Calibration of pneumotachographs using a calibrated syringe

2003 ◽  
Vol 95 (2) ◽  
pp. 571-576 ◽  
Author(s):  
Yongquan Tang ◽  
Martin J. Turner ◽  
Johnny S. Yem ◽  
A. Barry Baker
Keyword(s):  
Calibration Method ◽  
Linear Range ◽  
Data Sets ◽  
Constant Flow ◽  
Calibration Constant ◽  
Third Order ◽  
Polynomial Coefficients ◽  
Calibration Curves ◽  
Order Polynomial ◽  
Better Than

Pneumotachograph require frequent calibration. Constant-flow methods allow polynomial calibration curves to be derived but are time consuming. The iterative syringe stroke technique is moderately efficient but results in discontinuous conductance arrays. This study investigated the derivation of first-, second-, and third-order polynomial calibration curves from 6 to 50 strokes of a calibration syringe. We used multiple linear regression to derive first-, second-, and third-order polynomial coefficients from two sets of 6–50 syringe strokes. In part A, peak flows did not exceed the specified linear range of the pneumotachograph, whereas flows in part B peaked at 160% of the maximum linear range. Conductance arrays were derived from the same data sets by using a published algorithm. Volume errors of the calibration strokes and of separate sets of 70 validation strokes ( part A) and 140 validation strokes ( part B) were calculated by using the polynomials and conductance arrays. Second- and third-order polynomials derived from 10 calibration strokes achieved volume variability equal to or better than conductance arrays derived from 50 strokes. We found that evaluation of conductance arrays using the calibration syringe strokes yields falsely low volume variances. We conclude that accurate polynomial curves can be derived from as few as 10 syringe strokes, and the new polynomial calibration method is substantially more time efficient than previously published conductance methods.

Computerized Evaluations of the Relative Abilities of Seven Time-Temperature Parameters to Correlate and Extrapolate Nickel Alloy Stress-Rupture Data

1972 ◽  
Vol 94 (1) ◽  
pp. 7-12 ◽  
Author(s):  
P. K. Raut ◽  
W. R. Clough
Keyword(s):  
Stress Rupture ◽  
Computer Programs ◽  
Graphical Methods ◽  
Data Sets ◽  
Test Results ◽  
Master Curves ◽  
Third Order ◽  
Rupture Data ◽  
Order Polynomial ◽  
Nickel Base

A total of 31 stress-rupture data sets for 28 different nickel-base alloys, including 1153 individual test results, have been treated by graphical methods and computer programs to allow determinations of the relative abilities of Larson-Miller, Manson-Haferd, Sherby-Dorn, Goldhoff-Sherby, Manson-Succop, Conrad and Korchynsky parameters to correlate and extrapolate data. For the correlation of all data the Goldhoff-Sherby and Manson-Haferd methods are attractive, while for extrapolation to longer times some superiority of the Manson-Haferd and Manson-Succop parameters is demonstrated. Overall use of a third order polynomial approximation to Manson-Haferd master curves is recommended, as is the avoidance of external extrapolation. Results are primarily based on modified and original computer programs and standard statistical treatments of data.

scholarly journals The instrument constant of sky radiometer (POM-02), Part I: Calibration constant

2018 ◽  
Author(s):  
Akihiro Uchiyama ◽  
Tsuneo Matsunaga ◽  
Akihiro Yamazaki
Keyword(s):  
Seasonal Variation ◽  
Near Infrared ◽  
Calibration Method ◽  
Gas Absorption ◽  
Sensor Output ◽  
Correction Factors ◽  
Maximum Difference ◽  
Calibration Constant ◽  
Rms Error ◽  
Better Than

Abstract. Ground-based networks have been developed to determine the spatiotemporal distribution of aerosols using radiometers. In this study, the accuracy of the calibration constant (V0) for the sky radiometer (POM-02) which is used by SKYNET was investigated. The temperature dependence of the sensor output was also investigated, and the dependence in the 340, 380, and 2200 nm channels was found to be larger than for other channels, and varied with the instrument. In the summer, the sensor output had to be corrected by a factor of 1.5 to 2 % in the 340 and 380 nm channels and by 4 % in the 2200 nm channel in the measurements at Tsukuba. In the other channels, the correction factors were less than 0.5 %. The accuracy of V0 from the normal Langley method is between 0.2 and 1.3 %, except in the 940 nm channel. The effect of gas absorption was less than 1 % in the 1225, 1627, and 2200 nm channels. The degradation of V0 for shorter wavelengths was larger than that for longer wavelengths. The accuracy of V0 estimated from the side-by-side measurements was 0.1 to 0.5 %. The V0 determined by the improved Langley (IML) method had a seasonal variation of 1 to 3 %. The RMS error from the IML method was about 0.6 to 2.5 %, and in some cases, the maximum difference reached 5 %. The trend in V0 after removing the seasonal variation was almost the same as for the normal Langley method. The calibration method for water vapor in the 940 nm channel was developed using an empirical formula for transmittance. The accuracy of V0 was better than 1 % on relatively stable and fine days. A calibration method for the near-infrared channels, 1225, 1627, and 2200 nm, was also developed. The logarithm of the ratio of the sensor output can be written as a linear function of the airmass, by assuming that the ratio of the optical thicknesses between the two channels is constant. The accuracy of V0 was better than 1 % on days with good conditions.

scholarly journals A Tighter Bound for Graphical Models

2001 ◽  
Vol 13 (9) ◽  
pp. 2149-2171 ◽  
Author(s):  
M. A. R. Leisink ◽  
H. J. Kappen
Keyword(s):  
Graphical Models ◽  
Mean Field ◽  
Third Order ◽  
First Order ◽  
Direct Extension ◽  
Odd Order ◽  
Order Polynomial ◽  
The Mean ◽  
Mean Field Bound ◽  
Better Than

We present a method to bound the partition function of a Boltzmann machine neural network with any odd-order polynomial. This is a direct extension of the mean-field bound, which is first order. We show that the third-order bound is strictly better than mean field. Additionally, we derive a third-order bound for the likelihood of sigmoid belief networks. Numerical experiments indicate that an error reduction of a factor of two is easily reached in the region where expansion-based approximations are useful.

Multiple data parameter identification for nonlinear conceptual models

1997 ◽  
Vol 36 (5) ◽  
pp. 61-68 ◽  
Author(s):  
Hermann Eberl ◽  
Amar Khelil ◽  
Peter Wilderer
Keyword(s):  
Optimization Problem ◽  
Conceptual Models ◽  
Reference Data ◽  
Transport Model ◽  
Calibration Method ◽  
Data Sets ◽  
Multiple Data ◽  
Marquardt Algorithm ◽  
Multicriteria Optimization Problem ◽  
Higher Order Differential Equations

A numerical method for the identification of parameters of nonlinear higher order differential equations is presented, which is based on the Levenberg-Marquardt algorithm. The estimation of the parameters can be performed by using several reference data sets simultaneously. This leads to a multicriteria optimization problem, which will be treated by using the Pareto optimality concept. In this paper, the emphasis is put on the presentation of the calibration method. As an example identification of the parameters of a nonlinear hydrological transport model for urban runoff is included, but the method can be applied to other problems as well.

scholarly journals The Rabi problem with elliptical polarization

2020 ◽  
Vol 75 (11) ◽  
pp. 937-962
Author(s):  
Heinz-Jürgen Schmidt
Keyword(s):  
Floquet Theory ◽  
Equation Of Motion ◽  
Quantum Spin ◽  
Heun Equation ◽  
Elliptical Polarization ◽  
Third Order ◽  
Polynomial Coefficients ◽  
Resonance Frequencies ◽  
Classical Quantum ◽  
Elliptically Polarized

AbstractWe consider the solution of the equation of motion of a classical/quantum spin subject to a monochromatical, elliptically polarized external field. The classical Rabi problem can be reduced to third-order differential equations with polynomial coefficients and hence solved in terms of power series in close analogy to the confluent Heun equation occurring for linear polarization. Application of Floquet theory yields physically interesting quantities like the quasienergy as a function of the problem’s parameters and expressions for the Bloch–Siegert shift of resonance frequencies. Various limit cases are thoroughly investigated.

scholarly journals A Novel LSTM Model with Interaction Dual Attention for Radar Echo Extrapolation

2021 ◽  
Vol 13 (2) ◽  
pp. 164
Author(s):  
Chuyao Luo ◽  
Xutao Li ◽  
Yongliang Wen ◽  
Yunming Ye ◽  
Xiaofeng Zhang
Keyword(s):  
Short Term Memory ◽  
Weather Forecast ◽  
Vital Role ◽  
Data Sets ◽  
Short Term ◽  
Learning Techniques ◽  
Radar Echo ◽  
Hidden States ◽  
Better Than

The task of precipitation nowcasting is significant in the operational weather forecast. The radar echo map extrapolation plays a vital role in this task. Recently, deep learning techniques such as Convolutional Recurrent Neural Network (ConvRNN) models have been designed to solve the task. These models, albeit performing much better than conventional optical flow based approaches, suffer from a common problem of underestimating the high echo value parts. The drawback is fatal to precipitation nowcasting, as the parts often lead to heavy rains that may cause natural disasters. In this paper, we propose a novel interaction dual attention long short-term memory (IDA-LSTM) model to address the drawback. In the method, an interaction framework is developed for the ConvRNN unit to fully exploit the short-term context information by constructing a serial of coupled convolutions on the input and hidden states. Moreover, a dual attention mechanism on channels and positions is developed to recall the forgotten information in the long term. Comprehensive experiments have been conducted on CIKM AnalytiCup 2017 data sets, and the results show the effectiveness of the IDA-LSTM in addressing the underestimation drawback. The extrapolation performance of IDA-LSTM is superior to that of the state-of-the-art methods.

Polynomial Moving Fitting Method for Edge Identification

2011 ◽  
Vol 308-310 ◽  
pp. 2560-2564 ◽  
Author(s):  
Xiang Rong Yuan
Keyword(s):  
Edge Detection ◽  
Curve Fitting ◽  
Polynomial Function ◽  
High Order ◽  
Polynomial Fitting ◽  
Fitting Method ◽  
Order Polynomial ◽  
Better Than ◽  
Low Order

A moving fitting method for edge detection is proposed in this work. Polynomial function is used for the curve fitting of the column of pixels near the edge. Proposed method is compared with polynomial fitting method without sub-segment. The comparison shows that even with low order polynomial, the effects of moving fitting are significantly better than that with high order polynomial fitting without sub-segment.

SEC/MALDI-TOF Mass spectrometry study of hydroxy-, carboxy- and methyl ester-terminated aliphatic polyesters

e-Polymers ◽  
2005 ◽  
Vol 5 (1) ◽  
Author(s):  
Slim Salhi ◽  
Martine Tessier ◽  
Jean-Claude Blais ◽  
Rachid El Gharbi ◽  
Alain Fradet
Keyword(s):  
Dimethyl Ester ◽  
Calibration Method ◽  
Size Exclusion ◽  
Aliphatic Polyesters ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Calibration Curves ◽  
End Groups ◽  
Poly Ethylene ◽  
Tof Ms

AbstractPoly(ethylene adipate) (PEA) and poly(ethylene dodecanedioate) (PED) with dicarboxy-, dihydroxy-, dimethyl ester- and hydroxy-carboxy end-groups were synthesized and characterized by 13C NMR and MALDI-TOF MS. Size-exclusion chromatography (SEC) fractions of these polyesters were analyzed by MALDI-TOF MS and used as standards to obtain SEC calibration curves leading to the absolute molar masses of the unfractionated polyesters. PEA and PED calibration curves were different from each other, but the same calibration curve was obtained for each type of polyester, irrespective of the nature of end-groups, showing the predominant role of the nature of repeating units on the hydrodynamic volume of oligoesters. The study also shows that the conventional SEC calibration method using polystyrene standards leads to a significant overestimation of polyester average molar masses.

Thermal Error Modeling of Precision Positioning Stage

2013 ◽  
Vol 694-697 ◽  
pp. 767-770
Author(s):  
Jing Shu Wang ◽  
Ming Chi Feng
Keyword(s):  
Thermal Deformation ◽  
Thermal Error ◽  
Error Modeling ◽  
Precision Positioning ◽  
Third Order ◽  
Element Analysis ◽  
The Finite Element Analysis ◽  
Positioning Stage ◽  
Order Polynomial ◽  
The Relationship

As the thermal deformation significantly impacts the accuracy of precision positioning stage, it is necessary to realize the thermal error. The thermal deformation of the positioning stage is simulated by the finite element analysis. The relationship between the temperature variation and thermal error is fitted third-order polynomial function whose parameters are determined by genetic algorithm neural network (GANN). The operators of the GANN are optimized through a parametric study. The results show that the model can describe the relationship between the temperature and thermal deformation well.

scholarly journals Simultaneous Robot–World and Hand–Eye Calibration without a Calibration Object

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3949 ◽  
Author(s):  
Wei Li ◽  
Mingli Dong ◽  
Naiguang Lu ◽  
Xiaoping Lou ◽  
Peng Sun
Keyword(s):  
Three Dimensional ◽  
Real Data ◽  
Medical Robotics ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Data Sets ◽  
Rigid Transformation ◽  
Validation Experiment ◽  
Dimensional Reconstruction ◽  
Sparse Bundle Adjustment

An extended robot–world and hand–eye calibration method is proposed in this paper to evaluate the transformation relationship between the camera and robot device. This approach could be performed for mobile or medical robotics applications, where precise, expensive, or unsterile calibration objects, or enough movement space, cannot be made available at the work site. Firstly, a mathematical model is established to formulate the robot-gripper-to-camera rigid transformation and robot-base-to-world rigid transformation using the Kronecker product. Subsequently, a sparse bundle adjustment is introduced for the optimization of robot–world and hand–eye calibration, as well as reconstruction results. Finally, a validation experiment including two kinds of real data sets is designed to demonstrate the effectiveness and accuracy of the proposed approach. The translation relative error of rigid transformation is less than 8/10,000 by a Denso robot in a movement range of 1.3 m × 1.3 m × 1.2 m. The distance measurement mean error after three-dimensional reconstruction is 0.13 mm.

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