Software Clustering using Hybrid Multi-Objective Black Hole Algorithm

Abstract-Software clustering is the process of organizing software units into appropriate clusters so as to efficiently modularize complex program structure. In this paper, we investigate the use of hybrids of Black Hole algorithm (developed using weighted aggregation, auxiliary archive and Genetic Algorithm) to optimize multiple objectives for clustering of android mobile applications. It is empirically and statistically observed that multi-objective Black Hole algorithm when improved using Genetic Algorithm and auxiliary archive outperforms Two-Archive algorithm and its counterparts. Keywords-bio-inspired algorithm, edgesim, nature-inspired algorithm, serach based software engineering, software clsuterin

An optimized deep learning model for optical character recognition applications

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recognition applications; the proposed method was evaluated for performance in terms of computational accuracy, convergence analysis, and cost

Solving systems of transcendental equations involving the Heun functions

The Heun functions have wide application in modern physics and are expected to succeed the hypergeometrical functions in the physical problems of the 21st century. The numerical work with those functions, however, is complicated and requires filling the gaps in the theory of the Heun functions and also, creating new algorithms able to work with them efficiently. We propose a new algorithm for solving a system of two nonlinear transcendental equations with two complex variables based on the M\"uller algorithm. The new algorithm is particularly useful in systems featuring the Heun functions and for them, the new algorithm gives distinctly better results than Newton's and Broyden's methods. As an example for its application in physics, the new algorithm was used to find the quasi-normal modes (QNM) of Schwarzschild black hole described by the Regge-Wheeler equation. The numerical results obtained by our method are compared with the already published QNM frequencies and are found to coincide to a great extent with them. Also discussed are the QNM of the Kerr black hole, described by the Teukolsky Master equation.Comment: 17 pages, 4 figures. Typos corrected, one figure added, some sections revised. The article is a rework of the internal report arXiv:1005.537

Protector Control PC-AODV-BH in The Ad Hoc Networks

In this paper we deal with the protector control that which we used to secure AODV routing protocol in Ad Hoc networks. The considered system can be vulnerable to several attacks because of mobility and absence of infrastructure. While the disturbance is assumed to be of the black hole type, we purpose a control named "PC-AODV-BH" in order to neutralize the effects of malicious nodes. Such a protocol is obtained by coupling hash functions, digital signatures and fidelity concept. An implementation under NS2 simulator will be given to compare our proposed approach with SAODV protocol, basing on three performance metrics and taking into account the number of black hole malicious nodesComment: submit 15 pages, 19 figures, 1 table, Journal Indexing team, AIRCC 201

Characteristic Evolution and Matching

I review the development of numerical evolution codes for general relativity based upon the characteristic initial value problem. Progress in characteristic evolution is traced from the early stage of 1D feasibility studies to 2D axisymmetric codes that accurately simulate the oscillations and gravitational collapse of relativistic stars and to current 3D codes that provide pieces of a binary black hole spacetime. Cauchy codes have now been successful at simulating all aspects of the binary black hole problem inside an artificially constructed outer boundary. A prime application of characteristic evolution is to extend such simulations to null infinity where the waveform from the binary inspiral and merger can be unambiguously computed. This has now been accomplished by Cauchy-characteristic extraction, where data for the characteristic evolution is supplied by Cauchy data on an extraction worldtube inside the artificial outer boundary. The ultimate application of characteristic evolution is to eliminate the role of this outer boundary by constructing a global solution via Cauchy-characteristic matching. Progress in this direction is discussed.Comment: New version to appear in Living Reviews 2012. arXiv admin note: updated version of arXiv:gr-qc/050809