2014 IEEE 5th International Conference on Software Engineering and Service Science最新文献_第5页

A Kinect-based rehabilitation exercise monitoring and guidance system 基于kinect的康复运动监测与指导系统

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933678

Wenbing Zhao, Hai Feng, Roanna Lun, D. Espy, M. A. Reinthal

引用次数: 73

EEG-based emotion recognition using wavelet features 基于脑电图的小波特征情感识别

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933636

Zhengjie Zhou, Huiping Jiang, Xiaoyuan Song

引用次数: 8

Image clusters based 3D virtual tour schema 基于图像聚类的三维虚拟漫游模式

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933650

Dan Zhang, Rui Zheng, Guosheng Yang

引用次数: 1

The method of using hypernetworks and concept lattice to solve domain concepts' semantic inconsistencies 利用超网络和概念格解决领域概念语义不一致的方法

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933702

Fenghua Hu, Xiaogang Qiu, Lei Luo

{"title":"The method of using hypernetworks and concept lattice to solve domain concepts' semantic inconsistencies","authors":"Fenghua Hu, Xiaogang Qiu, Lei Luo","doi":"10.1109/ICSESS.2014.6933702","DOIUrl":"https://doi.org/10.1109/ICSESS.2014.6933702","url":null,"abstract":"There are many semantic inconsistencies between domain concepts, which made it difficult to model, to interoperate and also to compose models semantically in software engineering, M&S (modeling and simulation) or semantic web. Thus we described the domain concepts and concepts taxonomy by hypernetwork (concept hypergraph), whose nodes set is the concepts set and edge is consisted of the correlative properties. Firstly, we have found out that the nodes set of concept hypergraph has the feature of order. In addition, by the definition of formal context, we have proved that the concept set is a complete concept lattice. And then, the domain knowledge has been extended from both of aspects of concept's extent and intent simultaneously, while the hypernetwork system has also been expanded according to the extended concept set. Finally, to achieve the semantically consistent taxonomy of the domain concepts through the hypernetwork system's adjacency and path matrices sequentially, we illustrated the example of the semantic inconsistencies of the military domain artillery concept's taxonomy and have given the method and steps perfectly.","PeriodicalId":6473,"journal":{"name":"2014 IEEE 5th International Conference on Software Engineering and Service Science","volume":"94 1","pages":"863-867"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80703623","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

Feature selection using feature ranking, correlation analysis and chaotic binary particle swarm optimization 基于特征排序、关联分析和混沌二元粒子群优化的特征选择

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933569

Fei Wang, Yi Yang, Xianchao Lv, Jiao Xu, Lian Li

{"title":"Feature selection using feature ranking, correlation analysis and chaotic binary particle swarm optimization","authors":"Fei Wang, Yi Yang, Xianchao Lv, Jiao Xu, Lian Li","doi":"10.1109/ICSESS.2014.6933569","DOIUrl":"https://doi.org/10.1109/ICSESS.2014.6933569","url":null,"abstract":"In this paper, we propose a multi-stage feature selection algorithm, which focuses on the reduction of redundant features and the improvement of classification performance using feature ranking (FR), correlation analysis (CA) and chaotic binary particle swarm optimization (CBPSO). In the first stage, with the purpose of selecting the most effective features for classification, FR is introduced to select the top-ranked features according to the classification accuracies. In the second stage, CA is used to measure the correlation among the selected top-ranked features for reducing redundant features. In the third stage, in order to further eliminate redundant features and improve the classification performances, CBPSO is adopted to search the optimal feature subset. Ultimately, feature selection can be completed by using only some top-ranked features with less redundancy for classification. Support vector machine (SVM) with n-fold cross-validation is adopted to assess the classification performances on six datasets in the experiments. Experimental results show that the proposed algorithm can achieve better performance in terms of classification accuracy and the number of features than benchmark algorithms.","PeriodicalId":6473,"journal":{"name":"2014 IEEE 5th International Conference on Software Engineering and Service Science","volume":"50 1","pages":"305-309"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80743497","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

Big data technologies in support of real time capturing and understanding of electric vehicle customers dynamics 大数据技术支持实时捕捉和理解电动汽车客户动态

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933559

R. Qiu, K. Wang, Shan Li, Jin Dong, Ming Xie

{"title":"Big data technologies in support of real time capturing and understanding of electric vehicle customers dynamics","authors":"R. Qiu, K. Wang, Shan Li, Jin Dong, Ming Xie","doi":"10.1109/ICSESS.2014.6933559","DOIUrl":"https://doi.org/10.1109/ICSESS.2014.6933559","url":null,"abstract":"Energy overconsumption and greenhouse gas emission have been contributing to air pollutions and the global warming for years. The unceasingly increasing number of fossil fuels based vehicles around the world is considered as one of main factors making to the situation worse year by year. Electric vehicles (EV) are promoted as a viable and promising alternative transportation means for customers. However, there is an array of issues hindering EVs from the fast adoption in the global auto market. As these issues bear different priorities that surely vary with marketplaces, it becomes essential for EV makers and governments to capture and understand the dynamics of EV consumers in real time. This paper explores how the emerging big data technologies can be applied to facilitate the process of deciphering the acceptance and behavior of EV customers from marketplace to marketplace. A data-collecting web system is discussed. IBM BigInsights platform technologies, including Hadoop, Streams, SPSS modeler and text analytics, are utilized for looking into the insights of collected data. Examples are provided to show the promising future of big data technologies in the field of customer analytics in today's globalized economy.","PeriodicalId":6473,"journal":{"name":"2014 IEEE 5th International Conference on Software Engineering and Service Science","volume":"36 1","pages":"263-267"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83122552","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: 18

A novel software for harmonic analysis and harmonic source location 一种新的谐波分析和谐波源定位软件

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933525

T. Zang, Yuan Yang, Zhengyou He, Q. Qian

引用次数: 5

PCTL∗ stochastic model checking label-extended probabilistic Petri net system model PCTL *随机模型检验标记-扩展概率Petri网系统模型

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933565

Yang Liu

引用次数: 1

A method of virtual machine placement based on gray correlation degree 一种基于灰色关联度的虚拟机布局方法

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933596

Li He

引用次数: 3

Research on optimization of application model based on storm 基于风暴的应用模型优化研究

2014 IEEE 5th International Conference on Software Engineering and Service Science Pub Date : 2014-06-27 DOI: 10.1109/ICSESS.2014.6933555

Lin Zhao, Weifeng Shi

引用次数: 0