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1
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…The aim of this evolution is to reflect the unseen time overhead incurred by optimal real-time algorithm, represented by LRE-TL, which might hinder the claimed optimality of such algorithms when they are practically implemented. …”
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Conference or Workshop Item -
2
Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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Thesis -
3
A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
4
Network game (Literati) / Chung Mei Kuen
Published 2003“…With the powerful networking features of Java applet, it is expected that this project would produce a real game engine. …”
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Thesis -
5
Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Final Year Project / Dissertation / Thesis -
6
Route Optimization System
Published 2005“…Using that process, we have settled on Java as our development platform as we found it able to both implement DA and the GIS component (map display and manipulation). …”
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Final Year Project -
7
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Thesis -
8
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Monograph -
9
Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol implemented in real RFID system outperforms other related protocols because of 13.46 % shorter read time and write time consumed. …”
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Thesis -
10
Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural
Published 2006“…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
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Monograph -
11
Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms
Published 2022“…Data resampling technique (SMOTETomek) is applied and shows further improvement on the accuracy of predictions by machine learning algorithms when deal with imbalance data. …”
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Article -
12
A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…In this work, simple machine learning methods are used to classify breast cancer microarray data to normal and relapse. …”
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Article -
13
The Impact of Normalization Techniques on Performance Backpropagation Networks
Published 2004“…This study explored several normalization techniques using backpropagation learning. …”
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Thesis -
14
Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…Based on its simplicity, the K-means algorithm has been used in many fields. This paper proposes improved normalization and standardization techniques for higher purity in K-means clustering experimented with benchmark datasets from UCI machine learning repository and it was found that all the proposed techniques’ performance was much higher compared to the conventional K-means and the three classic transformations, and it is evidently shown by purity and Rand index accuracy results.…”
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Article -
15
Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. …”
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Proceedings -
16
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. The image clustering is major part of data mining where study about how to binds the similar data together in a cluster and show the meaningful data. …”
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Thesis -
17
One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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Student Project -
18
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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Thesis -
19
Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki
Published 2024“…Further enhancements might involve including machine learning algorithms to improve the prototype's accuracy by learning from a larger dataset, which would eventually improve the prototype's ability to offer deep understanding into handwriting patterns related to dyslexia.…”
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Thesis -
20
A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru
Published 2024“…Data preprocessing plays a crucial role in enhancing the performance of machine learning algorithms for classification tasks. …”
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