bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydrothermal Factors Influence on Spatial-Temporal Variation of Evapotranspiration-Precipitation Coupling over Climate Transition Zone of North China
Authors: Yang Zesu , Zhang Qiang , Zhang Yu , Yue Ping , Zhang Liang , Zeng Jian , Qi Yulei
Published: March 2022

As a land–atmosphere coupling “hot spot”, the northern China climate transition zone has a sharp spatial gradient of hydrothermal conditions, which plays an essential role in shaping the spatial and temporal pattern of evapotranspiration-precipitation coupling, but whose mechanisms still remain unclear. This study analyzes the spatial and temporal variation in land–atmosphere coupling strength (CS) in the climate transitional zone of northern China and its relationship with soil moisture and air temperature. Results show that CS gradually transitions from strong positive in the northwest to negative in the southeast and northeast corners. The spatial distribution of CS is closely related to climatic hydrothermal conditions, where soil moisture plays a more dominant role: CS increases first, and then decreases with increasing soil moisture, with the threshold of soil moisture at 0.2; CS gradually transitions from positive to negative at soil moisture between 0.25 and 0.35; CS shows an exponential decreasing trend with increasing temperature. In terms of temporal variation, CS is strongest in spring and weakens sequentially in summer, autumn, and winter, and has significant interdecadal fluctuations. The trend in CS shifts gradually from significantly negative in the west to a non-significant positive in the east. Soil moisture variability dominates the intra-annual variability of CS in the study regions, and determines the interannual variation of CS in arid and semi-arid areas. Moreover, the main reason for the positive and negative spatial differences in CS in the study area is the different driving regime of evapotranspiration (ET). ET is energy-limited in the southern part of the study area, leading to a positive correlation between ET and lifting condensation level (LCL), while in most of the northern part, ET is water-limited and is negatively correlated with LCL; LCL has a negative correlation with P across the study area, thus leading to a negative ET-P coupling in the south and a positive coupling in the north.
Flood Depth Estimation during Hurricane Harvey Using Sentinel-1 and UAVSAR Data
Authors: Kundu Sananda , Lakshmi Venkat , Torres Raymond
Published: March 2022

In August 2017, Hurricane Harvey was one of the most destructive storms to make landfall in the Houston area, causing loss of life and property. Temporal and spatial changes in the depth of floodwater and the extent of inundation form an essential part of flood studies. This work estimates the flood extent and depth from LiDAR DEM (light detection and ranging digital elevation model) using data from the Synthetic Aperture Radar (SAR)–Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and satellite sensor—Sentinel-1. The flood extent showed a decrease between 29–30 August and 5 September 2017. The flood depths estimated using the DEM were compared with the USGS gauge data and showed a correlation (R2) greater than 0.88. The use of Sentinel-1 and UAVSAR resulted in a daily temporal repeat, which helped to document the changes in the flood area and the water depth. These observations are significant for efficient disaster management and to assist relief organizations by providing spatially precise information for the affected areas.
Research on a Simulation Model of a Skywave Over-the-Horizon Radar Sea Echo Spectrum
Authors: Feng Mengyan , Fang Hanxian , Ai Weihua , Wu Xiongbin , Yue Xianchang , Zhang Lan , Guo Chaogang , Zhou Qing , Li Xiaoyan
Published: March 2022

The capability of a skywave over-the-horizon radar (SWR) to achieve the continuous observation of a wide range of ocean dynamics parameters via a single ionospheric reflection has been demonstrated by many scholars. In order to expand the method of SWR detection of ocean dynamics parameters, a simulation model of an SWR sea echo spectrum based on the Barrick sea surface scattering cross-section model (Barrick model) and 3D ray-tracing method, suitable for a narrow-beam, frequency-modulated continuous-wave radar system (FMCW), was established. Based on this model, we simulated ideal and contaminated SWR sea echo spectra, respectively with the 3D electron density data output by the International Reference Ionosphere (IRI) model. Then, we further analyzed the effects of the grazing incidence angle, scattering angle, scattering azimuth angle and fetch length on the sea surface scattering cross-sections, the retrieval precision of the sea surface wind direction, and the root-mean-square (RMS) wave height, using the simulation data calculated by the Barrick model. The results show that these angles and fetch length cause a small expansion and contraction of the scattering cross-section, and have no influence on the retrieval precision of the sea surface wind direction, but will affect the retrieval precision of the RMS wave height; the influence of the grazing incidence angle and scattering angle is ~2.5 times that of the scattering azimuth angle. The ideal SWR sea echo spectrum has small broadening, but the ionosphere phase contamination will cause serious broadening and shifting of the SWR sea echo spectrum, and the higher order nonlinear term has greater contamination.
Wind Speed Variation Mapped Using SAR before and after Commissioning of Offshore Wind Farms
Authors: Owda Abdalmenem , Badger Merete
Published: March 2022

When installing offshore wind farms (OWFs) adjacent to the coast, one needs to consider the combined effects of the wind wakes caused by the OWFs and natural horizontal coastal wind speed gradients (HCWSGs). This study exploits the full Sentinel 1A/B and Envisat archive of synthetic aperture radar (SAR) imagery covering the northern European seas. More than 8700 SAR scenes fit well with our selection criteria and are processed as wind maps for the height 10 m above the sea surface. For eight selected wind farm sites, we systematically compare the wind flow variation before and after wind farm commissioning. Before the commissioning, we observe wind speed gradients up to ±4% for onshore and offshore winds. After the commissioning, we detect a 2–10% reduction in the mean wind speed downstream of the turbines after taking into account the background wind speed gradients. These velocity deficits are proportional to the OWF capacity. Our findings indicate that wind speed maps retrieved from SAR can be used to quantify the complex interactions between natural HCWSGs and turbine-induced effects on the mean wind climate. Ultimately, this can be used in connection with farm planning in coastal waters.
On Spectral-Spatial Classification of Hyperspectral Images Using Image Denoising and Enhancement Techniques, Wavelet Transforms and Controlled Data Set Partitioning
Authors: Miclea Andreia Valentina , Terebes Romulus Mircea , Meza Serban , Cislariu Mihaela
Published: March 2022

Obtaining relevant classification results for hyperspectral images depends on the quality of the data and the proposed selection of the samples and descriptors for the training and testing phases. We propose a hyperspectral image classification machine learning framework based on image processing techniques for denoising and enhancement and a parallel approach for the feature extraction step. This parallel approach is designed to extract the features by employing the wavelet transform in the spectral domain, and by using Local Binary Patterns to capture the texture-like information linked to the geometry of the scene in the spatial domain. The spectral and spatial features are concatenated for a Support Vector Machine-based supervised classifier. For the experimental validation, we propose a controlled sampling approach that ensures the independence of the selected samples for the training data set, respectively the testing data set, offering unbiased performance results. We argue that a random selection applied on the hyperspectral dataset to separate the samples for the learning and testing phases can cause overlapping between the two datasets, leading to biased classification results. The proposed approach, with the controlled sampling strategy, tested on three public datasets, Indian Pines, Salinas and Pavia University, provides good performance results.
An Approach to Improve the Spatial Resolution and Accuracy of AMSR2 Passive Microwave Snow Depth Product Using Machine Learning in Northeast China
Authors: Wei Yanlin , Li Xiaofeng , Li Li , Gu Lingjia , Zheng Xingming , Jiang Tao , Li Xiaojie
Published: March 2022

Snow cover plays a highly critical role in the global water cycle and energy exchange. Accurate snow depth (SD) data are important for research on hydrologic processes, climate change, and natural disaster prediction. However, existing passive microwave (PMW) SD products have high uncertainty in Northeast China owing to their coarse spatial resolution. Surface environment parameters should also be considered to reduce errors in existing SD products. Otherwise, it is difficult to accurately capture snow spatiotemporal variations, especially in a complex environment (e.g., mountain or forests areas). To improve the inversion accuracy and spatial resolution of existing SD products in Northeast China, a multifactor SD downscaling model was developed by combining PMW SD data from the AMSR2 sensor, optical snow cover extent data, and surface environmental parameters to produce fine scale (500 m × 500 m) and high precision SD data. Validations at 98 ground meteorological stations show that the developed model greatly improved the spatial resolution and inversion accuracy of the raw AMSR2 SD product; its root-mean-square error (RMSE) reduced from 26.15 cm of the raw product to 7.58 cm, and the correlation coefficient (R) increased from 0.39 to 0.53. For other SD products (WESTDC and FY), the multifactor SD downscaling model still has good applicability, it could further improve the performance of the WESTDC and FY SD products in time and space and achieve better inversion accuracy than raw SD products. Furthermore, the proposed model exhibited good agreement with the observed SD data in a field quadrat (3 km × 2 km) within the fine scale, with an error ranging between −2 and 2 cm. Compared with the existing downscaling methods, the proposed model presented the best performance.
Fine-Spatial Boreal–Alpine Single-Tree Albedo Measured by UAV: Experiences and Challenges
Authors: Ramtvedt Eirik Næsset , Gobakken Terje , Næsset Erik
Published: March 2022

The boreal–alpine treeline is a fine-spatial heterogeneous ecotone with small single trees, tree clusters and open snow surfaces during wintertime. Due to climate change and decreased grazing of domestic animals, the treelines expand both upwards into the mountains and northwards into the tundra. To quantify and understand the biophysical radiative climatic feedback effect due to this expansion, it is necessary to establish measurement strategies of fine-spatial albedo by which relationships with the tree structure and snow-masking effect can be quantified. In this study, we measured single-tree Norway spruce albedo for small trees using an unmanned aerial vehicle (UAV). The platform allows the measurement of proximal remotely sensed albedo, enabling the provision of fine-spatial reflectance distributed over larger geographical areas. The albedo measurements varied from 0.39 to 0.99. The interaction between the diurnal course of the sun and sloping terrain constituted the most important driving factor on the albedo. Surprisingly, all tree structural variables revealed smaller correlations with the albedo than typically found for boreal and boreal–alpine summertime albedo. The snow-masking effect of the trees on the albedo was statistically significant and was found to be stronger than the effects of tree structural variables. Only the canopy density had a statistically significant effect on the albedo among the tree structural variables. This was likely explained by the imprecise heading of the hoovering positions of the UAV and insufficient spatial resolution of the reflected radiation measurements. For further development of fine-spatial UAV-measured albedo, we recommend the use of UAVs with high-precision navigation systems and field-stop devices to limit the spatial size of the measured reflected radiation.
Multidecadal Land Water and Groundwater Drought Evaluation in Peninsular India
Authors: Abhishek  , Kinouchi Tsuyoshi
Published: March 2022

To efficiently mitigate the multitude of direct and indirect impacts, basin-scale drought characterization is imperative, particularly for India, where water scarcity is continually increasing. We jointly used the GRACE gravity data, PCR-GLOBWB model outputs, and in situ data to quantify the deficits based on land water storage (LWS) and groundwater storage (GWS) in Peninsular India for 35 years from January 1980 to December 2014. The results showed that the study basins experienced high interannual variations despite the minimal linear LWS trends (0.26–0.56 mm yr−1). GWS showed a slow but persistent response (longest deficit spanning ~6 years) to the seasonal variations in the hydrological fluxes and remained the major contributor to LWS. We demonstrated (1) the potential of the PCR-GLOBWB model to analyze LWS and its segregated components beyond GRACE data records, (2) the LWS-based index as a better drought indicator than traditional drought indices, and (3) GRACE-LWS as a proxy indicator of real-time groundwater monitoring without relying upon the intermittent in situ observations. This study underscores the need to revise the water allocation strategies and irrigation systems to maintain the sustainability of groundwater systems and may serve as a holistic framework for remotely monitoring the water beneath our feet, especially in the data-limited regions globally.
The Church of S. Maria Delle Palate in Tusa (Messina, Italy): Digitization and Diagnostics for a New Model of Enjoyment
Authors: Giuffrida Dario , Bonanno Sara , Parrotta Francesco , Mollica Nardo Viviana , Anastasio Gianfranco , Saladino Maria Luisa , Armetta Francesco , Ponterio Rosina Celeste
Published: March 2022

Cultural places represent the tangible part of the identity and historical heritage of a civilization as well as an extraordinary driving force for the economic development of a country. Within its huge asset, Italy counts a wide number of archaeological sites and monuments which, despite their cultural value, are totally cut off from the most important cultural routes. This paper aims to demonstrate how specific actions of digitization can contribute to valorize (restoring a cultural value) ‘marginal’ landmarks, promoting their knowledge and inclusion. The case study described is represented by the Church of “Santa Maria delle Palate”, located inside the well-known Archaeological Park of Halaesa Arconidea (Tusa, ME). The church, built in 1551 and subject to several renovations throughout the centuries, has been investigated as part of an interdisciplinary training and skill transfer project carried out by a CNR-IPCF research team. During the activities, the group of trainees approached a multi-analytic method for the study of many Sicilian places using different techniques such as laser scanning, photogrammetry, thermography and spectroscopy and collecting a large amount of information and data. In 2019, the building in question was the object of a complete architectural survey in order to obtain an accurate digital replica; moreover, the wall painting representing St. Francis, preserved in the southern nave, was investigated through non-invasive investigations (IR-imaging, XRF and Raman spectrometry) with the intention of collecting information about its state of preservation and nature of pigments used and help the restoration work, which would have been carried out in the following months. The result of the work is a combined “digital archive” useful not only for the purposes of conservation, monitoring and dissemination, but as a container of information enjoyable at different levels of depth. In addition to the scientific outcomes achieved for the study of the painting, relevant from the historical and artistic point of view, we must underline the importance of the work for the implementation of a web-based platform where expert and inexpert users can virtually access the church virtual tour and search for specialized contents (e.g., measures, analyzes results). Media such as this are finally demonstrated to be able to promote the inclusion (e.g., for people unable to reach the place or with reducing mobility) and accessibility to cultural places during ordinary (maintenance, closure) or extraordinary events (pandemic).
Simulation of the Radar Cross Section of a Noctuid Moth
Authors: Addison Freya I. , Dally Thomas , Duncan Elizabeth J. , Rouse James , Evans William L. , Hassall Christopher , Neely Ryan R.
Published: March 2022

Electromagnetic modelling may be used as a tool for understanding the radar cross section (RCS) of volant animals. Here, we examine this emerging method in detail and delve deeper into the specifics of the modelling process for a single noctuid moth, with the hope of illuminating the importance of different aspects of the process by varying the morphometric and compositional properties of the model. This was accomplished by creating a high-fidelity three-dimensional insect model by micro-CT scanning a gold-palladium-coated insect. Electromagnetic simulations of the insect model were conducted by applying different morphological and compositional configurations using the WiPL-D Pro 3D Electromagnetic Solver. The simulation results show that high-resolution modelling of insects has advantages compared to the simple ellipsoidal models used in previous studies. We find that the inclusion of wings and separating the composition of the body, wings, and legs and antennae have an impact on the resulting RCS of the specimen. Such modifications to the RCS are missed when a prolate spheroid model is used and should not be ignored in future studies. Finally, this methodology has been shown to be useful in exploring the changes in the RCS that result from variations in specimen size. As such, utilising this methodology further for more species will improve the ability to quantitatively interpret aeroecological observations of weather surveillance radars and special-purpose entomological radars.
Zonal Asymmetry of the Stratopause in the 2019/2020 Arctic Winter
Authors: Shi Yu , Evtushevsky Oleksandr , Milinevsky Gennadi , Klekociuk Andrew , Han Wei , Ivaniha Oksana , Andrienko Yulia , Shulga Valery , Zhang Chenning
Published: March 2022

The aim of this work is to study the zonally asymmetric stratopause that occurred in the Arctic winter of 2019/2020, when the polar vortex was particularly strong and there was no sudden stratospheric warming. Aura Microwave Limb Sounder temperature data were used to analyze the evolution of the stratopause with a particular focus on its zonally asymmetric wave 1 pattern. There was a rapid descent of the stratopause height below 50 km in the anticyclone region in mid-December 2019. The descended stratopause persisted until mid-January 2020 and was accompanied by a slow descent of the higher stratopause in the vortex region. The results show that the stratopause in this event was inclined and lowered from the mesosphere in the polar vortex to the stratosphere in the anticyclone. It was found that the vertical amplification of wave 1 between 50 km and 60 km closely coincides in time with the rapid stratopause descent in the anticyclone. Overall, the behavior contrasts with the situation during sudden stratospheric warmings when the stratopause reforms at higher altitudes following wave amplification events. We link the mechanism responsible for coupling between the vertical wave 1 amplification and this form of zonally asymmetric stratopause descent to the unusual disruption of the quasi-biennial oscillation that occurred in late 2019.
Prediction of Inflammatory Bowel Disease Course Based on Fecal Scent
Authors: Bosch Sofie , Wintjens Dion S. J. , Wicaksono Alfian , Pierik Marieke , Covington James A. , de Meij Tim G. J. , de Boer Nanne K. H.
Published: March 2022

The early prediction of changes in disease state allows timely treatment of patients with inflammatory bowel disease (IBD) to be performed, which improves disease outcome. The aim of this pilot study is to explore the potential of fecal volatile organic compound (VOC) profiles to predict disease course. In this prospective cohort, IBD patients were asked to collect two fecal samples and fill in a questionnaire at set intervals. Biochemically, active disease was defined by FCP ≥ 250 mg/g and remission was defined by FCP < 100 mg/g. Clinically, active disease was defined by a Harvey Bradshaw Index (HBI) ≥ 5 for Crohn’s disease or by a Simple Clinical Colitis Activity Index (SCCAI) ≥ 3 for ulcerative colitis. Clinical remission was defined by an HBI < 4 or SCCAI ≤ 2. Fecal VOC profiles were measured using gas chromatography-ion mobility spectrometry (GC-IMS). The fecal samples collected first were included for VOC analysis to predict disease state at the following collection. A total of 182 subsequently collected samples met the disease-state criteria. The fecal VOC profiles of samples displaying low FCP levels at the first measurements differed between patients preceding exacerbation versus those who remained in remission (AUC 0.75; p < 0.01). Samples with FCP levels at the first time point displayed different VOC profiles in patients preceding remission compared with those whose disease remained active (AUC 0.86; p < 0.01). Based on disease activity scores, there were no significant differences in any of the comparisons. Alterations in fecal VOC profiles preceding changes in FCP levels may be useful to detect disease-course alterations at an early stage. This could lead to earlier treatment, decreased numbers of complications, surgery and hospital admission.
Receiver–Coil Location Detection in a Dynamic Wireless Power Transfer System for Electric Vehicle Charging
Authors: Simonazzi Mattia , Sandrolini Leonardo , Mariscotti Andrea
Published: March 2022

Receiver position sensing is investigated in a dynamic wireless power transfer (DWPT) system for electric vehicle (EV) charging. Exploiting the peculiar behaviour of the resonator arrays input impedance, it is possible to identify the position of the receiver coil by exciting the first array resonator with a signal at a proper frequency and measuring the resulting current. An analytical expression of the input impedance of the resonator array coupled with the EV receiver coil placed in a generic position is provided; its sensitivity to different circuit parameters is also analysed. The outline of a simple and effective algorithm for the localization of the EV is proposed and applied to a test case.
DICOMization of Proprietary Files Obtained from Confocal, Whole-Slide, and FIB-SEM Microscope Scanners
Authors: Gupta Yubraj , Costa Carlos , Pinho Eduardo , Bastião Silva Luís
Published: March 2022

The evolution of biomedical imaging technology is allowing the digitization of hundreds of glass slides at once. There are multiple microscope scanners available in the market including low-cost solutions that can serve small centers. Moreover, new technology is being researched to acquire images and new modalities are appearing in the market such as electron microscopy. This reality offers new diagnostics tools to clinical practice but emphasizes also the lack of multivendor system’s interoperability. Without the adoption of standard data formats and communications methods, it will be impossible to build this industry through the installation of vendor-neutral archives and the establishment of telepathology services in the cloud. The DICOM protocol is a feasible solution to the aforementioned problem because it already provides an interface for visible light and whole slide microscope imaging modalities. While some scanners currently have DICOM interfaces, the vast majority of manufacturers continue to use proprietary solutions. This article proposes an automated DICOMization pipeline that can efficiently transform distinct proprietary microscope images from CLSM, FIB-SEM, and WSI scanners into standard DICOM with their biological information maintained within their metadata. The system feasibility and performance were evaluated with fifteen distinct proprietary modalities, including stacked WSI samples. The results demonstrated that the proposed methodology is accurate and can be used in production. The normalized objects were stored through the standard communications in the Dicoogle open-source archive.
Dual-Cameras-Based Driver’s Eye Gaze Tracking System with Non-Linear Gaze Point Refinement
Authors: Wang Yafei , Ding Xueyan , Yuan Guoliang , Fu Xianping
Published: March 2022

The human eye gaze plays a vital role in monitoring people’s attention, and various efforts have been made to improve in-vehicle driver gaze tracking systems. Most of them build the specific gaze estimation model by pre-annotated data training in an offline way. These systems usually tend to have poor generalization performance during the online gaze prediction, which is caused by the estimation bias between the training domain and the deployment domain, making the predicted gaze points shift from their correct location. To solve this problem, a novel driver’s eye gaze tracking method with non-linear gaze point refinement is proposed in a monitoring system using two cameras, which eliminates the estimation bias and implicitly fine-tunes the gaze points. Supported by the two-stage gaze point clustering algorithm, the non-linear gaze point refinement method can gradually extract the representative gaze points of the forward and mirror gaze zone and establish the non-linear gaze point re-mapping relationship. In addition, the Unscented Kalman filter is utilized to track the driver’s continuous status features. Experimental results show that the non-linear gaze point refinement method outperforms several previous gaze calibration and gaze mapping methods, and improves the gaze estimation accuracy even on the cross-subject evaluation. The system can be used for predicting the driver’s attention.
A Neural Algorithm for the Detection and Correction of Anomalies: Application to the Landing of an Airplane
Authors: Mur Angel , Travé-Massuyès Louise , Chanthery Elodie , Pons Renaud , Ribot Pauline
Published: March 2022

The location of the plane is key during the landing operation. A set of sensors provides data to get the best estimation of plane localization. However, data can contain anomalies. To guarantee correct behavior of the sensors, anomalies must be detected. Then, either the faulty sensor is isolated or the detected anomaly is filtered. This article presents a new neural algorithm for the detection and correction of anomalies named NADCA. This algorithm uses a compact deep learning prediction model and has been evaluated using real and simulated anomalies in real landing signals. NADCA detects and corrects both fast-changing and slow-moving anomalies; it is robust regardless of the degree of oscillation of the signals and sensors with abnormal behavior do not need to be isolated. NADCA can detect and correct anomalies in real time regardless of sensor accuracy. Likewise, NADCA can deal with simultaneous anomalies in different sensors and avoid possible problems of coupling between signals. From a technical point of view, NADCA uses a new prediction method and a new approach to obtain a smoothed signal in real time. NADCA has been developed to detect and correct anomalies during the landing of an airplane, hence improving the information presented to the pilot. Nevertheless, NADCA is a general-purpose algorithm that could be useful in other contexts. NADCA evaluation has given an average F-score value of 0.97 for anomaly detection and an average root mean square error (RMSE) value of 2.10 for anomaly correction.
Specifying Inputs for the Computational Structure of a Surgical System via Optical Method and DLT Algorithm Based on In Vitro Experiments on Cardiovascular Tissue in Minimally Invasive and Robotic Surgery
Authors: Ilewicz Grzegorz , Ładyżyńska-Kozdraś Edyta
Published: March 2022

With the application of four optical CMOS sensors, it was possible to capture the trajectory of an endoscopic tool during an in vitro surgical experiment on a cardiovascular preparation. This was due to the possibility of obtaining a path when a reflective marker was attached. In the work, APAS (Ariel Performance Analysis System) software and DLT (direct linear transformation) algorithm were used. This made it possible to acquire kinematic inputs to the computational model of dynamics, which enabled, regardless of the type of surgical robot structure, derivation of the analogous motion of an endoscopic effector due to the mathematical transformation of the trajectory to joints coordinates. Experiments were carried out with the participation of a practiced cardiac surgeon employing classic endoscopic instruments and robot surgical systems. The results indicated by the experiment showed that the inverse task of kinematics of position for the surgical robot with RCM (remote center of motion) structure was solved. The achieved results from the experiment were used as inputs for deriving a numerical dynamics model of surgical robot during transient states that was obtained by applying the finite element method and by driving dynamics moments acquired through the block diagrams method using a steering system with DC (direct current) motor and PID (proportional–integral–derivative) controller. The results section illustrates the course of kinematic values of endoscopic tools which were employed to apply numerical models as inputs, the course of the driving torque of the model of the surgical robot that enabled the selection of the drive system and the strength values, stresses and displacements according to von Mises hypothesis in its structure during the analysis of transient states that made it possible to establish the strength safety of the surgical robot. For the conducted experiments, the accuracy was ±2 [mm]. In the paper, the employment of optical CMOS sensors in surgical robotics and endoscopy is discussed. The paper concludes that the usage of optical sensors for determining inputs for numerical models of dynamics of surgical robots provides the basis for setting the course of physical quantities that appear in their real object structure, in manners close to reality.
Vertical Cracks Excited in Lock-in Vibrothermography Experiments: Identification of Open and Inhomogeneous Heat Fluxes
Authors: Mendioroz Arantza , Castelo Alazne , Celorrio Ricardo , Salazar Agustín
Published: March 2022

Lock-in vibrothermography has proven to be very useful to characterizing kissing cracks producing ideal, homogeneous, and compact heat sources. Here, we approach real situations by addressing the characterization of non-compact (strip-shaped) heat sources produced by open cracks and inhomogeneous fluxes. We propose combining lock-in vibrothermography data at several modulation frequencies in order to gather penetration and precision data. The approach consists in inverting surface temperature amplitude and phase data by means of a least-squares minimization algorithm without previous knowledge of the geometry of the heat source, only assuming knowledge of the vertical plane where it is confined. We propose a methodology to solve this ill-posed inverse problem by including in the objective function penalty terms based on the expected properties of the solution. These terms are described in a comprehensive and intuitive manner. Inversions of synthetic data show that the geometry of non-compact heat sources is identified correctly and that the contours are rounded due to the penalization. Inhomogeneous smoothly varying fluxes are also qualitatively retrieved, but steep variations of the flux are hard to recover. These findings are confirmed by inversions of experimental data taken on calibrated samples. The proposed methodology is capable of identifying heat sources generated in lock-in vibrothermography experiments.
Advanced Impedance Spectroscopy for QCM Sensor in Liquid Medium
Authors: Burda Ioan
Published: March 2022

Technological evolution has allowed impedance analysis to become a versatile and efficient method for the precise measurement of the equivalent electrical parameters of the quartz crystal microbalance (QCM). By measuring the dissipation factor, or another equivalent electrical parameter, the QCM sensor provides access to the sample mass per unit area and its physical parameters, thus ensuring a detailed analysis. This paper aims to demonstrate the benefits of advanced impedance spectroscopy concerning the Butterworth–van Dyke (BVD) model for QCM sensors immersed with an electrode in a liquid medium. The support instrument in this study is a fast and accurate software-defined virtual impedance analyzer (VIA) with real-time computing capabilities of the QCM sensor’s electric model. Advanced software methods of self-calibration, real-time compensation, innovative post-compensation, and simultaneous calculation by several methods are the experimental resources of the results presented in this paper. The experimental results validate the theoretical concepts and demonstrate both the capabilities of VIA as an instrument and the significant improvements brought by the advanced software methods of impedance spectroscopy analysis related to the BVD model.
A Wideband Circularly Polarized Magnetoelectric Dipole Antenna for 5G Millimeter-Wave Communications
Authors: Askari Hussain , Hussain Niamat , Sufian Md. Abu , Lee Sang Min , Kim Nam
Published: March 2022

In this paper, a wideband circularly polarized (CP) magnetoelectric (ME) dipole antenna operating at 28 GHz band was proposed for 5G millimeter-wave (mm-wave) communications. The antenna geometry included two metallic plates with extended hook-shaped strips at its principal diagonal position, and two corners of truncated metallic plates at the secondary diagonal position. The pair of metallic vias connected the modified strips to the ground plane to create the magnetic dipole. The L-shaped probe feed between the strips was used to excite the antenna. The antenna showed stable gain and wideband characteristics. The simulated and measured results showed that the proposed CP ME dipole antenna had an overlapping (|S11|< −10 dB impedance and 3 dB axial ratio) bandwidth of 18.1% (25–30 GHz), covering the frequency bands dedicated for 5G new radio communications. Moreover, an average gain of 8 dBic was achieved by the antenna throughout the operating bandwidth. The measured data verified the design concept, and the proposed antenna had a small footprint of 0.83 λo × 0.83 λo × 0.125 λo (λo is free space wavelength at the lowest operating frequency), suitable for its application in 5G smart devices and sensors.
Sensor-Based Solid Waste Handling Systems: A Survey
Authors: Vishnu S. , Ramson S. R. Jino , Rukmini M. S. S. , Abu-Mahfouz Adnan M.
Published: March 2022

As a consequence of swiftly growing populations in the urban areas, larger quantities of solid waste also form rapidly. Since urban local bodies are found to be unable to manage this perilous situation effectively, there is a high probability of risks relative to the environment and public health. A sudden change is indispensable in the existing systems that are developed for the collection, transportation, and disposal of solid waste, which are entangled in turmoil. However, Smart sensors and wireless technology enable cyber-physical systems to automate solid waste management, which will revolutionize the industry. This work presents a comprehensive study on the evolution of automation approaches in solid waste management systems. This study is enhanced by dissecting the available literature in solid waste management with Radio Frequency Identification (RFID), Wireless Sensor Networks (WSN), and Internet of Things (IoT)-based approaches and analyzing each category with a typical architecture, respectively. In addition, various communication technologies adopted in the aforementioned categories are critically analyzed to identify the best choice for the deployment of trash bins. From the survey, it is inferred that IoT-based systems are superior to other design approaches, and LoRaWAN is identified as the preferred communication protocol for the automation of solid waste handling systems in urban areas. Furthermore, the critical open research issues on state-of-the-art solid waste handling systems are identified and future directions to address the same topic are suggested.
Low Memory Access Video Stabilization for Low-Cost Camera SoC
Authors: Lee Yun-Gu
Published: March 2022

Video stabilization is one of the most important features in consumer cameras. Even simple video stabilization algorithms may need to access the frames several times to generate a stabilized output image, which places a significant burden on the camera hardware. This high-memory-access requirement makes it difficult to implement video stabilization in real time on low-cost camera SoC. Reduction of the memory usage is a critical issue in camera hardware. This paper presents a structure and layout method to efficiently implement video stabilization for low-end hardware devices in terms of shared memory access amount. The proposed method places sub-components of video stabilization in a parasitic form in other processing blocks, and the sub-components reuse data read from other processing blocks without directly accessing data in the shared memory. Although the proposed method is not superior to the state-of-the-art methods applied in post-processing in terms of video quality, it provides sufficient performance to lower the cost of camera hardware for the development of real-time devices. According to my analysis, the proposed one reduces the memory access amount by 21.1 times compared to the straightforward method.
Intelligent Medical IoT-Enabled Automated Microscopic Image Diagnosis of Acute Blood Cancers
Authors: Karar Mohamed Esmail , Alotaibi Bandar , Alotaibi Munif
Published: March 2022

Blood cancer, or leukemia, has a negative impact on the blood and/or bone marrow of children and adults. Acute lymphocytic leukemia (ALL) and acute myeloid leukemia (AML) are two sub-types of acute leukemia. The Internet of Medical Things (IoMT) and artificial intelligence have allowed for the development of advanced technologies to assist in recently introduced medical procedures. Hence, in this paper, we propose a new intelligent IoMT framework for the automated classification of acute leukemias using microscopic blood images. The workflow of our proposed framework includes three main stages, as follows. First, blood samples are collected by wireless digital microscopy and sent to a cloud server. Second, the cloud server carries out automatic identification of the blood conditions—either leukemias or healthy—utilizing our developed generative adversarial network (GAN) classifier. Finally, the classification results are sent to a hematologist for medical approval. The developed GAN classifier was successfully evaluated on two public data sets: ALL-IDB and ASH image bank. It achieved the best accuracy scores of 98.67% for binary classification (ALL or healthy) and 95.5% for multi-class classification (ALL, AML, and normal blood cells), when compared with existing state-of-the-art methods. The results of this study demonstrate the feasibility of our proposed IoMT framework for automated diagnosis of acute leukemia tests. Clinical realization of this blood diagnosis system is our future work.
Shock Response Spectrum Analysis of Fatigued Runners
Authors: Benjamin Daniel , Odof Serge , Abbès Boussad , Fourchet François , Christiaen Benoit , Taïar Redha
Published: March 2022

The purpose of this study was to determine the effect of fatigue on impact shock wave attenuation and assess how human biomechanics relate to shock attenuation during running. In this paper, we propose a new methodology for the analysis of shock events occurring during the proposed experimental procedure. Our approach is based on the Shock Response Spectrum (SRS), which is a frequency-based function that is used to indicate the magnitude of vibration due to a shock or a transient event. Five high level CrossFit athletes who ran at least three times per week and who were free from musculoskeletal injury volunteered to take part in this study. Two Micromachined Microelectromechanical Systems (MEMS) accelerometers (RunScribe®, San Francisco, CA, USA) were used for this experiment. The two RunScribe pods were mounted on top of the foot in the shoelaces. All five athletes performed three maximum intensity runs: the 1st run was performed after a brief warmup with no prior exercise, then the 2nd and the 3rd run were performed in a fatigued state. Prior to the 2nd and the 3rd run, the athletes were asked to perform at maximum intensity for two minutes on an Assault AirBike to tire them. For all five athletes, there was a direct correlation between fatigue and an increase in the aggressiveness of the SRS. We noticed that for all five athletes for the 3rd run the average SRS peaks were significantly higher than for the 1st run and 2nd run (p < 0.01) at the same natural frequency of the athlete. This confirms our hypothesis that fatigue causes a decrease in the shock attenuation capacity of the musculoskeletal system thus potentially involving a higher risk of overuse injury.
How to Investigate the Effect of Music on Breathing during Exercise: Methodology and Tools
Authors: Innocenti Lorenzo , Nicolò Andrea , Massaroni Carlo , Minganti Carlo , Schena Emiliano , Sacchetti Massimo
Published: March 2022

Music is an invaluable tool to improve affective valence during exercise, with the potential contribution of a mechanism called rhythmic entrainment. However, several methodological limitations impair our current understanding of the effect of music on relevant psychophysiological responses to exercise, including breathing variables. This study presents conceptual, methodological, and operational insight favoring the investigation of the effect of music on breathing during exercise. Three tools were developed for the quantification of the presence, degree, and magnitude of music-locomotor, locomotor-breathing, and music-breathing entrainment. The occurrence of entrainment was assessed during 30 min of moderate cycling exercise performed either when listening to music or not, and was complemented by the recording of relevant psychophysiological and mechanical variables. Respiratory frequency and expiratory time were among the physiological variables that were affected to a greater extent by music during exercise, and a significant (p < 0.05) music-breathing entrainment was found in all 12 participants. These findings suggest the importance of evaluating the effect of music on breathing responses to exercise, with potential implications for exercise prescription and adherence, and for the development of wearable devices simultaneously measuring music, locomotor, and breathing signals.
Self-Powered Self-Contained Wireless Vibration Synchronous Sensor for Fault Detection
Authors: Aldawood Ghufran , Bardaweel Hamzeh
Published: March 2022

Failure in dynamic structures poses a pressing need for fault detection systems. Interconnected sensor nodes of wireless sensor networks (WSN) offer a solution by communicating information about their surroundings. Nonetheless, these battery-powered sensors have an immense labor cost and require periodical battery maintenance and replacement. Batteries pose a significant environmental threat that is expected to cause irreversible damage to the ecosystem. We introduce a fully integrated vibration-powered energy harvester sensor system that is interfaced with a custom-developed fault detection app. Vibrations are used to power a radio frequency (RF) transmitter that is integrated with the vibration sensor subunit. The harvester-sensor unit is comprised of dual moving magnets that are bordered by coil windings for power and signal generation. The power generated from the harvester is used to operate the transmitter while the signal generated from the sensor is transmitted as a vibration signal. Transmitted values are streamed into a high precision fault detection app capable of detecting the frequency of vibrations with an error of 1%. The app employs an FFT algorithm on the transmitted data and notifies the user when a threshold vibration level is reached. The total energy consumed by the transmitter is 0.894 µJ at a 3 V operation. The operable acceleration of the system is 0.7 g [m/s2] at 5–10.6 Hz.
Tiny Vehicle Detection for Mid-to-High Altitude UAV Images Based on Visual Attention and Spatial-Temporal Information
Authors: Yu Ruonan , Li Hongguang , Jiang Yalong , Zhang Baochang , Wang Yufeng
Published: March 2022

Mid-to-high altitude Unmanned Aerial Vehicle (UAV) imagery can provide important remote sensing information between satellite and low altitude platforms, and vehicle detection in mid-to-high altitude UAV images plays a crucial role in land monitoring and disaster relief. However, the high background complexity of images and limited pixels of objects challenge the performance of tiny vehicle detection. Traditional methods suffer from poor adaptation ability to complex backgrounds, while deep neural networks (DNNs) have inherent defects in feature extraction of tiny objects with finite pixels. To address the issue above, this paper puts forward a vehicle detection method combining the DNNs-based and traditional methods for mid-to-high altitude UAV images. We first employ the deep segmentation network to exploit the co-occurrence of the road and vehicles, then detect tiny vehicles based on visual attention mechanism with spatial-temporal constraint information. Experimental results show that the proposed method achieves effective detection of tiny vehicles in complex backgrounds. In addition, ablation experiments are performed to inspect the effectiveness of each component, and comparative experiments on tinier objects are carried out to prove the superior generalization performance of our method in detecting vehicles with a limited size of 5 × 5 pixels or less.
Evaluation of Decision Fusion Methods for Multimodal Biometrics in the Banking Application
Authors: Szczuko Piotr , Harasimiuk Arkadiusz , Czyżewski Andrzej
Published: March 2022

An evaluation of decision fusion methods based on Dempster-Shafer Theory (DST) and its modifications is presented in the article, studied over real biometric data from the engineered multimodal banking client verification system. First, the approaches for multimodal biometric data fusion for verification are explained. Then the proposed implementation of comparison scores fusion is presented, including details on the application of DST, required modifications, base probability, and mass conversions. Next, the biometric verification process is described, and the engineered biometric banking system principles are provided. Finally, the validation results of three fusion approaches on synthetic and real data are presented and discussed, considering the desired outcome manifested by minimized false non-match rates for various assumed thresholds and biometric verification techniques.