Sensors

Zhang, Jianlin;Yuan, Bo;Jiang, Zheng;Guo, Yuanyue;Wang, Dongjin

doi: 10.3390/s20236859pmid: 33266182

Microwave Staring Correlated Imaging (MSCI) is a newly proposed computational high-resolution imaging technique. The imaging performance of MSCI with the existence of modeling errors depends on the properties of the imaging matrix and the relative perturbation error resulted from existing errors. In conventional transient-radiation-fields-based MSCI, which is commonly accomplished by utilizing random frequency-hopping (FH) waveforms, the multiple transmitters should be controlled individually and simultaneously. System complexity and control difficulty are hence increased, and various types of modeling errors are introduced as well. The computation accuracy of radiation fields is heavily worsened by the modeling errors, and the transient effect makes it hard to take direct and high-precision measurements of the radiation fields and calibrate the modeling errors with the measuring result. To simplify the system complexity and reduce error sources, in this paper, steady-radiation-fields-sequence-based MSCI (SRFS-MSCI) method is proposed. The multiple transmitters are excited with coherent signals at the same observation moment, with the signal frequency varying in the whole frequency band during the imaging process. By elaborately designing the array configuration and the amplitude and phase sequences of the coherent transmitters, the SRFS-MSCI is thus implemented. Comparing the system architecture of the proposed SRFS-MSCI with the conventional random FH-based MSCI, it can be found that the proposed method significantly reduces the number of baseband modules and simplifies the system architecture and control logic, which contributes to reducing error sources such as baseband synchronization errors and decreasing deterioration caused by error cascade. To further optimize the design parameters in the proposed SRFS-MSCI system, the Simulated Annealing (SA) algorithm is utilized to optimize the amplitude sequences, the phase sequences, and the antenna positions individually and jointly. Numerical imaging experiments and real-world imaging experiment demonstrate the effectiveness of the proposed SRFS-MSCI method that recognizable high-resolution recovery results are obtained with simplified system structure and optimized system parameters.

Gbagir, Augustine-Moses Gaavwase;Colpaert, Alfred

doi: 10.3390/s20236881pmid: 33271976

The trophic state of Lake Ladoga was studied during the period 1997–2019, using the Copernicus Marine Environmental Monitoring Service (CMEMS) GlobColour-merged chlorophyll-a OC5 algorithm (GlobColour CHL-OC5) satellite observations. Lake Ladoga, in general, is mesotrophic but certain parts of the lake have been eutrophic since the 1960s due to the discharge of wastewater from industrial, urban, and agricultural sources. Since then, many ecological assessments of the Lake’s state have been made. These studies have indicated that various changes are taking place in the lake and continuous monitoring of the lake is essential to update the current knowledge of its state. The aim of this study was to assess the long-term trend in chl-a in Lake Ladoga. The results showed a gradual reduction in chl-a concentration, indicating a moderate improvement. Chl-a concentrations (minimum-maximum values) varied spatially. The shallow southern shores did not show any improvement while the situation in the north is much better. The shore areas around the functioning paper mill at Pitkäranta and city of Sortavala still show high chl-a values. These findings provide a general reference on the current trophic state of Lake Ladoga that could contribute to improve policy and management strategies. It is assumed that the present warming trend of surface water may result in phytoplankton growth increase, thus partly offsetting a decrease in nutrient load. Precipitation is thought to be increasing, but the influence on water quality is less clear. Future studies could assess the current chemical composition to determine the state of water quality of Lake Ladoga.

Fang, Xin;Gao, Tian;Zou, Liang;Ling, Zhenhua

doi: 10.3390/s20236784pmid: 33261046

Automatic speaker verification provides a flexible and effective way for biometric authentication. Previous deep learning-based methods have demonstrated promising results, whereas a few problems still require better solutions. In prior works examining speaker discriminative neural networks, the speaker representation of the target speaker is regarded as a fixed one when comparing with utterances from different speakers, and the joint information between enrollment and evaluation utterances is ignored. In this paper, we propose to combine CNN-based feature learning with a bidirectional attention mechanism to achieve better performance with only one enrollment utterance. The evaluation-enrollment joint information is exploited to provide interactive features through bidirectional attention. In addition, we introduce one individual cost function to identify the phonetic contents, which contributes to calculating the attention score more specifically. These interactive features are complementary to the constant ones, which are extracted from individual speakers separately and do not vary with the evaluation utterances. The proposed method archived a competitive equal error rate of 6.26% on the internal “DAN DAN NI HAO” benchmark dataset with 1250 utterances and outperformed various baseline methods, including the traditional i-vector/PLDA, d-vector, self-attention, and sequence-to-sequence attention models.

Pradhapan, Paruthi;Velazquez, Emmanuel Rios;Witteveen, Jolanda A.;Tonoyan, Yelena;Mihajlović, Vojkan

doi: 10.3390/s20236810pmid: 33260624

Assessing the human affective state using electroencephalography (EEG) have shown good potential but failed to demonstrate reliable performance in real-life applications. Especially if one applies a setup that might impact affective processing and relies on generalized models of affect. Additionally, using subjective assessment of ones affect as ground truth has often been disputed. To shed the light on the former challenge we explored the use of a convenient EEG system with 20 participants to capture their reaction to affective movie clips in a naturalistic setting. Employing state-of-the-art machine learning approach demonstrated that the highest performance is reached when combining linear features, namely symmetry features and single-channel features, with nonlinear ones derived by a multiscale entropy approach. Nevertheless, the best performance, reflected in the highest F1-score achieved in a binary classification task for valence was 0.71 and for arousal 0.62. The performance was 10–20% better compared to using ratings provided by 13 independent raters. We argue that affective self-assessment might be underrated and it is crucial to account for personal differences in both perception and physiological response to affective cues.

Bučar, Klemen;Malet, Jeanne;Stabile, Luca;Pražnikar, Jure;Seeger, Stefan;Žitnik, Matjaž

doi: 10.3390/s20236707pmid: 33255163

In this work, we characterise the performance of a Sharp optical aerosol sensor model GP2Y1010AU0F. The sensor was exposed to different environments: to a clean room, to a controlled atmosphere with known aerosol size distribution and to the ambient atmosphere on a busy city street. During the exposure, the output waveforms of the sensor pulses were digitised, saved and a following offline analysis enabled us to study the behaviour of the sensor pulse-by-pulse. A linear response of the sensor on number concentration of the monosized dispersed PSL particles was shown together with an almost linear dependence on particle diameters in the 0.4 to 4 micrometer range. The gathered data about the sensor were used to predict its response to an ambient atmosphere, which was observed simultaneously with a calibrated optical particle counter.

Kim, Hanna;Diaz, Melvin B.;Kim, Joo Yeon;Jung, Yong-Bok;Kim, Kwang Yeom

doi: 10.3390/s20236802pmid: 33260772

In-situ stress estimation plays an important role on the success of an underground project. However, no method is error-free, and therefore a combination of methods is desirable. In this study, the in-situ stresses for a geothermal project have been assessed through the analysis of a deep rock core taken at 4.2 km, using the diametrical core deformation analysis (DCDA) method that relates the diametrical core expansion after stress relief with the stresses assuming elastic deformation. The extracted granodiorite core sample of 100 mm of diameter was intersected with a closed joint at a dip angle of 80.8° with respect to the vertical coring direction. The core sample was scanned using an industrial X-ray computed tomography (CT), and the diametrical deformation measurements were computed with CT slices. Results from using the DCDA method indicated an average horizontal stress difference of 13.3 MPa, similar to that reported for a nearby exploration well. Furthermore, the stress orientations were compared with the orientation of maximum roughness values. The results indicated a correlation between the orientation of the maximum horizontal stress and the orientation of the minimum joint roughness coefficient, implying a possible tracking of stress orientation using joint roughness anisotropy.

Tai, Yongpeng;Zhou, Kai;Chen, Ning

doi: 10.3390/s20236958pmid: 33291441

The structure of a microresonator will affect the vibration characteristics and the performance of the system. Inspired by the structural characteristics of the human tympanic membrane, this paper proposed a microresonator with the bionic structure of a tympanic membrane. The structure of a tympanic membrane was simplified to a regular shape with three structural parameters: diameter, height, and thickness. To imitate the tympanic membrane, the contour surface of the bionic structure was modeled based on the formula of transverse vibration mode of a circular thin plate. The geometric model of the bionic structure was established by using the three structural parameters and the contour surface equation. The dynamic properties of the bionic model were studied by the finite element method (FEM). We discuss the modal characteristics of the bionic structure and study the effect of structural parameters and scale on the dynamic properties. The advantages of the bionic structure were investigated by a comparison with circular plate microresonators. The results illustrate that the bionic structure can significantly improve the resonant frequency and have a much larger effective area of vibration displacement.

López Escobar, Juan José ;Gil-Castiñeira, Felipe;Díaz Redondo, Rebeca P.

doi: 10.3390/s20236893pmid: 33276558

The emergence of Low-Power Wide-Area Network (LPWAN) technologies allowed the development of revolutionary Internet Of Things (IoT) applications covering large areas with thousands of devices. However, connectivity may be a challenge for non-line-of-sight indoor operation or for areas without good coverage. Technologies such as LoRa and Sigfox allow connectivity for up to 50,000 devices per cell, several devices that may be exceeded in many scenarios. To deal with these problems, this paper introduces a new multi-hop protocol, called JMAC, designed for improving long range wireless communication networks that may support monitoring in scenarios such smart cities or Industry 4.0. JMAC uses the LoRa radio technology to keep low consumption and extend coverage area, and exploits the potential mesh behaviour of wireless networks to improve coverage and increase the number of supported devices per cell. JMAC is based on predictive wake-up to reach long lifetime on sensor devices. Our proposal was validated using the OMNeT++ simulator to analyze how it performs under different conditions with promising results.

Stevens, Nicola-Ann;Lydon, Myra;Marshall, Adele H.;Taylor, Su

doi: 10.3390/s20236894pmid: 33276606

Machine learning and statistical approaches have transformed the management of infrastructure systems such as water, energy and modern transport networks. Artificial Intelligence-based solutions allow asset owners to predict future performance and optimize maintenance routines through the use of historic performance and real-time sensor data. The industrial adoption of such methods has been limited in the management of bridges within aging transport networks. Predictive maintenance at bridge network level is particularly complex due to the considerable level of heterogeneity encompassed across various bridge types and functions. This paper reviews some of the main approaches in bridge predictive maintenance modeling and outlines the challenges in their adaptation to the future network-wide management of bridges. Survival analysis techniques have been successfully applied to predict outcomes from a homogenous data set, such as bridge deck condition. This paper considers the complexities of European road networks in terms of bridge type, function and age to present a novel application of survival analysis based on sparse data obtained from visual inspections. This research is focused on analyzing existing inspection information to establish data foundations, which will pave the way for big data utilization, and inform on key performance indicators for future network-wide structural health monitoring.

Wu, Xi;Wang, Yafeng

doi: 10.3390/s20236740pmid: 33255711

In this paper, the uplink information-coupled polar-coded sparse code multiple access (PC-SCMA) system is proposed. For this system, we first design the encoding method of systematic joint parity check and CRC-aided (PCCA) polar code. Using the systematic PCCA-polar code as base code, the partially information-coupled (PIC) polar code is constructed. Then, a joint iterative detection and successive cancellation list (SCL)-decoding receiver is proposed for the PC-SCMA system. For the receiver, the coupled polar decoder’s extrinsic messages are calculated by the Bayes rule and soft cancellation (SCAN) algorithm. Based on the extrinsic information transfer (EXIT) idea, the PIC PCCA-polar code is optimized. Simulation results demonstrate that the PIC PCCA-PC-SCMA system outperforms the other polar (or LDPC) coded SCMA systems at various code rates and channel configurations. Additionally, compared with an uncoupled PC-SCMA system with SCL decoder, the complexity of PIC PCCA-PC-SCMA is reduced at a high Eb/N0