Abstract: It has become crucial over the years for nations to
improve their credit scoring methods and techniques in light of the
increasing volatility of the global economy. Statistical methods or
tools have been the favoured means for this; however artificial
intelligence or soft computing based techniques are becoming
increasingly preferred due to their proficient and precise nature and
relative simplicity. This work presents a comparison between Support
Vector Machines and Artificial Neural Networks two popular soft
computing models when applied to credit scoring. Amidst the
different criteria-s that can be used for comparisons; accuracy,
computational complexity and processing times are the selected
criteria used to evaluate both models. Furthermore the German credit
scoring dataset which is a real world dataset is used to train and test
both developed models. Experimental results obtained from our study
suggest that although both soft computing models could be used with
a high degree of accuracy, Artificial Neural Networks deliver better
results than Support Vector Machines.
Abstract: This paper presents a Reliability-Based Topology
Optimization (RBTO) based on Evolutionary Structural Optimization
(ESO). An actual design involves uncertain conditions such as
material property, operational load and dimensional variation.
Deterministic Topology Optimization (DTO) is obtained without
considering of the uncertainties related to the uncertainty parameters.
However, RBTO involves evaluation of probabilistic constraints,
which can be done in two different ways, the reliability index
approach (RIA) and the performance measure approach (PMA). Limit
state function is approximated using Monte Carlo Simulation and
Central Composite Design for reliability analysis. ESO, one of the
topology optimization techniques, is adopted for topology
optimization. Numerical examples are presented to compare the DTO
with RBTO.
Abstract: Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.
Abstract: Solving Ordinary Differential Equations (ODEs) by
using Partitioning Block Intervalwise (PBI) technique is our aim in
this paper. The PBI technique is based on Block Adams Method and
Backward Differentiation Formula (BDF). Block Adams Method
only use the simple iteration for solving while BDF requires Newtonlike
iteration involving Jacobian matrix of ODEs which consumes a
considerable amount of computational effort. Therefore, PBI is
developed in order to reduce the cost of iteration within acceptable
maximum error
Abstract: Environmental micro-organisms include a large number of taxa and some species that are generally considered nonpathogenic, but can represent a risk in certain conditions, especially for elderly people and immunocompromised individuals. Chemotaxonomic identification techniques are powerful tools for environmental micro-organisms, and cellular fatty acid methyl esters (FAME) content is a powerful fingerprinting identification technique. A system based on an unsupervised artificial neural network (ANN) was set up using the fatty acid profiles of standard bacterial strains, obtained by gas-chromatography, used as learning data. We analysed 45 certified strains belonging to Acinetobacter, Aeromonas, Alcaligenes, Aquaspirillum, Arthrobacter, Bacillus, Brevundimonas, Enterobacter, Flavobacterium, Micrococcus, Pseudomonas, Serratia, Shewanella and Vibrio genera. A set of 79 bacteria isolated from a drinking water line (AMGA, the major water supply system in Genoa) were used as an example for identification compared to standard MIDI method. The resulting ANN output map was found to be a very powerful tool to identify these fresh isolates.
Abstract: To model the human visual system (HVS) in the region of interest, we propose a new objective metric evaluation adapted to wavelet foveation-based image compression quality measurement, which exploits a foveation setup filter implementation technique in the DWT domain, based especially on the point and region of fixation of the human eye. This model is then used to predict the visible divergences between an original and compressed image with respect to this region field and yields an adapted and local measure error by removing all peripheral errors. The technique, which we call foveation wavelet visible difference prediction (FWVDP), is demonstrated on a number of noisy images all of which have the same local peak signal to noise ratio (PSNR), but visibly different errors. We show that the FWVDP reliably predicts the fixation areas of interest where error is masked, due to high image contrast, and the areas where the error is visible, due to low image contrast. The paper also suggests ways in which the FWVDP can be used to determine a visually optimal quantization strategy for foveation-based wavelet coefficients and to produce a quantitative local measure of image quality.
Abstract: In face recognition, feature extraction techniques
attempts to search for appropriate representation of the data. However,
when the feature dimension is larger than the samples size, it brings
performance degradation. Hence, we propose a method called
Normalization Discriminant Independent Component Analysis
(NDICA). The input data will be regularized to obtain the most
reliable features from the data and processed using Independent
Component Analysis (ICA). The proposed method is evaluated on
three face databases, Olivetti Research Ltd (ORL), Face Recognition
Technology (FERET) and Face Recognition Grand Challenge
(FRGC). NDICA showed it effectiveness compared with other
unsupervised and supervised techniques.
Abstract: Several combinations of the preprocessing algorithms,
feature selection techniques and classifiers can be applied to the data
classification tasks. This study introduces a new accurate classifier,
the proposed classifier consist from four components: Signal-to-
Noise as a feature selection technique, support vector machine,
Bayesian neural network and AdaBoost as an ensemble algorithm.
To verify the effectiveness of the proposed classifier, seven well
known classifiers are applied to four datasets. The experiments show
that using the suggested classifier enhances the classification rates for
all datasets.
Abstract: Weblogs are resource of social structure to discover and track the various type of information written by blogger. In this paper, we proposed to use mining weblogs technique for identifying the trends of influenza where blogger had disseminated their opinion for the anomaly disease. In order to identify the trends, web crawler is applied to perform a search and generated a list of visited links based on a set of influenza keywords. This information is used to implement the analytics report system for monitoring and analyzing the pattern and trends of influenza (H1N1). Statistical and graphical analysis reports are generated. Both types of the report have shown satisfactory reports that reflect the awareness of Malaysian on the issue of influenza outbreak through blogs.
Abstract: In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.
Abstract: The asymmetric trafc between uplink and downlink
over recent mobile communication systems has been conspicuous because
of providing new communication services. This paper proposes
an asymmetric trafc accommodation scheme adopting a multihop
cooperative transmission technique for CDMA/FDD cellular networks.
The proposed scheme employs the cooperative transmission
technique in the already proposed downlink multihop transmissions
for the accommodation of the asymmetric trafc, which utilizes
the vacant uplink band for the downlink relay transmissions. The
proposed scheme reduces the transmission power at the downlink
relay transmissions and then suppresses the interference to the uplink
communications, and thus, improves the uplink performance. The
proposed scheme is evaluated by computer simulation and the results
show that it can achieve better throughput performance.
Abstract: In this paper, Optimum adaptive loading algorithms
are applied to multicarrier system with Space-Time Block Coding
(STBC) scheme associated with space-time processing based on
singular-value decomposition (SVD) of the channel matrix over
Rayleigh fading channels. SVD method has been employed in
MIMO-OFDM system in order to overcome subchannel interference.
Chaw-s and Compello-s algorithms have been implemented to obtain
a bit and power allocation for each subcarrier assuming instantaneous
channel knowledge. The adaptive loaded SVD-STBC scheme is
capable of providing both full-rate and full-diversity for any number
of transmit antennas. The effectiveness of these techniques has
demonstrated through the simulation of an Adaptive loaded SVDSTBC
system, and the comparison shown that the proposed
algorithms ensure better performance in the case of MIMO.
Abstract: A reduced order modeling approach for natural
gas transient flow in pipelines is presented. The Euler
equations are considered as the governing equations and
solved numerically using the implicit Steger-Warming flux
vector splitting method. Next, the linearized form of the
equations is derived and the corresponding eigensystem is
obtained. Then, a few dominant flow eigenmodes are used to
construct an efficient reduced-order model. A well-known test
case is presented to demonstrate the accuracy and the
computational efficiency of the proposed method. The results
obtained are in good agreement with those of the direct
numerical method and field data. Moreover, it is shown that
the present reduced-order model is more efficient than the
conventional numerical techniques for transient flow analysis
of natural gas in pipelines.
Abstract: In this paper, a robust watermarking algorithm using
the wavelet transform and edge detection is presented. The efficiency
of an image watermarking technique depends on the preservation of
visually significant information. This is attained by embedding the
watermark transparently with the maximum possible strength. The
watermark embedding process is carried over the subband
coefficients that lie on edges, where distortions are less noticeable,
with a subband level dependent strength. Also, the watermark is
embedded to selected coefficients around edges, using a different
scale factor for watermark strength, that are captured by a
morphological dilation operation. The experimental evaluation of the
proposed method shows very good results in terms of robustness and
transparency to various attacks such as median filtering, Gaussian
noise, JPEG compression and geometrical transformations.
Abstract: In this paper, the 1-D conduction-radiation problem is solved by the lattice Boltzmann method. The effects of various parameters such as the scattering albedo, the conduction–radiation parameter and the wall emissivity are studied. In order to check on the accuracy of the numerical technique employed for the solution of the considered problem, the present numerical code was validated with the published study. The found results are in good agreement with those published
Abstract: Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.
Abstract: This paper presents a low-voltage low-power differential linear transconductor with near rail-to-rail input swing. Based on the current-mirror OTA topology, the proposed transconductor combines the Flipped Voltage Follower (FVF) technique to linearize the transconductor behavior that leads to class- AB linear operation and the virtual transistor technique to lower the effective threshold voltages of the transistors which offers an advantage in terms of low supply requirement. Design of the OTA has been discussed. It operates at supply voltages of about ±0.8V. Simulation results for 0.18μm TSMC CMOS technology show a good input range of 1Vpp with a high DC gain of 81.53dB and a total harmonic distortion of -40dB at 1MHz for an input of 1Vpp. The main aim of this paper is to present and compare new OTA design with high transconductance, which has a potential to be used in low voltage applications.
Abstract: The aim of this work is to analyze a viscous flow in
the axisymmetric nozzle taken into account the mesh size both in the
free stream and into the boundary layer. The resolution of the Navier-
Stokes equations is realized by using the finite volume method to
determine the supersonic flow parameters at the exit of convergingdiverging
nozzle. The numerical technique uses the Flux Vector
Splitting method of Van Leer. Here, adequate time stepping
parameter, along with CFL coefficient and mesh size level is selected
to ensure numerical convergence. The effect of the boundary layer
thickness is significant at the exit of the nozzle. The best solution is
obtained with using a very fine grid, especially near the wall, where
we have a strong variation of velocity, temperature and shear stress.
This study enabled us to confirm that the determination of boundary
layer thickness can be obtained only if the size of the mesh is lower
than a certain value limits given by our calculations.
Abstract: Sol-gel immobilization of enzymes, which can improve considerably their properties, is now one of the most used techniques. By deposition of the entrapped lipase on a solid support, a new and improved biocatalyst was obtained, which can be used with excellent results in acylation reactions. In this paper, lipase B from Candida antarctica was double immobilized on different adsorbents. These biocatalysts were employed in the kinetic resolution of several aliphatic secondary alcohols in organic medium. High total recovery yields of enzymatic activity, up to 560%, were obtained. For all the studied alcohols the enantiomeric ratios E were over 200. The influence of the reaction medium was studied for the kinetic resolution of 2-pentanol.
Abstract: The purpose of this study is to suggest energy efficient
routing for ad hoc networks which are composed of nodes with limited
energy. There are diverse problems including limitation of energy
supply of node, and the node energy management problem has been
presented. And a number of protocols have been proposed for energy
conservation and energy efficiency. In this study, the critical point of
the EA-MPDSR, that is the type of energy efficient routing using only
two paths, is improved and developed. The proposed TP-MESR uses
multi-path routing technique and traffic prediction function to increase
number of path more than 2. It also verifies its efficiency compared to
EA-MPDSR using network simulator (NS-2). Also, To give a
academic value and explain protocol systematically, research
guidelines which the Hevner(2004) suggests are applied. This
proposed TP-MESR solved the existing multi-path routing problem
related to overhead, radio interference, packet reassembly and it
confirmed its contribution to effective use of energy in ad hoc
networks.