bluuebunny/crossref_metadata_2025 huggingface dataset:
UAV-Based Terrain Modeling under Vegetation in the Chinese Loess Plateau: A Deep Learning and Terrain Correction Ensemble Framework
Authors: Na Jiaming , Xue Kaikai , Xiong Liyang , Tang Guoan , Ding Hu , Strobl Josef , Pfeifer Norbert
Published: October 2020

Accurate topographic mapping is a critical task for various environmental applications because elevation affects hydrodynamics and vegetation distributions. UAV photogrammetry is popular in terrain modelling because of its lower cost compared to laser scanning. However, this method is restricted in vegetation area with a complex terrain, due to reduced ground visibility and lack of robust and automatic filtering algorithms. To solve this problem, this work proposed an ensemble method of deep learning and terrain correction. First, image matching point cloud was generated by UAV photogrammetry. Second, vegetation points were identified based on U-net deep learning network. After that, ground elevation was corrected by estimating vegetation height to generate the digital terrain model (DTM). Two scenarios, namely, discrete and continuous vegetation areas were considered. The vegetation points in the discrete area were directly removed and then interpolated, and terrain correction was applied for the points in the continuous areas. Case studies were conducted in three different landforms in the loess plateau of China, and accuracy assessment indicated that the overall accuracy of vegetation detection was 95.0%, and the MSE (Mean Square Error) of final DTM (Digital Terrain Model) was 0.024 m.
Satellite Observations of Typhoon-Induced Sea Surface Temperature Variability in the Upwelling Region off Northeastern Taiwan
Authors: Kuo Yi-Chun , Lee Ming-An , Chang Yi
Published: October 2020

Typhoon-induced cooling in the cold dome region off northeastern Taiwan has a major influence on ocean biogeochemistry. It has previously been studied using numerical models and hydrographic observations. Strong cooling is related to upwelling of the Kuroshio subsurface water accompanied by the westward intrusion of the continental shelf by Kuroshio water. By employing satellite observations, local measurements, and a reanalysis of model data, this study compared 18 typhoon-induced sea surface temperature (SST) responses in the cold dome region and determined that SST responses can differ dramatically depending on the relative location of a typhoon path, the Kuroshio Current, and the topography off northeastern Taiwan. The results indicated that local westward and northward wind stress is positively correlated with upwelling intensity. Decreased northward transport in the Taiwan Strait created a condition that favored the Kuroshio intrusion, thus, the typhoon-induced change in Taiwan Strait transport was also positively correlated with the intensity of cooling. However, the strength of Ekman pumping was weakly correlated with the intensity of SST cooling. Nevertheless, Ekman pumping helped reduce the cover of warm water, facilitating the intrusion of the Kuroshio Current.
Enhanced Intensity Analysis to Quantify Categorical Change and to Identify Suspicious Land Transitions: A Case Study of Nanchang, China
Authors: Xie Zheyu , Pontius Jr Robert Gilmore , Huang Jinliang , Nitivattananon Vilas
Published: October 2020

Conventional methods to analyze a transition matrix do not offer in-depth signals concerning land changes. The land change community needs an effective approach to visualize both the size and intensity of land transitions while considering possible map errors. We propose a framework that integrates error analysis, intensity analysis, and difference components, and then uses the framework to analyze land change in Nanchang, the capital city of Jiangxi province, China. We used remotely sensed data for six categories at four time points: 1989, 2000, 2008, and 2016. We had a confusion matrix for only 2016, which estimated that the map of 2016 had a 12% error, while the temporal difference during 2008–2016 was 22% of the spatial extent. Our tools revealed suspected errors at other years by analyzing the patterns of temporal difference. For example, the largest component of temporal difference was exchange, which could indicate map errors. Our framework identified categories that gained during one time interval then lost during the subsequent time interval, which raised the suspicion of map error. This proposed framework facilitated visualization of the size and intensity of land transitions while illustrating possible map errors that the profession routinely ignores.
High-Resolution Sea Surface Temperatures Derived from Landsat 8: A Study of Submesoscale Frontal Structures on the Pacific Shelf off the Hokkaido Coast, Japan
Authors: Kuroda Hiroshi , Toya Yuko
Published: October 2020

Coastal and offshore waters are generally separated by a barrier or “ocean front” on the continental shelf. A basic question arises as to what the representative spatial scale across the front may be. To answer this question, we simply corrected skin sea surface temperatures (SSTs) estimated from Landsat 8 imagery with a resolution of 100 m using skin SSTs estimated from geostationary meteorological satellite Himawari 8 with a resolution of 2 km. We analyzed snapshot images of skin SSTs on 13 October 2016, when we performed a simultaneous ship survey. We focused in particular on submesoscale thermal fronts on the Pacific shelf off the southeastern coast of Hokkaido, Japan. The overall spatial distribution of skin SSTs was consistent between Landsat 8 and Himawari 8; however, the spatial distribution of horizontal gradients of skin SSTs differed greatly between the two datasets. Some parts of strong fronts on the order of 1 °C km−1 were underestimated with Himawari 8, mainly because of low resolution, whereas weak fronts on the order of 0.1 °C km−1 were obscured in the Landsat 8 imagery because the signal-to-noise ratios were low. The widths of the strong fronts were estimated to be 114–461 m via Landsat 8 imagery and 539–1050 m via in situ ship survey. The difference was probably attributable to the difference in measurement depth of the SST, i.e., about 10-μm skin layer by satellite and a few dozen centimeters below the sea surface by the in situ survey. Our results indicated that an ocean model with a grid size of no more than ≤100–200 m is essential for realistic simulation of the frontal structure on the shelf.
Using Leaf-Off and Leaf-On Multispectral Airborne Laser Scanning Data to Characterize Seedling Stands
Authors: Imangholiloo Mohammad , Saarinen Ninni , Holopainen Markus , Yu Xiaowei , Hyyppä Juha , Vastaranta Mikko
Published: October 2020

Information from seedling stands in time and space is essential for sustainable forest management. To fulfil these informational needs with limited resources, remote sensing is seen as an intriguing alternative for forest inventorying. The structure and tree species composition in seedling stands have created challenges for capturing this information using sensors providing sparse point densities that do not have the ability to penetrate canopy gaps or provide spectral information. Therefore, multispectral airborne laser scanning (mALS) systems providing dense point clouds coupled with multispectral intensity data theoretically offer advantages for the characterization of seedling stands. The aim of this study was to investigate the capability of Optech Titan mALS data to characterize seedling stands in leaf-off and leaf-on conditions, as well as to retrieve the most important forest inventory attributes, such as distinguishing deciduous from coniferous trees, and estimating tree density and height. First, single-tree detection approaches were used to derive crown boundaries and tree heights from which forest structural attributes were aggregated for sample plots. To predict tree species, a random forests classifier was trained using features from two single-channel intensities (SCIs) with wavelengths of 1550 (SCI-Ch1) and 1064 nm (SCI-Ch2), and multichannel intensity (MCI) data composed of three mALS channels. The most important and uncorrelated features were analyzed and selected from 208 features. The highest overall accuracies in classification of Norway spruce, birch, and nontree class in leaf-off and leaf-on conditions obtained using SCI-Ch1 and SCI-Ch2 were 87.36% and 69.47%, respectively. The use of MCI data improved classification by up to 96.55% and 92.54% in leaf-off and leaf-on conditions, respectively. Overall, leaf-off data were favorable for distinguishing deciduous from coniferous trees and tree density estimation with a relative root mean square error (RMSE) of 37.9%, whereas leaf-on data provided more accurate height estimations, with a relative RMSE of 10.76%. Determining the canopy threshold for separating ground returns from vegetation returns was found to be critical, as mapped trees might have a height below one meter. The results showed that mALS data provided benefits for characterizing seedling stands compared to single-channel ALS systems.
Multispectral LiDAR-Based Estimation of Surface Fuel Load in a Dense Coniferous Forest
Authors: Stefanidou Alexandra , Z. Gitas Ioannis , Korhonen Lauri , Georgopoulos Nikos , Stavrakoudis Dimitris
Published: October 2020

Surface fuel load (SFL) constitutes one of the most significant fuel components and is used as an input variable in most fire behavior prediction systems. The aim of the present study was to investigate the potential of discrete-return multispectral Light Detection and Ranging (LiDAR) data to reliably predict SFL in a coniferous forest characterized by dense overstory and complex terrain. In particular, a linear regression analysis workflow was employed with the separate and combined use of LiDAR-derived structural and pulse intensity information for the load estimation of the total surface fuels and individual surface fuel types. Following a leave-one-out cross-validation (LOOCV) approach, the models developed from the different sets of predictor variables were compared in terms of their estimation accuracy. LOOCV indicated that the predictive models produced by the combined use of structural and intensity metrics significantly outperformed the models constructed with the individual sets of metrics, exhibiting an explained variance (R2) between 0.59 and 0.71 (relative Root Mean Square Error (RMSE) 19.3–37.6%). Overall, the results of this research showcase that both structural and intensity variables provided by multispectral LiDAR data are significant for surface fuel load estimation and can successfully contribute to effective pre-fire management, including fire risk assessment and behavior prediction in case of a fire event.
Design of Tracking, Telemetry, Command (TT&C) and Data Transmission Integrated Signal in TDD Mode
Authors: Xue Linshan , Li Xue , Wu Weiren , Yang Yikang
Published: October 2020

For satellite or aircraft networks, tracking, telemetry, and control (TT&C) and data transmission between different nodes are necessary. Traditional measurement mostly adopts the frequency division duplex (FDD) mode and uses a continuous measurement system to achieve high-precision measurement. However, as the number of network nodes increases, the mode suffers from complex frequency domain allocation, and high-cost measurement and data transmission equipment is required. This paper proposes the integrated signal in time division duplex (TDD) mode to improve frequency utilization to address these circumstances. The proposed signal can transmit the TT&C and data at the same frequency. In addition, the high-precision time-frequency synchronization and relative measurement technology in the TDD mode for distributed spacecraft or aircraft networks are studied. The simulation results show that the signal can work normally when the Doppler extrapolation error is less than a quarter of the integration frequency. The distance extrapolation error should be less than a quarter of the length of a chip. The integrated signal reduces the frequency band occupation and realizes the integration of TT&C and data transmission. In addition, the measurement performance is reduced by only 2~3 dB compared with that of the traditional pure TT&C signal.
Hyperspectral Imagery Classification Based on Multiscale Superpixel-Level Constraint Representation
Authors: Yu Haoyang , Zhang Xiao , Song Meiping , Hu Jiaochan , Guo Qiandong , Gao Lianru
Published: October 2020

Sparse representation (SR)-based models have been widely applied for hyperspectral image classification. In our previously established constraint representation (CR) model, we exploited the underlying significance of the sparse coefficient and proposed the participation degree (PD) to represent the contribution of the training sample in representing the testing pixel. However, the spatial variants of the original residual error-driven frameworks often suffer the obstacles to optimization due to the strong constraints. In this paper, based on the object-based image classification (OBIC) framework, we firstly propose a spectral–spatial classification method, called superpixel-level constraint representation (SPCR). Firstly, it uses the PD in respect to the sparse coefficient from CR model. Then, transforming the individual PD to a united activity degree (UAD)-driven mechanism via a spatial constraint generated by the superpixel segmentation algorithm. The final classification is determined based on the UAD-driven mechanism. Considering that the SPCR is susceptible to the segmentation scale, an improved multiscale superpixel-level constraint representation (MSPCR) is further proposed through the decision fusion process of SPCR at different scales. The SPCR method is firstly performed at each scale, and the final category of the testing pixel is determined by the maximum number of the predicated labels among the classification results at each scale. Experimental results on four real hyperspectral datasets including a GF-5 satellite data verified the efficiency and practicability of the two proposed methods.
Spatio-Temporal Variation of the Urban Heat Island in Santiago, Chile during Summers 2005–2017
Authors: Montaner-Fernández Daniel , Morales-Salinas Luis , Rodriguez José Sobrino , Cárdenas-Jirón Luz , Huete Alfredo , Fuentes-Jaque Guillermo , Pérez-Martínez Waldo , Cabezas Julián
Published: October 2020

Urban heat islands (UHIs) can present significant risks to human health. Santiago, Chile has around 7 million residents, concentrated in an average density of 480 people/km2. During the last few summer seasons, the highest extreme maximum temperatures in over 100 years have been recorded. Given the projections in temperature increase for this metropolitan region over the next 50 years, the Santiago UHI could have an important impact on the health and stress of the general population. We studied the presence and spatial variability of UHIs in Santiago during the summer seasons from 2005 to 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery and data from nine meteorological stations. Simple regression models, geographic weighted regression (GWR) models and geostatistical interpolations were used to find nocturnal thermal differences in UHIs of up to 9 °C, as well as increases in the magnitude and extension of the daytime heat island from summer 2014 to 2017. Understanding the behavior of the UHI of Santiago, Chile, is important for urban planners and local decision makers. Additionally, understanding the spatial pattern of the UHI could improve knowledge about how urban areas experience and could mitigate climate change.
Modeling the Effects of Global and Diffuse Radiation on Terrestrial Gross Primary Productivity in China Based on a Two-Leaf Light Use Efficiency Model
Authors: Zhou Yanlian , Wu Xiaocui , Ju Weimin , Zhang Leiming , Chen Zhi , He Wei , Liu Yibo , Shen Yang
Published: October 2020

Solar radiation significantly affects terrestrial gross primary productivity (GPP). However, the relationship between GPP and solar radiation is nonlinear because it is affected by diffuse radiation. Solar radiation has undergone a shift from darker to brighter values over the past 30 years in China. However, the effects on GPP of variation in solar radiation because of changes in diffuse radiation are unclear. In this study, national global radiation in conjunction with other meteorological data and remotely sensed data were used as input into a two-leaf light use efficiency model (TL-LUE) that simulated GPP separately for sunlit and shaded leaves for the period from 1981 to 2012. The results showed that the nationwide annual global radiation experienced a significant reduction (2.18 MJ m−2 y−1; p < 0.05) from 1981 to 2012, decreasing by 1.3% over this 32-year interval. However, the nationwide annual diffuse radiation increased significantly (p < 0.05). The reduction in global radiation from 1981 to 2012 decreased the average annual GPP of terrestrial ecosystems in China by 0.09 Pg C y−1, whereas the gain in diffuse radiation from 1981 to 2012 increased the average annual GPP in China by about 50%. Therefore, the increase in canopy light use efficiency under higher diffuse radiation only partially offsets the loss of GPP caused by lower global radiation.
GB-SAR in the Diagnosis of Critical City Infrastructure—A Case Study of a Load Test on the Long Tram Extradosed Bridge
Authors: Kuras Przemysław , Ortyl Łukasz , Owerko Tomasz , Salamak Marek , Łaziński Piotr
Published: October 2020

This article describes a case of using remote sensing during a static load test of a large bridge, which, because of its location, belongs to a critical city infrastructure. The bridge in question is the longest tram flyover in Poland. This is an extradosed-type concrete structure. It conducts a long tram line over 21 other active lines of an important railway station in the center of Cracow. The diagnostic of such bridges involving the load test method is difficult. Traditional, contact measurements of span displacements are not enough anymore. In such cases, remote sensing becomes an indispensable solution. This publication presents an example of using the close-range radar remote sensing technique of ground-based radar interferometry. However, the cross-sections of the huge bridge were observed using several methods. The aim was to confirm the conditions and efficiency of radar displacement measurements. They were therefore traditional contact measurements using mechanic sensors conducted, if possible, to the bottom of the span, for precise leveling and measurement using electronic total station. Comparing the results as well as the discussion held demonstrated the fundamental advantages of remote sensing methods over the other more traditional techniques.
Active Tectonics of the Frontal Himalayas: An Example from the Manzai Ranges in the Recess Setting, Western Pakistan
Authors: Qureshi Kamil A. , Khan Shuhab D.
Published: October 2020

The Himalayan main frontal thrust (MFT) accommodates most of the present-day Indo–Asia convergence with related periodic earthquakes. The seismicity and deformation mechanism varies considerably across the frontal Himalayas. We mapped a segment (Manzai Ranges) of the MFT at the western margin of the Himalayas and analyzed its deformation mechanism and active tectonics using geomorphic indices and the Interferometric Synthetic Aperture Radar (InSAR) Small Baseline Subset (SBAS) technique. Two frontal thrust faults (Khirgi and Jandola) were mapped using Sentinel-2B band ratios in the study area. Water gaps were present in the form of deflected streams at the tip of the growing anticlines. The C-band RADAR interferometry (Sentinel-1A) showed an average uplift of 5–9 mm/year in the satellite line of sight (LOS) from May 2018 to October 2019. The velocity profiles show an uplift variation across the anticlines and may be related to the displacement transfer from the zone of compression in the Manzai Ranges to the zone of transpression in the Pezu–Bhittani Ranges. Four types of morphometric analyses were carried out to assess the relative tectonic activity, namely mountain front sinuosity index (Smf), valley floor width to height ratio (Vf), normalized longitudinal river profile, and normalized channel steepness index (Ksn). The landscape response to active tectonics in the study area was recorded as a deep fluvial incision in V-shaped valleys, convex river profiles, topographic breaks as knickpoints, and a high Ksn index. The geomorphic parameters show a relative increase in tectonic uplift and deformation from the Kundi anticline to the Khirgi and Manzai anticline. We concluded that the frontal structures in the western Himalayas are still going through an active phase of deformation and landscape development with both seismic and aseismic creep.
Assessing Agricultural Vulnerability to Drought in a Heterogeneous Environment: A Remote Sensing-Based Approach
Authors: Faridatul Mst Ilme , Ahmed Bayes
Published: October 2020

Agriculture is one of the fundamental economic activities in most countries; however, this sector suffers from various natural hazards including flood and drought. The determination of drought-prone areas is essential to select drought-tolerant crops in climate sensitive vulnerable areas. This study aims to enhance the detection of agricultural areas with vulnerability to drought conditions in a heterogeneous environment, taking Bangladesh as a case study. The normalized difference vegetation index (NDVI) and land cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images have been incorporated to compute the vegetation index. In this study, a modified vegetation condition index (mVCI) is proposed to enhance the estimation of agricultural drought. The NDVI values ranging between 0.44 to 0.66 for croplands are utilized for the mVCI. The outcomes of the mVCI are compared with the traditional vegetation condition index (VCI). Precipitation and crop yield data are used for the evaluation. The mVCI maps from multiple years (2006–2018) have been produced to compute the drought hazard index (DHI) using a weighted sum overlay method. The results show that the proposed mVCI enhances the detection of agricultural drought compared to the traditional VCI in a heterogeneous environment. The “Aus” rice-growing season (sown in mid-March to mid-April and harvested in mid-July to early August) receives the highest average precipitation (>400 mm), and thereby this season is less vulnerable to drought. A comparison of crop yields reveals the lowest productivity in the drought year (2006) compared to the non-drought year (2018), and the DHI map presents that the north-west region of Bangladesh is highly vulnerable to agricultural drought. This study has undertaken a large-scale analysis that is important to prioritize agricultural zones and initiate development projects based on the associated level of vulnerability.
A Stable Biotin-Streptavidin Surface Enables Multiplex, Label-Free Protein Detection by Aptamer and Aptamer-Protein Arrays Using Arrayed Imaging Reflectometry
Authors: Klose Alanna M. , Miller Benjamin L.
Published: October 2020

While label-free multiplex sensor technology enables “mixing and matching” of different capture molecules in principle, in practice this has been rarely (if ever) demonstrated. To fill this gap, we developed protocols for the preparation of mixed aptamer-protein arrays on the arrayed imaging reflectometry (AIR) sensing platform using streptavidin as a common attachment point for both biotinylated proteins and aptamers. Doing so required overcoming the noted instability of dried streptavidin monolayers on surfaces. After characterizing this degradation, stable surfaces were obtained using a commercial microarray product. Microarraying through the layer of stabilizer then provided mixed aptamer-antibody arrays. We demonstrate that sensor arrays prepared in this manner are suitable for several probes (thrombin and TGF-β1 aptamers; avi-tagged protein) and targets.
The Sensor-Based Biomechanical Risk Assessment at the Base of the Need for Revising of Standards for Human Ergonomics
Authors: Ranavolo Alberto , Ajoudani Arash , Cherubini Andrea , Bianchi Matteo , Fritzsche Lars , Iavicoli Sergio , Sartori Massimo , Silvetti Alessio , Vanderborght Bram , Varrecchia Tiwana , Draicchio Francesco
Published: October 2020

Due to the epochal changes introduced by “Industry 4.0”, it is getting harder to apply the varying approaches for biomechanical risk assessment of manual handling tasks used to prevent work-related musculoskeletal disorders (WMDs) considered within the International Standards for ergonomics. In fact, the innovative human–robot collaboration (HRC) systems are widening the number of work motor tasks that cannot be assessed. On the other hand, new sensor-based tools for biomechanical risk assessment could be used for both quantitative “direct instrumental evaluations” and “rating of standard methods”, allowing certain improvements over traditional methods. In this light, this Letter aims at detecting the need for revising the standards for human ergonomics and biomechanical risk assessment by analyzing the WMDs prevalence and incidence; additionally, the strengths and weaknesses of traditional methods listed within the International Standards for manual handling activities and the next challenges needed for their revision are considered. As a representative example, the discussion is referred to the lifting of heavy loads where the revision should include the use of sensor-based tools for biomechanical risk assessment during lifting performed with the use of exoskeletons, by more than one person (team lifting) and when the traditional methods cannot be applied. The wearability of sensing and feedback sensors in addition to human augmentation technologies allows for increasing workers’ awareness about possible risks and enhance the effectiveness and safety during the execution of in many manual handling activities.
Experimental Characterization of RGB LED Transceiver in Low-Complexity LED-to-LED Link
Authors: Galal Mariam , Ng Wai Pang , Binns Richard , Abd El Aziz Ahmed
Published: October 2020

This paper proposes a low-complexity and energy-efficient light emitting diode (LED)-to-LED communication system for Internet of Things (IoT) devices with data rates up to 200 kbps over an error-free transmission distance up to 7 cm. The system is based on off-the-shelf red-green-blue (RGB) LEDs, of which the red sub-LED is employed as photodetector in photovoltaic mode while the green sub-LED is the transmitter. The LED photodetector is characterized in the terms of its noise characteristics and its response to the light intensity. The system performance is then analysed in terms of bandwidth, bit error rate (BER) and the signal to noise ratio (SNR). A matched filter is proposed, which optimises the performance and increases the error-free distance.
Development of Instrumented Running Prosthetic Feet for the Collection of Track Loads on Elite Athletes
Authors: Petrone Nicola , Costa Gianfabio , Foscan Gianmario , Gri Antonio , Mazzanti Leonardo , Migliore Gianluca , Cutti Andrea Giovanni
Published: October 2020

Knowledge of loads acting on running specific prostheses (RSP), and in particular on running prosthetic feet (RPF), is crucial for evaluating athletes’ technique, designing safe feet, and biomechanical modelling. The aim of this work was to develop a J-shaped and a C-shaped wearable instrumented running prosthetic foot (iRPF) starting from commercial RPF, suitable for load data collection on the track. The sensing elements are strain gauge bridges mounted on the foot in a configuration that allows decoupling loads parallel and normal to the socket-foot clamp during the stance phase. The system records data on lightweight athlete-worn loggers and transmits them via Wi-Fi to a base station for real-time monitoring. iRPF calibration procedure and static and dynamic validation of predicted ground-reaction forces against those measured by a force platform embedded in the track are reported. The potential application of this wearable system in estimating determinants of sprint performance is presented.
Effect of Bout Length on Gait Measures in People with and without Parkinson’s Disease during Daily Life
Authors: Shah Vrutangkumar V. , McNames James , Harker Graham , Mancini Martina , Carlson-Kuhta Patricia , Nutt John G. , El-Gohary Mahmoud , Curtze Carolin , Horak Fay B.
Published: October 2020

Although the use of wearable technology to characterize gait disorders in daily life is increasing, there is no consensus on which specific gait bout length should be used to characterize gait. Clinical trialists using daily life gait quality as study outcomes need to understand how gait bout length affects the sensitivity and specificity of measures to discriminate pathological gait as well as the reliability of gait measures across gait bout lengths. We investigated whether Parkinson’s disease (PD) affects how gait characteristics change as bout length changes, and how gait bout length affects the reliability and discriminative ability of gait measures to identify gait impairments in people with PD compared to neurotypical Old Adults (OA). We recruited 29 people with PD and 20 neurotypical OA of similar age for this study. Subjects wore 3 inertial sensors, one on each foot and one over the lumbar spine all day, for 7 days. To investigate which gait bout lengths should be included to extract gait measures, we determined the range of gait bout lengths available across all subjects. To investigate if the effect of bout length on each gait measure is similar or not between subjects with PD and OA, we used a growth curve analysis. For reliability and discriminative ability of each gait measure as a function of gait bout length, we used the intraclass correlation coefficient (ICC) and area under the curve (AUC), respectively. Ninety percent of subjects walked with a bout length of less than 53 strides during the week, and the majority (>50%) of gait bouts consisted of less than 12 strides. Although bout length affected all gait measures, the effects depended on the specific measure and sometimes differed for PD versus OA. Specifically, people with PD did not increase/decrease cadence and swing duration with bout length in the same way as OA. ICC and AUC characteristics tended to be larger for shorter than longer gait bouts. Our findings suggest that PD interferes with the scaling of cadence and swing duration with gait bout length. Whereas control subjects gradually increased cadence and decreased swing duration as bout length increased, participants with PD started with higher than normal cadence and shorter than normal stride duration for the smallest bouts, and cadence and stride duration changed little as bout length increased, so differences between PD and OA disappeared for the longer bout lengths. Gait measures extracted from shorter bouts are more common, more reliable, and more discriminative, suggesting that shorter gait bouts should be used to extract potential digital biomarkers for people with PD.
Innovative Head-Mounted System Based on Inertial Sensors and Magnetometer for Detecting Falling Movements
Authors: Lin Chih-Lung , Chiu Wen-Ching , Chu Ting-Ching , Ho Yuan-Hao , Chen Fu-Hsing , Hsu Chih-Cheng , Hsieh Ping-Hsiao , Chen Chien-Hsu , Lin Chou-Ching K. , Sung Pi-Shan , Chen Peng-Ting
Published: October 2020

This work presents a fall detection system that is worn on the head, where the acceleration and posture are stable such that everyday movement can be identified without disturbing the wearer. Falling movements are recognized by comparing the acceleration and orientation of a wearer’s head using prespecified thresholds. The proposed system consists of a triaxial accelerometer, gyroscope, and magnetometer; as such, a Madgwick’s filter is adopted to improve the accuracy of the estimation of orientation. Moreover, with its integrated Wi-Fi module, the proposed system can notify an emergency contact in a timely manner to provide help for the falling person. Based on experimental results concerning falling movements and activities of daily living, the proposed system achieved a sensitivity of 96.67% in fall detection, with a specificity of 98.27%, and, therefore, is suitable for detecting falling movements in daily life.
Vision-Based Building Seismic Displacement Measurement by Stratification of Projective Rectification Using Lines
Authors: Guo Jia , Xiang Yang , Fujita Kohei , Takewaki Izuru
Published: October 2020

We propose a new flexible technique for accurate vision-based seismic displacement measurement of building structures via a single non-stationary camera with any perspective view. No a priori information about the camera’s parameters or only partial knowledge of the internal camera parameters is required, and geometric constraints in the world coordinate system are employed for projective rectification in this research. Whereas most projective rectifications are conducted by specifying the positions of four or more fixed reference points, our method adopts a stratified approach to partially determine the projective transformation from line-based geometric relationships on the world plane. Since line features are natural and plentiful in a man-made architectural building environment, robust estimation techniques for automatic projective/affine distortion removal can be applied in a more practical way. Both simulations and real-recorded data were used to verify the effectiveness and robustness of the proposed method. We hope that the proposed method could advance the consumer-grade camera system for vision-based structural measurement one more step, from laboratory environments to real-world structural health monitoring systems.
Temperature Compensation Method for Raster Projectors Used in 3D Structured Light Scanners
Authors: Adamczyk Marcin
Published: October 2020

Raster projectors are commonly used in many various measurement applications where active lighting is required, such as in three-dimensional structured light scanners. The effect of temperature on the raster projector, in some conditions, can lead to significant deterioration of the measurements performed with such a scanner. In this paper, the outcomes of several experiments concerning the effects of temperature on raster projectors are presented. The described research is focused on the thermal deformations of projected images caused by common thermal effects observed in projectors: those caused by the warming-up process and changes in ambient environmental temperature. A software compensation method is also presented. It is suitable for implementation in any existing measurement method that uses raster projectors. The results of performed verification experiments show that the developed compensation method can decrease the thermal drift of the projected images by up to 14 times in the ambient temperature range 14–42 °C.
High Performance Both in Low-Speed Tracking and Large-Angle Swing Scanning Based on Adaptive Nonsingular Fast Terminal Sliding Mode Control for a Three-Axis Universal Inertially Stabilized Platform
Authors: Wang Yuanchao , Yang Yongming , Kuang Haipeng , Yuan Dongming , Yu Chunfeng , Chen Juan , Hua Nan , Hou Han
Published: October 2020

In order to improve the performance in the practical engineering applications including so called low-speed video tracking and large-angle swing scanning imaging at the same time for a three-axis universal inertially stabilized platform (UISP), we propose an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) strategy subjected to the uncertain disturbances and input saturation constraints. First of all, a second-order dynamic model is established with uncertain disturbances and input saturation constraints. Secondly, a nonsingular fast terminal sliding mode controller (NTSMC) is constructed to ensure the system error converges to zero fast in a finite time; meanwhile, a novel reaching law based on a modified normal distribution function is designed to adjust the control gain. Thirdly, an adaptive control law is designed to online estimate the parameters of the lumped uncertain disturbances. Additionally, the stability of the control system is proved by Lyapunov theory. Finally, extensive comparative simulations and experiments are carried out, the results comprehensively show the effectiveness and superiority of the proposed control method, which can accelerate convergence, weaken the chattering, and has the better control accuracy and robust performance both in the low-speed tracking and large-angle swing scanning applications. Moreover, the exact dynamic model and the prior knowledge of the upper bounds of the disturbances are not required during the procedure of the controller design, which make it have more extensive application value in practical engineering.
Comparisons of Laboratory and On-Road Type-Approval Cycles with Idling Emissions. Implications for Periodical Technical Inspection (PTI) Sensors
Authors: Giechaskiel Barouch , Lähde Tero , Suarez-Bertoa Ricardo , Valverde Victor , Clairotte Michael
Published: October 2020

For the type approval of compression ignition (diesel) and gasoline direct injection vehicles, a particle number (PN) limit of 6 × 1011 p/km is applicable. Diesel vehicles in circulation need to pass a periodical technical inspection (PTI) test, typically every two years, after the first four years of circulation. However, often the applicable smoke tests or on-board diagnostic (OBD) fault checks cannot identify malfunctions of the diesel particulate filters (DPFs). There are also serious concerns that a few high emitters are responsible for the majority of the emissions. For these reasons, a new PTI procedure at idle run with PN systems is under investigation. The correlations between type approval cycles and idle emissions are limited, especially for positive (spark) ignition vehicles. In this study the type approval PN emissions of 32 compression ignition and 56 spark ignition vehicles were compared to their idle PN concentrations from laboratory and on-road tests. The results confirmed that the idle test is applicable for diesel vehicles. The scatter for the spark ignition vehicles was much larger. Nevertheless, the proposed limit for diesel vehicles was also shown to be applicable for these vehicles. The technical specifications of the PTI sensors based on these findings were also discussed.
Study on the Relations between Hyperspectral Images of Bananas (Musa spp.) from Different Countries, Their Compositional Traits and Growing Conditions
Authors: Wang Zhijun , Erasmus Sara Wilhelmina , Liu Xiaotong , van Ruth Saskia M.
Published: October 2020

Bananas are some of the most popular fruits around the world. However, there is limited research that explores hyperspectral imaging of bananas and its relationship with the chemical composition and growing conditions. In the study, the relations that exist between the visible near-infrared hyperspectral reflectance imaging data in the 400–1000 nm range of the bananas collected from different countries, the compositional traits and local growing conditions (altitude, temperature and rainfall) and production management (organic/conventional) were explored. The main compositional traits included moisture, starch, dietary fibre, protein, carotene content and the CIE L*a*b* colour values were also determined. The principal component analysis showed the preliminary separation of bananas from different geographical origins and production systems. The compositional and spectral data revealed positively and negatively moderate correlations (r around ±0.50, p < 0.05) between the carotene, starch content, and colour values (a*, b*) on the one hand and the wavelength ranges 405–525 nm, 615–645 nm, 885–985 nm on the other hand. Since the variation in composition and colour values were related to rainfall and temperature, the spectral information is likely also influenced by the growing conditions. The results could be useful to the industry for the improvement of banana quality and traceability.
Distributed Artificial Intelligence-as-a-Service (DAIaaS) for Smarter IoE and 6G Environments
Authors: Janbi Nourah , Katib Iyad , Albeshri Aiiad , Mehmood Rashid
Published: October 2020

Artificial intelligence (AI) has taken us by storm, helping us to make decisions in everything we do, even in finding our “true love” and the “significant other”. While 5G promises us high-speed mobile internet, 6G pledges to support ubiquitous AI services through next-generation softwarization, heterogeneity, and configurability of networks. The work on 6G is in its infancy and requires the community to conceptualize and develop its design, implementation, deployment, and use cases. Towards this end, this paper proposes a framework for Distributed AI as a Service (DAIaaS) provisioning for Internet of Everything (IoE) and 6G environments. The AI service is “distributed” because the actual training and inference computations are divided into smaller, concurrent, computations suited to the level and capacity of resources available with cloud, fog, and edge layers. Multiple DAIaaS provisioning configurations for distributed training and inference are proposed to investigate the design choices and performance bottlenecks of DAIaaS. Specifically, we have developed three case studies (e.g., smart airport) with eight scenarios (e.g., federated learning) comprising nine applications and AI delivery models (smart surveillance, etc.) and 50 distinct sensor and software modules (e.g., object tracker). The evaluation of the case studies and the DAIaaS framework is reported in terms of end-to-end delay, network usage, energy consumption, and financial savings with recommendations to achieve higher performance. DAIaaS will facilitate standardization of distributed AI provisioning, allow developers to focus on the domain-specific details without worrying about distributed training and inference, and help systemize the mass-production of technologies for smarter environments.
Development of the Correction Algorithm to Limit the Deformation of Bacterial Colonies Diffraction Patterns Caused by Misalignment and Its Impact on the Bacteria Identification in the Proposed Optical Biosensor
Authors: Buzalewicz Igor , Suchwałko Agnieszka , Karwańska Magdalena , Wieliczko Alina , Podbielska Halina
Published: October 2020

Recently proposed methods of bacteria identification in optical biosensors based on the phenomenon of light diffraction on macro-colonies offer over 98% classification accuracy. However, such high accuracy relies on the comparable and repeatable spatial intensity distribution of diffraction patterns. Therefore, it is essential to eliminate all non-species/strain-dependent factors affecting the diffraction patterns. In this study, the impact of the bacterial colony and illuminating beam misalignment on the variation of classification features extracted from diffraction patterns was examined. It was demonstrated that misalignment introduced by the scanning module significantly affected diffraction patterns and extracted classification features used for bacteria identification. Therefore, it is a crucial system-dependent factor limiting the identification accuracy. The acceptable misalignment level, when the accuracy and quality of the classification features are not affected, was determined as no greater than 50 µm. Obtained results led to development of image-processing algorithms for determination of the direction of misalignment and concurrent alignment of the bacterial colonies’ diffraction patterns. The proposed algorithms enable the rigorous monitoring and controlling of the measurement’s conditions in order to preserve the high accuracy of bacteria identification.
A Survey on the Security of Low Power Wide Area Networks: Threats, Challenges, and Potential Solutions
Authors: Adefemi Alimi Kuburat Oyeranti , Ouahada Khmaies , Abu-Mahfouz Adnan M. , Rimer Suvendi
Published: October 2020

Low power wide area network (LPWAN) is among the fastest growing networks in Internet of Things (IoT) technologies. Owing to varieties of outstanding features which include long range communication and low power consumption, LPWANs are fast becoming the most widely deployed connectivity standards in IoT domain. However, this promising network are exposed to various security and privacy threats and challenges. For reliable connectivity within networks, the security and privacy challenges need to be effectively addressed with proper mitigation protocol in place. In this paper, a comprehensive review on the security feature of LPWAN is presented. The paper mainly focuses on analyzing LPWAN’s key cybersecurity architecture and it present a significant emphasis on how the LPWAN is highly attractive to intruders and attackers. This paper aims at summarizing recent research works on key LPWAN security challenges such as replay attack, denial-of-service attack, worm hole attack, and eavesdropping attack, the effect of the attacks, and most importantly the various approaches proposed in the literature for the attacks’ mitigation. The paper concludes by highlighting major research gaps and future directions for the successful deployment of LPWAN.
Development of a High-Resolution All-Fiber Homodyne Laser Doppler Vibrometer
Authors: Shang Jianhua , He Yan , Wang Qi , Li Yilun , Ren Lihong
Published: October 2020

Based on the homodyne detection, a compact and cost-effective all-fiber laser Doppler vibrometer (LDV) with high resolution is presented. For the signal processing, the discrimination algorithm combined with the nonorthogonal correction is applied. The algorithm corrects the quadrature imbalance and other nonlinearity. In the calibration experiment, with the glass pasted on a piezoceramic transducer (PZT), the velocity resolution of 62 nm/s at 4 kHz and displacement resolution of 2.468 pm are achieved. For the LDV-based acousto-optic communication, the minimum detectable sound pressure level (SPL) reached 0.12 Pa under the hydrostatic air-water surface. The results demonstrate that the designed homodyne LDV has a low system background noise and can offer high precision in the vibration measurement.
An Unbalanced QPSK-Based Integrated Communication-Ranging System for Distributed Spacecraft Networking
Authors: Zhao Na , Chang Qing , Wang Hao , Zhang Zhibo
Published: October 2020

The spacecraft tracking telemetering and command (TT&C) system plays an essential role in celestial and terrestrial networks, requiring relative ranging and communication, particularly in satellite formation flying networks and distributed spacecraft networks. To achieve precious ranging and high-data-rate communication in a Master/Slave satellite architecture, an integrated communication-ranging system (ICRS) is introduced. ICRS is based on the inter-satellite spread spectrum ranging and spread/non-spread spectrum communication modulated by unbalanced quadrature phase shift keying (UQPSK). In both uplink and downlink, the in-phase (I) branches and the quadrature (Q) branches undertake the tasks of ranging and communication, respectively. In addition, a global navigation satellite system (GNSS) like signal is adopted in I branches for the sake of better ranging accuracy, and binary phase shift keying (BPSK) modulation is employed in Q branches for a higher data rate. Therefore, the key point of the ICRS design is the power resource allocation between two branches via the selection of a suitable power distribution factor (PWDF). Simulation results demonstrate the good performance of the proposed approach in ranging error and bit error rate (BER). In addition, a reasonable PWDF is recommended. Furthermore, the influence of clock offset is also taken into consideration.