Search Results - (( course evaluation tree algorithm ) OR ( panel automation system algorithm ))
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Integration Of Machine Vision In Industrial Robot For Automated Composite Panel Punching
Published 2018“…Position and rotation of panels are compared to three coordinate systems which are camera, workpiece and machining center. …”
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The implementation of fault management in distribution system using distribution automation system (DAS) in conjunction with SCADA
Published 2012“…Therefore, the implementation of proper fault management is highly important to be utilized such as by applying automation system in distribution system. Up to date, in Malaysia there is no automation technique being used for maintenance work in distribution system. …”
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A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. …”
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Network-based real-time integrated Fire Detection and Alarm (FDA) system with building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. …”
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Proceeding Paper -
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Implementation of hashed cryptography algorithm based on cryptography message syntax
Published 2019“…The important study in this research is an automated learning system for deep learning to enhance security. …”
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Tracking student performance in introductory programming by means of machine learning
Published 2023Conference Paper -
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Advanced solar tracking system with temperature control and real-time monitoring
Published 2025“…These algorithms dynamically control the servo motor, relay module, and LCD display, adapting the system based on environmental conditions. …”
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Book Section -
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An artificial intelligence approach to monitor student performance and devise preventive measures
Published 2023“…We developed a set of prediction models with distinct machine learning algorithms. Decision tree triumph over other models and thus is further transformed into easily explicable format. …”
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A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures
Published 2023“…Educational Data Mining tools, specifically Machine learning classifiers, appear supportive to develop prediction models which forecast students� final outcome in a course. This research evaluates the effectiveness of machine learning classifiers to monitor students� academic progress and informs the instructor about the students at the risk of producing unsatisfactory final result in a course. …”
Conference Paper -
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An early warning system for students at risk using supervised machine learning
Published 2024“…According to the research, 52% of students who sign up for a course would never read the course materials. Furthermore, throughout the course of five years, the dropout rate reached a stunning 96%. …”
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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah
Published 2024“…Particularly, the decision tree is identified as the most accurate predictive model, having a 0.60 accuracy value. …”
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DurianCare: optimising trunk disease detection and precision farming in a mobile application / Muhammad Haziq Azmi
Published 2025“…The project will implement automated detection and disease management recommendation algorithms while evaluating the functionality and usability of the designed application. …”
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Leveraging data lake architecture for predicting academic student performance
Published 2024“…In addition to forecasting the student performance, appropriate machine learning algorithms such as Support Vector Classifier, Naive Bayes, and Decision Trees are used to build prediction models by using the data lake's scalability and parallel processing capabilities. …”
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Collective behavior quantification on human odor effects against female Aedes aegypti mosquitoes—Open source development
Published 2017“…Although tracking large numbers of individual insects is hailed as one of the characteristics of an ideal automated image-based tracking system especially in 3D, it also is a costly method, often requiring specialized hardware and limited access to the algorithms used for mapping the specimens. …”
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