Search Results - (( java implementation level algorithm ) OR ( using detection model algorithm ))
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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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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
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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5
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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Article -
7
Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Student Project -
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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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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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10
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…The detection model used in this paper is Single-Shot multibox Detection (SSD) MobileNet detection model. …”
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Proceedings -
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Fraud detection in telecommunication industry using Gaussian mixed model
Published 2013“…In this article, we propose a new fraud detection algorithm using Gaussian mixed model (GMM), a probabilistic model successfully used in speech recognition problem. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…Next, the neural network is retrained using these ideal values in order for the intrusion detection model to be able to recognize new attacks. …”
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Article -
15
The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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16
Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms
Published 2024“…Diabetic retinopathy is one of the leading causes of vision impairment noticed among individuals with prolonged diabetes. Early-stage detection is very crucial for its treatment. Now, we present a hybrid model which is a combination of U-Net algorithm used for image segmentation and Vision Transformer for classification. …”
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Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti...
Published 2018“…Slope variability model is an algorithm that is being used for detecting terrain roughness. …”
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18
Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…The accuracy of fake news detection models relies mainly on the quality of the extracted features and the method used in detection. …”
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19
Human face detection using skin color segmentation and watershed algorithm
Published 2017“…This study provides depth analysis on most prominent color models. The use of those color models can handle well-defined problems in face detection such as occlusions, poses, and illumination conditions. …”
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Article -
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Experimenting the dendrite cell algorithm for disease outbreak detection model
Published 2014“…The characteristics of early outbreak signal which are weak and behaved under uncertainties has brought to the development of outbreak detection model based on dendrite cell algorithm.Although the algorithm is proven can improve detection performance, it relies on several parameters which need to be defined before mining.In this study, the most appropriate parameter setting for outbreak detection using dendrite cell algorithm is examined.The experiment includes four parameters; the number of cell cycle update, the number of dendrite cell allowed to be in population, weight, and migration threshold value. …”
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