Abstract: Artificial Immune Systems (AIS), inspired by the
human immune system, are algorithms and mechanisms which are
self-adaptive and self-learning classifiers capable of recognizing and
classifying by learning, long-term memory and association. Unlike
other human system inspired techniques like genetic algorithms and
neural networks, AIS includes a range of algorithms modeling on
different immune mechanism of the body. In this paper, a mechanism
of a human immune system based on apoptosis is adopted to build an
Intrusion Detection System (IDS) to protect computer networks.
Features are selected from network traffic using Fisher Score. Based
on the selected features, the record/connection is classified as either
an attack or normal traffic by the proposed methodology. Simulation
results demonstrates that the proposed AIS based on apoptosis
performs better than existing AIS for intrusion detection.
Abstract: Domestic goats (Capra hircus) are extremely diverse
species and principal animal genetic resource of the developing
world. These facilitate a persistent supply of meat, milk, fibre, and
skin and are considered as important revenue generators in small
pastoral environments. This study aimed to fingerprint β-LG gene at
PCR-RFLP level in native Saudi goat breeds (Ardi, Habsi and Harri)
in an attempt to have a preliminary image of β-LG genotypic patterns
in Saudi breeds as compared to other foreign breeds such as Indian
and Egyptian. Also, the Phylogenetic analysis was done to investigate
evolutionary trends and similarities among the caprine β-LG gene
with that of the other domestic specie, viz. cow, buffalo and sheep.
Blood samples were collected from 300 animals (100 for each breed)
and genomic DNA was extracted. A fragment of the β-LG gene
(427bp) was amplified using specific primers. Subsequent digestion
with Sac II restriction endonuclease revealed two alleles (A and B)
and three different banding patterns or genotypes i.e. AA, AB and
BB. The statistical analysis showed a general trend that β-LG AA
genotype had higher milk yield than β-LG AB and β-LG BB
genotypes. Nucleotide sequencing of the selected β-LG fragments
was done and submitted to GenBank NCBI (Accession No.
KJ544248, KJ588275, KJ588276, KJ783455, KJ783456 and
KJ874959). Phylogenetic analysis on the basis of nucleotide
sequences of native Saudi goats indicated evolutional similarity with
the GenBank reference sequences of goat, Bubalus bubalis and Bos
taurus. However, the origin of sheep which is the most closely
related from the evolutionary point of view, was located some
distance away.
Abstract: The objective of the Economic Dispatch(ED) Problems
of electric power generation is to schedule the committed generating
units outputs so as to meet the required load demand at minimum
operating cost while satisfying all units and system equality and
inequality constraints. This paper presents a new method of ED
problems utilizing the Max-Min Ant System Optimization.
Historically, traditional optimizations techniques have been used,
such as linear and non-linear programming, but within the past
decade the focus has shifted on the utilization of Evolutionary
Algorithms, as an example Genetic Algorithms, Simulated Annealing
and recently Ant Colony Optimization (ACO). In this paper we
introduce the Max-Min Ant System based version of the Ant System.
This algorithm encourages local searching around the best solution
found in each iteration. To show its efficiency and effectiveness, the
proposed Max-Min Ant System is applied to sample ED problems
composed of 4 generators. Comparison to conventional genetic
algorithms is presented.
Abstract: Distributed Generation (DG) can help in reducing the
cost of electricity to the costumer, relieve network congestion and
provide environmentally friendly energy close to load centers. Its
capacity is also scalable and it provides voltage support at distribution
level. Hence, DG placement and penetration level is an important
problem for both the utility and DG owner. DG allocation and capacity
determination is a nonlinear optimization problem. The objective
function of this problem is the minimization of the total loss of the
distribution system. Also high levels of penetration of DG are a new
challenge for traditional electric power systems. This paper presents a
new methodology for the optimal placement of DG and penetration
level of DG in distribution system based on General Algebraic
Modeling System (GAMS) and Genetic Algorithm (GA).
Abstract: Since the marine environmental conditions are
extremely different from the other ones, marine actinomycetes might
produce novel bioactive compounds. Therefore, actinomycete strains
were screened from marine water and sediment samples collected
from the coastal areas of Northern Vietnam. Ninety-nine
actinomycete strains were obtained on starch-casein agar media by
dilution technique, only seven strains, named HP112, HP12, HP411,
HPN11, HP 11, HPT13 and HPX12, showed significant antibacterial
activity against both gram-positive and gram-negative bacteria
(Bacillus subtilis ATCC 6633, Staphylococcus epidemidis ATCC
12228, Escherichia coli ATCC 11105). Further studies were carried
out with the most active HP411 strain against Candida albicans
ATCC 10231. This strain could grow rapidly on starch casein agar
and other media with high salt containing 7-10% NaCl at 28-30oC.
Spore-chain of HP411 showed an elongated and circular shape with
10 to 30 spores/chain. Identification of the strain was carried out by
employing the taxonomical studies including the 16S rRNA
sequence. Based on phylogenetic and phenotypic evidence it is
proposed that HP411 to be belongs to species Streptomyces
variabilis. The potent of the crude extract of fermentation broth of
HP411 that are effective against wide range of pathogens: both grampositive,
gram-negative and fungi. Further studies revealed that the
crude extract HP411 could obtain the anticancer activity for cancer
cell lines: Hep-G2 (liver cancer cell line); RD (cardiac and skeletal
muscle letters cell line); FL (membrane of the uterus cancer cell line).
However, the actinomycetes from marine ecosystem will be useful
for the discovery of new drugs in the future.
Abstract: Time and cost are the main goals of the construction
project management. The first schedule developed may not be a
suitable schedule for beginning or completing the project to achieve
the target completion time at a minimum total cost. In general, there
are trade-offs between time and cost (TCT) to complete the activities
of a project. This research presents genetic algorithms (GAs) multiobjective
model for project scheduling considering different
scenarios such as least cost, least time, and target time.
Abstract: Drying behavior of blanched sweet potato in a cabinet
dryer using different five air temperatures (40-80°C) and ten sweet
potato varieties sliced to 5mm thickness were investigated. The
drying data were fitted to eight models. The Modified Henderson and
Pabis model gave the best fit to the experimental moisture ratio data
obtained during the drying of all the varieties while Newton (Lewis)
and Wang and Singh models gave the least fit. The values of Deff
obtained for Bophelo variety (1.27 x 10-9 to 1.77 x 10-9 m2/s) was
the least while that of S191 (1.93 x 10-9 to 2.47 x 10-9 m2/s) was the
highest which indicates that moisture diffusivity in sweet potato is
affected by the genetic factor. Activation energy values ranged from
0.27-6.54 kJ/mol. The lower activation energy indicates that drying
of sweet potato slices requires less energy and is hence a cost and
energy saving method. The drying behavior of blanched sweet potato
was investigated in a cabinet dryer. Drying time decreased
considerably with increase in hot air temperature. Out of the eight
models fitted, the Modified Henderson and Pabis model gave the best
fit to the experimental moisture ratio data on all the varieties while
Newton, Wang and Singh models gave the least. The lower activation
energy (0.27 - 6.54 kJ/mol) obtained indicates that drying of sweet
potato slices requires less energy and is hence a cost and energy
saving method.
Abstract: The cooling channels of injection mould play a crucial
role in determining the productivity of moulding process and the
product quality. It’s not a simple task to design high quality cooling
channels. In this paper, an intelligent cooling channels design system
including automatic layout of cooling channels, interference checking
and assembly of accessories is studied. Automatic layout of cooling
channels using genetic algorithm is analyzed. Through integrating
experience criteria of designing cooling channels, considering the
factors such as the mould temperature and interference checking, the
automatic layout of cooling channels is implemented. The method of
checking interference based on distance constraint algorithm and the
function of automatic and continuous assembly of accessories are
developed and integrated into the system. Case studies demonstrate the
feasibility and practicality of the intelligent design system.
Abstract: Fuzzy systems have been successfully used for
exchange rate forecasting. However, fuzzy system is very confusing
and complex to be designed by an expert, as there is a large set of
parameters (fuzzy knowledge base) that must be selected, it is not a
simple task to select the appropriate fuzzy knowledge base for an
exchange rate forecasting. The researchers often look the effect of
fuzzy knowledge base on the performances of fuzzy system
forecasting. This paper proposes a genetic fuzzy predictor to forecast
the future value of daily US Dollar/Euro exchange rate time’s series.
A range of methodologies based on a set of fuzzy predictor’s which
allow the forecasting of the same time series, but with a different
fuzzy partition. Each fuzzy predictor is built from two stages, where
each stage is performed by a real genetic algorithm.
Abstract: This paper presents a new method to design nonlinear
feedback linearization controller for PEMFCs (Polymer Electrolyte
Membrane Fuel Cells). A nonlinear controller is designed based on
nonlinear model to prolong the stack life of PEMFCs. Since it is
known that large deviations between hydrogen and oxygen partial
pressures can cause severe membrane damage in the fuel cell,
feedback linearization is applied to the PEMFC system so that the
deviation can be kept as small as possible during disturbances or load
variations. To obtain an accurate feedback linearization controller,
tuning the linear parameters are always important. So in proposed
study NSGA (Non-Dominated Sorting Genetic Algorithm)-II method
was used to tune the designed controller in aim to decrease the
controller tracking error. The simulation result showed that the
proposed method tuned the controller efficiently.
Abstract: Economic Dispatch (ED) is one of the most
challenging problems of power system since it is difficult to determine
the optimum generation scheduling to meet the particular load demand
with the minimum fuel costs while all constraints are satisfied. The
objective of the Economic Dispatch Problems (EDPs) of electric
power generation is to schedule the committed generating units
outputs so as to meet the required load demand at minimum operating
cost while satisfying all units and system equality and inequality
constraints. In this paper, an efficient and practical steady-state genetic
algorithm (SSGAs) has been proposed for solving the economic
dispatch problem. The objective is to minimize the total generation
fuel cost and keep the power flows within the security limits. To
achieve that, the present work is developed to determine the optimal
location and size of capacitors in transmission power system where,
the Participation Factor Algorithm and the Steady State Genetic
Algorithm are proposed to select the best locations for the capacitors
and determine the optimal size for them.
Abstract: This paper presents a new meta-heuristic bio-inspired
optimization algorithm which is called Cuttlefish Algorithm (CFA).
The algorithm mimics the mechanism of color changing behavior of
the cuttlefish to solve numerical global optimization problems. The
colors and patterns of the cuttlefish are produced by reflected light
from three different layers of cells. The proposed algorithm considers
mainly two processes: reflection and visibility. Reflection process
simulates light reflection mechanism used by these layers, while
visibility process simulates visibility of matching patterns of the
cuttlefish. To show the effectiveness of the algorithm, it is tested with
some other popular bio-inspired optimization algorithms such as
Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and
Bees Algorithm (BA) that have been previously proposed in the
literature. Simulations and obtained results indicate that the proposed
CFA is superior when compared with these algorithms.
Abstract: Osteoporosis is a common multifactorial disease with
a strong genetic component characterized by reduced bone mass and
increased risk of fractures. Genetic factors play an important role in
the pathogenesis of osteoporosis. The aim of our study was to
identify the genotype and allele distribution of T245G polymorphism
in OPG gene in Slovak postmenopausal women. A total of 200
unrelated Slovak postmenopausal women with diagnosed
osteoporosis and 200 normal controls were genotyped for T245G
(rs3134069) polymorphism of OPG gene. Genotyping was performed
using the Custom Taqman®SNP Genotyping assays. Genotypes and
alleles frequencies showed no significant differences (p=0.5551;
p=0.6022). The results of the present study confirm the importance of
T245G polymorphism in OPG gene in the pathogenesis of
osteoporosis.
Abstract: Artificial Neural Networks (ANN) trained using backpropagation
(BP) algorithm are commonly used for modeling
material behavior associated with non-linear, complex or unknown
interactions among the material constituents. Despite multidisciplinary
applications of back-propagation neural networks
(BPNN), the BP algorithm possesses the inherent drawback of
getting trapped in local minima and slowly converging to a global
optimum. The paper present a hybrid artificial neural networks and
genetic algorithm approach for modeling slump of ready mix
concrete based on its design mix constituents. Genetic algorithms
(GA) global search is employed for evolving the initial weights and
biases for training of neural networks, which are further fine tuned
using the BP algorithm. The study showed that, hybrid ANN-GA
model provided consistent predictions in comparison to commonly
used BPNN model. In comparison to BPNN model, the hybrid ANNGA
model was able to reach the desired performance goal quickly.
Apart from the modeling slump of ready mix concrete, the synaptic
weights of neural networks were harnessed for analyzing the relative
importance of concrete design mix constituents on the slump value.
The sand and water constituents of the concrete design mix were
found to exhibit maximum importance on the concrete slump value.
Abstract: This study presents the numerical simulation of three-dimensional incompressible steady and laminar fluid flow and conjugate heat transfer of a trapezoidal microchannel heat sink using water as a cooling fluid in a silicon substrate. Navier-Stokes equations with conjugate energy equation are discretized by finite-volume method. We perform numerical computations for a range of 50 ≦ Re ≦ 600, 0.05W ≦ P ≦ 0.8W, 20W/cm2 ≦q"≦ 40W/cm2. The present study demonstrates the numerical optimization of a trapezoidal microchannel heat sink design using the response surface methodology (RSM) and the genetic algorithm method (GA). The results show that the average Nusselt number increases with an increase in the Reynolds number or pumping power, and the thermal resistance decreases as the pumping power increases. The thermal resistance of a trapezoidal microchannel is minimized for a constant heat flux and constant pumping power.
Abstract: This paper is concerned with minimization of mean
tardiness and flow time in a real single machine production
scheduling problem. Two variants of genetic algorithm as metaheuristic
are combined with hyper-heuristic approach are proposed to
solve this problem. These methods are used to solve instances
generated with real world data from a company. Encouraging results
are reported.
Abstract: This study deals with an advanced numerical
techniques to detect tensile forces in cable-stayed structures. The
proposed method allows us not only to avoid the trap of minimum at
initial searching stage but also to find their final solutions in better
numerical efficiency. The validity of the technique is numerically
verified using a set of dynamic data obtained from a simulation of the
cable model modeled using the finite element method. The results
indicate that the proposed method is computationally efficient in
characterizing the tensile force variation for cable-stayed structures.
Abstract: Organic cation transporter (OCT) 1could influence an individual’s response to various treatments and increase their susceptibility to diseases.Genotypic and allelic frequencies of nineteen non-synonymous and one intronic Single Nucleotide Polymorphism (SNP) from the OCT1 gene were determined in 101 unrelated healthy Zulu participants, using a SNaPshot® multiplex assay. Minor allele frequencies (MAF)were compared to representative populations of Africa, Asia and Europe, from Ensembl. MAFs for S14F, V519F, rs622342 and P341L were 2.0%, 6.0%, 6.0% and 1.0%, respectively. Sixteen of nineteen investigated non-synonymous SNPs were monomorphic. No study participant harbored variant alleles for S189L, G220V, P283L, G401S, M420V, M440I, G465R, I542V, R61C, R287G, C88S, A306T, A413V, I421F, C436F and V501E. Haplotype, CGTCGCCGCGCAAGAGGTGA, was most frequently observed (81.23%).Further investigations are encouraged to evaluate potential roles these SNPs could play in the therapeutic efficacy of clinically important drugs and in the development of various diseases in the Zulu population.
Abstract: This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.
Abstract: In this paper a nonlinear feedback control called augmented automatic choosing control (AACC) for a class of
nonlinear systems with constrained input is presented. When designed
the control, a constant term which arises from linearization of a
given nonlinear system is treated as a coefficient of a stable zero
dynamics. Parameters of the control are suboptimally selected by
maximizing the stable region in the sense of Lyapunov with the aid
of a genetic algorithm. This approach is applied to a field excitation
control problem of power system to demonstrate the splendidness
of the AACC. Simulation results show that the new controller can
improve performance remarkably well.