Sökning: "Learning Management System"

Visar resultat 1 - 5 av 227 avhandlingar innehållade orden Learning Management System.

1. 1. Collaboratively Learning Marketing: How Organizations Jointly Develop and Appropriate Marketing Knowledge

   Författare :Claus Baderschneider; Företagsekonomiska institutionen; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Nationalekonomi; economic policy; economic systems; economic theory; econometrics; Economics; Strategic alliances; Learning content; Marketing; Knowledge; Collaborative learning; Strategic collaboration; Organizational learning; Inter-organizational learning; ekonometri; ekonomisk teori; ekonomiska system; ekonomisk politik; Management of enterprises; Företagsledning; management;

   Sammanfattning : 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. LÄS MER

3. 2. Learning-by-modeling : Novel Computational Approaches for Exploring the Dynamics of Learning and Self-governance in Social-ecological Systems

   Författare :Emilie Lindkvist; Maja Schlüter; Jon Norberg; Örjan Ekeberg; James Dyke; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Complex adaptive systems; Renewable resources; Adaptive management; Small-scale fisheries; Artificial intelligence; Reinforcement learning; Agent-based modeling; agent-baserade modeller; artificiell intelligens; social-ekologiska system; komplexa adaptiva system; förnyelsebara naturresurser; adaptiv förvaltning; Sustainability Science; vetenskap om hållbar utveckling;

   Sammanfattning : 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. LÄS MER

4. 3. Data management improvements in the electrical grid : a pathway to a smarter cyber-physical system

   Författare :Sylvie Evelyne Koziel; Patrik Hilber; Ebrahim Shayesteh; Per Westerlund; Mathaios Panteli; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; asset management; data management; data analytics; distribution; grid operation and planning; machine learning; cyberinfrastructure upgrade; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : 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. LÄS MER

5. 4. Towards Next-Gen Machine Learning Asset Management Tools

   Författare :Samuel Idowu; Göteborgs universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Experiment Management; Experiment management tools; Asset Management; Asset Management Tools; Tools; ML Asset Taxonomy;

   Sammanfattning : 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. LÄS MER

7. 5. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection

   Författare :Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Internet of Medical Things; Patient-Centric Healthcare; Clinical Decision Support System; Predictive Modeling in Healthcare; Health Informatics; Healthcare analytics; COVID-19; Sepsis; COVID-19 Detection; Early Sepsis Detection; Lung Segmentation Detection; Medical Data Annotation Scarcity; Medical Data Sparsity; Medical Data Heterogeneity; Medical Data Security Privacy; Practical Usability Enhancement; Low-End Device Adaptability; Medical Significance; Interpretability; Visualization; LIME; SHAP; Grad-CAM; LRP; Electronic Health Records; Thermal Image; Tabular Medical Data; Chest X-ray; Machine Learning; Deep Learning; Federated Learning; Semi-Supervised Machine Learning; Multi-Task Learning; Transfer Learning; Multi-Modality; Natural Language Processing; ClinicalBERT; GAN; data- och systemvetenskap; Computer and Systems Sciences;

   Sammanfattning : 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. LÄS MER