Abstract: A generalized Dirichlet to Neumann map is
one of the main aspects characterizing a recently introduced
method for analyzing linear elliptic PDEs, through which it
became possible to couple known and unknown components
of the solution on the boundary of the domain without
solving on its interior. For its numerical solution, a well conditioned
quadratically convergent sine-Collocation method
was developed, which yielded a linear system of equations
with the diagonal blocks of its associated coefficient matrix
being point diagonal. This structural property, among others,
initiated interest for the employment of iterative methods for
its solution. In this work we present a conclusive numerical
study for the behavior of classical (Jacobi and Gauss-Seidel)
and Krylov subspace (GMRES and Bi-CGSTAB) iterative
methods when they are applied for the solution of the Dirichlet
to Neumann map associated with the Laplace-s equation
on regular polygons with the same boundary conditions on
all edges.
Abstract: A simple and easy algorithm is presented for a fast calculation of kernel functions which required in fluid simulations using the Smoothed Particle Hydrodynamic (SPH) method. Present proposed algorithm improves the Linked-list algorithm and adopts the Pair-Wise Interaction technique, which are widely used for evaluating kernel functions in fluid simulations using the SPH method. The algorithm is easy to be implemented without any complexities in programming. Some benchmark examples are used to show the simulation time saved by using the proposed algorithm. Parametric studies on the number of divisions for sub-domains, smoothing length and total amount of particles are conducted to show the effectiveness of the present technique. A compact formulation is proposed for practical usage.
Abstract: AAM (active appearance model) has been successfully
applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an
inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the
whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard
AAM-based face alignment method.
Abstract: Advances in information technology, recent changes in business environment, globalization, deregulation, privatization have made running a successful business more difficult than ever before. To remain successful and to be competitive have forced companies to react to the new changes in order to survive and succeed. The implementation of an Enterprise Resource planning (ERP) system improves information flow, reduce costs, establish linkage with suppliers and reduce response time to customer needs. This paper focuses on a sample of Greek companies, investigates the ERP market in Greece, the reasons why the Greek companies are investing in ERP systems, the benefits that users have achieved and the influence of ERP systems on the use of new accounting practices. The results indicate a greater level on information integration, flexibility in information access and greater functionality provided by ERP systems but little influence on the use of new accounting practices.
Abstract: This Paper presents an on-going research in the area of Model-Driven Engineering (MDE). The premise is that UML is too unwieldy to serve as the basis for model-driven engineering. We need a smaller, simpler notation with a cleaner semantics. We propose some ideas for a simpler notation with a clean semantics. The result is known as μML, or the Micro-Modelling Language.
Abstract: As the information age matures, major social
infrastructures such as communication, finance, military and energy,
have become ever more dependent on information communication
systems. And since these infrastructures are connected to the Internet,
electronic intrusions such as hacking and viruses have become a new
security threat. Especially, disturbance or neutralization of a major
social infrastructure can result in extensive material damage and social
disorder. To address this issue, many nations around the world are
researching and developing various techniques and information
security policies as a government-wide effort to protect their
infrastructures from newly emerging threats. This paper proposes an
evaluation method for information security levels of CIIP (Critical
Information Infrastructure Protection), which can enhance the security
level of critical information infrastructure by checking the current
security status and establish security measures accordingly to protect
infrastructures effectively.
Abstract: A new approach to promote the generalization ability
of neural networks is presented. It is based on the point of view of
fuzzy theory. This approach is implemented through shrinking or
magnifying the input vector, thereby reducing the difference between
training set and testing set. It is called “shrinking-magnifying
approach" (SMA). At the same time, a new algorithm; α-algorithm is
presented to find out the appropriate shrinking-magnifying-factor
(SMF) α and obtain better generalization ability of neural networks.
Quite a few simulation experiments serve to study the effect of SMA
and α-algorithm. The experiment results are discussed in detail, and
the function principle of SMA is analyzed in theory. The results of
experiments and analyses show that the new approach is not only
simpler and easier, but also is very effective to many neural networks
and many classification problems. In our experiments, the proportions
promoting the generalization ability of neural networks have even
reached 90%.
Abstract: This paper proposes a bi-objective model for the
facility location problem under a congestion system. The idea of the
model is motivated by applications of locating servers in bank
automated teller machines (ATMS), communication networks, and so
on. This model can be specifically considered for situations in which
fixed service facilities are congested by stochastic demand within
queueing framework. We formulate this model with two perspectives
simultaneously: (i) customers and (ii) service provider. The
objectives of the model are to minimize (i) the total expected
travelling and waiting time and (ii) the average facility idle-time.
This model represents a mixed-integer nonlinear programming
problem which belongs to the class of NP-hard problems. In addition,
to solve the model, two metaheuristic algorithms including nondominated
sorting genetic algorithms (NSGA-II) and non-dominated
ranking genetic algorithms (NRGA) are proposed. Besides, to
evaluate the performance of the two algorithms some numerical
examples are produced and analyzed with some metrics to determine
which algorithm works better.
Abstract: Time series models have been used to make predictions of academic enrollments, weather, road accident, casualties and stock prices, etc. Based on the concepts of quartile regression models, we have developed a simple time variant quantile based fuzzy time series forecasting method. The proposed method bases the forecast using prediction of future trend of the data. In place of actual quantiles of the data at each point, we have converted the statistical concept into fuzzy concept by using fuzzy quantiles using fuzzy membership function ensemble. We have given a fuzzy metric to use the trend forecast and calculate the future value. The proposed model is applied for TAIFEX forecasting. It is shown that proposed method work best as compared to other models when compared with respect to model complexity and forecasting accuracy.
Abstract: In industry, on of the most important subjects is die
and it's characteristics in which for cutting and forming different
mechanical pieces, various punch and matrix metal die are used.
whereas the common parts which form the main frame die are not
often proportion with pieces and dies therefore using a part as socalled
common part for frames in specified dimension ranges can
decrease the time of designing, occupied space of warehouse and
manufacturing costs. Parts in dies with getting uniform in their shape
and dimension make common parts of dies. Common parts of punch
and matrix metal die are as bolster, guide bush, guide pillar and
shank. In this paper the common parts and effective parameters in
selecting each of them as the primary information are studied,
afterward for selection and design of mechanical parts an
introduction and investigation based on the Mech. Desk. software is
done hence with developing this software can standardize the metal
common parts of punch and matrix. These studies will be so useful
for designer in their designing and also using it has with very much
advantage for manufactures of products in decreasing occupied
spaces by dies.
Abstract: Pulse code modulation is a widespread technique
in digital communication with significant impact on existing
modern and proposed future communication technologies. Its
widespread utilization is due to its simplicity and attractive
spectral characteristics. In this paper, we present a new
approach to the spectral analysis of PCM signals using
Riemann-Stieltjes integrals, which is very accurate for high bit
rates. This approach can serve as a model for similar spectral
analysis of other competing modulation schemes.
Abstract: Simulations play a major role in education not only because they provide realistic models with which students can interact to acquire real world experiences, but also because they constitute safe environments in which students can repeat processes without any risk in order to perceive easier concepts and theories. Virtual reality is widely recognized as a significant technological advance that can facilitate learning process through the development of highly realistic 3D simulations supporting immersive and interactive features. The objective of this paper is to analyze the influence of virtual reality-s use in chemistry instruction as well as to present an integrated web-based learning environment for the simulation of chemical experiments. The proposed application constitutes a cost-effective solution for both schools and universities without appropriate infrastructure and a valuable tool for distance learning and life-long education in chemistry. Its educational objectives are the familiarization of students with the equipment of a real chemical laboratory and the execution of virtual volumetric analysis experiments with the active participation of students.
Abstract: In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.
Abstract: The conventional GA combined with a local search
algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA)
for the traveling salesman problem (TSP). However, the geometric
properties which are problem specific knowledge can be used to
improve the search process of the HGA. Some tour segments (edges)
of TSPs are fine while some maybe too long to appear in a short tour.
This knowledge could constrain GAs to work out with fine tour
segments without considering long tour segments as often.
Consequently, a new algorithm is proposed, called intelligent-OPT
hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT
algorithm in order to reduce the search time for the optimal solution.
Based on the geometric properties, all the tour segments are assigned
2-level priorities to distinguish between good and bad genes. A
simulation study was conducted to evaluate the performance of the
IOHGA. The experimental results indicate that in general the IOHGA
could obtain near-optimal solutions with less time and better accuracy
than the hybrid genetic algorithm with simulated annealing algorithm
(HGA(SA)).
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: A theoretical approach to radiation damage evolution
is developed. Stable temporal behavior taking place in solids under
irradiation are examined as phenomena of self-organization in nonequilibrium
systems.
Experimental effects of temporal self-organization in solids under
irradiation are reviewed. Their essential common properties and
features are highlighted and analyzed.
Dynamical model to describe development of self-oscillation of
density of point defects under stationary irradiation is proposed. The
emphasis is the nonlinear couplings between rate of annealing and
density of defects that determine the kind and parameters of an
arising self-oscillation.
The field of parameters (defect generation rate and environment
temperature) at which self-oscillations develop is found. Bifurcation
curve and self-oscillation period near it is obtained.
Abstract: Electronic voting (E-voting) using an internet has been
recently performed in some nations and regions. There is no spatial
restriction which a voter directly has to visit the polling place, but an
e-voting using an internet has to go together the computer in which the
internet connection is possible. Also, this voting requires an access
code for the e-voting through the beforehand report of a voter. To
minimize these disadvantages, we propose a method in which a voter,
who has the wireless certificate issued in advance, uses its own cellular
phone for an e-voting without the special registration for a vote. Our
proposal allows a voter to cast his vote in a simple and convenient way
without the limit of time and location, thereby increasing the voting
rate, and also ensuring confidentiality and anonymity.
Abstract: The paper presents the results of theoretical and
numerical modeling of propagation of shock waves in bubbly liquids
related to nonlinear effects (realistic equation of state, chemical
reactions, two-dimensional effects). On the basis on the Rankine-
Hugoniot equations the problem of determination of parameters of
passing and reflected shock waves in gas-liquid medium for
isothermal, adiabatic and shock compression of the gas component is
solved by using the wide-range equation of state of water in the
analitic form. The phenomenon of shock wave intensification is
investigated in the channel of variable cross section for the
propagation of a shock wave in the liquid filled with bubbles
containing chemically active gases. The results of modeling of the
wave impulse impact on the solid wall covered with bubble layer are
presented.
Abstract: Three dimensional nanostructure materials have attracted the attention of many researches because the possibility to apply them for near future devices in sensors, catalysis and energy related. Tin dioxide is the most used material for gas sensing because its three-dimensional nanostructures and properties are related to the large surface exposed to gas adsorption. We propose the use of branch SnO2 nanowhiskers in interaction with ethanol. All Sn atoms are symmetric. The total energy, potential energy and Kinetic energy calculated for interaction between SnO2 and ethanol in different distances and temperatures. The calculations achieved by methods of Langevin Dynamic and Mont Carlo simulation. The total energy increased with addition ethanol molecules and temperature so interactions between them are endothermic.
Abstract: A new technique of topological multi-scale analysis is
introduced. By performing a clustering recursively to build a
hierarchy, and analyzing the co-scale and intra-scale similarities, an
Iterated Function System can be extracted from any data set. The study
of fractals shows that this method is efficient to extract
self-similarities, and can find elegant solutions the inverse problem of
building fractals. The theoretical aspects and practical
implementations are discussed, together with examples of analyses of
simple fractals.