Search Results - (( features detection device algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1

    Comparison of Feature Extractors for Real-Time Object Detection on Android Smartphone by Saipullah, Khairul Muzzammil

    Published 2013
    “…However due to the development of embedded hardware and object detection algorithm, current embedded device may be able to execute the object detection algorithm in real-time. …”
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    Article
  2. 2

    ANALYSIS OF REAL-TIME OBJECT DETECTION METHODS FOR ANDROID SMARTPHONE by Saipullah, Khairul Muzzammil

    Published 2012
    “…However due to the development of embedded hardware and object detection algorithm, current embedded device may be able to execute the object detection algorithm in real-time. …”
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    Conference or Workshop Item
  3. 3

    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
  4. 4

    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
    “…The algorithm does not employ any amplitude features in the detection process and employs only frequency features of the sEMG signal; therefore it is amplitude independent and can detect muscle activities in signals that have low signal to noise ratio. …”
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  5. 5

    Bio-inspired for Features Optimization and Malware Detection by Mohd Faizal, Ab Razak, Nor Badrul, Anuar, Fazidah, Othman, Ahmad, Firdaus, Firdaus, Afifi, Rosli, Salleh

    Published 2018
    “…A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications. …”
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  6. 6

    Bio-inspired for Features Optimization and Malware Detection by Razak, Mohd Faizal Ab, Anuar, Nor Badrul, Othman, Fazidah, Firdaus, Ahmad, Afifi, Firdaus, Salleh, Rosli

    Published 2018
    “…A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications. …”
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    Article
  7. 7

    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
  8. 8

    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
    “…However, in machine learning intelligence detection, too many insignificant features will decrease the percentage of the detection’s accuracy. …”
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    Article
  9. 9

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Feature selection has decreased the features from 41 to 21 features for intrusion detection and later normalization method is employed to perform and reduce the differences among the data. …”
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    Thesis
  10. 10
  11. 11

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

    Published 2017
    “…We extracted 30 different features from network traffic. We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  12. 12
  13. 13

    Anomaly detection in system log files using machine learning algorithms / Zahedeh Zamanian by Zahedeh, Zamanian

    Published 2019
    “…Moreover, log files have a lot of irrelevant and redundant features that act as noise. Also, log files are heterogenous and cannot fed them directly in machine learning algorithms. …”
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    Thesis
  14. 14

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
  15. 15

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
  16. 16

    An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

    Published 2019
    “…These features are able to disclose the sensitive information stored on the Android mobile devices. …”
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    Thesis
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    Classification of hand gestures from EMG signals / Diaa Albitar by Albitar, Diaa

    Published 2022
    “…Neighbourhood Component Analysis (NCA) are used as features selection technique has reduced the features to fourteen. …”
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    Thesis
  19. 19

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…Recently, deep learning algorithms for automatic feature representation have also been proposed to lessen the burden of reliance on handcrafted features and to increase performance accuracy. …”
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    Article
  20. 20

    Android mobile malware detection model based on permission features using machine learning approach by Sharfah Ratibah, Tuan Mat

    Published 2022
    “…Chi-square and information gain algorithms were used for features selection. The aim is to learn the behaviour of permission features that react to the accuracy according to the number of features. …”
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    Thesis