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  1. 1
    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
    “…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. We enhanced the Q-Learning algorithm for action selection based on potential action abilities and proposed a tool, namely CrashDroid, that allows the automation of testing context-aware Android applications. …”
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  2. 2
    Mobile game application development using evolutionary algorithms

    Mobile game application development using evolutionary algorithms by Ong, Jia Hui

    Published 2014
    “…Evolutionary Algorithms have never been used on mobile applications, thus it gives a novel idea of utilizing Evolutionary Algorithms in developing applications typically in games for mobile platforms. …”
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  3. 3
    A new mobile malware classification for call log exploitation

    A new mobile malware classification for call log exploitation by Madihah Mohd Saudi, Nurlida Basir, Mohd N.F.

    Published 2024
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  4. 4
    Neighbour-based on-demand routing algorithms for mobile ad hoc networks

    Neighbour-based on-demand routing algorithms for mobile ad hoc networks by Ejmaa, Ali Mohamed E.

    Published 2017
    “…In terms of the applications, The DCFP is more suitable to be used for education applications, while the SNBR is a good algorithm designed to be used for rescue system as data and energy is the main concern. …”
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  5. 5
    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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  6. 6
    Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

    Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions by Akhlaqi, Mohammad Yahya, Mohd Hanapi, Zurina

    Published 2023
    “…Many enterprise companies migrate their services and applications to the cloud to benefit from cloud computing advantages. …”
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  7. 7
    Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments

    Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments by Jauwairia Nasir, Fahad Islam, Yasar Ayaz

    Published 2013
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  8. 8
    Herb recognition for mobile apps / Jumriyanie Baba

    Herb recognition for mobile apps / Jumriyanie Baba by Baba, Jumriyanie

    Published 2017
    “…This project involves designing and developing on Herbs Recognition for Mobile Application. The mobile application is able to recognize the herbs type using the most suitable algorithm. …”
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  9. 9
    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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  10. 10
    Software agent as an effective tool for managing the Internet of thing data complexity

    Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

    Published 2017
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  11. 11
    Simulation model to improve QoS performance over fixed WiMAX using OPNET

    Simulation model to improve QoS performance over fixed WiMAX using OPNET by Lawal, I.A., Md Said, A., Mu'azu, A.A.

    Published 2013
    “…A Model was developed based on the proposed new distributed model (Master-Slave), the first scenario comprised of 3 Base Stations (BS) and thirty Subscriber Station (SS) with one Master BS selected by the designed algorithm (Nearest Neighborhood Algorithms). …”
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  12. 12
    Automatic generation of mobile content in entertainment applications using evolutionary computing

    Automatic generation of mobile content in entertainment applications using evolutionary computing by Teo, Jason Tze Wi, Chin, Kim On, Rayner Alfred, Ong Jia Hui

    Published 2010
    “…Hence it has opened up a whole new market with its mass among users and attracted a large number of smartphone application developers. …”
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  13. 13
    Empirical study on intelligent android malware detection based on supervised machine learning

    Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

    Published 2020
    “…In response, specific tools and anti-virus programs used conventional signature-based methods in order to detect such Android malware applications. …”
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  14. 14
    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin

    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

    Published 2021
    “…However, a common limitation of these tools is the low code coverage because of the tools' inability to find the right combination of actions that can drive the application into new and important states. …”
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  15. 15
    State-Aware re-configuration model for multi-radio wireless Mesh Networks

    State-Aware re-configuration model for multi-radio wireless Mesh Networks by Zakaria, Omar, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Khalifa, Othman Omran, Azram, Mohammad, Goudarzi, Shidrokh, Jivanadham, Lalitha Bhavani, Zareei, Mahdi

    Published 2017
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  16. 16
    A new efficient checkpointing algorithm for distributed mobile computing

    A new efficient checkpointing algorithm for distributed mobile computing by Mansouri, Houssem, Badache, Nadjib, Aliouat, Makhlouf, Pathan, Al-Sakib Khan

    Published 2015
    “…Such instability poses serious challenge for fault tolerant distributed mobile applications. Therefore, the classical checkpointing techniques, which make the applications more failure-resistant, are not always compatible with the mobile context. …”
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  17. 17
    New Lightweight Identity Based Encryption Algorithm for Mobile Device: Preliminary Study

    New Lightweight Identity Based Encryption Algorithm for Mobile Device: Preliminary Study by Norhidayah, Muhammad, Jasni, Mohamad Zain, Md Yazid, Mohd Saman

    Published 2012
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  18. 18
    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
    Conference Paper
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  19. 19
    A new Doppler Spread Estimation Algorithm Based on Zero Crossings of The Auto-correlation

    A new Doppler Spread Estimation Algorithm Based on Zero Crossings of The Auto-correlation by Altag Ali, Gassan, Jeoti , Varun, Manzoor, Shahid

    Published 2010
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  20. 20
    Thalassaemia detection using CBR Algorithm via mobile device

    Thalassaemia detection using CBR Algorithm via mobile device by Nur Faezah, Omar

    Published 2011
    “…This thesis proposes a Case-Based Reasoning model for medical diagnosis,particularly for Thalassaemia diagnosis. CBR Algorithm is an algorithm that can solve a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation in a new situation.CBR is suit for solving the problem in Thalassaemia cases.The model is designed and prototype is developed to test the diagnosis accuracy of the model.T his application is focus on Beta Thalassaemia and Haemoglobin E Trait only.For platform, this application will be using the mobile device such as PDA. …”
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