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  1. 1
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
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  2. 2
    Enhanced location and positioning in wimax networks with virtual mimo base station

    Enhanced location and positioning in wimax networks with virtual mimo base station by Othman, Muhammad Hakim

    Published 2015
    “…The SMBS algorithm with virtual base station utilizes both AOA and AOD measurement parameter (SMVirBS). …”
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    Thesis
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  3. 3
    ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation

    ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation by Hannan M.A., Abdolrasol M.G., Mohamed R., Al-Shetwi A., Ker P., Begum R., Muttaqi K.

    Published 2023
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  4. 4
    A review energy-efficient task scheduling algorithms in cloud computing

    A review energy-efficient task scheduling algorithms in cloud computing by Atiewi S., Yussof S., Ezanee M., Almiani M.

    Published 2023
    Conference Paper
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  5. 5
    Artificial Bee Colony Algorithm for Pairwise Test Generation

    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…In a case where PABC is not at its optimal stage or its best performance, the experiments of a test case are effectively competitive. PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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  6. 6
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  7. 7
    Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman

    Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman by Osman, Noor Diyana

    Published 2014
    “…The MAC algorithm was developed in MATLAB environment and was applied on virtual sinogram which directly computed through forward projection of CT images. …”
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  8. 8
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
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  9. 9
    Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels

    Compressed channel estimation for massive MIMO-OFDM systems over doubly selective channels by Uwaechia, Anthony Ngozichukwuka, Mahyuddin, Nor Muzlifah, Ain, Mohd Fadzil, Abdul Latiff, Nurul Muazzah, Za'bah, Nor Farahidah

    Published 2019
    “…Furthermore, we leverage the sparse nature of the massive MIMO-OFDM system to formulate the quantized AoDs estimation into a block-sparse signal recovery problem, where the measurement matrix is designed based on the estimated virtual AoD. Thus, a new algorithm namely, generalized quasi-block simultaneous orthogonal matching pursuit (gQBSO), is introduced to solve the problem by providing sparse signal reconstruction solution. …”
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  10. 10
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…To overcome this problem, fuzzy memberships have been employed to find optimal parameters. Since fuzzy clustering methods such as the fuzzy c-means and fuzzy G – K are computationally exhaustive in terms of time and memory requirements, a hierarchical approach have also been used in this work for their implementation. …”
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