Search Results - (( variables classification mining algorithm ) OR ( program implementation rsa algorithm ))
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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe
Published 2017“…Java programming language is used to implement the algorithm. …”
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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING
Published 2021“…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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Implementing Station-to-Station protocol using Multi Prime RSA Cryptosystem / Muhammad Arif Musa Abdullah
Published 2023“…The result will also produce the algorithm for implementing Multi Prime RSA cryptosystem into Station-to-Station protocol. …”
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Student Project -
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Using fuzzy association rule mining in cancer classification
Published 2011“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
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Encryption Technology on Windows Workstation
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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Crypto Embedded System for Electronic Document
Published 2006“…The RSA algorithm is implemented in a re-configurable hardware, in this case Field Programmable Gate Array (FPGA). …”
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Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2025“…Therefore, it is advisable for future studies to implement robust classification algorithms, such as ensemble methods, to effectively manage and extract potential insights.…”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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Thesis -
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Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024Proceedings Paper -
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Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms
Published 2016“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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Ensemble learning for multidimensional poverty classification
Published 2020“…Analysis of this study showed that Per Capita Income, State, Ethnic, Strata, Religion, Occupation and Education were found to be the most important variables in the classification of poverty at a rate of 99% accuracy confidence using Random Forest algorithm.…”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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Modeling forest fires risk using spatial decision tree
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Digitally signed electronic certificate for workshop / Azinuddin Baharum
Published 2017“…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Improving Classification Accuracy of Scikit-learn Classifiers with Discrete Fuzzy Interval Values
Published 2020“…Thus, the objective of this study is to observe the effect of fuzzy elements inside the discretization phase on the classification accuracy of Scikit-learn classifiers. In this study, fuzzy logic has been proposed to assist the existing discretization technique through fuzzy membership graph, linguistic variables and discrete interval values. …”
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Conference or Workshop Item -
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