Sensors, Volume 20, Issue 24 (December-2 2020) – 355 articles

X-ray single-grating interferometry was applied to conduct accurate wavefront corrections for hard X-ray nanofocusing mirrors. Systematic errors in the interferometer, originating from a grating, a detector, and alignment errors of the components, were carefully examined. Based on the measured wavefront errors, the mirror shapes were directly corrected using a differential deposition technique. The corrected X-ray focusing mirrors with a numerical aperture of 0.01 attained two-dimensionally diffraction-limited performance. The results of the correction indicate that the uncertainty of the wavefront measurement was less than λ/72 in root-mean-square value. Full article

The focus of this paper was designing and demonstrating bus structure FBG sensor networks using intensity wavelength division multiplexing (IWDM) techniques and a gated recurrent unit (GRU) algorithm to increase the capability of multiplexing and the ability to detect Bragg wavelengths with greater accuracy. Several Fiber Bragg grating (FBG) sensors are coupled with power ratios of 90:10 and 80:10, respectively in the suggested experimental setup. We used the latest IWDM multiplexing technique for the proposed scheme, as the IWDM system increases the number of sensors and allows us to alleviate the limited operational region drawback of conventional wavelength division multiplexing (WDM). However, IWDM has a crosstalk problem that causes high-sensor signal measurement errors. Thus, we proposed the GRU model to overcome this crosstalk or overlapping problem by converting the spectral detection problem into a regression problem and considered the sequence of spectral features as input. By feeding this sequential spectrum dataset into the GRU model, we trained the GRU system until we achieved optimal efficiency. Consequently, the well-trained GRU model quickly and accurately identifies the Bragg wavelength of each FBG from the overlapping spectra. The Bragg wavelength detection performance of our proposed GRU model is tested or validated using different numbers of FBG sensors, such as 3-FBG, 5-FBG, 7-FBG, and 10-FBG, separately. As a result, the experiment result proves that the well-trained GRU model accurately identifies each FBG Bragg wavelength, and even the number of FBG sensors increase, as well as the spectra of FBGs, which are partially or fully overlapped. Therefore, to boost the detection efficiency, reliability, and to increase the multiplexing capabilities of FBG sensor networks, the proposed sensor system is better than the other previously proposed methods. Full article

Mindfulness training is associated with improvements in psychological wellbeing and cognition, yet the specific underlying neurophysiological mechanisms underpinning these changes are uncertain. This study uses a novel brain-inspired artificial neural network to investigate the effect of mindfulness training on electroencephalographic function. Participants completed a 4-tone auditory oddball task (that included targets and physically similar distractors) at three assessment time points. In Group A (n = 10), these tasks were given immediately prior to 6-week mindfulness training, immediately after training and at a 3-week follow-up; in Group B (n = 10), these were during an intervention waitlist period (3 weeks prior to training), pre-mindfulness training and post-mindfulness training. Using a spiking neural network (SNN) model, we evaluated concurrent neural patterns generated across space and time from features of electroencephalographic data capturing the neural dynamics associated with the event-related potential (ERP). This technique capitalises on the temporal dynamics of the shifts in polarity throughout the ERP and spatially across electrodes. Findings support anteriorisation of connection weights in response to distractors relative to target stimuli. Right frontal connection weights to distractors were associated with trait mindfulness (positively) and depression (inversely). Moreover, mindfulness training was associated with an increase in connection weights to targets (bilateral frontal, left frontocentral, and temporal regions only) and distractors. SNN models were superior to other machine learning methods in the classification of brain states as a function of mindfulness training. Findings suggest SNN models can provide useful information that differentiates brain states based on distinct task demands and stimuli, as well as changes in brain states as a function of psychological intervention. Full article

Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation. Full article

To reduce the impact of acoustic interference in a microelectromechanical system (MEMS) gyroscope and to improve the reliability of output data, a filtering algorithm based on orthogonal demodulation is proposed. According to the working principle and failure mechanism of a MEMS gyroscope, the sound and angular velocity frequencies are not identical, which lead to a different frequency signal output of the original single-channel demodulation scheme. Therefore, a Q channel demodulation filtering process was added to the origin single-channel demodulation scheme. For the Q channel demodulated signal, a Hilbert transform was used to compensate for the 90 degree phase shift. The IQ dual-channel difference can remove the acoustic interference signal. The simulation results indicate that the scheme can effectively suppress the acoustic interference signal and it can eliminate more than 95% of the impact of sound waves. We assembled the acoustic interference experimental platform, collected the driving and sensing data, and verified the denoising performance with our algorithm, which eliminated more than 70% of the noise signal. The simulation and experimental results demonstrate that the scheme can eliminate acoustic interference signal without destroying angular velocity signal. Full article

Many lightweight lidar sensors employed for UAS lidar mapping feature a fan-style laser emitter-detector configuration which results in a non-uniform pattern of laser pulse returns. As the role of UAS lidar mapping grows in both research and industry, it is imperative to understand the behavior of the fan-style lidar sensor to ensure proper mission planning. This study introduces sensor modeling software for scanning simulation and analytical equations developed in-house to characterize the non-uniform return density (i.e., scan pattern) of the fan-style sensor, with special focus given to a popular fan-style sensor, the Velodyne VLP-16 laser scanner. The results indicate that, despite the high pulse frequency of modern scanners, areas of poor laser pulse coverage are often present along the scanning path under typical mission parameters. These areas of poor coverage appear in a variety of shapes and sizes which do not necessarily correspond to the forward speed of the scanner or the height of the scanner above the ground, highlighting the importance of scan simulation for proper mission planning when using a fan-style sensor. Full article

The study evaluates the suitability of a field asymmetric ion mobility spectrometry (FAIMS) system for early detection of the Pythium leak disease in potato tubers simulating bulk storage conditions. Tubers of Ranger Russet (RR) and Russet Burbank (RB) cultivars were inoculated with Pythium ultimum, the causal agent of Pythium leak (with negative control samples as well) and placed in glass jars. The headspace in sampling jars was scanned using the FAIMS system at regular intervals (in days up to 14 and 31 days for the tubers stored at 25 °C and 4 °C, respectively) to acquire ion mobility current profiles representing the volatile organic compounds (VOCs). Principal component analysis plots revealed that VOCs ion peak profiles specific to Pythium ultimum were detected for the cultivars as early as one day after inoculation (DAI) at room temperature storage condition, while delayed detection was observed for tubers stored at 4 °C (RR: 5th DAI and RB: 10th DAI), possibly due to a slower disease progression at a lower temperature. There was also some overlap between control and inoculated samples at a lower temperature, which could be because of the limited volatile release. Additionally, data suggested that the RB cultivar might be less susceptible to Pythium ultimum under reduced temperature storage conditions. Disease symptom-specific critical compensation voltage (CV) and dispersion field (DF) from FAIMS responses were in the ranges of −0.58 to −2.97 V and 30–84% for the tubers stored at room temperature, and −0.31 to −2.97 V and 28–90% for reduced temperature, respectively. The ion current intensities at −1.31 V CV and 74% DF showed distinctive temporal progression associated with healthy control and infected tuber samples. Full article

In order to assess the limits and applicability of Pitot tubes for the measurement of flow velocity in narrow ducts, e.g., biomass burning plants, an optical, dual function device was implemented. This sensor, based on spectroscopic techniques, targets a trace gas, injected inside the stack either in bursts, or continuously, so performing transit time or dilution measurements. A comparison of the two optical techniques with respect to Pitot readings was carried out in different flow conditions (speed, temperature, gas composition). The results of the two optical measurements are in agreement with each other and fit quite well the theoretical simulation of the flow field, while the results of the Pitot measurements show a remarkable dependence on position and inclination of the Pitot tube with respect to the duct axis. The implications for the metrology of small combustors’ emissions are outlined. Full article

Wearable devices play an increasing role in the rehabilitation of patients with movement disorders. Although information about muscular activation is highly interesting, no approach exists that allows reliable collection of this information when the sensor is applied autonomously by the patient. This paper aims to demonstrate the proof-of-principle of an innovative sEMG sensor system, which can be used intuitively by patients while detecting their muscular activation with sufficient accuracy. The sEMG sensor system utilizes a multichannel approach based on 16 sEMG leads arranged circularly around the limb. Its design enables a stable contact between the skin surface and the system’s dry electrodes, fulfills the SENIAM recommendations regarding the electrode size and inter-electrode distance and facilitates a high temporal resolution. The proof-of-principle was demonstrated by elbow flexion/extension movements of 10 subjects, proving that it has root mean square values and a signal-to-noise ratio comparable to commercial systems based on pre-gelled electrodes. Furthermore, it can be easily placed and removed by patients with reduced arm function and without detailed knowledge about the exact positioning of the sEMG electrodes. With its features, the demonstration of the sEMG sensor system’s proof-of-principle positions it as a wearable device that has the potential to monitor muscular activation in home and community settings. Full article

Chromatic confocal microscopy (CCM) has been intensively developed because it can exhibit effective focal position scanning based on the axial chromatic aberration of broadband light reflected from a target. To improve the imaging speed of three-dimensional (3D) surface profiling, we have proposed the novel concept of swept-source-based CCM (SS-CCM) and investigated the usefulness of the corresponding imaging system. Compared to conventional CCM based on a broadband light source and a spectrometer, a swept-source in the proposed SS-CCM generates light with a narrower linewidth for higher intensity, and a single photodetector employed in the system exhibits a fast and sensitive response by immediately obtaining spectrally encoded depth from a chromatic dispersive lens array. Results of the experiments conducted to test the proposed SS-CCM system indicate that the system exhibits an axial chromatic focal distance range of approximately 360 $\mathsf{\mu }\mathrm{m}$ for the 770–820 nm swept wavelength range. Moreover, high-speed surface profiling images of a cover glass and coin were successfully obtained with a short measurement time of 5 ms at a single position. Full article

Lodging, a commonly occurring rice crop disaster, seriously reduces rice quality and production. Monitoring rice lodging after a typhoon event is essential for evaluating yield loss and formulating suitable remedial policies. The availability of Sentinel-1 and Sentinel-2 open-access remote sensing data provides large-scale information with a short revisit time to be freely accessed. Data from these sources have been previously shown to identify lodged crops. In this study, therefore, Sentinel-1 and Sentinel-2 data after a typhoon event were combined to enable monitoring of lodging rice to be quickly undertaken. In this context, the sensitivity of synthetic aperture radar (SAR) features (SF) and spectral indices (SI) extracted from Sentinel-1 and Sentinel-2 to lodged rice were analyzed, and a model was constructed for selecting optimal sensitive parameters for lodging rice (OSPL). OSPL has high sensitivity to lodged rice and strong ability to distinguish lodged rice from healthy rice. After screening, Band 11 (SWIR-1) and Band 12 (SWIR-2) were identified as optimal spectral indices (OSI), and VV, VV + VH and Shannon Entropy were optimal SAR features (OSF). Three classification results of lodging rice were acquired using the Random Forest classification (RFC) method based on OSI, OSF and integrated OSI–OSF stack images, respectively. Results indicate that an overall level of accuracy of 91.29% was achieved with the combination of SAR and optical optimal parameters. The result was 2.91% and 6.05% better than solely using optical or SAR processes, respectively. Full article

Sampling-based calibration systems for calibrating “Sampled Value” (SV)-based instruments for substation automation require synchronised and time-aligned sampling processes. As the signal frequency of the power grid is always asynchronous to the standardised sampling frequencies according to IEC 61869-9, the sampled waveforms of the calibration system and of the SV-based device under test can be resampled to be synchronised and to allow better accuracy in the following measurements based on the Discrete Fourier Transform (DFT) of the resampled waveforms. The paper presents simulations and results for different resampling algorithms. A modified sinc interpolation method with a finite impulse response (FIR) is presented. The deviation of the results for the root mean square (RMS) and phase angle is in the order of 10⁻⁸V/V (or rad) for normalised frequencies of up to 20% of the sampling frequency. No practical degradation in the presence of noise and harmonics could be observed. In addition, laboratory experiments demonstrate the realization of the proposed resampling process in the future SV-based calibration systems for SV-based instrumentation. Full article

Autonomous vehicles are at the forefront of interest due to the expectations of changing transportation for the better. In order to make better decisions on the road, vehicles use information from various sources: their own sensors, messages arriving from surrounding vehicles and objects, as well as from centralized entities—including their own Digital Twin. Certain decisions require the information to arrive with low latency and some of this information (such as video) requires broadband communication. Furthermore, the vehicles can populate an area, so they can represent mass communication endpoints that still need low latency and massive broadband. The mobility of the vehicles obviously requires the complete coverage of the roads with reliable wireless communication technologies fulfilling the previously mentioned needs. The fifth generation of cellular mobile technologies, 5G, addresses these requirements. The current paper presents real-life scenarios—on the M86 highway and the ZalaZONE proving ground in Hungary—for the demonstration of vehicular communication with 5G support, where the cars exchange sensor and control information with each other, their environment, and their Digital Twins. The demonstrations were carried out through the Scenario-in-the-Loop (SciL) methodology, where some of the actionable triggers were not physically present around the vehicles, but sensed or simulated around their Digital Twin. The measurements around the demonstrations aim to reveal the feasibility of the 5G Non-Standalone Architecture for certain communication scenarios, and they mainly aim to reveal the current latency and throughput limitations under real-life conditions. Full article

This paper presents a 0.5 V fifth-order Butterworth low-pass filter based on multiple-input operational transconductance amplifiers (OTA). The filter is designed for electrocardiogram (ECG) acquisition systems and operates in the subthreshold region with nano-watt power consumption. The used multiple-input technique simplifies the overall structure of the OTA and reduces the number of active elements needed to realize the filter. The filter was designed and simulated in the Cadence environment using a 0.18 µm Complementary Metal Oxide Semiconductor (CMOS) process from Taiwan Semiconductor Manufacturing Company (TSMC). Simulation results show that the filter has a bandwidth of 250 Hz, a power consumption of 34.65 nW, a dynamic range of 63.24 dB, attaining a figure-of-merit of 0.0191 pJ. The corner (process, voltage, temperature: PVT) and Monte Carlo (MC) analyses are included to prove the robustness of the filter. Full article

Cloud computing has emerged as the primary choice for developers in developing applications that require high-performance computing. Virtualization technology has helped in the distribution of resources to multiple users. Increased use of cloud infrastructure has led to the challenge of developing a load balancing mechanism to provide optimized use of resources and better performance. Round robin and least connections load balancing algorithms have been developed to allocate user requests across a cluster of servers in the cloud in a time-bound manner. In this paper, we have applied the round robin and least connections approach of load balancing to HAProxy, virtual machine clusters and web servers. The experimental results are visualized and summarized using Apache Jmeter and a further comparative study of round robin and least connections is also depicted. Experimental setup and results show that the round robin algorithm performs better as compared to the least connections algorithm in all measuring parameters of load balancer in this paper. Full article

In recent years, the investigation and exploitation of hydrothermal region and polymetallic mineral areas has become a hot topic. The emergence of underwater vehicle platforms has made it possible for new chemical sensors to be applied in marine in-situ detection. Laser-induced breakdown spectroscopy (LIBS), with its advantages of rapid real-time analysis, sampling without pretreatment, simultaneous multi-element detection and stand-off detection, has great potential in marine applications. In this paper, a newly more compact and lighter underwater LIBS system based on the LIBSea system named LIBSea II was developed and tested both in the laboratory and sea trials. The system consists of a Nd:YAG single-pulse laser at 1064 nm, a fiber spectrometer, optical layout, a power supply module and an internal environment sensor. The system is encapsulated in a pressure vessel (Φ 190 mm × L 588 mm) with an optical window on the end cap. Experimental parameters of the system including laser energy and delay time were firstly optimized in the laboratory. Then, field test of the system in nearshore was performed with various samples, including pure metal and alloy samples as well as a manganese nodule sample from deep sea, to verify the detection performance of the LIBSea II system. In 2019, the system was deployed on a remotely operated vehicle (ROV) of Haima for deep sea trial, and atomic lines of K, Na, Ca and strong molecular bands of CaOH from a carbonate rock sample were obtained for the first time at depths of 1400 m. These results show that the LIBSea II system has great potential to be used in deep-sea geological exploration. Full article

Two-dimensional (2D) materials, such as molybdenum disulfide (MoS₂) of the transition metal dichalcogenides family, are widely investigated because of their outstanding electrical and optical properties. However, not much of the 2D materials research completed to date has covered large-area structures comprised of high-quality heterojunction diodes. We fabricated a large-area n-MoS₂/p-Si heterojunction structure by sulfurization of MoO_x film, which is thermally evaporated on p-type silicon substrate. The n-MoS₂/p-Si structure possessed excellent diode characteristics such as ideality factor of 1.53 and rectification ratio in excess of 10⁴. Photoresponsivity and detectivity of the diode showed up to 475 mA/W and 6.5 × 10¹¹ Jones, respectively, in wavelength ranges from visible to near-infrared. The device appeared also the maximum external quantum efficiency of 72%. The rise and decay times of optical transient response were measured about 19.78 ms and 0.99 ms, respectively. These results suggest that the sulfurization process for large-area 2D heterojunction with MoS₂ can be applicable to next-generation electronic and optoelectronic devices. Full article

With the recent development of artificial intelligence along with information and communications infrastructure, a new paradigm of online services is being developed. Whereas in the past a service system could only exchange information of the service provider at the request of the user, information can now be provided by automatically analyzing a particular need, even without a direct user request. This also holds for online platforms of used-vehicle sales. In the past, consumers needed to inconveniently determine and classify the quality of information through static data provided by service and information providers. As a result, this service field has been harmful to consumers owing to such problems as false sales, fraud, and exaggerated advertising. Despite significant efforts of platform providers, there are limited human resources for censoring the vast amounts of data uploaded by sellers. Therefore, in this study, an algorithm called YOLOv3+MSSIM Type 2 for automatically censoring the data of used-vehicle sales on an online platform was developed. To this end, an artificial intelligence system that can automatically analyze an object in a vehicle video uploaded by a seller, and an artificial intelligence system that can filter the vehicle-specific terms and profanity from the seller’s video presentation, were also developed. As a result of evaluating the developed system, the average execution speed of the proposed YOLOv3+MSSIM Type 2 algorithm was 78.6 ms faster than that of the pure YOLOv3 algorithm, and the average frame rate per second was improved by 40.22 fps. In addition, the average GPU utilization rate was improved by 23.05%, proving the efficiency. Full article

This study describe the characteristics of hemiplegic stroke gait with principal component analysis (PCA) of trunk movement (TM) and gait event (GE) parameters by the inertial measurement unit (IMU) sensors: (1) Background: This process can determine dominant variables through multivariate examination to identify the affected, unaffected, and healthy lower-limb sides; (2) Methods: The study monitored forty patients with stroke and twenty-eight healthy individuals comprising the control group for comparison. The IMU sensors were attached to each subject while performing a 6 m walking test. Sixteen variables extracted from the measured data were divided into 7 GE and 9 TM variables explaining pelvis tilt, oblique, and rotation. (3) Results: The tilt range variables of the trunk movement on the affected and unaffected sides were lower than those of the healthy side; this showed between-group differences in various GE variables. For the healthy and affected sides, 80% of variances were explained with 2 or 3 PCs involving only a few dominant variables; and (4) Conclusions: The difference between each side leg should be considered during the development of a diagnosis method. This research can be utilized to develop functional assessment tools for personalized treatment and to design appropriate training protocols. Full article

We document a feedback controller design for a nonlinear electrostatic transducer that exhibits a strong unloaded resonance. Challenging features of this type of transducer include the presence of multiple fixed points (some of which are unstable), nonlinear force-to-deflection transfer, effective spring-constant softening due to electrostatic loading and associated resonance frequency shift. Furthermore, due to the utilization of lowpass filters in the electronic readout circuitry, a significant amount of transport delay is introduced in the feedback loop. To stabilize this electro-mechanical system, we employ an active disturbance-rejecting controller with nonlinear force mapping and delay synchronization. As demonstrated by numerical simulations, the combination of these three control techniques stabilizes the system over a wide range of electrode deflections. The proposed controller shows good setpoint tracking and disturbance rejection, and improved settling time, compared to the sensor alone. Full article

Frequent location updates of individual Internet of Things (IoT) devices can cause several problems (e.g., signaling overhead in networks and energy depletion of IoT devices) in massive machine type communication (mMTC) systems. To alleviate these problems, we design a distributed group location update algorithm (DGLU) in which geographically proximate IoT devices determine whether to conduct the location update in a distributed manner. To maximize the accuracy of the locations of IoT devices while maintaining a sufficiently small energy outage probability, we formulate a constrained stochastic game model. We then introduce a best response dynamics-based algorithm to obtain a multi-policy constrained Nash equilibrium. From the evaluation results, it is demonstrated that DGLU can achieve an accuracy of location information that is comparable with that of the individual location update scheme, with a sufficiently small energy outage probability. Full article

Photoplethysmography is an extensively-used, portable, and noninvasive technique for measuring vital parameters such as heart rate, respiration rate, and blood pressure. The deployment of this technology in veterinary medicine has been hindered by the challenges in effective transmission of light presented by the thick layer of skin and fur of the animal. We propose an injectable capsule system to circumvent these limitations by accessing the subcutaneous tissue to enable reliable signal acquisition even with lower light brightness. In addition to the reduction of power usage, the injection of the capsule offers a less invasive alternative to surgical implantation. Our current prototype combines two application-specific integrated circuits (ASICs) with a microcontroller and interfaces with a commercial light emitting diode (LED) and photodetector pair. These ASICs implement a signal-conditioning analog front end circuit and a frequency-shift keying (FSK) transmitter respectively. The small footprint of the ASICs is the key in the integration of the complete system inside a 40-mm long glass tube with an inner diameter of 4 mm, which enables its injection using a custom syringe similar to the ones used with microchip implants for animal identification. The recorded data is transferred wirelessly to a computer for post-processing by means of the integrated FSK transmitter and a software-defined radio. Our optimized LED duty cycle of 0.4% at a sampling rate of 200 Hz minimizes the contribution of the LED driver (only 0.8 mW including the front-end circuitry) to the total power consumption of the system. This will allow longer recording periods between the charging cycles of the batteries, which is critical given the very limited space inside the capsule. In this work, we demonstrate the wireless operation of the injectable system with a human subject holding the sensor between the fingers and the in vivo functionality of the subcutaneous sensing on a pilot study performed on anesthetized rat subjects. Full article

This paper proposes a novel design for a chip-on-probe with the aim of overcoming the heat dissipation effect during brain stimulations using modulated microwave signals. The temperature of the stimulus chip during normal operation is generally 40 °C–60 °C, which is sufficient to cause unintended temperature effects during stimulation. This effect is particularly fatal in brain stimulation applications that require repeated stimulation. This paper proposes, for the first time, a topology that vertically separates the stimulus chip generating the stimulus signal and the probe delivering the signal into the brain to suppress the heat transfer while simultaneously minimizing the radio frequency (RF) transmission loss. As the proposed chip-on-probe should be attached to the head of a small animal, an auxiliary board with a heat sink was carefully designed considering the weight that does not affect the behavior experiment. When the transition structures are properly designed, a heat sink can be mounted to maximize the cooling effect, reducing the temperature by more than 13 °C in a simulation when the heat generated by the chip is transferred to the brain, while the transition from the chip to the probe experiences a loss of 1.2 dB. Finally, the effectiveness of the proposed design is demonstrated by fabricating a chip with the 0.28 μm silicon-on-insulator (SOI) complementary metal–oxide–semiconductor (CMOS) process and a probe with a RT6010 printed-circuit board (PCB), showing a temperature reduction of 49.8 °C with a maximum output power of 11 dBm. In the proposed chip-on-probe device, the temperature formed in the area in contact with the brain is measured at 31.1 °C. Full article

This paper proposes emotion amplification for TV chat agents allowing users to get more excited in TV sports programs, and a model that estimates the excitement level of TV programs based on the number of social comment posts. The proposed model extracts the exciting intervals from social comments to the program scenes. By synchronizing recorded video streams and the intervals, the agents may talk with the user dynamically changing the frequency and volume of upbeat utterances, increasing the excitement of the user. To test these agents, participants watched TV content under three conditions: without an agent, with four agents that utter with a flat voice, and with four agents with emotion amplification. Results from 24 young adult Japanese individuals showed that their arousal of participants’ subjective and physiological emotional responses were boosted because of the agents, enhancing their motivation to interact with the agent in the future. With empirical evidence, this paper supports these expectations and demonstrates that these agents can amplify the positive emotions of TV watchers, enhancing their motivation to interact with the agent in the future. Full article

Variable air humidity affects the characteristics of semiconductor metal oxides, which complicates the reliable and reproducible determination of CO content in ambient air by resistive gas sensors. In this work, we determined the sensor properties of electrospun ZnO and ZnO/Pd nanofibers in the detection of CO in dry and humid air, and investigated the sensing mechanism. The microstructure of the samples, palladium content, and oxidation state, type, and concentration of surface groups were characterized using complementary techniques: X-ray fluorescent spectroscopy, XRD, high-resolution transmission electron microscopy (HRTEM), high angle annular dark field scanning transmission electron microscopy (HAADF-STEM), energy-dispersive X-ray (EDX) mapping, XPS, and FTIR spectroscopy. The sensor properties of ZnO and ZnO/Pd nanofibers were studied at 100–450 °C in the concentration range of 5–15 ppm CO in dry (RH₂₅ = 0%) and humid (RH₂₅ = 60%) air. It was found that under humid conditions, ZnO completely loses its sensitivity to CO, while ZnO/Pd retains a high sensor response. On the basis of in situ diffuse reflectance IR Fourier transform spectroscopy (DRIFTS) results, it was concluded that high sensor response of ZnO/Pd nanofibers in dry and humid air was due to the electronic sensitization effect, which was not influenced by humidity change. Full article

For years, urban air quality networks have been set up by private organizations and governments to monitor toxic gases like NO₂. However, these networks can be very expensive to maintain, so their distribution is usually widely spaced, leaving gaps in the spatial resolution of the resulting air quality data. Recently, electrochemical sensors and their integration with unmanned aerial vehicles (UAVs) have attempted to fill these gaps through various experiments, none of which have considered the influence of a UAV when calibrating the sensors. Accordingly, this research attempts to improve the reliability of NO₂ measurements detected from electrochemical sensors while on board an UAV by introducing rotor speed as part of the calibration model. This is done using a DJI Matrice 100 quadcopter and Alphasense sensors, which are calibrated using regression calculations in different environments. This produces a predictive r-squared up to 0.97. The sensors are then calibrated with rotor speed as an additional variable while on board the UAV and flown in a series of flights to evaluate the performance of the model, which produces a predictive r-squared up to 0.80. This methodological approach can be used to obtain more reliable NO₂ measurements in future outdoor experiments that include electrochemical sensor integration with UAV’s. Full article

Baseball hitting is a highly dynamic activity, and advanced methods are required to accurately obtain biomechanical data. Inertial measurement units (IMUs) can capture the motion of body segments at high sampling rates both indoor and outdoor. The bat rotates around the longitudinal axis of the body; thus, trunk motion plays a key role in baseball hitting. Segmental coordination is important in transferring power to a moving ball and, therefore, useful in evaluating swing kinematics. The current study aimed to investigate the validity and reliability of IMUs with a sampling rate of 1000 Hz attached on the pelvis, thorax, and hand in assessing trunk and hand motion during baseball hitting. Results obtained using the IMU and optical motion capture system (OMCS) were compared. Angular displacements of the trunk segments and spine joint had a root mean square error of <5°. The mean absolute error of the angular velocities was ≤5%. The intra-class correlation coefficient (>0.950) had excellent reliability for trunk kinematics along the longitudinal-axis. Hand velocities at peak and impact corresponded to the values determined using the OMCS. In conclusion, IMUs with high sampling rates are effective in evaluating trunk and hand movement coordination during hitting motion. Full article

As a typical application of indirect-time-of-flight (ToF) technology, photonic mixer device (PMD) solid-state array Lidar has gained rapid development in recent years. With the advantages of high resolution, frame rate and accuracy, the equipment is widely used in target recognition, simultaneous localization and mapping (SLAM), industrial inspection, etc. The PMD Lidar is vulnerable to several factors such as ambient light, temperature and the target feature. To eliminate the impact of such factors, a proper calibration is needed. However, the conventional calibration methods need to change several distances in large areas, which result in low efficiency and low accuracy. To address the problems, this paper presents an improved calibration method based on electrical analog delay. The method firstly eliminates the lens distortion using a self-adaptive interpolation algorithm, meanwhile it calibrates the grayscale image using an integral time simulating based method. Then, the grayscale image is used to estimate the parameters of ambient light compensation in depth calibration. Finally, by combining four types of compensation, the method effectively improves the performance of depth calibration. Through several experiments, the proposed method is more adaptive to multiscenes with targets of different reflectivities, which significantly improves the ranging accuracy and adaptability of PMD Lidar. Full article

The aim of the present study was to assess the capability of conduction velocity amplitudes and directions of propagation of electrohysterogram (EHG) waves to better distinguish between preterm and term EHG surface records. Using short-time cross-correlation between pairs of bipolar EHG signals (upper and lower, left and right), the conduction velocities and their directions were estimated using preterm and term EHG records of the publicly available Term–Preterm EHG DataSet with Tocogram (TPEHGT DS) and for different frequency bands below and above 1.0 Hz, where contractions and the influence of the maternal heart rate on the uterus, respectively, are expected. No significant or preferred continuous direction of propagation was found in any of the non-contraction (dummy) or contraction intervals; however, on average, a significantly lower percentage of velocity vectors was found in the vertical direction, and significantly higher in the horizontal direction, for preterm dummy intervals above 1.0 Hz. The newly defined features—the percentages of velocities in the vertical and horizontal directions, in combination with the sample entropy of the EHG signal recorded in the vertical direction, obtained from dummy intervals above 1.0 Hz—showed the highest classification accuracy of 86.8% ($AUC=90.3\%$) in distinguishing between preterm and term EHG records of the TPEHGT DS. Full article

The purpose of this research was to develop a simple, cost-effective, but enough efficient solution for locating, tracking and distribution analysis of people and/or vehicle flowing, based on non-intrusive Bluetooth sensing and selective filtering algorithms employing artificial intelligence components. The solution provides a tool for analyzing density of targets in a specific area, useful when checking contact proximities of a target along a route. The principle consists of the detection of mobile devices that use active Bluetooth connections, such as personal notebooks, smartphones, smartwatches, Bluetooth headphones, etc. to locate and track their movement in the dedicated area. For this purpose, a specific configuration of three BT sensors is used and RSSI levels compared, based on a combination of differential location estimates. The solution may also be suited for indoor localization where GPS signals are usually weak or missing; for example, in public places such as subway stations or trains, hospitals, airport terminals and so on. The applicability of this solution is estimated to be vast, ranging from travel and transport information services, route guidance, passenger flows tracking, and path recovery for persons suspected to have SARS-COV2 or other contagious viruses, serving epidemiologic enquiries. The specific configuration of Bluetooth detectors may be installed either in a fixed location, or in a public transport vehicle. A set of filters and algorithms for triangulation-based location of detected targets and movement tracking, based on artificial intelligence is employed. When applied in the public transport field, this setup can be also developed to extract additional information on traffic, such as private traffic flowing, or passenger movement patterns along the vehicle route, improved location in absence of GPS signals, etc. Field tests have been carried out for determining different aspects concerning indoor location accuracy, reliability, selection of targets and filtering. Results and possible applications are also presented in the final section of the paper. Full article