Abstract: An induced graphoidal cover of a graph G is a collection ψ of (not necessarily open) paths in G such that every path in ψ has at least two vertices, every vertex of G is an internal vertex of at most one path in ψ, every edge of G is in exactly one path in ψ and every member of ψ is an induced cycle or an induced path. The minimum cardinality of an induced graphoidal cover of G is called the induced graphoidal covering number of G and is denoted by ηi(G) or ηi. Here we find induced graphoidal cover for some classes of graphs.
Abstract: Seasonal survey of freshwater snails in different water
courses in Egypt during two successive years included 13 snail
species. They represented by Biomphalaria alexandrina, Bulinus
truncatus, Physa acuta, Helisoma duryi, Lymnaea natalensis,
Planorbis pantries, Cleopatra bulimoides, Lanistes carinatus,
Bellamya unicolor, Melanoides tuberculata, Theodoxus niloticus,
Succinia cleopatra and Valvata nilotica. B. alexandrina was most
abundant during autumn and spring represented by 26and14
snails/site, respectively. B. truncatus was most abundant during
winter (7.7and3.6snails/site) of the two years, respectively. L.
natalensis was represented by 7snails/site in summer. The tolerance
of different snail species to the chemical elements was determined
seasonally and correlated to their abundance. In spring, autumn and
winter, B. alexandrina was significantly found to live under the
highest level of Pb, Cd,Cu, Na, K and Ca concentrations than the
other species (p
Abstract: Landfill gas, particularly methane is one of the
greenhouse gases which contributes to global warming. This paper presents the findings of a study on methane gas production from
simulated landfill reactor under saturated conditions. A reactor was constructed to represent a landfill cell of 2.5 m thickness on sandy
soil. The reactor was 0.2 m in diameter and 4 m in height. One meter of sand and pebble layer was packed at the bottom of the reactor
followed by 2.5 m of solid waste layer and 0.4 m of sand layer as the cover soil. Degradation of waste in the solid waste layer was at
acidification stage as indicated by the leachate quality with COD as
high as 55,511 mg/L and pH as low as 5.1. However, methanogenic
environment was established at the bottom sand layer after one year of operation indicated by pH of 7.2 and methane gas generation.
Leachate degradation took place as the leachate moved through the
sand layer at an infiltration of rate 0.7 cm/day. This resulted in landfill gas production of 77 mL/day/kg containing 55 to 65% methane. The application of sand layer contributed to the gas
production from landfill by an in-situ degradation of leachate in the
sand at the bottom of the landfill.
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: 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: The Master-s of Public Health (MPH) degree is
growing in popularity among a number of higher education
institutions throughout the world as a distance education graduate
program. This paper offers an overview of program design and
development strategies that promote successful distance delivery of
MPH programs. Design and development challenges are discussed in
terms of type of distance delivery, accreditation, student demand,
faculty development, user needs, course content, and marketing
strategies. The ongoing development of a distance education MPH
program at Utah State University will be used to highlight and
consider various aspects of this important but challenging process.
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 the present research, two nutraceuticals made from
red grape and walnut that showed previously to improve kidney
dysfunction were incorporated separately into functional foods' bread
made from barley and rice bran. The functional foods were evaluated
in rats in which chronic renal failure was induced through feeding
diet rich in adenine and phosphate (APD). The evaluation based on
assessing kidney function, oxidative stress, inflammatory biomarkers
and body weight gain. Results showed induction of chronic kidney
failure reflected in significant increase in plasma urea, creatinine,
malondialdehyde, tumor necrosis factor- α and low density
lipoprotein cholesterol along with significant reduction of plasma
albumin, and total antioxidant and creatinine clearance and body
weight gain on feeding APD compared to control healthy group.
Feeding the functional foods produced amelioration in the different
biochemical parameters and body weight gain indicating
improvement in kidney function.
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: A dual-reciprocity boundary element method is presented
for the numerical solution of a class of axisymmetric elastodynamic
problems. The domain integrals that arise in the integrodifferential
formulation are converted to line integrals by using the
dual-reciprocity method together suitably constructed interpolating
functions. The second order time derivatives of the displacement
in the governing partial differential equations are suppressed by
using Laplace transformation. In the Laplace transform domain, the
problem under consideration is eventually reduced to solving a system
of linear algebraic equations. Once the linear algebraic equations are
solved, the displacement and stress fields in the physical domain can
be recovered by using a numerical technique for inverting Laplace
transforms.
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: 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: This study presents an active vibration control
technique to reduce the earthquake responses of a retained structural
system. The proposed technique is a synthesis of the adaptive input
estimation method (AIEM) and linear quadratic Gaussian (LQG)
controller. The AIEM can estimate an unknown system input online.
The LQG controller offers optimal control forces to suppress
wall-structural system vibration. The numerical results show robust
performance in the active vibration control technique.
Abstract: Documents retrieval in Information Retrieval
Systems (IRS) is generally about understanding of
information in the documents concern. The more the system
able to understand the contents of documents the more
effective will be the retrieval outcomes. But understanding of the
contents is a very complex task. Conventional IRS apply algorithms
that can only approximate the meaning of document contents through
keywords approach using vector space model. Keywords may be
unstemmed or stemmed. When keywords are stemmed and conflated
in retrieving process, we are a step forwards in applying semantic
technology in IRS. Word stemming is a process in morphological
analysis under natural language processing, before syntactic and
semantic analysis. We have developed algorithms for Malay and
Arabic and incorporated stemming in our experimental systems in
order to measure retrieval effectiveness. The results have shown that
the retrieval effectiveness has increased when stemming is used in
the systems.
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: 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.