Abstract: In this paper, the fuzzy linear programming formulation
of fuzzy maximal flow problems are proposed and on the basis of the
proposed formulation a method is proposed to find the fuzzy optimal
solution of fuzzy maximal flow problems. In the proposed method all
the parameters are represented by triangular fuzzy numbers. By using
the proposed method the fuzzy optimal solution of fuzzy maximal
flow problems can be easily obtained. To illustrate the proposed
method a numerical example is solved and the obtained results are
discussed.
Abstract: In this paper, a robust statistics based filter to remove salt and pepper noise in digital images is presented. The function of the algorithm is to detect the corrupted pixels first since the impulse noise only affect certain pixels in the image and the remaining pixels are uncorrupted. The corrupted pixels are replaced by an estimated value using the proposed robust statistics based filter. The proposed method perform well in removing low to medium density impulse noise with detail preservation upto a noise density of 70% compared to standard median filter, weighted median filter, recursive weighted median filter, progressive switching median filter, signal dependent rank ordered mean filter, adaptive median filter and recently proposed decision based algorithm. The visual and quantitative results show the proposed algorithm outperforms in restoring the original image with superior preservation of edges and better suppression of impulse noise
Abstract: Culinary culture differences can cause health
problems for international tourists in Thailand. This paper drew upon
data collected from an international tourist survey conducted in
Bangkok, Thailand during summer of 2012. Summer is the period
that a variety food safety issues and incidents are often publicized in
Thailand. The survey targeted European Union tourists- concerns
toward a variety of food safety issues that they encountered during
their trip in Thailand. A total of 400 respondents were elicited as data
input for t-test, and one way ANOVA test. The findings revealed an
astonishing result that up to 46.5 percent of respondents were sick at
least one time or more in Thailand. However, the majority of
respondents trusted that the Thai hotel and Thai restaurants would
ensure food safety, but they did not trust street vendors to ensure food
safety. The level of food safety concern can be ranked from most
concern to least concern by using the value of mean scores as
follows: 1) artificial coloring, 2) use of preservatives, 3) antibiotics,
4) growth hormones, 5) chemical residues, and 6) bacterial
contamination. The overall mean score for level of concerns was
3.493 with standard deviation of 1.677 which did not indicate a very
high level of concern. In addition, the result for t-test and one way
ANOVA test revealed that there was not much effect from the
demographic differences to level of food safety concerns.
Abstract: ORC (Organic Rankine Cycle) has potential of
reducing consumption of fossil fuels and has many favorable
characteristics to exploit low-temperature heat sources. In this work
thermodynamic performance of ORC with regeneration is
comparatively assessed for various working fluids. Special attention is
paid to the effects of system parameters such as the turbine inlet
pressure on the characteristics of the system such as net work
production, heat input, volumetric flow rate per 1 MW of net work and
quality of the working fluid at turbine exit as well as thermal
efficiency. Results show that for a given source the thermal efficiency
generally increases with increasing of the turbine inlet pressure
however has optimal condition for working fluids of low critical
pressure such as iso-pentane or n-pentane.
Abstract: Various mechanisms providing mutual exclusion and
thread synchronization can be used to support parallel processing
within a single computer. Instead of using locks, semaphores, barriers
or other traditional approaches in this paper we focus on alternative
ways for making better use of modern multithreaded architectures
and preparing hash tables for concurrent accesses. Hash structures
will be used to demonstrate and compare two entirely different
approaches (rule based cooperation and hardware synchronization
support) to an efficient parallel implementation using traditional
locks. Comparison includes implementation details, performance
ranking and scalability issues. We aim at understanding the effects
the parallelization schemes have on the execution environment with
special focus on the memory system and memory access
characteristics.
Abstract: The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for crossdomain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.
Abstract: This paper mainly proposes an efficient modified
particle swarm optimization (MPSO) method, to identify a slidercrank
mechanism driven by a field-oriented PM synchronous motor.
In system identification, we adopt the MPSO method to find
parameters of the slider-crank mechanism. This new algorithm is
added with “distance" term in the traditional PSO-s fitness function to
avoid converging to a local optimum. It is found that the comparisons
of numerical simulations and experimental results prove that the
MPSO identification method for the slider-crank mechanism is
feasible.
Abstract: In this study, we present an advanced detection
technique for mass type breast cancer based on texture information
of organs. The proposed method detects the cancer areas in three
stages. In the first stage, the midpoints of mass area are determined
based on AHE (Adaptive Histogram Equalization). In the second
stage, we set the threshold coefficient of homogeneity by using
MLE (Maximum Likelihood Estimation) to compute the uniformity
of texture. Finally, mass type cancer tissues are extracted from the
original image. As a result, it was observed that the proposed
method shows an improved detection performance on dense breast
tissues of Korean women compared with the existing methods. It is
expected that the proposed method may provide additional
diagnostic information for detection of mass-type breast cancer.
Abstract: The purpose of this study is to identify the underlying
causes of late payment from the contractors- perspective in the
Malaysian construction industry and to recommend effective solutions
to mitigate late payment problems. The target groups of respondents in
this study were Grades G3, G5, G6 and G7 contractors with
specialization in building works and civil engineering works registered
with the Construction Industry Development Board (CIDB) in
Malaysia. Results from this study were analyzed with Statistical
Package for the Social Science (SPSS 15.0). From this study, it was
found that respondents have highest ranked five significant variables
out of a total of forty-one variables which can caused late payment
problems: a) cash flow problems due to deficiencies in client-s
management capacity (mean = 3.96); b) client-s ineffective utilization
of funds (mean = 3.88); c) scarcity of capital to finance the project
(mean = 3.81); d) clients failure to generate income from bank when
sales of houses do not hit the targeted amount (mean=3.72); and e)
poor cash flow because of lack of proper process implementation,
delay in releasing of the retention monies to contractor and delay in the
evaluation and certification of interim and final payment (mean =
3.66).
Abstract: Instead of traditional (nominal) classification we investigate
the subject of ordinal classification or ranking. An enhanced
method based on an ensemble of Support Vector Machines (SVM-s)
is proposed. Each binary classifier is trained with specific weights
for each object in the training data set. Experiments on benchmark
datasets and synthetic data indicate that the performance of our
approach is comparable to state of the art kernel methods for
ordinal regression. The ensemble method, which is straightforward
to implement, provides a very good sensitivity-specificity trade-off
for the highest and lowest rank.
Abstract: Currently searching through internet is very popular especially in a field of academic. A huge of educational information such as research papers are overload for user. So community-base web sites have been developed to help user search information more easily from process of customizing a web site to need each specifies user or set of user. In this paper propose to use association rule analyze the community group on research paper bookmarking. A set of design goals for community group frameworks is developed and discussed. Additionally Researcher analyzes the initial relation by using association rule discovery between the antecedent and the consequent of a rule in the groups of user for generate the idea to improve ranking search result and development recommender system.
Abstract: In this paper we present a general formalism for the
establishment of the family of selective regressor affine projection
algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA),
the SR partial rank algorithm (SR-PRA), the SR binormalized
data reusing least mean squares (SR-BNDR-LMS), and the SR normalized
LMS with orthogonal correction factors (SR-NLMS-OCF)
algorithms are established by this general formalism. We demonstrate
the performance of the presented algorithms through simulations in
acoustic echo cancellation scenario.
Abstract: As global industry developed rapidly, the energy
demand also rises simultaneously. In the production process, there’s a
lot of energy consumed in the process. Formally, the energy used in
generating the heat in the production process. In the total energy
consumption, 40% of the heat was used in process heat, mechanical
work, chemical energy and electricity. The remaining 50% were
released into the environment. It will cause energy waste and
environment pollution. There are many ways for recovering the waste
heat in factory. Organic Rankine Cycle (ORC) system can produce
electricity and reduce energy costs by recovering the waste of low
temperature heat in the factory. In addition, ORC is the technology
with the highest power generating efficiency in low-temperature heat
recycling. However, most of factories executives are still hesitated
because of the high implementation cost of the ORC system, even a lot
of heat are wasted. Therefore, this study constructs a nonlinear
mathematical model of waste heat recovery equipment configuration
to maximize profits. A particle swarm optimization algorithm is
developed to generate the optimal facility installation plan for the ORC
system.
Abstract: In this paper, we consider the effect of the initial
sample size on the performance of a sequential approach that used
in selecting a good enough simulated system, when the number
of alternatives is very large. We implement a sequential approach
on M=M=1 queuing system under some parameter settings, with a
different choice of the initial sample sizes to explore the impacts on
the performance of this approach. The results show that the choice
of the initial sample size does affect the performance of our selection
approach.
Abstract: A manufacturing inventory model with shortages with
carrying cost, shortage cost, setup cost and demand quantity as
imprecise numbers, instead of real numbers, namely interval number
is considered here. First, a brief survey of the existing works on
comparing and ranking any two interval numbers on the real line
is presented. A common algorithm for the optimum production
quantity (Economic lot-size) per cycle of a single product (so as
to minimize the total average cost) is developed which works well
on interval number optimization under consideration. Finally, the
designed algorithm is illustrated with numerical example.
Abstract: The e-government emerging concept transforms the
way in which the citizens are dealing with their governments. Thus,
the citizens can execute the intended services online anytime and
anywhere. This results in great benefits for both the governments
(reduces the number of officers) and the citizens (more flexibility and
time saving). Therefore, building a maturity model to assess the egovernment
portals becomes desired to help in the improvement
process of such portals. This paper aims at proposing an egovernment
maturity model based on the measurement of the best
practices’ presence. The main benefit of such maturity model is to
provide a way to rank an e-government portal based on the used best
practices, and also giving a set of recommendations to go to the
higher stage in the maturity model.
Abstract: The effect of beak trimming on behavior of two strains
of Thai native pullets kept in floor pens was studied. Six general
activities (standing, crouching, moving, comforting, roosting, and
nesting), 6 beak related activities (preening, feeding, drinking,
pecking at inedible object, feather pecking, and litter pecking), and 4
agonistic activities (head pecking, threatening, avoiding, and fighting)
were measured twice a for 15 consecutive days, started when the
pullets were 19 wk old. It was found that beak trimmed pullets drank
more frequent (P
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.
Abstract: In this study thermodynamic performance analysis of a
combined organic Rankine cycle and ejector refrigeration cycle is
carried out for use of low-grade heat source in the form of sensible
energy. Special attention is paid to the effects of system parameters
including the turbine inlet temperature and turbine inlet pressure on the
characteristics of the system such as ratios of mass flow rate, net work
production, and refrigeration capacity as well as the coefficient of
performance and exergy efficiency of the system. Results show that
for a given source the coefficient of performance increases with
increasing of the turbine inlet pressure. However, the exergy
efficiency has an optimal condition with respect to the turbine inlet
pressure.
Abstract: In this paper we present a method for gene ranking
from DNA microarray data. More precisely, we calculate the correlation
networks, which are unweighted and undirected graphs, from
microarray data of cervical cancer whereas each network represents
a tissue of a certain tumor stage and each node in the network
represents a gene. From these networks we extract one tree for
each gene by a local decomposition of the correlation network. The
interpretation of a tree is that it represents the n-nearest neighbor
genes on the n-th level of a tree, measured by the Dijkstra distance,
and, hence, gives the local embedding of a gene within the correlation
network. For the obtained trees we measure the pairwise similarity
between trees rooted by the same gene from normal to cancerous
tissues. This evaluates the modification of the tree topology due to
progression of the tumor. Finally, we rank the obtained similarity
values from all tissue comparisons and select the top ranked genes.
For these genes the local neighborhood in the correlation networks
changes most between normal and cancerous tissues. As a result
we find that the top ranked genes are candidates suspected to be
involved in tumor growth and, hence, indicates that our method
captures essential information from the underlying DNA microarray
data of cervical cancer.