Abstract: In this paper, we propose a Connect6 solver which
adopts a hybrid approach based on a tree-search algorithm and image
processing techniques. The solver must deal with the complicated
computation and provide high performance in order to make real-time
decisions. The proposed approach enables the solver to be
implemented on a single Spartan-6 XC6SLX45 FPGA produced by
XILINX without using any external devices. The compact
implementation is achieved through image processing techniques to
optimize a tree-search algorithm of the Connect6 game. The tree
search is widely used in computer games and the optimal search brings
the best move in every turn of a computer game. Thus, many
tree-search algorithms such as Minimax algorithm and artificial
intelligence approaches have been widely proposed in this field.
However, there is one fundamental problem in this area; the
computation time increases rapidly in response to the growth of the
game tree. It means the larger the game tree is, the bigger the circuit
size is because of their highly parallel computation characteristics.
Here, this paper aims to reduce the size of a Connect6 game tree using
image processing techniques and its position symmetric property. The
proposed solver is composed of four computational modules: a
two-dimensional checkmate strategy checker, a template matching
module, a skilful-line predictor, and a next-move selector. These
modules work well together in selecting next moves from some
candidates and the total amount of their circuits is small. The details of
the hardware design for an FPGA implementation are described and
the performance of this design is also shown in this paper.
Abstract: This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.
Abstract: The purpose of the article is to illustrate the main
characteristics of the corporate governance challenge facing the
countries of South-Eastern Europe (SEE) and to subsequently
determine and assess the extensiveness and effectiveness of corporate
governance regulations in these countries. Therefore, we start with an
overview on the subject of the key problems of corporate governance
in transition. We then address the issue of corporate governance
measurement for SEE countries. To this end, we include a review of
the methodological framework for determining both the
extensiveness and the effectiveness of corporate governance
legislation. We then focus on the actual analysis of the quality of
corporate governance codes, as well as of legal institutions
effectiveness and provide a measure of corporate governance in
Romania and other SEE emerging markets. The paper concludes by
emphasizing the corporate governance enforcement gap and by
identifying research issues that require further study.
Abstract: On one hand, SNMP (Simple Network Management
Protocol) allows integrating different enterprise elements connected
through Internet into a standardized remote management. On the
other hand, as a consequence of the success of Intelligent Houses
they can be connected through Internet now by means of a residential
gateway according to a common standard called OSGi (Open
Services Gateway initiative). Due to the specifics of OSGi Service
Platforms and their dynamic nature, specific design criterions should
be defined to implement SNMP Agents for OSGi in order to integrate
them into the SNMP remote management. Based on the analysis of
the relation between both standards (SNMP and OSGi), this paper
shows how OSGi Service Platforms can be included into the SNMP
management of a global enterprise, giving implementation details
about an SNMP Agent solution and the definition of a new MIB
(Management Information Base) for managing OSGi platforms that
takes into account the specifics and dynamic nature of OSGi.
Abstract: In this paper a functional interpretation of quantum
theory (QT) with emphasis on quantum field theory (QFT) is proposed.
Besides the usual statements on relations between a functions
initial state and final state, a functional interpretation also contains
a description of the dynamic evolution of the function. That is, it
describes how things function. The proposed functional interpretation
of QT/QFT has been developed in the context of the author-s work
towards a computer model of QT with the goal of supporting
the largest possible scope of QT concepts. In the course of this
work, the author encountered a number of problems inherent in the
translation of quantum physics into a computer program. He came
to the conclusion that the goal of supporting the major QT concepts
can only be satisfied, if the present model of QT is supplemented
by a "functional interpretation" of QT/QFT. The paper describes a
proposal for that
Abstract: In this paper, we present symbolic recognition models to extract knowledge characterized by document structures. Focussing on the extraction and the meticulous exploitation of the semantic structure of documents, we obtain a meaningful contextual tagging corresponding to different unit types (title, chapter, section, enumeration, etc.).
Abstract: In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.
Abstract: This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.
Abstract: One of the most important power quality issues is voltage flicker. Nowadays this issue also impacts the power system all over the world. The fact of the matter is that the more and the larger capacity of wind generator has been installed. Under unstable wind power situation, the variation of output current and voltage have caused trouble to voltage flicker. Hence, the major purpose of this study is to analyze the impact of wind generator on voltage flicker of power system. First of all, digital simulation and analysis are carried out based on wind generator operating under various system short circuit capacity, impedance angle, loading, and power factor of load. The simulation results have been confirmed by field measurements.
Abstract: An approach for experimental measurement of the
dynamic characteristics of linear electromagnet actuators is
presented. It uses accelerometer sensor to register the armature
acceleration. The velocity and displacement of the moving parts can
be obtained by integration of the acceleration results. The armature
movement of permanent magnet linear actuator is acquired using this
technique. The results are analyzed and the performance of the
supposed approach is compared with the most commonly used
experimental setup where the displacement of the armature vs. time
is measured instead of its acceleration.
Abstract: In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Abstract: The objective of this research was to study the
influence of marketing mix on customers purchasing behavior. A
total of 397 respondents were collected from customers who were the
patronages of the Chatuchak Plaza market. A questionnaire was
utilized as a tool to collect data. Statistics utilized in this research
included frequency, percentage, mean, standard deviation, and
multiple regression analysis. Data were analyzed by using Statistical
Package for the Social Sciences. The findings revealed that the
majority of respondents were male with the age between 25-34 years
old, hold undergraduate degree, married and stay together. The
average income of respondents was between 10,001-20,000 baht. In
terms of occupation, the majority worked for private companies. The
research analysis disclosed that there were three variables of
marketing mix which included price (X2), place (X3), and product
(X1) which had an influence on the frequency of customer
purchasing. These three variables can predict a purchase about 30
percent of the time by using the equation; Y1 = 6.851 + .921(X2) +
.949(X3) + .591(X1). It also found that in terms of marketing mixed,
there were two variables had an influence on the amount of customer
purchasing which were physical characteristic (X6), and the process
(X7). These two variables are 17 percent predictive of a purchasing
by using the equation: Y2 = 2276.88 + 2980.97(X6) + 2188.09(X7).
Abstract: This paper presents a novel method for inferring the
odor based on neural activities observed from rats- main olfactory
bulbs. Multi-channel extra-cellular single unit recordings were done
by micro-wire electrodes (tungsten, 50μm, 32 channels) implanted in
the mitral/tufted cell layers of the main olfactory bulb of anesthetized
rats to obtain neural responses to various odors. Neural response
as a key feature was measured by substraction of neural firing rate
before stimulus from after. For odor inference, we have developed a
decoding method based on the maximum likelihood (ML) estimation.
The results have shown that the average decoding accuracy is about
100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively. This
work has profound implications for a novel brain-machine interface
system for odor inference.
Abstract: Renewable energy systems are becoming a topic of
great interest and investment in the world. In recent years wind
power generation has experienced a very fast development in the
whole world. For planning and successful implementations of good
wind power plant projects, wind potential measurements are
required. In these projects, of great importance is the effective choice
of the micro location for wind potential measurements, installation of
the measurement station with the appropriate measuring equipment,
its maintenance and analysis of the gained data on wind potential
characteristics. In this paper, a wavelet transform has been applied to
analyze the wind speed data in the context of insight in the
characteristics of the wind and the selection of suitable locations that
could be the subject of a wind farm construction. This approach
shows that it can be a useful tool in investigation of wind potential.
Abstract: Lighvan cheese is basically made from sheep milk in
the area of Sahand mountainside which is located in the North West
of Iran. The main objective of this study was to investigate the effect
of enterococci isolated from traditional Lighvan cheese on the quality
of Iranian UF white during ripening. The experimental design was
split plot based on randomized complete blocks, main plots were four
types of starters and subplots were different ripening durations.
Addition of Enterococcus spp. did not significantly (P
Abstract: In high bitrate information hiding techniques, 1 bit is
embedded within each 4 x 4 Discrete Cosine Transform (DCT)
coefficient block by means of vector quantization, then the hidden bit
can be effectively extracted in terminal end. In this paper high bitrate
information hiding algorithms are summarized, and the scheme of
video in video is implemented. Experimental result shows that the host
video which is embedded numerous auxiliary information have little
visually quality decline. Peak Signal to Noise Ratio (PSNR)Y of host
video only degrades 0.22dB in average, while the hidden information
has a high percentage of survives and keeps a high robustness in
H.264/AVC compression, the average Bit Error Rate(BER) of hiding
information is 0.015%.
Abstract: The switching lag-time and the voltage drop across
the power devices cause serious waveform distortions and
fundamental voltage drop in pulse width-modulated inverter output.
These phenomenons are conspicuous when both the output frequency
and voltage are low. To estimate the output voltage from the PWM
reference signal it is essential to take account of these imperfections
and to correct them. In this paper, on-line compensation method is
presented. It needs three simple blocs to add at the ideal reference
voltages. This method does not require any additional hardware
circuit and off- line experimental measurement. The paper includes
experimental results to demonstrate the validity of the proposed
method. It is applied, finally, in case of indirect vector controlled
induction machine and implemented using dSpace card.
Abstract: Bloom filter is a probabilistic and memory efficient
data structure designed to answer rapidly whether an element is
present in a set. It tells that the element is definitely not in the set but
its presence is with certain probability. The trade-off to use Bloom
filter is a certain configurable risk of false positives. The odds of a
false positive can be made very low if the number of hash function is
sufficiently large. For spam detection, weight is attached to each set
of elements. The spam weight for a word is a measure used to rate the
e-mail. Each word is assigned to a Bloom filter based on its weight.
The proposed work introduces an enhanced concept in Bloom filter
called Bin Bloom Filter (BBF). The performance of BBF over
conventional Bloom filter is evaluated under various optimization
techniques. Real time data set and synthetic data sets are used for
experimental analysis and the results are demonstrated for bin sizes 4,
5, 6 and 7. Finally analyzing the results, it is found that the BBF
which uses heuristic techniques performs better than the traditional
Bloom filter in spam detection.
Abstract: Group contribution methods such as the UNIFAC are
very useful to researchers and engineers involved in synthesis,
feasibility studies, design and optimization of separation processes.
They can be applied successfully to predict phase equilibrium and
excess properties in the development of chemical and separation
processes. The main focus of this work was to investigate the
possibility of absorbing selected volatile organic compounds (VOCs)
into polydimethylsiloxane (PDMS) using three selected UNIFAC
group contribution methods. Absorption followed by subsequent
stripping is the predominant available abatement technology of
VOCs from flue gases prior to their release into the atmosphere. The
original, modified and effective UNIFAC models were used in this
work. The thirteen selected VOCs that have been considered in this
research are: pentane, hexane, heptanes, trimethylamine, toluene,
xylene, cyclohexane, butyl acetate, diethyl acetate, chloroform,
acetone, ethyl methyl ketone and isobutyl methyl ketone. The
computation was done for solute VOC concentration of 8.55x10-8
which is well in the infinite dilution region. The results obtained in
this study compare very well with those published in literature
obtained through both measurements and predictions. The phase
equilibrium obtained in this study show that PDMS is a good
absorbent for the removal of VOCs from contaminated air streams
through physical absorption.
Abstract: This paper deals with a high-order accurate Runge
Kutta Discontinuous Galerkin (RKDG) method for the numerical
solution of the wave equation, which is one of the simple case of a
linear hyperbolic partial differential equation. Nodal DG method is
used for a finite element space discretization in 'x' by discontinuous
approximations. This method combines mainly two key ideas which
are based on the finite volume and finite element methods. The
physics of wave propagation being accounted for by means of
Riemann problems and accuracy is obtained by means of high-order
polynomial approximations within the elements. High order accurate
Low Storage Explicit Runge Kutta (LSERK) method is used for
temporal discretization in 't' that allows the method to be nonlinearly
stable regardless of its accuracy. The resulting RKDG
methods are stable and high-order accurate. The L1 ,L2 and L∞ error
norm analysis shows that the scheme is highly accurate and effective.
Hence, the method is well suited to achieve high order accurate
solution for the scalar wave equation and other hyperbolic equations.