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2013 International Conference on Biological,Medical and Chemical Engineering(BMCE 2013)

作者： Hong-er TIAN Li-li CAO Yong-guo ZHAN Ling LIU Zi-hai JIAN Huannuer YASHENGBIEKE Aili KAIMIERDING Jian WU Zheng-bao ZHANG Zhi-qiang PAN Xi YANG Jun WANG Key Laboratory of Environment Medicine and Engineering Ministry of EducationSchool of Public HealthSoutheast University Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

To prevent the occurrence of burnout and karoshi,we try to detect and diagnose job stress in clinical practice using electroencephalogram(EEG).The EEG data were taken from 12 graduate students and 12 nurses from a third-grade class-A hospital,which two groups have the different job *** sampling frequency was 200 Hz,and the complexity of the electroencephalogram and its dynamic range were calculated based on Jensen-Shannon Divergence.T test value of the two groups was equal to 4.414 which confidence probability is 0.001,indicating the Jensen-Shannon Divergence value of students is less than that of ***,groups with different degree of job stress can be non-destructively and more easily diagnosed by the complexity of EEG data compared with blood samples,which is conducive to the evaluation,prevention and intervention of job stress and health promotion.

关键词： Electroencephalogram Complexity Job Stress Jensen-Shannon divergence

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Attention Electroencephalogram Analysis based on Jensen-Shannon Divergence Analysis

Attention Electroencephalogram Analysis based on Jensen-Shan...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Zhengzhong Zheng Junchang Zhao Xiaolin Huang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm Institute of Biomedical Electronic Engineering School of Electronic Science and EngineeringNanjing University

In this paper, the complexity analysis method based on Jensen-Shannon Divergence was used to calculate the complexity of the Idle states, the close eyes states and the count numbers states electroencephalogram The study found that the JSD value of close eyes states EEG was highest, followed by that of the Idle states EEG, and that of the count numbers states EEG was minimum The result can be used to assisted clinical diagnosis

关键词： Complexity electroencephalogram Jensen-Shannon Divergence

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An improved method in change detection of multitemporal remote sensing image

An improved method in change detection of multitemporal remo...

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Liao, Fangshun Yu, Sufen Li, Ying Zhang, Yanning Shaanxi Provincial Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an Shaanxi 710072 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Traditional Markov random Field (MRF) methods assume that neighboring pixels tend to have the same label. However, this assumption is always inconsistent with the actual situation and affects the resultant accuracy of the algorithm. To overcome this, we propose an object-based Markov Random Field (OMRF) model and a change detection method based on OMRF model. The OMRF model assumes that pixels within same object are in the same class. First, we generate the difference image from multi-temporal remote sensing images. Second, Mean Shift is applied to extract objects from difference image. Finally, change detection map is generated by iterative algorithm. The experimental results show that the algorithm can effectively improve the detection accuracy of the algorithm on real remote sensing datasets. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Change detection

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Fetal Electrocardiogram Extraction Based On Modified Robust Independent Component Analysis

Fetal Electrocardiogram Extraction Based On Modified Robust ...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Wenpo Yao Junchang Zhao Zhengzhong Zheng Tiebing Liu Hongxing Liu Jun Wang Image Processing and Image Communications Key Lab. Nanjing Univ. of Posts & Telecomm Nanjing General Hospital of Nanjing Military Command School of Electronic Science and Engineering Nanjing University

Fetal electrocardiogram(FECG) separation gets widely attention due to its clinical significance In the paper, we proposed an improved robust independent component analysis for fetal ECG separation Firstly, wavelet decomposition was applied to fetal ECG to get the relevant parameters Then, the Robust ICA was used to separate the mixed signals Compared to robust independent component analysis, computing speed of the improved algorithm increased by an average of 15 percent while minimum mean square error fluctuations 00008, which indicated that this algorithm could be effectively used in clinical fetal ECG monitoring

关键词： Robust ICA Wavelet Transform FECG Kurtosis

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Video summarization by robust low-rank subspace segmentation

Video summarization by robust low-rank subspace segmentation

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8th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2013

作者： Tu, Zhengzheng Sun, Dengdi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei230039 China School of Computer Science and Technology Anhui University Hefei230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei230039 China

ISBN: (纸本)9783642375019

Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper. Firstly, video frames are represented as multi-dimensional vectors, and then embedded into a group of affine subspaces using low-rank representation according to the content similarity of the frames in the same subspace. Secondly, a series of subspaces are segmented based on the Normalized Cuts algorithm. The video summary is finally generated by choosing key frames from the significant subspaces and ranking these key frames in temporal order. The experimental results demonstrate that the proposed summarization algorithm can produce crucial key frames and effectively reduce the visual content redundancy in summary comparing with the conventional approaches. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Vectors

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A local elitism based membrane evolutionary algorithm for point pattern matching

A local elitism based membrane evolutionary algorithm for po...

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8th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2013

作者： Ding, Zhuanlian Tang, Jin Zhang, Xingyi Luo, Bin School of Computer Science and Technology Anhui University HefeiAnhui230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province HefeiAnhui230039 China

ISBN: (纸本)9783642375019

Point pattern matching is a fundamental problem in computer vision and pattern recognition. Membrane computing is an emergent branch of bio-inspired computing, which provides a novel idea to solve computationally hard problems. In this paper, a new point pattern matching algorithm with local elitism strategy is proposed based on membrane computing models. Local elitism strategy is used to keep good correspondences of point pattern matching found during the search, so the matching rate and the convergence speed are improved. Five heuristic mutation rules are introduced to avoid the local optimum. Experiment results on both synthetic data and real world data illustrate that the proposed algorithm is of higher matching rate and better stability. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Membranes

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未来视频技术专题(英文)

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China communications 2013年第5期 8-10页

作者：陈熙霖朱秀昌王桥胡栋 Ming-Ting SUN the Institute of Computing Technology Chinese Academy of Sciences (CAS) the IEEE Transactions on Image Processing the Journal of Computer Science and Technology the Chinese Journal of Computers College of Communications and Information Engineering NUPT Image Processing and Image Communications Key Laboratory of Information Industrial Ministry and Jiangsu Province Signal and Information Processing Laboratory Southeast University

In the past few years, video has become one of the most powerful engines to push communications forward. The increasing of digital video technology requires larger and larger bandwidth for various applications, such as IPTV, VOD, video phone, mobile search, etc. The goal of this Feature Topic column is to present and highlight the latest progress and future video-related technologies. We hope this

关键词： IEEE over

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A compressive sensing based mobile video communication system

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Sensors and Transducers 2013年第6期153卷 186-191页

作者： Wu, Minghu Li, Ran Zhou, Shangli School of Electrical and Electronic Engineering Hubei University of Technology Wu'han 430068 China Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

A compressive sensing (CS) based mobile video communication system is proposed to meet the requirement that video service needs low-complexity video encoder in the mobile internet. In this system, the mobile client uses CS based video encoder having low computational complexity and power, and then its output bit-stream is decoded using CS recovery algorithm in the fixed base station or network server. The decoded video signal is transformed again as bits by the traditional H.264/MPEG video encoder, and the central base station transmits them to mobile clients so as to realizing low-complexity video decoding. The simulation experiments show that the proposed CS based mobile video communication system has the better rate-distortion performance, and can ensure high quality video reconstruction at low measurement rates. © 2013 IFSA.

关键词： Compressed sensing

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Symbolic transfer entropy-based premature signal analysis

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Chinese Physics B 2012年第1期21卷 535-538页

作者： Wang Jun Yu Zheng-Feng Image Processing and Image Communications Key Laboratory School of Geography and Biological InformationNanjing University of Posts&TelecommunicationsNanjing 210003China

In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency.

关键词： premature signal symbolic transfer entropy signal coupling

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Non-sparse Infinite-Kernel Learning for Automated Identification of Alzheimer's Disease Using PET Imaging

Non-sparse Infinite-Kernel Learning for Automated Identifica...

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International Conference on Control, Automation, Robotics & Vision

作者： Yong Xia Shen Lu Wei Wei David Dagan Feng Yanning Zhang Shaanxi Key Lab of Speech & Image Information Processing (SAIIP) School of Computer Science Northwestern Polytechnical University Xi'an 710072 China Biomedical and Multimedia Information Technology (BMIT) Research Group School of Information Technologies The University of Sydney NSW2006 Australia

ISBN: (纸本)9781479952007

Multi-kernel learning machine (MKLM) has recently been introduced to the research of computer-aided dementia identification and pathology progress tracking. Despite its good performance especially in case of using heterogeneous data, such learning schema and its variants usually utilize a L-1 norm constraint that promotes sparse solutions, which may cause loss of potentially important information. In this paper, we propose the non-sparse infinite-kernel learning machine (NS-IKLM) for automated identification of Alzheimer cases from normal controls. In our approach, a modified constraint is utilized to promotes non-sparse solutions and kernel parameters are automatically tuned during the learning process. The proposed algorithm has been evaluated on a set of FDG-PET images selected from the Alzheimer's disease neuroimaing initiative (ADNI) cohort. Our results demonstrate that the proposed non-sparse NS-IKLM is able to achieve satisfying dementia identification at a relatively low computational cost.

关键词： Infinite kernel learning dementia FDG-PET ADNI

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