Abstract: “Dengue" is an African word meaning “bone
breaking" because it causes severe joint and muscle pain that feels
like bones are breaking. It is an infectious disease mainly transmitted
by female mosquito, Aedes aegypti, and causes four serotypes of
dengue viruses. In recent years, a dramatic increase in the dengue
fever confirmed cases around the equator-s belt has been reported.
Several conventional indices have been designed so far to monitor the
transmitting vector populations known as House Index (HI),
Container Index (CI), Breteau Index (BI). However, none of them
describes the adult mosquito population size which is important to
direct and guide comprehensive control strategy operations since
number of infected people has a direct relationship with the vector
density. Therefore, it is crucial to know the population size of the
transmitting vector in order to design a suitable and effective control
program. In this context, a study is carried out to report a new
statistical index, ABURAS Index, using Poisson distribution based
on the collection of vector population in Jeddah Governorate, Saudi Arabia.
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents and evolutionary
computation techniques in legacy e-learning environments. It
introduces the design and development of a scalable and
interoperable integration platform supporting:
I) various assessment agents for e-learning environments,
II) a specific resource retrieval agent for the provision of
additional information from Internet sources matching the
needs and profile of the specific user and
III) a genetic algorithm designed to extract efficient information
(classifying rules) based on the students- answering input
data.
The agents are implemented in order to provide intelligent
assessment services based on computational intelligence techniques
such as Bayesian Networks and Genetic Algorithms.
The proposed Genetic Algorithm (GA) is used in order to extract
efficient information (classifying rules) based on the students-
answering input data. The idea of using a GA in order to fulfil this
difficult task came from the fact that GAs have been widely used in
applications including classification of unknown data.
The utilization of new and emerging technologies like web
services allows integrating the provided services to any web based
legacy e-learning environment.
Abstract: In this paper, the effects of radiation, chemical
reaction and double dispersion on mixed convection heat and mass
transfer along a semi vertical plate are considered. The plate is
embedded in a Newtonian fluid saturated non - Darcy (Forchheimer
flow model) porous medium. The Forchheimer extension and first
order chemical reaction are considered in the flow equations. The
governing sets of partial differential equations are nondimensionalized
and reduced to a set of ordinary differential
equations which are then solved numerically by Fourth order Runge–
Kutta method. Numerical results for the detail of the velocity,
temperature, and concentration profiles as well as heat transfer rates
(Nusselt number) and mass transfer rates (Sherwood number) against
various parameters are presented in graphs. The obtained results are
checked against previously published work for special cases of the
problem and are found to be in good agreement.
Abstract: Location selection is one of the most important
decision making process which requires to consider several criteria
based on the mission and the strategy. This study-s object is to
provide a decision support model in order to help the bank selecting
the most appropriate location for a bank-s branch considering a case
study in Turkey. The object of the bank is to select the most
appropriate city for opening a branch among six alternatives in the
South-Eastern of Turkey. The model in this study was consisted of
five main criteria which are Demographic, Socio-Economic, Sectoral
Employment, Banking and Trade Potential and twenty one subcriteria
which represent the bank-s mission and strategy. Because of
the multi-criteria structure of the problem and the fuzziness in the
comparisons of the criteria, fuzzy AHP is used and for the ranking of
the alternatives, TOPSIS method is used.
Abstract: Power system state estimation is the process of
calculating a reliable estimate of the power system state vector
composed of bus voltages' angles and magnitudes from telemetered
measurements on the system. This estimate of the state vector
provides the description of the system necessary for the operation
and security monitoring. Many methods are described in the
literature for solving the state estimation problem, the most important
of which are the classical weighted least squares method and the nondeterministic
genetic based method; however both showed
drawbacks. In this paper a modified version of the genetic
algorithm power system state estimation is introduced, Sensitivity of
the proposed algorithm to genetic operators is discussed, the
algorithm is applied to case studies and finally it is compared with
the classical weighted least squares method formulation.
Abstract: In our recent study, we have used ZnO nanoparticles assisted with UV light irradiation to investigate the photocatalytic degradation of Phenol Red (PR). The ZnO photocatalyst was characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), specific surface area analysis (BET) and UVvisible spectroscopy. X-ray diffractometry result for the ZnO nanoparticles exhibit normal crystalline phase features. All observed peaks can be indexed to the pure hexagonal wurtzite crystal structures, with the space group of P63mc. There are no other impurities in the diffraction peak. In addition, TEM measurement shows that most of the nanoparticles are rod-like and spherical in shape and fairly monodispersed. A significant degradation of the PR was observed when the catalyst was added into the solution even without the UV light exposure. In addition, the photodegradation increases with the photocatalyst loading. The surface area of the ZnO nanomaterials from the BET measurement was 11.9 m2/g. Besides the photocatalyst loading, the effect of some parameters on the photodegradation efficiency such as initial PR concentration and pH were also studied.
Abstract: An evolutionary method whose selection and recombination
operations are based on generalization error-bounds of
support vector machine (SVM) can select a subset of potentially
informative genes for SVM classifier very efficiently [7]. In this
paper, we will use the derivative of error-bound (first-order criteria)
to select and recombine gene features in the evolutionary process,
and compare the performance of the derivative of error-bound with
the error-bound itself (zero-order) in the evolutionary process. We
also investigate several error-bounds and their derivatives to compare
the performance, and find the best criteria for gene selection
and classification. We use 7 cancer-related human gene expression
datasets to evaluate the performance of the zero-order and first-order
criteria of error-bounds. Though both criteria have the same strategy
in theoretically, experimental results demonstrate the best criterion
for microarray gene expression data.
Abstract: To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.
Abstract: In this paper, we study on color transformation
method on website images for the color blind. The most common
category of color blindness is red-green color blindness which is
viewed as beige color. By transforming the colors of the images, the
color blind can improve their color visibility. They can have a better
view when browsing through the websites. To transform colors on
the website images, we study on two algorithms which are the
conversion techniques from RGB color space to HSV color space and
self-organizing color transformation. The comparative study focuses
on criteria based on the ease of use, quality, accuracy and efficiency.
The outcome of the study leads to enhancement of website images to
meet the color blinds- vision requirements in perceiving image
detailed.
Abstract: Transport and logistics are the lifeblood of societies.
There is a strong correlation between overall growth in economic
activity and growth of transport. The movement of people and goods
has the potential for creating wealth and prosperity, therefore the
state of transportation infrastructure and especially the condition of
road networks is often a governmental priority. The design, building
and maintenance of national roads constitute a substantial share of
government budgets. Taking into account the magnitude and
importance of these investments, the expedience, efficiency and
sustainability of these projects are of great public interest. This paper
provides an overview of supply chain management principles applied
to road construction. In addition, road construction performance
measurement systems and ICT solutions are discussed. Road
construction in Estonia is analyzed. The authors propose the
development of a national performance measurement system for road
construction.
Abstract: This study aimed to evaluate the muscularity and tissue composition of 24 legs of Ile de France lambs. They were fed with diets containing “in nature" or hydrolyzed sugarcane with 0.6% of calcium oxide in aerobic and anaerobic environments. Animals entered the trial at 15 and were slaughtered at 32 kg of body weight. The leg tissue composition, as well as muscularity (0.47), muscle:bone (6.66) and muscle:fat (4.25) were not affected (P>0.05) by treatments. The proportions found were: 67.62% for muscle, 17.52% for bone and 10.15% for fat. In relation to lambs fed with “in nature" sugarcane, hydrolyzed sugarcane with calcium oxide in aerobic and anaerobic environments did not affect muscularity and leg tissue composition of lambs.
Abstract: The onset of Marangoni convection in a horizontal
fluid layer with internal heat generation overlying a solid layer
heated from below is studied. The upper free surface of a fluid is
nondeformable and the bottom boundary are rigid and no-slip. The
resulting eigenvalue problem is solved exactly. The critical values of
the Marangoni numbers for the onset of Marangoni convection are
calculated and the latter is found to be critically dependent on the
internal heating, depth ratio and conductivity ratio. The effects of the
thermal conductivity and the thickness of the solid plate on the onset
of convective instability with internal heating are studied in detail.
Abstract: Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.
Abstract: In this paper, the detection of a fault in the Global Positioning System (GPS) measurement is addressed. The class of faults considered is a bias in the GPS pseudorange measurements. This bias is modeled as an unknown constant. The fault could be the result of a receiver fault or signal fault such as multipath error. A bias bank is constructed based on set of possible fault hypotheses. Initially, there is equal probability of occurrence for any of the biases in the bank. Subsequently, as the measurements are processed, the probability of occurrence for each of the biases is sequentially updated. The fault with a probability approaching unity will be declared as the current fault in the GPS measurement. The residual formed from the GPS and Inertial Measurement Unit (IMU) measurements is used to update the probability of each fault. Results will be presented to show the performance of the presented algorithm.
Abstract: Wet chemistry methods are used to prepare the
SiO2/Au nanoshells. The purpose of this research was to synthesize
gold coated SiO2 nanoshells for biomedical applications. Tunable
nanoshells were prepared by using different colloidal concentrations.
The nanoshells are characterized by FTIR, XRD, UV-Vis
spectroscopy and atomic force microscopy (AFM). The FTIR results
confirmed the functionalization of the surfaces of silica nanoparticles
with NH2 terminal groups. A tunable absorption was observed
between 470-600 nm with a maximum range of 530-560 nm. Based
on the XRD results three main peaks of Au (111), (200) and (220)
were identified. Also AFM results showed that the silica core
diameter was about 100 nm and the thickness of gold shell about 10
nm.
Abstract: Scene interpretation systems need to match (often ambiguous)
low-level input data to concepts from a high-level ontology.
In many domains, these decisions are uncertain and benefit greatly
from proper context. This paper demonstrates the use of decision
trees for estimating class probabilities for regions described by feature
vectors, and shows how context can be introduced in order to improve
the matching performance.
Abstract: Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Abstract: This paper presents and evaluates a new classification
method that aims to improve classifiers performances and speed up
their training process. The proposed approach, called labeled
classification, seeks to improve convergence of the BP (Back
propagation) algorithm through the addition of an extra feature
(labels) to all training examples. To classify every new example, tests
will be carried out each label. The simplicity of implementation is the
main advantage of this approach because no modifications are
required in the training algorithms. Therefore, it can be used with
others techniques of acceleration and stabilization. In this work, two
models of the labeled classification are proposed: the LMLP
(Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro
Fuzzy Classifier). These models are tested using Iris, wine, texture
and human thigh databases to evaluate their performances.
Abstract: Requirements that should be met when determining the regimes of circuits with variable elements are formulated. The interpretation of the variations in the regimes, based on projective geometry, enables adequate expressions for determining and comparing the regimes to be derived. It is proposed to use as the parameters of a generalized equivalent generator of an active two-pole with changeable resistor such load current and voltage which provide the current through this resistor equal to zero.
Abstract: Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.