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Session 1
Hussam M. Dahwa Abdulla, Vaclav Snasel:
hussamdahwa@hotmail.com,
vaclav.snasel@vsb.cz
Dept. of Computer Science, Faculty of Electrical
Engineering and Computer Science
VSB - Technical University of Ostrava, Czech Republic
Web Mining
Web data management has become a critical emerging
research area, due to the exponential increase in the
information circulation and dissemination over the Web.
Several research efforts have already appeared in the
area of Web data mining and this field seems to be of
interest for a wide academic and technical community.
Data mining, also known as knowledge-discovery, is the
practice of automatically searching large stores of data
for meaningful patterns (knowledge). With the advances
in the process of data collection, the 1990s has
witnessed an explosion in the growth of data available
online. This coupled with the stellar advances in
computing technologies really spruced up "Data Mining".
The web is the largest dynamic and online store known
today. Web mining refers to the process of extracting
knowledge from web pages by exploring their contents;
the hyperlinks that connect these pages; or usage
patterns of users; or Social Networks of users of these
pages.
Session 2
Mohammed Hamden:
mashamdan@yahoo.com
Department of Mechanical Engineering, Faculty of
Engineering and Technology, University of Jordan
Energy and Alternative Fuels
The continuous growth of petroleum price, the gradual
decrease in its reserves of conventional energy
resources, and the environmental problems created by the
combustion of this fuel, have placed great pressure on
energy supplies. Consequently researchers world wide
are working hard for alternative energy sources such as
biofuels, emulsified fuels and renewable energy
sources. Energy consumption in the transportation
sector in the world represents 26% of the total energy
consumption. So far almost all of this quantity is
consisting of crude oil derivatives. Currently, biofuel
and emulsified fuels are being used on very limited
scale as an alternative fuel to power internal
combustion engines in few countries, with biofuel being
derived from agricultural product, which will increase
the food shortage in the world. To solve crude oil
depletion without affecting the food status in the
world, biofuel has to be derived from other sources
Session 3
Kusum Deep, Millie Pant:
kusumfma@iitr.ernet.in;
kusumdeep@gmail.com;
millifpt@iitr.ernet.in;
milliepant.iitr@gmail.com
Department of Mathematics, Indian Institute of
Technology
Nature Inspired Optimization Techniques and
Applications
Nature Inspired Optimization (NIO) Techniques are
attractive global optimization methods inspired by the
various phenomena arising in nature. They include
Genetic Algorithms, Memetic Algorithms, Differential
Evolutions, Particle Swarm Optimization, Glowworm Swarm
Optimization, Bee Algorithms, Bacterial Foraging, Ant
Colony Algorithms, etc. These are relatively a newer
addition to the class of numerical optimization
algorithms. These methods have been successfully applied
to a wide range of real-world application problems. This
special session seeks to bring forward and highlight the
latest developments in this promising research area by
bringing together researchers and practitioners. Authors
are invited to submit their original and unpublished
work to this Special Session
Session
4
U. Sikoska, D. Davcev, Jordan Sikoski:
jordans@t-home.mk
Space and Time in Sensor Networks
Wireless sensor networks are an increasingly attractive
means to bridge the gap between the physical and virtual
world. A WSN consists of large numbers of cooperating
small-scale nodes, each capable of limited computation,
wireless communication, and sensing. In a wide variety
of application areas including geophysical monitoring,
precision agriculture, habitat monitoring,
transportation, military systems and business processes,
WSNs are envisioned to be used to fulfill complex
monitoring tasks. With this new class of networks also
come new challenges in many areas of the system’s
design. Space and time play a crucial role in wireless
sensor networks, since sensor nodes are used to
collaboratively monitor physical phenomena and their
spatio-temporal properties. Consequently, a number of
techniques and distributed algorithms for location
estimation and time synchronization have been developed
specifically for sensor networks. However, research in
these two domains has been performed by mostly separated
research communities. Wireless sensor networks (WSNs)
consist of large populations of wirelessly connected
nodes, capable of computation, communication, and
sensing. Sensor nodes cooperate in order to merge
individual sensor readings into a high-level sensing
result, such as integrating a time series of position
measurements into a velocity estimate. The physical time
of sensor readings is a key element in this process
called data fusion. Hence, time synchronization is a
crucial component of WSNs. We argue that time
synchronization schemes developed for traditional
networks are ill-suited for WSNs and suggest more
appropriate approaches.
A closer look on both research domains reveals that
there are many similarities. This does affect a variety
of aspects of location estimation and time
synchronization, ranging from applications and
requirements to basic approaches and concrete
algorithmic techniques. The purpose of this paper is to
make this close affinity explicit in order to further a
better understanding of both domains.
Session 5
Hussein A. lafta:
hzazmk@yahoo.com
Computer science dep., College of science for women,
Babylon university Babylon Iraq
Petri Nets Applications
Modeling and solving life applications by using Petri
Net with others, includes: fuzzy, genetic, neural nets,
color, time, stochastic, mobile control, ciphering
message on reliable channel and QOS used in network
communications.
Session 6
Chanwit Boonchuay:
chanwit.boonchuay@ait.ac.th
Energy Field of Study, Asian Institute of Technology,
Thailand
Computational Intelligent Applications to Power
Systems
Intelligent-based approaches are widely applied to power
system tasks such as operating, monitoring, and
planning, etc. This session will address various
intelligent techniques, i.e., simulate annealing,
artificial neural network, fuzzy logic, genetic
algorithms, bees algorithms, evolutionary algorithms,
ant colony optimization, and particle swarm optimization
applied to power system problems. Furthermore, novel and
modified intelligent techniques for power system
applications will be discussed.
Session 7 |
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M.T. Benmessaoud:
benmessaoudtarik@yahoo.fr
Department of Electrical Engineering, Faculty of
Electrical Engineering,
University of Science and Technology of Oran, Algeria
Autonomous Systems for Energy Production
In the world there
are many isolated sites, powered by autonomous systems
of power generation. These generators use local
renewable sources. There are photovoltaic panels, wind
turbines and microturbines. Electricity from renewable
sources is intermittent, dependent on climatic
conditions.
These renewable generators are coupled to a storage
system providing continuous availability of energy. To
improve hybrid systems while preserving their quality of
respect for the environment, an idea that appeared in
recent years, is to use hydrogen to store energy in the
long term. The development of hydrogen technologies has
been very important over the last ten years. Indeed, the
gas can be produced by an electrolyzer, stored without
significant loss regardless of the storage period, and
then converted into electricity in a fuel cell. These
systems, called Solar-Hydrogen-Hydrogen or PV, have many
advantages. Without moving parts, the electrolyzer and
fuel cells produce very little noise. In addition, we
expect these components high reliability, low operating
constraints and limited maintenance. Our energy future
must be based on clean energy with significant
resources. Renewables are the best candidates but the
intermittent production needs to find effective means of
storing and protecting the environment. A system
electrolyser / fuel cell can store electricity via a
storage form of gas and, in addition, generate heat.
Session 8
Muhammad H. Rais, Syed Manzoor Qasim:
mhrais@yahoo.com.au,
mhrais@ksu.edu.sa
King Saud University, College of Engineering, Electrical
Engineering Department, Riyadh, Saudi Arabia
FPGA-Based Digital Circuits and System Design
Field Programmable Gate Arrays (FPGAs) have
emerged to be a mainstream technology for realizing
digital systems. FPGAs offer the design flexibility of a
software and speed of hardware (ASICs). We are
soliciting original papers describing novel research and
developments in the following (and related) areas of
interest:
1.Implementation of Digital circuits and System designs
on FPGA to achieve high-performance, low power, or
high-reliability.
2.Applications of FPGA including, but not limited, to
Communications and networking, Cryptography, Computer
Vision, Arithmetic Circuits, Digital Signal Processing,
Application Acceleration, Aerospace, Image Processing,
Industrial Applications, and Embedded Systems
Session 9
Pandian Vasant:
pandian_vasant@yahoo.com,
pvasant@gmail.com
Engineering Mathematics Programme, FASD, University
Technology Petronas, Malaysia
Hybrid Optimization Techniques And Its Application To
Engineering and Financial Systems
Since the beginning of the modern industrial revolution,
optimization techniques have become one of the most
important decision making areas concerning industrial
and financial systems. Modern optimization also plays an
important role in service centered operations, and has
recently received much more attention with the
development of engineering and financial systems. The
failure of engineering and financial systems due to
uncertainties in fuzzy environment and the cause for
natural disaster and man made chaotic problems possibly
can be handled by an advanced modern optimization
techniques.
A great emphasis in this session is given to newly
developed hybrid optimization (HO) techniques. These
optimization methodologies are based on a mathematical
framework that was developed by logicians, engineer,
analyst and computer scientists to study the intrinsic
difficulty of algorithms and problems. It has proven
very useful for real world practical problem solving in
engineering and financial systems.
For the special session we seek original work that has
not been published or considered for publication of
topics such as, but not confined to: Fuzzy logic,
Genetic algorithms, Neural network, Evolutionary
computation, Tabu search, Simulated annealing, Rough
set, Direct search, Cultural algorithms, Artificial
immune systems, Particle swarm optimization, Ant colony
optimization, Application of HO in engineering, and
Application of HO in finance
Session 10
Herman Mawengkang, Erik Kropat, Gerhard Wilhelm
Weber:
hmawengkang@yahoo.com,
erik.kropat@unibw.de,
gweber@metu.edu.tr
The University of Sumatera Utara,
FMIPA USU, KAMPUS USU, Medan, Indonesia
Universitaet der Bundeswehr, Munich,
Germany
Institute of Applied Mathematics,
METU, Ankara, Turkey
Operation Research
This session displays some classical
and modern application areas of Operational Research
(OR). In its early years, OR was introduced to resolve
"operational" problems of the protection of countries
and their freedom and, then, to give answers to decision
problems from the worlds of business, economics and,
more and more, technology related. In fact, OR has
always been following an interdisciplinary approach, and
such that the use of quantitative mathematical methods
could become helpful for the handling of real-world
problems. During the last decade, urgent questions and
challenges from environmental protection, health care,
the entire sectors of computational, biology and
medicine, of social complexity, of development, in
particular, of the less privileged ones on earth, and of
sustainability, widened and enriched the scope of OR.
Since OR is a huge and rapidly growing area, in our
lectures, we may spend some extra care on the employment
of mathematical methods, in particular, of optimization
theory, which are considered to be a modern and exciting
scientific "key technology".
Session 11
Boonruang Marungsri:
bmshvee@sut.ac.th
School of Electrical Engineering, Suranaree University
of Technology, Muang District, Nakhon Ratchasima,
Thailand
Aging Deterioration of
High Voltage Insulating Materials and
Life Time Modelling
Generally in services, an insulation system subjected to
one or more stress that causes irreversible changes of
insulating material properties with time, thus reducing
progressively the attitude of insulation in enduring the
stress itself. This process is called aging
deterioration and ends when the insulation is no more
able to withstand the applied stress. The relevant time
is the time-to- failure or time-to-breakdown,
alternatively called insulation life time. Insulation
life time modelling consists of looking or adequate
relationships between insulation life time and the
magnitude of the stress applied to it. In the case of
electrical insulation, the stresses most commonly
applied in service are electric field due to voltage and
temperature due to loss, but also other stresses, such
as mechanical stresses (bending, vibration) and
environmental stresses (such as pollution, humidity) can
be present.
Session 12
Manu Pratap Singh:
manu_p_singh@hotmail.com
Department of Computer Science, Institute of Computer
and Information Science, Dr. B. R. Ambedkar University,
Agra -Uttar Pradesh, India
Multi objective Optimization with soft computing
The soft computing techniques are widely used for the
optimization of various real world problems since very
long. These techniques include neural network
optimization with Hopfield neural network model,
constraint free optimization with feedforward neural
network model, Gradient free optimization with Genetic
algorithm and many more hybrid evolutionary optimization
techniques are available. Most of the time in all these
techniques the problem of real world has been solved
with single objective i.e. either to minimize or
maximize the objective or cost function. The new trends
in this direction are for optimization of more than one
objective function. It means that the minimization of
one objective and maximization of another objective
function. As for as the case of pattern storage and its
recalling it is expected that the neural network will
occupy correct global minimum and simultaneously
minimize the time of recalling with minimization of
error in recalling and also maximize the pattern storage
capacity. This can also apply for the image storage and
its recalling even though the presented prototype input
of image is not complete or noisy. We can also explore
this possibility to the feedforward neural networks for
the pattern classification and mapping. The network is
expected to minimize the global error with minimum
epochs and maximize the convergence of the network for
efficient generalization and approximation. There are
different approaches can be employee together for
accomplish the task of multi objective optimization.
This session explore the possibility of various
techniques in combination for the multi objective
optimization for the various real world problems like
pattern recognition, image reconstruction, automated
controlling system, path finding problems and many more.
The most common approaches consist with evolutionary
neural network system, neural fuzzy system, Hybrid
evolutionary systems and hybrid neural networks. In this
session the emphasis will be on the discussion of
various evolutionary hybrid neural networks system for
the solution of various real world problems with their
multi objective optimal solutions.
Session 13
Niaz Ahmed Wassan:
N.A.Wassan@kent.ac.uk
Management Science Undergraduate Programme, Kent
Business School, Canterbury, UK
Heuristics/Metaheuristics Applications
Heuristics/Metaheuristics have been very successful in
tackling variety of optimization problems in areas such
as Industry, Business, logistics, Computer Science,
Engineering, Government etc. For this special session we
are inviting papers contributing to methodological
developments and successful implementations of
Heuristics/Metaheuristics and their hybrids. Special
emphasis is on Logistics and Supply Chains but other
implementations will also be considered
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