scholarly journals Estimating posterior quantity of interest expectations in a multilevel scalable framework

2020 ◽  
Author(s):  
Hillary R. Fairbanks ◽  
Sarah Osborn ◽  
Panayot S. Vassilevski
Keyword(s):  
Quantity Of Interest

The Field in a Narrow Circumferential Slot in a Coaxial Waveguide

1973 ◽  
Vol 51 (9) ◽  
pp. 946-955 ◽  
Author(s):  
R. A. Hurd
Keyword(s):  
Electric Field ◽  
Outer Wall ◽  
Coaxial Waveguide ◽  
Input Admittance ◽  
Quantity Of Interest ◽  
Cylindrical Antenna

The first three terms in the expansion of the electric field in a narrow circumferential gap in the outer wall of a coaxial waveguide have been determined. Also found is the input admittance of an infinite, coaxially fed cylindrical antenna, a quantity of interest in the theory of sleeve antennas.

scholarly journals The Price and Quantity of Interest Rate Risk

2020 ◽  
Author(s):  
Jennifer N. Carpenter ◽  
Fangzhou Lu ◽  
Robert F. Whitelaw
Keyword(s):  
Interest Rate ◽  
Interest Rate Risk ◽  
Quantity Of Interest ◽  
Rate Risk

Avalanches of electrons in a gas

1986 ◽  
Vol 23 (4) ◽  
pp. 867-879 ◽  
Author(s):  
F. W. Steutel
Keyword(s):  
State Process ◽  
Quantity Of Interest ◽  
Extra Electron ◽  
Moving Particle

The motion of electrons through a gas of particles is modelled as a two-state process: an electron is alternatingly moving and being held captive by a non-moving particle, during exponentially distributed periods.The model contains a parameter p, the probability that collision of an electron with a gas particle does not lead to its capture but produces an extra electron.The quantity of interest is the current C(t) produced by the moving electrons, as a function of time.

Feature Variation and its Impact on Structural Acoustic Response Predictions

2003 ◽  
Vol 125 (1) ◽  
pp. 31-38
Author(s):  
Kenneth A. Cunefare
Keyword(s):  
Acoustic Power ◽  
Reference State ◽  
Acoustic Response ◽  
Model Fidelity ◽  
Quantity Of Interest ◽  
Resonance Frequencies ◽  
Quadratic Response ◽  
Constant Bandwidth ◽  
Bandwidth Analysis ◽  
The Impact

This paper presents a screening technique to assess the impact on model fidelity introduced by variations in the properties or positions of features in harmonically forced fluid-loaded structural acoustic models. The perspective taken is one of knowledge of a reference state, with a desire to determine the impact on the total radiated acoustic power due to perturbations in the reference state. Such perturbations change the predicted resonance frequencies of a structure under consideration, and hence, change the predicted response amplitudes. The method uses a single degree of freedom response model in the local region of each fluid-loaded resonance, coupled with eigenvalue sensitivities or variations, to estimate the perturbation impact. The perturbation is scaled by the degree to which each given mode participates in the response quantity of interest. The SDOF model yields results that indicate that proportional bandwidth analysis will be less sensitive to perturbation than constant bandwidth analysis. This is demonstrated through comparison of a constant bandwidth analysis and a 1/3 octave analysis applied to the same system. Elements of the analysis method are not necessarily restricted to model perturbations nor acoustic power, rather they may be used to assess the perturbation of any quadratic response quantity of interest due to changes in resonance frequency.

Construction of Bayesian Prediction Intervals for Smart Systems

2013 ◽  
Author(s):  
Mami T. Wentworth ◽  
Ralph C. Smith
Keyword(s):  
Measurement Errors ◽  
Smart Material ◽  
Bayesian Prediction ◽  
Prediction Intervals ◽  
Smart Systems ◽  
Mcmc Algorithms ◽  
Quantity Of Interest ◽  
Input Parameters ◽  
Quantities Of Interest

In this paper, we employ adaptive Metropolis algorithms to construct densities for parameters and quantities of interest for models arising in the analysis of smart material structures. In the first step of the construction, MCMC algorithms are used to quantify the uncertainty in parameters due to measurement errors. We then combine uncertainties from the input parameters and measurement errors, and construct prediction intervals for the quantity of interest by propagating uncertainties through the models.

scholarly journals Indices of Informational Association and Analysis of Complex Socio-Economic Systems

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 367 ◽  
Author(s):  
Paulo dos Santos ◽  
Noé Wiener
Keyword(s):  
Social Identity ◽  
Economic Effects ◽  
Economic Systems ◽  
Social Inquiry ◽  
Quantity Of Interest ◽  
Large Numbers ◽  
The U.S

This paper is motivated by a distinctive appreciation of the difficulties posed by quantitative observational inquiry into complex social and economic systems. It develops ordinary and piecewise indices of joint and incremental informational association that enable robust approaches to a common problem in social inquiry: grappling with associations between a quantity of interest and two distinct sets of co-variates taking values over large numbers of individuals. The distinct analytical usefulness of these indices is illustrated with their application to inquiry into the systemic economic effects of patterns of discrimination by social identity in the U.S. economy.

scholarly journals Exploration vs. Data Refinement via Multiple Mobile Sensors

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 568 ◽  
Author(s):  
Mohammad Shekaramiz ◽  
Todd K. Moon ◽  
Jacob H. Gunther
Keyword(s):  
Decision Making ◽  
Regression Model ◽  
Physical Quantity ◽  
General Framework ◽  
Gaussian Process Regression ◽  
Mobile Sensors ◽  
Data Refinement ◽  
Epistemic Utility ◽  
Quantity Of Interest ◽  
Unknown Region

We examine the deployment of multiple mobile sensors to explore an unknown region to map regions containing concentration of a physical quantity such as heat, electron density, and so on. The exploration trades off between two desiderata: to continue taking data in a region known to contain the quantity of interest with the intent of refining the measurements vs. taking data in unobserved areas to attempt to discover new regions where the quantity may exist. Making reasonable and practical decisions to simultaneously fulfill both goals of exploration and data refinement seem to be hard and contradictory. For this purpose, we propose a general framework that makes value-laden decisions for the trajectory of mobile sensors. The framework employs a Gaussian process regression model to predict the distribution of the physical quantity of interest at unseen locations. Then, the decision-making on the trajectories of sensors is performed using an epistemic utility controller. An example is provided to illustrate the merit and applicability of the proposed framework.

Evaluation of p-FEM Approximations for Mid-Frequency Elasto-Acoustics

2003 ◽  
Vol 11 (02) ◽  
pp. 195-225 ◽  
Author(s):  
Saikat Dey
Keyword(s):  
Numerical Simulation ◽  
Numerical Experiments ◽  
Three Dimensional ◽  
High Order ◽  
Elastic Displacement ◽  
Frequency Range ◽  
Infinite Element ◽  
Pressure Fields ◽  
Quantity Of Interest

p-refinement strategies for numerical simulation of three-dimensional elasto-acoustic problems in the mid-frequency range are evaluated using high-order finite/infinite element-based approximations. Numerical experiments are used to study the convergence of an appropriate quantity-of-interest (QOI) as a function of polynomial degrees for the elastic-displacement and pressure fields.

A Semantics-Aware Communication Scheme to Estimate the Empirical Measure of A Quantity of Interest Via Multiple Access Fading Channels

2021 ◽  
Author(s):  
Johannes Dommel ◽  
Dennis Wieruch ◽  
Zoran Utkovski ◽  
Slawomir Stanczak
Keyword(s):  
Fading Channels ◽  
Multiple Access ◽  
Empirical Measure ◽  
Quantity Of Interest ◽  
Communication Scheme

scholarly journals Positive Dependence of Signals

2010 ◽  
Vol 47 (3) ◽  
pp. 893-897 ◽  
Author(s):  
Michel Denuit
Keyword(s):  
Conditional Expectation ◽  
Conditional Variance ◽  
Sufficient Condition ◽  
Convex Order ◽  
Positive Dependence ◽  
Increasing Convex Order ◽  
Quantity Of Interest ◽  
Conditional Expectations ◽  
Special Case

In this paper we further investigate the problem considered by Mizuno (2006) in the special case of identically distributed signals. Specifically, we first propose an alternative sufficient condition of crossing type for the convex order to hold between the conditional expectations given signal. Then, we prove that the bivariate (2,1)-increasing convex order ensures that the conditional expectations are ordered in the convex sense. Finally, the L2 distance between the quantity of interest and its conditional expectation given signal (or expected conditional variance) is shown to decrease when the strength of the dependence increases (as measured by the (2,1)-increasing convex order).

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