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Diagnosis of Poor Control Loop Performance: Investigate Support Vector Regression Method on Stiction Quantification for Control Valve Nonlinearity
Published 2016“…The quantification technique for the valve stiction is very important aspect in process control. …”
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Final Year Project -
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…Based on the 15 benchmark industrial loops with stiction, the proposed BSD-CNN quantification algorithm has shown reasonable accuracy when compared to other published quantification methods in literature. …”
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Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification
Published 2025“…Crack images obtained were processed and annotated to produce a dataset of 820 images for the training and testing of deep learning models. …”
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Final Year Project / Dissertation / Thesis -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). However, the process failed to state clearly the encoding strategy in its initial stage. …”
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Thesis -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Thesis -
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A comparative study of vibrational response based impact force localization and quantification using radial basis function network and multilayer perceptron
Published 2017“…Among various existing impact identification approaches, neural network based force identification method has received great attention because one does not need to have a system model. Thus, it is less likely to be affected by ill-posed problem that often occurs during the inversion process. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Conference or Workshop Item -
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Modelling of head movement in expression of disgust
Published 2010“…Head movement information can be acquired by video recording process. The recording process has to deal with image distortion correctable via plumb-line method. …”
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Thesis -
13
Gaussian process-based inversion: A new approach for estimating hydrocarbon parameters in controlled-source electromagnetic application
Published 2024“…A Gaussian process (GP)-based inversion was proposed to allow for greater flexibility in modeling numerous forward solutions by calibrating the stochastic process with computer experiment responses to estimate hydrocarbon parameters (i.e., depth and electrical resistivity) in marine CSEM application. …”
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Automated pavement imaging program (APIP) for pavement cracks classification and quantification – a photogrammetric approach
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Towards a multispectral imaging system for spatial mapping of chemical composition in fresh-cut pineapple (Ananas comosus)
Published 2023“…Prediction of chemical composition in each pixel of the multispectral images using the calibration models yielded spatially distributed quantification of the fruit slice, spatially varying according to the maturation of single fruitlets in the whole pineapple. …”
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Modelling COVID-19 Hotspot Using Bipartite Network Approach
Published 2021“…The ranking of location and human nodes in this network is computed using a web search algorithm. This model is considered verified as the error obtained from the comparison made between the benchmark model and the COVID-19 bipartite network model is small. …”
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Detection and Severity Identification of control valve stiction in industrial loops using integrated partially retrained CNN-PCA frameworks
Published 2021“…Recent neural network based stiction detection methods published are only able to perform either stiction detection or quantification, which open up an area of research to propose a simplified algorithm to simultaneously detect and quantify stiction with high generalization capability. …”
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Thesis -
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Detection And Identification Of Stiction In Control Valves Based On Fuzzy Clustering Method
Published 2016“…Finally as an alternative to stiction quantification, by configuring a fuzzy identifier, an appropriate model of process with control valve stiction is identified (identification). …”
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Thesis -
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SRPTackle: a semi-automated requirements prioritisation technique for scalable requirements of software system projects
Published 2021“…Method: SRPTackle provides a semiautomated process based on a combination of a constructed requirement priority value formulation function using a multi-criteria decision-making method (i.e. weighted sum model), clustering algorithms (K-means and K-means++) and a binary search tree to minimise the need for expert involvement and increase efficiency. …”
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