Search Results - (( development activation connection algorithm ) OR ( java application optimisation algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Thesis -
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Improved ADALINE Harmonics Extraction Algorithm for Boosting Performance of Photovoltaic Shunt Active Power Filter under Dynamic Operations
Published 2016“…For evaluation and comparison purposes, both proposed and existing algorithms have been developed. The PV SAPF with both algorithms was simulated in MATLABSimulink respectively, with and without operation or connection of PV. …”
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Improved ADALINE harmonics extraction algorithm for boosting performance of photovoltaic shunt active power filter under dynamic operations
Published 2016“…For evaluation and comparison purposes, both proposed and existing algorithms have been developed. The PV SAPF with both algorithms was simulated in MATLAB-Simulink respectively, with and without operation or connection of PV. …”
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Fundamental active current adaptive linear neural networks for photovoltaic shunt active power filters
Published 2016“…This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC) adaptive linear element (ADALINE) neural network with the integration of photovoltaic (PV) to shunt active power filters (SAPFs) as active current source. …”
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Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
Published 2019“…In the context of active power filtering, the ADALINE technique which was initially developed for a single-phase two-wire system has been further expanded to suit three-phase three-wire system. …”
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Fundamental active current adaptive linear neural networks for photovoltaic shunt active power filters
Published 2016“…This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC) adaptive linear element (ADALINE) neural network with the integration of photovoltaic (PV) to shunt active power filters (SAPFs) as active current source. …”
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Functional Connectivity Assessment on Aging Brain using Functional Near Infrared Spectroscopy (fNIRS)
Published 2017“…A new software algorithm has been developed to derive functional connectivity parameters. …”
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Final Year Project -
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Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
Published 2023“…In the context of active power filtering, the ADALINE technique which was initially developed for a single-phase two-wire system has been further expanded to suit three-phase three-wire system. …”
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A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining
Published 2009“…Moreover, navigation pattern mining has been done by finding connected components in the graph. In the online phase, the longest common subsequence algorithm is used as a new approach in recommendation system for classifying current user activities to predict user next movements. …”
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E-Handrawn Calculator
Published 2008“…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
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Final Year Project -
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Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease
Published 2022“…The classification algorithm developed based on the nonfractal connectivity feature and support vector machine classifier has shown an excellent performance, with an accuracy of 90.3 and 83.3 for the XHSLF dataset and ADNI dataset, respectively. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The main objectives for this project are focusing on the development of user interface that can connect with the machine learning build in Microsoft Azure for pump diagnostic purpose. …”
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Monograph -
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Optimization of supply chain management by simulation based RFID with XBEE Network
Published 2015“…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. This algorithm computes the optimal results of objective functions in a scientific manner. …”
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Forecasting of photovoltaic output using hybrid particle swarm optimization-artificial neural network model / Muhamad Faizol Adli Abdullah
Published 2010“…Two model have been develop: Classical Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) for the prediction of total AC power output from a grid connected photovoltaic system. …”
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Enhancement of bluetooth security authentication using hash-based message authentication code (HMAC) algorithm
Published 2014“…This proposed protocol uses Hash-based Message Authentication Code (HMAC) algorithm with Secure Hash Algorithm (SHA-256). The implementation of this proposal is based on the Arduino Integrated Development Environment (IDE) as software and a Bluetooth (BT) Shield connected to an Arduino Uno R3 boards as hardware. …”
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Proceeding Paper -
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Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim
Published 2019“…In this study, Meta Evolutionary–Firefly Algorithm (EMEFA) was initially developed to expedite the computational time in multi-DG installation with improved accuracy. …”
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Thesis -
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Intelligent DNA signature detection for internet worms
Published 2011“…Internet scanning worms are widely regarded to be a major security threat faced by the Internet community today. Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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Monograph
