{"title":"Impact of filtering chaotic signals on secure wireless communication systems based Chua's circuit","authors":"W. Al-Hussaibi","doi":"10.1109/INNOVATIONS.2013.6544399","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2013.6544399","url":null,"abstract":"One of the challenging issues involved in the development of future chaos-based secure communication (CBSC) for wireless applications is the synchronization between transmit and receive nodes. In this paper, effects of filtering chaotic signals of CBSC due to finite bandwidth of realistic channel environment and/or detection requirements on the synchronization are investigated. The double scroll chaotic attractor using Chua's circuit is employed at the transmit and receive nodes. Over wide range of filter cut-off frequency (η), simulation results show that as η decreased, below the bandwidth of chaotic signal (W), the synchronization error is increased due to high distortion in the normal geometrical configuration (state-space) of the attractor. Consequently, the system performance will be degraded significantly with high possibility of communication link failure. Thus, careful design should be made to eliminate the impact of filtering and achieve the essential synchronization towards the wide adoption of CBSC in next-generation systems.","PeriodicalId":438270,"journal":{"name":"2013 9th International Conference on Innovations in Information Technology (IIT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134081594","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":"Efficient implementation of Itoh's algorithm in 3D shape measurement using digital fringe projection technique","authors":"M. Ashfaq, N. Minallah, K. Yahya, I. Din, A. Ali","doi":"10.1109/INNOVATIONS.2013.6544415","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2013.6544415","url":null,"abstract":"Phase unwrapping is one of the challenging tasks in 3D shape measurement. Phase unwrapping is the computational intensive process which involves adding or subtracting multiples of 2π. In this paper the basic implementation of Itoh's algorithm[1] is shown which involves a lot of computations and unnecessary iterations to solve the phase unwrapping problem. To reduce the number of computations and iterations we have derived another implementation for Itoh's algorithm. In this implementation computational complexity has been reduced and is directly proportional to the number of pixels traversed.","PeriodicalId":438270,"journal":{"name":"2013 9th International Conference on Innovations in Information Technology (IIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122892404","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":"Predicting hypoglycemia in diabetic patients using data mining techniques","authors":"Khouloud Safi Eljil, G. Qadah, Michel Pasquier","doi":"10.1109/INNOVATIONS.2013.6544406","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2013.6544406","url":null,"abstract":"The proper control of blood glucose levels in diabetic patients reduces serious complications. Yet tighter glycemic control increases the risk of developing hypoglycemia, a sudden drop in patients' blood glucose levels that causes coma and possibly death if proper action is not taken immediately. In this paper, we propose a hypoglycemia prediction model, using recent history of subcutaneous glucose measurements collected via Continuous Glucose Monitoring (CGM) sensors. The model is able to predict hypoglycemia events within a prediction horizon of thirty minutes accurately (sensitivity= 86.47%, specificity= 96.22, accuracy= 95.97%) using only the last two glucose measurements and the difference between them. More remarkably, this study shows the ability to develop a generalized prediction model suitable for predicting hypoglycemia events for the group of patients participating in the study.","PeriodicalId":438270,"journal":{"name":"2013 9th International Conference on Innovations in Information Technology (IIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122028492","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}