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  1. 1

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

    Published 2017
    “…It is used to allow the client to identify the server and optionally allow the server to identify the client. The most common cryptographic algorithm used for this function is RSA. …”
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    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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    Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

    Published 2007
    “…A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. …”
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  6. 6

    From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

    Published 2023
    “…The effectiveness and dependability of the proposed hash function are evaluated by comparing it with two well-known hash algorithms, namely SHA-3 and SHA-2, as well as several other Chaos-based hash algorithms. …”
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    Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

    Published 2021
    “…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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    Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

    Published 2025
    “…<p dir="ltr">Speech denoising (SD) covers the algorithms that suppress the background noise from the contaminated speech and improve its clarity. …”
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    Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

    Published 2017
    “…Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”
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    A utility-based algorithm for joint uplink/downlink scheduling in wireless cellular networks by Saad, Walid

    Published 2012
    “…While most existing literature focuses on downlink-only or uplink-only scheduling algorithms, the proposed algorithm aims at ensuring a utility function that jointly captures the quality of service in terms of delay and channel quality on both links. …”
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  11. 11

    Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise by Saab, Samer S.

    Published 2005
    “…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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  12. 12

    Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

    Published 2023
    “…The results show an optimum resource allocation with an information-based cost function that is optimized by an Auction Algorithm.…”
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    A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

    Published 2024
    “…However, the present security measures cannot fully protect the IoT due to its vulnerability to malicious assaults. Intrusion detection can protect IoT devices from the most harmful attacks as a security tool. …”
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    Salp swarm algorithm: survey, analysis, and new applications by Abualigah, Laith

    Published 2024
    “…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…GA is enhanced by adding a multi-objective function, which selects the best features and achieves improved fitness outcomes to explore the essential features and helps minimize dimensions, enhance the true positive rate (TPR), and lower the false positive rate (FPR). …”
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    Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

    Published 2024
    “…The proposed technique offers an optimal solution with a lower cost with respect to conventional Voronoi-based techniques by effectively handling the issue of agents remaining stationary in regions void of information using a ranking function. The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”
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    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems by Agushaka, Jeffrey O.

    Published 2022
    “…The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.…”
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    Computational evluation of protein energy functions by Mansour, Nashat

    Published 2014
    “…A protein is characterized by its 3D structure, which defines its biological function. …”
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    Cross entropy error function in neural networks by Nasr, G.E.

    Published 2002
    “…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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