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  1. 1
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  2. 2
    Anomaly detection through spatio-temporal context modeling in crowded scenes

    Anomaly detection through spatio-temporal context modeling in crowded scenes by Lu, T., Wu, L., Ma, X., Shivakumara, P., Tan, C.L.

    Published 2014
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  3. 3
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  4. 4
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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    Monograph
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  5. 5
    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection

    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

    Published 2022
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  6. 6
    Alternate methods for anomaly detection in high-energy physics via semi-supervised learning

    Alternate methods for anomaly detection in high-energy physics via semi-supervised learning by Md. Ali, Mohd. Adli, Badrud’din, Nu’man, Abdullah, Hafidzul, Kemi, Faiz

    Published 2020
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  7. 7
    An improved artificial dendrite cell algorithm for abnormal signal detection

    An improved artificial dendrite cell algorithm for abnormal signal detection by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Abdul Wahab, Mohd Helmy

    Published 2018
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  8. 8
    Glass break detection system using deep auto encoders with fuzzy rules induction algorithm

    Glass break detection system using deep auto encoders with fuzzy rules induction algorithm by Nyein Naing, Wai Yan, Htike, Zaw Zaw

    Published 2019
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  9. 9
    Non-velocity based analysis of passive ultrasonic signal for source location detection in composite plates: a pilot study

    Non-velocity based analysis of passive ultrasonic signal for source location detection in composite plates: a pilot study by Z. M., Hafizi, Epaarachchi, J., Che Ku Eddy Nizwan, Che Ku Husin, Lau, K. T.

    Published 2012
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  10. 10
    A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection

    A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection by Mohammed A. F. Salah, Mohd Fadzli Marhusin, Rossilawati Sulaiman

    Published 2026
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  11. 11
    Real-Time Video Processing Using Native Programming on Android Platform

    Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

    Published 2012
    “…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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  12. 12
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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  13. 13
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  14. 14
    Mobile Malware Classification via System Calls and Permission for GPS Exploitation

    Mobile Malware Classification via System Calls and Permission for GPS Exploitation by Madihah Mohd Saudi, Husainiamer, MAB

    Published 2024
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  15. 15
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Waseem Alwan, Waseem Alwan, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Syahril Ramadhan Saufi, Syahril Ramadhan Saufi, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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  16. 16
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Ramadhan Saufi, Syahril, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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  17. 17
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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  18. 18
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Waseem Alwan, Waseem Alwan, Ngadiman, Nor Hasrul Akhmal, Adnan Hassan, Adnan Hassan, Syahril Ramadhan Saufi, Syahril Ramadhan Saufi, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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  19. 19
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Ramadhan Saufi, Syahril, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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  20. 20
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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