IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications最新文献_第10页

Development and assessment of Decentralized Energy Management System in a smart Microgrid 智能微电网分散式能源管理系统的开发与评估

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878746

F. Delfino, L. Barillari, F. Pampararo, M. Rossi, A. Zakariazadeh, P. Molfino, Andrea Podesta, A. Venturin, Nicoletta Robertelli

引用次数: 0

Stream correlation monitoring for uncertainty-aware data processing systems 不确定性感知数据处理系统的流相关监测

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878827

Aleka Seliniotaki, G. Tzagkarakis, V. Christophides, P. Tsakalides

{"title":"Stream correlation monitoring for uncertainty-aware data processing systems","authors":"Aleka Seliniotaki, G. Tzagkarakis, V. Christophides, P. Tsakalides","doi":"10.1109/IISA.2014.6878827","DOIUrl":"https://doi.org/10.1109/IISA.2014.6878827","url":null,"abstract":"In several industrial applications, monitoring large-scale infrastructures in order to provide notifications for abnormal behavior is of high significance. For this purpose, the deployment of large-scale sensor networks is the current trend. However, this results in handling vast amounts of low-level, and often unreliable, data, while an efficient and real-time data manipulation is a strong demand. In this paper, we propose an uncertainty-aware data management system capable of monitoring pairwise correlations of large sensor data streams in real-time. An efficient similarity function based on the truncated DFT is employed instead of the typical correlation coefficient to monitor dynamic phenomena for timely alerting notifications, and to guarantee the validity of detected extreme events. Experimental evaluation with a set of real data recorded by distinct sensors in an industrial water desalination plant reveals a high performance of our proposed approach in terms of achieving significantly reduced execution times, along with increased accuracy in detecting highly correlated pairs of sensor data streams.","PeriodicalId":298835,"journal":{"name":"IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122621077","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

A comparative study of one-class classifiers in machine learning problems with extreme class imbalance 一类分类器在极端类不平衡机器学习问题中的比较研究

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878723

Dionisios N. Sotiropoulos, Christos Giannoulis, G. Tsihrintzis

引用次数: 3

Android acoustic ranging 安卓声测距

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878721

Paul Curtis, M. Banavar, Sai Zhang, A. Spanias, V. Weber

引用次数: 17

An ICMetric based key generation scheme for controlled group communication 一种基于ICMetric的受控群通信密钥生成方案

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878816

Shahzaib Tahir, M. Afzal, M. Tahir

{"title":"An ICMetric based key generation scheme for controlled group communication","authors":"Shahzaib Tahir, M. Afzal, M. Tahir","doi":"10.1109/IISA.2014.6878816","DOIUrl":"https://doi.org/10.1109/IISA.2014.6878816","url":null,"abstract":"Secure group controlled communication refers to a dynamic environment that ensures secure collaboration among the participating group members. It is wrong to view group security as an aggravation of the simple one to one communication because the group is a dynamic environment composed of activities that are only exhibited by individuals in a group environment. Also as the number of hosts and clients increases the complexity of the communication security also increases. In this paper a security scheme is presented that allows group members to generate keys for group environment using the latest ICMetrics technology. The ICMetric technology is a breakthrough technology because it uses the unique features/attributes of a system to generate a number that can be used to identify the system uniquely. The proposed scheme in this paper uses the ICMetric technology for key generation and key distribution to provide secure communications in a group. To test the scalability properties of the scheme it has been simulated and a comparative study has been performed based on the running time of the algorithm.","PeriodicalId":298835,"journal":{"name":"IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123018839","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: 3

Ionian Music Archive: Application of digitization, management and dissemination technologies for musical cultural heritage 爱奥尼亚音乐档案:音乐文化遗产的数字化、管理和传播技术应用

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878753

D. Koukopoulos, D. Tsolis, G. Heliades

引用次数: 8

What drives social sentiment? An entropic measure-based clustering approach towards identifying factors that influence social sentiment polarity 是什么驱动着社会情绪?基于熵测度的聚类方法识别影响社会情感极性的因素

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878830

Dionisios N. Sotiropoulos, Chris D. Kounavis, Panos E. Kourouthanassis, G. Giaglis

{"title":"What drives social sentiment? An entropic measure-based clustering approach towards identifying factors that influence social sentiment polarity","authors":"Dionisios N. Sotiropoulos, Chris D. Kounavis, Panos E. Kourouthanassis, G. Giaglis","doi":"10.1109/IISA.2014.6878830","DOIUrl":"https://doi.org/10.1109/IISA.2014.6878830","url":null,"abstract":"Analyzing the public sentiment over social media streams constitutes an extremely demanding task mainly due to the difficulties that are imposed by the wide spectrum of discussion topics that underlie a given collection of posts. This paper addresses the problem of determining the underlying semantic factors that influence the social sentiment polarity in a given corpus of posts through the utilization of an entropic measure-based clustering approach. Extant studies examine the semantic structure of social network data primarily through topic modeling or sentiment analysis methods. The novelty of our approach lies upon the utilization of a semantically-aware clustering procedure that effectively combines topic modeling and sentiment analysis algorithms. Our approach extends the fundamental assumption behind traditional sentiment analysis methods, according to which sentiment can be associated with low level document features such as words, phrases or sentences. We argue that sentiment can be associated with higher level entities such as the semantic axes that span a given volume of posts, thus performing sentiment analysis at the topic level. Our experimentation provides strong evidence that combining topic modeling and sentiment analysis results by a semantically-aware clustering procedure can reveal the distribution of the overall public sentiment on the underlying semantic axes.","PeriodicalId":298835,"journal":{"name":"IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115210150","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: 7

Tourism sustainability methodologies: A critical assessment 旅游业可持续性方法论:一项关键评估

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878832

K. Glyptou, J. Paravantis, Andreas Papatheodorou, I. Spilanis

引用次数: 5

Optimizing Support Vector Machine in classifying sentiments on product brands from Twitter 支持向量机在Twitter产品品牌情感分类中的优化

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878768

Jao Allen Banados, K. Espinosa

{"title":"Optimizing Support Vector Machine in classifying sentiments on product brands from Twitter","authors":"Jao Allen Banados, K. Espinosa","doi":"10.1109/IISA.2014.6878768","DOIUrl":"https://doi.org/10.1109/IISA.2014.6878768","url":null,"abstract":"This paper involves giving a better solution in optimizing Support Vector Machine in classifying sentiments towards a product brand. Sentiment analysis rose to solve the problem of classifying sentiments and classifying as to positive or negative feedback towards a certain product brands. Using the Support Vector Machine learning algorithm, this study aims to improve the algorithm's accuracy through choice of kernel and proper tuning of SVM hyper-parameters as core factors in contributing to SVM accuracy, having a huge amount of training sets in order to widen the hyper plane of vectors and strong support vectors. The sentiments are gathered using the Twitter API and are pre-processed to filter unnecessary words. To be able to use the given tool, the pre-processed sentiments are converted to SVM format. By the given default parameters of the SVM tool used, with radial basis function as kernel type. The SVM type used is C-SVC, a multi-class classification. A training set is produced and is used as the training model for test sets and as of the initial results. The model produced an accuracy of 63.54% using SVM with the said default parameters and used 3768 tweets for training set.","PeriodicalId":298835,"journal":{"name":"IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126040986","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: 15

Evaluation of a mobile AAC application for Filipino language 菲律宾语的移动AAC应用程序的评估

IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications Pub Date : 2014-07-07 DOI: 10.1109/IISA.2014.6878789

Justin de los Reyes, Avery Nigel Rodriguez, Erwin Dennis Umali, M. R. Solamo, R. Feria

引用次数: 4