Search for dissertations about: "Mohamed-Rafik Bouguelia"
Found 5 swedish dissertations containing the words Mohamed-Rafik Bouguelia.
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1. Towards Reliable, Stable and Fast Learning for Smart Home Activity Recognition
Abstract : The current population age grows increasingly in industrialized societies and calls for more intelligent tools to monitor human activities. The aims of these intelligent tools are often to support senior people in their homes, to keep track of their daily activities, and to early detect potential health problems to facilitate a long and independent life. READ MORE
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2. Towards conformal methods for large-scale monitoring of district heating substations
Abstract : Increasing technical complexity, design variations, and customization options of IoT units create difficulties for the construction of monitoring infrastructure. These units can be associated with different domains, such as a fleet of vehicles in the mobility domain and a fleet of heat-pumps in the heating domain. READ MORE
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3. Towards large-scale monitoring of operationally diverse thermal energy systems with data-driven techniques
Abstract : The core of many typical large-scale industrial infrastructures consists of hundreds or thousands of systems that are similar in their basic design and purpose. For instance, District Heating (DH) utilities rely on a large network of substations to deliver heat to their customers. READ MORE
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4. From Domain Adaptation to Federated Learning
Abstract : Data-driven methods have been gaining increasing attention; however, along with the benefits they offer, they also present several challenges, particularly concerning data availability, accessibility, and heterogeneity, the three factors that have shaped the development of this thesis. Data availability is the primary consideration when employing data-driven methodologies. READ MORE
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5. Learning from Multiple Domains
Abstract : Domain adaptation (DA) transfers knowledge between domains by adapting them. The most well-known DA scenario in the literature is adapting two domains of source and target using the available labeled source samples to construct a model generalizable to the target domain. READ MORE