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    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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    Thesis
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    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
    “…LED Seven Segment displays have become embedded in our daily lives, beginning with small devices like wristwatches and progressing to massive mechanical equipment used in industry. …”
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    Proceeding Paper
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    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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    Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis by Akash, Nazmus Sakib, Rouf, Shakir, Jahan, Sigma, Chowdhury, Amlan, Uddin, Jia

    Published 2022
    “…This paper represents a model that accounts for the detection of botnets through the use of machine learning algorithms. …”
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    Article
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    Detection of eye movements based on EEG signals and the SAX algorithm by Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.

    Published 2018
    “…Classification algorithms have been investigated in past research to allow detection of eye movement. …”
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    Conference or Workshop Item
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    Detection of Counterfeit Telecommunication Products using Luhn Checksum Algorithm and an Adapted IMEI Authentication Method by Amusa, Morufu, Bamidele, Oluwade

    Published 2020
    “…This algorithm is generally used to validate identification numbers such as IMEI, debit/credit card numbers, social security numbers, national identification numbers etc. …”
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    Journal
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    Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. …”
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    Article
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    An amplitude independent muscle activity detection algorithm based on adaptive zero crossing technique and mean instantaneous frequency of the sEMG signal by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina

    Published 2017
    “…In order to enhance the efficacy of the prosthetic and orthotic robotic devices controlled by surface electromyography (sEMG) signals, muscle activity detection algorithms need to be independent of the amplitude variation in the sEMG signal to make these devices more feasible and reliable for the disabled people. …”
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    Conference or Workshop Item
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    Amplitude independent muscle activity detection algorithm of soft robotic glove system for hemiparesis stroke patients using single sEMG channel by Hameed, Husamuldeen Khalid

    Published 2020
    “…Many algorithms have been developed in the literature to detect muscle activities; however, most of these algorithms depend on amplitude features in the detection process. …”
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    Thesis
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    Moiré Method Based Tilt Sensing System For Landslides Monitoring Using Raspberry PI by Toh, Han Yaung

    Published 2019
    “…An algorithm to detect the centroid of the moiré fringe pattern was developed. …”
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    Monograph
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    Detection of muscle activities in the sEMG signal by using frequency features and adaptive decision threshold by Hameed, Husamuldeen Khalid, Wan Hasan, Wan Zuha, Shafie, Suhaidi, Ahmad, Siti Anom, Jaafar, Haslina, Inche Mat, Liyana Najwa

    Published 2020
    “…Moreover, the decision threshold value must be adaptive to the changes in the sEMG signal characteristics to reduce the number of false alarms that may arise with the fixed threshold and lead to unintended movements to these devices. In this paper, an amplitude-independent algorithm had been developed with an adaptive decision threshold; the algorithm employed only frequency features of the sEMG signal to detect muscle activities. …”
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    Article