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pro vyhledávání: '"Anastasiia Sedova"'
Autor:
Anastasiia Sedova
Publikováno v:
European Journal of Cultural Management and Policy. 12
Today, many churches all around the world are in various states of disrepair, which would be an irreparable loss. This research paper examines the new, mixed or extended adaptive use of underutilised and abandoned ecclesiastical cultural heritage wit
Strategies for improving the training and prediction quality of weakly supervised machine learning models vary in how much they are tailored to a specific task or integrated with a specific model architecture. In this work, we introduce Knodle, a sof
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d75cf1fa0a12b4c5e9bff1b5b37ef2a
Publikováno v:
E3S Web of Conferences, Vol 281, p 03007 (2021)
3D concrete printing is a perspective technology for sustainable construction and realization of sophisticated architectural projects. The current research proposes the thermal engineering calculation of wall structure based on the 3D printed concret
Autor:
Anastasiia Sedova, Alevtina Balakina
Publikováno v:
E3S Web of Conferences, Vol 263, p 04050 (2021)
Smart city concept concerns urban innovations based on but not limited by the wide application of IoT. Whereas, four dimensions encompass various elements of smart cities: governance dimension, environ-urban dimension, socio-institutional dimension,
Autor:
Alevtina Balakina, Anastasiia Sedova
Publikováno v:
IOP Conference Series: Materials Science and Engineering. 869:022023
A smart city concept is becoming more popular. Many cities shift directions for the development of to “smart” destination, which is able to address rapid growth in the urban population and climate change. The concept of smart development consists
Autor:
Olga Mitrofanova, Anastasiia Sedova
Publikováno v:
Proceedings of the International Conference IMS-2017.
The paper is devoted to processing parallel and comparable corpora by means of topic modelling. We focus our attention on Russian and English parallel and comparable texts. We use Latent Dirichlet Allocation (LDA) algorithm for building topic models