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Machine learning approach for automated optical inspection of electronic components
Published 2019“…The factor that affecting the confidence level of the supervised machine learning algorithm is discussed. …”
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Final Year Project / Dissertation / Thesis -
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…In the learning section,Support Vector Machine and Artificial Neural Network were selected as suitable classification algorithms,while Gradient Boosted Tree was employed to interpret the rule based on the black box classifiers.Testing the framework involved Pima Indian Dataset as public dataset and Semarang Hospital Dataset as private dataset (800 patients’ data).In validating the DRPF,four case studies investigated Subject Matter Expert (SME) groups based on the agreement level.The questionnaire consists of a DRPF component,implementation of DRPF,and viability of DRPF.DRPF components were validated by the SMEs,whereby the group ascertained five highest risk factors:HbA1c,systole/diastole,blood glucose,and creatinine and blood urea nitrogen that were assigned by attribute weighting.Results from the questionnaire revealed an average agreement level of 80%. …”
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Thesis -
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum
Published 2023“…Then, the selection of the critical features is chosen via Neural Network (NN) as classification algorithm and Genetic Algorithm (GA) as an optimization technique. …”
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Computer-assisted pterygium screening system: a review
Published 2022“…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Conference or Workshop Item -
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IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH
Published 2006“…The objective of this project is to develop algorithms inMATLAB and be able to implement image texture analysis by using the developed algorithms. …”
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Final Year Project -
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview
Published 2019“…Deep learning provides the mechanism to RL which enables the agent to solve the human level task. …”
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Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview
Published 2019“…Deep learning provides the mechanism to RL which enables the agent to solve the human level task. …”
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EEG-based emotion recognition using machine learning algorithms
Published 2024“…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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Final Year Project / Dissertation / Thesis -
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Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Academic Exercise -
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Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.]
Published 2022“…In supporting the intervention approaches, machine learning techniques have been widely utilized. Another challenge is the difficulty to implement machine learning analysis by the educators. …”
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From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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Thesis -
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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Estimating Depressive Tendencies Of Twitter User Via Social Media Data
Published 2023“…The twitter dataset can be used to test the level of depressive tendencies with three different machine learning algorithms. …”
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Undergraduates Project Papers -
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Prediction of the level of air pollution during wildfires using machine learning classification methods
Published 2020“…Recent studies indicate that data retrieved from remote sensing satellites is now an emerging alternative for air quality prediction at the ground level. Hence, this research aims to use satellite-based data to predict the air quality of East Malaysian cities with the help of different Machine Learning classification algorithms. …”
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