Abstract: Unlike its conventional counterpart, Islamic principles
forbid Islamic banks to take any interest-related income and thus
makes deposits from depositors as an important source of fund for its
operational and financing. Consequently, the risk of deposit
withdrawal by depositors is an important aspect that should be wellmanaged
in Islamic banking. This paper aims to investigate factors
that influence depositors- withdrawal behavior in Islamic banks,
particularly in Malaysia, using the framework of theory of reasoned
action. A total of 368 respondents from Klang valley are involved in
the analysis. The paper finds that all the constructs variable i.e.
normative beliefs, subjective norms, behavioral beliefs, and attitude
towards behavior are perceived to be distinct by the respondents. In
addition, the structural equation model is able to verify the structural
relationships between subjective norms, attitude towards behavior
and behavioral intention. Subjective norms gives more influence to
depositors- decision on deposit withdrawal compared to attitude
towards behavior.
Abstract: A multi-board run-time reconfigurable (MRTR)
system for evolvable hardware (EHW) is introduced with the aim to
implement on hardware the bidirectional incremental evolution (BIE)
method. The main features of this digital intrinsic EHW solution rely
on the multi-board approach, the variable chromosome length
management and the partial configuration of the reconfigurable
circuit. These three features provide a high scalability to the solution.
The design has been written in VHDL with the concern of not being
platform dependant in order to keep a flexibility factor as high as
possible. This solution helps tackling the problem of evolving
complex task on digital configurable support.
Abstract: An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.
Abstract: In This Article We establish moment inequality of
dependent random variables,furthermore some theorems of strong law
of large numbers and complete convergence for sequences of dependent
random variables. In particular, independent and identically
distributed Marcinkiewicz Law of large numbers are generalized to
the case of m0-dependent sequences.
Abstract: Chess is one of the indoor games, which improves the
level of human confidence, concentration, planning skills and
knowledge. The main objective of this paper is to help the chess
players to improve their chess openings using data mining
techniques. Budding Chess Players usually do practices by analyzing
various existing openings. When they analyze and correlate
thousands of openings it becomes tedious and complex for them. The
work done in this paper is to analyze the best lines of Blackmar-
Diemer Gambit(BDG) which opens with White D4... using data
mining analysis. It is carried out on the collection of winning games
by applying association rules. The first step of this analysis is
assigning variables to each different sequence moves. In the second
step, the sequence association rules were generated to calculate
support and confidence factor which help us to find the best
subsequence chess moves that may lead to winning position.
Abstract: Determination of nano particle size is substantial since
the nano particle size exerts a significant effect on various properties
of nano materials. Accordingly, proposing non-destructive, accurate
and rapid techniques for this aim is of high interest. There are some
conventional techniques to investigate the morphology and grain size
of nano particles such as scanning electron microscopy (SEM),
atomic force microscopy (AFM) and X-ray diffractometry (XRD).
Vibrational spectroscopy is utilized to characterize different
compounds and applied for evaluation of the average particle size
based on relationship between particle size and near infrared spectra
[1,4] , but it has never been applied in quantitative morphological
analysis of nano materials. So far, the potential application of nearinfrared
(NIR) spectroscopy with its ability in rapid analysis of
powdered materials with minimal sample preparation, has been
suggested for particle size determination of powdered
pharmaceuticals. The relationship between particle size and diffuse
reflectance (DR) spectra in near infrared region has been applied to
introduce a method for estimation of particle size. Back propagation
artificial neural network (BP-ANN) as a nonlinear model was applied
to estimate average particle size based on near infrared diffuse
reflectance spectra. Thirty five different nano TiO2 samples with
different particle size were analyzed by DR-FTNIR spectrometry and
the obtained data were processed by BP- ANN.
Abstract: The Major Depressive Disorder has been a burden of
medical expense in Taiwan as well as the situation around the world.
Major Depressive Disorder can be defined into different categories by
previous human activities. According to machine learning, we can
classify emotion in correct textual language in advance. It can help
medical diagnosis to recognize the variance in Major Depressive
Disorder automatically. Association language incremental is the
characteristic and relationship that can discovery words in sentence.
There is an overlapping-category problem for classification. In this
paper, we would like to improve the performance in classification in
principle of no overlapping-category problems. We present an
approach that to discovery words in sentence and it can find in high
frequency in the same time and can-t overlap in each category, called
Association Language Features by its Category (ALFC).
Experimental results show that ALFC distinguish well in Major
Depressive Disorder and have better performance. We also compare
the approach with baseline and mutual information that use single
words alone or correlation measure.
Abstract: A virtual collaborative classroom was created at East Carolina University, using videoconference technology via regular internet to bring students from 18 different countries, 2 at a time, to the ECU classroom in real time to learn about each other-s culture. Students from two countries are partnered one on one, they meet for 4-5 weeks, and submit a joint paper. Then the same process is repeated for two other countries. Lectures and student discussions are managed with pre-determined topics and questions. Classes are conducted in English and reading assignments are placed on the website. Administratively all partners are independent, students pay fees and get credits at their home institution. Familiarity with technology, knowledge in cultural understanding and attitude change were assessed, only attitude changes are reported in this paper. After taking this course, all students stated their comfort level in working with, and their desire to interact with, culturally different others grew stronger and their xenophobia and isolationist attitudes decreased.
Abstract: Societal security, continuity scenarios and methodological cycling approach explained in this article. Namely societal security organizational challenges ask implementation of international standards BS 25999-2 & global ISO 22300 which is a family of standards for business continuity management system. Efficient global organization system is distinguished of high entity´s complexity, connectivity & interoperability, having not only cooperative relations in a fact. Competing business have numerous participating ´enemies´, which are in apparent or hidden opponent and antagonistic roles with prosperous organization system, resulting to a crisis scene or even to a battle theatre. Organization business continuity scenarios are necessary for such ´a play´ preparedness, planning, management & overmastering in real environments.
Abstract: Data from 1731 Gentile di Puglia lambs, sired by 65 rams over a 5-year period were analyzed by a mixed model to estimate the variance components for heritability. The considered growth traits were: birth weight (BW), weight at 30 days of age (W30) and average daily gain from birth to 30 days of age (DG). Year of birth, sex of lamb, type of birth (single or twin), dam age at lambing and farm were significant sources of variation for all the considered growth traits. The average lamb weights were 3.85±0.16 kg at birth, 9.57±0.91 kg at 30 days of age and the average daily gain was 191±14 g. Estimates of heritability were 0.33±0.05, 0.41±0.06 and 0.16±0.05 respectively for the same traits. These values suggest there is a good opportunity to improve Gentile di Puglia lambs by selecting animals for growth traits.
Abstract: We developed a non-contact method for the in-situ
monitoring of the thermal forming of glass and Si foils to optimize
the manufacture of mirrors for high-resolution space x-ray
telescopes. Their construction requires precise and light-weight
segmented optics with angular resolution better than 5 arcsec. We
used 75x25 mm Desag D263 glass foils 0.75 mm thick and 0.6 mm
thick Si foils. The glass foils were shaped by free slumping on a
frame at viscosities in the range of 109.3-1012 dPa·s, the Si foils by
forced slumping above 1000°C. Using a Nikon D80 digital camera,
we took snapshots of a foil-s shape every 5 min during its isothermal
heat treatment. The obtained results we can use for computer
simulations. By comparing the measured and simulated data, we can
more precisely define material properties of the foils and optimize
the forming technology.
Abstract: We have investigated the effect of piezoelectric (PZ)
polarization property in binary as well as in ternary wurtzite nitrides.
It is found that with the presence of PZ polarization property, the
phonon group velocity is modified. The change in phonon group
velocity due to PZ polarization effect directly depends on
piezoelectric tensor value. Using different piezoelectric tensor values
recommended by different workers in the literature, percent change in
group velocities of phonons has been estimated. The Debye
temperatures and frequencies of binary nitrides GaN, AlN and InN
are also calculated using the modified group velocities. For ternary
nitrides AlxGa(1-x)N, InxGa(1-x)N and InxAl(1-x)N, the phonon group
velocities have been calculated as a functions of composition. A
small positive bowing is observed in phonon group velocities of
ternary alloys. Percent variations in phonon group velocities are also
calculated for a straightforward comparison among ternary nitrides.
The results are expected to show a change in phonon relaxation rates
and thermal conductivity of III-nitrides when piezoelectric
polarization property is taken into consideration.
Abstract: The effect of the rotational speed and axial torque on
the diagnostics of tapered rolling element bearing defects was
investigated. The accelerometer was mounted on the bearing housing
and connected to Sound and Vibration Analyzer (SVAN 958) and
was used to measure the accelerations from the bearing housing. The
data obtained from the bearing was processed to detect damage of the
bearing using statistical tools and the results were subsequently
analyzed to see if bearing damage had been captured. From this study
it can be seen that damage is more evident when the bearing is
loaded. Also, at the incipient stage of damage the crest factor and
kurtosis values are high but as time progresses the crest factors and
kurtosis values decrease whereas the peak and RMS values are low at
the incipient stage but increase with damage.
Abstract: How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
Abstract: In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.
Abstract: Direct conversion of methane to methanol by partial oxidation in a thermal reactor has a poor yield of about 2% which is less than the expected economical yield of about 10%. Conventional thermal catalytic reactors have been proposed to be superseded by plasma reactors as a promising approach, due to strength of the electrical energy which can break C-H bonds of methane. Among the plasma techniques, non-thermal dielectric barrier discharge (DBD) plasma chemical process is one of the most future promising technologies in synthesizing methanol. The purpose of this paper is presenting a brief review of CH4 oxidation with O2 in DBD plasma reactors based on the recent investigations. For this reason, the effect of various parameters of reactor configuration, feed ratio, applied voltage, residence time (gas flow rate), type of applied catalyst, pressure and reactor wall temperature on methane conversion and methanol selectivity are discussed.
Abstract: Solutions for the temperature profile around a moving
heat source are obtained using both analytic and finite element
(FEM) methods. Analytic and FEM solutions are applied to study the
temperature profile in welding. A moving heat source is represented
using both point heat source and uniform distributed disc heat source
models. Analytic solutions are obtained by solving the partial
differential equation for energy conservation in a solid, and FEM
results are provided by simulating welding using the ANSYS
software. Comparison is made for quasi steady state conditions. The
results provided by the analytic solutions are in good agreement with
results obtained by FEM.
Abstract: A number of routing algorithms based on learning
automata technique have been proposed for communication
networks. How ever, there has been little work on the effects of
variation of graph scarcity on the performance of these algorithms. In
this paper, a comprehensive study is launched to investigate the
performance of LASPA, the first learning automata based solution to
the dynamic shortest path routing, across different graph structures
with varying scarcities. The sensitivity of three main performance
parameters of the algorithm, being average number of processed
nodes, scanned edges and average time per update, to variation in
graph scarcity is reported. Simulation results indicate that the LASPA
algorithm can adapt well to the scarcity variation in graph structure
and gives much better outputs than the existing dynamic and fixed
algorithms in terms of performance criteria.
Abstract: The problem of exponential stability and periodicity for a class of cellular neural networks (DCNNs) with time-varying delays is investigated. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via the methods of variation parameters and inequality techniques. These conditions are represented by some blocks of the interconnection matrices. Compared with some previous methods, the method used in this paper does not resort to any Lyapunov function, and the results derived in this paper improve and generalize some earlier criteria established in the literature cited therein. Two examples are discussed to illustrate the main results.
Abstract: Knee joint forces are available by in vivo measurement
using an instrumented knee prosthesis for small to moderate knee
flexion but not for high flexion yet. We created a 2D mathematical
model of the lower limb incorporating several new features such as a
patello-femoral mechanism, a thigh-calf contact at high knee flexion
and co-contracting muscles' force ratio, then used it to determine knee
joint forces arising from high knee flexions in four kneeling
conditions: rising with legs in parallel, with one foot forward, with or
without arm use. With arms used, the maximum values of knee joint
force decreased to about 60% of those with arms not used. When rising
with one foot forward, if arms are not used, the forward leg sustains a
force as large as that sustained when rising with legs parallel.