{"title":"Integrating linked sensor data for on-line analytical processing on-the-fly","authors":"Koly Guilavogui, L. Kjiri, M. Fredj","doi":"10.1109/CIST.2014.7016592","DOIUrl":"https://doi.org/10.1109/CIST.2014.7016592","url":null,"abstract":"Sensor networks are gaining more and more attention in the current technology landscape. It is undeniable that their use allows a better monitoring of events that occur in the real world. Many sensors have been deployed for monitoring applications such as environmental monitoring, and traffic monitoring. A number of governments, corporates, and academic organizations or agencies hold independently sensor systems that generate a large amount of dynamic information from data sources with various formats of schemas and data. They are making this sensor data openly accessible by publishing it as Linked Sensor Data (LSD) on the Linked Open Data (LOD) cloud. LSD is the concept that defines the publication of public or private organization sensor data without restrictions. This is achieved by transforming raw sensor observations to RDF format and by linking it with other datasets on the LOD cloud. The seamless integration of LSD sources from multiple providers is a great challenge. In this paper, we investigate the possibility of integrating diverse LSD sources using the hybrid ontology approach for on-line analytical processing (OLAP) on-the-fly. With such an ontology-based integration framework, organizations or individuals will have greater opportunity to make their respective analysis based on a large amount of sensor data openly accessible on the Web.","PeriodicalId":106483,"journal":{"name":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128818065","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}
{"title":"Performance analysis of routing protocols for wireless sensor networks","authors":"Yassine Maleh, Abdellah Ezzati","doi":"10.1109/CIST.2014.7016657","DOIUrl":"https://doi.org/10.1109/CIST.2014.7016657","url":null,"abstract":"Wireless Sensor Network (WSN) is consisting of independent and distributed sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. Routing protocols represent an essential aspect of the performance of mobile wireless networks. This paper presents a comparative analysis between several routing algorithms and their impact on the performance of WSN. The performance of routing protocols is evaluated by providing simulation results based on packet delivery ratio, end to end delay (EED), and throughput. Our simulation is performed in NS2 by varying total number of nodes in the first scenario and varying pause time in the second.","PeriodicalId":106483,"journal":{"name":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124307975","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}
O. Lachhab, J. D. Martino, E. I. Elhaj, A. Hammouch
{"title":"Improving the recognition of pathological voice using the discriminant HLDA transformation","authors":"O. Lachhab, J. D. Martino, E. I. Elhaj, A. Hammouch","doi":"10.1109/CIST.2014.7016648","DOIUrl":"https://doi.org/10.1109/CIST.2014.7016648","url":null,"abstract":"In this paper, we propose a simple and fast method for evaluating the pathological voice (esophageal) by applying the continuous speech recognition in a speaker dependent mode, on our own database of the pathological voice, we call FPSD (French Pathological Speech Database). The recognition system used is implemented using the HTK platform, based on HMM/GMM monophone models. The acoustic vectors are linearly transformed by the HLDA (Heteroscedastic Linear Discriminant Analysis) method to reduce their size in a smaller space with good discriminative properties. The obtained phone recognition rate (63.59 %) is very promising when we know that esophageal voice contains unnatural sounds, difficult to understand.","PeriodicalId":106483,"journal":{"name":"2014 Third IEEE International Colloquium in Information Science and Technology (CIST)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121693177","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}