Results 81 to 90 of about 3,141,474 (179)

Automated Modal Analysis Using Stochastic Subspace Identification and Field Monitoring Data

Applied Sciences
The accurate identification of modal parameters is essential for structural health monitoring (SHM), as it provides critical insights into the presence of damage or degradation within the structure.
Shieh-Kung Huang, Zong-Zhi Lai, Hoong-Pin Lee, Yen-Yu Yang   +3 more
doaj   +1 more source

Visual Ensemble Analysis With Deep Learning Prediction for Studying the Effect of Tissue Properties on Radiofrequency Ablation

Computer Graphics Forum, EarlyView.
We present an interactive visual analysis tool to study how patient‐specific tissue properties influence radiofrequency ablation outcomes. Using a deep‐learning surrogate model, we predict ablation volumes for unseen parameter settings with accuracy superior to interpolation, supporting improved treatment planning. Abstract Radiofrequency (RF) ablation
R. Sabbagh Gol, M. Evers, K. Heimes, T. Gerrits, S. Gyawali, D. Sinden, T. Preusser, L. Linsen   +7 more
wiley   +1 more source

Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building

The Scientific World Journal, 2013
This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring.
Kyung-Won Min, Junhee Kim, Sung-Ah Park, Chan-Soo Park   +3 more
doaj   +1 more source

The combined deterministic stochastic subspace based system identification in buildings

Structural Engineering and Mechanics, 2011
The Combined Deterministic Stochastic Subspace based System Identification Technique (CDSSSIT) is a powerful input-output system identification technique which is known to be always convergent and numerically stable. The technique determines a Kalman state sequence from the projection of the output-input data.
openaire   +2 more sources

Optimized and Aligned Anisotropic Monte Carlo Sampling Patterns

Computer Graphics Forum, EarlyView.
Abstract Path tracing uses Monte Carlo integration to solve the rendering equation by evaluating the integrand at random sampling points. The convergence rate of the error can be significantly improved by using correlated instead of random sampling, especially on smooth integrands.
Mirco Werner, Johannes Hanika, Carsten Dachsbacher   +2 more
wiley   +1 more source

Unit Roots and Cointegrating Matrix Estimation using Subspace Methods [PDF]

We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series.
José Casals, Alfredo Garcia Hiernaux, Miguel Jerez   +2 more
core  

Online Intelligent Identification of Modal Parameters for Large Cable-Stayed Bridges

Shock and Vibration, 2020
Realizing online intelligent identification of bridge modal parameters requires not only the adaptive decomposition of structural response signals but also the enforcement of the automatic identification of modal parameters. Therefore, in this paper, the
Peng Wen, Inamullah Khan, He Jie, Chen Qiaofeng, Yang Shiyu   +4 more
doaj   +1 more source

GNOCHI: Generative Neural mOdel for Close Human‐Human Interactions

Computer Graphics Forum, EarlyView.
Abstract Creating realistic 3D human‐human interactions in virtual environments is challenging due to the high degrees of freedom in human body and the need for physically accurate poses that do not collide with each other. Traditional methods for humanhuman interaction are based on motion tracking or 3D body reconstruction, but lack generative ...
Gonzalo Gómez‐Nogales, Marc Comino‐Trinidad, Andrés Casado‐Elvira, Dan Casas   +3 more
wiley   +1 more source

Modal Parameter Identification of Electric Spindles Based on Covariance-Driven Stochastic Subspace

Machines
Electric spindles are a critical component of numerically controlled machine tools that directly affect machining precision and efficiency. The accurate identification of the modal parameters of an electric spindle is essential for optimizing design ...
Wenhong Zhou, Liuzhou Zhong, Weimin Kang, Yuetong Xu, Congcong Luan, Jianzhong Fu   +5 more
doaj   +1 more source

Goodness‐of‐Fit Tests for Positive Quadrant Dependence

International Statistical Review, EarlyView.
Summary When two random variables are positive quadrant dependent (PQD), they are more likely to assume small (or large) values simultaneously compared with when the random variables are independent. This dependence structure is of interest in many areas, including finance, actuarial science and engineering.
Chuan‐Fa Tang, Joshua M. Tebbs
wiley   +1 more source