Universiti Teknologi Malaysia

About: Universiti Teknologi Malaysia is a education organization based out in Johor Bahru, Malaysia. It is known for research contribution in the topics: Membrane & Control theory. The organization has 21644 authors who have published 39500 publications receiving 520635 citations.

Plant-driven removal of heavy metals from soil: uptake, translocation, tolerance mechanism, challenges, and future perspectives

Abstract: Increasing heavy metal (HM) concentrations in the soil have become a significant problem in the modern industrialized world due to several anthropogenic activities. Heavy metals (HMs) are non-biodegradable and have long biological half lives; thus, once entered in food chain, their concentrations keep on increasing through biomagnification. The increased concentrations of heavy metals ultimately pose threat on human life also. The one captivating solution for this problem is to use green plants for HM removal from soil and render it harmless and reusable. Although this green technology called phytoremediation has many advantages over conventional methods of HM removal from soils, there are also many challenges that need to be addressed before making this technique practically feasible and useful on a large scale. In this review, we discuss the mechanisms of HM uptake, transport, and plant tolerance mechanisms to cope with increased HM concentrations. This review article also comprehensively discusses the advantages, major challenges, and future perspectives of phytoremediation of heavy metals from the soil.

Evolutionary techniques in optimizing machining parameters

Abstract: Highlights? Several evolutionary techniques are reviewed to optimize machining parameter. ? It was found that genetic algorithm was widely applied by researchers. ? The most employed machining operation was multipass-turning. ? The most considered machining performance was surface roughness. In highly competitive manufacturing industries nowadays, the manufactures ultimate goals are to produce high quality product with less cost and time constraints. To achieve these goals, one of the considerations is by optimizing the machining process parameters such as the cutting speed, depth of cut, radial rake angle. Recently, alternative to conventional techniques, evolutionary optimization techniques are the new trend for optimization of the machining process parameters. This paper gives an overview and the comparison of the latest five year researches from 2007 to 2011 that used evolutionary optimization techniques to optimize machining process parameter of both traditional and modern machining. Five techniques are considered, namely genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO), ant colony optimization (ACO) and artificial bee colony (ABC) algorithm. Literature found that GA was widely applied by researchers to optimize the machining process parameters. Multi-pass turning was the largest machining operation that deals with GA optimization. In terms of machining performance, surface roughness was mostly studied with GA, SA, PSO, ACO and ABC evolutionary techniques.