Emerging market entry strategy and decision-making : the influence of tacit knowledge and explicit knowledge

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Video classification using deep learning by Newman, Gregory

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Bayesian machine learning : theory and applications by Payne, Megan Wendy

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Froth texture extraction with deep learning by Horn, Zander Christo

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Data-driven river flow routing using deep learning: predicting flow along the lower Orange river, Southern Africa by Briers, C. J.

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Understanding why practitioners prefer different methods for leadership development : a qualitative study by Spoelstra, Marli

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Evolutionary search strategies in constraint programming by Bennetto, Robert Andrew

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Theory for the practice of environmental assessment : mutual adjustment, critical rationality, and power in planning and decision making by Hill, Richard Charles

“…This thesis develops theory for the practice of Environmental Assessment (EA) by integrating philosophies with theories and models from the fields of EA, decision making, and city and regional planning. …”
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Characterizing variable renewable energy generation uncertainty towards improved forecasting and operational decision making by Mararakanye, Ndamulelo

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Meaning-making processes among bereaved mothers who have lost a child to cancer by Lipshitz, Marc

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When UTAUT2 meets design thinking mindset: Exploring e-learning champions? Adoption of blended learning at EMU by Issufo, Vali

“…Blended learning has increasingly been recognised as an effective approach to enhance student success in higher education, and to make this possible, educational technologies are crucial. …”
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Computational Psychiatry - Neuropsychological Bayesian reinforcement learning by Wolpe, Zach

“…In particular, theories of learning, operant conditioning and decision making have shown a natural synergy with statistical learning algorithms. …”
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Knowledge management and the learning organisation in the new economy by De Wet, Ben

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Applying the Seven Principles of Learning to Development Communication by Abd El Ghaffar, Lina

“…The suggested paradigm is more audience-centric than the current dominant paradigm and more structured than the current participatory paradigm. The suggested learning paradigm builds its conceptual model around the development communication campaign audience’s internal and external factors that directly influence their decision making. …”
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The contextual nature of learning in community schools in Lusaka

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Mixed-Criticality Scheduling Using Reinforcement Learning by ElSeadawy, Omar

“…We propose a somewhat unconventional approach, where we tackle the modeling complexities using deep reinforcement learning, particularly suitable for problems that generate a sequence of decisions in dynamic environments. …”
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Multimodal one-shot learning of speech and images by Eloff, Ryan

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Deep adaptive anomaly detection using an active learning framework by Sekyi, Emmanuel

“…We employ a Deep Learning and an Active Learning framework to learn features for anomaly detection. …”
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Deep learning for tabular data : an exploratory study by Marais, Jan Andre

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South African unit standards for sight-singing, realised in a multiple-media study package

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