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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
    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 proposed implementation shown significant speedups of 11Ã� and 5Ã� compared to the sequential and parallel CPU implementations respectively. …”
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  3. 3
    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 proposed implementation shown significant speedups of 11Ã� and 5Ã� compared to the sequential and parallel CPU implementations respectively. …”
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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    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 genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. …”
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  8. 8
    Job Matching Mobile Application using Fuzzy Analytic Hierarchy Process (FAHP) / Mohammad Ashraf Jefrizin

    Job Matching Mobile Application using Fuzzy Analytic Hierarchy Process (FAHP) / Mohammad Ashraf Jefrizin by Jefrizin, Mohammad Ashraf

    Published 2017
    “…FAHP is implemented in the job matching process. This project’s aim is to assist the job seekers to find ICT jobs that match to their preferences. …”
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  9. 9
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  10. 10
    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm

    Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

    Published 2023
    Conference Paper
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  11. 11
    MINIMIZATION OF RESOURCE UTILIZATION FOR A REAL-TIME DEPTH-MAP COMPUTATIONAL MODULE ON FPGA

    MINIMIZATION OF RESOURCE UTILIZATION FOR A REAL-TIME DEPTH-MAP COMPUTATIONAL MODULE ON FPGA by NGO , NGO HUY TAN

    Published 2011
    “…However, the issue can also be addressed by implementing hardware architectures without the need to modify the depth-map algorithm. …”
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  12. 12
    Enhanced and effective parallel optical flow method for vehicle detection and tracking

    Enhanced and effective parallel optical flow method for vehicle detection and tracking by Bhaskar, P.K., Yong, S.-P., Jung, L.T.

    Published 2016
    “…With a view to do improvements, it is proposed to develop an unique algorithm for vehicle data recognition and tracking using Parallel Optical Flow method based on Lucas-Kanade algorithm. …”
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  13. 13
    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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  14. 14
    Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm

    Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Kohbalan, Moorthy, Shahreen, Kasim, Ashraf Osman, Ibrahim

    Published 2017
    “…This paper present a hybrid method of Newton method, Differential Evolution Algorithm (DE) and Cooperative Coevolution Algorithm (CCA). …”
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  15. 15
    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm

    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
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  16. 16
    Fitness value based evolution algorithm approach for text steganalysis model

    Fitness value based evolution algorithm approach for text steganalysis model by Din, Roshidi, Samsudin, Azman, Tuan Muda, Tuan Zalizam, Lertkrai, P., Amphawan, Angela, Omar, Mohd Nizam

    Published 2013
    “…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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  17. 17
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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  18. 18
    A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach

    A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach by Puriwat, Lertkrai

    Published 2012
    “…Therefore, this research employed a detection factor based on the evolution algorithm method for text steganalysis. The aim of this project was to detect a hidden message in an observed message using text steganalysis.…”
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  19. 19
    Adopting morphology method in camera based EAN-13 1D barcode recognition using Simulink: article / Siti Nor Safinaz Ozaimidi

    Adopting morphology method in camera based EAN-13 1D barcode recognition using Simulink: article / Siti Nor Safinaz Ozaimidi by Ozaimidi, Siti Nor Safinaz

    Published 2012
    “…This paper studies barcode recognition which implements using Simulink MATLAB 7.13. The proposed algorithms and the implementations of image are for EAN-13 barcode by using camera devices. …”
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  20. 20
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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