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  1. 1
    Thalassaemia detection using CBR Algorithm via mobile device

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

    Published 2011
    “…Moreover,this application will be using the programming language Visual Basic. …”
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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., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

    Published 2024
    Conference Paper
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  3. 3
    Detecting resource consumption attack over MANET using an artificial immune algorithm

    Detecting resource consumption attack over MANET using an artificial immune algorithm by Abdelhaq, Maha, Hassan, Rosilah, Ismail, Mahamod, Israf Ali, Daud Ahmad

    Published 2011
    “…These algorithms are used to secure both host-based and network-based systems. …”
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  4. 4
    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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  5. 5
    Thalassaemia detection using CBR Algorithm via mobile device

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

    Published 2011
    “…Moreover,this application will be using the programming language Visual Basic. …”
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    Undergraduates Project Papers
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  6. 6
    AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR

    AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR by Mohd Shah, Hairol Nizam, Ab Rashid, Mohd Zamzuri, Mohd Sobran, Nur Maisarah

    Published 2013
    “…There have two part are involve which is mobile robot platform and classification algorithms by color. …”
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  7. 7
    Android Mobile Malware Classification Based on System Call and Permission Using Tokenization

    Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

    Published 2024
    thesis::master thesis
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  8. 8
    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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  9. 9
    Computing non-contactable drowsiness monitoring system with mobile machine vision

    Computing non-contactable drowsiness monitoring system with mobile machine vision by Alixson Polumpung, Lorita Angeline, Helen Sin Ee Chuo, Tan, Min Keng, Lim, Kit Guan, Teo, Kenneth Tze Kin

    Published 2022
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  10. 10
    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
    Article
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  11. 11
    Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion

    Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion by Alam, Mir Suhail, Morshidi, Malik Arman, Gunawan, Teddy Surya, Olanrewaju, Rashidah Funke, Arifin, Fatchul

    Published 2021
    “…The algorithm used for feature detection and description is Oriented-FAST Rotated-BRIEF (ORB), whereas to evaluate the homography for pose estimation, Random Sample Consensus (RANSAC) is used. …”
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  12. 12
    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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  13. 13
    Hardware development of autonomous mobile robot based on actuating lidar

    Hardware development of autonomous mobile robot based on actuating lidar by Mohd Romlay, Muhammad Rabani, Mohd Ibrahim, Azhar, Toha, Siti Fauziah, Rashid, Muhammad Mahbubur, Ahmad, Muhammad Syahmi

    Published 2022
    “…From here, the extracted values are implied on k-NN, Decision Tree and CNN training algorithm. The final result shows promising potential with 91% prediction when implemented on the Decision Tree algorithm based on our proposed system of a single actuating LiDAR sensor.…”
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  14. 14
    A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC

    A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC by Merrad, Yacine, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Gunawan, Teddy Surya

    Published 2020
    “…The proposed method is a machine learning based real-time notification system using the exciting Scale Invariant Feature Transform feature detector (SIFT) and Random Sample Consensus (RANSAC) algorithms. …”
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  15. 15
    Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques

    Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

    Published 2017
    “…Mobile ad-hoc network (MANET) is an evolving technology that is utilized in different applications (i.e. military surveillance, personal network, etc.) and developed in the recent years. …”
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  16. 16
    Auto-formation group chat for fitness application with rule-based / Amar Aslam Ramli

    Auto-formation group chat for fitness application with rule-based / Amar Aslam Ramli by Ramli, Amar Aslam

    Published 2018
    “…Moreover, the algorithm used for rule-based expert system is forward chaining method. …”
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    Student Project
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  17. 17
    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
    “…The result shows that the detection of malware within application category achieves higher accuracy compared to application with non-category based. …”
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  18. 18
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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  19. 19
    A wheelchair sitting posture detection system using pressure sensors

    A wheelchair sitting posture detection system using pressure sensors by Mohamad Yusoff, Muhammad Annuar Alhadi, Azmi, Nur Liyana, Nordin, Nor Hidayati Diyana

    Published 2024
    “…A graphical-user interface (GUI) based application was developed using the algorithm with the highest accuracy, DT classifier, to illustrate the result of the posture classification to the wheelchair user for any posture correction to be made in case of improper sitting posture detected.…”
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  20. 20
    WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.]

    WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.] by Ahmad, Illiasaak, Anak Buja, Alya@Geogiana, Abdullah Sani, Anis Shobirin

    Published 2013
    “…To solve this issue, we proposed a method to help the cloud provides a suitable content for devices. Our method is based on three stages: 1) define the problem formulation for device heterogeneity; 2) model a mathematical equation for device heterogeneity detection; 3) develop a cloud-based device heterogeneity detection algorithm. …”
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    Research Reports
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