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of Science and Technology, University of Coimbra III- Scientific supervision/coordination of the grant: André Manuel dos Santos Mendes IV - Work Plan / Goals to be achieved: Embedded systems programming
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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suitable voltage and frequency control strategies, based on state-of-the-art research, and development of dispatch algorithms for the isolated microgrid, considering the coordinated control of generation
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computer vision algorithms to detect clinical interventions performed by nurses and situations of agitation and risk of falling. Volume of data available for the project: Video capture in a hospital
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, inferential, and multivariate methods, including principal component analysis (PCA), regression, and machine learning algorithms (e.g., Random Forest), with the aim of integrating various environmental exposure
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of recommendation algorithms based on multiple data related to microorganisms and pathogens, and the implementation of the recommendation system on a testable platform. The work also includes the writing of technical
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(IMI, IMT, IRS, Census) with descriptive methods and causal econometric techniques. It will use various approaches to identify vacant dwellings, including machine learning algorithms to visually detect
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algorithms for analyzing electrocardiography, electromyography and movement signals, identifying characteristics and recognizing patterns in everyday activities. Testing and validation of methods developed in
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algorithms to combine information on cardiovascular activity obtained from heart sound signals, electrocardiogram, and photoplethysmography. Investigate the inclusion of prior knowledge about the application