Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Emil Laftchiev"'
Publikováno v:
International Journal of Prognostics and Health Management, Vol 10, Iss 4 (2019)
This paper addresses a multi-label predictive fault classification problem for multidimensional time-series data. While fault (event) detection problems have been thoroughly studied in literature, most of the state-of-the-art techniques can’t relia
Externí odkaz:
https://doaj.org/article/6a2836e7b342479abc1535df29555868
Autor:
Annamalai Natarajan, Emil Laftchiev
Publikováno v:
International Journal of Prognostics and Health Management, Vol 10, Iss 3 (2019)
Personal thermal comfort is the feeling that individuals have about how hot, cold or comfortable they are. Studies have hown that thermal comfort is a key component of human performance in the work place and that personalized thermal comfort models c
Externí odkaz:
https://doaj.org/article/bdb36c575ea6418dbf6249827294ad23
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:15339-15346
Maintaining individual thermal comfort in indoor spaces shared by multiple occupants is difficult because it requires both intuition about the thermal properties of the room, as well as an understanding of the thermal comfort preferences of each indi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a3bc1ed20878b14c2a264ae350e148a
https://doi.org/10.1609/aaai.v35i17.17801
https://doi.org/10.1609/aaai.v35i17.17801
Publikováno v:
ACC
Automatic optimization of individual thermal comfort in indoor spaces shared by multiple occupants is difficult, because it requires understanding of the individual thermal comfort preferences, modeling of the room thermodynamics, and fast online opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b91b3479b7863d16166bdcfe1f803e42
https://doi.org/10.23919/acc50511.2021.9483191
https://doi.org/10.23919/acc50511.2021.9483191
Publikováno v:
IEEE BigData
Rapid advances in information and communications technologies (ICT) have made it possible to deploy large collections of sensors to be used in traditional Supervisory Control and Data Acquisition (SCADA) systems and modern Internet of Things (IoT) in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fac162812dadc34c1bac40ad598e728c
https://doi.org/10.1109/bigdata50022.2020.9378144
https://doi.org/10.1109/bigdata50022.2020.9378144
Publikováno v:
Construction and Building Materials. 228:116661
This study evaluates the efficacy of machine learning (ML) methods to predict the compressive strength of field-placed concrete. We employ both field- and laboratory-obtained data to train and test ML models of increasing complexity to determine the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::509869047efa0da5b003f729f7958c57
https://doi.org/10.1016/j.conbuildmat.2019.08.042
https://doi.org/10.1016/j.conbuildmat.2019.08.042
Autor:
Emil Laftchiev, Daniel Nikovski
Publikováno v:
WF-IoT
Thermal comfort in office buildings is emerging as an important variable that can be used to maximize employee productivity. In this paper we propose a new Internet of Things (IoT) based system that creates a personalized model of thermal comfort. To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7742ad224071ef5ae6a6ddc8023170a5
https://doi.org/10.1109/wf-iot.2016.7845401
https://doi.org/10.1109/wf-iot.2016.7845401
Publikováno v:
CDC
Improvements in sensor technology and data processing rates are leading to the collection of vast databases of time series data. These data sets are spawning new applications that are transforming the way we live, work, and learn. In particular in th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::076aa096b715c9da9766bb38c5952806
https://doi.org/10.1109/cdc.2014.7040276
https://doi.org/10.1109/cdc.2014.7040276
Publikováno v:
CDC
Using terrain data and dynamical models is a promising approach to map-based passenger vehicle localization. In this approach, dynamical models are extracted from terrain data collected by a vehicle with a known location. The dynamical models are sto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0f049d80eb7cb831bd49a0126866273
https://doi.org/10.1109/cdc.2013.6760311
https://doi.org/10.1109/cdc.2013.6760311