Parametric Models of NIR Transmission and Reflectivity Spectra for Dyed Fabrics

2015 ◽  
Author(s):  
D. Aiken ◽  
S. Ramsey ◽  
T. Mayo ◽  
S. G. Lambrakos ◽  
J. Peak
Keyword(s):  
Parametric Models ◽  
Reflectivity Spectra ◽  
Dyed Fabrics

Parametric models of reflectance spectra for dyed fabrics

2016 ◽  
Author(s):  
Daniel C. Aiken ◽  
Scott Ramsey ◽  
Troy Mayo ◽  
Samuel G. Lambrakos ◽  
Joseph Peak
Keyword(s):  
Parametric Models ◽  
Reflectance Spectra ◽  
Dyed Fabrics

Reflectivity spectra of Eu rich EuO near the absorption edge

1979 ◽  
Vol 40 (3) ◽  
pp. 315-319 ◽  
Author(s):  
M. Escorne ◽  
A. Mauger ◽  
C. Godart ◽  
J.C. Achard
Keyword(s):  
Absorption Edge ◽  
Reflectivity Spectra

Non-Linear Dynamics of Cardiovascular Variability Signals

1994 ◽  
Vol 33 (01) ◽  
pp. 81-84 ◽  
Author(s):  
S. Cerutti ◽  
S. Guzzetti ◽  
R. Parola ◽  
M.G. Signorini
Keyword(s):  
Dimensional Space ◽  
Severe Heart Failure ◽  
Parametric Models ◽  
Deterministic Systems ◽  
Finite Dimensional ◽  
Return Maps ◽  
Pathological Conditions ◽  
Non Linear ◽  
Space State

Abstract:Long-term regulation of beat-to-beat variability involves several different kinds of controls. A linear approach performed by parametric models enhances the short-term regulation of the autonomic nervous system. Some non-linear long-term regulation can be assessed by the chaotic deterministic approach applied to the beat-to-beat variability of the discrete RR-interval series, extracted from the ECG. For chaotic deterministic systems, trajectories of the state vector describe a strange attractor characterized by a fractal of dimension D. Signals are supposed to be generated by a deterministic and finite dimensional but non-linear dynamic system with trajectories in a multi-dimensional space-state. We estimated the fractal dimension through the Grassberger and Procaccia algorithm and Self-Similarity approaches of the 24-h heart-rate variability (HRV) signal in different physiological and pathological conditions such as severe heart failure, or after heart transplantation. State-space representations through Return Maps are also obtained. Differences between physiological and pathological cases have been assessed and generally a decrease in the system complexity is correlated to pathological conditions.

Structural-parametric model of an electroelastic actuator for nanomechanics

2020 ◽  
pp. 3-11
Author(s):  
S.M. Afonin
Keyword(s):  
Transfer Function ◽  
Piezoelectric Actuator ◽  
Transfer Functions ◽  
Piezoelectric Effect ◽  
Parametric Model ◽  
Elastic Compliance ◽  
Parametric Models ◽  
Piezo Actuator ◽  
Structural Scheme ◽  
Model Transfer

Structural-parametric models, structural schemes are constructed and the transfer functions of electro-elastic actuators for nanomechanics are determined. The transfer functions of the piezoelectric actuator with the generalized piezoelectric effect are obtained. The changes in the elastic compliance and rigidity of the piezoactuator are determined taking into account the type of control. Keywords electro-elastic actuator, piezo actuator, structural-parametric model, transfer function, parametric structural scheme

Spectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data

2021 ◽  
pp. 875529302110279
Author(s):  
Sanaz Rezaeian ◽  
Linda Al Atik ◽  
Nicolas M Kuehn ◽  
Norman Abrahamson ◽  
Yousef Bozorgnia ◽  
...  
Keyword(s):  
Ground Motions ◽  
Damping Ratio ◽  
Spectral Shape ◽  
Parametric Models ◽  
Scaling Factors ◽  
Global Models ◽  
Motion Models ◽  
Subduction Earthquakes ◽  
Crustal Earthquakes ◽  
Subduction Zone Earthquakes

This article develops global models of damping scaling factors (DSFs) for subduction zone earthquakes that are functions of the damping ratio, spectral period, earthquake magnitude, and distance. The Next Generation Attenuation for subduction earthquakes (NGA-Sub) project has developed the largest uniformly processed database of recorded ground motions to date from seven subduction regions: Alaska, Cascadia, Central America and Mexico, South America, Japan, Taiwan, and New Zealand. NGA-Sub used this database to develop new ground motion models (GMMs) at a reference 5% damping ratio. We worked with the NGA-Sub project team to develop an extended database that includes pseudo-spectral accelerations (PSA) for 11 damping ratios between 0.5% and 30%. We use this database to develop parametric models of DSF for both interface and intraslab subduction earthquakes that can be used to adjust any subduction GMM from a reference 5% damping ratio to other damping ratios. The DSF is strongly influenced by the response spectral shape and the duration of motion; therefore, in addition to the damping ratio, the median DSF model uses spectral period, magnitude, and distance as surrogate predictor variables to capture the effects of the spectral shape and the duration of motion. We also develop parametric models for the standard deviation of DSF. The models presented in this article are for the RotD50 horizontal component of PSA and are compared with the models for shallow crustal earthquakes in active tectonic regions. Some noticeable differences arise from the considerably longer duration of interface records for very large magnitude events and the enriched high-frequency content of intraslab records, compared with shallow crustal earthquakes. Regional differences are discussed by comparing the proposed global models with the data from each subduction region along with recommendations on the applicability of the models.

scholarly journals Nonparametric inference for interventional effects with multiple mediators

2021 ◽  
Vol 9 (1) ◽  
pp. 172-189
Author(s):  
David Benkeser ◽  
Jialu Ran
Keyword(s):  
Interval Estimation ◽  
Small Sample ◽  
Parametric Models ◽  
Nonparametric Bootstrap ◽  
Mediation Effects ◽  
Specific Effects ◽  
Convergence Results ◽  
Large Sample Theory ◽  
Scientific Goal ◽  
Statistical Learning Techniques

Abstract Understanding the pathways whereby an intervention has an effect on an outcome is a common scientific goal. A rich body of literature provides various decompositions of the total intervention effect into pathway-specific effects. Interventional direct and indirect effects provide one such decomposition. Existing estimators of these effects are based on parametric models with confidence interval estimation facilitated via the nonparametric bootstrap. We provide theory that allows for more flexible, possibly machine learning-based, estimation techniques to be considered. In particular, we establish weak convergence results that facilitate the construction of closed-form confidence intervals and hypothesis tests and prove multiple robustness properties of the proposed estimators. Simulations show that inference based on large-sample theory has adequate small-sample performance. Our work thus provides a means of leveraging modern statistical learning techniques in estimation of interventional mediation effects.

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