Abstract: CEMTool is a command style design and analyzing
package for scientific and technological algorithm and a matrix based
computation language. In this paper, we present new 2D & 3D
finite element method (FEM) packages for CEMTool. We discuss
the detailed structures and the important features of pre-processor,
solver, and post-processor of CEMTool 2D & 3D FEM packages. In
contrast to the existing MATLAB PDE Toolbox, our proposed FEM
packages can deal with the combination of the reserved words. Also,
we can control the mesh in a very effective way. With the introduction
of new mesh generation algorithm and fast solving technique, our
FEM packages can guarantee the shorter computational time than
MATLAB PDE Toolbox. Consequently, with our new FEM packages,
we can overcome some disadvantages or limitations of the existing
MATLAB PDE Toolbox.
Abstract: Fuel cells have become one of the major areas of
research in the academia and the industry. The goal of most fish
farmers is to maximize production and profits while holding labor
and management efforts to the minimum. Risk of fish kills, disease
outbreaks, poor water quality in most pond culture operations,
aeration offers the most immediate and practical solution to water
quality problems encountered at higher stocking and feeding rates.
Many units of aeration system are electrical units so using a
continuous, high reliability, affordable, and environmentally friendly
power sources is necessary. Aeration of water by using PEM fuel cell
power is not only a new application of the renewable energy, but
also, it provides an affordable method to promote biodiversity in
stagnant ponds and lakes. This paper presents a new design and
control of PEM fuel cell powered a diffused air aeration system for a
shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence
(AI) techniques control is used to control the fuel cell output power
by control input gases flow rate. Moreover the mathematical
modeling and simulation of PEM fuel cell is introduced. A
comparison study is applied between the performance of fuzzy logic
control (FLC) and neural network control (NNC). The results show
the effectiveness of NNC over FLC.
Abstract: Duplicated region detection is a technical method to
expose copy-paste forgeries on digital images. Copy-paste is one
of the common types of forgeries to clone portion of an image
in order to conceal or duplicate special object. In this type of
forgery detection, extracting robust block feature and also high
time complexity of matching step are two main open problems.
This paper concentrates on computational time and proposes a local
block matching algorithm based on block clustering to enhance time
complexity. Time complexity of the proposed algorithm is formulated
and effects of two parameter, block size and number of cluster, on
efficiency of this algorithm are considered. The experimental results
and mathematical analysis demonstrate this algorithm is more costeffective
than lexicographically algorithms in time complexity issue
when the image is complex.
Abstract: detecting the deadlock is one of the important
problems in distributed systems and different solutions have been
proposed for it. Among the many deadlock detection algorithms,
Edge-chasing has been the most widely used. In Edge-chasing
algorithm, a special message called probe is made and sent along
dependency edges. When the initiator of a probe receives the probe
back the existence of a deadlock is revealed. But these algorithms are
not problem-free. One of the problems associated with them is that
they cannot detect some deadlocks and they even identify false
deadlocks. A key point not mentioned in the literature is that when
the process is waiting to obtain the required resources and its
execution has been blocked, how it can actually respond to probe
messages in the system. Also the question of 'which process should
be victimized in order to achieve a better performance when multiple
cycles exist within one single process in the system' has received
little attention. In this paper, one of the basic concepts of the
operating system - daemon - will be used to solve the problems
mentioned. The proposed Algorithm becomes engaged in sending
probe messages to the mandatory daemons and collects enough
information to effectively identify and resolve multi-cycle deadlocks
in distributed systems.
Abstract: Due to the excess of a vehicle operation through its life, some elements may face failure and deteriorate with time. This leads us to carry out maintenance, repair, tune up or full overhaul. After a certain period, the vehicle elements deteriorations increase with time which causes a very high increase of doing the maintenance operations and their costs. However, the logic decision at this point is to replace the current vehicle by a new one with minimum failure and maximum income. The importance of studying vehicle replacement problems come from the increase of stopping days due to many deteriorations in the vehicle parts. These deteriorations increase year after year causing an increase of operating costs and decrease the vehicle income. Vehicle replacement aims to determine the optimum time to keep, maintain, overhaul, renew and replace vehicles. This leads to an improvement in vehicle income, total operating costs, maintenance cost, fuel and oil costs, ton-kilometers, vehicle and engine performance, vehicle noise, vibration, and pollution. The aim of this paper is to find the optimum replacement policies of Kuwait Passenger Transport Company (KPTCP) fleet of busses. The objective of these policies is to maximize the busses pure profits. The dynamic programming (D.P.) technique is used to generate the busses optimal replacement policies
Abstract: In this paper a new Genetic Algorithm based on a heuristic operator and Centre of Mass selection operator (CMGA) is designed for the unbounded knapsack problem(UKP), which is NP-Hard combinatorial optimization problem. The proposed genetic algorithm is based on a heuristic operator, which utilizes problem specific knowledge. This center of mass operator when combined with other Genetic Operators forms a competitive algorithm to the existing ones. Computational results show that the proposed algorithm is capable of obtaining high quality solutions for problems of standard randomly generated knapsack instances. Comparative study of CMGA with simple GA in terms of results for unbounded knapsack instances of size up to 200 show the superiority of CMGA. Thus CMGA is an efficient tool of solving UKP and this algorithm is competitive with other Genetic Algorithms also.
Abstract: The database reverse engineering problems and
solving processes are getting mature, even though, the academic
community is facing the complex problem of knowledge transfer,
both in university and industrial contexts. This paper presents a new
CASE tool developed at the University of Jordan which addresses an
efficient support of this transfer, namely UJ-CASE-TOOL. It is a
small and self-contained application exhibiting representative
problems and appropriate solutions that can be understood in a
limited time. It presents an algorithm that describes the developed
academic CASE tool which has been used for several years both as
an illustration of the principles of database reverse engineering and
as an exercise aimed at academic and industrial students.
Abstract: Data mining techniques have been used in medical
research for many years and have been known to be effective. In order
to solve such problems as long-waiting time, congestion, and delayed
patient care, faced by emergency departments, this study concentrates
on building a hybrid methodology, combining data mining techniques
such as association rules and classification trees. The methodology is
applied to real-world emergency data collected from a hospital and is
evaluated by comparing with other techniques. The methodology is
expected to help physicians to make a faster and more accurate
classification of chest pain diseases.
Abstract: In this paper, linear multistep technique using power
series as the basis function is used to develop the block methods
which are suitable for generating direct solution of the special second
order ordinary differential equations with associated initial or
boundary conditions. The continuous hybrid formulations enable us
to differentiate and evaluate at some grids and off – grid points to
obtain two different four discrete schemes, each of order (5,5,5,5)T,
which were used in block form for parallel or sequential solutions of
the problems. The computational burden and computer time wastage
involved in the usual reduction of second order problem into system
of first order equations are avoided by this approach. Furthermore, a
stability analysis and efficiency of the block methods are tested on
linear and non-linear ordinary differential equations and the results
obtained compared favorably with the exact solution.
Abstract: The solution algorithm, based on Lagrangian relaxation, a sub-gradient method and a heuristic to find the upper bound of the solution, is proposed to solve the coordinated fleet routing and flight scheduling problems. Numerical tests are performed to evaluate the proposed algorithm using real operating data from two Taiwan airlines. The test results indicate that the solution algorithm is a significant improvement over those obtained with CPLEX, consequently they could be useful for allied airlines to solve coordinated fleet routing and flight scheduling problems.
Abstract: Linear induction motors are used in various industries
but they have some specific phenomena which are the causes for
some problems. The most important phenomenon is called end effect.
End effect decreases efficiency, power factor and output force and
unbalances the phase currents. This phenomenon is more important
in medium and high speeds machines. In this paper a factor, EEF , is
obtained by an accurate equivalent circuit model, to determine the
end effect intensity. In this way, all of effective design parameters on
end effect is described. Accuracy of this equivalent circuit model is
evaluated by two dimensional finite-element analysis using ANSYS.
The results show the accuracy of the equivalent circuit model.
Abstract: In this paper, we propose a new method to distinguish
between arousal and relaxation states by using multiple features
acquired from a photoplethysmogram (PPG) and support vector
machine (SVM). To induce arousal and relaxation states in subjects, 2
kinds of sound stimuli are used, and their corresponding biosignals are
obtained using the PPG sensor. Two features–pulse to pulse interval
(PPI) and pulse amplitude (PA)–are extracted from acquired PPG
data, and a nonlinear classification between arousal and relaxation is
performed using SVM.
This methodology has several advantages when compared with
previous similar studies. Firstly, we extracted 2 separate features from
PPG, i.e., PPI and PA. Secondly, in order to improve the classification
accuracy, SVM-based nonlinear classification was performed.
Thirdly, to solve classification problems caused by generalized
features of whole subjects, we defined each threshold according to
individual features.
Experimental results showed that the average classification
accuracy was 74.67%. Also, the proposed method showed the better
identification performance than the single feature based methods.
From this result, we confirmed that arousal and relaxation can be
classified using SVM and PPG features.
Abstract: In this article, some methods are mentioned for developing the theatrical language by giving information of “theatrical language" since the arising of the language in obsolete terms, and today, and also by examining the problems. Being able to talk meaningfully in the theater stage is a skillful art. Maybe, to be able to convey the idea of the poet, his/her world outlook and his/her feelings from the bottom of the heart as such, also conveying the speech norms without breaking them to the ear of audience in a fascinating way in adverse of a repellent way is the most difficult one. Because of this, “the word is the mirror of the idea". The importance of the theatrical language should not be perceived as only a post, it is “as the yarn that the culture carpet is weaved from". Thereby, it is a tool which transposes our culture and our life style from generation to generation. At the time of creativeness, the “word" comes out from the poet, “the word and feeling" art comes out from the actor. If it was not so, the audience could read the texts of the work himself/herself instead of going to the theater in order to see the performance. The fundamental works by the Turkish, Kazakh and English scientists have been taken as a basis for the research done.
Abstract: Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.
Abstract: The objective of this paper is the introduction to a
unified optimization framework for research and education. The
OPTILIB framework implements different general purpose algorithms
for combinatorial optimization and minimum search on standard continuous
test functions. The preferences of this library are the straightforward
integration of new optimization algorithms and problems
as well as the visualization of the optimization process of different
methods exploring the search space exclusively or for the real time
visualization of different methods in parallel. Further the usage of
several implemented methods is presented on the basis of two use
cases, where the focus is especially on the algorithm visualization.
First it is demonstrated how different methods can be compared
conveniently using OPTILIB on the example of different iterative
improvement schemes for the TRAVELING SALESMAN PROBLEM.
A second study emphasizes how the framework can be used to find
global minima in the continuous domain.
Abstract: In this paper, we establish existence and uniqueness of
solutions for a class of inverse problems of degenerate differential
equations. The main tool is the perturbation theory for linear operators.
Abstract: The advent of modern technology shadows its impetus repercussions on successful Legacy systems making them obsolete with time. These systems have evolved the large organizations in major problems in terms of new business requirements, response time, financial depreciation and maintenance. Major difficulty is due to constant system evolution and incomplete, inconsistent and obsolete documents which a legacy system tends to have. The myriad dimensions of these systems can only be explored by incorporating reverse engineering, in this context, is the best method to extract useful artifacts and by exploring these artifacts for reengineering existing legacy systems to meet new requirements of organizations. A case study is conducted on six different type of software systems having source code in different programming languages using the architectural recovery framework.
Abstract: Smoke discharging is a main reason of air pollution
problem from industrial plants. The obstacle of a building has an
affect with the air pollutant discharge. In this research, a mathematical
model of the smoke dispersion from two sources and one source with
a structural obstacle is considered. The governing equation of the
model is an isothermal mass transfer model in a viscous fluid. The
finite element method is used to approximate the solutions of the
model. The triangular linear elements have been used for discretising
the domain, and time integration has been carried out by semi-implicit
finite difference method. The simulations of smoke dispersion in
cases of one chimney and two chimneys are presented. The maximum
calculated smoke concentration of both cases are compared. It is then
used to make the decision for smoke discharging and air pollutant
control problems on industrial area.
Abstract: Selecting the word translation from a set of target
language words, one that conveys the correct sense of source word
and makes more fluent target language output, is one of core
problems in machine translation. In this paper we compare the 3
methods of estimating word translation probabilities for selecting the
translation word in Thai – English Machine Translation. The 3
methods are (1) Method based on frequency of word translation, (2)
Method based on collocation of word translation, and (3) Method
based on Expectation Maximization (EM) algorithm. For evaluation
we used Thai – English parallel sentences generated by NECTEC.
The method based on EM algorithm is the best method in comparison
to the other methods and gives the satisfying results.
Abstract: Clustering techniques have received attention in many areas including engineering, medicine, biology and data mining. The purpose of clustering is to group together data points, which are close to one another. The K-means algorithm is one of the most widely used techniques for clustering. However, K-means has two shortcomings: dependency on the initial state and convergence to local optima and global solutions of large problems cannot found with reasonable amount of computation effort. In order to overcome local optima problem lots of studies done in clustering. This paper is presented an efficient hybrid evolutionary optimization algorithm based on combining Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), called PSO-ACO, for optimally clustering N object into K clusters. The new PSO-ACO algorithm is tested on several data sets, and its performance is compared with those of ACO, PSO and K-means clustering. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for handing data clustering.