Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012 PDF
Preview Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012
Studies in Computational Intelligence 443 Editor-in-Chief Prof.JanuszKacprzyk SystemsResearchInstitute PolishAcademyofSciences ul.Newelska6 01-447Warsaw Poland E-mail:[email protected] Forfurthervolumes: http://www.springer.com/series/7092 Roger Lee (Ed.) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2012 ABC Editor Prof.Dr.RogerLee SoftwareEngineering&InformationTechnologyInstitute CentralMichiganUniversity Mt.Pleasant,Michigan48859 U.S.A. E-mail:[email protected] ISSN1860-949X e-ISSN1860-9503 ISBN978-3-642-32171-9 e-ISBN978-3-642-32172-6 DOI10.1007/978-3-642-32172-6 SpringerHeidelbergNewYorkDordrechtLondon LibraryofCongressControlNumber:2012942954 (cid:2)c Springer-VerlagBerlinHeidelberg2013 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped.Exemptedfromthislegalreservationarebriefexcerptsinconnection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. 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Printedonacid-freepaper SpringerispartofSpringerScience+BusinessMedia(www.springer.com) Preface The purpose of the 13thInternational Conference on Computer and Information Science(SNPD2012)heldonAugust8–10,2012inKyoto,Japanwastobringto- getherresearchersandscientists,businessmenandentrepreneurs,teachersandstu- dents to discuss the numerous fields of computer science, and to share ideas and informationin a meaningfulway. Ourconferenceofficersselected the best17 pa- persfromthosepapersacceptedforpresentationattheconferenceinordertopub- lishtheminthisvolume.Thepaperswerechosenbasedonreviewscoressubmitted by membersof the programcommittee,and underwentfurtherroundsof rigorous review. InChapter1,KenjiKawamotoetal.Inthispaper,weevaluatedthefeaturesused in previous studies while taking into account secular changes to classify normal trafficintothenormalcategoryandanomaloustrafficintotheanomalouscategory correctly. A secular change in this study is a difference in a feature between the datethetrainingdatawerecapturedandthedatethetestdatawerecapturedinthe samecircumstance.TheevaluationisbasedontheEuclideandistancebetweenthe normalcodebookoranomalouscodebookmadebyvectorquantizationandthetest data.Wereportonwhatcausesthesesecularchangesandwhichfeatureswithlittle ornosecularchangeareeffectiveformalwaredetection. InChapter2,HideoHiroseetal.Inthispaper,wefurtherinvestigatethepredic- tion accuracy of the tree-GA by comparing the trade-off curve obtained by using thetree-GAwiththatobtainedbyusingthePRIM(PatientRuleInductionMethod) proposedbyFriedmanandFisher.Wehavefoundthatthetree-GArevealsthesupe- riorityoverthePRIMinsomecases. InChapter3,TomohikoTakagietal.Thispaperproposesanovelback-to-back testing framework in which a SVM (support vector machine) classifies its results automatically. InChapter4,BiplobR.Ray.Inthispaper,weproposealightweightstenographic- based approach to ensure RFID data confidentiality and integrity as well as the recoveryoftamperedRFIDdata. In Chapter 5, Nazia Zaman et al. In this paper, we propose a novel approach, whichallowsaquickincreaseofthroughputbyusingexplicitfeedbackfromrouters. VI Preface In Chapter 6, GongzhuHu et al. In this paper,we build multivariateregression modelsofhomepricesusingadatasetcomposedof81homes.Wethenappliedthe maximuminformationcoefficient(MIC)statisticstotheobservedhomevalues(Y) andthepredictedvalues(X)asanevaluationoftheregressionmodels.Theresults showedveryhighstrengthoftherelationshipbetweenthetwovariablesXandY. InChapter7,TsuyoshiMiyazakietal.Inthispaper,wedescribeanimprovement ofthemethodthatdetectsdistinctivemouthshapesfromJapaneseutteranceimage sequence. In Chapter 8, Chung-HungHsieh et al. In thisstudy,we proposea totally non- contactimage-to-patientregistrationtechniqueusingkinectsensorandanICP-based (IterativeClosestPoint-based)registrationalgorithmwhichisnamedWAP-ICP. InChapter9,QimingChenetal.InthispaperWeproposethepage-flowapproach characterized by extending and externalizing the database buffer pool to DCP to allowtheproducerQEtoputqueryresultsasdatapages(blocks)totheDCPtobe retrievedbytheconsumerQE. In Chapter 10, Tomas Kucˇera et al. In this paper, we present an algorithm for automateddeploymentplanningofhierarchicalcomponentsystems.Thealgorithm incorporatescomponentdemandsandmachineresourcesinordertomaximizeper- formanceofdeployedapplications.Wealsopresentanimplementationofthealgo- rithmfortheSOFA2componentframework. InChapter11,KanuBokuetal.Inthispaper,weproposeacase-basedmethodfor generatingemotionalsyntheticspeechbyexploitingthecharacteristicsofthemaxi- mumamplitudeandtheutterancetimeofvowels,andthefundamentalfrequencyof emotionalspeech. InChapter12,YucongDuanetal.Inthispaper,weexploredatacleaningofvery largedatabasewithfocusonsemanticrichdataandlinkeddata,fromaknowledge managementperspective. In Chapter 13, Masahide Nakamura et al. This paper presents a novel service creation environment,called SensorService Binder (SSB),which providesa user- friendlyinterfaceforcreatingcontext-awareserviceswithintheHNS.Builtontop of the service-orientedHNS, the SSB allows non-expertusers to register contexts using the sensors, and to bind the registered context to any operation of the net- workedappliances. In Chapter 14, Masateru Tsunoda et al. In this paper, we focused risk factors whichhavestrongandstablerelationshipstocostoverrun,andanalyzedthemusing the Sharpe ratio based index. As a result, we identified some risk factors which haverelativelystrongandstablerelationshipstocostoverrun.Aftertheanalysis,we experimentallypredictedcostoverrunprojectsby collaborativefiltering,usingthe riskfactorsasindependentvariables.Theresultsuggestedthatcostoverrunprojects canbepredictedbytheriskfactors. In Chapter15,KazunoriIwataetal. Inthisstudy,we establish errorprediction modelsatvariousstagesofembeddedsoftwaredevelopmentusinghybridmethods ofself-organizingmaps(SOMs)andmultipleregressionanalyses(MRAs). SOMs areatypeofartificialneuralnetworksthatreliesonunsupervisedlearning. Preface VII InChapter16,TomokazuArita etal.Inthispaper,weintroduceattributegraph grammarsforlabeledgridgraphs,andproposetheirapplicationto generatingtab- ular forms representing program specification forms with grid structures, such as two–dimensionalarrays. In Chapter 17, Seiichi Serikawa et al. In this paper, we proposed a new fusion ruleformultimodalmedicalimagesbasedonMSFLCT. Itisoursincerehopethatthisvolumeprovidesstimulationandinspiration,and thatitwillbeusedasafoundationforworksyettocome. August2012 TeruhisaHochin NobuhiroInuzuka TokuroMatsuo Contents EvaluationofSecularChangesinStatisticalFeaturesofTrafficforthe PurposeofMalwareDetection.................................... 1 KenjiKawamoto,MasatsuguIchino,MitsuhiroHatada,YusukeOtsuki, HiroshiYoshiura,JiroKatto AComparativeStudyintheBumpHuntingbetweentheTree-GAand thePRIM ..................................................... 13 HideoHirose,GenkiKoga Back-to-Back Testing Framework Using a Machine Learning Method....................................................... 27 TomohikoTakagi,TakeshiUtsumi,ZengoFurukawa StenoCiphertoProvideDataConfidentialityandTamperedData RecoveryforRFIDTag.......................................... 37 BiplobR.Ray,MorshedChowdhury,JemalAbawajy Multimedia StreamRateControloverMANETBasedonRouter Feedback ..................................................... 53 NaziaZaman,MorshedChowdhury MultivariateRegressionModelingforHomeValueEstimateswith EvaluationUsingMaximumInformationCoefficient................. 69 GongzhuHu,JinpingWang,WenyingFeng AnImprovementofBasicMouthShapeDetectionRatefromJapanese UtteranceImageSequenceUsingOpticalFlow...................... 83 TsuyoshiMiyazaki,ToyoshiroNakashima,NaohiroIshii ANon-contactImage-to-PatientRegistrationMethodUsingKinect SensorandWAP-ICP ........................................... 95 Chung-HungHsieh,Chung-HsianHuang,Jiann-DerLee X Contents Page-FlowinQueryEngineGrid ................................. 103 QimingChen,MeichunHsu,RenWu AutomatedDeploymentofHierarchicalComponents................. 117 TomasKucˇera,PetrHneˇtynka,JanKofronˇ SpeechSynthesisofEmotionsUsingVowelFeatures ................. 129 KanuBoku,TaroAsada,YasunariYoshitomi,MasayoshiTabuse KnowledgeManagementforModelDrivenDataCleaningofVery LargeDatabase ................................................ 143 YucongDuan,RogerLee SupportingEnd-User DevelopmentofContext-AwareServicesin HomeNetworkSystem.......................................... 159 MasahideNakamura,ShuheiMatsuo,ShinsukeMatsumoto AnalyzingRiskFactorsAffectingProjectCostOverrun .............. 171 MasateruTsunoda,AkitoMonden,KenichiMatsumoto,RyosukeHatano, ToshihikoNakano,YutakaFukuchi ErrorPredictionMethodsfor Embedded SoftwareDevelopment Using Hybrid Models of Self-Organizing Maps and Multiple RegressionAnalyses ............................................ 185 KazunoriIwata,ToyoshiroNakashima,YoshiyukiAnan,NaohiroIshii AnAttributeLabeledGridGraphGrammarandItsApplicationto ProgramSpecificationForms .................................... 201 Tomokazu Arita, Tetsuro Nishino, Kimio Sugita, Kensei Tsuchida, TakeoYaku MultimodalMedicalImageFusioninExtendedContourletTransform Domain....................................................... 215 SeiichiSerikawa, HuiminLu, Yujie Li, LifengZhang,ShiyuanYang, AkiraYamawaki,ShotaNakashima,YuhkiKitazono AuthorIndex ..................................................... 227 List of Contributors JemalAbawajy WenyingFeng DeakinUniversity,Australia TrentUniversity,Canada [email protected] [email protected] YoshiyukiAnan YutakaFukuchi OmronSoftwareCo.,Ltd.,Japan Hitachi,Ltd.,Japan [email protected] [email protected] TomokazuArita ZengoFurukawa J.F.OberlinUniversity,Japan KagawaUniversity,Japan [email protected] [email protected] TaroAsada MitsuhiroHatada KyotoPrefecturalUniversity,Japan NTTCommunicationsCorporation, t [email protected] Japan [email protected] KanuBoku KyotoPrefecturalUniversity,Japan RyosukeHatano [email protected] Hitachi,Ltd.,Japan QimingChen HideoHirose HPLabs,USA KyushuInstituteofTechnology,Japan [email protected] [email protected] MorshedChowdhury PetrHneˇtynka DeakinUniversity,Australia CharlesUniversity,CzechRepublic [email protected] [email protected] YucongDuan Chung-HungHsieh UniversityofMilano-Bicocca,Italy ChangGungUniversity,Taiwan [email protected] [email protected] XII ListofContributors MeichunHsu TomasKucˇera HPLabs,USA CharlesUniversity,CzechRepublic [email protected] Jiann-DerLee GongzhuHu ChangGungUniversity,Taiwan CentralMichiganUniversity,USA [email protected] [email protected] RogerLee Chung-HsianHuang CentralMichiganUniversity,USA ChangGungUniversity,Taiwan [email protected] [email protected] YujieLi MasatsuguIchino KyushuInstituteofTechnology UniversityofElectoro-Communications, Japan HuiminLu KyushuInstituteofTechnology NaohiroIshii [email protected] AichiInstituteofTechnology,Japan [email protected] KenichiMatsumoto NaraInstituteofScienceand KazunoriIwata Technology,Japan AichiUniversity,Japan [email protected] [email protected] ShinsukeMatsumoto JiroKatto KobeUniversity,Japan WasedaUniversity,Japan [email protected] [email protected] ShuheiMatsuo KenjiKawamoto KobeUniversity,Japan WasedaUniversity,Japan [email protected] [email protected] TsuyoshiMiyazaki YuhkiKitazono KanagawaInstituteofTechnology, KitakyushuNationalCollegeof Japan Technology [email protected] [email protected] AkitoMonden JanKofronˇ NaraInstituteofScienceand CharlesUniversity,CzechRepublic Technology [email protected] [email protected] GenkiKoga MasahideNakamura NomuraResearchInstitute,Ltd., KobeUniversity,Japan Japan [email protected]
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