Abstract: This paper proposes the application of a hierarchical fuzzy system (HFS) based on multi-input power system stabilizer (MPSS) and also Static Var Compensator (SVC) in multi-machine environment.The number of rules grows exponentially with the number of variables in a conventional fuzzy logic system. The proposed HFS method is developed to solve this problem. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. In fact, by using HFS the total number of involved rules increases only linearly with the number of input variables. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type Power system stabilizer (PSS). Phasor model of SVC is described and used in this paper. The performances of MPSS, Conventional power system stabilizer (CPSS), hierarchical Fuzzy Multi-input Power System Stabilizer (HFMPSS) and the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. By using digital simulations the comparative study is illustrated. It can be seen that the proposed PSS is performing satisfactorily within the whole range of disturbances.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: This paper explores the effectiveness of machine
learning techniques in detecting firms that issue fraudulent financial
statements (FFS) and deals with the identification of factors
associated to FFS. To this end, a number of experiments have been
conducted using representative learning algorithms, which were
trained using a data set of 164 fraud and non-fraud Greek firms in the
recent period 2001-2002. The decision of which particular method to
choose is a complicated problem. A good alternative to choosing
only one method is to create a hybrid forecasting system
incorporating a number of possible solution methods as components
(an ensemble of classifiers). For this purpose, we have implemented
a hybrid decision support system that combines the representative
algorithms using a stacking variant methodology and achieves better
performance than any examined simple and ensemble method. To
sum up, this study indicates that the investigation of financial
information can be used in the identification of FFS and underline the
importance of financial ratios.
Abstract: This paper presents an algorithm which
combining ant colony optimization in the dynamic
programming for solving a dynamic facility layout problem.
The problem is separated into 2 phases, static and dynamic
phase. In static phase, ant colony optimization is used to find
the best ranked of layouts for each period. Then the dynamic
programming (DP) procedure is performed in the dynamic
phase to evaluate the layout set during multi-period planning
horizon. The proposed algorithm is tested over many
problems with size ranging from 9 to 49 departments, 2 and 4
periods. The experimental results show that the proposed
method is an alternative way for the plant layout designer to
determine the layouts during multi-period planning horizon.
Abstract: There are three distinct stages in the evolution of
economic thought, namely:
1. in the first stage, the major concern was to accelerate
economic growth with increased availability of material
goods, especially in developing economies with very low
living standards, because poverty eradication meant faster
economic growth.
2. in the second stage, economists made distinction between
growth and development. Development was seen as going
beyond economic growth, and bringing certain changes in
the structure of the economy with more equitable
distribution of the benefits of growth, with the growth
coming automatic and sustained.
3. the third stage is now reached. Our concern is now with
“sustainable development", that is, development not only
for the present but also of the future.
Thus the focus changed from “sustained growth" to “sustained
development". Sustained development brings to the fore the long
term relationship between the ecology and economic development.
Since the creation of UNEP in 1972 it has worked for
development without destruction for environmentally sound and
sustained development. It was realised that the environment cannot
be viewed in a vaccum, it is not separate from development, nor is it
competing. It suggested for the integration of the environment with
development whereby ecological factors enter development planning,
socio-economic policies, cost-benefit analysis, trade, technology
transfer, waste management, educational and other specific areas.
Industrialisation has contributed to the growth of economy of
several countries. It has improved the standards of living of its people
and provided benefits to the society. It has also created in the process
great environmental problems like climate change, forest destruction
and denudation, soil erosion and desertification etc.
On the other hand, industry has provided jobs and improved the
prospects of wealth for the industrialists. The working class
communities had to simply put up with the high levels of pollution in
order to keep up their jobs and also to save their income.
There are many roots of the environmental problem. They may be
political, economic, cultural and technological conditions of the
modern society. The experts concede that industrial growth lies
somewhere close to the heart of the matter. Therefore, the objective
of this paper is not to document all roots of an environmental crisis
but rather to discuss the effects of industrial growth and
development.
We have come to the conclusion that although public intervention
is often unnecessary to ensure that perfectly competitive markets will
function in society-s best interests, such intervention is necessary
when firms or consumers pollute.
Abstract: Mathematical programming has been applied to various
problems. For many actual problems, the assumption that the parameters
involved are deterministic known data is often unjustified. In
such cases, these data contain uncertainty and are thus represented
as random variables, since they represent information about the
future. Decision-making under uncertainty involves potential risk.
Stochastic programming is a commonly used method for optimization
under uncertainty. A stochastic programming problem with recourse
is referred to as a two-stage stochastic problem. In this study, we
consider a stochastic programming problem with simple integer
recourse in which the value of the recourse variable is restricted to a
multiple of a nonnegative integer. The algorithm of a dynamic slope
scaling procedure for solving this problem is developed by using a
property of the expected recourse function. Numerical experiments
demonstrate that the proposed algorithm is quite efficient. The
stochastic programming model defined in this paper is quite useful
for a variety of design and operational problems.
Abstract: Nowadays, Gene Ontology has been used widely by many researchers for biological data mining and information retrieval, integration of biological databases, finding genes, and incorporating knowledge in the Gene Ontology for gene clustering. However, the increase in size of the Gene Ontology has caused problems in maintaining and processing them. One way to obtain their accessibility is by clustering them into fragmented groups. Clustering the Gene Ontology is a difficult combinatorial problem and can be modeled as a graph partitioning problem. Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. Therefore, an approach for solving the automatic clustering of the Gene Ontology is proposed by incorporating cohesion-and-coupling metric into a hybrid algorithm consisting of a genetic algorithm and a split-and-merge algorithm. Experimental results and an example of modularized Gene Ontology in RDF/XML format are given to illustrate the effectiveness of the algorithm.
Abstract: Injection molding is a very complicated process to
monitor and control. With its high complexity and many process
parameters, the optimization of these systems is a very challenging
problem. To meet the requirements and costs demanded by the
market, there has been an intense development and research with the
aim to maintain the process under control. This paper outlines the
latest advances in necessary algorithms for plastic injection process
and monitoring, and also a flexible data acquisition system that
allows rapid implementation of complex algorithms to assess their
correct performance and can be integrated in the quality control
process. This is the main topic of this paper. Finally, to demonstrate
the performance achieved by this combination, a real case of use is
presented.
Abstract: Every day human life experiences new equipments
more automatic and with more abilities. So the need for faster
processors doesn-t seem to finish. Despite new architectures and
higher frequencies, a single processor is not adequate for many
applications. Parallel processing and networks are previous solutions
for this problem. The new solution to put a network of resources on a
chip is called NOC (network on a chip). The more usual topology for
NOC is mesh topology. There are several routing algorithms suitable
for this topology such as XY, fully adaptive, etc. In this paper we
have suggested a new algorithm named Intermittent X, Y (IX/Y). We
have developed the new algorithm in simulation environment to
compare delay and power consumption with elders' algorithms.
Abstract: In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.
Abstract: This paper present the harmonic elimination of hybrid
multilevel inverters (HMI) which could be increase the number of
output voltage level. Total Harmonic Distortion (THD) is one of the
most important requirements concerning performance indices.
Because of many numbers output levels of HMI, it had numerous
unknown variables of eliminate undesired individual harmonic and
THD nonlinear equations set. Optimized harmonic stepped waveform
(OHSW) is solving switching angles conventional method, but most
complicated for solving as added level. The artificial intelligent
techniques are deliberation to solve this problem. This paper presents
the Particle Swarm Optimization (PSO) technique for solving
switching angles to get minimum THD and eliminate undesired
individual harmonics of 15-levels hybrid multilevel inverters.
Consequently it had many variables and could eliminate numerous
harmonics. Both advantages including high level of inverter and
Particle Swarm Optimization (PSO) are used as powerful tools for
harmonics elimination.
Abstract: The use of hard and brittle material has become
increasingly more extensive in recent years. Therefore processing of
these materials for the parts fabrication has become a challenging
problem. However, it is time-consuming to machine the hard brittle
materials with the traditional metal-cutting technique that uses
abrasive wheels. In addition, the tool would suffer excessive wear as
well. However, if ultrasonic energy is applied to the machining
process and coupled with the use of hard abrasive grits, hard and
brittle materials can be effectively machined. Ultrasonic machining
process is mostly used for the brittle materials. The present research
work has developed models using finite element approach to predict
the mechanical stresses sand strains produced in the tool during
ultrasonic machining process. Also the flow behavior of abrasive
slurry coming out of the nozzle has been studied for simulation using
ANSYS CFX module. The different abrasives of different grit sizes
have been used for the experimentation work.
Abstract: In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.
Abstract: with increasing circuits- complexity and demand to
use portable devices, power consumption is one of the most
important parameters these days. Full adders are the basic block of
many circuits. Therefore reducing power consumption in full adders
is very important in low power circuits. One of the most powerconsuming
modules in full adders is XOR/XNOR circuit. This paper
presents two new full adders based on two new logic approaches. The
proposed logic approaches use one XOR or XNOR gate to implement
a full adder cell. Therefore, delay and power will be decreased. Using
two new approaches and two XOR and XNOR gates, two new full
adders have been implemented in this paper. Simulations are carried
out by HSPICE in 0.18μm bulk technology with 1.8V supply voltage.
The results show that the ten-transistors proposed full adder has 12%
less power consumption and is 5% faster in comparison to MB12T
full adder. 9T is more efficient in area and is 24% better than similar
10T full adder in term of power consumption. The main drawback of
the proposed circuits is output threshold loss problem.
Abstract: In recent years, there has been an increasing interest
toward the use of bovine genotyped embryos for commercial embryo
transfer programs. Biopsy of a few cells in morulla stage is essential
for preimplantation genetic diagnosis (PGD). Low amount of DNA
have limited performing the several molecular analyses within PGD
analyses. Whole genome amplification (WGA) promises to eliminate
this problem. We evaluated the possibility and performance of an
improved primer extension preamplification (I-PEP) method with a
range of starting bovine genomic DNA from 1-8 cells into the WGA
reaction. We optimized a short and simple I-PEP (ssI-PEP) procedure
(~3h). This optimized WGA method was assessed by 6 loci specific
polymerase chain reactions (PCRs), included restriction fragments
length polymorphism (RFLP). Optimized WGA procedure possesses
enough sensitivity for molecular genetic analyses through the few
input cells. This is a new era for generating characterized bovine
embryos in preimplantation stage.
Abstract: Elliptic curve-based certificateless signature is slowly
gaining attention due to its ability to retain the efficiency of
identity-based signature to eliminate the need of certificate
management while it does not suffer from inherent private
key escrow problem. Generally, cryptosystem based on elliptic
curve offers equivalent security strength at smaller key sizes
compared to conventional cryptosystem such as RSA which
results in faster computations and efficient use of computing
power, bandwidth, and storage. This paper proposes to implement
certificateless signature based on bilinear pairing to
structure the framework of IKE authentication. In this paper,
we perform a comparative analysis of certificateless signature
scheme with a well-known RSA scheme and also present the
experimental results in the context of signing and verification
execution times. By generalizing our observations, we discuss the
different trade-offs involved in implementing IKE authentication
by using certificateless signature.
Abstract: In this paper dynamics of a vapour bubble generated
due to a local energy input inside a vertical rigid cylinder and in the
absence of buoyancy forces is investigated. Different ratios of the
diameter of the rigid cylinder to the maximum radius of the bubble
are considered. The Boundary Integral Equation Method is employed
for numerical simulation of the problem. Results show that during
the collapse phase of the bubble inside a vertical rigid cylinder, two
liquid micro jets are developed on the top and bottom sides of the
vapour bubble and are directed inward. Results also show that
existence of a deposit rib inside the vertical rigid cylinder slightly
increases the life time of the bubble. It is found that by increasing the
ratio of the cylinder diameter to the maximum radius of the bubble,
the rate of the growth and collapse phases of the bubble increases
and the life time of the bubble decreases.
Abstract: Scheduling for the flexible job shop is very important
in both fields of production management and combinatorial
optimization. However, it quit difficult to achieve an optimal solution
to this problem with traditional optimization approaches owing to the
high computational complexity. The combining of several
optimization criteria induces additional complexity and new
problems. In this paper, a Pareto approach to solve the multi
objective flexible job shop scheduling problems is proposed. The
objectives considered are to minimize the overall completion time
(makespan) and total weighted tardiness (TWT). An effective
simulated annealing algorithm based on the proposed approach is
presented to solve multi objective flexible job shop scheduling
problem. An external memory of non-dominated solutions is
considered to save and update the non-dominated solutions during
the solution process. Numerical examples are used to evaluate and
study the performance of the proposed algorithm. The proposed
algorithm can be applied easily in real factory conditions and for
large size problems. It should thus be useful to both practitioners and
researchers.
Abstract: The main objective of this paper is a comparative
investigate in enhancement of damping power system oscillation via
coordinated design of the power system stabilizer (PSS) and static
synchronous series compensator (SSSC) and static synchronous
compensator (STATCOM). The design problem of FACTS-based
stabilizers is formulated as a GA based optimization problem. In this
paper eigenvalue analysis method is used on small signal stability of
single machine infinite bus (SMIB) system installed with SSSC and
STATCOM. The generator is equipped with a PSS. The proposed
stabilizers are tested on a weakly connected power system with
different disturbances and loading conditions. This aim is to enhance
both rotor angle and power system stability. The eigenvalue analysis
and non-linear simulation results are presented to show the effects of
these FACTS-based stabilizers and reveal that SSSC exhibits the best
effectiveness on damping power system oscillation.
Abstract: In the traditional concept of product life cycle management, the activities of design, manufacturing, and assembly are performed in a sequential way. The drawback is that the considerations in design may contradict the considerations in manufacturing and assembly. The different designs of components can lead to different assembly sequences. Therefore, in some cases, a good design may result in a high cost in the downstream assembly activities. In this research, an integrated design evaluation and assembly sequence planning model is presented. Given a product requirement, there may be several design alternative cases to design the components for the same product. If a different design case is selected, the assembly sequence for constructing the product can be different. In this paper, first, the designed components are represented by using graph based models. The graph based models are transformed to assembly precedence constraints and assembly costs. A particle swarm optimization (PSO) approach is presented by encoding a particle using a position matrix defined by the design cases and the assembly sequences. The PSO algorithm simultaneously performs design evaluation and assembly sequence planning with an objective of minimizing the total assembly costs. As a result, the design cases and the assembly sequences can both be optimized. The main contribution lies in the new concept of integrated design evaluation and assembly sequence planning model and the new PSO solution method. The test results show that the presented method is feasible and efficient for solving the integrated design evaluation and assembly planning problem. In this paper, an example product is tested and illustrated.