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  1. 1
    Sensing texture using an artificial finger and a data analysis based on the standard deviation

    Sensing texture using an artificial finger and a data analysis based on the standard deviation by Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, N. H. H, Cranny, Andy, White, Neil M.

    Published 2015
    “…The standard deviation analysis for texture detection is novel as it uses a combination of arthmetic processes. …”
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  2. 2
    Sensing texture using an artificial finger and a data analysis based on the standard deviation

    Sensing texture using an artificial finger and a data analysis based on the standard deviation by Chappell, Paul H., Muridan, Norasmahan, Mohamad Hanif, Nik Hazrin, Cranny, Andy, White, Neil M.

    Published 2015
    “…The output from the algorithm is the frequency spectrum of a signal. Plots, from the output of the algorithm, show events that correspond to the cyclic waveforms produced from the regularity of object surface patterns. …”
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  3. 3
    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function

    Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

    Published 2012
    “…We propose a novel error tolerance dissimilarity algorithm to detect deviations in the CGIFs. We evaluate our method in the context of analyzing real world financial statements for identifying deviating performance indicators. …”
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  4. 4
    Fault diagnostic algorithm for precut fractionation column

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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  5. 5
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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  6. 6
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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  7. 7
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Monograph
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  8. 8
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  9. 9
    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications

    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…Without human input, these algorithms discover patterns or groupings in the data. …”
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  10. 10
    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection

    A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

    Published 2022
    “…For generating an interpretable deep architecture for identifying deep intrusion patterns, this study proposes an approach that combines ANFIS (Adaptive Network-based Fuzzy Inference System) and DT (Decision Tree) for interpreting the deep pattern of intrusion detection. …”
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  11. 11
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  12. 12
    Gait pattern detection for amputated prosthetic using fuzzy algorithm

    Gait pattern detection for amputated prosthetic using fuzzy algorithm by Abdullah, Ahmad Faisal

    Published 2015
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  13. 13
    Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest

    Anomaly detection of denial-of-service network traffic attacks using autoencoders and isolation forest by Ghulam Hussain, Muhammad Thaqif, Shafeeq Lone, Aman, Maspo, Nur-Adib, Attarbashi, Zainab

    Published 2026
    “…The framework analyzes extracted traffic features, including packet length and IP address patterns, to detect deviations from normal behaviour without requiring labelled data. …”
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  14. 14
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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    Proceeding Paper
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  15. 15
    A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection

    A Bio-Inspired Behavior-Based Hybrid Framework for Ransomware Detection by Mohammed A. F. Salah, Mohd Fadzli Marhusin, Rossilawati Sulaiman

    Published 2026
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  16. 16
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
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  17. 17
    Network intrusion detection and alert system

    Network intrusion detection and alert system by To, Jin Yi

    Published 2024
    “…Signature-based detection compares network traffic packets with a real-time updated database of known attack patterns, while anomaly-based detection algorithms learn normal behavior patterns and identify deviations. …”
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    Final Year Project / Dissertation / Thesis
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  18. 18
    Near infrared palm image acquisition and two-finger valley point-based image extraction for palm vascular pattern detection

    Near infrared palm image acquisition and two-finger valley point-based image extraction for palm vascular pattern detection by Mohd Noh, Zarina

    Published 2019
    “…In summary, vascular pattern can be detected visually from the palm image acquired by the NIR palm image acquisition device developed in this research.…”
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  19. 19
    Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network

    Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network by Nazriyah, Haji Che Zan @ Che Zain

    Published 2016
    “…Statistical based features namely minimum, maximum, arithmetic average and standard deviation were extracted from each image channels within detected ROI to represent pineapple skin color's tendency and dispersion. …”
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  20. 20
    Suspicious activities detection for anti-money laundering using machine learning techniques

    Suspicious activities detection for anti-money laundering using machine learning techniques by Lim, Aun Chir

    Published 2025
    “…Machine learning is able to learn complex relationships within large datasets then identify anomalies that deviate from well-defined patterns. This enables machine learning model to detect those suspicious activities more accurately than traditional approaches. …”
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