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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 Bhupesh Kumar Dewangan</h3></div><div class="js-work-strip profile--work_container" data-work-id="75032488"><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/75032488/Hand_Gesture_Recognition_Through_Depth_Sensors"><img alt="Research paper thumbnail of Hand Gesture Recognition Through Depth Sensors" 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/75032488/Hand_Gesture_Recognition_Through_Depth_Sensors">Hand Gesture Recognition Through Depth Sensors</a></div><div class="wp-workCard_item"><span>Challenges and Applications for Hand Gesture Recognition</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A hand gesture recognition system allows for nonverbal communication that is natural, inventive, ...</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">A hand gesture recognition system allows for nonverbal communication that is natural, inventive, and modern. It can be used in a variety of applications involving human-computer interaction. Sign language is a type of communication in which people communicate using their gestures. The identification of hand gestures has become one of the most important aspects of human-computer interaction (HCI). The goal of HCI is to get to a point where human-computer interactions are as natural as human-human interactions, and adding gestures into HCI is an essential research topic in that direction. The history of hand gesture recognition is initially presented in this chapter, followed by a list of technical challenges. Researchers from all over the world are working on developing a reliable and efficient gesture recognition system, particularly a hand gesture recognition system, for a variety of applications. In this chapter, the core and advanced application areas and various applications tha...</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="75032488"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032488"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032488; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032488]").text(description); $(".js-view-count[data-work-id=75032488]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032488; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032488']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032488]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032488,"title":"Hand Gesture Recognition Through Depth Sensors","internal_url":"https://www.academia.edu/75032488/Hand_Gesture_Recognition_Through_Depth_Sensors","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032487"><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/75032487/Multi_Criteria_Decision_Making_Methodology_for_Sustainable_Creativity_in_Social_Media"><img alt="Research paper thumbnail of Multi-Criteria Decision-Making Methodology for Sustainable Creativity in Social Media" class="work-thumbnail" src="https://attachments.academia-assets.com/82966702/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/75032487/Multi_Criteria_Decision_Making_Methodology_for_Sustainable_Creativity_in_Social_Media">Multi-Criteria Decision-Making Methodology for Sustainable Creativity in Social Media</a></div><div class="wp-workCard_item"><span>Journal of Computer Science</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A major topic that every researcher is pursuing is sustainability in every aspect of knowledge an...</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">A major topic that every researcher is pursuing is sustainability in every aspect of knowledge and learning. In the 21st century, the world is facing a challenge. Some of the well-known Multi-Criteria Decision-Making tools are Analytic Network Process (ANP), Analytical Hierarchy Process (AHP), TOPSIS, ELECTRE, Choice Based Conjoint Analysis (CBC) etc. This approach is used in various research domains. The purpose of this study is to evaluate and find result for the queries based on reviews like which measures correlated to the sustainable environmental features involved in the development of social media? Which measures is most commonly used? What type of MCDM methods suitable for variety of social media? Is any different evidence for methods used for sustainable social media selection? Our focus was on analyzing the methods of choice and the criteria for result evaluations. In the spatial analysis the decision making is the main element in geographic studies and skills related to the success towards the planning process. MCDM focuses to analyzing decision problems and estimating the substitute to take decision for the preferences, privations the competence, handle spatial data for analysis. Ranking of influential users is most frequently used criteria followed by privacy, seriousness about reading terms and conditions and accurate quality and quantity.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4c95450c0297c38ac9badc8a5fa00b79" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966702,"asset_id":75032487,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966702/download_file?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="75032487"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032487"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032487; 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</script> <div class="js-work-strip profile--work_container" data-work-id="75032485"><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/75032485/Modeling_the_Efficiency_of_Emulsion_Separation_in_a_Combined_Apparatus"><img alt="Research paper thumbnail of Modeling the Efficiency of Emulsion Separation in a Combined Apparatus" 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/75032485/Modeling_the_Efficiency_of_Emulsion_Separation_in_a_Combined_Apparatus">Modeling the Efficiency of Emulsion Separation in a Combined Apparatus</a></div><div class="wp-workCard_item"><span>Mathematical Methods in Technologies and Technics</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="75032485"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032485"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032485; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75032485]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032485,"title":"Modeling the Efficiency of Emulsion Separation in a Combined Apparatus","internal_url":"https://www.academia.edu/75032485/Modeling_the_Efficiency_of_Emulsion_Separation_in_a_Combined_Apparatus","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032484"><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/75032484/Prediction_of_sonic_log_and_correlation_of_lithology_by_comparing_geophysical_well_log_data_using_machine_learning_principles"><img alt="Research paper thumbnail of Prediction of sonic log and correlation of lithology by comparing geophysical well log data using machine learning principles" class="work-thumbnail" src="https://attachments.academia-assets.com/82966627/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/75032484/Prediction_of_sonic_log_and_correlation_of_lithology_by_comparing_geophysical_well_log_data_using_machine_learning_principles">Prediction of sonic log and correlation of lithology by comparing geophysical well log data using machine learning principles</a></div><div class="wp-workCard_item"><span>GeoJournal</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The well logging technique is used to determine the petrophysical properties like porosity, perme...</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">The well logging technique is used to determine the petrophysical properties like porosity, permeability and fluid saturations of subsurface formations. However, the conventional way of log evaluation is very expensive and tiresome. The postacquisition processing and inversion provides an alternative to determine the properties of drilled formations. This study proposes a novel approach to predict sonic log, adopting a regression method using a supervised machine learning (ML) algorithm, along with the determination of lithology employing clustering and a neural network approach grounded on the basis of gamma-ray log values and hence creating a correlation between the two. The scarce acoustic data obtained upon the traditional well logging procedure often pose a barrier in further determining the rock physics. Regression analysis, a predictive modeling technique, uses other petrophysical data to predict the sonic wave travel time (shear and compressional) by estimating a relationship between the two variables. The model is trained on a set of 10,000 points with 80% training points giving an 86.314% accuracy result. RMSE and R 2 scores for training points and testing points came out to be 2.622 and 0.95, and 2.55 and 0.96, respectively, which helps in the validation of the model. Effective lithology determination is a crucial step of reservoir characterization. Traditional methods of core sample inspection and using well logs, however, cannot meet the needs of real-time due to complex sediment environment and reservoir heterogeneity. To deal with the problem, an unsupervised ML model, K-means clustering, a method of vector quantization grouping unlabeled data into arbitrary clusters based on similarities with respect to distance from the center is used. The model gave the optimum number of clusters as 5 and showed a presence of siltstone, coal and sandstone separated between these clusters. The Silhouette score which tests the accuracy came out to be 0.5840 along with a CH score of 27,192.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8a4940fa10005384639d6b097a3e5377" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966627,"asset_id":75032484,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966627/download_file?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="75032484"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032484"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032484; 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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="75032482"><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/75032482/A_Recommendation_System_for_Customizable_Items"><img alt="Research paper thumbnail of A Recommendation System for Customizable Items" class="work-thumbnail" src="https://attachments.academia-assets.com/82966626/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/75032482/A_Recommendation_System_for_Customizable_Items">A Recommendation System for Customizable Items</a></div><div class="wp-workCard_item"><span>Advances in Intelligent Systems and Computing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The amount of data on the Internet is growing rapidly. This information overload has increased th...</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">The amount of data on the Internet is growing rapidly. This information overload has increased the popularity of recommendation systems over the past few years. Recommendation systems are software tools that help users by providing them suggestions for items or products according to their preferences. They have been around for decades, over which time a strong community of researchers and industry practitioners have risen. Recommendation systems generate product recommendations that are mainly useful for users who lack adequate proficiency in the respective product domain. The generated recommendations may be personalized or non-personalized (in magazines or in newspapers) depending upon the requirement. There are several techniques involved in building a recommendation system. This work mainly emphasizes content-based filtering and constraint-based filtering approaches, and how they are used for recommending descriptive items that are customized to user's taste.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a3b9ae86a36e6b04a7d24eb7e252ed0c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966626,"asset_id":75032482,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966626/download_file?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="75032482"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032482"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032482; 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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="75032481"><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/75032481/Survey_on_User_Behavior_Trust_Evaluation_in_Cloud_Computing"><img alt="Research paper thumbnail of Survey on User Behavior Trust Evaluation in Cloud Computing" 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/75032481/Survey_on_User_Behavior_Trust_Evaluation_in_Cloud_Computing">Survey on User Behavior Trust Evaluation in Cloud Computing</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing may be defined as management and provision of resources, software, applications a...</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">Cloud computing may be defined as management and provision of resources, software, applications and information as services over the cloud (internet) on demand. Cloud computing is a model for enabling convenient, on demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction (2). With its ability to provide users dynamically scalable, shared resources over the Internet and avoid large upfront fixed costs, cloud computing has recently emerged as a promising hosting platform that performs an intelligent usage of a collection of services, applications, information and infrastructure comprised of pools of computer, network, information and storage resources. However along with these advantages, storing a large amount of data including critical information on the cloud motivates highly skilled hackers thus creating a need for the security to be considered as one of t...</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="75032481"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032481"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032481; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032481]").text(description); $(".js-view-count[data-work-id=75032481]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032481; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032481']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032481]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032481,"title":"Survey on User Behavior Trust Evaluation in Cloud Computing","internal_url":"https://www.academia.edu/75032481/Survey_on_User_Behavior_Trust_Evaluation_in_Cloud_Computing","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032480"><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/75032480/A_Self_Optimization_Based_Virtual_Machine_Scheduling_to_Workloads_in_Cloud_Computing_Environment"><img alt="Research paper thumbnail of A Self-Optimization Based Virtual Machine Scheduling to Workloads in Cloud Computing Environment" 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/75032480/A_Self_Optimization_Based_Virtual_Machine_Scheduling_to_Workloads_in_Cloud_Computing_Environment">A Self-Optimization Based Virtual Machine Scheduling to Workloads in Cloud Computing Environment</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Energy consumption in the cloud computing plays a vital role in operating cost to the service pro...</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">Energy consumption in the cloud computing plays a vital role in operating cost to the service provider and cloud user. The cloud is scalable and it can provide the access as per demand, due to this resource access requests are increasing, and submitted to the server. To manage all request, scheduling is the solution to assign request with the quality of service. To avoid high operating cost, resource scheduling needs to be energy-aware. In this paper, energy-aware resource scheduling in the cloud is proposing. Total resource utilization of each resource has been calculating and energy is optimizing through antlion optimization algorithm to avoid high consumption of power. The resource is identify with its best utilization value and assign to submit workloads as per priority basis. The experimental results of the proposed work are analyzing with existing autonomic frameworks, and it is observed that proposed work is performing utmost. Index Term: Energy, Resource Cost, Execution Time...</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="75032480"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032480"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032480; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032480]").text(description); $(".js-view-count[data-work-id=75032480]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032480; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032480']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032480]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032480,"title":"A Self-Optimization Based Virtual Machine Scheduling to Workloads in Cloud Computing Environment","internal_url":"https://www.academia.edu/75032480/A_Self_Optimization_Based_Virtual_Machine_Scheduling_to_Workloads_in_Cloud_Computing_Environment","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032479"><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/75032479/Data_Storage_in_Cloud_Server_by_Token_Pre_Computation"><img alt="Research paper thumbnail of Data Storage in Cloud Server by Token Pre-Computation" 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/75032479/Data_Storage_in_Cloud_Server_by_Token_Pre_Computation">Data Storage in Cloud Server by Token Pre-Computation</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing can be defined as a new style of computing in which dynamically scalable and ofte...</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">Cloud computing can be defined as a new style of computing in which dynamically scalable and often virtualized resources are provided as services over the internet. With cloud computing technology, users use a variety of devices, including PCs, laptops, smart phones, and PDAs to access programs, storage, and application-development platforms over the Internet, via services offered by cloud computing providers. Advantages of cloud computing technology include cost savings, high availability, and easy scalability. Cloud computing moves the application software and data bases to the large data centres, where administration of the data and services may not be fully trustworthy. This unique aspect, however, poses many new security challenges which have not been well understood. In this article, we focus on cloud storage security, which has always been important feature of quality of service. To ensure the correctness of users data in the cloud, we suggest an effective and flexible techni...</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="75032479"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032479"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032479; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032479]").text(description); $(".js-view-count[data-work-id=75032479]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032479; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032479']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032479]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032479,"title":"Data Storage in Cloud Server by Token Pre-Computation","internal_url":"https://www.academia.edu/75032479/Data_Storage_in_Cloud_Server_by_Token_Pre_Computation","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032478"><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/75032478/GAP_Hybrid_Task_Scheduling_Algorithm_for_Cloud"><img alt="Research paper thumbnail of GAP: Hybrid Task Scheduling Algorithm for Cloud" class="work-thumbnail" src="https://attachments.academia-assets.com/82966623/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/75032478/GAP_Hybrid_Task_Scheduling_Algorithm_for_Cloud">GAP: Hybrid Task Scheduling Algorithm for Cloud</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Received: 9 March 2020 Accepted: 16 July 2020 Resource optimization is cost effective process in ...</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">Received: 9 March 2020 Accepted: 16 July 2020 Resource optimization is cost effective process in cloud. The efficiency of load balancing completely depends on how the infrastructure is utilizing. As per the current study, the resource optimization techniques are very costly and taking more convergence time to execute the task and load distribution among different virtual machines (VM). The objective of this paper is to develop a hybrid optimization algorithm to find the best virtual machine based on their fitness values and schedule different task to the fittest VM so that each task should get complete on time, and system can utilize the VM as well. The proposed algorithm is hybrid version of genetic (GA), ant-colony (Aco), and particle-swarm (Pso) algorithms, which is implemented and tested in amazon web service and compared with existing algorithms based on VM utilization, completion time, and cost. The proposed hybrid system genetic-aco-pso based algorithm (GAP) perform utmost wh...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c398b2148de0cf1302fdd87194fb7ae1" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966623,"asset_id":75032478,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966623/download_file?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="75032478"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032478"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032478; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032478]").text(description); $(".js-view-count[data-work-id=75032478]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032478; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032478']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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: "c398b2148de0cf1302fdd87194fb7ae1" } } $('.js-work-strip[data-work-id=75032478]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032478,"title":"GAP: Hybrid Task Scheduling Algorithm for Cloud","internal_url":"https://www.academia.edu/75032478/GAP_Hybrid_Task_Scheduling_Algorithm_for_Cloud","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[{"id":82966623,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966623/thumbnails/1.jpg","file_name":"41410.pdf","download_url":"https://www.academia.edu/attachments/82966623/download_file","bulk_download_file_name":"GAP_Hybrid_Task_Scheduling_Algorithm_for.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966623/41410-libre.pdf?1648707816=\u0026response-content-disposition=attachment%3B+filename%3DGAP_Hybrid_Task_Scheduling_Algorithm_for.pdf\u0026Expires=1739704002\u0026Signature=cjY9I8Lbw4xbP-mGTF7e~Ve~TaNFEUv2KNvUMHCRgSu~o6gg5heQRasMMjcRntcUuHIzDZf8SRyxT7M4lLIWLGIqOzlEXSHlIhASADtelgWLz0sPPNPOEJMX2qAeSAR5yAT~ilJhngpFsk2D34iAAoh99S1OEp0XyxNBNN6p73fd8ZYcoi51ANoG5iROuJIKZ9qA4EZ3xg3FQ0YlKYBFwq7Rcwis9wY6Eo4I9z3zyZYWnSnrl1sFs7LZorY~GXG0z8U8cO8VYORrWopBDIfbiwBGcHO5YHp-N7bPH6V6jaV-wlB7G3W3CPLPRYepIPFz7UKgzaj42nwHt18SrtTIKQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":82966624,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966624/thumbnails/1.jpg","file_name":"41410.pdf","download_url":"https://www.academia.edu/attachments/82966624/download_file","bulk_download_file_name":"GAP_Hybrid_Task_Scheduling_Algorithm_for.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966624/41410-libre.pdf?1648707815=\u0026response-content-disposition=attachment%3B+filename%3DGAP_Hybrid_Task_Scheduling_Algorithm_for.pdf\u0026Expires=1739704002\u0026Signature=JDPudHOzj5Rg3d6jaZoiYl-FND3MEij1H8oUzlXyXOmKyVQ84QTXUdnJxg6j7mEPW9mmX4v5HCgHd6AUupAb29-571brIZfXYmrWLn7InCCWTR2bjeNphknfXWM-1YCgp1zE6y~4oEsdj8UmWEM0rpW1bOohl5Q~SvBRRU-NJ3e~rPYMrP1WSoXFEK8rXgBJfkopir0m85gdmA54omXdca9pyvucVRMCPU6tXe1hkgZkh6xv3odqF1O--2mjwj6Ihh5I7VsGvmUTgJaMCOnBcdk9AH4ozzOaem9czoTis8t~JprscVkOy53praM57Co9Q9AW3CNRwvHOkoe6Zwiblw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, 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="75032477"><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/75032477/Design_of_Self_Management_Aware_Autonomic_Resource_Scheduling_Scheme_in_Cloud"><img alt="Research paper thumbnail of Design of Self-Management Aware Autonomic Resource Scheduling Scheme in Cloud" class="work-thumbnail" src="https://attachments.academia-assets.com/82966621/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/75032477/Design_of_Self_Management_Aware_Autonomic_Resource_Scheduling_Scheme_in_Cloud">Design of Self-Management Aware Autonomic Resource Scheduling Scheme in Cloud</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing is an emerging technology through which resources can be shared over the internet...</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">Cloud computing is an emerging technology through which resources can be shared over the internet with different users either free or on a rent basis. Resource scheduling in cloud computing is a challenging area for researchers as is maximum utilization can opt through efficient resource scheduling algorithm. In this environment, incalculability, and expansion of resources meeting the problem of allocation. Other than this, virtual machine provisioning, packaging, and availability guarantee decrease the performance. To avoid this, an efficient resource management technique is required, which will manage the resources effectively, guarantee the availability, and execute the workloads automatically. In this paper, we present an autonomic resource management technique named as SMART (Self-management aware autonomic resource management technique for cloud). SMART offers self-optimization for maximum resource utilization, self-healing to avoid failures on execution, self-protection to st...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="15a49a90c1cb6eb44bd1048e80755775" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966621,"asset_id":75032477,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966621/download_file?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="75032477"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032477"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032477; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032477]").text(description); $(".js-view-count[data-work-id=75032477]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032477; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032477']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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: "15a49a90c1cb6eb44bd1048e80755775" } } $('.js-work-strip[data-work-id=75032477]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032477,"title":"Design of Self-Management Aware Autonomic Resource Scheduling Scheme in Cloud","internal_url":"https://www.academia.edu/75032477/Design_of_Self_Management_Aware_Autonomic_Resource_Scheduling_Scheme_in_Cloud","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[{"id":82966621,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966621/thumbnails/1.jpg","file_name":"IJCISIM_17.pdf","download_url":"https://www.academia.edu/attachments/82966621/download_file","bulk_download_file_name":"Design_of_Self_Management_Aware_Autonomi.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966621/IJCISIM_17-libre.pdf?1648707816=\u0026response-content-disposition=attachment%3B+filename%3DDesign_of_Self_Management_Aware_Autonomi.pdf\u0026Expires=1739704002\u0026Signature=UQ7mR2iilKag3V8CoTuXTzxY8uteoq98eyAQJeJHbzLs5fvE9uEUUXaxWB8CNPijBtzDIoA7yooTzC~xGKS2gW~tcfwKZfPCio-Vm~VeFoPY3KKsL5XH7q6BGlPdcsoVi7YZv1ZEDk-olqNL5tRAGh9E3O58eBfO-dvLLYtCSinq7cPJVMh3ZUUYtFX4AwigH8ZtVSonwPeXge3gRP3K2WNpxbeJLOn-RfxhXd9B-13f94JtkWbT7ZpEw4mOsy-oYq3Z4kY1iE1ntjhIp0BlDLDpmVqK7wfQ~23Yb9eoIU8~uT0pbCn~sNqxBUKvCsfZfrcDm7vz-eaQ~lTwcaze8A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":82966622,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966622/thumbnails/1.jpg","file_name":"IJCISIM_17.pdf","download_url":"https://www.academia.edu/attachments/82966622/download_file","bulk_download_file_name":"Design_of_Self_Management_Aware_Autonomi.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966622/IJCISIM_17-libre.pdf?1648707816=\u0026response-content-disposition=attachment%3B+filename%3DDesign_of_Self_Management_Aware_Autonomi.pdf\u0026Expires=1739704002\u0026Signature=S3b6-fOmLWTLaNkq-f8YkJlhpXuyQ5ItqVKjz1VPixjFrvRdguScbh0NOrHdjei4f~hsnN7-3ZjN2JHARpYS~y~2~zt7gNkyaZ5GDyIx99YxpKQi0HaE0UFu~CVDmp~6XynLjdrSb2FUQYFA4dl1obMPHBels5aR1T8xZnE4L5OWfgu9M-SidZZVIzsJJRUIy8Qqtm-lmqZdMO3UtTcbFrWBhZnUyFrdkra7Vl21XeNoDxDR4nsEXQA4uKkpXqR7LBhGB4399EJ0wag0gmLTlc0I6UhY5VksraHOOXN0bJlKVbIIGAXnlToXFkn6E7ZG~gtLpEpn40DX2cjFjHwcQQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, 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="75032476"><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/75032476/Task_Scheduling_Using_Hybrid_PSO_in_Cloud_Based_Environment"><img alt="Research paper thumbnail of Task Scheduling Using Hybrid PSO in Cloud Based Environment" class="work-thumbnail" src="https://attachments.academia-assets.com/82966700/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/75032476/Task_Scheduling_Using_Hybrid_PSO_in_Cloud_Based_Environment">Task Scheduling Using Hybrid PSO in Cloud Based Environment</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing ensures access to shared resources and ordinary infrastructure, providing service...</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">Cloud computing ensures access to shared resources and ordinary infrastructure, providing services on concern over a community for operations to fulfil changing industrial enterprise requirements. Scheduling may be a prominent activity that&#39;s finished during a cloud computing surroundings. To increase cloud computing work load performance, responsibilities programming is accomplished to induce most financial profit. In cloud, excessive communication cost prevents assignment schedulers from being distributed in immense scale assigned environments. This study proposes a hybrid improvement primarily based entirely on Particle Swarm improvement (PSO) and Genetic algorithmic program (GA) for programming in cloud environments.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d93f51bba80132a76ad9119159dfa85a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966700,"asset_id":75032476,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966700/download_file?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="75032476"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032476"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032476; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75032475"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75032475/Defense_in_Depth_for_Data_Storage_in_Cloud_Computing"><img alt="Research paper thumbnail of Defense in Depth for Data Storage in Cloud Computing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75032475/Defense_in_Depth_for_Data_Storage_in_Cloud_Computing">Defense in Depth for Data Storage in Cloud Computing</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75032475"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032475"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032475; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032475]").text(description); $(".js-view-count[data-work-id=75032475]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032475; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032475']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032475]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032475,"title":"Defense in Depth for Data Storage in Cloud Computing","internal_url":"https://www.academia.edu/75032475/Defense_in_Depth_for_Data_Storage_in_Cloud_Computing","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032474"><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/75032474/The_Sliding_Window_Method_An_Environment_To_Evaluate_User_Behavior_Trust_In_Cloud_Technology"><img alt="Research paper thumbnail of The Sliding Window Method: An Environment To Evaluate User Behavior Trust In Cloud Technology" 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/75032474/The_Sliding_Window_Method_An_Environment_To_Evaluate_User_Behavior_Trust_In_Cloud_Technology">The Sliding Window Method: An Environment To Evaluate User Behavior Trust In Cloud Technology</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">-Trust is one of the most concerned obstacles for the adoption and growth of cloud computing. Alt...</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">-Trust is one of the most concerned obstacles for the adoption and growth of cloud computing. Although several solutions have been proposed recently in managing trust feedbacks in cloud enviornemts, how to determine the credibility of trust feedback in a cloud environments is difficult problem due to unpredictable numbers of cloud services consumers and highly dynamic nature of cloud environments. In the cloud computing, due to users directly use and operate the software and OS, and even the basic programming environment and network infrastructure which provided by the cloud service providers, so the impact and destruction of the software and hardware cloud resources in cloud computing are worse than the current Internet users who use it to share resources. Therefore, that whether user behavior is trusted, how to evaluate user behavior trust is an important research content in cloud computing. In this paper we mainly discusses evaluation importance of user behavior trust and evaluation strategy, in the cloud computing, including trust object analysis, principle in evaluating user behavior trust, the basic idea of evaluating user behavior trust, evaluation strategy of behavior trust for each access, and long acsess. In trust evaluation, behavior evidence is the fundamental basis of behavior evaluation. But at present, researchers almost directly use node behavior results or use a third party’s evaluation results to synthesize it, not study the original evidence of node behavior and ignore an analysis of node behavior history, which limit the reliability, rationality and sharing of trust. Drawing on the characteristics of social trust and trust requirement, we first put forward basic criteria about evaluating node behavior trust, and then bring forward a kind of evaluation mechanism on node behavior trust based on sliding window model. Keyword: Node Behavior Trust, Trust Evaluation, Evaluation Principles, Sliding Window.</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="75032474"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032474"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032474; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032474]").text(description); $(".js-view-count[data-work-id=75032474]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032474; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032474']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032474]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032474,"title":"The Sliding Window Method: An Environment To Evaluate User Behavior Trust In Cloud Technology","internal_url":"https://www.academia.edu/75032474/The_Sliding_Window_Method_An_Environment_To_Evaluate_User_Behavior_Trust_In_Cloud_Technology","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032473"><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/75032473/A_Fuzzy_Interface_System_to_Predict_Depression_Risk"><img alt="Research paper thumbnail of A Fuzzy Interface System to Predict Depression Risk" class="work-thumbnail" src="https://attachments.academia-assets.com/82966620/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/75032473/A_Fuzzy_Interface_System_to_Predict_Depression_Risk">A Fuzzy Interface System to Predict Depression Risk</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Depression has been classified as a psychological disorder which is capable of affecting patients...</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">Depression has been classified as a psychological disorder which is capable of affecting patients both mentally and physically with unique presentation across patients. This unique presentation makes it difficult to predict the onset or the risk of onset of the disease. This paper presents the use of a fuzzy logic based interface system, which takes into account four primary predictors and then determines the risk of the onset of depression in three age groups. The approach shows promising results with high accuracy.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4459f13887d9ef1cd1eaefc933ebe8f1" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966620,"asset_id":75032473,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966620/download_file?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="75032473"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032473"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032473; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032473]").text(description); $(".js-view-count[data-work-id=75032473]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032473; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032473']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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: "4459f13887d9ef1cd1eaefc933ebe8f1" } } $('.js-work-strip[data-work-id=75032473]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032473,"title":"A Fuzzy Interface System to Predict Depression Risk","internal_url":"https://www.academia.edu/75032473/A_Fuzzy_Interface_System_to_Predict_Depression_Risk","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[{"id":82966620,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966620/thumbnails/1.jpg","file_name":"IJCISIM_26.pdf","download_url":"https://www.academia.edu/attachments/82966620/download_file","bulk_download_file_name":"A_Fuzzy_Interface_System_to_Predict_Depr.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966620/IJCISIM_26-libre.pdf?1648707819=\u0026response-content-disposition=attachment%3B+filename%3DA_Fuzzy_Interface_System_to_Predict_Depr.pdf\u0026Expires=1739704002\u0026Signature=HWI4jGDM7hpJ0qcwLtHwjit4mFtFEUGwtJwo5DPaKgDOS9r2yDfI9VUFSRh2QkqM2D0FUDGLuiVmCsbiSDukHvj-luDD9hAwQf1FOLcAjFnrCyKyCXsLieoK-B50JBMPqZIkuLh0bmv8~YVrWczkLPsAL6~NwcI48qS0cBrh5~IdmFEVaWtQOZcxlgSUPK4fy5MfP-3t69t2iL6~ATG6U-Ef-p7-feJBZNA0jLJQmyW0EG4aHCXSKhFoV-BfgH69aWdRUiZKYC1Pz2x48FPTgbwHNAVAyDJ6LrnqYepjpejslX7cmEfLuL555brRB-I6z~c4wJ31zY91RpyqtwWitg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, 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="75032472"><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/75032472/An_Efficient_Trajectory_representative_generation_moving_data_prediction_using_different_Clustering_algorithm"><img alt="Research paper thumbnail of An Efficient Trajectory representative generation moving data prediction using different Clustering algorithm" class="work-thumbnail" src="https://attachments.academia-assets.com/82966699/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/75032472/An_Efficient_Trajectory_representative_generation_moving_data_prediction_using_different_Clustering_algorithm">An Efficient Trajectory representative generation moving data prediction using different Clustering algorithm</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper highlighted Moving and Trajectory Object Cluster (MOTRACLUS) algorithm and analysis th...</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 highlighted Moving and Trajectory Object Cluster (MOTRACLUS) algorithm and analysis the sub-trajectories and real-trajectories algorithm for moving data and suggest a new approach of moving elements. This paper evaluates the Hurricane data measure and mass less data measure entropy of trajectories objects of moving data of Chhattisgarh location. The paper covered Prediction Generation with their distance cluster minimum description length (MDL) algorithm and others corresponding distance cluster (CLSTR) algorithm. This paper highlighted the k-nearest algorithm with least cluster section (LCSS) model and dimensional Euclidean of MDL algorithm. Our algorithm consists of two parts that is partitioning and grouping phase. This paper develops and enhances a cluster of trajectory object and calculates the actual distance of moving object. This algorithm works on the CLSTR algorithm and calculates Trajectory movement of object. In this we evaluate the entropy of moving object by...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8d13ba6b3bd05407bcc482ae7887e5b2" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966699,"asset_id":75032472,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966699/download_file?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="75032472"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032472"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032472; 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It implies a service oriented architecture, reduced information technology overhead for the end-user, great flexibility, reduced total cost of ownership, ondemand services and many other things. This paper discusses the concept of “cloud” computing, some of the issues it tries to address, related research topics, and a “cloud” implementation available today.</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="75032470"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032470"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032470; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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</script> <div class="js-work-strip profile--work_container" data-work-id="75032468"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75032468/The_Architecture_of_Autonomic_Cloud_Resource_Management"><img alt="Research paper thumbnail of The Architecture of Autonomic Cloud Resource Management" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75032468/The_Architecture_of_Autonomic_Cloud_Resource_Management">The Architecture of Autonomic Cloud Resource Management</a></div><div class="wp-workCard_item"><span>Autonomic Computing in Cloud Resource Management in Industry 4.0</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75032468"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032468"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032468; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75032468]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032468,"title":"The Architecture of Autonomic Cloud Resource Management","internal_url":"https://www.academia.edu/75032468/The_Architecture_of_Autonomic_Cloud_Resource_Management","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, dispatcherData: dispatcherData }); $(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="14453018" id="papers"><div class="js-work-strip profile--work_container" data-work-id="75032488"><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/75032488/Hand_Gesture_Recognition_Through_Depth_Sensors"><img alt="Research paper thumbnail of Hand Gesture Recognition Through Depth Sensors" 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/75032488/Hand_Gesture_Recognition_Through_Depth_Sensors">Hand Gesture Recognition Through Depth Sensors</a></div><div class="wp-workCard_item"><span>Challenges and Applications for Hand Gesture Recognition</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A hand gesture recognition system allows for nonverbal communication that is natural, inventive, ...</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">A hand gesture recognition system allows for nonverbal communication that is natural, inventive, and modern. It can be used in a variety of applications involving human-computer interaction. Sign language is a type of communication in which people communicate using their gestures. The identification of hand gestures has become one of the most important aspects of human-computer interaction (HCI). The goal of HCI is to get to a point where human-computer interactions are as natural as human-human interactions, and adding gestures into HCI is an essential research topic in that direction. The history of hand gesture recognition is initially presented in this chapter, followed by a list of technical challenges. Researchers from all over the world are working on developing a reliable and efficient gesture recognition system, particularly a hand gesture recognition system, for a variety of applications. In this chapter, the core and advanced application areas and various applications tha...</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="75032488"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032488"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032488; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032488]").text(description); $(".js-view-count[data-work-id=75032488]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032488; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032488']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032488]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032488,"title":"Hand Gesture Recognition Through Depth Sensors","internal_url":"https://www.academia.edu/75032488/Hand_Gesture_Recognition_Through_Depth_Sensors","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032487"><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/75032487/Multi_Criteria_Decision_Making_Methodology_for_Sustainable_Creativity_in_Social_Media"><img alt="Research paper thumbnail of Multi-Criteria Decision-Making Methodology for Sustainable Creativity in Social Media" class="work-thumbnail" src="https://attachments.academia-assets.com/82966702/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/75032487/Multi_Criteria_Decision_Making_Methodology_for_Sustainable_Creativity_in_Social_Media">Multi-Criteria Decision-Making Methodology for Sustainable Creativity in Social Media</a></div><div class="wp-workCard_item"><span>Journal of Computer Science</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A major topic that every researcher is pursuing is sustainability in every aspect of knowledge an...</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">A major topic that every researcher is pursuing is sustainability in every aspect of knowledge and learning. In the 21st century, the world is facing a challenge. Some of the well-known Multi-Criteria Decision-Making tools are Analytic Network Process (ANP), Analytical Hierarchy Process (AHP), TOPSIS, ELECTRE, Choice Based Conjoint Analysis (CBC) etc. This approach is used in various research domains. The purpose of this study is to evaluate and find result for the queries based on reviews like which measures correlated to the sustainable environmental features involved in the development of social media? Which measures is most commonly used? What type of MCDM methods suitable for variety of social media? Is any different evidence for methods used for sustainable social media selection? Our focus was on analyzing the methods of choice and the criteria for result evaluations. In the spatial analysis the decision making is the main element in geographic studies and skills related to the success towards the planning process. MCDM focuses to analyzing decision problems and estimating the substitute to take decision for the preferences, privations the competence, handle spatial data for analysis. Ranking of influential users is most frequently used criteria followed by privacy, seriousness about reading terms and conditions and accurate quality and quantity.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4c95450c0297c38ac9badc8a5fa00b79" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966702,"asset_id":75032487,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966702/download_file?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="75032487"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032487"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032487; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032487]").text(description); $(".js-view-count[data-work-id=75032487]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032487; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032487']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75032486"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75032486/Gradient_and_statistical_features_based_prediction_system_for_COVID_19_using_chest_X_ray_images"><img alt="Research paper thumbnail of Gradient and statistical features-based prediction system for COVID-19 using chest X-ray images" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75032486/Gradient_and_statistical_features_based_prediction_system_for_COVID_19_using_chest_X_ray_images">Gradient and statistical features-based prediction system for COVID-19 using chest X-ray images</a></div><div class="wp-workCard_item"><span>International Journal of Computer Applications in Technology</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75032486"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032486"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032486; 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</script> <div class="js-work-strip profile--work_container" data-work-id="75032485"><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/75032485/Modeling_the_Efficiency_of_Emulsion_Separation_in_a_Combined_Apparatus"><img alt="Research paper thumbnail of Modeling the Efficiency of Emulsion Separation in a Combined Apparatus" 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/75032485/Modeling_the_Efficiency_of_Emulsion_Separation_in_a_Combined_Apparatus">Modeling the Efficiency of Emulsion Separation in a Combined Apparatus</a></div><div class="wp-workCard_item"><span>Mathematical Methods in Technologies and Technics</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="75032485"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032485"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032485; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032485]").text(description); $(".js-view-count[data-work-id=75032485]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032485; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032485']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032485]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032485,"title":"Modeling the Efficiency of Emulsion Separation in a Combined Apparatus","internal_url":"https://www.academia.edu/75032485/Modeling_the_Efficiency_of_Emulsion_Separation_in_a_Combined_Apparatus","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032484"><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/75032484/Prediction_of_sonic_log_and_correlation_of_lithology_by_comparing_geophysical_well_log_data_using_machine_learning_principles"><img alt="Research paper thumbnail of Prediction of sonic log and correlation of lithology by comparing geophysical well log data using machine learning principles" class="work-thumbnail" src="https://attachments.academia-assets.com/82966627/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/75032484/Prediction_of_sonic_log_and_correlation_of_lithology_by_comparing_geophysical_well_log_data_using_machine_learning_principles">Prediction of sonic log and correlation of lithology by comparing geophysical well log data using machine learning principles</a></div><div class="wp-workCard_item"><span>GeoJournal</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The well logging technique is used to determine the petrophysical properties like porosity, perme...</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">The well logging technique is used to determine the petrophysical properties like porosity, permeability and fluid saturations of subsurface formations. However, the conventional way of log evaluation is very expensive and tiresome. The postacquisition processing and inversion provides an alternative to determine the properties of drilled formations. This study proposes a novel approach to predict sonic log, adopting a regression method using a supervised machine learning (ML) algorithm, along with the determination of lithology employing clustering and a neural network approach grounded on the basis of gamma-ray log values and hence creating a correlation between the two. The scarce acoustic data obtained upon the traditional well logging procedure often pose a barrier in further determining the rock physics. Regression analysis, a predictive modeling technique, uses other petrophysical data to predict the sonic wave travel time (shear and compressional) by estimating a relationship between the two variables. The model is trained on a set of 10,000 points with 80% training points giving an 86.314% accuracy result. RMSE and R 2 scores for training points and testing points came out to be 2.622 and 0.95, and 2.55 and 0.96, respectively, which helps in the validation of the model. Effective lithology determination is a crucial step of reservoir characterization. Traditional methods of core sample inspection and using well logs, however, cannot meet the needs of real-time due to complex sediment environment and reservoir heterogeneity. To deal with the problem, an unsupervised ML model, K-means clustering, a method of vector quantization grouping unlabeled data into arbitrary clusters based on similarities with respect to distance from the center is used. The model gave the optimum number of clusters as 5 and showed a presence of siltstone, coal and sandstone separated between these clusters. The Silhouette score which tests the accuracy came out to be 0.5840 along with a CH score of 27,192.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8a4940fa10005384639d6b097a3e5377" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966627,"asset_id":75032484,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966627/download_file?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="75032484"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032484"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032484; 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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="75032482"><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/75032482/A_Recommendation_System_for_Customizable_Items"><img alt="Research paper thumbnail of A Recommendation System for Customizable Items" class="work-thumbnail" src="https://attachments.academia-assets.com/82966626/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/75032482/A_Recommendation_System_for_Customizable_Items">A Recommendation System for Customizable Items</a></div><div class="wp-workCard_item"><span>Advances in Intelligent Systems and Computing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The amount of data on the Internet is growing rapidly. This information overload has increased th...</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">The amount of data on the Internet is growing rapidly. This information overload has increased the popularity of recommendation systems over the past few years. Recommendation systems are software tools that help users by providing them suggestions for items or products according to their preferences. They have been around for decades, over which time a strong community of researchers and industry practitioners have risen. Recommendation systems generate product recommendations that are mainly useful for users who lack adequate proficiency in the respective product domain. The generated recommendations may be personalized or non-personalized (in magazines or in newspapers) depending upon the requirement. There are several techniques involved in building a recommendation system. This work mainly emphasizes content-based filtering and constraint-based filtering approaches, and how they are used for recommending descriptive items that are customized to user's taste.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a3b9ae86a36e6b04a7d24eb7e252ed0c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966626,"asset_id":75032482,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966626/download_file?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="75032482"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032482"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032482; 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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="75032481"><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/75032481/Survey_on_User_Behavior_Trust_Evaluation_in_Cloud_Computing"><img alt="Research paper thumbnail of Survey on User Behavior Trust Evaluation in Cloud Computing" 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/75032481/Survey_on_User_Behavior_Trust_Evaluation_in_Cloud_Computing">Survey on User Behavior Trust Evaluation in Cloud Computing</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing may be defined as management and provision of resources, software, applications a...</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">Cloud computing may be defined as management and provision of resources, software, applications and information as services over the cloud (internet) on demand. Cloud computing is a model for enabling convenient, on demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction (2). With its ability to provide users dynamically scalable, shared resources over the Internet and avoid large upfront fixed costs, cloud computing has recently emerged as a promising hosting platform that performs an intelligent usage of a collection of services, applications, information and infrastructure comprised of pools of computer, network, information and storage resources. However along with these advantages, storing a large amount of data including critical information on the cloud motivates highly skilled hackers thus creating a need for the security to be considered as one of t...</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="75032481"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032481"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032481; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032481]").text(description); $(".js-view-count[data-work-id=75032481]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032481; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032481']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032481]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032481,"title":"Survey on User Behavior Trust Evaluation in Cloud Computing","internal_url":"https://www.academia.edu/75032481/Survey_on_User_Behavior_Trust_Evaluation_in_Cloud_Computing","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032480"><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/75032480/A_Self_Optimization_Based_Virtual_Machine_Scheduling_to_Workloads_in_Cloud_Computing_Environment"><img alt="Research paper thumbnail of A Self-Optimization Based Virtual Machine Scheduling to Workloads in Cloud Computing Environment" 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/75032480/A_Self_Optimization_Based_Virtual_Machine_Scheduling_to_Workloads_in_Cloud_Computing_Environment">A Self-Optimization Based Virtual Machine Scheduling to Workloads in Cloud Computing Environment</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Energy consumption in the cloud computing plays a vital role in operating cost to the service pro...</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">Energy consumption in the cloud computing plays a vital role in operating cost to the service provider and cloud user. The cloud is scalable and it can provide the access as per demand, due to this resource access requests are increasing, and submitted to the server. To manage all request, scheduling is the solution to assign request with the quality of service. To avoid high operating cost, resource scheduling needs to be energy-aware. In this paper, energy-aware resource scheduling in the cloud is proposing. Total resource utilization of each resource has been calculating and energy is optimizing through antlion optimization algorithm to avoid high consumption of power. The resource is identify with its best utilization value and assign to submit workloads as per priority basis. The experimental results of the proposed work are analyzing with existing autonomic frameworks, and it is observed that proposed work is performing utmost. Index Term: Energy, Resource Cost, Execution Time...</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="75032480"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032480"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032480; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032480]").text(description); $(".js-view-count[data-work-id=75032480]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032480; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032480']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032480]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032480,"title":"A Self-Optimization Based Virtual Machine Scheduling to Workloads in Cloud Computing Environment","internal_url":"https://www.academia.edu/75032480/A_Self_Optimization_Based_Virtual_Machine_Scheduling_to_Workloads_in_Cloud_Computing_Environment","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032479"><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/75032479/Data_Storage_in_Cloud_Server_by_Token_Pre_Computation"><img alt="Research paper thumbnail of Data Storage in Cloud Server by Token Pre-Computation" 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/75032479/Data_Storage_in_Cloud_Server_by_Token_Pre_Computation">Data Storage in Cloud Server by Token Pre-Computation</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing can be defined as a new style of computing in which dynamically scalable and ofte...</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">Cloud computing can be defined as a new style of computing in which dynamically scalable and often virtualized resources are provided as services over the internet. With cloud computing technology, users use a variety of devices, including PCs, laptops, smart phones, and PDAs to access programs, storage, and application-development platforms over the Internet, via services offered by cloud computing providers. Advantages of cloud computing technology include cost savings, high availability, and easy scalability. Cloud computing moves the application software and data bases to the large data centres, where administration of the data and services may not be fully trustworthy. This unique aspect, however, poses many new security challenges which have not been well understood. In this article, we focus on cloud storage security, which has always been important feature of quality of service. To ensure the correctness of users data in the cloud, we suggest an effective and flexible techni...</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="75032479"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032479"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032479; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032479]").text(description); $(".js-view-count[data-work-id=75032479]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032479; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032479']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032479]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032479,"title":"Data Storage in Cloud Server by Token Pre-Computation","internal_url":"https://www.academia.edu/75032479/Data_Storage_in_Cloud_Server_by_Token_Pre_Computation","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032478"><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/75032478/GAP_Hybrid_Task_Scheduling_Algorithm_for_Cloud"><img alt="Research paper thumbnail of GAP: Hybrid Task Scheduling Algorithm for Cloud" class="work-thumbnail" src="https://attachments.academia-assets.com/82966623/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/75032478/GAP_Hybrid_Task_Scheduling_Algorithm_for_Cloud">GAP: Hybrid Task Scheduling Algorithm for Cloud</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Received: 9 March 2020 Accepted: 16 July 2020 Resource optimization is cost effective process in ...</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">Received: 9 March 2020 Accepted: 16 July 2020 Resource optimization is cost effective process in cloud. The efficiency of load balancing completely depends on how the infrastructure is utilizing. As per the current study, the resource optimization techniques are very costly and taking more convergence time to execute the task and load distribution among different virtual machines (VM). The objective of this paper is to develop a hybrid optimization algorithm to find the best virtual machine based on their fitness values and schedule different task to the fittest VM so that each task should get complete on time, and system can utilize the VM as well. The proposed algorithm is hybrid version of genetic (GA), ant-colony (Aco), and particle-swarm (Pso) algorithms, which is implemented and tested in amazon web service and compared with existing algorithms based on VM utilization, completion time, and cost. The proposed hybrid system genetic-aco-pso based algorithm (GAP) perform utmost wh...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c398b2148de0cf1302fdd87194fb7ae1" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966623,"asset_id":75032478,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966623/download_file?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="75032478"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032478"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032478; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032478]").text(description); $(".js-view-count[data-work-id=75032478]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032478; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032478']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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: "c398b2148de0cf1302fdd87194fb7ae1" } } $('.js-work-strip[data-work-id=75032478]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032478,"title":"GAP: Hybrid Task Scheduling Algorithm for Cloud","internal_url":"https://www.academia.edu/75032478/GAP_Hybrid_Task_Scheduling_Algorithm_for_Cloud","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[{"id":82966623,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966623/thumbnails/1.jpg","file_name":"41410.pdf","download_url":"https://www.academia.edu/attachments/82966623/download_file","bulk_download_file_name":"GAP_Hybrid_Task_Scheduling_Algorithm_for.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966623/41410-libre.pdf?1648707816=\u0026response-content-disposition=attachment%3B+filename%3DGAP_Hybrid_Task_Scheduling_Algorithm_for.pdf\u0026Expires=1739704002\u0026Signature=cjY9I8Lbw4xbP-mGTF7e~Ve~TaNFEUv2KNvUMHCRgSu~o6gg5heQRasMMjcRntcUuHIzDZf8SRyxT7M4lLIWLGIqOzlEXSHlIhASADtelgWLz0sPPNPOEJMX2qAeSAR5yAT~ilJhngpFsk2D34iAAoh99S1OEp0XyxNBNN6p73fd8ZYcoi51ANoG5iROuJIKZ9qA4EZ3xg3FQ0YlKYBFwq7Rcwis9wY6Eo4I9z3zyZYWnSnrl1sFs7LZorY~GXG0z8U8cO8VYORrWopBDIfbiwBGcHO5YHp-N7bPH6V6jaV-wlB7G3W3CPLPRYepIPFz7UKgzaj42nwHt18SrtTIKQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":82966624,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/82966624/thumbnails/1.jpg","file_name":"41410.pdf","download_url":"https://www.academia.edu/attachments/82966624/download_file","bulk_download_file_name":"GAP_Hybrid_Task_Scheduling_Algorithm_for.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/82966624/41410-libre.pdf?1648707815=\u0026response-content-disposition=attachment%3B+filename%3DGAP_Hybrid_Task_Scheduling_Algorithm_for.pdf\u0026Expires=1739704002\u0026Signature=JDPudHOzj5Rg3d6jaZoiYl-FND3MEij1H8oUzlXyXOmKyVQ84QTXUdnJxg6j7mEPW9mmX4v5HCgHd6AUupAb29-571brIZfXYmrWLn7InCCWTR2bjeNphknfXWM-1YCgp1zE6y~4oEsdj8UmWEM0rpW1bOohl5Q~SvBRRU-NJ3e~rPYMrP1WSoXFEK8rXgBJfkopir0m85gdmA54omXdca9pyvucVRMCPU6tXe1hkgZkh6xv3odqF1O--2mjwj6Ihh5I7VsGvmUTgJaMCOnBcdk9AH4ozzOaem9czoTis8t~JprscVkOy53praM57Co9Q9AW3CNRwvHOkoe6Zwiblw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, 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="75032477"><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/75032477/Design_of_Self_Management_Aware_Autonomic_Resource_Scheduling_Scheme_in_Cloud"><img alt="Research paper thumbnail of Design of Self-Management Aware Autonomic Resource Scheduling Scheme in Cloud" class="work-thumbnail" src="https://attachments.academia-assets.com/82966621/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/75032477/Design_of_Self_Management_Aware_Autonomic_Resource_Scheduling_Scheme_in_Cloud">Design of Self-Management Aware Autonomic Resource Scheduling Scheme in Cloud</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing is an emerging technology through which resources can be shared over the internet...</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">Cloud computing is an emerging technology through which resources can be shared over the internet with different users either free or on a rent basis. Resource scheduling in cloud computing is a challenging area for researchers as is maximum utilization can opt through efficient resource scheduling algorithm. In this environment, incalculability, and expansion of resources meeting the problem of allocation. Other than this, virtual machine provisioning, packaging, and availability guarantee decrease the performance. To avoid this, an efficient resource management technique is required, which will manage the resources effectively, guarantee the availability, and execute the workloads automatically. In this paper, we present an autonomic resource management technique named as SMART (Self-management aware autonomic resource management technique for cloud). SMART offers self-optimization for maximum resource utilization, self-healing to avoid failures on execution, self-protection to st...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="15a49a90c1cb6eb44bd1048e80755775" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966621,"asset_id":75032477,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966621/download_file?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="75032477"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032477"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032477; 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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="75032476"><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/75032476/Task_Scheduling_Using_Hybrid_PSO_in_Cloud_Based_Environment"><img alt="Research paper thumbnail of Task Scheduling Using Hybrid PSO in Cloud Based Environment" class="work-thumbnail" src="https://attachments.academia-assets.com/82966700/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/75032476/Task_Scheduling_Using_Hybrid_PSO_in_Cloud_Based_Environment">Task Scheduling Using Hybrid PSO in Cloud Based Environment</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Cloud computing ensures access to shared resources and ordinary infrastructure, providing service...</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">Cloud computing ensures access to shared resources and ordinary infrastructure, providing services on concern over a community for operations to fulfil changing industrial enterprise requirements. Scheduling may be a prominent activity that&#39;s finished during a cloud computing surroundings. To increase cloud computing work load performance, responsibilities programming is accomplished to induce most financial profit. In cloud, excessive communication cost prevents assignment schedulers from being distributed in immense scale assigned environments. This study proposes a hybrid improvement primarily based entirely on Particle Swarm improvement (PSO) and Genetic algorithmic program (GA) for programming in cloud environments.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d93f51bba80132a76ad9119159dfa85a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966700,"asset_id":75032476,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966700/download_file?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="75032476"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032476"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032476; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75032475"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75032475/Defense_in_Depth_for_Data_Storage_in_Cloud_Computing"><img alt="Research paper thumbnail of Defense in Depth for Data Storage in Cloud Computing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75032475/Defense_in_Depth_for_Data_Storage_in_Cloud_Computing">Defense in Depth for Data Storage in Cloud Computing</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75032475"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032475"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032475; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75032475]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032475,"title":"Defense in Depth for Data Storage in Cloud Computing","internal_url":"https://www.academia.edu/75032475/Defense_in_Depth_for_Data_Storage_in_Cloud_Computing","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032474"><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/75032474/The_Sliding_Window_Method_An_Environment_To_Evaluate_User_Behavior_Trust_In_Cloud_Technology"><img alt="Research paper thumbnail of The Sliding Window Method: An Environment To Evaluate User Behavior Trust In Cloud Technology" 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/75032474/The_Sliding_Window_Method_An_Environment_To_Evaluate_User_Behavior_Trust_In_Cloud_Technology">The Sliding Window Method: An Environment To Evaluate User Behavior Trust In Cloud Technology</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">-Trust is one of the most concerned obstacles for the adoption and growth of cloud computing. Alt...</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">-Trust is one of the most concerned obstacles for the adoption and growth of cloud computing. Although several solutions have been proposed recently in managing trust feedbacks in cloud enviornemts, how to determine the credibility of trust feedback in a cloud environments is difficult problem due to unpredictable numbers of cloud services consumers and highly dynamic nature of cloud environments. In the cloud computing, due to users directly use and operate the software and OS, and even the basic programming environment and network infrastructure which provided by the cloud service providers, so the impact and destruction of the software and hardware cloud resources in cloud computing are worse than the current Internet users who use it to share resources. Therefore, that whether user behavior is trusted, how to evaluate user behavior trust is an important research content in cloud computing. In this paper we mainly discusses evaluation importance of user behavior trust and evaluation strategy, in the cloud computing, including trust object analysis, principle in evaluating user behavior trust, the basic idea of evaluating user behavior trust, evaluation strategy of behavior trust for each access, and long acsess. In trust evaluation, behavior evidence is the fundamental basis of behavior evaluation. But at present, researchers almost directly use node behavior results or use a third party’s evaluation results to synthesize it, not study the original evidence of node behavior and ignore an analysis of node behavior history, which limit the reliability, rationality and sharing of trust. Drawing on the characteristics of social trust and trust requirement, we first put forward basic criteria about evaluating node behavior trust, and then bring forward a kind of evaluation mechanism on node behavior trust based on sliding window model. Keyword: Node Behavior Trust, Trust Evaluation, Evaluation Principles, Sliding Window.</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="75032474"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032474"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032474; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75032474]").text(description); $(".js-view-count[data-work-id=75032474]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75032474; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75032474']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=75032474]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75032474,"title":"The Sliding Window Method: An Environment To Evaluate User Behavior Trust In Cloud Technology","internal_url":"https://www.academia.edu/75032474/The_Sliding_Window_Method_An_Environment_To_Evaluate_User_Behavior_Trust_In_Cloud_Technology","owner_id":215569238,"coauthors_can_edit":true,"owner":{"id":215569238,"first_name":"Bhupesh","middle_initials":null,"last_name":"Kumar Dewangan","page_name":"BKumarDewangan","domain_name":"independent","created_at":"2022-02-22T21:15:13.544-08:00","display_name":"Bhupesh Kumar Dewangan","url":"https://independent.academia.edu/BKumarDewangan"},"attachments":[]}, 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="75032473"><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/75032473/A_Fuzzy_Interface_System_to_Predict_Depression_Risk"><img alt="Research paper thumbnail of A Fuzzy Interface System to Predict Depression Risk" class="work-thumbnail" src="https://attachments.academia-assets.com/82966620/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/75032473/A_Fuzzy_Interface_System_to_Predict_Depression_Risk">A Fuzzy Interface System to Predict Depression Risk</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Depression has been classified as a psychological disorder which is capable of affecting patients...</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">Depression has been classified as a psychological disorder which is capable of affecting patients both mentally and physically with unique presentation across patients. This unique presentation makes it difficult to predict the onset or the risk of onset of the disease. This paper presents the use of a fuzzy logic based interface system, which takes into account four primary predictors and then determines the risk of the onset of depression in three age groups. The approach shows promising results with high accuracy.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4459f13887d9ef1cd1eaefc933ebe8f1" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966620,"asset_id":75032473,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966620/download_file?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="75032473"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032473"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032473; 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This paper evaluates the Hurricane data measure and mass less data measure entropy of trajectories objects of moving data of Chhattisgarh location. The paper covered Prediction Generation with their distance cluster minimum description length (MDL) algorithm and others corresponding distance cluster (CLSTR) algorithm. This paper highlighted the k-nearest algorithm with least cluster section (LCSS) model and dimensional Euclidean of MDL algorithm. Our algorithm consists of two parts that is partitioning and grouping phase. This paper develops and enhances a cluster of trajectory object and calculates the actual distance of moving object. This algorithm works on the CLSTR algorithm and calculates Trajectory movement of object. In this we evaluate the entropy of moving object by...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8d13ba6b3bd05407bcc482ae7887e5b2" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82966699,"asset_id":75032472,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82966699/download_file?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="75032472"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032472"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032472; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75032471"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75032471/Cyber_Security_in_Cloud_Platforms"><img alt="Research paper thumbnail of Cyber Security in Cloud Platforms" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75032471/Cyber_Security_in_Cloud_Platforms">Cyber Security in Cloud Platforms</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75032471"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032471"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032471; 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It implies a service oriented architecture, reduced information technology overhead for the end-user, great flexibility, reduced total cost of ownership, ondemand services and many other things. This paper discusses the concept of “cloud” computing, some of the issues it tries to address, related research topics, and a “cloud” implementation available today.</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="75032470"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75032470"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75032470; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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