Abstract: This study proposes and tests a rescapturing elements of perceived gain and loss that, by perceived value of medical tourism products, influencintention of potential customers. Data from 301 usable qwere tested against the research model using the structmodeling approach. The results indicated that perceivedkey predictor of customer intentions. As for benefimedical quality, service quality and enjoyment wcomponents that significantly influenced the perceptiRegarding sacrifice, the effects of perceived risk on pewere significant. The findings can provide insights intohow destination countries can make medical tourism a wfor themselves and international patients.KeywordsMedical tourism, perceived valueintention.
Abstract: Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.
Abstract: The purpose of this article is to study the effects of
plants cover on overland flow and, therefore, its influences on the
amount of eroded and transported soil. In this investigation, all the
experiments were conducted in the LEGHYD laboratory using a
rainfall simulator and a soil tray. The experiments were conducted
using an experimental plot (soil tray) which is 2m long, 0.5 m wide
and 0.15 m deep. The soil used is an agricultural sandy soil (62,08%
coarse sand, 19,14% fine sand, 11,57% silt and 7,21% clay). Plastic
rods (4 mm in diameter) were used to simulate the plants at different
densities: 0 stem/m2 (bared soil), 126 stems/m², 203 stems/m², 461
stems/m² and 2500 stems/m²). The used rainfall intensity is 73mm/h
and the soil tray slope is fixed to 3°. The results have shown that the
overland flow velocities decreased with increasing stems density, and
the density cover has a great effect on sediment concentration.
Darcy–Weisbach and Manning friction coefficients of overland flow
increased when the stems density increased. Froude and Reynolds
numbers decreased with increasing stems density and, consequently,
the flow regime of all treatments was laminar and subcritical. From
these findings, we conclude that increasing the plants cover can
efficiently reduce soil loss and avoid denuding the roots plants.
Abstract: The hydrodynamics behavior of fluid flow in microconverging
plates is investigated analytically. Effects of Knudsen number () on the microchannel hydrodynamics behavior and the
coefficient of friction are investigated. It is found that as increases the slip in the hydrodynamic boundary condition increases.
Also, the coefficient of friction decreases as increases.
Abstract: One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.
Abstract: Although White LED lighting systems powered by solar cells have presented for many years, they are not widely used in today application because of their cost and low energy conversion efficiency. The proposed system use the dc power generated by fixed solar cells module to energize White LED light sources that are operated by directly connected White LED with current limitation resistors, resulting in much more power consumption. This paper presents the use of white LED as a general lighting application powered by tracking solar cells module and using pulse to apply the electrical power to the White LED. These systems resulted in high efficiency power conversion, low power consumption, and long light of the white LED.
Abstract: In this paper an ant colony optimization algorithm is
developed to solve the permutation flow shop scheduling problem. In
the permutation flow shop scheduling problem which has been vastly
studied in the literature, there are a set of m machines and a set of n
jobs. All the jobs are processed on all the machines and the sequence
of jobs being processed is the same on all the machines. Here this
problem is optimized considering two criteria, makespan and total
flow time. Then the results are compared with the ones obtained by
previously developed algorithms. Finally it is visible that our
proposed approach performs best among all other algorithms in the
literature.
Abstract: Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time
Abstract: Organ motion, especially respiratory motion, is a technical challenge to radiation therapy planning and dosimetry. This motion induces displacements and deformation of the organ tissues within the irradiated region which need to be taken into account when simulating dose distribution during treatment. Finite element modeling (FEM) can provide a great insight into the mechanical behavior of the organs, since they are based on the biomechanical material properties, complex geometry of organs, and anatomical boundary conditions. In this paper we present an original approach that offers the possibility to combine image-based biomechanical models with particle transport simulations. We propose a new method to map material density information issued from CT images to deformable tetrahedral meshes. Based on the principle of mass conservation our method can correlate density variation of organ tissues with geometrical deformations during the different phases of the respiratory cycle. The first results are particularly encouraging, as local error quantification of density mapping on organ geometry and density variation with organ motion are performed to evaluate and validate our approach.
Abstract: We propose our genuine research of geometric
moments which detects the mineral inadequacy in the frail groundnut
plant. This plant is prone to many deficiencies as a result of the
variance in the soil nutrients. By analyzing the leaves of the plant, we
detect the visual symptoms that are not recognizable to the naked eyes.
We have collected about 160 samples of leaves from the nearby fields.
The images have been taken by keeping every leaf into a black box to
avoid the external interference. For the first time, it has been possible
to provide the farmer with the stages of deficiencies. This paper has
applied the algorithms successfully to many other plants like Lady-s
finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit
the results of the groundnut predominantly. The accuracy of our
algorithm and method is almost 93%. This will again pioneer a kind of
green revolution in the field of agriculture and will be a boon to that
field.
Abstract: There are many problems associated with the World Wide
Web: getting lost in the hyperspace; the web content is still accessible only
to humans and difficulties of web administration. The solution to these
problems is the Semantic Web which is considered to be the extension
for the current web presents information in both human readable and
machine processable form. The aim of this study is to reach new
generic foundation architecture for the Semantic Web because there
is no clear architecture for it, there are four versions, but still up to
now there is no agreement for one of these versions nor is there a
clear picture for the relation between different layers and
technologies inside this architecture. This can be done depending on
the idea of previous versions as well as Gerber-s evaluation method
as a step toward an agreement for one Semantic Web architecture.
Abstract: This work deals with aspects of support vector machine learning for large-scale data mining tasks. Based on a decomposition algorithm for support vector machine training that can be run in serial as well as shared memory parallel mode we introduce a transformation of the training data that allows for the usage of an expensive generalized kernel without additional costs. We present experiments for the Gaussian kernel, but usage of other kernel functions is possible, too. In order to further speed up the decomposition algorithm we analyze the critical problem of working set selection for large training data sets. In addition, we analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our tests and conclusions led to several modifications of the algorithm and the improvement of overall support vector machine learning performance. Our method allows for using extensive parameter search methods to optimize classification accuracy.
Abstract: Magetan area is going to be the object of this research
which is located in East Java, Indonesia. The data were obtained
from 270 civil servants working at the Magetan District government.
The data were analyzed using the Structural Equation Modeling with
Partial Least Square program. The research showed the following
findings: (1) job motivation variable has a positive and significant
effect on organizational citizenship behavior (OCB); (2) work
environment has positive and significant effect on OCB; (3)
leadership variable has positive and significant effect on OCB; (4)
job motivation variable has no significant effect on job satisfaction;
(5) work environment variable has no significant effect on job
satisfaction; (6) leadership variable has no significant effect on job
satisfaction; (7) OCB is positively and significantly associated with
job satisfaction; (8) job satisfaction variable is positively and
significantly correlated with quality of public service at the Magetan
District government.
Abstract: The aim of this study was to examine current levels of physical activity determined via heart rate monitoring. A total of 176 children (85 boys, 91 girls) aged 5-13 years wore sealed Polar heart rate monitors for at least 10 hours per day on at least 3 days. Mean daily minutes of moderate to vigorous-intensity physical activity was 65 ± 43 (mean ± SD) for boys and 54 ± 37 for girls. Daily minutes of vigorous-intensity activity was 31 ± 24 and 24 ± 21 for boys and girls respectively. Significant differences in physical activity levels were observed between school day and weekends, boys and girls, and among age and geographical groups. Only 36% of boys and 22% of girls met the New Zealand physical activity guideline. This research indicates that a large proportion of New Zealand children are not meeting physical activity recommendations.
Abstract: Since dealing with high dimensional data is
computationally complex and sometimes even intractable, recently
several feature reductions methods have been developed to reduce
the dimensionality of the data in order to simplify the calculation
analysis in various applications such as text categorization, signal
processing, image retrieval, gene expressions and etc. Among feature
reduction techniques, feature selection is one the most popular
methods due to the preservation of the original features.
In this paper, we propose a new unsupervised feature selection
method which will remove redundant features from the original
feature space by the use of probability density functions of various
features. To show the effectiveness of the proposed method, popular
feature selection methods have been implemented and compared.
Experimental results on the several datasets derived from UCI
repository database, illustrate the effectiveness of our proposed
methods in comparison with the other compared methods in terms of
both classification accuracy and the number of selected features.
Abstract: Stock portfolio selection is a classic problem in finance,
and it involves deciding how to allocate an institution-s or an individual-s
wealth to a number of stocks, with certain investment objectives
(return and risk). In this paper, we adopt the classical Markowitz
mean-variance model and consider an additional common realistic
constraint, namely, the cardinality constraint. Thus, stock portfolio
optimization becomes a mixed-integer quadratic programming problem
and it is difficult to be solved by exact optimization algorithms.
Chemical Reaction Optimization (CRO), which mimics the molecular
interactions in a chemical reaction process, is a population-based
metaheuristic method. Two different types of CRO, named canonical
CRO and Super Molecule-based CRO (S-CRO), are proposed to solve
the stock portfolio selection problem. We test both canonical CRO
and S-CRO on a benchmark and compare their performance under
two criteria: Markowitz efficient frontier (Pareto frontier) and Sharpe
ratio. Computational experiments suggest that S-CRO is promising
in handling the stock portfolio optimization problem.
Abstract: The electrochemical coagulation of a kaolin
suspension was investigated at the currents of 0.06, 0.12, 0.22, 0.44,
0.85 A (corresponding to 0.68, 1.36, 2.50, 5.00, 9.66 mA·cm-2,
respectively) for the contact time of 5, 10, 20, 30, and 50 min. The
TSS removal efficiency at currents of 0.06 A, 0.12 A and 0.22 A
increased with the amount of iron generated by the sacrificial anode,
while the removal efficiencies did not increase proportionally with
the amount of iron generated at the currents of 0.44 and 0.85 A,
where electroflotation was clearly observed. Zeta potential
measurement illustrated the presence of the highly positive charged
particles created by sorption of highly charged polymeric metal
hydroxyl species onto the negative surface charged kaolin particles at
both low and high applied currents. The disappearance of the
individual peaks after certain contact times indicated the attraction
between these positive and negative charged particles causing
agglomeration. It was concluded that charge neutralization of the
individual species was not the only mechanism operating in the
electrocoagulation process at any current level, but electrostatic
attraction was likely to co-operate or mainly operate.
Abstract: The development of Artificial Neural Networks
(ANNs) is usually a slow process in which the human expert has to
test several architectures until he finds the one that achieves best
results to solve a certain problem. This work presents a new
technique that uses Genetic Programming (GP) for automatically
generating ANNs. To do this, the GP algorithm had to be changed in
order to work with graph structures, so ANNs can be developed. This
technique also allows the obtaining of simplified networks that solve
the problem with a small group of neurons. In order to measure the
performance of the system and to compare the results with other
ANN development methods by means of Evolutionary Computation
(EC) techniques, several tests were performed with problems based
on some of the most used test databases. The results of those
comparisons show that the system achieves good results comparable
with the already existing techniques and, in most of the cases, they
worked better than those techniques.
Abstract: Arc welding is an important joining process widely used in many industrial applications including production of automobile, ships structures and metal tanks. In welding process, the moving electrode causes highly non-uniform temperature distribution that leads to residual stresses and different deviations, especially buckling distortions in thin plates. In order to control the deviations and increase the quality of welded plates, a fixture can be used as a practical and low cost method with high efficiency. In this study, a coupled thermo-mechanical finite element model is coded in the software ANSYS to simulate the behavior of thin plates located by a 3-2-1 positioning system during the welding process. Computational results are compared with recent similar works to validate the finite element models. The agreement between the result of proposed model and other reported data proves that finite element modeling can accurately predict the behavior of welded thin plates.
Abstract: Regular physical activity contributes positively to physiological and psychological health. This study aimed to identify exercise behavior changes, self efficacy and decisional balance in nursing and midwifery students. This was a cross-sectional study carried out in Iran.300undergraduate nursing and midwifery students participated in this study. Data were collected using a questionnaire including demographic information, exercise stages of change, exercise self efficacy and pros and cons exercise decisional balance. The analysis was performed using the SPSS.A p-value of less than 0.05 was considered as statistically significant.