Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Lorenzo Perini"'
Publikováno v:
IEEE Access, Vol 12, Pp 32938-32943 (2024)
Capacitance-voltage (C-V) measurements play a crucial role in evaluating semiconductor device performance by revealing vital parameters such as doping levels and charge carrier behavior. This study specifically investigates the impact of mesa structu
Externí odkaz:
https://doaj.org/article/17e3a04543084683bfdb2979f7d6a221
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264115
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2c7a81d02260771de77e6db75673f6e
https://doi.org/10.1007/978-3-031-26412-2_30
https://doi.org/10.1007/978-3-031-26412-2_30
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676636
ECML/PKDD (3)
ECML/PKDD (3)
Anomaly detection focuses on identifying examples in the data that somehow deviate from what is expected or typical. Algorithms for this task usually assign a score to each example that represents how anomalous the example is. Then, a threshold on th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9aa1336b6ae92d3f5d67755da9ab6bab
https://lirias.kuleuven.be/handle/123456789/657481
https://lirias.kuleuven.be/handle/123456789/657481
Publikováno v:
IJCAI
Estimating the proportion of positive examples (i.e., the class prior) from positive and unlabeled (PU) data is an important task that facilitates learning a classifier from such data. In this paper, we explore how to tackle this problem when the obs
Publikováno v:
ECML PKDD 2020 Workshops ISBN: 9783030659646
PKDD/ECML Workshops
PKDD/ECML Workshops
Anomaly detection attempts to learn models from data that can detect anomalous examples in the data. However, naturally occurring variations in the data impact the model that is learned and thus which examples it will predict to be anomalies. Ideally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11d37af1ad14569e05c91b84d5358e8b
https://doi.org/10.1007/978-3-030-65965-3_27
https://doi.org/10.1007/978-3-030-65965-3_27
Publikováno v:
Journal of The Electrochemical Society. 163:H3110-H3115
Autor:
Stefano Agnoli, Christian Durante, Ulrich Stimming, Wenbo Ju, Lorenzo Perini, Marco Favaro, Gaetano Granozzi, Oliver Schneider
Publikováno v:
Electrochimica Acta. 141:89-101
The combination of surface science and electrochemistry is an effective method to approach a fundamental understanding of electrocatalytic systems, especially of the catalyst/support assemblies. Extrinsic chemical defects in the support can affect th
Autor:
Marco Favaro, Tine Brülle, Christian Durante, Ulrich Stimming, Oliver Schneider, Lorenzo Perini, Wenbo Ju
Palladium nanoparticles (Pd NPs) were deposited electrochemically on highly oriented pyrolytic graphite (HOPG) substrates by using a potentiostatic double-pulse technique. The particle densities were in the order of 109 cm−2; the radius of the depo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::338bc53ce273cf453e8f677240b62a57
http://hdl.handle.net/11577/3167856
http://hdl.handle.net/11577/3167856
Autor:
Stefano Agnoli, Valentina Perazzolo, Lorenzo Perini, Marco Favaro, Armando Gennaro, Christian Durante, Oliver Schneider, Gaetano Granozzi
Publikováno v:
ACS applied materialsinterfaces. 7(2)
Mesoporous carbons are highly porous materials, which show large surface area, chemical inertness and electrochemical performances superior to traditional carbon material. In this study, we report the preparation of nitrogen-doped and undoped mesopor
Autor:
Lorenzo Perini, Christian Durante, Stefano Agnoli, Armando Gennaro, Gaetano Granozzi, Marco Favaro
Pd nanoparticles (NPs) were deposited electrochemically on three differently modified glassy carbon (GC) supports: pristine GC, nitrogen implanted GC and Ar implanted GC. The aim of such an approach is to discriminate whether the electrocatalytic act
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bcf8bb1b33e50fded37e503a5d31e24
http://hdl.handle.net/11577/2679468
http://hdl.handle.net/11577/2679468