Conference Statistics:
Submitted papers: 352
Accepted papers: 198
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.: Location: About Dallas:
Dallas, also known as Big D, was founded by John Neely Bryan in 1841. It is speculated that it was named after the George Mifflin Dallas who was the eleventh vice president of the United State. It was formally proclaimed as a city on the 2nd February of 1856 and legally became a city in 1871. Dallas is located in the state of Texas; it is the third-largest city of the state and the ninth-largest city of the USA. The city of Dallas covers 385 square miles and has approximately population equal to 1.2 million. The Globalization and World Cities Study Group & Network placed city of Dallas as the one of the eleven USA world-class cities. The city of Dallas is worldwide known as a centre for banking, insurance, business, transportation, computer technology, telecommunications and oil industry.
Many important events took place in Dallas. In 1958 Jack Kilby of the Texas Instruments invented the integrated circuit. On 22 November of 1963 a very well-known incidence took place in Dallas. It was the assassination of the President John F. Kennedy on the lm Street while his motorcade passed through Dealey Plaza in downtown Plaza. The spot where J.F. Kennedy died is one of the most famous touristic attractions of the city.
The city of Dallas offers a variety of entertainment schemes, with their majority located in downtown Dallas. It offers a unique blend of cosmopolitan flair and modern sophistication. The visitors of Dallas have plenty of enjoyable activities to spend their free time on. They could choose from museums, amusement parks, gardens, historic sites and arts. In addition Dallas is thriving with malls, shops, outlets, restaurants and nightlife. Visitors could go to the Dallas Museum of Art and the Morton H. Meyerson Symphony Center which are two of the most prominent features of the Dallas Art scene. Moreover there are several other museums in the Fair Park that tourists could visit, including the famous Science Place and the African American Museum.
http://www.dallas.world-guides.com/index.html . http://www.visitdallas.com/home/
.:Scientific Part
Review Process: Each paper was reviewed at least by 2 independent reviewers. The WSEAS Secretariat sent each paper to 4 reviewers. Some papers received reviews from 4 different referees. The WSEAS Secretariat forwarded these comments by personalized emails to the responsible for the correspondence author. The full list of the reviewers will be available in the web page: http://www.worldses.org/reviewers.htm
Only authors of those papers, which are found to have very positive response from 2 referees and which are modified sufficiently to take into account all the comments of (at least 2) referees of the conference are invited to send an extended version in the WSEAS Journals (WSEAS Transactions).
WSEAS sent a full report of the whole review process and the whole correspondence to the following international indexes that have recognized officially the Validity and the Reputation of the WSEAS Conferences: (see also: www.worldses.org/indexes )
Best Student Papers:
The Organizing Committee received the forms that the Session Chairmen filled in after the end of their Sessions and after additional evaluation and discussion decided the following.
The Criteria were
a) originality and scientific impact
b) good presentation
c) paper presented by a student
The results of this evaluation are:
The Best Student Paper Award for MATHEMATICAL METHODS AND COMPUTATIONAL TECHNIQUES IN ELECTRICAL ENGINEERING
was given to Ms. Grigoreta Sofia Moldovan for the paper:
A Formal Model For Clustering Based Aspect Mining
[Authors: Grigoreta Sofia Moldovan, Gabriela Serban]
The Best Student Paper Award for NON-LINEAR ANALYSIS, NON-LINEAR SYSTEMS AND CHAOS
was given to Ms. Maria Papadopoulou for the paper:
Antimonotonicity and Bubbles in a 4th Order Non Driven Circuit
[Authors: I. N. Stouboulos, I. M. Kyprianidis, M. S. Papadopoulou]
The Best Student Paper Award for WAVELET ANALYSIS & MULTIRATE SYSTEMS
was given to Mr. Omar Jose Lara for the paper:
Bearing Fault Diagnosis based on Neural Network Classification and Wavelet Transform
[Authors: Omar Jose Lara Castro, Cristina Castejon Sisamon, Juan Carlos Garcia Prada]
The Best Student Paper Award for DATA NETWORKS, COMMUNICATIONS and COMPUTERS
was given to Mr. Madalin Stefan Vlad for the paper:
Smart Card Technology used in Secured Personal Identification Systems
[Authors: Valentin Sgarciu, Madalin Stefan Vlad]
The Best Student Paper Award for DYNAMICAL SYSTEMS and CONTROL
was given to Mr. Kamuran Turkoglu for the paper:
H inf. Loop Shaping Robust Control vs. Classical PI(D) Control: A case study on the Longitudinal Dynamics of Hezarfen UAV
[Authors: Kamuran Turkoglu, Elbrous M. Jafarov]
The Best Student Paper Award for EDUCATIONAL TECHNOLOGIES
was given to Mr. Chia Feng Lin for the paper:
A Transformation Tool for Adapting SCORM Documents into Mobile Environment
[Authors: Chia-Feng Lin, Francis Lin, Shyan-Ming Yuan]
Indexes:
PROCEEDINGS: The Proceedings related to the Conference are covered by:
1. ISI (ISINET)
2. INSPEC (IET, former IEE)
3. CSA (Cambridge Scientific Abstracts)
4. ELSEVIER and Elsevier Bibliographic Database
5. ZENTRALBLATT
6. ULRICH
7. MATHSCINET of AMS (American Mathematical Society)
8. MATHEMATICAL REVIEWS of AMS (American Mathematical Society)
9. Directory of Published Proceedings
10. Computer Science Bibliography Administrator
11. American Chemical Society and its Index: Chemical Abstracts Service
12. European Library in Paris (France)
13. DEST Database (Australia)
14. Engineering Information
15. SCOPUS
16. EBSCO
17. EMBASE
18. Compendex (CPX)
19. GEOBASE
20. BIOBASE
21. BIOTECHNOBASE
22. FLUIDEX
23. OceanBase
24. BEILSTEIN Abstracts
25. World Textiles
26. MEDLINE
27. British Library
28. National Library of Greece
29. German National Library of Science and Technology
30. IARAS Index
JOURNALS:
The authors of the best papers will be invited to send extended versions of their papers to various international reputable journals. However, these papers must be of high-quality (break-through work).These journals are covered by:
1. ISI through the INSPEC (IEE)
2. INSPEC (IET, former IEE)
3. CSA (Cambridge Scientific Abstracts)
4. ELSEVIER and Elsevier Bibliographic Database
5. ZENTRALBLATT
6. MATHSCINET of AMS (American Mathematical Society)
7. ULRICH
8. MATHEMATICAL REVIEWS of AMS (American Mathematical Society)
9. Computer Science Bibliography Administrator
10. British Library
11. American Chemical Society and its Index: Chemical Abstracts Service
12. European Library in Paris (France)
13. DEST Database (Australia)
14. Swets Information Services
15. Engineering Information
16. SCOPUS
17. EBSCO
18. EMBASE
19. Compendex (CPX)
20. Geobase
21. BIOBASE
22. BIOTECHNOBASE
23. FLUIDEX
24. OceanBase
25. BEILSTEIN Abstracts
26. World Textiles
27. MEDLINE
28. Mayersche
29. Index of Information Systems Journals
30. National Library of Greece
31. IARAS Index
Plenary Speakers:
Data Mining and Fuzzy Neural Networks
Professor Arun Kulkarni
Computer Science Department
The University of Texas at Tyler, Tyler, TX 75799
Email: arun_kulkarni@uttyler.edu
Abstract: Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades. The World Wide Web as a global information system has flooded us with a tremendous amount of data. This explosive growth in data has generated a need for new techniques that can assist in transforming the vast amount of data into useful information. Many people treat data mining as a synonym for another popularly used term, Knowledge Discovery in Databases (KDD). Data mining is used in many practical applications. In biomedical engineering data mining techniques are used for identification of co-occurring gene sequences, linking genes to various diseases, mammography, MRI data analysis, and tissue analysis. In financial data analysis data mining tools are used for loan payment prediction, customer group identification, target marking, detection of money laundering and other financial crimes. In geosciences data mining techniques are used to analyze multispectral images for applications such as crop acreage estimation, environmental change detection, water resources management, land-use planning, and military reconnaissance. Most data mining problems are related to one of the four tasks: classification, estimation, prediction, or clustering. Many fuzzy neural network (FNN) models have been used in data mining. Until recently, FNNs have been viewed as “black boxes” which successfully classify data samples without anything for the user to see that explains how the network reached the decisions. Recently, there is a growing interest in the research community not only to understand how the neural network or the FNN arrived at a decision but how to decode information stored in the form of connection strengths in the network. One of major directions taken in this endeavor involves the extraction of fuzzy if-then rules from FNNs.
Fuzzy neural networks and data mining applications will be discussed.
Computational Trust Models and their Issues
Assc. Professor Keon Myung Lee
School of Electrical and Computer Engineering
Chungbuk National University
Gaeshin 12, Cheongju, Chungbuk
Korea
kmlee@cbnu.ac.kr
Abstract: With the proliferation of online businesses, lots of transactions take place among people and systems over the networks. Some participants have to inevitably run risks in their online transactions due to lack of public certification mechanisms. The trust information about counterparts would be helpful for participants to decide their deals. Trust models have been paid lots of attention in various fields. In this talk, we are first introduced the properties of trust and some related notions like reliability, reputation, belief, and subjective probability. Several trust models are then reviewed and compared in terms of their rationale and trust framework. Our model is presented in more detail which takes into account situational trust, dispositional trust, and general trust and makes use of both own experience and recommendations from others in order to get the trust value for counterparts. Some application examples and potential application domains of computational trust models and some related issues will be addressed.
Secure Power Systems Through Autonomous Microgrids
Assc. Professor Joydeep Mitra
The Klipsch School of Electrical & Computer Engineering
New Mexico State University
Las Cruces, New Mexico 88003, USA
jmitra@nmsu.edu
Abstract: In recent years, distributed energy resources (DER) have been receiving increasing attention worldwide, as alternatives to centralized generation. This is partly because of the many advantages offered by DERs, such as compact size, modularity, lower emission, and lower costs and losses in transmission and distribution (T&D), and partly because they are often an expedient alternative to the expensive and long drawn out processes of expanding or upgrading T&D. In the years to come, the penetration of microgrids is expected to grow dramatically. The bulk of DERs will be integrated into existing distribution systems, with necessary upgrades, and today’s distribution systems will evolve into microgrids. Microgrids can potentially make electric power systems highly reliable and secure. At the same time, the research and development necessary to make such secure microgrids a reality is diverse and cross-cutting, and offers myriad opportunities to engineers and scientists in a wide number of disciplines. This presentation discusses the tremendous potential of autonomous, customer-driven microgrids as tomorrow’s energy delivery system, and the opportunities for today’s scientists and engineers.
Some Features of the Game between the Supersonic ASM and the Counterattack AMM
Professor Fumiaki Imado
Department of Mechanical Systems Engineering
Shinshu University
4-17-1 Wakasato Nagano
Nagano 380-8553 JAPAN
E-mail imado@imado1.shinshu-u.ac.jp
Abstract: Since the Gulf war, defense missile systems against tactical ballistic missiles have been highlighted and the author also have published some studies. Recently some studies also have appeared, however, it seems that the threat of anti-surface-missiles (ASMs) to current ground sites and its countermeasures have not been sufficiently studied to date. A typical medium or long range surface-to-air missile (SAM) system is composed of ground radar sites for tracking and control, missiles, launchers, and other support systems. The system can intercept a subsonic cruising missile, but the possibility of intercepting a supersonic maneuvering missile is questionable. As is explained later, it is possible to produce a low cost long range ASM, with supersonic velocity and heavy maneuvers capable of attacking a SAM site. With the cost of one modern fighter, hundreds of such ASMs can be produced, therefore, it is highly probable that hundreds of ASMs will arrive in advance of the attacking aircraft. That is, for a SAM system to function effectively, a counter attack system against a flood of ASMs is essential. In this lecture, a cruising type ASM is briefly explained first. Next, a ballistic type ASM is explained. Then, a counterattack system by employing short range ground launched IR missiles is explained. In the following, some aspects of the game between the ground site defense system and the ASM are explained. The SAM site is assumed to be defended by guns and short range IR anti-missile missiles (AMMs). In the following, the characteristics of the AMM are explained. Next, some features of the game problem between the ASM and the AMM are studied and discussed in detail. A few comments are also added about the study. Finally the results are briefly summarized.
An Investigation on the Performance of Deterministic Approaches in Constrained Global Optimization Problems
Professor Linet Ozdamar
Izmir University of Economics
Izmir, Turkey
Email: linetozdamar@lycos.com , lozdamar@hotmail.com
Abstract: Constrained global optimization problems (COP) are encountered in many scientific fields concerned with industrial applications such as kinematics, chemical process optimization, molecular design, etc. In this speech, we would like to convey a recent investigation on the performance of several deterministic commercial optimization solvers in dealing with the COP. Additionally, we also discuss a variety of new efficient interval partitioning approaches (IP) that involve a new parallel sub-space partitioning method as well as a generic adaptive tree search approach that can also be implemented in non-interval Branch and Bound algorithms. New and existing IP methods are compared with commercial solvers on a test bed of COP benchmarks from the literature. The findings indicate that IP algorithms can be viable methods to use in tackling challenging COPs.
Forecasting Techniques based on Statistical and Neural Network Modeling of the Data Provided by the Texas Coastal Ocean Observation Network (TCOON)
Professor Alexey L Sadovski
Department of Mathematics and Statistic
Texas A & M University-Corpus Christi
TX 78412
alexey.sadovski@tamucc.edu
Abstract: The paper deals with different forecasting techniques based on statistical and neural network modeling of the data provided by The Texas Coastal Ocean Observation Network (TCOON) as well as other acquisition tools such as planes and remotely controlled shallow water boat. Tools and prediction methods are developed in the College of Science and Technology of Texas A&M University-Corpus Christi. TCOON consists of more than 50 data gathering stations located along the Texas Gulf coast from the Louisiana to Mexico borders. Data sampled at these stations include: precise water levels, wind speed and direction, atmospheric and water temperatures, barometric pressure, and water currents. The measurements collected at these stations are often used in legal proceedings such as littoral boundary determinations; therefore data are collected according to National Ocean Service standards. Some stations of TCOON collect parameters such as turbidity, salinity, and other water quality parameters been in operation since 1988. Since these water levels are the bases for a number of research calculations, such as, oil-spill response, navigation safety, environmental research, and recreation, it is essential to be able to make these water level data as correct and spike free as possible.
Scale Invariant Model of Statistical Mechanics and the Connection between the Problem of Turbulence and Quantum Mechanics
Assc. Professor Siavash H. Sohrab
Robert McCormick School of Engineering and Applied Science
Department of Mechanical Engineering
Northwestern University, Evanston, Illinois 60208
s-sohrab@northwestern.edu
Abstract: In the classical kinetic theory of gas by Maxwell and Boltzmann, particles are treated as point-mass singularities without any spatial extent. However, it is well known that in reality molecules and atoms are not point-mass singularities but rather finite-size stable composite structures made of many smaller more elementary particles. Therefore, the fact that the classical approach of assuming point-mass entities has been successful in the description of molecular dynamics suggests that this same approach could be generalized to macroscopic scales. Following such guidelines, a scale-invariant model of statistical mechanics is introduced that is applicable from cosmic to photonic scales. The invariant forms of conservation equations will be presented and their solutions for various classical problems of fluid mechanics at molecular-dynamics, cluster-dynamic and eddy-dynamic scales will be examined. The implication of the model to a modified statistical theory of turbulence and the associated closure problem will be assessed. The invariant forms of the Planck law of energy distribution and the Schrodinger equation will be described and the connection between the problem of turbulence on the one hand and quantum mechanics on the other hand will be examined. Finally, possible implication of the model to the important problem of Riemann hypothesis and the Hilbert-Polya conjecture will be discussed.
Estimation and Filtering of Multifractional Gaussian Processes
Professor Sergio Bianchi
Head of Department
DIMET, Faculty of Economics
Via S. Angelo
03043 CASSINO (FR), ITALY
sbianchi@eco.unicas.it
Abstract: The lecture will concern two related problems arising when multifractional Gaussian processes are used to model actual time series with a particular look to financial data. The first one is the estimation of the Holder function characterizing the multifractional Brownian motion. In order to address this problem a class of estimators originally used to calculate the parameter of a fractional Brownian motion is generalized to cover the multifractional case. In particular, we discuss the rate of convergence of the estimators, which is proved to be very good, and a technique, obtained as by-product, able to discriminate between unifractal and multifractal processes even without direct estimation of the Holder function. Applications to simulated and actual financial time series are considered.
The second issue, intimately related to the estimation problem, concerns the decomposition of the sample paths of a multifractional Brownian motion into sub sequences, each characterized by a different value of H. We show that filtering the whole time series using the method we suggest produces a nontrivial bias increasing with the strength of the dependence structure of the original dataset. Relevant applications concern for example the evaluation of financial risk.
.:Social Part (Coffee-Breaks, Banquet, Excursions)
The Coffee, Tea, Sweets, Cakes were available for the Guests during the coffee-breaks.
The Banquet was superb, fantastic with many surprises. It took place in a the Taverna of the Hotel from 20:00 until 23:00 in November 21.
Participants enjoyed a wonderful self-service buffet (more than 40 courses) with many attractions, country music, singers and american dance (see the photos above).
Several Excursions and short visits to the sightseeings of the town took place before and after the WSEAS Conferences.