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  1. 1
    Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population

    Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population by Yahaya, Yasmin Arijah Che

    Published 2023
    “…However, the Phenice age classification method is only applicable for sample age above 20 years old. …”
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  2. 2
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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  3. 3
    Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning

    Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning by Idris, S., Badruddin, N.

    Published 2021
    “…A total of 7 different classification algorithms were used to predict between 6 levels of CF, the Robust and Non-Robust groups, as well as the Robust and Frail with MCI groups. …”
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  4. 4
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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  5. 5
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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  6. 6
    Using algorithmic taxonomy to evaluate lecturer workload

    Using algorithmic taxonomy to evaluate lecturer workload by Hashim, Ruhil Hayati, Abdul Hamid, Jamaliah, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Mohayidin, Mohd Ghazali

    Published 2006
    “…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  7. 7
    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal

    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  8. 8
    Automated study plan generator using rule-based and knapsack problem

    Automated study plan generator using rule-based and knapsack problem by Salahuddin, Lizawati, Hashim, Ummi Rabaah, Salahuddin, Lizawati

    Published 2022
    “…Hence, this study aims to propose an algorithm to generate an automated and accurate study plan throughout the study duration. …”
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  9. 9
    Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm

    Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm by Foo, Yao Heng

    Published 2025
    “…University course timetabling problem (UCTP) is a scheduling problem that requires courses to be assigned to the limited time slots, classrooms, and lecturers, while adhering to a set of predefined constraints. …”
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  10. 10
    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal

    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hassan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  11. 11
    The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach

    The classification of skateboarding trick manoeuvres: A K-nearest neighbour approach by Muhammad Ar Rahim, Ibrahim, Muhammad Amirul, Abdullah, Muhammad Nur Aiman, Shapiee, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Muhammad Aizzat, Zakaria, Noor Azuan, Abu Osman, Anwar P. P., Abdul Majeed

    “…A number of features were extracted and engineered from the IMU data, i.e., mean, skewness, kurtosis, peak to peak, root mean square as well as standard deviation of the acceleration and angular velocities along the primary axes. …”
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  12. 12
    Odour based human identification and classification using neural networks

    Odour based human identification and classification using neural networks by Ahmed Qusay Sabri, Rayner Alfred

    Published 2019
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  13. 13
    Using web questionnaire for web-based course evaluation: advantages and disadvantages

    Using web questionnaire for web-based course evaluation: advantages and disadvantages by Fariborzi, Elham, Abu Bakar, Kamariah, Kasa, Zakaria, Abu Samah, Bahaman, Abdullah, Muhammad Taufik

    Published 2017
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  14. 14
    The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach

    The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Muhammad Muaz, Alim, Mohamad Razali, Abdullah

    Published 2018
    “…Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. …”
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  15. 15
    Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network

    Distortion-Free Digital Watermarking for Medical Images (Fundus) using Complex- Valued Neural Network by Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke

    Published 2015
    “…The algorithm was appraised by Mean Squared Error MSE and Average Difference Indicator (ADI). …”
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    Monograph
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  16. 16
    The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach

    The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach by Taha, Z., Musa, R.M., Majeed, A.P.P.A, Abdullah, M.R., Zakaria, M.A., Alim, M.M., Jizat, J.A.M., Ibrahim, M.F.

    Published 2018
    “…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. …”
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  17. 17
    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman

    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

    Published 2025
    “…Data for the study was collected from university records, and algorithm performance was tested against predefined scheduling criteria. …”
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  18. 18
    Virtual reality in algorithm programming course: practicality and implications for college students

    Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
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  19. 19
    Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan

    Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan by Hamrizan, Siti Fatimah Azzahra

    Published 2021
    “…The exam results from the ELC can be the features to help the students to know if they can pass the MUET exam and the lecturers can figure out which language skills need to be improved to help preparing the students to sit for MUET. The study aims to explore the K-Nearest Neighbour (KNN) algorithm in solving the MUET result prediction problem, to develop a prototype of MUET result prediction based on the KNN algorithm and to evaluate the accuracy of the KNN algorithm in MUET result prediction. …”
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  20. 20
    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
    “…The fall event behaviour classification classes are sleep, walk, sit, front fall, back fall, side fall, etc. …”
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