Robin, Yoann Faranda, Davide Vrac, Mathieu
CDSupdate is a Python package that automates the process of retrieving, processing, and managing climate data from the Copernicus Climate Change Service (C3S) Climate Data Store (CDS). The tool generates daily climate data summaries, performs calculations to create custom variables such as relative humidity and heat index which serve as risk assess...
Oliveira, Tiago Fogaça
Relatório (PIBIC) - Universidade Federal de Santa Catarina. Centro tecnológico. Engenharia de produção mecânica. / Este relatório além de evidenciar as atividades desenvolvidas no período de iniciação científica visa aumentar a previsibilidade da incidência de radiação solar a curto-prazo em regiões pré-determinadas do estado de Santa Catarina, atr...
Halstead, Ben Koh, Yun Sing Riddle, Patricia Pechenizkiy, Mykola Bifet, Albert
The distribution of streaming data often changes over time as conditions change, a phenomenon known as concept drift. Only a subset of previous experience, collected in similar conditions, is relevant to learning an accurate classifier for current data. Learning from irrelevant experience describing a different concept can degrade performance. A sy...
Amaya-Ramirez, Diego
This thesis presents a data science approach to explore the antigenicity of Human Leukocyte Antigen (HLA) molecules based on their three-dimensional (3D) structures and molecular dynamics (MD) simulations. The primary objective is to better understand the determinants of graft rejection caused by donor-specific antibodies (DSAs) and to improve dono...
Durivault, Lauren Bouillass, Ghada Saidani, Michael Yannou, Bernard Heidsieck, Robert
Transitioning from a linear economy to a circular economy (CE) in healthcare is essential forreducing human-induced environmental impacts and promoting sustainability. However, thisshift is challenged by a lack of standardization in circular procedures. This article identifieskey elements and challenges to implementing CE in complex industrial envi...
Mishra, Shrey
This thesis examines the extraction of mathematical statements and proofs from scholarly PDF articles by approaching it as a multimodal classification challenge. It is part of the broader TheoremKB project, which seeks to convert scientific literature into a comprehensive, open-access knowledge base of mathematical statements and their proofs. The ...
Acosta-Mérida, María Asunción
Published in
Cirugia espanola
Technological and computer advances have led to a "new era" of Surgery called Digital Surgery. In it, the management of information is the key. The development of Artificial Intelligence requires "Big Data" to create its algorithms. The use of digital technology for the systematic capture of data from the surgical process raises ethical issues of p...
Lichtstein, Gordon
This report, developed as part of the 2024 UCSF Industry Documents Library Undergraduate Summer Fellowship, examines four distinct projects that leverage natural language processing and data science within the context of the JUUL Labs Collection and the broader IDL. Project One investigates the optical character recognition (OCR) accuracy of low-qu...
El Amraoui, Yassine
When data scientists need to create machine learning workflows to solve a problem, they first understand the business needs, analyze the data, and then experiment to find a solution. They judge the success of each attempt using metrics like accuracy, recall, and F-score. If these metrics meet expectations on the test data, it's a success; otherwise...
Valentino, Rita J Nair, Sunila G Volkow, Nora D
Published in
Journal of neural transmission (Vienna, Austria : 1996)
The prevention and treatment of addiction (moderate to severe substance use disorder-SUD) have remained challenging because of the dynamic and complex interactions between multiple biological and social determinants that shape SUD. The pharmacological landscape is ever changing and the use of multiple drugs is increasingly common, requiring an unra...
