Measurement Principle Research Articles

Measuring Spatial Ability: Analysis of Spatial Ability Test for Gulf State Students Using Item Response Theory

This study evaluates the psychometric properties of the spatial ability test using the three-parameter logistic model within item response theory. The final version of the scale comprised 29 dichotomous items, administered to a sample of 2,694 male and female students from grades 5 and 6 across schools in the Arab Gulf region. The test adhered to the three-parameter model, satisfying the assumptions of unidimensionality and local independence. The item difficulty parameters ranged from -1.541 to 1.735, discrimination parameters spanned from 0.419 to 5.252, and guessing parameters varied between 0.00 and 0.346. With a marginal reliability coefficient of 0.86, the scale demonstrated strong stability. These findings indicate that the test items align with established measurement principles, supporting the spatial ability test as a valid and reliable assessment tool for measuring spatial abilities in the Gulf region. The results have important implications for educational assessment in the Arab Gulf and could guide the development of similar assessments in other educational contexts. Further research is recommended to improve the test’s precision and explore its application in diverse educational settings.

From Exhaust to Extraction: Evaluating Car Catalysts Waste for a Resilient Economy

Spent Automotive Catalytic Converters (SACC) are comprised of a support (a honeycomb ceramic structure) coated with a catalytic layer, where Platinum Group Elements (PGE), especially Pt and Pd, facilitate oxidation and reduction reactions to reduce hazardous emissions from car engines. This study provided information about various measurement procedures and principles for characterising SACC, revealing that SACC can release Potentially Toxic Elements (PTE) under environmental conditions. The SACC samples used primarily contain cordierite and moissanite, likely distinguishable upon visual inspection of waste piles. Unlike geological samples, the SACCs samples, considered as a homogeneous matrix, exhibit major elements such as Al, Si, Mg, and Ba, with minor elements including P, Na, Ca, Fe, Ti, Ce, and Zr, posing challenges for geoanalysts and environmental managers. Sequential extraction demonstrated high concentrations of PGE in the residual phase, especially Pt, Pd, and Rh. All other fractions, oxidisable, reducible and exchangeable, showed significant analytical recoveries of PTE such as Zn, Cu, and other trace elements. Watering bulk samples resulted in exceeded reference thresholds, with high Cd, Ni, and Zn, identifying SACC as a potentially hazardous materials. Toxicity tests on three aquatic species (A. fischeri, R. subcapitata, and D. magna) indicated both acute and chronic effects, further highlighting the need for proper waste management. The characterisation approach suggested here can help define the most appropriate SACC treatment demonstrating economic profit and ecological benefits.

QKSAN: A Quantum Kernel Self-Attention Network.

The Self-Attention Mechanism (SAM) excels at distilling important information from the interior of data to improve the computational efficiency of models. Nevertheless, many Quantum Machine Learning (QML) models lack the ability to distinguish the intrinsic connections of information like SAM, which limits their effectiveness on massive high-dimensional quantum data. To tackle the above issue, a Quantum Kernel Self-Attention Mechanism (QKSAM) is introduced to combine the data representation merit of Quantum Kernel Methods (QKM) with the efficient information extraction capability of SAM. Further, a Quantum Kernel Self-Attention Network (QKSAN) framework is proposed based on QKSAM, which ingeniously incorporates the Deferred Measurement Principle (DMP) and conditional measurement techniques to release half of quantum resources by mid-circuit measurement, thereby bolstering both feasibility and adaptability. Simultaneously, the Quantum Kernel Self-Attention Score (QKSAS) with an exponentially large characterization space is spawned to accommodate more information and determine the measurement conditions. Eventually, four QKSAN sub-models are deployed on PennyLane and IBM Qiskit platforms to perform binary classification on MNIST and Fashion MNIST, where the QKSAS tests and correlation assessments between noise immunity and learning ability are executed on the best-performing sub-model. The paramount experimental finding is that the QKSAN subclasses possess the potential learning advantage of acquiring impressive accuracies exceeding 98.05% with far fewer parameters than classical machine learning models. Predictably, QKSAN lays the foundation for future quantum computers to perform machine learning on massive amounts of data while driving advances in areas such as quantum computer vision.

A Novel Gold Nanoparticle‐Ionic Liquid Nanostructure Modified Pleurotus Ostreatus Based Microbial Biosensor System For Bisphenol A

AbstractThe current study develops the first and novel gold nanoparticle‐ionic liquid nanostructure modified microbial biosensor based on Pleurotus ostreatus for the sensitive determination of Bisphenol A. In the construction of the microbial biosensor, lyophilized P.ostreatus cells were modified with ionic liquid‐cysteamine mixture on a gold electrode which was modified with 1,6‐hexanedithiol and gold nanoparticle. The measurement principle of the biosensor is based on the detection of changes in current in a phosphate buffer system (pH 7.5, 50 mM and containing 5.0 mM K3[Fe(CN)6]) in the potential range of −0.2 to +0.6 V depending on the BPA concentration. In the optimization studies of the microbial biosensor; the most suitable ionic liquid‐cysteamin ratio was 1 : 2 (v/v) and the incubation time of 1,6‐hexanedithiol on the gold electrode was 6 hours. Optimum working conditions were determined to be pH:7.5, 100 mM potassium phosphate buffer, and 35°C. In the characterization studies of the microbial biosensor, parameters such as linearity, interference effects of some substances on the microbial biosensor responses, repeatability, reproducibility and storage stability of the microbial biosensor were determined. The linear range of the biosensor was obtained 10–250 μM. Limit of detection was determined to be 1.57 μM and the response time was obtained 20 seconds. Real sample analysis was carried out by water samples that kept in plastic bottles for 6 months by using both the microbial biosensor and HPLC method.

Low-cost automated cell counting module fabricated using CNC milling and soft lithography

Cell counting is one of the basic and essential procedures that researchers in cell biology, bioengineering, and other related fields learn at the outset. Systems based on various measurement principles are commercially available, and each has its own advantages and disadvantages in terms of performance, cost, and footprint. Herein, we developed a cost-effective, scalable, and compact module that enables cell counting with reasonable accuracy, throughput, and sensitivity. This cell counting module had a size of 29 × 48 × 16 mm and a cost of $165 USD. The module can be assembled by simply inserting commercially available optical and electronic components into a housing printed by CNC milling and soft lithography. To take full advantage of this module, we built an automated cell counting system using open-source and commercially available development platforms. The module exhibited a measurement accuracy (i.e., guaranteed accuracy in the concentration range of 0–500 cells/µL) and sorting resolution (i.e., selection of particles with diameters of 5 µm and 15 µm) tolerable for cellular experiments. This low-cost and small-size module can be a sufficient replacement for a routine system in cell experiments. We anticipate our work will benefit research fields such as cell biology and bioengineering.

Application of Imaging Algorithms for Gas-Water Two-Phase Array Fiber Holdup Meters in Horizontal Wells.

The flow dynamics of low-yield horizontal wells demonstrate considerable complexity and unpredictability, chiefly attributable to the structural attributes of the wellbore and the interplay of gas-water two-phase flow. In horizontal wellbores, precisely predicting flow patterns using conventional approaches is often problematic. Consequently, accurate monitoring and analysis of water holdup in gas-water two-phase flows are essential. This study performs a gas-water two-phase flow simulation experiment under diverse total flow and water cut conditions, utilizing air and tap water to represent downhole gas and formation water, respectively. The experiment relies on the measurement principles of an array fiber holdup meter (GAT) and the response characteristics of the sensors. In the experiment, GAT was utilized for real-time water holdup measurement, and the acquired sensor data were analyzed using three interpolation algorithms: simple linear interpolation, inverse distance weighted interpolation, and Gaussian radial basis function interpolation. The results were subsequently post-processed and visualized with 2020 version MATLAB software, generating two-dimensional representations of water holdup in the wellbore. The study findings demonstrate that, at total flow of 300 m3/d and 500 m3/d, the simple linear interpolation approach yields superior accuracy in water holdup calculations, with imaging outcomes closely aligning with the actual gas-water flow patterns and the authentic gas-water distribution. As total flow and water cut increase, the gas-water two-phase flow progressively shifts from stratified smooth flow to stratified wavy flow. In this paper, the Gaussian radial basis function and inverse distance weighted interpolation algorithms exhibit superior accuracy in water holdup calculations, effectively representing the fluctuating features of the gas-water interface and yielding imaging outcomes that align more closely with experimentally observed gas-water flow patterns.

Research on Voltage Self-Calibration Sensing Technology Based on Measurement Circuit Topology Changes

In capacitance-coupled voltage-sensing technology, the degree of coupling capacitance is affected by the sensing area, relative position deviation, and other factors, and thus the measurement coefficient is often difficult to determine accurately and presents greater implementation difficulties in actual deployment. This paper proposes a dynamic reconfiguration based on the measurement circuit topology of the voltage sensor adaptive calibration method in order to measure voltage sensor gain in the process of automatic measuring. Firstly, the basic principle of voltage measurement is introduced, and the self-calibration method is proposed, considering the influence of the sensing area and the relative position error on the change in the coupling capacitance. On this basis, the influence of calibration accuracy on sensor structure parameters is analyzed using network sensitivity analysis, and the parameter selection principle is given, according to which the selection criterion of parameter optimization is formulated to complete the sensor design. By analyzing the coupling effect of the three-phase measurement, the installation method of the sensing structure is proposed. An experimental platform is built to test the accuracy of the voltage measurement of the sensor under laboratory conditions. The experimental results show that the maximum relative error of the voltage measurement amplitude is 2.24%. In order to verify the feasibility of the sensor technology designed, the measurement models that integrate communication, acquisition, and processing are installed on both ends of the circuit breaker wire, and the voltage waveform generated during the circuit breaker closing process is recorded in real time. The experimental results show that the sensor technology can accurately record the voltage waveform of the signal to be measured, and the feasibility of its application in switchgear equipment signal measurement is preliminarily verified by the results.

Bending moment calibration for rotational bending fatigue testing machine based on strain measurement

Abstract Rotational bending fatigue testing is an important method to evaluate the fatigue of metal materials under cyclic loading. Specifically, the fatigue strength is evaluated through repeated rotational bending under complex loads with the accuracy affected by the bending moment. Here, a method based on strain measurements is proposed for calibrating the bending moment of rotational bending fatigue testing machines. Specifically, the strain of a metal sample under loading with resistance strain gauges was recorded using a strain acquisition system to measure the bending moment. The positions of strain gauges were designed according to the principle of strain measurements to establish a calibration program. Three metal samples of different sizes were tested on two types of rotational bending fatigue testing machines, and the measurement uncertainty was evaluated and verified. The experimental results showed that the proposed method measured and calibrated the bending moment of rotational bending fatigue testing machines rapidly, conveniently, and accurately. The results also provide a practical reference for research and application in related fields.

COMPARISON OF CONFOCAL SENSOR FOR DIAMETER MEASUREMENT WITH MEASURING PROBE

The measurement and inspection of products and their dimensions in industry plays an important role in determining the quality of a product. Correct measurement is a key factor in production. Many companies are subject to stringent safety standards and specific product requirements. Accurate measurement ensures compliance with these guidelines, avoiding fines, penalties and legal complications. Effective measurement processes can identify inefficiencies, defects and areas for improvement, leading to cost savings. By detecting defects early in the production cycle, manufacturers can reduce waste and optimize resource utilization thereby reducing overall production costs. A fundamental principle of good measurement is to ensure that the measuring instruments are suitable for the specific application and that they meet the measurement requirements for the measurement parameter. The objective of the experiment is to verify and compare the measurement capability of a confocal chromatic sensor against a measurement probe used in production. The parameter to be measured is the diameter, since the correct diameter plays an essential role in the production of shafts or other cylindrical products. The results contained in the thesis highlight the importance and differences between the different measuring devices and the qualification to use the measurement of a given parameter.

Blade tip clearance measurement method based on blade tip timing without the once per revolution sensor

Abstract The rotor blade tip clearance (BTC) of an aeroengine is a critical parameter that significantly impacts its performance and safety. Accurately determining dynamic BTC has been a focal point of research in experimental testing. Among the effective measurement methods for dynamic BTC, the laser triangulation method based on blade tip timing (BTT) stands out. However, this method typically relies on an once-per-revolution (OPR) sensor for rotor speed and blade serial number information during measurement, leading to increased installation and maintenance costs as well as additional measurement uncertainties. In response to this challenge, this paper presents two signal processing method that eliminate the need for an OPR sensor. The first method, referred to as "none OPR method 1," closely follows the measurement principles of the traditional method but employs a skewed dual light probe (SDLP) signal to extract rotational speed information, thus obviating the need for an OPR sensor. The second method, "none OPR method 2," introduces a novel data processing approach that enables BTC determination without any source of rotor speed information. Both methods utilize dynamic and static BTC matching techniques to identify blade serial numbers and achieve BTC measurement without an OPR sensor on a simulated rotor experimental bench. Comparative analysis with traditional method BTC measurements reveals that, under stable rotor speeds, all methods achieve similar levels of accuracy and repeatability errors within 0.025mm. However, when dealing with variable speed conditions, the traditional method's accuracy is significantly affected. None OPR method 1 mitigates the impact of rotor speed changes to some extent, while none OPR method 2 remains unaffected by such changes. Importantly, both none OPR methods demonstrate the capability to measure blade-by-blade tip clearances akin to the traditional method.

Drift compensation system of an autocollimator based on reciprocal roll angles and a feedback combination target

To address the issues of limited field of view and beam drift in traditional autocollimation measurements, a novel, to our knowledge, autocollimation measurement method is proposed. This method is based on the principle of full-circle continuous measurement using reciprocal roll angles of a compound biaxial system, combined with a feedback and compensation mechanism for beam drift using both calibration and compensation targets. A self-collimating small-angle measurement system model, coupled with a compound biaxial turntable and combined target, is established using ray tracing and perspective projection transformation techniques. Additionally, a closed-loop beam drift compensation system is developed by applying a BP neural network and a PID control algorithm. Experimental tests on the compensation system demonstrate a significant improvement in measurement accuracy and stability. The results show that this method satisfies the requirements for small-angle autocollimation measurement, and the method also enhances the overall stability of the autocollimation system.

Modeling of an inductive displacement sensor based on 1DCNN-LSTM-AT

Abstract The input-output relationship of inductive displacement sensors is typically nonlinear, which demands numerous computational resources for precise calculation. Therefore, the traditional analytical methods for the inductive displacement sensors cannot meet the real-time high-precision measurement requirements. In response to the aforementioned issues, this paper proposes an optimized Long Short-Term Memory (LSTM) neural networks based on one-dimensional convolutional neural networks (1DCNN) to modeling the input-output relationship of the inductive displacement sensor. First, the measurement principle of the inductive displacement sensors was analyzed, and the analytical model of the sensor output was derived. And the influences of the key parameters of sensors on the relationship between the induced voltage and the displacement were studied. Then, the 1DCNN-LSTM-AT network for modelling the input-output relationship of the inductive displacement sensor was studied. The spatial features of historical induced electromotive force (EMF) data generated by the induction coil were initially extracted using the 1DCNN network. And these spatial features were then utilized as input to the LSTM neural network to capture the temporal features of the historical induced EMF data. Subsequently, the spatiotemporal features of the induced EMF data were fed into the regression prediction layer to compute the displacement measurement results corresponding to the current input. Moreover, the attention mechanism was used for the 1DCNN-LSTM model to enhance the prediction accuracy and stability of the model. Finally, the experimental results demonstrate that the proposed 1DCNN-LSTM-AT model achieves an average absolute percentage error of 3.1%, significantly outperforming traditional models such as LSTM (29.3%), CNN (4.7%), and ANN (4.3%). This paper provides a new method for modelling the nonlinear relationships of the inductive displacement sensor, and presents a fresh perspective for research in the data processing of nonlinear sensors.

High‐speed and contactless inspection of defective micro‐LEDs through the photovoltaic effect

AbstractThe most significant challenge associated with micro‐light‐emitting‐diode (micro‐LED) displays, which are anticipated to be the next generation of display technology, is the high manufacturing cost. In order to reduce manufacturing costs, it is essential to improve yield. Improving the manufacturing yield of them necessitates the evaluation of micro‐LED chips prior to their installation onto substrates. However, the microsize and large quantity of these chips renders inspection difficult with conventional inspection methods. Herein, we propose a method for inspecting micro‐LED chips by measuring the voltage generated between the anode and cathode due to the photovoltaic effect using a developed proximity capacitance image sensor. As this inspection method does not require the use of probe pins to contact LED electrodes, it enables simultaneous inspection of multiple chips in a short time without causing any damage to the electrodes. In this paper, an experimental system equipped with this sensor was developed to demonstrate the basic measurement principle. Moreover, we demonstrated that more than 50,000 micro‐LED chips with a size of 60 μm × 34 μm can be simultaneously inspected in approximately 2 s.

A calibration method of line laser 3D gear measurement system

It is of great importance to ensure the accuracy of measurements taken by the line laser three-dimensional (3D) gear measurement system through the calibration of system in an accurate manner. This paper established a relevant measurement model based on the principle of line laser 3D gear measurement using generalized polar coordinates, designed a dedicated Polyhedral Artefact (PA), and proposed an accurate calibration method to address the challenges posed by the representation of 6 degrees of freedom (DOF) parameters for line laser sensor data in measurement space. Among them, the PA includes features such as cylindrical plane, planar plane, and V-groove etc., which can meet the requirements of high-precision machining while maintaining consistency with gear installation accuracy to further improve the accuracy of sensor pose parameters. The calibration method uses nonlinear optimization equations with point cloud data to simultaneously solve the required parameters for accurate measurement. Calibration and gear measurement experiments reveal that the standard deviation and range deviation of the total tooth profile deviation, obtained from 10 repeated measurements of a single tooth flank, are 0.244 μm and 0.86 μm, respectively. The results of the tooth profile measurements after the calibration of the system show good consistency compared with the contact measurements, which verifies the effectiveness of the method.

A Study of Data Processing Methods for Non-Contact Multispectral Method of Blood Oxygen Saturation.

Regular monitoring of blood oxygenation is important for disease prevention and treatment. Image photoplethysmography (IPPG) technology is a non-contact physiological parameter detection technology, which has been widely used in blood oxygenation detection. However, traditional imaging devices still have issues such as low detection accuracy, narrower receiving spectral range. In this paper, we proposed two improved detection methods based on the dual-wavelength measurement principle, that is, dual-band IPPG signal ratio method and dual-band IPPG signal AC/DC method. To verify the effectiveness of the two methods, we used different heartbeat period IPPG signals as sample data sets, and combined PLS and RF algorithms for model training, thus obtaining the best data processing method. The experimental results showed that the dual-band IPPG signal AC/DC method can effectively reduce the model training time. This method meets the strong demand for non-contact blood oxygen measurement and provides a new measurement idea.

Elastography as a Discriminator Between Fibrotic and Inflammatory Strictures in Crohn's Disease: A Dead End or Bright Future in Clinical Decision-Making? Critical Review.

Crohn's disease (CD) is a complex systemic entity, characterized by the progressive and relapsing inflammatory involvement of any part of the gastrointestinal tract. Its clinical pattern may be categorized as penetrating, stricturing or non-penetrating non-stricturing. In this paper, we performed a database search (Pubmed, MEDLINE, Mendeley) using combinations of the queries "crohn", "stricture" and "elastography" up to 19 June 2024 to summarize current knowledge regarding the diagnostic utility of ultrasound (US) and magnetic resonance (MR) elastography techniques in the evaluation of stricturing CD by means of an assessment of the transmural intestinal fibrosis. We decided to include papers published since 1 January 2017 for further evaluation (n = 24). Despite growing collective and original data regarding numerous applications of mostly ultrasound elastography (quantification of fibrosis, distinguishing inflammatory from predominantly fibrotic strictures, assessment of treatment response, predicting disease progression) constantly emerging, to date, we are still lacking a uniformization in both cut-off values and principles of measurements, i.e., reference tissue in strain elastography (mesenteric fat, abdominal muscles, unaffected bowel segment), units, not to mention subtle differences in technical background of SWE techniques utilized by different vendors. All these factors imply that ultrasound elastography techniques are hardly translatable throughout different medical centers and practitioners, largely depending on the local experience. Nonetheless, the existing medical evidence is promising, especially in terms of possible longitudinal comparative studies (follow-up) of patients in the course of the disease, which seems to be of particular interest in children (lack of radiation, less invasive contrast media) and terminal ileal disease (easily accessible).

Loaded tooth contact analysis for helical gears with surface waviness error

Meshing characteristics are crucial for the transmission performance of vibration noise and strength of gear systems. Gear transmission error has been acknowledged as a prominent excitation in vibration systems, but the surface waviness deviations that directly affect it in contact analysis are generally ignored. This study proposes a comprehensive model for quasi-static analysis of tooth surfaces with waviness error. The model reconstructs the actual tooth surface in reverse based on the gear Fourier measurement principle. Instead of solving the meshing equations to pre-assume contact position, the problem of normal contact between surfaces with deviations is solved by an innovative multiscale grid and a local iterative numerical algorithm. Combining the finite element numerical method and surface integral of the Boussinesq solution determines gear deformation and develops a loaded contact model. The validity of the model is verified through numerical examples. Furthermore, the proposed model is applied to discuss the tooth surfaces with different waviness amplitudes, frequencies, and distribution angles for the first time. It explains the interaction between local microscale and global scale introduced by waviness error on tooth surfaces and reveals the mechanism of the waviness error on meshing performance.

Environmental challenges and economic cooperation between Ukraine and the EU: prospects for sustainable development

The article is dedicated to analyzing the cooperation between Ukraine and the European Union, which began with the signing of the Partnership and Cooperation Agreement in 1994 and reached a new level after the signing of the Association Agreement in 2014. The focus is on the impact of this agreement on Ukraine’s domestic and foreign policies, particularly in the context of sustainable development and ensuring environmental security. The article examines the role of international agreements in regulating Ukraine’s environmental policy, particularly the principles of preventive measures and the use of natural resources within the framework of sustainable development. Despite the formal incorporation of relevant provisions in international treaties, the real situation regarding environmental security remains challenging due to the conflict between the economic interests of developed countries and transnational corporations and the demands of environmental protection. The article separately addresses the influence of international law on the development of Ukraine’s energy policy and its integration into the pan-European energy space. The importance of transitioning to renewable energy sources and the role of the European Union in financing and supporting such projects are analyzed. It is noted that sustainable development and environmental protection should become priorities within the framework of Ukraine’s energy security policy. The article also outlines the main challenges Ukraine faces in the context of international environmental security, particularly the insufficient effectiveness of international organizations in recognizing and counteracting environmental crimes. Despite this, the importance of cooperation with the EU to achieve a stable deceleration of environmental degradation is emphasized.

Symmetry Breaking and Modal Localization in a System of Parametrically Excited Microbeam Resonators

In this work, we study the nonlinear dynamics of parametrically excited bending vibrations of two weakly coupled beam microresonators under electrothermal excitation. A steady-state harmonic temperature distribution in the volume of the resonators in the frequency domain was obtained. A system of equations for mechanically coupled beam resonators is derived, considering the deposited particle on one of them. Using asymptotic methods of nonlinear dynamics, equations in slow variables were obtained, which were studied by methods of the theory of bifurcations. It is shown that in a perfectly symmetrical system in a certain frequency range, the effect of symmetry breaking is observed – the emergence of a mode with different amplitudes of oscillations of two beam resonators, which can be the basis for a new principle of high-precision measurements of weak disturbances of various physical natures, in particular – measurements of ultra-low masses of deposited particles.

Principles and prospects of Bose-Einstein correlation study at BESIII* *This study was supported by the National Key R&D Program of China (2020YFA0406403) and the National Natural Science Foundation of China (11275211, 11335008, 12035013)

One method for determining the characteristic parameters of a hadron production source is to measure the Bose-Einstein correlation functions. In this study, we present fundamental concepts and formulas related to the Bose-Einstein correlations, focusing on the measurement principles and the Lund model from an experimental perspective. We perform Monte Carlo simulations using the Lund model generator in the 2–3 GeV energy range. Through these feasibility studies, we identify key features of the Bose-Einstein correlations that offer valuable insights for experimental measurements. Utilizing data samples collected at BESIII, we perform measurements of the Bose-Einstein correlation functions, with an expected experimental precision of a few percent for the hadron source radius and incoherence parameter.