Search for dissertations about: "LEARNING MANAGEMENT SYSTEM"
Showing result 1 - 5 of 195 swedish dissertations containing the words LEARNING MANAGEMENT SYSTEM.
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1. Collaboratively Learning Marketing: How Organizations Jointly Develop and Appropriate Marketing Knowledge
Abstract : Business organizations increasingly face the problem of how to generate and share knowledge in collaboration with other, separate, business organizations. Researchers in the field of inter-organizational learning have started to study the partner-characteristic, partner-dynamic, and partner-situational factors that influence the process and outcome of such strategic learning collaboration. READ MORE
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2. Learning-by-modeling : Novel Computational Approaches for Exploring the Dynamics of Learning and Self-governance in Social-ecological Systems
Abstract : As a consequence of global environmental change, sustainable management and governance of natural resources face critical challenges, such as dealing with non-linear dynamics, increased resource variability, and uncertainty. This thesis seeks to address some of these challenges by using simulation models. READ MORE
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3. Data management improvements in the electrical grid : a pathway to a smarter cyber-physical system
Abstract : The current power system is a network of electrical components forming a physical system. It is experiencing changes, such as the deployment of electric vehicles and distributed energy sources. Meanwhile, cybernetworks are becoming coupled into the physical grid to an increasing degree. READ MORE
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4. Towards Next-Gen Machine Learning Asset Management Tools
Abstract : Context: The proficiency of machine learning (ML) systems in solving many real-world problems effectively has enabled a paradigm shift toward ML-enabled systems. In ML-enabled software, significant software code artifacts (i.e., assets) are replaced by ML-related assets, introducing multiple system development and production challenges. READ MORE
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5. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection
Abstract : This thesis presents a critical examination of the positive impact of Machine Learning (ML) and the Internet of Medical Things (IoMT) for advancing the Clinical Decision Support System (CDSS) in the context of COVID-19 and early sepsis detection.It emphasizes the transition towards patient-centric healthcare systems, which necessitate personalized and participatory care—a transition that could be facilitated by these emerging fields. READ MORE