Zobrazeno 1 - 10
of 25 174
pro vyhledávání: '"Silva Maria"'
Autor:
Poeiras Ana Patrícia, Oliveira Teresa, Reis Joana, Surový Peter, Silva Maria Emília, de Almeida Ribeiro Nuno
Publikováno v:
Central European Forestry Journal, Vol 68, Iss 1, Pp 3-14 (2022)
Cork oak (Quercus suber L.) grows in the Mediterranean basis including Portugal and is the main species producing cork which is used prevailingly in stopper industry. In our paper, cork from Quercus suber L. over three consecutive harvests from a tra
Externí odkaz:
https://doaj.org/article/12a214f8d6c84465ab6f76b9945dd609
Autor:
Jing Hu, Silva Maria do Carmo Vieira
Publikováno v:
RUDN Journal of Informatization in Education, Vol 18, Iss 1, Pp 12-26 (2021)
Problem and goal. With the advent of the information age, Internet-based online learning has also become one of the learning methods chosen by many learners. They can use these online learning platforms to complete knowledge construction while learni
Externí odkaz:
https://doaj.org/article/c8b2c14a53ec4f72b498bd521358ccb6
Despite blockchain data being publicly available, practical challenges and high costs often hinder its effective use by researchers, thus limiting data-driven research and exploration in the blockchain space. This is especially true when it comes to
Externí odkaz:
http://arxiv.org/abs/2407.18699
Despite the level of attention given to rollups there is limited empirical research about their performance. To address this gap, we conduct a comprehensive data-driven analysis of the late 2023 transaction boom that is attributed to inscriptions: a
Externí odkaz:
http://arxiv.org/abs/2405.15288
Late 2023 witnessed significant user activity on EVM chains, resulting in a surge in transaction activity and putting many rollups into the first live test. While some rollups performed well, some others experienced downtime during this period, affec
Externí odkaz:
http://arxiv.org/abs/2404.11189
In recent years, there has been a surge in the prevalence of high- and multi-dimensional temporal data across various scientific disciplines. These datasets are characterized by their vast size and challenging potential for analysis. Such data typica
Externí odkaz:
http://arxiv.org/abs/2311.11849