Search Results - (( java implementation case algorithm ) OR ( using equalization 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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Article -
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Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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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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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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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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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Microcrack Detection And Noise Reduction In Integrated Circuit Packages
Published 2018“…For the second algorithm, histogram equalization method has three stages, (i) image contrast enhancement through histogram equalization, (ii) image crack segmentation which subtracts the histogram equalized image with the image before histogram equalization process before merging the images using bitwise operation, and (iii) image denoising using morphological opening. …”
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Monograph -
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Garbage truck staff duty roster using genetic algorithm / Nadea Suneeza Zulkifli
Published 2017“…This technique is used because studies have shown reasonably good results when genetic algorithms are applied to the staff-scheduling problem. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm
Published 2018“…The proposed algorithm is applicable to all levels of MLI having equal and non-equal DC sources. …”
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Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images
Published 2012“…The algorithm was written by using MATLAB software. The local tone mapping method is based on the modified contrast limited adaptive histogram equalization (CLAHE) method. …”
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A comparison of watermarking image quality based on dual intermediate significant bit with genetic algorithm
Published 2013“…In this case, when the two hidden bits are equal to the original bits, there will be no change to the other remaining bits.However, if the original value is not equal to the embedded one, the nearest pixel to the original one will be chosen as the watermarked image.The second method, GA method is used to embed two bits of watermarking data within every pixel of the original image and to find the optimal value based on the existing DISB.On the other hand, if the two embedded bits are equal to the original bits then this means the watermarked image is still the same as the original one without any changes, while in the other case GA is used in determining the minimum fitness value in which the fittest is the absolute value between the pixel and chromosome and the value of chromosome between 0-255.The results indicate that the two methods produce a high quality watermarked image, but there is a big difference in the processing time, so the DISB method is faster than the GA method.…”
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