Abstract: With the advance of information technology in the
new era the applications of Internet to access data resources has
steadily increased and huge amount of data have become accessible
in various forms. Obviously, the network providers and agencies,
look after to prevent electronic attacks that may be harmful or may
be related to terrorist applications. Thus, these have facilitated the
authorities to under take a variety of methods to protect the special
regions from harmful data. One of the most important approaches is
to use firewall in the network facilities. The main objectives of
firewalls are to stop the transfer of suspicious packets in several
ways. However because of its blind packet stopping, high process
power requirements and expensive prices some of the providers are
reluctant to use the firewall. In this paper we proposed a method to
find a discriminate function to distinguish between usual packets and
harmful ones by the statistical processing on the network router logs.
By discriminating these data, an administrator may take an approach
action against the user. This method is very fast and can be used
simply in adjacent with the Internet routers.
Abstract: This paper investigates the effect of International
Financial Reporting Standards (IFRS) adoption on the frequency of
earnings managements towards small positive profits. We focus on
two emerging markets IFRS adopters: South Africa and Turkey.
We tested our logistic regression using appropriate panelestimation
techniques over a sample of 330 South African and 210
Turkish firm-year observations over the period 2002-2008. Our
results document that mandatory adoption of IFRS is not associated
with a reduction in earnings management towards small positive
profits in emerging markets. These results contradict most of the
previous findings of the studies conducted in developed countries.
Based on the legal system factor, we compare the intensity of
earnings management between a code law country (Turkey) and a
common law country (South Africa) over the pre and post-adoption
periods. Our findings show that the frequency of such earnings
management practice increases significantly for the code law
country.
Abstract: The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers, and an improved damping of the power oscillations as compared to the conventional PI controller.
Abstract: The ARMrayan Multimedia Mobile CMS (Content
Management System) is the first mobile CMS that gives the
opportunity to users for creating multimedia J2ME mobile
applications with their desired content, design and logo; simply,
without any need for writing even a line of code. The low-level
programming and compatibility problems of the J2ME, along with
UI designing difficulties, makes it hard for most people –even
programmers- to broadcast their content to the widespread mobile
phones used by nearly all people. This system provides user-friendly,
PC-based tools for creating a tree index of pages and inserting
multiple multimedia contents (e.g. sound, video and picture) in each
page for creating a J2ME mobile application. The output is a standalone
Java mobile application that has a user interface, shows texts
and pictures and plays music and videos regardless of the type of
devices used as long as the devices support the J2ME platform.
Bitmap fonts have also been used thus Middle Eastern languages can
be easily supported on all mobile phone devices. We omitted
programming concepts for users in order to simplify multimedia
content-oriented mobile applictaion designing for use in educational,
cultural or marketing centers. Ordinary operators can now create a
variety of multimedia mobile applications such as tutorials,
catalogues, books, and guides in minutes rather than months.
Simplicity and power has been the goal of this CMS. In this paper,
we present the software engineered-designed concepts of the
ARMrayan MCMS along with the implementation challenges faces
and solutions adapted.
Abstract: Chemical and physical functionalization of multiwalled
carbon nanotubes (MWCNT) has been commonly practiced to
achieve better dispersion of carbon nanotubes (CNTs) in polymer
matrix. This work describes various functionalization methods (acidtreatment,
non-ionic surfactant treatment with TritonX-100),
fabrication of MWCNT/PP nanocomposites via melt blending and
characterization of mechanical properties. Microscopy analysis
(FESEM, TEM, XPS) showed effective purification of MWCNTs
under acid treatment, and better dispersion under both chemical and
physical functionalization techniques combined, in their respective
order. Tensile tests showed increase in tensile strength for the
nanocomposites that contain MWCNTs up to 2 wt%. A decrease in
tensile strength was seen in samples that contain 4 wt% of MWCNTs
for both raw and Triton X-100 functionalized, signifying MWCNT
degradation/rebundling at composition with higher content of
MWCNTs. For the acid-treated MWCNTs, however, the tensile
results showed slight improvement even at 4wt%, indicating effective
dispersion of MWCNTs.
Abstract: The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method's query answering.
Abstract: To minimize power losses, it is important to
determine the location and size of local generators to be placed in
unbalanced power distribution systems. On account of some inherent
features of unbalanced distribution systems, such as radial structure,
large number of nodes, a wide range of X/R ratios, the conventional
techniques developed for the transmission systems generally fail on
the determination of optimum size and location of distributed
generators (DGs). This paper presents a simple method for
investigating the problem of contemporaneously choosing best
location and size of DG in three-phase unbalanced radial distribution
system (URDS) for power loss minimization and to improve the
voltage profile of the system. Best location of the DG is determined
by using voltage index analysis and size of DG is computed by
variational technique algorithm according to available standard size
of DGs. This paper presents the results of simulations for 25-bus and
IEEE 37- bus Unbalanced Radial Distribution system.
Abstract: Innovation is being view from four areas of
innovation, product, service, technology, and marketing. Whereas
customer loyalty is composed of customer expectation, perceived
quality, perceived value, corporate image, customer satisfaction,
customer trust/confidence, customer commitment, customer
complaint, and customer loyalty. This study aimed to investigate the
influence of innovation factors to customer loyalty to GSM in the
telecom companies where use of products and services. Structural
Equation Modeling (SEM) using to analyze innovation factors. It was
found the factor of innovation have significant influence on customer
loyalty.
Abstract: An automatic speech recognition system for the
formal Arabic language is needed. The Quran is the most formal
spoken book in Arabic, it is spoken all over the world. In this
research, an automatic speech recognizer for Quranic based speakerindependent
was developed and tested. The system was developed
based on the tri-phone Hidden Markov Model and Maximum
Likelihood Linear Regression (MLLR). The MLLR computes a set
of transformations which reduces the mismatch between an initial
model set and the adaptation data. It uses the regression class tree, as
well as, estimates a set of linear transformations for the mean and
variance parameters of a Gaussian mixture HMM system. The 30th
Chapter of the Quran, with five of the most famous readers of the
Quran, was used for the training and testing of the data. The chapter
includes about 2000 distinct words. The advantages of using the
Quranic verses as the database in this developed recognizer are the
uniqueness of the words and the high level of orderliness between
verses. The level of accuracy from the tested data ranged 68 to 85%.
Abstract: This paper considers the development of a two-point
predictor-corrector block method for solving delay differential
equations. The formulae are represented in divided difference form
and the algorithm is implemented in variable stepsize variable order
technique. The block method produces two new values at a single
integration step. Numerical results are compared with existing
methods and it is evident that the block method performs very well.
Stability regions of the block method are also investigated.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: Achievement motivation is believed to promote
giftedness attracting people to invest in many programs to adopt
gifted students providing them with challenging activities.
Intellectual giftedness is founded on the fluid intelligence and
extends to more specific abilities through the growth and inputs from
the achievement motivation. Acknowledging the roles played by the
motivation in the development of giftedness leads to an effective
nurturing of gifted individuals. However, no study has investigated
the direct and indirect effects of the achievement motivation and
fluid intelligence on intellectual giftedness. Thus, this study
investigated the contribution of motivation factors to giftedness
development by conducting tests of fluid intelligence using Cattell
Culture Fair Test (CCFT) and analytical abilities using culture
reduced test items covering problem solving, pattern recognition,
audio-logic, audio-matrices, and artificial language, and self report
questionnaire for the motivational factors. A number of 180 highscoring
students were selected using CCFT from a leading university
in Malaysia. Structural equation modeling was employed using Amos
V.16 to determine the direct and indirect effects of achievement
motivation factors (self confidence, success, perseverance,
competition, autonomy, responsibility, ambition, and locus of
control) on the intellectual giftedness. The findings showed that the
hypothesized model fitted the data, supporting the model postulates
and showed significant and strong direct and indirect effects of the
motivation and fluid intelligence on the intellectual giftedness.
Abstract: One of the long standing challenging aspect in mobile robotics is the ability to navigate autonomously, avoiding modeled and unmodeled obstacles especially in crowded and unpredictably changing environment. A successful way of structuring the navigation task in order to deal with the problem is within behavior based navigation approaches. In this study, Issues of individual behavior design and action coordination of the behaviors will be addressed using fuzzy logic. A layered approach is employed in this work in which a supervision layer based on the context makes a decision as to which behavior(s) to process (activate) rather than processing all behavior(s) and then blending the appropriate ones, as a result time and computational resources are saved.
Abstract: This paper presents the idea of a rough controller with application to control the overhead traveling crane system. The structure of such a controller is based on a suggested concept of a fuzzy logic controller. A measure of fuzziness in rough sets is introduced. A comparison between fuzzy logic controller and rough controller has been demonstrated. The results of a simulation comparing the performance of both controllers are shown. From these results we infer that the performance of the proposed rough controller is satisfactory.
Abstract: Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques with classifiers such as random
forests, neural networks and support vector machines. The data sets
are from MAGIC, a Cherenkov telescope experiment. The task is to
classify gamma signals from overwhelmingly hadron and muon
signals representing a rare class classification problem. We compare
the individual classifiers with their ensemble counterparts and
discuss the results. WEKA a wonderful tool for machine learning has
been used for making the experiments.
Abstract: In this paper, in addition to introducing good urban planning and its effects on globalization, some new methodologies in urban management and another urban aspects has been presented. Some new concerns in increasing of urban population , metropolitans and its relations on big problems has been focused in this paper. It is very important matter that future urban planning with based on globalization will be with full of basically changes in its management and perspectives.
Abstract: The building sector is the largest energy consumer and
CO2 emitter in the European Union (EU) and therefore the active
reduction of energy consumption and elimination of energy wastage
are among the main goals in it. Healthy housing and energy
efficiency are affected by many factors which set challenges to
monitoring, control and research of indoor air quality (IAQ) and
energy consumption, especially in old buildings. These challenges
include measurement and equipment costs, for example.
Additionally, the measurement results are difficult to interpret and
their usage in the ventilation control is also limited when taking into
account the energy efficiency of housing at the same time. The main
goal of this study is to develop a cost-effective building monitoring
and control system especially for old buildings. The starting point or
keyword of the development process is a wireless system; otherwise
the installation costs become too high. As the main result, this paper
describes an idea of a wireless building monitoring and control
system. The first prototype of the system has been installed in 10
residential buildings and in 10 school buildings located in the City of
Kuopio, Finland.
Abstract: Nowadays, butyl acetate, a pineapple flavor has been applied widely in food, beverage, cosmetic and pharmaceutical industries. In this study, Butyl acetate, a flavor ester was successfully synthesized via green synthesis of enzymatic reaction route. Commercial immobilized lipase from Rhizomucor miehei (Lipozyme RMIM) was used as biocatalyst in the esterification reaction between acetic acid and butanol. Various reaction parameters such as reaction time (RT), temperature (T) and amount of enzyme (E) were chosen to optimize the reaction synthesis in solvent-free system. The optimum condition to produce butyl acetate was at reaction time (RT), 18 hours; temperature (T), 37°C and amount of enzyme, 25 % (w/w of total substrate). Analysis of yield showed that at optimum condition, >78 % of butyl acetate was produced. The product was confirmed as butyl acetate from FTIR analysis whereby the presence of an ester group was observed at wavenumber of 1742 cm-1.
Abstract: Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteristic frequency components of faylted rotor will be detected by minimizing a fitness function using pso. Supply frequency and side band frequencies and their amplitudes can be estimated by the proposed method. The proposed method is applied to a faulty motor with one and two broken bars in different loading condition. Experimental results prove that the proposed method is effective and applicable.
Abstract: Virtual Assembly (VA) is one of the key technologies
in advanced manufacturing field. It is a promising application of
virtual reality in design and manufacturing field. It has drawn much
interest from industries and research institutes in the last two decades.
This paper describes a process for integrating an interactive Virtual
Reality-based assembly simulation of a digital mockup with the
CAD/CAM infrastructure. The necessary hardware and software
preconditions for the process are explained so that it can easily be
adopted by non VR experts. The article outlines how assembly
simulation can improve the CAD/CAM procedures and structures;
how CAD model preparations have to be carried out and which
virtual environment requirements have to be fulfilled. The issue of
data transfer is also explained in the paper. The other challenges and
requirements like anti-aliasing and collision detection have also been
explained. Finally, a VA simulation has been carried out for a ball
valve assembly and a car door assembly with the help of Vizard
virtual reality toolkit in a semi-immersive environment and their
performance analysis has been done on different workstations to
evaluate the importance of graphical processing unit (GPU) in the
field of VA.