Results 131 to 140 of about 120,084 (296)

Performance Models for Distributed Deep Learning Training Jobs on Ray [PDF]

Deep Learning applications are pervasive today, and efficient strategies are designed to reduce the computational time and resource demand of the training process.
Federica Filippini, Boris Lublinsky, Maximilien de Bayser, Danilo Ardagna   +3 more
core   +1 more source

Distributed interference coordination based on multi-agent deep reinforcement learning

Tongxin xuebao, 2020
A distributed interference coordination strategy based on multi-agent deep reinforcement learning was investigated to meet the requirements of file downloading traffic in interference networks.By the proposed strategy transmission scheme could be ...
Tingting LIU, Yi’nan LUO, Chenyang YANG   +2 more
doaj   +2 more sources

A Novel Interference Avoidance Based on a Distributed Deep Learning Model for 5G-Enabled IoT. [PDF]

Sensors (Basel), 2021
Osman RA, Saleh SN, Saleh YNM.
europepmc   +1 more source

Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial

Arthritis Care &Research, EarlyView.
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham, Thea Senger‐Carpenter, Jocelyn Zuckerman, Michelle Adler, Mallet R. Reid, Ashley Danguecan, Luana Flores Pereira, Sarah I. Mossad, Samantha L. Ely, Khalid Abulaban, Elizabeth A. Kessler, Natalie Rosenwasser, Tamar B. Rubinstein, Ekemini A. Ogbu, Emily A. Smitherman, Alaina Miller, Taylor Abounader, Elizabeth Ross, Livie Timmerman, Dhriti Sharma, Jennifer N. Stinson, Stacy Allen, Kabita Nanda, Tala El Tal, Deborah M. Levy, Linda T. Hiraki, Hermine I. Brunner, Mathew Reeves, Steven J. Pierce, Andrea Knight   +29 more
wiley   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Thermodynamic Pathways of Nonequilibrium Solidification in Wire‐Arc Additive Manufacturing Fe‐Based Multicomponent Alloy Structures

Advanced Engineering Materials, EarlyView.
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios, Anthony Gonzalez, Aleksander Aleman, Tyler Dolmetsch, Tanaji Paul, Arvind Agarwal   +5 more
wiley   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning

, 2020
This work proposes a novel distributed deep learning model for Remote Sensing (RS) images super-resolution. High Performance Computing (HPC) systems with GPUs are used to accelerate the learning of the unknown low to high resolution mapping from large ...
Gabriele Cavallaro, Cavallaro, Gabriele, Run Zhang, Zhang, Run, Jenia Jitsev, Jitsev, Jenia   +5 more
core   +1 more source

Secure deep learning for distributed data against maliciouscentral server

PLoS ONE, 2022
In this paper, we propose a secure system for performing deep learning with distributed trainers connected to a central parameter server. Our system has the following two distinct features: (1) the distributed trainers can detect malicious activities in ...
Le Trieu Phong
doaj