Search Results - (( java implementation case algorithm ) OR ( data detection based algorithm ))
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Pairwise testing tools based on hill climbing algorithm (PTCA)
Published 2014“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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Undergraduates Project Papers -
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Examination timetabling using genetic algorithm case study: KUiTTHO
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Java based expert system for selection of natural fibre composite materials
Published 2013“…In this paper, we develop a technology for the materials selection system using Java based expert system. The weighted-range method (WRM) was implemented to identify the range value and to scrutinise the candidate materials. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…According to the simulation results, the proposed algorithm produces the best solution among all algorithms in the proposed cases. � 2021 Little Lion Scientific…”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…CS and JA have implemented in the same platform (Intellij IDEA Community Edition 2020.2.3) using the same language (Java). …”
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Conference or Workshop Item -
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SANAsms: Secure short messaging system for secure GSM mobile communication
Published 2008“…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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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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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm
Published 2016“…It provides an algorithm to the discovery of error and duplicates entries in the data sets of existing data warehouse. …”
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MotionSure: a cloud-based algorithm for detection of injected object in data in motion
Published 2017“…Although there are few algorithms for data protection in the Cloud, However, such algorithms are still prone to attack, especially in real-time data movement due to the mechanism employed. …”
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Proceeding Paper -
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Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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Conference or Workshop Item -
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…However, the current DBN.NIDS model is still ineffective for large-scale real-world data due to some issues: 1) the pre-training of the DBN algorithm includes simple feature learning which does not work very well to extract important features from the attack data, 2) the classification task of the DBN algorithm is a poor detection for imbalanced class dataset and 3) the design of the DBN model could be weak and need to be continuously updated by modern definitions of abnormal to detect recent attacks. …”
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The effect of different similarity distance measures in detecting outliers using single-linkage clustering algorithm for univariate circular biological data
“…Clustering algorithms can be used to create an outlier detection procedure in univariate circular data. …”
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