Data base analyzer and parameter estimator (DBAPE) interactive computer program user's manual /

Mode of access: Internet.

Development and testing of INTRAS, a microscopic freeway simulation model. Volume 1: program design, parameter calibration and freeway dynamics component development. Final report.

Federal Highway Administration, Office of Research and Development, Washington, D.C.

DPMAS utilization vehicle parameter identification. Technical report. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Long Term Pavement Performance computed parameter : frost penetration /

"HRDI-13/11-08(1M)E"--P. 4 of cover.

Machine parameter deduction by program analysis /

Thesis (M.S.)--University of Illinois.

An atmospheric diffusion nomogram with extended parameter ranges /

"February 15, 1956."

Stresses in reinforced nozzle-cylinder attachments under external moment loadings analyzed by the finite-element method : a parameter study /

"ORNL/NUREG-52."

Synthesis of flight control systems subject to vehicle parameter variations.

Mode of access: Internet.

A Novel Framework for Real-time Traffic Flow Parameter Estimation from Aerial Videos

Thesis (Master's)--University of Washington, 2016-06

Robustness of quantum gates in the presence of noise

We define several quantitative measures of the robustness of a quantum gate against noise. Exact analytic expressions for the robustness against depolarizing noise are obtained for all bipartite unitary quantum gates, and it is found that the controlled-NOT gate is the most robust two-qubit quantum gate, in the sense that it is the quantum gate which can tolerate the most depolarizing noise and still generate entanglement. Our results enable us to place several analytic upper bounds on the value of the threshold for quantum computation, with the best bound in the most pessimistic error model being p(th)less than or equal to0.5.

Functionality, Robustness and Control of Nonlinear Network Dynamics: Modeling and Understanding the C. elegans Connectome

Thesis (Ph.D.)--University of Washington, 2016-06

Robust multivariable control of complex biological processes

This paper addresses advanced control of a biological nutrient removal (BNR) activated sludge process. Based on a previously validated distributed parameter model of the BNR activated sludge process, we present robust multivariable controller designs for the process, involving loop shaping of plant model, robust stability and performance analyses. Results from three design case studies showed that a multivariable controller with stability margins of 0.163, 0.492 and 1.062 measured by the normalised coprime factor, multiplicative and additive uncertainties respectively give the best results for meeting performance robustness specifications. The controller robustly stabilises effluent nutrients in the presence of uncertainties with the behaviour of phosphorus accumulating organisms as well as to effectively attenuate major disturbances introduced as step changes. This study also shows that, performance of the multivariable robust controller is superior to multi-loops SISO PI controllers for regulating the BNR activated sludge process in terms of robust stability and performance and controlling the process using inlet feed flowrate is infeasible. (C) 2003 Elsevier Ltd. All rights reserved.

Quantitative justification for target concentration intervention - parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

The HIPASS catalogue - II. Completeness reliability and parameter accuracy

The H I Parkes All Sky Survey (HIPASS) is a blind extragalactic H I 21-cm emission-line survey covering the whole southern sky from declination -90degrees to +25degrees. The HIPASS catalogue (HICAT), containing 4315 H I-selected galaxies from the region south of declination +2degrees, is presented in Meyer et al. (Paper I). This paper describes in detail the completeness and reliability of HICAT, which are calculated from the recovery rate of synthetic sources and follow-up observations, respectively. HICAT is found to be 99 per cent complete at a peak flux of 84 mJy and an integrated flux of 9.4 Jy km. s(-1). The overall reliability is 95 per cent, but rises to 99 per cent for sources with peak fluxes >58 mJy or integrated flux >8.2 Jy km s(-1). Expressions are derived for the uncertainties on the most important HICAT parameters: peak flux, integrated flux, velocity width and recessional velocity. The errors on HICAT parameters are dominated by the noise in the HIPASS data, rather than by the parametrization procedure.