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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Yufang Huang Jin Xu Zhen Cheng Zhihua Chen Xuncai Zhang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China School of Electronics Engineering and Computer Science Peking University Beijing China

Algorithmic self-assembly, a generalization of crystal growth, has been proposed as a mechanism for the bottom-up fabrication of autonomous DNA computation. In theory, growth can be programmed by designing a set of molecular tiles with binding interactions that enforce assembly rules. There are many interesting applications of the reordering problem in Mathematics, as well as Computer Sciences. It is a useful primitive operation for computation and construction in the field of science and engineering. It is worth exploring more efficient approach to solve this problem. In this paper, we provide a description of a novel method for the reordering problem by use of the programmable tile assembly model. We propose the thought of block assembly model which takes full advantage of the huge parallelism inherent in the tile assembly. On the basis of the structural property, we delicately devise a rule to produce a long reporter strand which can connect all the inputs of the given problem with the final results. It is proved that this method can be extended to any reordering problem with arbitrary size in theory. The great advantage of our schema is that it only needs a constant number of tile types and in time linear with the size of the input problem to solve any reordering problem.

关键词： Tiles Assembly Self-assembly DNA computing Molecular computing Fabrication Logic Biology computing Laboratories intelligent control

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A statistical approach to contour extraction based on quantum mechanics

A statistical approach to contour extraction based on quantu...

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Medical Imaging 2009 - image processing

作者： Sun, Yangguang Lan, Tian Fu, Xiaowei Ding, Mingyue Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475107

Contour extraction is a key issue in many medical applications. A novel statistical approach based on quantum mechanics to extract contour of the interested object of medical images was proposed in this paper. The natures of quantum statistical concepts such as the quantum discontinuity and the wave function correspond to the discrete and gray possibility of an image respectively. Contour extraction will be performed by the quantum particle movement, where the particle will be moved forward to the position with high probability density edges in image potential field. Experimental results with medical images demonstrated that the proposed approach has the capability to extract contours with arbitrary initialization and handle topology changes as well as both the inner and outer contours by a single initialization. keywords: Statistical approach, contour extraction, path integral, quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Medical applications

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Effects of Epidural Spinal Cord Stimulation and Treadmill Training on Locomotion Function and Ultrastructure of Spinal Cord Anterior Horn after Moderate Spinal Cord Injury in Rats

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中国康复医学杂志 2009年第6期24卷 485-488页

作者： WANG Yizhao HUANG Xiaolin XU Jiang XU Tao FANG Zhengyu XU Qi TU Xikai YANG Peipei Department of Rehabilitation Medicine Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan 430030 China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan 430000 China

Objective:To investigate the effects of epidural spinal cord stimulation(ESCS) and treadmill training on the locomotion function and ultrastructure of spinal cord anterior horn after moderate spinal cord injury in ***:Nine adult female Sprague-Dawley rats were randomly distributed into three groups:①spinal cord injury group(SI,n=3).②spinal cord injury plus ESCS group(SE,n=3).③spinal cord injury plus treadmill training group(TT,n=3).All rats received a moderate spinal cord injury *** weeks after surgery,rats in SE group received an electrode implantation procedure,with the electrode field covering spinal cord segments *** weeks after electrode implantation,rats received subthreshold ESCS for 30 min/*** in TT group received 4cm/s treadmill training for 30min/*** in SI group received no intervention,as a control *** procedures in these three groups lasted four *** open field Basso,Beattie and Bresnahan(BBB) scale was used before and after intervention to evaluate rats' hindlimb motor ***:After four weeks intervention,rats in TT group improved their open field locomotion scores to *** contrast,no significant improvement was observed in groups SI and *** morphology of synapses and neurons were similar regardless of whether rats had undergone ESCS,treadmill training or ***:ESCS alone was not sufficient to improve the walking ability of spinal cord injured *** or treadmill training alone might not contribute to the changes of ultrastructure in anterior horn of spinal cord that underlie the recovery of walking *** research is needed to understand the contributions of combination of ESCS and treadmill training to the rehabilitation of spinal cord injured rats.

关键词：脊髓损伤神经元治疗方法跑步训练

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M-elite coevolutionary algorithm for numerical optimization

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Ruan Jian Xue Bao/Journal of Software 2009年第11期20卷 2925-2938页

作者： Mu, Cai-Hong Jiao, Li-Cheng Liu, Yi Key Laboratory of Intelligent Perception and Image Understanding Xidian University Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China State Key Laboratory of Integrated Services Networks Xidian University Xi'an 710071 China School of Electronic Engineering Xidian University Xi'an 710071 China

The M-elite coevolutionary algorithm (MECA) is proposed for high-dimensional unconstrained numerical optimization problems based on the concept of coevolutionary algorithm and elitist strategy. In the MECA, the individuals with high fitness, called elite population, is considered to play dominant roles in the evolutionary process. The whole population is divided into two subpopulations which are elite population composed of M elites and common population including other individuals, and team members are selected to form M teams by M elites acting as the cores of the M teams (named as core elites) respectively. If the team member selected is another elite individual, it will exchange information with the core elite with the cooperating operation defined in the paper;If the team member is chosen from the common population, it will be led by the core elite with the leading operation. The cooperating and leading operation above are defined by different combinations of several crossover operators or mutation operators. The algorithm is proved to converge to the global optimization solution with probability one. Tests on 15 benchmark problems show that the algorithm can find the global optimal solution or near-optimal solution for most problems tested. Compared with three existing algorithms, MECA achieves an improved accuracy with the same number of function evaluations. Meanwhile, the runtime of MECA is less, even compared with the standard genetic algorithm with the same parameter setting. Moreover, the parameters of the MECA are analyzed in experiments and the results show that MECA is insensitive to parameters and easy to use. © by Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Global optimization

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An Improved Frame-Layer Bit Allocation Scheme for H.264/AVC Rate control

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Journal of Shanghai Jiaotong university(Science) 2009年第2期14卷 143-148页

作者：林贵旭郑世宝朱良家 Institute of Image Communication & Information Processing Department of Electronic EngineeringShanghai Jiaotong University Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Department of Automatic Control National University of Defense Technology

In this paper,we aim at improving the video quality degradation due to high motions or scene changes. An improved frame-layer bit allocation scheme for H.264/AVC rate control is ***,current frame is pre-encoded in 16×16 modes with a fixed quantization parameter(QP).The frame coding complexity is then measured based on the resulting bits and peak signal-to-ratio(PSNR) in the pre-coding ***,a bit budget is calculated for current frame according to its coding complexity and inter-frame PSNR fluctuation,combined with the buffer *** results show that,in comparison with the H.264 adopted rate control scheme, our method is more efficient to suppress the sharp PSNR drops caused by high motions and scene *** visual quality variations in a sequence are also relieved.

关键词： H.264/AVC rate control bit allocation quality degradation

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A Parallel Artificial Immune Model for Optimization

A Parallel Artificial Immune Model for Optimization

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International Conference on Computational Intelligence and Security

作者： Yutao Qi Fang Liu Licheng Jiao School of Computer Science And Technology Key Laboratory of Intelligent Perception and Imagee Understanding of Ministry of Education Xidian University Xi'an China Institute of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

This paper presents a parallel artificial immune model termed as tower master-slave model (TMSM) for solving optimising problems. Based on TMSM, the parallel immune memory clonal selection algorithm (PIMCSA) is also proposed. TMSM is a two level coarse-grained parallel artificial immune model with distributed immune response and distributed immune memory. In PIMCSA, vaccines are extracted and migrated between populations rather than individual migration as has been done in parallel genetic algorithms. It is a good balance between population diversity and the convergent speed. Experimental results on the numerical optimization and TSP problems show that PIMCSA achieves good performance in terms of both solution quality and computation time.

关键词： Immune system Genetic algorithms Artificial immune systems Competitive intelligence Master-slave Laboratories Computer science education Poles and towers Vaccines Parallel processing

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Three-dimensional source reconstruction for bioluminescence tomography using the LSQR method with preconditioning

Three-dimensional source reconstruction for bioluminescence ...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yu, Jingjing Liu, Fang Jiao, Licheng He, Xiaowei School of Computer Science and Technology Xidian University Xi'an 710071 China Scholl of Physics and Information Technology Shaanxi Normal University Xi'an 710062 China Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Information Science and Technology Northwest University Xi'an 710069 China

ISBN: (纸本)9780819478085

As a novel optical molecular imaging modality, Bioluminescence Tomography (BLT) aims at quantitative reconstruction of the bioluminescent source distribution inside the biological tissue from the optical signals measured on the living animal surface, which is a highly ill-posed inverse problem. In this paper, with the finite element method solving the diffusion equation, an iterative regularization algorithm, referred to as least square QR-factorization (LSQR), is applied to the inverse problem in BLT. The affect of the preconditioning strategy on the LSQR method (PLSQR) for BLT is also investigated. The Simulations with a heterogeneous mouse chest phantom demonstrate that by incorporating a priori knowledge of the permissible source region, the LSQR method can reconstruct the source accurately and stably. Moreover, by employing preconditioning strategy, PLSQR outperforms LSQR in terms of source power density and convergence speed. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Inverse problems

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Hardware neural network on an SOPC platform

Hardware neural network on an SOPC platform

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Liu, Yifei Ding, Mingyue Hu, Xia Zhou, Yanhong Department of Biomedical Engineering Xianning Institute Xianning Hubei 437100 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong Univ. of Science and Technology Wuhan 430074 China School of Medicine Xianning Institute Xianning Hubei 437100 China

ISBN: (纸本)9780819478078

SOPC (System on Programmable Chip) is an on-chip programmable system based on large scale Field Programmable Arrays (FPGAs). This paper presented an implementation of an SOPC system with a custom hardware neural network using Altera FPGA chip-EP2C35F672C. The embedded Nios processor was used as the test bench. The test result showed that the SOPC Platform with hardware neural network is faster than the software implementation respectively and the accuracy of the design meets the requirement of system. The verified SOPC system can closely model real-world system, which will have wide applications in different areas such as pattern recognition, data mining and signal processing. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Neural networks

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Bioluminescence tomography based on Bayesian approach

Bioluminescence tomography based on Bayesian approach

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Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Feng, Jinchao Jia, Kebin Tian, Jie Yan, Guorui Qin, Chenghu The College of Electronic Information and Control Engineering Beijing University of Technology Beijing 100022 China Medical Image Processing Group Key Laboratory of Complex Systems and Intelligence Science Institute of Automation P. O. Box 2728 Beijing 100190 China Life Science Research Center Xidian University Xi'an 710071 China

ISBN: (纸本)9780819475138

As a new mode of molecular imaging, bioluminescence tomography (BLT) will have *** *** on revealing the molecular and cellular information in vivo at the whole-body small animal level because of its high sensitive detection and facile operation. However, BLT is an ill-posed problem, it is necessary to incorporate a priori knowledge into the tomographic algorithm. In this paper, a novel Bayesian reconstruction algorithm for BLT is firstly proposed. In the algorithm, a priori permissible source region strategy is incorporated into the Bayesian network to reduce the ill-posedness of BLT. Then a generalized adaptive Gaussian Markov random field (GAGMRF) prior model for unknown source density estimation is developed to further reduce the ill-posedness of BLT on the basis of adaptive finite element analysis. Finally, the algorithm maximizes the log posterior probability with respect to a noise parameter and the unknown source density, the distribution of bioluminescent source can be reconstructed. In addition, the novel tomography algorithm based adaptive finite element makes the method more appropriate for complex phantom such as real mouse. In the numerical simulation, a heterogeneous phantom is used to evaluate the performance of the proposed algorithm with the Monte Carlo based synthetic data. The accurate localization of bioluminescent source and quantitative results show the effectiveness and potential of the tomographic algorithm for BLT. © 2009 SPIE.

关键词： Monte Carlo methods

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Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines

Gait Recognition Using Wavelet Packet Silhouette Representat...

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Congress on image and Signal processing, CISP

作者： Farzin Dadashi Babak N. Araabi Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI USA

Gait is an idiosyncratic biometric that can be used for human identification at a distance and as a result gained growing interest in intelligent visual surveillance. In this paper, an efficient gait recognition method based on describing subject outer body contour deformations using wavelet packets is proposed. With the use of matching pursuit algorithm, k bases of wavelet packet tree that have maximum similarity to the signal are selected and corresponding coefficients are used as features. Finally, transductive support vector machine (TSVM) classification is utilized on computed eigengait space for semi-supervised identification. The proposed method of selecting features which uses a complete orthogonal or near orthogonal basis from a wavelet packet library of bases and investigating the correlational structure of gait features for each individual using TSVM, result in encouraging identification performance.

关键词： Wavelet packets Support vector machines Matching pursuit algorithms Biometrics Humans Machine intelligence Surveillance Pursuit algorithms Support vector machine classification Libraries

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