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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING
Published 2021“…The encryption algorithms are playing an important part in the protection level for data. …”
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Thesis -
2
Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…Internet communication has become more common in this modern world recently, and one of the important algorithms used is ABS algorithm. However, most of the users have inadequate knowledge and understanding regard to this algorithm implementation in the communication field, as well as the level of security and accuracy will be questioned by the users because of the necessary to maintain the confidentiality of particular data transferred. …”
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Undergraduates Project Papers -
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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4
Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.]
Published 2023“…Customer churn is defined as the tendency of customers to cease doing business with a company in a given period. ABC Multistate Bank faces the challenges to hold clients. The purpose of this study is to apply machine learning algorithms to develop the most effective model for predicting bank customer churn. …”
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Article -
5
A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…Level one is the development of userID and password, level two involve the insertion of the testing parameter speed coding. …”
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6
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. The test results show that the Boyer Moore and Knuth Morris Pratt algorithms have an accuracy rate of 100%, and the Horspool algorithm 85.3%. …”
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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe
Published 2017“…We use a parallel technique that divides RSA power process into seperate threads and employs the use of Chinese Remainder Theorem (CRT) to decrease the time required for both encryption and decryption operation. Java programming language is used to implement the algorithm. …”
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Design and Implementation of Data-at-Rest Encryption for Hadoop
Published 2017“…Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. …”
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Conference or Workshop Item -
9
Design and Implementation of Data-at-Rest Encryption for Hadoop
Published 2017“…Therefore, the AES encryption algorithm has been implemented in HDFS to ensure the security of data stored in HDFS. …”
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Conference or Workshop Item -
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The Determinant Factors for the Issuance of Central Bank Digital Currency (CBDC) in Malaysia using Machine Learning Framework
Published 2024“…The overall CentralBank Digital Currency Project Index (CBDCPI) was selected as a target variable,while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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Article -
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The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework
Published 2024“…The overall Central Bank Digital Currency Project Index (CBDCPI) was selected as a target variable, while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…This research explores the application of unsupervised learning, a subset of Artificial Intelligence (AI), to analyze customer behavior in accepting personal loans within the banking sector. …”
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Evaluating Machine Learning Algorithms for Fake Currency Detection
Published 2024“…In this study, we evaluate the effectiveness of six supervised machine learning algorithms—K-Nearest Neighbor, Decision Trees, Support Vector Machine, Random Forests, Logistic Regression, and Naive Bayes—in detecting the authenticity of banknotes. …”
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Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
Published 2005“…The third objective is to perform Vertical Splitting Algorithm technique for digit segmentation. And lastly, to develop an Artificial Neural Network for digit recognition. …”
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Student Project -
15
Loan default prediction using machine learning algorithms: a systematic literature review 2020 -2023
Published 2024“…This study conducts a systematic literature review (SLR) on the prediction of loan defaults using machine learning algorithms (MLAs) from 2020 to 2023. It critically examines the transition from traditional statistical models to advanced ML techniques in assessing credit risk, with a focus on the banking sector's need for reliable default prediction methods. …”
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Loss minimization in load flow simulation in power system
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Learning Object -
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Machine learning based return prediction for digital financial portfolios
Published 2025“…The machine learning algorithm is introduced to optimize the digital financial portfolio investment return prediction system. …”
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Hybrid BLEU Algorithm For Structured Exam Management System
Published 2008“…Due to this problem, "Hybrid BLEU algorithm for Structured Exam Management System " is develop to aid the lecturers during assessment in the construction of quiz and test. …”
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Thesis -
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Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE
Published 2012“…The use of this learning technique has been increased in various domains such as e-commerce, banking and finance, as well as for speech and feature recognition to learn and classify intricate information. …”
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Article -
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Suspicious activities detection for anti-money laundering using machine learning techniques
Published 2025“…To solve money laundering, more effective techniques for detecting suspicious transactions must be developed. Machine learning is able to learn complex relationships within large datasets then identify anomalies that deviate from well-defined patterns. …”
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Final Year Project / Dissertation / Thesis
