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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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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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: Review of the State of the Art in AI and Procurement; General system design; Development of AI algorithms and functionalities (including testing and evaluation) Preparation of project reports as
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and computational implementation of methods, algorithms, and applications for the Portuguese use case. - Specification and development of the Portuguese pilot implementation. - Active
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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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(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
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algorithms for free-flying robots in microgravity.; • Implement and validate real-time multi-target tracking techniques.; • Validate the algorithms in simulated scenarios, evaluating robustness and accuracy