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    Towards Maximising Hardware Resources and Design Efficiency via High-Speed Implementation of HMAC based on SHA-256 Design by Shamsiah, Suhaili, Norhuzaimin, Julai, Rohana, Sapawi, Nordiana, Rajaee

    Published 2024
    “…There are various hash functions, including Message-Digest 5 (MD5), RACE Integrity Primitives Evaluation Message Digest 160 (RIPEMD-160), Secure Hash Algorithm 1 (SHA-1), and Secure Hash Algorithm 256 (SHA-256), among others. …”
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    Article
  2. 2

    Towards Maximising Hardware Resources and Design Efficiency via High-Speed Implementation of HMAC based on SHA-256 Design by Shamsiah, Suhaili, Norhuzaimin, Julai, Rohana, Sapawi, Nordiana, Rajaee

    Published 2024
    “…There are various hash functions, including Message-Digest 5 (MD5), RACE Integrity Primitives Evaluation Message Digest 160 (RIPEMD-160), Secure Hash Algorithm 1 (SHA-1), and Secure Hash Algorithm 256 (SHA-256), among others. …”
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    Article
  3. 3

    End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

    Published 2021
    “…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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    Thesis
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    Optimising Connectivity and Energy : The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by IZZAH NILAMSYUKRIYAH, BUANG, Kartinah, Zen, Syahrul Nizam, Junaini

    Published 2025
    “…This study provides a comprehensive review of energy-efficient routing algorithms for LoRaWAN in mobile IoT applications. A systematic approach is employed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to identify, evaluate, and synthesize pertinent literature, offering an in-depth exploration of existing methodologies, their advantages and limitations, and potential avenues for future research. …”
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    Feature extraction from natural language to aid requirements reuse in software product lines engineering / Noor Hasrina Bakar by Noor Hasrina, Bakar

    Published 2016
    “…Then, linguistic tagging is applied to extract software features followed by applying simple clustering algorithms to form groups of common features. In phase 4, the common features that are grouped together are passed to the feature modelling process and manual feature diagram are constructed as the final output. …”
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    Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB) by Hashim, Nurul Akmal

    Published 2017
    “…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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    Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

    Published 2020
    “…We compared the performance of the state-of-the-art image spam models. Lastly, we pointed out promising directions for future research.…”
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    Dynamic android malware category classification using semi-supervised deep learning by Mahdavifar, Samaneh, Kadir, Andi Fitriah Abdul, Fatemi, Rasool, Alhadidi, Dima, Ghorbani, Ali A

    Published 2020
    “…Our offered dataset comprises the most complete captured static and dynamic features among publicly available datasets. We evaluate our proposed model on CICMalDroid2020 and conduct a comparison with Label Propagation (LP), a well-known semi-supervised machine learning technique, and other common machine learning algorithms. …”
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    Proceeding Paper
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    Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

    Published 2013
    “…The performance of four artificial neural network (ANN) training algorithms was evaluated to identify the training algorithm appropriate for modeling the dynamics of soil pore-water pressure responses to rainfall patterns using multilayer perceptron (MLP) ANN. …”
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    Citation Index Journal
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    Enhancing Secure Sockets Layer Bulk Data Trnsfer Phase Performance With Parallel Cryptography Algorithm by Mohammed Alaidaros, Hashem

    Published 2007
    “…Hashed Message Authentication Code (HMAC) is widely used to provide authenticity, while symmetric encryption algorithms provide confidentiality. …”
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    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

    Published 2013
    “…The outputs from the individual NN models were combined by four different aggregation algorithms in NNs ensemble. …”
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    Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

    Published 2024
    “…To evaluate the model, the model accuracy, precision, recall, F1- score, and confusion matrix were used. …”
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    Thesis
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    Computational simulation for static and dynamic load of rectangular plate in elastic region for analysis of impact resilient structure. by Djojodihardjo, Harijono, Jamali, Hamed, Shokrani, Alireza, Mustapha, Faizal, Zahari, Rizal, Wiriadidjaja, Surjatin

    Published 2012
    “…Further simulations are carried out using commercial codes for some sample applications to explore impact resilient structural characteristics in the elastic region.…”
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    Conference or Workshop Item