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  1. 1
    Dynamic communication performance enhancement in hierarchical torus network by selection algorithm

    Dynamic communication performance enhancement in hierarchical torus network by selection algorithm by Rahman, M.M. Hafizur, Sato, Yukinori, Inoguchi, Yasushi

    Published 2012
    “…This paper addresses three adaptive routing algorithms -- link-selection, channel-selection, and a combination of link-selection and channel-selection -- for the efficient use of physical links and virtual channels of an HTN to enhance dynamic communication performance. …”
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  2. 2
    Routing performance enhancement in hierarchical torus network by link-selection algorithm

    Routing performance enhancement in hierarchical torus network by link-selection algorithm by Rahman, M.M. Hafizur, Horiguchi, Susumu

    Published 2005
    “…We find that the dynamic communication performance of an HTN using the link-selection algorithm is better than when the dimension-order routing algorithm is used.…”
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  3. 3
    Butterfly traffic pattern in selection algorithm on hierarchical torus network

    Butterfly traffic pattern in selection algorithm on hierarchical torus network by Rahman, M.M. Hafizur, Akhand, M. A. H, Shill, P.C., Inoguchi, Yasushi

    Published 2015
    “…The combination of link selection and channel selection (LS+CS) algorithm improves the dynamic communication performance of the HTN by efficient use of physical links and virtual channels. …”
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  4. 4
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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  5. 5
    Adaptive routing algorithms and implementation for TESH network

    Adaptive routing algorithms and implementation for TESH network by Miura, Yasuyuki, Kaneko, Masahiro, Rahman, M.M. Hafizur, Watanabe, Shigeyoshi

    Published 2013
    “…Thus, those algorithms can also be applied to TESH network. We have proposed three adaptive routing algorithms—channel-selection, link-selection, and dynamic dimension reversal—for the efficient use of network resources of a TESH network to improve dynamic communication performance. …”
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  6. 6
    The non-uniform communication performance of adaptive routing for hierarchical interconnection network for 3D VLSI

    The non-uniform communication performance of adaptive routing for hierarchical interconnection network for 3D VLSI by Miura, Yasuyuki, Watanabe, Shigeyoshi, Rahman, M.M. Hafizur

    Published 2015
    “…Thus, those algorithms can also be applied to TESH network. We have proposed three adaptive routing algorithms - channel-selection, link-selection, and dynamic dimension reversal - for the efficient use of network resources of a TESH network to improve dynamic communication performance. …”
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  7. 7
    A cost and delay estimation of a suite of low-cost adaptive routers for hierarchical torus network

    A cost and delay estimation of a suite of low-cost adaptive routers for hierarchical torus network by Rahman, M.M. Hafizur, Akhand, M. A. H

    Published 2012
    “…Three deadlock-free adaptive routing algorithms called link-selection, channel-selection, and a combination of link-selection and channel-selection was proposed for the efficient use of physical links and virtual channels of an HTN to improve dynamic communication performance. …”
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  8. 8
    Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications

    Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications by Teo, Chee Huat

    Published 2016
    “…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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  9. 9
    Classification of herbs plant diseases via hierarchical dynamic artificial neural network

    Classification of herbs plant diseases via hierarchical dynamic artificial neural network by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2010
    “…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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  10. 10
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…Besides, Extended Kalman Filter (EKF) algorithm was selected in this project as an algorithm for offline estimation data purposes. …”
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  11. 11
    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework

    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2011
    “…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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  12. 12
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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  13. 13
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…As the 50-50 probabilities for exploitation and exploration in the basic teaching learning-based optimization algorithm may be counterproductive, the Mamdani-type fuzzy inference system of the new algorithm takes these measures as a crisp inputs and generates selection as crisp output to choose either exploitation or exploration based on the current search requirement. …”
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  14. 14
    Development of cell formation algorithm and model for cellular manufacturing system

    Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

    Published 2011
    “…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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  15. 15
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This improved algorithm, known as the edge-template Contour Delineation (etCD), is based on the fusion of edge detection with corner-template detection and dynamic thresholding to produce enhanced edge map. …”
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  16. 16
    The development of semantic meta-database: an ontology based semantic integration of biological databases

    The development of semantic meta-database: an ontology based semantic integration of biological databases by Samsudin, Ruhaidah, Deris, Safaai, Othman, Muhammad Razib, Md. Illias, Rosli

    Published 2007
    “…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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    Monograph
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  17. 17
    Navigation and motion control techniques for surface unmanned vehicle and autonomous ground vehicle: a review

    Navigation and motion control techniques for surface unmanned vehicle and autonomous ground vehicle: a review by Putri Nur Farhanah, Mohd Shamsuddin, Roshahliza, M. Ramli, Muhamad Arifpin, Mansor

    Published 2021
    “…This paper concerns the similar algorithm used in the USV and AGV. Most of the selected techniques are basic algorithms and have been frequently implemented to control both vehicles' systems. …”
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  18. 18
    UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(ii) ions

    UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(ii) ions by Ling Ling T., Ahmad M., Yook Heng L.

    Published 2024
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  19. 19
    HybridFlood: minimizing the effects of redundant messages and maximizing search efficiency of unstructured peer-to-peer networks

    HybridFlood: minimizing the effects of redundant messages and maximizing search efficiency of unstructured peer-to-peer networks by Barjini, Hassan, Othman, Mohamed, Ibrahim, Hamidah, Udzir, Nur Izura

    Published 2014
    “…To improve this searching scheme and reduce redundant messages, this paper proposes a novel algorithm named HybridFlood. This algorithm is divided into two steps. …”
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  20. 20
    Vector Control Drive Of Permanent Magnet Synchronous Motor Based Dsspace DS1103 Implementation

    Vector Control Drive Of Permanent Magnet Synchronous Motor Based Dsspace DS1103 Implementation by Cheok, Yong Seng, Zulkifilie, Ibrahim

    Published 2012
    “…The PMSM vector control algorithm for a theoretical basic has been verified by experimental results and created a rapid control prototype environment by using MATLAB/ Simulink and the DS1103 DSP of dSPACE.…”
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