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Autor:
Christoph U. Germeier, Stefan Unger
Publikováno v:
Frontiers in Plant Science, Vol 10 (2019)
Documentation of phenotype information is a priority need in biodiversity, crop modeling, breeding, ecology, and evolution research, for association studies, gene discovery, retrospective statistical analysis and data mining, QTL re-mapping, choosing
Externí odkaz:
https://doaj.org/article/76e9b497e7b84fd3a651e5c596fa65ae
Publikováno v:
Moravian Geographical Reports, Vol 24, Iss 2, Pp 37-46 (2016)
The definition of functional meso regions for the territory of the Czech Republic is articulated in this article. Functional regions reflect horizontal interactions in space and are presented as a useful tool for various types of geographical analyse
Externí odkaz:
https://doaj.org/article/2b5871a857ac4d4585441cac01f306a4
Autor:
Banerjee, Arindham
Publikováno v:
Indian Institute of Management Ahmedabad, 2013, pp. 1-16.
Publikováno v:
2022 IEEE Symposium on Computers and Communications (ISCC)
Slices are deployed to continuously fulfill requirements from vertical industries. Thus, the management of service level agreements (SLAs) is fundamental. Composite network services (NSs), made up of multiple nested NSs, can be exploited to build sli
Autor:
Chandrima Chakravarty, Huseyin Aksu, Jessica A. Martinez B., Pablo Ramos, Michele Pavanello, Barry D. Dunietz
Publikováno v:
The journal of physical chemistry letters. 13(22)
The low energy excited states of the conformational isomers of solvated azobenzene are calculated with several DFT methods accounting for the solute-solvent interaction implicitly with the polarizable continuum model or explicitly with subsystem DFT.
Publikováno v:
2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS).
Here we summarise a series of combined workflows for the remote detection and monitoring of archaeological features. We integrate satellite constellations with new field data acquired from multi-sensor drones. Our methods make use of the multitempora
Reinforcement Learning (RL)-based algorithmic solutions have been profusely proposed in recent years for addressing multiple problems in the Radio Access Network (RAN). However, how RL algorithms have to be trained for a successful exploitation has n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7513592b93759fabc2da2d0368035c4b
https://hdl.handle.net/2117/380800
https://hdl.handle.net/2117/380800