Abstract: Genetic Folding (GF) a new class of EA named as is
introduced for the first time. It is based on chromosomes composed
of floating genes structurally organized in a parent form and
separated by dots. Although, the genotype/phenotype system of GF
generates a kernel expression, which is the objective function of
superior classifier. In this work the question of the satisfying
mapping-s rules in evolving populations is addressed by analyzing
populations undergoing either Mercer-s or none Mercer-s rule. The
results presented here show that populations undergoing Mercer-s
rules improve practically models selection of Support Vector
Machine (SVM). The experiment is trained multi-classification
problem and tested on nonlinear Ionosphere dataset. The target of this
paper is to answer the question of evolving Mercer-s rule in SVM
addressed using either genetic folding satisfied kernel-s rules or not
applied to complicated domains and problems.
Abstract: The objective of this research is to study the people’s level of participation in activities of the community, their satisfaction towards the community, the attachment they have to the community, factors that influence the attachment, as well as the characteristics of the relationships of military families’ of the Royal Guards community of Dusit District. The method used was non-probability sampling by quota sampling according to people’s age. The determined age group was 18 years or older.
One set of a sample group was done per family. The questionnaires were conducted by 287 people. Snowball sampling was also used by interviewing people of the community, starting from the Royal Guards Community’s leader, then by 20 of the community’s well-respected persons. The data was analyzed by using descriptive statistics, such as arithmetic mean and standard deviation, as well as by inferential statistics, such as Independent - Samples T test (T-test), One-Way ANOVA (F-test), Chi-Square. Descriptive analysis according to the structure of the interview content was also used. The results of the research is that the participation of the population in the Royal Guards Community in various activities is at a medium level, with the average participation level during Mother’s and Father’s Days. The people’s general level of satisfaction towards the premises of the Royal Guards Community is at the highest level.
The people were most satisfied with the transportation within the community and in contacting with people from outside the premises. The access to the community is convenient and there are various entrances. The attachment of the people to the Royal Guards Community in general and by each category is at a high level. The feeling that the community is their home rated the highest average. Factors that influence the attachment of the people of the Royal Guards Community are age, status, profession, income, length of stay in the community, membership of social groups, having neighbors they feel close and familiar with, and as well as the benefits they receive from the community. In addition, it was found that people that participate in activities have a high level of positive relationship towards the attachment of the people to the Royal Guards Community. The satisfaction of the community has a very high level of positive relationship with the attachment of the people to the Royal Guards Community.
The characteristics of the attachment of military families’ is that they live in big houses that everyone has to protect and care for, starting from the leader of the family as well as all members. Therefore, they all love the community they live in. The characteristics that show the participation of activities within the community and the high level of satisfaction towards the premises of the community will enable the people to be more attached to the community. The people feel that everyone is close neighbors within the community, as if they are one big family.
Abstract: Square pipes (pipes with square cross sections) are
being used for various industrial objectives, such as machine
structure components and housing/building elements. The utilization
of them is extending rapidly and widely. Hence, the out-put of those
pipes is increasing and new application fields are continually
developing.
Due to various demands in recent time, the products have to
satisfy difficult specifications with high accuracy in dimensions. The
reshaping process design of pipes with square cross sections;
however, is performed by trial and error and based on expert-s
experience.
In this paper, a computer-aided simulation is developed based on
the 2-D elastic-plastic method with consideration of the shear
deformation to analyze the reshaping process. Effect of various
parameters such as diameter of the circular pipe and mechanical
properties of metal on product dimension and quality can be
evaluated by using this simulation. Moreover, design of reshaping
process include determination of shrinkage of cross section,
necessary number of stands, radius of rolls and height of pipe at each
stand, are investigated. Further, it is shown that there are good
agreements between the results of the design method and the
experimental results.
Abstract: The objective of this research is to develop the
performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care
system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency
Medical Institute of Thailand (EMIT) was considered using strategic
analysis to developed Strategy Map (SM) and identified the Success
Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of
PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain
that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited
only with the first dimension of National Strategic Plan
(infrastructure and information technology development). Besides,
the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators
were developed from the analysis results of SM and SFs.
Abstract: The objective of this paper is to study the electrical
resistivity complexity between field and laboratory measurement, in
order to improve the effectiveness of data interpretation for
geophysical ground resistivity survey. The geological outcrop in
Penang, Malaysia with an obvious layering contact was chosen as the
study site. Two dimensional geoelectrical resistivity imaging were
used in this study to maps the resistivity distribution of subsurface,
whereas few subsurface sample were obtained for laboratory
advance. In this study, resistivity of samples in original conditions is
measured in laboratory by using time domain low-voltage technique,
particularly for granite core sample and soil resistivity measuring set
for soil sample. The experimentation results from both schemes are
studied, analyzed, calibrated and verified, including basis and
correlation, degree of tolerance and characteristics of substance.
Consequently, the significant different between both schemes is
explained comprehensively within this paper.
Abstract: The objective of this paper is to estimate realistic
principal extrusion process parameters by means of artificial neural
network. Conventionally, finite element analysis is used to derive
process parameters. However, the finite element analysis of the
extrusion model does not consider the manufacturing process
constraints in its modeling. Therefore, the process parameters
obtained through such an analysis remains highly theoretical.
Alternatively, process development in industrial extrusion is to a
great extent based on trial and error and often involves full-size
experiments, which are both expensive and time-consuming. The
artificial neural network-based estimation of the extrusion process
parameters prior to plant execution helps to make the actual extrusion
operation more efficient because more realistic parameters may be
obtained. And so, it bridges the gap between simulation and real
manufacturing execution system. In this work, a suitable neural
network is designed which is trained using an appropriate learning
algorithm. The network so trained is used to predict the
manufacturing process parameters.
Abstract: Environmental pollution problems have been globally
main concern in all fields including economy, society and culture into
the 21st century. Beginning with the Kyoto Protocol, the reduction on
the emissions of greenhouse gas such as CO2 and SOX has been a
principal challenge of our day. As most buildings unlike durable goods
in other industries have a characteristic and long life cycle, they
consume energy in quantity and emit much CO2. Thus, for green
building construction, more research is needed to reduce the CO2
emissions at each stage in the life cycle. However, recent studies are
focused on the use and maintenance phase. Also, there is a lack of
research on the initial design stage, especially the structure design.
Therefore, in this study, we propose an optimal design plan
considering CO2 emissions and cost in composite buildings
simultaneously by applying to the structural design of actual building.
Abstract: This paper presents the simulation results of electric field and potential distributions along surface of silicone rubber polymer insulators under clean and various contamination conditions with/without water droplets. Straight sheds insulator having leakage distance 290 mm was used in this study. Two type of contaminants, playwood dust and cement dust, have been studied the effect of contamination on the insulator surface. The objective of this work is to comparison the effect of contamination on potential and electric field distributions along the insulator surface when water droplets exist on the insulator surface. Finite element method (FEM) is adopted for this work. The simulation results show that contaminations have no effect on potential distribution along the insulator surface while electric field distributions are obviously depended on contamination conditions.
Abstract: The objective of this study is to design an adaptive
neuro-fuzzy inference system (ANFIS) for estimation of surface
roughness in grinding process. The Used data have been generated
from experimental observations when the wheel has been dressed
using a rotary diamond disc dresser. The input parameters of model
are dressing speed ratio, dressing depth and dresser cross-feed rate
and output parameter is surface roughness. In the experimental
procedure the grinding conditions are constant and only the dressing
conditions are varied. The comparison of the predicted values and the
experimental data indicates that the ANFIS model has a better
performance with respect to back-propagation neural network
(BPNN) model which has been presented by the authors in previous
work for estimation of the surface roughness.
Abstract: The main objective of this study is to test the
relationship between numbers of variables representing the firm
characteristics (market-related variables) and the extent of voluntary
disclosure levels (forward-looking disclosure) in the annual reports of
Egyptian firms listed on the Egyptian Stock Exchange. The results
show that audit firm size is significantly positively correlated (in all
the three years) with the level of forward-looking disclosure.
However, industry type variable (which divided to: industries,
cement, construction, petrochemicals and services), is found being
insignificantly association with the level of forward-looking
information disclosed in the annual reports for all the three years.
Abstract: Facility location problem involves locating a facility
to optimize some performance measures. Location of a public facility
to serve the community, such as a fire station, significantly affects its
service quality. Main objective in locating a fire station is to
minimize the response time, which is the time duration between
receiving a call and reaching the place of incident. In metropolitan
areas, fire vehicles need to cross highways and other traffic obstacles
through some obstacle-overcoming points which delay the response
time. In this paper, fire station location problem is analyzed.
Simulation models are developed for the location problems which
involve obstacles. Particular case problems are analyzed and the
results are presented.
Abstract: In this paper, the action research driven design of a
context relevant, developmental peer review of teaching model, its
implementation strategy and its impact at an Australian university is
presented. PRO-Teaching realizes an innovative process that
triangulates contemporaneous teaching quality data from a range of
stakeholders including students, discipline academics, learning and
teaching expert academics, and teacher reflection to create reliable
evidence of teaching quality. Data collected over multiple classroom
observations allows objective reporting on development differentials
in constructive alignment, peer, and student evaluations. Further
innovation is realized in the application of this highly structured
developmental process to provide summative evidence of sufficient
validity to support claims for professional advancement and learning
and teaching awards. Design decision points and contextual triggers
are described within the operating domain. Academics and
developers seeking to introduce structured peer review of teaching
into their organization will find this paper a useful reference.
Abstract: Lake Nasser is one of the largest reservoirs in the
world. Over 120 million metric tons of sediments are deposited in its
dead storage zone every year. The main objective of the present work
was to determine the physical and chemical characteristics of Lake
Nasser sediments. The sample had a relatively low surface area of 2.9
m2/g which increased more than 3-fold upon chemical activation. The
main chemical elements of the raw sediments were C, O and Si with
some traces of Al, Fe and Ca. The organic functional groups for the
tested sample included O-H, C=C, C-H and C-O, with indications of
Si-O and other metal-C and/or metal-O bonds normally associated
with clayey materials. Potentiometric titration of the sample in
different ionic strength backgrounds revealed an alkaline material with
very strong positive surface charge at pH values just a little less than
the pH of zero charge which is ~9. Surface interactions of the
sediments with the background electrolyte were significant. An
advanced surface complexation model was able to capture these
effects, employing a single-site approach to represent protolysis
reactions in aqueous solution, and to determine the significant surface
species in the pH range of environmental interest.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: Face detection and recognition has many applications
in a variety of fields such as security system, videoconferencing and
identification. Face classification is currently implemented in
software. A hardware implementation allows real-time processing,
but has higher cost and time to-market.
The objective of this work is to implement a classifier based on
neural networks MLP (Multi-layer Perceptron) for face detection.
The MLP is used to classify face and non-face patterns. The systm is
described using C language on a P4 (2.4 Ghz) to extract weight
values. Then a Hardware implementation is achieved using VHDL
based Methodology. We target Xilinx FPGA as the implementation
support.
Abstract: The objective of this study was to develop and compare alternative prediction equations of lean meat proportion (LMP) of lamb carcasses. Forty (40) male lambs, 22 of Churra Galega Bragançana Portuguese local breed and 18 of Suffolk breed were used. Lambs were slaughtered, and carcasses weighed approximately 30 min later in order to obtain hot carcass weight (HCW). After cooling at 4º C for 24-h a set of seventeen carcass measurements was recorded. The left side of carcasses was dissected into muscle, subcutaneous fat, inter-muscular fat, bone, and remainder (major blood vessels, ligaments, tendons, and thick connective tissue sheets associated with muscles), and the LMP was evaluated as the dissected muscle percentage. Prediction equations of LMP were developed, and fitting quality was evaluated through the coefficient of determination of estimation (R2 e) and standard error of estimate (SEE). Models validation was performed by k-fold crossvalidation and the coefficient of determination of prediction (R2 p) and standard error of prediction (SEP) were computed. The BT2 measurement was the best single predictor and accounted for 37.8% of the LMP variation with a SEP of 2.30%. The prediction of LMP of lamb carcasses can be based simple models, using as predictors the HCW and one fat thickness measurement.
Abstract: This paper aims to develop a model that assists the
international retailer in selecting the country that maximizes the
degree of fit between the retailer-s goals and the country
characteristics in his initial internationalization move. A two-stage
multi criteria decision model is designed integrating the Analytic
Hierarchy Process (AHP) and Goal Programming. Ethical, cultural,
geographic and economic proximity are identified as the relevant
constructs of the internationalization decision. The constructs are
further structured into sub-factors within analytic hierarchy. The
model helps the retailer to integrate, rank and weigh a number of
hard and soft factors and prioritize the countries accordingly. The
model has been implemented on a Turkish luxury goods retailer who
was planning to internationalize. Actual entry of the specific retailer
in the selected country is a support for the model. Implementation on
a single retailer limits the generalizability of the results; however, the
emphasis of the paper is on construct identification and model
development. The paper enriches the existing literature by proposing
a hybrid multi objective decision model which introduces new soft
dimensions i.e. perceived distance, ethical proximity, humane
orientation to the decision process and facilitates effective decision
making.
Abstract: The main objective of seismic rehabilitation in the
foundations is decreasing the range of horizontal and vertical
vibrations and omitting high frequencies contents under the seismic
loading. In this regard, the advantages of micropiles network is
utilized. Reduction in vibration range of foundation can be achieved
by using high dynamic rigidness module such as deep foundations. In
addition, natural frequency of pile and soil system increases in regard
to rising of system rigidness. Accordingly, the main strategy is
decreasing of horizontal and vertical seismic vibrations of the
structure. In this case, considering the impact of foundation, pile and
improved soil foundation is a primary concern. Therefore, in this
paper, effective factors are studied on the seismic rehabilitation of
foundations applying network micropiles in sandy soils with
nonlinear reaction.
Abstract: This article proposes a novel Pareto-based multiobjective
meta-heuristic algorithm named non-dominated ranking
genetic algorithm (NRGA) to solve multi-facility location-allocation
problem. In NRGA, a fitness value representing rank is assigned to
each individual of the population. Moreover, two features ranked
based roulette wheel selection including select the fronts and choose
solutions from the fronts, are utilized. The proposed solving
methodology is validated using several examples taken from the
specialized literature. The performance of our approach shows that
NRGA algorithm is able to generate true and well distributed Pareto
optimal solutions.
Abstract: Residual dye contents in textile dyeing wastewater have complex aromatic structures that are resistant to degrade in biological wastewater treatment. The objectives of this study were to determine the effectiveness of nanoscale zerovalent iron (NZVI) to decolorize Reactive Black 5 (RB5) and Reactive Red 198 (RR198) in synthesized wastewater and to investigate the effects of the iron particle size, iron dosage and solution pHs on the destruction of RB5 and RR198. Synthesized NZVI was confirmed by transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The removal kinetic rates (kobs) of RB5 (0.0109 min-1) and RR198 (0.0111 min-1) by 0.5% NZVI were many times higher than those of microscale zerovalent iron (ZVI) (0.0007 min-1 and 0.0008 min-1, respectively). The iron dosage increment exponentially increased the removal efficiencies of both RB5 and RR198. Additionally, lowering pH from 9 to 5 increased the decolorization kinetic rates of both RB5 and RR198 by NZVI. The destruction of azo bond (N=N) in the chromophore of both reactive dyes led to decolorization of dye solutions.