IEEE Catalog Number: CFP08INI ©2008 IEEE

IEEE Catalog Number: CFP08INI

ISBN: 978-1-4244-2171-8

ISSN: 1935-4576

©2008 IEEE

Authorized licensed use limited to: Universitatsbibliothek der TU Wien. Downloaded on February 2, 2009 at 04:49 from IEEE Xplore. Restrictions apply.

Table of Contents

SS-TCL : Tracking, communication and laser technology

Actuated Voltage Shift Mechanisms of MEMS Capacitive Switch Based on

Distributed Phase ShifterJia-hui Fu, Guo-hui Yang, Qun Wu 20

A Hierarchical and Partial-distributed Localization Scheme for Ad-hoc Wireless

Sensor NetworksLelin Zou, Zhiwen Zhao, Yuanqing Zheng 25

Study on photonic crystal filter for detecting the stimulated scattering signals in

atmosphereYuliang Zhang, Zhiwen Zhao, Fang Liu 30

Research on Channel Estimation for OFDM Receiver Based on IEEE 802.11aYuan Huimei, Ling Yingzhuan, Sun Hao 35

Optical Analysis for the Laser Scanning SystemTao Lv, Weihai Chen, Jianbin Zhang, Lihong Xu 40

Multi-Vision Information Fusion of a Laser Scanning SystemLihong Xu, Weihai Chen, Weiyang Song, Jianhua Wang 46

SS-IPSC : Image processing and system control

Color Map-Based Image FusionMohammed Hossny, Saeid Nahavandi, Doug Creighton 52

From Character Animation to Robot MotionShusong Xing, Huanyun Zhou 57

Biologically Inspired Robot Behavior Design Shusong Xing, Jiefeng Hua 63

Development and Application of Coastline Fractal Interpolation Computing

System Based on GIS and Fractal TheoryJiang Zhou, Pei-wu Li 68

Development of Urban Land Grading Information System Based on Component

GISJiang Zhou, Pei-wu Li 74


Mathematical model of coordinate transformations for 3D Depth-of-field

information collection systemLixia Rong, Weihai Chen, Shouqian Yu, Yabin Liu 80

An Adaptive Speed-adjustable Scheme for 3D Laser Scanning Based on FPGA

and DSPWeiyang Song, Weihai Chen, Jingmeng Liu, Lihong Xu 86

Research on the Architecture of Automatic Meter Reading in Next Generation

NetworkLi Li, Xiaoguang Hu, Jian Huang, Ketai He 92

SS-EIS : Embedded and Intelligent Systems

A High-speed DAC module Designed for Imaging RadarLi Wei, Wang Jun, Lei Peng 99

SVM Multiple Non-linear Regression for Moisture Content DectectingGuo-hui Yang, Qun Wu, Yu Jiang 103

A Novel Fusion Method for DR /GPS Integrated Navigation SystemSantong Zhang, Shiwu Yang 108

Research on fast and accurate occlusion detection technology of augmented

reality systemZhang Jinling, Sun Hanxu, Jia Qingxuan, Yao Fusheng 111

Research of SoPC-Based Reconfigurable Machine Tools ControllerWei Hongxing, Wang Songbai, Sun Kai, Chen Youdong, Wang Tianmiao 117

Research on ReconfigurableRobot Controller Based on ARM and FPGAWei Hongxing, Li Chengcheng, Chen Diansheng, Wang Jun, Wang Tianmiao 123

Kinematics Control for a 6-DOF Space Manipulator Based on ARM Processor

and FPGA Co-processorZheng Yili, Sun Hanxu, Jia Qingxuan, Shi Guozhen 129

A New Lightweight Database Encryption Scheme Transparent to ApplicationsLianzhong Liu, Jingfen Gai 135

A Framework for Business-Oriented Security AuditLianzhong Liu, Wenli Jiang, Qiang Huang 141

Hardware Circuit Design of NC System Based on ARM and FPGAJingmeng Liu, Weihai Chen, Youzhu Ling, Tianmiao Wang 147


Multi Sensor Data Fusion Method Based on Fuzzy Neural NetworkYouzhu Ling, Xiaoguang Xu, Lina Shen, Jingmeng Liu 153

SS-RF :　RF Devices Design and　Wireless Technology

Automated Robot Cell for EBiD-based Nano-AssemblyChristian Stolle, Sergej Fatikow 　　　　　　 160

Design of RF MEMS Phase Shifter Based on Saw-shaped CPWKai Tang, Qun Wu, Guohui Yang, Xun-jun He, Jiahui Fu, Lewei Li 　　　 166

A Novel Design of RF-MEMS Phase Shifter　 Based on Bridge-like Coplanar

Waveguide 　　　　　　　171

Lu-kui Jin, Qun Wu, Kai Tang, Xun-jun He, Jiahui Fu, Fang Zhang, Jongchul LeeModeling

Technique for Down-state of RF MEMS Phase Shifter Based on Artificial Neural

NetworkGuo-hui Yang, Qun Wu, Jia-hui Fu, Kai Tang, Xun-jun He 　 176

Fully-integrated CMOS Power Amplifier Design for WiMAX Application with

Semi-lumped TransformerBo-shi Jin, Qun Wu, Guohui Yang, Fanyi Meng, Jiahui Fu, Kai Tang 　 181

New Symbol Synchronization Algorithms for OFDM Systems Based on IEEE

802.11aYuan Huimei, Hu Xiaoguang, Ling Yingzhuan 186

Implementation of CCK Based on DSP for a WLAN TransceiverPeng Lei, Jun Wang, Wei Li 　　　　　　　　　 192

An Organization-OrientedModel for Federated Identity Management and Its

Application　

Lianzhong Liu, Junxiu Gao 197

A Trusted Role-Based Access Control Model for Dynamic Collaboration in a

Federated EnvironmentLianzhong Liu, Peng Liu 203

SS-LIE : Logistics and Industry Engineering

Operation Analysis of Headend Process Facility Using Discrete Event Simulation

HyoJik Lee,Sung Hyun Kim,Hee Sung Park,Chang Hwan Choi,Ji Sup Yoon,Byung Suk Park 210


Customer-Oriented Group Maintenance Model for Unreliable Service SystemGia-Shie Liu 215

Conceptual Design of Rail Transit Based Urban Logistics Delivery SystemKetai He, Juping Shao, Yubo Liu, Shaohua Dong 221

Process Abstraction and its Applications in Transportation SystemsKe Huang, Zhihong Li, Benjamin H.-Y. Koo 227

Improved Genetic Algorithm for Variable Fleet Vehicle Routing Problem with

Soft Time WindowQinghua Zhang, Yao Liu, Guoquan Cheng, Zhuan Wang, Haiqin Hu, Kui Liu 233

Code reuse based on information items pool and application in WMSQinghua Zhang, Haiqin Hu, Guoqian Cheng, Zhuan Wang, Yao Liu 239

Evaluation Model of Regional Logistics Competence Based on Hierarchy and

Fuzzy DecisionJuping Shao, Ketai He, Shaohua Dong, Lihua Wu, Tianyun Ma, Dong Wang 245

SS-DES : Dependable Embedded Systems

Safety Supervision LayerGeorg Hartner, Andreas Gerstinger 252

Modular Certification Support - the DECOS Concept of Generic Safety CasesEgbert Althammer,Erwin Schoitsch,Gerald Sonneck,Henrik Eriksson,Jonny Vinter 258

Outboard Flaps Control System based on the Avionics Deterministic

Fault-Tolerant Data Bus LTTPLeBel Kitoko, Lothar Klein, Georg Ried, Ulrich Zanker 264

IntegratingSafety and Multimedia Subsystems on a Time-Triggered

System-on-a-ChipRoman Obermaisser, Bernhard Frömel, Christian El-Salloum, Bernhard Huber 270

SS-IEC : Future Developments of IEC 61499 Standard

Considering IEC 61131-3 and IEC 61499 in the context of Component

FrameworksChristoph Sünder, Alois Zoitl, James H. Christensen, Heinrich Steininger, Josef Fritsche 277

Framework for Distributed Industrial Automation and Control (4DIAC)Thomas Strasser, Martijn Rooker, Gerhard Ebenhofer, Alois Zoitl, Christoph Sünder, Antonio

Valentini, Allan Martel 283


On Comparisons of the ISaGRAF implementation of IEC 61499 with FBDK and

other implementationsValeriy Vyatkin, Julien Chouinard 289

Implementation Model Alternatives for IEC 61499 Function Block NetworksKleanthis Thramboulidis, George Doukas 295

Defnition of the Execution Model Used in the Fuber IEC 61499 Runtime

EnvironmentGoran Cengic, Knut ÅKesson 301

Dynamic Reconfiguration of two Benchmarks Production SystemsMohamed Khalgui, Hans-Michael Hanisch 307

An Execution Semantic For Reconfigurable Manufacturing SystemsMohamed Khalgui, Hans-Michael Hanisch 315

SS-ITE : IT and Energy : Applications and Test Beds

KNIVES: A Distributed Demand Side Management System - Integration with

ZigBee Wireless Sensor Network and Application -Toshihiko Handa, Akihiro Oda, Tomokazu Tachikawa, Junichi Ichimura, Yuji Watanabe, Hiroaki

Nishi 324

Structural Health Monitoring System Considering Fault-toleranceYoshinao Matsushiba, Hiroaki Nishi 330

Cooperative Distributed Demand Control by Environment Sensor Network -

Estimating Number of People by CO2 Concentration -Tomokazu Tachikawa, Akihiro Oda, Toshihiko Handa, Junichi Ichimura, Yuji Watanabe, Hiroaki

Nishi 336

A simulation platform for distributed energy optimization algorithmsPeter Palensky, Friederich Kupzog, Adeel Abbas Zaidi, Kai Zhou 342

SS-ISS : Intelligent Sensing and Sensors

An Enhanced Parking Lot Service Model Using Wireless Sensor NetworkJung-Wook Lee, Sae-Sol Choi, Yoon-Bong Yoo, Jae-Jeung Rho 349

EEG Signal Classification Based on PCA and Fuzzy InferenceSo-Youn Park, Ju-Jang Lee 355

Bayesian Network-based Non-parametric Compact Genetic AlgorithmJoon-Yong Lee, Soung-Min Im, Ju-Jang Lee 359


Comfortable Environments for Mental Work by Suitable Work-rest schedule:

Mental Fatigue and RelaxationLanlan Chen 365

SS-IR : Intelligent Robot

Hierarchical Path Planning Approach for Mobile Robot Navigation under the

Dynamic EnvironmentZeng Bi, Yang Yimin, Yuan Wei 372

Locomotion Pattern Generation of Semi-Looper Type Robots Using Central

Pattern Generators Based on Van der Pol OscillatorsKeigo Watanabe, Akihito Tajima, Kiyotaka Izumi 377

A Switching Control of Underactuated Manipulators by Introducing a Definition

of Monotonically Decreasing EnergyKiyotaka Izumi, Yuichi Kamada, Keisuke Ichida, Keigo Watanabe 383

Simulation of Mobile Robot Motion Considering Uncertainties in Robot ModelNak Yong Ko, Dong Jin Seo, Gwang Jin Kim, Yongseon Moon, Youngchul Bae 389

Damage Reduction of Robot at the Emergence Crash by modifying StiffnessTae-Yong Choi, Ju-Jang Lee 395

EvolvingArtificial Neural Network using Simple Augmenting Weight Matrix

MethodDong-Hyun Lee, Ju-Jang Lee 401

Intelligent Vision Sensor for the Robotic Laser Welding 406

Chang-Hyun Kim, Tae-Yong Choi, Ju-Jang Lee, Jeong Suh, Kyoung-Taik Park, Hee-Shin Kang

Localization and Map-building of Mobile Robot Based on RFID Sensor Fusion

SystemByoung-Suk Choi, Joon-Woo Lee, Ju-Jang Lee 412

Development of Robot and Navigation Techniques for Humanitarian DeminingMaki Habib 418

SS-IRA : Industrial Robot and Its Application

Performance Test of Industrial Dual Arm RobotKyoung Taik Park, Chan Hun Park, Young Jae Shin 425


Design and Kinematics Analysis of Dual Arm Robot Manipulator for Precision

AssemblyChanhun Park, Kyoungtaik Park 430

Performance Test of Large Telescopic Robot for LCD Glass HandlingYoung-Jae Shin, Kyoung-Taik Park, Jung-Hoon Ha, Sang-Kyun Shim 436

Remote Control System of Industrial Field RobotsSoon-Young Yang, Soon-Kwang Kwon, Sung-Min Jin 442

A Low Cost Map Building Sensor System for Mobile RobotHyun-Seong Choi, Woong-Keun Hyun 448

SS-PCCT : Practice of Computational Intelligence Techniques in

Engineering

Robot Calibration Based On Multi-Thread Particle Swarm OptimizationLi Aiguo 454

Industry Robot and External Axle Calibration Using Particle Swarm Optimization

AlgorithmHuang Jin, Ma Zi, Hu Ying, Wang Yang, Yu Shuanghe 458

A Smart Supervisory Control System Framework for a Sugar Mill Crystallisation

StageRoland Dodd, Andrew Chiou, Xinghuo Yu, Ross Broadfoot 463

Hybrid Convolutional Neural NetworksIveta Mrazova, Marek Kukacka 469

Anfis controller for double inverted pendulumSheng Qiang 475

Adaptive Fuzzy Trajectory-Tracking Control of Uncertain Nonholonomic Mobile

RobotsShuanghe Yu, Shuang Liu, He Xu 481

Neural Network Modeling and Generalized Predictive Control for an Autonomous

Underwater VehicleJianan Xu, Mingjun Zhang 487

SS-PAC : Production Automation and Control, Innovative Future

Manufacturing


Learning the Inverse Kinematics of Robot Manipulator using the Bees AlgorithmD.T. Pham, M. Castellani, A. A. Fahmy 493

Measuring the Effort of a Reconfiguration ProcessAmro Farid, Wuttiphat Covanich 499

An Attempt to Obtain Scheduling Rules of Network-based Support System for

Decentralized Scheduling of Distributed Production SystemsHisaaki Yamaba, Shinichi Matsumoto, Shigeyuki Tomita 506

Research Topics in Manufacturing - The I*PROMS PAC Delphi Study -Michael Hoepf, Harry Valsamos 512

AmI-based Production Systems: Configuration of Sequential Process Flow and

SoA-based DiagnosisMartin Feike, Nataliya Popova, Armando Walter Colombo 517

SS-ISST : Information Security, Safety and Trust

Application of Support Vector Machine for Equipment Reliability Forecasting

Feng Ding 526

Object-Oriented Analysis and Design of Elliptic Curve CryptosystemGuicheng Shen, Xuefeng Zheng 531

Dynamic Trust Model Applied In Mobile AgentZhen Ye, Weiwei Song, Dayong Ye, Lei Yue 536

Design and evaluation of a client-friendly cross-realm framework for Kerberos 5Ken'ichi Kamada, Shoichi Sakane, Kazunori Miyazawa, Nobuo Okabe 541

Multipath Key Management with Aggregation in Sensor NetworksSoonhwa Sung 547

Detecting Code Theft via a Static Instruction Trace Birthmark for Java MethodsHeewan Park, Seokwoo Choi, Hyun-il Lim, Taisook Han 551

An Integrated Framework of the Modeling of Failure-Detection and

Fault-Correction Processes in Software Reliability AnalysisJung-Hua Lo 557

A Dynamic-entropy Algorithm for Fault IsolationWang Dong 563

SCADA System Security: Complexity, History and New DevelopmentsNing Cai, Jidong Wang, Xinghuo Yu 569

Domain based Security for Mobile AgentsNajmus Saqib Malik, Michael Sonntag, Friedrich Kupzog 575


Cryptanalysis on an Enhanced Identity-based Deniable Authentication ProtocolMeng Hui Lim, Sanggon Lee, Hoonjae Lee 581

Integrating Network Misuse and Anomaly PreventionYoseba Penya, Pablo García Bringas 586

A Proposal Framework for Adoption of Electronic Payment Services by Iranian

CustomersAbbas Keramati, Bahar Hadjiha, Mohamad Saremi 592

SS-SCT : Sensing and Communication Technologies

A Nonwhitening Post Filter to Improve the Performance of Sound Source

SeparationAugie Widyotriatmo, Harijono A. Tjokronegoro, Keum-Shik Hong 599

Redeployment Design Algorithm for Enhancing Channel Capacity in Multi-Agent

SystemsFeng-Li Lian, Jong-Hann Jean, Hou-Tsan Lee, Ko-Hsin Tsai 604

A High Dynamic Range SiGe HBT Variable Gain Amplifier for WCDMA

ApplicationsJunning Gan, Wanrong Zhang, Hongyun Xie, Dongyue Jin, Pei Shen, Jia Li, Lijian He, Wei

Zhang 610

Design a Wireless Sensor Network for Methane Monitoring System.Xuhui Zhang, Sunan Wang 614

Measurement and Analysis of Heart Signal Based on the Pressure SensorXu Wang, Jingjing Jin, Shilong Li 619

Application of Daubechies-Wavelet Based MRTD Schemes to Electromagnetic

ScatteringJiang Yu, Yu Shao-peng, Gao Hong-you, Xiao Hong, Teng Wei, Liu Xing-peng 623

Adaptive Optimization in A-D Converter SystemCe Fu 627

An Efficient Optimization for Passive Filter DesignCe Fu 631

A New Configuration of Differential CMOS LNAXuan Chen, Quanyuan Feng 635

An Automated Measurement System for Determining Magnetization

Characteristics of Switched Reluctance MotorsShun-Chung Wang, Yi-Hua Liu 639


A Wireless Escape System for Industrial Accidents Using Ad Hoc PositioningTengyue Zou, Huiyou Chang, Yang Yi 645

The Influence of Different Grid Length to the FDTD CalculationYu Jiang, Hong-you Gao, Shao-peng Yu, Hong Xiao, Xing-peng Liu, Wei Teng 651

A Real-time Finite Line Detection System Based on FPGA 655

Dongkyun Kim, Seung Hun Jin, Nguyen Tuong Thuy, Ki Hoon Kim, Jae Wook Jeon

ZigBee-based Wireless Extension of FOUNDATIO FieldbusTang Zhong, Zeng Peng, Yu Haibin, Wang Hong 661

Robust Filtering for Uncertain Discrete-Time Systems with Uncertain Noise

Covariance and Uncertain ObservationsShadyMohamed Korany Mohamed, Saeid Nahavandi 667

Real-time Sound Source Localization System based on an FPGASeunghun Jin, Dongkyun Kim, Hyung Soon Kim, Chang Hoon Lee, Jong Suk Choi, Jae Wook

Jeon 673

A Detailed Simulation Study for Troposcatter ChannelChen Shuxin, Gu Hailong 678

A Fast Encoding Algorithm for Vector Quantization Based on Haar Wavelet

TransformJiann-Der Lee, Yaw-Hwang Chiou 683

OCARI: Optimization of Communication for Ad hoc Reliable Industrial networksTuan Dang, Catherine Devic 688

A Study on the In-orbit Environment of a GPS Receiver for Low/Medium

Altitude SatellitesSung-in Chung, Hyo-sung Lee, Heung-ho Lee 694

Analysis of the Effects of High-energy electrons on a Low Earth Orbit Satellite

PartsSung-in Chung, Heung-ho Lee 700

Improved Method for Solving Permutation Problem of Frequency Domain Blind

Source SeparationWeihua Wang, Fenggang Huang 703

Packet Classification for Network Processors in WSN Traffic using ANNR. Rajkamal, P. Vanaja Ranjan 707

An Approach to Enhance Mobile Multicast Using Context TransferAisha Hassan,Wan Haslina Hassn 711

On Non-integer Order Rational Model IdentificationWu Defeng, Li Aiguo, Ma Zi, Zhu Quanmin 716


Nano-Level 3-D Measurement System Using 3-Wavelength Laser Light

InterferenceSeiji Hata, Junichiro Hayashi, Ichirou Ishimaru, Sigeaki Morimoto 721

Theoretical and Experimental Study on Parameters Setting of Ant Colony

OptimizationYanPeng Liu, Yongsheng Yu, Wanjun Tian, Mingguang Wu, Jixin Qian 726

Multi-Agent System Coordination Architecture and Its Use in Electric Power

Decision Support SystemLianzhong Liu, Xiangrong Zu, Ruizhi Xu 731

Objective Function of Semi-Supervised Fuzzy C-Means Clustering AlgorithmChunfang Li, Lianzhong Liu, Wenli Jiang 737

SS-SOA Service-Oriented Architecture

Service-Oriented Control Architecture for Reconfigurable Production SystemsJ. Marco Mendes, Paulo Leitão, Armando W. Colombo, Francisco Restivo 744

Service-oriented Process Control using High-Level Petri NetsJ. Marco Mendes, Paulo Leitão, Armando W. Colombo, Francisco Restivo 750

Roadmap to adopting OPC UATom Hannelius, Mikko Salmenperä, Seppo Kuikka 756

A Generic Communication Interface for DPWS-based Web ServicesLuis Ribeiro, Jose Barata, Armando Colombo, Francois Jammes 762

Integration of Multi-Agent Systems and Service-Oriented Architecture for

Industrial AutomationVladimir Villaseñor Herrera, Axel Bepperling, Andrei Lobov, Harm Smit, Armando W. Colombo,

Jose L. Martinez Lastra 768

A Web Services-enabled B2B Integration Approach for SMEs Wen Jing Yan, Puay Siew Tan, Eng Wah Lee 774

Modelling interaction-aware services from an orchestration viewpoint

Corina Popescu, Jose L.Martinez Lastra 780

Web-based Vertical Information Services for Mining Right TradeHaizhong An, Na Cui 786

Service Oriented Architecture in Developing of Loosely-coupled Manufacturing

SystemsAndrei Lobov, Juha Puttonen, Vladimir Villaseñor Herrera, Rajasekaran Andiappan, Jose Luis

Martinez Lastra 791


Device and Service Templates for the Devices Profile for Web ServicesAndreas Bobek, Elmar Zeeb, Hendrik Bohn, Frank Golatowski, Dirk Timmermann 797

SS-SCML : Supply Chain Management and Logistics

Strategic Supply Chain Positioning (SSCP) Methodology Development in SMEs

ContextRoland Lim, Laura Xu, Bin Ma 803

A Robust Pricing/Lot-sizing Model and A Solution Method Based on Geometric

ProgrammingSungmook Lim, Woo-Je Kim 808

An Implementation of Context-aware Partner Selection to Support Supply Chain

CollaborationsP.S. Tan, E.W. Lee, K. Mous, S.S.G. Lee, A.E.S. Goh 812

A Simulation System for Aerospace Spare Inventory Management and Decision

SupportKong-wei Lye, Lai-peng Chan, Xue-ming Yuan 819

Research on Dynamic Scheduling Operation Method in Supply Chain Based on

Ant Colony OptimizationWang Xu 825

Ontology-based Information Integration Framework for Mechatronics System

Multi-disciplinary DesignLuyan Bi, Zongxia Jiao, Shengtao Fan 831

A Mixed Integer Programming Model for Production Inventory Network DesignXue-Ming Yuan, Soumen Saha 837

Virtual Organization for Supply Chain IntegrationWilliam Y.C. Wang, Hing Kai Chan 843

To estimate the stage completion time for a two-stage flexible flow shop with

dynamic job arrivalMing-Hsien Yang, Shu-Hsing Chung, Ching-Kuei Kao 849

A Generic Model for Crossdock Truck Scheduling and Truck-to-Door Assignment

ProblemsMojtaba Shakeri, Malcolm Yoke Hean Low, Zhengping Li 857

Address Supply Chain Visibility from Knowledge Management Perspective

Allan N S Zhang 865


Optimal Decision-making on Product Ranking For Crossdocking/Warehousing

OperationsZheng Ping Li 871

Supplier Performance Measurement in a Supply ChainLaura Xu, Bin Ma, Roland Lim 877

On Wheat Storage Period Estimation Using Markov_ chain AnalysisGe Wang, Qin Li, Jane You 882

SS-MR Mechatronics and Robotics

Study of sliding mode control for Stewart platform based on simplified dynamic

modelQiang Wu, Juan Chen, Zhiyong Tang 889

Accurate prediction of interception positions for catching thrown objects in

production systemsDennis Barteit, Heinz Frank, Friederich Kupzog 893

A Method to Find Local Planar Region from 3D Range DataSung-Jo Kim, Dong Joong Kang 899

Motion Control Design of the Lower-Limb Mobile Training RobotSyh-Shiuh Yeh, Hung-Hsiu Yu 904

Research on Computer Control System of Close Precision WindingWei Jian 910

Control of Commutation of SR Motor Using its Magnetic Characteristics and

Back-of-Core Saturation EffectsNerey Mvungi 915

Nonlinear Parameter Neuro-Estimation for Optimal Tuning of Power System

StabilizersSeung-Mook Baek, Jung-Wook Park 921

A Novel Adaptive Current Regulator for Permanent Magnet Synchronous Motor

Based on Modified Current DynamicsHongZhe Jin, JangMyung Lee 927

System Modeling and Stability Design for Peak Current-mode Buck Power

ConverterXiao-fei Chen, Xue-cheng Zou 933

Unfolding Enhancements Speed FSM Based SimulationP. J. Radcliffe 939


SS-BNA : Buildings, Networks and Automation

Port choice behavior in Asia - a network perspectiveJoyce M.W. Low, Loon Ching Tang, Xue Ming Yuan 946

Design of One-channel Embedded Network Video ServerShurong Chen, Kaiyu Xu, Haiyun Gu 952

A Performance Analysis ofthe Ethernet Nets for Applications in Real-Time: IEEE

802.3 and 802.3 1QRicardo Valentim, Gláucio Brandão, Ana Guerreiro 956

NCS Flexible Experimental System with Network Load ControlledZaiping Chen, Nan Yang, Enzeng Dong, Chunxue Liu 962

Gateway System for Automotives: LIN, CAN, and FlexRaySeung-Han Kim, Suk-Hyun Seo, Jin-Ho Kim, Tae-Youn Moon, Sung-Ho Hwang, Key-Ho Kwon,

Jae-Wook Jeon 967

Gateway-free Integration of BACnet and KNX using Multi-Protocol DevicesWolfgang Granzer, Wolfgang Kastner, Christian Reinisch 973

MP-HA: Multicycles Protocol for Hospital Automation over Multicast with IEEE

802.3Ricardo Valentim, Antônio Morais, Ana Guerreiro, Gláucio Brandão, Carlos Paz de Araújo 979

A hierarchical position based routing scheme for data centric wireless sensor

networksSajjad Madani, Daniel Weber, Stefan Mahlknecht 985

Research of Intelligent Building Control Using an Agent-based ApproachJianmin Duan, Fan Lin 991

A Tracking Mechanism Using Agents For Personal Mobility In Ip NetworksWan H. Hassan 995

Mathematical Analysis of Prioritized Data Transmission in the Foundation

FieldbusYong HeeLee, Seung Hwan Min, Seung Ho Hong 1000

SS-CCI : Cognitive and Computational Intelligence in Industrial

Informatics

A Simulation-based Approach to Job Shop Scheduling with BottlenecksRui Zhang, Cheng Wu 1007


The Self-Organization Genetic Algorithm Based on the Mutation with Cycle

ProbabilitiesBaojuan Huang, Jian Zhuang, Dehong Yu 1013

Bee Colony Optimization with Local Search for Traveling Salesman ProblemLi-Pei Wong, Malcolm Yoke Hean Low, Chin Soon Chong 1019

Study of a New Online Least Squares Support Vector Machine Algorithm in Gas

PredictionXiao-hu Zhao, Ke-ke Zhao 1026

Using Goal-oriented Paradigm for Community ComputingSehyeong Cho 1031

Forecasting Exchange Rate by Weighted Average Defuzzification Based on

NEWFMSang-Hong Lee, Joon S. Lim 1036

Neuro-Symbolic Networks: Introduction to a New Information Processing

PrincipleRosemarie Velik, Dietmar Bruckner 1042

Natural Histogram for Very Small Population StatisticsRadu D. Rugescu, Valentin Silivestru, Sorin Aldea 1048

Wavelet Neuron Selection Method for ECG Data CompressionXinping Yan, Yongming Yang 1054

Optimization of the Neural Structure based on Domain Expert Previous

Knowledge via GA and Sensitivity FactorsFabrício Bittencout, Luis Zárate 1058

A New Approach in Discrete Chaos System Control by Differential Evolution

AlgorithmFei Gao, JuJang Lee 1064

A New Approach in Synchronization of Uncertain Chaos Systems Through

Particle Swarm OptimizationFei Gao, JuJang Lee 1069

Knowledge-based Multi-Agent Architecture for Dynamic Scheduling in

Manufacturing SystemsMunir Merdan, Pavel Vrba, Gottfried Koppensteiner, Alois Zoitl 1075

A System Scheme of 3D Object Reconstruction From Single 2D Graphics Based

on Neural NetworksGuangmin Sun, Lei Xu, Deming Chen, Gang Li, Jing Wang 1081


A Simulation Platform for Cognitive AgentsTobias Deutsch, Tehseen Zia, Heimo Zeilinger, Roland Lang 1086

Network of Cooperating Smart Sensors for Global-View Generation in

Surveillance ApplicationsDietmar Bruckner, Rosemarie Velik, Gerhard Zucker 1092

A Novel Hybrid Wavelet Neural Network and Its Performance EvaluationY. Z. Zhao, N. K. Vuong, X. Li 1097

A hybrid Architecture for Function ApproximationHASSAB ELGAWI Osman 1103

SS-DENC : Distributed, Embedded and Networked Control

Evaluation of Embedded RBF Neural Chip with Back-propagation Algorithm for

Pattern Recognition TasksJeong S. Kim, Seul Jung 1110

An Improved Window Control Scheme Over FAST TCPFuzhe Zhao, Jianzhong Zhou, Zhimeng Luo, Yang Xiao 1116

Model-Driven Embedded Systems Design Environment for the Industrial

Automation SectorThomas Strasser, Christoph Sünder, Antonio Valentini 1120

Networked Control Systems by PID Controller Improvement of Performance

Degradation Caused by Packet LossRyotaro Okano, Tetsuya Ohtani, Akira Nagashima 1126

Automatic Model Generation of IEC 61499 Function Block Using Net

Condition/Event SystemsCheng Pang, Valeriy Vyatkin 1133

Development of an Embedded Controller for BioCD InspectionsFu-Shin Lee, Rou-Jiun Shiu, Ming-Da Chiang 1139

A Fault-tolerantGateway for In-vehicle Networks 1144

Suk-Hyun Seo, Tae-Youn Moon, Jin-Ho Kim, Key Ho Kwon, Seong-Ho Hwang, Jae Wook Jeo

A method of Task Synchronization in a distributed system using FlexRayJin Ho Kim, Suk Hyun Seo, Tae Yoon Moon, Chang Wan Son, Key Ho Kwon, Sung Ho

Hwang, Jae Wook Jeon 1149

System Structure for FPGA-Based SOPC Design Using Hard TasksJianzhaung Wang, Youping Chen, Jingming Xie, Bing Chen, Haiping Lin 1154


Powering Flexible Manufacturing Systems with Intelligent Contact-less Power

TransferM. Budhia, V. Vyatkin, G. Covic 1160

Comprehensive Formal Description of IEC 61499 Control DevicesChristoph Sünder, Ivo Gosetti, Valeriy Vyatkin, Bernard Favre-Bulle 1166

Investigating Of Embedded Virtual Instruments MiddlewareNa Wang, Huasong Min 1173

Efficient Implementation of CNC Position Controller using FPGAYaodong Tao, Hu Lin, Yi Hu, Xiaohui Zhang, Zhicheng Wang 1177

An Efficient Calibration Method for RSSI-based Location AlgorithmsRafael Pereira Pires, Lucas Francisco Wanner, Antônio Augusto Fröhlich 1183

The reusable protocol-common block that can simulate the hardware

characteristicsTae-Yoon Moon, Suk-Hyun Seo, Seung-Han Kim, Jin-Ho Kim, Key Ho Kwon, Seong-Ho

Hwang, Jae Wook Jeon 1189

An Architecture for a Fault Tolerant Highly Reconfigurable Shop FloorLuis Ribeiro, Jose Barata, Bruno Ferreira, Jorge Pires 1194

A Proxy-based Approach for Mobility Support in the DDS SystemKi-Jeong Kwon, Chooog-Bum Park, Hoon Choi 1200

Extending timed net condition/event systems with hybrid petri netsJuha Puttonen, Andrei Lobov, Jose Luis Martinez Lastra 1206

Guidelines for Evaluating the Ease of Reconfiguration of Manufacturing SystemsWutthiphat Covanich, Duncan McFarlane, Amro Farid 1214

mplementation and Evalution of Decorators for Delayed Live Streaming Video on

Remote Control SystemShinichi Hamasaki 1220

SS-SME : e-Learning for Small and Medium Enterprises SME

The Universal Knowledge Moderator for Globally Distributed and Collaborative

e-ManufacturingH.K. Lin, J.A. Harding, A.K. Choudhary 1227

Market Orientation and Strategies in E-commerce CompaniesS. H. Chien, J. J. Wu, H. F. Lai 1232


Design and Implementation of a Medical Knowledge Service System for

Cross-Organization Healthcare CollaborationYuh-Jen Chen 1238

An Evaluation Instrument for E-learning EcosystemVanessa Chang 1244

SS-EPT : Emerging Platform Technologies in Industrial Informatics

ICT and Business Alignment in Virtual OrganizationTaivo Kangilaski 1251

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A Filter Approach for Myoelectric Channel

Selection

Gernot Kvas

Institute of Computer Technology

Vienna University of Technology

and

Otto Bock Healthcare Products GmbH

Email: [email protected]

Rosemarie Velik

Institute of Computer Technology

Vienna University of Technology

Email: [email protected]

Abstract—For the control of upper limb prostheses, machinelearning algorithms are increasingly common for disriminatingdifferent patterns of the surface myoelectric signal (MES).Sophisticated myoelectric controllers usually record data frommultiple bipolar channels, placed on muscle groups of interest.The appropriate number of channels is a delicate question. Oneusually tries to minimize the amount of channels required whilemaintaining reasonable classification performance. This paperpresents a filter approach to the channel selection problem byexploiting properties of the principal component analysis. Out ofa set of channels measured on the patient, a ”good” subset is se-lected for further processing by a pattern recognition algorithm.The method is applied to data recorded from an amputee whohas undergone targeted muscle reinnervation (TMR) surgery. Itis shown that the amount of channels can be reduced with onlyminor decrease of classification performance.

I. INTRODUCTION

The myoelectric signal (MES) recorded from the surface

of the skin is currently the most viable way for self-powered

upper limb prosthesis control. Such a prosthesis system would

typically consist of two bipolar electrodes, a controller, and

the mechanical arm itself. The electrical signal generated by

contracting muscles is picked up by the two bipolar electrodes

placed on the residual limb, amplified and finally processed by

the control algorithm. The controller translates the myoelectric

signal into joint movement of the artificial limb. Commercially

available systems predominatly use a rectified and filtered

MES as an input signal to the controller as an estimation

for the mean absolute value (MAV). This control strategy

can be easily applied in a clinical setting, is robust, and well

understood.

A. Pattern Recognition

The limited information of the MAV makes it difficult to

control complex artificial limbs with a high number of joints.

Research has therefore turned to more advanced features of

the myoeletric signal for better discrimination of the muscle

state. Features extracted from the MES range from simple

time domain charateristiscs like variance, zero crossings, and

length of the waveform to frequency and time-frequency

methods such as the short-time Fourier and wavelet transforms

[1]. The next processing step after feature extraction is a

classification algorithm, or in some cases a dimensionality

reduction algorithm [2] to improve the performance of the

subsequent classifier.

B. Targeted Muscle Reinnervation

Despite the advances due to the use of pattern recognition

algorithms and more informative features derived from remain-

ing muscles, there still exists what is known as the paradox in

myoelectric control [3]: The higher the level of amputation,

the more functionality the prosthesis has to provide. However,

with a high level of amputation the number of control sites,

remaining muscles from which the MES can be recorded,

decreases and control gets less intuitive for the patient.

Kuiken et al. [4] developed a new surgery method called

targeted muscle reinnveration (TMR) to overcome this prob-

lem. With TMR, otherwise unused nerves of the lost limb are

surgically connected to muscle groups in the chest and back

area that have lost their primary task due to the ampuation,

such as the m. pectoralis major and the m. pectoralis minor

in case of a shoulder disarticulation. Intended movements of

the lost limb now directly translate to muscle activity in the

respective area. This muscle activity can again be picked up by

electrodes and translated in prosthesis movements, resulting in

a very intuitive control.

C. Channel Selection

Initially, Zhou et al. [5] proposed high-density electromyo-

gram (EMG) recordings to capture all MES activity in the

area where reinnervation has been performed. A 127-channel

array of monopolar electrodes spaced 15 mm appart was used

to record different movements from TMR patients. As the

outcome of the surgery highly depends on how nerves grow

into their new target muscles, the global view given by such a

recording helps to assess surgery success. For a later fitting of

a prosthesis however, only a small subset of channels might

be used as data bandwidth and processing power are limited

on a battery-powered artificial limb. This paper proposes a

method to select a suitable subset of channels from a larger

number of bipolar electrodes attached to a patient using a

filter method based on principal component analysis (PCA).

Bipolar electrodes have been chosen such that both the initial

set of electrodes and the subset for classification use the same

electrode type.

II. ALGORITHM

Our method can be seen as a feature selection algorithm

with the notion that we don’t operate in the feature space

after feature extraction has taken place, but rather in the orig-

inal space, the physical channels. Two approaches to feature

selection algorithms are common for pattern recognition [6]:

filters and wrappers. Filters are independent of any subsequent

pattern recognition algorithm and work by filtering features

based on some performance measure. Wrappers, as the name

suggests, wrap around the classification algorithm used to

determine feature relevance. This work uses filters, with the

PCA as the performance measure.

A. Principal Component Analysis

Principal component analysis is a common method for

dimensionality reduction [7]. Given a n-dimensional original

space, PCA performs an orthogonal projection to a lower

dimensional space while maximizing the variance of the data.

Typically, PCA is applied as follows: Let X be a n×m matrix

with m n-dimensional feature vectors. Calculate X from X by

subtracting the mean from each of the n dimensions. With the

covariance matrix C calculated from X the following relation

holds:

CU = UL (1)

Columns of U are eigenvectors ui with the corresponding

eigenvalues in the diagonal matrix L with λ1 > λ2 > . . . >

λn.

L =

λ1 0 · · · 0

0 λ2 · · · 0

......

. . ....

0 0 · · · λn

(2)

Now the eigenvectors of the k largest eigenvalues (principal

components) are chosen to form a matrix U′

, where k has a

value between 1 and n. Let h be a vector from the original

n-dimensional space. Multiplication with matrix U′

will yield

a vector size k:

hn×1U′

k×n= h

′

k×1(3)

For k = n, no dimensionality reduction is achieved, but

rather a rotation of the original vector h coordinate axes along

the directions of largest variance. k, the number of principal

components kept, is typically chosen so that a certain threshold

(e.g., 0.9 or 0.95) of the variability of the original data is

retained:k∑

i=1

λi

n∑

i=1

λi

≥ threshold (4)

For each eigenvalue λi, the corresponding eigenvector ui

is a weight vector with the n-th coefficient indicating the

contribution of the n-th variable to this eigenvalue. As can

be seen in formula (3), all variables are used for a di-

mensionality reduction and the resulting vector as such has

no physical meaning. This is not desirable for reduction of

physical variables. The approach described in [8] can be used

to circumvent this problem, where the information from the

principal components is used to find important variables in the

original data. Let λn be the smallest eigenvalue. Now, find

the largest absolute value coefficent in the eigenvector un.

The variable corresponding to this coefficient is discarded, as

this variable contributes most to the smallest and thus least

important eigenvalue. In the next step, the variable with the

largest absolute value coefficient of eigenvector un−1 that has

not been already discarded is discarded. This is repeated for

each ui until the desired number of variables remain. The

number of variables can again be determined by formula (4).

B. Channel Selection

The abovementioned method is applied to the problem of

channel selection. Our algorithm is based on two underlying

assumptions: (a.) PCA projects data such that variance is

maximized. This favours channels with high inter-movement

variance. (b.) As input to the PCA, we propose the root mean

square value of each of the recorded signals. We assume that

regions of higher myoelectric activity carry more information.

Our algorithm therefore comprises the following steps:

1) Select a number of channels n

2) For each recorded movement in a set of m movements,

calculate the RMS value of each individual channel.

3) The result is a matrix Mof the size n × m.

4) Calculate and subtract the mean from each of the chan-

nels of M , yielding M′

.

5) Perform PCA given M′

.

6) Discard channels until the desired number of channels

remains using the method described.

The result is a subset of channels based on the variance

of the RMS values calculated from all channels over a set

of different movements. The channels are chosen by their

contribution to the most important principal components.

III. METHODS

To evaluate this method, EMG data from a patient who

has undergone targeted muscle reinnervation surgery has

been recorded. The patient is a double amputee with both

transhumeral and shoulder disarticulation amputations. TMR

surgery was performed on the shoulder disarticulation side at

the Vienna General Hospital in December 2006 [9].

Starting July 2007, multi-electrode measurements to facil-

itate prosthesis fitting have been made on a regular basis.

Custom active bipolar electrodes were fitted to the patient with

a gain of 40 dB at the electrode and further filtering and ampli-

fication was performed by a custom signal conditioning board.

The data were then digitized with a National Instruments USB-

6259 data acquisition unit. The sampling frequency was set

to 3 kHz. Digital filtering to eliminate 50 Hz interference and

harmonics was carried out in software. For feature calculation,

non-overlapping windows of 512 samples were used. At the

given sample frequency, this is well within the suggested 300

ms [10] that users would still perceive as real-time.

To assess the performance of the chosen channel subset,

feature extraction and classification was implemented. Both

autoregressive coefficients (AR) and time-domain (TD) fea-

ture sets were used in the feature extraction stage. 5th-order

autoregressive coefficients were computed using the Burg

method. For time domain features, zero-crossings, waveform

length and slope sign changes were calculated. Both feature

sets are known to shown good performance when classifying

MES [11] [10]. Classification was carried out with a linear

discriminant analysis (LDA) classifier and a support vector

machine implementation [12] with a radial basis function

(RBF) kernel. It is important to note that any features relying

on RMS values, such as the relative value between channels,

were omitted on purpose to avoid a possible interdependence

with the filter method. Feature vectors were normalized before

classification.

IV. EXPERIMENTAL RESULTS

To exercise the algorithm, four datasets have been recorded

over a period of seven months while working with the patient.

For each measurement session, the patient had to perform a

list of movements. Before each movement, the movement was

demonstrated by the physiotherapist. The patient is then asked

to hold each movement for approximatley 10 seconds. Table

I shows the number of movements and maximum number of

channels used for each session.

TABLE I

MOVEMENT CLASSES AND ELECTRODE CHANNELS

Movements Channels

Session 1 7 18

Session 2 12 24

Session 3 12 24

Session 4 12 24

Recordings of each session are split into training and testing

subsets. As a single ten-second movement at the given sample

rate of 3 kHz and window size of 512 samples would yield just

58 feature vectors, ten-fold cross validation is used to achieve

a better estimation of the classifier accuracy. A testing set

and a training set from the same session allows testing the

filter algorithm without the uncertainty of separate testing and

training sets, where the ability of the patient to reproduce the

exact movement greatly influences classification accuracy. For

each of the subsets of the cross validation step, a classifier is

trained and classification accuracy determined on the test set.

The error estimates are then averaged to yield an overall error

estimate. Figures 1 to 4 show the results for the AR and TD

feature sets and LDA and SVM classifiers.

Each plot shows the mean classification error over each

movement for one to the maximum number of channels

available for this measurement session. The solid line shows

the classification error of the subset chosen by the PCA

channel selection algorithm (”good” subset). For comparison

a subset selected from the first n channels discarded by the

algorithm (dotted line) is also shown.

Each of figures 1 to 4 is organised such that Session 1

results are in the top-left subfigure, with Session 2 results in

the top-right subfigure and Session 3 and 4 in the bottom left

and right, respectively.

1 4 7 10 13 160

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(a)

1 4 7 10 13 16 19 220

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(b)

1 4 7 10 13 16 19 220

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(c)

1 4 7 10 13 16 19 220

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(d)

Fig. 1. Results for a 5-th order AR model feature set and a LDA classifier.

1 4 7 10 13 160

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(a)

1 4 7 10 13 16 19 220

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(b)

1 4 7 10 13 16 19 220

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(c)

1 4 7 10 13 16 19 220

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Channels

Cla

ssific

ation E

rror

(d)

Fig. 2. Results for a TD feature set and a LDA classifier.

Figures 1 to 4 show similar results, independent of the

feature set and classifier. For a small number of channels

neither of the two subsets displayed can guarantee a reasonable

classification accuracy. For an increasing number of channels

however, the ”good” subset quickly shows reasonable accuracy

within 10% of the classification performance of the maximum

number of channels and not much performance improvement

1 4 7 10 13 160

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(a)

1 4 7 10 13 16 19 220

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(b)

1 4 7 10 13 16 19 220

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(c)

1 4 7 10 13 16 19 220

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(d)

Fig. 3. Results for a 5-th order AR model feature set and a SVM classifierwith RBF kernel.

1 4 7 10 13 160

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(a)

1 4 7 10 13 16 19 220

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(b)

1 4 7 10 13 16 19 220

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(c)

1 4 7 10 13 16 19 220

0.2

0.4

0.6

0.8

1

Channels

Cla

ssific

ation E

rror

(d)

Fig. 4. Results for a TD feature set and a SVM classifier with RBF kernel.

can be seen for a larger number of channels. Naturally, when

subsets start to overlap, as can be seen for a higher number of

channels, the performance of both ”good” and ”worse” subset

becomes similar.

V. CONCLUSION

We have presented a filter method to select a subset of MES

channels from a larger number of channels measured on a

patient with the purpose to maintain reasonable classification

performance over a set of movements when compared to the

entire set of channels. We have shown that by using principal

component analysis as our performance measure for a filter

method, this can be achieved.

The results indicate that a much smaller number of channels

is sufficient when appropriate channels are chosen. These are

important inputs when designing a system for artifical limb

control. Less channels and therefore less electrode contacts

simplify the process of socket fitting, reduce the number of

hardware for data acquisition and therefore power consump-

tion and decrease the computational complexity of classifica-

tion algorithms. As the algorithm shows that the RMS value

of the recorded signal is a good indication for classification

accuracy, this may also simplify the potential application of

pattern recognition algorithms in a clinical setting. The RMS

value of the MES can be easily measured clinically and can

subsequently be used as a guideline for electrode placement

when fitting the prosthesis. Classification algorithms offer

exciting possibilities for prosthesis control, but need to be as

easy to apply as current conventional methods to leverage the

improvements in a clinical setting.

ACKNOWLEDGMENT

The authors are indebted to Univ.-Prof. Manfred Frey, Univ.-

Prof. Oskar C. Aszmann, Univ.-Prof. Tatjana Paternostro-

Sluga (Vienna General Hospital) and physiotherapist Hei-

delinde Amon-Aspalter (PhysioLeoben) for providing invalu-

able assistance and experience when working with the patient.

The authors would like to thank Dr. Roland Pawlik and Dr.

Hubert Egger for project coordination.

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