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  1. 21

    Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

    Published 1999
    “…The core of the proposed algorithm is based on genetic algorithms. Tabu search is used to generate new population members in the reproduction phase of the genetic algorithm. …”
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  2. 22

    A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

    Published 2020
    “…In the proposed algorithm, genetic algorithm solution is coded as a mix between binary and decimal representation. …”
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    article
  3. 23

    Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

    Published 2020
    “…The core of the proposed algorithm is based on genetic algorithms. Tabu search is used to generate new population members in the reproduction phase of the genetic algorithm. …”
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    article
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    A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security by Shitharth Selvarajan (14157976)

    Published 2024
    “…The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. …”
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    COMPUTER AIDED PROGRAMMING EDUCATION (CAPE) by Al-Sukairi, Abdallah

    Published 2020
    “…CAPE consists of problem definition and algorithm construction modules. Algorithm construction module is currently supported with a facility to map an algorithm(s) into FORTRAN or Pascal code. …”
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    article
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    UML-based regression testing for OO software by Mansour, Nashat

    Published 2010
    “…Previous techniques have been mainly code-based and several of them have addressed procedural programs. …”
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    Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

    Published 2022
    “…Seasonal thresholds are set for sensor values, and the algorithm detects hazardous trends when values exceed safe limits, correlating them with related sensors to generate combined variables and error codes. …”
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  15. 35

    Practical Multiple Node Failure Recovery in Distributed Storage Systems by Itani, M.

    Published 2016
    “…The fractional repetition (FR) code is a class of regenerating codes that consists of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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  16. 36

    Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

    Published 2019
    “…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
  17. 37

    Dynamic multiple node failure recovery in distributed storage systems by Itani, May

    Published 2018
    “…We present a range of results for our proposed algorithms in several scenarios to assess the effectiveness of the solution approaches that are shown to generate results close to optimal.…”
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    Common weaving approach in mainstream languages for software security hardening by Alhadidi, Dima

    Published 2013
    “…In the first approach, we prove them according to the rules and algorithms provided in this paper. In the second approach, we accommodate Kniesel's discipline that ensures that security solutions specified by our approach are applied at all and only the required points in source code, taking into consideration weaving interactions and interferences. …”
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  20. 40

    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed method in this paper is unique in that it converts the mechanical behaviour of shell structures into images that are then used to train a machine learning algorithm. This is achieved by mapping shell deformations and stresses to a set of images that are used to train a conditional generative adversarial network. …”