Results 51 to 60 of about 5,647,510 (295)
FPGA Checkpointing for Scientific Computing
2021 IEEE 27th International Symposium on On-Line Testing and Robust System Design (IOLTS), 2021 This research has received funding from the European Union’s Horizon 2020 research and innovation programme under projects EuroEXA (grant agreement nº 754337) and eProcessor (grant agreement nº 956702).
Perelló Bacardit, Marc +2 more
openaire +2 more sources
High Performance Computing in Satellite SAR Interferometry: A Critical Perspective
Remote Sensing, 2021 Synthetic aperture radar (SAR) interferometry has rapidly evolved in the last decade and can be considered today as a mature technology, which incorporates computationally intensive and data-intensive tasks.
Pasquale Imperatore +2 more
doaj +1 more source
Successful operational integration of healthcare analytics at Seattle Children's
Learning Health Systems, 2023 Introduction As the quantity and complexity of health data grows, it is critical for healthcare organizations to devise analytic strategies that power data innovation so they can take advantage of new opportunities and improve outcomes.
Kathleen L. Frisbee, Ryan Sousa
doaj +1 more source
Advances in Electrical and Computer Engineering, 2022 Parallel programming is increasingly used to improve the performance of solving numerical methods used for scientific purposes. Numerical methods in the field of fluid dynamics require the calculation of a large number of operations per second.
TEKIC, J., TEKIC, P., RACKOVIC, M.
doaj +1 more source
A Hybrid Two-Stage GNG–Modified VGG Method for Bone X-Rays Classification and Abnormality Detection
IEEE Access, 2021 This paper introduces a novel, reliable, hybrid, two-stage method for bone x-ray classification and abnormality detection. The proposed method considers bones from seven areas of the upper extremities: namely, shoulder, humerus, forearm, elbow, wrist ...
Hadeer El-Saadawy +3 more
doaj +1 more source
Designing accurate emulators for scientific processes using calibration-driven deep models
Nature Communications, 2020 The success of machine learning for scientific discovery normally depends on how well the inherent assumptions match the problem in hand. Here, Thiagarajan et al. alleviate this constraint by allowing the change of optimization criterion in a data-driven
Jayaraman J. Thiagarajan +6 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) is assessed by cell counting and cytomorphology from cerebrospinal fluid (CSF) and is used for treatment stratification worldwide. The ratio of “CNS2” patients in clinical trials ranges from 3% to 40%, with unclear prognostic significance ...
Laura Almási +14 more
wiley +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Objective To compare the efficacy and safety of roxarestat versus recombinant human erythropoietin (rhEPO) in the management of renal anemia in patients undergoing maintenance hemodialysis. Methods This was a prospective, open‐label, randomized controlled trial.
Lingling Chen, Junjie Zhu, Qiaonan Ge
wiley +1 more source
, 2018 Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial ...
M. Heath
semanticscholar +3 more sources
SpackDev: Multi-Package Development with Spack [PDF]
EPJ Web of Conferences, 2020 High Energy Physics (HEP) software environments often involve ∼ hundreds of external packages and libraries, and similar numbers of experiment-specific, science-critical packages—many under continuous development.
Green Chris +4 more
doaj +1 more source