Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

“…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …”
Get full text
Get full text

Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

Get full text

A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
Get full text
Get full text

Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population by Amr M. Fahmi (21632909)

“…To compare the accuracy of a clinical warfarin dosing (CWD) versus genetic warfarin dosing algorithms (GWD) during warfarin initiation. …”

A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

“…The method formulates the allocation problem using the clique partitioning problem, an NP-complete problem, and handles multicycle functional units as well as structural pipelining. The algorithm has a running time complexity of O(1) for a circuit with n operations and c shared resources. …”
Get full text
Get full text
Get full text

A Comparative Study of Elgamal Based Cryptographic Algorithms by Haraty, Ramzi A.

“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
Get full text
Get full text
Get full text

Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
Get full text
Get full text
Get full text
Get full text

Radial basis function networks for contingency analysis of bulkpower systems by Refaee, J.A.

“…The performance of the RBFN is compared with a standard AC load flow algorithm…”
Get full text
Get full text

New fault models and efficient BIST algorithms for dual-portmemories by Amin, A.A.

“…The testability problem of dual-port memories is investigated. A functional model is defined, and architectural modifications to enhance the testability of such chips are described. …”
Get full text
Get full text

Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…In this paper, a novel SD algorithm is presented based on the deep deterministic policy gradient (DDPG) agent; an off-policy reinforcement learning (RL) agent with a continuous action space. …”

Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…<p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. …”

A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. …”
Get full text
Get full text

A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation by Iman M. Hosseini Naveh (16891482)

“…<p>This paper presents a comprehensive evaluation of the effect of quasi oppositional - based learning method utilization in output tracking control through a swarm-based multivariable Proportional-Integral-Derivative (SMPID) controller, which is tuned by a novel performance index based on the step response characteristics in multi-input multi-output (MIMO) system. …”

A comparative study of RSA based digital signature algorithms by Haraty, Ramzi A.

“…We implement the classical and modified RSA cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we implement attack algorithms to solve the factorization problem in Z, Z[<i>i</i>] and F[<i>x</i>]. …”
Get full text
Get full text
Get full text
Get full text

A novel network-based SIS framework for improved GA performance by Tohme, Rawane

“…In analogy, we adapt this formulation to improve the performance of genetic algorithms. We represent the set of possible solutions to a complex optimization problem as interconnected nodes in a scale-free network. …”
Get full text
Get full text
Get full text

Improving the Secure Socket Layer Protocol by modifying its Authentication function by El-Kassar, A. N.

“…SSL uses three interdependent cryptographic functions to perform a secure connection. The first function is authentication. …”
Get full text
Get full text
Get full text
Get full text

Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…In this paper we perform a comparative study among GA, SA, and TS. These algorithms have many similarities, but they also possess distinctive features, mainly in their strategies for searching the solution state space. …”
Get full text

A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani (14590504)

“…In this paper, a multiswarm-intelligence-based algorithm (MSIA) is developed to cope with bound constrained functions. …”

Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm by Zerguine, A.

“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
Get full text
Get full text

A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

Get full text
Get full text