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    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

    Published 2025
    “…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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    Article
  2. 2

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…Machine learning is an implementation of artificial intelligence (Al) that allows systems to learn and build on knowledge without being directly programmed automatically. …”
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    Thesis
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    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Finding a good classification algorithm is an important component of many data mining projects. …”
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    Thesis
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    Edge Detection Algorithm For Image Processing Of Search And Rescue Robot by A/L Sivem, Prasanthran

    Published 2016
    “…This paper highlights the various edge detection algorithms working method and comparison is made based on the advantages and disadvantages of the algorithms for the identification of an optimum edge detection algorithm. …”
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    Final Year Project
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    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure by Asmai, S. A.

    Published 2014
    “…The other 40% of the dataset is used to test generated rules. A simple program of C++ is implemented using Microsoft Visual Studio to test generated rules until accuracy of performance is obtained. …”
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    Conference or Workshop Item
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    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…Asymmetrically, anomaly based detection method can detect novel attacks but it has high false positive rate. …”
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    Conference or Workshop Item
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    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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    Thesis
  10. 10

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…In this research, a hand-written character recognition model are implemented in C++ programming with ability to classify digits 0, 1, 2, and 3. …”
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    Thesis
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    Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

    Published 2011
    “…This study proposes weighting method for damage detection algorithms based on the bending mode shapes for beam structures. …”
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    Article
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    Detection of head position using chain code algorithm by Fuad, Norfaiza

    Published 2007
    “…The main contribution of this thesis is it contributes an algorithm of head recognition and detecting which based on image segmentation, Prewitt edge detection and Chain Code algorithm. …”
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    Thesis
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    Detection of head position using chain code algorithm by Fuad, Norfaiza

    Published 2007
    “…The main contribution of this thesis is it contributes an algorithm of head recognition and detecting which based on image segmentation, Prewitt edge detection and Chain Code algorithm. …”
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    Thesis
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    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Moreover, shortage of reliable methods on a new dataset for the intrusion detection system and anomaly detection in terms of classification is an issue. …”
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    Thesis
  18. 18

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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    Article
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