bluuebunny/crossref_metadata_2025 huggingface dataset:
Three-Dimensional Surface Deformation Characteristics Based on Time Series InSAR and GPS Technologies in Beijing, China
Authors: Lei Kunchao , Ma Fengshan , Chen Beibei , Luo Yong , Cui Wenjun , Zhou Yi , Liu He , Sha Te
Published: October 2021

Excessive exploitation of the groundwater has resulted in obvious three-dimensional (3D) deformation features on the surface of the Beijing Plain. This paper, by combining Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) technologies, has obtained time-series information of the 3D surface deformation in the Beijing Plain, analyzing its spatial distribution characteristics. On this basis, the relationship between different controlling factors with the 3D deformation of the surface has been analyzed as well. The following results are obtained: (1) From 2013 to 2018, the land subsidence, which generally showed the trend of slowing down, was mainly concentrated in the eastern, northern, and southern regions of Beijing Plain, with multiple subsidence centers. (2) Under the International Terrestrial Reference Frame 2005 (ITRF2005), the horizontal direction of all GPS points in the plain is basically the same, with the dominant movement direction being NE112.5°~NE113.8°. Under the Eurasian reference frame, the horizontal movement rate of GPS points significantly decreases. The movement rate and direction of each point are not characteristic of overall trend activity. (3) The distribution and extent of the 3D surface deformation in the Beijing Plain are controlled by the basement structure. Part of the subsided area corresponds to a Quaternary depression formed at the junction of active faults disrupting the area. Similarly, the distribution of horizontal deformation in the E-W and N-S directions of the plain is controlled by the regional basement structure comprising major faults bounding horizontal deformation. (4) Groundwater exploitation is the main cause of the 3D surface deformation in the Beijing Plain. The groundwater funnels of the second and third confined aquifer are in suitable agreement with the land subsidence. The horizontal movement in the Beijing Plain is either directed toward the center of the groundwater or the land subsidence funnel, and the deformation is directed from areas with higher to areas with lower groundwater levels.
Galileo E5 AltBOC Signals: Application for Single-Frequency Total Electron Content Estimations
Authors: Padokhin Artem M. , Mylnikova Anna A. , Yasyukevich Yury V. , Morozov Yury V. , Kurbatov Gregory A. , Vesnin Artem M.
Published: October 2021

Global navigation satellite system signals are known to be an efficient tool to monitor the Earth ionosphere. We suggest Galileo E5 AltBOC phase and pseudorange observables—a single-frequency combination—to estimate the ionospheric total electron content (TEC). We performed a one-month campaign in September 2020 to compare the noise level for different TEC estimations based on single-frequency and dual-frequency data. Unlike GPS, GLONASS, or Galileo E5a and E5b single-frequency TEC estimations (involving signals with binary and quadrature phase-shift keying, such as BPSK and QPSK, or binary offset carrier (BOC) modulation), an extra wideband Galileo E5 AltBOC signal provided the smallest noise level, comparable to that of dual-frequency GPS. For elevation higher than 60 degrees, the 100 s root-mean-square (RMS) of TEC, an estimated TEC noise proxy, was as follows for different signals: ~0.05 TECU for Galileo E5 AltBOC, 0.09 TECU for GPS L5, ~0.1TECU for Galileo E5a/E5b BPSK, and 0.85 TECU for Galileo E1 CBOC. Dual-frequency phase combinations provided RMS values of 0.03 TECU for Galileo E1/E5, 0.03 and 0.07 TECU for GPS L1/L2 and L1/L5. At low elevations, E5 AltBOC provided at least twice less single-frequency TEC noise as compared with data obtained from E5a or E5b. The short dataset of our study could limit the obtained estimates; however, we expect that the AltBOC single-frequency TEC will still surpass the BPSK analogue in noise parameters when the solar cycle evolves and geomagnetic activity increases. Therefore, AltBOC signals could advance geoscience.
High-Accuracy Attitude Determination Using Single-Difference Observables Based on Multi-Antenna GNSS Receiver with a Common Clock
Authors: Zhang Chenglong , Dong Danan , Chen Wen , Cai Miaomiao , Peng Yu , Yu Chao , Wu Jianping
Published: October 2021

A global navigation satellite system (GNSS) receiver with multi-antenna using clock synchronization technology is a powerful piece of equipment for precise attitude determination and reducing costs. The single-difference (SD) can eliminate both the satellites and receiver clock errors with the common clock between antennas, which benefits the GNSS short-baseline attitude determination due to its lower noise, higher redundancy and stronger function model strength. However, the existence of uncalibrated phase delay (UPD) makes it difficult to obtain fixed SD attitude solutions. Therefore, the key problem for the fixed SD attitude solutions is to separate the SD UPD and fix the SD ambiguities into integers between antennas. This article introduces the one-step ambiguity substitution approach to separate the SD UPD, through which we merge the SD UPD parameter with the SD ambiguity of the reference satellite ambiguity as the new SD UPD parameter. Reconstructing the other SD ambiguities, the rank deficiency can be remedied by nature, and the new SD ambiguities can have a natural integer feature. Finally, the fixed SD baseline and attitude solutions are obtained by combining the ambiguity substitution approach with integer ambiguity resolution (IAR). To verify the effect of the ambiguity substitution approach and the advantages of the SD observables with a common clock in practical applications, we conducted static, kinematic, and vehicle experiments. In static experiments, the root mean squared errors (RMSEs) of the yaw and pitch angles obtained by the SD observables with a common clock were improved by approximately 80% and 93%, respectively, compared to double-difference (DD) observables with a common clock in multi-day attitude solutions. The kinematic results show that the dispersion of the SD-Fix in the pitch angle is two times less that of the DD-Fix, and the standard deviations (STDs) of the pitch angle for SD-Fix can reach 0.02°. Based on the feasibility, five bridges with low pitch angles in the vehicle experiment environment, which the DD observables cannot detect, were detected by the SD observables with a common clock. The attitude angles obtained by the SD observables were also consistent with the fiber optic gyroscope (FOG) inertial navigation system (INS). This research on the SD observables with a common clock provides higher accuracy.
Can Neural Networks Forecast Open Field Burning of Crop Residue in Regions with Anthropogenic Management and Control? A Case Study in Northeastern China
Authors: Bai Bing , Zhao Hongmei , Zhang Sumei , Zhang Xuelei , Du Yabin
Published: October 2021

Open burning is often used to remove crop residue during the harvest season. Despite a series of regulations by the Chinese government, the open burning of crop residue still frequently occurs in China, and the monitoring and forecasting crop fires have become a topic of active research. In this paper, crop fires in Northeastern China were forecasted using an artificial neural network (ANN) based on moderate-resolution imaging spectroradiometer (MODIS) satellite fire data from 2013–2020. Both natural factors (meteorological, soil moisture content, harvest date) and anthropogenic factors were considered. The model’s forecasting accuracy under natural factors reached 77.01% during 2013–2017. When considering the influence of anthropogenic management and control policies, such as the straw open burning prohibition areas in Jilin Province, the accuracy of the forecast results for 2020 was reduced to 60%. Although the forecasting accuracy was lower than for natural factors, the relative error between the observed fire points and the back propagation neural network (BPNN) forecasting results was acceptable. In terms of influencing factors, air pressure, the change in soil moisture content in a 24 h period and the daily soil moisture content were significantly correlated with open burning. The results of this study improve our ability to forecast agricultural fires and provide a scientific framework for regional prevention and control of crop residue burning.
Multi-Agent Deep Reinforcement Learning for Online 3D Human Poses Estimation
Authors: Fan Zhen , Li Xiu , Li Yipeng
Published: October 2021

Most multi-view based human pose estimation techniques assume the cameras are fixed. While in dynamic scenes, the cameras should be able to move and seek the best views to avoid occlusions and extract 3D information of the target collaboratively. In this paper, we address the problem of online view selection for a fixed number of cameras to estimate multi-person 3D poses actively. The proposed method exploits a distributed multi-agent based deep reinforcement learning framework, where each camera is modeled as an agent, to optimize the action of all the cameras. An inter-agent communication protocol was developed to transfer the cameras’ relative positions between agents for better collaboration. Experiments on the Panoptic dataset show that our method outperforms other view selection methods by a large margin given an identical number of cameras. To the best of our knowledge, our method is the first to address online active multi-view 3D pose estimation with multi-agent reinforcement learning.
Updates to and Performance of the cBathy Algorithm for Estimating Nearshore Bathymetry from Remote Sensing Imagery
Authors: Holman Rob , Bergsma Erwin W. J.
Published: October 2021

This manuscript describes and tests a set of improvements to the cBathy algorithm, published in 2013 by Holman et al. [hereafter HPH13], for the estimation of bathymetry based on optical observations of propagating nearshore waves. Three versions are considered, the original HPH13 algorithm (now labeled V1.0), an intermediate version that has seen moderate use but limited testing (V1.2), and a substantially updated version (V2.0). Important improvements from V1.0 include a new deep-water weighting scheme, removal of a spurious variable in the nonlinear fitting, an adaptive scheme for determining the optimum tile size based on the approximate wavelength, and a much-improved search seed algorithm. While V1.2 was tested and results listed, the primary interest is in comparing V1.0, the original code, with the new version V2.0. The three versions were tested against an updated dataset of 39 ground-truth surveys collected from 2015 to 2019 at the Field Research Facility in Duck, NC. In all, 624 cBathy collections were processed spanning a four-day period up to and including each survey date. Both the unfiltered phase 2 and the Kalman-filtered phase 3 bathymetry estimates were tested. For the Kalman-filtered estimates, only the estimate from mid-afternoon on the survey date was used for statistical measures. Of those 39 Kalman products, the bias, rms error, and 95% exceedance for V1.0 were 0.15, 0.47, and 0.96 m, respectively, while for V2.0, they were 0.08, 0.38, and 0.78 m. The mean observed coverage, the percentage of successful estimate locations in the map, were 99.1% for V1.0 and 99.9% for V2.0. Phase 2 (unfiltered) bathymetry estimates were also compared to ground truth for the 624 available data runs. The mean bias, rms error, and 95% exceedance statistics for V1.0 were 0.19, 0.64, and 1.27 m, respectively, and for V2.0 were 0.16, 0.56, and 1.19 m, an improvement in all cases. The coverage also increased from 78.8% for V1.0 to 84.7% for V2.0, about a 27% reduction in the number of failed estimates. The largest errors were associated with both large waves and poor imaging conditions such as fog, rain, or darkness that greatly reduced the percentage of successful coverage. As a practical mitigation of large errors, data runs for which the significant wave height was greater than 1.2 m or the coverage was less than 50% were omitted from the analysis, reducing the number of runs from 624 to 563. For this reduced dataset, the bias, rms error, and 95% exceedance errors for V1.0 were 0.15, 0.58, and 1.16 m and for V2.0 were 0.09, 0.41, and 0.85 m, respectively. Successful coverage for V1.0 was 82.8%, while for V2.0, it was 90.0%, a roughly 42% reduction in the number of failed estimates. Performance for V2.0 individual (non-filtered) estimates is slightly better than the Kalman results in the original HPH13 paper, and it is recommended that version 2.0 becomes the new standard algorithm.
A Comparison of Volumetric Reconstruction Methods of Archaeological Deposits Using Point-Cloud Data from Ahuahu, Aotearoa New Zealand
Authors: Emmitt Joshua , Pillay Patricia , Barrett Matthew , Middleton Stacey , Mackrell Timothy , Floyd Bruce , Ladefoged Thegn N.
Published: October 2021

Collection of 3D data in archaeology is a long-standing practice. Traditionally, the focus of these data has been visualization as opposed to analysis. Three-dimensional data are often recorded during archaeological excavations, with the provenience of deposits, features, and artefacts documented by a variety of methods. Simple analysis of 3D data includes calculating the volumes of bound entities, such as deposits and features, and determining the spatial relationships of artifacts within these. The construction of these volumes presents challenges that originate in computer-aided design (CAD) but have implications for how data are used in archaeological analysis. We evaluate 3D construction processes using data from Waitetoke, Ahuahu Great Mercury Island, Aotearoa, New Zealand. Point clouds created with data collected by total station, photogrammetry, and terrestrial LiDAR using simultaneous localization and mapping (SLAM) are compared, as well as different methods for generating surface area and volumes with triangulated meshes and convex hulls. The differences between methods are evaluated and assessed in relation to analyzing artifact densities within deposits. While each method of 3D data acquisition and modeling has advantages in terms of accuracy and precision, other factors such as data collection and processing times must be considered when deciding on the most suitable.
The Assessment of the Condition of Knee Joint Surfaces with Acoustic Emission Analysis
Authors: Sawaryn Bartłomiej , Piaseczna Natalia , Sieciński Szymon , Doniec Rafał , Duraj Konrad , Komorowski Dariusz , Tkacz Ewaryst J.
Published: October 2021

The knee joint, being the largest joint in the human body, is responsible for a great percentage of leg movements. The diagnosis of the state of knee joints is usually based on X-ray scan, ultrasound imaging, computerized tomography (CT), magnetic resonance imaging (MRI), or arthroscopy. In this study, we aimed to create an inexpensive, portable device for recording the sound produced by the knee joint, and a dedicated application for its analysis. During the study, we examined fourteen volunteers of different ages, including those who had a knee injury. The device effectively enables the recording of the sounds produced by the knee joint, and the spectral analysis used in the application proved its reliability in evaluating the knee joint condition.
Recognition of EEG Signals from Imagined Vowels Using Deep Learning Methods
Authors: Sarmiento Luis Carlos , Villamizar Sergio , López Omar , Collazos Ana Claros , Sarmiento Jhon , Rodríguez Jan Bacca
Published: October 2021

The use of imagined speech with electroencephalographic (EEG) signals is a promising field of brain-computer interfaces (BCI) that seeks communication between areas of the cerebral cortex related to language and devices or machines. However, the complexity of this brain process makes the analysis and classification of this type of signals a relevant topic of research. The goals of this study were: to develop a new algorithm based on Deep Learning (DL), referred to as CNNeeg1-1, to recognize EEG signals in imagined vowel tasks; to create an imagined speech database with 50 subjects specialized in imagined vowels from the Spanish language (/a/,/e/,/i/,/o/,/u/); and to contrast the performance of the CNNeeg1-1 algorithm with the DL Shallow CNN and EEGNet benchmark algorithms using an open access database (BD1) and the newly developed database (BD2). In this study, a mixed variance analysis of variance was conducted to assess the intra-subject and inter-subject training of the proposed algorithms. The results show that for intra-subject training analysis, the best performance among the Shallow CNN, EEGNet, and CNNeeg1-1 methods in classifying imagined vowels (/a/,/e/,/i/,/o/,/u/) was exhibited by CNNeeg1-1, with an accuracy of 65.62% for BD1 database and 85.66% for BD2 database.
A Class-Imbalanced Deep Learning Fall Detection Algorithm Using Wearable Sensors
Authors: Zhang Jing , Li Jia , Wang Weibing
Published: October 2021

Falling represents one of the most serious health risks for elderly people; it may cause irreversible injuries if the individual cannot obtain timely treatment after the fall happens. Therefore, timely and accurate fall detection algorithm research is extremely important. Recently, a number of researchers have focused on fall detection and made many achievements, and most of the relevant algorithm studies are based on ideal class-balanced datasets. However, in real-life applications, the possibilities of Activities of Daily Life (ADL) and fall events are different, so the data collected by wearable sensors suffers from class imbalance. The previously developed algorithms perform poorly on class-imbalanced data. In order to solve this problem, this paper proposes an algorithm that can effectively distinguish falls from a large amount of ADL signals. Compared with the state-of-the-art fall detection algorithms, the proposed method can achieve the highest score in multiple evaluation methods, with a sensitivity of 99.33%, a specificity of 91.86%, an F-Score of 98.44% and an AUC of 98.35%. The results prove that the proposed algorithm is effective on class-imbalanced data and more suitable for real-life application compared to previous works.
Estimation of Various Walking Intensities Based on Wearable Plantar Pressure Sensors Using Artificial Neural Networks
Authors: Chen Hsing-Chung , Sunardi  , Liau Ben-Yi , Lin Chih-Yang , Akbari Veit Babak Hamun , Lung Chi-Wen , Jan Yih-Kuen
Published: October 2021

Walking has been demonstrated to improve health in people with diabetes and peripheral arterial disease. However, continuous walking can produce repeated stress on the plantar foot and cause a high risk of foot ulcers. In addition, a higher walking intensity (i.e., including different speeds and durations) will increase the risk. Therefore, quantifying the walking intensity is essential for rehabilitation interventions to indicate suitable walking exercise. This study proposed a machine learning model to classify the walking speed and duration using plantar region pressure images. A wearable plantar pressure measurement system was used to measure plantar pressures during walking. An Artificial Neural Network (ANN) was adopted to develop a model for walking intensity classification using different plantar region pressure images, including the first toe (T1), the first metatarsal head (M1), the second metatarsal head (M2), and the heel (HL). The classification consisted of three walking speeds (i.e., slow at 0.8 m/s, moderate at 1.6 m/s, and fast at 2.4 m/s) and two walking durations (i.e., 10 min and 20 min). Of the 12 participants, 10 participants (720 images) were randomly selected to train the classification model, and 2 participants (144 images) were utilized to evaluate the model performance. Experimental evaluation indicated that the ANN model effectively classified different walking speeds and durations based on the plantar region pressure images. Each plantar region pressure image (i.e., T1, M1, M2, and HL) generates different accuracies of the classification model. Higher performance was achieved when classifying walking speeds (0.8 m/s, 1.6 m/s, and 2.4 m/s) and 10 min walking duration in the T1 region, evidenced by an F1-score of 0.94. The dataset T1 could be an essential variable in machine learning to classify the walking intensity at different speeds and durations.
Data-Efficient Sensor Upgrade Path Using Knowledge Distillation
Authors: Van Molle Pieter , De Boom Cedric , Verbelen Tim , Vankeirsbilck Bert , De Vylder Jonas , Diricx Bart , Simoens Pieter , Dhoedt Bart
Published: October 2021

Deep neural networks have achieved state-of-the-art performance in image classification. Due to this success, deep learning is now also being applied to other data modalities such as multispectral images, lidar and radar data. However, successfully training a deep neural network requires a large reddataset. Therefore, transitioning to a new sensor modality (e.g., from regular camera images to multispectral camera images) might result in a drop in performance, due to the limited availability of data in the new modality. This might hinder the adoption rate and time to market for new sensor technologies. In this paper, we present an approach to leverage the knowledge of a teacher network, that was trained using the original data modality, to improve the performance of a student network on a new data modality: a technique known in literature as knowledge distillation. By applying knowledge distillation to the problem of sensor transition, we can greatly speed up this process. We validate this approach using a multimodal version of the MNIST dataset. Especially when little data is available in the new modality (i.e., 10 images), training with additional teacher supervision results in increased performance, with the student network scoring a test set accuracy of 0.77, compared to an accuracy of 0.37 for the baseline. We also explore two extensions to the default method of knowledge distillation, which we evaluate on a multimodal version of the CIFAR-10 dataset: an annealing scheme for the hyperparameter α and selective knowledge distillation. Of these two, the first yields the best results. Choosing the optimal annealing scheme results in an increase in test set accuracy of 6%. Finally, we apply our method to the real-world use case of skin lesion classification.
Optimal Material Search for Infrared Markers under Non-Heating and Heating Conditions
Authors: Kubota Yuki , Ke Yushan , Hayakawa Tomohiko , Moko Yushi , Ishikawa Masatoshi
Published: October 2021

Research on optimal markers for infrared imaging and differences in their characteristics in the presence of heat sources has not yet been performed. This study investigates optimal material combinations for developing an accurate and detachable infrared marker for multiple conditions in the medium wave infrared (MWIR) region. Based on four requirements, 11 material combinations are systematically evaluated. Consequently, the optimal marker differs in relation to the presence of specular reflection components. Metal–insulator markers are suitable under non-heating and hot-air heating conditions without reflection components, although a printed marker made of copier paper is captured more clearly than metal–insulator markers during heating, using an optical radiation heating source with reflection components. Our findings can be applied in structural health monitoring and multi-modal projection involving heat sources.
Systematic Literature Reviews in Kansei Engineering for Product Design—A Comparative Study from 1995 to 2020
Authors: López Óscar , Murillo Clara , González Alfonso
Published: October 2021

Individual products and models on the market must be specifically differentiated from the rest to meet user demand. In terms of consumer purchasing behaviour, consumers increasingly base their decisions on subjective terms or the impression that the product leaves on them, both in terms of functionality, usability, safety, and price adequacy, and regarding the emotions and feelings that it triggers in them. This demand has lead both Asia and Europe to implement new methodologies to develop new products, such as “emotional design” or Kansei engineering. This paper presents a systematic literature review (SLR) on the most relevant methodologies based on Kansei engineering and their relevant results in the specific discipline of product design, addressing these five questions: (RQ1) How many studies on KE and emotional design are there in the Scopus and Web of Science (WoS) databases from 1995 to February 2021? (RQ2) Which research topics and types of KE are addressed? (RQ3) Who is leading the research on KE and emotional design? (RQ4) What are the benefits and drawbacks of using and applying the methodology? (RQ5) What are the limitations of the current research? We analysed 87 studies focusing on the Kansei methodology used for product design and device technologies (e.g., shape design, actuators, sensors, structure) and aesthetic aspects (e.g., Kansei words selection, the quantification of measured emotions of results, and detected shortcomings), and provided the database with all the collected information. One identified and highlighted sector in the results is the electronic–technological-device sector. Results confirm that this type of methodology has a majority and direct application in these sectors, and they are widely represented in the automotive and electronics industries. Lastly, this SLR provides researchers with a guide for comparative emotional-design work, and facilitates future designers who want to implement emotional design in their work by selecting the specific type according to the results of the SLR.
Evaluation of the Validity and Reliability of Connected Insoles to Measure Gait Parameters in Healthy Adults
Authors: Jacobs Damien , Farid Leila , Ferré Sabine , Herraez Kilian , Gracies Jean-Michel , Hutin Emilie
Published: October 2021

The continuous, accurate and reliable estimation of gait parameters as a measure of mobility is essential to assess the loss of functional capacity related to the progression of disease. Connected insoles are suitable wearable devices which allow precise, continuous, remote and passive gait assessment. The data of 25 healthy volunteers aged 20 to 77 years were analysed in the study to validate gait parameters (stride length, velocity, stance, swing, step and single support durations and cadence) measured by FeetMe® insoles against the GAITRite® mat reference. The mean values and the values of variability were calculated per subject for GAITRite® and insoles. A t-test and Levene’s test were used to compare the gait parameters for means and variances, respectively, obtained for both devices. Additionally, measures of bias, standard deviation of differences, Pearson’s correlation and intraclass correlation were analysed to explore overall agreement between the two devices. No significant differences in mean and variance between the two devices were detected. Pearson’s correlation coefficients of averaged gait estimates were higher than 0.98 and 0.8, respectively, for unipedal and bipedal gait parameters, supporting a high level of agreement between the two devices. The connected insoles are therefore a device equivalent to GAITRite® to estimate the mean and variability of gait parameters.
Analysis of Heart Rate Variability in Response to Serious Games in Elderly People
Authors: Hou Chun-Ju , Chen Yen-Ting , Capilayan Mycel , Lin Yu-Sian , Huang Min-Wei , Huang Ji-Jer
Published: October 2021

As the proportion of elderly people continues to grow, so does the concern about age-related cognitive decline. Serious games have been developed for cognitive training or treatment, but measuring the activity of the autonomic nervous system (ANS) has not been taken to account. However, cognitive functioning has been known to be heavily influenced by the autonomic nervous system (ANS), and ANS activity can be quantified using heart rate variability (HRV). This paper aims to analyze the physiological response in normal elderly people as they play two types of serious games using HRV features from electrocardiography (ECG). A wearable device designed in-house was used to measure ECG, and the data from this device was pre-processed using digital signal processing techniques. Ten HRV features were extracted, including time-domain, nonlinear, and frequency-domain features. The experiment proceeds as follows: rest for three minutes, play a cognitive aptitude game, rest for another three minutes, followed by two reaction time games. Data from thirty older adults (age: 65.9 ± 7.34; male: 15, female: 15) were analyzed. The statistical results show that there was a significant difference in the HRV between the two types of games. From this, it can be concluded that the type of game has a significant effect on the ANS response. This can be further used in designing games for the elderly, either for training or mood management.
Humidity-Sensing Chipless RFID Tag with Enhanced Sensitivity Using an Interdigital Capacitor Structure
Authors: Yeo Junho , Lee Jong-Ig , Kwon Younghwan
Published: October 2021

An eight-bit chipless radio frequency identification tag providing humidity sensing and identification information is proposed. A compact, enhanced-sensitivity resonator based on an interdigital capacitor (IDC) structure is designed for humidity sensing, whereas seven electric-field-coupled inductor capacitor (ELC) resonators are used for identification information. These eight resonators are placed in a two-by-four array arrangement. A step-by-step investigation for the effect of varying the number of elements and array configuration on the resonant frequency and radar cross-section (RCS) magnitude of the IDC resonator is conducted. The RCS value of the resonant peak frequency for the IDC resonator increases as the number of array elements placed nearby increases due to the mutual coupling among the elements, and the increase in the RCS value becomes larger as the number of arrays increases in the vertical direction. Polyvinyl alcohol (PVA) is coated on the IDC-based resonator at a thickness of 0.02 mm. A non-reflective temperature and humidity chamber is fabricated using Styrofoam, and the relative humidity (RH) is varied from 50% to 80% in 10% intervals at 25 °C in order to measure a bistatic RCS of the proposed tag. The humidity sensing performance of the IDC resonator in the proposed tag is measured by the shift in the resonant peak frequency and the RCS value, and is compared with a single ELC resonator. Experiment results show that when RH increased from 50% to 80%, the sensitivities of both the resonant peak frequency and the RCS value of the IDC resonator were better than those of the ELC resonator. The variation in the RCS value is much larger compared to the resonant peak frequency for both IDC and ELC resonators. In addition, the resonant peak frequency and RCS value of the PVA-coated IDC-based resonator change, whereas those of the other seven resonators without a PVA coating do not change.
Screen-Shooting Resilient Watermarking Scheme via Learned Invariant Keypoints and QT
Authors: Li Li , Bai Rui , Zhang Shanqing , Chang Chin-Chen , Shi Mengtao
Published: October 2021

This paper proposes a screen-shooting resilient watermarking scheme via learned invariant keypoints and QT; that is, if the watermarked image is displayed on the screen and captured by a camera, the watermark can be still extracted from the photo. A screen-shooting resilient watermarking algorithm should meet the following two basic requirements: robust keypoints and a robust watermark algorithm. In our case, we embedded watermarks by combining the feature region filtering model to SuperPoint (FRFS) neural networks, quaternion discrete Fourier transform (QDFT), and tensor decomposition (TD). First we applied FRFS to locate the embedding feature regions which are decided by the keypoints that survive screen-shooting. Second, we structured watermark embedding regions centered at keypoints. Third, the watermarks were embedded by the QDFT and TD (QT) algorithm, which is robust for capturing process attacks. In a partial shooting scenario, the watermark is repeatedly embedded into different regions in an image to enhance robustness. Finally, we extracted the watermarks from at least one region at the extraction stage. The experimental results showed that the proposed scheme is very robust for camera shooting (including partial shooting) different shooting scenarios, and special attacks. Moreover, the efficient mechanism of screen-shooting resilient watermarking could have propietary protection and leak tracing applications.
Step-to-Step Kinematic Validation between an Inertial Measurement Unit (IMU) 3D System, a Combined Laser+IMU System and Force Plates during a 50 M Sprint in a Cohort of Sprinters
Authors: van den Tillaar Roland , Nagahara Ryu , Gleadhill Sam , Jiménez-Reyes Pedro
Published: October 2021

The purpose was to compare step-by-step kinematics measured using force plates (criterion), an IMU only and a combined laser IMU system in well-trained sprinters. Fourteen male experienced sprinters performed a 50-m sprint. Step-by-step kinematics were measured by 50 force plates and compared with an IMU-3D motion capture system and a combined laser+IMU system attached to each foot. Results showed that step kinematics (step velocity, length, contact and flight times) were different when measured with the IMU-3D system, compared with force plates, while the laser+IMU system, showed in general the same kinematics as measured with force plates without a systematic bias. Based upon the findings it can be concluded that the laser+IMU system is as accurate in measuring step-by-step kinematics as the force plate system. At the moment, the IMU-3D system is only accurate in measuring stride patterns (temporal parameters); it is not accurate enough to measure step lengths (spatial) and velocities due to the inaccuracies in step length, especially at high velocities. It is suggested that this laser+IMU system is valid and accurate, which can be used easily in training and competition to obtain step-by step kinematics and give direct feedback of this information during training and competition.
Analytical Blind Beamforming for a Multi-Antenna UAV Base-Station Receiver in Millimeter-Wave Bands
Authors: Liu Pingchuan , Fan Kuangang , Chen Yuhang
Published: October 2021

Over the last decade, unmanned aerial vehicles (UAVs) with antenna arrays have usually been employed for the enhancement of wireless communication in millimeter-wave bands. They are commonly used as aerial base stations and relay platforms in order to serve multiple users. Many beamforming methods for improving communication quality based on channel estimation have been proposed. However, these methods can be resource-intensive due to the complexity of channel estimation in practice. Thus, in this paper, we formulate an MIMO blind beamforming problem at the receivers for UAV-assisted communications in which channel estimation is omitted in order to save communication resources. We introduce one analytical method, which is called the analytical constant modulus algorithm (ACMA), in order to perform blind beamforming at the UAV base station; this relies only on data received by the antenna. The feature of the constant modulus (CM) is employed to restrict the target user signals. Algebraic operations, such as singular value decomposition (SVD), are applied to separate the user signal space from other interferences. The number of users in the region served by the UAV can be detected by exploring information in the measured data. We seek solutions that are expressible as one Kronecker product structure in the signal space; then, the beamformers that correspond to each user can be successfully estimated. The simulation results show that, by using this analytically derived blind method, the system can achieve good signal recovery accuracy, a reasonable system sum rate, and acceptable complexity.
Sensing Using Light: A Key Area of Sensors
Authors: López-Higuera José Miguel
Published: October 2021

This invited featured paper offers a Doctrinal Conception of sensing using Light (SuL) as an “umbrella” in which any sensing approach using Light Sciences and Technologies can be easily included. The key requirements of a sensing system will be quickly introduced by using a bottom-up methodology. Thanks to this, it will be possible to get a general conception of a sensor using Light techniques and know some related issues, such as its main constituted parts and types. The case in which smartness is conferred to the device is also considered. A quick “flight” over 10 significant cases using different principles, techniques, and technologies to detect diverse measurands in various sector applications is offered to illustrate this general concept. After reading this paper, any sensing approach using Light Sciences and Technologies may be easily included under the umbrella: sensing using Light or photonic sensors (PS).
Promising types of packaging for canned products
Authors: Soldatova S.Yu. , Guseva T.B. , Korzunov S.A.
Published: October 2021

The article discusses modern types of packaging for canned products and analyzes their advantages and disadvantages.
To the scientific substantiation of the technology of fish superchilling
Authors: Arkhipov L.O.
Published: October 2021

The relevance of the development of new methods of refrigeration and storage of food products, ensuring the preservation of quality, safety, and an increase in the duration of storage, is reflected. The possibility of using fish superchilling as a method of refrigeration and storage of fishery products, which makes it possible to obtain products comparable to chilled ones, has been experimentally confirmed. The importance of determining the values of the cryoscopic temperature of raw materials as their significant technological indicator has been substantiated.
Integration processes in higher education
Authors: Polozhishnikova M.A. , Raikova E.Yu.
Published: October 2021

The article defines the features of higher education in the Eurasian Economic Union and the prospects for cooperation with the European Union in the field of training personnel capable of solving the problems of eliminating technical barriers in the implementation of foreign economic activity and identifies the main integration processes in the higher education system.
The analysis of the influence of temperature and type of vegetable oil on the rate of thermal oxidation
Authors: Chalykh T.I. , Borisevich A.V.
Published: October 2021

The article discusses the influence of temperature and type of vegetable oil on the rate of its thermal oxidation when deep-fried. To determine the degree of thermal oxidation of oils, the spectroscopic method was used; the measurements were carried out in the range from 200–250 nm. The issue of the safety of oils in the fast food system is considered.
Fortification of food products with nanostructured iodine preparations
Authors: Krolevets A.A. , Glotova S.G. , Mamaeva E.M. , Solodovnikova M.Yu. , Golubkova K.V.
Published: October 2021

The paper presents the properties of nanostructured iodine preparations using the example of potassium iodide and microalgae — spirulina and their application for the production of functional food products for preventive purposes, for instance kefir, fermented baked milk, marmalade, ice cream and bakery products. The sizes of nanostructured preparations were determined by the NTA method. As it turned out, the size of nanoparticles is 42–460 nm, which makes it possible to use these products for the functional purpose.

English version of the article is available on pp. 720-733 at URL: https://panor.ru/articles/enrichment-of-food-products-with-nanostructured-iodine-specimen/70300.html
Study of manufacturers of bread pre-dust and sauces on the example of Khabarovsk
Authors: Kupchak D.V. , Shpak A.V. , Sergienko A.V.
Published: October 2021

The article presents the results of studying the structure of the assortment of bread pre-dust and sauces sold in the retail trade network by country and manufacturer.
State and development prospects of the packaging market
Authors: Nikolaeva M.A. , Mayskova P.I.
Published: October 2021

The article examines the state of the packaging market in the world and in Russia. The structure of the assortment of the produced packaging is revealed; the requirements for packaging at different stages of the technological cycle are established. A comparative characteristic of the environmental friendliness of different types of packaging has been carried out. The promising directions for improving packaging and developing its market are demonstrated.
Evolution of Internal Audit in the Context of Management Theories
Authors: Danilkova S. A.
Published: October 2021

Based on the study of the economic literature of Russian and foreign authors, the historical stages of the formation and development of internal audit are considered, the approaches of scientists to the periodization of internal audit are systematized, the strengths and weaknesses of various opinions are determined. The author revealed the content of the theories of the audit with the indication of their advantages and disadvantages, and justified the author’s opinion on the issue of the evolution of internal audit in the context of various criteria and organizational and management theories, the directions for the implementation of internal audit in the context of managerial theories are indicated.
Project Financing in Housing Construction: Status and Prospects (on the Example of the Novosibirsk Region)
Authors: Rerikh L. M.
Published: October 2021

Negative aspects in the practice of financing housing construction at the expense of citizens and legal entities led to the search for new methods of paying for housing construction in order to prevent the growth of long-term construction, the emergence of new defrauded equity holders. The article presents material on the implementation of project financing by developers of the Novosibirsk region through the use of escrow accounts. The uncertainty of the long-term prospects for the application of the existing method of financing housing construction, the lack of a firm position on the part of the government of the Russian Federation on alternative payment mechanisms are noted.
The Theoretical Platform of the Digital Economy
Authors: Shvetsov Yu G.
Published: October 2021

The article discusses the basic provisions of the theory of the digital economy, synthesizing the practical experience of its formation in Russian society. The new content of commodity-money relations, the leading role of intangible assets in it, the objective nature of the monopoly of electronic money, which have lost a number of its specific functions, and the transformation of monetary institutions into multi-disciplinary financial concerns are substantiated. It is proved the need to exclude individuals from the sphere of taxation and its focus on the fiscal accounting of intellectual, digital property and capital, to turn the budget into a financial instrument of redistribution of gross public product in favor of non-working citizens. The concept of a two-tier economy is introduced, in which the class of intermediaries parasitizing on its achievements is gradually eliminated.
Relação com o saber e tempo integral: escuta de estudantes fora do tempo
Authors: Souza Maria Celeste Reis Fernandes de , Nonato Eunice Maria Nazarethe , Nonato Eunice Maria Nazarethe
Published: October 2021

O texto coloca em discussão a distorção idade-série sob a ótica da relação com o saber. Esse aporte teórico é assumido, no estudo de base qualitativa, para refletir sobre a relação tempo-aprendizagem do ponto de vista de estudantes do 9º ano do Ensino Fundamental (EF) que vivem a situação de distorção-idade série na Escola em Tempo Integral (ETI). Os dados foram produzidos por meio de entrevistas e a análise buscou captar os sentidos e a mobilização dos sujeitos em direção à aprendizagem. Os resultados mostram descompassos entre o modo como os estudantes descrevem seu envolvimento com a escola e as lógicas escolares, e como a ampliação da jornada escolar aliada à ação docente produz efeitos de mobilização para esses estudantes. Distorção idade-série e tempo integral permanecem como desafios da educação brasileira, acentuados pelas consequências da Covid-19
As relações com os saberes no processo de orientação acadêmica de professoras-pesquisadoras de educação física escolar
Authors: Venâncio Luciana , Lima Cyntia Emanuelle Souza , Ferreira Emmanuelle Cynthia Da Silva
Published: October 2021

O processo de orientação no campo acadêmico é permeado por relações de poder, hierárquicas e institucionalizadas, quanto à valorização dos saberes de orientadores(as) em detrimento dos saberes de orientandos(as). Há também interseccionalidades nessas relações, como questões étnico-raciais, de gênero e classe social. Reconhecer essa complexidade relacional implica na reflexão sobre pautas específicas da justiça social – como o antirracismo, o antissexismo e o anticapitalismo – na formação de professores(as)-pesquisadores(as). Neste artigo, três coautoras – uma orientadora e duas orientandas – que investigam a noção de relação com o saber analisam as suas próprias relações com os saberes em um processo de orientação acadêmica. O objetivo é situar as reflexões sobre as escolhas metodológicas baseadas nas narrativas de saberes das três professoras-pesquisadoras. A temática abrange aproximações teórico-metodológicas – no âmbito da orientação acadêmica em um programa de pós-graduação em educação física – e narrativas que se entrelaçam na mobilização para aprender em um grupo de pesquisa.
A relação com o saber de um estudante surdo de uma escola pública
Authors: Nascimento Willdson Silva , Pires de Camargo Eder , Santos Correia Eanes Dos
Published: October 2021

A pesquisa tem como objetivo analisar alguns resultados da presença do intérprete de Libras em sala de aula a partir das experiências explicitadas por um estudante surdo recém-concluinte do ensino médio em uma instituição de ensino público do estado de Sergipe. Trata-se de uma pesquisa qualitativa do tipo exploratória descritiva tendo como instrumento de constituição de dados a entrevista semiestruturada e organização de dados baseado em alguns elementos da Análise de Discurso. E como suporte teórico, apresentamos a Relação com o Saber, de Bernard Charlot e a noção do Duplo Triângulo Pedagógico de Correia, Silva, Nascimento e Charlot (2020). Os resultados demonstram alguns efeitos da presença do intérprete de Libras para o estudante surdo, que se materializam através do “aprender”, “mais vontade de estudar” e “Eles fazem a mediação da aula”.
Comparing the strategies used to maintain the coach-athlete relationship in Japan and the United Kingdom
Authors: Rhind Daniel , Frank Owusu-Sekyere  , Ando Daichi
Published: October 2021

The present study explored the strategies used to maintain the quality of the coach-athlete relationship amongst rowers in Japan and the United Kingdom. A total of 93 athletes from Japan (N = 49) and UK (N = 44) completed the Coach Athlete Relationship Maintenance Questionnaire (CARM-Q) and the Athlete Satisfaction Questionnaire (ASQ). The results of T-tests showed that (a) university rowers in the UK were significantly more satisfied with the coach-athlete relationship than those in Japan; (b) the athletes in Japan expressed higher scores on Preventative strategies than the ones in the UK; (c) the athletes in the UK expressed higher scores on all other CARM-Q subscales with the exception of Social Networks. The results of correlation analyses revealed positive associations between the use of maintenance strategies and athlete satisfaction. These findings evidence the importance of coaches using strategies to maintain the effectiveness of their relationship with athletes as well as the importance of researchers taking cultural factors into account.