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  1. 1
    A new mobile botnet classification based on permission and API calls

    A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

    Published 2024
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  2. 2
    A New Mobile Botnet Classification based on Permission and API Calls

    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
    Proceedings Paper
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  3. 3
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  4. 4
    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
    “…Furthermore, the proposed techniques based on the QLearning algorithm do not consider context-based actions. Thus, these techniques are unable to detect failures that occur due to the improper use of context data, which is becoming an increasingly common issue in mobile applications nowadays. …”
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  5. 5
    Age And Gender Recognition Mobile App

    Age And Gender Recognition Mobile App by Wee, Quo Lung

    Published 2023
    “…Therefore, this study aimed to develop age and gender recognition mobile application using deep learning algorithm. …”
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    Final Year Project Report / IMRAD
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  6. 6
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…The proposed algorithm employs a combined model that uses two different measures (nonconformity metric measures and Local Distance-based Outlier Factor (LDOF)) to improve its detection ability. …”
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  7. 7
    “myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.]

    “myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.] by Abu Mangshor, Nur Nabilah, Abdul Rahman, Mohamed Al Arabee, Sabri, Nurbaity, Ibrahim, Shafaf, Ibrahim, Zaidah, Shari, Anis Amilah

    Published 2020
    “…In addition, it also contributes to the exploration and implementation of learning algorithm in mobile-based application.…”
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  8. 8
    Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm

    Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm by Elshamarka, Ibrahim, Saman, Abu Bakar Sayuti

    Published 2012
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    Citation Index Journal
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  9. 9
    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
    “…Thus, these techniques are unable to detect failures that occur due to the improper use of context data, which is becoming an increasingly common issue in mobile applications nowadays. …”
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  10. 10
    Hierarchical gaussian reinforcement learning for path planning in uncertain environments

    Hierarchical gaussian reinforcement learning for path planning in uncertain environments by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw, Akmeliawati, Rini, Shafie, Amir Akramin

    Published 2015
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  11. 11
    Home intruder detection system using machine learning and IoT

    Home intruder detection system using machine learning and IoT by Sahlan, Fadhluddin, Feizal, Faeez Zimam, Mansor, Hafizah

    Published 2022
    “…HIDES successfully achieves its objective in detecting persons precisely and alerting the detection to users through mobile application remotely. …”
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  12. 12
    DESIGN OF IMPROVED GRID FOR TURTLE ROBOT

    DESIGN OF IMPROVED GRID FOR TURTLE ROBOT by Adnan, Muhammad Zulhilmi

    Published 2013
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    Final Year Project
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  13. 13
    Detection of Malaysian sign language with single shot detector algorithm/ Nurfarah Idayu Mohamad Fauzi, Shahirah Mohamed Hatim and Zalikha Zulkifli

    Detection of Malaysian sign language with single shot detector algorithm/ Nurfarah Idayu Mohamad Fauzi, Shahirah Mohamed Hatim and Zalikha Zulkifli by Mohamad Fauzi, Nurfarah Idayu, Mohamed Hatim, Shahirah, Zulkifli, Zalikha

    Published 2023
    “…Single Shot Detector (SSD) algorithm was implemented to perform the Malaysian Sign Language object detection in the application. …”
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  14. 14
    A framework of modified adaptive neuro-fuzzy inference engine

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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  15. 15
    A Static Approach towards Mobile Botnet Detection

    A Static Approach towards Mobile Botnet Detection by Shahid, Anwar, Jasni, Mohamad Zain, Inayat, Zakira, Ul Haq, Riaz, Ahmad, Karim, Jaber, Aws Naser

    Published 2016
    “…In this study we propose a static approach towards mobile botnet detection. This technique combines MD5, permissions, broadcast receivers as well as background services and uses machine learning algorithm to detect those applications that have capabilities for mobile botnets. …”
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    Conference or Workshop Item
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  16. 16
    Risk Concentration for Context Assessment (RiCCA) of SMS Messages using Danger Theory

    Risk Concentration for Context Assessment (RiCCA) of SMS Messages using Danger Theory by Kamahazira Binti Zainal

    Published 2024
    “…This RiCCA prototype is developed from Danger Theory algorithms that is Dendritic Cell Algorithm (DCA) and Deterministic Dendritic Cell Algorithm (dDCA). …”
    thesis::doctoral thesis
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  17. 17
    'Chapter 7: Smartphone penetration test: Securing Industry 5.0 mobile applications' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Algorithms".

    'Chapter 7: Smartphone penetration test: Securing Industry 5.0 mobile applications' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Al... by Eka Wahyu, Aditya, Nur Haryani, Zakaria, Fazli, Azzali, Mohamad Nazim, Jambli

    Published 2024
    “…The Future of Human-Computer Integration: Industry 5.0 Technology, Tools, and Algorithms provides a valuable insight into how Industry 5.0 technologies, tools, and algorithms can revolutionise industries and drive innovation. …”
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    Book Chapter
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  18. 18
    Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol

    Location-Based Approach for Route Maintenance in Dynamic Source Routing Protocol by Sjaugi, Muhammad Farhan

    Published 2008
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    Thesis
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  19. 19
    Convolutional neural network based mobile application for poisonous mushroom detection

    Convolutional neural network based mobile application for poisonous mushroom detection by Amirul, Shazlin Nizam, Mohd Sabri, Norlina, Gloria, Jennis Tan, Redwan, Nurul Ainina, Zhiping, Zhang

    Published 2025
    “…To address these issues, this study aims to develop a mushroom detection prototype specifically for identifying poisonous mushrooms using a mobile application. The application leverages a Convolutional Neural Network (CNN) algorithm to accurately classify mushrooms based on user-submitted images. …”
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  20. 20
    Deep learning-based single-shot and real-time vehicle detection and ego-lane estimation

    Deep learning-based single-shot and real-time vehicle detection and ego-lane estimation by Abdul Matin, M. A. A., Ahmad Fakhri, A. S., Mohd Zaki, Hasan Firdaus, Zainal Abidin, Zulkifli, Mohd Mustafah, Y., Abd Rahman, H., Mahamud, N. H., Hanizam, S., Ahmad Rudin, N. S.

    Published 2020
    “…In practice, it is exceptionally hard to accurately and efficiently develop an algorithm for FCWS application due to the complexity of steps involved in FCWS. …”
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