Search Results - (( protocol directed learning algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…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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Spatio-temporal event association using reward-modulated spike-time-dependent plasticity by Yusoff, Nooraini, Ibrahim, Mohammed Fadhil

“…For goal-directed learning in spiking neural networks, target spike templates are usually required.Optimal performance is achieved by minimising the error between the desired and output spike timings.However, in some dynamic environments, a set of learning targets with precise encoding is not always available.For this study, we associate a pair of spatio-temporal events with a target response using a reinforcement learning approach.The learning is implemented in a recurrent spiking neural network using reward-modulated spike-time-dependent plasticity.The learning protocol is simple and inspired by a behavioural experiment from a neuropsychology study.For a goal-directed application, learning does not require a target spike template.In this study, convergence is measured by synchronicity of activities in associated neuronal groups.As a result of learning, a network is able to associate a pair of events with a temporal delay in a dynamic setting. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…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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Distributed denial of service attack in HTTP/2: review on security issues and future challenges by Liang Ming, Leau, Yu-Beng, Ying Xie

“…Additionally, it highlights the potential applicability of deep learning algorithms in the context of the HTTP/2 protocol. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…In machine learning algorithm, choosing the most relevant features for each attack is a very important requirement, especially in mobile ad hoc networks where the network topology dynamically changes. …”
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A review of deep learning-based defect detection and panel localization for photovoltaic panel surveillance system by Mohamed Ameerdin, Muhammad Irshat, Jamaluddin, Muhammad Herman, Shukor, Ahmad Zaki, Mohamad, Syazwani

“…This review introduces an integrated deep learning framework that leverages Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and You Only Look Once (YOLO) algorithms to enhance defect detection in solar panels. …”
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Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

“…PSO is lightweight heuristic optimization algorithm with each CH will move towards the best solutions by individual interaction with one another while learning from their own experience. …”
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Comparative evaluation of anomaly-based controller area network IDS by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

“…This work contributes to these efforts by reporting results of the comparative evaluation of four statistical and two machine learning-based CAN intrusion detection algorithm, against the Real ORNL Automotive Dynamometer (ROAD) CAN intrusion dataset. …”
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Advancements in battery technologies and management systems for electric vehicles A mini-review by Shanmuganathan, Elengespwaran, Norazlianie, Sazali, Kettner, Maurice, Salim, Naqib, Ismayuzri, Ishak

“…Additionally, the role of simulation tools such as Simulink in evaluating various charging methodologies is discussed, highlighting their significance in optimizing charging protocols. The review also examines developments in direct current (DC) fast charging infrastructure, including technologies such as Tesla’s Superchargers and AVL’s advanced charging solutions, which aim to provide rapid and efficient charging while addressing thermal and electrochemical challenges. …”
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Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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