Search Results - (( develop missing learning algorithm ) OR ( java implementation rsa algorithm ))
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RSA Encryption & Decryption using JAVA
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 -
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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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Thesis -
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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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Article -
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Secure Image Steganography Using Encryption Algorithm
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 -
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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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Thesis -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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Article -
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Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm
Published 2021“…In this work, preliminary study of the implementation of one of the latest deep learning algorithms, i.e. YOLOv5, has been carried out in the detection and classification of missing road lane markings. …”
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Proceeding Paper -
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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm
Published 2024“…Missing data poses a significant challenge in extensive datasets, particularly those containing time-series information, leading to potential inaccuracies in data analysis and machine learning model development. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
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Thesis -
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
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An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa
Published 2020“…The results demonstrate that the performance measure of 90.77% has been recorded for detection rate with average processing time of 1.02 to 1.04 seconds per image. The developed algorithm is reported to be reliable to assist the radiologist in ischemic PF diagnosis which is important for future healthcare needs.…”
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Thesis -
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Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network
Published 2006“…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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Final Year Project Report / IMRAD -
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours
Published 2010“…An enhanced Bucket Brigade Algorithm (BBA) is developed to avoid the problem of choosing classifiers with high strength value but with incorrect behaviour. …”
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Thesis -
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Federated deep learning for automated detection of diabetic retinopathy
Published 2022“…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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Proceeding Paper -
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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