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Karachi, Pakistan

Karachi Institute of Economics and Technology was established in 1997 with the aim of providing quality of education at affordable cost. Its academic programs are designed to prepare the students to meet the challenges of the nation and industry. KIET received the recognition by the Higher Education Commission vide letter no. 15-22/UGC-SEC/97/1291 dated 1 August 1998. HEC ranks KIET as 8th best university in Business/IT category.KIET was awarded a degree-granting status through a charter from the Government of Sindh on 24 May 2000. Wikipedia.


Naseem I.,Karachi Institute of Economics & Technology | Naseem I.,University of Western Australia | Togneri R.,University of Western Australia | Bennamoun M.,University of Western Australia
Pattern Recognition | Year: 2012

In this paper we address the problem of robust face recognition by formulating the pattern recognition task as a problem of robust estimation. Using a fundamental concept that in general, patterns from a single object class lie on a linear subspace (Barsi and Jacobs, 2003 [1]), we develop a linear model representing a probe image as a linear combination of class specific galleries. In the presence of noise, the well-conditioned inverse problem is solved using the robust Huber estimation and the decision is ruled in favor of the class with the minimum reconstruction error. The proposed Robust Linear Regression Classification (RLRC) algorithm is extensively evaluated for two important cases of robustness i.e. illumination variations and random pixel corruption. Illumination invariant face recognition is demonstrated on three standard databases under exemplary evaluation protocols reported in the literature. Comprehensive comparative analysis with the state-of-art illumination tolerant approaches indicates a comparable performance index for the proposed RLRC algorithm. The efficiency of the proposed approach in the presence of severe random noise is validated under several exemplary noise models such as dead-pixel problem, salt and pepper noise, speckle noise and Additive White Gaussian Noise (AWGN). The RLRC algorithm is found to be favorable compared with the benchmark generative approaches. © 2011 Elsevier Ltd. All rights reserved. Source


Ishaque K.,University of Technology Malaysia | Ishaque K.,Karachi Institute of Economics & Technology | Salam Z.,University of Technology Malaysia
IEEE Transactions on Industrial Electronics | Year: 2013

This paper proposes a deterministic particle swarm optimization to improve the maximum power point tracking (MPPT) capability for photovoltaic system under partial shading condition. The main idea is to remove the random number in the accelerations factor of the conventional PSO velocity equation. Additionally, the maximum change in velocity is restricted to a particular value, which is determined based on the critical study of $P$-$V$ characteristics during partial shading. Advantages of the method include: 1) consistent solution is achieved despite a small number of particles, 2) only one parameter, i.e., the inertia weight, needs to be tuned, and 3) the MPPT structure is much simpler compared to the conventional PSO. To evaluate the idea, the algorithm is implemented on a buck-boost converter and compared to the conventional hill climbing (HC) MPPT method. Simulation results indicate that the proposed method outperforms the HC method in terms of global peak tracking speed and accuracy under various partial shading conditions. Furthermore, it is tested using the measured data of a tropical cloudy day, which includes rapid movement of the passing clouds and partial shading. Despite the wide fluctuations in array power, the average efficiency for the 10-h test profile reaches 99.5%. © 1982-2012 IEEE. Source


Ishaque K.,Karachi Institute of Economics & Technology | Ishaque K.,University of Technology Malaysia | Salam Z.,University of Technology Malaysia
Renewable and Sustainable Energy Reviews | Year: 2013

This paper presents a review on the state-of-the-art maximum power point tracking (MPPT) techniques for PV power system applications. The main techniques that will be deliberated are the Perturb and Observe, Incremental Conductance and Hill Climbing. The coverage will also encompass their variations and adaptive forms. In addition, the more recent MPPT approaches using soft computing methods such as Fuzzy Logic Control, Artificial Neural Network and Evolutionary Algorithms are included. Whilst the paper provides as thorough treatment of MPPT at normal (uniform) insolation, its focus will be on the applications of the abovementioned techniques during partial shading conditions. It is envisaged that this review work will be a source of valuable information for PV professionals to keep abreast with the latest progress in this area, as well as for new researchers to get started on MPPT. © 2012 Elsevier Ltd. Source


Ducruet C.,CITES | Zaidi F.,Karachi Institute of Economics & Technology | Zaidi F.,French Institute for Research in Computer Science and Automation
Maritime Policy and Management | Year: 2012

The analysis of community structures is one major research field in the science of networks. This exercise is often biased by strong hierarchical configurations as it is the case in container shipping. After reviewing the multiple definitions of port systems, this paper applies a topological decomposition method to worldwide inter-port maritime links. Isolating ports of comparable size reveals hidden substructures with the help of graph visualization. While geographic proximity is one main explanatory factor in the emergence of port systems, other logics also appear, such as specialized and long-distance trading links. This research provides interesting evidence about the role of geography, technology and trade in the architecture of maritime networks. © 2012 Copyright Taylor and Francis Group, LLC. Source


Chin V.J.,University of Technology Malaysia | Salam Z.,University of Technology Malaysia | Ishaque K.,Karachi Institute of Economics & Technology
Applied Energy | Year: 2015

This review paper deliberates the important works on the modelling and parameters estimation of photovoltaic (PV) cells for PV simulation. It provides the concepts, features, and highlights the advantages and drawbacks of three main PV cell models, namely the single diode RS-, RP- and the two-diode. For the parameter estimation techniques, both the analytical and the soft computing approach are covered. A critical evaluation is carried out to summarize the performance of the models, while at the end, a summary of the future trend and direction of research is given. Since the literature on this subject is very large and dispersed, the availability a single cohesive and comprehensive document on the subject matter is crucial in order to piece the information together and understand the bigger picture. Therefore it is envisaged that this work will be convenient for new entrants as well as experienced researchers and practitioners to update their knowledge in the latest development in the area of PV modelling and simulation. © 2015 Elsevier Ltd. Source

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