IPR2021-01459
`U.S. Patent 8,489,599
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`______________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`______________________
`TWITTER, INC.,
`Petitioner
`
`v.
`
`PALO ALTO RESEARCH CENTER INC.,
`Patent Owner
`______________________
`Case IPR2021-01459
`Patent 8,489,599
`______________________
`
`DECLARATION OF MICHAEL F. MILEA
`
`
`
`
`Twitter Exhibit 1015
`Page 00001
`
`

`

`IPR2021-01459
`U.S. Patent 8,489,599
`
`I, Michael F. Milea, make the following Declaration pursuant to 28 U.S.C. § 1746:
`
`1.
`
`I am an associate at the law firm of Paul, Weiss, Rifkind, Wharton &
`
`Garrison LLP.
`
`2.
`
`I provide this Declaration in connection with the above-identified Petition
`
`for Inter Partes Review proceeding that is being requested at the U.S. Patent and
`
`Trademark Office under 35 U.S.C. §§ 311-319, 37 C.F.R. § 42. Unless otherwise
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`stated, the facts stated in this Declaration are based on my personal knowledge.
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`3.
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`Attached hereto as Appendix A is a true and correct copy of an excerpted
`
`article titled “CASTmiddleware: Security Middleware of Context-Awareness
`
`Simulation Toolkit for Ubiquitous Computer Research Environment” and other
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`excerpted portions of Volume 344 of Lecture Notes in Control and Information
`
`Sciences, entitled Intelligent Control and Automation, International Conference on
`
`Intelligent Computing, ICI 2006 Kunming China, August 16–19, 2006. I
`
`understand that the Research Department of my law firm (at my instruction)
`
`requested a hard copy of the book from Texas A&M University, which had the
`
`book catalogued in WorldCat. The book was shipped to me via FedEx on August
`
`27, 2021, and I received it on August 28, 2021. I imaged excerpts of the book and
`
`an appendix label on the first page has been added but no alterations have been
`
`made.
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`Page 00002
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`

`

`IPR2021-01459
`U.S. Patent 8,489,599
`I have compared the copy of “CASTmiddleware: Security Middleware of
`
`4.
`
`Context-Awareness Simulation Toolkit for Ubiquitous Computer Research
`
`Environment” that is included in Appendix A to this declaration to the copy of that
`
`same article that is provided as EX1006 in the above-identified Petition for Inter
`
`Partes Review proceeding and have confirmed that those copies are identical.
`
`5.
`
`EX1005 in the above-identified Petition for Inter Partes Review proceeding
`
`is a true and correct copy of Yau, et al., “A Context-aware and Adaptive Learning
`
`Schedule framework for supporting learners’ daily routines.” I understand that the
`
`Research Department of my law firm (at my instruction) downloaded EX1005
`
`from IEEE Xplore (https://ieeexplore.ieee.org/document/4196333). An exhibit
`
`label on the first page has been added and page numbers on all pages have been
`
`added to the bottom of this document but no alterations have been made.
`
`6.
`
`EX1024 in the above-identified Petition for Inter Partes Review proceeding
`
`is a true and correct copy of EXHIBIT TW01 to PO’s Initial Infringement
`
`Contentions in Palo Alto Research Center Inc. v. Twitter, Inc., C.A. No. 2:20-cv-
`
`10754 AB(MRWx) (C.D. Cal.), which I received from counsel for PARC on May
`
`11, 2021.
`
`7.
`
`I have been warned that willful false statements and the like are punishable
`
`by fine or imprisonment, or both. I make this declaration of my own personal
`
`2
`
`Page 00003
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`

`

`IPR2021-01459
`U.S. Patent 8,489,599
`knowledge, and all statements are true. If called to testify as to the truth of the
`
`matters stated herein, I could and would testify competently.
`
`8.
`
`I declare under penalty of perjury that the foregoing is true and correct.
`
`Executed on this 31st day of August, 2021 at New York, NY.
`
` __________________
`
` Michael F. Milea
`
`3
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`Page 00004
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`APPENDIX A
`APPENDIX A
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`Page 00005
`Page 00005
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`pireToh NoTES IN CONTROL
`PONee Orbe) aye.4wes SCIENCES.
`
`Y) Springer Page 00006
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`Page 00006
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`Intelligent Control
`and Automation
`
`International Conference
`on Intelligent Computing, ICIC 2006
`Kunming, China, August 2006
`
`

`

`Lecture Notes
`in Control and Information Sciences 344
`
`Editors: M. Thoma, M. Morari
`
`Page 00007
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`

`

`De-Shuan~ J:Iuang, Kang Li,
`George Wilham Irwin (Eds.)
`
`Intelligent Control
`and Automation
`International Conf ere nee on
`Intelligent Computing, ICIC 2006
`Kunming, China, August 16-19, 2006
`
`~ Springer
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`Page 00008
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`

`

`St•rflos Advisory Uonrd
`I• All~i\Wl' I, p l<ll't11inp., P. Kol-.otovic,
`A I\. Klllll1,msi...,, 11. K wnkl•111ank,
`A. R,nll ll'I, l N Ts11-.iklis
`
`Editors
`Dl' Shuang Huang
`\nstih1t~ of lntelligent Machines
`Chitll'st' Acadt•my of Sc,cnccs
`lkk1, nhni, China
`h-mail: dshuang (!t" ii m.ac.cn
`
`Kang Li
`Queen' University
`Belfast, UK
`E-mail: K.Li@qub.ac.uk
`
`George William Irwin
`Queen's University
`Belfast, UK
`E-mail: G.Irwin @qub.ac.uk
`
`Library of Congress Control Number: 2006930913
`
`ISSN print edition: o 170-8643
`ISSN electronic edition: 1610-7411
`ISBN- IO 3-540-37255-5 Springer Berlin Heidelberg New York
`ISBN-13 978-3-540-37255-4 Springer Berlin Heidelberg New York
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`This work is subject to copyright. All rights are reserved, whether the whole or part of the materi~ is
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`Page 00009
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`

`

`Preface
`
`The International Conference on Intelligent Computing (ICIC) was formed to provide
`an annual forum dedicated to the emerging and cha11enging topics in artificial
`intelligence, machine learning, bioinformatics, and computational biology, etc. It aims
`to bring together researchers and practitioners from both academia and industry to
`share ideas, problems and solutions related to the multifaceted aspects of intelligent
`computing.
`ICIC 2006 held in Kunming, Yunnan, China, August 16-19, 2006, was the second
`International Conference on Intelligent Computing, built upon the success of ICIC
`2005 held in Hefei, China, 2005.
`This year, the conference concentrated mainly on the theories and methodologies
`as well as the emerging applications of intelligent computing. It intended to unify the
`contemporary intelligent computing techniques within an integral framework that
`highlights the trends in advanced computational intelligence and bridges theoretical
`research with applications. In particular, bio-inspired computing emerged as having a
`key role in pursuing for novel technology in recent years. The resulting techniques
`vitalize life science engineering and daily life applications. In light of this trend, the
`theme for this conference was "Emerging Intelligent Computing Technology and
`Applications". Papers related to this theme were especially solicited, including
`theories, methodologies, and applications in science and technology.
`ICIC 2006 received over 3000 submissions from 36 countries and regions. All
`papers went through a rigorous peer review procedure and each paper received at least
`three review reports. Based on the review reports, the Program Committee finally
`selected 703 high-quality papers for presentation at ICIC 2006. These papers cover 29
`topics and 16 special sessions, and are included in five volumes of proceedings
`published by Springer, including one volume of Lecture Notes in Computer Science
`(LNCS), one volume of Lecture Notes in Artificial Intelligence (LNAI), one volume
`of Lecture Notes in Bioinformatics (LNBI), and two volumes of Lecture Notes in
`Control and Information Sciences (LNCIS).
`This volume of Lecture Notes in Control and Information Sciences (LNCIS)
`includes 142 papers covering 4 relevant topics and 1 special session topics.
`The organizers of ICIC 2006, including Yunan University, the Institute of
`Intelligent Machines of the Chinese Academy of Science, and Queen's University
`Belfast, have made enormous effort to ensure the success of ICIC 2006. We hereby
`would like to thank the members of the ICIC 2006 Advisory Committee for their
`guidance and advice, the members of the Program Committee and the referees for
`their collective effort in reviewing and soliciting the papers, and the members of the
`Publication Committee for their significant editorial work. We would like to thank
`Alfred Hofmann, executive editor from Springer, for his frank and helpful advice and
`guidance throughout and for his support in publishing the proceedings in the Lecture
`Notes series. In particular, we would like to thank all the authors for contributing their
`
`Page 00010
`
`

`

`Vl
`
`Prl'fan'
`
`papers. \Vithout the high-quality submissions from the authors, the succ
`conlcrcncl' would not have been possible. FinaIJy, we are especially gratee;s of the
`1
`to the
`IEEE Computational Intelligence Society, The International Neural Netw
`/
`8
`and tht' ational Sl'icncc Foundation of China for the their sponsorship. or
`0ciety
`
`June ~006
`
`. Institute of Intelligent Ja;~ng
`
`De-Shuan
`
`Chmese Academy of Sci·e
`htnes
`nces f'I.·
`I '--lllna
`KangL·
`.
`,
`Q
`ueen s Umversity 8 1~
`1
`e ,ast, UI(
`George William I
`.
`Queen's University Bel~
`nvin
`,ast, UI(
`
`Page 00011
`
`

`

`Table of Contents
`
`Blind Source Separation
`
`A Unified Framework of l\tlorphological Associative Memories
`Naiqm Feng, Yuhui Qiu, Fang Wang, Yuqiang Sun.................
`
`I
`
`A New Speech Denoising Method Based on WPD-ICA Feature
`Extraction
`Qinghua Huang, Jie Yang, Yue Zhou.................. .. ........ .
`
`An Efficient Algorithm for Blind Separation of Binary Symmetrical
`Signals
`Wenbo Xia, Beihai Tan.........................................
`
`A New Blind Source Separation Algorithm Based on Second-Order
`Statistics for TITO
`ZhenLi Wang, Xiong Wei Zhang, Tie Yong Cao . . . . . . . . . . . . . . . . . . . .
`
`A New Step-Adaptive Natural Gradient Algorithm for Blind Source
`Separation
`Huan Tao, Jian-yun Zhang, Lin Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`An Efficient Blind SIMO Channel Identification Algorithm Via
`Eigenvalue Decomposition
`Min Shi, Qingming Yi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`An Improved Independent Component Analysis Algorithm and Its
`Application in Preprocessing of Bearing Sounds
`Guangrui Wen, Liangsheng Qu, Xining Zhang.....................
`
`Array Signal MP Decomposition and Its Preliminary Applications
`to DOA Estimation
`Jianying Wang, Lei Chen, Zhongke Yin . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`Mixture Matrix Identification of Underdetermined Blind Source
`Separation Based on Plane Clustering Algorithm
`Beihai Tan, Yuli Fu............................................
`
`Non-linear Blind Source Separation Using Constrained Genetic
`Algorithm
`Zuyuan Yang, Yongle Wan......................................
`
`12
`
`21
`
`29
`
`35
`
`41
`
`48
`
`54
`
`60
`
`66
`
`Page 00012
`
`

`

`r Wireless
`d·ng fo
`Co i
`
`Sensor
`
`Sun · · ·
`
`t'ng
`s Compu I
`.... . ·
`for l)b1q
`· uitou
`. . . . . · · · · · · · ·
`Lee · · ·
`
`f con"""
`i<S
`etwor
`-r,hle ,,
`•
`or N
`~1,
`Sens
`l·gcnt
`Jmage
`Intel t
`-B~.,rc
`1
`1ravclct
`Distril"'tcd
`)'01,rtan
`~ ,
`1,,,rk,
`.
`]iongor
`,g Lu,
`\
`· .
`< 1 D011g.
`Service
`Hyunghyo
`• Event
`l 111
`Lee.
`f Srrtll<'
`. Wireless
`nee m
`I pw11t o S ungyong
`I k Lre. c .
`DrH:' o
`O
`. • Maintena
`.
`101mg
`nectiv1t.)
`...... .
`an Zeng . . . .
`Efficient Con
`·n Sensor
`Eocrg.r
`He. Yuanyu
`d .. for Coverage 1
`fontta119
`eeds and~ u Haibin Yu ....
`. .
`The Cnt1cal Sp Wei Liang,
`' . Wireless Sensor
`Chuanzhi Zang,
`l S hema io1
`..
`........... . . .
`S Contro c
`.. .......... . . . .
`A Distributed Qo
`Jin Wu ....... .
`
`Sensor
`
`Networks
`.....
`
`Networks
`..
`
`.
`
`Networks
`........ .
`
`72
`
`83
`
`95
`
`106
`
`118
`
`for Context
`. g System
`Data Processm
`k
`f I -Situ Sensor
`~ Framework o n
`L Mi Par '
`Dong Gyu ee,
`.
`Ok Kim ........ ... .
`Awareness . J ng Yang Koo Lee,
`Young Jm u Hak Cheol Kim, Kyung
`d Detection
`Keun Ho Ryu,
`i-· al Model for Energy-E c1en
`ffi ·
`t Coverage an
`A Mathema,,c
`in Wireless Sensor Networ~s D i Zhi Wang, Youxian Sun ........ .
`Xiaodong Wang, Huaping a'
`.
`
`....... .
`
`....
`
`A l\fethod of Controlling Packet 'fransm1ss10
`. . n Rate with Fuzzy Logic
`
`S G . Ti e Park
`for Ad Hoc Networks
`....... . ....... .
`..
`Kyung-Bae Chang, Tae-Hwan on, wi- a
`
`A Novel Algorithm for Doppler Frequency Rate Estimation
`of Spaceborne Synthetic Aperture Radar
`
`Shiqi Huang, Daizhi Liu, Liang Chen, Yunf eng Liu .. . . · · · · · · · · · ·
`
`A Novel Genetic Algorithm to Optimize QoS Multicast Routing
`Guangbin Bao, Zhanting Yuan, Qiuyu Zhang, X uhui Chen . . . . · · ·
`
`~ Probe for the Performance of Low-.1\ate Wireless Personal Arca
`
`Networks
`
`Shuqin llen, Khin Mi Mi Aung, Jong Sou Park ................. .. .
`AC-Ne: An Automatic Genera("
`11
`.
`fo,. Dynamic NetworJ M
`•on echn1que of Network Components
`anagcnient
`p
`t
`'Un llee Kirn, Mvung Jin Lee, Keun Ho fl.
`
`yu ................... .
`
`124
`
`130
`
`138
`
`144
`
`150
`
`158
`
`165
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`Page 00013
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`

`

`Table of Contents
`
`XV
`
`Clustering Algorithm in vVircless Sem,or N0Lworks Using Transmit
`Power Control an<l Soft CompuLing
`Kyung-Bae Chang, Young-Ba<' Kong, Gwi-Tae Park................ 171
`
`Discriminating Fire Detection Via Support Vector Machines
`Heshou Wang, Shuibo Zheng, Chi Chen, Wenbin Yang, Lei Wu,
`Xin Cheng, Minrui Fei, Chuanping Hu . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
`
`Dynamic Deployment Optimization in Wireless Sensor Networks
`Xue Wang, Sheng Wang, Junjie Ma. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
`
`Energy-Efficient Aggregation Control for Mobile Sensor Networks
`Liang Yuan, Weidong Chen, Yugeng Xi . . . . . . . . . . . . . . . . . . . . . . . . . . 188
`
`Intelligent MAC Protocol for Efficient Support of Multiple SOPs
`in UWB-Based Sensor Networks
`Peng Gong, Peng Xue, Duk Kyung Kim . . . . . . . . . . . . . . . . . . . . . . . . . . 194
`
`Topology Control in Wireless Sensor Networks with Interference
`Consideration
`Yanxiang He, Yuanyuan Zeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
`
`Intelligent Control and Automation
`
`Adaptive Depth Control for Autonomous Underwater Vehicles Based
`on Feedforward Neural Networks
`Yang Shi, Weiqi Qian, Weisheng Yan, Jun Li . . . . . . . . . . . . . . . . . . . . . 207
`
`Adaptive Fuzzy Sliding-Mode Control for Non-minimum Phase
`Overload System of Missile
`Yongping Bao, Wenchao Du, Daquan Tang, Xiuzhen Yang,
`Jinyong Yu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
`
`An Improved Genetic & Ant Colony Optimization Algorithm and Its
`Applications
`Tiaoping Fu, Yushu Liu, Jiguo Zeng, Jianhua Chen . . . . . . . . . . . . . . . . 229
`
`Application of Adaptive Disturbance Canceling to Attitude Control
`of Flexible Satellite
`Ya-qiu Liu, Jun Cao, Wen-long Song . . . ... .. ..... ............... . 240
`
`Application of Resource Allocating Network and Particle Swarm
`Optimization to ALS
`Jih-Gau Juang, Bo-Shian Lin, Feng-Chu Lin... ... .. . . . .. ... ... . .. 252
`
`Page 00014
`
`

`

`X\ I
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`Jnhlc of
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`utl'nts
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`.;o1~m W11119, Hui fong . . . . . . . .
`.
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`. . . . . . . . . . . 287
`
`·n Control for Chaotic Systems Usmg
`. . . . . . . . . . 299
`Intelligent. I3ar.kst.cpp1c17ra1 Network
`. /I u I-Fang Clmng ........... .
`clf-Growmg Fuzzy N
`s ,
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`Ghih-Min L1'.n, Clmn.-rct
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`r:i
`
`t th Semi-arid Small
`.
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`Modeling of Rainfall-Runoff Ilclat1onsl11p a
`c
`Catrhmcnt..c, Using Artificial Neural Networks
`Mu. .. ~taf a Tombul, Ersin Ogul · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
`
`. . . . . . . . 309
`
`A Novel Multi-agent Based Complex Process Control System and Its
`Application
`Yi-Nan Guo, Jian Cheng, Dun-wei Gong, Jian-hua Zhang ...... · · · ·
`
`319
`
`Neural Network Based Soft Switching Control of a Single Phase AC
`Voltage Restorer
`Kayhan Gulez, Tank Veli Mumcu, Ibrahim Aliskan. . . . . . . . . . . . . . . . . 331
`
`Neural Nct~or~ Training Using PSO Algorithm in ATM Traffic Control
`Yuan-wei Jmg, Tao Ren, Yu-cheng Zhou. . . . . . . . . . . . . . . . . . . . . . . . . . 341
`Parameter Identification of Dynarni . 1 S
`ca ystcrm1 DEJ.l,lc<l on Improved
`Particle Swarm Optirnizatio
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`M
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`~u~acturing System (HMS)
`d ~duhng Problem of Holonic
`ts Solution with a H b . <l PSO
`un
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`y ri
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`Fuqmg Zhao
`' Q,uyu Zhang, Ya!umg Yang .....
`.
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`Towlirds HIU
`a11u111g by Sarn 1·
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`z eny, llonobin z,
`on OHtacleH' Surfaces
`<mg !Jiu, Xu,,z1,, · D
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`" ia, K emiug Chen
`Electro.b d
`........ , ..... .
`ntroJ D~cJ
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`Y rauJic Se
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`Chunta, Yu, liua~vo McchanlHru. •Y oura.l Nutwork for M1'
`<mg Xu Y:
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`iu, Shiqi JI
`uang ...
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`351
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`361
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`373
`
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`
`I I . I I . t
`
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`
`385
`Page 00015
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`

`

`Table of Contents XVII
`
`Stability Analysis of Network Data Flow Control for Dynamic Link
`Capacity Case
`Yuequan Yang, Yaqin Li, Min Tan, Jianqiang Yi, John T. Wen,
`X uewu Guo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
`
`Matrix Measure Stability Criteria for a Class of Switched Linear
`Systems
`Hongbo Zou, Hongye Su, Jian Chu .. .. ..... . . . ............... . ... 407
`
`Study on FOG-SINS/ GPS Integrated Attitude Determination System
`Using Adaptive Kalman Filter
`X iyuan Chen... . ... .. . . . . ....... .... . . .. .. . . .. . . ... . . . ... . .... 417
`
`Supervisory Control for Rotary Kiln Temperature Based
`on Reinforcement Learning
`Xiaojie Zhou, Heng Yue, Tianyou Chai, Binhao Fang . . . . . . . . . . . . . . 428
`
`A Data Reorganization Algorithm to Improve Transmission Efficiency
`in CAN Networks
`Jung-Ki Choi, Sungyun Jung, Kwang-Ryul Baek........... .. . . ... . 438
`
`A Neural Network Approach to QoS Management in Networked
`Control Systems over Ethernet
`Wenhong Zhao, Feng Xia.. . ........ .. ....... . .. . . . ... . ... .. . . . . 444
`
`A Novel Micro-positioning Controller for Piezoelectric Actuators
`Van-Tsai Liu, Chun-Liang Lin, Hsiang-Chan Huang, Zi-Jie Jian . . . . 450
`
`A Study on the Robust Control of an Inverted Pendulum Using
`Discrete Sliding-Mode Control
`J. Y. Yang, H.J. Lee, J.H. Hwang, N.K. Lee, H. W. Lee, G.A. Lee,
`S.M. Bae . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 456
`
`A VRC Algorithm Based on Fuzzy Immune PID-Smith
`Ling He, Yu-cheng Zhou, Yuan-wei Jing, Hai-yu Zhu. . . . ... . ... . . .. 463
`
`Absolute Stability of State Feedback Time-Delay Systems
`Hanlin He, Zhongsheng Wang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
`
`Adaptive Fuzzy Control of Nonlinear Systems Based on Terminal
`Sliding Mode
`Shuanghe Yu .. . . .... . . .... . . .. .. .. . ...... . . ... . ..... .. · . · , . · . . 474
`
`Simulation of Air Fuel Ratio Control Utting Radius Basis Function
`Neural Network
`Zhixiang Hou ... . .. , . · . · · , , · , · ......... · ... · , · · · · · · · · · · · · · · · · · · 480
`
`Page 00016
`
`

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`494
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`500
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`506
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`t Awareness Simulation
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`Tovlkit for Ub1qmtous k L HyungHyo Lee .. . .... . . . .... .
`InSu Kim, YmmgLo
`ee,
`
`fong/1 Sh,. Cha
`
`. . . ... ... .
`
`Cybernation Process of L1dar System
`.
`
`Detecting the Atmospheric
`
`'7h
`.
`C~rbon Dioxide
`Yue-Feng Zhao, Yin-Chao LJ, ang,
`
`Pei-Tao Zhao, Jia Su, Xin Fang,
`
`Jun Xie, K ai-feng Qv .. · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
`
`Design of a Robust Output Feedback Controller for Robot Manipulators
`Using Visual Feedback
`
`Min Seok Jie, Chin Su Kim, Kang Woong Lee ......... .. .. . · .. ····
`
`Fuzzy Sliding Mode Controller with RBF Neural Network for Robotic
`Manipulator 'Irajectory 'Iracking
`
`514
`
`520
`
`Ayca Gokhan Ak, Calip Cansever............ .. .... . . . . . . . . . . . . . . 527
`
`Hybrid Fuzzy Neural Network Control for Complex Industrial Process
`Q,ngyu Yang, Ltncang Ju, Sibo Ge, Ren Shi, Yuanli Cai ....... . .. . .
`Intelligent Vehicle Control by Optimal S I t'
`e ec ion of Image Data
`M. Junaid Khan Dany y,
`J
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`a ao, uan Zhao, Shuning Wang, Yu Cai . .. .
`Rul~Based Expert System for Selectin S
`g cene Matching Area
`Guozhong Zhang L•n h
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`Tao Sh,n, Jian-she Son
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`. . . . . . . . . . . . . . . . . . . . . . . .
`559
`Page 00017
`
`533
`
`539
`
`546
`
`554
`
`•
`
`

`

`1able of Contents
`
`XIX
`
`~cural ::'.\fc_>twork-1:fased an AclriptivP Disc·n •t c-Timr Global Sliding ~lode
`Control 'chPrnc
`Zhrnyon H'nng .. hnggonq Zhnnq, Zhnnr, ('hrn : Yonzhao He. . . .. . . . . 565
`
`Rral Cod<'d Genetic Algoril lun for Optimizing Fuzzy Logic Control of
`Greenhouse :-.Iicroclima tc
`Fang Xu . .Jwoliao Ch en. L1bm Zhang, llongwu Zhan . . . . . . . . . . . . . . . 571
`
`Research and lmplem<'ntation on the !vlobile Intelligent Controller for
`Home Automation Service
`.Jonghwa Cho1, Dongkyoo Shin, Dongil Shin . . . . . . . . . . . . . . . . . . . . . . . 578
`
`ampled-Data Systems with Quantization and Slowly Varying Inputs
`Ge Guo. Huipu Xu, Yuan Tian............. ... ... . .............. 584
`
`Set-Stabilization with Occasional Feedback
`Ge Guo, Jigong Li . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 590
`
`Spatial Reasoning for Collision Detection and Hardware Implementation
`Chirag Nepal. Seung Woo Nam, Dohyung Kim, Kyungsook Han... . .. 596
`
`Stability Criteria for Switched Linear Systems
`H ongbo Zou. H ongye Su, Jian Chu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 602
`
`Suppressing of Chaotic State Based on Delay Feedback
`lVenli Zhao. Linze Wang ....... .... .......... . ......... ........ 608
`
`Yector Controlled PivISl\I Drive Based on Adaptive Neuro-fuzzy Speed
`Controller
`Xianqing Cao, Liping Fan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 616
`
`Data Fusion, Knowledge Discovery and Data Mining
`
`--Intelligent Yardstick'', an Approach of Ranking to Filter Non-promising
`Attributes from Schema in Data Mining Process
`lifohammad A!. Hassan ...... ... .... . .. . .. . ... . . ... ............ .
`
`623
`
`A Local Computing-Based Hierarchical Clustering Algorithm Building
`Density Trees
`.
`.
`lVei-di Dai, Jie-Liu, Da-yi Zhao, Zhen-liua Liu, Jun-xian Zhang,
`Pi-lian He ............. · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
`
`633
`
`Support Vector Clustering and Type-Entropy Bru;cd Joint
`De-interleaving/recognition Syst ern of Radar Pubc Sequence
`Qiang Guo. Z/zrng Li, X irigzhou Zha1t9 .......................... .
`
`642
`
`Page 00018
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`Ruiming Liu, Erqi Liu, Jie Yang, Ming Li, Fanglin Wang. . . . . . . . . . . 712
`
`Prediction of Sinter Burn-Through Point Based on Support Vector
`Machines
`Xiaofeng Wu, Minn.ti Fei, Heshou Wang, Shuibo Zheng . ........... . 722
`Under:Sampling Approaches for Improving Prediction of the Minority
`Class m an Imbalanced Dataset
`Show-Jane Yen, Yue-Shi Lee
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`Utilizing a Hierarchical Meth d
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`Page 00019
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`

`Tahlc of Contents
`
`XXI
`
`\ "t'\\ lllS \\' r Imnge Frn~ion 7\lcthod Based 011 \VcightPd Regional
`l '~t \\l't'S
`J, • ll u, llm_qktm 1 rn. J foa /Ji u, .Jmwc11 Tum . . . . . . . . . . . . . . . . . . . . . 765
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`ti. RuJing \\fang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771
`
`\ ~oYl'l Discn"tizcr for Knowledge Discovery Based on Multiknowledge
`. \ ppnxwhes
`Q ·ngSiang n·u. Girijesh Prasad, TAI AlcGinnity, David Bell,
`"' htwChun Zhong, Jiwen Guan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 778
`
`A XoYel Neural Network for Sensor Fusion Applied to Wood Growth
`Ring 1Ioisture l\Ieasurement
`Jfingbao Li. Shiqiang Zheng. Jun Hua . . . . . . . . . . . . . . . . . . . . . . . . . . . . 784
`
`_.\ ~oYel Reduction Algorithm Based Decomposition and Merging
`trategy
`Feng Hu. Xinghua Fan, Simon.X Yang, Chaohai Tao . . . . . . . . . . . . . . . 790
`
`A Pattern Distance-Based Evolutionary Approach to Time Series
`Segmentation
`Jingwen Yu. Jian Yin, Duanning Zhou, Jun Zhang. . . . . . . . . . . . . . . . . 797
`
`A Quality Prediction :Method of Injection Molding Processes Using
`Sub-stage PCA-SI
`XiaoPing Guo, Pu.Li Wang, MingXing Jia . . . . . . . . . . . . . . . . . . . . . . . . 803
`
`A Robust Algorithm for Watermark Numeric Relational Databases
`Xinchun Cui, Xiaolin Qin, Gang Sheng, Jiping Zheng . . . . . . . . . . . . . . 810
`
`A Study on the RAP Approach and Its Application
`Jian Cao, Gengui Zhou, Feng Tang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`An Analytical Model for Web Prefetching
`Lei Shi, Lin Wei, Zhimin Gu, Yingjie Han, Yun Shi . . . . . . . . . . . . . . .
`
`An Optimal Interval for Computing Course and Ship Speed in Marine
`Gravity Survey Based on Approximate Reasoning
`Lilma Zhang, Chong Fang, Xiaosan Ge, Yilong Li . . . . . . . . . . . . . . . . .
`
`Application of A:;sociation Rules in Education
`Sylvia Enche11a, Sharil Tomin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`16
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`Page 00020
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`Tica-Suk Kim, Yang-Sae Moon, Jinho Kim, Woong-Kee Loh. . . . . . . . . 857
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