Results Of Real Measurements Research Articles

Methodology of integrated measurements with radon diffusion chamber

Calibration of Solid-State Nuclear Track Detectors - SSNTD in the diffusion chamber in most cases assumes a constant radon concentration outside the diffusion chamber and a steady state. Although this has been proven to be a valid approximation in most cases, the fact is that the radon concentration outside the chamber is not constant. In this way, the detectors are calibrated to measure the mean radon concentration. For this reason, there is doubt if the time-dependent concentration in dwellings results in the same number of tracks on the detector as the time-averaged radon concentration for the same exposure period. To obtain an answer, time-dependent and steady-state diffusion equations for radon and its progeny were solved. Then the number of tracks on the detector was calculated for these two cases and compared. For that goal, software for solving the time-dependent diffusion equation for time-varying external radon concentration was developed. Results show that concentrations measured using a diffusion chamber are the real concentrations at the measuring site. However, it was also found that the validity of results is not a universal property, as shown in the current paper. In some cases, results can be wrong. For some extreme conditions when diffusion coefficients are disrupted calibration using stationary conditions model will lead to incorrect results of real measurements in experiments where ambiental concentration is time-varying.

Operator dependence of methods for obtaining metric characteristics of a face with real measurements and digital images

BACKGROUND: No studies in the scientific literature have established the operator dependence of portrait identification with the manual method of measuring facial parameters in subjects compared with measurements from digital images. The labor costs and accuracy of the measurements with these methods have not been established.
 AIM: To establish the operator dependence of methods of real-face measurement and measurement on digital images.
 MATERIALS AND METHODS: Facial parameters were instrumentally measured in 24 Caucasian women aged 19–20 years who were studying at the Professor V.F. Voino-Yasenetsky Krasnoyarsk State Medical University by four researchers independently of each other. The same type of standard digital photography of each subject’s face was taken in five projections, followed by a comparison of the results of real measurements with digital ones.
 RESULTS: When comparing the results of facial measurements obtained from digital images and manual method, an error was observed both in the measurements of one parameter by one researcher using two methods and in the excellent results obtained by other researchers. However, the greatest deviations were observed with the manual method, which may be due to the dependence of measurements on the operator.
 CONCLUSION: With a streamlined and methodically verified approach to working with digital facial images, this technique is more accurate and less labor-intensive than real measurements because of the absence of operator dependence, which can be used in investigating crimes.

APPLICATION OF TEMPERATURE DEPENDENCE OF PARAMETERS IN A SINGLE-DIODE TWO-RESISTORS MODEL OF SOLAR PANEL WITH PARALLEL CONNECTED CELLS

The need to take into account the temperature dependences of parallel and series resistances in the model of solar panels has been repeatedly proven in our previous works․ In the previous works, it can be seen how the inclusion of the temperature dependences of the specified elements in the model clearly improves the obtained I-V (current-voltage) characteristics, bringing them closer to the real characteristics given by the datasheet of the given panels. The improvement is evident not only from the obtained curves but also from the most important parameters calculated from them, such as root mean square deviation (RMSD) and the maximum power point (MPP). The latter almost perfectly coincide with the results of real measurements. However, until now, we have studied only the cases of sequential connection of solar modules. In this work, we have applied the same method to the parallel circuit panel, in particular, we have applied the improved model to the simulation of the VDS-S144/M10H solar panel module in which the solar cells are connected in parallel. The purpose of this experiment is to once again prove the repeatability of the method regardless of the panel model and the way (serial or parallel) the cells are connected.

FDTD Simulation to Investigate the Effect of Nanopattern on Light Extraction Distribution of ZnS:Cu LED

Light Emitting Diode (LED) technology is very common in everyday life. Due to the large refractive index difference between LED material and air, many excited photons from the active layer cannot be passed on to the air, thereby Total Internal Reflection (TIR) will occur and reducing the Light Extraction Efficiency (LEE) of LED. The use of nanopatterns on the LED surface can help trapped photons to get out of the LED by changing the direction and angle of photons’ propagation. Because the shape of the nanopattern will affect the increase in the LEE of LEDs and its fabrication is expensive, simulations are needed to design and study the effect of the shape and size of the nanopattern on the LEE of LEDs. In this study, FDTD simulations will be carried out on nano-sized grating patterns on the ZnS:Cu LED surface and then compared with experimental results to see the accuracy of the simulation results using Ansys Lumerical FDTD. The simulation results obtained in light emission distribution are consistent with the real measurement results. The simulation results are also used to evaluate the performance of the LEDs with and without the nanopattern on the surface.

An Advanced Energy-Efficient Environmental Monitoring in Precision Agriculture Using LoRa-Based Wireless Sensor Networks.

Sensor networks, as a special subtype of wireless networks, consist of sets of wirelessly connected sensor nodes often placed in hard-to-reach environments. Therefore, it is expected that sensor nodes will not be powered from the power grid. Instead, sensor nodes have their own power sources, the replacement of which is often impractical and requires additional costs, so it is necessary to ensure minimum energy consumption. For that reason, the energy efficiency of wireless sensor networks used for monitoring environmental parameters is essential, especially in remote networking scenarios. In this paper, an overview of the latest research progress on wireless sensor networks based on LoRa was provided. Furthermore, analyses of energy consumption of sensor nodes used in agriculture to observe environmental parameters were conducted using the results of real measurements in the field, as well as simulations carried out based on collected data about real equipment. Optimization methods of energy consumption, in terms of choosing the appropriate data collection processes from the conducted field measurements, as well as the settings of network radio parameters imitating real conditions used in conducted simulations were highlighted. In the analyses, special emphasis was placed on choosing the optimal packet size. Unlike in other papers analyzing energy efficiency of LoRa communication, in this paper, it was proven that the adjustment of the transmission speed to the actual size of the packet is important for better energy efficiency of communication and that it can reduce energy consumption considerably. Moreover, in the paper, the contents of a packet that can be used in precision agriculture is suggested in order to prove that the 6-bit packet is sufficient for energy-efficient collection of parameters from the environment, in contrast to the 11-bit packets used in standard commercially available equipment.

Experimental characterization, parameter identification and numerical sensitivity analysis of a novel hybrid sensible/latent thermal energy storage prototype for industrial retrofit applications

Hybrid design combinations of sensible and latent heat thermal energy storage (TES) leverage the advantages and reduce the disadvantages of both types. Thus, the range of application of said individual storage types is extended and crucial retrofit opportunities are enabled. Such hybrid TES concept consisting of a Ruths steam storage (RSS) and a surrounding layer of storage containers filled with an eutectic mixture of sodium nitrate (NaNO3) and lithium nitrate (LiNO3) as phase change material (PCM) was for the first time realized and investigated during operation in a steel production plant.In this work, the hybrid TES prototype is characterized with the help of detailed modelling and real measurement results. Uncertain model parameters are identified via parameter optimization and the numerical models show satisfactory validation results. Additional 30% of thermal energy could be stored in the PCM containers retrofitted to the lab-scale RSS. Charging/discharging times and specific thermal power of the PCM containers were roughly measured as 8h and 12h and 560kWm−3/−802kWm−3, respectively, in the typical operation region. A sensitivity analysis of the performance indicators reveals potential but also engineering challenges for following generations of the hybrid TES concept. Compared to the achieved experimental results, charging/discharging power could be increased by up to 10 and 5 times, respectively, in the future by adequate measures to increase heat transfer between both storage types.

Indoor environmental quality in green certified office buildings

The presented paper deals with the assessment of selected indoor environmental quality (IEQ) factors, specifically the parameters of thermal comfort and indoor air quality (IAQ), in two buildings of a modern office complex. Both buildings are LEED certified. The monitoring of selected IEQ risk factors took place in selected office spaces (cell and open-space offices) representative of all occupied areas under operating conditions. The results of real measurements of IAQ parameters indicate that the monitored office spaces in both buildings did not exceed the required limits set by the LEED certification system. The measured parameters of thermal comfort were within the permissible legislative limits and the results of Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) indices show that a suitable level of thermal comfort can be expected in the given buildings during their occupancy. Based on the results of real measurements, it can be stated that both office buildings actually meet the LEED criteria for IAQ and guarantee a healthy and comfortable working environment for their occupants.

Three-Axis Capacitive Sensor Arrays for Local and Global Shear Force Detection

We report the real time characterization and measurement results of a new tri-axial capacitive sensing array. Each unit cell of the Kapton based sensor has an overlapping electrode geometry that allows for the measurement of normal and shear force magnitudes, and the estimation of the 2D and 3D angle of the shear force. The use of a patterned Ecoflex dielectric layer further improves the shear force response and the tunability of the sensor. A custom readout circuit was developed to selectively read the differential capacitances in the sensor array. The local (unit cell) and global (array) force response of the sensor was characterized using a tilt stage, allowing us to determine both the normal and the shear response at different angles in the range of 0-20N. The results show that the Unit Cell response is uniform in the linear range of 0-10N for normal forces (4.6fF/N for all four differential capacitances) and shows good sensitivity for shear forces (1.4 fF/N difference between the right and left differential capacitances at the minimum) and low cross talk. Similar results were seen when a global force was applied across the sensor array. 2D and 3D models were developed to extrapolate the shear force angle from the capacitance data. We also characterized the flexible patterned dielectric layer to understand the effect of its structural dimensions on the effective relative permittivity and developed an analytical model to easily calculate the effective relative permittivity, which showed excellent correlation with the experimentally obtained results. [2020-0382]

Illumination Correction of Multi-Time RGB Images Obtained with an Unmanned Aerial Vehicle

The goal of this research was to study and optimize multi-temporal RGB images obtained by a UAV (unmanned aerial vehicle). A digital camera onboard the UAV allows obtaining data with a high temporal and spatial resolution of ground objects. In the case considered by us, the object of study is agricultural fields, for which, based on numerous images covering the agricultural field, image mosaics (orthomosaics) are constructed. The acquisition time for each orthomosaic takes at least several hours, which imposes a change in the illuminance of each image, when considered separately. Orthomosaics obtained in different periods of the year (several months) will also differ from each other in terms of illuminance. For a comparative analysis of different parts of the field (orthomosaic), obtained in the same time interval or comparison of areas for different periods of time, their alignment by illumination is required. Currently, the majority of alignment approaches rely rather on colour (RGB) methods, which cannot guarantee finding efficient solutions, especially when it is necessary to obtain a quantitative result. In the paper, a new method is proposed that takes into account the change in illuminance during the acquisition of each image. The general formulation of the problem of light correction of RGB images in terms of assessing the colour vegetation index Greenness is considered. The results of processing real measurements are presented.

An Underwater Acoustic Channel Modeling for Internet of Things Networks

Interest in wideband and medium distance underwater acoustic communication systems is increasing due to the practical application of underwater Internet of Things (IoT) networks. In this paper, we propose a simplified empirical channel model for the medium distance underwater acoustic channels based on real measurement results. The simple and tractable channel model is critical for the development of advanced underwater communications technology. The underwater channel measurements were performed at 20 m sea water depth, the transmitters (TXs) were located at 5 m and 15 m from the bottom, the receivers (RXs) were located at 4 m, 8 m, 12 m, and 16 m from the bottom, and the TX–RX distances were 21 m, 71 m, 127 m, and 273 m. We derived the path loss from the measured dataset, and modified the log-distance model to create a model suitable for an underwater IoT channel. Numerical results show that the proposed model is accurate and reliable enough to use in the development of advanced underwater communication technologies.

К настройке алгоритма вычисления барометрической высоты летательного аппарата системой воздушных сигналов

Introduction. In conditions of increasing requirements for the accuracy of determining the altitude and speed parameters of aircraft, the task of tuning up the algorithmic support of their air signal systems (SHS) based on real flight data is quite relevant. Aim. Consider the task of assessing the real value of the temperature gradient along the height of the atmosphere for the purpose of operational adjustment of the standard algorithmic support of SHS. Materials and methods. The traditional approach is to use the numerical value of the temperature gradient, adopted for the international standard atmosphere (ISA). A feature of the proposed approach is that the temperature gradient in height is determined by current measurements of atmospheric pressure and temperature, and not height and temperature. Results. Adaptive and non-adaptive parametric identification algorithms are developed. An improved version of the adaptive algorithm is proposed, which ensures proper tuning of its filtering properties to a specific statistical situation. Algorithms were tested both according to the characteristics of the ISA using computer-generated random interference, and according to the results of real measurements known in the literature obtained using a meteorological rocket. The properties of adaptive and non-adaptive algorithms are compared. It is shown that repeated “running” of the same experimental data through an adaptive algorithm leads to almost the same accuracy of the gradient estimate, as when using a non-adaptive algorithm. Conclusion. The implementation of the algorithms improves the accuracy of determining the barometric altitude of the aircraft (AC), does not require any modernization of the hardware of the SHS, only some addition of the algorithmic support of the system is necessary. The adaptive algorithm is recommended for use in the case of a significant drift of atmospheric characteristics for the operational adjustment of the system.

Validation of land management information system model (SILAHAN) on plot scale, case study in Citaman, Nagreg, West Java

Upland has potential uses for agriculture practices in indonesia. However there are some problems to manage, one of them is many existing upland in sloping areas and high risk to erosion and runoff. Indonesian Soil Research Institute developed a recommendation model for the land management information system (SILAHAN) based on the study of criteria for soil conservation indicators with calculation of erosion hazard index and surface runoff. The aim of this study was to validation SILAHAN prediction models from surface runoff aspects on a plot scale as the basis for formulating recommendations for the most complex land management technology. Validation of the prediction results of surface runoff in SILAHAN model is done by comparing surface runoff results of real measurements in field with the results of predicted by SILAHAN with three simulation. The results of statistical tests with r pearson correlation coefficient is 0,31, 0,31, and 0,32, PBias is -90,6, -86,6 and -83,5, and NSE is -0,76, -0,68, and -0,63. The results of the prediction of plot scale surface runoff in the SILAHAN model were not same as the measurements result on the field observations. it is suggested to determine the correction factors and development capabilities of the SILAHAN model to assess the effectiveness of a land management system in reducing the amount of surface runoff.

Energy-Aware CPU Frequency Scaling for Mobile Video Streaming

The energy consumed by video streaming includes the energy consumed for data transmission and CPU processing, which are both affected by the CPU frequency. High CPU frequency can reduce the data transmission time but it consumes more CPU energy. Low CPU frequency reduces the CPU energy but increases the data transmission time and then increases the energy consumption. In this paper, we aim to reduce the total energy of mobile video streaming by adaptively adjusting the CPU frequency. Based on real measurement results, we model the effects of CPU frequency on TCP throughput and system power. Based on these models, we propose an Energy-aware CPU Frequency Scaling (EFS) algorithm which selects the CPU frequency that can achieve a balance between saving the data transmission energy and CPU energy. Since the downloading schedule of existing video streaming apps is not optimized in terms of energy, we also propose a method to determine when and how much data to download. Through trace-driven simulations and real measurement, we demonstrate that the EFS algorithm can reduce 30 percent of energy for the Youtube app, and the combination of our download method and EFS algorithm can save 50 percent of energy than the default Youtube app.

Exploiting the T(x) function in fast hysteresis models for transient circuit simulations

PurposeThe purpose of this paper is to investigate an alternative to established hysteresis models.Design/methodology/approachDifferent mathematical representations of the magnetic hysteresis are compared and some differences are briefly discussed. After this, the application of the T(x) function is presented and an inductor model is developed. Implementation details of the used transient circuit simulator code are further discussed. From real measurement results, parameters for the model are extracted. The results of the final simulation are finally discussed and compared to measurements.FindingsThe T(x) function possesses a fast mathematical formulation with very good accuracy. It is shown that this formulation is very well suited for an implementation in transient circuit simulator codes. Simulation results using the developed model are in very good agreement with measurements.Research limitations/implicationsFor the purpose of this paper, only soft magnetic materials were considered. However, literature suggests, that the T(x) function can be extended to hard magnetic materials. Investigations on this topic are considered as future work.Originality/valueWhile the mathematical background of the T(x) function is very well presented in the referenced papers, the application in a model of a real device is not very well discussed yet. The presented paper is directly applicable to typical problems in the field of power electronics.

Implementation of machine learning based real time range estimation method without destination knowledge for BEVs

In this work, an advanced range estimation method based on experimental test data including environmental factors and dynamic vehicle parameters with driver and road type predictions is proposed for electric vehicles.The focus point of the given study is to predict remaining range in general, at first start-up, without knowing future driving profile, in terms of giving an idea of how much distance can be travelled with the remaining amount of energy. Road type and driver profile are estimated by utilizing decision tree method and periodogram of jerk trace, respectively. Based on the preliminary results, utilized decision tree algorithm classifies the road type with an accuracy over 98%.Vehicle range is estimated online by using machine learning algorithm based on experimental train data sets where chassis dynamometer tests were conducted by performing specific driving cycle in various conditions. For a real life verification, the vehicle is driven for a 50.4 km distance in a road having mostly urban driving characteristics. The results of real life measurements show that the proposed method predicts range with a low margin of error and estimates final remaining capacity 11.3% better than rated one.

Validation of advanced grid functions of battery storage systems through a controller hardware-in-the-loop setup

In order to evaluate and validate new distributed energy resources (DER) by means of controller hardware-in-the-loop (c-HIL) methods, the power electronics part is modelled within a real-time system and is connected to the control panel via a customized interface. Such a setup allows advanced testing of the control system of a DER converter and its high-level grid functions (e.g. Q(U) or P(f) functions), without any safety concern, and with the possibility of testing against conditions that rarely happen in the field. This paper describes the validation of a battery storage system with advanced grid functions using a c-HIL approach. Therefore, a laboratory and field trial setup are used and validated against real measurement results, which is also presented in this paper.

Vital Sign Monitoring and Cardiac Triggering at 1.5 Tesla: A Practical Solution by an MR-Ballistocardiography Fiber-Optic Sensor.

This article presents a solution for continuous monitoring of both respiratory rate (RR) and heart rate (HR) inside Magnetic Resonance Imaging (MRI) environments by a novel ballistocardiography (BCG) fiber-optic sensor. We designed and created a sensor based on the Fiber Bragg Grating (FBG) probe encapsulated inside fiberglass (fiberglass is a composite material made up of glass fiber, fabric, and cured synthetic resin). Due to this, the encapsulation sensor is characterized by very small dimensions (30 × 10 × 0.8 mm) and low weight (2 g). We present original results of real MRI measurements (conventionally most used 1.5 T MR scanner) involving ten volunteers (six men and four women) by performing conventional electrocardiography (ECG) to measure the HR and using a Pneumatic Respiratory Transducer (PRT) for RR monitoring. The acquired sensor data were compared against real measurements using the objective Bland–Altman method, and the functionality of the sensor was validated (95.36% of the sensed values were within the ±1.96 SD range for the RR determination and 95.13% of the values were within the ±1.96 SD range for the HR determination) by this means. The accuracy of this sensor was further characterized by a relative error below 5% (4.64% for RR and 4.87% for HR measurements). The tests carried out in an MRI environment demonstrated that the presence of the FBG sensor in the MRI scanner does not affect the quality of this imaging modality. The results also confirmed the possibility of using the sensor for cardiac triggering at 1.5 T (for synchronization and gating of cardiovascular magnetic resonance) and for cardiac triggering when a Diffusion Weighted Imaging (DWI) is used.

The quality standardization in suburban bus transport by the transformation of the service quality loop

Abstract The article is dealing with the standardization of quality level in total approach it means the transformation of the service quality loop by STN EN 13816. The quality loop reflects the rating of the service provided from the point of view of the customer as well as from the operators (authorities) point of view. Individual quality aspects are closely related. The aim is to minimize the differences between the expected and the provided quality in order to stabilize the passenger demand. The article includes the possible approaches and methods for determining the standard service quality level in suburban bus transport which are based on the results of real measurements in Žilina self-governing region in specific years.

Estimation of Power System Inertia From Ambient Wide Area Measurements

This study presents a method of estimating the effective inertia of a power system from ambient frequency and active power signals measured by phasor measurement units. Most importantly, we demonstrate that inertia can be estimated from ambient measurement data, not only from disturbances. This leads to the possibility of monitoring inertia in a close to continuous manner in the time scale of minutes or tens of minutes. The method allows the system to be divided into a number of areas and the effective inertia of each area to be estimated as a separate quantity. In principle, inertia is estimated by observing the dynamics between changes in active power and resulting frequency deviations during normal operation of the system. The method is based on applying system identification on these measurements and extracting inertia values from identified models. Efficacy of the method is demonstrated on results of real measurements from the Icelandic power system.

Comparison of Solar Radiation Intensity Forecasting Using ANFIS and Multiple Linear Regression Methods

Solar radiation forecasting is important in solar energy power plants (SEPPs) development. The electrical energy generated from the sunlight depends on the weather and climate conditions in the area where the SEPPs are installed. The condition of solar irradiation will indirectly affect the electrical grid system into which the SEPPs are injected, i.e. the amount and direction of the power flow, voltage, frequency, and also the dynamic state of the system. Therefore, the prediction of solar radiation condition is very crucial to identify its impact into the system. There are many methods in determining the prediction of solar radiation, either by mathematical approach or by heuristic approach such as artificial intelligent method. This paper analyzes the comparison of two methods, Adaptive Neuro Fuzzy Inference (ANFIS) method, which belongs into the heuristic methods, and Multiple Linear Regression (MLP) method, which uses a mathematical approach. The performance of both methods is measured using the root mean square error (RMSE) and the mean absolute error (MAE) values. The data of the Swiss Basel city from Meteoblue are used to test the performance of the two methods being compared. The data are divided into four cases, being classified as the training data and the data used as predictions. The solar radiation prediction using the ANFIS method indicates the results which are closer to the real measurement results, being compared to the the use MLP method. The average values of RMSE and MAE achieved are 123.27 W/m2 and 90.91 W/m2 using the ANFIS method, being compared to 138.70 W/m2 and 101.56 W/m2 respectively using the MLP method. The ANFIS method gives better prediction performance of 12.51% for RMSE and 11.71% for MAE with respect to the use of the MLP method.