Research on meta‐action decomposition and meta‐action unit modeling technology for electromechanical product

2019 ◽  
Vol 36 (1) ◽  
pp. 268-284 ◽  
Author(s):  
Yulong Li ◽  
Xiaogang Zhang ◽  
Yan Ran ◽  
Genbao Zhang ◽  
Yongqin Wang

The variants of the division of the life cycle of a construction object at the stages adopted in the territory of the Russian Federation, as well as in other countries are considered. Particular attention is paid to the exemplary work plan – "RIBA plan of work", used in England. A feature of this document is its applicability in the information modeling of construction projects (Building information Modeling – BIM). The article presents a structural and logical scheme of the life cycle of a building object and a list of works that are performed using information modeling technology at various stages of the life cycle of the building. The place of information models in the process of determining the service life of the building is shown. On the basis of the considered sources of information, promising directions for the development of the life cycle management system of the construction object (Life Cycle Management) and the development of the regulatory framework in order to improve the use of information modeling in construction are given.


2009 ◽  
Vol 35 (2) ◽  
pp. 198-201 ◽  
Author(s):  
Lei WANG ◽  
Bei-Ji ZOU ◽  
Xiao-Ning PENG

Author(s):  
Dakai Ren ◽  
Xiangmin Wen ◽  
Jiazhong Chen ◽  
Yu Han ◽  
Shiqi Zhang

Author(s):  
Yulong Li ◽  
Shutao Wen ◽  
Shengquan Liu ◽  
Lingyu Zhao ◽  
Qinghang Wang ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4222
Author(s):  
Shushi Namba ◽  
Wataru Sato ◽  
Masaki Osumi ◽  
Koh Shimokawa

In the field of affective computing, achieving accurate automatic detection of facial movements is an important issue, and great progress has already been made. However, a systematic evaluation of systems that now have access to the dynamic facial database remains an unmet need. This study compared the performance of three systems (FaceReader, OpenFace, AFARtoolbox) that detect each facial movement corresponding to an action unit (AU) derived from the Facial Action Coding System. All machines could detect the presence of AUs from the dynamic facial database at a level above chance. Moreover, OpenFace and AFAR provided higher area under the receiver operating characteristic curve values compared to FaceReader. In addition, several confusion biases of facial components (e.g., AU12 and AU14) were observed to be related to each automated AU detection system and the static mode was superior to dynamic mode for analyzing the posed facial database. These findings demonstrate the features of prediction patterns for each system and provide guidance for research on facial expressions.


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