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Partial end-to-end reinforcement learning for robustness towards model-mismatch in autonomous racing’
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Metaheuristics for the selection and scheduling of jobs with time-dependent durations
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Study of the TR Synchronization and Video Conversion Unit
Published 2015“…A new SVCU architecture, utilizing high speed ADCs and digital integrators, was then tested. …”
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Performance analysis of FBMC over OFDM in Cognitive Radio Network
Published 2019“…A resource allocation algorithm was proposed where much attention was focused on interference and power constraint. …”
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Screening for Proteinopathic-related Dementias in Low-resource Clinical Contexts: A Machine Learning Approach
Published 2024“…Information from 20 clinical variables were used as features for the analysis. We used C5.0 algorithms to identify the most important features for PRD diagnosis and to derive an algorithm that could accurately diagnose these types of dementia. …”
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Genolve : a bioinformatics tool for the study of structure-driven genome evolution
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Slotted time based protocol and polling strategies for low speed, narrow band applications
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Automated brick sculpture construction
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Modelling of the deaerator system in Flownex
Published 2017“…The analytical model was developed by writing a Mathcad algorithm that solved the steady state one-dimensional mass and energy conservation equations around the deaerator boundary together with the oxygen component continuity equation. …”
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Bayesian analysis of historical functional linear models with application to air pollution forecasting
Published 2023“…The efficiency of the MCMC algorithms is increased by implementing a Cholesky decomposition to sample from high-dimensional Gaussian distributions and by taking advantage of the orthogonal properties of the functional principal components used to model the functional covariates. …”
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A graph-based framework towards trading financial markets
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Structural analysis in a distributed collaboratory
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Automated Machine Learning for Predicting Trends in Time Series Data
Published 2022“…Recently, a hybrid Deep Neural Network (DNN) algorithm, TreNet was proposed for predicting trends in time series data. …”
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Improved decoder metrics for DS-CDMA in practical 3G systems
Published 2016“…MUDs, however, suffer from high complexity, including most of sub-optimal algorithms. Hence, most commercial implementations still use conventional single-user matched filter detectors. …”
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The application of machine learning for computational electromagnetic solver selection
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A comparative study of recurrent neural networks and statistical techniques for forecasting the stock prices of JSE-listed securities
Published 2023“…The number of input observations utilised were varied from four to fifteen observations whilst making forecasts from one up to ten timesteps into the future. …”
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A computer vision framework towards automated scene understanding & analysis
Published 2025“…Most computer vision algorithms are deep learning based approaches but differ significantly in architecture. …”
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