Abstract: The IFS is a scheme for describing and manipulating complex fractal attractors using simple mathematical models. More precisely, the most popular “fractal –based" algorithms for both representation and compression of computer images have involved some implementation of the method of Iterated Function Systems (IFS) on complete metric spaces. In this paper a new generalized space called Multi-Fuzzy Fractal Space was constructed. On these spases a distance function is defined, and its completeness is proved. The completeness property of this space ensures the existence of a fixed-point theorem for the family of continuous mappings. This theorem is the fundamental result on which the IFS methods are based and the fractals are built. The defined mappings are proved to satisfy some generalizations of the contraction condition.
Abstract: Evolvable hardware (EHW) is a developing field that
applies evolutionary algorithm (EA) to automatically design circuits,
antennas, robot controllers etc. A lot of research has been done in this
area and several different EAs have been introduced to tackle
numerous problems, as scalability, evolvability etc. However every
time a specific EA is chosen for solving a particular task, all its
components, such as population size, initialization, selection
mechanism, mutation rate, and genetic operators, should be selected
in order to achieve the best results. In the last three decade the
selection of the right parameters for the EA-s components for solving
different “test-problems" has been investigated. In this paper the
behaviour of mutation rate for designing logic circuits, which has not
been done before, has been deeply analyzed. The mutation rate for an
EHW system modifies the number of inputs of each logic gates, the
functionality (for example from AND to NOR) and the connectivity
between logic gates. The behaviour of the mutation has been
analyzed based on the number of generations, genotype redundancy
and number of logic gates for the evolved circuits. The experimental
results found provide the behaviour of the mutation rate during
evolution for the design and optimization of simple logic circuits.
The experimental results propose the best mutation rate to be used for
designing combinational logic circuits. The research presented is
particular important for those who would like to implement a
dynamic mutation rate inside the evolutionary algorithm for evolving
digital circuits. The researches on the mutation rate during the last 40
years are also summarized.
Abstract: The problem of generation expansion planning (GEP)
has been extensively studied for many years. This paper presents
three topics in GEP as follow: statistical model, models for
generation expansion, and expansion problem. In the topic of
statistical model, the main stages of the statistical modeling are
briefly explained. Some works on models for GEP are reviewed in
the topic of models for generation expansion. Finally for the topic of
expansion problem, the major issues in the development of a longterm
expansion plan are summarized.
Abstract: Most of the well known methods for generating
Gaussian variables require at least one standard uniform distributed
value, for each Gaussian variable generated. The length of the
random number generator therefore, limits the number of
independent Gaussian distributed variables that can be generated
meanwhile the statistical solution of complex systems requires a
large number of random numbers for their statistical analysis. We
propose an alternative simple method of generating almost infinite
number of Gaussian distributed variables using a limited number of
standard uniform distributed random numbers.
Abstract: Fault-proneness of a software module is the
probability that the module contains faults. To predict faultproneness
of modules different techniques have been proposed which
includes statistical methods, machine learning techniques, neural
network techniques and clustering techniques. The aim of proposed
study is to explore whether metrics available in the early lifecycle
(i.e. requirement metrics), metrics available in the late lifecycle (i.e.
code metrics) and metrics available in the early lifecycle (i.e.
requirement metrics) combined with metrics available in the late
lifecycle (i.e. code metrics) can be used to identify fault prone
modules using Genetic Algorithm technique. This approach has been
tested with real time defect C Programming language datasets of
NASA software projects. The results show that the fusion of
requirement and code metric is the best prediction model for
detecting the faults as compared with commonly used code based
model.
Abstract: Mushrooms are a group of fleshy macroscopic fungi.
They have been valued throughout the world as both edible and
medicine. They are highly nutritious with good amount of quality
proteins, vitamins and minerals. An edible mushroom, Calocybe
indica was selected to validate its nutritional and medicinal
properties. Since tissue damage in hyperglycemia has been related to
oxidative stress, we evaluated the enzymatic and non-enzymatic
antioxidant status in the serum, liver and kidney since they are the
target organs in diabetic complications. From the results, increased
oxidative stress and decreased antioxidants might be related to the
causation of diabetes mellitus. The treatment in the diabetic rats with
the Calocybe indica showed an increase in the antioxidant system
and decrease in the production of free radicals. The mushrooms
which contain antioxidant phytochemicals has potential free radical
scavenging capacity and hence can induce the antioxidant system in
the body significantly reduces the generated free radicals thereby
maintaining the normal levels of the antioxidants
Abstract: A reliable estimate of the average bond stress within
the anchorage of steel reinforcing bars in tension is critically
important for the design of reinforced concrete member. This paper
describes part of a recently completed experimental research program
in the Centre for Infrastructure Engineering and Safety (CIES) at the
University of New South Wales, Sydney, Australia aimed at
assessing the effects of different factors on the anchorage
requirements of modern high strength steel reinforcing bars. The
study found that an increase in the anchorage length and bar diameter
generally leads to a reduction of the average ultimate bond stress. By
the extension of a well established analytical model of bond and
anchorage, it is shown here that the differences in the average
ultimate bond stress for different anchorage lengths is associated with
the variable degree of plastic deformation in the tensile zone of the
concrete surrounding the bar.
Abstract: This paper presents a practical scheme that can be used for allocating the transmission loss to generators and loads. In this scheme first the share of a generator or load on the current through a branch is determined using Z-bus modified matrix. Then the current components are decomposed and the branch loss allocation is obtained. A motivation of proposed scheme is to improve the results of Z-bus method and to reach more fair allocation. The proposed scheme has been implemented and tested on several networks. To achieve practical and applicable results, the proposed scheme is simulated and compared on the transmission network (400kv) of Khorasan region in Iran and the 14-bus standard IEEE network. The results show that the proposed scheme is comprehensive and fair to allocating the energy losses of a power market to its participants.
Abstract: This paper presents the development and application of an adaptive neuro fuzzy inference system (ANFIS) based intelligent hybrid neuro fuzzy controller for automatic generation control (AGC) of two-area interconnected thermal power system with reheat non linearity. The dynamic response of the system has been studied for 1% step load perturbation in area-1. The performance of the proposed neuro fuzzy controller is compared against conventional proportional-integral (PI) controller, state feedback linear quadratic regulator (LQR) controller and fuzzy gain scheduled proportionalintegral (FGSPI) controller. Comparative analysis demonstrates that the proposed intelligent neuro fuzzy controller is the most effective of all in improving the transients of frequency and tie-line power deviations against small step load disturbances. Simulations have been performed using Matlab®.
Abstract: Since 1992, year where Hugo de Garis has published
the first paper on Evolvable Hardware (EHW), a period of intense
creativity has followed. It has been actively researched, developed
and applied to various problems. Different approaches have been
proposed that created three main classifications: extrinsic, mixtrinsic
and intrinsic EHW. Each of these solutions has a real interest.
Nevertheless, although the extrinsic evolution generates some
excellent results, the intrinsic systems are not so advanced. This
paper suggests 3 possible solutions to implement the run-time
configuration intrinsic EHW system: FPGA-based Run-Time
Configuration system, JBits-based Run-Time Configuration system
and Multi-board functional-level Run-Time Configuration system.
The main characteristic of the proposed architectures is that they are
implemented on Field Programmable Gate Array. A comparison of
proposed solutions demonstrates that multi-board functional-level
run-time configuration is superior in terms of scalability, flexibility
and the implementation easiness.
Abstract: In this paper, by using Mawhin-s continuation theorem of coincidence degree and a method based on delay differential inequality, some sufficient conditions are obtained for the existence and global exponential stability of periodic solutions of cellular neural networks with distributed delays and impulses on time scales. The results of this paper generalized previously known results.
Abstract: The inherent flexibilities of XML in both structure
and semantics makes mining from XML data a complex task with
more challenges compared to traditional association rule mining in
relational databases. In this paper, we propose a new model for the
effective extraction of generalized association rules form a XML
document collection. We directly use frequent subtree mining
techniques in the discovery process and do not ignore the tree
structure of data in the final rules. The frequent subtrees based on the
user provided support are split to complement subtrees to form the
rules. We explain our model within multi-steps from data preparation
to rule generation.
Abstract: Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, research is limited by the cost of genotyping the tremendous number of SNPs. Therefore, it is important to identify a small subset of informative SNPs, the so-called tag SNPs. This subset consists of selected SNPs of the genotypes, and accurately represents the rest of the SNPs. Furthermore, an effective evaluation method is needed to evaluate prediction accuracy of a set of tag SNPs. In this paper, a genetic algorithm (GA) is applied to tag SNP problems, and the K-nearest neighbor (K-NN) serves as a prediction method of tag SNP selection. The experimental data used was taken from the HapMap project; it consists of genotype data rather than haplotype data. The proposed method consistently identified tag SNPs with considerably better prediction accuracy than methods from the literature. At the same time, the number of tag SNPs identified was smaller than the number of tag SNPs in the other methods. The run time of the proposed method was much shorter than the run time of the SVM/STSA method when the same accuracy was reached.
Abstract: Not many studies have been undertaken on shareholder activism in emerging economies, including Malaysia. Shareholder activism in emerging economies is on the rise. This paper seeks to comprehend the elements of this activism that are unique to Malaysia, specifically with respect to how the agency problem is controlled through shareholder activism in improving corporate governance practices within target companies. Through shareholder activism, shareholders make contact with a target company to voice their dissatisfaction, suggestions, or recommendations. This paper utilises agency theory to explain institutional shareholder activism. This theory has been extensively used within literature on corporate governance with regards to shareholder activism. The effectiveness of shareholder activism in improving corporate governance will be examined as well. This research provides a further understanding of shareholder activism in emerging economies, such as Malaysia; this research also has the potential to enhance shareholder activism and corporate governance practices in general.
Abstract: Since polymerase chain reaction (PCR) has been
invented, it has emerged as a powerful tool in genetic analysis. The
PCR products are closely linked with thermal cycles. Therefore, to
reduce the reaction time and make temperature distribution uniform in
the reaction chamber, a novel oscillatory thermal cycler is designed.
The sample is placed in a fixed chamber, and three constant isothermal
zones are established and lined in the system. The sample is oscillated
and contacted with three different isothermal zones to complete
thermal cycles. This study presents the design of the geometric
characteristics of the chamber. The commercial software
CFD-ACE+TM is utilized to investigate the influences of various
materials, heating times, chamber volumes, and moving speed of the
chamber on the temperature distributions inside the chamber. The
chamber moves at a specific velocity and the boundary conditions
with time variations are related to the moving speed. Whereas the
chamber moves, the boundary is specified at the conditions of the
convection or the uniform temperature. The user subroutines compiled
by the FORTRAN language are used to make the numerical results
realistically. Results show that the reaction chamber with a rectangular
prism is heated on six faces; the effects of various moving speeds of
the chamber on the temperature distributions are examined. Regarding
to the temperature profiles and the standard deviation of the
temperature at the Y-cut cross section, the non-uniform temperature
inside chamber is found as the moving speed is larger than 0.01 m/s.
By reducing the heating faces to four, the standard deviation of the
temperature of the reaction chamber is under 1.4×10-3K with the range
of velocities between 0.0001 m/s and 1 m/s. The nature convective
boundary conditions are set at all boundaries while the chamber moves
between two heaters, the effects of various moving velocities of the
chamber on the temperature distributions are negligible at the assigned
time duration.
Abstract: Five original strains of entomopathogenic bacteria
with insecticidal activity against mosquito larvae of the genera Aedes,
Culex and Anopheles have been isolated from natural conditions in
Armenia and characterized. According to morphological,
physiological and biochemical parameters, all isolates were identified
as Bacillus thuringiensis spp. israelensis (Bti). High larvicidal
activity has been showed by three strains Bti. These strains can be
recommended for industrial production of bacterial preparations.
Abstract: Traffic enforcement units (the Police) are partly
responsible for the severity and frequency of the traffic accidents via
the effectiveness of their safety measures. The Police claims that the
reductions in accidents and their severities occur largely by their
timely interventions at the black spots, through traffic management
or temporary changes in the road design (guiding, reducing speeds
and eliminating sight obstructions, etc.). Yet, some other external
factors than the Police measures may intervene into which such
claims require a statistical confirmation. In order to test the net
impact of the Police contribution in the reduction of the number of
crashes, Chi square test was applied for 25 spots (streets and
intersections) and an average evaluation was achieved for general
conclusion in the case study of Izmir city. Separately, the net impact
of economic crisis in the reduction of crashes is assessed by the
trend analysis for the case of the economic crisis with the probable
reduction effects on the trip generation or modal choice. Finally, it
was proven that the Police measures were effective to some degree as
they claimed, though the economic crisis might have only negligible
contribution to the reductions in the same period observed.
Abstract: Serial Analysis of Gene Expression is a powerful
quantification technique for generating cell or tissue gene expression
data. The profile of the gene expression of cell or tissue in several
different states is difficult for biologists to analyze because of the large
number of genes typically involved. However, feature selection in
machine learning can successfully reduce this problem. The method
allows reducing the features (genes) in specific SAGE data, and
determines only relevant genes. In this study, we used a genetic
algorithm to implement feature selection, and evaluate the
classification accuracy of the selected features with the K-nearest
neighbor method. In order to validate the proposed method, we used
two SAGE data sets for testing. The results of this study conclusively
prove that the number of features of the original SAGE data set can be
significantly reduced and higher classification accuracy can be
achieved.
Abstract: This paper deals with dynamic load balancing using PVM. In distributed environment Load Balancing and Heterogeneity are very critical issues and needed to drill down in order to achieve the optimal results and efficiency. Various techniques are being used in order to distribute the load dynamically among different nodes and to deal with heterogeneity. These techniques are using different approaches where Process Migration is basic concept with different optimal flavors. But Process Migration is not an easy job, it impose lot of burden and processing effort in order to track each process in nodes. We will propose a dynamic load balancing technique in which application will intelligently balance the load among different nodes, resulting in efficient use of system and have no overheads of process migration. It would also provide a simple solution to problem of load balancing in heterogeneous environment.
Abstract: Understanding how precipitation inter-annually
changes and its implication in agricultural drought and production change in winter wheat (Triticum aestivum L.) growth season is critical for crop production in China. MODIS Temperature-Vegetation Dryness Index (TVDI) and daily mean precipitation time series for the main growth season(Feb. to May) of winter wheat from 2000 to 2010
were used to analyze the distribution of trends of precipitation,
agricultural drought and winter wheat yield change respectively, and
relationships between them in North China region(Huang-huai-hai
region, HHH region), China. The results indicated that the trend of
precipitation in HHH region past 11 years was increasing, which had
induced generally corresponding decreasing trend of agricultural
drought and increasing trend of wheat yield, while the trend of drought
was spatially diverse. The study could provide a basis for agricultural
drought research during winter wheat season in HHH region under the
ground of climate change.