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  1. 1
    Selective video encryption algorithm based on H.264/AVC and AES

    Selective video encryption algorithm based on H.264/AVC and AES by Omar zakaria, Mohamed Abomhara, Khalifa, Othman Omran

    Published 2011
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  2. 2
    Performance evaluation of symmetric cryptography algorithm for database system / Mariam Azwa Yazid

    Performance evaluation of symmetric cryptography algorithm for database system / Mariam Azwa Yazid by Yazid, Mariam Azwa

    Published 2015
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  3. 3
    A new KD-3D-CA block cipher with dynamic S boxes based on 3D cellular automata

    A new KD-3D-CA block cipher with dynamic S boxes based on 3D cellular automata by Hamdi, Ayman Majid

    Published 2019
    “…Lastly, KD-3D-CA Block cipher is more complex and it outperforms AES with more than 25% for different key sizes. Deductively, the proposed KD-3D-CA block cipher algorithm is more secure than other block cipher algorithms and can be implemented for data encryption and decryption.…”
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  4. 4
    Dynamic key scheduling algorithm for block ciphers using quasigroup string transformation

    Dynamic key scheduling algorithm for block ciphers using quasigroup string transformation by Hassan Disina, Abdulkadir

    Published 2018
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  5. 5
    Development of a personified face emotion recognition technique using fitness function

    Development of a personified face emotion recognition technique using fitness function by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa

    Published 2009
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  6. 6
    Estimating Face Emotion using Genetic Algorithm

    Estimating Face Emotion using Genetic Algorithm by Karthigayan, M., Mohd Rizon, Muhamed Juhari, Sazali, Yaacob, Nagarayan, R.

    Published 2009
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  7. 7
    Japanese face emotions classification using lip features

    Japanese face emotions classification using lip features by Mohamad Rizon, Mohamed Juhari, Muthukaruppan, Karthigayan, Sazali, Yaacob, Nagarajan, R.

    Published 2009
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  8. 8
    Pixel Intensity-Based Contrast Algorithm (PICA) for Image Edges Extraction (IEE)

    Pixel Intensity-Based Contrast Algorithm (PICA) for Image Edges Extraction (IEE) by Al-Ghaili A.M., Kasim H., Al-Hada N.M., Othman M., Saleh M.A., Jihua W.

    Published 2023
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  9. 9
    Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion

    Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

    Published 2009
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  10. 10
    Identification of Electrooculography Signals Frequency Energy Distribution Using Wavelet Algorithm

    Identification of Electrooculography Signals Frequency Energy Distribution Using Wavelet Algorithm by W. Daud, W. M. Bukhari, Sudirman, Rubita, Omar, Camallil

    Published 2011
    “…Conclusion: From the result, it is proved that the different EOG signals exhibit differences in signals energy with their corresponding scale such as leftward with scale 6 (8- 16Hz), rightward with scale 8 (2-4Hz), downward with scale 9 (1-2Hz) and upward with level 7 (4-8Hz). …”
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  11. 11
    Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification

    Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification by Kamarudin, Noraziahtulhidayu, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abushariah, Mohammad A. M., Hashim, Shaiful Jahari, Hassan Azhari, Abd Rauf

    Published 2015
    “…In order to verify our methodology, audio files have been collected for Surat Ad-Duhaa for five different Quranic accents (Qiraat), namely: (1) Ad-Duri, (2) Al-Kisaie, (3) Hafs an A’asem, (4) IbnWardan, and (5) Warsh. …”
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  12. 12
    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…In our research, extraction pattern from the first module will be fed to this algorithm and is used to make the prediction of named entity candidate category. …”
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  13. 13
    Development and implementation of GPS for location tracking / Ahmad Ashraff Ariffin

    Development and implementation of GPS for location tracking / Ahmad Ashraff Ariffin by Ariffin, Ahmad Ashraff

    Published 2011
    “…This algorithm has the ability of extract the data from GPS receiver and communicate via RS232 to test the interaction from GPS receiver. …”
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  14. 14
    Instant Sign Language Recognition by WAR Strategy Algorithm Based Tuned Machine Learning

    Instant Sign Language Recognition by WAR Strategy Algorithm Based Tuned Machine Learning by Abd Al-Latief S.T., Yussof S., Ahmad A., Khadim S.M., Abdulhasan R.A.

    Published 2025
    “…Afterward, the WAR Strategy optimization algorithm has been adopted in two procedures, first in optimizing the extracted set of features, and second to fine-tune the hyperparameters of six standard machine learning models in order to achieve precise and efficient sign language recognition. …”
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  15. 15
    PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm

    PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm by Muhamad Zahim, Sujod, Siti Nor Azlina, Mohd Ghazali, Mohd Fadzil, Abdul Kadir, Al-Shetwi, Ali Qasem

    Published 2024
    “…Scalable PV array is modelled with the generated power of 10 kW for small-scale, 250 kW for medium-scale and 2 MW for large-scale. In the training and testing of the models, the RF-CV algorithm with set combination of FE was employed to diagnose and classify different types of faults. …”
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  16. 16
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. In addition, amongst the eighteen TL models evaluated based on the CWT transformation, fourteen was f ound to be able to extract the features reasonable, i.e., VGG16, VGG19, ResNet101, ResNet101 V2, ResNet152, ResNet152 V2, Inception V3, Inception ResNet V2, Xception, MobileNetV2, DenseNet 121, DenseNet 169, NasNetMobile and NasNetLarge. …”
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  17. 17
    Personalized human emotion classification using genetic algorithm

    Personalized human emotion classification using genetic algorithm by Mohd Rizon, Hazry, Desa, Karthigayan, M., Nagarajan, Ramachandran, Alajlan, N., Sazali, Yaacob, Prof. Dr., Nor Azmi, Johari, Ina Suryani, Ab Rahim

    Published 2010
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  18. 18
    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)

    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

    Published 2017
    “…The spike encoding was used for feature extraction. The algorithm for this learning model adopted the reward-modulated STDP. …”
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  19. 19
    Design and performance evaluation of parallel elliptic curve cryptosystem with GF(P) projective coordinates

    Design and performance evaluation of parallel elliptic curve cryptosystem with GF(P) projective coordinates by Hussein Fayiz, Mohammad Al-Khatib

    Published 2012
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  20. 20
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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