{"title":"Channel selection strategy for Cognitive Radio using NS2","authors":"Vinaya.Y. Deshmukh, P. Varade, Y. Ravinder","doi":"10.1109/ICHCI-IEEE.2013.6887771","DOIUrl":"https://doi.org/10.1109/ICHCI-IEEE.2013.6887771","url":null,"abstract":"For Cognitive Radio network's (CRN's) channel selection plays a very crucial role in efficient and reliable data distribution. In the perspective of Cognitive Radio Network (CRN), channel selection is more difficult because the channel may be occupied by primary radio (PR) nodes. Furthermore, Cognitive Radio (CR) transmission must not degrade the reception quality of PR nodes and should instantaneously switch to other available band, each time a neighboring PR activity is detected. As a consequence, it is important and but tremendously difficult for CR nodes to properly select channel allowing reliable communication. This paper proposes a method which predicts future idle times of various channels based on the past sequence which allows a cognitive radio (CR) to select the best channels for data transmission. The simulation results using NS2 validates that intelligent channel selection improves the throughput and reduces channel switching as compared to random channel selection.","PeriodicalId":419263,"journal":{"name":"2013 International Conference on Human Computer Interactions (ICHCI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114789950","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":"Parametric modeling of EEG signals with real patient data for simulating seizures and pre-seizures","authors":"U. Qidwai, M. Shakir, A. Malik, N. Kamel","doi":"10.1109/ICHCI-IEEE.2013.6887810","DOIUrl":"https://doi.org/10.1109/ICHCI-IEEE.2013.6887810","url":null,"abstract":"Numerous theories and models have been developed to associate various findings or in relating EEG patterns to develop a software simulators. In this paper, a Dynamic model for simulating the EEG signal has been developed with empirical reference to real EEG signals from patients suffering from Seizure and Partial Seizure. Real EEG data set can be obtained in either .edf or .tdms or .txt formats from any clinical patient tests or database repository. The proposed model for the EEG signal has led to the development of a simulator which can be used to obtain any number of samples of data of a specific type (Normal, Pre-Seizure, and Seizure) and can be used by researchers for algorithmic testing. The presented simulator has a core of 22 patient's data with a variety of ages and gender selection options with possible connectivity to hardware based modules to generate the real EEG signal for external use as well. One can simulate, validate and test the detection algorithms beforehand, before actual clinical testing of the algorithms. Further, one can also develop pre-prediction algorithms for Seizure and pre-seizure states of a patient to take appropriate precautions just before the actual occurrence of the seizure. The model is based on the conventional ARX structure with subset frequencies from the real EEG signal used as excitation input. When plotted together, the resemblance between the original and simulated signals was very significant thus providing with a means to keep simulating with those frequencies to whatever length needed, with whatever variability in terms of amplitude and patient specific parameters.","PeriodicalId":419263,"journal":{"name":"2013 International Conference on Human Computer Interactions (ICHCI)","volume":"101 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116272635","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":"Weak eyesight therapy: A case study in designing an application for m-health systems","authors":"A. Saini, P. Yammiyavar","doi":"10.1109/ICHCI-IEEE.2013.6887804","DOIUrl":"https://doi.org/10.1109/ICHCI-IEEE.2013.6887804","url":null,"abstract":"Progressively emerging information and e-communication technologies hold immense potential for applications in the health care sector. Growth of personal healthcare requirements can only be met through use of mobile technologies in the future. A future wheredoctors e-prescribe mobile applications in place of medicines, monitor and control patients' health through remote supervision is envisioned through this design case. This paper discusses the design of an application that facilitates patient-doctor consultation, remotely, after the mandatory initial consultative physical checkup. A system of follow up healthcare to impart therapeutic supervision through use of m-health technologies has been proposed. Object Oriented System Design methodology is used as a framework to conceptualize the system components and attributes. This system is contextualized to the problem of weak eyesight due to work related stress or old age and a proof of concept tablet application has been designed to impart weak eyesight therapy. The design methodology followed incorporated user centered design tools like Persona and Scenario building and user participation through Card sorting technique. The application has been prototyped and tested for usability. The methodology of design and outcome is presented in this paper.","PeriodicalId":419263,"journal":{"name":"2013 International Conference on Human Computer Interactions (ICHCI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124979763","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}