A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

“…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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An improved kernelization algorithm for r-Set Packing by Abu-Khzam, Faisal N.

“…Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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A method for the minimum coloring problem using genetic algorithms by Harmanani, Haidar

“…This paper presents a method to solve the graph coloring problem for arbitrary graphs using genetic algorithms. The graph coloring problem, an NP-hard problem, has important applications in many areas including time tabling and scheduling, frequency assignment, and reg ister allocation. …”
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Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

“…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

“…This paper presents a hardware implementation to solve the graph colouring problem (chromatic number χ(G)) for arbitrary graphs using the Hopfield neural network (HNN) model of computation. …”
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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

“…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System by Mohamed Ali Zeddini (22047920)

“…<p dir="ltr">The arbitrary selection of the Crow Search Algorithm (CSA) parameters, the Awareness Probability (AP) and the Flight Length (fl) results in poor convergence performance and efficiency even if the CSA performs well when solving global optimization problems. …”

Complexities of special matrix multiplication problems by Takche, J.

“…Efficient algorithms are also developed to multiply a tridiagonal matrix by an arbitrary matrix, and to multiply two tridiagonal matrices.…”
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Learn while tracking. (c2013) by Toukhtarian, Raffi

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Fast, effective vertex cover kernelization by Abu-Khzam, F.N.

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Crown Structures for Vertex Cover Kernelization by Abu-Khzam, Faisal N.

“…Crown structures in a graph are defined and shown to be useful in kernelization algorithms for the classic vertex cover problem. Two vertex cover kernelization methods are discussed. …”
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The architecture of a highly reconfigurable RISC dataflow array processor by Sait, Sadiq M.

“…The array can be programmed to execute arbitrary algorithms in both static and dynamic manner. …”
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Learn while Tracking by Saab, Samer S.

“…Arbitrary small settling time along with arbitrary small steady-state output error are studied. …”
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A quadratic kernel for 3-set packing by Abu-Khzam, Faisal N.

“…Such parameterized reductions are known as kernelization algorithms, and each reduced instance is called a problem kernel. …”
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Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

“…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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A MIMO Sampling-Rate-Dependent Controller by Saab, Samer S.

“…The SRD controller aims at achieving uniform output tracking in the sense of attaining arbitrary small steady-state errors as well as arbitrary small settling time. …”
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Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…Although our algorithm is sensitive to initialization errors, to the best of our knowledge, the resulting method is the first working solution for arbitrary large dimensions and arbitrary large observation errors while its computation throughput appears insignificant. …”
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Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…The numerical computation of open-channel flows requires preparing and processing larger volumes of boundary and bathymetry data for computer inputs and the development of numerical algorithms for treating complex boundary condition, channel properties, and free surface effects. …”
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