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  1. 1
    SANAsms: Secure short messaging system for secure GSM mobile communication

    SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

    Published 2008
    “…J2ME phone and Symbian Operating System (OS) as the platform for the application to run. The encryption algorithm that implemented in the system is Advanced Encryption Standard (AES) with 128-bit block size and together with the SHA1 (Secure Hash Algorithm) hash functions. …”
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  2. 2
    Challenges of hidden data in the unused area two within executable files

    Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

    Published 2009
    “…The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file(exe.file). …”
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  3. 3
    Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing

    Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing by Yahaya, Bakri

    Published 2016
    “…The designed modules is in the form of algorithms, GridSim, Java Development Kits and Java Language used to support the design process whereas the Netbeans software serves as the platform to simulate the experiment so as to obtain the results. …”
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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
    “…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
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  5. 5
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
    Conference paper
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  6. 6
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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  7. 7
    A block cipher based on genetic algorithm

    A block cipher based on genetic algorithm by Zakaria, Nur Hafiza

    Published 2016
    “…The development of block ciphers have resulted in a number of cryptographic algorithms such as, AES, ARIA, BLOWFISH256, DESL, 3D-AES and many more. …”
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  8. 8
    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive

    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

    Published 2023
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  9. 9
    Computing the autopilot control algorithm using predictive functional control for unstable model

    Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

    Published 2009
    “…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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  10. 10
    Effort Estimation Model for Function Point Measurement

    Effort Estimation Model for Function Point Measurement by Koh, Tieng Wei

    Published 2007
    “…Software Cost Estimation is a practical process that is applied to find out basically the effort and development time requirements for a software product, which is going to be developed. …”
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  11. 11
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…The output of the algorithm is a set of extreme points that can be used to construct a minimal error approximation function. …”
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  12. 12
    Chebyshev approximation of discrete polynomials and splines

    Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

    Published 2004
    “…The output of the algorithm is a set of extreme points that can be used to construct a minimal error approximation function. …”
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  13. 13
    A video-rate color image segmentation using adaptive and statistical membership function

    A video-rate color image segmentation using adaptive and statistical membership function by Sojodishijani, Omid, Rostami, Vahid, Ramli, Abdul Rahman

    Published 2010
    “…Typically, the image segmentation algorithms in video processing system require very high computation power, so it is desirable to develop algorithms for implementation as a real-time system. …”
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  14. 14
    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil

    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 1998
    “…The Genetic Algorithm developed in the project was tested on two objective functions for optimizing the economic dispatch problem, which are the total generation cost and the incremental cost function. …”
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  15. 15
    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy

    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

    Published 2022
    “…These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. …”
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  16. 16
    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function

    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function by Mohamed, Najihah

    Published 2019
    “…The optimisation technique consists of exact algorithm, and approximate algorithm. The approximate algorithm is a good technique to be highlighted since it is a feasible way to develop an easier, more convenient curve fitting method, that will save great computation, solve a large scale problem and produce a better quality end result. …”
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  17. 17
    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah

    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah by Ali, Sadollah

    Published 2013
    “…Furthermore, a comparative study was carried out to show the effectiveness of the proposed algorithms over other well-known methods in terms of computational time (speed) and function values. …”
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  18. 18
    Estimation of the denitrification in the lower Mississippi Valley

    Estimation of the denitrification in the lower Mississippi Valley by Saleh, Abdul Razak

    Published 2001
    “…The CREAMS denitrification algorithm is a function of the number of days of drainage from the bottom layer of the profile. …”
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  19. 19
    Designing New Block Cipher Based On Genetic Algorithm Approach

    Designing New Block Cipher Based On Genetic Algorithm Approach by Nur Hafiza Binti Zakaria, Ramlan Mahmod, Nur Izura Udzir, Zuriati Ahmad Zukarnain, Suriyani Ariffin

    Published 2024
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  20. 20
    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…Then, the histogram distance function for each location is computed using a pseudo-probability combination of novel histogram distance functions on a clustered histogram. …”
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