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    Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

    Published 2025
    “…This study explores the application of sentiment analysis using the Naive Bayes algorithm to understand public perceptions of marital issues, particularly factors contributing to the rising divorce rate. …”
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    Thesis
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    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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    Article
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    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…Based on this knowledge, an algorithm for detection of these patterns is designed, developed and tested. …”
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    Article
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    Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

    Published 2023
    “…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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    Thesis
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    Design and implementation of cordic algorithm with sinusoidal pulse width modulation switching strategy by Madzzaini, Nur Sofea Eleena

    Published 2017
    “…Usually, one sinusoidal wave is used for one inverter. In this design, SPWM is used for multilevel inverter application in photovoltaic (PV) system. …”
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    Student Project
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    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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    Conference or Workshop Item
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    Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…The signals were then clustered using the feature extraction algorithms. This paper tested two feature extraction algorithms namely Principal Component Analysis (PCA) and Auto-Regressive (AR). …”
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    Article
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    Sentiment Analysis on Users' Satisfaction for Mobile Banking Apps in Malaysia by Misinem, ., Tri Basuki, Kurniawan, Mohd Zaki, Zakaria, Muhammad Aqil Azfar, Uzailee

    Published 2022
    “…The best accuracy result shows 94.37% by the Decision Tree algorithm, and Naïve Bayes obtained the worst outcome at 66%.…”
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    Article
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    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

    Published 2010
    “…First, the algorithms‘ performances were evaluated using numerical simulation employing two different scanning geometries: limited and full view scanning geometries, where the applicability of these algorithms was accessed by comparing the reconstructed images with actual model. …”
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    Thesis
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