efficient random access based on the join predicates. A special case includes the join scenario considered by Fagin [1] for joins based on identical keys, and in that case, our algorithms perform as efficiently as Fagin’s. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="4016039" id="papers"><div class="js-work-strip profile--work_container" data-work-id="112039365"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/112039365/Site_Based_Biosurveillance"><img alt="Research paper thumbnail of Site-Based Biosurveillance" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/112039365/Site_Based_Biosurveillance">Site-Based Biosurveillance</a></div><div class="wp-workCard_item"><span>PsycEXTRA Dataset</span><span>, 2004</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="112039365"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="112039365"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 112039365; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="89460770"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/89460770/PetroSPIRE_Indexing_and_retrieval_of_seismic_data_for_oil_and_gas_exploration"><img alt="Research paper thumbnail of PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/89460770/PetroSPIRE_Indexing_and_retrieval_of_seismic_data_for_oil_and_gas_exploration">PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration</a></div><div class="wp-workCard_item"><span>SEG Technical Program Expanded Abstracts 2003</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We describe a novel approach to index a seismic data archive as a database in order to provide su...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We describe a novel approach to index a seismic data archive as a database in order to provide sufficient precision and recall in specific tasks such as retrieving seismic data containing faults and strong horizons, which commonly arise in oil and gas exploration scenarios. The results show that 70% recall with 80% precision can be achieved using this methodology. This technology could be deployed as a significant aid to geologists working to interpret or explore seismic data. Seismic data archives present one of the most difficult challenges for search and retrieval from 3D archives due to the requirements of domain specific knowledge and large data volumes for the retrieval tasks.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="89460770"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="89460770"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 89460770; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=89460770]").text(description); $(".js-view-count[data-work-id=89460770]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 89460770; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='89460770']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 89460770, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=89460770]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":89460770,"title":"PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration","translated_title":"","metadata":{"abstract":"We describe a novel approach to index a seismic data archive as a database in order to provide sufficient precision and recall in specific tasks such as retrieving seismic data containing faults and strong horizons, which commonly arise in oil and gas exploration scenarios. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="85269371"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/85269371/Toward_Business_Integrity_Modeling_and_Analysis_Framework_for_Risk_Measurement_and_Analysis"><img alt="Research paper thumbnail of Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis" class="work-thumbnail" src="https://attachments.academia-assets.com/90019216/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/85269371/Toward_Business_Integrity_Modeling_and_Analysis_Framework_for_Risk_Measurement_and_Analysis">Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis</a></div><div class="wp-workCard_item"><span>Applied Sciences</span><span>, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Financialization has contributed to economic growth but has caused scandals, misselling, rogue tr...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, ope...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="eab27754da043c8f4622b53e081a1d43" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":90019216,"asset_id":85269371,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/90019216/download_file?st=MTczMjM3ODQ3NCw4LjIyMi4yMDguMTQ2&st=MTczMjM3ODQ3Myw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85269371"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="85269371"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 85269371; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=85269371]").text(description); $(".js-view-count[data-work-id=85269371]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 85269371; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='85269371']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 85269371, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "eab27754da043c8f4622b53e081a1d43" } } $('.js-work-strip[data-work-id=85269371]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":85269371,"title":"Toward Business Integrity Modeling and Analysis Framework for Risk Measurement and Analysis","translated_title":"","metadata":{"abstract":"Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, ope...","publisher":"MDPI AG","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"publication_name":"Applied Sciences"},"translated_abstract":"Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. 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However, inappropriate user-generated content in the form of violent, disturbing, infringing or fraudulent materials has become a serious challenge for public safety, law enforcement, and business integrity. It has also become increasingly difficult for end users to locate the most relevant content from the huge amount and variety of potentially interesting content selections. Therefore, content moderation and curation serve the two key purposes of protection and promotion to ensure compliance to site policy, local tastes or norms, or even the law, as well as the creation of an entertaining and compelling user experience via high-quality content. In this paper, we survey the governance, processes, standards, and technologies developed and deployed within the industry. 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No.04TH8763)</span><span>, 2004</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3c98944d38bdb36b1e2755d736f2d340" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83028034,"asset_id":75138361,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83028034/download_file?st=MTczMjM3ODQ3NCw4LjIyMi4yMDguMTQ2&st=MTczMjM3ODQ3NCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75138361"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75138361"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75138361; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75138361]").text(description); $(".js-view-count[data-work-id=75138361]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75138361; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75138361']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75138361, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "3c98944d38bdb36b1e2755d736f2d340" } } $('.js-work-strip[data-work-id=75138361]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75138361,"title":"Content transcoding middleware for pervasive geospatial intelligence access","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":2004,"errors":{}},"publication_name":"2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69664097"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/69664097/Supporting_Incremental_Join_Queries_on_Ranked_Inputs"><img alt="Research paper thumbnail of Supporting Incremental Join Queries on Ranked Inputs" class="work-thumbnail" src="https://attachments.academia-assets.com/79671919/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/69664097/Supporting_Incremental_Join_Queries_on_Ranked_Inputs">Supporting Incremental Join Queries on Ranked Inputs</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper investigates the problem of incremental joins of multiple ranked data sets when the jo...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper investigates the problem of incremental joins of multiple ranked data sets when the join condition is a list of arbitrary user-defined predicates on the input tuples. This problem arises in many important applications dealing with ordered inputs and multiple ranked data sets, and requiring the top solutions. We use multimedia applications as the motivating examples but the problem is equally applicable to traditional database applications involving optimal resource allocation, scheduling, decision making, ranking, etc. We propose an algorithm that enables querying of ordered data sets by imposing arbitrary userdefined join predicates. The basic version of the algorithm does not use any random access but a variation can exploit available indexes for efficient random access based on the join predicates. A special case includes the join scenario considered by Fagin [1] for joins based on identical keys, and in that case, our algorithms perform as efficiently as Fagin’s. 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