Abstract: This paper presents a comparison of metaheuristic
algorithms, Genetic Algorithm (GA) and Ant Colony Optimization
(ACO), in producing freeman chain code (FCC). The main problem
in representing characters using FCC is the length of the FCC
depends on the starting points. Isolated characters, especially the
upper-case characters, usually have branches that make the traversing
process difficult. The study in FCC construction using one
continuous route has not been widely explored. This is our
motivation to use the population-based metaheuristics. The
experimental result shows that the route length using GA is better
than ACO, however, ACO is better in computation time than GA.
Abstract: In this paper 2D Simulation of catalytic Fixed Bed Reactor in Fischer-Tropsch Synthesis of GTL technology has been performed utilizing computational fluid dynamics (CFD). Synthesis gas (a mixture of carbon monoxide and hydrogen) has been used as feedstock. The reactor was modeled and the model equations were solved employing finite volume method. The model was validated against the experimental data reported in literature. The comparison showed a good agreement between simulation results and the experimental data. In addition, the model was applied to predict the concentration contours of the reactants and products along the length of reactor.
Abstract: Wireless sensor network has recently emerged as enablers
of several areas. Real applications of WSN are being explored
and some of them are yet to come. While the potential of sensor
networks has been only beginning to be realized, several challenges
still remain. One of them is the experimental evaluation of WSN.
Therefore, deploying and operating a testbed to study the real
behavior of WSN become more and more important. The main
contribution of this work is to analysis the RF link budget behavior
of wireless sensor networks in underground mine gallery.
Abstract: A vast array of biological materials, especially algae have received increasing attention for heavy metal removal. Algae have been proven to be cheaper, more effective for the removal of metallic elements in aqueous solutions. A fresh water algal strain was isolated from Zoo Lake, Johannesburg, South Africa and identified as Desmodesmus sp. This paper investigates the efficacy of Desmodesmus sp.in removing heavy metals contaminating the Wonderfonteinspruit Catchment Area (WCA) water bodies. The biosorption data fitted the pseudo-second order and Langmuir isotherm models. The Langmuir maximum uptakes gave the sequence: Mn2+>Ni2+>Fe2+. The best results for kinetic study was obtained in concentration 120 ppm for Fe3+ and Mn2+, whilst for Ni2+ was at 20 ppm, which is about the same concentrations found in contaminated water in the WCA (Fe3+115 ppm, Mn2+ 121 ppm and Ni2+ 26.5 ppm).
Abstract: Biclustering is a very useful data mining technique for
identifying patterns where different genes are co-related based on a
subset of conditions in gene expression analysis. Association rules
mining is an efficient approach to achieve biclustering as in
BIMODULE algorithm but it is sensitive to the value given to its
input parameters and the discretization procedure used in the
preprocessing step, also when noise is present, classical association
rules miners discover multiple small fragments of the true bicluster,
but miss the true bicluster itself. This paper formally presents a
generalized noise tolerant bicluster model, termed as μBicluster. An
iterative algorithm termed as BIDENS based on the proposed model
is introduced that can discover a set of k possibly overlapping
biclusters simultaneously. Our model uses a more flexible method to
partition the dimensions to preserve meaningful and significant
biclusters. The proposed algorithm allows discovering biclusters that
hard to be discovered by BIMODULE. Experimental study on yeast,
human gene expression data and several artificial datasets shows that
our algorithm offers substantial improvements over several
previously proposed biclustering algorithms.
Abstract: Research has suggested that implicit learning tasks
may rely on episodic processing to generate above chance
performance on the standard classification tasks. The current
research examines the invariant features task (McGeorge and Burton,
1990) and argues that such episodic processing is indeed important.
The results of the experiment suggest that both rejection and
similarity strategies are used by participants in this task to
simultaneously reject unfamiliar items and to accept (falsely) familiar
items. Primarily these decisions are based on the presence of low or
high frequency goal based features of the stimuli presented in the
incidental learning phase. It is proposed that a goal based analysis of
the incidental learning task provides a simple step in understanding
which features of the episodic processing are most important for
explaining the match between incidental, implicit learning and test
performance.
Abstract: In this work, the results of mixing study by a jet mixer in a tank have been investigated in the laboratory scale. The tank dimensions are H/D=1 and the jet entrance have been considered in
the center of upper surface of tank. RNG-k-ε model is used as the
turbulent model for the prediction of the pattern of turbulent flow
inside the tank. For this purpose, a tank with volume of 110 liter is
simulated and it has been divided into 410,000 tetrahedral control
cells for performing the calculations. The grids at the vicinity of the
nozzle and suction pare are finer to get more accurate results. The
experimental results showed that in a vertical jet, the lowest mixing
time takes place at 35 degree. In addition, mixing time decreased by
increasing the Reynolds number. Furthermore, the CFD simulation
predicted the items as well a flow patterns precisely that validates the
experiments.
Abstract: In this content analysis research note the aim was to explore to how sustainability and especially environmental issues are conveyed into environmental items in annual reports and disclosures. As The Global Reporting Initiative (GRI) is a globally wide multistakeholder process, the enterprises using voluntarily GRI framework are considered to be aware of sustainability and environmental concerns. The findings were that although these enterprises included in an environmentally sensitive industry sector and had special capabilities to consider environmental issues there were few GRIreporting enterprises presented substantially detailed environmental items in audited financial statements. There were only slight differences between publishing years 2008 and 2009 - the beginning years of economic turmoil. The environmental issues seemed not to be considered substantial enough for financial reporting as a basis for concerning investment or voting decisions.
Abstract: This paper describes a concept of stereotype student
model in adaptive knowledge acquisition e-learning system. Defined
knowledge stereotypes are based on student's proficiency level and
on Bloom's knowledge taxonomy. The teacher module is responsible
for the whole adaptivity process: the automatic generation of
courseware elements, their dynamic selection and sorting, as well as
their adaptive presentation using templates for statements and
questions. The adaptation of courseware is realized according to
student-s knowledge stereotype.
Abstract: Bringing change to the housing industry requires
multiple efforts from various angles especially to overcome any
resistances in the form of technology, human aspects, financial and
resources. The transition from conventional to sustainable approach
consumes time as it requires changes from different facets in the
industry ranging from individual, organisational to industry level. In
Malaysia, there are various efforts to bring green into the industry but
the progress is low-moderate. Will the current efforts bear larger
fruits in the near future? This study examines the perceptions of the
developers in Malaysia on the future of the green housing sector for
the next 5 years. The introduction of GBI rating system, improvement
of awareness and knowledge among the stakeholders, support from
the government and local industry and the effect of competitive
advantage would support brighter future. Meanwhile, the status quo
in rules and regulation, lack of public interest and demand,
organization disinterest, local authority enforcement and project cost
escalation would hinder a faster progress.
Abstract: In order to achieve better road utilization and traffic
efficiency, there is an urgent need for a travel information delivery
mechanism to assist the drivers in making better decisions in the
emerging intelligent transportation system applications. In this paper,
we propose a relayed multicast scheme under heterogeneous networks
for this purpose. In the proposed system, travel information consisting
of summarized traffic conditions, important events, real-time traffic
videos, and local information service contents is formed into layers
and multicasted through an integration of WiMAX infrastructure and
Vehicular Ad hoc Networks (VANET). By the support of adaptive
modulation and coding in WiMAX, the radio resources can be
optimally allocated when performing multicast so as to dynamically
adjust the number of data layers received by the users. In addition to
multicast supported by WiMAX, a knowledge propagation and
information relay scheme by VANET is designed. The experimental
results validate the feasibility and effectiveness of the proposed
scheme.
Abstract: The effect of chemical treatment in CdCl2 on the
compositional changes and defect structures of potentially useful ZnS
solar cell thin films prepared by vacuum deposition method was
studied using the complementary Rutherford backscattering (RBS)
and Thermoluminesence (TL) techniques. A series of electron and
hole traps are found in the various as deposited samples studied.
After treatment, perturbation on the intensity is noted; mobile defect
states and charge conversion and/or transfer between defect states are
found.
Abstract: In many applications, magnetic suspension systems
are required to operate over large variations in air gap. As a result,
the nonlinearities inherent in most types of suspensions have a
significant impact on performance. Specifically, it may be difficult to
design a linear controller which gives satisfactory performance,
stability, and disturbance rejection over a wide range of operating
points. in this paper an optimal controller based on discontinuous
mathematical model of the system for an electromagnetic suspension
system which is applied in magnetic trains has been designed .
Simulations show that the new controller can adapt well to the
variance of suspension mass and gap, and keep its dynamic
performance, thus it is superior to the classic controller.
Abstract: The human knee joint has a three dimensional
geometry with multiple body articulations that produce complex
mechanical responses under loads that occur in everyday life and
sports activities. To produce the necessary joint compliance and
stability for optimal daily function various menisci and ligaments are
present while muscle forces are used to this effect. Therefore,
knowledge of the complex mechanical interactions of these load
bearing structures is necessary when treatment of relevant diseases is
evaluated and assisting devices are designed.
Numerical tools such as finite element analysis are suitable for
modeling such joints in order to understand their physics. They have
been used in the current study to develop an accurate human knee
joint and model its mechanical behavior. To evaluate the efficacy of
this articulated model, static load cases were used for comparison
purposes with previous experimentally verified modeling works
drawn from literature.
Abstract: This paper systematically investigates the timedependent
health outcomes for office staff during computer work
using the developed mathematical model. The model describes timedependent
health outcomes in multiple body regions associated with
computer usage. The association is explicitly presented with a doseresponse
relationship which is parametrized by body region
parameters. Using the developed model we perform extensive
investigations of the health outcomes statically and dynamically. We
compare the risk body regions and provide various severity rankings
of the discomfort rate changes with respect to computer-related
workload dynamically for the study population. Application of the
developed model reveals a wide range of findings. Such broad
spectrum of investigations in a single report literature is lacking.
Based upon the model analysis, it is discovered that the highest
average severity level of the discomfort exists in neck, shoulder, eyes,
shoulder joint/upper arm, upper back, low back and head etc. The
biggest weekly changes of discomfort rates are in eyes, neck, head,
shoulder, shoulder joint/upper arm and upper back etc. The fastest
discomfort rate is found in neck, followed by shoulder, eyes, head,
shoulder joint/upper arm and upper back etc. Most of our findings are
consistent with the literature, which demonstrates that the developed
model and results are applicable and valuable and can be utilized to
assess correlation between the amount of computer-related workload
and health risk.
Abstract: Prediction of highly non linear behavior of suspended
sediment flow in rivers has prime importance in the field of water
resources engineering. In this study the predictive performance of
two Artificial Neural Networks (ANNs) namely, the Radial Basis
Function (RBF) Network and the Multi Layer Feed Forward (MLFF)
Network have been compared. Time series data of daily suspended
sediment discharge and water discharge at Pari River was used for
training and testing the networks. A number of statistical parameters
i.e. root mean square error (RMSE), mean absolute error (MAE),
coefficient of efficiency (CE) and coefficient of determination (R2)
were used for performance evaluation of the models. Both the models
produced satisfactory results and showed a good agreement between
the predicted and observed data. The RBF network model provided
slightly better results than the MLFF network model in predicting
suspended sediment discharge.
Abstract: The present study is concerned with the free
convective two dimensional flow and heat transfer, within the
framework of Boussinesq approximation, in anisotropic fluid filled
porous rectangular enclosure subjected to end-to-end temperature
difference have been investigated using Lattice Boltzmann method
fornon-Darcy flow model. Effects of the moving lid direction (top,
bottom, left, and right wall moving in the negative and positive x&ydirections),
number of moving walls (one or two opposite walls), the
sliding wall velocity, and four different constant temperatures
opposite walls cases (two surfaces are being insulated and the
twoother surfaces areimposed to be at constant hot and cold
temperature)have been conducted. The results obtained are discussed
in terms of the Nusselt number, vectors, contours, and isotherms.
Abstract: Nowadays increasingly the population makes use of
Information Technology (IT). As such, in recent year the Portuguese
government increased its focus on using the IT for improving
people-s life and began to develop a set of measures to enable the
modernization of the Public Administration, and so reducing the gap
between Public Administration and citizens.Thus the Portuguese
Government launched the Simplex Program. However these
SIMPLEX eGov measures, which have been implemented over the
years, present a serious challenge: how to forecast its impact on
existing Information Systems Architecture (ISA). Thus, this research
is focus in addressing the problem of automating the evaluation of the
actual impact of implementation an eGovSimplification and
Modernization measures in the Information Systems Architecture. To
realize the evaluation we proposes a Framework, which is supported
by some key concepts as: Quality Factors, ISA modeling,
Multicriteria Approach, Polarity Profile and Quality Metrics
Abstract: The present study has been conducted to characterize
the prophenoloxidase (PPO) system of the desert locust, Schistocerca
gregaria following injection of Bacillus thuringiensis kurstaki (Bt).
The bulk of PPO system was associated with haemocytes and a little
amount was found in plasma. This system was activated by different
activators such as laminarin, lipopolysaccharide (LPS) and trypsin
suggesting that the stimulatory mechanism may involve an enzyme
cascade of one or more associated molecules. These activators did
not activate all the molecules of the cascade. Presence of
phenoloxidase activity (PO) coincides with the appearance of protein
band with molecular weight (MW) 70.154 KD (Kilo Dalton).
Abstract: Deep Brain Stimulation or DBS is the second solution
for Parkinson's Disease. Its three parameters are: frequency, pulse
width and voltage. They must be optimized to achieve successful
treatment. Nowadays it is done clinically by neurologists and there is
not certain numerical method to detect them. The aim of this research
is to introduce simulation and modeling of Parkinson's Disease
treatment as a computational procedure to select optimum voltage.
We recorded finger tremor signals of some Parkinsonian patients
under DBS treatment at constant frequency and pulse width but
variable voltages; then, we adapted a new model to fit these data. The
optimum voltages obtained by data fitting results were the same as
neurologists- commented voltages, which means modeling can be
used as an engineering method to select optimum stimulation
voltages.