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  1. 1
    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe

    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

    Published 2017
    “…Java programming language is used to implement the algorithm. …”
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  2. 2
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
    “…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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  3. 3
    A parallel version of a binary method and vector addition chains precomputation for exponentiation in RSA / Siti Khatijah Nor Abdul Rahim and Siti Rozanae Ismail

    A parallel version of a binary method and vector addition chains precomputation for exponentiation in RSA / Siti Khatijah Nor Abdul Rahim and Siti Rozanae Ismail by Abdul Rahim, Siti Khatijah Nor, Ismail, Siti Rozanae

    Published 2006
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    Research Reports
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  4. 4
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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  5. 5
    Implementing Station-to-Station protocol using Multi Prime RSA Cryptosystem / Muhammad Arif Musa Abdullah

    Implementing Station-to-Station protocol using Multi Prime RSA Cryptosystem / Muhammad Arif Musa Abdullah by Abdullah, Muhammad Arif Musa

    Published 2023
    “…The result will also produce the algorithm for implementing Multi Prime RSA cryptosystem into Station-to-Station protocol. …”
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  6. 6
    Comparative analysis of text classification algorithms for automated labelling of quranic verses

    Comparative analysis of text classification algorithms for automated labelling of quranic verses by Adeleke, Abdullah, Samsudin, Noor Azah, Mustapha, Aida, Mohd Nawi, Nazri

    Published 2017
    “…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. …”
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  7. 7
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…As the result, the pattern classification accuracy is also xii increase. For examples, after applying the proposed integration system, the classification accuracy of Fisher’s Iris, Wine and Bacteria18Class has been increased from 88.67% to 96.00%, from 78.33% to 83.45% and from 93.33% to 94.67% respectively as compared to only used unsupervised clustering algorithm. …”
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  8. 8
    Multi-label learning based on positive label correlations using predictive apriori

    Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

    Published 2019
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  9. 9
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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  10. 10
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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  11. 11
    Multi label ranking based on positive pairwise correlations among labels

    Multi label ranking based on positive pairwise correlations among labels by Alazaidah, Raed, Ahmad, Farzana Kabir, Mohsin, Mohamad

    Published 2020
    “…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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  12. 12
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  13. 13
    Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm

    Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm by Dhewa, Oktaf Agni, Utama, Safitri Yuliana, Nasuha, Aris, Gunawan, Teddy Surya, Pratama, Gilang Nugraha Putu

    Published 2024
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  14. 14
    Encryption Technology on Windows Workstation

    Encryption Technology on Windows Workstation by Amdan, Zulkhaimi

    Published 2004
    “…This study is done because current encryption method in Windows environment is quite weak (e.g.: Windows password) and easily breakable using program like LC4(@stake LC4, about). Windows NT, 2000 and XP use Security Accounts Manager (SAM) file to store encrypted users passwords using RSA MD4 scheme(Windows NT SAM permission Vulnerability, bulletin), so if the RSA technique is enhanced it will enable a stronger and harder to break workstations. …”
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    Final Year Project
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  15. 15
    Performances of machine learning algorithms for binary classification of network anomaly detection system

    Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

    Published 2018
    “…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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    Conference or Workshop Item
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  16. 16
    Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie

    Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie by Mat Saffie, Nur Amira

    Published 2019
    “…Furthermore, most classification algorithms, using either fuzzy or non-fuzzy approaches, produce results in the form of crisp or categorical classification outcomes. …”
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  17. 17
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  18. 18
    The classification of FTIR plastic bag spectra via label spreading and stacking

    The classification of FTIR plastic bag spectra via label spreading and stacking by Almanifi, Omair Rashed Abdulwareth, Ng, Jee Kwan, Anwar P. P., Abdul Majeed

    Published 2021
    “…Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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  19. 19
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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  20. 20
    EMOTION RECOGNITION USING GALVANIC SKIN RESPONSE (GSR) SIGNAL

    EMOTION RECOGNITION USING GALVANIC SKIN RESPONSE (GSR) SIGNAL by RAMOS UKAR, YAKOBUS

    Published 2022
    “…The classified affective GSR signals with labels were obtained from the arousal seven-point emotional scale approach using machine learning algorithms. …”
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    Final Year Project Report / IMRAD
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