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  1. 1
    Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system

    Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system by Krishnan P.S., Kiong T.S., Koh J., Yap D.

    Published 2023
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  2. 2
    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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  3. 3
    High performance visualization of human tumor growth software

    High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

    Published 2008
    “…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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  4. 4
    High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems

    High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems by Pheng, H. S., Alias, Norma, Mohd. Said, Norfarizan

    Published 2007
    “…This paper focuses on the implementation of parallel algorithm for the simulation of brain tumours growth using one dimensional parabolic equation, design on a distributed parallel computer system. …”
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  5. 5
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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  6. 6
    High performance simulation for brain tumours growth using parabolic equation on heterogeneous parallel computer system

    High performance simulation for brain tumours growth using parabolic equation on heterogeneous parallel computer system by Pheng H. S., Norma Alias, Norfarizan Mohd Said

    Published 2007
    “…This paper focuses on the implementation of parallel algorithm for the simulation of brain tumours growth using one dimensional parabolic equation, design on a distributed parallel computer system. …”
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  7. 7
    WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm

    WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm by Prajindra S.K., Tiong S.K., Johnny Koh S.P., Yap D.F.W.

    Published 2023
    “…The algorithm works by finding the minimum transmitter power with the help of Distributed Parallel Genetic Algorithm (DPGA) employed on an offload microcontroller system to form optimal beam coverage to reduce power usage of adaptive antenna at WCDMA base station. …”
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  8. 8
    A critical analysis of simulators in grid

    A critical analysis of simulators in grid by Dakkak, Omar, Che Mohamed Arif, Ahmad Suki, Awang Nor, Shahrudin

    Published 2015
    “…In parallel and distributed computing environment such as "The Grid", anticipating the behavior of the resources and tasks based on certain scheduling algorithm is a great challenging.Thus, studying and improving these types of environments becomes very difficult. …”
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  9. 9
    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt

    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

    Published 2020
    “…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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  10. 10
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…In addition, a distributed environment is set up to conduct parallel optimization of the proposed method so that multi-local optimizations could be performed simultaneously. …”
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  11. 11
    A modified conjugate gradient coefficient with inexact line search for unconstrained optimization

    A modified conjugate gradient coefficient with inexact line search for unconstrained optimization by Mustafa, M., Aini, N., Rivaie, M

    Published 2016
    “…Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. …”
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  12. 12
    The convergence properties of a new hybrid conjugate gradient parameter for unconstrained optimization models

    The convergence properties of a new hybrid conjugate gradient parameter for unconstrained optimization models by Sulaiman, I.M, Mamat, M., Waziri, M.Y., Yakubu, U.A., Malik, M.

    Published 2021
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  13. 13
    A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application

    A Descent Three-Term Conjugate Gradient Direction For Problems Of Unconstrained Optimization With Application by Sulaiman M. Ibrahim, Nur Idalisa, Norhaslinda Zullpakka, P. Kaelo, Norrlaili Shapiee

    Published 2026
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  14. 14
    Performance analysis of a modified conjugate gradient algorithm for optimization models

    Performance analysis of a modified conjugate gradient algorithm for optimization models by S.E., Olowo, I. M., Sulaiman, M., Mamat, A.E., Owoyemi, M.A., Zaini, Kalfin, ., S. H., Yuningsih

    Published 2021
    “…The Conjugate gradient (CG) algorithms is very important and widely used in solving optimization models. …”
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  15. 15
    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…SGD uses random or batch data sets to compute gradient in solving optimization problems. It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
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  16. 16
    Automatic generic process migration system in linux

    Automatic generic process migration system in linux by Zarrabi, Amirreza

    Published 2012
    “…A fexible interface to the underlying checkpoint/ restart subsystem is designed which permits users to specify the migration mechanism according to process constraints. A migration algorithm is designed which attempts to exploit the unique features of the basic migration algorithms to form a generic algorithm. …”
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  17. 17
    New Quasi-Newton Equation And Method Via Higher Order Tensor Models

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…The global and local convergence properties of the new method on uniformly convex problems are also analyzed. …”
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  18. 18
    Towards optimal search: a modified secant method for efficient search in a big database

    Towards optimal search: a modified secant method for efficient search in a big database by M. Nomani, Kabir, Ali, Jahan, Alginahi, Yasser M., Benseghir, Hocine

    Published 2018
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  19. 19
    Application of sampling-based motion planning algorithms in autonomous vehicle navigation

    Application of sampling-based motion planning algorithms in autonomous vehicle navigation by Khaksar, Weria, Mohamed Sahari, Khairul Salleh, Tang, Sai Hong

    Published 2016
    “…In this chapter, a novel sampling-based navigation architecture is introduced, which employs the optimal properties of RRT* planner and the low running time property of low-dispersion sampling-based algorithms. …”
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  20. 20
    Hybrid DFP-CG method for solving unconstrained optimization problems

    Hybrid DFP-CG method for solving unconstrained optimization problems by Mustafa, Mamat, Wan Osman, W.F.H, Hery Ibrahim, M.A

    Published 2017
    “…The conjugate gradient (CG) method and quasi-Newton method are both well known method for solving unconstrained optimization method. …”
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