Abstract: In April 2009, a new variant of Influenza A virus
subtype H1N1 emerged in Mexico and spread all over the world. The
influenza has three subtypes in human (H1N1, H1N2 and H3N2)
Types B and C influenza tend to be associated with local or regional
epidemics. Preliminary genetic characterization of the influenza
viruses has identified them as swine influenza A (H1N1) viruses.
Nucleotide sequence analysis of the Haemagglutinin (HA) and
Neuraminidase (NA) are similar to each other and the majority of
their genes of swine influenza viruses, two genes coding for the
neuraminidase (NA) and matrix (M) proteins are similar to
corresponding genes of swine influenza. Sequence similarity between
the 2009 A (H1N1) virus and its nearest relatives indicates that its
gene segments have been circulating undetected for an extended
period. Nucleic acid sequence Maximum Likelihood (MCL) and
DNA Empirical base frequencies, Phylogenetic relationship amongst
the HA genes of H1N1 virus isolated in Genbank having high
nucleotide sequence homology.
In this paper we used 16 HA nucleotide sequences from NCBI for
computing sequence relationships similarity of swine influenza A
virus using the following method MCL the result is 28%, 36.64% for
Optimal tree with the sum of branch length, 35.62% for Interior
branch phylogeny Neighber – Join Tree, 1.85% for the overall
transition/transversion, and 8.28% for Overall mean distance.
Abstract: This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
Abstract: The optimal bisection width of r-dimensional N×
· · ·× N grid is known to be Nr-1 when N is even, but when
N is odd, only approximate values are available. This paper
shows that the exact bisection width of grid is Nr
-1
N-1 when N is odd.
Abstract: The purpose of this research is to establish the experimental conditions for removal of Cibacron Brilliant Yellow 3G-P dye (CBY) from aqueous solutions by sorption onto coffee husks as a low-cost sorbent. The effects of various experimental parameters (e.g. initial CBY dye concentration, sorbent mass, pH, temperature) were examined and the optimal experimental conditions were determined. The results indicated that the removal of the dye was pH dependent and at initial pH of 2, the dye was removed effectively. The CBY dye sorption data were fitted to Langmuir, Freundlich, Temkin and Dubinin-Radushkevich equilibrium models. The maximum sorption capacity of CBY dye ions onto coffee husks increased from 24.04 to 35.04 mg g-1 when the temperature was increased from 293 to 313 K. The calculated sorption thermodynamic parameters including ΔG°, ΔH°, and ΔS° indicated that the CBY dye sorption onto coffee husks is a spontaneous, endothermic and mainly physical in nature.
Abstract: This paper presents an approach for daily optimal operation of distribution networks considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. A genetic algorithm is used to solve the optimal operation problem. The approach is tested on an IEEE34 buses distribution feeder.
Abstract: This paper solves the environmental/ economic dispatch
power system problem using the Non-dominated Sorting Genetic
Algorithm-II (NSGA-II) and its hybrid with a Convergence Accelerator
Operator (CAO), called the NSGA-II/CAO. These multiobjective
evolutionary algorithms were applied to the standard IEEE 30-bus
six-generator test system. Several optimization runs were carried out
on different cases of problem complexity. Different quality measure
which compare the performance of the two solution techniques were
considered. The results demonstrated that the inclusion of the CAO
in the original NSGA-II improves its convergence while preserving
the diversity properties of the solution set.
Abstract: The objective of current issue was to develop a model
of testicular herpes simplex virus (HSV) type I infection for
assessment of viral effect on fertility. 56 male mice were inoculated
intraperitoneally with different concentrations of HSV on 8 day post
partum. It was revealed that the optimal dose was 100 plaque
forming units per mice as it provided testicular infection in 100% of
survivors. HSV proteins were detected both in somatic and germ
cells (spermatogonia, spermatocytes, spermatides). Although DNA
load in testis was descending from 3 to 28 days post infection only
12.5% of infected males had offspring after mating with uninfected
females comparing to 87.5% in control (p=0.012). These results are
the first direct evidence for HSV impact in male sterility. Prepuberal
mice appeared to be a suitable model for investigation of
pathogenesis of virus-associated fertility disorders.
Abstract: For decades financial economists have been attempted to determine the optimal investment policy by recognizing the option value embedded in irreversible investment whose project value evolves as a geometric Brownian motion (GBM). This paper aims to examine the effects of the optimal investment trigger and of the misspecification of stochastic processes on investment in real options applications. Specifically, the former explores the consequence of adopting optimal investment rules on the distributions of corporate value under the correct assumption of stochastic process while the latter analyzes the influence on the distributions of corporate value as a result of the misspecification of stochastic processes, i.e., mistaking an alternative process as a GBM. It is found that adopting the correct optimal investment policy may increase corporate value by shifting the value distribution rightward, and the misspecification effect may decrease corporate value by shifting the value distribution leftward. The adoption of the optimal investment trigger has a major impact on investment to such an extent that the downside risk of investment is truncated at the project value of zero, thereby moving the value distributions rightward. The analytical framework is also extended to situations where collection lags are in place, and the result indicates that collection lags reduce the effects of investment trigger and misspecification on investment in an opposite way.
Abstract: In this paper, the fuzzy linear programming formulation
of fuzzy maximal flow problems are proposed and on the basis of the
proposed formulation a method is proposed to find the fuzzy optimal
solution of fuzzy maximal flow problems. In the proposed method all
the parameters are represented by triangular fuzzy numbers. By using
the proposed method the fuzzy optimal solution of fuzzy maximal
flow problems can be easily obtained. To illustrate the proposed
method a numerical example is solved and the obtained results are
discussed.
Abstract: The paper presents the applications of artificial
intelligence technique called adaptive tabu search to design the
controller of a buck converter. The averaging model derived from the
DQ and generalized state-space averaging methods is applied to
simulate the system during a searching process. The simulations
using such averaging model require the faster computational time
compared with that of the full topology model from the software
packages. The reported model is suitable for the work in the paper in
which the repeating calculation is needed for searching the best
solution. The results will show that the proposed design technique
can provide the better output waveforms compared with those
designed from the classical method.
Abstract: In this paper, an attempt has been made to obtain nonsensitive
solutions in the multi-objective optimization of a
photovoltaic/thermal (PV/T) air collector. The selected objective
functions are overall energy efficiency and exergy efficiency.
Improved thermal, electrical and exergy models are used to calculate
the thermal and electrical parameters, overall energy efficiency,
exergy components and exergy efficiency of a typical PV/T air
collector. A computer simulation program is also developed. The
results of numerical simulation are in good agreement with the
experimental measurements noted in the previous literature. Finally,
multi-objective optimization has been carried out under given
climatic, operating and design parameters. The optimized ranges of
inlet air velocity, duct depth and the objective functions in optimal
Pareto front have been obtained. Furthermore, non-sensitive solutions
from energy or exergy point of view in the results of multi-objective
optimization have been shown.
Abstract: Optimal selection of electrical insulations in electrical
machinery insures reliability during operation. From the insulation
studies of view for electrical machines, stator is the most important
part. This fact reveals the requirement for inspection of the electrical
machine insulation along with the electro-thermal stresses. In the
first step of the study, a part of the whole structure of machine in
which covers the general characteristics of the machine is chosen,
then based on the electromagnetic analysis (finite element method),
the machine operation is simulated. In the simulation results, the
temperature distribution of the total structure is presented
simultaneously by using electro-thermal analysis. The results of
electro-thermal analysis can be used for designing an optimal cooling
system. In order to design, review and comparing the cooling
systems, four wiring structures in the slots of Stator are presented.
The structures are compared to each other in terms of electrical,
thermal distribution and remaining life of insulation by using Finite
Element analysis. According to the steps of the study, an optimization
algorithm has been presented for selection of appropriate structure.
Abstract: This study proposes a hybrid minimal repair policy
which combines periodic maintenance policy with age-based maintenance policy for a serial production system. Parameters of such policy are defined as and which indicate as hybrid minimal
repair time and planned preventive maintenance time
respectively . Under this hybrid policy, the system is
repaired minimally if it fails during , . A perfect repair is
conducted on the first failure after at any machines. At the same time, we take opportunity to advance the preventive maintenance of
other machines simultaneously. If the system is still operating
properly up to , then the preventive maintenance is carried out as its
predetermined schedule. For a given , we obtain the optimal value which minimizes the expected cost per time unit. Numerical
example is presented to illustrate the properties of the optimal solution.
Abstract: Nowadays companies in all sectors are looking for the
sources of competitive advantages. Holistic marketing approach
searches for their emergence based on the integration of all
components and elements across the organization. Modern marketing
sees the sources of competitive advantage in implementing the latest
managerial practices, motivation, intelligent project management,
knowledge management, collaborative marketing, CSR and, in the
recent years, also in the business process optimization. With the use
of modern tools including business process management and business
process modelling the company can markedly increase its internal
efficiency which can lead not only to lowering the costs but to
creating the environment for optimal customer care, positive
corporate culture and for origination of innovations as well. In the
article the authors analyze the recent trend in this area and introduce
suggestions to companies to identify and optimize the key processes
that have a significant impact of the company´s competitiveness.
Abstract: Distributed Power generation has gained a lot of
attention in recent times due to constraints associated with
conventional power generation and new advancements in DG
technologies .The need to operate the power system economically
and with optimum levels of reliability has further led to an increase
in interest in Distributed Generation. However it is important to place
Distributed Generator on an optimum location so that the purpose of
loss minimization and voltage regulation is dully served on the
feeder. This paper investigates the impact of DG units installation on
electric losses, reliability and voltage profile of distribution networks.
In this paper, our aim would be to find optimal distributed
generation allocation for loss reduction subjected to constraint of
voltage regulation in distribution network. The system is further
analyzed for increased levels of Reliability. Distributed Generator
offers the additional advantage of increase in reliability levels as
suggested by the improvements in various reliability indices such as
SAIDI, CAIDI and AENS. Comparative studies are performed and
related results are addressed. An analytical technique is used in order
to find the optimal location of Distributed Generator. The suggested
technique is programmed under MATLAB software. The results
clearly indicate that DG can reduce the electrical line loss while
simultaneously improving the reliability of the system.
Abstract: The forming process parameters of Selective Laser
Sintering(SLS) directly affect the forming efficiency and forming
quality. Therefore, to determine reasonable process parameters is
particularly important. In this paper, the weight of each target of the
forming quality and efficiency is firstly calculated with the Analytic
Hierarchy Process. And then the size of each target is measured by
orthogonal experiment. Finally, the sum of the product of each target
with the weight is compared to the process parameters in each group
and obtained the optimal molding process parameters.
Abstract: This paper presents the optimal design and development
of an axial flux motor for blood pump application. With the design
objective of maximizing the motor efficiency and torque, different
topologies of AFPM machine has been examined. Selection of
optimal magnet fraction, Halbach arrangement of rotor magnets and
the use of Soft Magnetic Composite (SMC) material for the stator
core results in a novel motor with improved efficiency and torque
profile. The results of the 3D Finite element analysis for the novel
motor have been shown.
Abstract: In this paper we illuminate a frequency domain based
classification method for video scenes. Videos from certain topical
areas often contain activities with repeating movements. Sports
videos, home improvement videos, or videos showing mechanical
motion are some example areas. Assessing main and side frequencies
of each repeating movement gives rise to the motion type. We
obtain the frequency domain by transforming spatio-temporal motion
trajectories. Further on we explain how to compute frequency features
for video clips and how to use them for classifying. The focus of
the experimental phase is on transforms utilized for our system.
By comparing various transforms, experiments show the optimal
transform for a motion frequency based approach.
Abstract: The paper describes the evaluation of quality of
control for cases of controlled non-minimal phase plants. Control
circuits containing non-minimal phase plants have different
properties, they manifest reversed reaction at the beginning of unit
step response. For these types of plants are developed special
criterion of quality of control, which considers the difference and can
be helpful for synthesis of optimal controller tuning. All results are
clearly presented using Matlab/Simulink models.
Abstract: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).