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  1. 1
    Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA)

    Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA) by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Ferda, Ernawan, Syifak, Izhar Hisham, Mohd Faizal, Ab Razak

    Published 2023
    “…This experiment used real 3799 Android samples with 217 features and achieved the best accuracy rate of detection of more than 98% by using Unordered Fuzzy Rule Induction (FURIA).…”
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  2. 2
    Improved Malware detection model with Apriori Association rule and particle swarm optimization

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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  3. 3
    Dingle's Model-based EEG Peak Detection using a Rule-based Classifier

    Dingle's Model-based EEG Peak Detection using a Rule-based Classifier by Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai

    Published 2015
    “…The employment of peak detection algorithm is prominent in several clinical applications such as diagnosis and treatment of epilepsy patients, assisting to determine patient syndrome, and guiding paralyzed patients to manage some devices. …”
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  4. 4
    WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.]

    WURFL detection engine using cosine string similarity algortlhm / Illiasaak Ahmad ... [et al.] by Ahmad, Illiasaak, Anak Buja, Alya@Geogiana, Abdullah Sani, Anis Shobirin

    Published 2013
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  5. 5
    Approach for detecting lane line boundaries / Mamadou Baldeh

    Approach for detecting lane line boundaries / Mamadou Baldeh by Baldeh, Mamadou

    Published 2020
    “…In this paper, previous vision based lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. …”
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  6. 6
    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State

    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State by Mohamed, Shakir, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  7. 7
    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state

    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  8. 8
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
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  9. 9
    Multiple and solid data background scheme for testing static single cell faults on SRAM memories

    Multiple and solid data background scheme for testing static single cell faults on SRAM memories by Zakaria, Nor Azura

    Published 2013
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  10. 10
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
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  11. 11
    Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System

    Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System by Tawafan, Adnan, Sulaiman , Marizan, Ibrahim, Zulkifilie

    Published 2012
    “…High impedance fault (HIF) is abnormal event on electric power distribution feeder which does not draw enough fault current to be detected by conventional protective devices. The algorithm for HIF detection based on the amplitude ratio of second and odd harmonics to fundamental is presented. …”
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  12. 12
    Shunt active power filter with modified synchronous reference frame technique and fuzzy logic current controller for harmonic mitigation

    Shunt active power filter with modified synchronous reference frame technique and fuzzy logic current controller for harmonic mitigation by Suleiman, Musa

    Published 2017
    “…From both results, the proposed algorithms show good performances when compared with the conventional algorithms. …”
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  13. 13
    Vision Based Multi Sensor Feedback System For Robot System With Intelligent

    Vision Based Multi Sensor Feedback System For Robot System With Intelligent by Syed Mohamad Shazali, Syed Abdul Hamid

    Published 2009
    “…Finally, a set of experiments to validate the proposed algorithms has been conducted. The algorithms function with success rate from 74% up to 100% and could handle the orientation of a tilted object up to 45 degrees. …”
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  14. 14
    Comparison between fuzzy and non-fuzzy classification methods in the prediction of residential household water leakage / Nor Aishah Md Noh, Dr. Khairul Anwar Rasmani and Nur Rasyida Mohd Rashid

    Comparison between fuzzy and non-fuzzy classification methods in the prediction of residential household water leakage / Nor Aishah Md Noh, Dr. Khairul Anwar Rasmani and Nur Rasyid... by Md Noh, Nor Aishah, Rasmani, Khairul Anwar, Mohd Rashid, Nur Rasyida

    Published 2013
    “…The aim of this research is to predict residential households water leakage using models created based on training data with fuzzy rule-based and non-fuzzy rule-based algorithms available in WEKA Machine Learning Software (Witten and Frank, 2005). …”
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  15. 15
    Compression Header Analyzer Intrusion Detection System (CHA - IDS) for 6LoWPAN Communication Protocol

    Compression Header Analyzer Intrusion Detection System (CHA - IDS) for 6LoWPAN Communication Protocol by Napiah, Mohamad Nazrin, Idris, Mohd Yamani Idna, Ramli, Roziana, Ahmedy, Ismail

    Published 2018
    “…Prior 6LoWPAN intrusion detection system (IDS) utilized several features to detect various malicious activities. …”
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  16. 16
    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction

    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

    Published 2013
    “…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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  17. 17
    Implementation of RBG-HS-CbCr skin colour model using mobile python PyS60

    Implementation of RBG-HS-CbCr skin colour model using mobile python PyS60 by Ngui,, Lin Hui.

    Published 2009
    “…These algorithms are often tested and applied on PC. …”
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  18. 18
    Portable Stress Detection System for Autistic Children Using Fuzzy Logic

    Portable Stress Detection System for Autistic Children Using Fuzzy Logic by Melinda Melinda, Verdy Setiawan, Yunidar Yunidar, Gopal Sakarkar, Nurlida Basir

    Published 2024
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  19. 19
    Enhancing navigation for the visually impaired: a Mamdani type 1 fuzzy logic approach to obstacle detection

    Enhancing navigation for the visually impaired: a Mamdani type 1 fuzzy logic approach to obstacle detection by Ibharim, Aisyah, Toha, Siti Fauziah, Nordin, Nor Hidayati Diyana, Mohammad O., Tokhi

    Published 2025
    “…Most previous research has focused on image detection algorithms for assistive devices, but they are less reliable in poor visibility and sensitive to environmental conditions. …”
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  20. 20
    An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach

    An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach by Khan, T., Singh, K., Shariq, M., Ahmad, K., Savita, K.S., Ahmadian, A., Salahshour, S., Conti, M.

    Published 2023
    “…The proposed machine learning algorithm extracts various trust features such as Co-Location Relationship (CLR), Co-Work Relationship (CWR), Cooperativeness-Frequency-Duration (CFD), and Reward (R) to obtain a robust trust rating of sensor devices and predict future misbehavior. …”
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