Abstract: This paper presents a novel approach for tuning unified power flow controller (UPFC) based damping controller in order to enhance the damping of power system low frequency oscillations. The design problem of damping controller is formulated as an optimization problem according to the eigenvalue-based objective function which is solved using iteration particle swarm optimization (IPSO). The effectiveness of the proposed controller is demonstrated through eigenvalue analysis and nonlinear time-domain simulation studies under a wide range of loading conditions. The simulation study shows that the designed controller by IPSO performs better than CPSO in finding the solution. Moreover, the system performance analysis under different operating conditions show that the δE based controller is superior to the mB based controller.
Abstract: The population structure of the Tor tambroides was
investigated with morphometric data (i.e. morphormetric
measurement and truss measurement). A morphometric analysis was
conducted to compare specimens from three waterfalls: Sunanta, Nan
Chong Fa and Wang Muang waterfalls at Khao Nan National Park,
Nakhon Si Thammarat, Southern Thailand. The results of stepwise
discriminant analysis on seven morphometric variables and 21 truss
variables per individual were the same as from a neural network. Fish
from three waterfalls were separated into three groups based on their
morphometric measurements. The morphometric data shows that the
nerual network model performed better than the stepwise
discriminant analysis.
Abstract: Multi-agent system is composed by several agents
capable of reaching the goal cooperatively. The system needs an agent
platform for efficient and stable interaction between intelligent agents.
In this paper we propose a flexible and scalable agent platform by
composing the containers with multiple hierarchical agent groups. It
also allows efficient implementation of multiple domain presentations
of the agents unlike JADE. The proposed platform provides both
group management and individual management of agents for
efficiency. The platform has been implemented and tested, and it can
be used as a flexible foundation of the dynamic multi-agent system
targeting seamless delivery of ubiquitous services.
Abstract: This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Abstract: In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.
Abstract: Boon Rawd Brewery is a beer company based in
Thailand that has an exemplary image, both as a good employer and a
well-managed company with a strong record of social responsibility.
The most famous of the company’s products is Singha beer. To study
the company’s marketing strategy, a case study analysis was
conducted together with qualitative research methods. The study
analyzed the marketing strategy of Boon Rawd Brewery before the
liberalization of the liquor market in 2000. The company’s marketing
strategies consisted of the following: product line strategy, product
development strategy, block channel strategy, media strategy, trade
strategy, and consumer incentive strategy. Additionally, the company
employed marketing mix strategy based on the 4Ps: product, price,
promotion and place (of distribution).
Abstract: Efficient preprocessing is very essential for automatic
recognition of handwritten documents. In this paper, techniques on
segmenting words in handwritten Arabic text are presented. Firstly,
connected components (ccs) are extracted, and distances among
different components are analyzed. The statistical distribution of this
distance is then obtained to determine an optimal threshold for words
segmentation. Meanwhile, an improved projection based method is
also employed for baseline detection. The proposed method has been
successfully tested on IFN/ENIT database consisting of 26459
Arabic words handwritten by 411 different writers, and the results
were promising and very encouraging in more accurate detection of
the baseline and segmentation of words for further recognition.
Abstract: It is well known that a linear dynamic system including
a delay will exhibit limit cycle oscillations when a bang-bang sensor
is used in the feedback loop of a PID controller. A similar behaviour
occurs when a delayed feedback signal is used to train a neural
network. This paper develops a method of predicting this behaviour
by linearizing the system, which can be shown to behave in a manner
similar to an integral controller. Using this procedure, it is possible
to predict the characteristics of the neural network driven limit cycle
to varying degrees of accuracy, depending on the information known
about the system. An application is also presented: the intelligent
control of a spark ignition engine.
Abstract: There are many kinds of metal borates found not only
in nature but also synthesized in the laboratory such as magnesium
borates. Due to its excellent properties, as remarkable ceramic
materials, they have also application areas in anti-wear and friction
reducing additives as well as electro-conductive treating agents. The
synthesis of magnesium borate powders can be fulfilled simply with
two different methods, hydrothermal and thermal synthesis.
Microwave assisted method, also another way of producing
magnesium borate, can be classified into thermal synthesis because of
using the principles of solid state synthesis. It also contributes
producing particles with small size and high purity in nano-size
material synthesize. In this study the production of magnesium
borates, are aimed using MgCl2.6H2O and H3BO3. The identification
of both starting materials and products were made by the equipments
of, X-Ray Diffraction (XRD) and Fourier Transform Infrared
Spectroscopy (FT-IR). After several synthesis steps magnesium
borates were synthesized and characterized by XRD and FT-IR, as
well.
Abstract: The aim of this paper is to investigate the influence of
market share and diversification on the nonlife insurers- performance.
The underlying relationships have been investigated in different
industries and different disciplines (economics, management...), still,
no consistency exists either in the magnitude or statistical
significance of the relationship between market share (and
diversification as well) on one side and companies- performance on
the other side. Moreover, the direction of the relationship is also
somewhat questionable. While some authors find this relationship to
be positive, the others reveal its negative association. In order to test
the influence of market share and diversification on companies-
performance in Croatian nonlife insurance industry for the period
from 1999 to 2009, we designed an empirical model in which we
included the following independent variables: firms- profitability
from previous years, market share, diversification and control
variables (i.e. ownership, industrial concentration, GDP per capita,
inflation). Using the two-step generalized method of moments
(GMM) estimator we found evidence of a positive and statistically
significant influence of both, market share and diversification, on
insurers- profitability.
Abstract: Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of ANN is used. The designed neural network can predict the natural gas viscosity using pseudo-reduced pressure and pseudo-reduced temperature with AARD% of 0.221. The accuracy of designed ANN has been compared to other published empirical models. The comparison indicates that the proposed method can provide accurate results.
Abstract: The study was a case study analysis about Thai Asia
Pacific Brewery Company. The purpose was to analyze the
company’s marketing objective, marketing strategy at company level,
and marketing mix before liquor liberalization in 2000. Methods used
in this study were qualitative and descriptive research approach
which demonstrated the following results of the study demonstrated
as follows: (1) Marketing objective was to increase market share of
Heineken and Amtel, (2) the company’s marketing strategies were
brand building strategy and distribution strategy. Additionally, the
company also conducted marketing mix strategy as follows. Product
strategy: The company added more beer brands namely Amstel and
Tiger to provide additional choice to consumers, product and
marketing research, and product development. Price strategy: the
company had taken the following into consideration: cost,
competitor, market, economic situation and tax. Promotion strategy:
the company conducted sales promotion and advertising. Distribution
strategy: the company extended channels its channels of distribution
into food shops, pubs and various entertainment places. This strategy
benefited interested persons and people who were engaged in the beer
business.
Abstract: This research presented in this paper is an on-going
project of an application of neural network and fuzzy models to
evaluate the sociological factors which affect the educational
performance of the students in Sri Lanka. One of its major goals is to
prepare the grounds to device a counseling tool which helps these
students for a better performance at their examinations, especially at
their G.C.E O/L (General Certificate of Education-Ordinary Level)
examination. Closely related sociological factors are collected as raw
data and the noise of these data are filtered through the fuzzy
interface and the supervised neural network is being utilized to
recognize the performance patterns against the chosen social factors.
Abstract: A spectrophotometric method was developed for simultaneous quantification of pseudoephedrine hydrochloride (PSE) triprolidine hydrochloride (TRI) using second derivative method (zero-crossing technique). The second derivative amplitudes of PSE and TRI were measured at 271 and 321 nm, respectively. The calibration curves were linear in the range of 200 to 1,000 g/ml for PSE and 10 to 50 g/ml for TRI. The method was validated for specificity, accuracy, precision, limit of detection and limit of quantitation. The proposed method was applied to the assaying and dissolution of PSE and TRI in commercial tablets without any chemical separation. The results were compared with those obtained by the official USP31 method and statistical tests showed that there is no significant between the methods at 95% confidence level. The proposed method is simple, rapid and suitable for the routine quality control application. KeywordsTriprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.
Abstract: A system for market identification (SMI) is presented.
The resulting representations are multivariable dynamic demand
models. The market specifics are analyzed. Appropriate models and
identification techniques are chosen. Multivariate static and dynamic
models are used to represent the market behavior. The steps of the
first stage of SMI, named data preprocessing, are mentioned. Next,
the second stage, which is the model estimation, is considered in more
details. Stepwise linear regression (SWR) is used to determine the
significant cross-effects and the orders of the model polynomials. The
estimates of the model parameters are obtained by a numerically stable
estimator. Real market data is used to analyze SMI performance.
The main conclusion is related to the applicability of multivariate
dynamic models for representation of market systems.
Abstract: The utilization of cheese whey as a fermentation
substrate to produce bio-ethanol is an effort to supply bio-ethanol
demand as a renewable energy. Like other process systems, modeling
is also required for fermentation process design, optimization and
plant operation. This research aims to study the fermentation process
of cheese whey by applying mathematics and fundamental concept in
chemical engineering, and to investigate the characteristic of the
cheese whey fermentation process. Steady state simulation results for
inlet substrate concentration of 50, 100 and 150 g/l, and various
values of hydraulic retention time, showed that the ethanol
productivity maximum values were 0.1091, 0.3163 and 0.5639 g/l.h
respectively. Those values were achieved at hydraulic retention time
of 20 hours, which was the minimum value used in this modeling.
This showed that operating reactor at low hydraulic retention time
was favorable. Model of bio-ethanol production from cheese whey
will enhance the understanding of what really happen in the
fermentation process.
Abstract: This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.
Abstract: A framework to estimate the state of dynamically
varying environment where data are generated from heterogeneous
sources possessing partial knowledge about the environment is presented.
This is entirely derived within Dempster-Shafer and Evidence
Filtering frameworks. The belief about the current state is expressed
as belief and plausibility functions. An addition to Single Input
Single Output Evidence Filter, Multiple Input Single Output Evidence
Filtering approach is introduced. Variety of applications such as
situational estimation of an emergency environment can be developed
within the framework successfully. Fire propagation scenario is used
to justify the proposed framework, simulation results are presented.
Abstract: Carbon disulfide is widely used for the production of
viscose rayon, rubber, and other organic materials and it is a
feedstock for the synthesis of sulfuric acid. The objective of this
paper is to analyze possibilities for efficient production of CS2 from
sour natural gas reformation (H2SMR) (2H2S+CH4 =CS2 +4H2) .
Also, the effect of H2S to CH4 feed ratio and reaction temperature on
carbon disulfide production is investigated numerically in a
reforming reactor. The chemical reaction model is based on an
assumed Probability Density Function (PDF) parameterized by the
mean and variance of mixture fraction and β-PDF shape. The results
show that the major factors influencing CS2 production are reactor
temperature. The yield of carbon disulfide increases with increasing
H2S to CH4 feed gas ratio (H2S/CH4≤4). Also the yield of C(s)
increases with increasing temperature until the temperature reaches
to 1000°K, and then due to increase of CS2 production and
consumption of C(s), yield of C(s) drops with further increase in the
temperature. The predicted CH4 and H2S conversion and yield of
carbon disulfide are in good agreement with result of Huang and TRaissi.
Abstract: Sociological models (e.g., social network analysis, small-group dynamic and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This study also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biological model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization.