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  1. 1

    Utilization of canny and velocity bunching algorithms for modelling shoreline change by Marghany, Maged, Hashim, Mazlan

    Published 2006
    “…Then, rate of shoreline is simulated by using velocity bunching model. …”
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    Conference or Workshop Item
  2. 2

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    Thesis
  3. 3

    Analysis of artificial neural network and viola-jones algorithm based moving object detection by Rashidan, M. Ariff, Mohd Mustafah, Yasir, Zainal Abidin, Zulkifli, Zainuddin, N. Afiqah, A. Aziz, Nor Nadirah

    Published 2014
    “…Analysis of moving object detection methods is presented in this paper, includes Artificial Neural Network (ANN) and Viola-Jones algorithm. …”
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    Proceeding Paper
  4. 4

    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani by Seyed Asadollah, Abdiesfandani

    Published 2016
    “…The algorithm simulates two important tasks that are frequently used by the human experts to identify summarizing strategies used to produce the summary sentences: 1) sentences relevance identification; and 2) summarizing strategies identification. …”
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    Thesis
  5. 5

    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

    Published 2018
    “…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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    Thesis
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    Immune-genetic algorithm(IGA) with local search for intrusion detection system in computer network / Hamizan Suhaimi, Saiful Izwan Suliman, and Ismail Musirin by Suhaimi, Hamizan, Suliman, Saiful Izwan, Musirin, Ismail

    Published 2021
    “…The performance in terms of average intrusion detection rate and false alarm rate of the proposed method and other available techniques were analyzed to evaluate and determine the best performance. …”
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    Article
  8. 8

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…In the past decades, machine learning methods have been successfully used in several intrusion detection methods because of their ability to discover and detect novel attacks. …”
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    Thesis
  9. 9

    Recursive linear network modeling for detecting gas leak by Md Akib, Afifi, Saad, Nordin, Asirvadam, Vijanth

    Published 2010
    “…Relative mass loss of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithm. …”
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    Conference or Workshop Item
  10. 10
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    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Results show that the proposed method is able to detect islanding conditions with 100% accuracy, 100% detection rate and 0% false alarm with detection time of less than 0.19s. …”
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    Thesis
  12. 12

    Smart fall detection by enhanced SVM with fuzzy logic membership function by Harum, Norharyati, Khalil, Mohamad Kchouri, Hazimeh, Hussein, Obeid, Ali

    Published 2023
    “…An overall accuracy of about 99.87% in detecting the fall function was obtained. Furthermore, the overall sensitivity of 100% with no false negative rate obtained was achieved by implementing the proposed method. …”
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    Article
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    Fatigue State Detection Through Multiple Machine Learning Classifiers Using EEG Signal by Hasan, Md Mahmudul, Hossain, Mirza Mahfuj, Norizam, Sulaiman

    Published 2023
    “…The study revealed that employing all the classifiers resulted in a satisfactory accuracy rate compared to existing state-of-the-art methods for detecting fatigue states. …”
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    Article
  16. 16

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors.…”
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    Article
  17. 17

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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    Thesis
  18. 18

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…The results of bit error rate simulation have shown that reduced rank-JCE based detectors have an improvement by 5 dB lower than other traditional full rank-JCE based detectors.…”
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    Article
  19. 19

    A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification by Kamaruddin, B., Zabiri, H., Mohd Amiruddin, A.A.A., Teh, W.K., Ramasamy, M., Jeremiah, S.S.

    Published 2020
    “…Based on the 15 benchmark industrial loops with stiction, the proposed BSD-CNN quantification algorithm has shown reasonable accuracy when compared to other published quantification methods in literature. …”
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    Article
  20. 20

    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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    Article