Zobrazeno 1 - 10
of 1 085
pro vyhledávání: '"geometric features"'
Publikováno v:
Engineering Applications of Computational Fluid Mechanics, Vol 18, Iss 1 (2024)
Many aerodynamic shape optimization methods often focus on utilizing the end-to-end relationship between design variables and aerodynamic performance to find the optimal design, while overlooking the exploration of geometric knowledge of the shape it
Externí odkaz:
https://doaj.org/article/05fbe462a7ce4701b81e6789f3a6c7a6
Autor:
Rabia Rashdi, Iván Garrido, Jesús Balado, Pablo Del Río-Barral, Juan Luis Rodríguez-Somoza, Joaquín Martínez-Sánchez
Publikováno v:
European Journal of Remote Sensing, Vol 57, Iss 1 (2024)
ABSTRACTMobile laser scanners are vital for intelligent transport infrastructure, capturing detailed 3D road representations, but their accuracy depends on factors like sensor positioning and environment. This study compares two van-mounted Mobile La
Externí odkaz:
https://doaj.org/article/9f621d08233744d6bd1ea94dc2b8fa80
Publikováno v:
Frontiers in Earth Science, Vol 12 (2024)
The precise characterization of the rock microstructure is crucial for predicting the physical characteristics, flow behavior, and mechanical properties of rocks. This is particularly important for carbonate rocks, which depict a complex microstructu
Externí odkaz:
https://doaj.org/article/afd7730a5eb4429492b4a78b8158ea69
Autor:
BAI Jie, YUAN Chao
Publikováno v:
Meikuang Anquan, Vol 54, Iss 7, Pp 188-195 (2023)
To explore the influence of fracture structure on mechanical properties of rock mass, compression simulation experiment were carried out on rock samples with prefabricated fractures. Based on SEM, NMR and Vic-3D technology, multi-scale study was carr
Externí odkaz:
https://doaj.org/article/a7a2f255962c4b3e97b32a980222a58f
Autor:
B. Raghuram, Bhukya Hanumanthu
Publikováno v:
Measurement: Sensors, Vol 30, Iss , Pp 100905- (2023)
The health services research network is showing a lot of interest in the Internet of Medical Things (IoMT). In IoMT, the Internet is used to help compile important health-related data. A brain tumor is caused by a mass of random cells inside the brai
Externí odkaz:
https://doaj.org/article/5d72b6fbab9340e6970ae1e639ce6859
Publikováno v:
Sensors, Vol 24, Iss 11, p 3534 (2024)
Three-dimensional point cloud evaluation is used in photogrammetry to validate and assess the accuracy of data acquisition in order to generate various three-dimensional products. This paper determines the optimal accuracy and correctness of a 3D poi
Externí odkaz:
https://doaj.org/article/0b0536be942a41e7be5065b85e6e0374
Autor:
Massimiliano Pepe, Alfredo Restuccia Garofalo, Domenica Costantino, Federica Francesca Tana, Donato Palumbo, Vincenzo Saverio Alfio, Enrico Spacone
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1630 (2024)
The aim of the paper is to identify an efficient method for transforming the point cloud into parametric objects in the fields of architecture, engineering and construction by four main steps: 3D survey of the structure under investigation, generatio
Externí odkaz:
https://doaj.org/article/452b46545a374303a7e65807bed7c55b
Publikováno v:
Engineering Proceedings, Vol 65, Iss 1, p 13 (2024)
The aim of this project is to verify the suitability of three-dimensional (3D) scanners with computer-aided systems as a new method of geometric feature inspection. Three-dimensional scanners are widely used for field recording and model reconstructi
Externí odkaz:
https://doaj.org/article/85a9a3c9b79c4c469537c234d3f97134
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 13, Iss 3, p 95 (2024)
The classification of urban functional areas is important for understanding the characteristics of urban areas and optimizing the utilization of urban land resources. Existing related methods have improved accuracy. However, they neglect cognitive di
Externí odkaz:
https://doaj.org/article/e3da454fcb7b4845b185fe2e8ad29224
Publikováno v:
Results in Engineering, Vol 19, Iss , Pp 101368- (2023)
In this study, we develop and train a domain-expert supervised learning framework for reliable prediction of the radiative properties of heterogeneous porous media. Our chosen model is based on a hybrid deep learning (HDL) approach employing convolut
Externí odkaz:
https://doaj.org/article/eaeecd5d9d5b44d4bc3a9083ae60ef3f