Advances in Machine Learning and Data Science: Recent Achievements and Research Directives PDF
Preview Advances in Machine Learning and Data Science: Recent Achievements and Research Directives
Advances in Intelligent Systems and Computing 705 Damodar Reddy Edla · Pawan Lingras Editors Venkatanareshbabu K. Advances in Machine Learning and Data Science Recent Achievements and Research Directives Advances in Intelligent Systems and Computing Volume 705 Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected] The series “Advances in Intelligent Systems and Computing” contains publications on theory, applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all disciplines such as engineering, natural sciences, computer and information science, ICT, economics, business,e-commerce,environment,healthcare,lifesciencearecovered.Thelistoftopicsspansallthe areasofmodernintelligentsystemsandcomputingsuchas:computationalintelligence,softcomputing includingneuralnetworks,fuzzysystems,evolutionarycomputingandthefusionoftheseparadigms, social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and society, cognitive science and systems, Perception and Vision, DNA and immune based systems, self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric computing, recommender systems, intelligent control, robotics and mechatronics including human-machine teaming,knowledge-based paradigms,learning paradigms,machineethics,intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligentnetworksecurity,trustmanagement,interactiveentertainment,Webintelligenceandmultimedia. Thepublicationswithin“AdvancesinIntelligentSystemsandComputing”areprimarilyproceedings ofimportantconferences,symposiaandcongresses.Theycoversignificantrecentdevelopmentsinthe field,bothofafoundationalandapplicablecharacter.Animportantcharacteristicfeatureoftheseriesis theshortpublicationtimeandworld-widedistribution.Thispermitsarapidandbroaddisseminationof researchresults. AdvisoryBoard Chairman NikhilR.Pal,IndianStatisticalInstitute,Kolkata,India e-mail:[email protected] Members RafaelBelloPerez,UniversidadCentral“MartaAbreu”deLasVillas,SantaClara,Cuba e-mail:[email protected] EmilioS.Corchado,UniversityofSalamanca,Salamanca,Spain e-mail:[email protected] HaniHagras,UniversityofEssex,Colchester,UK e-mail:[email protected] LászlóT.Kóczy,SzéchenyiIstvánUniversity,Győr,Hungary e-mail:[email protected] VladikKreinovich,UniversityofTexasatElPaso,ElPaso,USA e-mail:[email protected] Chin-TengLin,NationalChiaoTungUniversity,Hsinchu,Taiwan e-mail:[email protected] JieLu,UniversityofTechnology,Sydney,Australia e-mail:[email protected] PatriciaMelin,TijuanaInstituteofTechnology,Tijuana,Mexico e-mail:[email protected] NadiaNedjah,StateUniversityofRiodeJaneiro,RiodeJaneiro,Brazil e-mail:[email protected] NgocThanhNguyen,WroclawUniversityofTechnology,Wroclaw,Poland e-mail:[email protected] JunWang,TheChineseUniversityofHongKong,Shatin,HongKong e-mail:[email protected] Moreinformationaboutthisseriesathttp://www.springer.com/series/11156 ⋅ Damodar Reddy Edla Pawan Lingras Venkatanareshbabu K. Editors Advances in Machine Learning and Data Science Recent Achievements and Research Directives 123 Editors Damodar ReddyEdla Venkatanareshbabu K. Department ofComputer Science Department ofComputer Science andEngineering andEngineering National Institute National Institute ofTechnology Goa ofTechnology Goa Goa Goa India India PawanLingras Department ofMathematics andComputing Science Saint Mary’s University Halifax, NS Canada ISSN 2194-5357 ISSN 2194-5365 (electronic) Advances in Intelligent Systems andComputing ISBN978-981-10-8568-0 ISBN978-981-10-8569-7 (eBook) https://doi.org/10.1007/978-981-10-8569-7 LibraryofCongressControlNumber:2018934903 ©SpringerNatureSingaporePteLtd.2018 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authorsortheeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinor for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. Printedonacid-freepaper ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSingaporePteLtd. partofSpringerNature Theregisteredcompanyaddressis:152BeachRoad,#21-01/04GatewayEast,Singapore189721, Singapore Preface It is our pleasure to present the reader the proceedings of the first international conference on Latest Advances in Machine learning and Data Science (LAMDA 2017) organized during October 25–27, 2017, in the Department of Computer Science and Engineering, National Institute of Technology Goa, India. LAMDA 2017 is the first international conference, which aims at providing an opportunity for scientists, engineers, educators, and students to gather so as to present the state-of-the-art advancements in the fertile domains of machine learning and data science. Machine learning is a field of computer science that provides computers the ability tolearn without being explicitly programmed. Machine learningfocuses on constructing computer programs that improves with experience. Machine learning is a fast-growing field, which is widely used in the Web browsing, information filteringontheWeb,creditcardfrauddetection,andmanymoreapplications.Data scienceisaninterdisciplinaryfieldaboutscientificmethods,processes,andsystems to extract knowledge or insights from data in various forms, either structured or unstructured.Itincludesdataanalysisfieldssuchasdatamining,machinelearning, statistics, and knowledge discovery of data. Data science can be used in domains like pattern and speech recognition, robotics, bioinformatics. We received 123 papers from different regions, and based on the reviews, technical program chairs selected 48 quality papers for the proceedings, out of which38papershavebeenpublishedinthisvolume.Thesepaperscomprisetopics related to machine learning and data science including classification of images, data, videos, clustering techniques, support vector machines, statistical learning, association rules, mining of images, graph mining, Web mining. AtLAMDA2017,technicalinteractionswithintheresearchcommunitywerein the form of keynote speeches, panel discussions, and oral presentations. It encourages open debate and disagreement as this is the right way to push the field forward in the new directions. It provides an environment for the participants to present new results, to discuss state of the art, and to interchange information on emerging areas and future trends of machine learning and data science. It also v vi Preface createsanopportunityfortheparticipantstomeetcolleaguesandmakefriendswho share similar research interests. TheorganizersandvolunteersinLAMDA2017madegreateffortstoensurethe success of this event. The success of the conference was also due to the precious collaboration of the co-chairs and the members of the local organizing committee. We would also like to thank the members of the program committee and the referees for reviewing the papers and the publication committee for checking and compiling the papers. We would also like to thank the publisher, Springer-Verlag, for their agreement and cooperation to publish the proceedings as a volume of “Advances in Machine Learning and Data Science—Recent Achievements and Research Directives.” We wish to extend our gratitude to all the keynote speakers and participants who enabled the success of this year’s edition of LAMDA. Goa, India Damodar Reddy Edla Halifax, Canada Pawan Lingras Goa, India Venkatanareshbabu K. October 2017 Contents Optimization of Adaptive Resonance Theory Neural Network Using Particle Swarm Optimization Technique . . . . . . . . . . . . . . . . . . . . . . . . 1 Khushboo Satpute and Rishik Kumar Accelerating Airline Delay Prediction-Based P-CUDA Computing Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Dharavath Ramesh, Neeraj Patidar, Teja Vunnam and Gaurav Kumar IDPC-XML: Integrated Data Provenance Capture in XML. . . . . . . . . . 21 Dharavath Ramesh, Himangshu Biswas and Vijay Kumar Vallamdas Learning to Classify Marathi Questions and Identify Answer Type Using Machine Learning Technique. . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Sneha Kamble and S. Baskar A Dynamic Clustering Algorithm for Context Change Detection in Sensor-Based Data Stream System. . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Nitesh Funde, Meera Dhabu and Umesh Balande Predicting High Blood Pressure Using Decision Tree-Based Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Satyanarayana Nimmala, Y. Ramadevi, Srinivas Naik Nenavath and Ramalingaswamy Cheruku Design of Low-Power Area-Efficient Shift Register Using Transmission Gate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Akash S. Band and Vishal D. Jaiswal Prediction and Analysis of Liver Patient Data Using Linear Regression Technique. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Deepankar Garg and Akhilesh Kumar Sharma Image Manipulation Detection Using Harris Corner and ANMS. . . . . . 81 Choudhary Shyam Prakash, Sushila Maheshkar and Vikas Maheshkar vii viii Contents Spatial Co-location Pattern Mining Using Delaunay Triangulation . . . . 95 G. Kiran Kumar, Ilaiah Kavati, Koppula Srinivas Rao and Ramalingaswamy Cheruku Review on RBFNN Design Approaches: A Case Study on Diabetes Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Ramalingaswamy Cheruku, Diwakar Tripathi, Y. Narasimha Reddy and Sathya Prakash Racharla Keyphrase and Relation Extraction from Scientific Publications . . . . . . 113 R. C. Anju, Sree Harsha Ramesh and P. C. Rafeeque Mixing and Entrainment Characteristics of Jet Control with Crosswire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 S. Manigandan, K. Vijayaraja, G. Durga Revanth and A. V. S. C. Anudeep GCV-Based Regularized Extreme Learning Machine for Facial Expression Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Shraddha Naik and Ravi Prasad K. Jagannath Prediction of Social Dimensions in a Heterogeneous Social Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Aiswarya and Radhika M. Pai Game Theory-Based Defense Mechanisms of Cyber Warfare . . . . . . . . 149 Monica Ravishankar, D. Vijay Rao and C. R. S. Kumar Challenges Inherent in Building an Intelligent Paradigm for Tumor Detection Using Machine Learning Algorithms . . . . . . . . . . 153 A. S. Shinde, V. V. Desai and M. N. Chavan Segmentation Techniques for Computer-Aided Diagnosis of Glaucoma: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Sumaiya Pathan, Preetham Kumar and Radhika M. Pai Performance Analysis of Information Retrieval Models on Word Pair Index Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 N. Karthika and B. Janet Fast Fingerprint Retrieval Using Minutiae Neighbor Structure . . . . . . . 187 Ilaiah Kavati, G. Kiran Kumar and Koppula Srinivas Rao Key Leader Analysis in Scientific Collaboration Network Using H-Type Hybrid Measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Anand Bihari and Sudhakar Tripathi A Graph-Based Method for Clustering of Gene Expression Data with Detection of Functionally Inactive Genes and Noise. . . . . . . . . . . . 203 Girish Chandra, Akshay Deepak and Sudhakar Tripathi Contents ix OTAWE-Optimized Topic-Adaptive Word Expansion for Cross Domain Sentiment Classification on Tweets . . . . . . . . . . . . . . . . . . . . . . 213 Savitha Mathapati, Ayesha Nafeesa, S. H. Manjula and K. R. Venugopal DCaP—Data Confidentiality and Privacy in Cloud Computing: Strategies and Challenges. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Basappa B. Kodada and Demian Antony D’Mello Design and Development of a Knowledge-Based System for Diagnosing Diseases in Banana Plants . . . . . . . . . . . . . . . . . . . . . . . . . . 239 M. B. Santosh Kumar, V. G. Renumol and Kannan Balakrishnan A Review on Methods Applied on P300-Based Lie Detectors. . . . . . . . . 251 Annushree Bablani and Diwakar Tripathi Implementation of Spectral Subtraction Using Sub-band Filtering in DSP C6748 Processor for Enhancing Speech Signal. . . . . . . . . . . . . . 259 U. Purushotham and K. Suresh In-silico Analysis of LncRNA-mRNA Target Prediction. . . . . . . . . . . . . 269 Deepanjali Sharma and Gaurav Meena Energy Aware GSA-Based Load Balancing Method in Cloud Computing Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 Vijayakumar Polepally and K. Shahu Chtrapati Relative Performance Evaluation of Ensemble Classification with Feature Reduction in Credit Scoring Datasets . . . . . . . . . . . . . . . . . . . . 293 Diwakar Tripathi, Ramalingaswamy Cheruku and Annushree Bablani Family-Based Algorithm for Recovering from Node Failure in WSN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Rajkumar Krishnan and Ganeshkumar Perumal Classification-Based Clustering Approach with Localized Sensor Nodes in Heterogeneous WSN (CCL). . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Ditipriya Sinha, Ayan Kumar Das, Rina Kumari and Suraj Kumar Multimodal Biometric Authentication System Using Local Hand Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 Gaurav Jaswal, Amit Kaul and Ravinder Nath Automatic Semantic Segmentation for Change Detection in Remote Sensing Images. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337 Tejashree Kulkarni and N Venugopal A Model for Determining Personality by Analyzing Off-line Handwriting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 345 Vasundhara Bhade and Trupti Baraskar
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