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Rasheed A.,Mohammad Ali Jinnah University | Ajmal S.,Center for Advanced Studies in Engineering | Qayyum A.,Mohammad Ali Jinnah University
The Scientific World Journal | Year: 2014

High relative node velocity and high active node density have presented challenges to existing routing approaches within highly scaled ad hoc wireless networks, such as Vehicular Ad hoc Networks (VANET). Efficient routing requires finding optimum route with minimum delay, updating it on availability of a better one, and repairing it on link breakages. Current routing protocols are generally focused on finding and maintaining an efficient route, with very less emphasis on route update. Adaptive route update usually becomes impractical for dense networks due to large routing overheads. This paper presents an adaptive route update approach which can provide solution for any baseline routing protocol. The proposed adaptation eliminates the classification of reactive and proactive by categorizing them as logical conditions to find and update the route. © 2014 Asim Rasheed et al. Source


Khan I.,Center for Advanced Studies in Engineering
IEEE Transactions on Multimedia | Year: 2014

Non-rigid structure-from-motion is one of the difficult and challenging problems in computer vision, especially when the only input available is 2D correspondences in monocular video sequence. This paper proposed a new constraint based framework for underconstrained non-rigid structure-from-motion problem to constrain the space of solution. The proposed method is based on a point trajectory approach with an additional uniqueness constraint applied to shape coefficients to reduce the basis required to construct the non-rigid 3D shape. A framework for occluded and incomplete measured data is also proposed using low rank matrix fitting which is a robust factorization scheme for the matrix completion problem. This method offers not only new theoretical insight, but also a practical, everyday solution, to non-rigid structure-from-motion. The proposed method is positively compared to the state-of-the-art in non-rigid structure-from-motion, providing improved results on high-frequency deformations of both articulated and simpler deformable shapes. © 1999-2012 IEEE. Source


Iqbal M.,Center for Advanced Studies in Engineering | Bhatti A.I.,Mohammad Ali Jinnah University | Ayubi S.I.,Mohammad Ali Jinnah University | Ayubi S.I.,University of Leicester | Khan Q.,Mohammad Ali Jinnah University
IEEE Transactions on Industrial Electronics | Year: 2011

This paper presents the design, simulation, and experimental results of a new scheme for the robust parameter estimation of uncertain nonlinear dynamic systems. The technique is established on the estimation of robust time derivatives using a variable-structure differentiator observer. A second-order sliding motion is established along designed sliding manifolds to estimate the time derivatives of flat outputs and inputs, leading to better tracking performance of estimates during transients. The parameter convergence and accuracy analysis is rigorously explored systematically for the proposed class of estimators. The proposed method is validated using two case studies; first, the parameters of an uncertain nonlinear system with known, but uncertain nominal parametric values are estimated to demonstrate the convergence, accuracy, and robustness of the scheme; in the second application, the experimental parameter estimation of an onboard-diagnosis-II-compliant automotive vehicle engine is presented. The estimated parameters of the automotive engine are used to tune the theoretical mean value engine model having inaccuracies due to modeling errors and approximation assumptions. The resulting dynamics of the tuned engine model matches exactly with experimental engine data, verifying the accuracy of the estimates. © 2011 IEEE. Source


Rizvi M.A.,Mohammad Ali Jinnah University | Bhatti Sr. A.I.,Mohammad Ali Jinnah University | Butt Q.R.,Center for Advanced Studies in Engineering
IEEE Transactions on Industrial Electronics | Year: 2011

This paper proposes a novel hybrid model for an internal combustion engine, with the power generated due to combustion as the input and the crankshaft speed fluctuations as the output. The individual cylinders of the engine are considered as subsystems for which a nonlinear model, based on the physical principles, is derived. The proposed model is linearized at an operating point, and a switched linear model is formed. The simulation results of the proposed model are validated by matching the results with the experimentally observed data. Using the properties of the validated model, it is shown that the crankshaft speed variations observed in the engine are a Markov process. A novel algorithm that is based on the Markov chain is proposed to detect the misfire in the spark ignition engines. In the ensuing engine rig experiments, an igniter misfire is introduced in the system and is successfully detected. The analysis of the data shows that the engine also has an air leakage in a cylinder (a developing misfire), which is experimentally confirmed later. © 2009 IEEE. Source


Saleem M.,Center for Advanced Studies in Engineering | Di Caro G.A.,Istituto Dalle Molle di Studi sullIntelligenza Artificiale | Farooq M.,National University of Computer and Emerging Sciences
Information Sciences | Year: 2011

Swarm intelligence is a relatively novel field. It addresses the study of the collective behaviors of systems made by many components that coordinate using decentralized controls and self-organization. A large part of the research in swarm intelligence has focused on the reverse engineering and the adaptation of collective behaviors observed in natural systems with the aim of designing effective algorithms for distributed optimization. These algorithms, like their natural systems of inspiration, show the desirable properties of being adaptive, scalable, and robust. These are key properties in the context of network routing, and in particular of routing in wireless sensor networks. Therefore, in the last decade, a number of routing protocols for wireless sensor networks have been developed according to the principles of swarm intelligence, and, in particular, taking inspiration from the foraging behaviors of ant and bee colonies. In this paper, we provide an extensive survey of these protocols. We discuss the general principles of swarm intelligence and of its application to routing. We also introduce a novel taxonomy for routing protocols in wireless sensor networks and use it to classify the surveyed protocols. We conclude the paper with a critical analysis of the status of the field, pointing out a number of fundamental issues related to the (mis) use of scientific methodology and evaluation procedures, and we identify some future research directions. © 2011 Elsevier Inc. All rights reserved. Source

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