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  1. 1

    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
    “…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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    Student Project
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    Integrating finance dictionary in lexicon-based approach with machine learning algorithm to analyse the impact of OPEC news sentiment on financial market / Wu Ling by Wu, Ling

    Published 2020
    “…Since last few decades, machine learning algorithm which trains computers to learn from experience, is one of the most rapidly developing techniques which settles in the intersection research field of statistics and computer science. …”
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    Thesis
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    The impact of news sentiment on the stock market fluctuation : the case of selected energy sector by Ling, Wu, Siew, Hock Ow

    Published 2021
    “…We developed a financial news sentiment classifier by combining machine learning algorithms and lexicon-based labelling methods. …”
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    Article
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    Using streaming data algorithm for intrusion detection on the vehicular controller area network by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

    Published 2022
    “…This has prompted researchers to develop statistical and machine learning based intrusion detection systems for the CAN bus that use various features such as message timing and frequency to detect attacks. …”
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    Proceeding Paper
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    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

    Published 2023
    “…This study was solely concerned with the Windows malware dataset. The malware classification was determined by testing and training the supervised ML algorithms using the extracted features from the malware dataset. …”
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    Article
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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    Conference or Workshop Item
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Thesis
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    A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

    Published 2019
    “…Standard base machine learning algorithms, which include a total of twelve individual methods as well as the AdaBoost and Bagging methods, are firstly used. …”
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    Thesis
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    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Thesis
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    Optimized processing of satellite signal via evolutionary search algorithm by Hassan, Azmi, Othman, Rusli, Tang, Kieh Ming

    Published 2000
    “…The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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    Article
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    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

    Published 2004
    “…Interactive Learning Package for Artificial Neural Network (Demonstration Module) is a learning package that allow the users to learn and enhance the understanding of the ANN subject in more detailed way and apply in the demonstration parts. …”
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    Thesis
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    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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    Article
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    Noise reduction techniques in ECG signal by Muhumed, Sakarie Muse, Ibrahimy, Muhammad Ibn

    Published 2023
    “…A dataset of ECG signals with varying levels of EMG noise has been collected using the MIT-BIH dataset. An algorithm has been designed and implemented using the DA FIR filter coupled with Kaiser windowing technique to filter out the noise. …”
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    Article
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    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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    Article
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    Thesis