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Improved SfM-Based Indoor Localization with Occlusion Removal 改进的基于sfm的室内定位与遮挡去除
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-07-01 DOI: 10.4018/IJSSCI.2018070102
Yushi Li, G. Baciu, Yu Han, Chenhui Li
{"title":"Improved SfM-Based Indoor Localization with Occlusion Removal","authors":"Yushi Li, G. Baciu, Yu Han, Chenhui Li","doi":"10.4018/IJSSCI.2018070102","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018070102","url":null,"abstract":"This article describes a novel 3D image-based indoor localization system integrated with an improved SfM (structure from motion) approach and an obstacle removal component. In contrast with existing state-of-the-art localization techniques focusing on static outdoor or indoor environments, the adverse effects, generated by moving obstacles in busy indoor spaces, are considered in this work. In particular, the problem of occlusion removal is converted into a separation problem of moving foreground and static background. A low-rank and sparse matrix decomposition approach is used to solve this problem efficiently. Moreover, a SfM with RT (re-triangulation) is adopted in order to handle the drifting problem of incremental SfM method in indoor scene reconstruction. To evaluate the performance of the system, three data sets and the corresponding query sets are established to simulate different states of the indoor environment. Quantitative experimental results demonstrate that both query registration rate and localization accuracy increase significantly after integrating the authors' improvements.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125015197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of Structural Properties of Seismic Data to Prediction of Hydrocarbon Distribution 地震资料结构性质在油气分布预测中的应用
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-07-01 DOI: 10.4018/IJSSCI.2018070103
Wei Zhou, Haimin Guo, Yaoting Lin
{"title":"Application of Structural Properties of Seismic Data to Prediction of Hydrocarbon Distribution","authors":"Wei Zhou, Haimin Guo, Yaoting Lin","doi":"10.4018/IJSSCI.2018070103","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018070103","url":null,"abstract":"This article describes how under the influence of traps and trap ranges in size, final moisture content in oil production and changes in the reservoir is very large. Due to this, thin and dispersed oil concentration, facies changes and oil complexes, and strong segmentation, results in poor comparability between wells and conventional methods of seismic reservoir prediction has been more difficult to meet the development needs of the block. Therefore, the introduction of methods of seismic data structure characteristics, with a method based on sequence structure of underground rock formations, rock and petroleum allows the prediction for oil and gas purposes. Through the application of seismic structural properties, the result has been verified in practice and achieved a good application effect.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129929310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Jamming-Resilient Wideband Cognitive Radios with Multi-Agent Reinforcement Learning 基于多智能体强化学习的抗干扰宽带认知无线电
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-07-01 DOI: 10.4018/IJSSCI.2018070101
Mohamed A. Aref, S. Jayaweera
{"title":"Jamming-Resilient Wideband Cognitive Radios with Multi-Agent Reinforcement Learning","authors":"Mohamed A. Aref, S. Jayaweera","doi":"10.4018/IJSSCI.2018070101","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018070101","url":null,"abstract":"This article presents a design of a wideband autonomous cognitive radio (WACR) for anti-jamming and interference-avoidance. The proposed system model allows multiple WACRs to simultaneously operate over the same spectrum range producing a multi-agent environment. The objective of each radio is to predict and evade a dynamic jammer signal as well as avoiding transmissions of other WACRs. The proposed cognitive framework is made of two operations: sensing and transmission. Each operation is helped by its own learning algorithm based on Q-learning, but both will be experiencing the same RF environment. The simulation results indicate that the proposed cognitive anti-jamming technique has low computational complexity and significantly outperforms non-cognitive sub-band selection policy while being sufficiently robust against the impact of sensing errors.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130168272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Dynamic Monitoring of Forest Volumes by a Feature Extraction Method 基于特征提取方法的森林体积动态监测
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-07-01 DOI: 10.4018/IJSSCI.2018070104
Xu Jie, Dawei Qi
{"title":"Dynamic Monitoring of Forest Volumes by a Feature Extraction Method","authors":"Xu Jie, Dawei Qi","doi":"10.4018/IJSSCI.2018070104","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018070104","url":null,"abstract":"In this article, in order to improve tree volume calculation method, a measurement method based on tree information point feature extraction is proposed, the method based on image processing and binocular vision, according to the measurement result of information point change and tree growth model, achieve through the distance change of information point to study the tree volume change. The visual measurement method is compared with the traditional method, the feasibility and accuracy of the method are proven. From the results, tree volume changes through the information point feature extraction and the traditional breast diameter measurement is very similar, the maximal percentage increase is 2.570% and 2.546%, the minimum percentage increase is 0.092% and 0.068%, which shows that volume change is consistent with the results, confirmed the tree volume change scheme of visual measurement is feasible and the result is reliable, which can reduce the impact of environmental change in the manual measurement.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114983432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Fine-Grained Stateful Data Analytics Method Based on Resilient State Table 基于弹性状态表的细粒度状态数据分析方法
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-04-01 DOI: 10.4018/IJSSCI.2018040105
Jike Ge, Wenbo He, Zuqin Chen, Can Liu, Jun Peng, Guorong Chen
{"title":"A Fine-Grained Stateful Data Analytics Method Based on Resilient State Table","authors":"Jike Ge, Wenbo He, Zuqin Chen, Can Liu, Jun Peng, Guorong Chen","doi":"10.4018/IJSSCI.2018040105","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018040105","url":null,"abstract":"Thisarticledescribeshowstatefuldataanalyticframeworkshaveemergedtoprovidefreshandlowlatencyresultsforbigdataprocessing.Atpresent,itisdesiredtoachievethefine-graineddatamodel inSparkdataprocessingframework.However,Sparkadoptscoarse-graineddatamodelinorderto facilitateparallelization,itischallengingindealingwiththefine-graineddataaccessinstatefuldata analytics.Inthispaper,theauthorsintroduceafine-grainedstatefuldatacomponent,ResilientState Table(RST),toSparkframework.Forfillingthegapbetweenthecoarse-graineddatamodelinSpark andthefine-graineddataaccessrequirementsinstatefuldataanalytics,theydevisetheprogramming model of RST which interacts with Spark’s coarse-grained memory representation seamlessly, andenableuserstoquery/updatethestateentriesinfinegranularitywithSpark-likeprogramming interfaces.Performanceevaluationexperimentsinvariousapplicationfieldsdemonstratethattheir proposedsolutionachievestheimprovementsinlatency,fault-tolerance,aswellasscalability. KeywoRDS Big Data, Resilient Distributed Dataset, Resilient State Table, Spark, Stateful Data Analytics","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"18 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124338144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Nuclei Segmentation for Quantification of Brain Tumors in Digital Pathology Images 数字病理图像中量化脑肿瘤的核分割
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-04-01 DOI: 10.4018/IJSSCI.2018040103
P. Guo, A. Evans, P. Bhattacharya
{"title":"Nuclei Segmentation for Quantification of Brain Tumors in Digital Pathology Images","authors":"P. Guo, A. Evans, P. Bhattacharya","doi":"10.4018/IJSSCI.2018040103","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018040103","url":null,"abstract":"","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":" 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120829443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Passenger Condition Based Route-Planning for Cognitive Vehicle System 基于乘客状况的认知车辆系统路径规划
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-04-01 DOI: 10.4018/IJSSCI.2018040102
H. Hiraishi
{"title":"Passenger Condition Based Route-Planning for Cognitive Vehicle System","authors":"H. Hiraishi","doi":"10.4018/IJSSCI.2018040102","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018040102","url":null,"abstract":"Thisarticleproposesaroute-planningmethodforanenvironmentinwhichself-drivingvehiclesare widelyused.Suchvehiclesgenerateanewroutetoavoidtrafficcongestionwhenitoccurs.Through theself-developedtrafficsimulator,theauthorwasabletoclarifythatitisnotalwaysbesttogenerate anavoidanceroute,andthedecisiontodrivealongthecurrentroutewithoutgeneratinganavoidance routebecomesimportantincertaincases.Thus,theauthorproposesamethodinwhichavehiclejudges whethertogenerateanavoidanceroutebasedonthepassenger’scondition.Todetectthepassenger’s condition,theauthorusesasitting-pressuresensorandsucceededinrecognizingpassengerfatigue. Theauthorcanthereforemakecertainjudgments:Thevehiclewillgoalongthecurrentrouteifthe passengerseemstoberelaxedandinacomfortableatmosphere,thevehiclewillarriveearlierby avoidingtrafficcongestionifthepassengerseemstobetiredorirritated,orthevehiclewillstopfor abreakperiodifthepassengerseemstobesignificantlytired. KeywoRdS A* Search, Cognitive Route Search, Cognitive Vehicle System, Route-Planning, Self-Driving, Sitting-Pressure Sensor, Traffic Congestion, Traffic Simulation","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"560 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127081809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Investigations on the Brain Connectivity Parameters for Co-Morbidities of Autism Using EEG 自闭症共病脑连接参数的脑电图研究
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-04-01 DOI: 10.4018/IJSSCI.2018040104
K. Priya, A. Kavitha
{"title":"Investigations on the Brain Connectivity Parameters for Co-Morbidities of Autism Using EEG","authors":"K. Priya, A. Kavitha","doi":"10.4018/IJSSCI.2018040104","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018040104","url":null,"abstract":"","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125420000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Discovering Attribute-Specific Features From Online Reviews: What Is the Gap Between Automated Tools and Human Cognition? 从在线评论中发现属性特定的特征:自动化工具和人类认知之间的差距是什么?
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2018-04-01 DOI: 10.4018/IJSSCI.2018040101
X. Jing, Penghao Wang, Julia M. Rayz
{"title":"Discovering Attribute-Specific Features From Online Reviews: What Is the Gap Between Automated Tools and Human Cognition?","authors":"X. Jing, Penghao Wang, Julia M. Rayz","doi":"10.4018/IJSSCI.2018040101","DOIUrl":"https://doi.org/10.4018/IJSSCI.2018040101","url":null,"abstract":"Thisarticledescribeshowonlinereviewsplayanimportantroleindatadrivendecisionmaking. Manyeffortshavebeeninvestedindeterminingtheoverallsentimentcarriedbythereviews.However, oftentimes,theoverallratingsofthereviewsdonotrepresentopinionstowardspecificattributes ofaproduct.Anidealopinionminingtoolshouldaimatfindingboththeproductattributesand theircorrespondingopinions.Theauthorsproposeanapproachforextractingtheattributespecific featuresfromonlinereviewsusingaWord2Vecmodelcombinedwithclustering.Twoexperiments aredescribed in thispaper: thefirst focuseson testing theperformanceof theWord2Vecmodel onextractingproductaspectwords,thesecondaddresseshowwelltheextractedfeaturesobtained arerecognizablebyhumancognition.Anewmetriccalledthe“splitvalue”thatisbasedoncluster similarityanddiversityisintroducedtoexaminetheconsistencyofclusteringalgorithm.Theauthors’ experimentssuggestthatmeaningfulclusters,whichprovideinsightstotheproductattributesand sentiments,couldbeextractedfromthereviews. KeyWORDS Artificial Intelligence, Clustering, Cognition, Feature Extraction, Opinion Mining, Text Understand, Word2Vec","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"35 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134450398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Human Identification Using Gait Skeletal Joint Distance Features 基于步态骨骼关节距离特征的人体识别
Int. J. Softw. Sci. Comput. Intell. Pub Date : 2017-10-01 DOI: 10.4018/IJSSCI.2017100102
Md Wasiur Rahman, M. Gavrilova
{"title":"Human Identification Using Gait Skeletal Joint Distance Features","authors":"Md Wasiur Rahman, M. Gavrilova","doi":"10.4018/IJSSCI.2017100102","DOIUrl":"https://doi.org/10.4018/IJSSCI.2017100102","url":null,"abstract":"Gaitnotonlydefinesthewayapersonwalks,butalsoprovidesinsightsonanindividual’sdaily routine,mentalstateorevencognitivefunction.Theimportanceofincorporatingcognitivebehavior andanalysisinbiometricsystemshasbeennotedrecently.Inthisarticle,authorsdevelopabiometric securitysystemusinggait-basedskeletalinformationobtainedfromMicrosoftKinectv1sensor.The gaitcycleiscalculatedbydetectingthethreeconsecutivelocalminimabetweenthejointdistance ofleftandrightankles.Authorshaveutilizedthedistancefeaturevectorforeachofthejointswith respecttootherjointsinthegaitcycle.Aftermeanandvariancefeaturesareextractedfromthedistance featurevector,theKNNalgorithmisusedforclassificationpurpose.Theclassificationaccuracyofthe authors’approachis93.33%.Experimentalresultsshowthattheproposedapproachachievesbetter recognitionaccuracythenotherstate-of-the-artapproaches.Incorporatinggaitbiometricinasituation awarenesssystemforidentificationofamentalstateisoneofthefuturedirectionsofthisresearch. KeywoRDS Biometric System, Cognitive Function, Feature Distance Vector, Gait, Gait Cycle, K Nearest Neighbors (KNN), Kinect Sensor, Pattern Recognition","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127675051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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