Abstract: The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.
Abstract: This study aims to examine the determinants of
purchase intention in C2C e-commerce. Specifically the role of
instant messaging in the C2C e-commerce contextis investigated. In
addition to instant messaging, we brought in two antecedents of
purchase intention - trust and customer satisfaction - to establish a
theoretical research model. Structural equation modeling using
LISREL was used to analyze the data.We discussed the research
findings and suggested some implications for researchers and
practitioners.
Abstract: A key requirement for e-learning materials is
reusability and interoperability, that is the possibility to use at least
part of the contents in different courses, and to deliver them trough
different platforms. These features make possible to limit the cost of
new packages, but require the development of material according to
proper specifications. SCORM (Sharable Content Object Reference
Model) is a set of guidelines suitable for this purpose. A specific
adaptation project has been started to make possible to reuse existing
materials. The paper describes the main characteristics of SCORM
specification, and the procedure used to modify the existing material.
Abstract: This paper presents a hand vein authentication system
using fast spatial correlation of hand vein patterns. In order to
evaluate the system performance, a prototype was designed and a
dataset of 50 persons of different ages above 16 and of different
gender, each has 10 images per person was acquired at different
intervals, 5 images for left hand and 5 images for right hand. In
verification testing analysis, we used 3 images to represent the
templates and 2 images for testing. Each of the 2 images is matched
with the existing 3 templates. FAR of 0.02% and FRR of 3.00 %
were reported at threshold 80. The system efficiency at this threshold
was found to be 99.95%. The system can operate at a 97% genuine
acceptance rate and 99.98 % genuine reject rate, at corresponding
threshold of 80. The EER was reported as 0.25 % at threshold 77. We
verified that no similarity exists between right and left hand vein
patterns for the same person over the acquired dataset sample.
Finally, this distinct 100 hand vein patterns dataset sample can be
accessed by researchers and students upon request for testing other
methods of hand veins matching.
Abstract: The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to control the amount of de-noising in any region of image, according to relative information of local feature scale. Experimental results demonstrate the efficient of the proposed algorithm. Compared with standard Total Variation, our algorithm can better preserve smaller-scaled features and show better performance.
Abstract: In this paper, we present an experimental testing for
a new algorithm that determines an optimal controller-s coefficients
for output variance reduction related to Linear Time Invariant (LTI)
Systems. The algorithm features simplicity in calculation, generalization
to minimal and non-minimal phase systems, and could be
configured to achieve reference tracking as well as variance reduction
after compromising with the output variance. An experiment of DCmotor
velocity control demonstrates the application of this new
algorithm in designing the controller. The results show that the
controller achieves minimum variance and reference tracking for a
preset velocity reference relying on an identified model of the motor.
Abstract: This paper presents a real-time defect detection
algorithm for high-speed steel bar in coil. Because the target speed is
very high, proposed algorithm should process quickly the large
volumes of image for real-time processing. Therefore, defect detection
algorithm should satisfy two conflicting requirements of reducing the
processing time and improving the efficiency of defect detection. To
enhance performance of detection, edge preserving method is
suggested for noise reduction of target image. Finally, experiment
results show that the proposed algorithm guarantees the condition of
the real-time processing and accuracy of detection.
Abstract: In rapidly changing market environment, firms are investing a lot of time and resources into new product development (NPD) projects to make profit and to obtain competitive advantage. However, failure rate of NPD projects is becoming high due to various internal and external risks which hinder successful NPD projects. To reduce the failure rate, it is critical that risks have to be managed effectively and efficiently through good strategy, and treated by optimal responses to minimize risk cost. Four strategies are adopted to handle the risks in this study. The optimal responses are characterized by high reduction of risk costs with high efficiency. This study suggests a framework to decide the optimal responses considering the core risks, risk costs, response efficiency and response costs for successful NPD projects. Both binary particles warm optimization (BPSO) and multi-objective particle swarm optimization (MOPSO) methods are mainly used in the framework. Although several limitations exist in use for real industries, the frame work shows good strength for handling the risks with highly scientific ways through an example.
Abstract: Transcription factors are a group of proteins that
helps for interpreting the genetic information in DNA.
Protein-protein interactions play a major role in the execution
of key biological functions of a cell. These interactions are
represented in the form of a graph with nodes and edges.
Studies have showed that some nodes have high degree of
connectivity and such nodes, known as hub nodes, are the
inevitable parts of the network. In the present paper a method
is proposed to identify hub transcription factor proteins using
sequence information. On a complete data set of transcription
factor proteins available from the APID database, the
proposed method showed an accuracy of 77%, sensitivity of
79% and specificity of 76%.
Abstract: In an Orthogonal Frequency Division Multiplexing (OFDM) systems, the Peak to Average power Ratio (PAR) is high. The clipping signal scheme is a useful and simple method to reduce the PAR. However, it introduces additional noise that degrades the systems performance. We propose an oversampling scheme to deal with the received signal in order to reduce the clipping noise by using Finite Impulse Response (FIR) filter. Coefficients of filter are obtained by correlation function of the received signal and the oversampling information at receiver. The performance of the proposed technique is evaluated for frequency selective channel. Results show that the proposed scheme can mitigate the clipping noise significantly for OFDM systems and in order to maintain the system's capacity, the clipping ratio should be larger than 2.5.
Abstract: This paper investigates the robust stability of uncertain neutral system with time-varying delay. By using Lyapunov method and linear matrix inequality technology, new delay-dependent stability criteria are obtained and formulated in terms of linear matrix inequalities (LMIs), which can be easy to check the robust stability of the considered systems. Numerical examples are given to indicate significant improvements over some existing results.
Abstract: This paper proposes an improvement method of classification
efficiency in a classification model. The model is used
in a risk search system and extracts specific labels from articles
posted at bulletin board sites. The system can analyze the important
discussions composed of the articles. The improvement method
introduces ensemble learning methods that use multiple classification
models. Also, it introduces expressions related to the specific labels
into generation of word vectors. The paper applies the improvement
method to articles collected from three bulletin board sites selected
by users and verifies the effectiveness of the improvement method.
Abstract: Fractional delay FIR filters design method based on
the differential evolution algorithm is presented. Differential evolution
is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach,
an evolutionary algorithm is used to determine the coefficients of
a fractional delay FIR filter based on the Farrow structure. Basic
differential evolution is enhanced with a restricted mating technique,
which improves the algorithm performance in terms of convergence
speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude
response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares
method.
Abstract: Artifact free photoplethysmographic (PPG) signals are
necessary for non-invasive estimation of oxygen saturation (SpO2) in
arterial blood. Movement of a patient corrupts the PPGs with motion
artifacts, resulting in large errors in the computation of Sp02. This
paper presents a study on using Kalman Filter in an innovative way
by modeling both the Artillery Blood Pressure (ABP) and the
unwanted signal, additive motion artifact, to reduce motion artifacts
from corrupted PPG signals. Simulation results show acceptable
performance regarding LMS and variable step LMS, thus
establishing the efficacy of the proposed method.
Abstract: Truss optimization problem has been vastly studied
during the past 30 years and many different methods have been
proposed for this problem. Even though most of these methods
assume that the design variables are continuously valued, in reality,
the design variables of optimization problems such as cross-sectional
areas are discretely valued. In this paper, an improved hill climbing
and an improved simulated annealing algorithm have been proposed
to solve the truss optimization problem with discrete values for crosssectional
areas. Obtained results have been compared to other
methods in the literature and the comparison represents that the
proposed methods can be used more efficiently than other proposed
methods
Abstract: This paper aims to explain the project carried out at
the University of Cordoba, specifically at the High Polytechnic
School in collaboration with two other organizations belonging to the
Andalusian Ministry of Innovation, Science and Business:
Andalusian Innovation and Development Agency (IDEA agency) [1]
and the Territorial Net of Entrepreneurship Support (in Spanish Red
Territorial de Apoyo al Emprendedor) [11].
The project is being developed in several stages of which only the
first one has already been completed. However, several important
preliminary results derive from it, based mainly in the description of
the nature of entrepreneurship in the field of university education and
its impact on student-s competency as recommended by the European
Higher Education Area. Some problems holding back the correct
future development will also be shown as derived from the specific
context of application of the project.
Abstract: Roundabout work on the principle of circulation and
entry flows, where the maximum entry flow rates depend largely on
circulating flow bearing in mind that entry flows must give away to
circulating flows. Where an existing roundabout has a road hump
installed at the entry arm, it can be hypothesized that the kinematics
of vehicles may prevent the entry arm from achieving optimum
performance. Road humps are traffic calming devices placed across
road width solely as speed reduction mechanism. They are the
preferred traffic calming option in Malaysia and often used on single
and dual carriageway local routes. The speed limit on local routes is
30mph (50 km/hr). Road humps in their various forms achieved the
biggest mean speed reduction (based on a mean speed before traffic
calming of 30mph) of up to 10mph or 16 km/hr according to the UK
Department of Transport. The underlying aim of reduced speed
should be to achieve a 'safe' distribution of speeds which reflects the
function of the road and the impacts on the local community.
Constraining safe distribution of speeds may lead to poor drivers
timing and delayed reflex reaction that can probably cause accident.
Previous studies on road hump impact have focused mainly on speed
reduction, traffic volume, noise and vibrations, discomfort and delay
from the use of road humps. The paper is aimed at optimal entry and
circulating flow induced by road humps. Results show that
roundabout entry and circulating flow perform better in
circumstances where there is no road hump at entrance.
Abstract: Quality Function Deployment (QFD) is an expounded, multi-step planning method for delivering commodity, services, and processes to customers, both external and internal to an organization. It is a way to convert between the diverse customer languages expressing demands (Voice of the Customer), and the organization-s languages expressing results that sate those demands. The policy is to establish one or more matrices that inter-relate producer and consumer reciprocal expectations. Due to its visual presence is called the “House of Quality" (HOQ). In this paper, we assumed HOQ in multi attribute decision making (MADM) pattern and through a proposed MADM method, rank technical specifications. Thereafter compute satisfaction degree of customer requirements and for it, we apply vagueness and uncertainty conditions in decision making by fuzzy set theory. This approach would propound supervised neural network (perceptron) for MADM problem solving.
Abstract: Gene, principal unit of inheritance, is an ordered
sequence of nucleotides. The genes of eukaryotic organisms include
alternating segments of exons and introns. The region of
Deoxyribonucleic acid (DNA) within a gene containing instructions
for coding a protein is called exon. On the other hand, non-coding
regions called introns are another part of DNA that regulates gene
expression by removing from the messenger Ribonucleic acid (RNA)
in a splicing process. This paper proposes to determine splice
junctions that are exon-intron boundaries by analyzing DNA
sequences. A splice junction can be either exon-intron (EI) or intron
exon (IE). Because of the popularity and compatibility of the
artificial neural network (ANN) in genetic fields; various ANN
models are applied in this research. Multi-layer Perceptron (MLP),
Radial Basis Function (RBF) and Generalized Regression Neural
Networks (GRNN) are used to analyze and detect the splice junctions
of gene sequences. 10-fold cross validation is used to demonstrate
the accuracy of networks. The real performances of these networks
are found by applying Receiver Operating Characteristic (ROC)
analysis.
Abstract: The purpose of this paper is to present two different
approaches of financial distress pre-warning models appropriate for
risk supervisors, investors and policy makers. We examine a sample
of the financial institutions and electronic companies of Taiwan
Security Exchange (TSE) market from 2002 through 2008. We
present a binary logistic regression with paned data analysis. With
the pooled binary logistic regression we build a model including
more variables in the regression than with random effects, while the
in-sample and out-sample forecasting performance is higher in
random effects estimation than in pooled regression. On the other
hand we estimate an Adaptive Neuro-Fuzzy Inference System
(ANFIS) with Gaussian and Generalized Bell (Gbell) functions and
we find that ANFIS outperforms significant Logit regressions in both
in-sample and out-of-sample periods, indicating that ANFIS is a
more appropriate tool for financial risk managers and for the
economic policy makers in central banks and national statistical
services.