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This article introduces a time delay calibration technique designed for processing broadband lightning interferometer data with the aim of solving the problem of increased noises in the location results when reducing the length of the data analysis window. The locating performances using three analysis window lengths, 1024 ns, 256 ns, and 128 ns, were compared and analyzed using a cloud-to-ground lightning record as an example. Without using the time delay calibration, the locating noises significantly increased as the length of the analysis window decreased. After the calibration, the problem was solved. Using statistical analysis of the least squares residuals and the signal correlation coefficients within the analysis windows, it was found that overall, there was no significant change in the distribution of residuals after using the time delay calibration method, but the correlation coefficients were significantly improved. The results indicate that the time delay calibration technique can improve the correlation of signals within the analysis window, thereby greatly reducing the ineffective locating results generated after narrowing down the analysis window. The article also analyzed the locating results, as well as the correlation coefficients and signal strength characteristics at the analysis window of 32 ns, the smallest ever reported before. Even at such a small window, the time delay calibration method can still ensure computational stability. The relevant analysis suggests that according to data usage, the correlation coefficient can be flexibly used as a quality control condition of the located results. [ABSTRACT FROM AUTHOR]

The geometrical measurement precision of laser spots is affected by the deviation between the parameters of the laser altimeter and the laboratory measurement results, and the inversion accuracy of surface object height is also limited. The measurement parameters and the load state can be obtained by calibration of the laser altimeter system. Usually, ground detectors are deployed to calibrate the measurement parameters of the laser altimeter, including the divergence angle and the energy distribution of the laser beam. A calibration method for a laser footprint spot without a calibration field was proposed in this paper, focused on the airborne large-footprint laser altimeter system. The geometric parameters of the laser spot were calibrated through the laser echo waveforms of a specific terrain. The experimental results show that geometric calibration of the large-footprint laser altimeter can be achieved in the area of the step surface. The divergence angle of the laser beams obtained from the six experimental areas is 4.604 ± 0.359 mRad, and the consistency of the energy distribution from each laser spot reaches 92.67%. A new method of on-orbit calibration and verification is provided for the satellite laser altimeter system. [ABSTRACT FROM AUTHOR]

Systematic measurement of pasture biomass (kg DM/ha) is crucial for optimising pasture utilisation and increasing dairy farm profitability. On-farm pasture monitoring can be conducted using various sensors, but calibrations are necessary to convert the measured variable into pasture biomass. In this study, we conducted three experiments in New South Wales (Australia) to evaluate the use of the rising plate meter (RPM), pasture reader (PR), unmanned aerial vehicles (UAV) and satellites as pasture monitoring tools. We tested various calibration methods that can improve the accuracy of the estimations and be implemented more easily on-farm. The results indicate that UAV and satellite-derived reflectance indices (e.g., Normalised Difference Vegetation Index) can be indirectly calibrated with height measurements obtained from an RPM or PR. Height measurements can be then converted into pasture biomass ideally by conducting site-specific sporadic calibrations cuts. For satellites, using the average of the entire paddock, root mean square error (RMSE) = 226 kg DM/ha for kikuyu (Pennisetum clandestinum Hochst. ex Chiov) and 347 kg DM/ha for ryegrass (Lolium multiflorum L.) is as effective as but easier than matching NDVI pixels with height measurement using a Global Navigation Satellite System (RMSE = 227 kg DM/ha for kikuyu and 406 kg DM/ha for ryegrass). For situations where no satellite images are available for the same date, the average of all images available within a range of up to four days from the day ground measurements were taken could be used (RMSE = 225 kg DM/ha for kikuyu and 402 kg DM/ha for ryegrass). These methodologies aim to develop more practical and easier-to-implement calibrations to improve the accuracy of the predictive models in commercial farms. However, more research is still needed to test these hypotheses under extended periods, locations, and pasture species. [ABSTRACT FROM AUTHOR]

The shape of corn seeds not being spherical affects their mobility. This study focuses on modeling the typically shaped corn seeds and calibrating the coefficient of rolling friction for different shape types to improve simulation reliability. By analyzing the corn seed shape characteristics and size statistics, this study establishes a classification system that enables the determination of the average value and quantity of different types of corn seed using the spherical granule cluster method. The discrete element method is used to model simplified corn models, and contact parameters are validated through two types of repose angle and a seed metering experiment. In the collapse repose experiment, the relative error between the simulation and the experiment was only 0.72%, while the relative error in another repose experiment was 0.2%. The verification experiment for the metering of seeds showed that the relative error between the simulation and the experiment was below 15% at both low and high speeds, and the multi-grain rate error was less than 10%. This shows that the method proposed in this paper is somewhat accurate. [ABSTRACT FROM AUTHOR]

Outliers are observations that are significantly different from the other observations in a dataset. These types of observations are asymmetric in nature due to a lack of symmetry. The estimation of the cumulative distribution function (CDF) is an important statistical measure commonly discussed for symmetric datasets. However, the estimation of the CDF in the case of the asymmetric nature of the dataset is not a much-explored topic. In this article, we use calibration methodology with auxiliary information for modifying the traditional stratification weight, and hence, we obtain efficient estimates of the CDF using robust measures, i.e., mid-range and tri-mean, under the different distance functions. A simulation study is carried out to see the performance of proposed and existing estimators using asymmetric real-life datasets. [ABSTRACT FROM AUTHOR]

Fire spread behavior models are used to estimate fire behavior metrics, fire hazard, exposure, and risk across the landscape. One of the most widely used fire spread models is the minimum travel time (MTT), which requires a very time-consuming, interactive, trial-and-error calibration process to reproduce observed fire regimens. This study presents the MTTfireCAL package for R, a tool that enables fast calibration of the MTT fire spread models by testing and combining multiple settings and then ranking them based on the model's capacity to reproduce historical fire patterns, such as fire size distribution and fire frequency. Here, we explain the main methodological steps and validate the package by comparing it against the typical calibration procedures in two study areas. In addition, we estimate the minimum number of fire runs required to ensure a reliable calibration. Overall, the use of MTTfireCAL R package and the optimization of the number of ignitions used allowed for a faster calibration of the MTT modeling system than the typical trial-and-error calibration. The MTT modeling system calibrated using MTTfireCAL was also able to better reproduce the historical fire patterns. This tool has the potential to support the academic and operational community working with MTT. [ABSTRACT FROM AUTHOR]

Simple Summary: Around 30% of patients with stage III non-small cell lung cancer (NSCLC) receiving radical chemoradiotherapy will develop symptomatic brain metastases (BM) during the disease course. Identifying risk factors for BM can help improve the management of these patients. The aim of this current study was to identify clinical risk factors, including gross tumor volume (GTV) radiomics features, for developing BM in patients with radically treated stage III NSCLC. We found that age, NSCLC subtype, and GTV of lymph nodes (GTVn) were significant factors for BM. GTVn radiomics features provided higher predictive value than GTV of primary tumor (GTVp) and GTV. Therefore, GTVp and GTVn should be separated in clinical and research practice. Purpose: To identify clinical risk factors, including gross tumor volume (GTV) and radiomics features, for developing brain metastases (BM) in patients with radically treated stage III non-small cell lung cancer (NSCLC). Methods: Clinical data and planning CT scans for thoracic radiotherapy were retrieved from patients with radically treated stage III NSCLC. Radiomics features were extracted from the GTV, primary lung tumor (GTVp), and involved lymph nodes (GTVn), separately. Competing risk analysis was used to develop models (clinical, radiomics, and combined model). LASSO regression was performed to select radiomics features and train models. Area under the receiver operating characteristic curves (AUC-ROC) and calibration were performed to assess the models' performance. Results: Three-hundred-ten patients were eligible and 52 (16.8%) developed BM. Three clinical variables (age, NSCLC subtype, and GTVn) and five radiomics features from each radiomics model were significantly associated with BM. Radiomic features measuring tumor heterogeneity were the most relevant. The AUCs and calibration curves of the models showed that the GTVn radiomics model had the best performance (AUC: 0.74; 95% CI: 0.71–0.86; sensitivity: 84%; specificity: 61%; positive predictive value [PPV]: 29%; negative predictive value [NPV]: 95%; accuracy: 65%). Conclusion: Age, NSCLC subtype, and GTVn were significant risk factors for BM. GTVn radiomics features provided higher predictive value than GTVp and GTV for BM development. GTVp and GTVn should be separated in clinical and research practice. [ABSTRACT FROM AUTHOR]

Multi-camera systems are an effective solution for perceiving large areas or complex scenarios with many occlusions. In such a setup, an accurate camera network calibration is crucial in order to localize scene elements with respect to a single reference frame shared by all the viewpoints of the network. This is particularly important in applications such as object detection and people tracking. Multi-camera calibration is a critical requirement also in several robotics scenarios, particularly those involving a robotic workcell equipped with a manipulator surrounded by multiple sensors. Within this scenario, the robot-world hand-eye calibration is an additional crucial element for determining the exact position of each camera with respect to the robot, in order to provide information about the surrounding workspace directly to the manipulator. Despite the importance of the calibration process in the two scenarios outlined above, namely (i) a camera network, and (ii) a camera network with a robot, there is a lack of standard datasets available in the literature to evaluate and compare calibration methods. Moreover they are usually treated separately and tested on dedicated setups. In this paper, we propose a general standard dataset acquired in a robotic workcell where calibration methods can be evaluated in two use cases: camera network calibration and robot-world hand-eye calibration. The Multi-Eye To Robot Indoor Calibration (METRIC) dataset consists of over 10,000 synthetic and real images of ChAruCo and checkerboard patterns, each one rigidly attached to the robot end-effector, which was moved in front of four cameras surrounding the manipulator from different viewpoints during the image acquisition. The real images in the dataset includes several multi-view image sets captured by three different types of sensor networks: Microsoft Kinect V2, Intel RealSense Depth D455 and Intel RealSense Lidar L515, to evaluate their advantages and disadvantages for calibration. Furthermore, in order to accurately analyze the effect of camera-robot distance on calibration, we acquired a comprehensive synthetic dataset, with related ground truth, with three different camera network setups corresponding to three levels of calibration difficulty depending on the cell size. An additional contribution of this work is to provide a comprehensive evaluation of state-of-the-art calibration methods using our dataset, highlighting their strengths and weaknesses, in order to outline two benchmarks for the two aforementioned use cases. [ABSTRACT FROM AUTHOR]

Accurate sky identification is one of the most important functions of an automated telescope mount. The more accurately the robotic telescope is navigated to the investigated part of the sky, the better the observations and discoveries made. In this paper, we present mathematical methods for accurate sky identification (celestial coordinates determination). They include the automatic selection of the reference stars, preliminary and full sky identification, as well as an interaction with international databases, which are a part of the astrometric calibration. All described methods help to receive accurately calculated astrometric data and use it for the positional calibration and better navigation of the automated telescope mount. The developed methods were successfully implemented in the Collection Light Technology (CoLiTec) software. Through its use, more than 1600 small solar system objects were discovered. It has been used in more than 700,000 observations and successful sky identifications, during which, five comets were discovered. Additionally, the accuracy indicators of the processing results of the CoLiTec software are provided in the paper, which shows benefits of the CoLiTec software and lower standard deviation of the sky identification in the case of low signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

Acousto-optic interaction geometry determines the spectral and spatial response of an acousto-optic tunable filter (AOTF). The precise calibration of the acousto-optic interaction geometry of the device is a necessary process before designing and optimizing optical systems. In this paper, we develop a novel calibration method based on the polar angular performance of an AOTF. A commercial AOTF device with unknown geometry parameters was experimentally calibrated. The experimental results show high precision, in some cases falling within 0.01°. In addition, we analyzed the parameter sensitivity and Monte Carlo tolerance of the calibration method. The results of the parameter sensitivity analysis show that the principal refractive index has a large influence on the calibration results, while other factors have little influence. The results of the Monte Carlo tolerance analysis show that the probability of the results falling 0.1° using this method is greater than 99.7%. This work provides an accurate and easy-to-perform method for AOTF crystal calibration and can contribute to the characteristic analysis of AOTFs and the optical design of spectral imaging systems. [ABSTRACT FROM AUTHOR]

The total harmonic distortion (THD) index and its calculation methods are presented to calibrate the sinusoidal motion of the low-frequency angular acceleration rotary table (LFAART) and make up the incomprehensive evaluation based on the angular acceleration amplitude and frequency error indexes. The THD is calculated from two measurement schemes: a unique scheme combining the optical shaft encoder and the laser triangulation sensor and a regular scheme using the fiber optical gyroscope (FOG). An improved reversing moments recognition method is presented to upgrade the accuracy of solving the angular motion amplitude based on optical shaft encoder output. The field experiment shows that the difference in the THD values achieved using the combining scheme and FOG is within 0.11% when the signal-to-noise ratio of the FOG signal is higher than 7.7 dB, indicating the accuracy of the proposed methods and the feasibility of taking THD as the index. [ABSTRACT FROM AUTHOR]

The flexible strain sensor's measuring range is usually over 5000 με, while the conventional variable section cantilever calibration model has a measuring range within 1000 με. In order to satisfy the calibration requirements of flexible strain sensors, a new measurement model was proposed to solve the inaccurate calculation problem of the theoretical strain value when the linear model of a variable section cantilever beam was applied to a large range. The nonlinear relationship between deflection and strain was established. The finite element analysis of a variable section cantilever beam with ANSYS shows that the linear model's relative deviation is as high as 6% at 5000 με, while the relative deviation of the nonlinear model is only 0.2%. The relative expansion uncertainty of the flexible resistance strain sensor is 0.365% (k = 2). Simulation and experimental results show that this method solves the imprecision of the theoretical model effectively and realizes the accurate calibration of a large range of strain sensors. The research results enrich the measurement models and calibration models for flexible strain sensors and contribute to the development of strain metering. [ABSTRACT FROM AUTHOR]

Barometric process separation (BaPS) is an automated laboratory system for the simultaneous measurement of microbial respiration and gross nitrification rates in soil samples. To ensure optimal functioning, the sensor system, consisting of a pressure sensor, an O2 sensor, a CO2 concentration sensor, and two temperature probes, must be accurately calibrated. For the regular on-site quality control of the sensors, we developed easy, inexpensive, and flexible calibration procedures. The pressure sensor was calibrated by means of a differential manometer. The O2 and CO2 sensors were simultaneously calibrated through their exposure to a sequence of O2 and CO2 concentrations obtained by sequentially exchanging O2/N2 and CO2/N2 calibration gases. Linear regression models were best suited for describing the recorded calibration data. The accuracy of O2 and CO2 calibration was mainly affected by the accuracy of the utilized gas mixtures. Because the applied measuring method is based on the O2 conductivity of ZrO2, the O2 sensor is particularly susceptible to aging and to consequent signal shifts. Sensor signals were characterized by high temporal stability over the years. Deviations in the calibration parameters affected the measured gross nitrification rate by up to 12.5% and affected the respiration rate by up to 5%. Overall, the proposed calibration procedures are valuable tools for ensuring the quality of BaPS measurements and for promptly identifying sensor malfunctions. [ABSTRACT FROM AUTHOR]

The magnetic spectrometer AMS-100, which includes a superconducting coil, is designed to measure cosmic rays and detect cosmic antimatter in space. This extreme environment requires a suitable sensing solution to monitor critical changes in the structure such as the beginning of a quench in the superconducting coil. Rayleigh-scattering-based distributed optical fibre sensors (DOFS) fulfil the high requirements for these extreme conditions but require precise calibration of the temperature and strain coefficients of the optical fibre. Therefore, the fibre-dependent strain and temperature coefficients K T and K ϵ for the temperature range from 77 K to 353 K were investigated in this study. The fibre was integrated into an aluminium tensile test sample with well-calibrated strain gauges to determine the fibre's K ϵ independently of its Young's modulus. Simulations were used to validate that the strain caused by changes in temperature or mechanical conditions was the same in the optical fibre as in the aluminium test sample. The results indicated a linear temperature dependence of K ϵ and a non-linear temperature dependence of K T . With the parameters presented in this work, it was possible to accurately determine the strain or temperature of an aluminium structure over the entire temperature range from 77 K to 353 K using the DOFS. [ABSTRACT FROM AUTHOR]

Balance assessment, or posturography, tracks and prevents health complications for a variety of groups with balance impairment, including the elderly population and patients with traumatic brain injury. Wearables can revolutionize state-of-the-art posturography methods, which have recently shifted focus to clinical validation of strictly positioned inertial measurement units (IMUs) as replacements for force-plate systems. Yet, modern anatomical calibration (i.e., sensor-to-segment alignment) methods have not been utilized in inertial-based posturography studies. Functional calibration methods can replace the need for strict placement of inertial measurement units, which may be tedious or confusing for certain users. In this study, balance-related metrics from a smartwatch IMU were tested against a strictly placed IMU after using a functional calibration method. The smartwatch and strictly placed IMUs were strongly correlated in clinically relevant posturography scores (r = 0.861–0.970, p < 0.001). Additionally, the smartwatch was able to detect significant variance (p < 0.001) between pose-type scores from the mediolateral (ML) acceleration data and anterior-posterior (AP) rotation data. With this calibration method, a large problem with inertial-based posturography has been addressed, and wearable, "at-home" balance-assessment technology is within possibility. [ABSTRACT FROM AUTHOR]

The radiometric calibration network (RadCalNet) comprises four pseudo-invariant calibration sites (PICS): Gobabeb, Baotou, Railroad Valley Playa, and La Crau. Due to its site stability characteristics, it is widely used for sensor performance monitoring and radiometric calibration, which require high spatiotemporal stability. However, some studies have found that PICS are not invariable. Previous studies used top-of-atmosphere (TOA) data without verifying site data, which could affect the accuracy of their results. In this study, we analyzed the short- and long-term radiometric trends of RadCalNet sites using bottom-of-atmosphere (BOA) data, and verified the trends revealed by the TOA data from Landsat 7, 8, and Sentinel-2. Besides the commonly used methods (e.g., nonparametric Mann–Kendall and sequential Mann–Kendall tests), a more robust Sen's slope method was used to estimate the magnitude of the change. We found that (1) the trends based on TOA reflectance contrasted with those based on BOA reflectance in certain cases, e.g., the reflectance trends in the red band of BOA data for La Crau in summer and autumn and Baotou were not significant, while the TOA data showed a significant downward trend; (2) the temporal trends showed statistically significant and abrupt changes in all PICS, e.g., the SWIR2 band of La Crau in winter and spring changed by 1.803% per year, and the SWIR1 band of Railroad Valley Playa changed by >0.282% per year, indicating that the real changes in sensor performance are hard to detect using these sites; (3) spatial homogeneity was verified using the coefficient of variation (CV) and Getis statistic (Gi*) for each PICS (CV < 3% and Gi* > 0). Overall, the RadCalNet remains a highly reliable tool for vicarious calibration; however, the temporal stability should be noted for radiometric performance monitoring of sensors. [ABSTRACT FROM AUTHOR]

Monitoring global greenhouse gas concentration information via satellite remote sensing has become a critical area of research to support the further understanding of global carbon emissions. The Greenhouse-gases Absorption Spectrometer-2 (GAS-2) is being developed as the primary payload of the Fengyun-3H (FY-3H), which will be launched in 2024. Achieving high-precision mesurements of greenhouse gases requires precise spectral calibration. However, currently, there is no method for assessing the detection accuracy of GAS-2 using spectral calibration light sources, and quantitative studies are lacking. In this study, the influence model of calibration light sources on spectral calibration accuracy is established, and the spectral radiance acquired via GAS-2 is simulated using the line-by-line radiative transfer model (LBLRTM). We investigated the impact of different linewidths and wavelength stabilities of the calibration light source on its accuracy in four wavelength bands. This study is the first to examine the effects of the linewidth and wavelength stability of a calibration light source on the spectral radiance acquired via GAS-2. The initial results demonstrate that if the linewidth of the calibration light source is approximately 100 MHz and the wavelength stability is in the order of subpicometers, the radiance error obtained by GAS-2 is less than 10%. Among the four bands, the 2.06 μ m (strong- C O 2 ) band is more affected by the calibration light source than the other three bands. In addition, the wavelength stability of the light source has a greater influence on the error than the linewidth of the light source under the same error condition. The research findings can be used to guide and reference the selection of light sources in the laboratory spectral calibration of GAS-2, ultimately contributing to the instrument's quantitative development level. [ABSTRACT FROM AUTHOR]

The multispectral imager (MII), onboard the Sustainable Development Science Satellite 1 (SDGSAT-1), performs detailed terrestrial change detection and coastal monitoring. SDGSAT-1 was launched at 2:19 UTC on 5 November 2021, as the world's first Earth science satellite to serve the United Nations 2030 Sustainable Development Agenda. A vicarious radiometric calibration experiment was conducted at the Dunhuang calibration site (Gobi Desert, China) on 14 December 2021. In-situ measurements of ground reflectance, aerosol optical depth (AOD), total columnar water vapor, radiosonde data, and diffuse-to-global irradiance (DG) ratio were performed to predict the top-of-atmosphere radiance by the reflectance-, irradiance-, and improved irradiance-based methods using the moderate resolution atmospheric transmission model. The MII calibration coefficients were calculated by dividing the top-of-atmosphere radiance by the average digital number value of the image. The radiometric calibration coefficients calculated by the three calibration methods were reliable (average relative differences: 2.20% (reflectance-based vs. irradiance-based method) and 1.43% (reflectance-based vs. improved irradiance-based method)). The total calibration uncertainties of the reflectance-, irradiance-, and improved irradiance-based methods were 2.77–5.23%, 3.62–5.79%, and 3.50–5.23%, respectively. The extra DG ratio measurements in the latter two methods did not improve the calibration accuracy for AODs ≤ 0.1. The calibrated MII images were verified using Landsat-8 Operational Land Imager (OLI) and Sentinel-2A MultiSpectral Instrument (MSI) images. The retrieved ground reflectances of the MII over different surface types were cross-compared with those of OLI and MSI using the FAST Line-of-sight Atmospheric Analysis of Hypercubes software. The MII retrievals differed by <0.0075 (7.13%) from OLI retrievals and <0.0084 (7.47%) from MSI retrievals for calibration coefficients from the reflectance-based method; <0.0089 (7.57%) from OLI retrievals and <0.0111 (8.65%) from MSI retrievals for the irradiance-based method; and <0.0082 (7.33%) from OLI retrievals and <0.0101 (8.59%) from MSI retrievals for the improved irradiance-based method. Thus, our findings support the application of SDGSAT-1 data. [ABSTRACT FROM AUTHOR]

The celebrated Heston's stochastic volatility (SV) model for the valuation of European options provides closed form solutions that are given in terms of characteristic functions. However, the numerical calibration of this five-parameter model, which is based on market option data, often remains a daunting task. In this paper, we provide a theoretical solution to the long-standing 'open problem' of characterizing the class of risk neutral distributions (RNDs), if any, that satisfy Heston's SV for option valuation. We prove that the class of scale parameter distributions with mean being the forward spot price satisfies Heston's solution. Thus, we show that any member of this class could be used for the direct risk neutral valuation of option prices under Heston's stochastic volatility model. In fact, we also show that any RND with mean being the forward spot price that satisfies Heston's option valuation solution must also be a member of the scale family of distributions in that mean. As particular examples, we show that under a certain re-parametrization, the one-parameter versions of the log-normal (i.e., Black–Scholes), gamma, and Weibull distributions, along with their respective inverses, are all members of this class and thus, provide explicit RNDs for direct option pricing under Heston's SV model. We demonstrate the applicability and suitability of these explicit RNDs via exact calculations and Monte Carlo simulations, using already published index data and a calibrated Heston's model (S&P500, ODAX), as well as an illustration based on recent option market data (AMD). [ABSTRACT FROM AUTHOR]

Accurate measurement of low-level thoron gas and high-accuracy calibration of thoron measurement devices are essential for assessing and preventing thoron radiological risks. This study aimed to develop a thoron gas measurement technique using an airflow-through scintillation cell for both low-level measurement and high-accuracy calibration. To achieve this, a compartment model was developed to estimate the influence of progeny deposition and accumulation on the wall of the scintillation cell to prevent an overestimation of thoron. A self-developed scintillation cell was utilised to implement and validate this technique. The lower detection limit and measurement uncertainty were then evaluated to assess the feasibility of the technique for low-level measurement and high-accuracy calibration. The results showed that the compartment model effectively addressed the influence of progeny deposition. The measurement technique achieved a lower detection limit below 100 Bq m−3 even with the coexistence of that of 100 Bq m−3 of radon and attained a measurement uncertainty (k = 2) below 10% when the concentration of thoron exceeded 1000 Bq m−3. In summary, this study developed a reliable and practical thoron gas measurement technique using an airflow-through scintillation cell with a consideration of progeny deposition, and is expected to contribute to the assessment and prevention of thoron radiological risk. [ABSTRACT FROM AUTHOR]

Recent developments in robotics have enabled humanoid robots to be used in tasks where they have to physically interact with humans, including robot-supported caregiving. This interaction—referred to as physical human–robot interaction (pHRI)—requires physical contact between the robot and the human body; one way to improve this is to use efficient sensing methods for the physical contact. In this paper, we use a flexible tactile sensing array and integrate it as a tactile skin for the humanoid robot HRP-4C. As the sensor can take any shape due to its flexible property, a particular focus is given on its spatial calibration, i.e., the determination of the locations of the sensor cells and their normals when attached to the robot. For this purpose, a novel method of spatial calibration using B-spline surfaces has been developed. We demonstrate with two methods that this calibration method gives a good approximation of the sensor position and show that our flexible tactile sensor can be fully integrated on a robot and used as input for robot control tasks. These contributions are a first step toward the use of flexible tactile sensors in pHRI applications. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to reliably calibrate a pair of sensorized insoles utilizing an array of capacitive tactile pixels (taxels). A new calibration setup is introduced that is scalable and suitable for multiple kinds of wearable sensors and a procedure for the simultaneous calibration of each of the sensors in the insoles is presented. The calibration relies on a two-step optimization algorithm that, firstly, enables determination of a relevant set of mathematical models based on the instantaneous measurement of the taxels alone, and, then, expands these models to include the relevant portion of the time history of the system. By comparing the resulting models with our previous work on the same hardware, we demonstrate the effectiveness of the novel method both in terms of increased ability to cope with the non-linear characteristics of the sensors and increased pressure ranges achieved during the experiments performed. [ABSTRACT FROM AUTHOR]

In vivo determination of the skin's thermal properties is of growing interest. Several types of sensors are being designed and tested. In this field, we have developed a skin calorimeter for the determination of the heat flow, the heat capacity and the thermal resistance of the skin. The calorimeter calibration consists of the determination of the parameters of the model we have chosen to represent the behavior of the device. This model considers the heat capacity and the thermal resistance of the skin, which depend on the case (body zone, subject, physical state, etc.) and also have a strong time dependence. Therefore, this work includes a validation study with reference materials. Finally, it is concluded that the heat capacity determined is a function of the thermal penetration depth of the measurement characteristics. In the case of high thermal conductivity materials in which the thermal penetration is nearly total, the heat capacity obtained coincides with that of the reference material sample. [ABSTRACT FROM AUTHOR]

The accuracy and consistency of Earth observation (EO) instrument radiometric calibration is a fundamental prerequisite for achieving accurate results and delivering reliable predictions. Frequent calibration and validation (Cal/Val) activities are needed during the instrument's lifetime, and this procedure is often extended to historical archives. Numerous satellites in orbit and proposed future missions have incorporated lunar observation into their vicarious calibration components over recent years, facilitated by the extreme long-term photometric stability of the Moon. Since the birth of the first lunar calibration reference model, lunar-dependent calibration techniques have developed rapidly, and the application and refinement of the lunar radiometric model have become a welcome research focus in the calibration community. Within the context of the development of lunar observation activities and calibration systems globally, we provide a comprehensive review of the activities and results spawned by treating the Moon as a reference for instrument response and categorize them against the understanding of lunar radiometric reference. In general, this appears to be a process of moving from data to instruments, then back into data, working towards a stated goal. Here we highlight lunar radiometric models developed by different institutions or agencies over the last two decades while reporting on the known limitations of these solutions, with unresolved challenges remaining and multiple lunar observation plans and concepts attempting to address them from various perspectives, presenting a temporal development. We also observe that the methods seeking uncertainty reduction at this stage are rather homogeneous, lacking the combination of approaches or results from lunar surface studies conducted by many spacecraft missions, and joint deep learning methods to extract information. The factors that influence the accuracy of the measurement irradiance may be regulated when practical models arrive. As a central element in lunar calibration, the development of an absolute radiometric datum helps to better understand the Earth system. [ABSTRACT FROM AUTHOR]

Remotely sensed hydrologic variables, in conjunction with streamflow data, have been increasingly used to conduct multivariable calibration of hydrologic model parameters. Here, we calibrated the Soil and Water Assessment Tool (SWAT) model using different combinations of streamflow and remotely sensed hydrologic variables, including Atmosphere–Land Exchange Inverse (ALEXI) Evapotranspiration (ET), Moderate Resolution Imaging Spectroradiometer (MODIS) ET, and Soil MERGE (SMERGE) soil moisture. The results show that adding remotely sensed ET and soil moisture to the traditionally used streamflow for model calibration can impact the number and values of parameters sensitive to hydrologic modeling, but it does not necessarily improve the model performance. However, using remotely sensed ET or soil moisture data alone led to deterioration in model performance as compared with using streamflow only. In addition, we observed large discrepancies between ALEXI or MODIS ET data and the choice between these two datasets for model calibration can have significant implications for the performance of the SWAT model. The use of different combinations of streamflow, ET, and soil moisture data also resulted in noticeable differences in simulated hydrologic processes, such as runoff, percolation, and groundwater discharge. Finally, we compared the performance of SWAT and the SWAT-Carbon (SWAT-C) model under different multivariate calibration setups, and these two models exhibited pronounced differences in their performance in the validation period. Based on these results, we recommend (1) the assessment of various remotely sensed data (when multiple options available) for model calibration before choosing them for complementing the traditionally used streamflow data and (2) that different model structures be considered in the model calibration process to support robust hydrologic modeling. [ABSTRACT FROM AUTHOR]

Three advanced methodologies were performed during Landsat-9 on orbit and initialization and verification (OIV): Extended Pseudo Invariant Calibration Sites Absolute Calibration Model Double Ratio (ExPAC Double Ratio) and Extended Pseudo Invariant Calibration Sites (EPICS)-based cross-calibration utilizing stable regions in Northern African desert sites (EPICS-NA) and a global scale (EPICS-Global). The development of these three techniques was described using uncertainties analysis. The ExPAC Double Ratio was derived based on the ratio between ExPAC model prediction and satellite measurements for Landsat-8 and Landsat-9. The ExPAC Double Ratio can be performed to determine differences between sensors ranging from visible, red edge, near-infrared, to short-wave infrared wavelengths. The ExPAC Double Ratio and EPICS-based inter-comparison ratio uncertainties were determined using the Monte Carlo Simulation. It was found that the uncertainty levels of 1–2% can be achieved. The EPICS-based cross-calibration results were derived using two targets: EPICS-NA and EPICS-Global, with uncertainties of 1–2.2% for all spectral bands. The inter-comparison results between Landsat-9 and Landsat-8 during the OIV period using the three advanced methods were well within 0.5% for all spectral bands except for the green band, which showed sub 1% agreement. [ABSTRACT FROM AUTHOR]

As the resolution of airborne hyperspectral imagers (AHIs) continues to improve, the demand for accurate boresight calibration also increases. However, the high cost of ground control points (GCPs) and the low horizontal resolution of open digital elevation model (DEM) datasets limit the accuracy of AHI's boresight calibration. We propose a method to enhance the accuracy of DEM-based boresight calibration using coplanarity constraints to address this issue. Our approach utilizes the relative accuracy of DEM in low-resolution DEM datasets. To make better use of the DEM, we apply coplanarity constraints to identify image features that display similar displacement in overlapping areas, and extract their corresponding elevation values from the DEM. These features and their relative heights are then incorporated into an optimization problem for boresight calibration. In the case of low-resolution DEM datasets, our method fully utilizes the relative accuracy of the DEM to improve the boresight correction precision. We have proven that the relative accuracy of elevation is more reliable than absolute accuracy in this situation. Our approach has been tested on the dataset from AHI, and the results have shown that the proposed method has better accuracy on low-resolution DEM datasets. In summary, our method provides a novel approach to improving the accuracy of DEM-based boresight calibration for AHIs, which can benefit applications, such as remote sensing and environmental monitoring. This research highlights the importance of utilizing the relative accuracy of low-resolution DEM datasets for improving the accuracy of boresight calibration. [ABSTRACT FROM AUTHOR]

In this study, an on-orbit radiometric calibration campaign of the GF5-02 AHSI was performed at the RadCalNet Baotou site, based on the automated observation of reflectance and atmospheric parameters of a 300 m × 300 m homogeneous desert area. The consistency of the radiometric calibration coefficients was validated both at the Dunhuang calibration site and the Baotou site. The average relative difference between the calibrated top-of-atmospheric (TOA) radiance and the predicted TOA radiance were less than 7%. The R2 of these two TOA radiances were all higher than 0.99. These results showed that the accuracy of calibration coefficients could meet the requirements of hyperspectral quantification applications. The uncertainty of GF5-02 AHSI radiometric calibration was 6.18%. This study also demonstrated that automated observation data of the Baotou site were reliable for high-frequency radiometric calibration and radiometric performance monitoring of GF5-02 AHSI. [ABSTRACT FROM AUTHOR]

Electrical resistance strain gauges are widely used in asymmetric structures for measurement and monitoring, but their thermal output in changing temperature environments has a significant impact on the measurement results. Since thermal output is related to the coefficient of thermal expansion of the strain gauge's sensitive grating material and the measured object, the temperature self-compensation technique of strain gauges fails to eliminate the additional strain caused by temperature because it cannot match the coefficient of thermal expansion of various measured objects. To address this problem, in this study, the principle of the thermal output of electrical resistance strain gauges was analyzed, a calibration experiment for thermal output in the case of a mismatch between the coefficient of linear expansion of the measured object and the strain gauge grating material was conducted, and the mechanism for temperature influence on thermal output was revealed. A method was proposed to obtain the thermal output curves for different materials by using thermostats with dual temperatures to conduct temperature calibration experiments. A linear regression method was used to obtain a linear formula for the thermal output corresponding to each temperature. The thermal output conversion relationship was derived for materials with different coefficients of linear expansion. An in situ temperature compensation technique for electrical resistance strain gauges that separates the measured strain into thermal and mechanical strains was proposed. The results showed that the thermal output curve for the measured object can be calibrated in advance and then deducted from the measured strain, thus reducing the influence of temperature-induced additional strain on the mechanical strain. In addition, a new method was provided for the calculation of the thermal output among materials with similar coefficients of linear expansion, providing a reference for the health monitoring of asymmetric structures. [ABSTRACT FROM AUTHOR]

Simple Summary: Personalized breast cancer screening has the potential to improve the accuracy and effectiveness of breast cancer screening by tailoring the screening protocol to an individual's risk factors. Currently, most women undergo mammograms at regular intervals based on age and family history, regardless of their risk factors. We examined the applicability of the Gail model, a well-known breast cancer prediction tool including several risk factors, in an Asian population. While the tool predicts the risks of developing breast cancer in the next 2, 5, 10, and 15 years to some extent, the age at which the disease occurs cannot be estimated. In addition, the tool performs better for longer prediction horizons (10 or 15 years), limiting its utility for risk prediction for two-year screening intervals. Personalized breast cancer risk profiling has the potential to promote shared decision-making and improve compliance with routine screening. We assessed the Gail model's performance in predicting the short-term (2- and 5-year) and the long-term (10- and 15-year) absolute risks in 28,234 asymptomatic Asian women. Absolute risks were calculated using different relative risk estimates and Breast cancer incidence and mortality rates (White, Asian-American, or the Singapore Asian population). Using linear models, we tested the association of absolute risk and age at breast cancer occurrence. Model discrimination was moderate (AUC range: 0.580–0.628). Calibration was better for longer-term prediction horizons (E/Olong-term ranges: 0.86–1.71; E/Oshort-term ranges:1.24–3.36). Subgroup analyses show that the model underestimates risk in women with breast cancer family history, positive recall status, and prior breast biopsy, and overestimates risk in underweight women. The Gail model absolute risk does not predict the age of breast cancer occurrence. Breast cancer risk prediction tools performed better with population-specific parameters. Two-year absolute risk estimation is attractive for breast cancer screening programs, but the models tested are not suitable for identifying Asian women at increased risk within this short interval. [ABSTRACT FROM AUTHOR]

Simple Summary: Nowadays, the options available to perform external dosimetric audits of the high dose rate (HDR) brachytherapy treatment process are limited. In this work, we present a methodology that allows for performing dosimetric audits in this field. A phantom was designed and manufactured for this purpose. The criteria for its design, together with the in-house measurements for its characterization, are presented. The result is a user-friendly system that can be mailed to perform dosimetric audits in HDR brachytherapy on-site for systems using either Iridium-192 (192Ir) or Cobalt-60 (60Co) sources. Objectives: The main goal of this work is to design and characterize a user-friendly methodology to perform mailed dosimetric audits in high dose rate (HDR) brachytherapy for systems using either Iridium-192 (192Ir) or Cobalt-60 (60Co) sources. Methods: A solid phantom was designed and manufactured with four catheters and a central slot to place one dosimeter. Irradiations with an Elekta MicroSelectron V2 for 192Ir, and with a BEBIG Multisource for 60Co were performed for its characterization. For the dose measurements, nanoDots, a type of optically stimulated luminescent dosimeters (OSLDs), were characterized. Monte Carlo (MC) simulations were performed to evaluate the scatter conditions of the irradiation set-up and to study differences in the photon spectra of different 192Ir sources (Microselectron V2, Flexisource, BEBIG Ir2.A85-2 and Varisource VS2000) reaching the dosimeter in the irradiation set-up. Results: MC simulations indicate that the surface material on which the phantom is supported during the irradiations does not affect the absorbed dose in the nanoDot. Generally, differences below 5% were found in the photon spectra reaching the detector when comparing the Microselectron V2, the Flexisource and the BEBIG models. However, differences up to 20% are observed between the V2 and the Varisource VS2000 models. The calibration coefficients and the uncertainty in the dose measurement were evaluated. Conclusions: The system described here is able to perform dosimetric audits in HDR brachytherapy for systems using either 192Ir or 60Co sources. No significant differences are observed between the photon spectra reaching the detector for the MicroSelectron V2, the Flexisource and the BEBIG 192Ir sources. For the Varisource VS2000, a higher uncertainty is considered in the dose measurement to allow for the nanoDot response. [ABSTRACT FROM AUTHOR]

Few shot class incremental learning (FSCIL) is an extremely challenging but valuable problem in real-world applications. When faced with novel few shot tasks in each incremental stage, it should take into account both catastrophic forgetting of old knowledge and overfitting of new categories with limited training data. In this paper, we propose an efficient prototype replay and calibration (EPRC) method with three stages to improve classification performance. We first perform effective pre-training with rotation and mix-up augmentations in order to obtain a strong backbone. Then a series of pseudo few shot tasks are sampled to perform meta-training, which enhances the generalization ability of both the feature extractor and projection layer and then helps mitigate the over-fitting problem of few shot learning. Furthermore, an even nonlinear transformation function is incorporated into the similarity computation to implicitly calibrate the generated prototypes of different categories and alleviate correlations among them. Finally, we replay the stored prototypes to relieve catastrophic forgetting and rectify prototypes to be more discriminative in the incremental-training stage via an explicit regularization within the loss function. The experimental results on CIFAR-100 and miniImageNet demonstrate that our EPRC significantly boosts the classification performance compared with existing mainstream FSCIL methods. [ABSTRACT FROM AUTHOR]

There is a global trend of new guidelines highly recommending quantitative neuromuscular monitoring in the operating room. In fact, it is almost certain that quantitatively monitoring the depth of intraoperative muscle paralysis may permit the rational use of muscle relaxants and avoid some of the major related complications, namely postoperative pulmonary complications. A specific culture related to this issue is necessary to integrate quantitative monitoring of muscle relaxants as part of a major monitoring entity in anesthetized patients. For this purpose, it is necessary to fully understand the physiology, pharmacology and concept of monitoring as well as the choice of pharmacological reversal, including the introduction of sugammadex a decade ago. [ABSTRACT FROM AUTHOR]

Magneto-optical indicator films (MOIFs) are a very useful tool for direct studies of the spatial distribution of magnetic fields and the magnetization processes in magnetic materials and industrial devices such as magnetic sensors, microelectronic components, micro-electromechanical systems (MEMS), and others. The ease of application and the possibility for direct quantitative measurements in combination with a straightforward calibration approach make them an indispensable tool for a wide spectrum of magnetic measurements. The basic sensor parameters of MOIFs, such as a high spatial resolution down to below 1 μm combined with a large spatial imaging range of up to several cm and a wide dynamic range from 10 μT to over 100 mT, also foster their application in various areas of scientific research and industry. The history of MOIF development totals approximately 30 years, and only recently have the underlying physics been completely described and detailed calibration approaches been developed. The present review first summarizes the history of MOIF development and applications and then presents the recent advances in MOIF measurement techniques, including the theoretical developments and traceable calibration methods. The latter make MOIFs a quantitative tool capable of measuring the complete vectorial value of a stray field. Furthermore, various scientific and industrial application areas of MOIFs are described in detail. [ABSTRACT FROM AUTHOR]

Kappa-angle calibration shows its importance in gaze tracking due to the special structure of the eyeball. In a 3D gaze-tracking system, after the optical axis of the eyeball is reconstructed, the kappa angle is needed to convert the optical axis of the eyeball to the real gaze direction. At present, most of the kappa-angle-calibration methods use explicit user calibration. Before eye-gaze tracking, the user needs to look at some pre-defined calibration points on the screen, thereby providing some corresponding optical and visual axes of the eyeball with which to calculate the kappa angle. Especially when multi-point user calibration is required, the calibration process is relatively complicated. In this paper, a method that can automatically calibrate the kappa angle during screen browsing is proposed. Based on the 3D corneal centers and optical axes of both eyes, the optimal objective function of the kappa angle is established according to the coplanar constraint of the visual axes of the left and right eyes, and the differential evolution algorithm is used to iterate through kappa angles according to the theoretical angular constraint of the kappa angle. The experiments show that the proposed method can make the gaze accuracy reach 1.3 ° in the horizontal plane and 1.34 ° in the vertical plane, both of which are within the acceptable margins of gaze-estimation error. The demonstration of explicit kappa-angle calibration is of great significance to the realization of the instant use of gaze-tracking systems. [ABSTRACT FROM AUTHOR]

Active radar calibrators (ARCs), also known as calibration transponders, are often used as reference targets for the absolute radiometric calibration of radar systems due to their large radar cross-sections (RCSs). Before such a transponder can be used as a reference target, the hardware itself has to be calibrated. A novel method, called the three-transponder method, was proposed some years ago to allow for RCS calibration of digital transponders without using any known RCS targets as reference. The first part of this paper refines the technique and presents the measurement setup as well as the results of a comprehensive measurement campaign performed to calibrate a single digital transponder. In this part of the paper, the results are validated and a comprehensive uncertainty analysis is performed to estimate the total RCS uncertainty associated with the presented measurement data. This uncertainty analysis follows the international standard "Guide to the expression of uncertainty in measurement" (GUM) and will derive expressions for all major sources of uncertainty. For the validation, the measurement results will be compared with full-wave electromagnetic simulations of trihedral corner reflectors; there is excellent agreement between the simulation and measurements. [ABSTRACT FROM AUTHOR]

This research aimed to develop a novel dark hyperspectral absolute calibration (DAHAC) model using stable dark targets of "Global Cluster-36" (GC-36), one of the clusters from the "300 Class Global Classification". The stable dark sites were identified from GC-36 called "Dark EPICS-Global" covering the surface types viz. dark rock, volcanic area, and dark sand. The Dark EPICS-Global shows a temporal variation of 0.02 unit reflectance. This work used the Landsat-8 (L8) Operational Land Imager (OLI), Sentinel-2A (S2A) Multispectral Instrument (MSI), and Earth Observing One (EO-1) Hyperion data for the DAHAC model development, where well-calibrated L8 and S2A were used as the reference sensors, while EO-1 Hyperion with a 10 nm spectral resolution was used as a hyperspectral library. The dark hyperspectral dataset (DaHD) was generated by combining the normalized hyperspectral profile of L8 and S2A for the DAHAC model development. The DAHAC model developed in this study takes into account the solar zenith and azimuth angles, as well as the view zenith and azimuth angles in Cartesian coordinates form. This model is capable of predicting TOA reflectance in all existing spectral bands of any sensor. The DAHAC model was then validated with the Landsat-7 (L7), Landsat-9 (L9), and Sentinel-2B (S2B) satellites from their launch dates to March 2022. These satellite sensors vary in terms of their spectral resolution, equatorial crossing time, spatial resolution, etc. The comparison between the DAHAC model and satellite measurements showed an accuracy within 0.01 unit reflectance across the overall spectral band. The proposed DAHAC model uncertainty level was determined using Monte Carlo simulation and found to be 0.04 and 0.05 unit reflectance for the VNIR and SWIR channels, respectively. The DAHAC model double ratio was used as a tool to perform the inter-comparison between two satellites. The sensor inter-comparison results for L8 and L9 showed a 2% difference and 1% for S2A and S2B across all spectral bands. [ABSTRACT FROM AUTHOR]

FY-3E WindRAD (Fengyun-3E Wind Radar) is a dual-frequency rotating fan-beam scatterometer. Its data characteristics, NOC (NWP Ocean Calibration), and wind retrieval performance are investigated in this paper. The diversity of the radar view geometry varies across the swaths, with maximum diversity in the sweet swaths and limited diversity in the outer and nadir swaths. When NOC backscatter calibration coefficients are computed as a function of incidence angle only (NOCint), a smooth correction is found. However, when relative antenna azimuth angle is included (NOCant), it appears that the corrections as a function of relative azimuth angle vary harmonically and substantially for a specific incidence angle. NOCant corrections yield a better fit of the measurements to the GMF (Geophysical Model Function). Hence, NOCant is applied for the analysis of wind retrieval from the Ku-band and C-band. An extra engineering correction of 0.15 dB and 0.20 dB is applied on Ku-band and C-band backscatter values, respectively, to reduce the wind speed bias without increasing the standard deviation. Overall, NOCant is the best option for both channels. In addition, the instrument backscatter data stability over time is good, and the retrieved winds can fulfill operational requirements. [ABSTRACT FROM AUTHOR]

This paper presents a fully-differential touch screen panel (TSP) self-capacitance sensing (SCS) system with a self-capacitance mismatch calibration technique. Due to the self-capacitance mismatch of TSP, the analog front-end (AFE) of the receiver (RX) circuit suffers from dynamic range degradation and gain limitations, which lead to the signal-to-noise ratio (SNR) loss for the TSP SCS system. The proposed calibration introduces the difference in input resistance and the driving amplifier's strength between the fully-differential input. Thus, the mismatch effect is efficiently relieved in terms of area and power consumption. The proposed calibration restores the SNR by 19.54 dB even under the worst self-capacitance mismatch case. [ABSTRACT FROM AUTHOR]

A variety of low-cost sensors have recently appeared to measure air quality, making it feasible to face the challenge of monitoring the air of large urban conglomerates at high spatial resolution. However, these sensors require a careful calibration process to ensure the quality of the data they provide, which frequently involves expensive and time-consuming field data collection campaigns with high-end instruments. In this paper, we propose machine-learning-based approaches to generate calibration models for new Particulate Matter (PM) sensors, leveraging available field data and models from existing sensors to facilitate rapid incorporation of the candidate sensor into the network and ensure the quality of its data. In a series of experiments with two sets of well-known PM sensor manufacturers, we found that one of our approaches can produce calibration models for new candidate PM sensors with as few as four days of field data, but with a performance close to the best calibration model adjusted with field data from periods ten times longer. [ABSTRACT FROM AUTHOR]

This paper studies the effect of reference frame selection in sensor-to-sensor extrinsic calibration when formulated as a motion-based hand–eye calibration problem. As the sensor trajectories typically contain some composition of noise, the aim is to determine which selection strategies work best under which noise conditions. Different reference selection options are tested under varying noise conditions in simulations, and the findings are validated with real data from the KITTI dataset. The study is conducted for four state-of-the-art methods, as well as two proposed cost functions for nonlinear optimization. One of the proposed cost functions incorporates outlier rejection to improve calibration performance and was shown to significantly improve performance in the presence of outliers, and either match or outperform the other algorithms in other noise conditions. However, the performance gain from reference frame selection was deemed larger than that from algorithm selection. In addition, we show that with realistic noise, the reference frame selection method commonly used in the literature, is inferior to other tested options, and that relative error metrics are not reliable for telling which method achieves best calibration performance. [ABSTRACT FROM AUTHOR]

A novel visual 3D reconstruction system, composed of a two-axis galvanometer scanner, a camera with a lens, and a set of control units, is introduced in this paper. By changing the mirror angles of the galvanometer scanner fixed in front of the camera, the boresight of the camera can be quickly adjusted. With the variable boresight, the camera can serve as a virtual multi-ocular system (VMOS), which captures the object at different perspectives. The working mechanism with a definite physical meaning is presented. A simple and efficient method for calibrating the intrinsic and extrinsic parameters of the VMOS is presented. The applicability of the proposed system for 3D reconstruction is investigated. Owing to the multiple virtual poses of the camera, the VMOS can provide stronger constraints in the object pose estimation than an ordinary perspective camera does. The experimental results demonstrate that the proposed VMOS is able to achieve 3D reconstruction performance competitive with that of a conventional stereovision system with a much more concise hardware configuration. [ABSTRACT FROM AUTHOR]

In the vision-based inspection of specular or shiny surfaces, we often compute the camera pose with respect to a reference plane by analyzing images of calibration grids, reflected in such a surface. To obtain high precision in camera calibration, the calibration target should be large enough to cover the whole field of view (FOV). For a camera with a large FOV, using a small target can only obtain a locally optimal solution. However, using a large target causes many difficulties in making, carrying, and employing the large target. To solve this problem, an improved calibration method based on coplanar constraint is proposed for a camera with a large FOV. Firstly, with an auxiliary plane mirror provided, the positions of the calibration grid and the tilt angles of the plane mirror are changed several times to capture several mirrored calibration images. Secondly, the initial parameters of the camera are calculated based on each group of mirrored calibration images. Finally, adding with the coplanar constraint between each group of calibration grid, the external parameters between the camera and the reference plane are optimized via the Levenberg-Marquardt algorithm (LM). The experimental results show that the proposed camera calibration method has good robustness and accuracy. [ABSTRACT FROM AUTHOR]

Calibration of the existing building simulation model is key to correctly evaluating the energy savings that are achievable through retrofit. However, calibration is a non-standard phase where different approaches can possibly lead to different models. In this study, an existing residential building is simulated in parallel by four research groups with different dynamic simulation tools. Manual/automatic methodologies and basic/detailed measurement data sets are used. The calibration is followed by a validation on two evaluation periods. Monitoring data concerning the windows opening by the occupants are used to analyze the calibration outcomes. It is found that for a good calibration of a model of a well-insulated building, the absence of data regarding the users' behavior is more critical than uncertainty on the envelope properties. The automatic approach is more effective in managing the model complexity and reaching a better performing calibration, as the RMSE relative to indoor temperature reaches 0.3 °C compared to 0.4–0.5 °C. Yet, a calibrated model's performance is often poor outside the calibration period (RMSE increases up to 10.8 times), and thus, the validation is crucial to discriminate among multiple solutions and to refine them, by improving the users' behavior modeling. [ABSTRACT FROM AUTHOR]

Detection of the Doppler shift of airglow radiation in the middle and upper atmosphere is one of the most important methods for remote sensing of the atmospheric wind field. Laboratory and routine field calibration of an optical interferometer for wind measurement is very important. We report a novel calibration system that simulates a frequency shift of airglow emission lines introduced by wind in the middle and upper atmosphere for calibrating passive optical interferometers. The generator avoids the shortcomings of traditional motor-driven Doppler-shift generators in terms of stability and security while improving accuracy and simplifying assemblies. A simulated wind speed can be determined simultaneously using the light-beat method. The wind error simulated by the generator mainly comes from the light source, which is about 0.63 m/s. An experimental demonstration was conducted using a calibrated Fabry–Perot interferometer and showed that the root mean square of the measurement uncertainty is 0.91 m/s. The novel calibration system was applied to calibrate an asymmetric spatial heterodyne spectrometer (ASHS)-type interferometer successfully. The results demonstrate the feasibility of the system. [ABSTRACT FROM AUTHOR]

To improve the confidence and quality of measurements produced by regional and international infrasound monitoring networks, this work investigates a methodology for propagating uncertainty associated with on-site measurement systems. We focus on the propagation of sensor calibration uncertainties. The proposed approach is applied to synthetic infrasound signals with known back azimuth and trace velocity, recorded at the array elements. Relevant input uncertainties are investigated for propagation targeting the incoming signals (noise), instrumentation (microbarometers, calibration system, wind noise reduction system), and the time-delay-of-arrival (TDOA) model (frequency band). Uncertainty propagation is performed using the Monte Carlo method to obtain the corresponding uncertainties of the relevant output quantities of interest, namely back azimuth and trace velocity. The results indicate that, at high frequencies, large sensor uncertainties are acceptable. However, at low frequencies (<0.1 Hz), even a 2 ∘ sensor phase uncertainty can lead to errors in the back azimuth of up to 5 ∘ and errors in the trace velocity of 20 m/s. [ABSTRACT FROM AUTHOR]

The calibration of channel imbalances is currently the main concern in polarimetric calibration (POLCAL) since the crosstalk of recent polarimetric synthetic aperture radar (Pol-SAR) systems is lower than −20 dB. The existing channel imbalance calibration method without corner reflectors utilizes both volume-dominated and Bragg-like targets. However, there are two limitations to using volume-dominated targets. One is that the inaccurate selection of volume-dominated areas in the uncalibrated Pol-SAR images has a negative influence on the estimation of cross-polarization (x-pol) channel imbalance, which subsequently impacts the estimation of copolarization (copol) channel imbalance. The other is that there are minimal volume-dominated areas in some special applications of Pol-SAR, such as planetary exploration. Thus, only selecting Bragg-like targets to estimate the values of both transmitting and receiving channel imbalances, which is proposed in this paper, can avoid the uncertainty brought about by selecting other distributed targets in an uncalibrated imaginary. In addition, the reciprocity assumption and characteristics corresponding to H/ α ¯  decomposition are introduced to eliminate the phase ambiguity for the first time. Compared with previous methods, our method had an obvious advantage in terms of universality, since Bragg-like targets are common in the most illuminating areas. The novel method was applied to both the simulated data from the L-band Advanced Land Observing Satellite (ALOS) and C-band GaoFen-3 (GF-3), and to real data with corner reflectors on site. The results from the simulated data showed that the errors of the amplitude and phase estimation were less than 0.5 dB and 5.0° in most topographical features. Meanwhile, the  V V / H H  terms from all trihedral corner reflectors were less than 0.3 dB for amplitude, and 5.5° for phase after calibration by using the estimated channel imbalances. [ABSTRACT FROM AUTHOR]

Recent works have made strong efforts to produce standardised photometry in RGB bands. For this purpose, we carefully defined the transmissivity curves of RGB bands and defined a set of standard sources using the photometric information present in Gaia EDR3. This work aims not only to significantly increase the number and accuracy of RGB standards but also to provide, for the first time, reliable uncertainty estimates using the BP and RP spectrophotometry published in Gaia DR3 instead of their integrated photometry to predict RGB photometry. Furthermore, this method allows including calibrated sources regardless of how they are affected by extinction, which was a major shortcoming of previous work. The RGB photometry is synthesised from the Gaia BP and RP low-resolution spectra by directly using their set of coefficients multiplied with some basis functions provided in the Gaia catalogue for all sources published in Gaia DR3. The output synthetic magnitudes are compared with the previous catalogue of RGB standards available. [ABSTRACT FROM AUTHOR]

Comparison across somatosensory domains, important for clinical and scientific goals, requires prior calibration of impairment severity. Provided test score distributions are comparable across domains, valid comparisons of impairment can be made by reference to score locations in the corresponding distributions (percentile rank or standardized scores). However, this is often not the case. Test score distributions for tactile texture discrimination (n = 174), wrist joint proprioception (n = 112), and haptic object identification (n = 98) obtained from pooled samples of stroke survivors in rehabilitation settings were investigated. The distributions showed substantially different forms, undermining comparative calibration via percentile rank or standardized scores. An alternative approach is to establish comparable locations in the psychophysical score ranges spanning performance from just noticeably impaired to maximally impaired. Several simulation studies and a theoretical analysis were conducted to establish the score distributions expected from completely insensate responders for each domain. Estimates of extreme impairment values suggested by theory, simulation and observed samples were consistent. Using these estimates and previously discovered values for impairment thresholds in each test domain, comparable ranges of impairment from just noticeable to extreme impairment were found. These ranges enable the normalization of the three test scales for comparison in clinical and research settings. [ABSTRACT FROM AUTHOR]

AOTF calibration is a complex topic that has various aspects. As far as geometric calibration is concerned, it includes not only processing errors and fixing errors in the optical system, but also the error of geometric parameters of crystal (GPC). GPC is the preset input in the optical design and optimization of Zemax, which determines the key parameters, including the spatial resolution, the field of view, and aberration. In particular, the compensation of aberration during the optical design requires accurate values of GPC. However, it is currently considered ideal. Therefore, two calibration methods based on the principle of parallel tangent are proposed: (1) the minimum-central wavelength method; (2) the minimum-frequency method. The deviation of the parallel tangent incident angle calibrated by the two methods is 0.03°. As a result, the tuning curve calculated in theory with the calibrated geometric parameters of AOTF is consistent with the tuning curve measured in practice. [ABSTRACT FROM AUTHOR]