Characteristics in EEG signals related to the motor imagery can be used to build up a biometric system. However, for the practical implementation of a biometric system, the classifier plays a crucial role. In this paper, I compared the performance of three different classifiers for the detection of the imagined movements in a group of subjects on the basis of EEG signals. The classifiers compared here were those based on Linear Discrimination Analysis (LDA), Artificial Neural Network (ANN) and Support Virtual Machine (SVM). Results show a better performance of the LDA classifier with the respect to the other classifiers.
{"title":"Comparison of Different Classifiers for Biometric System Based on EEG Signals","authors":"Huangfu Jian-feng","doi":"10.1109/ITCS.2010.77","DOIUrl":"https://doi.org/10.1109/ITCS.2010.77","url":null,"abstract":"Characteristics in EEG signals related to the motor imagery can be used to build up a biometric system. However, for the practical implementation of a biometric system, the classifier plays a crucial role. In this paper, I compared the performance of three different classifiers for the detection of the imagined movements in a group of subjects on the basis of EEG signals. The classifiers compared here were those based on Linear Discrimination Analysis (LDA), Artificial Neural Network (ANN) and Support Virtual Machine (SVM). Results show a better performance of the LDA classifier with the respect to the other classifiers.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124740430","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}
Body temperature state pattern is the most important index, which can reflect normal and abnormal running state of the high power loading devices for the vehicle on subway, in order to timely, quickly and accurately recognize body temperature state of the objective device, and reduce false alarming probability, make use of neural network system intelligent Agent and expert system intelligent Agent which simultaneously recognize body temperature state of the objective devices and get probability pattern recognition, and applies D-S evidence theory and weight factor into steps which fuse several intelligent agents into one union intelligent agent, finally make a intelligent decision result. The practical results show that this method greatly strengthens reliability of recognition ability for device temperature state pattern, and also is easy to expandable.
{"title":"Multi-Agent Temperature State Recognition Based on D-S Evidence Theory","authors":"Guo Qi-yi, Zhuo Chunyang","doi":"10.1109/ITCS.2010.70","DOIUrl":"https://doi.org/10.1109/ITCS.2010.70","url":null,"abstract":"Body temperature state pattern is the most important index, which can reflect normal and abnormal running state of the high power loading devices for the vehicle on subway, in order to timely, quickly and accurately recognize body temperature state of the objective device, and reduce false alarming probability, make use of neural network system intelligent Agent and expert system intelligent Agent which simultaneously recognize body temperature state of the objective devices and get probability pattern recognition, and applies D-S evidence theory and weight factor into steps which fuse several intelligent agents into one union intelligent agent, finally make a intelligent decision result. The practical results show that this method greatly strengthens reliability of recognition ability for device temperature state pattern, and also is easy to expandable.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"27 22","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120867000","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}
Peng Ren, Qian Jian-sheng, Sun Yan-jing, Jiang Hai-feng, Lu Zhao-lin
In order to solve uneven data throughput phenomenon for wireless sensor networks under coal mine, which cause “hot spots” problem, energy-efficient uneven clustering scheme based on the energy and distribution density of cluster heads ( UCS-ED ) is proposed, which formed by many existing routing protocols used in wireless sensor networks. In the cluster heads election phase it put the energy and distribution density as two elements to join the election, form an uneven density of backbone around the Sink. Simulation results show that UCS-ED outperform LEACH and HEED in balancing energy consumption and prolonging the network lifetime.
{"title":"Energy-Balanced Scheme Based Unequal Density of Backbone for Wireless Sensor Networks Under Coal Mine","authors":"Peng Ren, Qian Jian-sheng, Sun Yan-jing, Jiang Hai-feng, Lu Zhao-lin","doi":"10.1109/ITCS.2010.20","DOIUrl":"https://doi.org/10.1109/ITCS.2010.20","url":null,"abstract":"In order to solve uneven data throughput phenomenon for wireless sensor networks under coal mine, which cause “hot spots” problem, energy-efficient uneven clustering scheme based on the energy and distribution density of cluster heads ( UCS-ED ) is proposed, which formed by many existing routing protocols used in wireless sensor networks. In the cluster heads election phase it put the energy and distribution density as two elements to join the election, form an uneven density of backbone around the Sink. Simulation results show that UCS-ED outperform LEACH and HEED in balancing energy consumption and prolonging the network lifetime.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129882079","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}
The location estimation of sensor nodes is a fundamental and essential issue for wireless sensor networks (WSNs), because the gathered data is meaningful only when the location information of the sensor nodes is known. In this paper, we proposed a novel localization algorithm. In the proposed scheme, we first estimate the location of sensor nodes using Convex Position Estimation (CPE), and then refine the location of sensor nodes using the location of the two-hop beacon nodes. Simulation shows that compared with convex localization algorithm, the proposed localization algorithm can enhance the localization accuracy efficiently.
{"title":"A Novel Localization Algorithm for Wireless Sensor Network Using Two-hop Beacon Nodes","authors":"Jianmin Zhang, Jian Li","doi":"10.1109/ITCS.2010.18","DOIUrl":"https://doi.org/10.1109/ITCS.2010.18","url":null,"abstract":"The location estimation of sensor nodes is a fundamental and essential issue for wireless sensor networks (WSNs), because the gathered data is meaningful only when the location information of the sensor nodes is known. In this paper, we proposed a novel localization algorithm. In the proposed scheme, we first estimate the location of sensor nodes using Convex Position Estimation (CPE), and then refine the location of sensor nodes using the location of the two-hop beacon nodes. Simulation shows that compared with convex localization algorithm, the proposed localization algorithm can enhance the localization accuracy efficiently.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134559908","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}
Quantified logic in the many-valued logic system is established by Wang G J, which is based on linear evaluation lattice frame. The variable truth degree is defined in the propositional logic system associated with rhombus evaluation lattice and Gaines-Rescher implication operation, the fundamental nature of the variable truth degree is studied, the distribution of truth degree of formulae and inference rule based on truth degree are obtained, on the basis of which the inference degree's numerical is proved.
{"title":"The Variable Truth Degree of Formula in a Propositional Logic with Rhombus Evaluation Lattice","authors":"Weibing Zuo","doi":"10.1109/ITCS.2010.52","DOIUrl":"https://doi.org/10.1109/ITCS.2010.52","url":null,"abstract":"Quantified logic in the many-valued logic system is established by Wang G J, which is based on linear evaluation lattice frame. The variable truth degree is defined in the propositional logic system associated with rhombus evaluation lattice and Gaines-Rescher implication operation, the fundamental nature of the variable truth degree is studied, the distribution of truth degree of formulae and inference rule based on truth degree are obtained, on the basis of which the inference degree's numerical is proved.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133673801","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}
The network-based GPS technique provides a broad Spectrum of corrections for real-time kinematic. And the atmospheric refraction error is the main factors to be sufficient to support the ambiguity resolution (AR) and accuracy of the long-distance RTK. However, due to the strong spatial correlated of the tropospheric delay, the elevation difference between the reference plane and the rove station will cause the deviation of tropospheric error in the system so that the accuracy of troposphere correction will be lowered. In this paper, a new tropospheric error model based on neural network is presented. The neural network model takes into account not only the level factors, but also the elevation factor. It establishes the model in the spatial space. And the experimental results show that the accuracy of tropospheric delay model is within 5cm regardless of interpolation points in the network or network.
{"title":"An Tropospheric Delay Model for GPS NET RTK","authors":"Qiu Lei, L. Lei, W. Zemin","doi":"10.1109/ITCS.2010.30","DOIUrl":"https://doi.org/10.1109/ITCS.2010.30","url":null,"abstract":"The network-based GPS technique provides a broad Spectrum of corrections for real-time kinematic. And the atmospheric refraction error is the main factors to be sufficient to support the ambiguity resolution (AR) and accuracy of the long-distance RTK. However, due to the strong spatial correlated of the tropospheric delay, the elevation difference between the reference plane and the rove station will cause the deviation of tropospheric error in the system so that the accuracy of troposphere correction will be lowered. In this paper, a new tropospheric error model based on neural network is presented. The neural network model takes into account not only the level factors, but also the elevation factor. It establishes the model in the spatial space. And the experimental results show that the accuracy of tropospheric delay model is within 5cm regardless of interpolation points in the network or network.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133325087","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}
The narrow bandwidth of wireless communication network limited the applications of the remote image surveillance in the unattended substation. A new method is proposed to adapt the wireless environment. The technique, implemented to obtain the digital instrument’s reading which is set as the ROI(region of interest) automatically, utilizes corner detection based on SUSAN algorithm. Then the ROI encoding in JPEG2000 technology is utilized in the image of the region of interest compressed at a higher quality than the rest of the image. The instrument’s reading information of unattended substation can be transmitted to dispatching center using wireless network effectively. Experimental results show that the presented method is feasible in terms of image quality and compression, adapting the narrow bandwidth, and improving the image of the real-time transmission.
{"title":"Image Surveillance System in the Unattended Substation Based on SUSAN Corner Detection","authors":"Song Jia, Liang Yuyan","doi":"10.1109/ITCS.2010.57","DOIUrl":"https://doi.org/10.1109/ITCS.2010.57","url":null,"abstract":"The narrow bandwidth of wireless communication network limited the applications of the remote image surveillance in the unattended substation. A new method is proposed to adapt the wireless environment. The technique, implemented to obtain the digital instrument’s reading which is set as the ROI(region of interest) automatically, utilizes corner detection based on SUSAN algorithm. Then the ROI encoding in JPEG2000 technology is utilized in the image of the region of interest compressed at a higher quality than the rest of the image. The instrument’s reading information of unattended substation can be transmitted to dispatching center using wireless network effectively. Experimental results show that the presented method is feasible in terms of image quality and compression, adapting the narrow bandwidth, and improving the image of the real-time transmission.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"10 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129317335","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}
ADV212 is a SOC which is to implement JPEG2000 encoding and decoding. An embedded RISC processor, a dedicated wavelet transform engine, three entropy codec and on-chip memory system are integrated in ADV212. It provides a complete JPEG2000 compression and decompression solution for real-time application of standard or high resolution video or still image. The ADV212 implements the function described in the JPEG2000 Standard Part I except the ROI. Two chips of ADV212 are used to perform lossy and lossless compression of high resolution aero image. The system architecture is mainly discussed in the paper and also the software and hardware design method to use ADV212 to compress still image. The experimental results show that the system could implement real-time compression of high resolution aero image.
{"title":"ADV212-based High Resolution Still Image Compression System Design","authors":"Chen Zhe, Duan Zong-tao, Sun Zhaoyun, W. Dongmei","doi":"10.1109/ITCS.2010.48","DOIUrl":"https://doi.org/10.1109/ITCS.2010.48","url":null,"abstract":"ADV212 is a SOC which is to implement JPEG2000 encoding and decoding. An embedded RISC processor, a dedicated wavelet transform engine, three entropy codec and on-chip memory system are integrated in ADV212. It provides a complete JPEG2000 compression and decompression solution for real-time application of standard or high resolution video or still image. The ADV212 implements the function described in the JPEG2000 Standard Part I except the ROI. Two chips of ADV212 are used to perform lossy and lossless compression of high resolution aero image. The system architecture is mainly discussed in the paper and also the software and hardware design method to use ADV212 to compress still image. The experimental results show that the system could implement real-time compression of high resolution aero image.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125792473","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}
An optimized multi-class classification algorithm based on SVM decision tree (SVMDT) is proposed. But by SVMDT, the generalization ability depends on the tree structure. In this paper, the relativity separability measure between classes is defined based on the distribution of the training samples to improve the generalization ability of SVMDT. SVM is extended to non-linear SVM by using kernel functions and the classification experiments prove the algorithm is more effective and feasible for classification accuracy.
{"title":"An Optimized Multi-class Classification Algorithm Based on SVM Decision Tree","authors":"Chen Donghui, Li Zhijing","doi":"10.1109/ITCS.2010.17","DOIUrl":"https://doi.org/10.1109/ITCS.2010.17","url":null,"abstract":"An optimized multi-class classification algorithm based on SVM decision tree (SVMDT) is proposed. But by SVMDT, the generalization ability depends on the tree structure. In this paper, the relativity separability measure between classes is defined based on the distribution of the training samples to improve the generalization ability of SVMDT. SVM is extended to non-linear SVM by using kernel functions and the classification experiments prove the algorithm is more effective and feasible for classification accuracy.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125806155","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}
The acquisition and tracking processes of Global Navigation Satellite System (GNSS) are heavy in the computation load of a GNSS receiver [1]. In order to track and decode the navigation information in the GPS signal, an acquisition algorithm must be used to detect the presence of the satellite signal. Once the signal is acquired, the necessary parameters such as code delay and Doppler shift must be obtained and then the parameters are passed to the tracking program in order to obtain the navigation information. This paper presents the serial search algorithm and the FFT acquisition algorithm based on real GPS IF data. Experiments are finished to compare the performance and computing speed of both the algorithms. As a result, it shows that FFT acquisition algorithm is efficient and further reduces the processing time in signal acquisition process.
{"title":"GPS Signal Acquisition Based on FFT","authors":"Qiu Lei, L. Lei","doi":"10.1109/ITCS.2010.33","DOIUrl":"https://doi.org/10.1109/ITCS.2010.33","url":null,"abstract":"The acquisition and tracking processes of Global Navigation Satellite System (GNSS) are heavy in the computation load of a GNSS receiver [1]. In order to track and decode the navigation information in the GPS signal, an acquisition algorithm must be used to detect the presence of the satellite signal. Once the signal is acquired, the necessary parameters such as code delay and Doppler shift must be obtained and then the parameters are passed to the tracking program in order to obtain the navigation information. This paper presents the serial search algorithm and the FFT acquisition algorithm based on real GPS IF data. Experiments are finished to compare the performance and computing speed of both the algorithms. As a result, it shows that FFT acquisition algorithm is efficient and further reduces the processing time in signal acquisition process.","PeriodicalId":340471,"journal":{"name":"2010 Second International Conference on Information Technology and Computer Science","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124750348","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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