Výsledky vyhledávání - "Martin Juan Carlos"

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Personal Data Transfers to Non-EEA Domains: A Tool for Citizens and An Analysis on Italian Public Administration Websites

Autor: Laudadio, Lorenzo, Vetrò, Antonio, Coppola, Riccardo, De Martin, Juan Carlos, Torchiano, Marco

Six years after the entry into force of the GDPR, European companies and organizations still have difficulties complying with it: the amount of fines issued by the European data protection authorities is continuously increasing. Personal data transfe

Externí odkaz: http://arxiv.org/abs/2407.13467

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Ejected Particles after Impact Splash on Mars: Aggregates and Aerodynamics

Autor: Becker, Tim, Teiser, Jens, Jardiel, Teresa, Peiteado, Marco, Muñoz, Olga, Martikainen, Julia, Martin, Juan Carlos Gomez, Merrison, Jonathan, Wurm, Gerhard

Publikováno v: Planet. Sci. J. 4 180 (2023)

Our earlier laboratory measurements showed that low-velocity sand impacts release fine <5 {\mu}m dust from a Martian simulant soil. This dust will become airborne in the Martian atmosphere. Here, we extend this study by measuring aerodynamic properti

Externí odkaz: http://arxiv.org/abs/2310.09133

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Releasing Atmospheric Martian Dust in Sand Grain Impacts

Autor: Becker, Tim, Teiser, Jens, Jardiel, Teresa, Peiteado, Marco, Munoz, Olga, Martikainen, Julia, Martin, Juan Carlos Gomez, Wurm, Gerhard

Publikováno v: Planet. Sci. J. 3 195 (2022)

Emission of dust up to a few micrometer in size by impacts of sand grains during saltation is thought to be one source of dust within the Martian atmosphere. To study this dust fraction, we carried out laboratory impact experiments. Small numbers of

Externí odkaz: http://arxiv.org/abs/2208.14761

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Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: a proof of concept

Objective: To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. Methods: Two SARS-CoV-2 models were prepared as engineered lentiviruse

Externí odkaz: http://arxiv.org/abs/2204.14050

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AI-based artistic representation of emotions from EEG signals: a discussion on fairness, inclusion, and aesthetics

Autor: Riccio, Piera, Bergaust, Kristin, Christensen-Scheel, Boel, De Martin, Juan-Carlos, Zuluaga, Maria A., Nichele, Stefano

While Artificial Intelligence (AI) technologies are being progressively developed, artists and researchers are investigating their role in artistic practices. In this work, we present an AI-based Brain-Computer Interface (BCI) in which humans and mac

Externí odkaz: http://arxiv.org/abs/2202.03246

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Detecting discriminatory risk through data annotation based on Bayesian inferences

Autor: Beretta, Elena, Vetrò, Antonio, Lepri, Bruno, De Martin, Juan Carlos

Thanks to the increasing growth of computational power and data availability, the research in machine learning has advanced with tremendous rapidity. Nowadays, the majority of automatic decision making systems are based on data. However, it is well k

Externí odkaz: http://arxiv.org/abs/2101.11358

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The invisible power of fairness. How machine learning shapes democracy

Autor: Beretta, Elena, Santangelo, Antonio, Lepri, Bruno, Vetrò, Antonio, De Martin, Juan Carlos

Many machine learning systems make extensive use of large amounts of data regarding human behaviors. Several researchers have found various discriminatory practices related to the use of human-related machine learning systems, for example in the fiel

Externí odkaz: http://arxiv.org/abs/1903.09493

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