bluuebunny/crossref_metadata_2025 huggingface dataset:
Small Object Detection in Remote Sensing Images Based on Super-Resolution with Auxiliary Generative Adversarial Networks
Authors: Courtrai Luc , Pham Minh-Tan , Lefèvre Sébastien
Published: September 2020

This article tackles the problem of detecting small objects in satellite or aerial remote sensing images by relying on super-resolution to increase image spatial resolution, thus the size and details of objects to be detected. We show how to improve the super-resolution framework starting from the learning of a generative adversarial network (GAN) based on residual blocks and then its integration into a cycle model. Furthermore, by adding to the framework an auxiliary network tailored for object detection, we considerably improve the learning and the quality of our final super-resolution architecture, and more importantly increase the object detection performance. Besides the improvement dedicated to the network architecture, we also focus on the training of super-resolution on target objects, leading to an object-focused approach. Furthermore, the proposed strategies do not depend on the choice of a baseline super-resolution framework, hence could be adopted for current and future state-of-the-art models. Our experimental study on small vehicle detection in remote sensing data conducted on both aerial and satellite images (i.e., ISPRS Potsdam and xView datasets) confirms the effectiveness of the improved super-resolution methods to assist with the small object detection tasks.
A Bistatic Analytical Approximation Model for Doppler Rate Estimation Error from Real-Time Spaceborne SAR Onboard Orbit Determination Data
Authors: Yan Xiaoyu , Chen Jie , Nies Holger , Loffeld Otmar
Published: September 2020

Real-time spaceborne bistatic SAR imaging could significantly reduce the whole processing time and can enhance the spaceborne SAR mission availability. Onboard real-time SAR imaging relies on the Doppler parameters estimated from the real-time onboard orbit determination system (OODS) measurement, whose accuracy level is not comparable to the orbit ephemeris data in ground-based SAR processing. The investigation of the impact of error in real-time OODS measurements on bistatic SAR image quality is necessary, and it can help to clarify the key parameter limits of the real-time OODS. The monostatic analytical approximation model (MonoAAM) for spaceborne SAR reduces simulation complexity and processing time compared to the widely used numerical simulation method. However, due to the different configurations between spaceborne bistatic and monostatic SAR, simply applying the MonoAAM on spaceborne bistatic SAR cannot guarantee the desired result. A bistatic analytical approximation model (BiAAM) for Doppler rate estimation error from real-time OODS measurement in real-time spaceborne bistatic SAR imaging is proposed for characterizing the estimation error. Selecting quadratic phase error (QPE) as an evaluation variable, the proposed BiAAM model can provide QPE estimation results for each position of the satellite in its orbit and the maximum QPE estimation for the whole orbit, while revealing the different process of OODS measurement error transferring to QPE in spaceborne bistatic SAR. The correctness and reliability of BiAAM are evaluated by comparing the result with a Monte Carlo numerical simulation method. With the supporting result from BiAAM, the concept and early-stage development of a real-time onboard bistatic SAR imaging mission could be possibly benefited.
GPM-Based Multitemporal Weighted Precipitation Analysis Using GPM_IMERGDF Product and ASTER DEM in EDBF Algorithm
Authors: Ullah Sana , Zuo Zhengkang , Zhang Feizhou , Zheng Jianghua , Huang Shifeng , Lin Yi , Iqbal Imran , Sun Yiyuan , Yang Ming , Yan Lei
Published: September 2020

To obtain the high-resolution multitemporal precipitation using spatial downscaling technique on a precipitation dataset may provide a better representation of the spatial variability of precipitation to be used for different purposes. In this research, a new downscaling methodology such as the global precipitation mission (GPM)-based multitemporal weighted precipitation analysis (GMWPA) at 0.05° resolution is developed and applied in the humid region of Mainland China by employing the GPM dataset at 0.1° and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m DEM-based geospatial predictors, i.e., elevation, longitude, and latitude in empirical distribution-based framework (EDBF) algorithm. The proposed methodology is a two-stepped process in which a scale-dependent regression analysis between each individual precipitation variable and the EDBF-based weighted precipitation with geospatial predictor(s), and to downscale the predicted multitemporal weighted precipitation at a refined scale is developed for the downscaling of GMWPA. While comparing results, it shows that the weighted precipitation outperformed all precipitation variables in terms of the coefficient of determination (R2) value, whereas they outperformed the annual precipitation variables and underperformed as compared to the seasonal and the monthly variables in terms of the calculated root mean square error (RMSE) value. Based on the achieved results, the weighted precipitation at the low-resolution (e.g., at 0.75° resolution) along-with the original resolution (e.g., at 0.1° resolution) is employed in the downscaling process to predict the average multitemporal precipitation, the annual total precipitation for the year 2001 and 2004, and the average annual precipitation (2001–2015) at 0.05° resolution, respectively. The downscaling approach resulting through proposed methodology captured the spatial patterns with greater accuracy at higher spatial resolution. This work showed that it is feasible to increase the spatial resolution of a precipitation variable(s) with greater accuracy on an annual basis or as an average from the multitemporal precipitation dataset using a geospatial predictor as the proxy of precipitation through the weighted precipitation in EDBF environment.
Toronto Water Vapor Lidar Inter-Comparison Campaign
Authors: Mariani Zen , Stanton Noah , Whiteway James , Lehtinen Raisa
Published: September 2020

This study presents comparisons between vertical water vapor profile measurements from a Raman lidar and a new pre-production broadband differential absorption lidar (DIAL). Vaisala’s novel DIAL system operates autonomously outdoors and measures the vertical profile of water vapor within the boundary layer 24 h a day during all weather conditions. Eight nights of measurements in June and July 2018 were used for the Toronto water vapor lidar inter-comparison field campaign. Both lidars provided reliable atmospheric backscatter and water vapor profile measurements. Comparisons were performed during night-time observations only, when the York Raman lidar could measure the water vapor profile. The purpose was to validate the water vapor profile measurements retrieved by the new DIAL system. The results indicate good agreement between the two lidars, with a mean difference (DIAL–Raman) of 0.17 ± 0.14 g/kg. There were two main causes for differences in their measurements: horizontal displacement between the two lidar sites (3.2 km) and vertical gradients in the water vapor profile. A case study analyzed during the campaign demonstrates the ability for both lidars to measure sudden changes and large gradients in the water vapor’s vertical structure due to a passing frontal system. These results provide an initial validation of the DIAL’s measurements and its ability to be implemented as part of an operational program.
Soil Moisture Retrievals by Combining Passive Microwave and Optical Data
Authors: Tong Cheng , Wang Hongquan , Magagi Ramata , Goïta Kalifa , Zhu Luyao , Yang Mengying , Deng Jinsong
Published: September 2020

This paper aims to retrieve the temporal dynamics of soil moisture from 2015 to 2019 over an agricultural site in Southeast Australia using the Soil Moisture Active Passive (SMAP) brightness temperature. To meet this objective, two machine learning approaches, Random Forest (RF), Support Vector Machine (SVM), as well as a statistical Ordinary Least Squares (OLS) model were established, with the auxiliary data including the 16-day composite MODIS NDVI (MOD13Q1) and Surface Temperature (ST). The entire data were divided into two parts corresponding to ascending (6:00 p.m. local time) and descending (6:00 a.m. local time) orbits of SMAP overpasses. Thus, the three models were trained using the descending data acquired during the five years (2015 to 2019), and validated using the ascending product of the same period. Consequently, three different temporal variations of the soil moisture were obtained based on the three models. To evaluate their accuracies, the retrieved soil moisture was compared against the SMAP level-2 soil moisture product, as well as to in-situ ground station data. The comparative results show that the soil moisture obtained using the OLS, RF and SVM algorithms are highly correlated to the SMAP level-2 product, with high coefficients of determination (R2OLS = 0.981, R2SVM = 0.943, R2RF = 0.983) and low RMSE (RMSEOLS = 0.016 cm3/cm3, RMSESVM = 0.047 cm3/cm3, RMSERF = 0.016 cm3/cm3). Meanwhile, the estimated soil moistures agree with in-situ station data across different years (R2OLS = 0.376~0.85, R2SVM = 0.376~0.814, R2RF = 0.39~0.854; RMSEOLS = 0.049~0.105 cm3/cm3, RMSESVM = 0.073~0.1 cm3/cm3, RMSERF = 0.047~0.102 cm3/cm3), but an overestimation issue is observed for high vegetation conditions. The RF algorithm outperformed the SVM and OLS, in terms of the agreement with the ground measurements. This study suggests an alternative soil moisture retrieval scheme, in complementary to the SMAP baseline algorithm, for a fast soil moisture retrieval.
Eye and Voice-Controlled Human Machine Interface System for Wheelchairs Using Image Gradient Approach
Authors: Anwer Saba , Waris Asim , Sultan Hajrah , Butt Shahid Ikramullah , Zafar Muhammad Hamza , Sarwar Moaz , Niazi Imran Khan , Shafique Muhammad , Pujari Amit N.
Published: September 2020

Rehabilitative mobility aids are being used extensively for physically impaired people. Efforts are being made to develop human machine interfaces (HMIs), manipulating the biosignals to better control the electromechanical mobility aids, especially the wheelchairs. Creating precise control commands such as move forward, left, right, backward and stop, via biosignals, in an appropriate HMI is the actual challenge, as the people with a high level of disability (quadriplegia and paralysis, etc.) are unable to drive conventional wheelchairs. Therefore, a novel system driven by optical signals addressing the needs of such a physically impaired population is introduced in this paper. The present system is divided into two parts: the first part comprises of detection of eyeball movements together with the processing of the optical signal, and the second part encompasses the mechanical assembly module, i.e., control of the wheelchair through motor driving circuitry. A web camera is used to capture real-time images. The processor used is Raspberry-Pi with Linux operating system. In order to make the system more congenial and reliable, the voice-controlled mode is incorporated in the wheelchair. To appraise the system’s performance, a basic wheelchair skill test (WST) is carried out. Basic skills like movement on plain and rough surfaces in forward, reverse direction and turning capability were analyzed for easier comparison with other existing wheelchair setups on the bases of controlling mechanisms, compatibility, design models, and usability in diverse conditions. System successfully operates with average response time of 3 s for eye and 3.4 s for voice control mode.
Vital-Signs Detector Based on Frequency-Shift Keying Radar
Authors: Sim Jae Young , Park Jae-Hyun , Yang Jong-Ryul
Published: September 2020

A frequency-shift keying (FSK) radar in the 2.45-GHz band is proposed for highly accurate vital-signs detection. The measurement accuracy of the proposed detector for the heartbeat is increased by using the cross-correlation between the phase differences of signals at two frequencies used by the FSK radar, which alternately transmits and receives the signals with different frequencies. Two frequencies—2.45 and 2.5 GHz—are effectively discriminated by using the envelope detection with the frequency control signal of the signal generator in the output waveform of the FSK radar. The phase difference between transmitted and received signals at each frequency is determined after calibrating the I / Q imbalance and direct-current offset using a data-based imbalance compensation algorithm, the Gram–Schmidt procedure, and the Pratt method. The absolute-distance measurement results for a human being show that the vital signs obtained at each frequency using the proposed FSK radar have a cross-correlation. The heartbeat detection results for the proposed FSK radar at a distance of < 2.4 m indicate a reduction in the error rate and an increase in the signal-to-noise ratio compared with those obtained using a single operating frequency.
Application of Composite Spectrum in Agricultural Machines
Authors: Feijoo Fernando , Gomez-Gil Francisco Javier , Gomez-Gil Jaime
Published: September 2020

Composite spectrum (CS) is a data-fusion technique that reduces the number of spectra to be analyzed, simplifying the analysis process for machine monitoring and fault detection. In this work, vibration signals from five components of a combine harvester (thresher, chopper, straw walkers, sieve box, and engine) are obtained by placing four accelerometers along the combine-harvester chassis in non-optimal locations. Four individual spectra (one from each accelerometer) and three CS (non-coherent, coherent and poly-coherent spectra) from 18 cases are analyzed. The different cases result from the combination of three working conditions of the components—deactivated (off), balanced (healthy), and unbalanced (faulty)—and two speeds—idle and maximum revolutions per minute (RPM). The results showed that (i) the peaks can be identified in the four individual spectra that correspond to the rotational speeds of the five components in the analysis; (ii) the three formulations of the CS retain the relevant information from the individual spectra, thereby reducing the number of spectra required for monitoring and detecting rotating unbalances within a combine harvester; and, (iii) data noise reduction is observed in coherent and poly-coherent CS with respect to the non-coherent CS and the individual spectra. This study demonstrates that the rotating unbalances of various components within agricultural machines, can be detected with a reduced number of accelerometers located in non-optimal positions, and that it is feasible to simplify the monitoring with CS. Overall, the coherent CS may be the best composite spectra formulation in order to monitor and detect rotating unbalances in agricultural machines.
Improved Dynamic Obstacle Mapping (iDOMap)
Authors: Llamazares Ángel , Molinos Eduardo , Ocaña Manuel , Ivan Vladimir
Published: September 2020

The goal of this paper is to improve our previous Dynamic Obstacle Mapping (DOMap) system by means of improving the perception stage. The new system must deal with robots and people as dynamic obstacles using LIght Detection And Range (LIDAR) sensor in order to collect the surrounding information. Although robot movement can be easily tracked by an Extended Kalman Filter (EKF), people’s movement is more unpredictable and it might not be correctly linearized by an EKF. Therefore, to deal with a better estimation of both types of dynamic objects in the local map it is recommended to improve our previous work. The DOMap has been extended in three key points: first the LIDAR reflectivity remission is used to make more robust the matching in the optical flow of the detection stage, secondly static and a dynamic occlusion detectors have been proposed, and finally a tracking stage based on Particle Filter (PF) has been used to deal with robots and people as dynamic obstacles. Therefore, our new improved-DOMap (iDOMap) provides maps with information about occupancy and velocities of the surrounding dynamic obstacles (robots, people, etc.) in a more robust way and they are available to improve the following planning stage.
Numerical and Experimental Analysis of Matched Filter Interrogation of FBG Sensors with Large Side Lobes
Authors: Skorupski Krzysztof , Cięszczyk Sławomir , Panas Patryk , Kisała Piotr
Published: September 2020

This article presents the effect of fiber Bragg gratings side lobes on interrogation systems consisting of sensor and matched filters. The conducted research shows that high-value side lobe structures applied as sensors and/or filters are characterized by some interesting properties. The paper presents both numerical analysis and experimental verification of the fiber Bragg gratings (FBG) interrogation systems with matched filters for gratings containing high side lobes. Numerical modeling of Bragg structures was performed for two different cases: uniform and inverse apodization. Modification of apodization can change the side lobe reflectance level even above levels found in uniform structures. This is a case not described in the literature, especially in terms of possible applications. Transfer characteristics, i.e., the relationship between power intensity as a function of wavelength shift, were determined. A collection of gratings with spectra corresponding to those analyzed in numerical experiments were fabricated. Next, the transfer characteristics of the interrogation systems containing real FBG were determined. The properties of the proposed systems are described. It has been shown that a significant level of sidebands, which is often the subject of many drawbacks in filtering or telecommunications systems, can be an advantage. It has been demonstrated that a high level of side lobes can be used to increase the measurement range of the FBG sensor interrogation systems. It has been determined numerically and confirmed experimentally that from the point of view of the design of sensor interrogation systems, it is beneficial to combine specific pairs of gratings: one with a spectrum characterized by a low side lobe level and a second one in which the spectrum has very high side lobes.
Unmanned Aerial System Integrated Sensor for Remote Gamma and Neutron Monitoring
Authors: Barzilov Alexander , Kazemeini Monia
Published: September 2020

Tools for remote radiation sensing are essential for environmental safety and nuclear power applications. The use of unmanned aerial systems (UASs) equipped with sensors allows for substantially reducing the radiation exposure of personnel. An ambient temperature Cs2LiYCl6:Ce3+ (CLYC) elpasolite scintillation sensor for simultaneous gamma and neutron measurements was designed as a user-friendly “plug and fly” module integrated into an octocopter robotic platform. Robot Operating System (ROS) was used to analyze the sensor’s data. The measured CLYC’s energy resolution was <5% at 662 keV gamma rays; neutron flux was measured using 6Li(n,α)t reaction. Time and GPS data were combined with radiation data in the ROS, supporting real time monitoring and assessment tasks, as well as radiation source search missions. Because UASs can be irradiated, radiation damage of the sensor and robot’s electronics was estimated using FLUKA code.
Radar Data Integrity Verification Using 2D QIM-Based Data Hiding
Authors: Changalvala Raghu , Fedoruk Brandon , Malik Hafiz
Published: September 2020

The modern-day vehicle is evolved in a cyber-physical system with internal networks (controller area network (CAN), Ethernet, etc.) connecting hundreds of micro-controllers. From the traditional core vehicle functions, such as vehicle controls, infotainment, and power-train management, to the latest developments, such as advanced driver assistance systems (ADAS) and automated driving features, each one of them uses CAN as their communication network backbone. Automated driving and ADAS features rely on data transferred over the CAN network from multiple sensors mounted on the vehicle. Verifying the integrity of the sensor data is essential for the safety and security of occupants and the proper functionality of these applications. Though the CAN interface ensures reliable data transfer, it lacks basic security features, including message authentication, which makes it vulnerable to a wide array of attacks, including spoofing, replay, DoS, etc. Using traditional cryptography-based methods to verify the integrity of data transmitted over CAN interfaces is expected to increase the computational complexity, latency, and overall cost of the system. In this paper, we propose a light-weight alternative to verify the sensor data’s integrity for vehicle applications that use CAN networks for data transfers. To this end, a framework for 2-dimensional quantization index modulation (2D QIM)-based data hiding is proposed to achieve this goal. Using a typical radar sensor data transmission scenario in an autonomous vehicle application, we analyzed the performance of the proposed framework regarding detecting and localizing the sensor data tampering. The effects of embedding-induced distortion on the applications using the radar data were studied through a sensor fusion algorithm. It was observed that the proposed framework offers the much-needed data integrity verification without compromising on the quality of sensor fusion data and is implemented with low overall design complexity. This proposed framework can also be used on any physical network interface other than CAN, and it offers traceability to in-vehicle data beyond the scope of the in-vehicle applications.
Monitoring the BTEX Volatiles during 3D Printing with Acrylonitrile Butadiene Styrene (ABS) Using Electronic Nose and Proton Transfer Reaction Mass Spectrometry
Authors: Wojnowski Wojciech , Kalinowska Kaja , Gębicki Jacek , Zabiegała Bożena
Published: September 2020

We describe a concept study in which the changes of concentration of benzene, toluene, ethylbenzene, and xylene (BTEX) compounds and styrene within a 3D printer enclosure during printing with different acrylonitrile butadiene styrene (ABS) filaments were monitored in real-time using a proton transfer reaction mass spectrometer and an electronic nose. The quantitative data on the concentration of the BTEX compounds, in particular the concentration of carcinogenic benzene, were then used as reference values for assessing the applicability of an array of low-cost electrochemical sensors in monitoring the exposure of the users of consumer-grade fused deposition modelling 3D printers to potentially harmful volatiles. Using multivariate statistical analysis and machine learning, it was possible to determine whether a set threshold limit value for the concentration of BTEX was exceeded with a 0.96 classification accuracy and within a timeframe of 5 min based on the responses of the chemical sensors.
Space-Borne GNSS-R Ionospheric Delay Error Elimination by Optimal Spatial Filtering
Authors: Zhang Qiuyang , Liu Yang , Xia Junming
Published: September 2020

Global Navigation Satellite System Reflectometry (GNSS-R) technology is a new and promising remote sensing technology, especially satellite-based GNSS-R remote sensing, which has broad application prospects. In this work, the ionospheric impacts on space-borne GNSS-R sea surface altimetry were investigated. An analysis of optimal values for spatial filtering to remove ionospheric delays in space-borne GNSS-R altimetry was conducted. Considering that there are few satellite-borne GNSS-R orbit observations to date, simulated high-resolution space-borne GNSS-R orbital data were used for a comprehensive global and applicable study. The curves of absolute bias in relation to the bilateral filtering points were verified to achieve the minimum absolute bias. The optimal filtering points were evaluated in both statistical probability density and quantile analysis to show the reliability of the selected values. The proposed studies are helpful and valuable for the future implementation of high-accuracy space-borne GNSS-R sea surface altimetry.
Impact of Using GPS L2 Receiver Antenna Corrections for the Galileo E5a Frequency on Position Estimates
Authors: Araszkiewicz Andrzej , Kiliszek Damian
Published: September 2020

Knowledge of Global Navigation Satellite System (GNSS) antenna phase center variations plays a key role in precise positioning. Proper modeling is achieved by accessing antenna phase center corrections, which are determined in the calibration process. For most receiver antenna types, the International GNSS Service provides such corrections for two GPS and GLONASS carrier signals. In the case of Galileo, access to phase center corrections is difficult; only antennas calibrated in the anechoic chambers have available corrections for Galileo frequencies. Hence, in many of the studies, GPS-dedicated corrections are used for these Galileo frequencies. Differential analysis was conducted in this study to evaluate the impact of such change. In total, 25 stations belonging to the EUREF Permanent Network and equipped with individual calibrated antennas were the subject of this research. The results for both the absolute and relative positioning methods are clear: using GPS L2 corrections for Galileo E5a frequency causes a bias in the estimated height of almost 8 mm. For the horizontal component, a significant difference can be noticed for only one type of antenna.
Angle-Sensitive Detector Based on Silicon-On-Insulator Photodiode Stacked with Surface Plasmon Antenna
Authors: Nagarajan Anitharaj , Hara Shusuke , Satoh Hiroaki , Panchanathan Aruna Priya , Inokawa Hiroshi
Published: September 2020

We present a pixel-level angle sensitive detector composed of silicon-on-insulator (SOI) photodiode (PD) stacked with a gold surface plasmon (SP) antenna to affect the direction of the incoming light. The surface plasmons are excited in the grating-type SP antenna and enhance the diffraction efficiency of the grating. The diffracted light is coupled strongly with the propagation light in the SOI waveguide when the phase matching condition is satisfied. The phase matching takes place at a specific angle of light incidence, and the discrimination of the light based on the incident angle is achieved. As spatial patterns in the polar coordinate of the elevation-azimuth angles (θ, ϕ) of the incident light, we present the phase matching condition theoretically, the absorption efficiency in the SOI by simulation, and also the quantum efficiency of the SOI PD experimentally for different SP antennas of one-dimensional (1D) line-and-space (L/S) and two-dimensional (2D) hole array gratings under various polarization angles. 1D grating offers a polarization sensitive angle detection and 2D grating exhibits angle detection in two orthogonal directions, enabling a polarization independent angle sensitivity. A good agreement among the theory, simulation, and experiment are attained. The proposed device features relatively high quantum efficiency as an angle-sensitive pixel (ASP) and gives wider opportunities in applications such as three-dimensional (3D) imaging, depth-of-field extension, and lensless imaging.
Multi-Camera-Based Universal Measurement Method for 6-DOF of Rigid Bodies in World Coordinate System
Authors: Zhao Zuoxi , Zhu Yuchang , Li Yuanhong , Qiu Zhi , Luo Yangfan , Xie Chaoshi , Zhang Zhuangzhuang
Published: September 2020

The measurement of six-degrees-of-freedom (6-DOF) of rigid bodies plays an important role in many industries, but it often requires the use of professional instruments and software, or has limitations on the shape of measured objects. In this paper, a 6-DOF measurement method based on multi-camera is proposed, which is accomplished using at least two ordinary cameras and is made available for most morphological rigid bodies. First, multi-camera calibration based on Zhang Zhengyou’s calibration method is introduced. In addition to the intrinsic and extrinsic parameters of cameras, the pose relationship between the camera coordinate system and the world coordinate system can also be obtained. Secondly, the 6-DOF calculation model of proposed method is gradually analyzed by the matrix analysis method. With the help of control points arranged on the rigid body, the 6-DOF of the rigid body can be calculated by the least square method. Finally, the Phantom 3D high-speed photogrammetry system (P3HPS) with an accuracy of 0.1 mm/m was used to evaluate this method. The experiment results show that the average error of the rotational degrees of freedom (DOF) measurement is less than 1.1 deg, and the average error of the movement DOF measurement is less than 0.007 m. In conclusion, the accuracy of the proposed method meets the requirements.
Evaluation of Vegetation Index-Based Curve Fitting Models for Accurate Classification of Salt Marsh Vegetation Using Sentinel-2 Time-Series
Authors: Sun Chao , Li Jialin , Cao Luodan , Liu Yongchao , Jin Song , Zhao Bingxue
Published: September 2020

The successful launch of the Sentinel-2 constellation satellite, along with advanced cloud detection algorithms, has enabled the generation of continuous time series at high spatial and temporal resolutions, which is in turn expected to enable the classification of salt marsh vegetation over larger spatiotemporal scales. This study presents a critical comparison of vegetation index (VI) and curve fitting methods—two key factors for time series construction that potentially influence vegetation classification performance. To accomplish this objective, the stability of five different VI time series, namely Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), Green Normalized Difference Vegetation Index (GNDVI), and Water-Adjusted Vegetation Index (WAVI), was compared empirically; the suitability between three curve fitting methods, namely Asymmetric Gaussian (AG), Double Logistic (DL), and Two-term Fourier (TF), and VI time series was measured using the coefficient of determination, and the salt marsh vegetation separability among different combinations of VI time series and curve fitting methods (i.e., VI time series-based curve fitting model) was quantified using overall the Jeffries–Matusita distance. Six common types of salt marsh vegetation from three typical coastal sites in China were used to validate these findings, which demonstrate: (1) the SAVI performed best in terms of time series stability, while the EVI exhibited relatively poor time series stability with conspicuous outliers induced by the sensitivity to omitted clouds and shadows; (2) the DL method commonly resulted in the most accurate classification of different salt marsh vegetation types, especially when combined with the EVI time series, followed by the TF method; and (3) the SAVI/NDVI-based DL/TF model demonstrated comparable efficiency for classifying salt marsh vegetation. Notably, the SAVI/NDVI-based DL model performed most strongly for high latitude regions with a continental climate, whilst the SAVI/NDVI-based TF model appears to be better suited to mid- to low latitude regions dominated by a monsoonal climate.
Video-Based Stress Detection through Deep Learning
Authors: Zhang Huijun , Feng Ling , Li Ningyun , Jin Zhanyu , Cao Lei
Published: September 2020

Stress has become an increasingly serious problem in the current society, threatening mankind’s well-beings. With the ubiquitous deployment of video cameras in surroundings, detecting stress based on the contact-free camera sensors becomes a cost-effective and mass-reaching way without interference of artificial traits and factors. In this study, we leverage users’ facial expressions and action motions in the video and present a two-leveled stress detection network (TSDNet). TSDNet firstly learns face- and action-level representations separately, and then fuses the results through a stream weighted integrator with local and global attention for stress identification. To evaluate the performance of TSDNet, we constructed a video dataset containing 2092 labeled video clips, and the experimental results on the built dataset show that: (1) TSDNet outperformed the hand-crafted feature engineering approaches with detection accuracy 85.42% and F1-Score 85.28%, demonstrating the feasibility and effectiveness of using deep learning to analyze one’s face and action motions; and (2) considering both facial expressions and action motions could improve detection accuracy and F1-Score of that considering only face or action method by over 7%.
Fast Recursive Computation of Sliding DHT with Arbitrary Step
Authors: Kober Vitaly
Published: September 2020

Short-time (sliding) transform based on discrete Hartley transform (DHT) is often used to estimate the power spectrum of a quasi-stationary process such as speech, audio, radar, communication, and biomedical signals. Sliding transform calculates the transform coefficients of the signal in a fixed-size moving window. In order to speed up the spectral analysis of signals with slowly changing spectra, the window can slide along the signal with a step of more than one. A fast algorithm for computing the discrete Hartley transform in windows that are equidistant from each other is proposed. The algorithm is based on a second-order recursive relation between subsequent equidistant local transform spectra. The performance of the proposed algorithm with respect to computational complexity is compared with the performance of known fast Hartley transform and sliding algorithms.
Electrochemical Immuno- and Aptamer-Based Assays for Bacteria: Pros and Cons over Traditional Detection Schemes
Authors: Jamal Rimsha Binte , Shipovskov Stepan , Ferapontova Elena E.
Published: September 2020

Microbiological safety of the human environment and health needs advanced monitoring tools both for the specific detection of bacteria in complex biological matrices, often in the presence of excessive amounts of other bacterial species, and for bacteria quantification at a single cell level. Here, we discuss the existing electrochemical approaches for bacterial analysis that are based on the biospecific recognition of whole bacterial cells. Perspectives of such assays applications as emergency-use biosensors for quick analysis of trace levels of bacteria by minimally trained personnel are argued.
Determinism in Cyber-Physical Systems Specified by Interpreted Petri Nets
Authors: Wisniewski Remigiusz , Grobelna Iwona , Karatkevich Andrei
Published: September 2020

In this paper, we study selected aspects of determinism in the control part of a cyber-physical system (CPS) that is specified by a Petri net-based model. In particular, the control interpreted Petri nets (CIPNs) are applied, which are an extension of the ordinary Petri nets, supplemented by signals (related to sensors and actuators) that permit communication with the environment. The notions of weak and strong determinism in a system described by a CIPN are introduced in the paper. The proposed concepts are supported by formal definitions and theorems. Moreover, a novel modelling methodology for a deterministic system specified by a CIPN is proposed. The presented solutions are illustrated by a case study example of a real-life cyber-physical system. Finally, the results of experimental verification of the proposed determinism-based techniques are demonstrated and discussed.
The Change in Students’ Attitude towards Favourable and Unfavourable Factors of Online Learning Environments
Authors: Valantinaitė Ilona , Sederevičiūtė-Pačiauskienė Živilė
Published: September 2020

This article aims to present the results of a study on favourable and unfavourable factors of using online learning environments in the study process as a digital learning strategy to promote education for sustainable development. Technologies have changed traditional face-to-face classrooms through online environments to hybrid learning spaces. Personal experiences and expectations are part of these hybrid learning setups and learner-positive attitudes to such sessions could contribute to the effectiveness of hybrid learning and student satisfaction. The quasi-experiment was carried out to determine the attitude of students towards favourable and unfavourable factors of using an online learning environment (OLE) in the study process. Five groups of students studied for one semester using the flipped classroom method. The sample was made up of 106 secondary school students, selected by means of non-probability sampling. Students were given pre-test and post-test questionnaires in the beginning and at the end of the semester. Favourable factors of using an online learning environment identified by students in the beginning of the quasi-experiment were grouped in five categories: material resources/base; teacher personality; student personality, information presentation and increase of accessibility at the institutional level. As students gain more experience in using an OLE for learning, it is not technical issues and computer literacy that become important, but students’ and teachers’ attitudes and the motivation to improve and learn. At the end of the project, the participants emphasised other favourable factors: continuous uploading of materials, convenience of use and the promotion of online learning environments for studies in all subjects. The role of the teacher while using an online learning environment was highlighted. This research contributes to the improvement of teacher pedagogical competences, creating conditions for increasing student satisfaction.
Environmental Impacts of Photoluminescence and Light-Emitting Diode (LED) Lighting Technologies in Horticulture: Case Study on Compact Fluorescent Lamp (CFL) and LED Lights for “Night Break” of Chrysanthemum Cultivation
Authors: Hoang Thi Thu Linh , Do Thi Gam , Nguyen Van Thao , Nguyen Hoai Chau , Phan Hong Khoi
Published: September 2020

The environmental impacts of photoluminescence and light-emitting diode (LED) lighting technologies in horticulture are described in this paper. As a case study, the life cycle assessment (LCA) associated with the raw materials, air, water and natural resources of screw-based compact fluorescent lamps (CFLs) and screw-based horticultural LED lamps (abbreviated as H-LED) used for “night break” effect in chrysanthemum cultivation is considered. Instead of the unit of radiant power of lighting sources (lumens) used in human lighting, the photon flux (micromoles per second) of the plant light is used in this study. The results of the study show that the environmental impacts of the H-LED lighting technology are markedly less than the fluorescent lamps. Therefore, the shift to LED lighting technology in horticulture in general, and “night break” chrysanthemum cultivation in particular, brings about tremendous benefits not only for saving energy and improving crop quality, but also for protecting the air/climate, water, soil and natural resources.
Bibliometric and Visualized Analysis of Mobile Technology in Tourism
Authors: Chen Sirong , Law Rob , Xu Shaogui , Zhang Mu
Published: September 2020

With the advent of the fifth-generation mobile communication technology era, mobile technology will further change tourism. However, studies on mobile technology in tourism from the perspective of bibliometrics and visualization are limited. This research aimed to systematically, comprehensively, and objectively analyze the current research status and potential future research directions in this field through a visual bibliometric analysis of mobile technology research in tourism. This study used CiteSpace software to analyze 803 related journal papers from the Web of Science Core Collection and provided insights into the research of mobile technology in tourism from the aspects of research trends, research areas, top journals, author/institution/country or region collaboration networks, research keywords, and research foundations. The study can help related personnel in academia and industry to fully understand the research of mobile technology in tourism and provides valuable references for related research fields on bibliometric and visualized analysis.
Confinement Effect of Reinforced Concrete Columns with Rectangular and Octagon-Shaped Spirals
Authors: Kim Hyeong-Gook , Jeong Chan-Yu , Kim Dong-Hwan , Kim Kil-Hee
Published: September 2020

Conventional spiral-type transverse reinforcement is effective at increasing the ductility and the maximum strength of reinforced concrete (RC) columns because it confines the inner concrete and the longitudinal reinforcement. However, when arranging crossties in a RC column with spirals, problems such as mutual interference with longitudinal reinforcement, overcrowding of reinforcement, and deterioration of constructability occur. Furthermore, the loosening of 90 and 130-degree standard hooks due to the lateral expansion of concrete causes buckling of the longitudinal reinforcement. This paper describes the ability of a newly developed spiral-type transverse reinforcement with various yield strengths to confine RC columns subjected to cyclic lateral load and constant axial load. The ductility capacity, energy dissipation, and effective stiffness of RC columns confined by the developed spiral-type transverse reinforcement were compared with those of RC columns confined by typical rectangular reinforcement. The experimental results showed that RC column specimens with the developed spiral-type transverse reinforcement have better performances in terms of ductility capacity and energy dissipation, even though the amount of reinforcement used for the specimens decreased by about 27% compared with the specimen with typical rectangular reinforcement.
Sustainable Industry 4.0 in Production and Operations Management: A Systematic Literature Review
Authors: Felsberger Andreas , Reiner Gerald
Published: September 2020

This study draws attention to the upcoming changes within sustainable value chains and manufacturing environments caused by the digital transformation. With a special focus on Industry 4.0 (I4.0), the presented study explores the scientific progress within this research field. A systematic literature review approach using a set of predefined keywords and with several exclusion criteria was adopted in order to identify the literature that is related to sustainability in I4.0 and its impact in the area of production and operations management (P&OM). A total of 89 papers from the period 2010–2020 were identified, which were then examined along the lines of the most influential journals, key topics of the selected literature, geographical distribution, and sustainability dimensions. The analysis was executed via bibliometric and text mapping tools, namely NVivo and BibExcel. Furthermore, a focus group discussion with experts from European semiconductor manufacturing companies and researchers from several academic institutions was conducted to derive practical insights. The results of this study will contribute to the evaluation of sustainable I4.0 innovations from the past 10 years. The key issues and research gaps identified in this article will provide a reference point to encourage and guide interested researchers for future studies, thus supporting both theoretical and practical progress in this research area.
Knowledge and Practices of Indigenous Peoples in the Context of Resource Management in Relation to Climate Change in Southeast Asia
Authors: Persoon Gerard A. , Minter Tessa
Published: September 2020

In this article, we document how four indigenous peoples in insular Southeast Asia (Indonesia and the Philippines) have reacted to external interventions and discuss to what extent climate change has been a factor in the adjustment of their way of life. All groups share a similar environment, that is tropical low land rainforest. However, their traditional modes of exploitation of this environment vary, which can be ascribed to specific geographical and cultural characteristics. In recent years, these indigenous peoples have faced encroachment of their lands through logging and mining activities and the arrival of migrants looking for arable lands. They have developed various ways to cope with the changing conditions, ranging from efforts to retreat into the remaining rainforest to increased resource extraction and losing a long-term interest in the sustainability of their home territory. The younger generation seems to take a different stand towards their future in relation to their natural environment and the way of life of their ancestors. Though there can be no doubt about climate change in the context of insular Southeast Asia, this change is difficult to differentiate from the cumulative environmental impacts brought about by other forms of anthropogenic change, notably forest degradation. Examples that will be discussed in this article are the Agta of Northeastern Luzon in the Philippines, and the Orang Rimba, the Mentawaians, and the Ngaju Dayak in Indonesia.
Climate Change Risk Perceptions of Audiences in the Climate Change Blogosphere
Authors: van Eck Christel W. , Mulder Bob C. , van der Linden Sander
Published: September 2020

The Climate Change Risk Perception Model (CCRPM, Van der Linden, 2015) has been used to characterize public risk perceptions; however, little is known about the model’s explanatory power in other (online) contexts. In this study, we extend the model and investigate the risk perceptions of a unique audience: The polarized climate change blogosphere. In total, our model explained 84% of the variance in risk perceptions by integrating socio-demographic characteristics, cognitive factors, experiential processes, socio-cultural influences, and an additional dimension: Trust in scientists and blogs. Although trust and the scientific consensus are useful additions to the model, affect remains the most important predictor of climate change risk perceptions. Surprisingly, the relative importance of social norms and value orientations is minimal. Implications for risk and science communication are discussed.
Work–Family Conflict on Sustainable Creative Performance: Job Crafting as a Mediator
Authors: Zhang Man , Wang Fan , Das Anupam Kumar
Published: September 2020

The psychology of sustainability in terms of sustainable development for work–family conflict (WFC) in organizations has become increasingly relevant in sustainable human resource management research, and the pursuit of sustainable creative performance is an important aspect of corporate sustainable development. Taking a regulatory focus perspective, this study integrates a moderated-mediation model to examine the relationship between work–family conflict and sustainable creative performance. Data were collected from 203 supervisor–subordinate dyads from two branches of a high-end manufacturing enterprise in Shanghai, China. The results reveal that work–family conflict has a positive effect on sustainable creative performance through job crafting, and the effect is stronger when individuals show higher promotion regulatory focus. We discuss the theoretical and practical implications of the study, along with potential future research directions.