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  1. 1
    Wearable based-sensor fall detection system using machine learning algorithm

    Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

    Published 2021
    “…To prevent such kinds of deadly scenarios, a reliable fall detection system must be developed to help many lives. In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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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
    “…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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  3. 3
    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
    “…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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  4. 4
    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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  5. 5
    Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin

    Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin by Samsuddin, Nur Haida Hanna

    Published 2020
    “…A classifier will be designed and developed which is Linear Support Vector Machine (LSVM). …”
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    Thesis
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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
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  8. 8
    Kodepoly: an engaging approach to blended futuristic learning in coding

    Kodepoly: an engaging approach to blended futuristic learning in coding by Abd Rahman, Norsyafrina, Azhar Amanullah, Ayn Nur Azhana

    Published 2024
    “…By combining the strategic elements of Monopoly with a curriculum comprised of coding challenges, debugging exercises, and algorithmic puzzles, Kodepoly aims to render the learning process both enjoyable and substantial in content. …”
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  9. 9
    Develpoment of combinatorial optimisation for cutting tool path strategy

    Develpoment of combinatorial optimisation for cutting tool path strategy by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

    Published 2009
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    Conference or Workshop Item
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  10. 10
    Poverty Classification of Central Perak Population Using Machine Learning

    Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

    Published 2019
    “…The picture of Central Perak development reveals many families are not benefiting from national economic growth. …”
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    Final Year Project
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  11. 11
    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
    “…We utilise the Q-Learning algorithm to compare actions, including context-based actions, to effectively detect crashes and achieve a higher code coverage.…”
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  12. 12
    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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  13. 13
    Harmony Search algorithm-based gasoline consumption modeling for Indonesia

    Harmony Search algorithm-based gasoline consumption modeling for Indonesia by Anggarani, Riesta, Watada, Junzo

    Published 2012
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  14. 14
    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
    thesis::doctoral thesis
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  15. 15
    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
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  16. 16
    A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS

    A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

    Published 2023
    “…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. The machine learning algorithms that will be used and compared are Support Vector Machines (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Artificial Neural Network (ANN), and Linear Regression (LR). …”
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    Final Year Project Report / IMRAD
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  17. 17
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
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    Monograph
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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
    Investigating photovoltaic solar power output forecasting using machine learning algorithms

    Investigating photovoltaic solar power output forecasting using machine learning algorithms by Essam Y., Ahmed A.N., Ramli R., Chau K.-W., Idris Ibrahim M.S., Sherif M., Sefelnasr A., El-Shafie A.

    Published 2023
    “…To address this issue, continuous research and development is required to determine the best machine learning (ML) algorithm for PV solar power output forecasting. …”
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  20. 20
    Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023

    Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: a cross-sectional SHAP-based analysis of NHANES 2009-2023 by Tang, Yan, Jia, Lei, Zhou, Junjun, Dou, Jin, Qian, Jingjuan, Yi, Xin, Soh, Kim Lam

    Published 2026
    “…Variable selection was performed using least absolute shrinkage and selection operator regression. Five machine learning algorithms - random forest, extreme gradient boosting (XGBoost), multilayer perceptron, logistic regression, and support vector machine - were trained and evaluated using 5-fold cross-validation. …”
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