Results 11 to 20 of about 12,438,139 (288)

Data–Model Fusion Methods and Applications Toward Smart Manufacturing and Digital Engineering

Engineering
As pivotal supporting technologies for smart manufacturing and digital engineering, model-based and data-driven methods have been widely applied in many industrial fields, such as product design, process monitoring, and smart maintenance. While promising,
Fei Tao, Yilin Li, Yupeng Wei, Chenyuan Zhang, Ying Zuo   +4 more
doaj   +3 more sources

7 Tesla MRI Followed by Histological 3D Reconstructions in Whole-Brain Specimens

Frontiers in Neuroanatomy, 2020
Post mortem magnetic resonance imaging (MRI) studies on the human brain are of great interest for the validation of in vivo MRI. It facilitates a link between functional and anatomical information available from MRI in vivo and neuroanatomical knowledge ...
Anneke Alkemade, Kerrin Pine, Evgeniya Kirilina, Evgeniya Kirilina, Max C. Keuken, Martijn J. Mulder, Martijn J. Mulder, Rawien Balesar, Rawien Balesar, Josephine M. Groot, Ronald L. A. W. Bleys, Robert Trampel, Nikolaus Weiskopf, Andreas Herrler, Harald E. Möller, Pierre-Louis Bazin, Pierre-Louis Bazin, Pierre-Louis Bazin, Birte U. Forstmann   +18 more
doaj   +1 more source

A model-based method for building reconstruction [PDF]

First IEEE International Workshop on Higher-Level Knowledge in 3D Modeling and Motion Analysis, 2003. HLK 2003., 2003
Model-based reconstruction methods are applied to the detailed reconstruction of buildings from close-range images. The 3D points obtained through image matching are segmented into a coarse polyhedral model with a robust regression algorithm, then the geometry of this model is refined with predefined shape templates in order to automatically recover a ...
Konrad Schindler, Joachim Bauer
openaire   +1 more source

Automated Identification of Valid Model Networks Using Model-Based Systems Engineering

Systems, 2022
To handle increasing complexity in product development, model-based systems engineering (MBSE) approaches are well suited, in which the technical system is represented in a system model. To efficiently test requirements, domain models are integrated into
Julius Moritz Berges, Kathrin Spütz, Georg Jacobs, Julia Kowalski, Thilo Zerwas, Jörg Berroth, Christian Konrad   +6 more
doaj   +1 more source

Wireless communications empowered by reconfigurable intelligent surfaces: Model-based vs model-free channel estimation

Journal of Information and Intelligence, 2023
Reconfigurable intelligent surfaces (RISs) are lately being attractive for their great potential in future sixth generation wireless communications (6G), which is attributed to their affordable energy consumption and easy integration.
Li Wei, Chongwen Huang, George C. Alexandropoulos, Ahmet M. Elbir, Zhaohui Yang, Zhaoyang Zhang, Marco Di Renzo, Mérouane Debbah, Chau Yuen   +8 more
doaj   +1 more source

An Experimental Comparison of Model-Based Clustering Methods [PDF]

Machine Learning, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marina Meila, David Heckerman
openaire   +2 more sources

Model Order Reduction of Non-Linear Magnetostatic Problems Based on POD and DEI Methods [PDF]

, 2014
In the domain of numerical computation, Model Order Reduction approaches are more and more frequently applied in mechanics and have shown their efficiency in terms of reduction of computation time and memory storage requirements. One of these approaches,
CLENET, Stéphane, HENNERON, Thomas
core   +3 more sources

Longitudinal data clustering methods: A Systematic Review

Journal of Biostatistics and Epidemiology, 2023
 In the last few decades, in many research fields, different methods were introduced to discover groups with the same trends in longitudinal data. The clustering process is an unsupervised learning method, which classifies longitudinal data based on ...
Arefeh Dehghani tafti, Yunes Jahani, Sara Jambarsang, Abbas Bahrampour   +3 more
doaj   +1 more source

SADD: STOCHASTIC ANALYSIS OF DESTRUCTIVELY MEASURED DATA - POSSIBILITIES TO INCLUDE BIOLOGICAL VARIATIONS IN STATISTICAL ANALYSIS [PDF]

, 2010
Three techniques are presented to include the structural variation always present in measured data in statistical analysis. The methods are investigated and compared using cross sectional data, generated based on an exponential model as if gathered by ...
Jongbloed, G., Kessler, M., Tijskens, L.M.M.   +2 more
core   +2 more sources

A model‐based multithreshold method for subgroup identification [PDF]

Statistics in Medicine, 2019
Thresholding variable plays a crucial role in subgroup identification for personalized medicine. Most existing partitioning methods split the sample based on one predictor variable. In this paper, we consider setting the splitting rule from a combination of multivariate predictors, such as the latent factors, principle components, and weighted sum of ...
Jingli Wang, Jialiang Li, Yaguang Li, Weng Kee Wong   +3 more
openaire   +4 more sources