Showing 21 - 40 results of 42 for search '(( elements deer algorithm ) OR ((( data encoding algorithm ) OR ( data backing algorithm ))))', query time: 0.11s Refine Results
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    Transaction Dependency Based Approach for Database Damage Assessment Using a Matrix by Haraty, Ramzi Ahmed

    Published 2017
    “…Hence, both affected and benign transactions will be rolled back, which is a waste of time. This paper presents an algorithm that works efficiently to assess the damage caused in the database by malicious transaction and recovers it. …”
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  3. 23

    A Geometric-Primitives-Based Compression Scheme for Testing Systems-on-a-Chip by El-Maleh, Aiman H.

    Published 2001
    “…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data.…”
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  4. 24

    A geometric-primitives-based compression scheme for testingsystems-on-a-chip by El-Maleh, A.

    Published 2001
    “…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data…”
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    article
  5. 25

    STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

    Published 2025
    “…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …”
  6. 26

    Neural network-based failure rate prediction for De Havilland Dash-8 tires by Al-Garni, Ahmed Z.

    Published 2006
    “…An artificial neural network (ANN) model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the twolayered feed-forward back-propagation algorithm as a learning rule is developed. …”
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  7. 27

    NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES by Al-Garni, Ahmed Z.

    Published 2020
    “…One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …”
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    article
  8. 28

    Failure-Rate Prediction for De Havilland Dash-8 Tires Employing Neural-Network Technique by Al-Garni, Ahmed Z.

    Published 2006
    “…An artificial neural-network model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the two-layered feedforward back-propagation algorithm as a learning rule is developed. …”
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    article
  9. 29

    FAILURE RATE ANALYSIS OF BOEING 737 BRAKES EMPLOYING NEURAL NETWORK by Al-Garni, Ahmed Z.

    Published 2007
    “…One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …”
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    article
  10. 30

    Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks by Sharma, Neetan

    Published 2023
    “…A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. …”
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    Query acceleration in distributed database systems by Haraty, Ramzi A.

    Published 2001
    “…Query optimization strategies aim to minimize the cost of transferring data across networks. Many techniques and algorithms have been proposed to optimize queries. …”
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    Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers by Ali Sharida (17947847)

    Published 2023
    “…The DT is trained offline using a set of experimental data and updated online to get the maximum possible accuracy. …”
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    Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

    Published 2016
    “…We compare our models to others constructed using other well established techniques such as C4.5, Genetic Algorithms, Simulated Annealing, Tabu Search, multi-layer perceptron with back-propagation, multi-layer perceptron hybridized with ABC and the majority classifier. …”
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