Results 101 to 110 of about 210,628 (307)

FPGA-RICH: A low-latency, high-throughput online partial particle identification system for the NA62 experiment [PDF]

EPJ Web of Conferences
FPGA-RICH is an FPGA-based online partial particle identification system for the NA62 experiment utilizing Artificial Intelligence (AI) techniques. Integrated between the readout of the Ring Imaging Cherenkov detector (RICH) and the low-level trigger ...
Perticaroli Pierpaolo, Ammendola Roberto, Biagioni Andrea, Chiarini Carlotta, Ciardiello Andrea, Cretaro Paolo, Frezza Ottorino, Lo Cicero Francesca, Martinelli Michele, Piandani Roberto, Pontisso Luca, Raggi Mauro, Rossi Cristian, Simula Francesco, Turisini Matteo, Vicini Piero, Lonardo Alessandro   +16 more
doaj   +1 more source

High dimensional parameter tuning for event generators

European Physical Journal C: Particles and Fields, 2020
Monte Carlo Event Generators are important tools for the understanding of physics at particle colliders like the LHC. In order to best predict a wide variety of observables, the optimization of parameters in the Event Generators based on precision data ...
Johannes Bellm, Leif Gellersen
doaj   +1 more source

Hydrogel‐Based Capacitive Sensor Model for Ammonium Monitoring in Aquaculture

Advanced Engineering Materials, EarlyView.
Traditional techniques for monitoring aquaculture water quality, particularly ammonium levels, harm fish. This work presents a novel capacitive sensor with an ionic hydrogel transducer to monitor ammonium concentration in real time based on the ammonium‐induced hydrogel dissociation and osmotic pressure. Monitoring aquaculture water quality, especially
Mohammad Mirzaee, Mahdi Askari‐sedeh, Ali Zolfagharian, Mostafa Baghani   +3 more
wiley   +1 more source

End-to-End Event Classification of High-Energy Physics Data

Journal of Physics: Conference Series, 2018
Feature extraction algorithms, such as convolutional neural networks, have introduced the possibility of using deep learning to train directly on raw data without the need for rule-based feature engineering.
M. Andrews, M. Paulini, S. Gleyzer, Barnabás Póczos   +3 more
semanticscholar   +1 more source

Machine learning uncertainties with adversarial neural networks

European Physical Journal C: Particles and Fields, 2019
Machine Learning is a powerful tool to reveal and exploit correlations in a multi-dimensional parameter space. Making predictions from such correlations is a highly non-trivial task, in particular when the details of the underlying dynamics of a ...
Christoph Englert, Peter Galler, Philip Harris, Michael Spannowsky   +3 more
doaj   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

SPECTROSCOPIC AND PHYSICAL PROPERTIES OF ATMOSPHERIC AEROSOL PARTICLES DURING HIGH-POLLUTION EVENTS IN SOUTHERN CALIFORNIA

, 2023
High pollution events like biomass burning and fireworks are short lived but produce large amounts of atmospheric aerosol particulate matter that may affect human health and the Earth’s climate. Measuring spectroscopic properties of the particles, such as the refractive index of the particles, is important to better understand their impact on Earth’s ...
openaire   +1 more source

A Different Perspective on the Solid Lubrication Performance of Black Phosphorous: Friend or Foe?

Advanced Engineering Materials, EarlyView.
Researchers investigate black phosphorous (BP) as a standalone solid lubricant coating through ball‐on‐disc linear‐reciprocating sliding experiments in dry conditions. Testing on different metals shows BP doesn't universally reduce friction and wear. However, it achieves 33% friction reduction on rougher iron surfaces and 23% wear reduction on aluminum.
Matteo Vezzelli, Manel Rodríguez Ripoll, Sabine Schwarz, Ali Erdemir, Maria Clelia Righi, Carsten Gachot   +5 more
wiley   +1 more source

TrackHHL: A Quantum Computing Algorithm for Track Reconstruction at the LHCb [PDF]

EPJ Web of Conferences
In the future high-luminosity LHC era, high-energy physics experiments face unprecedented computational challenges for event reconstruction. Employing the LHCb vertex locator as a case study we investigate a novel approach for charged particle track ...
Chiotopoulos Xenofon, Lucio Martinez Miriam, Nicotra Davide, de Vries Jacco A., Driessens Kurt, Merk Marcel, Winands Mark H.M.   +6 more
doaj   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

Advanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source