Calibration of a modular trap detector system towards a new realisation of the luminous intensity unit

A modular photometric trap detector system has recently been developed at Physikalisch-Technische Bundesanstalt (PTB). All parts of the detector are now completely calibrated. The new planned traceability chain for the realisation of luminous intensity unit can therefore be established for the first time. This contribution shows the results of the individual calibration steps including the associated measurement uncertainties and correlations. A major part of the calibrations along the traceability chain is done at the upgraded measurement setup TULIP (TUnable Lasers In Photometry). The improvements of the TULIP setup are presented and the effects on the measurement uncertainty are shown. The result of the first complete calibration according to the new traceability chain is compared to previous calibration results both in terms of spectral irradiance responsivity and luminous responsivity. The further steps required towards implementing the new traceability chain and the possible implications are discussed.

Application of ImageJ Software in the assessment of flowering Intensity and growth Vigor of pear Trees

The study evaluated the possibility of using the image acquisition and processing method with ImageJ software for estimating growth vigor and flowering intensity of ‘Conference’ pear trees. For assessing flowering intensity, manual counting of flower clusters and taking of photographs of the trees were conducted at full bloom. Tree vigor was estimated by manually measuring the total length of the central leader and shoots of individual trees. The trees were photographed from the same distance using a hand-held camera. The calibration model for assessing the vigor or flowering of trees by image analysis was based on measurements and photographs taken for nine selected trees differing in the total length of shoots or in the number of flower clusters. Then, a quality assessment of the model was carried out on 26 nonselected trees. Image processing was performed using ImageJ software. High regression coefficients were obtained between the surface area of petals measured on the photographs and the number of inflorescences counted (r2 = 0.98); however, observations carried out in the following year indicate the need for individual calibration of estimation models in each evaluation season. Subsequently, the quality of estimating the flowering intensity of pear trees was assessed using a previously determined calibration model. Mean absolute percentage error (MAPE) values ranged from 14.0% to 21.8%, depending on the measurement time. In the assessment of tree growth vigor, a high correlation (r2 = 0.98) was also obtained between the actual length of shoots measured individually for each tree and the values obtained by analyzing the photographic image, where the MAPE error was 12.9%.

Factory Oriented Technique for Thermal Drift Compensation in MEMS Capacitive Accelerometers

Capacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve their performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated using a lightweight algorithm by knowing the characteristic thermal parameters of the accelerometer (Temperature Drift of Bias and Temperature Drift of Scale Factor). These parameters vary in each accelerometer and axis, making an individual calibration necessary. In this work, a simple and fast calibration method that allows the characteristic parameters of the three axes to be obtained simultaneously through a single test is proposed. This method is based on the study of two specific orientations, each at two temperatures. By means of the suitable selection of the orientations and the temperature points, the data obtained can be extrapolated to the entire working range of the accelerometer. Only a mechanical anchor and a heat source are required to perform the calibration. This technique can be scaled to calibrate multiple accelerometers simultaneously. A lightweight algorithm is used to analyze the test data and obtain the compensation parameters. This algorithm stores only the most relevant data, reducing memory and computing power requirements. This allows it to be run in real time on a low-cost microcontroller during testing to obtain compensation parameters immediately. This method is aimed at mass factory calibration, where individual calibration with traditional methods may not be an adequate option. The proposed method has been compared with a traditional calibration using a six-sided orthogonal die and a thermal camera. The average difference between the compensations according to both techniques is 0.32 mg/°C, calculated on an acceleration of 1 G; the maximum deviation being 0.6 mg/°C.

PTT-based Contact-less Blood Pressure Measurement using an RGB-Camera

Commonly used blood pressure measurement devices have noticeable limitations in accuracy, measuring time, comfort or safety. To overcome these limitations, we developed and tested a surrogate-based, non-invasive blood pressure measurement method using an RGB-camera. Our proposed method employs the relation between the pulse transit time (PTT) and blood pressure. Two remote photoplethysmography (rPPG) signals at different distances from the heart are extracted to calculate the temporal delay of the pulse wave. In order to establish the correlation between the PTT values and the blood pressure, a regression model is trained and evaluated. Tests were performed with five subjects, where each subject was recorded fifteen times for 30 seconds. Since the physiological parameters of the cardiac system are different for each person, an individual calibration is required to obtain the systolic and diastolic blood pressure from the PTT values. The calibration results are limited by the small number of samples and the accuracy of the reference system. However, our results show a strong correlation between the PTT values and the blood pressure and we obtained a mean error of 0.18 +/- 5.50 mmHg for the diastolic blood pressure and 0.01 +/- 7.71 mmHg for the systolic pressure, respectively.

Calibration and assessment of electrochemical low-cost sensors in remote alpine harsh environments

This work presents results from an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. Our study was conducted at the Col Margherita Observatory (2543 m above sea level), in the Italian Eastern Alps. The sensor system mounts three commercial low-cost O3/NO2 sensors that have been calibrated before field deployment against a laboratory standard (Thermo Scientific; 49i-PS), calibrated against the standard reference photometer no. 15 calibration scale of the World Meteorological Organization (WMO). Intra- and intercomparison between the sensors and a reference instrument (Thermo Scientific; 49c) have been conducted for 7 months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. We showed that it is possible to reduce the bias of one LCS by using the average coefficient values of another LCS working in tandem, suggesting a way forward for the development of remote field calibration techniques. We showed that it is possible reconstruct the environmental ozone concentration during the loss of reference instrument data in situations caused by power outages. The evaluation of the analytical performances of this sensing system provides a limit of detection (LOD) <5 ppb (parts per billion), limit of quantification (LOQ) <17 ppb, linear dynamic range (LDR) up to 250 ppb, intra-Pearson correlation coefficient (PCC) up to 0.96, inter-PCC >0.8, bias >3.5 ppb and ±8.5 at 95 % confidence. This first implementation of a LCS system in an alpine remote location demonstrated how to obtain valuable data from a low-cost instrument in a remote environment, opening new perspectives for the adoption of low-cost sensor networks in atmospheric sciences.

CUFF-LESS MEASUREMENT OF BLOOD PRESSURE BY USING NEURAL NETWORKS

This article attempts to consider a new approach to continuous measurement of blood pressure (BP), based on the pulse propagation time between two points of a blood vessel (PTT). The measuring of PTT based on the signal processing and analysis of the electrocardiogram (ECG), photoplethysmogram (PPG). The PTT-based blood pressure estimation algorithms, used by most authors, suggest their individual calibration for each patient. More flexible is a different approach - the use of machine learning. It is especially noted that the use of machine learning reduce the error in blood pressure measuring.

Intelligent system for measuring the level and mass of liquid in fuel tanks and tanks during pitching and tilting

An overview of the existing methods for measuring the liquid level and their disadvantages in the case of surface vibrations is presented. A system for continuous measurement of the mass of liquids in fuel tanks and tanks during rolling and tilting of vehicles and ships, implemented in a level gauge based on intelligent sensors, is proposed. The sensors include a microcontroller with an individual calibration characteristic of the volume-level dependence, taking into account the shape of the tank or fuel tank, and nanosensors built into the intelligent sensor (ID) for measuring density, permittivity and ambient temperature. It is established that the actual metrological characteristics of the ID are significantly higher than the characteristics of traditional sensors. The number and dimensions of the plates of flat capacitors are justified and the scheme of their arrangement on the roof of the tanks is presented. The exclusion of movable elements increased the reliability of operation, simplified maintenance and design requirements of the measuring object. Analytical expressions for calculating the level and mass of the liquid, implemented by the microcontroller, are given. The use of the proposed measurement system with complex computational processing and taking into account corrections for temperature, density, humidity and permittivity of the liquid made it possible to increase the accuracy and stability of the level meter readings. Analytical expressions are derived that relate the liquid level and the output frequency of the generator from the composition of the level gauge.

Subject-Independent Functional Near-Infrared Spectroscopy-Based Brain–Computer Interfaces Based on Convolutional Neural Networks

Functional near-infrared spectroscopy (fNIRS) has attracted increasing attention in the field of brain–computer interfaces (BCIs) owing to their advantages such as non-invasiveness, user safety, affordability, and portability. However, fNIRS signals are highly subject-specific and have low test-retest reliability. Therefore, individual calibration sessions need to be employed before each use of fNIRS-based BCI to achieve a sufficiently high performance for practical BCI applications. In this study, we propose a novel deep convolutional neural network (CNN)-based approach for implementing a subject-independent fNIRS-based BCI. A total of 18 participants performed the fNIRS-based BCI experiments, where the main goal of the experiments was to distinguish a mental arithmetic task from an idle state task. Leave-one-subject-out cross-validation was employed to evaluate the average classification accuracy of the proposed subject-independent fNIRS-based BCI. As a result, the average classification accuracy of the proposed method was reported to be 71.20 ± 8.74%, which was higher than the threshold accuracy for effective BCI communication (70%) as well as that obtained using conventional shrinkage linear discriminant analysis (65.74 ± 7.68%). To achieve a classification accuracy comparable to that of the proposed subject-independent fNIRS-based BCI, 24 training trials (of approximately 12 min) were necessary for the traditional subject-dependent fNIRS-based BCI. It is expected that our CNN-based approach would reduce the necessity of long-term individual calibration sessions, thereby enhancing the practicality of fNIRS-based BCIs significantly.

Calibration and assessment of electrochemical low-cost sensors in remote alpine harsh environments

The present work presents the results obtained using an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. We conducted our study at the Col Margherita Observatory (2543 m a.s.l.), a World Meteorological Organization Global Atmosphere Watch Regional Station, located in the Italian Eastern Alps. The sensing system mounts three equivalent commercial low-cost sensors that have been calibrated using a laboratory standard (Thermo 49iPS), referenced to the Standard Reference Photometer #15 calibration scale by the WMO, before field deployment. Intra and inter-comparison between sensors and reference (Thermo 49c) have been conducted for seven months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. The evaluation of the analytical performances of this sensing system provides an LOD 3.5 ppb and ±8.5 at 95 % of confidence. Thanks to the first implementation of an LCS System in an alpine site, it has been demonstrated how it is possible to obtain valuable data from a low-cost instrument in a remote environment. This opens new perspectives for the adoption of a low-cost sensor network in atmospheric sciences.

Content of double bonds in polyethylene

The content of double bonds in high-pressure polyethylene of various brands obtained from Russian and foreign manufacturers was studied. The essence of the method was to build a calibration curve on an infrared Fourier spectrometer for standard substances with a previously known arrangement of the double bond, saturation of double bonds in the initial polyethylene using gaseous bromine, and subsequent assessment of the locations and number of double bonds in the studied brands of high pressure polyethylene. The calibration substances were trans-4-decene with a purity of 96%, 1-decene with a purity of 95%, and 2-methyl-1-heptene with a purity of 98%. To record infrared spectra, calibration substances were dissolved in carbon disulfide with a purity of 99.5%. The spectra of the calibration substances were recorded in the transmission mode. The recording of the spectra of the high-pressure polyethylene samples was carried out in the reflection mode. To calculate the molar adsorption coefficient of individual calibration substances, the areas of the peak absorption of individual substances were allocated. The Peak Separation NETZSCH software was used for this purpose. For all analyzed samples, both brominated and not brominated, the ratio of the areas of absorption peaks was calculated. For each sample of high-pressure polyethylene, the content of trans-vinylidene, vinyl, and vinylidene groups C=C per 1000 carbon atoms was determined. The total number of double bonds was calculated as the sum of all analyzed bonds contained in the polyethylene sample. The accuracy of the analysis method performed by a single laboratory on a single sample is ±10% of double bonds per 1000 carbon atoms. The technique allows one to evaluate such a characteristic of low density polyethylene as the content of double bonds. This characteristic is essential for the efficient development of crosslinkable polyethylene compounds.