Constructing a Virtual Large Reference Plate with High-precision for Calibrating Cameras with Large FOV

It is well known that the accuracy of camera calibration is constrained by the size of the reference plate,it is difficult to fabricate large reference plates with high precision.Therefore,it is non-trivial to calibrate a camera with large field of view(FOV).In this paper,a method is proposed to construct a virtual large reference plate with high precision.Firstly,a high precision datum plane is constructed with a laser interferometer and one-dimensional air guideway,and then the reference plate is positioned at different locations and orientations in the FOV of the camera.The feature points of reference plate are projected to the datum plane to obtain a virtual large reference plate with high-precision.The camera is moved to several positions to get different virtual reference plates,and the camera is calibrated with the virtual reference plates.The experimental results show that the mean re-projection error of the camera calibrated with the proposed method is 0.062 pixels.The length of a scale bar with standard length of 959.778mm was measured with a vision system composed of two calibrated cameras,and the length measurement error is 0.389mm.

A Calibrating Device for Rogowski Coil Development

A calibrating device for the Rogowski coil is developed, which can be used to calibrate the Rogowski coil having a partial response time within tens of nanoseconds. Its key component is a step current generator, which can generate the output with a rise time of less than 2 ns and a duration of larger than 300 ns. The step current generator is composed by a pulse forming line （PFL） and a pulse transmission line （PTL）. A TEM （transverse electromagnetic mode） coaxial measurement unit is used as PTL, and the coil to be calibrated and the referenced standard Rogowski coil can be fixed in the unit. The effect of the dimensions of the TEM unit is discussed theoretically as well as experimentally.

Empirical mode decomposition using variable filtering with time scale calibrating

A novel and efficient method for decomposing a signal into a set of intrinsic mode functions （IMFs） and a trend is proposed. Unlike the original empirical mode decomposition （EMD）, which uses spline fits to extract variations from the signal by separating the local mean from the fluctuations in the decomposing process, this new method being proposed takes advantage of the theory of variable finite impulse response （FIR） filtering where filter coefficients and breakpoint frequencies can be adjusted to track any peak-to-peak time scale changes. The IMFs are results of a multiple variable frequency response FIR filtering when signals pass through the filters. Numerical examples validate that in contrast with the original EMD, the proposed method can fine-tune the frequency resolution and suppress the aliasing effectively.

A method for calibrating the confocal volume of a confocal three-dimensional micro-x-ray fluorescence setup

The measurement of the confocal volume of a confocal three-dimensional micro-x-ray fluorescence(3D-XRF)setup is a key step in the field of confocal 3D-XRF analysis.With the development of x-ray facilities and optical devices,3D-XRF analysis with a micro confocal volume will create a great potential for 2D and 3D microstructural analysis and accurate quantitative analysis.However,the classic measurement method of scanning metal foils of a certain thickness leads to inaccuracy.A method for calibrating the confocal volume is proposed in this paper.The new method is based on the basic content of the textbook,and the theoretical results and the feasibility are given in detail for the 3D-XRF mono-chromatic x-ray condition and the poly-chromatic x-ray condition.We obtain a set of experimental confirmation using the poly-chromatic x-ray tube in the laboratory.It is proved that the sensitivity factor of the 3D-XRF can be directly and accurately obtained in a real calibration process.

Experimental verification of bridge seismic damage states quantified by calibrating analytical models with empirical field data

Bridges are one of the most vulnerable components of a highway transportation network system subjected to earthquake ground motions. Prediction of resilience and sustainability of bridge performance in a probabilistic manner provides valuable information for pre-event system upgrading and post-event functional recovery of the network. The current study integrates bridge seismic damageability information obtained through empirical, analytical and experimental procedures and quantifies threshold limits of bridge damage states consistent with the physical damage description given in HAZUS. Experimental data from a large-scale shaking table test are utilized for this purpose. This experiment was conducted at the University of Nevada, Reno, where a research team from the University of California, Irvine, participated. Observed experimental damage data are processed to identify and quantify bridge damage states in terms of rotational ductility at bridge column ends. In parallel, a mechanistic model for fragility curves is developed in such a way that the model can be calibrated against empirical fragility curves that have been constructed from damage data obtained during the 1994 Northridge earthquake. This calibration quantifies threshold values of bridge damage states and makes the analytical study consistent with damage data observed in past earthquakes. The mechanistic model is transportable and applicable to most types and sizes of bridges. Finally, calibrated damage state definitions are compared with that obtained using experimental findings. Comparison shows excellent consistency among results from analytical, empirical and experimental observations.

Calibrating the linearity between grayscale and element content for X-ray KES imaging of alloys

Doped elements in alloys significantly impact their performance.Conventional methods usually sputter the surface material of the sample,or their performance is limited to the surface of alloys owing to their poor penetration ability.The X-ray K-edge subtraction(KES)method exhibits great potential for the nondestructive in situ detection of element contents in alloys.However,the signal of doped elements usually deteriorates because of the strong absorption of the principal component and scattering of crystal grains.This in turn prevents the extensive application of X-ray KES imaging to alloys.In this study,methods were developed to calibrate the linearity between the grayscale of the KES image and element content.The methods were aimed at the sensitive analysis of elements in alloys.Furthermore,experiments with phantoms and alloys demonstrated that,after elaborate calibration,X-ray KES imaging is capable of nondestructive and sensitive analysis of doped elements in alloys.

Calibrating Remotely Sensed Ocean Chlorophyll Data: An Application of the Blending Technique in Three Dimensions (3D)

In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.

In situ calibrating optical tweezers with sinusoidal-wave drag force method

We introduce a corrected sinusoidal-wave drag force method （SDFM） into optical tweezers to calibrate the trapping stiffness of the optical trap and conversion factor （CF） of photodetectors. First, the theoretical analysis and experimental result demonstrate that the correction of SDFM is necessary, especially the error of no correction is up to 11.25% for a bead of 5μm in diameter. Second, the simulation results demonstrate that the SDFM has a better performance in the calibration of optical tweezers than the triangular-wave drag force method （TDFM） and power spectrum density method （PSDM） at the same signal-to-noise ratio or trapping stiffness. Third, in experiments, the experimental standard deviations of calibration of trapping stiffness and CF with the SDFM are about less than 50% of TDFM and PSDM especially at low laser power. Finally, the experiments of stretching DNA verify that the in situ calibration with the SDFM improves the measurement stability and accuracy.

Dynamic Calibrating Technique for Super－Precision Gyrorotor Measuring Instrument

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SIGNAL SUBSPACE METHOD FOR CALIBRATING SENSOR LOCATION OF DIRECTION FINDER

Sensor location uncertainty of array degrades severely the performance of eigenstruc-ture based direction finding system.A new calibration method of sensor location is presentedwith three far field sources whose directions are not known accurately.A signal subspace basediteration algorithm for sensor location calibration is developed and its convergence to the globaloptimal point has been shown.The guide line for selecting directions of calibrating sources isgiven.Simulation results illustrate that the new method is successful and practicable.

Calibrating volume measurements made using the dual-field conductance catheter

The conductance catheter technique allows real- time measurements of ventricular volume based on changes in the electrical conductance of blood within the ventricular cavity. Conductance volume measurements are corrected with a calibration coefficient, α, in order to improve accuracy. However, conductance volume measurements are also affected by parallel conductance, which may confound cali-bration coefficient estimation. This study was un-dertaken to examine the variation in α using a physical model of the left ventricle without parallel conductance. Calibration coefficients were calculated as the conductance-volume quotient (αV(t)) or the stroke conductance-stroke volume quotient (αSV). Both calibration coefficients varied as a non-linear function of the ventricular volume. Conductance volume measurements calibrated with αV(t) estimated ventricular volume to within 2.0 ±6.9%. By contrast, calibration with αSV substantially over-estimated the ventricular volume in a volume-dependent manner, increasing from 26 ±20% at 100ml to 106 ±36% at 500ml. The accuracy of conductance volume measurements is affected by the choice of calibration coefficient. Using a fixed or constant calibration coeffi-cient will result in volume measurement errors. The conductance-stroke volume quotient is associated with particularly significant and volume-dependent measurement errors. For this reason, conductance volume measurements should ideally be calibrated with an alternative measurement of ventricular vol-ume.

Formulation and solution for calibrating boundedly rational activity-travel assignment:An exploratory study

Parameter calibration of the traffic assignment models is vital to travel demand analysis and management.As an extension of the conventional traffic assignment,boundedly rational activity-travel assignment(BR-ATA)combines activity-based modeling and traffic assignment endogenously and can capture the interdependencies between high dimensional choice facets along the activity-travel patterns.The inclusion of multiple episodes of activity participation and bounded rationality behavior enlarges the choice space and poses a challenge for calibrating the BR-ATA models.In virtue of the multi-state supernetwork,this exploratory study formulates the BRATA calibration as an optimization problem and analyzes the influence of the two additional components on the calibration problem.Considering the temporal dimension,we also propose a dynamic formulation of the BR-ATA calibration problem.The simultaneous perturbation stochastic approximation algorithm is adopted to solve the proposed calibration problems.Numerical examples are presented to calibrate the activity-based travel demand for illustrations.The results demonstrate the feasibility of the solution method and show that the parameter characterizing the bounded rationality behavior has a significant effect on the convergence of the calibration solutions.

An innovative method for calibrating local cooling rate in electroslag remelting of M42 high-speed steel

The determination of the local cooling rate has a great significance in optimizing the parameters of electroslag remelting(ESR)and improving the quality of the ingots.An innovative method was proposed for calibrating the local cooling rate of M42 high-speed steel(HSS)in the ESR process.After resolidification at different cooling rates under high-temperature laser confocal microscopy,the carbide network spacing of the specimen was observed using a scanning electron microscope.A functional relationship between the cooling rate and average carbide network spacing was established.The average local cooling rate of the solidification process of the M42 HSS ingot was calibrated.The results show that the higher the cool-ing rate,the smaller the network spacing of the carbides.For the steel ingot with a diameter of 360 mm,the average local cooling rate was 0.562℃/s at the surface,0.057℃/s at the position of 0.25D(where D is the diameter of the ingot),and 0.046℃/s at the center of the ingot.

从中国首台紫外-可见光高光谱卫星仪器反演得到的高空间分辨率臭氧廓线

Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport,as well as when analyzing the physical and chemical properties of the atmosphere.One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations.The Environmental Trace Gases Monitoring Instrument(EMI)deployed on the Gaofen-5 satellite is the first Chinese ultraviolet-visible hyperspectral spectrometer.However,retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio.The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87%of the EMI pixels.Therefore,we developed an algorithm specific to the characteristics of the EMI.The fitting residuals are smaller than 0.3%in most regions.The retrieved ozone profiles were in good agreement with ozonesonde data,with maximum mean biases of 20%at five latitude bands.By applying EMI averaging kernels to the ozonesonde profiles,the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data,The lower layers(0-7.5 km)of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center(CNEMC).However,the upper layers(9.7-16.7 km)of the ozone profiles show different trends,with the ozone peak occurring at an altitude of 9.7-16.7 km in March,2019.A stratospheric intrusion event in central China from August 11 to 15,2019,is captured using the EMI ozone profiles,potential vorticity data,and relative humidity data.The increase in the CNEMC ozone co ncentration showed that downward transport enhanced surface ozone pollution.

Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model

Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.

A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation metrics.In this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised information.For this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the network.Specifically,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd images.In addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density estimation.The experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

Non-crossing Quantile Regression Neural Network as a Calibration Tool for Ensemble Weather Forecasts

Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,under-dispersed.As such,forecast calibration tools have become popular.Among those tools,quantile regression(QR)is highly competitive in terms of both flexibility and predictive performance.Nevertheless,a long-standing problem of QR is quantile crossing,which greatly limits the interpretability of QR-calibrated forecasts.On this point,this study proposes a non-crossing quantile regression neural network(NCQRNN),for calibrating ensemble NWP forecasts into a set of reliable quantile forecasts without crossing.The overarching design principle of NCQRNN is to add on top of the conventional QRNN structure another hidden layer,which imposes a non-decreasing mapping between the combined output from nodes of the last hidden layer to the nodes of the output layer,through a triangular weight matrix with positive entries.The empirical part of the work considers a solar irradiance case study,in which four years of ensemble irradiance forecasts at seven locations,issued by the European Centre for Medium-Range Weather Forecasts,are calibrated via NCQRNN,as well as via an eclectic mix of benchmarking models,ranging from the naïve climatology to the state-of-the-art deep-learning and other non-crossing models.Formal and stringent forecast verification suggests that the forecasts post-processed via NCQRNN attain the maximum sharpness subject to calibration,amongst all competitors.Furthermore,the proposed conception to resolve quantile crossing is remarkably simple yet general,and thus has broad applicability as it can be integrated with many shallow-and deep-learning-based neural networks.

Kinematic calibration under the expectation maximization framework for exoskeletal inertial motion capture system

This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift.In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79%and 7.16%respectively in comparison to the traditional calibration method.

基于5 μm厚向列相液晶的高效圆极化相控阵系统的设计、校准和实验验证

This paper presents a systematic investigation and demonstration of a K-band circularly polarized liquidcrystal-based phased array(LCPA),including the design,over-the-air(OTA)in-array calibration,and experimental validation.The LCPA contains 16 phase-shifting radiating channels,each consisting of a circularly polarized stacked patch antenna and a liquid-crystal-based phase shifter(LCPS)based on a loaded differential line structure.Thanks to its slow-wave properties,the LCPS exhibits a maximum phase-shifting range of more than 360°with a figure of merit of 78.3(°)·dB^(-1)based on a liquid crystal layer with a thickness of only 5μm.Furthermore,an automatic OTA calibration based on a state ergodic method is proposed,which enables the extraction of the phase-voltage curve of every individual LCPA channel.The proposed LCPA is manufactured and characterized with a total profile of only 1.76 mm,experimentally demonstrating a scanned circularly polarized beam from-40°to+40°with a measured peak gain of 12.5 dBic and a scanning loss of less than 2.5 dB.The bandwidth of the LCPA,which satisfies the require-ments of port reflection(|S_(11)|)<-15 dB,an axial ratio(AR)<3 dB,beam squinting<3°,and a gain variation<2.2 dB,spans from 25.5 to 26.0 GHz.The total efficiency is about 34%,which represents a new state of the art.The use of the demonstrated low-profile LCPA to support circularly polarized scanning beams,along with the systematic design and calibration methodology,holds potential promise for a variety of millimeter-wave applications.

Parameter calibration of the tensile-shear interactive damage constitutive model for sandstone failure

The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.