Accuracy Of Sensor Research Articles

An accurate and sensitive sensor based on the internal filtration effect for the detection of alkaline phosphatase and ascorbic acid by the Fenton reaction and dual readout signal

Ascorbic acid (AA) and alkaline phosphatase (ALP) in human serum are indispensable substances in the process of biological metabolism, and their abnormal contents are strongly associated with a range of diseases. Therefore, it is meaningful to develop a simple, accurate and sensitive assay for the detection of AA and ALP. Up-conversion nanoparticles (UCNPs) have some unique characteristics, especially, the potential for background-free excitation by the near-infrared region (NIR) significantly improves the limits of detection (LODs). Moreover, sensors based on the inner filter effect (IFE) do not require covalent linkage between receptors and fluorophores or surface modification, thus the probe fabrication is simple and flexible UCNP-based. Therefore, a simple, selective, sensitive, and flexible sensing system for the detection of AA and ALP is proposed by combining the IFE and the cyclic signal amplification strategy. Under ideal circumstances, the LODs of ALP through the colorimetric and fluorescence method were 0.192 U/L and 0.013 U/L. The established sensing platform was applied to assessing ALP activity in human serum, and the detection results are close to those of commercially available kits, indicating its immense potential as an effective and convenient tool for monitoring ALP activity in clinical settings.

Machine Learning-Assisted High-Throughput Strategy for Real-Time Detection of Spermine Using a Triple-Emission Ratiometric Probe.

In this study, we designed and fabricated a spermine-responsive triple-emission ratiometric fluorescent probe using dual-emissive carbon nanoparticles and quantum dots, which improve the sensor's accuracy and reduce interfering environmental effects. The probe is advantageous for the proportionate detection of spermine because it has good emission resolution, and the maximum points of the two emission peaks differ by 95 nm. As a proof of concept, cuvettes and a 96-well plate were combined with a smartphone and YOLO series algorithms to accomplish real-time, visual, and high-throughput detection of seafood and meat freshness. In addition, the reaction mechanism was verified by density functional theory and fundamental characterizations. Upon exposure to different amounts of spermine, the intensity of the fluorescent probe changed linearly, and the fluorescent color shifted from yellow-green to red, with a limit of detection of 0.33 μM. To enable visual identification of food-originated spermine, a hydrogel-based visual sensing platform was successfully developed utilizing the triple-emission fluorescent probe. Consequently, spermine could be identified and quantified without complicated equipment.

Time-varying uncertainty evaluation of the shock wave pressure measurements with small samples in an aerospace shock tube

Shock tube is a crucial device for the dynamic calibration of pressure sensors in aerospace and defense fields. Accurate measurement of the shock wave pressure (SWP) in the shock tube and reliable evaluation of the measurement uncertainty are the basis for improving the calibration accuracy of pressure sensors. However, the repeated measurement results of the SWP in shock tube have typical features of time-varying and small samples, leading to a poor reliability of the measurement uncertainty evaluation. To address this issue, an improved method is proposed to accurately evaluate the time-varying uncertainty of the SWP measurement results with small samples in an aerospace shock tube. The time-varying SWP measurement signals are firstly decomposed into four components by the multicomponent extraction based on signal decomposition algorithms. For the repeated SWP measurement data with small samples, a sample size expansion based on the bootstrap method is presented to reduce the mean estimation error of the four components. A time-varying uncertainty evaluation model of the four components is established based on the conjugate prior Bayesian theory. The reliable evaluation of the time-varying uncertainty of the SWP measurements is finally realized according to the uncertainty propagation principle. Simulations and the SWP measurement experiments in an aerospace shock tube are carried out to validate the performance of the proposed method. The results show that the proposed method works well in the time-varying uncertainty evaluation of the SWP measurements with small samples. Furthermore, the comparative experiments demonstrate the superiority of the proposed method over the Bessel method and the Bayesian method for the SWP measurement uncertainty evaluation in both accuracy and reliability.

Testing the Real-World Accuracy of the Dexcom G6 Pro CGM During the Insulin-Only Bionic Pancreas Pivotal Trial.

Continuous glucose monitors (CGMs) have transformed the way people with type 1 diabetes can self-monitor glucose levels. Past studies have evaluated the accuracy of CGMs in clinic-based studies, but few have analyzed their accuracy in real-world settings. The Insulin-Only Bionic Pancreas Trial provided the opportunity to assess real-world accuracy of the blinded Dexcom G6 Pro sensor over the first 48-60 h of wear using a blood glucose meter (BGM) as a comparator for 1073 CGM-BGM pairs across 53 participants. The mean absolute relative difference (MARD) was 11.0% over a median period of 50 h (range 47-79 h). The MARD was 13.6% in the first 12 h, 10.5% in hours 12-24, and 10.1% after the first 24 h. These results are comparable with accuracy shown previously with laboratory-based measurements and provide real-world evidence of Dexcom G6 Pro accuracy, which improved after the first 12 h and then remained stable thereafter. Clinical Trial Registry: clinicaltrials.gov; NCT04200313.

Photometric Monitoring of Electronic Cigarette Puff Topography.

To study and monitor the adverse health consequences of using electronic cigarettes, a user's puff topography, which are quantification parameters of the user's vaping habits, plays a central role. In this work, we introduce a topography sensor to measure the mass of total particulate matter generated in every puff and to estimate the nicotine yield. The sensor is compact and low-cost, and is integrated into the electronic cigarette device to promptly and conveniently monitor the user's daily puff topography. The topography sensor is comprised of a photometric sensor and a pressure sensor. The photometric sensor measures the mass concentration of the aerosol, based on scattering of near-infrared light from airborne particles, while the pressure sensor measures the flow rate. The topography sensor was tested under various conditions including a wide range of atomizer power, puff duration, and inhalation pressure. The sensor's accuracy was validated by comparing the sensor's readings with reference measurements, and the results matched closely with the trends reported by existing studies on electronic cigarettes. An example application for tracking a user's puff topography was also demonstrated. Our topography sensor holds great promise in mitigating the health risks of vaping, and in promoting quality control of electronic cigarette products.

A novel mechanism for low- and high pressure measurement with variable-thickness diaphragm

ABSTRACT In pressure sensors, pressure measurement is based on the movements of the elastic elements under different pressures. Since there is no elastic element able to move under low and high pressures, there is a serious limitation to measuring low and high pressures concurrently. This paper proposes an innovative mechanism for measuring high and low pressures concurrently. In the proposed mechanism, a variable-thickness diaphragm and a protective part were used to measure a broad range of pressures. The proposed mechanism was manufactured and the accurate pressure source was used to test the behavior of the mechanism under different pressures. Using this configuration raised the sensitivity and accuracy of high-range pressure sensors, and increased the turndown ratio to 1500 by employing a new elastic element. Employing this mechanism in pressure sensors leads to use one pressure sensor for measuring a broad range of pressure instead of using several distinct sensors.

Influence of Temperature on 17-4PH Characteristics of Torque Sensor Elastomer

The elastomer is the core component of the torque sensor, and its performance directly affects the accuracy of the torque sensor. The elastic modulus, as a key parameter of elastomers, can affect the output performance of sensors at extreme temperatures due to the temperature response. In this paper, the mathematical model of the torque sensor is analyzed, and the theoretical model of the elastic modulus of the material under the action of temperature is constructed. Then, the temperature performance test and the torque calibration test under the changing temperature environment are carried out for the elastomer made of 17-4PH material. The test results show that the relationship between the elastic modulus of the elastomer and the temperature is nonlinear, and the higher the temperature, the faster the elastic modulus decreases. The change law of the elastic modulus model considering the temperature effect is consistent with the change of the sensor output value, which provides a reliable basis for the precise design of the torque sensor.

Finite element modeling of the electrical impedance tomography technique driven by machine learning

To create a human-like skin for a robotic application, current touch sensor technologies have a few drawbacks. Electrical Impedance Tomography (EIT) is a candidate for this application due to its applicability over complex geometries; nevertheless, it has accuracy concerns. This study employs artificial neural networks (ANNs) to investigate the accuracy and capability of EIT-based touch sensors. A finite element (FE) model is utilized to solve the forward EIT problem while simultaneously determining the system’s comprehensive mechanical response. The FE model is comprised of a polyurethane (PU) foam domain, a conductive spray layer and a set of sixteen electrodes. To replicate the process of touching the sensor body, a punch of varying diameters and touch forces is utilized. The mechanical response of the sensor body is modeled using the hyperfoam material model calibrated through experimental uniaxial and shear test data, while the electric conductivity of the sprayed skin surface is obtained experimentally as function of applied strain. The viscoelastic behavior of the PU foam material is also obtained experimentally. These experimental data were implemented in the FE model through user subroutines to model the mechanical and electrical properties of the sensor in the EIT forward problem. The traditional EIT inverse problem image reconstruction was replaced utilizing ANNs as an alternative to extract mechanics based parameters. The ANNs were created to predict the spatial coordinates of the touch point, and they were proven to be extremely accurate. Using the EIT voltage readings as input, the ANNs were utilized to forecast the system’s mechanical behavior such as contact pressure, contact area, indentation depth, and touching force.

Practical examples for the flight data compatibility check

Accurate information about aircraft speed, altitude, and aerodynamic flow angles is essential for evaluating aircraft performance and handling qualities. These quantities are determined from air data measurements taken by sensors normally located near the aircraft cockpit. Since these sensors are affected by the distorted flow field around the fuselage, a correction must be applied. Before the first flight, a set of calibration parameters is usually determined from wind tunnel experiments or CFD calculations. However, the Data Compatibility Check (DCC) method allows a more accurate air data sensor calibration during the certification flight test. This method reconstructs air data quantities from inertial acceleration, angular rate measurements and the flight path. By comparing the reconstructed quantities with the measured ones, the structure and parameters of air data sensor models can be identified. In this paper, an introduction to the data compatibility check method and the setup used in a flight test for system identification is given. The DCC is applied on data gathered from a test campaign with the new DLR research aircraft Dassault Falcon 2000LX ISTAR. Use cases for the calibration of the nose boom airflow vanes and the correction of sensors during large sideslip maneuvers will be presented in this paper.

Design of the Gianyar – Amlapura 150 KV Tower Delivery Landslide Detection System

In supporting tourism on the Island of the Gods, PLN personnel are expected to provide the best possible service to consumers. Therefore, the Bali Transmission System needs to provide a reliable transmission system that provides world-class services to electricity consumers in Bali. Current monitoring methods are not effective enough to monitor the critical condition of towers and are prone to landslides which can occur at any time, especially during the rainy season and extreme weather. The need for a reliable transmission system led researchers to the idea of ​​having monitoring equipment that can work in real time to detect the condition of the tower or the movement of the ground around the tower as quickly as possible. The measurement accuracy of the MPU6050 sensor reaches 98.8% which can be said to be very suitable as a sensor for detecting the angle of the slope of the ground, the slightest slope can be detected

Fabrication of an electrochemical sensor based on eggshell waste recycling for the voltammetric simultaneous detection of the antibiotics ofloxacin and ciprofloxacin

In this work, an accurate, highly sensitive, and economical electrochemical sensor based on a carbon paste electrode modified by Ca2CuO3 nanostructure (Ca2CuO3 NS) was constructed using Eggshell waste recycling as a cheap source of calcium. The Ca2CuO3 NS was analyzed using FTIR, SEM, and XRD measurements. The synthesized nanomaterials utilized for the first time to enhance the electrocatalytic efficiency of carbon paste electrode (CPE) toward fluoroquinolones antibiotics ofloxacin (OFL) and ciprofloxacin (CIP), The drugs used to treat pneumonia caused by COVID-19. The synthesized Ca2CuO3 NS dramatically enhanced the anodic peak response of CPE toward both drugs compared to the unmodified one and other modified electrodes. The simultaneous detection of the two antibiotics was performed in the linear range of 0.09–1.0 μM for OFL and 0.05–0.8 μM for CIP with the LOD of 0.027 μM and 0.012 μM, respectively. The suggested method was applied successfully to determine OFL and CIP in real samples.

A-360 Reproducible Graphene Sensor with Desiccated Biology

Abstract Background Graphene, a two-dimensional material composed of carbon atoms, has garnered significant attention for its potential application in biosensors due to its unique electrical properties. Despite its promising attributes, however, the non-reproducible nature of graphene biosensors has hindered their widespread commercialization. This issue arises from the difficulty in obtaining a clean graphene layer due to: photoresist such as PMMA residues that effect the performance of graphene; etching process which affect the physical and chemical properties of graphene; variation in the coating of bio-receptors on to graphene. All these issues affect reliable and accurate sensor performance. These challenges have made it difficult for graphene biosensors to reach their full potential as commercial products and have limited their widespread adoption. Hememics has developed a unique process for synthesizing and fabricating graphene-based biosensors. This represents a major breakthrough in the commercialization of graphene-based biosensors and will likely lead to widespread adoption of these devices in the medical and biotechnology industries. Methods HemChip™ contains multiple sensor areas that are coated with ultra-sensitive graphene. Using Hememics’ unique proprietary process, the graphene layer is functionalized with bioreceptors such as aptamers and stabilized with HemSol™ to allow room temperature storage. The relative difficulty of stabilizing aptamers on a hydrophobic graphene substrate has been overcome by using HemSol™ to secure its structure during dry storage. Each sensor on the biochip allows independent functionalization with a bioreceptor. These sensors coated with bioreceptors are freeze-dried and stored in a sealed pouch at room temperature until use. Results We have tested over 2000 samples using our modified process. The functionality of the graphene-based biosensor is evaluated by measuring the distribution of Dirac points. The results show that the distribution follows a Gaussian distribution with a median of 80 mV and a very narrow spread of approximately 35 mV. This indicates that the majority of the Dirac points are tightly clustered around the median value of 80 mV. Furthermore, one standard deviation of the Dirac points fall within the range of 50 mV to 120 mV. In contrast, the standard published process of producing graphene-based biosensor shows a much wider distribution of Dirac points, ranging from 250–1500 mV. Conclusion Hememics has developed a production process for making graphene-based biosensors with desiccated detection biology that deliver repeatable performance data. The results of the Dirac point distribution demonstrate the high precision and accuracy for the functionalized biosensors. This combined with the ability to mass produce the biosensor, make graphene-based biosensors an attractive molecular and immuno-based detection tool. Additionally, the results suggest that the Hememics process can be adapted to produce functional graphene-based biosensors for wide ranging bio detection applications.

UASN‐3D: An energy efficient localization based on LEACH‐BR algorithm (EELBL‐BR)

AbstractUnderwater acoustic sensor networks (UASN) research is gaining popularity as it has various applications such as military communication, oil rig maintenance, animal survival, linking submarines to land, gathering data for water monitoring, and other commercial fields. The two most critical requirements for the application's proper operation are the accurate knowledge of sensor node locations and the efficient transmission of accurate underwater sensor node information to the base station with efficient energy consumption. The proposed energy efficient localization based on the LEACH‐beacon and reinforced node (EELBL‐BR) algorithm satisfies both the requirements in 3D‐UASN. The proposed algorithm considers the deployment and computation of accurate location of sensor nodes in the underwater environment by applying I‐LASP (improvement of localization algorithm for compensating stratification effect based on extended improved particle swarm optimization technique) (Yadav N, Khilar PM. Trans Emerg Telecommun Technol. 2023;34:e4772.) for 3D environment. It performs clustering of sensor nodes for enhancing network lifetime using three different types of nodes such as beacon, reinforced, and member nodes. The proposed clustering LEACH‐BR (low‐energy adaptive clustering hierarchy‐beacon and reinforced nodes) algorithm is based upon the LEACH algorithm which provides accurate location of all the sensor nodes, improves energy consumption and reliability in the underwater environment. The result shows that the proposed algorithm EELBL‐BR, considering both beacon and reinforced nodes, provides the improvement in the number of alive nodes, reduction in the number of dead nodes, reduction in energy consumption and enhances residual energy in the UASN by 68.90%, 51.91%, 51.47%, and 68.12% respectively with respect to the number of rounds as compared to that of the existing algorithm by Rizvi et al. (Wirel Pers Commun. 2022;124(4):3725–3741.) and thus outperforms the existing algorithm (Rizvi HH, Khan SA, Enam RN. Wirel Pers Commun. 2022;124(4):3725–3741.).

Enhanced dual-mode electrochemical zinc ion sensing by electric field-driven bi-directional mass transport

Electric field-driven bi-directional mass transport strategy was introduced for high accuracy and sensitive electrochemical (EC) zinc ion chip. The detection sensitivity and sensing accuracy of the EC sensor were significantly improved. The related process parameters including inter-electrode spacing and electrode absorbability were explored and surveyed. A limit of detection of 33.1 pM of chip was achieved for detecting zinc ion with excellent selectivity, stability, and flexibility, which was two orders of magnitude better than that without electric field. The mechanism of the EC chip was elucidated and discussed based on the experimental results. The real samples were detected by the chip integrating with smartphone-based portable system to prove the practical application. This work would provide new insights of the sensor for mobile environmental detection and biomedical monitoring.

Comparison of photoacoustic spectroscopy and cavity ring-down spectroscopy for ambient methane monitoring at Hohenpeißenberg

Abstract. With an atmospheric concentration of approximately 2000 parts per billion (ppbV, 10−9), methane (CH4) is the second most abundant greenhouse gas (GHG) in the atmosphere after carbon dioxide (CO2). The task of long-term and spatially resolved GHG monitoring to verify whether climate policy actions are effective is becoming more crucial as climate change progresses. In this paper we report the CH4 concentration readings of our photoacoustic (PA) sensor over a 5 d period at Hohenpeißenberg, Germany. As a reference device, a calibrated cavity ring-down spectrometer, Picarro G2301, from the meteorological observatory of the German Weather Service (DWD) was employed. Trace gas measurements with photoacoustic instruments promise to provide low detection limits at comparably low costs. However, PA devices are often susceptible to cross-sensitivities related to fluctuating environmental conditions, e.g. ambient humidity. The obtained results show that for PA sensor systems non-radiative relaxation effects induced by varying humidity are a non-negligible factor. Applying algorithm compensation techniques, which are capable of calculating the influence of non-radiative relaxation effects on the photoacoustic signal, increase the accuracy of the photoacoustic sensor significantly. With an average relative deviation of 1.11 % from the G2301, the photoacoustic sensor shows good agreement with the reference instrument.

Determination of regularities that influence the acoustic pressure and accuracy of inertial sensors

This study investigated the influence of high-intensity acoustic radiation on the elements of a navigation system, namely, the angular velocity sensor DUSU-2AS. The measurement error of the device under the influence of acoustic pressure is determined. High-intensity acoustic radiation causes measurement errors that are greater than the sensitivity threshold of the device. Numerical analyses of the degree of influence when the penetrating acoustic radiation is 140 dB demonstrate that the maximum bending vibration is 4.471 µm. Computational models for calculating the diffraction of the sound waves are proposed and tested. This study assessed the influence degree of penetrating acoustic radiation on inertial sensors, as well as the degree of danger of technological risks such as resonance manifestations. Acoustic radiation that passes into a device generates many vibration modes on the surface and can have a considerable effect on the precision of inertial sensors.

Realistic sensor simulations for the digital twin

Digital twins use actual sensor data to replicate the current state of a plant in a virtual model. They can be used to evaluate the current state, predict future behavior, and thus allow to refine control or optimize operation, enable predictive maintenance as well as detection of anomalies and failures.The model of a digital twin includes models of the components, behaviors and dynamics of a system. With the ability to simulate real scenarios, such models can therefore also be used before a plant is actually implemented, e.g., to predict the actual performance, identify potential issues for the implementation and to develop optimal operation strategy and algorithms. Furthermore, interfaces may be defined, implemented, and tested with such models allowing fast and easy commissioning of the physical implementation.Accurate digital twins therefore also need to include realistic sensor models, considering adverse effects that impact their output signals. The proposed work presents approaches for accurate sensor simulations allowing researchers and industries to assess sensor performance, optimize algorithms, and evaluate system-level integration. We address Frequency Modulated Continuous Wave (FMCW) radar sensors and time-of-flight cameras as examples for far-field sensors and capacitive sensors as an example for near-field sensors. The approaches can be transferred to other sensors, e.g., ultrasound sensors, LiDAR sensors and inductive or magnetic sensors so that a wide range of industrial sensors can be covered.The proposed simulations are benchmarked with different tests, including real-world experiments and compared with the corresponding real sensors.

An In Situ Signal Amplification Sensor for Measuring In‐Plane Current Density Distribution in a Proton Exchange Membrane Fuel Cell

Inconsistency of current density distribution in‐plane in fuel cells is a common phenomenon. This study develops a novel highly integrated sensor with the feature of signal in situ amplification for measuring in‐plane current density. First, the sensor is designed and fabricated based on the idea of in situ amplification of in‐plane signals before transmission. Then, the sensor accuracy is quantitatively evaluated prior to fuel cell experiments based on a single‐point calibration approach. Finally, the distribution of in‐plane current density is observed using the sensor in the fuel cell test system. Additionally, the measurement accuracy of the circuit current in the test bench is compared by introducing the calibrated segment average amplification factors. The results indicate that these signals amplified by the sensor can effectively withstand the effects of signal transmission loss and interference, and it can be determined that the measurement accuracy of the sensor is controlled within 97% in the small current range and within 98% in the nonsmall current range in normal operation. This work provides a feasible solution for in situ measurements of in‐plane current density, with significant improvements in signal acquisition, structural matching, and fabrication process compared to existing such sensors.

Automated Georectification, Mosaicking and 3D Point Cloud Generation Using UAV-Based Hyperspectral Imagery Observed by Line Scanner Imaging Sensors

Hyperspectral sensors mounted on unmanned aerial vehicles (UAV) offer the prospect of high-resolution multi-temporal spectral analysis for a range of remote-sensing applications. However, although accurate onboard navigation sensors track the moment-to-moment pose of the UAV in flight, geometric distortions are introduced into the scanned data sets. Consequently, considerable time-consuming (user/manual) post-processing rectification effort is generally required to retrieve geometrically accurate mosaics of the hyperspectral data cubes. Moreover, due to the line-scan nature of many hyperspectral sensors and their intrinsic inability to exploit structure from motion (SfM), only 2D mosaics are generally created. To address this, we propose a fast, automated and computationally robust georectification and mosaicking technique that generates 3D hyperspectral point clouds. The technique first morphologically and geometrically examines (and, if possible, repairs) poorly constructed individual hyperspectral cubes before aligning these cubes into swaths. The luminance of each individual cube is estimated and normalised, prior to being integrated into a swath of images. The hyperspectral swaths are co-registered to a targeted element of a luminance-normalised orthomosaic obtained using a standard red–green–blue (RGB) camera and SfM. To avoid computationally intensive image processing operations such as 2D convolutions, key elements of the orthomosaic are identified using pixel masks, pixel index manipulation and nearest neighbour searches. Maximally stable extremal regions (MSER) and speeded-up robust feature (SURF) extraction are then combined with maximum likelihood sample consensus (MLESAC) feature matching to generate the best geometric transformation model for each swath. This geometrically transforms and merges individual pushbroom scanlines into a single spatially continuous hyperspectral mosaic; and this georectified 2D hyperspectral mosaic is then converted into a 3D hyperspectral point cloud by aligning the hyperspectral mosaic with the RGB point cloud used to create the orthomosaic obtained using SfM. A high spatial accuracy is demonstrated. Hyperspectral mosaics with a 5 cm spatial resolution were mosaicked with root mean square positional accuracies of 0.42 m. The technique was tested on five scenes comprising two types of landscape. The entire process, which is coded in MATLAB, takes around twenty minutes to process data sets covering around 30 Ha at a 5 cm resolution on a laptop with 32 GB RAM and an Intel® Core i7-8850H CPU running at 2.60 GHz.

Improving the electrochemical properties of Ti3C2Tx MXene for H2S electrochemical sensor by calcination

The existence level and metabolic mechanism of hydrogen sulfide (H2S) have been proved to have an important impact on organisms, even affecting the generation and development of many neurological diseases. Therefore, it is essential to develop sensitive and accurate H2S sensors to detect H2S concentration at trace level and provide effective research tools for studying the mechanism of action of H2S on organisms. MXene is a class of two-dimensional transition metal carbonitrides with a graphene-like structure, which indicating great application prospects as a biosensor due to its large specific surface area and good conductivity. In this work, the properties of multilayer Ti3C2Tx MXene materials are optimized concerning their physical structure and functional groups. Based on the Li + intercalation method, SL-Ti3C2Tx MXene is prepared by a mild route, and its electrochemical performance is optimized by high temperature calcination under high purity argon conditions. The change in material properties at high temperature is discussed through structural and chemical analysis, and the optimal calcination temperature is determined to be 700 °C. The constructed H2S electrochemical sensor exhibits high stability and reproducibility in applications, with a detection range of 0.1–500 μM, and the detection limit is reduced to 5.77 nM.