Kuwait City, Kuwait

American University of Kuwait

Kuwait City, Kuwait

The American University of Kuwait is a private liberal arts institution based on the American model of higher education in Kuwait City, Kuwait. Although established in 2003, the University opened to students, faculty and the general public in September 2004. It is sister colleges with Dartmouth College, in Hanover, New Hampshire. Professor Dr. Nizar Hamzeh currently serves the office of the President. Wikipedia.

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Zaher A.A.,American University of Kuwait
Midwest Symposium on Circuits and Systems | Year: 2017

This paper investigates the application of a recursive synchronization technique that can be applied to chaotic systems, using a single time series. The Unified system is used to exemplify the chaotic systems due to its versatile characteristics. The proposed method doesn't require the direct construction of an error signal between the measurable state and its estimate; thus, allowing for easily constructing a reduced-order state observer. Proving the stability of the synchronization mechanism is done using a systematic Lyapunov-based approach. Adjusting the decay rates of the synchronization errors is achieved by tuning of the proposed observation gains of the system. It is demonstrated that different sets of gains can be chosen to achieve a stable satisfactory performance, which is an added advantage to the proposed system. Different scenarios that include the Lorenz, the Lü, and the Chen systems are explored to provide a rich comparison between the proposed system and other synchronization techniques, reported in the literature. Extensions, improvements, and possible real-world applications are also discussed to complete the analysis of the recursive nature of the proposed system. © 2016 IEEE.

Damaj I.W.,American University of Kuwait
Midwest Symposium on Circuits and Systems | Year: 2017

Modern computing systems are hybrid in nature and employ various processing technologies that range from specific-To general-purpose processors. In co-design environments, specific-purpose processors, also known as hardware, work to support software implementations under general-purpose systems to create high-performance computers. Algorithms and computationally intensive tasks are partitioned among the different processing subsystems to achieve desirable degrees of parallel processing and performance characteristics. In this paper, a unified statistical performance analysis formulation is presented. The proposed statistical formulation combines the heterogeneous characteristics of both hardware and software implementations to provide grounds for thorough evaluations. The formulation includes the development of performance profiles, key indicators, and the composition of a master indicator based-on heterogeneous measurements. The investigation includes a case-study that targets a set of simple cryptographic algorithms. The two main targeted high performance computing devices are multicore processors for software implementations and high-end Field Programmable Gate Arrays for hardware implementations. © 2016 IEEE.

El-Abd M.,American University of Kuwait
Swarm and Evolutionary Computation | Year: 2016

Brain storm optimization (BSO) is a population-based metaheuristic algorithm that was recently developed to mimic the brainstorming process in humans. It has been successfully applied to many real-world engineering applications involving non-linear continuous optimization. In this work, we propose improving the performance of BSO by introducing a global-best version combined with per-variable updates and fitness-based grouping. In addition, the proposed algorithm incorporates a re-initialization scheme that is triggered by the current state of the population. The introduced Global-best BSO (GBSO) is compared against other BSO variants on a wide range of benchmark functions. Comparisons are based on final solutions and convergence characteristics. In addition, GBSO is compared against global-best versions of other meta-heuristics on recent benchmark libraries. Results prove that the proposed GBSO outperform previous BSO variants on a wide range of classical functions and different problem sizes. Moreover, GBSO outperforms other global-best meta-heuristic algorithms on the well-known CEC05 and CEC14 benchmarks. © 2017 Elsevier B.V.

El-Abd M.,American University of Kuwait
Information Sciences | Year: 2012

The class of foraging algorithms is a relatively new field based on mimicking the foraging behavior of animals, insects, birds or fish in order to develop efficient optimization algorithms. The artificial bee colony (ABC), the bees algorithm (BA), ant colony optimization (ACO), and bacterial foraging optimization algorithms (BFOA) are examples of this class to name a few. This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. To the best of our knowledge, most of the work conducted so far using foraging algorithms has been tested on classical functions. This work provides the comparison using the well-known CEC05 benchmark functions based on the solution reached, the success rate, and the performance rate. © 2011 Elsevier Inc. All rights reserved.

Khanafer M.,American University of Kuwait | Guennoun M.,University of Ottawa | Mouftah H.T.,University of Ottawa
IEEE Communications Surveys and Tutorials | Year: 2014

IEEE 802.15.4 is the de facto standard for Wireless Sensor Networks (WSNs) that outlines the specifications of the PHY layer and MAC sub-layer in these networks. The MAC protocol is needed to orchestrate sensor nodes access to the wireless communication medium. Although distinguished by a set of strengths that contributed to its popularity in various WSNs, IEEE 802.15.4 MAC suffers from several limitations that play a role in deteriorating its performance. Also, from a practical perspective, 80.15.4-based networks are usually deployed in the vicinity of other wireless networks that operate in the same ISM band. This means that 802.15.4 MAC should be ready to cope with interference from other networks. These facts have motivated efforts to devise improved IEEE 802.15.4 MAC protocols for WSNs. In this paper we provide a survey for these protocols and highlight the methodologies they follow to enhance the performance of the IEEE 802.15.4 MAC protocol. © 2014 IEEE.

El-Abd M.,American University of Kuwait
Genetic and Evolutionary Computation Conference, GECCO'11 | Year: 2011

The Artificial Bee Colony (ABC) algorithm is a relatively new algorithm for function optimization. The algorithm is inspired by the foraging behavior of honey bees. In this work, the performance of ABC is enhanced by introducing the concept of opposition-based learning. This concept is introduced through the initialization step and through generation jumping. The performance of the proposed opposition-based ABC (OABC) is compared to the performance of ABC and opposition-based Differential Evolution (ODE) when applied to the Black-Box Optimization Benchmarking (BBOB) library introduced in the previous two GECCO conferences. Copyright 2011 ACM.

El-Khasawneh B.S.,American University of Kuwait
Journal of Manufacturing Technology Management | Year: 2012

Purpose - The paradigm shift in global competition and the resulting business challenges have led manufacturing enterprises, particularly in the developing world, to take a different look at their operations. Responding to this climate meant reassessing their competitive advantage, and re-engineering their business models and operations. The purpose of this paper is to discuss many of these new challenges and present potential solutions from the practitioner point of view. Design/methodology/approach - This paper discusses many of these new challenges and presents potential solutions. The results are from interviews with the enterprise managers and owners. Findings - The issues are divided into three categories based on who can manipulate them: regional and international, national, and enterprise factors. The level of enterprises' ability to respond to these issues varies from full control to partial or no control. Nevertheless, issues' impact could be minimized by certain adopted polices and action plans. Practical implications - The paper creates a guiding compass for developing countries' manufacturing enterprises, by which they can navigate around the arising challenges, in a well-rounded, comprehensive overview. Originality/value - The paper lays a foundation for a road map for researchers and practitioners to assist small and medium-sized enterprises in becoming more competitive and improving their survivability, in a well-rounded, comprehensive way. © 2012 Emerald Group Publishing Limited.

Kadry S.,American University of Kuwait
AIP Conference Proceedings | Year: 2011

In this paper, we investigate the periodicity of the solutions of the stochastic system of rational difference equations xn= a/y n-p, yn = b/xn+p-2(p≥1), and we develop a new analytic technique to solve it, where a, b, x0 = N y0 = M are independent random variables. © 2011 American Institute of Physics.

El-Abd M.,American University of Kuwait
2013 IEEE Congress on Evolutionary Computation, CEC 2013 | Year: 2013

In this paper we test a hybrid Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithm on the CEC13 testbed. The hybridization technique is a component-based one, where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. © 2013 IEEE.

El-Abd M.,American University of Kuwait
Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 - Companion Publication | Year: 2010

This paper benchmarks the Artificial Bee Colony (ABC) algorithm using the noise-free BBOB 2010 testbed. The results show how this algorithm is highly successful in the separable and weak structured functions. © 2010 ACM.

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