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  1. 1
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  2. 2
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…Several machine learning techniques based on supervised learning have been applied to classify malware. …”
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  3. 3
    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding

    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

    Published 2007
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  4. 4
    Pairwise testing tools based on hill climbing algorithm (PTCA)

    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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    Undergraduates Project Papers
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  5. 5
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…Several machine learning techniques based on supervised learning have been adopted in the classification of malware. …”
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    Proceeding Paper
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  6. 6
    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing

    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…We utilized the enhanced Q-Learning algorithm to compare actions, including context-based actions, to effectively achieve higher code coverage. …”
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  7. 7
    Object-Oriented Programming semantics representation utilizing agents

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…The algorithm requires source codes comparison based on keyword similarity to extract the words that exist in the two related source codes. …”
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  8. 8
    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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  9. 9
    Experimental implementation controlled SPWM inverter based harmony search algorithm

    Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb M., Mansor M., Razali R., Daniyal H., Yahaya J.A.F.

    Published 2023
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  10. 10
    Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application

    Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

    Published 2021
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  11. 11
    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection

    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

    Published 2024
    “…Most of the algorithms got promising results and classify packets based on DSCP accurately. …”
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  12. 12
    Why coding? Why now? From coding to computational thinking through computational mathematics problem based learning (CM-PBL)

    Why coding? Why now? From coding to computational thinking through computational mathematics problem based learning (CM-PBL) by Ku, Soh Ting, Talib, Othman, Md. Yunus, Aida Suraya, Zolkepli, Maslina

    Published 2019
    “…To achieve these goals, computational mathematics problem based learning (CM-PBL) instructional strategy is developed to promote an active learning environment for classroom management involving problem solving. …”
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    Conference or Workshop Item
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  13. 13
    Deep learning based emotion recognition for image and video signals: matlab implementation

    Deep learning based emotion recognition for image and video signals: matlab implementation by Ashraf, Arselan, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2021
    “…This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. …”
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  14. 14
    Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique

    Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

    Published 2024
    “…In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD). …”
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  15. 15
    Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR)

    Efficient Malware Detection And Response Model Using Enhanced Parallel Deep Learning (EPDL-MDR) by Chowdhury Sajadul Islam

    Published 2026
    “…Attackers use code obfuscation to conceal malicious code, making it difficult for conventional systems and machine learning classifiers to detect threats. …”
    thesis::doctoral thesis
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  16. 16
    Age-based facial recognition using convoluted neural network deep learning algorithm

    Age-based facial recognition using convoluted neural network deep learning algorithm by Julius Yong Wu Jien, Aslina Baharum, Shaliza Hayati A. Wahab, Nordin Saad, Muhammad Omar, Noorsidi Aizuddin Mat Noor

    Published 2020
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  17. 17
    Heart Attack Prediction with Deep Learning

    Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

    Published 2023
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  18. 18
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
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  19. 19
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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  20. 20
    Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems

    Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

    Published 2017
    “…Therefore, the aim of this study is to minimize the computation time during RFS by improving the standard rsync algorithm. Previously, several algorithms and techniques have been proposed for partial file synchronization but many of them were based on controlling the block size, checksums, and delta compression of the matched blocks, to solve the searching problem of the rsync algorithm. …”
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