Search Results - (( java implementation path algorithm ) OR ( learning programme learning algorithm ))
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…This work investigates the suitability and effectiveness of machine learning algorithms such as Multinomial Naive Bayes, KNN, Logistic Regression, Decision Tree for predicting levels of arousal intensity among the programmers and LSTM deep learning algorithm to classify the programmers according to their performance. …”
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Effectiveness of algorithm visualisation in studying complex algorithms: a case study using TRAKLA Ravie / Chandren Muniyandi, Ali Maroosi
Published 2015“…Algorithm visualisation (AV) can be utilised to improve students ’programming and programme comprehension skills. …”
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A Machine Learning Classification Application to Identify Inefficient Novice Programmers
Published 2023“…Data mining; Graphical user interfaces; Learning algorithms; Machine learning; Nearest neighbor search; Academic performance; Application layers; Computer science students; Educational data mining; Educational Institutes; K-near neighbor; Machine learning classification; Nearest-neighbour; Novice programmer; Productive tools; Students…”
Conference Paper -
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Predicting usage for a marketable e-learning portal
Published 2014“…To date, existing e-learning portals focuses on providing various learning materials via online.Such an approach may provide huge benefit to the learners; nevertheless, less value can be obtained by the developers or owners.The knowledge transfer programme provides an insight on how existing e-learning portal can be upgraded.The academia has introduced the industry to a computational modelling that is built upon the behaviour of nature community (i.e bees)The utilization of Artificial Bee Colony algorithm in predicting learners' usage of an e-learning portal provides an indicator to the developers on the portals effectiveness.Such information is then useful in producing a marketable and valuable e-learning portal…”
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Prioritisation Assessment and Robust Predictive System for Medical Equipment: A Comprehensive Strategic Maintenance Management
Published 2024journal::journal article -
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Enhancing problem-solving skills of novice programmers in an introductory programming course
Published 2023Article -
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Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph
Published 2023“…Synthesia AI is a cutting-edge technology that revolutionizes students’ immersive learning experience. With its advanced machine learning algorithms, Synthesia AI can generate photorealistic video content featuring virtual actors and presenters that can be programmed to speak in multiple languages, accents, and even emotional tones. …”
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CT-eKit: computational thinking interactive learning / Ong Sing Ling, Jill Ling and Fetylyana Nor Pazilah
Published 2023“…A mixed method was employed to investigate the students' learning experience with CT-eKit. This study involved 120 students from the Foundation in Science programme of the University of Technology Sarawak (UTS). …”
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Book Section -
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Contextualising Computational Thinking: A Case Study in Remote Rural Sarawak Borneo
Published 2020“…The paper describes an exploratory case study on novice indigenous children’s learning characteristics as they learn Computational thinking (CT) competencies, such as abstraction, decomposition, and algorithmic thinking. …”
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HELM based Reinforcement Learning for Goal Localization
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Proceeding Paper -
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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Examining Social Presence and Online Learning Satisfaction Among Malaysian University Students During the COVID-19 Pandemic
Published 2022“…The results also demonstrate the singifiant contribution of teaching and learning approach, programme or intervention to facilitate social presenc. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan
Published 2021“…The machine learning technique used to develop the prediction prototype is the KNN algorithm. …”
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Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps
Published 2024“…CONCLUSION: Our results support the development of an automatic classification of pests on a sticky trap, which should focus on colour and deep learning architecture to achieve good results. Future studies could aim to incorporate the trap system into pest monitoring, providing more accurate and cost-effective results in a pest management programme. © 2024 The Author(s). …”
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