rss_2.0Measurement Science Review FeedSciendo RSS Feed for Measurement Science Review Science Review Feed Approach to Recognise Lung Diseases Using Segmentation and Classification<abstract> <title style='display:none'>Abstract</title> <p>Lung cancer is one of the most common causes of death in people worldwide. One of the key procedures for early detection of cancer is segmentation or analysis and classification or assessment of lung images. Radiotherapists have to invest a lot of effort into the manual segmentation of medical images. To solve this issue, early-stage lung cancer is detected using Computed Tomography (CT) scan images. The proposed system for diagnosing lung cancer is divided into two main components: the first part is an analyser component built on the upper layer of the U-shaped Network Transformer (UNT), and the second component is an assessment component built on the upper layer of the self-supervised network, which is used to categorise the output segmentation component as benign or cancerous. The proposed method provides a powerful tool for the early detection and treatment of lung cancer by combining CT scan data with 2D input. Numerous experiments are conducted to improve the analysis and evaluation of the findings. Using the public dataset, both test and training experiments were conducted. New state-of-the-art performances were achieved with experimental results: an analyser accuracy of 96.9% and an assessment accuracy of 96.98%. The proposed approach provides a new powerful tool for leveraging 2D-input CT scan data for early detection and treatment of lung cancer using a variety of methods.</p> </abstract>ARTICLEtrue Microstrip Feed Hybrid Rectangular Dielectric Resonator Antenna for Wireless Tri-Band Applications<abstract> <title style='display:none'>Abstract</title> <p>This article reports the Modified Microstrip Feed Hybrid Rectangular Dielectric Resonator Antenna (RDRA). The proposed structure has a ground plane with a plus-shaped slot on an FR4 substrate with a height of 1.6 mm and dimensions of 38 mm x 35 mm. The proposed Dielectric resonator antenna is made of a material with 10 as its dielectric constant, and the dimensions of the DR are 19 x 20 x 18 mm<sup>3</sup>. The DR is connected to a modified microstrip feed with an octagonal ring through the plus-shaped slot in the ground. The proposed structure operates in frequencies from 2.60 GHz - 2.74 GHz, 3.12 GHz - 3.37 GHz, and 4.25 GHz - 4.37 GHz. The resonant frequency of the final proposed RDRA is 2.68 GHz, 3.26 GHz, and 4.31 GHz, which covers WLAN, WIMAX and Wireless Avionics Intra-Communications (WAIC) applications, respectively. The entire structure was simulated using the CST microwave studio. The simulated results agree with the measured results and both are presented. The compact size, stable radiation pattern and reasonable gain make this antenna suitable for the proposed applications.</p> </abstract>ARTICLEtrue Experimental Setup for Power Loss Measurement up to 1 kHz using an Epstein Frame at CMI<abstract> <title style='display:none'>Abstract</title> <p>This paper describes an experimental setup used at the Czech Metrology Institute (CMI) to measure the specific power loss of oriented and non-oriented electrical steel sheets up to 1 kHz using an Epstein frame. Special attention is given to a) a description of the hardware that is used, b) a description of the feedback control and measurement software, and c) an analysis of the sources of uncertainty and validation. Calibration expanded uncertainty of (0.5 up to 1.6)% for k = 2 can be achieved with this setup.</p> </abstract>ARTICLEtrue Measurement Method of Oil-Water Two-Phase Flow with High Water Holdup and Low Rate by Phase State Regulation<abstract> <title style='display:none'>Abstract</title> <p>Flow rate and holdup are two essential parameters to describe oil-water two-phase flow. The distribution of oil-water two-phase flow in the pipeline is very uneven, and there is a significant slippage between the phases. This makes it difficult to measure these two flow parameters. In this paper, a new measurement method of flow rate and holdup based on phase state regulation is proposed. The oil-water two-phase flow is adjusted to oil or water single-phase flow according to the time sequence by the phase state regulation, and the oil-water phase interface is measured with a conductance sensor. A wavelet transform based phase inflection point detection model is proposed to detect the oil-water phase change point. The experimental results show that the maximum measurement error of the flow rate of water is 3.73%, the maximum measurement error of the flow rate of oil is 3.68%, and the flow rate measurement repeatability is 0.0002. The accuracy of the measurement holdup is better than 3.23%, and the repeatability of the measurement holdup is 0.0003. The prototype designed based on this method has two advantages. One is that it is small in size, the other is that it does not depend on the accuracy of the sensor. Therefore, it can be widely used in oilfield ground measurement.</p> </abstract>ARTICLEtrue Deep Learning-Based Recognition Model for EEG Enabled Brain-Computer Interfaces Using Motor-Imagery<abstract> <title style='display:none'>Abstract</title> <p>Brain-Computer Interfaces (BCIs) facilitate the translation of brain activity into actionable commands and act as a crucial link between the human brain and the external environment. Electroencephalography (EEG)-based BCIs, which focus on motor imagery, have emerged as an important area of study in this domain. They are used in neurorehabilitation, neuroprosthetics, and gaming, among other applications. Optimal Deep Learning-Based Recognition for EEG Signal Motor Imagery (ODLR-EEGSM) is a novel approach presented in this article that aims to improve the recognition of motor imagery from EEG signals. The proposed method includes several crucial stages to improve the precision and effectiveness of EEG-based motor imagery recognition. The pre-processing phase starts with the Variation Mode Decomposition (VMD) technique, which is used to improve EEG signals. The EEG signals are decomposed into different oscillatory modes by VMD, laying the groundwork for subsequent feature extraction. Feature extraction is a crucial component of the ODLR-EEGSM method. In this study, we use Stacked Sparse Auto Encoder (SSAE) models to identify significant patterns in the pre-processed EEG data. Our approach is based on the classification model using Deep Wavelet Neural Network (DWNN) optimized with Chaotic Dragonfly Algorithm (CDFA). CDFA optimizes the weight and bias values of the DWNN, significantly improving the classification accuracy of motor imagery. To evaluate the efficacy of the ODLR-EEGSM method, we use benchmark datasets to perform rigorous performance validation. The results show that our approach outperforms current methods in the classification of EEG motor imagery, confirming its promising performance. This study has the potential to make brain-computer interface applications in various fields more accurate and efficient, and pave the way for brain-controlled interactions with external systems and devices.</p> </abstract>ARTICLEtrue the Performance of wav2vec Embedding for Parkinson's Disease Detection<abstract> <title style='display:none'>Abstract</title> <p>Speech is one of the most serious manifestations of Parkinson's disease (PD). Sophisticated language/speech models have already demonstrated impressive performance on a variety of tasks, including classification. By analysing large amounts of data from a given setting, these models can identify patterns that would be difficult for clinicians to detect. We focus on evaluating the performance of a large self-supervised speech representation model, wav2vec, for PD classification. Based on the computed wav2vec embedding for each available speech signal, we calculated two sets of 512 derived features, wav2vec-sum and wav2vec-mean. Unlike traditional signal processing methods, this approach can learn a suitable representation of the signal directly from the data without requiring manual or hand-crafted feature extraction. Using an ensemble random forest classifier, we evaluated the embedding-based features on three different healthy vs. PD datasets (participants rhythmically repeat syllables /pa/, Italian dataset and English dataset). The obtained results showed that the wav2vec signal representation was accurate, with a minimum area under the receiver operating characteristic curve (AUROC) of 0.77 for the /pa/ task and the best AUROC of 0.98 for the Italian speech classification. The findings highlight the potential of the generalisability of the wav2vec features and the performance of these features in the cross-database scenarios.</p> </abstract>ARTICLEtrue Effect of Differential Pressure and Permanent Pressure Loss on Multi-Hole Orifice Plate<abstract> <title style='display:none'>Abstract</title> <p>The widely used orifice plate falls under restricted type flow devices, has the highest differential pressure and permanent pressure drop in the ensemble. The objective is to curtail the permanent pressure drop and maintain the differential pressure across the orifice plate, and thereby, the power required to pump the liquid is retrenched. So, three-hole, four-hole and five-hole orifice plates with an identical area to that of the single-hole orifice plate were designed and experiments were carried out. It is observed that the experimental results almost matched with the simulation data. In comparing the performance, the four-hole orifice plate yielded a higher differential pressure and higher-pressure loss. In contrast, the five-hole orifice yielded lower differential pressure and higher-pressure loss compared to the single-hole orifice plate. In case of three-hole orifice plate it performed better than the single-hole orifice with reduced pressure loss and higher differential pressure. It was also found that the power consumed by the pump for pumping was lower for three-hole, four-hole and five-hole orifice plates compared to the single-hole orifice plate. Thus, the three-hole orifice plate performs better than a single-hole orifice plate in terms of higher differential pressure, reduced permanent pressure loss and lower power consumption of the pump.</p> </abstract>ARTICLEtrue Approach to Investigate the Effect of High-Dose Methylprednisolone on Erythrocyte Morphology: White Light Diffraction Microscopy<abstract> <title style='display:none'>Abstract</title> <p>The present study focuses on quantitative phase imaging of erythrocytes with the aim to evaluate the effects of high-dose methylprednisolone (HDMP) on erythrocytes in vivo under physiological conditions in human blood samples. Samples from ten patients, prescribed to be treated with 1000 mg/day intravenous methylprednisolone for 5 days, were analyzed by white light diffraction phase microscopy (WDPM) for quantitative imaging. WDPM, an optical measurement technique, enables single shot measurement and low speckle noise using white light. Quantitative phase imaging performed with this experimental setup allowed the determination of erythrocyte morphology with 9 different parameters. In vivo quantitative analysis of erythrocytes by WDPM, which is a simple and reliable method, shows that HDMP treatment has no significant effect on erythrocyte morphology. With the developing technology, interdisciplinary studies on individuals under treatment should play an important role in elucidating the interaction between steroids and erythrocytes.</p> </abstract>ARTICLEtrue Pose Measurement Method for Large Components Based on Draw-Wire Displacement Sensors<abstract> <title style='display:none'>Abstract</title> <p>A method for measuring the docking pose of large components based on the draw-wire displacement sensor is proposed. In this method, coordinate systems and measurement points are established on the docking surfaces of fixed and moving components. The draw-wire displacement sensor is used to measure the distances between these measurement points. A mathematical model based on the distances between the measurement points is established, and the three-sphere rendezvous positioning principle is optimized to obtain the spatial positions of the measurement points. Consequently, the pose deviations of the fixed and moving components in all six degrees of freedom (6DOF) are determined. A simulation analysis of the measurement uncertainty of the obtained pose deviations is performed, resulting in a composite standard uncertainty obtained from the measurement standard uncertainties of different sensors. The simulation results show that the composite standard uncertainty is most affected in the <italic>x</italic>-axis translation direction and least affected in the <italic>x</italic>-axis rotation direction. With this method, only the distances between the measurement points need to be measured to determine the corresponding pose relationships. The cost of the equipment is low, and it is not easily affected by external factors such as the environment.</p> </abstract>ARTICLEtrue of Heart Pulse Transmission Parameters Determined from Multi-Channel PPG Signals Acquired by a Wearable Optical Sensor<abstract> <title style='display:none'>Abstract</title> <p>The article describes the development and testing of a special prototype wearable device consisting of three optical photoplethysmography (PPG) sensors. The functionality of the developed triple PPG sensor was tested under normal laboratory conditions and in a running magnetic resonance imaging (MRI) scanner working with a low magnetic field. The results of the first measurements under normal laboratory conditions show that the obtained mutual positions of systolic/diastolic blood pressure values and heart pulse transmission parameters determined from the PPG waves can be fitted by a line segment with a sufficiently high slope. Measurement experiments inside the open-air MRI tomograph show the practical influence of vibrations and acoustic noise on the cardiac system of the examined persons, which was confirmed by a slight increase in the heart pulse rate and changes in pulse transmission time and pulse wave velocity. We plan to perform further measurements inside the whole-body MRI device producing more intensive vibrations and noise with expected higher stress impact on an exposed person.</p> </abstract>ARTICLEtrue Volumetric, DTI and H MRS Rat Brain Protocol for Monitoring Early Neurodegeneration and Efficacy of the Used Therapy<abstract> <title style='display:none'>Abstract</title> <p>The aim of our study was to develop a multimodal experimental protocol for <italic>in vivo</italic> imaging and metabolic parameters (MRI, DTI and <sup>1</sup>H MRS) in an animal model of neurodegeneration. We have successfully developed the protocol for simultaneous DTI/MRI/<sup>1</sup>H MRS measurement to ensure unaltered conditions for repeatable non-invasive experiments. In this experiment, diffusion tensor imaging, spectroscopic and volumetric “bio-markers” were generated in the brain for the D-galactose model of “age-related dementia”. The hippocampal relative volume, taurine and myo-inositol relative concentrations were found to be significant predictors contributing to the differences between the groups of rats treated with D-galactose in simulated “neurodegeneration”, even in response to the applied Huperzine A therapy.</p> </abstract>ARTICLEtrue Validation of a High-Speed Tracked Vehicle Powertrain Simulation Model<abstract> <title style='display:none'>Abstract</title> <p>High-speed tracked vehicles have complex powertrains that, in addition to power transfer and transformation, also perform the functions of vehicle steering and braking systems, as well as power supply system for various subsystems on the vehicle. Analyzing the power balance of a tracked vehicle, especially in specific moving scenarios such as the turning process, is of great importance for understanding the power requirements and workload of the powertrain components and their optimization. A simulation model was developed, based on the construction parameters of an experimentally tested high-speed tracked vehicle to reduce the time and material resources required for experimental testing. Both the simulation and experimental tests were conducted using the same input parameters and driving conditions for different vehicle turning scenarios. Simulation and experimental test results are compared to verify the accuracy of the simulation model. The analysis of the obtained results shows that the average value of the relative rpm error is about 5%, the average value of the relative torque error is about 7%, while the average value of the relative power error is about 6.5%.</p> </abstract>ARTICLEtrue the Flow of Time with Multi-Output Models<abstract> <title style='display:none'>Abstract</title> <p>Recent work has paid close attention to the first principle of Granger causality, according to which cause precedes effect. In this context, the question may arise whether the detected direction of causality also reverses after the time reversal of unidirectionally coupled data. Recently, it has been shown that for unidirectionally causally connected autoregressive (AR) processes <italic>X</italic> → <italic>Y</italic>, after time reversal of data, the opposite causal direction <italic>Y</italic> → <italic>X</italic> is indeed detected, although typically as part of the bidirectional <italic>X ↔ Y</italic> link. As we argue here, the answer is different when the measured data are not from AR processes but from linked deterministic systems. When the goal is the usual forward data analysis, cross-mapping-like approaches correctly detect <italic>X</italic> → <italic>Y</italic>, while Granger causality-like approaches, which should not be used for deterministic time series, detect causal independence <italic>X</italic> ⫫ <italic>Y</italic> . The results of backward causal analysis depend on the predictability of the reversed data. Unlike AR processes, observables from deterministic dynamical systems, even complex nonlinear ones, can be predicted well forward, while backward predictions can be difficult (notably when the time reversal of a function leads to one-to-many relations). To address this problem, we propose an approach based on models that provide multiple candidate predictions for the target, combined with a loss function that consideres only the best candidate. The resulting good forward and backward predictability supports the view that unidirectionally causally linked deterministic dynamical systems <italic>X</italic> → <italic>Y</italic> can be expected to detect the same link both before and after time reversal.</p> </abstract>ARTICLEtrue of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers<abstract> <title style='display:none'>Abstract</title> <p>The article describes the non-contact and contact analysis of 1-MVA dry power transformers with epoxy-resin insulation using an acoustic camera and frequency analyzer with automatic sweeping for low-middle frequency areas. Power transformers are most commonly used for construction component (core, windings, taps) analysis. The electrical, non-rotating machine generates electromagnetic and acoustic emissions that can be used to analyze dry transformers during their operation. Non-contact online diagnostic methods have many advantages over offline methods because it is not necessary to shut down the transformer, and also, the condition and behaviour of the machine are analyzed during its normal operation. The article presents the analysis and comparison of structural parts of the distribution dry transformers of the same type and power. The problem of insufficient or incorrect clamp-screw connection was identified using the SFRA (Sweep Frequency Response Analysis) method.</p> </abstract>ARTICLEtrue Control and Parameter Optimization: A Study on Hubble Space Telescope<abstract> <title style='display:none'>Abstract</title> <p>In this work, we build a satellite attitude Proportional-Integral-Derivative (PID) controlled system by using the Hubble Space Telescope (HST) parameters as a reference and tune its controller parameters using various tuning methods. First, we give the equations for the motion of a satellite. We elaborate the control structure as controller, actuator, dynamics, and kinematics subsystems and construct an external disturbance model. We use a reaction wheel assembly used in the HST with the same configuration as the actuator. We evaluate the performance of the linearization by comparing it with the nonlinear model output. By working on the linearized model, we tune the PID controller parameters using two different methods: “Model-Based Root Locus Tuning” and “Genetic Algorithm Based Tuning”. First, we obtain the controller parameters by manipulating the poles on the root locus plot of the linearized system. In addition, we use genetic algorithms to find the optimized controller values of the system. Finally, we compare the performances of the two methods based on their cost function values and find that the Genetic Algorithm-based tuned parameters are more fruitful in terms of the cost function value than the parameters obtained by the Root Locus-based tuning. However, it is found that the Root Locus-based tuning performs better in disturbance rejection.</p> </abstract>ARTICLEtrue Concentration Monitoring Using Microstrip Spurline Sensor<abstract> <title style='display:none'>Abstract</title> <p>This article reports a microstrip spurline sensor for glucose concentration monitoring. The microstrip spurline sensor is a low-cost and easy-to-fabricate device that uses printed circuit board (PCB) technology. It consists of a combination of four spurlines and transmission lines. The four spurlines are used to reject unwanted frequencies, while the transmission lines allow the desired frequencies to pass through. The resonance frequency (Fr) and reflection coefficient (S11) were recorded through meticulous simulations and experiments over a frequency range from 1.5 GHz to 4 GHz. In addition, the sensor was used to detect changes in glucose concentration, ranging from 0 mg/dL to 150 mg/dL. The findings of this study show that the antenna-based sensor proposed in this research can effectively measure glucose levels across the diabetes range, from hypoglycemia to normoglycemia to hyperglycemia, with a high degree of sensitivity of 7.82 x 10<sup>−3</sup> dB/(mg/dL) and 233.33 kHz/(mg/dL).</p> </abstract>ARTICLEtrue and Multi-Point Non-Orthogonal Multiple Access based Power Adaptive Design for Improving Bit Error Ratio<abstract> <title style='display:none'>Abstract</title> <p>In the framework of next-generation communication systems, Non-Orthogonal Multiple Access (NOMA) has attracted considerable interest. The fundamental advantage is that it has greater spectrum utilization than its orthogonal equivalents. This proposed work integrates Single-Input Single-Output NOMA (SISO) with Coordinated Multi-Point (CoMP). It uses both systems based on Quadrature Phase-Shift Keying (QPSK). A power-tolerant NOMA reduces the system’s vulnerability to erroneous power allocation by adaptively modifying each user’s signal power. The transmitted data is used to modify the power in the Power-Adaptive NOMA (PANOMA). PANOMA helps improve the Bit Error ratio and also improves the computational complexity. The Bit Error Rate (BER) and the lower limit capacity efficiency across Rayleigh fading channels are determined in precise closure representations of more than two consumer situations to measure its capability. The proposed method PA-CoMP-NOMA improves the Bit Error ratio in both systems. It improves the average BER among all users. Compared to its orthogonal cousin, NOMA has higher spectral efficiency. Nevertheless, our proposed method retains this feature as well as superior BER performance, although its spectral effectiveness is lower than that of the classic sum-rate based power NOMA.</p> </abstract>ARTICLEtrue and Construction of Metrological Equipment for Torque Sensors with a Carbon-based Measuring Arm<abstract> <title style='display:none'>Abstract</title> <p>The paper presents a comprehensive design of metrological equipment for torque sensor verification and calibration, detailing the process from conception to construction and highlighting the specifics of the structural design to meet metrological requirements. The measuring device’s functionality and the individual structural components are described, as is the methodology for creating a complete product. The paper addresses the crucial issue of measurement uncertainty and the required accuracy, achieved through the construction of a special measuring arm made of carbon material. FEM analyses of the carbon arm are presented and compared with the required metrological accuracies. In addition, we discuss the different properties of various carbon structures in Pre-preg materials used in the construction of the measuring arm and present the results of measurements on such carbon materials. This paper provides a comprehensive insight into the design and construction of metrological equipment for torque sensors, with a focus on its compliance with metrological requirements. The proposed device aims to establish the foundations for primary metrology of torque in Slovakia and has potential applications in a wide range of industries.</p> </abstract>ARTICLEtrue Parameter Estimation Algorithm for Damped Real-value Sinusoid in Noise<abstract> <title style='display:none'>Abstract</title> <p>To improve the parameter estimation performance of damped real-value sinusoid in noise, a novel algorithm with high accuracy and computational efficiency is proposed that combines the characteristics of good anti-interference, small computation of frequency-domain methods, and high parameter estimation accuracy of time-domain methods. First, the Discrete Fourier Transform (DFT) algorithm and the two-point spectrum interpolation algorithm of the frequency-domain methods are used to improve the noise immunity. Then, the linear prediction property and the enhancement filter of the time-domain methods are used to improve the parameter estimation accuracy. In addition, the parameter estimation performance of the proposed algorithm is verified by computational complexity analysis and test experiments, and the practical application effectiveness of the proposed algorithm is demonstrated on the Coriolis Mass Flowmeter (CMF) experimental platform. The experimental results show that the proposed algorithm effectively improves the real-time performance and the parameter estimation accuracy is better than that of the existing excellent algorithms.</p> </abstract>ARTICLEtrue of the Bruker Minispec Instrumentation into the Static Magnetic Field Standard<abstract> <title style='display:none'>Abstract</title> <p>The static magnetic field standard is part of many scientific experiments aimed at measuring the magnetic field. Often this device has to be built by oneself, if there is no possibility to buy it off the shelf. One possibility is also to convert a suitable device into a static magnetic field standard. Such a method is also described in this article. When the first experiments showed that the key parts could not be obtained under the existing conditions, it was decided to convert Bruker’s Minispec into a static magnetic field standard. Such a standard will not be completely universal, but it will accommodate many experiments, and the experience may help in the future when a more perfect standard is built. This article describes the design of the apparatus, briefly describing all the equipment, which includes many parts of the original device. The parts specific to the new construction are described in more detail. An alternative solution for frequency deviation calculation using a software quadrature detector, tested only in the form of a computer simulation, is also described.</p> </abstract>ARTICLEtrue