Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293364
Saleha Khatun, Ruhi Mahajan, B. Morshed
For biomedical and scientific fields, Electroencephalography (EEG) has turned out to be an important tool to understand, study, and utilize brain functionalities. To fully utilize EEG signals in real-life closed-loop applications, artifacts such as ocular must be removed. Wavelet transform is one of the powerful methods to remove ocular artifacts from single channel EEG devices. In this study, both stationary and discrete wavelet transforms (SWT and DWT, respectively) have been compared with various wavelet basis functions, such as sym3, haar, coif3, and bior4.4 using either universal threshold (UT) or statistical threshold (ST). Different combinations of wavelet transform techniques, mother wavelets, and thresholds are compared to identify an optimum combination for ocular artifact removal. Performance metrics like Correlation Coefficient (CC), Normalized Mean Square Error (NMSE), Time Frequency Analysis, and execution time have been calculated for measuring the effectiveness of each combination. According to CC, DWT+UT combination turned out to be a good option for the ocular artifact removal. However, according to NMSE and time frequency analysis, SWT+ST has generated better performance in keeping neural segments of EEG unaffected. According to the measurement of execution times, DWT+ST is faster compared to other combinations. The study shows that wavelet transform is suitable in artifact removal from single channel EEG data to implement in ambulatory real-time EEG systems.
{"title":"Comparative analysis of wavelet based approaches for reliable removal of ocular artifacts from single channel EEG","authors":"Saleha Khatun, Ruhi Mahajan, B. Morshed","doi":"10.1109/EIT.2015.7293364","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293364","url":null,"abstract":"For biomedical and scientific fields, Electroencephalography (EEG) has turned out to be an important tool to understand, study, and utilize brain functionalities. To fully utilize EEG signals in real-life closed-loop applications, artifacts such as ocular must be removed. Wavelet transform is one of the powerful methods to remove ocular artifacts from single channel EEG devices. In this study, both stationary and discrete wavelet transforms (SWT and DWT, respectively) have been compared with various wavelet basis functions, such as sym3, haar, coif3, and bior4.4 using either universal threshold (UT) or statistical threshold (ST). Different combinations of wavelet transform techniques, mother wavelets, and thresholds are compared to identify an optimum combination for ocular artifact removal. Performance metrics like Correlation Coefficient (CC), Normalized Mean Square Error (NMSE), Time Frequency Analysis, and execution time have been calculated for measuring the effectiveness of each combination. According to CC, DWT+UT combination turned out to be a good option for the ocular artifact removal. However, according to NMSE and time frequency analysis, SWT+ST has generated better performance in keeping neural segments of EEG unaffected. According to the measurement of execution times, DWT+ST is faster compared to other combinations. The study shows that wavelet transform is suitable in artifact removal from single channel EEG data to implement in ambulatory real-time EEG systems.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127567475","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293436
E. Hohenberger, Vivian Zeng, Zhili Xiao, V. Korampally
We present our preliminary efforts on the evaluation of novel nanoporous organosilicate thin films as supports to drive the formation of Pd nanostructures for application as Pd based resistive sensors. Nanoporous organosilicate thin films are a recently developed technology offering great versatility in being able to fine tune their three dimensional nanostructure degree of porosity pore sizes and thicknesses. The underlying surface texture is then utilized to direct the formation of high surface area Pd nanoclusters by depositing Pd upon these films at different thicknesses (In this study - 5 nm and 10 nm). These samples where then configured to be used as resistance based hydrogen sensors. The response of the various samples to exposure to 1% hydrogen were studied and discussed. Pd films deposited upon nanoporous films exhibited improved sensor characteristics and interesting contrasting behavior when compared to Pd thin films of the same thickness deposited upon flat control substrates.
{"title":"Evaluation of nanoporous organosilicate films as supports for Pd based hydrogen sensing","authors":"E. Hohenberger, Vivian Zeng, Zhili Xiao, V. Korampally","doi":"10.1109/EIT.2015.7293436","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293436","url":null,"abstract":"We present our preliminary efforts on the evaluation of novel nanoporous organosilicate thin films as supports to drive the formation of Pd nanostructures for application as Pd based resistive sensors. Nanoporous organosilicate thin films are a recently developed technology offering great versatility in being able to fine tune their three dimensional nanostructure degree of porosity pore sizes and thicknesses. The underlying surface texture is then utilized to direct the formation of high surface area Pd nanoclusters by depositing Pd upon these films at different thicknesses (In this study - 5 nm and 10 nm). These samples where then configured to be used as resistance based hydrogen sensors. The response of the various samples to exposure to 1% hydrogen were studied and discussed. Pd films deposited upon nanoporous films exhibited improved sensor characteristics and interesting contrasting behavior when compared to Pd thin films of the same thickness deposited upon flat control substrates.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115430657","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293431
Mohammad Khanjary, M. Sabaei, M. Meybodi
In many applications of percolation theory, checking the establishment of the spanning clump/cluster of overlapping particles that spans all over the field is an essential task. Given a percolation theory field modeled by two-dimensional lattice (matrix), in this paper, we present an algorithm which determines if there is a spanning clump in lattice or not. The spanning clump is the largest cluster in the field which that spans the entire network vertically, horizontally or both. Due to wide range of properties and applications of cellular automata such as simplicity and distributedness, we use them in our algorithm. The proposed algorithm is simple but yet useful and also could be run in a parallel / multicore machines. Also, the approach of the algorithm could be extended to higher dimensions.
{"title":"A percolation algorithm based on cellular automata","authors":"Mohammad Khanjary, M. Sabaei, M. Meybodi","doi":"10.1109/EIT.2015.7293431","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293431","url":null,"abstract":"In many applications of percolation theory, checking the establishment of the spanning clump/cluster of overlapping particles that spans all over the field is an essential task. Given a percolation theory field modeled by two-dimensional lattice (matrix), in this paper, we present an algorithm which determines if there is a spanning clump in lattice or not. The spanning clump is the largest cluster in the field which that spans the entire network vertically, horizontally or both. Due to wide range of properties and applications of cellular automata such as simplicity and distributedness, we use them in our algorithm. The proposed algorithm is simple but yet useful and also could be run in a parallel / multicore machines. Also, the approach of the algorithm could be extended to higher dimensions.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130842474","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293435
Renu Sharma
In this paper, the author represents energy efficient data compression application based on LTC (Lightweight Temporal Compression) algorithm in wireless sensor networks (WSNs). WSNs are essentially constrained by motes' limited battery power and networks bandwidth. The author focuses on data compression algorithm which effectively supports data compression for data gathering in WSNs. Data reduction before transmission such as by compression will significantly decrease the resource usage. Therefore, the main idea of this paper is to show how a data compression application such as collection tree protocol (CTP) is used for data collection from different sensor nodes into the root node in order to increase the network lifetime. LTC algorithm is used to minimize the amount of error in each reading. In the context of the use of wireless sensor network technology for environmental monitoring, the two main elementary activities of wireless sensor network are data acquisition and transmission. However, transmitting/receiving data are power consuming task in order to reduce transmission associated power consumption; we explore data compression by processing information locally. The inception of sensor networks, in-network processing has been touted as enabling technology for long-lived deployments. Radio communication is the overriding consumer of energy in such networks. Therefore, data reduction before transmission, either by compression or feature extraction, will directly & significantly increase network lifetime. In many applications where all data must transport out of network, data may be compressed before transport, so chosen compression technique can operate under stringent resource constraints of low-power nodes and induces tolerable errors. This paper evaluates temporal compression scheme designed specially to be used by mica motes. By using LTC, it is possible to compress data up to -20 to -1. Furthermore this algorithm is simple and requires little storage as compared to other compression techniques. The proposed application is implemented on the tinyOS platform using the nesC programming language. To evaluate their work, the author conducts simulation via TOSSIM or a real-world testbed FlockLab. The result demonstrates the significance of the application.
{"title":"A data compression application for wireless sensor networks using LTC algorithm","authors":"Renu Sharma","doi":"10.1109/EIT.2015.7293435","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293435","url":null,"abstract":"In this paper, the author represents energy efficient data compression application based on LTC (Lightweight Temporal Compression) algorithm in wireless sensor networks (WSNs). WSNs are essentially constrained by motes' limited battery power and networks bandwidth. The author focuses on data compression algorithm which effectively supports data compression for data gathering in WSNs. Data reduction before transmission such as by compression will significantly decrease the resource usage. Therefore, the main idea of this paper is to show how a data compression application such as collection tree protocol (CTP) is used for data collection from different sensor nodes into the root node in order to increase the network lifetime. LTC algorithm is used to minimize the amount of error in each reading. In the context of the use of wireless sensor network technology for environmental monitoring, the two main elementary activities of wireless sensor network are data acquisition and transmission. However, transmitting/receiving data are power consuming task in order to reduce transmission associated power consumption; we explore data compression by processing information locally. The inception of sensor networks, in-network processing has been touted as enabling technology for long-lived deployments. Radio communication is the overriding consumer of energy in such networks. Therefore, data reduction before transmission, either by compression or feature extraction, will directly & significantly increase network lifetime. In many applications where all data must transport out of network, data may be compressed before transport, so chosen compression technique can operate under stringent resource constraints of low-power nodes and induces tolerable errors. This paper evaluates temporal compression scheme designed specially to be used by mica motes. By using LTC, it is possible to compress data up to -20 to -1. Furthermore this algorithm is simple and requires little storage as compared to other compression techniques. The proposed application is implemented on the tinyOS platform using the nesC programming language. To evaluate their work, the author conducts simulation via TOSSIM or a real-world testbed FlockLab. The result demonstrates the significance of the application.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121580607","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293399
Ernest Workman, I. Chang, S. Noghanian
Flexible conductive textile material can make it possible to design flexible antennas that are wearable and nonintrusive to the user. It is this simplicity to the user that makes them suitable for applications such as health-monitoring systems. With the goal in mind of designing a wearable flexible antenna, a two element textile antenna array is designed to work at 2.45 GHz frequency. CST Microwave Studio has been used to verify the design. Various fabrication techniques were used. To further decrease the size of the antenna, a slot loaded design is proposed. In addition to the antenna, a connector design which will provide a reliable physically strong connection is proposed in this paper. For the cutting of the fabric a craft cutting machine was used. This machine has an accuracy of 0.05 mm, which is sufficient for the prototype manufacturing. The connector design is done by 3D printing method.
{"title":"Flexible textile antenna array","authors":"Ernest Workman, I. Chang, S. Noghanian","doi":"10.1109/EIT.2015.7293399","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293399","url":null,"abstract":"Flexible conductive textile material can make it possible to design flexible antennas that are wearable and nonintrusive to the user. It is this simplicity to the user that makes them suitable for applications such as health-monitoring systems. With the goal in mind of designing a wearable flexible antenna, a two element textile antenna array is designed to work at 2.45 GHz frequency. CST Microwave Studio has been used to verify the design. Various fabrication techniques were used. To further decrease the size of the antenna, a slot loaded design is proposed. In addition to the antenna, a connector design which will provide a reliable physically strong connection is proposed in this paper. For the cutting of the fabric a craft cutting machine was used. This machine has an accuracy of 0.05 mm, which is sufficient for the prototype manufacturing. The connector design is done by 3D printing method.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124195395","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293381
Vinay Bhargav Vasudevamurt, A. Uskov
Serious games and their applications in industry, businesses and other “serious” areas is a fast growing tendency. A success of serious game or serious gamified application's implementation and use in industry significantly depends on quality of external technical gamification platform to be used, or, serious game engine (SGE). The goals of the current SGE Research Group project at Bradley University (Peoria, IL) include an analysis of 100+ serious games and serious gamified applications in industry, development of a comprehensive SGE Comparative Analysis Framework, and classification of SGE and ranking of quality of SGE features, and generation of a set of recommendations on selection and utilization of SGE. This paper presents the main findings and outcomes of the SGE research project.
{"title":"Serious game engines: Analysis and applications","authors":"Vinay Bhargav Vasudevamurt, A. Uskov","doi":"10.1109/EIT.2015.7293381","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293381","url":null,"abstract":"Serious games and their applications in industry, businesses and other “serious” areas is a fast growing tendency. A success of serious game or serious gamified application's implementation and use in industry significantly depends on quality of external technical gamification platform to be used, or, serious game engine (SGE). The goals of the current SGE Research Group project at Bradley University (Peoria, IL) include an analysis of 100+ serious games and serious gamified applications in industry, development of a comprehensive SGE Comparative Analysis Framework, and classification of SGE and ranking of quality of SGE features, and generation of a set of recommendations on selection and utilization of SGE. This paper presents the main findings and outcomes of the SGE research project.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124295182","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293425
Ghassan Azar, Clay S. Gloster, Naser El-Bathy, Su Yu, Rajasree Himabindu Neela, Israa Alothman
Inappropriate diagnosis of mental health illnesses leads to wrong treatment and causes irreversible deterioration in the client's mental health status including hospitalization and/or premature death. About 12 million patients are misdiagnosed annually in US. In this paper, a novel study introduces a semi-automated system that aids in preliminary diagnosis of the psychological disorder patient. This is accomplished based on matching description of a patient's mental health status with the mental illnesses illustrated in DSM-IV-TR, Fourth Edition Text Revision. The study constructs the semi-automated system based on an integration of the technology of genetic algorithm, classification data mining and machine learning. The goal is not to fully automate the classification process of mentally ill individuals, but to ensure that a classifier is aware of all possible mental health illnesses could match patient's symptoms. The classifier/psychological analyst will be able to make an informed, intelligent and appropriate assessment that will lead to an accurate prognosis. The analyst will be the ultimate selector of the diagnosis and treatment plan.
{"title":"Intelligent data mining and machine learning for mental health diagnosis using genetic algorithm","authors":"Ghassan Azar, Clay S. Gloster, Naser El-Bathy, Su Yu, Rajasree Himabindu Neela, Israa Alothman","doi":"10.1109/EIT.2015.7293425","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293425","url":null,"abstract":"Inappropriate diagnosis of mental health illnesses leads to wrong treatment and causes irreversible deterioration in the client's mental health status including hospitalization and/or premature death. About 12 million patients are misdiagnosed annually in US. In this paper, a novel study introduces a semi-automated system that aids in preliminary diagnosis of the psychological disorder patient. This is accomplished based on matching description of a patient's mental health status with the mental illnesses illustrated in DSM-IV-TR, Fourth Edition Text Revision. The study constructs the semi-automated system based on an integration of the technology of genetic algorithm, classification data mining and machine learning. The goal is not to fully automate the classification process of mentally ill individuals, but to ensure that a classifier is aware of all possible mental health illnesses could match patient's symptoms. The classifier/psychological analyst will be able to make an informed, intelligent and appropriate assessment that will lead to an accurate prognosis. The analyst will be the ultimate selector of the diagnosis and treatment plan.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117261917","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293354
Madallah Alruwaili, L. Gupta
Analyses of images acquired in dusty environments show that the images tend to have noise, blur, small dynamic ranges, low contrast, diminished blue components, and high red components. The goal of this paper is to develop a strategy to enhance such dusty images using a sequence of image processing steps. A statistical adaptive algorithm consisting of image restoration using the Wiener filter, contrast stretching using the RGB color model, intensity stretching using the HSI color model, and color cast removal using color balance, is introduced. Enhancement experiments are conducted on real dusty images and it is shown that the strategy is quite effective in enhancing dusty images. Furthermore the results are superior to those obtained through histogram equalization, gray world, and white patch algorithms. In addition, the complexity of the proposed algorithm is very low thus making it attractive for real time-image processing.
{"title":"A statistical adaptive algorithm for dust image enhancement and restoration","authors":"Madallah Alruwaili, L. Gupta","doi":"10.1109/EIT.2015.7293354","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293354","url":null,"abstract":"Analyses of images acquired in dusty environments show that the images tend to have noise, blur, small dynamic ranges, low contrast, diminished blue components, and high red components. The goal of this paper is to develop a strategy to enhance such dusty images using a sequence of image processing steps. A statistical adaptive algorithm consisting of image restoration using the Wiener filter, contrast stretching using the RGB color model, intensity stretching using the HSI color model, and color cast removal using color balance, is introduced. Enhancement experiments are conducted on real dusty images and it is shown that the strategy is quite effective in enhancing dusty images. Furthermore the results are superior to those obtained through histogram equalization, gray world, and white patch algorithms. In addition, the complexity of the proposed algorithm is very low thus making it attractive for real time-image processing.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123215505","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293404
Rawa Adla, Youssef A. Bazzi, N. Al-Holou
Motor vehicle collisions are the leading cause of death in the Unites States. Rear-end crashes alone occur approximately 1.6 million times each year [1]. These statistics demonstrate the obvious need to reduce the number of vehicle collisions and save lives. In response, the government, automobile industry, and academia have conducted intensive research in an effort to enhance the safety in the U.S. transportation system. Such research has led to a recent trend to develop the next generation driverless car. This paper proposes a new methodology for use in vehicle safety system that has the potential to be used in autonomous driving (driverless vehicles). The new method applies Bayes' probabilistic reasoning technique to a multi sensor data fusion system in order to enhance a vehicle collision avoidance system in real time. The proposed methodology integrates multiple sensor readings, such as the speedometer of the host vehicle, and other sensors mounted on the vehicle to measure the speed of the leading vehicle. This methodology was modeled by using MATLAB and proved to produce a more reliable and certain decision for the host vehicle to react in order to avoid any potential collision.
{"title":"Bayesian network based collision avoidance systems","authors":"Rawa Adla, Youssef A. Bazzi, N. Al-Holou","doi":"10.1109/EIT.2015.7293404","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293404","url":null,"abstract":"Motor vehicle collisions are the leading cause of death in the Unites States. Rear-end crashes alone occur approximately 1.6 million times each year [1]. These statistics demonstrate the obvious need to reduce the number of vehicle collisions and save lives. In response, the government, automobile industry, and academia have conducted intensive research in an effort to enhance the safety in the U.S. transportation system. Such research has led to a recent trend to develop the next generation driverless car. This paper proposes a new methodology for use in vehicle safety system that has the potential to be used in autonomous driving (driverless vehicles). The new method applies Bayes' probabilistic reasoning technique to a multi sensor data fusion system in order to enhance a vehicle collision avoidance system in real time. The proposed methodology integrates multiple sensor readings, such as the speedometer of the host vehicle, and other sensors mounted on the vehicle to measure the speed of the leading vehicle. This methodology was modeled by using MATLAB and proved to produce a more reliable and certain decision for the host vehicle to react in order to avoid any potential collision.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129303659","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}
Pub Date : 2015-05-21DOI: 10.1109/EIT.2015.7293432
Mohammad Khanjary, M. Sabaei, M. Meybodi
In many applications of directional sensor networks especially border/barrier surveillance and intrusion detection applications, checking the establishment of the spanning clump/cluster of collaborated sensors that spans all over the region of interest is an essential task. Two sensors are collaborating sensors if their sensing ranges have been overlapped. When the spanning clump of collaborating sensors occurs, nothing could pass the region unless it will be detected by the network. In static networks (when orientation of sensor nodes is fixed), one time checking is needed. But in dynamic networks (when sensor nodes can adjust their orientations by using an algorithm) or hybrid networks (when some nodes are static and other nodes are dynamic), checking must be done periodically upon network topology changes. Therefore, it is very important to have an algorithm to test the establishment of spanning clump. In this paper, we present a distributed algorithm based on cellular automata to find out the establishment of spanning clump (percolation) in the region of interest by directional sensor networks consist of sensors with field-of-view angles between and π. The proposed algorithm is distributed and works locally which makes it suitable for using in sensor networks. Moreover, the algorithm could be in other technical problems of sensor networks such as scheduling and topology control.
{"title":"A percolation algorithm for directional sensor networks","authors":"Mohammad Khanjary, M. Sabaei, M. Meybodi","doi":"10.1109/EIT.2015.7293432","DOIUrl":"https://doi.org/10.1109/EIT.2015.7293432","url":null,"abstract":"In many applications of directional sensor networks especially border/barrier surveillance and intrusion detection applications, checking the establishment of the spanning clump/cluster of collaborated sensors that spans all over the region of interest is an essential task. Two sensors are collaborating sensors if their sensing ranges have been overlapped. When the spanning clump of collaborating sensors occurs, nothing could pass the region unless it will be detected by the network. In static networks (when orientation of sensor nodes is fixed), one time checking is needed. But in dynamic networks (when sensor nodes can adjust their orientations by using an algorithm) or hybrid networks (when some nodes are static and other nodes are dynamic), checking must be done periodically upon network topology changes. Therefore, it is very important to have an algorithm to test the establishment of spanning clump. In this paper, we present a distributed algorithm based on cellular automata to find out the establishment of spanning clump (percolation) in the region of interest by directional sensor networks consist of sensors with field-of-view angles between and π. The proposed algorithm is distributed and works locally which makes it suitable for using in sensor networks. Moreover, the algorithm could be in other technical problems of sensor networks such as scheduling and topology control.","PeriodicalId":415614,"journal":{"name":"2015 IEEE International Conference on Electro/Information Technology (EIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129656783","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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