Abstract: This study investigated the pattern and seasonal index of influenza cases in Thailand. Our results showed that southern Thailand had the highest influenza incidence among the four regions of Thailand (i.e. north, northeast, central and southern Thailand). The influenza pattern in southern Thailand was similar to that of northeastern Thailand. Seasonal index values of influenza cases in Thailand were higher in the hot season than in the wet season. Influenza cases started to increase at the beginning of the hot season (April), reached a maximum in August, rapidly declined in the middle of the wet season and reached the lowest value in December. Seasonal index values for northern Thailand differed from other regions of Thailand.
Abstract: The evolution of technology and construction techniques has enabled the upgrading of transport networks. In particular, the high-speed rail networks allow convoys to peak at above 300 km/h. These structures, however, often significantly impact the surrounding environment. Among the effects of greater importance are the ones provoked by the soundwave connected to train transit. The wave propagation affects the quality of life in areas surrounding the tracks, often for several hundred metres. There are substantial damages to properties (buildings and land), in terms of market depreciation. The present study, integrating expertise in acoustics, computering and evaluation fields, outlines a useful model to select project paths so as to minimize the noise impact and reduce the causes of possible litigation. It also facilitates the rational selection of initiatives to contain the environmental damage to the already existing railway tracks. The research is developed with reference to the Italian regulatory framework (usually more stringent than European and international standards) and refers to a case study concerning the high speed network in Italy.
Abstract: Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.
Abstract: In this article, we propose a new surgical device for
circumferentially excision of high anal fistulas in a minimally
invasive manner. The new apparatus works on the basis of axially
rotating and moving a tubular blade along a fistulous tract
straightened using a rigid straight guidewire. As the blade moves
along the tract, its sharp circular cutting edge circumferentially
separates approximately 2.25 mm thickness of tract encircling the
rigid guidewire. We used the new set to excise two anal fistulas in a
62-year-old male patient, an extrasphincteric type and a long tract
with no internal opening. With regard to the results of this test, the
new device can be considered as a sphincter preserving mechanism
for treatment of high anal fistulas. Consequently, a major reduction
in the risk of fecal incontinence, recurrence rate, convalescence
period and patient morbidity may be achieved using the new device
for treatment of fistula-in-ano.
Abstract: This study focuses on examining why the range of
experience with respect to HIV infection is so diverse, especially in
regard to the latency period. An agent-based approach in modelling
the infection is used to extract high-level behaviour which cannot be
obtained analytically from the set of interaction rules at the cellular
level. A prototype model encompasses local variation in baseline
properties, contributing to the individual disease experience, and is
included in a network which mimics the chain of lymph nodes. The
model also accounts for stochastic events such as viral mutations.
The size and complexity of the model require major computational
effort and parallelisation methods are used.
Abstract: This study was conducted to determine the
objectivity, reliability and validity of the 90º push-ups test protocol
among male and female students of Sports Science Program, Faculty
of Sports Science and Coaching Sultan Idris University of Education.
Samples (n = 300), consisted of males (n = 168) and females (n =
132) students were randomly selected for this study. Researchers
tested the 90º push-ups on the sample twice in a single trial, test and
re-test protocol in the bench press test. Pearson-Product Moment
Correlation method's was used to determine the value of objectivity,
reliability and validity testing. The findings showed that the 900 pushups
test protocol showed high consistency between the two testers
with a value of r = .99. Likewise, The reliability value between test
and re-test for the 90º push-ups test for the male (r=.93) and female
(r=.93) students was also high. The results showed a correlation
between 90º push-ups test and bench press test for boys was r = .64
and girls was r = .28. This finding indicates that the use of the 90º
push-ups to test muscular strength and endurance in the upper body
of males has a higher validity values than female students.
Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
Abstract: In this paper, we propose an approach of unsupervised
segmentation with fuzzy connectedness. Valid seeds are first specified
by an unsupervised method based on scale space theory. A region is
then extracted for each seed with a relative object extraction method of
fuzzy connectedness. Afterwards, regions are merged according to the
values between them of an introduced measure. Some theorems and
propositions are also provided to show the reasonableness of the
measure for doing mergence. Experiment results on a synthetic image,
a color image and a large amount of MR images of our method are
reported.
Abstract: Leonotisleonurus a shrub indigenous to Southern
Africa is widely used in traditional medicine to treat a variety of
conditions ranging from skin diseases and cough to epileptic fits and
‘heart problems’. Studies on the aqueous extract of the leaves have
indicated cycloxegenase enzyme inhibitory activity and an
antihypertensive effect.
Five methanol leaf extract fractions (MLEa - MLEe) of L.
leonurus were tested on anaesthetized normotensive male Wistar rats
(AWR) and isolated perfused working rat hearts (IWH). Fraction
MLEc (0.01mg/kg – 0.05mg/kg) induced significant increases in BP
and HR in AWR and positive chronotropic and inotropic effects in
IWH (1.0mg/ml – 5.0mg/ml). Pre-administration of atenolol
(2.0mg/kg) and prazosin (60μg/kg) significantly inhibited MLEc
effect on HR and MAP respectively in vivo, while atenolol
(7.0mg/ml) pre-perfusion significantly inhibited MLEc effect in vitro.
The hypertensive effect of MLEc is probably via β1agonism.
Results also indicate the presence of multiple cardioactive
compounds in L. leonurus.
Abstract: The dynamic or complex modulus test is considered
to be a mechanistically based laboratory test to reliably characterize
the strength and load-resistance of Hot-Mix Asphalt (HMA) mixes
used in the construction of roads. The most common observation is
that the data collected from these tests are often noisy and somewhat
non-sinusoidal. This hampers accurate analysis of the data to obtain
engineering insight. The goal of the work presented in this paper is to
develop and compare automated evolutionary computational
techniques to filter test noise in the collection of data for the HMA
complex modulus test. The results showed that the Covariance
Matrix Adaptation-Evolutionary Strategy (CMA-ES) approach is
computationally efficient for filtering data obtained from the HMA
complex modulus test.
Abstract: Equilibrium and stability equations of a thin rectangular plate with length a, width b, and thickness h(x)=C1x+C2, made of functionally graded materials under thermal loads are derived based on the first order shear deformation theory. It is assumed that the material properties vary as a power form of thickness coordinate variable z. The derived equilibrium and buckling equations are then solved analytically for a plate with simply supported boundary conditions. One type of thermal loading, uniform temperature rise and gradient through the thickness are considered, and the buckling temperatures are derived. The influences of the plate aspect ratio, the relative thickness, the gradient index and the transverse shear on buckling temperature difference are all discussed.
Abstract: Primary studies are being carried out in Turkey for
expanding information and communication technologies (ICT) aided instruction activities. Subject of the present study is to identify
whether those studies achieved their goals in the application. Information technologies (IT) formative teachers in the primary
schools, and academicians in the faculties of education were interviewed to investigate the process and results of implementing
computer-aided instruction methods whose basis is strengthened in theory. Analysis of the results gained from two separate surveys
demonstrated that capability of the teachers in elementary education institutions for carrying into effect computer-aided instruction and
technical infrastructure has not been established for computer-aided instruction practices yet. Prospective teachers must be well-equipped in ICT to duly fulfill requirements of modern education and also
must be self-confident. Finally, scope and intensity of the courses given in connection with teaching of the ICT in faculties of education needs to be revised.
Abstract: Urinary Tract Infections (UTI) account for an estimated 25-40% nosocomial infection, out of which 90% are associated with urinary catheter, called Catheter associated urinary tract infection (CAUTI). The microbial populations within CAUTI frequently develop as biofilms. In the present study, microbial contamination of indwelling urinary catheters was investigated. Biofilm forming ability of the isolates was determined by tissue culture plate method. Prevention of biofilm formation in the urinary catheter by Pseudomonas aeruginosa was also determined by coating the catheter with some enzymes, gentamycin and EDTA. It was found that 64% of the urinary catheters get contaminated during the course of catheterization. Of the total 6 isolates, biofilm formation was seen in 100% Pseudomonas aeruginosa and E. coli, 90% in Enterococci, 80% in Klebsiella and 66% in S. aureus. It was noted that the biofilm production by Pseudomonas was prolonged by 7 days in amylase, 8 days in protease, 6 days in lysozyme, 7days in gentamycin and 5 days in EDTA treated catheter.
Abstract: Grid computing is growing rapidly in the distributed
heterogeneous systems for utilizing and sharing large-scale resources
to solve complex scientific problems. Scheduling is the most recent
topic used to achieve high performance in grid environments. It aims
to find a suitable allocation of resources for each job. A typical
problem which arises during this task is the decision of scheduling. It
is about an effective utilization of processor to minimize tardiness
time of a job, when it is being scheduled. This paper, therefore,
addresses the problem by developing a general framework of grid
scheduling using dynamic information and an ant colony
optimization algorithm to improve the decision of scheduling. The
performance of various dispatching rules such as First Come First
Served (FCFS), Earliest Due Date (EDD), Earliest Release Date
(ERD), and an Ant Colony Optimization (ACO) are compared.
Moreover, the benefit of using an Ant Colony Optimization for
performance improvement of the grid Scheduling is also discussed. It
is found that the scheduling system using an Ant Colony
Optimization algorithm can efficiently and effectively allocate jobs
to proper resources.
Abstract: A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together in colonies. We use comprehensive learning particle swarm optimization (CLPSO) technique to find optimal fuzzy rules and membership functions because it discourages premature convergence. Here each particle of the swarm codes a set of fuzzy rules. During evolution, a population member tries to maximize a fitness criterion which is here high classification rate and small number of rules. Finally, particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Our results, using this method for soccer field image segmentation in Robocop contests shows 89% performance. Less computational load is needed when using this method compared with other methods like ANFIS, because it generates a smaller number of fuzzy rules. Large train dataset and its variety, makes the proposed method invariant to illumination noise
Abstract: It has been established that microRNAs (miRNAs) play
an important role in gene expression by post-transcriptional regulation
of messengerRNAs (mRNAs). However, the precise relationships
between microRNAs and their target genes in sense of numbers,
types and biological relevance remain largely unclear. Dissecting the
miRNA-target relationships will render more insights for miRNA
targets identification and validation therefore promote the understanding
of miRNA function. In miRBase, miRanda is the key
algorithm used for target prediction for Zebrafish. This algorithm
is high-throughput but brings lots of false positives (noise). Since
validation of a large scale of targets through laboratory experiments
is very time consuming, several computational methods for miRNA
targets validation should be developed. In this paper, we present an
integrative method to investigate several aspects of the relationships
between miRNAs and their targets with the final purpose of extracting
high confident targets from miRanda predicted targets pool. This is
achieved by using the techniques ranging from statistical tests to
clustering and association rules. Our research focuses on Zebrafish.
It was found that validated targets do not necessarily associate with
the highest sequence matching. Besides, for some miRNA families,
the frequency of their predicted targets is significantly higher in the
genomic region nearby their own physical location. Finally, in a case
study of dre-miR-10 and dre-miR-196, it was found that the predicted
target genes hoxd13a, hoxd11a, hoxd10a and hoxc4a of dre-miR-
10 while hoxa9a, hoxc8a and hoxa13a of dre-miR-196 have similar
characteristics as validated target genes and therefore represent high
confidence target candidates.
Abstract: With increasing utilization of the wireless devices in
different fields such as medical devices and industrial fields, the
paper presents a method for simplify the Bluetooth packets with
throughput enhancing. The paper studies a vital issue in wireless
communications, which is the throughput of data over wireless
networks. In fact, the Bluetooth and ZigBee are a Wireless Personal
Area Network (WPAN). With taking these two systems competition
consideration, the paper proposes different schemes for improve the
throughput of Bluetooth network over a reliable channel. The
proposition depends on the Channel Quality Driven Data Rate
(CQDDR) rules, which determines the suitable packet in the
transmission process according to the channel conditions. The
proposed packet is studied over additive White Gaussian Noise
(AWGN) and fading channels. The Experimental results reveal the
capability of extension of the PL length by 8, 16, 24 bytes for classic
and EDR packets, respectively. Also, the proposed method is suitable
for the low throughput Bluetooth.
Abstract: In the multi objective optimization, in the case when generated set of Pareto optimal solutions is large, occurs the problem to select of the best solution from this set. In this paper, is suggested a method to order of Pareto set. Ordering the Pareto optimal set carried out in conformity with the introduced distance function between each solution and selected reference point, where the reference point may be adjusted to represent the preferences of a decision making agent. Preference information about objective weights from a decision maker may be expressed imprecisely. The developed elicitation procedure provides an opportunity to obtain surrogate numerical weights for the objectives, and thus, to manage impreciseness of preference. The proposed method is a scalable to many objectives and can be used independently or as complementary to the various visualization techniques in the multidimensional case.
Abstract: The use of Electronic Commerce (EC)
technologies enables Small Medium Enterprises (SMEs) to improve their efficiency and competitive position. Much of the literature proposes an extensive set of benefits for
organizations that choose to adopt and implement ECommerce
systems. Factors of Business –to-business (B2B)
E-Commerce adoption and implementation have been
extensively investigated. Despite enormous attention given to encourage Small Medium Enterprises (SMEs) to adopt and
implement E-Commerce, little research has been carried out in identifying the factors of Business-to-Consumer ECommerce adoption and implementation for SMEs. To conduct the study, Tornatsky and Fleischer model was adopted
and tested in four SMEs located in Christchurch, New
Zealand. This paper explores the factors that impact the
decision and method of adoption and implementation of ECommerce
systems in automobile industry. Automobile
industry was chosen because the product they deal with i.e.
cars are not a common commodity to be sold online, despite this fact the eCommerce penetration in automobile industry is
high. The factors that promote adoption and implementation of
E-Commerce technologies are discussed, together with the
barriers. This study will help SME owners to effectively
handle the adoption and implementation process and will also
improve the chance of successful E-Commerce
implementation. The implications of the findings for
managers, consultants, and government organizations engaged in promoting E-Commerce adoption and implementation in
small businesses and future research are discussed.
Abstract: In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.