Big Data and Visual Analytics PDF
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Sang C. Suh Thomas Anthony Editors Big Data and Visual Analytics Big Data and Visual Analytics Sang C. Suh • Thomas Anthony Editors Big Data and Visual Analytics 123 Editors SangC.Suh ThomasAnthony DepartmentofComputerScience DepartmentofElectricaland TexasA&MUniversity-Commerce ComputerEngineering Commerce,TX,USA TheUniversityofAlabamaatBirmingham Birmingham,AL,USA ISBN978-3-319-63915-4 ISBN978-3-319-63917-8 (eBook) https://doi.org/10.1007/978-3-319-63917-8 LibraryofCongressControlNumber:2017957724 ©SpringerInternationalPublishingAG2017 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. Printedonacid-freepaper ThisSpringerimprintispublishedbySpringerNature TheregisteredcompanyisSpringerInternationalPublishingAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Foreword Theeditorsofthisbook,anaccomplishedseniordatascientistandsystemsengineer, Thomas Anthony, and an academic leader, Dr. Sang Suh, with broad expertise fromartificialintelligencetodataanalytics,constituteaperfectteamtoachievethe goal of compiling a book on Big Data and Visual Analytics. For most uninitiated professionals“BigData”isnothingbutabuzzwordoranewfad.Forthepeoplein thetrenches,suchasSangandThomas,BigDataandassociatedanalyticsisamatter ofseriousbusiness.Iamhonoredtohavebeengiventheopportunitytoreviewtheir compiledvolumeandwriteaforewordtoit. Afterreviewingthechapters,Irealizedthattheyhavedevelopedacomprehensive book for data scientists and students by taking into account both theoretical and practical aspects of this critical and growing area of interest. The presentations are broad and deep as the need arise. In addition to coveringall criticalprocesses involvingdatascience,theyhaveuniquelyprovidedverypracticalvisualanalytics applicationssothatthereaderlearnsfromtheperspectiveexecutedasanengineer- ing discipline. This style of presentation is a unique contribution to this new and growingareaandplacesthisbookatthetopofthelistofcomparablebooks. Thechapterscoveredare1.AutomatedDetectionofCentralRetinalVeinOcclu- sion Using ConvolutionalNeuralNetwork,by “Bismita Choudhury,PatrickH. H. Then,andValliappanRaman”;2.SwarmIntelligenceAppliedtoBigDataAnalytics forRescueOperationswithRASENSensorNetworks,by“U.JohnTanik,Yuehua Wang, and Serkan G. ldal”; 3. Gender Classification Based on Deep Learning, by “Dhiraj Gharana, Sang Suh, and Mingon Kang”; 4. Social and Organizational Culture in Korea and Women’s Career Development, by “Choonhee Yang and YongmanKwon”;5.BigDataFrameworkforAgileBusiness(BDFAB)asaBasis for DevelopingHolistic Strategies in Big Data Adoption, by “Bhuvan Unhelkar”; 6.ScalableGeneSequenceAnalysisonSpark,by“MuthaharSyed,JinohKim,and TaehyunHwang”;7.BigSensorDataAcquisitionandArchivingwithCompression, by “Dongeun Lee”; 8. Advanced High Performance Computing for Big Data LocalVisualMeaning,“OzgurAksu”;9.TransdisciplinaryBenefitsofConvergence in Big Data Analytics, “U. John Tanik and Darrell Fielder”; 10. A Big Data Analytics Approach in Medical Image Segmentation Using Deep Convolutional v vi Foreword NeuralNetworks,by“ZhengZhang,DavidOdaibo,andMuratM.Tanik”;11.Big DatainLibraries,by“RobertOlendorfandYanWang”;12.AFrameworkforSocial Network Sentiment Analysis Using Big Data Analytics, by “Bharat Sri Harsha KarpurapuandLeonJololian”;13.BigDataAnalyticsandVisualization:Finance, by“P. ShyamandLarryMave”;14.Studyof HardwareTrojansin a Closed Loop Control System for an Internet-of-Things Application, by “Ranveer Kumar and Karthikeyan Lingasubramanian”; 15. High Performance/Throughput Computing Workflow for a Neuro-Imaging Application: Provenance and Approaches, by “T.Anthony,J.P.Robinson,J.Marstrander,G.Brook,M.Horton,andF.Skidmore.” The review of the above diverse content convinces me that the promise of the wide application of big data becomes abundantly evident. A comprehensive transdisciplinary approach is also evident from the list of chapters. At this point IhavetoinvoketheroadmappublishedbytheNationalAcademyofSciencestitled “Convergence:FacilitatingTransdisciplinaryIntegrationofLifeSciences,Physical Sciences, Engineering, and Beyond” (ISBN 978-0-309-30151-0). This document and its NSF counterpart states convergence as “an approach to problem solving thatcutsacrossdisciplinaryboundaries.Itintegratesknowledge,tools,andwaysof thinkingfromlife and health sciences, physical,mathematical, and computational sciences, engineering disciplines, and beyond to form a comprehensive synthetic frameworkfortacklingscientificandsocietalchallengesthatexistattheinterfaces ofmultiplefields.” Big data andassociated analyticsis a twenty-firstcenturyarea of interest, providing a transdisciplinary framework to the problems that can be addressedwithconvergence. Interestingly,theSocietyforDesignandProcessScience(SDPS),www.sdpsnet. org,whichoneoftheauthorshasbeeninvolvedwithfromthebeginning,hasbeen investigating convergence issues since 1995. The founding technical principle of SDPShasbeentoidentifytheunique“approachtoproblemsolvingthatcutsacross disciplinaryboundaries.”TheanswerwastheobservationthatthenotionsofDesign and Process cut across all disciplines and they should be studied scientifically in their own merits, while being applied for developing the engineering of artifacts. Thisbookbringsthedesignandprocessmatterstotheforefrontthroughthestudy of data science and, as such, brings an important perspective on convergence. Incidentally,theSDPS2017conferencewasdedicatedto“ConvergenceSolutions.” SDPSisaninternational,cross-disciplinary,multiculturalorganizationdedicated to transformative research and education through transdisciplinary means. SDPS celebrateditstwenty-secondyearduringtheSDPS2017conferencewithemphasis on convergence. Civilizations depend on technology and technology comes from knowledge. The integration of knowledge is the key for the twenty-first century problems.Data science in generaland Big Data Visual Analyticsin particularare partoftheanswertoourgrowingproblems. This book is a timely addition to serve data science and visual analytics communityofstudentsandscientists.We hopethatitwillbepublishedontimeto bedistributedduringtheSDPS2018conference.Thecomprehensiveandpractical natureof thebook,addressingcomplextwenty-firstcenturyengineeringproblems in a transdisciplinary manner, is something to be celebrated. I am, as one of the Foreword vii foundersof SDPS, a military and commercialsystems developer,industrial grade software developer, and a teacher, very honored to write this foreword for this importantpracticalbook. I am convincedthat it will take its rightfulplace in this growingareaofimportance. ElectricalandComputerEngineeringDepartment MuratM.Tanik UAB,Birmingham,AL,USA WallaceR.Bunn EndowedProfessorof Telecommunications Contents AutomatedDetectionof CentralRetinalVeinOcclusionUsing ConvolutionalNeuralNetwork................................................. 1 BismitaChoudhury,PatrickH.H.Then,andValliappanRaman SwarmIntelligence Applied to Big Data AnalyticsforRescue OperationswithRASENSensorNetworks.................................... 23 U.JohnTanik,YuehuaWang,andSerkanGüldal GenderClassificationBasedonDeepLearning .............................. 55 DhirajGharana,SangC.Suh,andMingonKang SocialandOrganizationalCultureinKoreaandWomen’sCareer Development...................................................................... 71 ChoonheeYangandYongmanKwon BigDataFrameworkforAgileBusiness(BDFAB)AsaBasisfor DevelopingHolisticStrategiesinBigDataAdoption ........................ 85 BhuvanUnhelkar ScalableGeneSequenceAnalysisonSpark................................... 97 MuthaharSyed,TaehyunHwang,andJinohKim BigSensorDataAcquisitionandArchivingwithCompression ............ 115 DongeunLee AdvancedHighPerformanceComputingforBigDataLocalVisual Meaning........................................................................... 145 OzgurAksu TransdisciplinaryBenefitsofConvergenceinBigDataAnalytics.......... 165 U.JohnTanikandDarrellFielder ABigDataAnalyticsApproachinMedicalImagingSegmentation UsingDeepConvolutionalNeuralNetworks.................................. 181 ZhengZhang,DavidOdaibo,FrankM.Skidmore,andMuratM.Tanik ix x Contents BigDatainLibraries ............................................................ 191 RobertOlendorfandYanWang AFrameworkforSocialNetworkSentimentAnalysisUsingBig DataAnalytics.................................................................... 203 BharatSri HarshaKarpurapuandLeonJololian BigDataAnalyticsandVisualization:Finance............................... 219 ShyamPrabhakarandLarryMaves StudyofHardwareTrojansinaClosedLoopControlSystemfor anInternet-of-ThingsApplication ............................................. 231 RanveerKumarandKarthikeyanLingasubramanian High Performance/Throughput Computing Workflow for aNeuro-ImagingApplication:ProvenanceandApproaches................ 245 T.Anthony,J.P.Robinson,J.R. Marstrander,G.R. Brook,M.Horton, andF.M.Skidmore Index............................................................................... 257 Automated Detection of Central Retinal Vein Occlusion Using Convolutional Neural Network BismitaChoudhury,PatrickH.H.Then,andValliappanRaman Abstract TheCentralRetinalVeinOcclusion(CRVO)isthenextsupremereason for the vision loss among the elderly people, after the Diabetic Retinopathy. The CRVO causes abrupt, painless vision loss in the eye that can lead to visual impairmentoverthetime.Therefore,theearlydiagnosisofCRVOisveryimportant to preventthe complicationsrelated to CRVO. But, the early symptomsof CRVO are so subtle that manually observing those signs in the retina image by the ophthalmologists is difficult and time consuming process. There are automatic detectionsystemsfordiagnosingoculardisease,buttheirperformancedependson variousfactors.Thehaemorrhages,theearlysignofCRVO,canbeofdifferentsize, color and texture from dot haemorrhages to flame shaped. For reliable detection of the haemorrhages of all types; multifaceted pattern recognition techniques are required.Toanalysethetortuosityanddilationoftheveins,complexmathematical analysis is required in order to extract those features. Moreover, the performance of such feature extraction methods and automatic detection system depends on the quality of the acquired image. In this chapter, we have proposed a prototype for automated detection of the CRVO using the deep learning approach. We have designed a Convolutional Neural Network (CNN) to recognize the retina with CRVO. The advantage of using CNN is that no extra feature extraction step is required. We have trained the CNN to learn the features from the retina images havingCRVOandclassifythemfromthenormalretinaimage.Wehaveobtainedan accuracyof97.56%fortherecognitionofCRVO. Keywords Retinal vein occlusion (cid:129) Central retinal vein occlusion (cid:129) Convolu- tion (cid:129) Features B.Choudhury((cid:2))(cid:129)P.H.H.Then(cid:129)V.Raman CentreforDigitalFuturesandFacultyofEngineering,ComputingandScience,Swinburne UniversityofTechnology,SarawakCampus,Kuching,Sarawak,Malaysia e-mail:[email protected] ©SpringerInternationalPublishingAG2017 1 S.C.Suh,T.Anthony(eds.),BigDataandVisualAnalytics, https://doi.org/10.1007/978-3-319-63917-8_1
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