Abstract: Transportation is one of the main activities related to
creating value for the tourists. Transport management in tourism
mainly focuses on managing transfer points and vehicle capacity.
However, transport service level must also be ensured as it now
relates to tourist-s experiences. This paper emphasizes on the
responsiveness as one of key service performance measures. An
evaluation framework is developed and illustarted by using the case
of small bus service in Pattaya city. It can be seen as a great potential
for the city to utilize the small bus transportation in order to meet the
needs of more diverse group of passengers and to support the
expansion of tourist areas. The framework integrates with service
operations management, logistics, and tourism behavior perspectives.
The findings from the investigation of existing small bus service are
presented and preliminarily validate the usability of the framework.
Abstract: The objective of this study is to design an adaptive
neuro-fuzzy inference system (ANFIS) for estimation of surface
roughness in grinding process. The Used data have been generated
from experimental observations when the wheel has been dressed
using a rotary diamond disc dresser. The input parameters of model
are dressing speed ratio, dressing depth and dresser cross-feed rate
and output parameter is surface roughness. In the experimental
procedure the grinding conditions are constant and only the dressing
conditions are varied. The comparison of the predicted values and the
experimental data indicates that the ANFIS model has a better
performance with respect to back-propagation neural network
(BPNN) model which has been presented by the authors in previous
work for estimation of the surface roughness.
Abstract: This paper present the implementation of a new ordering strategy on Successive Overrelaxation scheme on two dimensional boundary value problems. The strategy involve two directions alternatingly; from top and bottom of the solution domain. The method shows to significantly reduce the iteration number to converge. Four numerical experiments were carried out to examine the performance of the new strategy.
Abstract: There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.
Abstract: Using Turkish data, in this study it is investigated that
whether a firm’s ownership structure has an impact on its stock
prices after the crisis. A linear regression model is conducted on the
data of non-financial firms that are trading in Istanbul Stock
Exchange 100 Index (ISE 100) index. The findings show that, all
explanatory variables such as inside ownership, largest ownership,
concentrated ownership, foreign shareholders, family controlled and
dispersed ownership are not very important to explain stock prices
after the crisis. Family controlled firms and concentrated ownership
is positively related to stock price, dispersed ownership, largest
ownership, foreign shareholders, and inside ownership structures
have negative interaction between stock prices, but because of the p
value is not under the value of 0.05 this relation is not significant. In
addition, the analysis shows that, the shares of firms that have inside,
largest and dispersed ownership structure are outperform comparing
with the other firms. Furthermore, ownership concentrated firms
outperform to family controlled firms.
Abstract: Multi-dimensional principal component analysis
(PCA) is the extension of the PCA, which is used widely as the
dimensionality reduction technique in multivariate data analysis, to
handle multi-dimensional data. To calculate the PCA the singular
value decomposition (SVD) is commonly employed by the reason of
its numerical stability. The multi-dimensional PCA can be calculated
by using the higher-order SVD (HOSVD), which is proposed by
Lathauwer et al., similarly with the case of ordinary PCA. In this
paper, we apply the multi-dimensional PCA to the multi-dimensional
medical data including the functional independence measure (FIM)
score, and describe the results of experimental analysis.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: Eukaryotic protein-coding genes are interrupted by spliceosomal introns, which are removed from the RNA transcripts before translation into a protein. The exon-intron structures of different eukaryotic species are quite different from each other, and the evolution of such structures raises many questions. We try to address some of these questions using statistical analysis of whole genomes. We go through all the protein-coding genes in a genome and study correlations between the net length of all the exons in a gene, the number of the exons, and the average length of an exon. We also take average values of these features for each chromosome and study correlations between those averages on the chromosomal level. Our data show universal features of exon-intron structures common to animals, plants, and protists (specifically, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Cryptococcus neoformans, Homo sapiens, Mus musculus, Oryza sativa, and Plasmodium falciparum). We have verified linear correlation between the number of exons in a gene and the length of a protein coded by the gene, while the protein length increases in proportion to the number of exons. On the other hand, the average length of an exon always decreases with the number of exons. Finally, chromosome clustering based on average chromosome properties and parameters of linear regression between the number of exons in a gene and the net length of those exons demonstrates that these average chromosome properties are genome-specific features.
Abstract: In the recent works related with mixture discriminant
analysis (MDA), expectation and maximization (EM) algorithm is
used to estimate parameters of Gaussian mixtures. But, initial values
of EM algorithm affect the final parameters- estimates. Also, when
EM algorithm is applied two times, for the same data set, it can be
give different results for the estimate of parameters and this affect the
classification accuracy of MDA. Forthcoming this problem, we use
Self Organizing Mixture Network (SOMN) algorithm to estimate
parameters of Gaussians mixtures in MDA that SOMN is more robust
when random the initial values of the parameters are used [5]. We
show effectiveness of this method on popular simulated waveform
datasets and real glass data set.
Abstract: Prior to the use of detectors, characteristics
comparison study was performed and baseline established. In patient
specific QA, the portal dosimetry mean values of area gamma,
average gamma and maximum gamma were 1.02, 0.31 and 1.31 with
standard deviation of 0.33, 0.03 and 0.14 for IMRT and the
corresponding values were 1.58, 0.48 and 1.73 with standard
deviation of 0.31, 0.06 and 0.66 for VMAT. With ImatriXX 2-D
array system, on an average 99.35% of the pixels passed the criteria
of 3%-3 mm gamma with standard deviation of 0.24 for dynamic
IMRT. For VMAT, the average value was 98.16% with a standard
deviation of 0.86. The results showed that both the systems can be
used in patient specific QA measurements for IMRT and VMAT.
The values obtained with the portal dosimetry system were found to
be relatively more consistent compared to those obtained with
ImatriXX 2-D array system.
Abstract: The purposes of this study were as follows to evaluate
the economic value of Phu Kradueng National Park by the travel cost
method (TCM) and the contingent valuation method (CVM) and to
estimate the demand for traveling and the willingness to pay. The
data for this study were collected by conducting two large scale
surveys on users and non-users. A total of 1,016 users and 1,034
non-users were interviewed. The data were analyzed using multiple
linear regression analysis, logistic regression model and the
consumer surplus (CS) was the integral of demand function for trips.
The survey found, were as follows:
1)Using the travel cost method which provides an estimate of direct
benefits to park users, we found that visitors- total willingness to pay
per visit was 2,284.57 bath, of which 958.29 bath was travel cost,
1,129.82 bath was expenditure for accommodation, food, and
services, and 166.66 bath was consumer surplus or the visitors -net
gain or satisfaction from the visit (the integral of demand function for
trips).
2) Thai visitors to Phu Kradueng National Park were further willing
to pay an average of 646.84 bath per head per year to ensure the
continued existence of Phu Kradueng National Park and to preserve
their option to use it in the future.
3) Thai non-visitors, on the other hand, are willing to pay an average
of 212.61 bath per head per year for the option and existence value
provided by the Park.
4) The total economic value of Phu Kradueng National Park to Thai
visitors and non-visitors taken together stands today at 9,249.55
million bath per year.
5) The users- average willingness to pay for access to Phu Kradueng
National Park rises
from 40 bath to 84.66 bath per head per trip for improved services
such as road improvement, increased cleanliness, and upgraded
information.
This paper was needed to investigate of the potential market
demand for bio prospecting in Phu Kradueng national Park and to
investigate how a larger share of the economic benefits of tourism
could be distributed income to the local residents.
Abstract: This study comprehensively simulate the use of k-ε
model for predicting flow and heat transfer with measured flow field
data in a stationary duct with elucidates on the detailed physics
encountered in the fully developed flow region, and the sharp 180°
bend region. Among the major flow features predicted with accuracy
are flow transition at the entrance of the duct, the distribution of
mean and turbulent quantities in the developing, fully developed, and
sharp 180° bend, the development of secondary flows in the duct
cross-section and the sharp 180° bend, and heat transfer
augmentation. Turbulence intensities in the sharp 180° bend are
found to reach high values and local heat transfer comparisons show
that the heat transfer augmentation shifts towards the wall and along
the duct. Therefore, understanding of the unsteady heat transfer in
sharp 180° bends is important. The design and simulation are related
to concept of fluid mechanics, heat transfer and thermodynamics.
Simulation study has been conducted on the response of turbulent
flow in a rectangular duct in order to evaluate the heat transfer rate
along the small scale multiple rectangular duct
Abstract: This paper examines the problem of designing robust H controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (S) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the system. A sufficient condition of the controller for this system is given in term of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through simulation results. It has been shown that the anti-HIV vaccines are critically important in reducing the infected cells.
Abstract: The main aim of this work is to develop a model of hydrogen sulfide (H2S) separation from natural gas by using membrane separation technology. The model is developed by incorporating three diffusion mechanisms which are Knudsen, viscous and surface diffusion towards membrane selectivity and permeability. The findings from the simulation result shows that the permeability of the gas is dependent toward the pore size of the membrane, operating pressure, operating temperature as well as feed composition. The permeability of methane has the highest value for Poly (1-trimethylsilyl-1-propyne ) PTMSP membrane at pore size of 0.1nm and decreasing toward a minimum peak at pore range 1 to 1.5 nm as pore size increased before it increase again for pore size is greater than 1.5 nm. On the other hand, the permeability of hydrogen sulfide is found to increase almost proportionally with the increase of membrane pore size. Generally, the increase of pressure will increase the permeability of gas since more driving force is provided to the system while increasing of temperature would decrease the permeability due to the surface diffusion drop off effect. A corroboration of the simulation result also showed a good agreement with the experimental data.
Abstract: In this paper we introduce an efficient solution
method for the Eigen-decomposition of bisymmetric and per
symmetric matrices of symmetric structures. Here we decompose
adjacency and Laplacian matrices of symmetric structures to submatrices
with low dimension for fast and easy calculation of
eigenvalues and eigenvectors. Examples are included to show the
efficiency of the method.
Abstract: Lake Nasser is one of the largest reservoirs in the
world. Over 120 million metric tons of sediments are deposited in its
dead storage zone every year. The main objective of the present work
was to determine the physical and chemical characteristics of Lake
Nasser sediments. The sample had a relatively low surface area of 2.9
m2/g which increased more than 3-fold upon chemical activation. The
main chemical elements of the raw sediments were C, O and Si with
some traces of Al, Fe and Ca. The organic functional groups for the
tested sample included O-H, C=C, C-H and C-O, with indications of
Si-O and other metal-C and/or metal-O bonds normally associated
with clayey materials. Potentiometric titration of the sample in
different ionic strength backgrounds revealed an alkaline material with
very strong positive surface charge at pH values just a little less than
the pH of zero charge which is ~9. Surface interactions of the
sediments with the background electrolyte were significant. An
advanced surface complexation model was able to capture these
effects, employing a single-site approach to represent protolysis
reactions in aqueous solution, and to determine the significant surface
species in the pH range of environmental interest.
Abstract: Face detection and recognition has many applications
in a variety of fields such as security system, videoconferencing and
identification. Face classification is currently implemented in
software. A hardware implementation allows real-time processing,
but has higher cost and time to-market.
The objective of this work is to implement a classifier based on
neural networks MLP (Multi-layer Perceptron) for face detection.
The MLP is used to classify face and non-face patterns. The systm is
described using C language on a P4 (2.4 Ghz) to extract weight
values. Then a Hardware implementation is achieved using VHDL
based Methodology. We target Xilinx FPGA as the implementation
support.
Abstract: Students in high education are presented with new terms and concepts in nearly every lecture they attend. Many of them prefer Web-based self-tests for evaluation of their concepts understanding since they can use those tests independently of tutors- working hours and thus avoid the necessity of being in a particular place at a particular time. There is a large number of multiple-choice tests in almost every subject designed to contribute to higher level learning or discover misconceptions. Every single test provides immediate feedback to a student about the outcome of that test. In some cases a supporting system displays an overall score in case a test is taken several times by a student. What we still find missing is how to secure delivering of personalized feedback to a user while taking into consideration the user-s progress. The present work is motivated to throw some light on that question.
Abstract: Restarted GMRES methods augmented with approximate eigenvectors are widely used for solving large sparse linear systems. Recently a new scheme of augmenting with error approximations is proposed. The main aim of this paper is to develop a restarted GMRES method augmented with the combination of harmonic Ritz vectors and error approximations. We demonstrate that the resulted combination method can gain the advantages of two approaches: (i) effectively deflate the small eigenvalues in magnitude that may hamper the convergence of the method and (ii) partially recover the global optimality lost due to restarting. The effectiveness and efficiency of the new method are demonstrated through various numerical examples.
Abstract: The optimal control problem of a linear distributed
parameter system is studied via shifted Legendre polynomials (SLPs)
in this paper. The partial differential equation, representing the
linear distributed parameter system, is decomposed into an n - set
of ordinary differential equations, the optimal control problem is
transformed into a two-point boundary value problem, and the twopoint
boundary value problem is reduced to an initial value problem
by using SLPs. A recursive algorithm for evaluating optimal control
input and output trajectory is developed. The proposed algorithm is
computationally simple. An illustrative example is given to show the
simplicity of the proposed approach.