Development Of Measurement System Research Articles

Sensor for Real-Time Glucose Measurement in Aqueous Media based on Nanomaterials Incorporating an Artificial Neural Network Algorithm on a System-On-Chip

The aim of this paper is to present the development of a real-time measurement system for glucose in aqueous media. The proposed system incorporates two lines of research: i) design, synthesis, and implementation of a non-enzymatic electrochemical sensor of Multi-Walled Carbon Nanotubes with Copper nanoparticles (MWCNT-Cu) and ii) design and implementation of a machine learning algorithm based on an Artificial Neural Network Multilayer Perceptron (ANN-MLP), which is embedded in an ESP32 SoC (System on Chip). From the current data that is extracted in real-time during the oxidation-reduction process to which an aqueous medium is subjected, it feeds the algorithm embedded in the ESP32 SoC to estimate the glucose value. The experimental results show that the nanostructured sensor improves the resolution in the amperometric response by identifying an ideal place for data collection. For its part, the incorporation of the algorithm based on an ANN embedded in a SoC provides a level of 97.8 % accuracy in the measurements. It is concluded that incorporating machine learning algorithms embedded in low-cost SoC in complex experimental processes improves data manipulation, increases the reliability of results, and adds portability.

Design and Development of a Microcontroller-based Weight Measurement System for Liquid Agriculture Produce

This research presents the development of a microcontroller-based weight measurement system tailored for liquid agricultural products. The system addresses the limitations of traditional manual weighing methods by incorporating a load cell, ADC, microcontroller, LCD, and Bluetooth module. The load cell converts weight into an electrical signal, processed by the microcontroller and displayed on the LCD. Calibration ensures accurate weight measurements. The system's portability, cost-effectiveness, and user-friendly interface make it a promising solution for agricultural applications. Quantitative aspects include the precise weight measurement enabled by the load cell and ADC, with calibration enhancing accuracy. Qualitative aspects encompass the system's ease of use, portability, and potential for integration into broader agricultural management systems. Future enhancements include additional sensors for comprehensive product analysis, cellular communication for remote data transmission, and data logging capabilities. This research contributes to the automation and efficiency of liquid weight measurement in agriculture, potentially improving resource utilization and crop yields.

Validation of Artificial Intelligence in the Classification of Adolescent Idiopathic Scoliosis and the Compairment to Clinical Manual Handling.

The accurate measurement of Cobb angles is crucial for the effective clinical management of patients with adolescent idiopathic scoliosis (AIS). The Lenke classification system plays a pivotal role in determining the appropriate fusion levels for treatment planning. However, the presence of interobserver variability and time-intensive procedures presents challenges for clinicians. The purpose of this study is to compare the measurement accuracy of our developed artificial intelligence measurement system for Cobb angles and Lenke classification in AIS patients with manual measurements to validate its feasibility. An artificial intelligence (AI) system measured the Cobb angle of AIS patients using convolutional neural networks, which identified the vertebral boundaries and sequences, recognized the upper and lower end vertebras, and estimated the Cobb angles of the proximal thoracic, main thoracic, and thoracolumbar/lumbar curves sequentially. Accordingly, the Lenke classifications of scoliosis were divided by oscillogram and defined by the AI system. Furthermore, a man-machine comparison (n = 300) was conducted for senior spine surgeons (n = 2), junior spine surgeons (n = 2), and the AI system for the image measurements of proximal thoracic (PT), main thoracic (MT), thoracolumbar/lumbar (TL/L), thoracic sagittal profile T5-T12, bending views PT, bending views MT, bending views TL/L, the Lenke classification system, the lumbar modifier, and sagittal thoracic alignment. In the AI system, the calculation time for each patient's data was 0.2 s, while the measurement time for each surgeon was 23.6 min. The AI system showed high accuracy in the recognition of the Lenke classification and had high reliability compared to senior doctors(ICC 0.962). The AI system has high reliability for the Lenke classification and is a potential auxiliary tool for spinal surgeons.

Design and Development of A Portable Conductivity-Based Salinity Measurement System for Coastal Well Water

Design and Development of A Portable Conductivity-Based Salinity Measurement System for Coastal Well Water

Intelligent non-destructive measurement of coal moisture via microwave spectroscopy and chemometrics

The rapid and non-destructive measurement of coal moisture content is essential in the coal industry for production, transportation and utilization purposes. Existing measurement methods have still drawbacks, such as being time-consuming, producing destructive samples and yielding unstable outcomes. To address these issues, this paper explored the utilization of broadband microwave spectrum for intelligent coal moisture measurement. A multi-type outliers detection method based on the Monte-Carlo cross-validation (MCCV) strategy was used to prevent masking effect of microwave spectra. In order to effectively extract microwave spectral features and establish correlations with coal moisture, a novel neural network model, UC-PLSR, is proposed by combining U-Net, Convolutional Block Attention Module (CBAM) and Partial Least Squares Regression (PLSR) algorithm. Furthermore, a design scheme/case of a microwave measurement device for coal moisture was presented, offering guidance for the development of rapid coal moisture measurement instruments or on-site measurement systems. Experimental results demonstrated that the proposed model outperformed traditional chemometrics methods, achieving superior prediction accuracy and generalization capability with R2 = 0.8756, MAE = 1.2523 and RMSE=1.6560.

Multiprobe Planar Near-field Range Antenna Measurement System with Improved Performance

This article presents a novel multiprobe planar near-field range (PNFR) measurement system. The said system simplifies the overall mechanical design, making it simpler than the existing scanning probe PNFR measurements, and also significantly reduces testing time. A dielectric-based probe is introduced to reduce the antenna size, thereby improving resolution. The probe under consideration is an antipodal Vivaldi antenna offering broadband support and ensuring wideband characteristics of aerials. Numerical results for representative X-band antenna models, presented in the Matlab environment, demonstrate robust performance of the developed measurement system.

SPECIFICS OF DESIGNING AN INFRARED PYROMETER-REFLECTOMETER FOR SEMICONDUCTOR HETEROSTRUCTURE FABRICATION

There are general technical requirements for all types of reactors for chemical vapour deposition technology using AIII- BV metalorganic compounds. Among them, it is worth highlighting the large temperature gradients that cause the origin of convection loops, which in turn, taking into account the high speed of the gas flow, lead to turbulence in the reactor instead of the expected laminar flow. It is also important to take into account the change in parameters of the wafer surface during the growth process and the need for signal separation between the useful signal from the wafer surface and the background signal from the wafer carrier, which rotates at fixed speed for uniform deposition of compounds. To obtain high-quality heterostructures with reproducible parameters, it is important to have a system of precise temperature control on the wafer surface directly in the deposition area, since the deposition process for many complex semiconductor devices (for example, laser diodes, LEDs, photodiodes, transistors on heterojunctions) is very sensitive to temperature changes. The method of optical pyrometry is a non-contact method that allows to precisely determine the temperature of the wafer surface and meets the technical requirements of CVD epitaxy growth reactors. This article is devoted to the analysis of the features of the development of optoelectronic systems for precise temperature measurement during epitaxial growth in order to determine the criteria for the selection or development of components of the optoelectronic system of the pyrometer-reflectometer. The main physical processes, electro-optical characteristics of Si photodiode, AlGaAs/GaAs LED and parameters of bandpass interference filters were investigated. Based on the analysis of the obtained research and measurement results, scientific recommendations have been developed. The recommendations aimed at the selection and optimization of the parameters of the components of the pyrometer-reflectometer (photodetectors, light emitting diodes, optical filters) in order to improve the accuracy and temperature stability of measurements in the pyrometer’s operation conditions, which take into account the compensation of emissivity change from the surface of the wafer.

A wide range oxygen sensing strategy with the collaboration of multiple phosphorescence probes

A wide range oxygen measurement system with the relative measurement error of less than 1.5% across 4 orders of magnitude of oxygen dynamic range has been developed. We proposed a theoretical evaluation method of the measurement capability of oxygen probes, which points that the relative measurement error (δ) is equal to the reciprocal of the product of signal-to-noise ratio (SNR) and relative sensitivity (S r). A minimum value point in the curve of δ with oxygen concentration is existing due to the opposite trends of SNR and S r Based on the evaluation results, an oxygen probe group was selected scientifically for wide range oxygen measurement. The efficacy of the developed measurement system, featuring adaptive oxygen probe switching, was verified through testing, confirming its compliance with accuracy requirements for measurements.

P-EcStat: A Versatile Design of Photoelectrochemical and Electrochemical Sensing System with Smartphone Interface via Bluetooth Low Energy

Electrochemical and photoelectrochemical sensors are a rapidly developing field in analytical chemistry. However, commercial systems often lack versatility and affordability, hindering wider adoption. Additionally, the absence of integrated excitation light sources limits their application in photoelectrochemical sensing. Here, we present a highly precise, versatile, affordable measurement system for both electrochemical and photoelectrochemical sensing applications. The system incorporates a three-electrode potentiostat with a synchronized excitation light source. This design enables the system to perform conventional electrochemical measurements like cyclic voltammetry, chronoamperometry, and photoelectrochemical amperometric measurements with controlled light excitation. The developed measurement system operates within a voltage range suitable for a measurable current range of 1 nA to 18 mA, with a high precision of 99%. The excitation source is a monochromatic LED system offering seven distinct wavelengths with digitally controlled intensity via a digital-to-analog converter. Furthermore, an Android-based user interface allows wireless system control via Bluetooth Low Energy. The report also details the construction of a photoelectrochemical experiment using copper (II) oxide nanorods synthesized by the hydrothermal process as the photoactive material employed to test the experiment on a potassium ferricyanide/potassium ferrocyanide solution. This user-friendly system allows broader exploration of electrochemical and photoelectrochemical sensing applications.

Improved design, development and field investigation of the wheel-soil interaction measurement system under aircraft load

This paper proposed the method and model to solve the issue of wheel-soil interaction on the soil runway and attained the equipment for measuring wheel-soil interaction and structural response by improving the design. Furthermore, through field tests, the research results show the characteristics of the three-direction force of the wheel on the soil runway under different tire loads and tire pressures, and present the mechanical response law of the soil runway structure under different soil strengths. In particular, it is found that the rolling resistance and rolling resistance coefficient of the wheel on the soil runway. Finally, the validity of the field test results is verified. This research lays a critical foundation for field testing on the load of aircraft and the formulation of a sophisticated wheel-soil interaction model, which has significant prospects for the structural design, the evaluation of the performance and life of soil runways.

Development of a soil electrical conductivity measurement system in paddy fields

This study aims to develop a data collection system for measuring soil electrical conductivity (EC) in Paddy Fields using the Wenner measurement principle, with one electrode configuration based on the Veris 3100 measuring machine, and a second electrode configuration with fixed electrodes. The result is a system that measures soil EC using the fixed electrode configuration for more stable results compared to the coulter electrode configuration on the Veris 3100. This system comprises three main components: a 7-inch industrial touchscreen monitor used for real-time monitoring and storing collected data on external memory, a controller that provides reverse direct current (DC) power supply to the electrodes and measures voltage and current parameters on the electrodes, two mechanical configurations including six electrodes in contact with the soil. The system is developed to operate best after soil preparation and before seed sowing. The collected data is processed and compared to actual measurements using an artificial neural network (ANN), resulting in an R2=0.7449, equivalent to linear regression. The system has been successfully installed and operated on a handheld tractor and tested in Paddy Fields on the outskirts of Can Tho City, Vietnam.

Development of an Optical System for Strain Drop Measurement of Osteosarcoma Cells on Substrates with Different Stiffness.

Adherent cells perceive mechanical feedback from the underlying matrix and convert it into biochemical signals through a process known as mechanotransduction. The response to changes in the microenvironment relies on the cell's mechanical properties, including elasticity, which was recently identified as a biomarker for various diseases. Here, we propose the design, development, and characterization of a new system for the measurement of adherent cells' strain drop, a parameter correlated with cells' elasticity. To consider the interplay between adherent cells and the host extracellular matrix, cell stretching was combined with adhesion on substrates with different stiffnesses. The technique is based on the linear stretching of silicone chambers, high-speed image acquisition, and feedback for image centering. The system was characterized in terms of the strain homogeneity, impact of collagen coating, centering capability, and sensitivity. Subsequently, it was employed to measure the strain drop of two osteosarcoma cell lines, low-aggressive osteoblast-like SaOS-2 and high-aggressive 143B, cultured on two different substrates to recall the stiffness of the bone and lung extracellular matrices. Results demonstrated good substrate homogeneity, a negligible effect of the collagen coating, and an accurate image centering. Finally, the experimental results showed an average strain drop that was lower in the 143B cells in comparison with the SaOS-2 cells in all the tested conditions.

Research on the optical properties and effect of the transparent epoxy for the JUNO central detector

The Central Detector (CD) of the Jiangmen Underground Neutrino Observatory (JUNO) has a large acrylic sphere containing 20,000 tons of liquid scintillator (LS) and is immersed in high purity water. The CD consists of 263 acrylic spherical panels and two chimneys, which are bonded together by mass polymerization. Transmittance and stress are critical factors for the CD, with transmittance affecting JUNO's energy resolution and stress affecting the structural integrity of the detector. The bonding areas of the CD are of particular concern, leading to the development of specialized measurement systems for acrylic stress and transmittance. Stress measurements revealed the presence of higher than expected levels of stress in the bonding areas, requiring assessments and protective measures. The application of a transparent epoxy on the bonding areas was proposed as an effective structural protection measure, although it may reduce the transmittance of these areas. Consequently, the optical properties of the transparent epoxy, such as refractive index and absorbance at 420 nm, were studied using acrylic samples to analyze the effect of the epoxy application on the transmittance performance of the CD. These results are detailed and discussed in this article.

Bayesian uncertainty evaluation applied to the tilted-wave interferometer

The tilted-wave interferometer is a promising technique for the development of a reference measurement system for the highly accurate form measurement of aspheres and freeform surfaces. The technique combines interferometric measurements, acquired with a special setup, and sophisticated mathematical evaluation procedures. To determine the form of the surface under test, a computational model is required that closely mimics the measurement process of the physical measurement instruments. The parameters of the computational model, comprising the surface under test sought, are then tuned by solving an inverse problem. Due to this embedded structure of the real experiment and computational model and the overall complexity, a thorough uncertainty evaluation is challenging. In this work, a Bayesian approach is proposed to tackle the inverse problem, based on a statistical model derived from the computational model of the tilted-wave interferometer. Such a procedure naturally allows for uncertainty quantification to be made. We present an approximate inference scheme to efficiently sample quantities of the posterior using Monte Carlo sampling involving the statistical model. In particular, the methodology derived is applied to the tilted-wave interferometer to obtain an estimate and corresponding uncertainty of the pixel-by-pixel form of the surface under test for two typical surfaces taking into account a number of key influencing factors. A statistical analysis using experimental design is employed to identify main influencing factors and a subsequent analysis confirms the efficacy of the method derived.

The development, validation, and application of the campus walk score measurement system

Improving campus walkability can encourage students to walk and may inhibit the development of sedentary lifestyle habits, obesity, diabetes, and other health issues. This study aimed to formulate an optimized campus Walk Score (WS) measurement system that combines students' weekly demand for the use of facilities and unique campus environments. Bivariate correlation analysis and regression models were used to verify this system. The verified system was further applied to assess campus walkability and its influencing factors. The facility weight and walking time were established through questionnaires distributed on eight campuses in Tianjin, China. GIS and field audits were utilized to collect data on the objective built environment (BE), subjective environmental quality variables, and pedestrian volume (PV). Pearson's correlation analysis and Negative binomial regression models without spatial autocorrelation were used to verify the campus WS measurement system. The significant relationships between BE features and overall WS were found. PV was significantly correlated with overall WS and classified WSs. These findings were all found in the overall and three types of campuses. Therefore, our optimized system can be verified. Additionally, the WS was closely associated with facility distribution, planning mode, and other spatial attributes. Based on our results, how our findings can be utilized to promote campus walkability was proposed.

Recurrent multi-view collaborative registration network for 3D reconstruction and optical measurement of blade profiles

Aligning multiple viewpoints to reconstruct a complete profile is crucial for the three-dimensional optical measurement of blade profiles. As foundational solutions, rigid pairwise point cloud registration methods often struggle to produce satisfactory results due to significant cumulative errors stemming from pairwise registration errors, while current multi-view registration methods also face challenges when their prerequisites conflict with the practical measurement scenarios of blade profiles. To address these issues, this study proposes a learning framework to recover a transformation vector between the coordinate frames of both the optical sensor and the rotational axis in our developed optical measurement system based on extracted adaptive feature embeddings from the initial coordinate representation of viewpoints, which simultaneously aligns all viewpoints into a complete profile without relying on any prerequisites. Furthermore, an elaborate recurrent updating strategy is incorporated into the framework that enables incremental refinement of the transformation vector, thus aiding the framework in meeting the high-precision measurement requirements at the 0.01 mm level. Experimental results from both theoretical and real-world data, conducted on three representative blades and compared against nine state-of-the-art algorithms, consistently demonstrate the superiority of the proposed method in terms of accuracy, time efficiency, and robustness. The source code is available at https://github.com/Clarkxielf/Recurrent-Multi-View-Collaborative-Registration-Network.

Applicability of an Ionising Radiation Measuring System for Real-Time Effective-Dose-Optimised Route Finding Solution during Nuclear Accidents

The reduction in the effective dose of evacuated injured persons through contaminated areas of nuclear accidents is an essential emergency services requirement. In this context, there appeared a need to develop a dose-optimised route finding method for firefighting rescue vehicles, which includes the development of a real-time decision support measurement and evaluation system. This determines and visualises the radiation exposure of possible routes in a tested area. The system inside and outside of the vehicle measures the ambient dose equivalent rate, the gamma spectra, and also the airborne radioactive aerosol and iodine levels. The method uses gamma radiation measuring NaI(Tl) scintillation detectors mounted on the outside of the vehicle, to determine the dose rate inside the vehicle using the previously recorded attenuation conversation function, while continuously collecting the air through a filter and using an alpha, beta, and gamma radiation measuring NaI(Tl)+ PVT + ZnS(Ag) scintillator to determine the activity concentration in the air, using these measured values to determine the effective dose for all routes and all kinds of vehicles. The energy-dependent shielding effect of the vehicle, the filtering efficiency of the collective protection equipment, and the vehicle’s speed and travel time were taken into account. The results were validated by using gamma point sources with different activity and energy levels. The measurement results under real conditions and available real accident data used in our simulations for three different vehicles and pedestrians proved the applicability of the system. During a nuclear accident based on our model calculations, the inhalation of radioactive aerosols causes a dose almost an order of magnitude higher than the external gamma radiation caused by the fallout contamination. The selection of the appropriate vehicle and its route is determined by the spectrum that can be measured at the accident site but especially by the radioactive aerosol concentration in the air that can be measured in the area. In the case of radiation measuring detectors, the shielding effect of the carrier vehicle must be taken into account, especially in the case of heavy shielding vehicles. The method provides an excellent opportunity to reduce the damage to the health of accident victims and first responders during rescue operations.

Development and Evaluation of a Hybrid Measurement System to Determine the Kinematics of the Wrist.

Optical Motion Capture Systems (OMCSs) are considered the gold standard for kinematic measurement of human movements. However, in situations such as measuring wrist kinematics during a hairdressing activity, markers can be obscured, resulting in a loss of data. Other measurement methods based on non-optical data can be considered, such as magneto-inertial measurement units (MIMUs). Their accuracy is generally lower than that of an OMCS. In this context, it may be worth considering a hybrid system [MIMU + OMCS] to take advantage of OMCS accuracy while limiting occultation problems. The aim of this work was (1) to propose a methodology for coupling a low-cost MIMU (BNO055) to an OMCS in order to evaluate wrist kinematics, and then (2) to evaluate the accuracy of this hybrid system [MIMU + OMCS] during a simple hairdressing gesture. During hair cutting gestures, the root mean square error compared with the OMCS was 4.53° (1.45°) for flexion/extension, 5.07° (1.30°) for adduction/abduction, and 3.65° (1.19°) for pronation/supination. During combing gestures, they were significantly higher, but remained below 10°. In conclusion, this system allows for maintaining wrist kinematics in case of the loss of hand markers while preserving an acceptable level of precision (<10°) for ergonomic measurement or entertainment purposes.

SQUID magnetoneurography: an old-fashioned yet new tool for noninvasive functional imaging of spinal cords and peripheral nerves.

We are engaged in the development and clinical application of a neural magnetic field measurement system that utilizes biomagnetic measurements to observe the activity of the spinal cord and peripheral nerves. Unlike conventional surface potential measurements, biomagnetic measurements are not affected by the conductivity distribution within the body, making them less influenced by the anatomical structure of body tissues. Consequently, functional testing using biomagnetic measurements can achieve higher spatial resolution compared to surface potential measurements. The neural magnetic field measurement, referred to as magnetoneurography, takes advantage of these benefits to enable functional testing of the spinal cord and peripheral nerves, while maintaining high spatial resolution and noninvasiveness. Our magnetoneurograph system is based on superconducting quantum interference devices (SQUIDs) similar to the conventional biomagnetic measurement systems. Various design considerations have been incorporated into the SQUID sensor array structure and signal processing software to make it suitable for detecting neural signal propagation along spinal cord and peripheral nerve. The technical validation of this system began in 1999 with a 3-channel SQUID system. Over the course of more than 20 years, we have continued technological development through medical-engineering collaboration, and in the latest prototype released in 2020, neural function imaging of the spinal cord and peripheral nerves, which could also be applied for the diagnosis of neurological disorders, has become possible. This paper provides an overview of the technical aspects of the magnetoneurograph system, covering the measurement hardware and software perspectives for providing diagnostic information, and its applications. Additionally, we discuss the integration with a helium recondensing system, which is a key factor in reducing running costs and achieving practicality in hospitals.

Development of Amplitude Measurement System for Ultrasonic Vibration Assisted Micro Forming

Microforming is a process that involves forming a material through plastic deformation at a micro level. However, this method encounters an issue at the micro-scale known as the size effect. There are several new approaches to overcome these difficulties, one of which is using Ultrasonic Vibration Assisted (UVA) micro forming. UVA micro forming is a forming method by applying high-frequency vibrations to the workpiece to reduce forming forces, increase smooth zone, reduce surface roughness, and increase accuracy. A bolted Langevin transducer is needed to produce vibration, which converts electrical signals into acoustic signals in the ultrasonic frequency range. Therefore, the vibration characteristics must be considered in detail to find the best parameters in the micro forming process. This study aims to develop an amplitude measurement system for UVA micro forming. Several things that need to be considered in designing a measurement system are pre-stress characteristics, resonant frequency of the machine, and the amplitude of the vibration generated by the system. Firstly, a pre-stress test was carried out by tightening the pre-stress bolt slowly until the resonant frequency did not change. Then, the resonant frequency is measured using signal generator, oscilloscope, transducer, and resistor to determine the system’s resonant frequency. Finally, the vibration amplitude is measured by observing the displacement at the end of the punch using a digimatic indicator. The result shows that the resonance frequency that produces longitudinal vibration for UVA micro forming system is 28,720 Hz, with a pre-stress of 30 MPa with torque of 14.36 Nm, and total displacement on the normal axis is 9 μm.