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Evaluate the performance of university timetabling problem with various artificial intelligence techniques
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Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm
Published 2025“…University course timetabling problem (UCTP) is a scheduling problem that requires courses to be assigned to the limited time slots, classrooms, and lecturers, while adhering to a set of predefined constraints. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening. …”
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Development of MyCGPA for early predicting students’ academic performance
Published 2025“…One of the primary concerns in higher education is the early identification of underperforming students. …”
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Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation
Published 2018“…It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga
Published 2022“…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. …”
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Thesis -
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
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Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques
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Undergraduates Project Papers -
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A PSO inspired asynchronous cooperative distributed hyper-heuristic for course timetabling problems
Published 2017“…The performances of the proposed cooperative hyper-heuristics are evaluated using the standard course timetabling benchmark problem. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Early identification of high-risk patients enables timely intervention and implementation of preventive measures, potentially reducing the burden of stroke-related complications. …”
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Development of IoT-based heatstroke early symptoms monitoring system for students in Malaysia
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Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning
Published 2025“…The sound emitted by Vertical Take Off and Landing (VTOL) UAVs offers valuable insights into their flight performance, serving as a crucial element for the efficient monitoring of flying conditions and early detection of potential faults. This paper will focus on developing fault detection and identification using audio data of different propeller conditions. …”
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Outlier Detection Technique in Data Mining: A Research Perspective
Published 2005“…In this paper we will explain the first part of our research, which is focused on outlier identification and provide a description of why an identified outlier exceptional, based on Distance-Based outlier detection and Density-Based outlier detection.…”
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Object-oriented online course recommendation systems based on deep neural networks
Published 2024“…To tackle these issues, this paper introduces a comprehensive analysis and design of an object-oriented online course recommendation system. Employing a deep neural network algorithm for course recommendation, our system adeptly captures user preferences, course attributes, and intricate relationships between them. …”
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Autonomous self-exam monitoring for early diabetes detection
Published 2020“…An autonomous self-exam monitoring is developed in order to assist the physicians in identifying diabetes at the early stage. Iris image is used to recognise the early detection of diabetes. …”
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Video surveillance: explosion detection
Published 2025“…By leveraging three motion-based variables, including motion ratio, new pixel ratio and optical flow values, together with three detection approaches, namely global detection, non-eroded detection and eroded detection, the system demonstrates the effectiveness of motion based methods in detecting explosions at an early stage with acceptable performance. …”
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Final Year Project / Dissertation / Thesis -
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