Zobrazeno 1 - 10 of 12 pro vyhledávání: '"Arjuna Chala"'
1
Akademický článek
The forecast of COVID-19 spread risk at the county level
Autor: Murtadha D. Hssayeni, Arjuna Chala, Roger Dev, Lili Xu, Jesse Shaw, Borko Furht, Behnaz Ghoraani
Publikováno v: Journal of Big Data, Vol 8, Iss 1, Pp 1-16 (2021)
Abstract The early detection of the coronavirus disease 2019 (COVID-19) outbreak is important to save people’s lives and restart the economy quickly and safely. People’s social behavior, reflected in their mobility data, plays a major role in spr
Externí odkaz: https://doaj.org/article/9732286aab0f4a76be77312a31a8f995
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2
Akademický článek
Modeling and tracking Covid-19 cases using Big Data analytics on HPCC system platformm
Autor: Flavio Villanustre, Arjuna Chala, Roger Dev, Lili Xu, Jesse Shaw LexisNexis, Borko Furht, Taghi Khoshgoftaar
Publikováno v: Journal of Big Data, Vol 8, Iss 1, Pp 1-24 (2021)
Abstract This project is funded by the US National Science Foundation (NSF) through their NSF RAPID program under the title “Modeling Corona Spread Using Big Data Analytics.” The project is a joint effort between the Department of Computer & Elec
Externí odkaz: https://doaj.org/article/e1377e9010cc4cc4bc738608ea59f001
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4
The forecast of COVID-19 spread risk at the county level
Autor: Lili Xu, Roger Dev, Murtadha D. Hssayeni, Borko Furht, Behnaz Ghoraani, Jesse C P B Shaw, Arjuna Chala
Publikováno v: Journal of Big Data
Journal of Big Data, Vol 8, Iss 1, Pp 1-16 (2021)
The early detection of the coronavirus disease 2019 (COVID-19) outbreak is important to save people’s lives and restart the economy quickly and safely. People’s social behavior, reflected in their mobility data, plays a major role in spreading th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c54b9b8448744914e234faddd44ddaf7
https://doi.org/10.1186/s40537-021-00491-1
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5
Modeling and tracking Covid-19 cases using Big Data analytics on HPCC system platform
Autor: Jesse Shaw LexisNexis, Flavio Villanustre, Borko Furht, Arjuna Chala, Taghi M. Khoshgoftaar, Lili Xu, Roger Dev
Publikováno v: Journal of Big Data, Vol 8, Iss 1, Pp 1-24 (2021)
Journal of Big Data
This project is funded by the US National Science Foundation (NSF) through their NSF RAPID program under the title “Modeling Corona Spread Using Big Data Analytics.” The project is a joint effort between the Department of Computer & Electrical En
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::830bfd7a8b9b4874a56a2f2af39548dd
https://doi.org/10.1186/s40537-021-00423-z
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7
Large Scale Financial Filing Analysis on HPCC Systems
Autor: Matthias Murray, Arjuna Chala, Lili Xu, Roger Dev
Publikováno v: IEEE BigData
Insights from public companies’ financial filings are necessary for securities analysts and investors to make the right investment decisions. Synthesizing salient facts from such filings is a complex language task, especially now as the data volume
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0d8e7e9a51a5027d6fd7f80832e11298
https://doi.org/10.1109/bigdata50022.2020.9378388
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8
Massively Scalable Parallel KMeans on the HPCC Systems Platform
Autor: Amy Apon, Roger Dev, Arjuna Chala, Lili Xu, Flavio Villanustre
Publikováno v: 2019 4th International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS).
Clustering algorithms are an important part of unsupervised machine learning. With Big Data, applying clustering algorithms such as KMeans has become a challenge due to the significantly larger volume of data and the computational complexity of the s
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b515a01971516a78ec9ac8b3143988c5
https://doi.org/10.1109/csitss47250.2019.9031047
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9
Design and Implementation of Machine Learning Evaluation Metrics on HPCC Systems
Autor: A. Suryanarayanan, Arjuna Chala, Jyoti Shetty, Lili Xu, Roger Dev, G. Shobha
Publikováno v: 2019 4th International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS).
The HPCC Systems Production Machine Learning bundles provide a diverse set of features that allow the parallelized creation and training of Machine learning models and a large set of evaluation metrics that can be used to test the trained model to as
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d45ab28f2f72347de600c6fe120c89ad
https://doi.org/10.1109/csitss47250.2019.9031056
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10
Data Skew Profiling using HPCC Systems
Autor: G. Shobha, Arjuna Chala, Jayanth S, Jyoti Shetty, Harsh Mishra, Dan Camper
Publikováno v: Proceedings of the 2019 International Conference on Big Data and Education.
Over the last few decades, there has been a tremendous increase in the volume of data available for analysis in various domains. Although processing power has scaled up as well, it is well known that the rate of increase of data far supersedes the hi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f223991815cd26a6ef1f614853e1e7d0
https://doi.org/10.1145/3322134.3322142
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