Muhammad Arif Abdul Rahim

Bio: Muhammad Arif Abdul Rahim is an academic researcher from Universiti Teknologi Malaysia. The author has contributed to research in topics: Electrical discharge machining & Machining. The author has an hindex of 6, co-authored 16 publications receiving 703 citations. Previous affiliations of Muhammad Arif Abdul Rahim include Universiti Tun Hussein Onn Malaysia & Carleton University.

A study of the contribution of nearest-neighbour thermodynamic parameters to the DNA sequences generated by ant colony optimisation

Abstract: The process of designing a set of good DNA sequences is an essential problem and one of the most practical and important research topics in DNA-based computing and the DNA nanotechnology area. In this field of research, a DNA sequence design problem is defined as a multi-objective problem, and it is evaluated using four objective functions, h-measure, similarity, continuity and hairpin. In addition, two constraints, GC content and melting temperature (Tm), are used to maintain uniform chemical characteristics of the sequences. In the authors' previous research, an ant colony system (ACS) was proposed to solve the DNA sequence design problem based on nearest neighbour. The Watson-Crick base pair ΔGo37 was used as the distance between nodes for the thermodynamic parameters in the problem models for the heuristic approach in the ACS algorithms. In the current study, a non-heuristic approach and four new models using the heuristic approach are proposed, and results from the models are compared.

A comprehensive survey on gravitational search algorithm

Abstract: Gravitational Search Algorithm (GSA) is an optimization method inspired by the theory of Newtonian gravity in physics. Till now, many variants of GSA have been introduced, most of them are motivated by gravity-related theories such as relativity and astronomy. On the one hand, to solve different kinds of optimization problems, modified versions of GSA have been presented such as continuous (real), binary, discrete, multimodal, constraint, single-objective, and multi-objective GSA. On the other hand, to tackle the difficulties in real-world problems, the efficiency of GSA has been improved using specialized operators, hybridization, local search, and designing the self-adaptive algorithms. Researchers have utilized GSA to solve various engineering optimization problems in diverse fields of applications ranging from electrical engineering to bioinformatics. Here, we discussed a comprehensive investigation of GSA and a brief review of GSA developments in solving different engineering problems to build up a global picture and to open the mind to explore possible applications. We also made a number of suggestions that can be undertaken to help move the area forward.

Comparison of Global Food Traceability Regulations and Requirements

Abstract: The food traceability regulations of 21 Organization for Economic Co-Operation and Development (OECD) countries were examined with attention to whether these regulations are comprehensive for all food commodities and processed foods. The countries were evaluated based on responses to a series of questions that were developed to allow assessment of their traceability programs. The questions sought background information on whether: mandatory traceability regulation(s) exists at the national level within a given country; regulations include imported products, and the nature of required documentation for imports; an electronic database(s) for traceability exists and, if present, its accessibility; and labeling regulations allow consumer access and understanding of traceability. The examination ranked the countries that have specific traceability regulations for all commodities, both domestic and imports, as "Progressive," while countries with less broad or stringent regulations were ranked as "Moderate," and countries that were still in the developmental stage of mandatory or industry-led traceability requirements were ranked as "Regressive." Aggregate scores were developed from all of the rankings, determined on the basis of the questions, for each of the 21 countries, to provide an overall world ranking score. The aggregate scores were "Superior," "Average," or "Poor."

Assessment of Soil Heavy Metal Pollution with Principal Component Analysis and Geoaccumulation Index

Abstract: The assessment of pollution levels of heavy metals soil contamination is significant to human health and environmental management. The purpose of this article is to apply two methods, which are Principal component analysis (PCA) and Geoaccumulation index ( I geo ), to assess heavy metals contamination levels in the area around copper mine tailing, and to compare the results with Hakanson potential ecological risk index techniques (RI). The rank of soil Cd pollution levels, which is assessed using I geo , is consistent with the one by RI, while the PCA assessments result of comprehensive contamination level in soil discrepancy with RI and I geo . PCA concerned with the distribution of all elements in soil, while I geo and RI are mainly determined by the elements with high concentration or big Toxic Response Factor value. The combined application of PCA and I geo can effectively identify the comprehensive and single pollution levels of elements in soil, thus important to the extent determination of heavy metals pollution in soil.