bluuebunny/crossref_metadata_2025 huggingface dataset:
Feasibility of Using MODIS Products to Simulate Sun-Induced Chlorophyll Fluorescence (SIF) in Boreal Forests
Authors: Guo Meng , Li Jing , Huang Shubo , Wen Lixiang
Published: February 2020

Solar-induced chlorophyll fluorescence (SIF) is a novel approach to gain information about plant activity from remote sensing observations. However, there are currently no continuous SIF data produced at high spatial resolutions. Many previous studies have discussed the relationship between SIF and gross primary production (GPP) and showed a significant correlation between them, but few researchers have focused on forests, which are one the most important terrestrial ecosystems. This study takes Greater Khingan Mountains, a typical boreal forest in China, as an example to explore the feasibility of using MODerate resolution Imaging Spectroradiometer (MODIS) products and Orbiting Carbon Observatory-2 (OCO-2) SIF data to simulate continuous SIF at higher spatial resolutions. The results show that there is no significant correlation between SIF and MODIS GPP at a spatial resolution of 1 km; however, significant correlations between SIF and the enhanced vegetation index (EVI) were found during growing seasons. Furthermore, the broadleaf forest has a higher SIF than coniferous forest because of the difference in leaf and canopy bio-chemical and structural characteristic. When using MODIS EVI to model SIF, linear regression models show average performance (R2 = 0.58, Root Mean Squared Error (RMSE) = 0.14 from Julian day 145 to 257) at a 16-day time scale. However, when using MODIS EVI and temperature, multiple regressions perform better (R2 = 0.71, RMSE = 0.13 from Julian day 145 to 241). An important contribution of this paper is the analysis of the relationships between SIF and vegetation indices at different spatial resolutions and the finding that the relationships became closer with a decrease in spatial resolution. From this research, we conclude that the SIF of the boreal forest investigated can mainly be explained by EVI and air temperature.
Non-locally Enhanced Feature Fusion Network for Aircraft Recognition in Remote Sensing Images
Authors: Xiong Yunsheng , Niu Xin , Dou Yong , Qie Hang , Wang Kang
Published: February 2020

Aircraft recognition has great application value, but aircraft in remote sensing images have some problems such as low resolution, poor contrasts, poor sharpness, and lack of details caused by the vertical view, which make the aircraft recognition very difficult. Especially when there are many kinds of aircraft and the differences between aircraft are subtle, the fine-grained recognition of aircraft is more challenging. In this paper, we propose a non-locally enhanced feature fusion network(NLFFNet) and attempt to make full use of the features from discriminative parts of aircraft. First, according to the long-distance self-correlation in aircraft images, we adopt non-locally enhanced operation and guide the network to pay more attention to the discriminating areas and enhance the features beneficial to classification. Second, we propose a part-level feature fusion mechanism(PFF), which crops 5 parts of the aircraft on the shared feature maps, then extracts the subtle features inside the parts through the part full connection layer(PFC) and fuses the features of these parts together through the combined full connection layer(CFC). In addition, by adopting the improved loss function, we can enhance the weight of hard examples in the loss function meanwhile reducing the weight of excessively hard examples, which improves the overall recognition ability of the network. The dataset includes 47 categories of aircraft, including many aircraft of the same family with slight differences in appearance, and our method can achieve 89.12% accuracy on the test dataset, which proves the effectiveness of our method.
Observation-Based Attitude Realization for Accurate Jason Satellite Orbits and Its Impact on Geodetic and Altimetry Results
Authors: Bloßfeld Mathis , Zeitlhöfler Julian , Rudenko Sergei , Dettmering Denise
Published: February 2020

For low Earth orbiting satellites, non-gravitational forces cause one of the largest perturbing accelerations. During a precise orbit determination (POD), the accurate modeling of the satellite-body attitude and solar panel orientation is important since the satellite’s effective cross-sectional area is directly related to the perturbing acceleration. Moreover, the position of tracking instruments that are mounted on the satellite body are affected by the satellite attitude. For satellites like Jason-1/-2/-3, attitude information is available in two forms—as a so-called nominal yaw steering model and as observation-based (measured by star tracking cameras) quaternions of the spacecraft body orientation and rotation angles of the solar arrays. In this study, we have developed a preprocessing procedure for publicly available satellite attitude information. We computed orbits based on Satellite Laser Ranging (SLR) observations to the Jason satellites at an overall time interval of approximately 25 years, using each of the two satellite attitude representations. Based on the analysis of the orbits, we investigate the influence of using preprocessed observation-based attitude in contrast to using a nominal yaw steering model for the POD. About 75% of all orbital arcs calculated with the observation-based satellite attitude data result in a smaller root mean square (RMS) of residuals. More precisely, the resulting orbits show an improvement in the overall mission RMS of SLR observation residuals of 5.93% (Jason-1), 8.27% (Jason-2) and 4.51% (Jason-3) compared to the nominal attitude realization. Besides the satellite orbits, also the estimated station coordinates benefit from the refined attitude handling, that is, the station repeatability is clearly improved at the draconitic period. Moreover, altimetry analysis indicates a clear improvement of the single-satellite crossover differences (6%, 15%, and 16% reduction of the mean of absolute differences and 1.2%, 2.7%, and 1.3% of their standard deviations for Jason-1/-2/-3, respectively). On request, the preprocessed attitude data are available.
Which Precipitation Product Works Best in the Qinghai-Tibet Plateau, Multi-Source Blended Data, Global/Regional Reanalysis Data, or Satellite Retrieved Precipitation Data?
Authors: Bai Lei , Wen Yuanqiao , Shi Chunxiang , Yang Yanfen , Zhang Fan , Wu Jing , Gu Junxia , Pan Yang , Sun Shuai , Meng Junyao
Published: February 2020

Precipitation serves as a crucial factor in the study of hydrometeorology, ecology, and the atmosphere. Gridded precipitation data are available from a multitude of sources including precipitation retrieved by satellites, radar, the output of numerical weather prediction models, and extrapolation by ground rain gauge data. Evaluating different types of products in ungauged regions with complex terrain will not only help researchers in applying scientific data, but also provide useful information that can be used to improve gridded precipitation products. The present study aims to evaluate comprehensively 12 precipitation datasets made by raw retrieved products, blended with rain gauge data, and blended multiple source datasets in multi-temporal scales in order to develop a suitable method for creating gridded precipitation data in regions with snow-dominated regions with complex terrain. The results show that the Multi-Source Weighted-Ensemble Precipitation (MSWEP), Global Satellite Mapping of Precipitation with Gauge Adjusted (GSMaP_GAUGE), Tropical Rainfall Measuring Mission (TRMM_3B42), Climate Prediction Center Morphing Technique blended with Chinese observations (CMORPH_SUN), and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) can represent the spatial pattern of precipitation in arid/semi-arid and humid/semi-humid areas of the Qinghai-Tibet Plateau on a climatological spatial pattern. On interannual, seasonal, and monthly scales, the TRMM_3B42, GSMaP_GAUGE, CMORPH_SUN, and MSWEP outperformed the other products. In general, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN_CCS) has poor performance in basins of the Qinghai-Tibet Plateau. Most products overestimated the extreme indices of the 99th percentile of precipitation (R99), the maximal of daily precipitation in a year (Rmax), and the maximal of pentad accumulation of precipitation in a year (R5dmax). They were underestimated by the extreme index of the total number of days with daily precipitation less than 1 mm (dry day, DD). Compared to products blended with rain gauge data only, MSWEP blended with more data sources, and outperformed the other products. Therefore, multi-sources of blended precipitation should be the hotspot of regional and global precipitation research in the future.
Simulation of Ku-Band Profile Radar Waveform by Extending Radiosity Applicable to Porous Individual Objects (RAPID2) Model
Authors: Du Kai , Huang Huaguo , Zhu Yuyi , Feng Ziyi , Hakala Teemu , Chen Yuwei , Hyyppä Juha
Published: February 2020

Similar to light detection and ranging (lidar), profile radar can detect forest vertical structure directly. Recently, the first Ku-band profile radar system designed for forest applications, called Tomoradar, has been developed and evaluated in boreal forest. However, the physical relationships between the waveform and forest structure parameters such as height, leaf area index (LAI), and aboveground biomass are still unclear, which limits later forestry applications. Therefore, it is necessary to develop a theoretical model to simulate the relationship and interpret the mechanism behind. In this study, we extend the Radiosity Applicable to Porous IndiviDual objects (RAPID2) model to simulate the profile radar waveform of forest stands. The basic assumption is that the scattering functions of major components within forest canopy are similar between profile radar and the side-looking radar implemented in RAPID2, except several modifications. These modifications of RAPID2 mainly include: (a) changing the observation angle from side-looking to nadir-looking; (b) enhancing the ground specular scattering in normal direction using Fresnel coefficient; (c) increasing the timing resolution and recording waveform. The simulated waveforms were evaluated using two plots of Tomoradar waveforms at co- and cross- polarizations, which are collected in thin and dense forest stands respectively. There is a good agreement (R2 ≥ 0.80) between the model results and experimental waveforms in HH and HV polarization modes and two forest scenes. After validation, the extended RAPID2 model was used to explore the sensitivity of the stem density, single tree LAI, crown shape, and twig density on the penetration depth in the Ku-band. Results indicate that the backscattering of the profile radar penetrates deeper than previous studies of synthetic aperture radar (SAR), and the penetration depth tends to be several meters in Ku-band. With the increasing of the needle and twig density in the microwave propagation path, the penetration depth decreases gradually. It is worth noting that variation of stem density seems to have the least effect on the penetration depth, when there is no overlapping between the single tree crowns.
Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference
Authors: Ma Chaoqun , Hu Xiaoguang , Xiao Jin , Du Huanchao , Zhang Guofeng
Published: February 2020

This paper presents an improved Oriented Features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) algorithm named ORB using three-patch and local gray difference (ORB-TPLGD). ORB takes a breakthrough in real-time aspect. However, subtle changes of the image may greatly affect its final binary description. In this paper, the feature description generation is focused. On one hand, instead of pixel patch pairs comparison method used in present ORB algorithm, a three-pixel patch group comparison method is adopted to generate the binary string. In each group, the gray value of the main patch is compared with that of the other two companion patches to determine the corresponding bit of the binary description. On the other hand, the present ORB algorithm simply uses the gray size comparison between pixel patch pairs, while ignoring the information of the gray difference value. In this paper, another binary string based on the gray difference information mentioned above is generated. Finally, the feature fusion method is adopted to combine the binary strings generated in the above two steps to generate a new feature description. Experiment results indicate that our improved ORB algorithm can achieve greater performance than ORB and some other related algorithms.
Highly Selective Adsorption on SiSe Monolayer and Effect of Strain Engineering: A DFT Study
Authors: Zhou Quan , Liu Lian , Liu Qipeng , Wang Zeping , Gao Chenshan , Liu Yufei , Ye Huaiyu
Published: February 2020

The adsorption types of ten kinds of gas molecules (O2, NH3, SO2, CH4, NO, H2S, H2, CO, CO2, and NO2) on the surface of SiSe monolayer are analyzed by the density-functional theory (DFT) calculation based on adsorption energy, charge density difference (CDD), electron localization function (ELF), and band structure. It shows high selective adsorption on SiSe monolayer that some gas molecules like SO2, NO, and NO2 are chemically adsorbed, while the NH3 molecule is physically adsorbed, the rest of the molecules are weakly adsorbed. Moreover, stress is applied to the SiSe monolayer to improve the adsorption strength of NH3. It has a tendency of increment with the increase of compressive stress. The strongest physical adsorption energy (−0.426 eV) is obtained when 2% compressive stress is added to the substrate in zigzag direction. The simple desorption is realized by decreasing the stress. Furthermore, based on the similar adsorption energy between SO2 and NH3 molecules, the co-adsorption of these two gases are studied. The results show that SO2 will promote the detection of NH3 in the case of SO2-NH3/SiSe configuration. Therefore, SiSe monolayer is a good candidate for NH3 sensing with strain engineering.
Joint Adaptive Sampling Interval and Power Allocation for Maneuvering Target Tracking in a Multiple Opportunistic Array Radar System
Authors: Han Qinghua , Pan Minghai , Long Weijun , Liang Zhiheng , Shan Chenggang
Published: February 2020

In this paper, a joint adaptive sampling interval and power allocation (JASIPA) scheme based on chance-constraint programming (CCP) is proposed for maneuvering target tracking (MTT) in a multiple opportunistic array radar (OAR) system. In order to conveniently predict the maneuvering target state of the next sampling instant, the best-fitting Gaussian (BFG) approximation is introduced and used to replace the multimodal prior target probability density function (PDF) at each time step. Since the mean and covariance of the BFG approximation can be computed by a recursive formula, we can utilize an existing Riccati-like recursion to accomplish effective resource allocation. The prior Cramér-Rao lower boundary (prior CRLB-like) is compared with the upper boundary of the desired tracking error range to determine the adaptive sampling interval, and the Bayesian CRLB-like (BCRLB-like) gives a criterion used for measuring power allocation. In addition, considering the randomness of target radar cross section (RCS), we adopt the CCP to package the deterministic resource management model, which minimizes the total transmitted power by effective resource allocation. Lastly, the stochastic simulation is embedded into a genetic algorithm (GA) to produce a hybrid intelligent optimization algorithm (HIOA) to solve the CCP optimization problem. Simulation results show that the global performance of the radar system can be improved effectively by the resource allocation scheme.
An Opto-Electronic Sensor-Ring to Detect Arthropods of Significantly Different Body Sizes
Authors: Balla Esztella , Flórián Norbert , Gergócs Veronika , Gránicz Laura , Tóth Franciska , Németh Tímea , Dombos Miklós
Published: February 2020

Arthropods, including pollinators and pests, have high positive and negative impacts on human well-being and the economy, and there is an increasing need to monitor their activity and population growth. The monitoring of arthropod species is a time-consuming and financially demanding process. Automatic detection can be a solution to this problem. Here, we describe the setup and operation mechanism of an infrared opto-electronic sensor-ring, which can be used for both small and large arthropods. The sensor-ring consists of 16 infrared (IR) photodiodes along a semicircle in front of an infrared LED. Using 3D printing, we constructed two types of sensor-ring: one with a wider sensing field for detection of large arthropods (flying, crawling, surface-living) in the size range of 2–35 mm; and another one with a narrower sensing field for soil microarthropods in the size range of 0.1–2 mm. We examined the detection accuracy and reliability of the two types of sensor-ring in the laboratory by using particles, and dead and living arthropods at two different sensitivity levels. For the wider sensor-ring, the 95% detectability level was reached with grain particles of 0.9 mm size. This result allowed us to detect all of the macroarthropods that were applied in the tests and that might be encountered in pest management. In the case of living microarthropods with different colors and shapes, when we used the narrower sensor-ring, we achieved the 95% detectability level at 1.1 mm, 0.9 mm, and 0.5 mm in the cases of F. candida, H. nitidus, and H. aculeifer, respectively. The unique potential of arthropod-detecting sensors lies in their real-time measurement system; the data are automatically forwarded to the server, and the end-user receives pest abundance data daily or even immediately. This technological innovation will allow us to make pest management more effective.
A Subspace Approach to Sparse Sampling Based Data Gathering in Wireless Sensor Networks
Authors: He Jingfei , Zhang Xiaoyue , Zhou Yatong , Maibvisira Miriam
Published: February 2020

Data gathering is an essential concern in Wireless Sensor Networks (WSNs). This paper proposes an efficient data gathering method in clustered WSNs based on sparse sampling to reduce energy consumption and prolong the network lifetime. For data gathering scheme, we propose a method that can collect sparse sampled data in each time slot with a fixed percent of nodes remaining in sleep mode. For data reconstruction, a subspace approach is proposed to enforce an explicit low-rank constraint for data reconstruction from sparse sampled data. Subspace representing spatial distributions of the WSNs data can be estimated from previous reconstructed data. Incorporating total variation constraint, the proposed reconstruction method reconstructs current time slot data efficiently. The results of experiments indicate that the proposed method can reduce the energy consumption and prolong the network lifetime with satisfying recovery accuracy.
Augmented RFID Technologies for the Internet of Things and Beyond
Authors: Tarricone Luciano , Grosinger Jasmin
Published: February 2020

Radio frequency identification (RFID) is one of the crucial enabling technologies for the Internet of Things (IoT). This is leading to a continuous augmentation of RFID technologies, in terms of sensing capabilities, energetic autonomy, usability, and cost affordability, and this special issue proposes an overview on such a challenging scenario. The proposed results, in terms of cost reduction, miniaturization, and compatibility with complex systems and technologies, as well as the identification of the relevant criticalities, also pave the way to future steps being taken that go beyond the current IoT.
Ethanol Gas Sensitivity Sensor Based on Roughened POF Taper of Modified Polypyrrole Films
Authors: Liu Wenyi , Hu Yanjun , Hou Yulong
Published: February 2020

The three polypyrrole (PPy) films with different mixture ratios, namely PPy1, PPy2, and PPy3, were synthesized by chemical oxidation with pyrrole and ferric chloride (FeCl3). The roughened plastic optical fiber (POF) taper assembled PPy films (POF-PPy1, POF-PPy2, and POF-PPy3) were facilely prepared and bent U shape structure for testing ethanol gas at room temperature. The morphologies of the PPy films and the roughened POF taper were studied using electron microscopy. The effect of the three PPy films on the gas response was investigated and the results showed that the POF-PPy2 exhibited a high sensitivity of 5.08 × 10−5 dB/ppm. The detection limit of the sensor was 140 ppm and its response and recovery times were 5 s and 8 s, respectively. The results also showed that as the bending radius decreased, the response and recovery times gradually shortened, while the output power increased. In addition, the proposed sensor has advantages of a low cost and simple structure.
Design of a Carrier Wave for Capacitive Transducer with Large Dynamic Range
Authors: Li Zhu , Zhang Xian , Zou Shu , Huang Xiangqing , Xue Chao , Liu Jianping , Liu Qi , Yang Shanqing , Tu Liangcheng
Published: February 2020

Capacitive transducers are widely used in fundamental physics experiments, seismology, Earth or planetary observations, and space scientific and technical applications because of their high precision, simple structure, and compatibility with various measurements. However, in real applications, there is a trade-off between their resolution and dynamic range. Therefore, this paper is aimed at enlarging the dynamic range while ensuring high resolution. In this paper, a noise analysis of a capacitive transducer is presented, which shows that the amplitude noise of the carrier wave is the main limiting factor. Hence, a new method of generating a carrier wave with lower-amplitude noise is proposed in the paper. Based on the experimental verification, it is found that the carrier wave produced through the new method performed significantly better than the typical digital carrier wave when they were compared in the same sensing circuit. With the carrier wave produced through the new method, the dynamic range of the capacitive transducer can reach 120.7 dB, which is 18.3 dB greater than for the typical direct digital synthesis (DDS) method. In addition, the resolution of the carrier wave is mainly limited by the voltage reference components.
Performance Improvement of Dual-Pulse Heterodyne Distributed Acoustic Sensor for Sound Detection
Authors: He Xiangge , Zhang Min , Gu Lijuan , Xie Shangran , Liu Fei , Lu Hailong
Published: February 2020

Phase fading is fatal to the performance of distributed acoustic sensors (DASs) influencing its capability of distributed measurement as well as its noise level. Here, we report the experimental observation of a strong negative correlation between the relative power spectrum density (PSD) at the heterodyne frequency and the noise floor of the detected phase for the heterodyne demodulated distributed acoustic sensor (HD-DAS) system. We further propose a weighted-channel stack algorithm (WCSA) to alleviate the phase fading noise via an enhancement of the relative PSD at the heterodyne frequency. Experimental results show that the phase noise of the demodulated signal can be suppressed by 13.7 dB under optimal condition. As a potential application, we exploited the improved HD-DAS system to retrieve a piece of music lasted for 205 s, demonstrating the reliability of detecting wideband sound signal without distortion.
Automated Parameter Extraction Of ScAlN MEMS Devices Using An Extended Euler–Bernoulli Beam Theory
Authors: Krey Maximilian , Hähnlein Bernd , Tonisch Katja , Krischok Stefan , Töpfer Hannes
Published: February 2020

Magnetoelectric sensors provide the ability to measure magnetic fields down to the pico tesla range and are currently the subject of intense research. Such sensors usually combine a piezoelectric and a magnetostrictive material, so that magnetically induced stresses can be measured electrically. Scandium aluminium nitride gained a lot of attraction in the last few years due to its enhanced piezoelectric properties. Its usage as resonantly driven microelectromechanical system (MEMS) in such sensors is accompanied by a manifold of influences from crystal growth leading to impacts on the electrical and mechanical parameters. Usual investigations via nanoindentation allow a fast determination of mechanical properties with the disadvantage of lacking the access to the anisotropy of specific properties. Such anisotropy effects are investigated in this work in terms of the Young’s modulus and the strain on basis of a MEMS structures through a newly developed fully automated procedure of eigenfrequency fitting based on a new non-Lorentzian fit function and subsequent analysis using an extended Euler–Bernoulli theory. The introduced procedure is able to increase the resolution of the derived parameters compared to the common nanoindentation technique and hence allows detailed investigations of the behavior of magnetoelectric sensors, especially of the magnetic field dependent Young‘s modulus of the magnetostrictive layer.
Textile Electrocardiogram (ECG) Electrodes for Wearable Health Monitoring
Authors: Arquilla Katya , Webb Andrea , Anderson Allison
Published: February 2020

Wearable health-monitoring systems should be comfortable, non-stigmatizing, and able to achieve high data quality. Smart textiles with electronic elements integrated directly into fabrics offer a way to embed sensors into clothing seamlessly to serve these purposes. In this work, we demonstrate the feasibility of electrocardiogram (ECG) monitoring with sewn textile electrodes instead of traditional gel electrodes in a 3-lead, chest-mounted configuration. The textile electrodes are sewn with silver-coated thread in an overlapping zig zag pattern into an inextensible fabric. Sensor validation included ECG monitoring and comfort surveys with human subjects, stretch testing, and wash cycling. The electrodes were tested with the BIOPAC MP160 ECG data acquisition module. Sensors were placed on 8 subjects (5 males and 3 females) with double-sided tape. To detect differences in R peak detectability between traditional and sewn sensors, effect size was set at 10% of a sample mean for heart rate (HR) and R-R interval. Paired student’s t-tests were run between adhesive and sewn electrode data for R-R interval and average HR, and a Wilcoxon signed-rank test was run for comfort. No statistically significant difference was found between the traditional and textile electrodes (R-R interval: t = 1.43, p > 0.1; HR: t = −0.70, p > 0.5; comfort: V = 15, p > 0.5).
Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring
Authors: Yahya Noorhana , Mui Nyuk Chai , Ismail Ahmad Fauzi , Hussain Nazabat , Rostami Amir , Ismail Atef , Ganeson Menaka , Ali Abdullah Musa
Published: February 2020

In the current study, we developed an adaptive algorithm that can predict oil mobilization in a porous medium on the basis of optical data. Associated mechanisms based on tuning the electromagnetic response of magnetic and dielectric nanoparticles are also discussed. This technique is a promising method in rational magnetophoresis toward fluid mobility via fiber Bragg grating (FBG). The obtained wavelength shift due to Fe3O4 injection was 75% higher than that of dielectric materials. This use of FBG magneto-optic sensors could be a remarkable breakthrough for fluid-flow tracking in oil reservoirs. Our computational algorithm, based on piecewise linear polynomials, was evaluated with an analytical technique for homogeneous cases and achieved 99.45% accuracy. Theoretical values obtained via coupled-mode theory agreed with our FBG experiment data of at a level of 95.23% accuracy.
Spatial and Temporal Variability of Plant Leaf Responses Cascade after PSII Inhibition: Raman, Chlorophyll Fluorescence and Infrared Thermal Imaging
Authors: Vítek Petr , Veselá Barbora , Klem Karel
Published: February 2020

The use of photosystem II (PSII) inhibitors allows simulating cascade of defense and damage responses, including the oxidative stress. In our study, PSII inhibiting herbicide metribuzin was applied to the leaf of the model plant species Chenopodium album. The temporally and spatially resolved cascade of defense responses was studied noninvasively at the leaf level by combining three imaging approaches: Raman spectroscopy as a principal method, corroborated by chlorophyll a fluorescence (ChlF) and infrared thermal imaging. ChlF imaging show time-dependent transport in acropetal direction through veins and increase of area affected by metribuzin and demonstrated the ability to distinguish between fast processes at the level of electron transport (1 − Vj) from slow processes at the level of non-photochemical energy dissipation (NPQ) or maximum efficiency of PSII photochemistry (Fv/Fm). The high-resolution resonance Raman images show zones of local increase of carotenoid signal 72 h after the herbicide application, surrounding the damaged tissue, which points to the activation of defense mechanisms. The shift in the carotenoid band indicates structural changes in carotenoids. Finally, the increase of leaf temperature in the region surrounding the spot of herbicide application and expanding in the direction to the leaf tip proves the metribuzin effect on slow stomata closure.
Seismic Exploration Wireless Sensor System Based on Wi-Fi and LTE
Authors: Yin Zhiyuan , Zhou Yan , Li Yongxin
Published: February 2020

In present seismic exploration wireless sensor systems with large acquisition channels, it is difficult to achieve a high data rate, high reliability and long distance in wireless data transmission simultaneously. In this paper, a wireless seismic exploration system using a dual-layer network is proposed. The dual-layer network is designed based on Wi-Fi and LTE, so that long-distance high-rate seismic data transmission with a high reliability can be achieved. In the proposed system, the sensor array is composed of two kinds of nodes, the gateway node and the collecting node. Based on the proposed nodes, collecting node positioning, seismic data acquisition, seismic local data storage and quasi real-time remote seismic data transmission can be realized. Reliability mechanisms have been put forward to deal with the exceptions. An experiment was carried out to test the data transmission efficiency of the proposed system. The results show that the seismic exploration wireless sensor system with a dual-layer network structure can achieve quasi real-time remote seismic data transmission with no packet loss.
Hybrid Network with Attention Mechanism for Detection and Location of Myocardial Infarction Based on 12-Lead Electrocardiogram Signals
Authors: Fu Lidan , Lu Binchun , Nie Bo , Peng Zhiyun , Liu Hongying , Pi Xitian
Published: February 2020

The electrocardiogram (ECG) is a non-invasive, inexpensive, and effective tool for myocardial infarction (MI) diagnosis. Conventional detection algorithms require solid domain expertise and rely heavily on handcrafted features. Although previous works have studied deep learning methods for extracting features, these methods still neglect the relationships between different leads and the temporal characteristics of ECG signals. To handle the issues, a novel multi-lead attention (MLA) mechanism integrated with convolutional neural network (CNN) and bidirectional gated recurrent unit (BiGRU) framework (MLA-CNN-BiGRU) is therefore proposed to detect and locate MI via 12-lead ECG records. Specifically, the MLA mechanism automatically measures and assigns the weights to different leads according to their contribution. The two-dimensional CNN module exploits the interrelated characteristics between leads and extracts discriminative spatial features. Moreover, the BiGRU module extracts essential temporal features inside each lead. The spatial and temporal features from these two modules are fused together as global features for classification. In experiments, MI location and detection were performed under both intra-patient scheme and inter-patient scheme to test the robustness of the proposed framework. Experimental results indicate that our intelligent framework achieved satisfactory performance and demonstrated vital clinical significance.
Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications
Authors: Hübner Patrick , Clintworth Kate , Liu Qingyi , Weinmann Martin , Wursthorn Sven
Published: February 2020

The Microsoft HoloLens is a head-worn mobile augmented reality device that is capable of mapping its direct environment in real-time as triangle meshes and localize itself within these three-dimensional meshes simultaneously. The device is equipped with a variety of sensors including four tracking cameras and a time-of-flight (ToF) range camera. Sensor images and their poses estimated by the built-in tracking system can be accessed by the user. This makes the HoloLens potentially interesting as an indoor mapping device. In this paper, we introduce the different sensors of the device and evaluate the complete system in respect of the task of mapping indoor environments. The overall quality of such a system depends mainly on the quality of the depth sensor together with its associated pose derived from the tracking system. For this purpose, we first evaluate the performance of the HoloLens depth sensor and its tracking system separately. Finally, we evaluate the overall system regarding its capability for mapping multi-room environments.
The Development of ASIC Type GSR Sensor Driven by GHz Pulse Current
Authors: Honkura Yoshinobu , Honkura Shinpei
Published: February 2020

The GigaHertz spin rotation (GSR) effect was observed through the excitement of Giga Hertz (GHz) pulse current flowing through amorphous wire. The GSR sensor that was developed provides excellent features that enhanced magnetic sensitivity and sine functional relationship, as well as good linearity, absence of hysteresis, and low noise. Considering the GHz frequency range used for the GSR sensor, we assume that the physical phenomena associated with the operation of the sensor are based on spin reduction and rotation of the magnetization. The proper production technology needed was developed and a micro-sized GSR sensor was produced by directly forming micro coils on the surface of the application-specific integrated circuit (ASIC). Some prototypes of the ASIC type GSR sensor have been produced in consideration of applications such as automotive use, mobile device use, and medical use. Therefore, we can conclude that GSR sensors have great potential to become promising magnetic sensors for many applications.
3D Hydrogen Titanate Nanotubes on Ti Foil: A Carrier for Enzymatic Glucose Biosensor
Authors: Ma Lulu , Yue Zhao , Huo Guona , Zhang Shasha , Zhu Baolin , Zhang Shoumin , Huang Weiping
Published: February 2020

Glucose oxidase (GOx) based biosensors are commercialized and marketed for the high selectivity of GOx. Incorporation nanomaterials with GOx can increase the sensitivity performance. In this work, an enzyme glucose biosensor based on nanotubes was fabricated. By using Ti foil as a carrier, hydrogen titanate nanotubes (HTNTs), which present fine 3D structure with vast pores, were fabricated in-situ by the hydrothermal treatment. The multilayer nanotubes are open-ended with a diameter of 10 nm. Then glucose oxidase (GOx) was loaded on the nanotubes by cross-linking to form an electrode of the amperometric glucose biosensor (GOx/HTNTs/Ti electrode). The fabricated GOx/HTNTs/Ti electrode had a linear response to 1–10 mM glucose, and the response time was 1.5 s. The sensitivity of the biosensor was 1.541 μA·mM-1·cm-2, and the detection limit (S/N = 3) was 59 μM. Obtained results indicate that the in-situ fabrication and unique 3D structure of GOx/HTNTs/Ti electrode are beneficial for its sensitivity.
Energy-Efficient Depth-Based Opportunistic Routing with Q-Learning for Underwater Wireless Sensor Networks
Authors: Lu Yongjie , He Rongxi , Chen Xiaojing , Lin Bin , Yu Cunqian
Published: February 2020

Underwater Wireless Sensor Networks (UWSNs) have aroused increasing interest of many researchers in industry, military, commerce and academe recently. Due to the harsh underwater environment, energy efficiency is a significant theme should be considered for routing in UWSNs. Underwater positioning is also a particularly tricky task since the high attenuation of radio-frequency signals in UWSNs. In this paper, we propose an energy-efficient depth-based opportunistic routing algorithm with Q-learning (EDORQ) for UWSNs to guarantee the energy-saving and reliable data transmission. It combines the respective advantages of Q-learning technique and opportunistic routing (OR) algorithm without the full-dimensional location information to improve the network performance in terms of energy consumption, average network overhead and packet delivery ratio. In EDORQ, the void detection factor, residual energy and depth information of candidate nodes are jointly considered when defining the Q-value function, which contributes to proactively detecting void nodes in advance, meanwhile, reducing energy consumption. In addition, a simple and scalable void node recovery mode is proposed for the selection of candidate set so as to rescue packets that are stuck in void nodes unfortunately. Furthermore, we design a novel method to set the holding time for the schedule of packet forwarding base on Q-value so as to alleviate the packet collision and redundant transmission. We conduct extensive simulations to evaluate the performance of our proposed algorithm and compare it with other three routing algorithms on Aqua-sim platform (NS2). The results show that the proposed algorithm significantly improve the performance in terms of energy efficiency, packet delivery ratio and average network overhead without sacrificing too much average packet delay.
Development of a Shock and Detonation Velocity Measurement System Using Chirped Fiber Bragg Gratings
Authors: Barbarin Yohan , Lefrançois Alexandre , Chuzeville Vincent , Magne Sylvain , Jacquet Laurent , Elia Thomas , Woirin Karol , Collet Christelle , Osmont Antoine , Luc Jérôme
Published: February 2020

Dynamic measurements of shock and detonation velocities are performed using long chirped fiber Bragg gratings (CFBGs). Such thin probes, with a diameter of typically 125 µm or even 80 µm can be directly inserted into high-explosive (HE) samples or simply glued laterally. During the detonation, the width of the optical spectrum is continuously reduced by the propagation of the wave-front, which physically shortens the CFBG. The light power reflected back shows a ramp-down type signal, from which the wave-front position is obtained as a function of time, thus yielding a detonation velocity profile. A calibration procedure was developed, with the support of optical simulations, to cancel out the optical spectrum distortions from the different optical components and to determine the wavelength-position transfer function of the CFBG. The fitted slopes of the X–T diagram give steady detonation velocity values which are in very good agreement with the classical measurements obtained from discrete electrical shorting pins (ESP). The main parameters influencing the uncertainties on the steady detonation velocity value measured by CFBG are discussed. To conclude, different HE experimental configurations tested at CEA (Commissariat à l’Energie Atomique et aux Energies Alternatives) are presented: bare cylindrical sticks, wedges for shock-to-detonation transitions (SDT), spheres, a cast-cured stick around a CFBG, and a detonation wave-front profile configuration.
The Effect of the Orientation Towards Analyte Flow on Electrochemical Sensor Performance and Current Fluctuations
Authors: Sedlák Petr , Kuberský Petr
Published: February 2020

Analyte flow influences the performance of every gas sensor; thus, most of these sensors usually contain a diffusion barrier (layer, cover, inlet) that can prevent the negative impact of a sudden change of direction and/or the rate of analyte flow, as well as various unwanted impacts from the surrounding environment. However, several measurement techniques use the modulation of the flow rate to enhance sensor properties or to extract more information about the chemical processes that occur on a sensitive layer or a working electrode. The paper deals with the experimental study on how the analyte flow rate and the orientation of the electrochemical sensor towards the analyte flow direction influence sensor performance and current fluctuations. Experiments were carried out on a semi-planar, three-electrode topology that enabled a direct exposure of the working (sensing) electrode to the analyte without any artificial diffusion barrier. The sensor was tested within the flow rate range of 0.1–1 L/min and the orientation of the sensor towards the analyte flow direction was gradually set to the four angles 0°, 45°, 90° and 270° in the middle of the test chamber, while the sensor was also investigated in the standard position at the bottom of the chamber.
An 8-Tap CMOS Lock-In Pixel Image Sensor for Short-Pulse Time-of-Flight Measurements
Authors: Shirakawa Yuya , Yasutomi Keita , Kagawa Keiichiro , Aoyama Satoshi , Kawahito Shoji
Published: February 2020

An 8-tap CMOS lock-in pixel image sensor that has seven carrier-capturing and a draining time window was developed for short-pulse time-of-flight (TOF) measurements. The proposed pixel for the short-pulse TOF measurements has seven consecutive time-gating windows, each of which has the width of 6 ns, which is advantageous for high-resolution range imaging, particularly for relatively longer distances (>5 m) and under high ambient light operations. In order to enhance the depth resolution, a technique for the depth-adaptive time-gating-number assignment (DATA) for the short-pulse TOF measurement is proposed. A prototype of the 8-tap CMOS lock-in pixel image sensor is implemented with a 1POLY 4METAL 0.11-μm CIS process. The maximum non-linearity error of 1.56%FS for the range of 1–6.4 m and the depth resolution of 6.4 mm was obtained at 6.2 m using the DATA technique.
Harmonic Distortion Optimization for Sigma-Delta Modulators Interface Circuit of TMR Sensors
Authors: Li Xiangyu , Hu Jianping , Liu Xiaowei
Published: February 2020

The tunneling magnetoresistance micro-sensors (TMR) developed by magnetic multilayer material has many advantages, such as high sensitivity, high frequency response, and good reliability. It is widely used in military and civil fields. This work presents a high-performance interface circuit for TMR sensors. Because of the nonlinearity of signal conversion between sensitive structure and interface circuit in feedback loop and forward path, large harmonic distortion occurs in output signal spectrum, which greatly leads to the reduction of SNDR (signal noise distortion rate). In this paper, we analyzed the main source of harmonic distortion in closed-loop detection circuit and establish an accurate harmonic distortion model in TMR micro-sensors system. Some factors are considered, including non-linear gain of operational amplifier unit, effective gain bandwidth, conversion speed, nonlinearity of analog transmission gate, and nonlinearity of polycrystalline capacitance in high-order sigma-delta system. We optimized the CMOS switch and first-stage integrator in the switched-capacitor circuit. The harmonic distortion parameter is optimally designed in the TMR sensors system, aiming at the mismatch of misalignment of front-end system, non-linearity of quantizer, non-linearity of capacitor, and non-linearity of analog switch. The digital output is attained by the interface circuit based on a low-noise front-end interface circuit and a third-order sigma-delta modulator. The digital interface circuit is implemented by 0.35μm CMOS (complementary metal oxide semiconductor) technology. The high-performance digital TMR sensors system is implemented by double chip integration and the active interface circuit area is about 3.2 × 2 mm. The TMR sensors system consumes 20 mW at a single 5 V supply voltage. The TMR sensors system can achieve a linearity of 0.3% at full scale range (±105 nT) and a resolution of 0.25 nT/Hz1/2(@1Hz).
IoT-Based Smart Irrigation Systems: An Overview on the Recent Trends on Sensors and IoT Systems for Irrigation in Precision Agriculture
Authors: García Laura , Parra Lorena , Jimenez Jose M. , Lloret Jaime , Lorenz Pascal
Published: February 2020

Water management is paramount in countries with water scarcity. This also affects agriculture, as a large amount of water is dedicated to that use. The possible consequences of global warming lead to the consideration of creating water adaptation measures to ensure the availability of water for food production and consumption. Thus, studies aimed at saving water usage in the irrigation process have increased over the years. Typical commercial sensors for agriculture irrigation systems are very expensive, making it impossible for smaller farmers to implement this type of system. However, manufacturers are currently offering low-cost sensors that can be connected to nodes to implement affordable systems for irrigation management and agriculture monitoring. Due to the recent advances in IoT and WSN technologies that can be applied in the development of these systems, we present a survey aimed at summarizing the current state of the art regarding smart irrigation systems. We determine the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions. We provide an overview of the most utilized nodes and wireless technologies. Lastly, we will discuss the challenges and the best practices for the implementation of sensor-based irrigation systems.
Friction and Wear Mechanism Analysis of Polymer Flexible Cable Using a High Natural Frequency Piezoelectric Sensor
Authors: Ni Jing , Ren Xu , Zheng Junqiang
Published: February 2020

The friction and wear of flexible cables are the main factors that cause electrical breakdown and insulation aging, and they greatly reduce the reliability and safety of robots. In order to enhance the reliability and safety of the robot, it is of great necessity to investigate the friction and wear mechanisms of the flexible cable. In this research, the friction and wear mechanisms have been discussed. The effects of relative speed, ambient temperature, and positive pressure on the flexible cables are considered by an orthogonal frictional movement. The cable friction force has been measured by a piezoelectric sensor with high natural frequency characteristics. The relations among friction and different factors affecting friction have also been discussed. The results show that the relative speed and the ambient temperature are the main factors affecting the friction and wear of the cable; the main form of flexible cable wear is mechanical-force chemical friction and wear. Those discoveries will greatly deepen the understanding of the friction and wear mechanisms of flexible cables, and will be beneficial to robot cable-reliability design.