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Eng. Proc., 2021, ECSA-8

 The 8th International Electronic Conference on Sensors and Applications

Online | 1–15 November 2021

Volume Editors: Stefano Mariani, Alberto Vallan, Stefan Bosse and Francisco Falcone

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Cover Story (view full-size image): This issue of Engineering Proceedings gathers papers presented at the 8th International Electronic Conference on Sensors and Applications (ECSA-8), held online on 1–15 November 2021. Video [...] Read more.
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Editorial
Preface: Proceedings of the 8th International Electronic Conference on Sensors and Applications
Eng. Proc. 2021, 10(1), 79; https://doi.org/10.3390/engproc2021010079 - 30 Jan 2022
Viewed by 515
Abstract
This issue of Engineering Proceedings gathers the papers presented at the 8th International Electronic Conference on Sensors and Applications (ECSA-8), held online on 1–15 November 2021, through the sciforum.net platform developed by MDPI [...] Full article

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Proceeding Paper
Material Damping Analysis of Triangular Cantilever Beam for Electromagnetic Vibration Energy Harvesting Applications
Eng. Proc. 2021, 10(1), 1; https://doi.org/10.3390/ecsa-8-11272 - 01 Nov 2021
Viewed by 210
Abstract
Triangular cantilever beams are often desired in piezoelectric vibration energy harvesting applications, as they result in a better performance due to the higher and more uniform stress they exhibit. However, the application of this cantilever geometry has not yet been explored for other [...] Read more.
Triangular cantilever beams are often desired in piezoelectric vibration energy harvesting applications, as they result in a better performance due to the higher and more uniform stress they exhibit. However, the application of this cantilever geometry has not yet been explored for other transduction methods. In this study, the application of a triangular cantilever beam for a cantilevered electromagnetic vibration energy harvester was examined by analyzing its material damping and comparing it to a regular rectangular beam. The material damping of the harvester was predicted through finite element analysis using the critically damped stress method. Under the same beam volume or beam length, the triangular cantilever beam exhibited an approximately 7.1% lower material damping when compared to a rectangular cantilever beam. Further analysis shows that the triangular beam can also deliver a 21.7% higher power output than the rectangular beam. Full article
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Proceeding Paper
Optimization of Focused Ion Beam Patterning Parameters for Direct Integration of Plasmonic Nanostructures on Silicon Photodiodes
Eng. Proc. 2021, 10(1), 2; https://doi.org/10.3390/ecsa-8-11259 - 01 Nov 2021
Viewed by 193
Abstract
The possibility of integrating plasmonic nanostructures directly on an active device, such as a silicon photodetector, is a challenging task of interest in many applications. Among the available nanofabrication techniques to realize plasmonic nanostructures, Focused Ion Beam (FIB) is surely the most promising, [...] Read more.
The possibility of integrating plasmonic nanostructures directly on an active device, such as a silicon photodetector, is a challenging task of interest in many applications. Among the available nanofabrication techniques to realize plasmonic nanostructures, Focused Ion Beam (FIB) is surely the most promising, even if it is characterized by certain limitations, such as ion implantation in the substrate. In this work, we demonstrate the direct integration of plasmonic nanostructures directly on an active Si-photodetector by patterning a silver film with FIB. To avoid ion implantation and to therefore guarantee unaltered device behavior, both the patterning parameters and the geometry of the nanostructures were implemented by Montecarlo and Finite-Difference Time-Domain simulations. Full article
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Proceeding Paper
Synthesis, Characterization, and Hydrogen Gas Sensing of ZnO/g-C3N4 Nanocomposite
Eng. Proc. 2021, 10(1), 3; https://doi.org/10.3390/ecsa-8-11337 - 08 Dec 2021
Viewed by 301
Abstract
In this paper, the preparation of the ZnO/g-C3N4 nanocomposite is discussed. The synthesis of nanocomposite is performed by the direct pyrolysis of the precursor (zinc acetate hexahydrate). The material synthesis is validated by different characterization tools, such as X-ray Diffraction [...] Read more.
In this paper, the preparation of the ZnO/g-C3N4 nanocomposite is discussed. The synthesis of nanocomposite is performed by the direct pyrolysis of the precursor (zinc acetate hexahydrate). The material synthesis is validated by different characterization tools, such as X-ray Diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM). The SEM and TEM analysis revealed the formation of nanorods on g-C3N4 support. The gas sensing property of the ZnO/g-C3N4 was studied for various concentrations of hydrogen gas. Response and recovery times were recorded by the sensor. Full article
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Proceeding Paper
Factory Oriented Technique for Thermal Drift Compensation in MEMS Capacitive Accelerometers
Eng. Proc. 2021, 10(1), 4; https://doi.org/10.3390/ecsa-8-11299 - 01 Nov 2021
Viewed by 180
Abstract
Capacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve their performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated using a lightweight [...] Read more.
Capacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve their performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated using a lightweight algorithm by knowing the characteristic thermal parameters of the accelerometer (Temperature Drift of Bias and Temperature Drift of Scale Factor). These parameters vary in each accelerometer and axis, making an individual calibration necessary. In this work, a simple and fast calibration method that allows the characteristic parameters of the three axes to be obtained simultaneously through a single test is proposed. This method is based on the study of two specific orientations, each at two temperatures. By means of the suitable selection of the orientations and the temperature points, the data obtained can be extrapolated to the entire working range of the accelerometer. Only a mechanical anchor and a heat source are required to perform the calibration. This technique can be scaled to calibrate multiple accelerometers simultaneously. A lightweight algorithm is used to analyze the test data and obtain the compensation parameters. This algorithm stores only the most relevant data, reducing memory and computing power requirements. This allows it to be run in real time on a low-cost microcontroller during testing to obtain compensation parameters immediately. This method is aimed at mass factory calibration, where individual calibration with traditional methods may not be an adequate option. The proposed method has been compared with a traditional calibration using a six-sided orthogonal die and a thermal camera. The average difference between the compensations according to both techniques is 0.32 mg/°C, calculated on an acceleration of 1 G; the maximum deviation being 0.6 mg/°C. Full article
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Proceeding Paper
An Effect of Coupling Factor on the Power Output for Electromagnetic Vibration Energy Harvester
Eng. Proc. 2021, 10(1), 5; https://doi.org/10.3390/ecsa-8-11279 - 01 Nov 2021
Viewed by 182
Abstract
Sensors are devices that measures a change in physical stimulus by converting it into an electronic signal which can be read by a designated instrument. To overcome the real-life challenges associated with powering a sensor using conventional batteries and chargers, this work focuses [...] Read more.
Sensors are devices that measures a change in physical stimulus by converting it into an electronic signal which can be read by a designated instrument. To overcome the real-life challenges associated with powering a sensor using conventional batteries and chargers, this work focuses on formulating analytical framework for designing an ecofriendly, cheap, almost zero retrofit implication (except on damage) power module for sensors using an electromagnetic vibration energy harvester. This principle relies on the electromagnetic transduction whose harvested voltage/power is formulated from Faraday law of electromagnetic induction. An electromagnetic parameter that determines the degree of transduction is the coupling constant. The value of coupling constant must be accurately set during harvester design because it directly determines harvester damping ratio and the power available for the sensor. All parameters used to compute the coupling except the flux density are constant. In this work, we focus on formulating a set of analytical equations that could effectively determine the harvester’s optimum magnetic flux parameter to be used in computing the optimum coupling constant, the electromagnetic damping ratio, and the harvested power at resonant. This work concludes that the degree of coupling for the determined optimum flux density increases with an increased load resistance and hence larger harvested power is available to power the sensor. Full article
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Proceeding Paper
Forest Burned Area Mapping Using Bi-Temporal Sentinel-2 Imagery Based on a Convolutional Neural Network: Case Study in Golestan Forest
Eng. Proc. 2021, 10(1), 6; https://doi.org/10.3390/ecsa-8-11291 - 01 Nov 2021
Cited by 1 | Viewed by 259
Abstract
Forest areas are profoundly important to the planet, since they offer considerable advantages. The mapping and estimation of burned areas covered with trees are critical during decision making processes. In such cases, remote sensing can be of great help. This paper presents a [...] Read more.
Forest areas are profoundly important to the planet, since they offer considerable advantages. The mapping and estimation of burned areas covered with trees are critical during decision making processes. In such cases, remote sensing can be of great help. This paper presents a method to estimate burned areas based on the Sentinel-2 imagery using a convolutional neural network (CNN) algorithm. The framework touches change detection using pre- and post-fire datasets. The proposed framework utilizes a multi-scale convolution block to extract deep features. We investigate the performance of the proposed method via visual and numerical analyses. The case study for this research is Golestan Forest, which is located in the north of Iran. The results of the burned area detection process show that the proposed method produces a performance accuracy rate of more than 97% in terms of overall accuracy, with a Kappa score greater than 0.933. Full article
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Proceeding Paper
OpenSim Visualization of the Classification of Finger Movements Based on Electromyography Signal as the Single-Input Variable during Predefined Movements
Eng. Proc. 2021, 10(1), 7; https://doi.org/10.3390/ecsa-8-11262 - 01 Nov 2021
Viewed by 157
Abstract
A classifier is commonly generated for multifunctional prostheses control or also as input devices in human–computer interfaces. The complementary use of the open-access biomechanical simulation software, OpenSim, is demonstrated for the hand-movement classification performance visualization. A classifier was created from a previously captured [...] Read more.
A classifier is commonly generated for multifunctional prostheses control or also as input devices in human–computer interfaces. The complementary use of the open-access biomechanical simulation software, OpenSim, is demonstrated for the hand-movement classification performance visualization. A classifier was created from a previously captured database, which has 15 finger movements that were acquired during synchronized hand-movement repetitions with an 8-electrode sensor array placed on the forearm; a 92.89% recognition based on a complete movement was obtained. The OpenSim’s upper limb wrist model is employed, with movement in each of the joints of the hand–fingers. Several hand-motion visualizations were then generated, for the ideal hand movements, and for the best and the worst (53.03%) reproduction, to perceive the classification error in a specific task movement. This demonstrates the usefulness of this simulation tool before applying the classifier to a multifunctional prosthesis. Full article
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Proceeding Paper
Solving the Inter-Ring Distances Optimization Problem for Pentapolar and Sextopolar Concentric Ring Electrodes Based on the Negligible Dimensions Model of the Electrode
Eng. Proc. 2021, 10(1), 8; https://doi.org/10.3390/ecsa-8-11280 - 01 Nov 2021
Viewed by 152
Abstract
Concentric ring electrodes are noninvasive and wearable sensors for electrophysiological measurement capable of estimating the surface Laplacian (second spatial derivative of surface potential) at each electrode. Previously, progress was made toward optimization of inter-ring distances (distances between the recording surfaces of a concentric [...] Read more.
Concentric ring electrodes are noninvasive and wearable sensors for electrophysiological measurement capable of estimating the surface Laplacian (second spatial derivative of surface potential) at each electrode. Previously, progress was made toward optimization of inter-ring distances (distances between the recording surfaces of a concentric ring electrode), maximizing the accuracy of the surface Laplacian estimate based on the negligible dimensions model of the electrode. However, this progress was limited to tripolar (number of concentric rings n equal to 2) and quadripolar (n = 3) electrode configurations only. In this study, the inter-ring distances optimization problem is solved for pentapolar (n = 4) and sextopolar (n = 5) concentric ring electrode configurations using a wide range of truncation error percentiles ranging from 1st to 25th. Obtained results also suggest consistency between all the considered concentric ring electrode configurations corresponding to n ranging from 2 to 5 that may allow estimation of optimal ranges of inter-ring distances for electrode configurations with n ≥ 6. Therefore, this study may inform future concentric ring electrode design for n ≥ 4 which is important since the accuracy of surface Laplacian estimation has been shown to increase with an increase in n. Full article
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Proceeding Paper
FTIR Spectroscopy for Evaluation and Monitoring of Lipid Extraction Efficiency for Murine Liver Tissues Analysis
Eng. Proc. 2021, 10(1), 9; https://doi.org/10.3390/ecsa-8-11321 - 01 Nov 2021
Viewed by 109
Abstract
Over the past several decades, growing research on lipids and lipidomic technologies have shown the important role played by lipids in many different situations. A powerful technique used for lipids detection and characterization in biological tissues is Fourier Transform Infrared (FTIR) spectroscopy. The [...] Read more.
Over the past several decades, growing research on lipids and lipidomic technologies have shown the important role played by lipids in many different situations. A powerful technique used for lipids detection and characterization in biological tissues is Fourier Transform Infrared (FTIR) spectroscopy. The main goal of the present work is to exploit FTIR spectroscopy as a tool for monitoring lipid extraction efficiency by evaluating three different lipid extraction methods in murine liver tissues. In particular, infrared spectra have been obtained in the 4000–600 cm−1 wavenumber region and the contributions of different functional groups have been evidenced. The ratio values estimated using the absorbance of selected bands related to different liver constituents have been used for a quantitative comparison of the efficiency of the different extraction methods. Full article
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Proceeding Paper
Humidity Dependence of Commercial Thick and Thin-Film MOX Gas Sensors under UV Illumination
Eng. Proc. 2021, 10(1), 10; https://doi.org/10.3390/ecsa-8-11246 - 01 Nov 2021
Viewed by 129
Abstract
Enhancing the performance of a chemo-resistive gas sensor is often challenging due to environmental humidity influencing its sensitivity and baseline resistance. One of the most promising ways of overcoming this challenge is through ultraviolet (UV) illumination of the sensing material. Most research has [...] Read more.
Enhancing the performance of a chemo-resistive gas sensor is often challenging due to environmental humidity influencing its sensitivity and baseline resistance. One of the most promising ways of overcoming this challenge is through ultraviolet (UV) illumination of the sensing material. Most research has focused on using UV with in-house developed sensors, which has limited their widespread use. In this work, we have evaluated if UV can enhance the performance of commercially available MOX-based gas sensors. The performance of five different MOX sensors has been evaluated, specifically SGX Microtech MiCS6814 (thin-film triple sensor), FIGARO TGS2620 (n-type thick film), and Alphasense VOC sensor (p-type thick film). These sensors were tested towards isobutylene gas under UV light at different wavelengths (UV-278 nm and UV-365 nm) to investigate its effect on humidity, sensitivity, baseline drift, and recovery time of each sensor. We found the response time of thin-film sensors for reducing gases was improved by 70 s under UV- 365 nm at normal operating temperatures. In addition, all the sensors were left in a dirty environment and the humid-gas testing was repeated. However, due to their robust design, the sensitivity and baseline drift of all the sensors remained the same. This indicates that UV has only limited uses with commercial gas sensors. Full article
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Proceeding Paper
The Use of Ultrasounds in the Preparation of Chemosensory Microstructures
Eng. Proc. 2021, 10(1), 11; https://doi.org/10.3390/ecsa-8-11294 - 01 Nov 2021
Cited by 1 | Viewed by 169
Abstract
In many fields, the goal is to obtain structures with small dimensions in the order of micro/nanometers. Small-sized systems can have countless applications in various industries such as cosmetology, medicine, and nutrition technology. Many techniques are used to obtain the most miniature possible [...] Read more.
In many fields, the goal is to obtain structures with small dimensions in the order of micro/nanometers. Small-sized systems can have countless applications in various industries such as cosmetology, medicine, and nutrition technology. Many techniques are used to obtain the most miniature possible spheres, such as interference with the composition, use of surfactants, or mechanical interference: rapid mixing, increased pressure, and ultrasound. The use of ultrasound in the development of colloidal systems can be an effective method of reducing the size of particles of dispersed phase and influencing the functions they represent. An important aspect here is the time during which the ultrasound is used. In this work, the influence of ultrasound on the chemosensory properties and size of produced ion-sensitive microspheres was investigated and compared. The chemosensory response of the developed microspheres was studied using spectrophotometry and spectrofluorimetry, while the size of the microsphere optodes was estimated by confocal microscopy. Full article
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Proceeding Paper
Computer Vision Technique for Blind Identification of Modal Frequency of Structures from Video Measurements
Eng. Proc. 2021, 10(1), 12; https://doi.org/10.3390/ecsa-8-11298 - 01 Nov 2021
Viewed by 169
Abstract
Operational modal analysis (OMA) is required for the maintenance of large-scale civil structures. This paper developed a novel methodology of non-contact-based blind identification of the modal frequency of a vibrating structure from its video measurement. There are two stages in the proposed methodology. [...] Read more.
Operational modal analysis (OMA) is required for the maintenance of large-scale civil structures. This paper developed a novel methodology of non-contact-based blind identification of the modal frequency of a vibrating structure from its video measurement. There are two stages in the proposed methodology. The first stage is extracting the motion data of the vibrating structure from its video using a complex steerable pyramid. In the second stage, the principal component analysis combined with analytical mode decomposition is used for modal frequency separation from the motion data. Numerical validation of the methodology on a 10 DOF model is presented. The application of the proposed methodology on the London Millennium Bridge is also presented. Full article
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Proceeding Paper
Microfluidic Devices with Selectable Optical Pathlength for Quality Control of Alcoholic Solutions
Eng. Proc. 2021, 10(1), 13; https://doi.org/10.3390/ecsa-8-11286 - 01 Nov 2021
Viewed by 152
Abstract
In this work, we present a micro-opto-fluidic platform for the analytical testing of alcoholic solutions (isopropyl alcohol, also known as isopropanol, and ethylene glycol) based on their absorption properties in the wavelength region 1.0–1.7 μm. The investigated fluidic channel is a rectangular glass [...] Read more.
In this work, we present a micro-opto-fluidic platform for the analytical testing of alcoholic solutions (isopropyl alcohol, also known as isopropanol, and ethylene glycol) based on their absorption properties in the wavelength region 1.0–1.7 μm. The investigated fluidic channel is a rectangular glass microcapillary externally coated with aluminum layers, to create a zig-zag guiding effect for the radiation provided by a tungsten lamp. Light crosses the capillary multiple times before being directed towards an optical spectrum analyzer; thanks to the enhanced optical path-length inside the sample, the measurement sensitivity is strongly increased. Preliminary experimental results are reported to show sensing performances. Full article
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Proceeding Paper
Classifier Module of Types of Movements Based on Signal Processing and Deep Learning Techniques
Eng. Proc. 2021, 10(1), 14; https://doi.org/10.3390/ecsa-8-11316 - 01 Nov 2021
Viewed by 310
Abstract
Human Activity Recognition (HAR) has been widely addressed by deep learning techniques. However, most prior research applied a general unique approach (signal processing and deep learning) to deal with different human activities including postures and gestures. These types of activity typically have highly [...] Read more.
Human Activity Recognition (HAR) has been widely addressed by deep learning techniques. However, most prior research applied a general unique approach (signal processing and deep learning) to deal with different human activities including postures and gestures. These types of activity typically have highly diverse motion characteristics, which could be captured with wearable sensors placed on the user’s body. Repetitive movements such as running or cycling have repetitive patterns over time and generate harmonics in the frequency domain, while postures such as sitting or lying are characterized by a fixed position, with some positional changes and gestures or non-repetitive movements being based on an isolated movement usually performed by a limb. This work proposes a classifier module to perform an initial classification among these different types of movements, which would allow for applying afterwards the most appropriate approach in terms of signal processing and deep learning techniques for each type of movement. This classifier has been evaluated using the PAMAP2 and OPPORTUNITY datasets using a subject-wise cross-validation methodology. These datasets contain recordings from inertial sensors on hands, arms, chest, hip, and ankles, collected in a non-intrusive way. In the case of PAMAP2, the baseline approach for classifying the 12 activities using 5-s windows in the frequency domain obtained an accuracy of 85.26 ± 0.25%. However, an initial classifier module could distinguish between repetitive movements and postures using 5-s windows reaching higher performances. Afterward, specific window size, signal format, and deep learning architecture were used for each type of movement module, obtaining a final accuracy of 90.09 ± 0.35% (an absolute improvement of 4.83%). Full article
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Proceeding Paper
Acoustic Positioning System for 3D Localization of Sound Sources Based on the Time of Arrival of a Signal for a Low-Cost System
Eng. Proc. 2021, 10(1), 15; https://doi.org/10.3390/ecsa-8-11307 - 01 Nov 2021
Viewed by 393
Abstract
The localization of sound sources has received increasing interest over the last few decades, given its wide range of applications. The triangulation method using the Time of Arrival (ToA) of a signal has shown to be useful and easy-to-use and, at [...] Read more.
The localization of sound sources has received increasing interest over the last few decades, given its wide range of applications. The triangulation method using the Time of Arrival (ToA) of a signal has shown to be useful and easy-to-use and, at the same time, provides accurate results. In this work, the acoustic trilateration method is applied in experimental measures to study and demonstrate its precision in air. Firstly, the method is tested in an anechoic chamber (low reverberating environment) demonstrating its functionality and accuracy. The next step has been the application of the method by using a low-cost system to demonstrate how a non-anechoic environment affects the accuracy of the localization. The detection of the received signal is implemented using a cross-correlation method in the time domain for both cases. Furthermore, the influence of the number and positions of the receiver that are used for this process in the accuracy of the results is also studied. Full article
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Proceeding Paper
Assessment of Rogowski Coils for Measurement of Full Discharges in Power Transformers
Eng. Proc. 2021, 10(1), 16; https://doi.org/10.3390/ecsa-8-11309 - 01 Nov 2021
Cited by 1 | Viewed by 199
Abstract
Science and industry have sought to develop systems aiming to avoid total failures in power transformers since these machines can be working under overloads, moisture, mechanical and thermal stresses, among others. These non-conformities can promote the degradation of the insulation system and lead [...] Read more.
Science and industry have sought to develop systems aiming to avoid total failures in power transformers since these machines can be working under overloads, moisture, mechanical and thermal stresses, among others. These non-conformities can promote the degradation of the insulation system and lead the transformer to total failure. In the incipient stages of these faults, it is common to detect Full Discharges (FDs), which are short circuits between degraded coils. Therefore, several techniques were developed to perform FD diagnosis using UHF, acoustics, and current sensors. In this scenario, this article presents a mathematical model for Rogowski coils and compares two different types of cores: Ferrite and Teflon. For this purpose, FDs were induced in an oil-filled transformer. The sensitivity and frequency response of the Rogowski coils were compared. This analysis was achieved using the Power Spectrum Density (PSD) and the energy of the acquired signals. Additionally, the Short-Time Fourier Transform (STFT) was applied to detect repetitive discharges. The results indicated that the Ferrite core increases the sensitivity by 50 times in the frequency band between 0 and 1 MHz. However, the Teflon core showed higher sensitivity between 5 and 10 MHz. Full article
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Proceeding Paper
Surface Reconstruction for Ground Map Generation in Autonomous Excavation
Eng. Proc. 2021, 10(1), 17; https://doi.org/10.3390/ecsa-8-11296 - 01 Nov 2021
Viewed by 112
Abstract
Excavator’s main tasks include digging, trenching, and ground leveling at construction sites, as well as work efficiency and safety can be improved by using an autonomous excavator. A prerequisite step to achieving an autonomous excavation is to obtain a sound perception of the [...] Read more.
Excavator’s main tasks include digging, trenching, and ground leveling at construction sites, as well as work efficiency and safety can be improved by using an autonomous excavator. A prerequisite step to achieving an autonomous excavation is to obtain a sound perception of the surrounding ground. For this, a LiDAR sensor has been widely used to scan the environment. However, the point cloud generated by the LiDAR is not ideal for surface reconstruction to generate a ground map, as it suffers from flaws such as noise and outlier points. To tackle this issue, our paper proposes advanced methodologies for surface reconstruction algorithms. Full article
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Proceeding Paper
Assessment of Partial Discharges Evolution in Bushing by Infrared Analysis
Eng. Proc. 2021, 10(1), 18; https://doi.org/10.3390/ecsa-8-11253 - 01 Nov 2021
Viewed by 164
Abstract
The quality of power systems is related to their capability to predict failures, avoid stoppages, and increase the lifetime of their components. Therefore, science has been developing monitoring systems to identify failures in induction motors, transformers, and transmission lines. In this context, one [...] Read more.
The quality of power systems is related to their capability to predict failures, avoid stoppages, and increase the lifetime of their components. Therefore, science has been developing monitoring systems to identify failures in induction motors, transformers, and transmission lines. In this context, one of the most crucial components of the electrical systems is the insulation devices such as bushings, which are constantly subjected to dust, thermal stresses, moisture, etc. These conditions promote insulation deterioration, leading to the occurrence of partial discharges. Partial discharges are localized dielectric breakdown that emits ultra-violet radiation, heat, electromagnet, and acoustics waves. The most traditional techniques to identify these flaws on bushings are based on the current, ultra high frequency, and acoustic emission analysis. However, thermal analysis stands out as a noise-resistant technique to monitor several components in the power systems. Although the thermal method is applied to detect different types of faults, such as bad contacts, overloads, etc, this technique has not been previously applied to perform partial discharge detection and evaluate its evolution on bushings. Based on this issue, this article proposes two new indexes to characterize the discharge evolution based on the infrared thermal analysis: the area ratio coefficient and the Red, Green, and Blue (RGB) ratio coefficient. Seven discharge levels were induced in a contaminated bushing, and an infrared thermal camera captured 20 images per condition, totalizing 140 images. New coefficients were used to perform the identification of discharge evolution. Results indicated that values of the new indexes increase with the partial discharge activity. Thus, the new imaging processing approach can be a promising contribution to literature, improving the reliability and maintenance planning for power transmission systems. Full article
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Proceeding Paper
Temperature Stability Investigations of Neural Network Models for Graphene-Based Gas Sensor Devices
Eng. Proc. 2021, 10(1), 19; https://doi.org/10.3390/ecsa-8-11250 - 01 Nov 2021
Viewed by 192
Abstract
Chemiresistive gas sensors are a crucial tool for monitoring gases on a large scale. For the estimation of gas concentrations based on the signals provided by such sensors, pattern recognition tools, such as neural networks, are widely used after training them on data [...] Read more.
Chemiresistive gas sensors are a crucial tool for monitoring gases on a large scale. For the estimation of gas concentrations based on the signals provided by such sensors, pattern recognition tools, such as neural networks, are widely used after training them on data measured by sample sensors and reference devices. However, in the production process of low-cost sensor technologies, small variations in their physical properties can occur, which can alter the measuring conditions of the devices and make them less comparable to the sample sensors, leading to less adapted algorithms. In this work, we study the influence of such variations with a focus on changes in the operating and heating temperature of graphene-based gas sensors in particular. To this end, we trained machine learning models on synthetic data provided by a sensor simulation model. By varying the operation temperatures between −15% and +15% from the original values, we could observe a steady decline in algorithm performance, if the temperature deviation exceeds 10%. Furthermore, we were able to substantiate the effectiveness of training the neural networks with several temperature parameters by conducting a second, comparative experiment. A well-balanced training set has shown to improve the prediction accuracy metrics significantly in the scope of our measurement setup. Overall, our results provide insights into the influence of different operating temperatures on the algorithm performance and how the choice of training data can increase the robustness of the prediction algorithms. Full article
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Proceeding Paper
Predictive Glucose Monitoring for People with Diabetes Using Wearable Sensors
Eng. Proc. 2021, 10(1), 20; https://doi.org/10.3390/ecsa-8-11317 - 01 Nov 2021
Viewed by 252
Abstract
Diabetes is a chronic non-communicable disease resulting from pancreatic inability to produce the hormone insulin, or a physiological cellular inability to use this hormone effectively. This leads to unregulated blood glucose levels, which can cause significant and often irreversible physiological damage. Current means [...] Read more.
Diabetes is a chronic non-communicable disease resulting from pancreatic inability to produce the hormone insulin, or a physiological cellular inability to use this hormone effectively. This leads to unregulated blood glucose levels, which can cause significant and often irreversible physiological damage. Current means of glucose level monitoring range from infrequent capillary blood glucose sampling to continuous interstitial fluid glucose monitoring. However, the accuracy of these methods is limited by numerous factors. A potential solution to this shortcoming involves the use of wearable sensors that record an individual’s physiological responses to a range of daily activities, which are subsequently fused and processed with machine learning (ML) algorithms to provide a prediction of an individual’s glucose level and can provide an artificial intelligence-driven glucose monitoring platform. In this paper, we conduct a comparison case study using quadratic discriminant analysis (QDA) and support vector machine (SVM) algorithms for the classification of glucose levels with data acquired from the wearable sensors of a type 1 diabetic individual. Preliminary results demonstrate predicted glucose levels with >70% accuracy, indicating potential for this approach to be used in the design of an ergonomic glucose prediction platform utilizing wearable sensors. Further work will involve the exploration of additional datasets from affordable wearables to enhance and improve the prediction power of the ML algorithms. Full article
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Proceeding Paper
Drift Control of Pedestrian Dead Reckoning (PDR) for Long Period Navigation under Different Smartphone Poses
Eng. Proc. 2021, 10(1), 21; https://doi.org/10.3390/ecsa-8-11302 - 01 Nov 2021
Viewed by 285
Abstract
The inherent errors of low-cost inertial sensors cause significant heading drift that accumulates over time, making it difficult to rely on Pedestrian Dead Reckoning (PDR) for navigation over a long period. Moreover, the flexible portability of the smartphone poses a challenge to PDR, [...] Read more.
The inherent errors of low-cost inertial sensors cause significant heading drift that accumulates over time, making it difficult to rely on Pedestrian Dead Reckoning (PDR) for navigation over a long period. Moreover, the flexible portability of the smartphone poses a challenge to PDR, especially for heading determination. In this work, we aimed to control the PDR drift under the conditions of the unconstrained smartphone to eventually enhance the PDR performance. To this end, we developed a robust step detection algorithm that efficiently captures the peak and valley events of the triggered steps regardless of the device’s pose. The correlation between these events was then leveraged as distinct features to improve smartphone pose detection. The proposed PDR system was then designed to select the step length and heading estimation approach based on a real-time walking pattern and pose discrimination algorithm. We also leveraged quasi-static magnetic field measurements that have less disturbance for estimating reliable compass heading and calibrating the gyro heading. Additionally, we also calibrated the step length and heading when a straight walking pattern is observed between two base nodes. Our results showed improved device pose recognition accuracy. Furthermore, robust and accurate results were achieved for step length, heading and position during long-term navigation under unconstrained smartphone conditions. Full article
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Proceeding Paper
Kinematic Characteristics of National and College Level Weightlifters during the Snatch Technique Using Wearable Inertial Sensors
Eng. Proc. 2021, 10(1), 22; https://doi.org/10.3390/ecsa-8-11255 - 01 Nov 2021
Viewed by 240
Abstract
Weightlifting performance is strongly dependent on technique, explosive strength, and flexibility. There are two major lifts involved in competition: the snatch and the clean and jerk, and the snatch is the most technical component of the weightlifting competition. Most technical analyses have previously [...] Read more.
Weightlifting performance is strongly dependent on technique, explosive strength, and flexibility. There are two major lifts involved in competition: the snatch and the clean and jerk, and the snatch is the most technical component of the weightlifting competition. Most technical analyses have previously been performed using either video analysis or conventional optical camera systems. However, few studies have investigated the kinematic characteristics of the weightlifters using inertial measurement unit (IMU) sensors. In this study, we investigated the joint kinematics of the trunk, shoulder, elbow, hip, and knee as well as the main phases during the snatch technique for national and college level weightlifters using multiple IMU sensors. Seven female Mongolian weightlifters (three national level and four college level) participated. Each participant performed three snatch attempts at 70% of their one-repetition maximum. The joint angles were calculated using three-axis acceleration and three-axis gyroscope data from the IMU sensors. The six main phases of the snatch technique were defined based on knee flexion. All parameters were compared between the national and college level weightlifters. The national team showed a higher elbow range of motion and a greater extension of the hip and knee joints at the second pull compared with college-level athletes. In addition, the college team did not exhibit the transition phase, and the proportion of the turnover phase was larger. This study provides a kinematic difference between the two different level weightlifters, which may help coaches and athletes to improve their training strategy and weightlifting performance. Full article
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Proceeding Paper
A Comparison of Landsat-8 OLI, Sentinel-2 MSI and PlanetScope Satellite Imagery for Assessing Coastline Change in El-Alamein, Egypt
Eng. Proc. 2021, 10(1), 23; https://doi.org/10.3390/ecsa-8-11258 - 01 Nov 2021
Viewed by 254
Abstract
The objective of this study was to provide an assessment of coastline extraction and change analysis using different sensors from three satellites over time. Imagery from Landsat-8 OLI, Sentinel-2A MSI, and PlanetScope-3B were used to detect geomorphological changes along the El-Alamein coastline on [...] Read more.
The objective of this study was to provide an assessment of coastline extraction and change analysis using different sensors from three satellites over time. Imagery from Landsat-8 OLI, Sentinel-2A MSI, and PlanetScope-3B were used to detect geomorphological changes along the El-Alamein coastline on the Mediterranean Sea between August 2016 and August 2021. The normalized difference water index (NDWI) was applied to automate, detect and map water bodies based on thresholding techniques and coastline extraction. The extracted coastlines were analyzed using geographic information systems (GIS)-based digital shoreline analysis system (DSAS.v5) model, a GIS software tool for the estimation of shoreline change rates calculated through two statistical techniques: net shoreline movement (NSM) and end point rate (EPR). The results indicate that measuring coastline morphological change using satellite-based imagery depends very much on the resolution of the imagery. It is necessary to tailor the selection of imagery to the accuracy of the measurement needed. Higher resolution imagery such at PlanetScope (3 m) produces higher resolution measurements. However, medium resolution imagery from Landsat may be sufficiently good for objectives requiring less spatial resolution. Full article
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Proceeding Paper
Smart Seismocardiography: A Machine Learning Approach for Automatic Data Processing
Eng. Proc. 2021, 10(1), 24; https://doi.org/10.3390/ecsa-8-11325 - 01 Nov 2021
Cited by 1 | Viewed by 192
Abstract
Seismocardiography (SCG) is a non-invasive method that measures local vibrations created by the mechanical cardiovascular exercises on the chest wall. Thereby, mechanical movements of the heart are recorded in real-time from vibration sensors positioned on the chest of the subject, to further compute [...] Read more.
Seismocardiography (SCG) is a non-invasive method that measures local vibrations created by the mechanical cardiovascular exercises on the chest wall. Thereby, mechanical movements of the heart are recorded in real-time from vibration sensors positioned on the chest of the subject, to further compute the heart rate and retrieve the SCG waveform. Although such events have been widely studied, robust signal processing methods remain a challenging task. On the other hand, the use of piezoelectric sensors has been favored in recent years due to its features and low cost. However, robust data processing techniques should be developed to increase their performance and reliability. In this work, we propose an attractive method for SCG data processing based on the K-Means clustering algorithm to automatically label waveform events. Interestingly, the SCG signals are recovered from a custom-made device built around an ultra-low-cost piezoelectric sensor. Once the signals are measured, they are pre-processed by spectral filtering. Afterwards, the signal spectrum is used to compute the heart rate (HR). Thereby, the filtered signal is sequentially segmented, and every frame is processed by a light-weight K-Means algorithm. Finally, we show the performance of the smart seismocardiography by analyzing SCG waveforms at different physiological conditions. Full article
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Proceeding Paper
Amide I Band Analysis Applied to Vibrational Micro-Spectroscopies of Gingival Crevicular Fluid Samples for Orthodontic Treatment Monitoring
Eng. Proc. 2021, 10(1), 25; https://doi.org/10.3390/ecsa-8-11266 - 01 Nov 2021
Viewed by 148
Abstract
Vibrational micro-spectroscopies were applied to investigate the gingival crevicular fluid (GCF) for monitoring orthodontic treatment with fixed appliances. The GCF samples were investigated using Fourier transform infrared, Raman, and surface-enhanced Raman micro-spectroscopies. The GCF spectra collected at different times of orthodontic tooth movement [...] Read more.
Vibrational micro-spectroscopies were applied to investigate the gingival crevicular fluid (GCF) for monitoring orthodontic treatment with fixed appliances. The GCF samples were investigated using Fourier transform infrared, Raman, and surface-enhanced Raman micro-spectroscopies. The GCF spectra collected at different times of orthodontic tooth movement were used to characterize the biochemical changes occurring during the treatment. We examined the amide I band region by means of deconvolution analysis using Gaussian–Lorentzian curves for infrared spectra and Lorentzian curves for Raman spectra. This analysis allowed us to evidence the contribution of the different subcomponents of the amide I band and the changes occurring during orthodontic treatment. These changes can be ascribed to modifications in the secondary structure of protein content and could contribute to make vibrational spectroscopies a useful tool for monitoring the individual patient’s response to orthodontic force application. Full article
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Proceeding Paper
Cost-Effective Flexible CSRR-Based Sensor for Noninvasive Measurement of Permittivity of Biomaterials
Eng. Proc. 2021, 10(1), 26; https://doi.org/10.3390/ecsa-8-11303 - 01 Nov 2021
Viewed by 286
Abstract
A novel, cost-effective, flexible microwave sensor is proposed to facilitate point-of-care testing (POCT) methods for medical diagnosis. The sensor is based on the complementary split-ring resonator (CSRR) to accurately measure the permittivity of biomaterials over a wide range of frequencies. This ability can [...] Read more.
A novel, cost-effective, flexible microwave sensor is proposed to facilitate point-of-care testing (POCT) methods for medical diagnosis. The sensor is based on the complementary split-ring resonator (CSRR) to accurately measure the permittivity of biomaterials over a wide range of frequencies. This ability can be used to characterize various materials under test (MUT) such as blood, saliva, tissue samples, etc. The flexibility of the proposed sensor means that it can be used when the accessibility of the sample has technical difficulties, such as on curved surfaces. Firstly, the optimized structure and coupling to the readout transmission line are evaluated using finite element method (FEM) simulations. Then, the prototype of the optimized structure is fabricated on a thin polydimethylsiloxane (PDMS) substrate as a biocompatible economical polymer, and aluminium is carefully chosen for the fabrication of CSRR and readout parts. The proposed flexible sensor is tested and compared to conventional rigid CSRR sensors. The proposed structure withstood the different bending positions well, and also showed an improvement in the results for curved MUT. Full article
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Proceeding Paper
Dedicated Wearable Sensitive Strain Sensor, Based on Carbon Nanotubes, for Monitoring the Rat Respiration Rate
Eng. Proc. 2021, 10(1), 27; https://doi.org/10.3390/ecsa-8-11293 - 01 Nov 2021
Viewed by 331
Abstract
This paper presents a highly sensitive and novel wearable strain sensor using one-dimensional material for monitoring the respiration rate of an anesthetized rat. The dedicated sensitive sensor, based on carbon nanotubes mixed with poly(3,4-ethylenedioxythiophene) polystyrene sulfonate, was attached above the rat chest. A [...] Read more.
This paper presents a highly sensitive and novel wearable strain sensor using one-dimensional material for monitoring the respiration rate of an anesthetized rat. The dedicated sensitive sensor, based on carbon nanotubes mixed with poly(3,4-ethylenedioxythiophene) polystyrene sulfonate, was attached above the rat chest. A Wheatstone bridge electrical circuit, associated with a multifunction portable device, was connected to the strain sensor. The change of the strain sensor’s resistance value, induced by the mechanical deformability during the rat respiration, was detected and transformed into a voltage signal. The respiration information could be thus extracted and analyzed. Full article
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Proceeding Paper
A Feasibility Study of the Application of Signal Processing Techniques to Corona Discharge Characterization on HVDC Systems
Eng. Proc. 2021, 10(1), 28; https://doi.org/10.3390/ecsa-8-11318 - 01 Nov 2021
Viewed by 190
Abstract
This paper presents an initial and feasibility study of corona discharge characterization on HVDC systems using an alternative strategy based on digital signal processing techniques. In the corona discharge test, high voltages varying from ±30 to ±80 kV were applied through a DC [...] Read more.
This paper presents an initial and feasibility study of corona discharge characterization on HVDC systems using an alternative strategy based on digital signal processing techniques. In the corona discharge test, high voltages varying from ±30 to ±80 kV were applied through a DC high-voltage generator. In addition, corona discharges around the conductor were measured by means of a data acquisition prototype system equipped with a metal electrode device for the purpose of corona current measurement. The signals collected were subjected to digital signal processing parameters to extract the most relevant information related to corona discharge occurrence in specific frequency bands. The results reveal that the proposed method was able to detect the corona discharge characteristics following the changes in the signal content, especially, for narrow frequency ranges. The results indicate the feasibility of the proposed method to detect and characterize the corona discharge in a simple way, which expands the research field in corona discharge characterization in HVDC systems by means of digital signal processing and feature extraction. Full article
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Proceeding Paper
Insole Gait Acquisition System Based on Wearable Sensors
Eng. Proc. 2021, 10(1), 29; https://doi.org/10.3390/ecsa-8-11275 - 01 Nov 2021
Viewed by 368
Abstract
Human gait analysis is a growing field of research interest in medical treatment, sports training and structural health monitoring. In our study, we propose a low-cost insole design with wearable sensors based on piezoelectric discs (PZT) and an inertial measurement unit (IMU) to [...] Read more.
Human gait analysis is a growing field of research interest in medical treatment, sports training and structural health monitoring. In our study, we propose a low-cost insole design with wearable sensors based on piezoelectric discs (PZT) and an inertial measurement unit (IMU) to acquire the human gait. The sensors are placed at three points of a shoe sole: toe, metatarsal and heel. The human gait obtained from such an insole layout is significantly affected by plantar pressure distribution and alignment of the feet. The PZT sensors give an insight into the pressure map under the feet, and the IMUs record projection and orientation of the feet. Full article
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Proceeding Paper
Conceptional Designs of the Rotation Mechanism with Antiphase Energy Harvester
Eng. Proc. 2021, 10(1), 30; https://doi.org/10.3390/ecsa-8-11300 - 01 Nov 2021
Viewed by 182
Abstract
Due to the increased demand for a sustainable source of energy, the research on energy harvesting has increased in the last twenty years. Energy harvesting aims to gain energy from the ambient environment and convert this energy into electrical power. There are different [...] Read more.
Due to the increased demand for a sustainable source of energy, the research on energy harvesting has increased in the last twenty years. Energy harvesting aims to gain energy from the ambient environment and convert this energy into electrical power. There are different kinds of renewable energy sources and vibration energy harvesting (VEH) is the most promising source owing to its low maintenance cost. This paper focuses on an electromagnetic vibration energy harvester based on the concept of rotational energy harvesting. The proposed device uses a rotating rotor with permanent magnets and moves the repulsive magnet block up and down. The block is connected to an antiphase harvester, which creates power by cutting the magnetic flux density. The antiphase was proven to double the voltage when the antiphase was moving. To improve the vibration amplitude of the magnet block and the antiphase, springs were added to the proposed design. In the concept, four configurations—with and without different spring positions—were proposed. The experimental results showed that when the spring was placed in the upper and bottom part of the moving part, the spring at the bottom would generate the largest vibration amplitude. Based on Faraday’s Law of Induction, voltage is proportional to the velocity or vibration amplitude. Hence, for both cases, at least six times the voltage was generated compared to the design without added springs. Full article
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Proceeding Paper
Towards a Multi-Interdigital Transducer Configuration to Combine Focusing and Trapping of Microparticles within a Microfluidic Platform: A 3D Numerical Analysis
Eng. Proc. 2021, 10(1), 31; https://doi.org/10.3390/ecsa-8-11256 - 01 Nov 2021
Viewed by 252
Abstract
In Lab-On-a-chip devices, the separation and manipulation of micro-particles within microfluidic channels are important operations in the process of biological analyses. In this study, the microfluidic flow is coupled with acoustic waves through a 3D multi-physics numerical solution in order to generate optimized [...] Read more.
In Lab-On-a-chip devices, the separation and manipulation of micro-particles within microfluidic channels are important operations in the process of biological analyses. In this study, the microfluidic flow is coupled with acoustic waves through a 3D multi-physics numerical solution in order to generate optimized acoustic pressure pattern. Exploiting interdigital transducers (IDTs), surface acoustic waves (SAWs) are generated on the surface of a piezoelectric substrate (lithium niobate). These waves interfere constructively to generate a standing pressure field within a fluid contained in a microchannel placed between them. Several studies and applications have been reported exploiting two facing IDTs, effective in particle focusing due to the acoustic radiation force developed by the acoustic pressure. In this work, a configuration made by four IDTs is investigated to enhance the focusing effect and provide trapping capabilities. A complex matrix of pressure wave nodes (zero wave amplitude) and antinodes (maximum wave amplitude) is generated and optimized to acquire the right acoustic pressure pattern. Results obtained show particle focusing effects but also trapping on specific sites depending on the distribution of waves. These innovative results, based on multiphysics 3D numerical analysis, highlight the versatility and the efficiency of this configuration depending on the design of the microfluidic structure implemented in the SAW-based platform. Applications towards biological cell sorting and assembling can be considered based on this principle. Full article
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Proceeding Paper
DEEPHER: Human Emotion Recognition Using an EEG-Based DEEP Learning Network Model
Eng. Proc. 2021, 10(1), 32; https://doi.org/10.3390/ecsa-8-11249 - 01 Nov 2021
Cited by 1 | Viewed by 233
Abstract
Emotion identification and categorization have been emerging in the brain machine interface in the current era. Audio, visual, and electroencephalography (EEG) data have all been shown to be useful for automated emotion identification in a number of studies. EEG-based emotion detection is a [...] Read more.
Emotion identification and categorization have been emerging in the brain machine interface in the current era. Audio, visual, and electroencephalography (EEG) data have all been shown to be useful for automated emotion identification in a number of studies. EEG-based emotion detection is a critical component of psychiatric health assessment for individuals. If EEG sensor data are collected from multiple experimental sessions or participants, the underlying signals are invariably non-stationary. As EEG signals are noisy, non-stationary, and non-linear, creating an intelligent system that can identify emotions with good accuracy is challenging. Many researchers have shown evidence that EEG brain waves may be used to determine feelings. This study introduces a novel automated emotion identification system that employs deep learning principles to recognize emotions through EEG signals from computer games. EEG data were obtained from 28 distinct participants using 14-channel Emotive Epoc+ portable and wearable EEG equipment. Participants played four distinct emotional computer games for five minutes each, with a total of 20 min of EEG data available for each participant. The suggested framework is simple enough to categorize four classes of emotions during game play. The results demonstrate that the suggested model-based emotion detection framework is a viable method for recognizing emotions from EEG data. The network achieves 99.99% accuracyalong with less computational time. Full article
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Proceeding Paper
Smart Glasses for Visually Evoked Potential Applications: Characterisation of the Optical Output for Different Display Technologies
Eng. Proc. 2021, 10(1), 33; https://doi.org/10.3390/ecsa-8-11263 - 01 Nov 2021
Viewed by 153
Abstract
Off-the-shelf consumer-grade smart glasses are being increasingly used in extended reality and brain–computer interface applications that are based on the detection of visually evoked potentials from the user’s brain. The displays of these kinds of devices can be based on different technologies, which [...] Read more.
Off-the-shelf consumer-grade smart glasses are being increasingly used in extended reality and brain–computer interface applications that are based on the detection of visually evoked potentials from the user’s brain. The displays of these kinds of devices can be based on different technologies, which may affect the nature of the visual stimulus received by the user. This aspect has substantial impact in the field of applications based on wearable sensors and devices. We measured the optical output of three models of smart glasses with different display technologies using a photo-transducer in order to gain insight on their exploitability in brain–computer interface applications. The results suggest that preferring a particular model of smart glasses may strongly depend on the specific application requirements. Full article
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Proceeding Paper
A Soft Robot Arm with Flexible Sensors for Master–Slave Operation
Eng. Proc. 2021, 10(1), 34; https://doi.org/10.3390/ecsa-8-11311 - 01 Nov 2021
Viewed by 234
Abstract
In our study, a soft robot arm consisting of McKibben artificial muscles and a silicone rubber structure was developed. This robot arm can perform bending and twisting motions by ap-plying pneumatic pressure to the artificial muscles. The robot arm is made of flexible [...] Read more.
In our study, a soft robot arm consisting of McKibben artificial muscles and a silicone rubber structure was developed. This robot arm can perform bending and twisting motions by ap-plying pneumatic pressure to the artificial muscles. The robot arm is made of flexible materials only, and therefore it has high flexibility and shape adaptability. In this report on the fundamental investigation of the master–slave feedback control of the soft robot arm for intentional operation, we focus on the bending motion of the soft robot arm. Three flexible strain sensors were placed on the soft robot arm for measuring the bending motion. By establishing a master–slave feedback system using the sensors, the bending motion of the soft robot arm followed the operator’s wrist motion detected via the wearable interface device. Full article
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Proceeding Paper
Displacement Sensing of an Active String Actuator by an Optical Fiber
Eng. Proc. 2021, 10(1), 35; https://doi.org/10.3390/ecsa-8-11310 - 01 Nov 2021
Cited by 1 | Viewed by 134
Abstract
We have fabricated a string-shaped actuator called “Active string” that has high contractile displacement/force by accumulating thin pneumatic artificial muscles using the string production process. However, displacement control of the active string is challenging because general bulky and rigid displacement sensors are not [...] Read more.
We have fabricated a string-shaped actuator called “Active string” that has high contractile displacement/force by accumulating thin pneumatic artificial muscles using the string production process. However, displacement control of the active string is challenging because general bulky and rigid displacement sensors are not suitable for the sensor element of the active string. Therefore, in this report, a flexible optical fiber sensor is combined with the active string to enable sensing of its displacement. As the active string contracts, the radius of curvature of the optical fiber decreases, and light intensity propagating in the optical fiber decreases due to bending loss. The experimental results showed that the optical fiber sensor value changed with corresponding to the displacement of the active string. It shows the possibility that it is possible to make a displacement estimation of the displacement of the active string using an optical fiber sensor. Full article
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Proceeding Paper
3D Printable Piezoelectric Composite Sensors for Guided Ultrasonic Wave Detection
Eng. Proc. 2021, 10(1), 36; https://doi.org/10.3390/ecsa-8-11308 - 01 Nov 2021
Cited by 2 | Viewed by 246
Abstract
Commercially available photopolymer resin is combined with Lead Zirconate Titanate (PZT) micrometer size piezoelectric particles to form 3D printable suspensions that solidify under UV light. This in turn allows achieving various non-standard sensor geometries that might bring benefits, such as increased piezoelectric output [...] Read more.
Commercially available photopolymer resin is combined with Lead Zirconate Titanate (PZT) micrometer size piezoelectric particles to form 3D printable suspensions that solidify under UV light. This in turn allows achieving various non-standard sensor geometries that might bring benefits, such as increased piezoelectric output in specific conditions. However, it is unclear whether piezoelectric composite materials are suitable for Guided Ultrasonic Wave (GUW) detection, which is crucial for Structural Health Monitoring (SHM) in different applications. In this study, thin piezoelectric composite sensors are tape casted, solidified under UV light, covered with electrodes, polarized in a high electric field and adhesively bonded onto a wave guide. This approach helps to understand the capabilities of thin piezoelectric composite sensors for GUW detection. In an experimental study, thin 2-dimensional rectangular, circular and annulus segment shaped piezoelectric composite sensors with an effective surface area smaller than 400 mm2 applied to an aluminum plate with a thickness of 2 mm demonstrate successful detection of GUW up to 250 kHz. An analytical calculation of the maximum and minimum amplitude for the ratio of the wavelength and the sensor length in wave propagation direction shows good agreement with the sensor-recorded amplitude. The output of the piezoelectric composite sensors is compared to commercial piezoelectric discs to evaluate their performance. Full article
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Proceeding Paper
Estimation of Building Heights and DEM Accuracy Assessment Using ICESat-2 Data Products
Eng. Proc. 2021, 10(1), 37; https://doi.org/10.3390/ecsa-8-11442 - 01 Nov 2021
Viewed by 411
Abstract
The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the [...] Read more.
The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the compactness of urban areas, population expansion, and urban surface geometry. This study makes use of the ‘Ice, cloud, and land elevation satellite-2′ (ICESat-2) ATL 03 photon data for building height estimation using a sample of 30 buildings in three experimental sites. A comparison of computed heights with the heights of the respective buildings from google image and google earth pro was done to assess the accuracy and the result of 2.04 m RMSE was obtained. Another popularly used method by planners and policymakers to map the vertical dimension of urban terrain is the Digital Elevation Model (DEM). An assessment of the openly available DEM products—TanDEM-X and Cartosat-1 has been done over Urban and Rural areas. TanDEM-X is a German earth observation satellite that uses InSAR (Synthetic Aperture Radar Interferometry) technique to acquire DEM while Cartosat-1 is an optical stereo acquisition satellite launched by the Indian Space Research Organization (ISRO) that uses photogrammetric techniques for DEM acquisition. Both the DEMs have been compared with ICESat-2 (ATL-08) Elevation data as the reference and the accuracy has been evaluated using Mean error (ME), Mean absolute error (MAE) and Root mean square error (RMSE). In the case of Greater Hyderabad Municipal Corporation (GHMC), RMSE values 5.29 m and 7.48 m were noted for TanDEM-X 90 and CartoDEM V3 R1 respectively. While the second site of Bellampalli Mandal rural area observed 5.15 and 5.48 RMSE values for the same respectively. Therefore, it was concluded that TanDEM-X has better accuracy as compared to the CartoDEM V3 R1. Full article
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Proceeding Paper
A New Approach for Monitoring Sweat Ammonia Levels Using a Ventilated Capsule
Eng. Proc. 2021, 10(1), 38; https://doi.org/10.3390/ecsa-8-11332 - 01 Nov 2021
Viewed by 170
Abstract
Ammonium levels in sweat can potentially be used to measure muscle fatigue and to diagnose particular metabolic myopathies. To research the potential use of ammonia in sweat as a biomarker, a new real-time monitoring system is developed. This system consists of a capsule [...] Read more.
Ammonium levels in sweat can potentially be used to measure muscle fatigue and to diagnose particular metabolic myopathies. To research the potential use of ammonia in sweat as a biomarker, a new real-time monitoring system is developed. This system consists of a capsule that is placed on the skin and ventilated with dry air. A metal-oxide gas sensor in the capsule detects the ammonia that is evaporated from sweat. The sensor system was built, and calibration experiments were performed. The sensors show good sensitivity from 27 mV/ppm to 1.1 mV/ppm in the desired measurement range of 1 to 30 ppm, respectively. A temperature and humidity sensor is integrated to compensate for temperature and humidity effects on the NH3 sensor. Full article
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Proceeding Paper
Design and Characterization of a Passive Wireless DNA Sensor
Eng. Proc. 2021, 10(1), 39; https://doi.org/10.3390/ecsa-8-11261 - 01 Nov 2021
Viewed by 144
Abstract
This paper presents a concept for a passive wireless DNA sensing platform that exploits a multidisciplinary area, synthesizing the conventional DNA capacitive sensing mechanism and the surface-based conformational characterization throughout DNA immobilization and hybridization. The resonant frequency shift, caused by the change of [...] Read more.
This paper presents a concept for a passive wireless DNA sensing platform that exploits a multidisciplinary area, synthesizing the conventional DNA capacitive sensing mechanism and the surface-based conformational characterization throughout DNA immobilization and hybridization. The resonant frequency shift, caused by the change of capacitance throughout DNA immobilization and hybridization and occurring on top of an interdigital capacitor, is monitored by means of an impedance analyzer. 32 samples were measured throughout the experiment and the average capacitance measurements represented a variety of surface charges resulting from DNA molecule immobilization and hybridization. The capacitance changed from 11.58 pF to 114.5 pF when specific ssDNA was attached to electrodes and then increased to 218.6 pF once complementary strand DNA was introduced and hybridized with existing DNA chains. In addition, using impedance analyzer measurements, the resonant frequency decreased from 2.01 MHz to 1.97 MHz in the presence of ssDNA and decreased further down to 0.95 MHz after the complementary strand DNA was deposited. Full article
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Proceeding Paper
Sensors Applied to Bearing Fault Detection in Three-Phase Induction Motors
Eng. Proc. 2021, 10(1), 40; https://doi.org/10.3390/ecsa-8-11319 - 01 Nov 2021
Viewed by 210
Abstract
Three-Phase Induction Motors (TIMs) are widely applied in industries. Therefore, there is a need to reduce operational and maintenance costs since their stoppages can impair production lines and lead to financial losses. Among all the TIM components, bearings are crucial in the machine [...] Read more.
Three-Phase Induction Motors (TIMs) are widely applied in industries. Therefore, there is a need to reduce operational and maintenance costs since their stoppages can impair production lines and lead to financial losses. Among all the TIM components, bearings are crucial in the machine operation once they couple rotor to the motor frame. Furthermore, they are constantly subjected to friction and mechanical wearing. Consequently, they represent around 41% of the motor fault, according to IEEE. In this context, several studies have sought to develop monitoring systems based on different types of sensors. Therefore, considering the high demand, this article aims to present the state of the art of the past five years concerning the sensing techniques based on current, vibration, and infra-red analysis, which are characterized as promising tools to perform bearing fault detection. The current and vibration analysis are powerful tools to assess damages in the inner race, outer race, cages, and rolling elements of the bearings. These sensing techniques use current sensors like hall effect-based, Rogowski coils, and current transformers, or vibration sensors such as accelerometers. The effectiveness of these techniques is due to the previously developed models, which relate the current and vibration frequencies to the origin of the fault. Therefore, this article also presents the bearing fault mathematical modeling for these techniques. The infra-red technique is based on heat emission, and several image processing techniques were developed to optimize bearing fault detection, which is presented in this review. Finally, this work is a contribution to pushing the frontiers of the bearing fault diagnosis area. Full article
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Proceeding Paper
Analysis and Automatic Classification of the Soundscape of a Natural Park Close to the Airport of Barcelona during the 2021 Lockdown Period
Eng. Proc. 2021, 10(1), 41; https://doi.org/10.3390/ecsa-8-11267 - 01 Nov 2021
Viewed by 143
Abstract
The noise caused by airports and its impact on human health, together with train, road traffic, leisure, and wind nose has been widely analyzed, even in the reports published in 2019 by the WHO. Noise effect has also been studied in the literature [...] Read more.
The noise caused by airports and its impact on human health, together with train, road traffic, leisure, and wind nose has been widely analyzed, even in the reports published in 2019 by the WHO. Noise effect has also been studied in the literature on other species, such as birds and amphibians. In this work, we focus on a natural environment of special singularity due to its location: the natural space of the Delta del Llobregat, next to the city of Barcelona. The Delta del Llobregat is placed in an area close to the Port of Barcelona, and directly on the route of the planes taking off from Barcelona airport. In this paper, we present a first analysis of the typology of the sounds found in the natural environment of the Delta del Llobregat after conducting a simultaneous recording campaign at three separate spots of biological interest, determined by the park’s curators. We identify the interfering sounds, as well as the amount of wildlife sounds in relation to the noises caused by the airport activity. The recordings and posterior analysis were made on 5 March 2021, when airport activity was still greatly diminished by the mobility restrictions. In addition, we apply machine learning techniques to classify the acoustic events produced by both airport activity and wildlife, aiming to build an automatic system that would allow us to gather labelled data in future works. Full article
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Proceeding Paper
Feature Selection Based on Evolutionary Algorithms for Affective Computing and Stress Recognition
Eng. Proc. 2021, 10(1), 42; https://doi.org/10.3390/ecsa-8-11288 - 01 Nov 2021
Viewed by 179
Abstract
In the area of affective computing, machine learning is used to recognize patterns in datasets based on extracted features. Feature selection is used to select the most relevant features from the large number of extracted features. Conventional feature selection methods are associated with [...] Read more.
In the area of affective computing, machine learning is used to recognize patterns in datasets based on extracted features. Feature selection is used to select the most relevant features from the large number of extracted features. Conventional feature selection methods are associated with a high computational cost depending on the classifier used. This paper presents a feature selection approach based on evolutionary algorithms using techniques inspired by natural evolution to optimize the computational process. Our method is implemented using an Optimize Selection operator from RapidMiner and is integrated within our previously developed workflow for affective computing and stress recognition from biosignals. The performance is evaluated based on the random forests classifier and a cross validation using our uulmMAC database for machine learning applications. Our proposed approach is faster than the forward selection method at similar recognition rates and does not stop at a local optimum, allowing a promising feature selection alternative in the field of affective computing. Full article
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Proceeding Paper
Collaborative Tracking Control Strategy for Autonomous Excavation of a Hydraulic Excavator
Eng. Proc. 2021, 10(1), 43; https://doi.org/10.3390/ecsa-8-11333 - 01 Nov 2021
Viewed by 205
Abstract
A hydraulic excavator consists of multiple electrohydraulic actuators (EHA). Due to uncertainties and nonlinearities in EHAs, it is challenging to devise a proper control strategy. To tackle this issue, a major goal of our study is to provide an efficient control strategy to [...] Read more.
A hydraulic excavator consists of multiple electrohydraulic actuators (EHA). Due to uncertainties and nonlinearities in EHAs, it is challenging to devise a proper control strategy. To tackle this issue, a major goal of our study is to provide an efficient control strategy to minimize tracking errors of the bucket tip position for autonomous excavation. To accomplish the goal, the study offers a collaboration of PID and fuzzy controllers that are used to compensate for contour errors and achieve accurate actuator position control, respectively. Co-simulation models including control algorithms and hydraulic components were created using Matlab and Amesim to validate the performance of the designed controllers. Simulations indicate that the proposed method enables achieving accurate tracking control for autonomous excavation with small tracking errors despite the nonlinear characteristics of the hydraulic excavator system. Full article
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Proceeding Paper
Data-Centric Performance Improvement Strategies for Few-Shot Classification of Chemical Sensor Data
Eng. Proc. 2021, 10(1), 44; https://doi.org/10.3390/ecsa-8-11335 - 01 Nov 2021
Viewed by 166
Abstract
Metal oxide (MOX) sensors offer a low-cost solution to detect volatile organic compound (VOC) mixtures. However, their operation involves time-consuming heating cycles, leading to a slower data collection and data classification process. This work introduces a few-shot learning approach that promotes rapid classification. [...] Read more.
Metal oxide (MOX) sensors offer a low-cost solution to detect volatile organic compound (VOC) mixtures. However, their operation involves time-consuming heating cycles, leading to a slower data collection and data classification process. This work introduces a few-shot learning approach that promotes rapid classification. In this approach, a model trained on several base classes is fine-tuned to recognize a novel class using a small number (n = 5, 25, 50 and 75) of randomly selected novel class measurements/shots. The used dataset comprises MOX sensor measurements of four different juices (apple, orange, currant and multivitamin) and air, collected over 10-minute phases using a pulse heater signal. While high average accuracy of 82.46 is obtained for five-class classification using 75 shots, the model’s performance depends on the juice type. One-shot validation showed that not all measurements within a phase are representative, necessitating careful shot selection to achieve high classification accuracy. Error analysis revealed contamination of some measurements by the previously measured juice, a characteristic of MOX sensor data that is often overlooked and equivalent to mislabeling. Three strategies are adopted to overcome this: (E1) and (E2) fine-tuning after dropping initial/final measurements and the first half of each phase, respectively, (E3) pretraining with data from the second half of each phase. Results show that each of the strategies performs best for a specific number of shots. E3 results in the highest performance for five-shot learning (accuracy 63.69), whereas E2 yields the best results for 25-/50-shot learning (accuracies 79/87.1) and E1 predicts best for 75-shot learning (accuracy 88.6). Error analysis also showed that, for all strategies, more than 50% of air misclassifications resulted from contamination, but E1 was affected the least. This work demonstrates how strongly data quality can affect prediction performance, especially for few-shot classification methods, and that a data-centric approach can improve the results. Full article
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Proceeding Paper
Removal of ECG Baseline Wander Using a Resting Cycle Template
Eng. Proc. 2021, 10(1), 45; https://doi.org/10.3390/ecsa-8-11289 - 01 Nov 2021
Viewed by 330
Abstract
The development of electrocardiogram (ECG) wearable devices has increased due to its applications on ambulatory patients. ECG signals provide useful information about the heart behavior, but when daily activities are monitored, motion artifacts are introduced producing saturation of the signal, thus losing the [...] Read more.
The development of electrocardiogram (ECG) wearable devices has increased due to its applications on ambulatory patients. ECG signals provide useful information about the heart behavior, but when daily activities are monitored, motion artifacts are introduced producing saturation of the signal, thus losing the information. The typical resolution used to record ECG signals is of maximum 16-bit, which might not be enough to detect low-amplitude potentials and at the same time avoid saturation due to baseline wander, since this last issue demands a low-gain signal chain. A high-resolution provides a more detailed ECG signal under a low gain input, and if the signal is corrupted by motion artifact noise but is not saturated, it can be filtered to recover the signal of interest. In this work, a 24-bit ADC is used to record the ECG, and a new method, the rest ECG cycle template, is proposed to remove the baseline wander. This new method is compared to high-pass filter and spline interpolation methods in their ability to remove baseline wander. This new method presumes that a user is able to establish a rest ECG during his/her daily activities. Full article
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Proceeding Paper
A New Three-Phase Smart Meter for Cloud Connection: Network Architecture and Performances
Eng. Proc. 2021, 10(1), 46; https://doi.org/10.3390/ecsa-8-11260 - 01 Nov 2021
Viewed by 139
Abstract
Efficient energy consumption is essential for the development of a smart grid in the power system. As a response, reliable monitoring and management of energy usage is a main priority for the smart grid. The existing energy meter system has a host of [...] Read more.
Efficient energy consumption is essential for the development of a smart grid in the power system. As a response, reliable monitoring and management of energy usage is a main priority for the smart grid. The existing energy meter system has a host of concerns, one of which is the lack of full-duplex transmission. To solve this problem, in this paper, we present a novel architecture for a cloud-connected Smart Energy Meter. The proposed meter is capable of real-time measurement of the energy network status and data transfer to a cloud architecture. The meter is suitable for single and polyphase measurement. Its performances are validated on a test field performed on the island of Lipari (Italy). Full article
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Proceeding Paper
Performance Analysis of Mesh Based Enterprise Network Using RIP, EIGRP and OSPF Routing Protocols
Eng. Proc. 2021, 10(1), 47; https://doi.org/10.3390/ecsa-8-11285 - 01 Nov 2021
Cited by 1 | Viewed by 485
Abstract
Computer network communication is quickly growing in this pandemic situation. Phone conferencing, video streaming and sharing file/printing are all made easier with communications technologies. Data transmitted in time with little interruption become a significant achievement of wireless sensor networks (WSNs). A massive network [...] Read more.
Computer network communication is quickly growing in this pandemic situation. Phone conferencing, video streaming and sharing file/printing are all made easier with communications technologies. Data transmitted in time with little interruption become a significant achievement of wireless sensor networks (WSNs). A massive network is interconnection computer networks in the globe connected by the Internet, and the Internet plays a critical role in WSNs. Data access is a key element of any enterprise network, and the routing protocol is used to transmit data or access data. Due to the growing use of WSNs, it is essential to know about the network structure, the routing protocol. The routing protocols must be used to route all data sent over the Internet between the source and the destination. Which chooses the optimum routes between any two nodes in an enterprise network. This research focused on how the routing table will determine the optimum path/route of data packets to be transmitted from source to destination. The performance of three routing protocols, Routing Information Protocol (RIP), Enhanced Interior Gateway Routing Protocol (EIGRP) and Open Shortest Path First (OSPF), is investigated in this research for the massive mesh based enterprise wireless sensor network. We also investigated the behaviors of end-to-end packet latency, convergence time on flapping connections and average point-to-point throughput (bits/sec) between network links. Finally, the simulation results are compared to the efficacy and performance of these protocols implemented in the wireless LAN and internet-based wireless sensor network. Full article
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Proceeding Paper
On the Sensing and Decoding of Phantom Motions for Control of the Cybernetics of the Upper-Limb Prosthesis
Eng. Proc. 2021, 10(1), 48; https://doi.org/10.3390/ecsa-8-11314 - 01 Nov 2021
Viewed by 167
Abstract
The cybernetic interface within an upper-limb prosthesis facilitates a Human–Machine interaction and ultimately control of the prosthesis limb. A coherent flow between the phantom motion and subsequent actuation of the prosthesis limb to produce the desired gesture hinges heavily upon the physiological sensing [...] Read more.
The cybernetic interface within an upper-limb prosthesis facilitates a Human–Machine interaction and ultimately control of the prosthesis limb. A coherent flow between the phantom motion and subsequent actuation of the prosthesis limb to produce the desired gesture hinges heavily upon the physiological sensing source and its ability to acquire quality signals, alongside appropriate decoding of these intent signals with the aid of appropriate signal processing algorithms. In this paper, we discuss the sensing and signal processing aspects of the overall prosthesis control cybernetics, with emphasis on transradial, transhumeral, and shoulder disarticulate amputations, which represent considerable upper-limb amputees typically encountered within the population. Full article
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Proceeding Paper
Sensor Selection and Placement for Track Switch Condition Monitoring through Validated Structural Digital Twin Models of Train–Track Interactions
Eng. Proc. 2021, 10(1), 49; https://doi.org/10.3390/ecsa-8-11297 - 01 Nov 2021
Viewed by 356
Abstract
Railway track switches experience high failure rates, which can be reduced by monitoring their structural health. The results obtained from a validated Finite Element (FE) model for train–track switch interaction have been introduced to support sensor selection and placement. For the FE models [...] Read more.
Railway track switches experience high failure rates, which can be reduced by monitoring their structural health. The results obtained from a validated Finite Element (FE) model for train–track switch interaction have been introduced to support sensor selection and placement. For the FE models with nominal and damaged rail profiles, virtual strain sensor measurements have been obtained after converting the true strains to engineering strains. Comparisons for the strains before and after the introduction of the fault have demonstrated greater amplitude for the strains after fault introduction. The highest difference in strain amplitude is in the vertical direction, followed by the longitudinal and lateral directions. Full article
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Proceeding Paper
Design of Compaction Operation Monitoring System for Intelligent Vibratory Roller Based on Internet of Things
Eng. Proc. 2021, 10(1), 50; https://doi.org/10.3390/ecsa-8-11265 - 01 Nov 2021
Viewed by 155
Abstract
In recent years, an intelligent vibratory roller with adjustable mode has become the leading direction for the development of compaction equipment that can obtain the state of the pressed material during the compaction operation and then control the working parameters and the excitation [...] Read more.
In recent years, an intelligent vibratory roller with adjustable mode has become the leading direction for the development of compaction equipment that can obtain the state of the pressed material during the compaction operation and then control the working parameters and the excitation mode of the whole machine according to the condition of the pressed material. The intelligent vibratory roller can better meet today’s requirements for compaction. This paper proposes a compaction operation monitoring system for an intelligent vibratory roller based on the Internet of Things. Firstly, a hardware system for real-time compaction operation monitoring was established, including the selection of a sensor module and signal conditioning module. Secondly, a method for real-time compaction monitoring data evaluation and analysis of compaction was proposed and a detailed analysis process of the compaction data was designed. Finally, the compaction operation monitoring prototype system based on the Internet of Things technology was designed and constructed. Full article
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Proceeding Paper
Surface-Mounted Smart PZT Sensors for Monitoring Damage Using EMI-Based Multi-Sensing Technique
Eng. Proc. 2021, 10(1), 51; https://doi.org/10.3390/ecsa-8-11254 - 01 Nov 2021
Viewed by 143
Abstract
In this article, a multi-sensing technique on surface-mounted PZT sensors is proposed. The investigation was performed on concrete structures to detect and localize structural damage. Multiple smart sensing units (SSU) were adhesively bonded on the top surface of a concrete beam. As each [...] Read more.
In this article, a multi-sensing technique on surface-mounted PZT sensors is proposed. The investigation was performed on concrete structures to detect and localize structural damage. Multiple smart sensing units (SSU) were adhesively bonded on the top surface of a concrete beam. As each PZT sensor features a small zone of influence, the use of multiple smart sensors is recommended for effective damage detection. The conductance signatures were obtained at different stages in the frequency range of 0–450 kHz. This article also presents an effective methodology for damage localization, which assumes the parallel connection of SSUs in MISO mode. The methodology adopted for structural damage detection is effective, as it is verified by the experimental results performed on concrete structures with multiple surface-mounted PZT sensors. Full article
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Proceeding Paper
Research on Assembly Process Simulation of Construction Machinery Arm Based on Digital Twin
Eng. Proc. 2021, 10(1), 52; https://doi.org/10.3390/ecsa-8-11331 - 01 Nov 2021
Viewed by 157
Abstract
The construction machinery arm is the key component of construction machinery to complete the operation task; its assembly link directly affects the product quality and operational performance of the whole machinery. To solve the problems of low assembly efficiency and the inability to [...] Read more.
The construction machinery arm is the key component of construction machinery to complete the operation task; its assembly link directly affects the product quality and operational performance of the whole machinery. To solve the problems of low assembly efficiency and the inability to fully reflect the assembly process indexes and product characteristics in the traditional construction machinery arm assembly, this paper studies assembly process modeling and simulation for the construction machinery arm based on assembly sensing data and digital twin. By extracting and processing the assembly resource data and field measurement data of the machinery arm, the assembly process information database under the digital twin environment is constructed, which lays the foundation for the virtual assembly model construction of the machinery arm. Through the real-time data interaction between virtual space and physical space, a complete assembly of digital twin spaces is formed. Finally, taking the assembly line of an excavator armed as an example, it is shown that the digital twin-based assembly simulation can monitor the assembly process in real-time and optimize its configuration to improve assembly efficiency. Therefore, an effective closed-loop feedback mechanism is constructed for the whole assembly process of the construction machinery arm. Full article
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Proceeding Paper
Starter Kit for Electrochemical Sensors Based on Polythiophene Thin Films—Synthesis of High-Quality Films and Protocol for Fast and Gentle Electrode Regeneration
Eng. Proc. 2021, 10(1), 53; https://doi.org/10.3390/ecsa-8-11292 - 01 Nov 2021
Cited by 1 | Viewed by 151
Abstract
Due to their unique properties, polythiophene and other conductive polymers have become the subject of intensive research and are promising substrate materials for innovative and trendsetting applications. To this day, boron trifluoride diethyl etherate (BFEE) is the preferred solvent for the electropolymerization of [...] Read more.
Due to their unique properties, polythiophene and other conductive polymers have become the subject of intensive research and are promising substrate materials for innovative and trendsetting applications. To this day, boron trifluoride diethyl etherate (BFEE) is the preferred solvent for the electropolymerization of thiophene, although it does not allow for reproducible film qualities due to its decomposition under ambient conditions. We therefore want to equip the reader with a starter kit for the electropolymerization of high-quality polythiophene films from stable solvents and a simple yet efficient method to remove the deposited films from the electrodes for their reuse. By drying the working solution prior to its utilization, and by adding a Lewis acid catalyst, films that display enhanced electron transfer and a smooth surface topography can be obtained, which can both be beneficial for the analytic performance of a subsequently built biosensor. Full article
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Proceeding Paper
Sons al Balcó, a Citizen Science Approach to Map the Soundscape of Catalonia
Eng. Proc. 2021, 10(1), 54; https://doi.org/10.3390/ecsa-8-11619 - 01 Nov 2021
Viewed by 170
Abstract
Sons al Balcó (Catalan for “Sounds of the balcony”) was a project born to study the effect that the COVID-19 pandemic lockdown caused on the perception of noise in Catalonia. One of the aims of the project was to combine the research activities—acoustic [...] Read more.
Sons al Balcó (Catalan for “Sounds of the balcony”) was a project born to study the effect that the COVID-19 pandemic lockdown caused on the perception of noise in Catalonia. One of the aims of the project was to combine the research activities—acoustic and image processing, urbanistic analysis and health and annoyance evaluation—with the dynamic collaboration with citizens and other stakeholders to create social and environmental impact, to raise awareness and design tools to improve citizenship development and empowerment. This first year of Sons al Balcó has shown that citizens are willing to participate in initiatives that work with their everyday life, because one year after the lockdown, a new soundscape map of Catalonia has been built with their collaboration and their perceptual impact from their balconies or windows. This has allowed the inclusion of other issues that enhance the final goal of describing and finding relationships between the annoyance caused by noise, and other factors as the environment (urban, suburban, rural) and the landscape, including the soundscape and noise levels in this evaluation. Objective measurements of LAeq have been conducted during the lockdown and in the months afterwards to describe the average noise and its possible link with outdoor activities. During this second collecting campaign, Sons al Balcó managed to gather more than 220 contributions. In this work, we detail the definitions of the metrics that include urbanistic and health-related environmental elements (water, trees, etc.), together with the socio-economic and demographic data that correspond to the answers of the questionnaires, and finally, the information extracted from the audios and the videos sent by the citizens. Preliminary results show encouraging dependencies between perception gathered with the questionnaires and the objective data collected, still in process of analysis, and a clear bias to a worse soundscape in 2021 in comparison to the 2020 campaign. Full article
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Proceeding Paper
Two Realizations of the Wearable PPG Sensor Working in Reflectance Mode for Measurement in Weak Magnetic Field
Eng. Proc. 2021, 10(1), 55; https://doi.org/10.3390/ecsa-8-11252 - 01 Nov 2021
Cited by 1 | Viewed by 112
Abstract
The paper describes and compares properties of two realizations of wearable sensors based on the photoplethysmography (PPG) principle for non-invasive acquisition of the human heart rate. The designed sensors enable measurement of the PPG signal in the magnetic field environment with the inherent [...] Read more.
The paper describes and compares properties of two realizations of wearable sensors based on the photoplethysmography (PPG) principle for non-invasive acquisition of the human heart rate. The designed sensors enable measurement of the PPG signal in the magnetic field environment with the inherent radiofrequency and electromagnetic disturbance. They can monitor the stress of a tested person during examination in the scanning area of the open-air magnetic resonance tomograph. The performed auxiliary experiments verify the practical functionality of both developed sensors including real-time wireless transmission of the measured PPG signal samples to the control device for further analysis and processing. Full article
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Proceeding Paper
Evaluating Suitability of a DS18B20 Temperature Sensor for Use in an Accurate Air Temperature Distribution Measurement Network
Eng. Proc. 2021, 10(1), 56; https://doi.org/10.3390/ecsa-8-11277 - 01 Nov 2021
Viewed by 457
Abstract
We analysed literature data and our experimental results to determine why the readings of different temperature sensors might be notably different in air despite being placed in close proximity. We attributed these differences to two factors—unrestricted air movements and differences in the sensors’ [...] Read more.
We analysed literature data and our experimental results to determine why the readings of different temperature sensors might be notably different in air despite being placed in close proximity. We attributed these differences to two factors—unrestricted air movements and differences in the sensors’ response times. After elimination of these factors, the temperature readings of Pt100 and DS18B20 sensors exhibited an excellent agreement which, together with the convenient networking features provided by the DS18B20 sensors, confirmed their suitability for our use case. Full article
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Proceeding Paper
System for Continuous and Prolonged Ambulatory ECG Monitoring with Hosting and Visualization on the Cloud
Eng. Proc. 2021, 10(1), 57; https://doi.org/10.3390/ecsa-8-11326 - 01 Nov 2021
Viewed by 151
Abstract
In this paper, we propose investigating the ability to integrate a portable Electrocardiogram (ECG) device to commercial platforms to analyze and visualize information hosted in the cloud. Our ECG system based on the ADX8232 microchip was evaluated regarding its performance of recordings of [...] Read more.
In this paper, we propose investigating the ability to integrate a portable Electrocardiogram (ECG) device to commercial platforms to analyze and visualize information hosted in the cloud. Our ECG system based on the ADX8232 microchip was evaluated regarding its performance of recordings of a synthetic ECG signal for periods of 1, 2, 12, 24, and 36 h on six different cloud services to investigate whether it maintains reliable ECG records. Our results show that there are few cloud services capable of 24 h or longer ECG recordings. But some existing services are limited to small file sizes of less than 1,000,000 lines or 100 MB, or approximately 45 min of an ECG recording at a sampling rate of 360 Hz, making it difficult an extended time monitoring. Cloud platforms reveal some limitations of storage and visualization in order to provide support to health care specialists to access information related to a patient at any time. Full article
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Proceeding Paper
Design of a Characterisation Environment for a MEMS Ultrasound Sensor under Guided Ultrasonic Wave Excitation
Eng. Proc. 2021, 10(1), 58; https://doi.org/10.3390/ecsa-8-11306 - 01 Nov 2021
Cited by 2 | Viewed by 190
Abstract
Microelectromechanical Systems (MEMS) are a current subject of research in the field of structural health monitoring (SHM) for the detection of guided ultrasonic waves (GUW). The dispersive behaviour of GUW, reflections and other kinds of wave interactions might result in a complex wave [...] Read more.
Microelectromechanical Systems (MEMS) are a current subject of research in the field of structural health monitoring (SHM) for the detection of guided ultrasonic waves (GUW). The dispersive behaviour of GUW, reflections and other kinds of wave interactions might result in a complex wave field that requires a specific analysis and interpretation of the recorded signals. This makes it difficult or impossible to interpret the sensor signal regarding the distinguishability between the sensor transfer behaviour and the specific behaviour of the test structure. Therefore, a proper application-suited design of the tested structure is crucial for reliable sensor characterisation. The aim of this contribution is the design and evaluation of a setup that allows a representative situation for a GUW application and provides a defined vibration energy for a MEMS sensor characterisation. Parameters such as the specimen’s geometry, material properties and the sensor specifications are taken into account as well as the experimental settings of the GUW excitation. Furthermore, the requirements for the test application case are discussed. Full article
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Proceeding Paper
Accuracy Assessment of TanDEM-X 90 and CartoDEM Using ICESat-2 Datasets for Plain Regions of Ratlam City and Surroundings
Eng. Proc. 2021, 10(1), 59; https://doi.org/10.3390/ecsa-8-11441 - 01 Nov 2021
Viewed by 119
Abstract
The spaceborne LiDAR dataset from the Ice, Cloud, and Land Elevation Satellite (ICESat-2) provides highly accurate measurements of heights for the Earth’s surface, which helps in terrain analysis, visualization, and decision making for many applications. TanDEM-X 90 (90 m) and CartoDEM V3R1 (30 [...] Read more.
The spaceborne LiDAR dataset from the Ice, Cloud, and Land Elevation Satellite (ICESat-2) provides highly accurate measurements of heights for the Earth’s surface, which helps in terrain analysis, visualization, and decision making for many applications. TanDEM-X 90 (90 m) and CartoDEM V3R1 (30 m) elevation are among the high-quality openly accessible DEM datasets for the plain regions in India. These two DEMs are validated against the ICESat-2 elevation datasets for the relatively plain areas of Ratlam City and its surroundings. The mean error (ME), mean absolute error (MAE), and root mean square error (RMSE) of TanDEM-X 90 DEM are 1.35 m, 1.48 m, and 2.19 m, respectively. The computed ME, MAE, and RMSE for CartoDEM V3R1 are 3.05 m, 3.18 m, and 3.82 m, respectively. The statistical results reveal that TanDEM-X 90 performs better in plain areas than CartoDEMV3R1. The study further indicates that these DEMs and spaceborne LiDAR datasets can be useful for planning various works requiring height as an important parameter, such as the layout of pipelines or cut and fill calculations for various construction activities. The TanDEM-X 90 can assist planners in quick assessments of the terrain for infrastructural developments, which otherwise need time-consuming traditional surveys using theodolite or a total station. Full article
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Proceeding Paper
Pregnancy Labor Prediction Using Magnetomyography Sensing and a Self-Sorting Cybernetic Model
Eng. Proc. 2021, 10(1), 60; https://doi.org/10.3390/ecsa-8-11312 - 01 Nov 2021
Viewed by 156
Abstract
To date, effective means of predicting pregnancy labor continues to lack. Magnetic field signals during uterine contraction have shown, in recent studies, to be a good source of information for predicting labor state with a greater accuracy compared with existing methods. The means [...] Read more.
To date, effective means of predicting pregnancy labor continues to lack. Magnetic field signals during uterine contraction have shown, in recent studies, to be a good source of information for predicting labor state with a greater accuracy compared with existing methods. The means of labor prediction methods from such signals appear to rely on a supervised learning post-processing framework whose calibration relies on an effective labelling of the training sample set. As a potential solution to this, using a reduced electrode channel from magnetomyography instrumentation, we propose a multi-stage self-sorting cybernetic model that is comprised of an ensemble of various post-processing methods, and is underpinned by an unsupervised learning framework that allows for an automated method towards learning from the trend in the data to infer labor state and imminency. Experimental results showed a comparable accuracy with those from a supervised learning method adopted in a prior study. Additionally, an architecture of how an intelligent cybernetic model can be used for labor prediction and cost saving benefits within a clinical setting is offered by this study. Full article
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Proceeding Paper
Characterization of the Radiation-Induced Damage in a PEN (Polyethylene Naphthalate) Scintillation Detector
Eng. Proc. 2021, 10(1), 61; https://doi.org/10.3390/ecsa-8-11334 - 01 Nov 2021
Viewed by 111
Abstract
The radiation hardness of a Polyethylene Naphthalate (PEN) thin film scintillator has been characterized in terms of the light yield loss after irradiation with 11 MeV protons and 1 MeV electrons. The light yield distributions induced by excitation with radioactive sources have been [...] Read more.
The radiation hardness of a Polyethylene Naphthalate (PEN) thin film scintillator has been characterized in terms of the light yield loss after irradiation with 11 MeV protons and 1 MeV electrons. The light yield distributions induced by excitation with radioactive sources have been measured on samples irradiated with different doses and the induced light loss has been computed. Results showed the good radiation hardness behaviors of PEN scintillators, with a light yield loss of ~15% at 10 Mrad and ~35% at the maximum delivered dose of 80 Mrad. Full article
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Proceeding Paper
Ultrasonic Oscillating Temperature Sensor for Operation in Air
Eng. Proc. 2021, 10(1), 62; https://doi.org/10.3390/ecsa-8-11276 - 01 Nov 2021
Viewed by 169
Abstract
Ultrasonic oscillating temperature sensors (UOTSs) were shown to respond to temperature changes in aqueous solutions faster than conventional temperatures sensors [1]. This study describes a recently developed air UOTS and presents experimental results on its response to air temperature step changes [...] Read more.
Ultrasonic oscillating temperature sensors (UOTSs) were shown to respond to temperature changes in aqueous solutions faster than conventional temperatures sensors [1]. This study describes a recently developed air UOTS and presents experimental results on its response to air temperature step changes recorded simultaneously using AHT20 and BMP280 air temperature sensors. These results demonstrate a remarkably fast UOTS response time. Full article
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Proceeding Paper
Comparison of Hybrid Localization Methods Using Images and Wi-Fi Signals
Eng. Proc. 2021, 10(1), 63; https://doi.org/10.3390/ecsa-8-10851 - 01 Nov 2021
Viewed by 113
Abstract
Indoor localization is important for many applications, such as navigation, movement tracking, geotagging, and augmented reality. Most studies have used either Wi-Fi or image signals to determine the user’s location. However, each localization method has advantages and disadvantages. In this study, we propose [...] Read more.
Indoor localization is important for many applications, such as navigation, movement tracking, geotagging, and augmented reality. Most studies have used either Wi-Fi or image signals to determine the user’s location. However, each localization method has advantages and disadvantages. In this study, we propose a hybrid localization system combining the advantages of Wi-Fi- and image-based methods. The localization is calculated based on the best four outputs of either image or Wi-Fi localization system. The system was evaluated by comparing the accuracy and unit errors of image-based, Wi-Fi-based, hybrid (image + Wi-Fi), and hybrid (Wi-Fi + image) methods. The results showed accuracies of 77.2%, 49.5%, 73.1%, and 81.6% in the image-based, Wi-Fi-based, hybrid (image + Wi-Fi), and hybrid (Wi-Fi + image) methods, respectively. The hybrid (Wi-Fi and image) method has the lowest error and highest accuracy of the four methods compared. In addition, the image-based localization system shows the highest error, while the Wi-Fi-based localization system shows the lowest accuracy. The robot tests prove that the proposed hybrid system can achieve excellent performance in indoor localization. The proposed hybrid system uses both image processing and Wi-Fi fingerprinting methods to determine the location of the mobile device by creating the two-phase framework, which can help improve the accuracy of indoor localization. Full article
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Proceeding Paper
Accuracy Assessment of Openly Accessible CartoDEM V3 R1 and TanDEM-X 90 Using a Smartphone with Assisted GPS for Ratlam City and Surroundings
Eng. Proc. 2021, 10(1), 64; https://doi.org/10.3390/ecsa-8-11328 - 01 Nov 2021
Viewed by 139
Abstract
The Digital Elevation Model (DEM) is mostly used to extract the terrain parameters for surface and elevation analysis to represent the topography of the earth’s surface in the best possible way. Nowadays, smart devices such as smartphones and tablets employed with GPS chipsets [...] Read more.
The Digital Elevation Model (DEM) is mostly used to extract the terrain parameters for surface and elevation analysis to represent the topography of the earth’s surface in the best possible way. Nowadays, smart devices such as smartphones and tablets employed with GPS chipsets are easily available in the market. These smart devices can measure elevation data and are cost effective. The relatively plain areas of Ratlam City (Madhya Pradesh) were the study area. A Vivo 1606 smartphone incorporated with Assisted-GPS (A-GPS) was used with a GPS utility App called Mobile Topographer to collect the ground coordinates and elevation data. The ground control points (GCPs) were collected in parts of urban areas, such as open grounds, streets, parks, and other uniformly distributed GCP locations with few GCPs in outer regions of the city. Using smartphone-derived GCPs as a reference, the two openly accessible DEMs—namely CartoDEM V3 R1 and TanDEM-X—were evaluated statistically. Statistical parameters such as Mean Error (ME), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were computed for comparative quality analysis between CartoDEM V3 R1 and TanDEM-X 90, using the observed GPS elevation data. The ME (4.60 m), MAE (6.12 m), and RMSE (7.15 m) for TanDEM-X 90 were higher than that of CartoDEM V3 R1, ME (3.09 m), MAE (5.05 m), and RMSE (6.17 m), respectively. The results from the A-GPS Smartphone revealed that the accuracy of CartoDEM V3 R1 is higher and it statistically performs better than TanDEM-X in plain areas of Ratlam using the Smartphone A-GPS. Full article
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Proceeding Paper
Investigating the Terrain Complexity from ATL06 ICESat-2 Data for Terrain Elevation and Its Use for Assessment of Openly Accessible InSAR Based DEMs in Parts of Himalaya’s
Eng. Proc. 2021, 10(1), 65; https://doi.org/10.3390/ecsa-8-11327 - 01 Nov 2021
Viewed by 159
Abstract
Spaceborne sensors are now providing invaluable datasets for the Earth’s surface studies. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) with the Advanced Topographic Laser Altimeter System (ATLAS) was launched by NASA on 15 September 2018, to measure the elevation of the Earth’s [...] Read more.
Spaceborne sensors are now providing invaluable datasets for the Earth’s surface studies. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) with the Advanced Topographic Laser Altimeter System (ATLAS) was launched by NASA on 15 September 2018, to measure the elevation of the Earth’s surface using a laser wavelength of 532 nm and pulse repetition frequency of 10 kHz giving a footprint of approximately 70 cm on the ground. The ICESat-2 datasets are used in this study for the visualization and investigation of the complex Himalayan terrain in the parts of the Kinnaur district and surroundings, which are prone to frequent landslides due to the geology of the region as observed during the recent landslide events. The ICESat-2 elevation datasets were compared with the openly accessible DEM datasets namely, ALOS PALSAR RTC HR (12.5 m) and TanDEM-X (90 m) at ICESat-2 footprint locations. The preprocessing of datasets was completed for selecting ICESat-2 footprints (Track ID: 325, 1270, 828, 386) at locations of high-quality datasets for analysis. The analysis of pre-processed 19,755 ICESat-2 footprints (out of 20,948 footprints) was performed with ALOS PALSAR RTC HR (12.5 m) and TanDEM-X (90 m) datasets. The visualization of the region in the Google earth and OpenAltimetry 3D viewer depicts that the mountain slopes are very steep indicating rugged terrain difficult to access and challenging for construction of transport facilities. The results of Track ID: 325, show that the range of elevations in ICESat-2 elevation values in the study area is from 3409.75 m to 5976.31 m. The standard deviation representing terrain ruggedness using ICESat-2 elevation values is found as 432.06 m. Considering higher accuracy ICESat-2 values for the difficult terrain as a reference, the mean error (ME), mean absolute error (MAE), and RMSE for TanDEM-X were found as 0.26 m, 12.92 m, and 17.4 m, respectively. Whereas the ME, MAE, and RMSE for ALOS PALSAR RTC HR DEM were found as 0.20 m, 9.50 m, and 13.88 m, respectively. Thus, for the study site, using ICESat-2 ATL06 products, ALOS PALSAR RTC HR DEM is found more suitable than TanDEM-X 90 m openly accessible datasets for any kind of application in such a terrain. Full article
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Proceeding Paper
Monitoring of the Production Process and the Force Sensing Quality of a Reduced Graphene Oxide (rGO) Sensor
Eng. Proc. 2021, 10(1), 66; https://doi.org/10.3390/ecsa-8-11278 - 01 Nov 2021
Viewed by 143
Abstract
Graphene oxide (GO) has the advantage of a uniform dispersion in water, which is essential for producing high-quality sensors. In this research, we monitor the production of a GO sensor by measuring the change in conductance of the aqueous GO during painting, heating [...] Read more.
Graphene oxide (GO) has the advantage of a uniform dispersion in water, which is essential for producing high-quality sensors. In this research, we monitor the production of a GO sensor by measuring the change in conductance of the aqueous GO during painting, heating and drying, and converting GO to reduced Graphene oxide with a heat shock. Subsequent testing of the sensor with three-point bending on the compression side of a substrate revealed a clean conductance signal and an anhysteretic and almost linear calibration curve. Full article
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Proceeding Paper
Evaluating Temperature Influence on Low-Cost Microphone Response for 3D Printing Process Monitoring
Eng. Proc. 2021, 10(1), 67; https://doi.org/10.3390/ecsa-8-11251 - 01 Nov 2021
Viewed by 139
Abstract
The 3D printing process deals with the manufacture of parts by adding layers of material onto a heated printing bed. Electret microphones are widely used as low-cost and precise measuring devices. However, its response was negatively affected by higher temperatures due to the [...] Read more.
The 3D printing process deals with the manufacture of parts by adding layers of material onto a heated printing bed. Electret microphones are widely used as low-cost and precise measuring devices. However, its response was negatively affected by higher temperatures due to the field effect transistor utilized in its construction. The Pencil Lead Break (PLB) method is a standardized artificial acoustic emission source utilized for the evaluation of sensors response. The present work aimed to study the electret microphone response for 3D printing monitoring and to evaluate the efficiency of a proposed housing to reduce the printing bed temperature’s influence on the electret microphone’s response. The microphone housing was 3D-printed utilizing ABS filament; its geometry was designed with the purpose of separating the sensor from the heated bed and creating an acoustic shell. Then, PLB tests were performed, and the raw signal was collected from housed and non-housed microphones at 5 MHz sampling frequency. The sensors were tested under three temperatures of the printer bed: at 25 °C (ambient), at 65 °C (operating temperature), and, finally, after the temperature of the table was naturally stabilized from 65 °C to 25 °C. The signals were investigated in the time and frequency domain. The results showed that the housing impacts the microphone’s response positively when operating at 25 °C, where the signals presented higher amplitudes in both domains. However, the response obtained by the housed sensor was considerably attenuated at 65 °C. Furthermore, the signals collected at 25 °C after exposing the housed microphone to heat demonstrated a “greenhouse effect”, keeping the sensor at higher temperatures for an extended period. It can be concluded that the proposed housing failed in reducing the temperature effects in the sensor’s response. However, these effects were shown to be significant and the need for an alternative method to attenuate them was reinforced. Full article
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Proceeding Paper
MMI Sensor for Diameter Measurement
Eng. Proc. 2021, 10(1), 68; https://doi.org/10.3390/ecsa-8-11324 - 01 Nov 2021
Viewed by 160
Abstract
Cylindrical structure analysis is important in several areas and can be performed through the evaluation of the diameter changes of these structures. Two important areas can be mentioned: pipelines for oil or gas distribution and the condition and growth of trees. In the [...] Read more.
Cylindrical structure analysis is important in several areas and can be performed through the evaluation of the diameter changes of these structures. Two important areas can be mentioned: pipelines for oil or gas distribution and the condition and growth of trees. In the tree diameter changes, monitoring is directly related to irrigation, since it depends on the water soil deficit and trees are important in the global circulation of heat and water. This diameter can change in the order of 5 mm for some species. In this paper, a strain gauge sensor based on a core diameter mismatch technique for diameter measurement is proposed and investigated. The sensor structure is formed by splicing an uncoated short section of MMF (Multimode Fiber) between two standard SMFs (Singlemode Fiber) called SMF–MMF–SMF (SMS); the MMF length is 15 mm. Two cylindrical structures were placed on a 3D printer, with different diameter sizes (DS: 80 mm and 110 mm), to assist in monitoring the diameter changes. The SMS sensor was placed on the printed structure and fixed at two points, such that, by reducing the diameter of the structure, the sensor presents dips or peaks shift of the transmittance spectrum due to the induced curvature and strain. Three values were used for the spacing between the fixation points (FP): (a) 5 mm, (b) 10 mm, and (c) 15 mm. For each choice of fixation points, DS = 80 mm: (a) a sensitivity of −0.876 nm/mm, R2 of 0.9909 and a dynamic range of 5 mm; (b) a sensitivity of −0.3892 nm/mm, R2 of 0.9954 and a dynamic range of 4 mm; and (c) a sensitivity of −0.768 nm/mm, R2 of 0.9811 and a dynamic range of 2 mm. For DS = 110 mm, the sensor presents for each choice of fixation points: (a) a sensitivity of −0.22 nm/mm, R2 of 0.9979 and a dynamic range of 8 mm; (b) a sensitivity of −0.2284 nm/mm, R2 of 0.9888 and a dynamic range of 6 mm; and (c) a sensitivity of −0.691 nm/mm, R2 of 0.9892 and a dynamic range of 3.5 mm. Full article
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Proceeding Paper
Finding Earthquake Victims by Voice Detection Techniques
Eng. Proc. 2021, 10(1), 69; https://doi.org/10.3390/ecsa-8-11248 - 01 Nov 2021
Viewed by 120
Abstract
After an earthquake or a building collapse, victim recovery is a challenging task. Recovery methods must include the location of victims by non-visual means; human speech is one such parameter that can be used in victim and rescue operations. In this paper, we [...] Read more.
After an earthquake or a building collapse, victim recovery is a challenging task. Recovery methods must include the location of victims by non-visual means; human speech is one such parameter that can be used in victim and rescue operations. In this paper, we discuss the application of a voice-detection technique for the discrimination of voice and non-voice sounds, based on frequency parameters such as flux, centroid, and roll-off of audio signals. Using the cross-validation tests based on a linear discriminant analysis model, flux and centroid individually displayed the highest success rates for all categories of test sample. By combining these two parameters, the recognition rate was improved to 78% for the signals with high background noise. Full article
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Proceeding Paper
Design of a LIOR-Based De-Dust Filter for LiDAR Sensors in Off-Road Vehicles
Eng. Proc. 2021, 10(1), 70; https://doi.org/10.3390/ecsa-8-11338 - 01 Nov 2021
Cited by 1 | Viewed by 177
Abstract
LiDAR sensors have played an important role in a variety of related applications due to their merits of providing high-resolution and accurate information about the environment. However, their detection performance significantly degrades under dusty conditions, thereby making the whole perception of the vehicles [...] Read more.
LiDAR sensors have played an important role in a variety of related applications due to their merits of providing high-resolution and accurate information about the environment. However, their detection performance significantly degrades under dusty conditions, thereby making the whole perception of the vehicles prone to failure. To deal with this problem, we designed a de-dust filter using a LIOR filtering technique that offers a viable method of eliminating dust particles from the measurement data. Experimental results confirm that the proposed method is robust in the face of dust particles by successfully removing them from the measured point cloud with good filtering accuracy while maintaining rich information about the environment. Full article
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Proceeding Paper
0.1 THz Imaging with a Monolithic High-Tc Superconducting Transition-Edge Detector
Eng. Proc. 2021, 10(1), 71; https://doi.org/10.3390/ecsa-8-11304 - 01 Nov 2021
Viewed by 185
Abstract
Terahertz imaging has attracted significant interest for its applications in noninvasive medical diagnosis, security systems, and industrial inspections. Superconducting bolometers are one of the promising technologies of ultra-sensitive terahertz detection. Here, we present THz images captured by a low-cost superconducting transition-edge detector. The [...] Read more.
Terahertz imaging has attracted significant interest for its applications in noninvasive medical diagnosis, security systems, and industrial inspections. Superconducting bolometers are one of the promising technologies of ultra-sensitive terahertz detection. Here, we present THz images captured by a low-cost superconducting transition-edge detector. The sensing element of the detector is a meander line patterned YBa2Cu3O7x (YBCO) thin film realizing monolithically the absorber and thermometer of the detector. A total of 400 nm YBCO film is deposited on Yttrium-stabilized Zirconia substrate by the metal-organic deposition method which is well-known as an economic and scalable chemical, vacuum-free technique. The meander line pattern consists of 15 series connected parallel lines with a length of 1.5 mm and a width of 50 micrometers. This pattern has shown a significant response to the 0.1 THz equivalents to 3 mm wavelength radiation without any coupled antenna or separate absorber that may reduce the detection speed. The voltage response amplitude of the fabricated detector to 0.1 THz radiation at different modulation frequencies is measured and the detector is utilized for imaging concealed objects including cigarettes and metallic items. Full article
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Proceeding Paper
Experimental Study on Stress Impact during FML Manufacturing on the Functional Conformity of an Embeddable SHM-Sensor-Node
Eng. Proc. 2021, 10(1), 72; https://doi.org/10.3390/ecsa-8-11323 - 01 Nov 2021
Cited by 2 | Viewed by 129
Abstract
Experimental studies were conducted to determine if the stresses occurring during the manufacturing process of Fiber Metal Laminates (FML) cause irreversible damage to electronic components. This is especially interesting for electronic systems to be embedded into such FML for later structural health monitoring [...] Read more.
Experimental studies were conducted to determine if the stresses occurring during the manufacturing process of Fiber Metal Laminates (FML) cause irreversible damage to electronic components. This is especially interesting for electronic systems to be embedded into such FML for later structural health monitoring purposes. Depending on the requirements of the used prepreg material, required temperatures and pressures for manufacturing can be quite high. First studies were conducted on electronic components separately, to validate their functionality after 3.5 h at elevated temperatures and pressures, exceeding manufacturers specifications. The functionality tests were successfully performed afterwards for every tested component, and no malfunctions could be identified. Further experiments will be conducted investigating the influence on a fully functional, programmed electronic system under the same conditions to investigate the influence on memory and soldering joints as well. Full article
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Proceeding Paper
Soft Wearable Patch for Continuous Cardiac Biometric Security
Eng. Proc. 2021, 10(1), 73; https://doi.org/10.3390/ecsa-8-11336 - 01 Nov 2021
Viewed by 200
Abstract
Recent studies show the possibility of using the sound information of an individual as the basis of a biometric security system. This paper introduces a soft wearable system that includes a miniaturized microphone and a wireless circuit for real-time, continuous detection and transmission [...] Read more.
Recent studies show the possibility of using the sound information of an individual as the basis of a biometric security system. This paper introduces a soft wearable system that includes a miniaturized microphone and a wireless circuit for real-time, continuous detection and transmission of sounds measured on the chest. The skin-wearable patch that is non-invasive, flexible, and skin-friendly measures high-quality cardiac sounds to gather personalized biometric data. Convolutional neural network-based machine learning provides a real-time classification of detected sounds for biometric-based recognition of specific people. Creating such an identification key particular to an individual is markedly easier and more effective than the existing biometric systems currently in use because of its consistency and ability to be used continuously. Full article
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Proceeding Paper
A System-on-Chip Assay for Bilirubin Levels Measurement in Whole Blood
Eng. Proc. 2021, 10(1), 74; https://doi.org/10.3390/ecsa-8-11295 - 01 Nov 2021
Cited by 1 | Viewed by 144
Abstract
Bilirubin (BR) is clinically confirmed as a biomarker for liver health and is used to assess the prognosis of cirrhosis. Optical and chemical methods have been utilized for blood BR biosensing. While optical methods offer real-time monitoring and are handy and immune to [...] Read more.
Bilirubin (BR) is clinically confirmed as a biomarker for liver health and is used to assess the prognosis of cirrhosis. Optical and chemical methods have been utilized for blood BR biosensing. While optical methods offer real-time monitoring and are handy and immune to infection, measurements may not be practical due to the instrument complexity and space requirements. This study investigated the dual-wavelength (DWL) technique for BR estimation using a system-on-chip (SoC). The SoC includes an optical module with blue (455 nm) and green (530 nm) LEDs which were used for DWL measurement. Porcine blood was used as a surrogate of human blood and BR levels were kept within the pathophysiological ranges projected from healthy individuals (<1.2 mg/dL) to cirrhotic patients (up to 50 mg/dL). Our findings show a high BR sensitivity in blood. This lays the groundwork for point-of-care testing for BR levels, primarily for hyperbilirubinemia infants and cirrhotic adults out in homes or in-community settings. Full article
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Proceeding Paper
Tapered Optical Fiber for Hydrogen Sensing Application Based on Molybdenum Trioxide (MoO3)
Eng. Proc. 2021, 10(1), 75; https://doi.org/10.3390/ecsa-8-11315 - 01 Nov 2021
Viewed by 157
Abstract
In this work, molybdenum trioxide (MoO3) was synthesized and deposited on tapered optical fiber using the drop-casting technique for hydrogen (H2) detection at room temperature. A transducing platform in a transmission mode was constructed using multimode optical fiber (MMF) [...] Read more.
In this work, molybdenum trioxide (MoO3) was synthesized and deposited on tapered optical fiber using the drop-casting technique for hydrogen (H2) detection at room temperature. A transducing platform in a transmission mode was constructed using multimode optical fiber (MMF) with a 125 µm cladding and a 62.5 µm core diameter. To enhance the evanescent light field surrounding the fiber, the fibers were tapered from 125 µm in diameter to 20 µm in diameter with a 10 mm waist. The microstructures and chemical compositions of the fabricated sensor were analyzed by field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX), differential X-ray (XRD), and atomic force microscopy (AFM). In addition, the gas detection properties of the fabricated sensor were studied by exposing it to various concentrations of hydrogen gas from 0.125% to 2.00%. As a result, the sensitivity, response, and recovery time were 11.96 vol%, 220 s, and 200 s, respectively. Overall, the fabricated sensor exhibits good sensitivity as well as repeatability and stability for hydrogen gas detection. Full article
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Proceeding Paper
Mechanically Flexible Fluid Flow Sensor for Macro-Tubular Architectures
Eng. Proc. 2021, 10(1), 76; https://doi.org/10.3390/ecsa-8-11330 - 01 Nov 2021
Viewed by 184
Abstract
Flow sensors are essential for a variety of applications in fluidic industries. This paper proposes a liquid flow sensor using a microfluidic channel for macrotubular architectures. The sensor comprised a firm poly(methyl methacrylate) (PMMA) microfluidic channel bridge on a mechanically flexible polydimethylsiloxane (PDMS) [...] Read more.
Flow sensors are essential for a variety of applications in fluidic industries. This paper proposes a liquid flow sensor using a microfluidic channel for macrotubular architectures. The sensor comprised a firm poly(methyl methacrylate) (PMMA) microfluidic channel bridge on a mechanically flexible polydimethylsiloxane (PDMS) platform installed on the inner wall of tubular systems. The flexible platform was compatible with various tubular architectures and adopted curvatures. In addition, the microscale fluidic channel surpassed the primary disadvantages of common bulky and rigid flowmeters that cause flow streams disturbance and significant pressure drops in tubular systems. Moreover, the microchannel flow sensor is based on detecting the dominated dynamic pressure generated from the fluid velocity inside the microchannel since the tube flow rate is proportional to the flow velocity inside the channel. The pressure sensors for the microchannel flowmeter displayed a sensitivity of 10 pF/kPa and were fabricated inside the PDMS platform. In particular, the pressure was measured using a capacitive pressure sensor owing to its compatibility with flexible electronics and low power consumption. The capacitive pressure sensor inside the microchannel measures the flowrate based on the force generated on the internal walls from the fluid flow velocity inside the channel. Furthermore, the flow sensor behavior was studied for the overall tubular system and validated using a simulation model for volume flow rate ranging from 500 to 2000 mL/min. Full article
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Proceeding Paper
An Overview of Wearable Photoplethysmographic Sensors and Various Algorithms for Tracking of Heart Rates
Eng. Proc. 2021, 10(1), 77; https://doi.org/10.3390/engproc2021010077 - 27 Jan 2022
Cited by 1 | Viewed by 391
Abstract
It is very challenging to estimate the accurate heart rate/beat during intense physical activities due to corruption of motion artifacts (MAs). However, it is difficult to reconstruct a clean signal and extract heart rate/beat from contaminated photoplethysmography (PPG) signals. It was also observed [...] Read more.
It is very challenging to estimate the accurate heart rate/beat during intense physical activities due to corruption of motion artifacts (MAs). However, it is difficult to reconstruct a clean signal and extract heart rate/beat from contaminated photoplethysmography (PPG) signals. It was also observed that various algorithms have been developed for use in the detection of heart rates during physical activities by reconstructing the contaminated PPG signals to clean PPG signals. Against this backdrop, an overview of the various algorithms was conducted with their results from various works. These results are such that the motion-tolerant adaptive algorithm indicated high agreement and high correlation of more than 0.98 for heart rate (HR) and 0.7 for pulse oxygen saturation (SpO2) extraction between measurements by reference sensors and the algorithm. In addition, the distortion rates were reduced from 52.3% to 3.53%, at frequencies between 1 Hz and 2.5 Hz, when the two-dimensional active noise cancellation algorithm was applied representing daily motion such as walking and jogging. The correlation coefficient between the power spectral densities of the reference and reconstructed heart-rate time series was found to be 0.98, which showed that the spectral filter algorithm for motion artifacts and heart-rate reconstruction (SpaMA) method has a potential for PPG-based HR monitoring in wearable devices for fitness tracking and health monitoring during intense physical activities. The experimental result of the single-notch filter and ensemble empirical mode decomposition (NFEEMD) algorithm using the Pearson correlation was 0.992 which illustrated that the NFEEMD algorithm is not only suitable for HR estimation during continuous activities but also for intense physical activities with acceleration. Other algorithms suitable for HR estimation during physical activities include the time–frequency spectrum for the detection of motion artifacts (TifMA) algorithm, novel time-varying spectral filtering algorithm, noise-robust heart-rate estimation algorithm, real-time QRS detection algorithm, and many other algorithms in this regard. Full article
Proceeding Paper
Spatial Damage Prediction in Composite Materials Using Multipath Ultrasonic Monitoring, Advanced Signal Feature Selection and a Combined Classifying–Regression Artificial Neural Network
Eng. Proc. 2021, 10(1), 78; https://doi.org/10.3390/ecsa-8-11283 - 01 Nov 2021
Viewed by 187
Abstract
Automated damage detection in carbon fibre and fibre metal laminates is still a challenge. Impact damage is typically not visible from the outside. Different measuring and analysis methods are available to detect hidden damage, e.g., delamination or cracks. Examples are X-ray computer tomography [...] Read more.
Automated damage detection in carbon fibre and fibre metal laminates is still a challenge. Impact damage is typically not visible from the outside. Different measuring and analysis methods are available to detect hidden damage, e.g., delamination or cracks. Examples are X-ray computer tomography and methods based on guided ultrasonic waves (GUW). All measuring techniques are characterised by high-dimensional sensor data—in the case of GUW, a set of time-resolved signals as a response to an actuated stimulus. We present a simple but powerful two-level method that reduces the input data (time-resolved sensor signals) significantly through a signal feature selection computation, which can then be applied to a damage predictor function. Besides multi-path sensing and analysis, the novelty of this work is a feed-forward ANN with low complexity which is used to implement the predictor function: it combines a classifier and a spatial regression model. Full article
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Proceeding Paper
The Design of an Environmental-Noise-Labeling App for Citizen Participation in Smart Cities
Eng. Proc. 2021, 10(1), 80; https://doi.org/10.3390/ecsa-8-11273 - 01 Nov 2021
Viewed by 200
Abstract
The urban acoustic environment is composed of a great variety of sounds, whose effects citizens are mainly unaware of, despite medical studies showing that urban noise affects quality of life and health, causing various problems from sleep disturbances to cardiovascular diseases. The development [...] Read more.
The urban acoustic environment is composed of a great variety of sounds, whose effects citizens are mainly unaware of, despite medical studies showing that urban noise affects quality of life and health, causing various problems from sleep disturbances to cardiovascular diseases. The development and deployment of wireless acoustic sensor networks (WASNs) presents new ways to meet urban acoustic challenges in the context of a smart city environment. The improvement of the quality of life of the citizens cannot be limited to measuring the equivalent levels of noise in the streets but should also identify the type of noise source and its impact on the overall noise measurement. For this purpose, the collection of noise sources information requires the application of many techniques, including the recording and labeling of noise events. The latter is a task that is mostly performed manually by experts, using certain types of software, and it is very time-consuming. To improve this task and to take advantage of the rise of new technologies, we propose the design of a game using a mobile application to encourage citizens’ participation in research. The goals of the app are two-fold: to raise awareness of the problems generated by noise and to help experts in the work of pre-labeling sounds for later analysis. We detail the envisioned mechanics of the proposed game, its dynamics and its design. Full article
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Proceeding Paper
Micro-Oscillator as Integrable Sensor for Structure-Borne Ultrasound
Eng. Proc. 2021, 10(1), 81; https://doi.org/10.3390/ecsa-8-11313 - 01 Nov 2021
Cited by 2 | Viewed by 150
Abstract
Motivated by their functional conformity, micro-cantilever-based MEMS oscillators are investigated in this study as structure-integrable transducers for the acquisition of guided ultrasonic waves in fiber–metal laminates. While acceleration-sensitive oscillators are limited in their maximum frequency, the presented displacement-sensitive oscillator is operated quasi-free in [...] Read more.
Motivated by their functional conformity, micro-cantilever-based MEMS oscillators are investigated in this study as structure-integrable transducers for the acquisition of guided ultrasonic waves in fiber–metal laminates. While acceleration-sensitive oscillators are limited in their maximum frequency, the presented displacement-sensitive oscillator is operated quasi-free in the fashion of a seismometer, making it particularly sensitive for high-frequency displacements above the sensor’s resonance frequency. The potential of this non-traditional application of a seismometer for the acquisition of structure-borne ultrasound is demonstrated experimentally. Therefore, MEMS oscillators are formed from the membrane of established pressure sensors by femtosecond laser micro-machining and mounted onto a setup for stimulation by structure-borne ultrasound. Experimental results indicate the targeted proportionality of the high-frequency stimulus and the sensor response. In conclusion, MEMS oscillators enable acquisition of high-frequency displacements and could therefore serve as structure-integrable sensors for guided ultrasonic waves. Full article
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