Abstract: The present contribution deals with the
thermophoretic deposition of nanoparticles over a rapidly rotating
permeable disk in the presence of partial slip, magnetic field, thermal
radiation, thermal-diffusion, and diffusion-thermo effects. The
governing nonlinear partial differential equations such as continuity,
momentum, energy and concentration are transformed into nonlinear
ordinary differential equations using similarity analysis, and the
solutions are obtained through the very efficient computer algebra
software MATLAB. Graphical results for non-dimensional
concentration and temperature profiles including thermophoretic
deposition velocity and Stanton number (thermophoretic deposition
flux) in tabular forms are presented for a range of values of the
parameters characterizing the flow field. It is observed that slip
mechanism, thermal-diffusion, diffusion-thermo, magnetic field and
radiation significantly control the thermophoretic particles deposition
rate. The obtained results may be useful to many industrial and
engineering applications.
Abstract: Natural gas flow contains undesirable solid particles,
liquid condensation, and/or oil droplets and requires reliable
removing equipment to perform filtration. Recent natural gas
processing applications are demanded compactness and reliability of
process equipment. Since conventional means are sophisticated in
design, poor in efficiency, and continue lacking robust, a supersonic
nozzle has been introduced as an alternative means to meet such
demands.
A 3-D Convergent-Divergent Nozzle is simulated using
commercial Code for pressure ratio (NPR) varies from 1.2 to 2. Six
different shapes of nozzle are numerically examined to illustrate the
position of shock-wave as such spot could be considered as a
benchmark of particle separation. Rectangle, triangle, circular,
elliptical, pentagon, and hexagon nozzles are simulated using Fluent
Code with all have same cross-sectional area.
The simple one-dimensional inviscid theory does not describe the
actual features of fluid flow precisely as it ignores the impact of
nozzle configuration on the flow properties. CFD Simulation results,
however, show that nozzle geometry influences the flow structures
including location of shock wave.
The CFD analysis predicts shock appearance when p01/pa>1.2 for
almost all geometry and locates at the lower area ratio (Ae/At).
Simulation results showed that shock wave in Elliptical nozzle has
the farthest distance from the throat among the others at relatively
small NPR. As NPR increases, hexagon would be the farthest. The
numerical result is compared with available experimental data and
has shown good agreement in terms of shock location and flow
structure.
Abstract: Adaptive Genetic Algorithms extend the Standard Gas
to use dynamic procedures to apply evolutionary operators such as
crossover, mutation and selection. In this paper, we try to propose a
new adaptive genetic algorithm, which is based on the statistical
information of the population as a guideline to tune its crossover,
selection and mutation operators. This algorithms is called Statistical
Genetic Algorithm and is compared with traditional GA in some
benchmark problems.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: The hospital and the health-care center of a
community, as a place for people-s life-care and health-care settings,
must provide more and better services for patients or residents. After
Establishing Electronic Medical Record (EMR) system -which is a
necessity- in the hospital, providing pervasive services is a further
step. Our objective in this paper is to use pervasive computing in a
case study of healthcare, based on EMR database that coordinates
application services over network to form a service environment for
medical and health-care. Our method also categorizes the hospital
spaces into 3 spaces: Public spaces, Private spaces and Isolated
spaces. Although, there are many projects about using pervasive
computing in healthcare, but all of them concentrate on the disease
recognition, designing smart cloths, or provide services only for
patient. The proposed method is implemented in a hospital. The
obtained results show that it is suitable for our purpose.
Abstract: European Union candidate status provides a
strong motivation for decision-making in the candidate
countries in shaping the regional development policy where
there is an envisioned transfer of power from center to the
periphery. The process of Europeanization anticipates the
candidate countries configure their regional institutional
templates in the context of the requirements of the European
Union policies and introduces new instruments of incentive
framework of enlargement to be employed in regional
development schemes. It is observed that the contribution of
the local actors to the decision making in the design of the
allocation architectures enhances the efficiency of the funds
and increases the positive effects of the projects funded under
the regional development objectives. This study aims at
exploring the performances of the three regional development
grant schemes in Turkey, established and allocated under the
pre-accession process with a special emphasis given to the
roles of the national and local actors in decision-making for
regional development. Efficiency analyses have been
conducted using the DEA methodology which has proved to
be a superior method in comparative efficiency and
benchmarking measurements. The findings of this study as
parallel to similar international studies, provides that the
participation of the local actors to the decision-making in
funding contributes both to the quality and the efficiency of
the projects funded under the EU schemes.
Abstract: Although services play a crucial role in economy,
service did not gain as much importance as productivity management
in manufacturing. This paper presents key findings from literature
and practice. Based on an initial definition of complex services, seven
productivity concepts are briefly presented and assessed by relevant,
complex service specific criteria. Following the findings a complex
service productivity model is proposed. The novel model comprises
of all specific dimensions of service provision from both, the
provider-s as well as costumer-s perspective. A clear assignment of
identified value drivers and relationships between them is presented.
In order to verify the conceptual service productivity model a case
study from a project engineering department of a chemical plant
development and construction company is presented.
Abstract: The purposes of this research were 1) to survey the
number of drugstores that unlawful dispense of asthma prescription
drugs, in form of drug combinations in the Phaya Thai district of
Bangkok, 2) to find the steroids contained in that drug combinations,
3) to find a means for informing general public about the dangers of
drugs and for a campaign to stop dispensing them.
Researcher collected drug combinations from 69 drugstores in
Phaya Thai district from Feb 15, 2012 to Mar 15, 2012. The survey
found 30.43%, 21, drug stores, sold asthma drug combinations to
customers without a prescription. These collected samples were
tested for steroid contamination by using Immunochromatography
kits. Eleven samples, 52.38%, were found contaminated with
steroids. In short, there should be control and inspection of
drugstores in the distribution of steroid medications. To improve the
knowledge of self health maintenance and drug usage among public,
Thai Government and Department of Public Health should educate
people about the side effects of using drug combinations and steroids.
Abstract: To strengthen the capital market, there is a need to
integrate the capital markets within the region by removing legal or informal restriction, specifically, stock market liberalization. Thus the paper is to investigate the effects of the subsequent stock market liberalization on stock market integration in 4 ASEAN countries (Malaysia, Indonesia, Thailand, Singapore) and Korea from 1997 to 2007. The correlation between stock market liberalization and stock
market integration are to be examined by analyzing the stock prices
and returns within the region and in comparison with the world
MSCI index. Event study method is to be used with windows of ±12
months and T-7 + T. The results show that the subsequent stock
market liberalization generally, gives minor positive effects to stock
returns, except for one or two countries. The subsequent
liberalization also integrates the markets short-run and long-run.
Abstract: The phenomenon of global warming or climate
change has led to many environmental issues including higher
atmospheric temperatures, intense precipitation, increased
greenhouse gaseous emissions and increased indoor discomfort.
Studies have shown that bringing nature to the roof such as
constructing green roof and implementing high-reflective roof may
give positive impact in mitigating the effects of global warming and
in increasing thermal comfort sensation inside buildings. However,
no study has been conducted to compare both types of passive roof
treatments in Malaysia in order to increase thermal comfort in
buildings. Therefore, this study is conducted to investigate the effect
of green roof and white painted roof as passive roof treatment in
improving indoor comfort of Malaysian homes. This study uses an
experimental approach in which the measurements of temperatures
are conducted on the case study building. The measurements of
outdoor and indoor environments were conducted on the flat roof
with two different types of roof treatment that are green roof and
white roof. The measurement of existing black bare roof was also
conducted to act as a control for this study.
Abstract: The Block Sorting problem is to sort a given
permutation moving blocks. A block is defined as a substring
of the given permutation, which is also a substring of the
identity permutation. Block Sorting has been proved to be
NP-Hard. Until now two different 2-Approximation algorithms
have been presented for block sorting. These are the best known
algorithms for Block Sorting till date. In this work we present
a different characterization of Block Sorting in terms of a
transposition cycle graph. Then we suggest a heuristic,
which we show to exhibit a 2-approximation performance
guarantee for most permutations.
Abstract: A steady two-dimensional magnetohydrodynamics
flow and heat transfer over a stretching vertical sheet influenced by
radiation and porosity is studied. The governing boundary layer
equations of partial differential equations are reduced to a system of
ordinary differential equations using similarity transformation. The
system is solved numerically by using a finite difference scheme
known as the Keller-box method for some values of parameters,
namely the radiation parameter N, magnetic parameter M, buoyancy
parameter l , Prandtl number Pr and permeability parameter K. The
effects of the parameters on the heat transfer characteristics are
analyzed and discussed. It is found that both the skin friction
coefficient and the local Nusselt number decrease as the magnetic
parameter M and permeability parameter K increase. Heat transfer
rate at the surface decreases as the radiation parameter increases.
Abstract: Power cables are vulnerable to failure due to aging or
defects that occur with the passage of time under continuous
operation and loading stresses. PD detection and characterization
provide information on the location, nature, form and extent of the
degradation. As a result, PD monitoring has become an important
part of condition based maintenance (CBM) program among power
utilities. Online partial discharge (PD) localization of defect sources
in power cable system is possible using the time of flight method.
The information regarding the time difference between the main and
reflected pulses and cable length can help in locating the partial
discharge source along the cable length. However, if the length of
the cable is not known and the defect source is located at the extreme
ends of the cable or in the middle of the cable, then double ended
measurement is required to indicate the location of PD source. Use of
multiple sensors can also help in discriminating the cable PD or local/
external PD. This paper presents the experience and results from
online partial discharge measurements conducted in the laboratory
and the challenges in partial discharge source localization.
Abstract: Seaweed farming is emerging as a viable alternative
activity in the Indonesian fisheries sector. This paper aims to
investigate people-s perceptions of seaweed farming, to analyze its
social and economic impacts and to identify the problems and
obstacles hindering its continued development. Structured and
semi-structured questionnaires were prepared to obtain qualitative
data, and interviews were conducted with fishermen who also plant
seaweed. The findings showed that fishermen in the Laikang Bay were
enthusiastic about cultivating seaweeds and that seaweed plays a major
role in supporting the household economy of fishermen. However,
current seaweed drying technologies cannot support increased
seaweed production on a farm or plot, especially in the rainy season.
Additionally, variable monsoon seasons and long marketing channels
are still major constraints on the development of the industry. Finally,
capture fisheries, the primary economic livelihood of fishermen of
older generations, is being slowly replaced by seaweed farming.
Abstract: Next generation networks with the idea of convergence of service and control layer in existing networks (fixed, mobile and data) and with the intention of providing services in an integrated network, has opened new horizon for telecom operators. On the other hand, economic problems have caused operators to look for new source of income including consider new services, subscription of more users and their promotion in using morenetwork resources and easy participation of service providers or 3rd party operators in utilizing networks. With this requirement, an architecture based on next generation objectives for service layer is necessary. In this paper, a new architecture based on IMS model explains participation of 3rd party operators in creation and implementation of services on an integrated telecom network.
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: 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: Detection, feature extraction and pose estimation of
people in images and video is made challenging by the variability of
human appearance, the complexity of natural scenes and the high
dimensionality of articulated body models and also the important
field in Image, Signal and Vision Computing in recent years. In this
paper, four types of people in 2D dimension image will be tested and
proposed. The system will extract the size and the advantage of them
(such as: tall fat, short fat, tall thin and short thin) from image. Fat
and thin, according to their result from the human body that has been
extract from image, will be obtained. Also the system extract every
size of human body such as length, width and shown them in output.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Abstract: Recent developments in storage technology and
networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate
decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is
logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among
concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data
streams.