Abstract: In this paper we consider a nonlinear feedback
control called augmented automatic choosing control (AACC)
using the automatic choosing functions of gradient optimization
type for nonlinear systems. Constant terms which arise from sectionwise
linearization of a given nonlinear system are treated as
coefficients of a stable zero dynamics. Parameters included in the
control are suboptimally selected by minimizing the Hamiltonian
with the aid of the 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.
Abstract: Inflammatory bowel disease (IBD) is a chronic
relapsing-remitting condition that afflicts millions of people
throughout the world and impairs their daily functions and quality of
life. Treatment of IBD depends largely on 5-aminosalicylic acid (5-
ASA) and corticosteroids. The present study aimed to clarify the
effects of 5-aminosalicylic acid, budesonide and currcumin on 90
male albino rats against trinitrobenzene sulfonic acid (TNB) induced
colitis. TNB was injected intrarectally to 50 rats. The other 40 rats
served as control groups. Both 5-ASA (in a dose of 120 mg/kg) and
budesonide (in a dose of 0.1 mg/kg) were administered daily for one
week whereas currcumin was injected intraperitonially (in a dose of
30 mg/kg daily) for 14 days after injection of either TNB in the
colitis rats (group B) or saline in control groups (group A). The study
included estimation of macroscopic score index, histological
examination of H&E stained sections of the colonic tissue,
biochemical estimation of myeloperoxidase (MPO), nitric oxide
(NO), and caspase-3 levels, in addition to studying the effect of tested
drugs on colonic motility. It was found that budesonide and curcumin
improved mucosal healing, reduced both NO production and caspase-
3 level. They had the best impact on the disturbed colonic motility in
TNBS-model of colitis.
Abstract: In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.
Abstract: In this paper an efficient implementation of Ripemd-
160 hash function is presented. Hash functions are a special family
of cryptographic algorithms, which is used in technological
applications with requirements for security, confidentiality and
validity. Applications like PKI, IPSec, DSA, MAC-s incorporate
hash functions and are used widely today. The Ripemd-160 is
emanated from the necessity for existence of very strong algorithms
in cryptanalysis. The proposed hardware implementation can be
synthesized easily for a variety of FPGA and ASIC technologies.
Simulation results, using commercial tools, verified the efficiency of
the implementation in terms of performance and throughput. Special
care has been taken so that the proposed implementation doesn-t
introduce extra design complexity; while in parallel functionality was
kept to the required levels.
Abstract: The Helmholtz equation often arises in the study of physical problems involving partial differential equation. Many researchers have proposed numerous methods to find the analytic or approximate solutions for the proposed problems. In this work, the exact analytical solutions of the Helmholtz equation in spherical polar coordinates are presented using the Nikiforov-Uvarov (NU) method. It is found that the solution of the angular eigenfunction can be expressed by the associated-Legendre polynomial and radial eigenfunctions are obtained in terms of the Laguerre polynomials. The special case for k=0, which corresponds to the Laplace equation is also presented.
Abstract: In this paper a new method is suggested for risk
management by the numerical patterns in data-mining. These patterns
are designed using probability rules in decision trees and are cared to
be valid, novel, useful and understandable. Considering a set of
functions, the system reaches to a good pattern or better objectives.
The patterns are analyzed through the produced matrices and some
results are pointed out. By using the suggested method the direction
of the functionality route in the systems can be controlled and best
planning for special objectives be done.
Abstract: Using a set of confidence intervals, we develop a
common approach, to construct a fuzzy set as an estimator for
unknown parameters in statistical models. We investigate a method
to derive the explicit and unique membership function of such fuzzy
estimators. The proposed method has been used to derive the fuzzy
estimators of the parameters of a Normal distribution and some
functions of parameters of two Normal distributions, as well as the
parameters of the Exponential and Poisson distributions.
Abstract: This paper describes a 3D modeling system in
Augmented Reality environment, named 3DARModeler. It can be
considered a simple version of 3D Studio Max with necessary
functions for a modeling system such as creating objects, applying
texture, adding animation, estimating real light sources and casting
shadows. The 3DARModeler introduces convenient, and effective
human-computer interaction to build 3D models by combining both
the traditional input method (mouse/keyboard) and the tangible input
method (markers). It has the ability to align a new virtual object with
the existing parts of a model. The 3DARModeler targets nontechnical
users. As such, they do not need much knowledge of
computer graphics and modeling techniques. All they have to do is
select basic objects, customize their attributes, and put them together
to build a 3D model in a simple and intuitive way as if they were
doing in the real world. Using the hierarchical modeling technique,
the users are able to group several basic objects to manage them as a
unified, complex object. The system can also connect with other 3D
systems by importing and exporting VRML/3Ds Max files. A
module of speech recognition is included in the system to provide
flexible user interfaces.
Abstract: This paper introduces a new instantaneous frequency
computation approach -Counting Instantaneous Frequency for a
general class of signals called simple waves. The classsimple wave
contains a wide range of continuous signals for which the concept
instantaneous frequency has a perfect physical sense. The concept of
-Counting Instantaneous Frequency also applies to all the discrete data.
For all the simple wave signals and the discrete data, -Counting
instantaneous frequency can be computed directly without signal
decomposition process. The intrinsic mode functions obtained through
empirical mode decomposition belongs to simple wave. So
-Counting instantaneous frequency can be used together with
empirical mode decomposition.
Abstract: This paper describes a new method for affine parameter
estimation between image sequences. Usually, the parameter
estimation techniques can be done by least squares in a quadratic
way. However, this technique can be sensitive to the presence
of outliers. Therefore, parameter estimation techniques for various
image processing applications are robust enough to withstand the
influence of outliers. Progressively, some robust estimation functions
demanding non-quadratic and perhaps non-convex potentials adopted
from statistics literature have been used for solving these. Addressing
the optimization of the error function in a factual framework for
finding a global optimal solution, the minimization can begin with
the convex estimator at the coarser level and gradually introduce nonconvexity
i.e., from soft to hard redescending non-convex estimators
when the iteration reaches finer level of multiresolution pyramid.
Comparison has been made to find the performance of the results
of proposed method with the results found individually using two
different estimators.
Abstract: This paper describes an efficient and practical method
for economic dispatch problem in one and two area electrical power
systems with considering the constraint of the tie transmission line
capacity constraint. Direct search method (DSM) is used with some
equality and inequality constraints of the production units with any
kind of fuel cost function. By this method, it is possible to use several
inequality constraints without having difficulty for complex cost
functions or in the case of unavailability of the cost function
derivative. To minimize the number of total iterations in searching,
process multi-level convergence is incorporated in the DSM.
Enhanced direct search method (EDSM) for two area power system
will be investigated. The initial calculation step size that causes less
iterations and then less calculation time is presented. Effect of the
transmission tie line capacity, between areas, on economic dispatch
problem and on total generation cost will be studied; line
compensation and active power with reactive power dispatch are
proposed to overcome the high generation costs for this multi-area
system.
Abstract: A simple and easy algorithm is presented for a fast calculation of kernel functions which required in fluid simulations using the Smoothed Particle Hydrodynamic (SPH) method. Present proposed algorithm improves the Linked-list algorithm and adopts the Pair-Wise Interaction technique, which are widely used for evaluating kernel functions in fluid simulations using the SPH method. The algorithm is easy to be implemented without any complexities in programming. Some benchmark examples are used to show the simulation time saved by using the proposed algorithm. Parametric studies on the number of divisions for sub-domains, smoothing length and total amount of particles are conducted to show the effectiveness of the present technique. A compact formulation is proposed for practical usage.
Abstract: In this paper, based on the past project cost and time
performance, a model for forecasting project cost performance is
developed. This study presents a probabilistic project control concept
to assure an acceptable forecast of project cost performance. In this
concept project activities are classified into sub-groups entitled
control accounts. Then obtain the Stochastic S-Curve (SS-Curve), for
each sub-group and the project SS-Curve is obtained by summing
sub-groups- SS-Curves. In this model, project cost uncertainties are
considered through Beta distribution functions of the project
activities costs required to complete the project at every selected time
sections through project accomplishment, which are extracted from a
variety of sources. Based on this model, after a percentage of the
project progress, the project performance is measured via Earned
Value Management to adjust the primary cost probability distribution
functions. Then, accordingly the future project cost performance is
predicted by using the Monte-Carlo simulation method.
Abstract: The paper presents an optimization study based on
genetic algorithms (GA-s) for a radio-frequency applicator used in
heating dielectric band products. The weakly coupled electro-thermal
problem is analyzed using 2D-FEM. The design variables in the
optimization process are: the voltage of a supplementary “guard"
electrode and six geometric parameters of the applicator. Two
objective functions are used: temperature uniformity and total active
power absorbed by the dielectric. Both mono-objective and multiobjective
formulations are implemented in GA optimization.
Abstract: In this paper, a new approach is introduced to solve
Blasius equation using parameter identification of a nonlinear
function which is used as approximation function. Bees Algorithm
(BA) is applied in order to find the adjustable parameters of
approximation function regarding minimizing a fitness function
including these parameters (i.e. adjustable parameters). These
parameters are determined how the approximation function has to
satisfy the boundary conditions. In order to demonstrate the
presented method, the obtained results are compared with another
numerical method. Present method can be easily extended to solve a
wide range of problems.
Abstract: The adoption of e-learning in Hong Kong has been
increasing rapidly in the past decade. To understand the e-learning
experiences of the students, the School of Professional and Continuing
Education of The University of Hong Kong conducted a survey. The
survey aimed to collect students- experiences in using learning
management system, their perceived e-learning advantages, barriers in
e-learning and preferences in new e-learning development. A
questionnaire with 84 questions was distributed in mid 2012 and 608
valid responds were received. The analysis results showed that the
students found e-learning helpful to their study. They preferred
interactive functions and mobile features. Blended learning mode,
both face-to-face learning mode integrated with online learning and
face-to-face learning mode supplemented with online resources, were
preferred by the students. The results of experiences of Hong Kong
students in e-learning provided a contemporary reference to the
e-learning practitioners to understand the e-learning situation in Asia.
Abstract: Let Gα ,β (γ ,δ ) denote the class of function
f (z), f (0) = f ′(0)−1= 0 which satisfied e δ {αf ′(z)+ βzf ′′(z)}> γ i Re
in the open unit disk D = {z ∈ı : z < 1} for some α ∈ı (α ≠ 0) ,
β ∈ı and γ ∈ı (0 ≤γ 0 . In
this paper, we determine some extremal properties including
distortion theorem and argument of f ′( z ) .
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
Abstract: With the prevalence of computer and development of information technology, Geographic Information Systems (GIS) have long used for a variety of applications in electrical engineering. GIS are designed to support the analysis, management, manipulation and mapping of spatial data. This paper presents several usages of GIS in power utilities such as automated route selection for the construction of new power lines which uses a dynamic programming model for route optimization, load forecasting and optimizing planning of substation-s location and capacity with comprehensive algorithm which involves an accurate small-area electric load forecasting procedure and simulates the different cost functions of substations.
Abstract: The governing differential equations of laminated
plate utilizing trigonometric shear deformation theory are derived
using energy approach. The governing differential equations
discretized by different radial basis functions are used to predict the
free vibration behavior of symmetric laminated composite plates.
Effect of orthotropy and span to thickness ratio on frequency
parameter of simply supported laminated plate is presented.
Numerical results show the accuracy and good convergence of radial
basis functions.