The brain-computer interface (BCI) aim to use Electroencephalography (EEG) or other measures of brain functions can be implemented for communication with smart devices for disabled persons. For connection with different smart devices was used recorded with experimental setup electrophysiological signals for execution of five different mental tasks. The recorded brain signals were processed for their transformation into commands to different devices. This signal processing aims to extract some specific features of brain signals and transform them into algorithms for connection with smart devices. Processed signals after noise filtering, clustering and classification with Bayesian Network classifier and pair-wise classifier was estimated and put into brain-computer interface for connection with smart devices. Recent advances in emotion recognition use a combination of two intrapersonal modalities face and EEG to estimate emotion. In this research is made an attempt to combine received results on the base of record electrophysiological signals at execution of five different mental tasks with estimation of human emotion. This will help to provide a framework for reliable EEG emotional state estimation combined with facial emotion analysis in developed task-oriented BCI.
{"title":"BRAIN - COMPUTER INTERFACE FOR COMMUNICATION AND ESTIMATION OF HUMAN EMOTION FROM EEG AND VIDEO","authors":"S. Radeva, D. Radev","doi":"10.17781/P002028","DOIUrl":"https://doi.org/10.17781/P002028","url":null,"abstract":"The brain-computer interface (BCI) aim to use Electroencephalography (EEG) or other measures of brain functions can be implemented for communication with smart devices for disabled persons. For connection with different smart devices was used recorded with experimental setup electrophysiological signals for execution of five different mental tasks. The recorded brain signals were processed for their transformation into commands to different devices. This signal processing aims to extract some specific features of brain signals and transform them into algorithms for connection with smart devices. Processed signals after noise filtering, clustering and classification with Bayesian Network classifier and pair-wise classifier was estimated and put into brain-computer interface for connection with smart devices. Recent advances in emotion recognition use a combination of two intrapersonal modalities face and EEG to estimate emotion. In this research is made an attempt to combine received results on the base of record electrophysiological signals at execution of five different mental tasks with estimation of human emotion. This will help to provide a framework for reliable EEG emotional state estimation combined with facial emotion analysis in developed task-oriented BCI.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133670502","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":"GPU-BASED OBJECT IDENTIFICATION IN LARGE-SCALE IMAGES FOR REAL-TIME RADAR SIGNAL ANALYSIS","authors":"I. Shioya, Takahiro Yamamoto","doi":"10.17781/P002225","DOIUrl":"https://doi.org/10.17781/P002225","url":null,"abstract":"","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"22 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134386954","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}
Idris Zakariyya, Mohd Nazri Ismail M Nordin A Rahman
Congestion control and internet network resources management are complex and critical issues in a high-speed packet switch data network, due to the emergence growth of modern multimedia streaming services. The increasing number of computer users in various organizations and institutions of higher learning have spurred a great deal of research on network traffic control. Network administrators are facing the challenges of providing efficient services that can satisfy user requirements. This research study proposed queuing algorithm based on classbased weighted fair queue scheme to complement congestion. Network simulation environment are designed and modeled using OPNET simulation software in-order to overcome the limitation of the traditional queuing approach. Various simulations scenarios are conducted. Analysis comparison with first-in-first-out and priority queue is recorded. And also, various network traffics such as: HTTP, video conferencing and voice applications among others are considered. From the graphical results obtained clearly shows that the overall applications services performances optimize significantly. In terms of the throughput, packet loss and queuing delay, the algorithms performs excellently compared with the FIFO and priority queue. This paper examines the implication of queuing scheduling algorithms on an IP router. It also outlines the effectiveness of the proposed algorithm in managing network resources during the period of congestion.
{"title":"MODELLING THE PERFORMANCE OF CLASS-BASED WEIGHTED FAIR QUEUE USING OPNET","authors":"Idris Zakariyya, Mohd Nazri Ismail M Nordin A Rahman","doi":"10.17781/p001709","DOIUrl":"https://doi.org/10.17781/p001709","url":null,"abstract":"Congestion control and internet network resources management are complex and critical issues in a high-speed packet switch data network, due to the emergence growth of modern multimedia streaming services. The increasing number of computer users in various organizations and institutions of higher learning have spurred a great deal of research on network traffic control. Network administrators are facing the challenges of providing efficient services that can satisfy user requirements. This research study proposed queuing algorithm based on classbased weighted fair queue scheme to complement congestion. Network simulation environment are designed and modeled using OPNET simulation software in-order to overcome the limitation of the traditional queuing approach. Various simulations scenarios are conducted. Analysis comparison with first-in-first-out and priority queue is recorded. And also, various network traffics such as: HTTP, video conferencing and voice applications among others are considered. From the graphical results obtained clearly shows that the overall applications services performances optimize significantly. In terms of the throughput, packet loss and queuing delay, the algorithms performs excellently compared with the FIFO and priority queue. This paper examines the implication of queuing scheduling algorithms on an IP router. It also outlines the effectiveness of the proposed algorithm in managing network resources during the period of congestion.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133228567","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}
Image processing is a computational operation that requires many CPU cycles for simple image transformation. It takes every pixel of an image to perform a transformation to a new image. The image can be divided into smaller chunks, with same transformation operations being implemented on each. Thus, image processing is a good candidate for running on a parallel processor to improve the speed of computation when there are multiple images to be processed. In fact, this research focuses on Canny edge detection as a case study of probing parallelism. This work presents the design and implementation of sequential and parallel edge detection algorithms that are capable of producing high-quality results and performing at high speed. Therefore, this research aims to improve the Canny edge detection algorithm in terms of speed and scalability with different sizes of images. The algorithm is implemented using parallel clusters on KACST’s SANAM supercomputer. It is found that there is a valuable gained speedup with respect to the sequential version.In addition, it is found that more parallelism is explored in larger image sizes with Canny edge detector.
{"title":"Acceleration of Canny Edge Detection Algorithm Using Parallel Clusters","authors":"Njood S. Alassmi, S. S. Zaghloul","doi":"10.17781/P002370","DOIUrl":"https://doi.org/10.17781/P002370","url":null,"abstract":"Image processing is a computational operation that requires many CPU cycles for simple image transformation. It takes every pixel of an image to perform a transformation to a new image. The image can be divided into smaller chunks, with same transformation operations being implemented on each. Thus, image processing is a good candidate for running on a parallel processor to improve the speed of computation when there are multiple images to be processed. In fact, this research focuses on Canny edge detection as a case study of probing parallelism. This work presents the design and implementation of sequential and parallel edge detection algorithms that are capable of producing high-quality results and performing at high speed. Therefore, this research aims to improve the Canny edge detection algorithm in terms of speed and scalability with different sizes of images. The algorithm is implemented using parallel clusters on KACST’s SANAM supercomputer. It is found that there is a valuable gained speedup with respect to the sequential version.In addition, it is found that more parallelism is explored in larger image sizes with Canny edge detector.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132961408","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}
Software testing is one of the important steps of SDLC. In software testing one of the important issues is how to allocate the limited resources so that we finish our testing on time and will deliver quality software. Number of Software Reliability Growth Models (SRGM) has been developed for allocating the testing resource in the past three decades but majority of models are developed in static environment. In this paper we developed model in a dynamic environment and also the software is divided into different modules. We also used Pontryagin Maximum principle for solving the model. At last one numerical example is solved for allocating the resource for a given module. For allocating resource optimally we used Genetic Algorithm (GA). GA is used as a powerful tool for solving search & optimization kind of problems.
{"title":"TESTING RESOURCE ALLOCATION FOR MODULAR SOFTWARE USING GENETIC ALGORITHM","authors":"M. Nasar, P. Johri","doi":"10.17781/p001647","DOIUrl":"https://doi.org/10.17781/p001647","url":null,"abstract":"Software testing is one of the important steps of SDLC. In software testing one of the important issues is how to allocate the limited resources so that we finish our testing on time and will deliver quality software. Number of Software Reliability Growth Models (SRGM) has been developed for allocating the testing resource in the past three decades but majority of models are developed in static environment. In this paper we developed model in a dynamic environment and also the software is divided into different modules. We also used Pontryagin Maximum principle for solving the model. At last one numerical example is solved for allocating the resource for a given module. For allocating resource optimally we used Genetic Algorithm (GA). GA is used as a powerful tool for solving search & optimization kind of problems.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122435205","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}
In the domain of Human Computer Interaction (HCI), the communication between humans and software is an ongoing challenge. On the one hand, humans have growing needs and expectations. On the other hand, software has more advanced features and functionalities. This dual complexity growth results in difficulty in interaction. User interface is the battleground where sophisticated cognitive demands need to be resolved between the user and the software for effective communication. When interaction involves big data retrieval, communication often takes the form of software displaying data, and users comprehending their meaning, then requesting more date, or requesting some processing to be applied on
{"title":"APPLICATION-AGNOSTIC INTERACTIVE DATA: MANAGING HCI COMPLEXITY AT THE SOURCE","authors":"A. Gaffar","doi":"10.17781/P001","DOIUrl":"https://doi.org/10.17781/P001","url":null,"abstract":"In the domain of Human Computer Interaction (HCI), the communication between humans and software is an ongoing challenge. On the one hand, humans have growing needs and expectations. On the other hand, software has more advanced features and functionalities. This dual complexity growth results in difficulty in interaction. User interface is the battleground where sophisticated cognitive demands need to be resolved between the user and the software for effective communication. When interaction involves big data retrieval, communication often takes the form of software displaying data, and users comprehending their meaning, then requesting more date, or requesting some processing to be applied on","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127762097","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}
Image processing is a computational operation that requires many CPU cycles for simple image transformation. It takes every pixel of an image to perform a transformation to a new image. The image can be divided into smaller chunks, with same transformation operations being implemented on each. Thus, image processing is a good candidate for running on a parallel processor to improve the speed of computation when there are multiple images to be processed. In fact, this research focuses on Canny edge detection as a case study of probing parallelism. This work presents the design and implementation of sequential and parallel edge detection algorithms that are capable of producing high-quality results and performing at high speed. Therefore, this research aims to improve the Canny edge detection algorithm in terms of speed and scalability with different sizes of images. The algorithm is implemented using Java language with the Parallel Java library. In the first phase of the project, the Canny is implemented on a sharedmemory processor. It is found that there is a valuable gained speedup with respect to the sequential version. In addition, it is found that more parallelism is explored in larger image sizes with Canny edge detector.
{"title":"Speeding Up Canny Edge Detection Using Shared Memory Processing","authors":"S. S. Zaghloul, Njood S. Alassmi","doi":"10.17781/P002313","DOIUrl":"https://doi.org/10.17781/P002313","url":null,"abstract":"Image processing is a computational operation that requires many CPU cycles for simple image transformation. It takes every pixel of an image to perform a transformation to a new image. The image can be divided into smaller chunks, with same transformation operations being implemented on each. Thus, image processing is a good candidate for running on a parallel processor to improve the speed of computation when there are multiple images to be processed. In fact, this research focuses on Canny edge detection as a case study of probing parallelism. This work presents the design and implementation of sequential and parallel edge detection algorithms that are capable of producing high-quality results and performing at high speed. Therefore, this research aims to improve the Canny edge detection algorithm in terms of speed and scalability with different sizes of images. The algorithm is implemented using Java language with the Parallel Java library. In the first phase of the project, the Canny is implemented on a sharedmemory processor. It is found that there is a valuable gained speedup with respect to the sequential version. In addition, it is found that more parallelism is explored in larger image sizes with Canny edge detector.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127599260","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":"Forecasting of HOSR for Different Mobile Carriers in Kano Using Conventional and Intelligent Techniques","authors":"S. B. Abdullahi","doi":"10.17781/p002599","DOIUrl":"https://doi.org/10.17781/p002599","url":null,"abstract":"","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"391 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124781028","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}
Monitoring and control of soil parameters such as temperature, moisture and micronutrients play an important role in producing quality horticulture crops. The farms at Pwani Region needed close monitoring and control of soil parameters because the type of soil in this place is alluvial which can drain water and loose macronutrients easily. Recently Wireless Sensor Network (WSN) has been used to monitors soil parameters, however many systems developed from existing frameworks were unable to meet requirements for small and medium scale horticulture farmers. This paper addresses the challenges mentioned above and provides solution that fits the left gap by improving previous frameworks. The gap was identified after comparing different WSN related technologies and requirements obtained from experts and farmers. The framework designed from this information was used to develop WSN system which can be easily used by farmers of different levels of education.
{"title":"A FRAMEWORK FOR DEPLOYMENT OF EASY TO USE WIRELESS SENSOR NETWORKS FOR FARM SOIL MONITORING AND CONTROL: A CASE STUDY OF HORTICULTURE FARMS IN PWANI REGION TANZANIA","authors":"Kosmas Kapis, Mathias Ombeni","doi":"10.17781/p001927","DOIUrl":"https://doi.org/10.17781/p001927","url":null,"abstract":"Monitoring and control of soil parameters such as temperature, moisture and micronutrients play an important role in producing quality horticulture crops. The farms at Pwani Region needed close monitoring and control of soil parameters because the type of soil in this place is alluvial which can drain water and loose macronutrients easily. Recently Wireless Sensor Network (WSN) has been used to monitors soil parameters, however many systems developed from existing frameworks were unable to meet requirements for small and medium scale horticulture farmers. This paper addresses the challenges mentioned above and provides solution that fits the left gap by improving previous frameworks. The gap was identified after comparing different WSN related technologies and requirements obtained from experts and farmers. The framework designed from this information was used to develop WSN system which can be easily used by farmers of different levels of education.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123560443","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}
Robots that works in a dynamic environment must possess, the ability to autonomously cope with the changes in the environment. This paper proposes an approach to predict changes in the state and actions of robots. Further, this approach attempts to apply predicted future actions to current actions. This method predicts the robot’s state and action for the distant future using the states that the robot adopts repeatedly. Using this method, the actions that the robot will take in the future can be predicted. The method proposed in this paper predicts the state and action of a robot each time it decides to perform an action. In particular, this paper focuses on defining weight coefficients, using the characteristics of the future prediction results. Using this method, the compensatory current action will be obtained. This paper presents the results of our study and discusses methods that allow the robot to quickly determine its most desirable action, using state prediction and optimal control methods.
{"title":"FUTURE MOTION DECISIONS USING STATE-ACTION PAIR PREDICTIONS","authors":"Masashi Sugimoto, K. Kurashige","doi":"10.17781/p001896","DOIUrl":"https://doi.org/10.17781/p001896","url":null,"abstract":"Robots that works in a dynamic environment must possess, the ability to autonomously cope with the changes in the environment. This paper proposes an approach to predict changes in the state and actions of robots. Further, this approach attempts to apply predicted future actions to current actions. This method predicts the robot’s state and action for the distant future using the states that the robot adopts repeatedly. Using this method, the actions that the robot will take in the future can be predicted. The method proposed in this paper predicts the state and action of a robot each time it decides to perform an action. In particular, this paper focuses on defining weight coefficients, using the characteristics of the future prediction results. Using this method, the compensatory current action will be obtained. This paper presents the results of our study and discusses methods that allow the robot to quickly determine its most desirable action, using state prediction and optimal control methods.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"548 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134350201","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}
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