IEEE CIS > Members Activities

Electronic Letter

Derong Liu, Manager (2008) Department of Electrical and Computer Engineering (M/C 154) University of Illinois at Chicago 851 S. Morgan Street Chicago, IL 60607-7053, USA phone: (+1 312) 355 4475 fax: (+1 312) 996 6465 email: dliu .a_t. ieee.org www: liu.ece.uic.edu

Submit your contributions at http://www.ci-eletter.org or http://liu.ece.uic.edu/eletter

Issue 16, February 2006

1. IEEE CIS News and Announcements

1.1 Call for IEEE Fellow Nominations

Posted by on January 26th, 2006

The grade of IEEE Fellow is the highest grade of membership in the IEEE. Nominations for IEEE Fellow are due to IEEE by March 1, 2006. Information on forms for nominating individuals can be found at http://www.ieee.org/portal/pages/about/awards/fellows/committee.html (or go to www.ieee.org and search for "Fellow Nominations").

Please ensure that your complete nomination packets are submitted by the deadline as no extensions are anticipated. If you have any questions on the IEEE Fellow process, please contact David Fogel, VP Members Activities (dfogel@natural-selection.com) or Robert Marks, IEEE CIS Fellows Committee Chairman (Robert_Marks@baylor.edu).

1.2 IEEE CIS Tutorials Update

Posted by on January 27th, 2006

The multimedia tutorials committee is pleased to announce the new IEEE CIS Tutorials Center sponsored by the IEEE Computational Intelligence Society. The tutorials center is created to serve the need of the CIS members in continuing education. It is a means of disseminating fundamental knowledge and technical know-hows in the area of computational intelligence.

The first set of tutorials is now available (http://ebrains.la.asu.edu/~jennie/tutorial/index.htm). More tutorials are to be added to the center. Frequent updates are planned to increase the quality and quantity of the tutorials. Interested readers are welcome to check the center out for a subject of interest. Feedback is also welcome.

For questions and inquiries, please contact Prof. Jennie Si at si@asu.edu.

2. Awards

No submissions.

3. Computational Intelligence Forum

3.1 Simulation of a Spiking Model Having the Size of the Human Brain

Posted by on January 10th, 2006

Scientists at The Neurosciences Institute in San Diego simulated a large-scale model having microcircuitry of the mammalian thalamo-cortical system and the size of the human brain: 100,000,000,000 neurons (hundred billion or 1011) and almost 1,000,000,000,000,000 (one quadrillion or 1015) synapses. It represents 300x300 mm2 of mammalian thalamo-cortical surface, specific, non-specific, and reticular thalamic nuclei, and spiking neurons with firing properties corresponding to those recorded in the mammalian brain. The model exhibited alpha and gamma rhythms, moving clusters of neurons in up- and down-states, and other interesting phenomena (movies are available at www.izhikevich.com).

One second of simulation took 50 days on a beowulf cluster of 27 processors (3GHz each), indicating that real-time simulations of such brain models will not be possible until 2016.

3.2 A Multi-Class Classifier Based on SVM Decision Tree

Posted by on January 25th, 2006

In order to solve the unclassifiable region problem, some multi-class classifiers, i.e. DTSVMs were proposed in previous works. But there still exist two main disadvantages with the classifiers. One is that the trained decision tree is an unbalanced binary tree. The other is that the calculation of separability measurement is not reasonable. To solve the two problems, a multi-class classifier Support Vector Machine based Decision Tree (SVMDT) is proposed in this paper. The SVMDT grows from leaf to root. And an equivalent distance is used as the forking rule. Unlike the distance calculation in DTSVMs, the equivalent distance calculation makes use of center distance between classes and their distributions in feature space. Therefore, the separability measurement is more reasonable. To solve the unbalanced tree problem, a Local Class Cluster (LCC) concept is introduced in this paper. By utilizing the LCC in tining process, the binary tree SVMDT is more balanced. At the same time, in order to decrease the computation complexity,he minimum distance principle is used at training phase. And the maximum distance principle is used at classification phase.

At last, the experiment based on UCI data set (glass, iris, wine, liver, pima, breast and image) shows that the SVMDT classifier has more rapid training speed, classifyineed and better generalization performance than conventional one-versus-all classifier.

3.3 A Multiple Function and Programming Fuzzy Controller

Posted by Xiang Shiwu, Yan Lijun (xia-8we@online.sh.cn) on January 13th, 2006

This controller can be used to control temperature, fluid, pressure, liquid level, rotate velocity with different sensors. This controller is accepted as a successful research by the Shanghai Education Senor Bureau. The controller uses 803l microprocessor; it is ontrolled by fuzzy theory. The controller hve these advantages: the system response is quicker, the regulation over ouput is less, and the static precision is more precise. It nee not set up mathematical model for controlled object. It is very easy to obtain good reslt. It takes dual integration A/D converter, digital filter and analoge filter. The interference is very small. The output of contoller has 80 segments curves; It can be programmed by key. Each segment curve has the rang from 0-7200 minutes The controller system has the programmed range from (0-7200)*80 (minutes). The range is very large. The controlled curve can be run for one or circulate.

3.4 Website Announcement www.type2fuzzylogic.org

Posted by Simon Coupland (simonc@dmu.ac.uk) on January 27th, 2006

The Centre for Computational Intelligence at De Montfort University, UK has launched an online resource for type-2 fuzzy logic researchers. Our site includes news, conferences, a publications list and other useful information. This is intended to be a site for both those already working in the community and for those who wish to find out more aboutpe-2 fuzzy logic.

The address is www.type2fuzzylogic.org

3.5 Reputation-Based Trust Model in Grid Security System

Posted by BaoLin Ma on January 20th, 2006

The security problems is a hot topic in grid research due to the dynamics and uncertainty of grid system. There are three entities defined as users, applications and resources in grid environment. In such situation, users are vulnerable to risks because of potential incomplete or distorted information provided by malicious resources, and as grid system grows tremendously in size, the possibility of users attack the network by providing aggressive or vicious applications will increase greatly. Trust management is an effective method to maintain the credibility of system and keep honest of entities. This paper presents a trust model, which is used to compute and compare the trustworthiness of resources/users in the same autonomous and different domains. Our model considers three parameters to evaluate the trustworthiness of user or resource: number of transactions, the old value of trustworthiness and the credibility of feedback. And we provide different methods to deal with the problems of users and related resources belonging to the same or different domains. Furthermore, we provide a simulation experiment to evaluate the trust model, and the simulation result shows it is effective to resolve security problems in grid environment.

4. Doctoral Dissertations

No submissions.

5. Career Opportunities

5.1 Assistant Professor, Computer Science at University of Idaho

Posted by on January 31st, 2006

The Department of Computer Science at the University of Idaho invites applications for a full-time, academic year, tenure-track faculty position at the assistant professor level, contingent upon funding.

Application Procedures: To be considered, complete the online application including a resume/vita and letter of qualification addressing the minimum and desirable qualifications and how your skills relate to the responsibilities of the position.

Contact: Questions may be directed to Robert Hiromoto at (+1 208) 885-7232 or hiromoto@uidaho.edu

The Department of Computer Science is in the College of Engineering. The faculty member will be located at the University of Idaho at Idaho Falls (UIIF) and will maintain a close relationship with the Moscow Campus Computer Science Department.

This position will provide leadership for undergraduate and graduate programs in computer science in Idaho Falls.

Specialization: Candidates should have a specialization in one or more of the following areas; reliability, performability, survivability modeling, neural networks or fuzzy logic; however, candidates in other areas will also be considered. Experience advising and teaching in outreach campuses and teaching workshops for professional development is desirable. Successful candidates are expected to pursue an active research program, perform graduate and undergraduate teaching, supervise graduate students, and administer the computer science offerings at UIIF.

Campus Information: On the Moscow campus, the department has 11 tenure-track faculty, approximately 228 undergraduate and 54 graduate students. The department currently offers BS, MS, and PhD degrees in computer science. At UIIF there are approximately 35 undergraduate and 8 graduate students. UIIF is adjacent to the Idaho National Laboratory (INL) allowing numerous opportunities for collaborative research projects with members of the INL. More information about the Department of Computer Science and the UIIF can be found at http://www.cs.uidaho.edu and http://if.uidaho.edu

Major Function: The full-time assistant professor will teach graduate/undergraduate level courses and workshops in computer science topics such as reliability and operability, software engineering and neural networks; will assist in advising of students in coordination with other UIIF faculty; and will conduct research.

RESPONSIBILITIES

Instruction: 50%
Organize instructional materials, lecture, grade student performance, etc., for UIIF computer science courses, including teaching classes over the compressed video system to Moscow. Some classes may also be video taped and distributed at a distance by the Engineering Outreach program. Provide professional development workshops on topics of interest to area professionals.

Research: 25%
Conduct research in computer science topics of interest and need to the Idaho Falls area in general and INL in particular. Seek outside funding and publish results.

Miscellaneous: 20%
Miscellaneous activities as assigned by the Department Chair of Computer Science.

Advising: 5%
Assist undergraduate and graduate students at UIIF with the advising process.

5.2 Assistant or Associate Professor, Neurotechnology at Brown University

Posted by on January 31st, 2006

Tenure-track position in Neurotechnology at Brown University

The interdepartmental Brain Science Program of Brown University (brainscience.brown.edu) seeks a faculty member with experience and research interests in neural engineering for a tenured/tenure-track position in one of the related constituent departments in the Brain Science Program. The University has committed substantial resources to brain science research and is expanding in the area of neurotechnology.

Electronic applications received by March 1, 2006 will be given full consideration. Please specify if you are applying at Assistant or Associate Professor level. Electronic .pdf format applications should include a curriculum vita, a research and teaching statement, and 3 (Assistant Professor) or 5 (Associate Professor) reference letters. Please send your electronic application to Neurotech_Search@yoshi.neuro.brown.edu

Requirements:
Candidates should have a Ph. D., M. D., or equivalent and research experience in areas related to neurotechnology. Appropriate fields of study include research on brain-implantable elecnic devices, advanced neural prostheses, functional near-infrared imaging (fNIR), functional electrical stimulation (FES), and devices and coding methods for recording from and stimulating peripheral nerves. Other areas of interest include new techniques for employing nanomaterials and nanodevices for highly targeted noninvasive imaging, brain activation, and focal drugivery, which require the intersection of engineering, physics, chemistry, and advanced biotechnology. The successful candidate must be qualified to develop an externally funded research program and contribute to the educational and training missions of Brown University at the undergraduate, graduate and postgraduate levels.

Contact:
Andrea Senerchia
Brown University
Brain Science Program, Box 1953
Providence, RI 02912
Phone: +1-401-863-9524

6. Bookshelf

6.1 Knowledge-Based Clustering

Posted by on January 18th, 2006

Knowledge-Based Clustering by Witold Pedrycz
J. Wiley & Sons, Hoboken, NJ, 2005
308 pages +xvii
ISBN 0-471-46966-1

Data and patterns become an integral and ultimate cultural fabric of our information society. The grand challenge we are confronted every day is to cope with the flood of data generated by banking transactions, millions of sensors, WWW log records, communication traffic of cellular calls, satellite image collection systems, and networks of intelligent home appliances, just to throw in a few simple yet highly convincing examples.

Making sense of data has become a holy grail of intelligent data analysis (IDA), data mining (DM), sensor fusion, image understanding, and logic-driven system modeling. As never before we have been faced with the growing need to construct a powerful computer eye: a highly human-centric, human-interactive, and human-sensitive computer environment that helps us understand data and on this basis make sensible decisions.

Clustering is one of the well-established manifestations of such computer eye. With its underlying agenda of venturing in the data spaces and discovering their genuine structure: clusters of data, clustering becomes an ideal vehicle of exploration of vast territories of data spaces. From the early concepts going back to the thirties of the 20th century, just recently this field has undergone a rapid expansion fueled by new conceptual and computing challenges. The today's omnipresent visibility of clustering is astonishing. Even a quick and fairly unsophisticated search completed for any library database or Web search returns thousands of hits revealing an impressive breadth of applications: from biomedicine to marketing, engineering, economics, biological sciences, chemistry, military, food engineering, finances and education.

Clustering has become a synonym of a diversified suite of methodologies and algorithms that are almost exclusively data-driven and in which any optimization is predominantly, if not exclusively, data-oriented. Clustering gives rise to a variety of information granules using which we reveal the structure of data. The existing formalisms of Granular Computing help design clustering methods geared towards meeting some user-defined objectives. Within this genuinely diversified landscape of clustering, the algorithms operating within the framework of fuzzy sets have assumed an important and unique position. The reason is rather obvious: fuzzy sets regarded as fundamental information granules are very much human-centric. Dealing with concepts and groups (clusters) that allow for partial membership is highly appealing. Identifying data (patterns) that are of borderline character and may require special attention as potential outliers is a useful value-added feature of fuzzy clustering. Discovering patterns that are of the highest typicality (coming with the highest membership values) in the cluster is another important feature offered by fuzzy sets.

In light of the recent applications and new avenues of agent-based technology, Web-based pursuits and rapidly growing dimensionality and inherent heterogeneity of data sets, the issue of human-centricity of clustering has become even more essential. The paradigm of data-centric clustering has to be augmented. The paradigm of knowledge-based clustering introduced in the book is about reconciling two important driving forces of clustering activities namely data and domain knowledge and building a highly coherent platform of navigation in the highly dimensional and very often heterogeneous data spaces.

Table of Contents
Foreword (L. A. Zadeh)

1. Clustering and Fuzzy Clustering
2. Computing with Granular Information
3. Logic Oriented Neurocomputing
4. Conditional Fuzzy Clustering
5. Clustering with Partial Supervision
6. Principles of Knowledge-Based Guidance in Fuzzy Clustering
7. Collaborative Clustering
8. Directional Clustering
9. Fuzzy Relational Clustering
10. Fuzzy Clustering of Heterogeneous Patterns
11. Hyperbox Models of Granular Data: The Tchebyshev FCM
12. Genetic Tolerance Fuzzy Neural Networks
13. Granular Prototyping
14. Granular Mappings
15. Linguistic Modeling

6.2 Lectures on Robotics and Intelligent Systems

Posted by Robert Stengel (stengel@princeton.edu) on January 24th, 2006

"Robotics and Intelligent Systems" is an undergraduate course that presents the theory of robotic and intelligent systems. Particular attention is given to modeling dynamic systems, measuring and controlling their behavior, and making decisions about future courses of action. Twenty-three 80-minute lectures were given during the Fall 2005 term. The slides used as lecture materials may be downloaded for non-commercial, educational use only, with acknowledgment of the source. The portable document files can be found at
http://www.princeton.edu/~stengel/MAE345Lectures.html.

7. Most Recent Issues of Journals

7.1 IEEE/ACM Transactions on Computational Biology and Bioinformatics, no.1, 2006

Posted by Richard Mavis (rmavis@computer.org) on January 27th, 2006

EDITORIAL

State of the Journal
Dan Gusfield
http://doi.ieeecomputersoty.org/10.1109/TCBB.2006.12

PAPERS

Jointly Analyzing Gene Expression and Copy Number Data in Breast Cancer Using Data Reduction Models
John A. Berger, Sampsa Hautaniemi, Sanjit K. Mitra, Jaakko Astola
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.10

Spatio-Temporal Analysis of Constitutive Exocytosis in Epithelial Cells
Rafael Sebastian, Maria-Elena Diaz, Guillermala, Kresimir Letinic, Jose Moncho-Bogani, Derek Toomre
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.11

Statistical Analysis of RNA Backbone
Eli Hershkovitz, Guillermo Sapiro, Allen Tannenbaum, Loren Dean Williams
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.13

Gene Mapping and Marker Clustering Using Shannon's Mutual Information
Zaher Dawy, Bernhard Goebel, Joachim Hagenauer, Christophe Andreoli, Thomas Meitinger, Jakob C. Mueller
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.9

A Hidden Markov Model for Transcriptional Regulation in Single Cells
John Goutsias
http://doi.ieeecompursociety.org/10.1109/TCBB.2006.2

A Hill-Climbing Approach for Automatic Gridding of cDNA Microarray Images
Luis Rueda, Vidya Vidyadharan
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.3

Unicyclic Networks: Compatibility and Enumeration
Charles Semple, Mike Steel
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.14

SHORT PAPERS

A Short Proof that Phylogenetic Tree Reconstruction by Maximum Likelihood Is Hard
Sebastien Roch
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.4

REVIEWERS LIST

2005 Reviewers List
http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.1

7.2 IEEE Transactions on Evolutionary Computation, vol.10, no.1, 2006

Posted by Derong Liu (dliu@ece.uic.edu) on January 31st, 2006

Bounds for Probability of Success of Classical Genetic Algorithm Based on Hamming Distance
Yuen, S.Y.; Cheung, B.K.S.
Page(s): 1-18

A Saw-Tooth Genetic Algorithm Combining the Effects of Variable Population Size and Reinitialization to Enhance Performance
Koumousis, V.K.; Katsaras, C.P.
Page(s): 19-28

A Faster Algorithm for Calculating Hypervolume
While, L.; Hingston, P.; Barone, L.; Huband, S.
Page(s): 29-38

Evolving the Structure of Hidden Markov Models
Won, K.-J.; Prugel-Bennett, A.; Krogh, A.
Page(s): 39-49

ParEGO: A Hybrid Algorithm With On-Line Landscape Approximation for Expensive Multiobjective Optimization Problems
Knowles, J.
Page(s): 50-66

An Organizational Coevolutionary Algorithm for Classification
Jiao, L.; Liu, J.; Zhong, W.
Page(s): 67-80

Evolutionary Discriminant Analysis
Sierra, A.; Echeverria, A.
Page(s): 81-92

Automated Passive Filter Synthesis Using a Novel Tree Representation and Genetic Programming
Chang, S.-J.; Hou, H.-S.; Su, Y.-K.
Page(s): 93-100

8. Conference Calendar and Call for Papers

8.1 IEEE WCCI 2006: Paper Submission Deadline Extension - February 15, 2006

Posted by Gary G. Yen (gyen@okstate.edu) on January 31st, 2006

Due to overwhelming demand, the web-based paper submission systems for IJCNN 2006, FUZZ-IEEE 2006, and CEC 2006 will remain open till February 15, 2006. This date will then be in consistent with the deadline set for papers submitted to special sessions.

WCCI, held every four years during the past, is a joint event of IJCNN, FUZZ- IEEE, and CEC. Each conference holds its annual conference in its own time. As a result, the deadline of January 31 has been made difficult for various communities. In addition, our web server has been fluctuated with occasional down time which has caused some inconvenience. To accommodate the authors with strong desires to participate this Olympic event in computational intelligence, the paper submissions system for
IJCNN 2006 (http://ieee-cis.org/conferences/ijcnn2006/upload.php)
FUZZ-IEEE 2006 (http://ieee-cis.org/conferences/fuzzieee2006/upload.php)
CEC 2006 (http://ieee-cis.org/conferences/cec2006/upload.php)
will remain open till February 15, 2006. This deadline applies to all submissions to special sessions and at large. The Organizers are committed to make this event a great success by fostering cross-disciplinary technical exchanges, informing state-of-the-art emerging discoveries, renewing everlasting friendships, and establishing new collaborations. For general inquiries, please contact General Chair Gary Yen at gyen@okstate.edu.

8.2 2006 IEEE International Symposium on Intelligent Control

Posted by: Chun-Yi Su (cysu@me.concordia.ca)
Date submitted: Jan. 22nd, 2006

2006 IEEE International Symposium on Intelligent Control
October 4-6, 2006, Munich, Germany
http://www.elet.polimi.it/conferences/cca06

New deadline for paper submission: February 10, 2006

The 2006 IEEE International Symposium on Intelligent Control, ISIC'06, will be held on October 4-6, 2006 in Munich, Germany. The Symposium offers a unique platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas in the areas of intelligent control.

Topics of interest include but are not limited to:

• Next generation intelligent control architectures
• Multi-agent based planning, control and intelligence
• Distributed/Decentralized intelligent control
• Neural networks, fuzzy logic and genetic algorithms
• Swarm intelligence , learning and control
• Intelligent control of networked dynamic systems
• Intelligent control of wireless adhoc and sensor networks
• Embedded intelligent control
• Biological learning control systems
• Machine learning
• Hybrid dynamical systems control, pattern discovery
• Distributed or decentralized control methods
• Probabilistic approaches, knowledge-based sensor fusion
• Distributed and embedded systems, large scale systems
• AI and expert systems, distributed intelligence

Contributed papers are intended to be a complete description of finished work. For the purpose of review, all regular and invited papers are limited to eight (8) pages. For publication in the conference proceedings, all accepted papers are limited to six (6) pages.

Important dates
Paper/Invited session/Workshop proposal: February 10, 2006
Paper acceptance/rejection notification: April 15, 2006
Final manuscript submission deadline: May 19, 2006

Andras Varga, General Chair
Derong Liu, Program Chair

8.3 Bioenergetics, the Immune System, and Bioinformatics

Posted by: Krzysztof Cios (krys.cios@cudenver.edu)
Date submitted: Jan. 4th, 2006

Call for chapters for the book entitled "Bioenergetics, the Immune System, and Bioinformatics"
edited by Newell / Cios / Lightner
to be published by Springer-Verlag series "Studies in Computational Intelligence

For details see http://isl.cudenver.edu/Publications/CFP.htm

8.4 CFP: Special Session on Swarm-Based Hybrid Systems During IEEE SIS'06

Posted by: Arun Khosla (arun.khosla@gmail.com)
Date submitted: Jan. 5th, 2006

Special Session at IEEE SIS'06:
Different intelligent techniques are being used for solving real-world problems. Each specific technique has its particular strengths and weaknesses that make it suitable for certain situations and not effective for others. These limitations have been a central driving force behind the creation of hybrid intelligent systems, where two or more techniques are combined in a manner to mitigate the limitations and take advantages of the strengths to produce systems that are more effective and powerful than those could be built with single technique.

Swarm algorithms such as Particle Swarm Optimization, Ant Colony Optimization and others h been emerging as an innovative and powerful computational metaphor for solving complex problems in design, optimization, control, management, business and finance. These algorithms lay emphasis on methodology that features autonomy, emergence and distributed computing and the solutions sed on this framework have been found to be more robust, flexible and adaptable.

The aim of this special session is to advocate the hybridization of swarm- based systems with other intelligent techniques. It is epected that the prospective contributions are unpublished and present novel, fundamental research offering innovative contributions either from a methodological viewpoint or from an application perspective base on hybrid intelligent approaches, where swarm-based algorithm is one of the constituent techniques.

Topics of interest include but not limited to:

• Hybridization of Swarm-based algorithms with Fuzzy Logic, Neural Networks and Genetic Algorithms
• Swarm-based Multi-Agent System
• Hybridization of Swarm systems with Rough Sets, Bayesian Networks
• Application of Swarm-based hybrid systems in Signal and Image Processing
• Control, Medical Diagnosis, Data Mining
• Application of Swarm-based hybrid systems in Business, Finance and Management

Important Dates
Deadline for paper submission: January 31, 2006
Notification of acceptance: March 1, 2006
Deadline for camera-ready papers: March 15, 2006
Early registration: March 15, 2006
SIS'06 in Indianapolis, Indiana, USA: May 12-14, 2006

Submission Information for Authors
Maximum Pages: 8
Paper Preparation Format: IEEE (Double-Column)
Sample available at http://www.computelligence.org/sis/paperform.html
Submit your paper (in PDF or Word format) as an email attachment to arun.ksla@gmail.com or khoslaak@nitj.in

Special Session Organizers

K.K. Aggarwal
Vice-Chancellor
GGS Indraprastha University Delhi 110006, INDIA

Shakti Kumar
Director
Center for Advanced Technologies
Haryana Engineering College Jagadhari 135003, INDIA

Arun Khosla
Sr Lecturer
Department of Electronics and Communication Engineering
National Institute of Technology Jalandhar 144 011 INDIA

Corresponding Organizer:
Arun Khosla, khoslaak@nitj.ac.in, arun.khosla@gmail.com
Phone: +91-181-2690301, 2690302 Ext. 364 (Office) +91-9888068332 (Mobile)
Fax:+91-181-2690320

8.5 Intelligent Systems and Computing: Theory and Applications

Posted by: Petros Ioannou (ioannou@usc.edu)
Date submitted: Jan. 5th, 2006

International Conference on Intelligent Systems and Computing: Theory and Applications
5-7 July 2006,
Ayia Napa, Cyprus
web site: http://www.cs.ucy.ac.cy/ISYC06

SCOPE:
System theory involves the use of intelligent techniques for modelling, sensing, control and computing in different disciplines and areas. While the approaches followed are often conceptually similar on the high level, they appear to be different on the lower levels. In addition the frequent use of different notation and language makes it awkward for people in one area to understand the approaches followed in another area. The scope of this conference is to gather researchers from different areas and disciplines to present results and participate in discussions under the common theme of intelligent systems and computing. These interactions will facilitate a better understanding of the diversity of the different approaches as well as of their similarities. In addition it will open the way for applying approaches that have been successful in one area to problem solving in different areas and applications.

Topics include:
Modeling and Control of Complex Systems, Computational Intelligence in Complex Systems, Neural and Fuzzy Systems, Signal and Image Processing Systems, Mobile Computing, Pervasive computing. Distributed databases, Large Space Structures, Aerospace Systems, Control of Flows, Biological Systems, Transportation Systems, Communication Networks, Wireless and Mobile Networks, Ad-hock and Sensor Networks, Robotics

Paper Submission: 20 February 2006
Notification of paper acceptance: 1st April 2006
Camera-Ready Version Due: 20th May 2006

8.6 Call for Papers: 2006 International Conference on Intelligent Computing

Posted by: De-Shuang Huang (dshuang@iim.ac.cn)
Date submitted: Jan. 8th, 2006

2006 International Conference on Intelligent Computing (ICIC'06)
http://www.ic-ic.org/2006/index.htm
August 16-19, 2006
Harbour Plaza, Kunming, China

Technically co-sponsored by the IEEE Computational Intelligence Society and International Neural Network Society

Paper Submission Deadline: March 1, 2006

2006 International Conference on Intelligent Computing (ICIC'06) will be held on August 16-19, 2006 in Kunming Yunnan Province, China (please refer to the conference website: http://www.ic-ic.org/2006/index.htm). This is the second International Conference on Intelligent Computing, which is built upon the success of ICIC'05 held in Hefei, China.

The intelligent computing annual conference primarily aims to promote the research, development and application of advanced intelligent computing techniques by providing a vibrant and effective forum across a variety of disciplines to be presented. This conference has a further aim of increasing the awareness of industry of advanced intelligent computing techniques and the economic benefits that can be gained by implementing them.

The concept of intelligent computing is quite fluid. It is seen to include a range of techniques such as artificial intelligence, evolutionary and adaptive computing, bio-inspired computing, fuzzy inference, case based and constrained reasoning, agents, networking and computer supported co- operative working, human computer interface issues, etc. Our theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Particularly in recent years, bio-inspired computing emerges as a key role in pursuing for novel technology. The resulting techniques vitalize life science engineering and daily life applications. In light of this trend, the theme for this conference is Emerging Intelligent Computing Technology and Applications.

Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology. Topics covering industrial issues/applications and academic research into intelligent computing will be welcome (The complete list of topic is available from Topics section at http://www.ic-ic.org/2006/index.htm).

The goal of this conference is to bring together the researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of Intelligent Computing fields. This conference will feature world-class plenary speakers, exhibitions, and a large number of oral and poster presentations and some special sessions focused on popular topics.

Prospective authors are invited to submit full-length papers by the submission deadline (March 1, 2006). The submission of a paper implies that the paper is original and has not been submitted to elsewhere for review or copyright protected and will be presented by one of the author(s) if accepted. All papers should be submitted electronically via Online Electronic Submission System. The initial submissions are acceptable in the formats of PDF, Word, or Postscript. Besides papers in regular sessions, papers in Special Sessions are also encouraged to submit for those new topics and innovative applications of established approaches. Each special session proposal should be well motivated and should consist of 5 to 8 papers. Each paper must have the title, authors with e-mails/web sites, and as detailed an abstract as possible. The special session organizer(s) contact information should also be included. All special session organizers must obtain firm commitments from their special session presenters and authors to submit apers or extended abstracts in a timely fashion (if the special session is accepted) and, of course, present them at the ICIC 2006.

All accepted papers will be published by Springer's Lecture Notes in Computer Science (LNCS)/Lecture Notes in Artificial Intelligence (LNAI), and a small selected number of papers will be extended and revised for possible inclusion in several main stream international journals.

Important Dates
Paper submission: 1 March 2006
Decision notification: 1 May 2006
Special session proposal: 31 January 2006
Tutorial proposal: 1 March 20
Camera-ready submission: 20 May 2006
Registration: 31 May 2006
Conference: 16-19 August 2006

For more information, please visit the conference websitehttp://www.ic-ic.org/2006/index.htm.

8.7 Brain Inspired Cognitive Systems BICS 06

Posted by: Jeanny S. Ryffel (planningc.ab.ca)
Date submitted: Jan. 12th, 2006

Brain Inspired Cognitive Systems
Island of Lesvos, Greece
Hotel Delfinia
October 10 - 14, 2006
http://www.icsc-naiso.org/conferences/bics2006/bics06-cfp.html
General Chair: Igor Aleksander, Imperial College London, U.K.

First International ICSC Symposium on Machine Models of Consciousness (MoC 2006)
Discussions of this new burgeoning paradigm
Chair: Ron Chrisley, University of Sussex, U.K.M

Third International ICSC Symposium on Biologically Inspired Systems (BIS 2006)
Broader issues in biological inspiration and neuromorphic systems
Chair: Leslie Smith, University of Stirling, U.K.

Second International ICSC Symposium on Cognitive NeuScience (CNS 2006)
From computationally inspired models to brain-inspired computation
Chair: Igor Aleksander, Imperl College London, U.K

Fourth International ICSC Symposium on Neural Computation (NC'2006)
Progress in neural systems
Chair: Amir Hussain, University of Stirling, U.K.

Why this conference, and who should attend:
Brain Inspired Cognitive Systems 2006 aims to bring together leading scientists nd engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, specifically, of the brain, d to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. The four major symposia are organized in patterns that encourage cross-fertilization across the symposia topics. This emphasizes that BICS 2006 will be a major point of contact for researchers and practitioners who can benefit from not only the major advances in their specialist fields but also from the diversity of each other's views. Each of the four mornings is devoted to papers that will be selected for their clear novelty and proven scientific impact, while the afternoons will provide scope for researchers to present theicurrent work and discuss their aims and ambitions. Debates across disciplines will unite researchers with differing perspectives.

Deadline for submissions: March 10, 2006

SUB-THEMES (including, but not limited to):

Models of consciousness: (MoC)
Global Workspace Theory
Imagination/synthetic phenomenology
Virtual Machine Approaches
Axiomatic Models
Control Theory/Methodology
Developmental/Infant Models
Will/volition/emotion/affect
Philosophical implications
Grounding in neurophysiology
Enactive approaches
Heterophenomenology

Cognitive Neuroscience (CNS)
Attentional Mechanisms
Cognitive Neuroscience of vision
CN of non-vision sensoryodalities
CN of volition
Affective Systems
Language
Cortical Models
Sub-Cortical Models
Cerebellar Models
Event location in the brain
Others

Biologically Inspired Systems (BIS)
Brain Inspired (BI) Vision
BI Audition and sound processing
BI Other sensory modalities
BI Motion processing
BI Robotics
BI Evolutionary systems
BI Oscillatory systems
BI Signal processing
BI Learning
Neuromorphic systems
Others

Neural Computation (NC)
NeuroComputational (NC) Hybrid Systems
NC Learning
NC Control Systems
NC Signal Processing
Architectures
Devices
Pattern Classifiers
Support Vector Machines
Fuzzy or Neuro-Fuzzy Systems
Evolutionary Neural Networks
Biological Neural Network Models
Applications
Others

INVITED SPEAKERS:
Christof Koch, Koch Laboratory CALTECH, USA
Shun-ichi Amari, RIKEN Brain Science Institute, Japan
Holk Cruse, University of Bielefeld, Germany
Pentti Haikonen, Nokia Research Center, Finland
Timothy K Horiuchi, University of Maryland, USA
John Taylor, Kings College, London, U.K.
Steve Potter, Gatech, USA
Jacek M Zurada, University of Louisville, USA
Marios Polycarpou, University of Cyprus, Cyprus
Others TBA

CONFERENCE VENUE:
Hotel Delphinia (http://www.molyvoshotel.com/) at the ancient village of Molivos (http://www.molivos.net/index.htm).

ORGANIZED BY:
ICSC Interdisciplinary Research, Planning Division Canada (http://www.icsc-naiso.org/html/

8.8 Spacial Issue of Neurocomputing, Elsevier

Posted by: Nadia Nedjah (nadia@eng.uerj.br)
Date submitted: Jan. 13th, 2006

Special Issue of Neurocomputing, Elsevier
http://www.elsevier.com/wps/find/journaldescription.cws_home/505628/description

Call for papers also available at
http://www.isebis.eng.uerj.br/Neurocomputing-SI.html

Genetic Algorithms (GA), Artificial Neural Networks (ANN) as well as Fuzzy Systems (FS) are becoming omnipresent in almost every intelligent system design. Just to name few, engineering, control, economics and forecasting are some of the scientific fields that enjoy the use of ANN and FS.

Unfortunately, the majority of the applications is complex and so requires a large computational effort to yield useful and practical results. Therefore, dedicated hardware for evolutionary, neural and fuzzy computation is becoming a key issue for designers. With the spread of reconfigurable hardware such as FPGAs and FPAAs, digital as well as analog hardware implementations of such computation become cost-effective. The focus of this special issue will be on all aspects of for high-speed hardware implementations for genetic algorithms, neural networks and fuzzy controllers. Hybrid implementations using co-design methodology are also welcome. The main topics can be listed as follows:

Topics include, but are not limited to:

• Hardware implementations of genetic algorithms;
• Hardware implementations of Neural Networks;
• Hardware implementations of fuzzy systems;
• Hardware/Software co-design of GA;
• Hardware/Software co-design of ANNs;
• Hardware/Software co-design of FSs;
• Hardware for hybrid systems

Important dates:
Paper Submission: 12 May 2006
Decision Notification: 29 September 2006
Camera-Ready Submission: 3 November 2006

If you intend to contribute to this special issue, please send a tentative title and abstract of your contribution to the guest editors at nadia@eng.uerj.br.

Guest Editors:

• Nadia Nedjah
  Electronics Engineering & Telecommunications
  Faculty of Engineering
  State University of Rio de Janeiro
  http://www.eng.uerj.br/~nadia/english.html
• Luiza de Macedo Mourelle
  Systems Engineering & Computation
  Faculty of Engineering
  State University of Rio de Janeiro
  http://www.eng.uerj.br/~ldmm

8.9 TFS Special Issue on Granular Computing

Posted by: N. R. Pal (nikhil@isical.ac.in)
Date submitted: Jan. 19th, 2006

CALL FOR PAPERS
IEEE Transactions on Fuzzy Systems: Special Issue on Granular Computing

IEEE Transactions on Fuzzy Systems (TFS) seeks original manuscripts for a Special Issue on Granular Computing scheduled to appear in early 2007.

Granular computing is an emerging computing paradigm of information processing. It concerns processing of complex information entities called "information granules", which arise in the process of abstraction of data and derivation of knowledge from information; this process is called information granulation. Granular Computing (GrC) is a general computation theory for effectively using granules such as classes, clusters, subsets, groups and intervals to build an efficient computational model for complex applications with huge amounts of data, information and knowledge. Though the label is relatively recent, the basic notions and principles of granular computing, under different names, have appeared in many related fields, such as information hiding in programming, granularity in artificial intelligence, divide and conquer in theoretical computer science, interval computing, cluster analysis, fuzzy and rough set theories, neutrosophic computing, quotient space theory, belief functions, machine learning, databases, and many others. In the past few years, we have witnessed a renewed and fast growing interest in GrC. Granular computing has begun to play important roles in bioinformatics, e-Business, security, machine learning, data mining, high-performance computing and wireless mobile computing in terms of efficiency, effectiveness, robustness and uncertainty. Generally speaking, information granules are collection of entities that are grouped together due to their similarity, functional adjacency, indistinguishability, coherency or the like. Although, at this point, it is difficult to give a precise and uncontroversial definition of granular computing, it can be described from several perspectives. Granular computing can be conceived as a category of theories, methodologies, techniques and tools that make use of information granules in the process of problem solving.

The special issue seeks original research work in theory and applications of Granular Computing. Submitted articles must not have been previously published or currently submitted for journal publication elsewhere and must meet the requirements of IEEE copyright policy. Processing of manuscripts will be done through Manuscript central as per standard TFS norms. Authors' information can be found at http://ieee-cis.org/pubs/tfs/

Important dates:
Submission Deadline: May 1, 2006
Completion of First Round of Reviews: August 1, 2006
Minor Revisions Due: Sept. 15, 2006
Final Acceptance Notification: October 15, 2006
Publication: Early 2007

Please address all correspondences regarding this special issue to the Guest Editors.

GUEST EDITORS
Professor T.Y. Lin, tylin@cs.sjsu.edu, San Jose State University
Lotfi Zedeh, zadeh@cs.berkeley.edu, UC-Berkeley

8.10 Special Issue of Computational Intelligence Magazine

Posted by: David Zhang (csdzhang@comp.polyu.edu.hk)
Date submitted: Jan. 22nd, 2006

CALL FOR PAPERS
IEEE Computational Intelligence Magazine (CIM)
Special Issue on CI Based Biometrics Technologies and Systems

A special issue of the IEEE Computational Intelligence Magazine (CIM) will be dedicated to Computational Intelligence based Biometric Technologies.

Perspective authors are invited to submit their original unpublished research and application development work. Comprehensive tutorial and survey papers will be also considered. The decision on the submissions is based on their originality, technical strength and the quality of content.

Computational intelligence methods, such as neural networks, fuzzy systems, rough sets, Bayesian networks, evolutionary computation, artificial intelligence, machine learning, expert systems, and multi-modal systems, have proved to be an effective and efficient technology to deal with biometric authentication and identification. This special issue will collate efforts and major achievements in different biometric recognition systems that contribute to robust solutions to the many challenging problems. The related topics include but are not limited to:

• Biometric System Traits: fingerprint, face, iris, palm, voice, hand, finger, retina, signature, keystroke, gait, gesture, odor, DNA/RNA, etc.
• Computational Intelligence Approaches: fuzzy systems, neural networks, rough sets, Bayesian networks, multi-modal biometric fusion, knowledge-based, off- and on-line methods, etc.
• Successful Industrial Implementations: integration, evaluation, large-scale performance estimation, parallel & pipeline, distribution, VLSI, etc.
• Application Oriented Development: security, immigration, access control, forensics, medicine, genetics, welfare, military, smart cards, PKI, embedded applications, personalization, etc.

Important Dates:
Paper submission due: July 15, 2006
Notification of acceptance: October 1, 2006
Final version due: November 15, 2006
Intended Issue of publication: February 2007

Manuscript submission:
Authors should send their softcopy to any guest editor by email.

Guest Editors:

• Dr. David Zhang, Chair Professor
  Director, Biometrics Research Centre
  Department of Computing
  The Hong Kong Polytechnic University
  Hung Hom, Kowloon, Hong Kong
  Csdzhang@comp.polyu.edu.hk
• Dr. Qinghan Xiao
  Defence Scientist
  Defence R&D Canada - Ottawa
  3701 Carling Avenue, Ottawa
  Ontario, Canada K1A 0Z4
  Qinghan.Xiao@drdc-rddc.gc.ca

8.11 2nd International Symposium on Evolving Fuzzy Systems

Posted by: Plamen Angelov (p.angelov@lancaster.ac.uk)
Date submitted: Jan. 25th, 2006

The deadline for paper submissions to the 2nd International Symposium on Evolving Fuzzy Systems (http://www.efs06.org ) is EXTENDED till 27 February 2006!

Take this opportunity to submit a high quality contribution and attend this specialized high quality event that will shape this emerging area of research. The Symposium (technically co-sponsored by Computational Intelligence Society and Systems, Man, and Cybernetics Society as well as by IFSA and EUSFLAT) is co-organized by InfoLab21, Lancaster University, UK and the Genetic Fuzzy Systems Task Force to the Technical Committee on Fuzzy Systems, CIS, IEEE and is planned to be a very focused single-track event with no parallel sessions. The Symposium will give an excellent opportunity to:

• meet the leaders in this emerging area (R. Yager, P. Bonissone, N. Kasabov, D. Filev, F. Gomide, O. Cordon, H. Ishibuchi, A. Abraham, B. Carse, J. Casillas, T. Sudkamp, F. Hoffmann, F. Klawonn, A. Dourado, G. Vachkov, H. Hagras, B. John, A. Bugarin, K. Valavanis etc. - for the full list of confirmed key note and invited speakers, please, visit http://www.efs06.org/program.php?PHPSESSID=40c960bbe1f9ddb3ace1ca4d7ba3b7ee
• see selected and focused presentations concerning advanced industrial applications of evolving fuzzy systems;
• discuss in a warm and close environment the problems, tendencies, and opportunities that this emerging area pose;
• win one of the series of 'best paper awards' generously provided by the co- sponsors of the event (BAE Systems, Nokia-UK, J&S Marine, and Retail Analytics, Ltd.);
• have a peer reviewed paper in a Proceeding published by IEEE after a careful selection.
• relax in the UK-leading all-year round resort overlooking Lake Windermere (a home of many World speed records), near Lancaster, UK and enjoy the dinner on a boat.

For details and updates, please, visit the Symposium web-site at http://www.efs06.org

8.12 2006 IEEE CIHSPS - Call for Papers

Posted by: Vincenzo Piuri (piuri@dti.unimi.it)
Date submitted: Feb. 1st, 2006

2006 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety
Alexandria, VA, USA
16-17 October 2006

SUBMIT DRAFT PAPERS BY 30 MAY 2006

The detailed call for papers and more information about the conference are available at http://cihsps.dti.unimi.it/cihsps2006/

8.13 2006 IEEE CIMSA - Call for Papers

Posted by: Vincenzo Piuri (piuri@dti.unimi.it)
Date submitted: Feb. 1st, 2006

2006 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications
La Coruna, Spain, 12-14 July 2006

SUBMIT EXTENDED ABSTRACTS OR DRAFT PAPERS BY 10 MARCH 2006

The detailed call for papers and more information about the conference are available at http://ewh.ieee.org/soc/im/cimsa/

8.14 CEC'06 Special Session on Differential Evolution

Posted by: Uday K. Chakraborty (uday@cs.umsl.edu)
Date submitted: Feb. 2nd, 2006

Deadline extended to February 15, 2006

Special session on Differential Evolution
IEEE Congress on Evolutionary Computation, CEC-2006
(IEEE World Congress on Computational Intelligence 2006)
Vancouver, BC, Canada, July 16-21, 2006

Original, unpublished work is invited. A submission should not exceed 8 single-spaced, two-column pages. The review process for the Special Session papers is the same as that of the regular ("at large") papers. Special Session papers will be reviewed by at least three referees and accepted papers will be included in the conference proceedings. While submitting your paper using the on-line paper submission system, please choose "Zh: Differential Evolution (Chakraborty)" as the "Main Research Topic".

More information:
WCCI 2006: www.wcci2006.org
Special Sessions: http://www.wcci2006.org/WCCI-Web_Special_Session.html
Instructions for Authors: http://www.wcci2006.org/WCCI-Web_paper_submit.html

Topics of interest include, but are not limited to:

• Theory of differential evolution
• Analysis of parameter settings (population size, scale factor, crossover rate)
• Multi-objective differential evolution
• Differential evolution for noisy problems
• Differential evolution for constrained optimization
• Hybridization (with local search and other soft computing approaches)
• Application in diverse domains (e.g., digital filter design, clustering, engineering design, bioinformatics, etc.)

Important dates
Submission: February 15, 2006
Notification: March 15, 2006
Camera-Ready: April 15, 2006
Conference: June 16-21, 2006

Special Session Chair:
Uday K. Chakraborty
Department of Mathematics and Computer Science
University of Missouri, St. Louis
MO 63121, USA
Phone: + 1 314 516 6339
Fax: +1 314 516 5400
http://www.cs.umsl.edu/~uday