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  1. 1
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  2. 2
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  3. 3
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  4. 4
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  5. 5
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This algorithm is used to extract important points from a lengthy document, by which it classifies each word in the document under its relevant category and constructs the structure of the summary with reference to the categorized words. …”
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    Final Year Project
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  6. 6
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This algorithm is used to extract important points from a lengthy document, by which it classifies each word in the document under its relevant category and constructs the structure of the summary with reference to the categorized words. …”
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    Final Year Project
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  7. 7
    Fuzzy based technique for microchip lead inspection using machine vision

    Fuzzy based technique for microchip lead inspection using machine vision by Hawari, Yasser, Salami, Momoh Jimoh Emiyoka, Aburas, Abdurazzag Ali

    Published 2008
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    Proceeding Paper
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  8. 8
    Machine Vision Application For Automatic Defect Segmentation In Weld Radiographs

    Machine Vision Application For Automatic Defect Segmentation In Weld Radiographs by Soo , Say Leong

    Published 2006
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  9. 9
    EEG-based emotion recognition using machine learning algorithms

    EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

    Published 2024
    “…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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  10. 10
    Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia

    Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

    Published 2023
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  11. 11
    Named entity recognition using a new fuzzy support vector machine.

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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  12. 12
    Text Extraction Algorithm for Web Text Classification

    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
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  13. 13
    A machine learning approach to predict the activity of smart home inhabitant

    A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.

    Published 2023
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  14. 14
    Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning

    Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

    Published 2020
    “…Although Mask R-CNN achieves 85% accuracy, its sensitivity and F1- score are just 45% and 47% respectively. vii 4. Six supervised machine learning algorithms (Linear Regression, Logistic Regression, K Nearest Neighbors (KNN), Decision Trees (DT), Support Vector Machine (SVM) and Random Forest) are used to perform disease prediction. …”
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  15. 15
    Jogging activity recognition using k-NN algorithm

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  16. 16
    Malware Classification and Detection using Variations of Machine Learning Algorithm Models

    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. …”
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  17. 17
    Waste classification using support vector machine with SIFT-PCA feature extraction

    Waste classification using support vector machine with SIFT-PCA feature extraction by Puspaningrum, Adita Putri, Endah, Sukmawati Nur, Sasongko, Priyo Sidik, Kusumaningrum, Retno, ., Khadijah, ., Rismiyati, Ernawan, Ferda

    Published 2020
    “…This research proposes waste image classification to support automatic waste sorting using Support Vector Machine (SVM) classification algorithm and SIFT-PCA (Scale Invariant Feature Transform - Principal Component Analysis) feature extraction. …”
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    Conference or Workshop Item
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  18. 18
    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme

    Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme by Ashour, Mohammed Waleed, Khalid, Fatimah, Al-Obaydee, Mohammed

    Published 2013
    “…The proposed methodology focuses mainly on three main stages for an input image, firstly extracting features by commonly used features extraction methods such as edge detection, and histogram. …”
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  19. 19
    Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan

    Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

    Published 2024
    “…This paper proposes a sophisticated Job Position Prediction system utilizing Machine Learning algorithms and leveraging data from LinkedIn profiles. …”
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  20. 20
    Real‑time chatter detection during turning operation using wavelet scattering network

    Real‑time chatter detection during turning operation using wavelet scattering network by Sharma, Sanjay, Gupta, Vijay Kumar, Rahman, Mustafizur, Saleh, Tanveer

    Published 2024
    “…Experiments are performed to collect the acoustic signal during the turning operation to train and validate the algorithm. The automatic extracted chatter features are then used in supervised machine learning (ML) algorithms. …”
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