Abstract: Data mining incorporates a group of statistical
methods used to analyze a set of information, or a data set. It operates
with models and algorithms, which are powerful tools with the great
potential. They can help people to understand the patterns in certain
chunk of information so it is obvious that the data mining tools have
a wide area of applications. For example in the theoretical chemistry
data mining tools can be used to predict moleculeproperties or
improve computer-assisted drug design. Classification analysis is one
of the major data mining methodologies. The aim of thecontribution
is to create a classification model, which would be able to deal with a
huge data set with high accuracy. For this purpose logistic regression,
Bayesian logistic regression and random forest models were built
using R software. TheBayesian logistic regression in Latent GOLD
software was created as well. These classification methods belong to
supervised learning methods.
It was necessary to reduce data matrix dimension before construct
models and thus the factor analysis (FA) was used. Those models
were applied to predict the biological activity of molecules, potential
new drug candidates.
Abstract: There are two common methodologies to verify
signatures: the functional approach and the parametric approach. This
paper presents a new approach for dynamic handwritten signature
verification (HSV) using the Neural Network with verification by the
Conjugate Gradient Neural Network (NN). It is yet another avenue in
the approach to HSV that is found to produce excellent results when
compared with other methods of dynamic. Experimental results show
the system is insensitive to the order of base-classifiers and gets a
high verification ratio.
Abstract: Business transformation initiatives are required by
any organization to jump from its normal mode of operation to the
one that is suitable for the change in the environment such as
competitive pressures, regulatory requirements, changes in labor
market, etc., or internal such as changes in strategy/vision, changes in
the capability, change in the management, etc. Recent advances in
information technology in automating the business processes have
the potential to transform an organization to provide it with a
sustained competitive advantage. Process constitutes the skeleton of
a business. Thus, for a business to exist and compete well, it is
essential for the skeleton to be robust and agile. This paper details
“transformation" from a business perspective, methodologies to bring
about an effective transformation, process-based transformation, and
the role of services computing in this. Further, it details the benefits
that could be achieved through services computing.
Abstract: Fuzzy logic control (FLC) systems have been tested in
many technical and industrial applications as a useful modeling tool
that can handle the uncertainties and nonlinearities of modern control
systems. The main drawback of the FLC methodologies in the
industrial environment is challenging for selecting the number of
optimum tuning parameters.
In this paper, a method has been proposed for finding the optimum
membership functions of a fuzzy system using particle swarm
optimization (PSO) algorithm. A synthetic algorithm combined from
fuzzy logic control and PSO algorithm is used to design a controller
for a continuous stirred tank reactor (CSTR) with the aim of
achieving the accurate and acceptable desired results. To exhibit the
effectiveness of proposed algorithm, it is used to optimize the
Gaussian membership functions of the fuzzy model of a nonlinear
CSTR system as a case study. It is clearly proved that the optimized
membership functions (MFs) provided better performance than a
fuzzy model for the same system, when the MFs were heuristically
defined.
Abstract: Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.
Abstract: Many agent-oriented software engineering
methodologies have been proposed for software developing; however
their application is still limited due to their lack of maturity.
Evaluating the strengths and weaknesses of these methodologies
plays an important role in improving them and in developing new
stronger methodologies. This paper presents an evaluation framework
for agent-oriented methodologies, which addresses six major areas:
concepts, notation, process, pragmatics, support for software
engineering and marketability. The framework is then used to
evaluate the Gaia methodology to identify its strengths and
weaknesses, and to prove the ability of the framework for promoting
the agent-oriented methodologies by detecting their weaknesses in
detail.
Abstract: This paper explores how Critical Systems Thinking and Action Research can be used to improve student performance in Networking. When describing a system from a systems thinking perspective, the following aspects can be identified: the total system performance, the systems environment, the resources, the components and the management of the system. Following the history of system thinking we observe three emerged methodologies namely, hard systems, soft systems, and critical systems. This paper uses Critical Systems Thinking (CST) which describes systems in terms of contradictions and conflict. It demonstrates how CST can be used in an Action Research (AR) project to improve the performance of students. Intervention in terms of student assessment is discussed and the impact of the intervention is discussed.