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Mohammed M.J.,University Putra Malaysia | Rakhimov I.S.,University Putra Malaysia | Shitan M.,Institute for Mathematical Research INSPEM | Ibrahim R.W.,University of Malaya | Mohammed N.F.,University Putra Malaysia
Saudi Journal of Biological Sciences | Year: 2015

Smoking problem is considered as one of the hot topics for many years. In spite of overpowering facts about the dangers, smoking is still a bad habit widely spread and socially accepted. Many people start smoking during their gymnasium period. The discovery of the dangers of smoking gave a warning sign of danger for individuals. There are different statistical methods used to analyze the dangers of smoking. In this study, we apply an algebraic statistical method to analyze and classify real data using Markov basis for the independent model on the contingency table. Results show that the Markov basis based classification is able to distinguish different date elements. Moreover, we check our proposed method via information theory by utilizing the Shannon formula to illustrate which one of these alternative tables is the best in term of independent. © 2015 The Authors.

Djauhari M.A.,Institute for Mathematical Research INSPEM | Lee G.S.,University of Technology Malaysia
ICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings | Year: 2015

Stocks market is a complex system. To understand its behavior, random matrix theory and/or graph theory are/is usually used. In this paper, the latter is used to analyze the dynamics of correlations network at New York Stock Exchange (NYSE) during global crisis in 2008. For that purpose, first, correlations network stability is tested. Second, complex network representation is provided to study the correlations network dynamics and their minimal spanning tree (MST) is constructed to study the evolution of network topological properties. Some changes of these properties in terms of stock's degree and graph diameter will be highlighted to demonstrate the advantages of complex network approach. © 2015 IEEE.

Husain S.K.S.,Institute for Mathematical Research INSPEM | Hassan M.A.,Institute for Mathematical Research INSPEM | Rakhimov I.S.,Institute for Mathematical Research INSPEM
AIP Conference Proceedings | Year: 2010

The paper aims to investigate the classification problem of 5 th dimensional complex filiform Leibniz algebras. There are two sources to get classification of filiform Leibniz algebras. The first of them is the naturally graded non-Lie filiform Leibniz algebras and another one is the naturally graded filiform Lie algebras. Here we consider Leibniz algebras appearing both sources. It is known that this class in its turn can be split into three subclasses, first and second classes are non-Lie filiform Leibniz algebras while the third class include the filiform Lie algebra. However, isomorphisms within each class were not investigated there. In this paper we propose an approach to the isomorphism problem in terms of invariants. Using this approach we give the complete classification of one of the above mentioned of complex filiform Leibniz algebras in 5 th dimension. © 2010 American Institute of Physics.

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