Large Scale Agent Based Social Simulations with High Resolution Raster Inputs in Distributed HPC Environments

2020 ◽  
pp. 205-214
Author(s):  
Sergiy Gogolenko
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Agent Based

A Large Scale, High Resolution Agent-Based Insurgency Model

2013 ◽  
Author(s):  
Lucas A. Overbey ◽  
Bradley Mitchell ◽  
Samuel Yaryan ◽  
Kenneth McCullough
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Agent Based

MODELING THE SOUTH ATLANTIC OCEAN FROM MEDIUM TO HIGH RESOLUTION

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Mariela Gabioux ◽  
Vladimir Santos da Costa ◽  
Joao Marcos Azevedo Correia de Souza ◽  
Bruna Faria de Oliveira ◽  
Afonso De Moraes Paiva
Keyword(s):  
High Resolution ◽  
Atlantic Ocean ◽  
Large Scale ◽  
South Atlantic ◽  
Surface Relaxation ◽  
The South ◽  
Small Surface ◽  
Basic Model ◽  
Basic Set ◽  
Set Up

Results of the basic model configuration of the REMO project, a Brazilian approach towards operational oceanography, are discussed. This configuration consists basically of a high-resolution eddy-resolving, 1/12 degree model for the Metarea V, nested in a medium-resolution eddy-permitting, 1/4 degree model of the Atlantic Ocean. These simulations performed with HYCOM model, aim for: a) creating a basic set-up for implementation of assimilation techniques leading to ocean prediction; b) the development of hydrodynamics bases for environmental studies; c) providing boundary conditions for regional domains with increased resolution. The 1/4 degree simulation was able to simulate realistic equatorial and south Atlantic large scale circulation, both the wind-driven and the thermohaline components. The high resolution simulation was able to generate mesoscale and represent well the variability pattern within the Metarea V domain. The BC mean transport values were well represented in the southwestern region (between Vitória-Trinidade sea mount and 29S), in contrast to higher latitudes (higher than 30S) where it was slightly underestimated. Important issues for the simulation of the South Atlantic with high resolution are discussed, like the ideal place for boundaries, improvements in the bathymetric representation and the control of bias SST, by the introducing of a small surface relaxation. In order to make a preliminary assessment of the model behavior when submitted to data assimilation, the Cooper & Haines (1996) method was used to extrapolate SSH anomalies fields to deeper layers every 7 days, with encouraging results.

scholarly journals COVID‐19 Modeling: High‐Resolution Agent‐Based Modeling of COVID‐19 Spreading in a Small Town (Adv. Theory Simul. 3/2021)

2021 ◽  
Vol 4 (3) ◽  
pp. 2170005
Author(s):  
Agnieszka Truszkowska ◽  
Brandon Behring ◽  
Jalil Hasanyan ◽  
Lorenzo Zino ◽  
Sachit Butail ◽  
...  
Keyword(s):  
High Resolution ◽  
Small Town ◽  
Agent Based Modeling ◽  
Agent Based

scholarly journals Author Correction: High-resolution, large-scale laboratory measurements of a sandy beach and dynamic cobble berm revetment

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Chris E. Blenkinsopp ◽  
Paul M. Bayle ◽  
Daniel C. Conley ◽  
Gerd Masselink ◽  
Emily Gulson ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Sandy Beach ◽  
Laboratory Measurements

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00874-2.

scholarly journals Rapid Single Image-Based DTM Estimation from ExoMars TGO CaSSIS Images Using Generative Adversarial U-Nets

2021 ◽  
Vol 13 (15) ◽  
pp. 2877
Author(s):  
Yu Tao ◽  
Siting Xiong ◽  
Susan J. Conway ◽  
Jan-Peter Muller ◽  
Anthony Guimpier ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Imaging System ◽  
Landing Site ◽  
Parameter Tuning ◽  
Processing Parameters ◽  
Input Image ◽  
Large Area ◽  
Laser Altimeter ◽  
Imaging Science

The lack of adequate stereo coverage and where available, lengthy processing time, various artefacts, and unsatisfactory quality and complexity of automating the selection of the best set of processing parameters, have long been big barriers for large-area planetary 3D mapping. In this paper, we propose a deep learning-based solution, called MADNet (Multi-scale generative Adversarial u-net with Dense convolutional and up-projection blocks), that avoids or resolves all of the above issues. We demonstrate the wide applicability of this technique with the ExoMars Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) 4.6 m/pixel images on Mars. Only a single input image and a coarse global 3D reference are required, without knowing any camera models or imaging parameters, to produce high-quality and high-resolution full-strip Digital Terrain Models (DTMs) in a few seconds. In this paper, we discuss technical details of the MADNet system and provide detailed comparisons and assessments of the results. The resultant MADNet 8 m/pixel CaSSIS DTMs are qualitatively very similar to the 1 m/pixel HiRISE DTMs. The resultant MADNet CaSSIS DTMs display excellent agreement with nested Mars Reconnaissance Orbiter Context Camera (CTX), Mars Express’s High-Resolution Stereo Camera (HRSC), and Mars Orbiter Laser Altimeter (MOLA) DTMs at large-scale, and meanwhile, show fairly good correlation with the High-Resolution Imaging Science Experiment (HiRISE) DTMs for fine-scale details. In addition, we show how MADNet outperforms traditional photogrammetric methods, both on speed and quality, for other datasets like HRSC, CTX, and HiRISE, without any parameter tuning or re-training of the model. We demonstrate the results for Oxia Planum (the landing site of the European Space Agency’s Rosalind Franklin ExoMars rover 2023) and a couple of sites of high scientific interest.

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