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International Conference on Information and Automation (ICIA)

作者： Cui Xu Liankui Qiu Ming Liu Bin Kong Yunjian Ge Department of Automation University of Science and Technology Hefei Anhui China Center for Biomimetic Sensing and Control Research Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China Department of Electrical and Computer Systems Engineering Monash University Melbourne VIC Australia

In this paper, we present a real-time stereo vision based pose and motion estimation system that will be used for landing an unmanned helicopter on a moving target such as a ship deck. The vision algorithm mainly consists of a feature extraction task and a pose and motion estimation task. The 2D planer target with regular features defined can significantly simplify the feature extraction task such as corner detection and feature points matching. To effectively estimate the distance between the camera carrier and target a stereo camera system is applied. By means of sub-pixel corner location the precisions of pose estimation and relative motion detection can be improved. We present results from semi-physical simulation which show that our vision algorithm is accurate and robust. The methodology provides an effective subsystem for the development of autonomous robot helicopter that will land on a given target under the guide of vision.

关键词： Stereo vision Motion estimation Helicopters Feature extraction Cameras Robot vision systems Real time systems Marine vehicles Metalworking machines computer vision

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Rule-based decision-making framework for knowledge-based anatomical landmark localization (K-BALL)

Rule-based decision-making framework for knowledge-based ana...

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IEEE International Symposium on Biomedical Imaging

作者： M.-R. Siadat H. Soltanian-Zadeh K. Elisevich Henry Ford Health System Radiology Image Analysis Laboratory Detroit MI USA Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Neurosurgery Henry Ford Health System Detroit MI USA

K-BALL is a general method for localization of anatomical phenomena of the same origin with natural discrepancies distributed over a reference space, e.g., human brain anatomical structures. In this paper, we focus on information analysis step (2nd step) of K-BALL during which landmarks extracted in its first step are evaluated. We provide a framework in which rules are automatically generated based on estimated and derived models. We show that the rules based on the derived models can improve the overall success rate of K-BALL. Each rule evaluates the extracted points by producing an intermediate confidence factor (ICNF). A total confidence factor is calculated using ICNF's to facilitate the acceptance or rejection of a set of points as landmarks of interest. Using the rules merely based on the estimated models, simulation study produced an overall success rate of 91.8%. Using the rules based on both of the estimated and derived models, this rate increased to 92.5%

关键词： Decision making Hippocampus Information analysis Data mining Humans Radiology Image analysis Radio control Process control control systems

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Robust stability condition of an uncertain networked system with delayed data dropout in both forward and feedback channels

Robust stability condition of an uncertain networked system ...

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SICE Annual Conference

作者： Hyo-sung Ahn Yangquan Chen Wonpil Yu Intelligent Task Control Research Team Intelligent Robot Research Division Electronics and Telecommunications Research Institute Daejeon South Korea Department of Electrical and Computer Engineering Center of Self-Organizing and Intelligent Systems Utah State University Logan UT USA

This paper provides stability conditions of an uncertain networked control system with both forward control signal loss and feedback output signal loss. It is assumed that both the forward control signal and the output measurement signal are intermittent independently, and the remote plant has a model uncertainty. Also, in this paper, an observer-based controller is used in the remote place because the full states are not accessible. Thus, the main research goal is to analyze the overall stability of this uncertain intermittent networked system. In the second part of this paper, we consider delay effects of both forward signal and feedback signal during the network transfer

关键词： Robust stability Delay systems Output feedback control systems Intelligent networks Intelligent robots Networked control systems Stability analysis Delay effects electrical equipment industry

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Development of Portable Wireless Brain computer Interface with Embedded Systems

Development of Portable Wireless Brain Computer Interface wi...

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2006 IEEE Biomedical Circuits and Systems Conference (BioCAS 2008)

作者： Chin-Teng Lin Hung-Yi Hsieh Li-Wei Ko May Lin Sheng-Fu Liang Department of Electrical and Control Engineering Computer Science National Chiao Tung University Hsinchu Taiwan Department of Electrical and Control Engineering Brain Research Center National Chiao Tung University Hsinchu Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

In this paper, we propose an embedded multi-task scheduling system to make the wireless brain computer interface to real-time receive electroencephalogram signal more accurate. This method we propose also can increase the flexibility of the system. Base on the method, we can change the peripheral devices easily. And the tasks are taken as modules, so it also can increase the flexibility of system programs. The proposed system integrates electroencephalogram signal amplifier technique, wireless transmission technique, and embedded real-time system. The OMAP (Open Multimedia Architecture Platform) is used as a development platform and an embedded operating system is also used.

关键词： Wireless communication Digital signal processing Electroencephalography Real time systems Band pass filters Logic gates Memory management

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AUTOMATED SEGMENTATION OF THE ARTICULAR SPACE IN MR IMAGES OF THE HIP JOINT

AUTOMATED SEGMENTATION OF THE ARTICULAR SPACE IN MR IMAGES O...

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2006 IET International Conference on Visual Information engineering

作者： M. Khanmohammadi R. A. Zoroofi Y. Sato T. Nishii K. Nakanishi H. Tanaka N. Sugano H. Yoshikawa H. Nakamura S. Tamura Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran Divsion of Image Analysis Osaka University Graduate School of Medicine Osaka Japan Department of Orthopaedic Surgery Osaka University Graduate School of Medicine Osaka Japan Department of Radiology Osaka University Graduate School of Medicine Osaka Japan

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Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy

Medical Data Mining using Particle Swarm Optimization for Te...

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Congress on Evolutionary computation

作者： M. Ghannad-Rezaie H. Soltanain-Zadeh M.-R. Siadat K.V. Elisevich Henry Ford Health System and Wayne State University Detroit MI USA Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Neurosurgery Department Henry Ford Health System Detroit MI USA

In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians and decrease decision accuracy. computerized knowledge extraction is an active area of research in medical informatics. This paper suggests a new medical data mining approach using an advanced swarm intelligence data mining algorithm. Considering medical knowledge discovery difficulties, this approach addresses common issues such as missing value management and interactive rule extraction. Here, surgery candidate selection in temporal lobe epilepsy is the main target application. However, the general idea can be applied to other medical knowledge discovery problems. Experimental results show noticeable performance improvement in the final rule-set quality while the method is flexible and fast.

关键词： Data mining Particle swarm optimization Temporal lobe Epilepsy Medical diagnostic imaging Biomedical imaging Coronary arteriosclerosis Diseases Surgery Medical services

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Converse Lyapunov theorems and robust asymptotic stability for hybrid systems

Converse Lyapunov theorems and robust asymptotic stability f...

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2005 American control Conference, ACC

作者： Cai, Chaohong Teel, Andrew R. Goebel, Rafal Center for Control Engineering and Computation Department of Electrical and Computer Engineering University of California Santa Barbara

ISBN: (纸本)0780390989

We state results on the existence of smooth Lyapunov functions for hybrid systems whose solutions satisfy a class-K script L sign script L sign estimate with respect to two measures. The class-K script L sign script L sign estimate, a natural extension of class-K script L sign estimate, is in terms of the elapsed time and the number of jumps that have occurred. The main result is that a smooth Lyapunov function exists if and only if the class-K script L sign script L sign estimate is robust. In turn, sufficient conditions for robustness are given. Special cases include systems with compact attractors. Most of the results parallel, and unify, what has been developed previously for differential inclusions and difference inclusions. © 2005 AACC.

关键词： Hybrid computers

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Decoy-state quantum key distribution with two-way classical postprocessing

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Physical Review A 2006年第3期74卷 032330-032330页

作者： Xiongfeng Ma Chi-Hang Fred Fung Frédéric Dupuis Kai Chen Kiyoshi Tamaki Hoi-Kwong Lo Center for Quantum Information and Quantum Control Department of Physics and Department of Electrical & Computer Engineering University of Toronto Toronto Ontario Canada M5S 1A7 Département IRO Université de Montréal Montréal Québec Canada H3C 3J7 NTT Basic Research Laboratories NTT Corporation 3-1 Morinosato Wakamiya Atsugi-Shi Kanagawa 243-0198 and CREST JST Agency 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan

Decoy states have recently been proposed as a useful method for substantially improving the performance of quantum key distribution (QKD) protocols when a coherent-state source is used. Previously, data postprocessing schemes based on one-way classical communications were considered for use with decoy states. In this paper, we develop two data postprocessing schemes for the decoy-state method using two-way classical communications. Our numerical simulation (using parameters from a specific QKD experiment as an example) results show that our scheme is able to extend the maximal secure distance from 142km (using only one-way classical communications with decoy states) to 181km. The second scheme is able to achieve a 10% greater key generation rate in the whole regime of distances. We conclude that decoy-state QKD with two-way classical postprocessing is of practical interest.

关键词： Quantum theory

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Using Novel MEMS EEG Sensors in Detecting Drowsiness Application

Using Novel MEMS EEG Sensors in Detecting Drowsiness Applica...

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2006 IEEE Biomedical Circuits and Systems Conference (BioCAS 2008)

作者： Jin-Chern Chiou Li-Wei Ko Chin-Teng Lin Chao-Ting Hong Tzyy-Ping Jung Sheng-Fu Liang Jong-Liang Jeng Brain Research Center National Chiao Tung University Hsinchu Taiwan Department of Electrical and Control Engineering National Chiao-Tong University Hsin-Chu Taiwan China Institute of Neural Computation University of California La Jolla CA USA Department of Biological Science and Technology National Chiao Tung University Hsinchu Taiwan

Electroencephalographic (EEG) analysis has been widely adopted for the monitoring of cognitive state changes and sleep stages because abundant information in EEG recording reflects changes in drowsiness, arousal, sleep, and attention, etc. In this study, Micro-Electro-Mechanical Systems (MEMS) based silicon spiked electrode array, namely dry electrodes, are fabricated and characterized to bring EEG monitoring to the operational workplaces without requiring conductive paste or scalp preparation. An isotropic/anisotropic reactive ion etching with inductive coupled plasma (RIE-ICP) micromachining fabrication process was developed to manufacture the needle-like micro probes to pierce the stratum corneum of skin and obtain superior electrically conducting characteristics. This article reports a series of prosperity testing and evaluations of continuous EEG recordings. Our results suggest that the dry electrodes have advantages in electrode-skin interface impedance, signal intensity and size over the conventional (wet) electrodes. In addition, we also developed an EEG-based drowsiness estimation system that consists of the dry-electrode array, power spectrum estimation, Principal Component Analysis (PCA)-based EEG signal analysis, and multivariate linear regression to estimate driver's drowsiness level in a virtual-reality-based dynamic driving simulator to demonstrate the potential applications of the MEMS electrodes in operational environments.

关键词： Drowsiness Estimation Dry Electrode Electroencephalogram Micro-electro-mechanical Systems Principle Component Analysis

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Pedestrian detection system

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International Journal of Fuzzy Systems 2005年第2期7卷 45-52页

作者： Lin, Chin-Teng Chung, Jen-Feng Pu, Her-Chang Department of Computer Science Engineering National Chiao Tung University 1001 Ta Hsueh RD. Hsinchu 300 Taiwan Department of Electrical and Control Engineering Taiwan College of Electrical Engineering and Computer Science Taiwan Brain Research Center NCTU Taiwan IEEE Taiwan Tau Beta Pi Eta Kappa Nu Phi Kappa Phi Honorary Societies United States Department of Electrical and Control Engineering NCTU Taiwan

In this paper, we propose a new pedestrian detection algorithm, and use it to develop a real-time pedestrian detection system. The pedestrian detection algorithm can be functionally partitioned into two parts: moving object segmentation and pedestrian recognition. In moving object segmentation, we segment the moving objects in the scene by modified temporal differencing method. This method combines general temporal differencing method with detection nets. In pedestrian recognition, we obtain multi-type wavelet templates from input images. Interest points are extracted from wavelet templates. Then, feature points are extracted by statistical method from interest point templates. Finally, these feature points are fed into a trained multilayer back-propagation neural network. The output of the neural network implies the result - pedestrian or non-pedestrian. From experiments, accuracy rate of recognition achieves 95%. We implement this algorithm in a real-time pedestrian detection system. The system can detect pedestrians in the scene in real time. The pedestrian detection rate is 92.58%. © 2005 TFSA.

关键词： Algorithms

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