Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Arghya Kusum Das"'
Autor:
Falk Huettmann, Phillip Andrews, Moriz Steiner, Arghya Kusum Das, Jacques Philip, Chunrong Mi, Nathaniel Bryans, Bryan Barker
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract The currently available distribution and range maps for the Great Grey Owl (GGOW; Strix nebulosa) are ambiguous, contradictory, imprecise, outdated, often hand-drawn and thus not quantified, not based on data or scientific. In this study, we
Externí odkaz:
https://doaj.org/article/2b0a7b1cd243429f82c9818e6aeae847
Publikováno v:
BMC Genomics, Vol 20, Iss S11, Pp 1-15 (2019)
Abstract Background Long-read sequencing has shown the promises to overcome the short length limitations of second-generation sequencing by providing more complete assembly. However, the computation of the long sequencing reads is challenged by their
Externí odkaz:
https://doaj.org/article/2bdd415b4042490b8ed1ff99a04c8e48
Publikováno v:
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
Publikováno v:
Data Management, Analytics and Innovation ISBN: 9789811925993
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd2b7fa72f12cfa760318118f5b99e67
https://doi.org/10.1007/978-981-19-2600-6_15
https://doi.org/10.1007/978-981-19-2600-6_15
Autor:
Arghya Kusum Das
In this paper, we introduce SwarMED, a decentralized yet high throughput interoperability system for big biomedical data. SwarMED uses Etehreum blockchain for trustless security and Swarm p2p storage to handle high throughput transaction of big data.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ac04f842415098e235d434507e91346
Autor:
Arghya Kusum Das, Ajanta Das
BACKGROUND An electronic consent management system can improve the care service significantly by balancing the risks to patient privacy with the benefits of health information exchange and interoperability. Patients leave their health information on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cc380a50a91ad11309cd503fa9f60a1
https://doi.org/10.2196/preprints.23296
https://doi.org/10.2196/preprints.23296
Publikováno v:
International Journal of Computational Science and Engineering. 1:1
Publikováno v:
PEARC
We introduce a novel framework, DARE-MetaQA, enabling large-scale Question Answering (QA). By enhancing the Key-Value Memory Network (KV-MemNN) model, our framework is capable of overcoming inherent challenges of the baseline model in two specific as