Výsledky vyhledávání

The Monitoring with Advanced Sensors, Transmission and E-Resuscitation in Traumatic Brain Injury (MASTER-TBI) collaborative: bringing data science to the ICU bedside

Autor: Shiv Meka, Daniel Fatovich

Publikováno v: Critical Care and Resuscitation. 24:39-42

BACKGROUND: With the adoption of multimodal neuromonitoring techniques, a large amount of high resolution neurophysiological data is generated during the treatment of patients with moderate to severe traumatic brain injury (m-sTBI) that is available

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0dadb4a965a826c3d277215d9447210a
https://doi.org/10.51893/2022.1.oa5

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A self-supervised learning based approach to analyze Martian water–ice cloud properties for planetary atmospheric applications

Autor: John E. Moores, Gretchen Benedix, Shiv Meka, Daniel Marrable, Kevin Chai, Charissa L. Campbell, Christina L. Smith, Andrew L. Rohl

Publikováno v: Acta Astronautica. 181:1-13

Currently, Martian water–ice cloud properties, such as wind direction and angular wind velocity, are determined through manual analysis of atmospheric movies taken by the Mars Science Laboratory (MSL, Curiosity). These atmospheric movies, known as

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::01afc75c67e8b5560585c2a17551ea39
https://doi.org/10.1016/j.actaastro.2020.12.041

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Hierarchical clustering of MS/MS spectra from the firefly metabolome identifies new lucibufagin compounds

Autor: Caroline S. Moffat, Darcy A. B. Jones, Shiv Meka, Suman Rakshit, Paula Moolhuijzen, Catherine Rawlinson

Publikováno v: Scientific Reports, Vol 10, Iss 1, Pp 1-9 (2020)
Scientific Reports

Metabolite identification is the greatest challenge when analysing metabolomics data, as only a small proportion of metabolite reference standards exist. Clustering MS/MS spectra is a common method to identify similar compounds, however interrogation

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c499aaa65b507486e6f0523a7adbaf88
http://link.springer.com/article/10.1038/s41598-020-63036-1

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pyROM: A computational framework for reduced order modeling

Autor: Shiv Meka, Vladimir Puzyrev, Mehdi Ghommem

Publikováno v: Journal of Computational Science. 30:157-173

Model reduction techniques reduce the overall complexity of dynamic systems and allow to speed up simulations of their behavior several orders of magnitude while retaining good accuracy. Despite being useful to obtain real-time simulations and apply

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f73621e9d08de53a44fe9c6c77668d92
https://doi.org/10.1016/j.jocs.2018.12.004

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Fluctuation of recent large impact craters rate on Mars from automatic crater detection

Autor: Anthony Lagain, Misha Kreslavsky, Gretchen Benedix, David Baratoux, Phil Bland, Martin Towner, Jonathan Paxman, Sylvain Bouley, Chris Norman, Seamus Anderson, Konstantinos Servis, Eleanor Samson, Kevin Chai, Shiv Meka

Knowledge of collision rates through time and space is essential because meteoritic impact crater counting is the only way to determine the ages of surface geological units and processes on the solid bodies of our Solar System. All chronology models

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4d5991ce14cf97d065c82c8d673d00d5
https://doi.org/10.5194/egusphere-egu2020-5003

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Deriving Surface Ages on Mars Using Automated Crater Counting

Autor: Kevin Chai, Anthony Lagain, C. Norman, Seamus Anderson, Jonathan Paxman, Martin C. Towner, Gretchen Benedix, Shiv Meka, Tele Tan, Philip A. Bland

Publikováno v: Earth and Space Science, Vol 7, Iss 3, Pp n/a-n/a (2020)

Impact craters on solar system bodies are used to determine the relative ages of surfaces. The smaller the limiting primary crater size, the higher the spatial resolution in surface/resurfacing age dating. A manually counted database (Robbins & Hynek

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb224135ee1dba0238093959567b13b8
https://doi.org/10.1029/2019ea001005

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Planetary Geochronology Using Machine Learning

Autor: Gretchen Benedix, Anthony Lagain, Kevin Chai, Shiv Meka, Kostantinos Servis, Philip Bland, Christopher Norman, Martin Towner, Eleanor Sansom, Seamus Anderson

Publikováno v: Goldschmidt Abstracts.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e51557e79921ee2bcfd1d5972f3dc2e6
https://doi.org/10.46427/gold2020.165

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A decision support system for grain harvesting, storage, and distribution logistics

Autor: Ryan Loxton, Luke Gamble, Shiv Meka, Elham Mardaneh

Publikováno v: Knowledge-Based Systems. 223:107037

This paper presents a decision support system to help farmers compare different grain harvesting and distribution strategies—for example, whether to store grain on farm or use bulk storage facilities located away from the farm. The system is underp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c54a44529ebb6edcc742cf60e21d7091
https://doi.org/10.1016/j.knosys.2021.107037

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Deep Convolutional Neural Networks for 1D Inversion of Electromagnetic Data

Autor: Shiv Meka, Vladimir Puzyrev, Andrei Swidinsky

Publikováno v: 81st EAGE Conference and Exhibition 2019.

We investigate the potential of deep learning based approaches to 1D EM inversion. Our approach to inversion based on deep neural networks is entirely data-driven, does not employ traditional gradient-based techniques and provides a guess to the mode

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f7b0916f3c05eba47bb03cc140ceb174
https://doi.org/10.3997/2214-4609.201901485

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