Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Ruimin, Xie"'
Publikováno v:
International Polymer Processing. 37:25-37
This paper considers a model of melt spinning with stress-induced crystallization, where the melt uses the Phan Thien-Tanner model, and the solid adopts the rubber elastic model. We design a computationally efficient algorithm for solving the model.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d92378891b94f3d34f5645ba980546c
https://doi.org/10.1515/ipp-2021-4033
https://doi.org/10.1515/ipp-2021-4033
Publikováno v:
Neurocomputing. 434:126-136
In this paper, a new soft sensor that combines eXtreme Gradient Boosting (Xgboost) decision trees and a bidirectional, converted gate long short-term memory (BiCG-LSTMs) self-attention (SEA) mechanism network is proposed. Xgboost is first utilized to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7eb5a812e29ca1a8531245f6c87c9ad7
https://doi.org/10.1016/j.neucom.2020.12.028
https://doi.org/10.1016/j.neucom.2020.12.028
Publikováno v:
IEEE Transactions on Industrial Electronics. 67:7034-7043
Data-driven soft sensors, estimating the pivotal quality variables, have been widely employed in industrial process. This paper proposes a novel soft sensor modeling approach based on a two-stream ${\rm{\lambda }}$ gated recurrent unit ( $TS - {\rm{\
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36619440fbc64d2708583911f03b5e7e
https://doi.org/10.1109/tie.2019.2927197
https://doi.org/10.1109/tie.2019.2927197
Publikováno v:
IEEE Transactions on Industrial Informatics. 16:2820-2828
Autoencoder (AE) is a deep neural network that has been widely utilized in process industry owing to its superior abilities of feature extraction and data reconstruction. Recently, assuming the latent variables to be random variables, a probabilistic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60647a0cad513fa21f4d3d4e53cbe8f3
https://doi.org/10.1109/tii.2019.2951622
https://doi.org/10.1109/tii.2019.2951622
Publikováno v:
Science of The Total Environment. 857:159495
Textile industry has yet to be developed beyond low efficiency, high resources consumption, and toxic emissions, with wet processing process a dominant contributor to resources consumption and pollution emissions. Recognition of the environmental imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe6785ccd87867fb5edab0e1a07f82d0
https://doi.org/10.1016/j.scitotenv.2022.159495
https://doi.org/10.1016/j.scitotenv.2022.159495
Publikováno v:
Zhonghua wei zhong bing ji jiu yi xue. 33(8)
To investigate the risk factors affecting the prognosis of patients with acute kidney injury (AKI) in the intensive care unit (ICU) based on the Medical Information Mart for Intensive Care III (MIMIC-III) database, and to establish a prognostic model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::3f834906e0732fce8ee4386d222dc2f6
https://pubmed.ncbi.nlm.nih.gov/34590562
https://pubmed.ncbi.nlm.nih.gov/34590562
Background Fracture healing is regulated by endocrine hormones and biochemical and biophysical factors, including hyaluronic acid (HA), which is a component of the extracellular matrix. The prerequisites for biological responses that promote fracture
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac251c0acb25525249bfc6fe63707fc0
https://doi.org/10.21203/rs.2.24766/v1
https://doi.org/10.21203/rs.2.24766/v1
Publikováno v:
Chemometrics and Intelligent Laboratory Systems. 197:103922
This paper presents a variational autoencoder-based just-in-time (JIT) learning framework for soft sensor modeling. Just-in-Time learning is often applied for soft sensor modeling in industrial processes. However, traditional just-in-time learning me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4d1b1a2c6923fd8b9940e57a833c9ca
https://doi.org/10.1016/j.chemolab.2019.103922
https://doi.org/10.1016/j.chemolab.2019.103922
Publikováno v:
Bioscience Reports
Human osteosarcoma is the most frequent primary malignant of bone, and often occurs in adolescents. However, molecular mechanism of this disease remains unclear. In the present study, we found that the level of Rhotekin 2 (RTKN2) was up-regulated in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::425d385cf054e961996f129e9e41f868
https://doi.org/10.1042/bsr20181384
https://doi.org/10.1042/bsr20181384
Publikováno v:
ASCC
In this paper, a prediction method of the melt spinning properties based on the Gated Recurrence Units (GRU) neural network model is proposed considering the time series property of the data. Spinning process plays a key role in the melt spinning pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4242cecf351c5306181b3f175b5dcc21
https://doi.org/10.1109/ascc.2017.8287531
https://doi.org/10.1109/ascc.2017.8287531