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: 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 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: 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: An attempt has been made to determine the strength
and impact properties of Cr-Mo steel weld and base materials by
varying the current during manual metal arc welding. Toughness over
a temperature range from -32 to 100°C of base, heat affected zone
(HAZ) and weld zones at three current settings are made. It is
observed that the deterioration in notch toughness at any zone with
the temperature decreases. The values of notch toughness for all
zones at -32°C are almost same for any current settings. The values
of notch toughness at HAZ area are higher than that of weld area due
to the coarsening of ferrite grain of HAZ occurs with higher heat
input. From microhardness and microstructure result, it can be
concluded that large inclusion content in weld deposit is the cause of
lower notch toughness value.
Abstract: Air quality studies were carried out in the towns of
Putrajaya, Petaling Jaya and Nilai in the Malaysian Peninsular. In this
study, the variations of Ozone (O3) concentrations over a four year
period (2008-2011) were investigated using data obtained from the
Malaysian Department of the Environment (DOE). This study aims to
identify and describe the daily and monthly variations of O3
concentrations at the monitoring sites mentioned. The SPPS program
(Statistical Package for the Social Science) was used to analyze this
data in order to obtain the variations of O3 and also to clarify the
relationship between the stations. The findings of the study revealed
that the highest concentration of O3 occurred during the midday and
afternoon (between 13:00-15:00 hrs). The comparison between
stations also showed that highest O3 concentrations were recorded in
Putrajaya. The comparisons of average and maximum concentrations
of O3 for the three stations showed that the strongest significant
correlation was recorded in the Petaling Jaya station with the value
R2= 0.667. Results from this study indicate that in the urban areas of
Peninsular Malaysia, the concentration of O3 depends on the
concentration of NOx. Furthermore, HYSPLIT back trajectories
(-72h) indicated that air-mass transport patterns can also influence the
O3 concentration in the areas studied.
Abstract: In order to investigate water deficit stress on 24 of
soybean (Glycine Max. L) cultivars and lines in temperate climate, an
experiment was conducted in Iran Seed and Plant Improvement
Institute. Stress levels were irrigation after evaporation of 50, 100,
150 mm water from pan, class A. Randomized Completely Block
Design was arranged for each stress levels. Some traits such as, node
number, plant height, pod number per area, grain number per pod,
grain number per area, 1000 grains weight, grain yield and harvest
index were measured. Results showed that water deficit stress had
significant effect on node number, plant height, pod number per area,
grain number per pod, grain number per area, 1000 grains weight and
harvest index. Also all of agronomic traits except harvest index
influenced significantly by cultivars and lines. The least and most
grain yield was belonged to Ronak X Williams and M41 x Clark
respectively.
Abstract: In this paper we ultra low-voltage and high speed CMOS domino logic. For supply voltages below 500mV the delay for a ultra low-voltage NAND2 gate is aproximately 10% of a complementary CMOS inverter. Furthermore, the delay variations due to mismatch is much less than for conventional CMOS. Differential domino gates for AND/NAND and OR/NOR operation are presented.
Abstract: A wireless sensor network with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in wireless sensor networks is developing an energy-efficient routing protocol which has a significant impact on the overall lifetime of the sensor network. In this paper, we propose a novel hierarchical with static clustering routing protocol called Energy-Efficient Protocol with Static Clustering (EEPSC). EEPSC, partitions the network into static clusters, eliminates the overhead of dynamic clustering and utilizes temporary-cluster-heads to distribute the energy load among high-power sensor nodes; thus extends network lifetime. We have conducted simulation-based evaluations to compare the performance of EEPSC against Low-Energy Adaptive Clustering Hierarchy (LEACH). Our experiment results show that EEPSC outperforms LEACH in terms of network lifetime and power consumption minimization.