Search Results - (( java application optimisation algorithm ) OR ( enable interactive learning 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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Visualization Tool for Pathfinding Algorithms by Mathias Sam, Francis

“…By incorporating interactive features and step-by-step animations of popular pathfinding algorithms, the tool empowers students to actively engage in the learning process and experiment with different algorithmic approaches. …”
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Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

“…Python scripts can now be transformed into interactive web apps through the integration of Streamlit, enabling dynamic viewing and real-time interaction with classification results. …”
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Fast and efficient sequential learning algorithms using direct-link RBF networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George

“…Novel fast and efficient sequential learning algorithms are proposed for direct-link radial basis function (DRBF) networks. …”
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Innovating education: AI-powered self-instructional materials for the Moodle platform by Mohd Yatim, Siti Ainor, Ramli, Nurulhuda, Abdul Hamid, Hazrul, Mansor, Mohd Asyraf

“…The SIM utilizes AI algorithms to personalize learning paths, adapt to individual student pacing, and offer interactive tutorials, adaptive quizzes, and real-time feedback. …”
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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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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Adil Soomro, Zubair, Adrianshah, Andi

“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Zubair Adil Soomro, Zubair Adil Soomro, Andi Adrianshah, Andi Adrianshah

“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Soomro, Zubair Adil, Adrianshah, Andi

“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Abu Bakar, Mohamad Hafiz, Shamsudin, Abu Ubaidah, Abdul Rahim, Ruzairi, Adil Soomro, Zubair, Adrianshah, Andi

“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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'Chapter 10: 5G-enabled IoT applications in healthcare: Transforming the Industry 5.0 healthcare landscape' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 T... by Mohamad Nazim, Jambli, Mohamad Zul Haziq, Mohd Fadzli, Sinarwati, Mohamad Suhaili, Nur Haryani, Zakaria

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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning by Mohamad Hafiz Abu Bakar, Mohamad Hafiz Abu Bakar, Abu Ubaidah Shamsudin, Abu Ubaidah Shamsudin, Ruzairi Abdul Rahim, Ruzairi Abdul Rahim, Zubair Adil Soomro, Zubair Adil Soomro, Andi Adrianshah, Andi Adrianshah

“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

“…By providing a holistic perspective of student performance and course interactions, the proposed learning analytics framework holds great promise for educational institutions seeking data-driven strategies to enhance student outcomes and optimize learning experiences.…”
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Immersive AR pet game with hand motion by Chong, Jing Voon

“…ManoMotion is a hand-tracking software that uses machine learning algorithms to track and recognise hand movements in real-time. …”
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Innovating communication adaptation on social media using AI-based decision support systems by Zakaria, Noor Azura, Adriana, Dadi, Budi, Danang Surya, Mardiana, Mardiana, Rafika, Ageng Setiani, Asmawati, Ari

“…Leveraging intelligent algorithms, the research investigates mechanisms that enable dynamic analysis and personalized recommendations to improve message clarity, relevance, and impact. …”
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Disability people: SiLang translator / Elhan Marzuki … [et al.] by Marzuki, Elhan, Mohamed Hanapi, Halme Hakemie, Abdullah, Amirah Fakhira, Mohd Azmy, Fify Ashaqiera, Shahrulnizam, Nuralia Nabihah, Salimin, Nur Fitrialia, Daud, Shahreena

“…By leveraging advanced computer vision and machine learning algorithms, Sign Language Translator enables real-time interpretation of sign language, allowing users to easily communicate with each other. …”
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Career recommender system in Malaysia using content-based filtering / Muhammad Luqman Shamsul by Shamsul, Muhammad Luqman

“…The prototype, implemented in Python with a Flask-based interface, enables efficient data preprocessing, seamless user interaction, and accurate job recommendations. …”
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Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis by Ahmad Izzuddin, Tarmizi, Mat Safri, Norlaili, Othman, Mohd Afzan

“…Recently, due to the popularity of end-to-end deep learning, the applicability of algorithms such as convolutional neural networks (CNN) has been explored to achieve the mentioned tasks. …”
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An efficient trust-based decision-making approach for WSNs: Machine learning oriented approach by Khan, T., Singh, K., Shariq, M., Ahmad, K., Savita, K.S., Ahmadian, A., Salahshour, S., Conti, M.

“…The proposed machine learning algorithm extracts various trust features such as Co-Location Relationship (CLR), Co-Work Relationship (CWR), Cooperativeness-Frequency-Duration (CFD), and Reward (R) to obtain a robust trust rating of sensor devices and predict future misbehavior. …”
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