Moni M.A.,University of Cambridge |
Moni M.A.,Bangladesh University |
Xu H.,University of Cambridge |
Lio P.,University of Cambridge
Bioinformatics | Year: 2015
Summary: CytoCom is an interactive plugin for Cytoscape that can be used to search, explore, analyse and visualize human disease comorbidity network. It represents disease-disease associations in terms of bipartite graphs and provides International Classification of Diseases, Ninth Revision (ICD9)-centric and disease name centric views of disease information. It allows users to find associations between diseases based on the two measures: Relative Risk (RR) and I-correlation values. In the disease network, the size of each node is based on the prevalence of that disease. CytoCom is capable of clustering disease network based on the ICD9 disease category. It provides user-friendly access that facilitates exploration of human diseases, and finds additional associated diseases by double-clicking a node in the existing network. Additional comorbid diseases are then connected to the existing network. It is able to assist users for interpretation and exploration of the human diseases by a variety of built-in functions. Moreover, CytoCom permits multi-colouring of disease nodes according to standard disease classification for expedient visualization. copy; 2014 © The Author 2014. Published by Oxford University Press. © The Author 2014. Published by Oxford University Press. All rights reserved.
Khan K.,Bangladesh University |
Akbar M.A.,University of Rajshahi
International Journal of Dynamical Systems and Differential Equations | Year: 2015
The paper employs the exp(-Φ(ξ))-expansion method for finding exact solutions of the Vakhnenko-Parkes (VP) equation. Each of the obtained solutions, namely hyperbolic function solutions, trigonometric function solutions, exponential function solutions and rational function solutions, contain an explicit function of the variables in the considered equation. It has been shown that the method provides a powerful mathematical tool for solving non-linear wave equations in mathematical physics and engineering problems. Copyright © 2014 Inderscience Enterprises Ltd.
Alam M.N.,Bangladesh University |
Akbar M.A.,University of Rajshahi |
Mohyud-Din S.T.,HITEC University
Chinese Physics B | Year: 2014
In this article, a novel (G′/G)-expansion method is proposed to search for the traveling wave solutions of nonlinear evolution equations. We construct abundant traveling wave solutions involving parameters to the Boussinesq equation by means of the suggested method. The performance of the method is reliable and useful, and gives more general exact solutions than the existing methods. The new (G′/G)-expansion method provides not only more general forms of solutions but also cuspon, peakon, soliton, and periodic waves. © 2014 Chinese Physical Society and IOP Publishing Ltd.
Alam M.N.,Bangladesh University
Results in Physics | Year: 2015
The new generalized (G'/G)-expansion method is an interesting approach to find new and more general exact solutions to the nonlinear evolution equations (NLEEs) in mathematical physics and engineering. In this paper, the method is applied to construct exact solutions involving parameters for the foam drainage equation. When these parameters are taken to be special values, the solitary wave solutions, the periodic wave and the rational function solutions are derived from exact solutions. These solutions might be imperative and significant for the explanation of some practical physical phenomena. It is shown that the method is an easy and advanced mathematical tool for solving NLEEs. © 2015 The Authors.
Chakrabortty R.K.,Rajshahi University of Engineering and Technology |
Akhtar Hasin M.A.,Bangladesh University
International Journal of Industrial Engineering Computations | Year: 2013
In hierarchical production planning system, Aggregate Production Planning (APP) falls between the broad decisions of long-range planning and the highly specific and detailed short-range planning decisions. This study develops an interactive Multi-Objective Genetic Algorithm (MOGA) approach for solving the multi-product, multi-period aggregate production planning (APP) with forecasted demand, related operating costs, and capacity. The proposed approach attempts to minimize total costs with reference to inventory levels, labor levels, overtime, subcontracting and backordering levels, and labor, machine and warehouse capacity. Here several genetic algorithm parameters are considered for solving NP-hard problem (APP problem) and their relative comparisons are focused to choose the most auspicious combination for solving multiple objective problems. An industrial case demonstrates the feasibility of applying the proposed approach to real APP decision problems. Consequently, the proposed MOGA approach yields an efficient APP compromise solution for large-scale problems. © 2012 Growing Science Ltd.