Search Results - parallel computing ((((using algorithm) OR (matching algorithm))) OR (learning algorithm))*

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  1. 1
    GPU-based odd and even hybrid string matching algorithm

    GPU-based odd and even hybrid string matching algorithm by Rahbari, Ghazal, Abdul Rashid, Nur’Aini, Husain, Wahidah

    Published 2016
    “…String matching is considered as one of the fundamental problems in computer science.Many computer applications provide the string matching utility for their users, and how fast one or more occurrences of a given pattern can be found in a text plays a prominent role in their user satisfaction.Although numerous algorithms and methods are available to solve the string matching problem, the remarkable increase in the amount of data which is produced and stored by modern computational devices demands researchers to find much more efficient ways for dealing with this issue.In this research, the Odd and Even (OE) hybrid string matching algorithm is redesigned to be executed on the Graphics Processing Unit (GPU), which can be utilized to reduce the burden of compute-intensive operations from the Central Processing Unit (CPU).In fact, capabilities of the GPU as a massively parallel processor are employed to enhance the performance of the existing hybrid string matching algorithms.Different types of data are used to evaluate the impact of parallelization and implementation of both algorithms on the GPU. …”
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  2. 2
    Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems

    Multithreaded Scalable Matching Algorithm For Intrusion Detection Systems by Hnaif, Adnan Ahmad Abdelfattah

    Published 2010
    “…Therefore, the performance of the existing algorithms needs to be improved both in sequential and parallel to enhance the speed of the detection engine used in SNORT-NIDS. …”
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  3. 3
    Speeding up index construction with GPU for DNA data sequences

    Speeding up index construction with GPU for DNA data sequences by Rahmaddiansyah, , Abdul Rashid, Nur’aini

    Published 2011
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  4. 4
    A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences

    A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences by M. Othman, Razib, Deris, Safaai, Md. IIlias, Rosli

    Published 2008
    “…The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. …”
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  5. 5
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
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  6. 6
    Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources

    Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources by Abed, Munther Hameed, Mohd Nizam Mohmad, Kahar

    Published 2022
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  7. 7
    Effect Of The Addition Of Wastepaper To Concrete Mix

    Effect Of The Addition Of Wastepaper To Concrete Mix by Shukeri, Ritzawaty Mohamad

    Published 2009
    “…Therefore, the performance of the existing algorithms needs to be improved both in sequential and parallel to enhance the speed of the detection engine used in SNORT-NIDS. …”
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  8. 8
    Parallel Quick-Skip Search Hybrid Algorithm For The Exact String Matching Problem.

    Parallel Quick-Skip Search Hybrid Algorithm For The Exact String Matching Problem. by Naser, Mustafa Abdulsahib

    Published 2010
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  9. 9
    Parallel batch self-organizing map on graphics processing unit using CUDA

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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  10. 10
    Parallel batch self-organizing map on graphics processing unit using CUDA

    Parallel batch self-organizing map on graphics processing unit using CUDA by Daneshpajouh, H., Delisle, P., Boisson, J.-C., Krajecki, M., Zakaria, N.

    Published 2018
    “…The most computationally expensive parts of its training algorithm (such as steps to compute distance between each data vector and neuron, and determining the Best Matching Unit based on minimum distance) are identified and mapped on GPU to be processed in parallel. …”
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  11. 11
    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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  12. 12
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. …”
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  13. 13
    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi

    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

    Published 2015
    “…Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN. …”
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  14. 14
    CUDA implementation of fractal image compression

    CUDA implementation of fractal image compression by Al Sideiri A., Alzeidi N., Al Hammoshi M., Chauhan M.S., AlFarsi G.

    Published 2023
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  15. 15
    Grid portal technology for web based education of parallel computing courses, applications and researches

    Grid portal technology for web based education of parallel computing courses, applications and researches by Alias, Norma, Islam, Md. Rajibul, Mydin, Suhaimi, Hamzah, Norhafiza, Safiza Abd. Ghaffar, Zarith, Satam, Noriza, Darwis, Roziha

    Published 2009
    “…This paper proposes the web service education technology for postgraduate parallel computing course, e-learning students, real-time solutions and for supervising projects related to the application of parallel computing, that focuses on the fundamental principles to parallel computer architecture, multimedia, communication cost, master-worker model, parallel algorithm, web services and performance evaluations. …”
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  16. 16
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
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  17. 17
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  18. 18
    The forecasting of poverty using the ensemble learning classification methods

    The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

    Published 2023
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  19. 19
    Resource Minimization in a Real-time Depth-map Processing System on FPGA

    Resource Minimization in a Real-time Depth-map Processing System on FPGA by Ngo, Huy Tan, Hamid, Nor Hisham, Sebastian , Patrick, Yap, Vooi Voon

    Published 2011
    “…Depth-map algorithm allows camera system to estimate depth. It is a computational intensive algorithm, but can be implemented with high speed on hardware due to the parallelism property. …”
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  20. 20
    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…This paper proposed the NAGE method as a straight forward transformation from sequential to parallel algorithm using domain decomposition and splitting strategies. …”
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