Published Articles

2022-10-04
09:27
 A System for Sustainable Usage of Computing Resources Leveraging Deep Learning Predictions / Cioca, Marius (Unlisted, RO) ; Schuszter, Ioan Cristian (CERN ; Petrosani U.) In this paper, we present the benefit of using deep learning time-series analysis techniques in order to reduce computing resource usage, with the final goal of having greener and more sustainable data centers. Modern enterprises and agile ways-of-working have led to a complete revolution of the way that software engineers develop and deploy software, with the proliferation of container-based technology, such as Kubernetes and Docker. [...] 2022 - 20 p. - Published in : Appl. Sciences 12 (2022) 8411 Fulltext: PDF;

2022-10-04
09:27
 Visual control through narrow passages for an omnidirectional wheeled robot / Morra, Damiano (Naples U.) ; Cervera, Enric (Jaume I U., Castellon) ; Buonocore, Luca Rosario (CERN) ; Cacace, Jonathan (Naples U.) ; Ruggiero, Fabio (Naples U.) ; Lippiello, Vincenzo (Naples U.) ; Castro, Mario Di (CERN) Robotic systems are gradually replacing human intervention in dangerous facilities to improve human safety and prevent risky situations. In this domain, our work addresses the problem of autonomous crossing narrow passages in a semi-structured (i.e., partially-known) environment. [...] 2022 - 6 p. - Published in : 10.1109/MED54222.2022.9837221

2022-10-04
09:27
 A procedural solution for determining the temperature dependence of transport critical current in Nb$_{3}$Sn superconducting wires using magnetization measurements / Pong, Ian (LBNL, Berkeley) ; Ekin, Jack (NIST, Boulder) ; Baumgartner, Thomas (Vienna, Tech. U.) ; Bordini, Bernardo (CERN) ; Cheggour, Najib (Florida State U.) Using magnetization techniques to determine the temperature dependence of critical current in Nb$_{3}$Sn wires is attractive because of the relative ease compared with using variable-temperature transport measurements. However, there is a known mismatch in the temperature scaling characterizations when using magnetization data compared to transport data. [...] 2022 - 20 p. - Published in : Supercond. Sci. Technol. 35 (2022) 095006

2022-10-04
09:27
 An Enhanced Sensitivity Operation Mode for Floating Gate Dosimeters / Rizzo, Marta (CERN ; Milan, Polytech.) ; Brucoli, Matteo (CERN) ; Danzeca, Salvatore (CERN) ; Masi, Alessandro (CERN) ; Pineda, Àlvaro (Unlisted, ES) ; Mas, Bartomeu Servera (Unlisted, ES) A new method for enhancing the sensitivity of the Floating Gate DOSimeter (FGDOS) has been investigated. By increasing the electric field in the silicon dioxide, it is possible to improve the fractional yield of collection of the electron–hole pairs, thus to increase the device’s sensitivity. [...] 2022 - 8 p. - Published in : IEEE Trans. Nucl. Sci. 69 (2022) 1876-1883

2022-10-04
09:27
 Differential geometry method for minimum hard-way bending 3D design of coils with ReBCO tape conductor / Nes, T H (CERN ; Twente U., Enschede) ; de Rijk, G (CERN) ; Kario, A (Twente U., Enschede) ; ten Kate, H H J (Twente U., Enschede) The use of tape conductor poses design challenges for superconducting magnets. Due to its very high aspect ratio, it is hardly possible to bend the conductor over its thin edges (hard-way bending) rather than over its wide side (easy-way bending). [...] 2022 - 14 p. - Published in : Supercond. Sci. Technol. 35 (2022) 105011 Fulltext: PDF;

2022-10-04
09:27
 Contactless doping characterization of ${\mathrm{Ga}_{2}\mathrm{O}_{3}}$ using acceptor Cd probes / Barbosa, Marcelo B (Porto U. ; Singapore Natl. U.) ; Correia, João Guilherme (IST/ITN, Lisbon ; CERN) ; Lorenz, Katharina (Lisbon, IST) ; Lopes, Armandina M L (Porto U.) ; Oliveira, Gonçalo N P (Porto U.) ; Fenta, Abel S (CERN ; Aveiro U. ; Leuven U.) ; Schell, Juliana (CERN ; U. Duisburg-Essen) ; Teixeira, Ricardo (IST, Lisbon (main)) ; Nogales, Emilio (Madrid U.) ; Méndez, Bianchi (Madrid U.) et al. Finding suitable p-type dopants, as well as reliable doping and characterization methods for the emerging wide bandgap semiconductor $\beta$-${\mathrm{Ga}_{2}\mathrm{O}_{3}}$ could strongly influence and contribute to the development of the next generation of power electronics. In this work, we combine easily accessible ion implantation, diffusion and nuclear transmutation methods to properly incorporate the Cd dopant into the $\beta$-${\mathrm{Ga}_{2}\mathrm{O}_{3}}$ lattice, being subsequently characterized at the atomic scale with the Perturbed Angular Correlation (PAC) technique and Density Functional Theory (DFT) simulations. [...] 2022 - 9 p. - Published in : Sci. Rep. 12 (2022) 14584 Fulltext: PDF;

2022-10-04
09:27
 Performance tests of the B-RAD radiation survey meter / Ferrulli, Francesca (Caen U. ; CERN) ; Silari, Marco (CERN) This article discusses performance tests of the B-RAD by ELSE NUCLEAR. The B-RAD is a portable survey meter for l. [...] 2022 - 8 p. - Published in : Nucl. Instrum. Methods Phys. Res., A 1042 (2022) 167430

2022-10-01
04:47
 Cosmology and dark matter / Rubakov, V.A. (Moscow, INR ; Moscow State U.) Cosmology and astroparticle physics give strongest possible evidence for the incompleteness of the Standard Model of particle physics. Leaving aside misterious dark energy, which may or may not be just the cosmological constant, two properties of the Universe cannot be explained by the Standard Model: dark matter and matter-antimatter asymmtery. [...] arXiv:1912.04727; INR-TH-2019-022.- 2022-09-05 - 76 p. - Published in : CERN Yellow Rep. School Proc.: 5 (2022) , pp. 129 Fulltext: 1912.04727 - PDF; document - PDF; In : 2019 European School of High-Energy Physics, Saint Petersburg, Russia, 4 - 17 Sep 2019, pp.129

2022-10-01
04:46
 Flavor physics and CP violation / Vysotsky, M.I. (Moscow, ITEP) Lectures at the 53rd Winter School of Petersburg Nuclear Physics Institute and European School on High Energy Physics ESHEP2019, Saint-Petersburg, Russia.. arXiv:1912.08717.- 2022-09-05 - 37 p. - Published in : CERN Yellow Rep. School Proc. 5 (2022) 47 Fulltext: document - PDF; 1912.08717 - PDF; In : 2019 European School of High-Energy Physics, Saint Petersburg, Russia, 4 - 17 Sep 2019, pp.47

2022-09-29
06:02
 Simulating the LHCb hadron calorimeter with generative adversarial networks / Lancierini, D (U. Zurich (main)) ; Owen, P (U. Zurich (main)) ; Serra, N (U. Zurich (main)) Generative adversarial networks are known as a tool for fast simulation of data. Our aim is to research and develop a physical application of these tools by simulating LHCb hadron calorimeter (HCAL) in order to speed up the Monte Carlo datasets production.. 2019 - 4 p. - Published in : Nuovo Cimento C 42 (2019) 197 Fulltext: PDF; In : 17th Incontri di Fisica delle Alte Energie, Milan, Italy, 04 - 06 Apr 2018, pp.197

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