Results 111 to 120 of about 3,910,298 (308)
Solving the applied tasks using the heterogeneous computing systems
The urgency of the discussed issue is caused by the wide spreading of graphics processors and the ability to use them to improve the performance by parallel computing.
T. E. Loshchukhina, V. A. Dorofeev
doaj
In this study, we investigate the underlying causes of drift in the time history curves of measured parameters obtained through strain electrical measurements and assess their impacts on load measurements.
Yongwei Tian +3 more
doaj +1 more source
Objective Systemic sclerosis (SSc) is characterized by cardiovascular risk excess not fully explained by traditional factors. Whether the severity of microvascular damage correlates with structural subclinical atherosclerosis remains unclear. We investigated the relationship between nailfold videocapillaroscopy (NVC) abnormalities and carotid ...
Eugenio Capparelli +13 more
wiley +1 more source
The problem of the interferometric phase unwrapping in radar remote sensing of Earth systems is considered. Such interferograms are widely used in the problems of creating and updating maps of the relief of the Earth’s surface in geodesy, cartography ...
Petr S. Martyshko +3 more
doaj +1 more source
Objective We examined associations of posttraumatic stress disorder (PTSD) and other mental health disorders (OMH) with rheumatoid arthritis (RA), accounting for effects of smoking. Methods We conducted a matched case‐control study, identifying incident RA cases and controls using national Veterans Health Administration data (2006–2019).
Kelsey Coziahr +15 more
wiley +1 more source
Parallel algorithm to find Bayes-Nash solution to the bimatrix informational extended game [PDF]
We propose to use the new methodology for solving the complete and perfect information bimatrix game. To solve the games of these type we construct the incomplete and imperfect information game generated by the informational extended strategies.
Boris Hancu, Anatolie Gladei
doaj
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
An Efficient Parallel Algorithm for LISSOM Neural Network
We present a parallel algorithm for laterally interconnected synergetically self-organizing map (LISSOM) neural network, a self-organizing map with lateral excitatory and inhibitory connections, to enhance the computational efficiency. A general strategy
Chang, Li-Chiu;Chang,Fi-John +1 more
core
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
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 +2 more
wiley +1 more source
Exploiting Immunological Metaphors in the Development of Serial, Parallel and Distributed Learning Algorithms [PDF]
This thesis examines the use of immunological metaphors in building serial, parallel, and distributed learning algorithms. It offers a basic study in the development of biologically-inspired algorithms which merge inspiration from biology with known ...
Watkins, Andrew
core

