Results 121 to 130 of about 105,118 (315)

Atlas Tile Calorimeterarrel module0 instrumentation

, 1996
Atlas Tile Calorimeterarrel module0 instrumentation at CERN ...
CERN, photos
core  

The ATLAS Tile Calorimeter experience with 10,000 readout photomultipliers operating since the start of the p-p collisions at LHC

, 2017
The channels of TileCal, the hadron calorimeter of the Atlas experiment at the LHC, is readout with 8-stage fine-mesh PhotoMulTipliers (PMTs), a special version of the Hamamatsu model R5900. About 10000 PMTs are operating in TileCal.
ATLAS Tile Collaboration, Lazar, Hadar
core   +1 more source

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

THE CONTEMPORARY AZULEJO: AN IDENTITY ISSUE?

Art is on, 2018
One of the aspects that has supported the idea of the azulejo (tile) as a cultural heritage of the Portuguese identity is its continuous employment since the end of the fifteenth century until today, now having become a part of the projects of artists ...
Inês Leitão
doaj  

Upgrade of the ATLAS Hadronic Tile Calorimeter for the High Luminosity LHC

, 2020
The Tile Calorimeter (TileCal) is the hadronic calorimeter covering the central region of the ATLAS experiment. It is a sampling calorimeter with steel as absorber and scintillators as active medium.
ATLAS Tile Collaboration, Clement, Christophe   +1 more
core   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

The Method for Storing a Seabed Photo Map of the During Surveys Conducted by an Autonomous Underwater Vehicle

Drones
The paper introduces a novel method for creating a photographic map of the seabed using images captured by the on-board photo and video systems of autonomous underwater vehicles (AUVs) during various missions, while incorporating navigation parameters ...
Chang Liu, Vladimir Filaretov, Eduard Mursalimov, Alexander Timoshenko, Alexander Zuev   +4 more
doaj   +1 more source

Atlas Tile Calorimeter Geant4 tutorial in 1999

, 1999
Atlas Tile Calorimeter first Geant4 tutorial at CERN in February ...
Cobal, Marina
core  

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Tilings with the Minimal Tile Property

, 2020
A square tiling of the unit square is said to have the minimal tile property if the smallest tile can tile all the other tiles. We show that in such a tiling, the smallest tile cannot be too small.
openaire   +2 more sources