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Sensors, Volume 22, Issue 3 (February-1 2022) – 599 articles

Cover Story (view full-size image): Computer vision has shown potential for assisting post-earthquake inspection of buildings by means of automatic damage detection in images. However, assessing the safety of an earthquake-damaged building requires that the damage be considered in the context of its global impact on the structural system. We present a framework for assessing the safety of an earthquake-damaged structure based on an exterior photographic survey using unmanned aerial vehicles (UAVs). The system is built around a building information model (BIM), which serves as a reference frame for UAV images and 3D point clouds generated from those images. The BIM links any identified damage to a corresponding element in a structural analysis model, ultimately enabling a performance-based assessment of the target building. View this paper
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Article
SAR Imaging Algorithm of Ocean Waves Based on Optimum Subaperture
Sensors 2022, 22(3), 1299; https://doi.org/10.3390/s22031299 - 08 Feb 2022
Viewed by 530
Abstract
Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean [...] Read more.
Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean images are usually blurred, which seriously affects the acquisition of ocean information. The reasons for the wave blurring in SAR images mainly include the following two aspects. One is that when SAR observes the ocean, the motion of ocean waves will have a greater impact on imaging quality. The other is that the ocean’s surface is seriously decorrelated within the integration time. In order to obtain clear SAR images of ocean waves, a SAR imaging algorithm of ocean waves based on the optimum subaperture is proposed, aiming at the above two aspects. The optimum focus setting of the ocean waves is calculated, drawing support from the azimuth phase velocity of the dominant wave. The optimum subaperture is further calculated according to the proposed new evaluation, namely, F. Finally, according to the optimum focus setting and the optimum subaperture, the dominant wave is refocused, and a clear SAR image of the dominant wave can be obtained. The proposed algorithm was applied to airborne L-band and P-band SAR data. Furthermore, the proposed algorithm was compared with present methods, and the results sufficiently demonstrated the effectiveness and superiority of the proposed algorithm. Full article
(This article belongs to the Special Issue Radar Ocean Remote Sensing)
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Communication
Using a Tip Characterizer to Investigate Microprobe Silicon Tip Geometry Variation in Roughness Measurements
Sensors 2022, 22(3), 1298; https://doi.org/10.3390/s22031298 - 08 Feb 2022
Viewed by 443
Abstract
Given their superior dynamics, microprobes represent promising probe candidates for high-speed roughness measurement applications. Their disadvantage, however, lies in the fact that the volume of the microprobe’s silicon tip decreases dramatically during roughness measurement, and the unstable tip geometry leads to an increase [...] Read more.
Given their superior dynamics, microprobes represent promising probe candidates for high-speed roughness measurement applications. Their disadvantage, however, lies in the fact that the volume of the microprobe’s silicon tip decreases dramatically during roughness measurement, and the unstable tip geometry leads to an increase in measurement uncertainty. To investigate the factors that influence tip geometry variation during roughness measurement, a rectangular-shaped tip characterizer was employed to characterize the tip geometry, and a method for reconstructing the tip geometry from the measured profile was introduced. Experiments were conducted to explore the ways in which the tip geometry is influenced by tip wear, probing force, and the relative movement of the tip with respect to the sample. The results indicate that tip fracture and not tip wear is the main reason for tip volume loss, and that the lateral dynamic load on the tip during scanning mode is responsible for more tip fracture than are other factors. Full article
(This article belongs to the Special Issue Cantilever Sensors for Industrial Applications)
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Article
LSO-FastSLAM: A New Algorithm to Improve the Accuracy of Localization and Mapping for Rescue Robots
Sensors 2022, 22(3), 1297; https://doi.org/10.3390/s22031297 - 08 Feb 2022
Viewed by 475
Abstract
This paper improves the accuracy of a mine robot’s positioning and mapping for rapid rescue. Specifically, we improved the FastSLAM algorithm inspired by the lion swarm optimization method. Through the division of labor between different individuals in the lion swarm optimization algorithm, the [...] Read more.
This paper improves the accuracy of a mine robot’s positioning and mapping for rapid rescue. Specifically, we improved the FastSLAM algorithm inspired by the lion swarm optimization method. Through the division of labor between different individuals in the lion swarm optimization algorithm, the optimized particle set distribution after importance sampling in the FastSLAM algorithm is realized. The particles are distributed in a high likelihood area, thereby solving the problem of particle weight degradation. Meanwhile, the diversity of particles is increased since the foraging methods between individuals in the lion swarm algorithm are different so that improving the accuracy of the robot’s positioning and mapping. The experimental results confirmed the improvement of the algorithm and the accuracy of the robot. Full article
(This article belongs to the Section Sensors and Robotics)
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Article
VDBFusion: Flexible and Efficient TSDF Integration of Range Sensor Data
Sensors 2022, 22(3), 1296; https://doi.org/10.3390/s22031296 - 08 Feb 2022
Viewed by 611
Abstract
Mapping is a crucial task in robotics and a fundamental building block of most mobile systems deployed in the real world. Robots use different environment representations depending on their task and sensor setup. This paper showcases a practical approach to volumetric surface reconstruction [...] Read more.
Mapping is a crucial task in robotics and a fundamental building block of most mobile systems deployed in the real world. Robots use different environment representations depending on their task and sensor setup. This paper showcases a practical approach to volumetric surface reconstruction based on truncated signed distance functions, also called TSDFs. We revisit the basics of this mapping technique and offer an approach for building effective and efficient real-world mapping systems. In contrast to most state-of-the-art SLAM and mapping approaches, we are making no assumptions on the size of the environment nor the employed range sensor. Unlike most other approaches, we introduce an effective system that works in multiple domains using different sensors. To achieve this, we build upon the Academy-Award-winning OpenVDB library used in filmmaking to realize an effective 3D map representation. Based on this, our proposed system is flexible and highly effective and, in the end, capable of integrating point clouds from a 64-beam LiDAR sensor at 20 frames per second using a single-core CPU. Along with this publication comes an easy-to-use C++ and Python library to quickly and efficiently solve volumetric mapping problems with TSDFs. Full article
(This article belongs to the Special Issue Best Practice in Simultaneous Localization and Mapping (SLAM))
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Article
Monitoring Particulate Matter with Wearable Sensors and the Influence on Student Environmental Attitudes
Sensors 2022, 22(3), 1295; https://doi.org/10.3390/s22031295 - 08 Feb 2022
Viewed by 599
Abstract
The mobile monitoring of air pollution is a growing field, prospectively filling in spatial gaps while personalizing air-quality-based risk assessment. We developed wearable sensors to record particulate matter (PM), and through a community science approach, students of partnering Chicago high schools monitored PM [...] Read more.
The mobile monitoring of air pollution is a growing field, prospectively filling in spatial gaps while personalizing air-quality-based risk assessment. We developed wearable sensors to record particulate matter (PM), and through a community science approach, students of partnering Chicago high schools monitored PM concentrations during their commutes over a five- and thirteen-day period. Our main objective was to investigate how mobile monitoring influenced students’ environmental attitudes and we did this by having the students explore the relationship between PM concentrations and urban vegetation. Urban vegetation was approximated with a normalized difference vegetation index (NDVI) using Landsat 8 satellite imagery. While the linear regression for one partner school indicated a negative correlation between PM and vegetation, the other indicated a positive correlation, contrary to our expectations. Survey responses were scored on the basis of their environmental affinity and knowledge. There were no significant differences between cumulative pre- and post-experiment survey responses at Josephinum Academy, and only one weakly significant difference in survey results at DePaul Prep in the Knowledge category. However, changes within certain attitudinal subscales may possibly suggest that students were inclined to practice more sustainable behaviors, but perhaps lacked the resources to do so. Full article
(This article belongs to the Special Issue Feature Papers in Wearables Section 2021)
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Article
Signal Processing Platform for Long-Range Multi-Spectral Electro-Optical Systems
Sensors 2022, 22(3), 1294; https://doi.org/10.3390/s22031294 - 08 Feb 2022
Cited by 1 | Viewed by 487
Abstract
In this paper, we present a hardware and software platform for signal processing (SPP) in long-range, multi-spectral, electro-optical systems (MSEOS). Such systems integrate various cameras such as lowlight color, medium or long-wave-infrared thermal and short-wave-infrared cameras together with other sensors such as laser [...] Read more.
In this paper, we present a hardware and software platform for signal processing (SPP) in long-range, multi-spectral, electro-optical systems (MSEOS). Such systems integrate various cameras such as lowlight color, medium or long-wave-infrared thermal and short-wave-infrared cameras together with other sensors such as laser range finders, radars, GPS receivers, etc. on rotational pan-tilt positioner platforms. An SPP is designed with the main goal to control all components of an MSEOS and execute complex signal processing algorithms such as video stabilization, artificial intelligence-based target detection, target tracking, video enhancement, target illumination, multi-sensory image fusion, etc. Such algorithms might be very computationally demanding, so an SPP enables them to run by splitting processing tasks between a field-programmable gate array (FPGA) unit, a multicore microprocessor (MCuP) and a graphic processing unit (GPU). Additionally, multiple SPPs can be linked together via an internal Gbps Ethernet-based network to balance the processing load. A detailed description of the SPP system and experimental results of workloads for typical algorithms on demonstrational MSEOS are given. Finally, we give remarks regarding upgrading SPPs as novel FPGAs, MCuPs and GPUs become available. Full article
(This article belongs to the Section Electronic Sensors)
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Article
Non-Cooperative SAR Automatic Target Recognition Based on Scattering Centers Models
Sensors 2022, 22(3), 1293; https://doi.org/10.3390/s22031293 - 08 Feb 2022
Viewed by 482
Abstract
This article proposes an Automatic Target Recognition (ATR) algorithm to classify non-cooperative targets in Synthetic Aperture Radar (SAR) images. The scarcity or nonexistence of measured SAR data demands that classification algorithms rely only on synthetic data for training purposes. Based on a model [...] Read more.
This article proposes an Automatic Target Recognition (ATR) algorithm to classify non-cooperative targets in Synthetic Aperture Radar (SAR) images. The scarcity or nonexistence of measured SAR data demands that classification algorithms rely only on synthetic data for training purposes. Based on a model represented by the set of scattering centers extracted from purely synthetic data, the proposed algorithm generates hypotheses for the set of scattering centers extracted from the target under test belonging to each class. A Goodness of Fit test is considered to verify each hypothesis, where the Likelihood Ratio Test is modified by a scattering center-weighting function common to both the model and target. Some algorithm variations are assessed for scattering center extraction and hypothesis generation and verification. The proposed solution is the first model-based classification algorithm to address the recently released Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset on a 100% synthetic training data basis. As a result, an accuracy of 91.30% in a 10-target test within a class experiment under Standard Operating Conditions (SOCs) was obtained. The algorithm was also pioneered in testing the SAMPLE dataset in Extend Operating Conditions (EOCs), assuming noise contamination and different target configurations. The proposed algorithm was shown to be robust for SNRs greater than 5 dB. Full article
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Article
Robotic Manipulation Planning for Automatic Peeling of Glass Substrate Based on Online Learning Model Predictive Path Integral
Sensors 2022, 22(3), 1292; https://doi.org/10.3390/s22031292 - 08 Feb 2022
Viewed by 411
Abstract
Autonomous planning robotic contact-rich manipulation has long been a challenging problem. Automatic peeling of glass substrates of LCD flat panel displays is a typical contact-rich manipulation task, which requires extremely high safe handling through the manipulation process. To this end of peeling glass [...] Read more.
Autonomous planning robotic contact-rich manipulation has long been a challenging problem. Automatic peeling of glass substrates of LCD flat panel displays is a typical contact-rich manipulation task, which requires extremely high safe handling through the manipulation process. To this end of peeling glass substrates automatically, the system model is established from data and is used for the online planning of the robot motion in this paper. A simulation environment is designed to pretrain the process model with deep learning-based neural network structure to avoid expensive and time-consuming collection of real-time data. Then, an online learning algorithm is introduced to tune the pretrained model according to the real-time data from the peeling process experiments to cover the uncertainties of the real process. Finally, an Online Learning Model Predictive Path Integral (OL-MPPI) algorithm is proposed for the optimal trajectory planning of the robot. The performance of our algorithm was validated through glass substrate peeling tasks of experiments. Full article
(This article belongs to the Topic Robotics and Automation in Smart Manufacturing Systems)
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Article
Crossing Frequency Method Applicable to Intermediate Pressure Plasma Diagnostics Using the Cutoff Probe
Sensors 2022, 22(3), 1291; https://doi.org/10.3390/s22031291 - 08 Feb 2022
Viewed by 384
Abstract
Although the recently developed cutoff probe is a promising tool to precisely infer plasma electron density by measuring the cutoff frequency (fcutoff) in the S21 spectrum, it is currently only applicable to low-pressure plasma diagnostics below several torr. To [...] Read more.
Although the recently developed cutoff probe is a promising tool to precisely infer plasma electron density by measuring the cutoff frequency (fcutoff) in the S21 spectrum, it is currently only applicable to low-pressure plasma diagnostics below several torr. To improve the cutoff probe, this paper proposes a novel method to measure the crossing frequency (fcross), which is applicable to high-pressure plasma diagnostics where the conventional fcutoff method does not operate. Here, fcross is the frequency where the S21 spectra in vacuum and plasma conditions cross each other. This paper demonstrates the fcross method through three-dimensional electromagnetic wave simulation as well as experiments in a capacitively coupled plasma source. Results demonstrate that the method operates well at high pressure (several tens of torr) as well as low pressure. In addition, through circuit model analysis, a method to estimate electron density from fcross is discussed. It is believed that the proposed method expands the operating range of the cutoff probe and thus contributes to its further development. Full article
(This article belongs to the Special Issue Terahertz and Millimeter Wave Sensing and Applications)
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Article
Minimal Gluten Exposure Alters Urinary Volatile Organic Compounds in Stable Coeliac Disease
Sensors 2022, 22(3), 1290; https://doi.org/10.3390/s22031290 - 08 Feb 2022
Viewed by 451
Abstract
Coeliac disease (CD) patients are distinguishable from healthy individuals via urinary volatile organic compounds (VOCs) analysis. We exposed 20 stable CD patients on gluten-free diet (GFDs) to a 14-day, 3 g/day gluten challenge (GCh), and assessed urinary VOC changes. A control cohort of [...] Read more.
Coeliac disease (CD) patients are distinguishable from healthy individuals via urinary volatile organic compounds (VOCs) analysis. We exposed 20 stable CD patients on gluten-free diet (GFDs) to a 14-day, 3 g/day gluten challenge (GCh), and assessed urinary VOC changes. A control cohort of 20 patients continued on GFD. Urine samples from Days 0, 7, 14, 28 and 56 were analysed using Lonestar FAIMS and Markes Gas Chromatography–Time of Flight–Mass Spectrometer (GC-TOF-MS). VOC signatures on D (day) 7–56 were compared with D0. Statistical analysis was performed using R. In GCh patients, FAIMS revealed significant VOC differences for all time points compared to D0. GC-TOF-MS revealed significant changes at D7 and D14 only. In control samples, FAIMS revealed significant differences at D7 only. GC-TOF-MS detected no significant differences. Chemical analysis via GC-MS-TOF revealed 12 chemicals with significantly altered intensities at D7 vs. D0 for GCh patients. The alterations persisted for six chemicals at D14 and one (N-methyltaurine) remained altered after D14. This low-dose, short-duration challenge was well tolerated. FAIMS and GC-TOF-MS detected VOC signature changes in CD patients when undergoing a minimal GCh. These findings suggest urinary VOCs could have a role in monitoring dietary compliance in CD patients. Full article
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Article
Evaluation of Static Autonomous GNSS Positioning Accuracy Using Single-, Dual-, and Tri-Frequency Smartphones in Forest Canopy Environments
Sensors 2022, 22(3), 1289; https://doi.org/10.3390/s22031289 - 08 Feb 2022
Cited by 1 | Viewed by 622
Abstract
Determining the current position in a forest is essential for many applications and is often carried out using smartphones. Modern smartphones now support various GNSS constellations and multi-frequency analyses, which are expected to provide more accurate positioning. This study compares the static autonomous [...] Read more.
Determining the current position in a forest is essential for many applications and is often carried out using smartphones. Modern smartphones now support various GNSS constellations and multi-frequency analyses, which are expected to provide more accurate positioning. This study compares the static autonomous GNSS positioning accuracy under forest conditions of four multi-frequency multi-constellation smartphones as well as six single-frequency smartphones and a geodetic receiver. Measurements were carried out at 15 different study sites under forest canopies, with 24 measurements lasting approximately 10 min each taken for the 11 GNSS receivers. The results indicate that, on average, multi-frequency smartphones can achieve a higher positioning accuracy. However, the accuracy varies greatly between smartphones, even between identical or quasi-identical tested smartphones. Therefore, no accuracy should be generalised depending on the number of usable frequencies or constellations, but each smartphone should be considered separately. The dual-frequency Xiaomi Mi 10 clearly stands out compared with the other smartphone with a DRMS of 4.56 m and has a 34% lower absolute error than the best single-frequency phone. Full article
(This article belongs to the Section Remote Sensors)
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Article
People-Centred Development of a Smart Waste Bin
Sensors 2022, 22(3), 1288; https://doi.org/10.3390/s22031288 - 08 Feb 2022
Viewed by 586
Abstract
The study presented in this article focuses on the role of a smart waste bin (waste container) designed for waste management and explores what types of interventions people consider more appropriate in promoting environmentally responsible behaviour—based on norms or on an individual’s emotions. [...] Read more.
The study presented in this article focuses on the role of a smart waste bin (waste container) designed for waste management and explores what types of interventions people consider more appropriate in promoting environmentally responsible behaviour—based on norms or on an individual’s emotions. The smart waste bin development process was people-centred and paid particular attention to human experiences, allowing for various interaction modalities. By incorporating various sensors for waste volume and weight measurement in conjunction with presence and user identification capabilities, the experience was personalised. User feedback was collected by an extensive survey, consisting of four systematic sections, where values, attitudes, norms, perceived behavioural control, behavioural intention and actual behaviour were examined. The survey was completed by 194 respondents. The results showed that participants at the declarative level show a high level of environmental awareness and are very much willing to handle waste appropriately. Additionally, the results of the R&D process indicated that relatively cheap and efficient technological solutions can be developed to support waste management and sustainable lifestyles if the human-centred approach is taken into account. Full article
(This article belongs to the Section Electronic Sensors)
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Article
Designing Man’s New Best Friend: Enhancing Human-Robot Dog Interaction through Dog-Like Framing and Appearance
Sensors 2022, 22(3), 1287; https://doi.org/10.3390/s22031287 - 08 Feb 2022
Viewed by 630
Abstract
To understand how to improve interactions with dog-like robots, we evaluated the importance of “dog-like” framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e., in need of development) versus simply a [...] Read more.
To understand how to improve interactions with dog-like robots, we evaluated the importance of “dog-like” framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e., in need of development) versus simply a robot would result in more positive responses and interactions. We also predicted that adding fur to Aibo would make it appear more dog-like, likable, and interactive. Twenty-nine participants engaged with Aibo in a 2 × 2 (framing × appearance) design by issuing commands to the robot. Aibo and participant behaviors were monitored per second, and evaluated via an analysis of commands issued, an analysis of command blocks (i.e., chains of commands), and using a T-pattern analysis of participant behavior. Participants were more likely to issue the “Come Here” command than other types of commands. When framed as a puppy, participants used Aibo’s dog name more often, praised it more, and exhibited more unique, interactive, and complex behavior with Aibo. Participants exhibited the most smiling and laughing behaviors with Aibo framed as a puppy without fur. Across conditions, after interacting with Aibo, participants felt Aibo was more trustworthy, intelligent, warm, and connected than at their initial meeting. This study shows the benefits of introducing a socially robotic agent with a particular frame and importance on realism (i.e., introducing the robot dog as a puppy) for more interactive engagement. Full article
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Article
A Compact Fiber-Coupled NIR/MIR Laser Absorption Instrument for the Simultaneous Measurement of Gas-Phase Temperature and CO, CO2, and H2O Concentration
Sensors 2022, 22(3), 1286; https://doi.org/10.3390/s22031286 - 08 Feb 2022
Viewed by 483
Abstract
A fiber-coupled, compact, remotely operated laser absorption instrument is developed for CO, CO2, and H2O measurements in reactive flows at the elevated temperatures and pressures expected in gas turbine combustor test rigs with target pressures from 1–25 bar and [...] Read more.
A fiber-coupled, compact, remotely operated laser absorption instrument is developed for CO, CO2, and H2O measurements in reactive flows at the elevated temperatures and pressures expected in gas turbine combustor test rigs with target pressures from 1–25 bar and temperatures of up to 2000 K. The optical engineering for solutions of the significant challenges from the ambient acoustic noise (~120 dB) and ambient test rig temperatures (60 °C) are discussed in detail. The sensor delivers wavelength-multiplexed light in a single optical fiber from a set of solid-state lasers ranging from diodes in the near-infrared (~1300 nm) to quantum cascade lasers in the mid-infrared (~4900 nm). Wavelength-multiplexing systems using a single optical fiber have not previously spanned such a wide range of laser wavelengths. Gas temperature is inferred from the ratio of two water vapor transitions. Here, the design of the sensor, the optical engineering required for simultaneous fiber delivery of a wide range of laser wavelengths on a single optical line-of-sight, the engineering required for sensor survival in the harsh ambient environment, and laboratory testing of sensor performance in the exhaust gas of a flat flame burner are presented. Full article
(This article belongs to the Special Issue Optical Gas Sensing: Media, Mechanisms and Applications)
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Article
Fracture Detection in Wrist X-ray Images Using Deep Learning-Based Object Detection Models
Sensors 2022, 22(3), 1285; https://doi.org/10.3390/s22031285 - 08 Feb 2022
Viewed by 1017
Abstract
Hospitals, especially their emergency services, receive a high number of wrist fracture cases. For correct diagnosis and proper treatment of these, images obtained from various medical equipment must be viewed by physicians, along with the patient’s medical records and physical examination. The aim [...] Read more.
Hospitals, especially their emergency services, receive a high number of wrist fracture cases. For correct diagnosis and proper treatment of these, images obtained from various medical equipment must be viewed by physicians, along with the patient’s medical records and physical examination. The aim of this study is to perform fracture detection by use of deep-learning on wrist X-ray images to support physicians in the diagnosis of these fractures, particularly in the emergency services. Using SABL, RegNet, RetinaNet, PAA, Libra R-CNN, FSAF, Faster R-CNN, Dynamic R-CNN and DCN deep-learning-based object detection models with various backbones, 20 different fracture detection procedures were performed on Gazi University Hospital’s dataset of wrist X-ray images. To further improve these procedures, five different ensemble models were developed and then used to reform an ensemble model to develop a unique detection model, ‘wrist fracture detection-combo (WFD-C)’. From 26 different models for fracture detection, the highest detection result obtained was 0.8639 average precision (AP50) in the WFD-C model. Huawei Turkey R&D Center supports this study within the scope of the ongoing cooperation project coded 071813 between Gazi University, Huawei and Medskor. Full article
(This article belongs to the Section Sensing and Imaging)
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Article
Acoustic Dual-Function Communication and Echo-Location in Inaudible Band
Sensors 2022, 22(3), 1284; https://doi.org/10.3390/s22031284 - 08 Feb 2022
Cited by 1 | Viewed by 414
Abstract
Acoustic communications are experiencing renewed interest as alternative solutions to traditional RF communications, not only in RF-denied environments (such as underwater) but also in areas where the electromagnetic (EM) spectrum is heavily shared among several wireless systems. By introducing additional dedicated channels, independent [...] Read more.
Acoustic communications are experiencing renewed interest as alternative solutions to traditional RF communications, not only in RF-denied environments (such as underwater) but also in areas where the electromagnetic (EM) spectrum is heavily shared among several wireless systems. By introducing additional dedicated channels, independent from the EM ones, acoustic systems can be used to ensure the continuity of some critical services such as communication, localization, detection, and sensing. In this paper, we design and implement a novel acoustic system that uses only low-cost off-the-shelf hardware and the transmission of a single, suitably designed signal in the inaudible band (18–22 kHz) to perform integrated sensing (ranging) and communication. The experimental testbed consists of a common home speaker transmitting acoustic signals to a smartphone, which receives them through the integrated microphone, and of an additional receiver exploiting the same signals to estimate distance information from a physical obstacle in the environment. The performance of the proposed dual-function system in terms of noise, data rate, and accuracy in distance estimation is experimentally evaluated in a real operational environment. Full article
(This article belongs to the Special Issue Acoustic Sensing Systems and Their Applications in Smart Environments)
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Article
Evaluation of Upper Limb Joint Contribution to Racket Head Speed in Elite Tennis Players Using IMU Sensors: Comparison between the Cross-Court and Inside-Out Attacking Forehand Drive
Sensors 2022, 22(3), 1283; https://doi.org/10.3390/s22031283 - 08 Feb 2022
Viewed by 484
Abstract
This study aimed to quantify and compare the upper limb angular kinematics and its contributions to the racket head speed between the cross-court (CC) and inside-out (IO) attacking tennis forehand of elite tennis players in a competitive environment. A new approach was used [...] Read more.
This study aimed to quantify and compare the upper limb angular kinematics and its contributions to the racket head speed between the cross-court (CC) and inside-out (IO) attacking tennis forehand of elite tennis players in a competitive environment. A new approach was used to study the forehand drive with mini-inertial sensors of motion capture to record the kinematic data. Six strokes in each direction per participant (72 shots in total) were chosen for analysis. Upper limb kinematics were calculated in the Visual 3D platform (Visual 3D Professional V5.01.21, C-motion, Germantown, MD, USA). The method used to calculate the upper limb’s contributions was performed with MATLAB software and used the segment’s (upper arm, forearm and hand) angular velocities and their respective displacement vectors obtained through the inertial sensors. Upper limb kinematics demonstrated a higher shoulder rotation in the IO direction with significant differences at the end of the backswing, which could be a key factor in distinguishing the two directions of the shot. Results also demonstrated that the horizontal flexion of the upper arm (around the shoulder joint) was primarily responsible for the racket velocity in the anteroposterior direction (48.1% CC and 45.2% IO), followed by the extension of the forearm (around the elbow joint) (17.3% CC and 20.9% IO) and the internal rotation of the upper arm (around the shoulder joint) (15.6% CC and 14.2% IO). No significant differences were shown in the contributions of upper limbs to the racket head velocity between the two directions of the shot. Tennis coaches and players should develop a specific training programme to perform higher angular velocities in these specific joint rotations. Full article
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Review
Electrochemically Deposited Molecularly Imprinted Polymer-Based Sensors
Sensors 2022, 22(3), 1282; https://doi.org/10.3390/s22031282 - 08 Feb 2022
Cited by 1 | Viewed by 852
Abstract
This review is dedicated to the development of molecularly imprinted polymers (MIPs) and the application of MIPs in sensor design. MIP-based biological recognition parts can replace receptors or antibodies, which are rather expensive. Conducting polymers show unique properties that are applicable in sensor [...] Read more.
This review is dedicated to the development of molecularly imprinted polymers (MIPs) and the application of MIPs in sensor design. MIP-based biological recognition parts can replace receptors or antibodies, which are rather expensive. Conducting polymers show unique properties that are applicable in sensor design. Therefore, MIP-based conducting polymers, including polypyrrole, polythiophene, poly(3,4-ethylenedioxythiophene), polyaniline and ortho-phenylenediamine are frequently applied in sensor design. Some other materials that can be molecularly imprinted are also overviewed in this review. Among many imprintable materials conducting polymer, polypyrrole is one of the most suitable for molecular imprinting of various targets ranging from small organics up to rather large proteins. Some attention in this review is dedicated to overview methods applied to design MIP-based sensing structures. Some attention is dedicated to the physicochemical methods applied for the transduction of analytical signals. Expected new trends and horizons in the application of MIP-based structures are also discussed. Full article
(This article belongs to the Special Issue Affinity-Based Sensors)
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Article
A Simple Yet Effective Preanalytical Strategy Enabling the Application of Aptamer-Conjugated Gold Nanoparticles for the Colorimetric Detection of Antibiotic Residues in Raw Milk
Sensors 2022, 22(3), 1281; https://doi.org/10.3390/s22031281 - 08 Feb 2022
Viewed by 579
Abstract
The misuse of antibiotics in the cattle sector can lead to milk contamination, with concomitant effects on the dairy industry and human health. Biosensors can be applied in this field; however, the influence of the milk matrix on their activity has been poorly [...] Read more.
The misuse of antibiotics in the cattle sector can lead to milk contamination, with concomitant effects on the dairy industry and human health. Biosensors can be applied in this field; however, the influence of the milk matrix on their activity has been poorly studied in light of the preanalytical process. Herein, aptamer-conjugated gold nanoparticles (nanoaptasensors) were investigated for the colorimetric detection in raw milk of four antibiotics used in cattle. The effect of milk components on the colorimetric response of the nanoaptasensors was analyzed by following the selective aggregation of the nanoparticles, using the absorption ratio A520/A720. A preanalytical strategy was developed to apply the nanoaptasensors to antibiotic-contaminated raw milk samples, which involves a clarification step with Carrez reagents followed by the removal of cations through dilution, chelation (EDTA) or precipitation (NaHCO3). The colorimetric signals were detected in spiked samples at concentrations of antibiotics as low as 0.25-fold the maximum residue limits (MRLs) for kanamycin (37.5 μg/L), oxytetracycline (25 μg/L), sulfadimethoxine (6.25 μg/L) and ampicillin (1 μg/L), according to European and Chilean legislation. Overall, we conclude that this methodology holds potential for the semiquantitative analysis of antibiotic residues in raw milk obtained directly from dairy farms. Full article
(This article belongs to the Special Issue Optical Sensors Technology and Applications)
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Article
Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking
Sensors 2022, 22(3), 1280; https://doi.org/10.3390/s22031280 - 08 Feb 2022
Viewed by 646
Abstract
Video tracking involves detecting previously designated objects of interest within a sequence of image frames. It can be applied in robotics, unmanned vehicles, and automation, among other fields of interest. Video tracking is still regarded as an open problem due to a number [...] Read more.
Video tracking involves detecting previously designated objects of interest within a sequence of image frames. It can be applied in robotics, unmanned vehicles, and automation, among other fields of interest. Video tracking is still regarded as an open problem due to a number of obstacles that still need to be overcome, including the need for high precision and real-time results, as well as portability and low-power demands. This work presents the design, implementation and assessment of a low-power embedded system based on an SoC-FPGA platform and the honeybee search algorithm (HSA) for real-time video tracking. HSA is a meta-heuristic that combines evolutionary computing and swarm intelligence techniques. Our findings demonstrated that the combination of SoC-FPGA and HSA reduced the consumption of computational resources, allowing real-time multiprocessing without a reduction in precision, and with the advantage of lower power consumption, which enabled portability. A starker difference was observed when measuring the power consumption. The proposed SoC-FPGA system consumed about 5 Watts, whereas the CPU-GPU system required more than 200 Watts. A general recommendation obtained from this research is to use SoC-FPGA over CPU-GPU to work with meta-heuristics in computer vision applications when an embedded solution is required. Full article
(This article belongs to the Topic Complex Systems and Artificial Intelligence)
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Communication
Real-Time Metasurface Sensor for Monitoring Micropoisons in Aqueous Solutions Based on Gold Nanoparticles and Terahertz Spectroscopy
Sensors 2022, 22(3), 1279; https://doi.org/10.3390/s22031279 - 08 Feb 2022
Viewed by 449
Abstract
Proof of concept of a new real-time metasurface sensor for micropoison monitoring in aqueous solutions is proposed in this study. The sensor comprises a perfect absorber metasurface and gold nanoparticle layer on the front side of it. Frequency-domain terahertz spectroscopy system was used [...] Read more.
Proof of concept of a new real-time metasurface sensor for micropoison monitoring in aqueous solutions is proposed in this study. The sensor comprises a perfect absorber metasurface and gold nanoparticle layer on the front side of it. Frequency-domain terahertz spectroscopy system was used to measure the resonance frequency shift due to the presence of the micropoison. The perfect absorber metasurface sensor was fabricated using a double-sided FR4 substrate printed board circuit, which is very inexpensive. A significant increase in the metasurface sensor sensitivity was achieved by adding a gold nanoparticle layer to the gap of the double split rectangular resonator on the front side of the metasurface sensor. Full article
(This article belongs to the Section Sensor Materials)
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Article
Bridge Digital Twinning Using an Output-Only Bayesian Model Updating Method and Recorded Seismic Measurements
Sensors 2022, 22(3), 1278; https://doi.org/10.3390/s22031278 - 08 Feb 2022
Cited by 1 | Viewed by 1001
Abstract
Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation [...] Read more.
Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The described process is a practice of digital twinning and the updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism. Full article
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Article
An Inkjet Printed Flexible Electrocorticography (ECoG) Microelectrode Array on a Thin Parylene-C Film
Sensors 2022, 22(3), 1277; https://doi.org/10.3390/s22031277 - 08 Feb 2022
Viewed by 556
Abstract
Electrocorticography (ECoG) is a conventional, invasive technique for recording brain signals from the cortical surface using an array of electrodes. In this study, we developed a highly flexible 22-channel ECoG microelectrode array on a thin Parylene film using novel fabrication techniques. Narrow (<40 [...] Read more.
Electrocorticography (ECoG) is a conventional, invasive technique for recording brain signals from the cortical surface using an array of electrodes. In this study, we developed a highly flexible 22-channel ECoG microelectrode array on a thin Parylene film using novel fabrication techniques. Narrow (<40 µm) and thin (<500 nm) microelectrode patterns were first printed on PDMS, then the patterns were transferred onto Parylene films via vapor deposition and peeling. A custom-designed, 3D-printed connector was built and assembled with the Parylene-based flexible ECoG microelectrode array without soldering. The impedance of the assembled ECoG electrode array was measured in vitro by electrochemical impedance spectroscopy, and the result was consistent. In addition, we conducted in vivo studies by implanting the flexible ECoG sensor in a rat and successfully recording brain signals. Full article
(This article belongs to the Section Biomedical Sensors)
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Article
Flexible and Transparent Circularly Polarized Patch Antenna for Reliable Unobtrusive Wearable Wireless Communications
Sensors 2022, 22(3), 1276; https://doi.org/10.3390/s22031276 - 08 Feb 2022
Cited by 3 | Viewed by 572
Abstract
This paper presents a circularly polarized flexible and transparent circular patch antenna suitable for body-worn wireless-communications. Circular polarization is highly beneficial in wearable wireless communications, where antennas, as a key component of the RF front-end, operate in dynamic environments, such as the human [...] Read more.
This paper presents a circularly polarized flexible and transparent circular patch antenna suitable for body-worn wireless-communications. Circular polarization is highly beneficial in wearable wireless communications, where antennas, as a key component of the RF front-end, operate in dynamic environments, such as the human body. The demonstrated antenna is realized with highly flexible, robust and transparent conductive-fabric-polymer composite. The performance of the explored flexible-transparent antenna is also compared with its non-transparent counterpart manufactured with non-transparent conductive fabric. This comparison further demonstrates the suitability of the proposed materials for the target unobtrusive wearable applications. Detailed numerical and experimental investigations are explored in this paper to verify the proposed design. Moreover, the compatibility of the antenna in wearable applications is evaluated by testing the performance on a forearm phantom and calculating the specific absorption rate (SAR). Full article
(This article belongs to the Special Issue Applications of Antenna Technology in Sensors)
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Article
Visible Particle Series Search Algorithm and Its Application in Structural Damage Identification
Sensors 2022, 22(3), 1275; https://doi.org/10.3390/s22031275 - 08 Feb 2022
Viewed by 389
Abstract
Identifying structural damage is an essential task for ensuring the safety and functionality of civil, mechanical, and aerospace structures. In this study, the structural damage identification scheme is formulated as an optimization problem, and a new meta-heuristic optimization algorithm, called visible particle series [...] Read more.
Identifying structural damage is an essential task for ensuring the safety and functionality of civil, mechanical, and aerospace structures. In this study, the structural damage identification scheme is formulated as an optimization problem, and a new meta-heuristic optimization algorithm, called visible particle series search (VPSS), is proposed to tackle that. The proposed VPSS algorithm is inspired by the visibility graph technique, which is a technique used basically to convert a time series into a graph network. In the proposed VPSS algorithm, the population of candidate solutions is regarded as a particle series and is further mapped into a visibility graph network to obtain visible particles. The information captured from the visible particles is then utilized by the algorithm to seek the optimum solution over the search space. The general performance of the proposed VPSS algorithm is first verified on a set of mathematical benchmark functions, and, afterward, its ability to identify structural damage is assessed by conducting various numerical simulations. The results demonstrate the high accuracy, reliability, and computational efficiency of the VPSS algorithm for identifying the location and the extent of damage in structures. Full article
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Article
On Quadratic Interpolation of Image Cross-Correlation for Subpixel Motion Extraction
Sensors 2022, 22(3), 1274; https://doi.org/10.3390/s22031274 - 08 Feb 2022
Cited by 1 | Viewed by 316
Abstract
Digital image correlation techniques are well known for motion extraction from video images. Following a two-stage approach, the pixel-level displacement is first estimated by maximizing the cross-correlation between two images, then the estimation is refined in the vicinity of the cross-correlation peak. Among [...] Read more.
Digital image correlation techniques are well known for motion extraction from video images. Following a two-stage approach, the pixel-level displacement is first estimated by maximizing the cross-correlation between two images, then the estimation is refined in the vicinity of the cross-correlation peak. Among existing subpixel refinement methods, quadratic surface fitting (QSF) provides good performances in terms of accuracy and computational burden. It estimates subpixel displacement by interpolating cross-correlation values with a quadratic surface. The purpose of this paper is to analytically investigate the QSF method. By means of counterexamples, it is first shown in this paper that, contrary to a widespread intuition, the quadratic surface fitted to the pixel-level cross-correlation values in the neighborhood of the cross-correlation peak does not always have a maximum. The main contribution of this paper then consists in establishing the mathematical conditions ensuring the existence of a maximum of this fitted quadratic surface, based on a rigorous analysis. Algorithm modifications for handling the failure cases of the QSF method are also proposed in this paper, in order to consolidate it for subpixel motion extraction. Experimental results based on two typical types of images are also reported. Full article
(This article belongs to the Section Sensing and Imaging)
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Article
Capacitive Sensor and Alternating Drive Mixing for Microfluidic Applications Using Micro Diaphragm Pumps
Sensors 2022, 22(3), 1273; https://doi.org/10.3390/s22031273 - 08 Feb 2022
Viewed by 368
Abstract
Microfluidic systems are of paramount importance in various fields such as medicine, biology, and pharmacy. Despite the plethora of methods, accurate dosing and mixing of small doses of liquid reagents remain challenges for microfluidics. In this paper, we present a microfluidic device that [...] Read more.
Microfluidic systems are of paramount importance in various fields such as medicine, biology, and pharmacy. Despite the plethora of methods, accurate dosing and mixing of small doses of liquid reagents remain challenges for microfluidics. In this paper, we present a microfluidic device that uses two micro pumps and an alternating drive pattern to fill a microchannel. With a capacitive sensor system, we monitored the fluid process and controlled the micro pumps. In a first experiment, the system was set up to generate a 1:1 mixture between two fluids while using a range of fluid packet sizes from 0.25 to 2 µL and pumping frequencies from 50 to 100 Hz. In this parameter range, a dosing accuracy of 50.3 ± 0.9% was reached, validated by a gravimetric measurement. Other biased mixing ratios were tested as well and showed a deviation of 0.3 ± 0.3% from the targeted mixing ratio. In a second experiment, Trypan blue was used to study the mixing behavior of the system. Within one to two dosed packet sets, the two reagents were reliably mixed. The results are encouraging for future use of micro pumps and capacitive sensing in demanding microfluidic applications. Full article
(This article belongs to the Section Biomedical Sensors)
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Article
A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists
Sensors 2022, 22(3), 1272; https://doi.org/10.3390/s22031272 - 08 Feb 2022
Cited by 1 | Viewed by 724
Abstract
We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and [...] Read more.
We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and an optical particle-matter (PM) sensor for PM2.5 and PM10 concentrations. The electronic instrumentation was home-developed for this application. To ensure a constant air flow, the input fan of the particle sensor is used as an air supply pump to the rest of the sensors. Eight identical devices were built; two were collocated in parallel with a reference urban-air-quality-monitoring station and calibrated using a neural network (R2 > 0.83). Several bicycle routes were carried out throughout the city of Badajoz (Spain) to allow the device to be tested in real field conditions. An air-quality index was calculated to facilitate the user’s understanding. The results show that this index provides data on the spatiotemporal variability of pollutants between the central and peripheral areas, including changes between weekdays and weekends and between different times of the day, thus providing valuable information for citizens through a dedicated cloud-based data platform. Full article
(This article belongs to the Special Issue Chemical Gas Sensors for Environment Monitoring)
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Article
A Consortium Blockchain-Based Secure and Trusted Electronic Portfolio Management Scheme
Sensors 2022, 22(3), 1271; https://doi.org/10.3390/s22031271 - 08 Feb 2022
Viewed by 1044
Abstract
In recent times, electronic portfolios (e-portfolios) are being increasingly used by students and lifelong learners as digital online multimedia résumés that showcase their skill sets and achievements. E-portfolios require secure, reliable, and privacy-preserving credential issuance and verification mechanisms to prove learning achievements. However, [...] Read more.
In recent times, electronic portfolios (e-portfolios) are being increasingly used by students and lifelong learners as digital online multimedia résumés that showcase their skill sets and achievements. E-portfolios require secure, reliable, and privacy-preserving credential issuance and verification mechanisms to prove learning achievements. However, existing systems provide private institution-wide centralized solutions that primarily rely on trusted third parties to issue and verify credentials. Furthermore, they do not enable learners to own, control, and share their e-portfolio information across organizations, which increases the risk of forged and fraudulent credentials. Therefore, we propose a consortium blockchain-based e-portfolio management scheme that is decentralized, secure, and trustworthy. Smart contracts are leveraged to enable learners to completely own, publish, and manage their e-portfolios, and also enable potential employers to verify e-portfolio credentials and artifacts without relying on trusted third parties. Blockchain is used as an immutable distributed ledger that records all transactions and logs for tamper-proof trusted data provenance, accountability, and traceability. This system guarantees the authenticity and integrity of user credentials and e-portfolio data. Decentralized identifiers and verifiable credentials are used for user profile identification, authentication, and authorization, whereas verifiable claims are used for e-portfolio credential proof authentication and verification. We have designed and implemented a prototype of the proposed scheme using a Quorum consortium blockchain network. Based on the evaluations, our solution is feasible, secure, and privacy-preserving. It offers excellent performance. Full article
(This article belongs to the Section Internet of Things)
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Article
Application of Knowledge Distillation Based on Transfer Learning of ERNIE Model in Intelligent Dialogue Intention Recognition
Sensors 2022, 22(3), 1270; https://doi.org/10.3390/s22031270 - 08 Feb 2022
Viewed by 465
Abstract
The ‘intention’ classification of a user question is an important element of a task-engine driven chatbot. The essence of a user question’s intention understanding is the text classification. The transfer learning, such as BERT (Bidirectional Encoder Representations from Transformers) and ERNIE (Enhanced Representation [...] Read more.
The ‘intention’ classification of a user question is an important element of a task-engine driven chatbot. The essence of a user question’s intention understanding is the text classification. The transfer learning, such as BERT (Bidirectional Encoder Representations from Transformers) and ERNIE (Enhanced Representation through Knowledge Integration), has put the text classification task into a new level, but the BERT and ERNIE model are difficult to support high QPS (queries per second) intelligent dialogue systems due to computational performance issues. In reality, the simple classification model usually shows a high computational performance, but they are limited by low accuracy. In this paper, we use knowledge of the ERNIE model to distill the FastText model; the ERNIE model works as a teacher model to predict the massive online unlabeled data for data enhancement, and then guides the training of the student model of FastText with better computational efficiency. The FastText model is distilled by the ERNIE model in chatbot intention classification. This not only guarantees the superiority of its original computational performance, but also the intention classification accuracy has been significantly improved. Full article
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