Search Results - (( java implementation rsa algorithm ) OR ( program classification issues algorithm ))

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  1. 1

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
  2. 2

    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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    Thesis
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    Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

    Published 2016
    “…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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    Conference or Workshop Item
  5. 5

    Digitally signed electronic certificate for workshop / Azinuddin Baharum by Baharum, Azinuddin

    Published 2017
    “…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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    Thesis
  6. 6

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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    Thesis
  7. 7

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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    Thesis
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    Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

    Published 2019
    “…In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. …”
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    Final Year Project
  11. 11

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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    Thesis
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    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…Back-propagation is the most common artificial neural training algorithm, however it is suffering with the slow convergence rate issue. …”
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    Thesis
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    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…However, wireless communication has critical issues with network failure, and these issues significantly affect the communication system. …”
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    Thesis
  17. 17

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…However, wireless communication has critical issues with network failure, and these issues significantly affect the communication system. …”
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    Thesis
  18. 18

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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    Conference or Workshop Item
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    Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

    Published 2016
    “…The study proposes the use of software metric thresholds in the classification process during the GA representation. …”
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    Thesis
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    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…In this study, DE is chosen and applied to feed forward neural network to enhance the learning process and the network learning is validated in terms of convergence rate and classification accuracy. Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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    Thesis