{"title":"The Effects of Mobile Phone Usage on Human Brainwave Using EEG","authors":"Z. H. Murat, R. S. AbdulKadir, R. M. Isa, M. Taib","doi":"10.1109/UKSIM.2011.17","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.17","url":null,"abstract":"The aim of this research is to investigate any effects of mobile phone usage on human brainwaves using electroencephalograph (EEG) particularly on alpha wave. EEG signals were recorded from thirty samples that make calls from a mobile phone to another party without conversation. The mobile phone is strapped to the right ear. The EEG recording took place before, during and after the mobile phone calls. In addition, samples will be interviewed with questions related to the usage of hand phones prior to EEG recording. The brainwave signals were analyzed using statistical analysis. The EEG result shows that the alpha level of the right side decreases significantly during the calls and further decreases within the period of five minutes after the calls were ended. However, the alpha level of the left side remains consistent throughout the experiment. It follows that the correlation between the left and the right brainwaves signal decreases significantly during the calls and further decreases within the period of five minutes after calls. There is evidence that the usage of mobile phones affect the alpha brainwaves.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127983574","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}
K. Rezaie, A. Ansarinejad, A. Haeri, Amin Nazari Shirkouhi, S. N. Shirkouhi
{"title":"Evaluating the Business Intelligence Systems Performance Criteria Using Group Fuzzy AHP Approach","authors":"K. Rezaie, A. Ansarinejad, A. Haeri, Amin Nazari Shirkouhi, S. N. Shirkouhi","doi":"10.1109/UKSIM.2011.75","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.75","url":null,"abstract":"Organizations must make good use of information system tools such as business intelligence (BI) systems to quickly acquire desirable information from huge volume of data to reduce the time and increase the efficiency of decision-making procedure. Despite the huge operational and managerial advantages of BI systems, many companies face problems in the completely utilization of these tools, therefore, to reduce risk of failure in utilization and also to measure the amount of realized benefits of BI tool defining and choosing the most proper performance measurement criteria and technique is an important issue. In this paper a practical framework based on appropriate criteria and Fuzzy Analytical Hierarchy Process technique is presented to performance evaluation of BI Systems. Result shows that a \" Fitness\" criterion is the most important criteria in the performance evaluation of BI System.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122734731","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":"PeerSim: An Efficient & Scalable Testbed for Heterogeneous Cluster-based P2P Network Protocols","authors":"Irum Kazmi, Syed Fahim Yousaf Bukhari","doi":"10.1109/UKSIM.2011.86","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.86","url":null,"abstract":"This research work explains different aspects of Peer Sim simulator used to create nodes and simulate peer to peer overlay network topology generation protocols. PeerSimhas been tested over various protocols specifically designed to work with a heterogeneous environment and its efficiency and scalability is evaluated considering different properties of the nodes and network. These protocols are used to introduce clusters for efficient resource retrieval, behaviour of cooperation and security. PeerSim has proven to be a very efficient and scalable test bed for the generation of nodes through gossip based protocol and implementing different protocols on the nodes generated. The aim of this paper is to provide a detailed description and evaluation of PeerSimthrough study of already implemented protocols, for the researchers working in the field of P2P networking.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122786896","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":"Introduction of a New Optimization Mechanism for Electimize","authors":"M. Abdel-Raheem, A. Khalafallah","doi":"10.1109/UKSIM.2011.12","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.12","url":null,"abstract":"Electimize is a new evolutionary algorithm that simulates the phenomenon of the flow of electrons and electrical conductivity. Previous research proved Electimize to be very efficient in solving NP-hard optimization problems. The algorithm demonstrates higher capabilities in searching the solution space extensively, and identifying global optimal alternatives, if any. The basic advantage of Electimize over other evolutionary algorithms (EAs) lies in the evaluation process of the quality of the solution strings. Unlike other EAs, Electimize evaluates the quality of every value in the solution string independently. Recent research showed that Electimize is slow in converging towards the optimal solution, if the size of problem is increased. This paper presents a new mechanism for enhancing the performance of Electimize by introducing new parameters that would guide the algorithm towards the optimal values. The paper discusses the methodology of the work, the basic theory behind the newly introduced parameters, and the main steps of optimization.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"401 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115854486","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":"Modelling of High-Level Structures and Communications Associated with Thought Processes and Related Tasks","authors":"R. Zobel","doi":"10.1109/UKSIM.2011.29","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.29","url":null,"abstract":"Modelling and simulation of the organization structure, communications and functionality of the brains of living creatures has been of interest to philosophers, scientists, engineers and artists for centuries. The possibilities for large numbers of simple microprocessors to be programmed to operate in a way which mimics the human brain, raises the knotty problem of how to do parallel programming. This paper considers an alternative top-down approach involving high-level associative activities between an assembly of local areas of excellence with variable low-speed connectivity, as a possible model for improving the understanding of the concepts surrounding intelligence and learning, based on the authors' experience in science, engineering, live music and singing.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115676730","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":"A Kalman Filter Based Approach to De-noise the Stereo Vision Based Pedestrian Position Estimation","authors":"A. Sinharay, A. Pal, B. Bhowmick","doi":"10.1109/UKSIM.2011.30","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.30","url":null,"abstract":"This paper presents a methodology of using Kalman filter to minimize the error in stereo vision based distance measurement data (3D position of pedestrians). In stereo vision, little point mis-correspondence leads to a very bad estimate of depth during triangulation. There are robust correspondence algorithms but all of them suffer from algorithm complexity affecting the time performance. If simple correspondence algorithms are used that gave good real time performance, then the results suffer from erroneous depth measurement. In this paper, we have applied a predictive-corrective model using Kalman filter on the erroneous depth measurement. Being applied in time domain as compared to stereo image domain, the proposed approach has much less algorithm complexity and hence gives good real-time performance. The results also show that the proposed algorithm is able to significantly reduce the measurement noise without affecting the pedestrian tracking ability.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122651697","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}
N. Sulaiman, M. Taib, S. Lias, Z. H. Murat, S. A. M. Aris, N. Hamid
{"title":"EEG-based Stress Features Using Spectral Centroids Technique and k-Nearest Neighbor Classifier","authors":"N. Sulaiman, M. Taib, S. Lias, Z. H. Murat, S. A. M. Aris, N. Hamid","doi":"10.1109/UKSIM.2011.23","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.23","url":null,"abstract":"This paper presents the combination of electroencephalogram (EEG) power spectrum ratio and Spectral Centroids techniques to extract unique features for human stress from EEG signals. The combination of these techniques was able to improve the k-NN (k-Nearest Neighbor) clasifier accuracy to detect and classify human stress from two cognitive states, Close-eye (CE) and Open-eye (OE). The EEG power spectrum in term of Energy Spectral Density (ESD) for each frequency bands (Delta, Theta, Alpha and Beta) was calculated. The ratio of EEG power spectrum and the average value of Spectral Centroids were selected as features to k-Nearest Neighbor (k-NN). The training and testing of the classifier were evaluated at 50:50 ratios and 70:30 ratios. The results showed that the combination of EEG power spectrum and Spectral Centroids techniques with the training and testing of k-NN set at 70:30 able to detect and classify the unique features for human stress at 88.89% accuracy.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128622447","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":"Feature Extraction of EEG Signals and Classification Using FCM","authors":"S. A. M. Aris, M. Taib, S. Lias, N. Sulaiman","doi":"10.1109/UKSIM.2011.20","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.20","url":null,"abstract":"EEG data were collected between two conditions, relax wakefulness (close-eyes) and non-relax (IQ test). Data segmentation and linear regression model is used to extract the EEG features and to obtain the slope and the mean relative power from 43 participants. All of the data were then normalized and classified using Fuzzy C-Means (FCM) clustering. Results shown that there are different of activities exist in the EEG which proved that the feature extraction using linear regression model manage to discern between two different brain behaviors.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121353855","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":"Evaluating Mobility Impact on Wireless Sensor Network","authors":"S. F. Pileggi, C. Fernández-Llatas, T. Meneu","doi":"10.1109/UKSIM.2011.94","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.94","url":null,"abstract":"An increasing number of applications based on Wireless Sensor Networks assume mobile environments(Mobile WSNs). Mobile WSNs propose several converging issues with Mobile Ad-hoc Networks (MANETs) but the peculiarities of their technology and application domain advise a specific theoretical analysis of mobility impact on network connectivity. Network performance depends by several factors; there is a clear relationship between overall performance and the efficiency of network mechanisms (e.g. topology control and routing) that are directly affected by network connectivity. The paper first proposes an evaluation of randomly deployed clustered WSNs in function of network size/density, topology and communication range. Then, the mobility impact on network connectivity is analyzed and evaluated extending the analysis to overlay configuration. This evaluation has an implicit relationship with mobile behaviors. In order to provide extended analysis capabilities, an analytic model for mobile behaviors is also proposed. All reported results were obtained through simulations according to a general approach, independent from routing protocols or any other domain specific mechanisms as well as by environmental conditions.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115970625","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":"Automatic and Robust Detection of Facial Features in Frontal Face Images","authors":"A. Majumder, L. Behera, K. Venkatesh","doi":"10.1109/UKSIM.2011.69","DOIUrl":"https://doi.org/10.1109/UKSIM.2011.69","url":null,"abstract":"Automatic detection of facial features in an image is important stage for various facial image interpretation work, such as face recognition, facial expression recognition, 3Dface modeling and facial features tracking. Detection of facial features like eye, pupil, mouth, nose, nostrils, lip corners, eye corners etc., with different facial expression and illumination is a challenging task. In this paper, we presented different methods for fully automatic detection of facial features. Viola-Jones' object detector along with haar-like cascaded features are used to detect face, eyes and nose. Novel techniques using the basic concepts of facial geometry, are proposed to locate the mouth position, nose position and eyes position. The estimation of detection region for features like eye, nose and mouth enhanced the detection accuracy significantly. An algorithm, using the H-plane of the HSV color space is proposed for detecting eye pupil from the eye detected region. FEI database of frontal face images is mainly used to test the algorithm. Proposed algorithm is tested over 100 frontal face images with two different facial expression (neutral face and smiling face). The results obtained are found to be 100% accurate for lip, lip corners, nose and nostrils detection. The eye corners, and eye pupil detection is giving approximately 95% accurate results.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133557618","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}