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Human pose completion in partial body camera shots
(2023-07-28)
Article
Restricted access - publisher's policyMany actual images contain partial body camera shots, in which a significant part of the body is not visible. This issue is especially prevalent in film images, where less than 10% are full-body shots. Most 2D human pose ... -
Automatizing the creation of specialized high-performance computing containers
(SAGE publishing, 2023-07)
Article
Open AccessWith Exascale computing already here, supercomputers are systems every time larger, more complex, and heterogeneous. While expert system administrators can install and deploy applications in the systems correctly, this is ... -
Embedded federated learning over a LoRa mesh network
(Elsevier, 2023-06)
Article
Open AccessIn on-device training of machine learning models on microcontrollers a neural network is trained on the device. A specific approach for collaborative on-device training is federated learning. In this paper, we propose ... -
Enhancing iteration performance on distributed task-based workflows
(Elsevier, 2023-12)
Article
Restricted access - publisher's policyTask-based programming models have proven to be a robust and versatile way to approach development of applications for distributed environments. They provide natural programming patterns with high performance. However, ... -
Balancing EC-Earth3 improving the performance of EC-Earth CMIP6 configurations by minimizing the coupling cost
(John Wiley & sons, 2023-08)
Article
Open AccessEarth System Models (ESMs) are complex systems used in weather and climate studies generally built from different independent components responsible for simulating a specific realm (ocean, atmosphere, biosphere, etc.). To ... -
Meshing strategies for 3d geo-electromagnetic modeling in the presence of metallic infrastructure
(2023-09-08)
Article
Open AccessIn 3D geo-electromagnetic modeling, an adequate discretisation of the modeling domain is crucial to obtain accurate forward responses and reliable inversion results while reducing the computational cost. This paper ... -
Thermodynamics-informed neural network for recovering supercritical fluid thermophysical information from turbulent velocity data
(Elsevier, 2023-11)
Article
Open AccessRecent research has highlighted the potential of supercritical fluids under high-pressure transcritical conditions to achieve microconfined turbulence as a result of the thermophysical properties they exhibit in the vicinity ... -
A one-pass clustering based sketch method for network monitoring
(Institute of Electrical and Electronics Engineers (IEEE), 2023-01-01)
Article
Open AccessNetwork monitoring solutions need to cope with increasing network traffic volumes, as a result, sketch-based monitoring methods have been extensively studied to trade accuracy for memory scalability and storage reduction. ... -
Electromagnetic imaging and deep learning for transition to renewable energies: a technology review
(Frontiers Media SA, 2023-08-17)
Article
Open AccessElectromagnetic imaging is a technique that has been employed and perfected to investigate the Earth subsurface over the past three decades. Besides the traditional geophysical surveys (e.g., hydrocarbon exploration, ... -
Determining real-time communication feasibility in IoT systems supported by LoRaWAN
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-04-26)
Article
Open AccessLoRaWAN is a long range and low power protocol devised for connecting devices under the Internet of Things (IoT) paradigm. This protocol was not conceived to support real-time message delivery; therefore, it is not always ... -
High performance computing PP-distance algorithms to generate X-ray spectra from 3D models
(Multidisciplinary Digital Publishing Institute (MDPI), 2022-09-27)
Article
Open AccessX-ray crystallography is a powerful method that has significantly contributed to our understanding of the biological function of proteins and other molecules. This method relies on the production of crystals that, however, ... -
RouteNet-Fermi: network modeling with graph neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 2023-05-08)
Article
Open AccessNetwork models are an essential block of modern networks. For example, they are widely used in network planning and optimization. However, as networks increase in scale and complexity, some models present limitations, such ...