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Skyllas-Kazacos M.,University of New South Wales | Chakrabarti M.H.,University of Malaya | Hajimolana S.A.,University of Malaya | Mjalli F.S.,Sultan Qaboos University | Saleem M.,Karachi Institute of Power Engineering
Journal of the Electrochemical Society | Year: 2011

The past few decades have shown a rapid and continuous exhaustion of the available energy resources which may lead to serious energy global crises. Researchers have been focusing on developing new and renewable energy resources to meet the increasing fuel demand and reduce greenhouse gas emissions. A surge of research effort is also being directed towards replacing fossil fuel based vehicles with hybrid and electric alternatives. Energy storage is now seen as a critical element in future smart grid and electric vehicle applications. Electrochemical energy storage systems offer the best combination of efficiency, cost and flexibility, with redox flow battery systems currently leading the way in this aspect. In this work, a panoramic overview is presented for the various redox flow battery systems and their hybrid alternatives. Relevant published work is reported and critically discussed. A comprehensive study of the available technologies is conducted in terms of technical aspects as well as economic and environmental consequences. Some of the flow battery limitations and technical challenges are also discussed and a range of further research opportunities are presented. Of the flow battery technologies that have been investigated, the all-vanadium redox flow battery has received the most attention and has shown most promise in various pre-commercial to commercial stationary applications to date, while new developments in hybrid redox fuel cells are promising to lead the way for future applications in mechanically and electrically refuelable electric vehicles. © 2011 The Electrochemical Society. Source


Hussain A.,Asian Institute of Technology | Afzulpur N.,Asian Institute of Technology | Ashraf M.W.,Asian Institute of Technology | Tayyaba S.,Asian Institute of Technology | Abbasi A.R.,Karachi Institute of Power Engineering
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2011

Research on Human-Computer-Interaction (HCI) technology is gaining popularity from last few years. In this paper, the results of our proposed low-level gesture detection module have been presented. This module may serve as a building block for a real-time gesture identification and mental state prediction system. The system has four major processing modules such as skin blob detection module, skin blob tracking module, gesture recognition module and mental state prediction module. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE). Source


Saleem M.,Karachi Institute of Power Engineering | Chakrabarti M.H.,University of Malaya | Irfan M.F.,University of Malaya | Hajimolana S.A.,University of Malaya | And 3 more authors.
International Journal of Electrochemical Science | Year: 2011

Electrokinetic remediation of nickel from low permeability soil using titanium electrodes having inter-electrode spacing of 10 cm was carried out in a cylindrical reactor. The influences of current density, voltage gradient and electrolyte pH were investigated upon removal efficiency for 60 h experimental runs. Efficiency improved from 49.3% to 57.2% when the current density was increased from 4.36 mA/cm2 to 13.1 mA/cm2. Furthermore, an enhancement in efficiency from 38.5% to 54.3% was observed when voltage gradient increased from 1 V/cm to 2 V/cm (at 13.1 mA/cm2). Further increase in voltage gradient to 2.5 V/cm improved efficiency during initial runs. However, an overall reduction of 3.2% was observed after 60 h of operation in comparison to that obtained at 2 V/cm. This may be attributed to precipitation and localized accumulation of metallic ions. An inverse relationship between efficiency and electrolyte pH was also observed (at 13.1 mA/cm2 and 2 V/cm). Although a removal of 74.1% was achieved at pH = 4.5, the system required optimization as the nickel content in treated soil was above the maximum values given in international standards. © 2011 by ESG. Source


Chakrabarti M.H.,University of Malaya | Ali M.,NED University of Engineering and Technology | Baroutian S.,University of Malaya | Saleem M.,Karachi Institute of Power Engineering
Process Safety and Environmental Protection | Year: 2011

Eruca sativa L. (known as taramira in South Asia) oil biodiesel shows good fuel properties when tested against ASTM D 6751 standard. Environmental performance of taramira oil B10 (10% (v/v) biodiesel blends with mineral diesel fuel, which is based upon the target set by the Government of Pakistan for 2025) in terms of engine exhaust emissions of CO2, CO, SO2, NOX and PM10 is compared with jatropha, castor and canola oil B10 fuels and found to be better. However, its calorific value is low thus resulting in poor engine performance in comparison to other B10 fuels. In addition, due to the high cost of taramira oil at present, it is not economical to produce in comparison to jatropha biodiesel. Study suggested that these drawbacks may be circumvented by growing taramira plants on large scale on marginal lands across South Asian countries and conducting further research to increase its calorific value. © 2010 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Source


Abbasi A.R.,Karachi Institute of Power Engineering | Hussain A.,Asian Institute of Technology | Afzulpurkar N.V.,Asian Institute of Technology
ECTI-CON 2010 - The 2010 ECTI International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology | Year: 2010

Affective computing systems with situated or ambient intelligence could be extremely effective in various application scenarios. However, majority of the proposed systems have limited utility since either they are strictly context-sensitive or otherwise too general. In this paper, we report on building and evaluating a context-aware yet situation-adaptive Bayesian inference framework that predicts human mental states in varying contexts.We use real and synthetic data to validate our hypothesis by modeling a three-layered Bayesian network (BN). We test this BN with two, and three context scenario, incrementally. The network gives an accuracy of above 85%. Thus, the framework may be utilized for multiple contexts, in variety of affective computing application scenarios. Source

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