Abstract: In order to integrate knowledge in heterogeneous
case-based reasoning (CBR) systems, ontology-based CBR system
has become a hot topic. To solve the facing problems of
ontology-based CBR system, for example, its architecture is
nonstandard, reusing knowledge in legacy CBR is deficient, ontology
construction is difficult, etc, we propose a novel approach for
semi-automatically construct ontology-based CBR system whose
architecture is based on two-layer ontology. Domain knowledge
implied in legacy case bases can be mapped from relational database
schema and knowledge items to relevant OWL local ontology
automatically by a mapping algorithm with low time-complexity. By
concept clustering based on formal concept analysis, computing
concept equation measure and concept inclusion measure, some
suggestions about enriching or amending concept hierarchy of OWL
local ontologies are made automatically that can aid designers to
achieve semi-automatic construction of OWL domain ontology.
Validation of the approach is done by an application example.
Abstract: Image compression plays a vital role in today-s
communication. The limitation in allocated bandwidth leads to
slower communication. To exchange the rate of transmission in the
limited bandwidth the Image data must be compressed before
transmission. Basically there are two types of compressions, 1)
LOSSY compression and 2) LOSSLESS compression. Lossy
compression though gives more compression compared to lossless
compression; the accuracy in retrievation is less in case of lossy
compression as compared to lossless compression. JPEG, JPEG2000
image compression system follows huffman coding for image
compression. JPEG 2000 coding system use wavelet transform,
which decompose the image into different levels, where the
coefficient in each sub band are uncorrelated from coefficient of
other sub bands. Embedded Zero tree wavelet (EZW) coding exploits
the multi-resolution properties of the wavelet transform to give a
computationally simple algorithm with better performance compared
to existing wavelet transforms. For further improvement of
compression applications other coding methods were recently been
suggested. An ANN base approach is one such method. Artificial
Neural Network has been applied to many problems in image
processing and has demonstrated their superiority over classical
methods when dealing with noisy or incomplete data for image
compression applications. The performance analysis of different
images is proposed with an analysis of EZW coding system with
Error Backpropagation algorithm. The implementation and analysis
shows approximately 30% more accuracy in retrieved image
compare to the existing EZW coding system.
Abstract: Iris-based biometric authentication is gaining importance
in recent times. Iris biometric processing however, is a complex
process and computationally very expensive. In the overall processing
of iris biometric in an iris-based biometric authentication system,
feature processing is an important task. In feature processing, we extract
iris features, which are ultimately used in matching. Since there
is a large number of iris features and computational time increases
as the number of features increases, it is therefore a challenge to
develop an iris processing system with as few as possible number of
features and at the same time without compromising the correctness.
In this paper, we address this issue and present an approach to feature
extraction and feature matching process. We apply Daubechies D4
wavelet with 4 levels to extract features from iris images. These
features are encoded with 2 bits by quantizing into 4 quantization
levels. With our proposed approach it is possible to represent an
iris template with only 304 bits, whereas existing approaches require
as many as 1024 bits. In addition, we assign different weights to
different iris region to compare two iris templates which significantly
increases the accuracy. Further, we match the iris template based on
a weighted similarity measure. Experimental results on several iris
databases substantiate the efficacy of our approach.
Abstract: It is by reason of the unified measure of varieties of resources and the unified processing of the disposal of varieties of resources, that these closely related three of new basic models called the resources assembled node and the disposition integrated node as well as the intelligent organizing node are put forth in this paper; the three closely related quantities of integrative analytical mechanics including the disposal intensity and disposal- weighted intensity as well as the charge of resource charge are set; and then the resources assembled space and the disposition integrated space as well as the intelligent organizing space are put forth. The system of fundamental equations and model of complete factor synergetics is preliminarily approached for the general situation in this paper, to form the analytical base of complete factor synergetics. By the essential variables constituting this system of equations we should set twenty variables respectively with relation to the essential dynamical effect, external synergetic action and internal synergetic action of the system.
Abstract: Classification of Persian printed numeral characters
has been considered and a proposed system has been introduced. In
representation stage, for the first time in Persian optical character
recognition, extended moment invariants has been utilized as
characters image descriptor. In classification stage, four different
classifiers namely minimum mean distance, nearest neighbor rule,
multi layer perceptron, and fuzzy min-max neural network has been
used, which first and second are traditional nonparametric statistical
classifier. Third is a well-known neural network and forth is a kind of
fuzzy neural network that is based on utilizing hyperbox fuzzy sets.
Set of different experiments has been done and variety of results has
been presented. The results showed that extended moment invariants
are qualified as features to classify Persian printed numeral
characters.
Abstract: This paper proposes rough set models with three
different level knowledge granules in incomplete information system
under tolerance relation by similarity between objects according to
their attribute values. Through introducing dominance relation on the
discourse to decompose similarity classes into three subclasses: little
better subclass, little worse subclass and vague subclass, it dismantles
lower and upper approximations into three components. By using
these components, retrieving information to find naturally hierarchical
expansions to queries and constructing answers to elaborative queries
can be effective. It illustrates the approach in applying rough set
models in the design of information retrieval system to access different
granular expanded documents. The proposed method enhances rough
set model application in the flexibility of expansions and elaborative
queries in information retrieval.
Abstract: Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.
Abstract: Given a parallel program to be executed on a heterogeneous
computing system, the overall execution time of the program
is determined by a schedule. In this paper, we analyze the worst-case
performance of the list scheduling algorithm for scheduling tasks
of a parallel program in a mixed-machine heterogeneous computing
system such that the total execution time of the program is minimized.
We prove tight lower and upper bounds for the worst-case
performance ratio of the list scheduling algorithm. We also examine
the average-case performance of the list scheduling algorithm. Our
experimental data reveal that the average-case performance of the list
scheduling algorithm is much better than the worst-case performance
and is very close to optimal, except for large systems with large
heterogeneity. Thus, the list scheduling algorithm is very useful in
real applications.
Abstract: Rapid steps made in the field of Information and Communication Technology (ICT) has facilitated the development of teaching and learning methods and prepared them to serve the needs of an assorted educational institution. In other words, the information age has redefined the fundamentals and transformed the institutions and method of services delivery forever. The vision is the articulation of a desire to transform the method of teaching and learning could proceed through e-learning. E-learning is commonly deliberated to use of networked information and communications technology in teaching and learning practice. This paper deals the general aspects of the e-leaning with its issues, developments, opportunities and challenges, which can the higher institutions own.
Abstract: This paper presents a software quality support tool, a
Java source code evaluator and a code profiler based on
computational intelligence techniques. It is Java prototype software
developed by AI Group [1] from the Research Laboratories at
Universidad de Palermo: an Intelligent Java Analyzer (in Spanish:
Analizador Java Inteligente, AJI). It represents a new approach to
evaluate and identify inaccurate source code usage and transitively,
the software product itself.
The aim of this project is to provide the software development
industry with a new tool to increase software quality by extending
the value of source code metrics through computational intelligence.
Abstract: Graph coloring is an important problem in computer
science and many algorithms are known for obtaining reasonably
good solutions in polynomial time. One method of comparing
different algorithms is to test them on a set of standard graphs where
the optimal solution is already known. This investigation analyzes a
set of 50 well known graph coloring instances according to a set of
complexity measures. These instances come from a variety of
sources some representing actual applications of graph coloring
(register allocation) and others (mycieleski and leighton graphs) that
are theoretically designed to be difficult to solve. The size of the
graphs ranged from ranged from a low of 11 variables to a high of
864 variables. The method used to solve the coloring problem was
the square of the adjacency (i.e., correlation) matrix. The results
show that the most difficult graphs to solve were the leighton and the
queen graphs. Complexity measures such as density, mobility,
deviation from uniform color class size and number of block
diagonal zeros are calculated for each graph. The results showed that
the most difficult problems have low mobility (in the range of .2-.5)
and relatively little deviation from uniform color class size.
Abstract: In this paper, a pipelined version of genetic algorithm,
called PLGA, and a corresponding hardware platform are described.
The basic operations of conventional GA (CGA) are made pipelined
using an appropriate selection scheme. The selection operator, used
here, is stochastic in nature and is called SA-selection. This helps
maintaining the basic generational nature of the proposed pipelined
GA (PLGA). A number of benchmark problems are used to compare
the performances of conventional roulette-wheel selection and the
SA-selection. These include unimodal and multimodal functions with
dimensionality varying from very small to very large. It is seen that
the SA-selection scheme is giving comparable performances with
respect to the classical roulette-wheel selection scheme, for all the
instances, when quality of solutions and rate of convergence are considered.
The speedups obtained by PLGA for different benchmarks
are found to be significant. It is shown that a complete hardware
pipeline can be developed using the proposed scheme, if parallel
evaluation of the fitness expression is possible. In this connection
a low-cost but very fast hardware evaluation unit is described.
Results of simulation experiments show that in a pipelined hardware
environment, PLGA will be much faster than CGA. In terms of
efficiency, PLGA is found to outperform parallel GA (PGA) also.
Abstract: Discrete particle swarm optimization (DPSO) is a
powerful stochastic evolutionary algorithm that is used to solve the
large-scale, discrete and nonlinear optimization problems. However,
it has been observed that standard DPSO algorithm has premature
convergence when solving a complex optimization problem like
transmission expansion planning (TEP). To resolve this problem an
advanced discrete particle swarm optimization (ADPSO) is proposed
in this paper. The simulation result shows that optimization of lines
loading in transmission expansion planning with ADPSO is better
than DPSO from precision view point.
Abstract: Distributed denial-of-service (DDoS) attacks pose a
serious threat to network security. There have been a lot of
methodologies and tools devised to detect DDoS attacks and reduce
the damage they cause. Still, most of the methods cannot
simultaneously achieve (1) efficient detection with a small number of
false alarms and (2) real-time transfer of packets. Here, we introduce
a method for proactive detection of DDoS attacks, by classifying the
network status, to be utilized in the detection stage of the proposed
anti-DDoS framework. Initially, we analyse the DDoS architecture
and obtain details of its phases. Then, we investigate the procedures
of DDoS attacks and select variables based on these features. Finally,
we apply the k-nearest neighbour (k-NN) method to classify the
network status into each phase of DDoS attack. The simulation result
showed that each phase of the attack scenario is classified well and
we could detect DDoS attack in the early stage.
Abstract: In this paper, we propose a dual version of the first
threshold ring signature scheme based on error-correcting code proposed
by Aguilar et. al in [1]. Our scheme uses an improvement of
Véron zero-knowledge identification scheme, which provide smaller
public and private key sizes and better computation complexity than
the Stern one. This scheme is secure in the random oracle model.
Abstract: Although the World Wide Web is considered the
largest source of information there exists nowadays, due to its
inherent dynamic characteristics, the task of finding useful and
qualified information can become a very frustrating experience. This
study presents a research on the information mining systems in the
Web; and proposes an implementation of these systems by means of
components that can be built using the technology of Web services.
This implies that they can encompass features offered by a services
oriented architecture (SOA) and specific components may be used by
other tools, independent of platforms or programming languages.
Hence, the main objective of this work is to provide an architecture
to Web mining systems, divided into stages, where each step is a
component that will incorporate the characteristics of SOA. The
separation of these steps was designed based upon the existing
literature. Interesting results were obtained and are shown here.
Abstract: The intent of this essay is to evaluate the effectiveness
of surge suppressor aimed at power supply used for automation
devices in power distribution system which is consist of MOV and
T type low-pass filter. Books, journal articles and e-sources related
to surge protection of power supply used for automation devices in
power distribution system were consulted, and the useful information
was organized, analyzed and developed into five parts: characteristics
of surge wave, protection against surge wave, impedance characteristics
of target, using Matlab to simulate circuit response after
5kV,1.2/50s surge wave and suggestions for surge protection. The
results indicate that various types of load situation have great impact
on the effectiveness of surge protective device. Therefore, type and
parameters of surge protective device need to be carefully selected,
and load matching is also vital to be concerned.
Abstract: Recently, various services such as television and the
Internet have come to be received through various terminals.
However, we could gain greater convenience by receiving these
services through cellular phone terminals when we go out and then
continuing to receive the same services through a large screen digital
television after we have come home. However, it is necessary to go
through the same authentication processing again when using TVs
after we have come home. In this study, we have developed an
authentication method that enables users to switch terminals in
environments in which the user receives service from a server through
a terminal. Specifically, the method simplifies the authentication of
the server side when switching from one terminal to another terminal
by using previously authenticated information.
Abstract: We present a method for fast volume rendering using
graphics hardware (GPU). To our knowledge, it is the first implementation
on the GPU. Based on the Shear-Warp algorithm, our
GPU-based method provides real-time frame rates and outperforms
the CPU-based implementation. When the number of slices is not
sufficient, we add in-between slices computed by interpolation. This
improves then the quality of the rendered images. We have also
implemented the ray marching algorithm on the GPU. The results
generated by the three algorithms (CPU-based and GPU-based Shear-
Warp, GPU-based Ray Marching) for two test models has proved that
the ray marching algorithm outperforms the shear-warp methods in
terms of speed up and image quality.
Abstract: This paper studies the dependability of componentbased
applications, especially embedded ones, from the diagnosis
point of view. The principle of the diagnosis technique is to
implement inter-component tests in order to detect and locate the
faulty components without redundancy. The proposed approach for
diagnosing faulty components consists of two main aspects. The first
one concerns the execution of the inter-component tests which
requires integrating test functionality within a component. This is the
subject of this paper. The second one is the diagnosis process itself
which consists of the analysis of inter-component test results to
determine the fault-state of the whole system. Advantage of this
diagnosis method when compared to classical redundancy faulttolerant
techniques are application autonomy, cost-effectiveness and
better usage of system resources. Such advantage is very important
for many systems and especially for embedded ones.