In tune : leadership coaching and Hartmut Rosa’s theory of resonance by Garbini, Kirsten

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Machine learning approaches towards tuning ALICE TRD simulations by Ramraj, Nikhiel

“…In this work an exploration of the discrepancies existing between real and simulated data pertaining to the ALICE Transition Radiation Detector is carried out as a motivation to tune the necessary parameters in the ALICE Online-Offline simulation software (O2 ). …”
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Tuning optimization algorithms under multiple objective function evaluation budgets

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Automatic tuning of a MIMO PI controller of a flotation bank

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On-line auto-tuning of multivariable industrial processes using Bayesian optimisation

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A systematic approach to the tuning of multivariable Dynamic Matrix Control (DMC) controllers

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Multi-fidelity parameter tuning of parallel Monte-Carlo tree search variants by Mouton, Alexander

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Channel parameter tuning in a hybrid Wi-Fi-Dynamic Spectrum Access Wireless Mesh Network by Zlobinsky, Natasha

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Tuned aperture computed tomography (TACT) : an investigation on the factors associated with its image quality for caries detection by De Abreu, Murillo Jose Nunes

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Sentiment analysis using unsupervised learning for local government elections in South Africa

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Development and testing of a screening tool for mine workers with possible hand arm vibration syndrome

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Regulating domestic work : international and comparative perspectives in South Africa, Namibia and Indonesia by Afadameh, Amanoshokunu

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A Self-Tunable Piezoelectric Energy Harvester by Hussein, Ashraf

“…Finally, a parametric study was performed to study the effect of changing the main systems parameters as the tuning masses, the tuning arm length, and length of the beam on the natural frequency. …”
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From text annotation to an auto-regressive language model for sentiment analysis in South African financial reviews

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An Enhanced Cloud-Native Deep Learning Pipeline for the Classification of Network Traffic by ElKenawy, Ahmed Sobhy

“…In addition, our approach reached better accuracy within a limited time budget in comparison with existing work. We begin by defining the problem. Then, we survey the background and studies that attempt to use different approaches. …”
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Optimising the Optimiser: Meta NeuroEvolution for Artificial Intelligence Problems by Hayes, Max Nieuwoudt

“…This was not possible on the task in experiment 3, due to limited computing resources and the increased complexity of the reinforcement learning task in experiment 3, making the transfer of hyperparameters from one task (Task A) to the more difficult task (Task B) highly beneficial for solving the more computationally expensive task. The purpose of this work is to explore the effectiveness of Bayesian Optimisation as a hyperparameter tuning algorithm on the reinforcement learning algorithm NEAT's hyperparemters. …”
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Development of a vibration isolation system for a rotary wing unmanned aerial vehicle

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A few-shot learning approach for a multilingual agro-information question answering system

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Characterisation of thick liquids using a vibrating transducer by Mlambo, O S

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Implementation and performance analysis of a model-based controller on a batch pulp digester

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