bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sewing gesture image detection method based on improved SSD model
Authors: Wang Wenjie , He Mengling , Wang Xiaohua , Yao Weiming 
Published: March 2021

AbstractIn this letter, the authors present a novel sewing gesture image detection method based on an improved single shot MultiBox detector (SSD) model. The deeper Resnet50 residual network replaces the VGG16 basic network of the original SSD model to improve the feature extraction ability. High and low level features are fused based on a feature pyramid network (FPN) for enhanced small‐target detection performance. The model is trained via transfer learning to resolve the small sample shortage problem. The proposed model shows an average precision of 88.69% on a sewing gesture data set constructed by the authors. The proposed model outperforms the Faster R‐CNN, YOLO, and SSD networks in terms of accuracy with acceptable operating speed on the same data set and fully satisfies the real‐time requirements for sewing gesture detection.
Remote sensing target tracking in satellite videos based on a variable‐angle‐adaptive Siamese network
Authors: Bi Fukun , Sun Jiayi , Han Jianhong , Wang Yanping , Bian Mingming 
Published: March 2021

AbstractRemote sensing target tracking in satellite videos plays a key role in various fields. However, due to the complex backgrounds of satellite video sequences and many rotation changes of highly dynamic targets, typical target tracking methods for natural scenes cannot be used directly for such tasks, and their robustness and accuracy are difficult to guarantee. To address these problems, an algorithm is proposed for remote sensing target tracking in satellite videos based on a variable‐angle‐adaptive Siamese network (VAASN). Specifically, the method is based on the fully convolutional Siamese network (Siamese‐FC). First, for the feature extraction stage, to reduce the impact of complex backgrounds, we present a new multifrequency feature representation method and introduce the octave convolution (OctConv) into the AlexNet architecture to adapt to the new feature representation. Then, for the tracking stage, to adapt to changes in target rotation, a variable‐angle‐adaptive module that uses a fast text detector with a single deep neural network (TextBoxes++) is introduced to extract angle information from the template frame and detection frames and performs angle consistency update operations on the detection frames. Finally, qualitative and quantitative experiments using satellite datasets show that the proposed method can improve tracking accuracy while achieving high efficiency.
A two‐step abnormal data analysis and processing method for millimetre‐wave radar in traffic flow detection applications
Authors: Liu Haiqing , Teng Kunmin , Rai Laxmisha , Zhang Yu , Wang Shengli 
Published: March 2021

AbstractIn a new application scenario where the millimetre‐wave radar is installed above the road for detecting traffic flow in downward looking direction, the original data of the radar includes all kinds of background noises and false targets. In order to acquire effective vehicle trajectories, a two‐step abnormal data processing method for millimetre‐wave radar in traffic flow detection application is proposed. In the first step, the rational range of distance, angle and speed are studied, and proper thresholds are presented for reducing the samples of which the single parameter is with the obvious abnormality. Moreover, the nearest neighbour analysis method is used to further extract vehicle trajectories based on the similarity and slope characteristics of each sample to its neighbours. Taking actual detected data as samples, the weighting coefficients, similarity threshold, average slope threshold and standard deviation threshold are calibrated for the proposed nearest neighbour analysis method. The two‐step processing method presents a higher performance in extracting effective trajectory samples, and the ratio of noise points is reduced to 4.1%, compared with 239.9% in the original data sample. The proposed method can provide an effective reference for further applications, such as driving behaviour analysis and traffic flow parameter identification.
Size‐dependent static bending of anisotropic rectangular nanoplates with cubic crystal structures
Authors: Assadi Abbas , Najaf Hossein , Nazemizadeh Mostafa 
Published: March 2021

AbstractHere, size‐dependent static bending of anisotropic rectangular nanoplates is investigated based on surface elasticity theory. The governing equations of the nanoplate are derived considering the most common boundary conditions in MEMS/NEMS. To solve the derived equations, the generalized differential quadrature method is used and the results are verified with experimental ones due to similarities of the results for cantilever nanoplates and nanobeams. Also, several simulations are performed considering fully clamped, two edges clamped, and cantilever boundary conditions for the mostly used anisotropic materials with face‐centred cubic and body‐centred cubic crystal structures. The obtained results indicate that the static bending behaviour of the nanoplate extremely depends on material anisotropy and orientation, surface effects, and boundary conditions. Moreover, the results are comprehensively discussed for changing the geometrical aspect ratio of the nanoplate.
N‐1 security‐constrained coordinated scheduling of integrated electricity and natural gas system considering gas dynamics and wind power uncertainty
Authors: Chen Dawei , Wan Can , Song Yonghua , Liu Hui , Wang Fei 
Published: March 2021

AbstractThis paper develops a novel N‐1 security‐constrained coordinated scheduling model of integrated electricity and natural gas system (IEGS) with consideration of gas dynamics and wind power uncertainty. Direct quantile regression method and Monte Carlo simulation are applied to model the uncertainty associated with wind power forecast in scenarios. Then, the bilinear functions of natural gas constraints are transformed to a set of linear constraints based on McCormick envelopes. To integrate gas dynamics with security analysis in IEGS, a linear dynamic gas flow model considering N‐1 contingency of pipeline is established by means of big‐M method and the fully implicit finite difference method. Finally, the proposed stochastic coordinated scheduling problem of IEGS is formulated as a mixed‐integer linear programming model. Numerical experiments are implemented to verify the superior accuracy of the linear dynamic gas flow model and the effectiveness of the proposed stochastic scheduling model.
A hybrid MFO‐GHNN tuned self‐adaptive FOPID controller for ALFC of renewable energy integrated hybrid power system
Authors: Ramachandran Rajeswari , Satheesh Kumar Jeevitha , Madasamy Balasubramonian , Veerasamy Veerapandiyan 
Published: March 2021

AbstractThis paper proposes a hybrid moth flame optimization–generalized Hopfield neural network (MFO‐GHNN) optimized self‐adaptive fractional order proportional integral derivative (FOPID) controller for automatic load frequency control of multi‐area hybrid power system (HPS). The control problem is formulated with an objective function of area control error associated with unknown parameters such as Kp, Ki, Kd, λ and μ of FOPID controller. The fractional order of differentiator and integrator terms, and the initial values of Kp, Ki and Kd, are drawn from MFO algorithm. Then, the Kp, Ki and Kd are fine‐tuned by solving the dynamic equations governing the behaviour of GHNN under system uncertainties. To test the practicability and effectiveness of the proposed controller, the multi‐area HPS is studied with uncertain change in load demand, system parameters, solar and wind power generation. The proposed method is modelled using MATLAB/Simulink. The results showed that the steady state and transient performance indices of proposed FOPID controller are significantly enhanced than the PID, MFO‐FOPID and GHNN‐PID controllers. In addition, the stability of non‐linear dynamic HPS is analysed using Matignon's theorem of stability. Further, the performance of controller is validated using real time digital simulator run in hardware‐in‐the loop environment.
Steady‐state model of DFIG‐based wind power plant for load flow analysis
Authors: Gianto Rudy 
Published: March 2021

AbstractThe steady‐state models of electric power system components are crucial for the analysis of system load flow or preliminary study of the system stability. At present, penetration of wind power plant (WPP) in power system continues to increase, and its modelling development and investigation is also still a very active research area. This paper proposes a simple technique for modelling doubly fed induction generator (DFIG)‐based WPP to be used in power system steady‐state (i.e. load flow) studies. In the proposed method, derivation of the WPP mathematical model is carried out based only on power formulations of the WPP, namely, DFIG power output and turbine mechanical power input formulas. Detailed power converter modelling, which is usually quite complicated, is not required in the proposed method. Case studies are also presented in this paper where the proposed model is applied to a simple system as well as to multi‐bus systems. In the studies, the model is tested for various wind speeds ranging from 5 to 12 m/s. With these wind speeds, it is found that power outputs of the WPP vary around 0.1 to 2.1 MW. This result also indicates that the proposed DFIG model is valid both for sub‐synchronous and super‐synchronous conditions.
Parameter estimation of frequency shift keying radar signal intercepted by Nyquist folding receiver using periodic linear frequency modulation local oscillator
Authors: Qiu Zhaoyang , Wang Pei , Sun Minhong , Teng Xuyang , Su Mingkun , Zhang Liangliang 
Published: March 2021

AbstractFrequency shift keying (FSK) signal has been widely used in modern radar systems. To intercept the FSK radar signal with a high interception probability, radar reconnaissance receiver should have an ultra‐wideband receiving ability. The Nyquist folding receiver (NYFR) is a novel non‐cooperative ultra‐wideband receiver and it requires a small amount of equipment. When the FSK radar signal is intercepted by the NYFR, the corresponding output is a hybrid modulation signal. Therefore, it is necessary to investigate the parameter estimation of FSK radar signal intercepted by the NYFR. Herein, based on the NYFR using sinusoidal frequency modulation local oscillator (LO), the drawbacks of several existing parameter estimation methods are first analysed. To overcome these drawbacks, the NYFR architecture is improved by changing the LO modulation type to periodic linear frequency modulation. Then, based on the improved NYFR, a novel parameter estimation approach is proposed according to the LO modulation characteristics and the template matching rule. The proposed method is suitable for different kinds of common FSK radar signal code schemes and its computational load is low. At last, several simulation results show the merits of the proposed method.
COMMA: A new LoRaWAN communication optimisation mechanism for mobility adaptation of IoT
Authors: Picard Alexis , Lapayre Jean‐Christophe , Hanna Fouad , Muthada Pottayya Ronnie 
Published: March 2021

AbstractCommunication protocols for the Internet of Things (IoT) have been optimised to meet the specific requirements of this fast‐growing domain. They have been adapted mainly to optimise power consumption, maximise coverage area and facilitate their implementation. One of these protocols is LoRaWAN, which uses the ADR algorithm (Adaptive Data Rate) and aims to reduce power consumption by reducing data rate and transmission power. The ADR algorithm has been specifically optimised for static systems, that is, systems where devices do not move or have limited mobility. In this article, we introduce COMMA (Communication Optimisation Mechanism for Mobility Adaptation), an adaptive data rate mechanism optimised for everyday mobility of devices and people. We use COMMA in telemedicine, our area of expertise, to develop a medical remote‐monitoring platform for mobile patients suffering from chronic diseases.
The role of planetary interior in the long-term evolution of atmospheric CO2on Earth-like exoplanets
Authors: Oosterloo M. , Höning D. , Kamp I. E. E. , van der Tak F. F. S. 
Published: March 2021

Context.The long-term carbonate silicate cycle plays an important role in the evolution of Earth’s climate and, therefore, may also be an important mechanism in the evolution of the climates of Earth-like exoplanets. However, given the large diversity in the possible interiors for Earth-like exoplanets, the ensuing evolution of the atmospheric CO2pressure may be widely different.Aims.We assess the role of the thermal evolution of the planetary interior on the long-term carbon cycle of Earth-like exoplanets. In particular, we investigate the effects of radiogenic mantle heating, core size, and planetary mass on the atmospheric partial CO2pressure, and the ability of a long-term carbon cycle driven by plate tectonics to control the atmospheric CO2pressure.Methods.We developed a box-model which connects carbon cycling to parametrized mantle convection. Processes considered in the carbon cycle are temperature-dependent continental weathering, seafloor weathering, subduction, and degassing through ridge and arc volcanism. The carbon cycle was coupled to the thermal evolution via the plate speed, which was parametrized in terms of the global Rayleigh number.Results.We find decreasing atmospheric CO2pressure with time, up to an order of magnitude over the entire main sequence lifetime of a solar-type star. High abundances of radioactive isotopes allow for more efficient mantle degassing, resulting in higher CO2pressures. Within the spread of abundances found in solar-type stars, atmospheric CO2pressures at 4.5 Gyr were found to vary from 14 Pa to 134 Pa. We find a decreasing Rayleigh number and plate speed toward planets with larger core mass fractionsfc, which leads to reduced degassing and lower atmospheric CO2pressure. In particular forfc≳ 0.8, a rapid decrease of these quantities is found. Variations in planet mass have more moderate effects. However, more massive planets may favor the development of more CO2rich atmospheres due to hotter interiors.Conclusions.The dependence of plate tectonics on mantle cooling has a significant effect on the long-term evolution of the atmospheric CO2pressure. Carbon cycling mediated by plate tectonics is efficient in regulating planetary climates for a wide range of mantle radioactive isotope abundances, planet masses and core sizes. More efficient carbon cycling on planets with a high mantle abundance of thorium or uranium highlights the importance of mapping the abundances of these elements in host stars of potentially habitable exoplanets. Inefficient carbon recycling on planets with a large core mass fraction (≳0.8) emphasizes the importance of precise mass-radius measurements of Earth-sized exoplanets.
Stochastic light variations in hot stars from wind instability: finding photometric signatures and testing against the TESS data
Authors: Krtička J. , Feldmeier A. 
Published: March 2021

Context. Line-driven wind instability is expected to cause small-scale wind inhomogeneities, X-ray emission, and wind line profile variability. The instability can already develop around the sonic point if it is initiated close to the photosphere due to stochastic turbulent motions. In such cases, it may leave its imprint on the light curve as a result of wind blanketing.
Aims. We study the photometric signatures of the line-driven wind instability.
Methods. We used line-driven wind instability simulations to determine the wind variability close to the star. We applied two types of boundary perturbations: a sinusoidal one that enables us to study in detail the development of the instability and a stochastic one given by a Langevin process that provides a more realistic boundary perturbation. We estimated the photometric variability from the resulting mass-flux variations. The variability was simulated assuming that the wind consists of a large number of independent conical wind sectors. We compared the simulated light curves with TESS light curves of OB stars that show stochastic variability.
Results. We find two typical signatures of line-driven wind instability in photometric data: a knee in the power spectrum of magnitude fluctuations, which appears due to engulfment of small-scale structure by larger structures, and a negative skewness of the distribution of fluctuations, which is the result of spatial dominance of rarefied regions. These features endure even when combining the light curves from independent wind sectors.
Conclusions. The stochastic photometric variability of OB stars bears certain signatures of the line-driven wind instability. The distribution function of observed photometric data shows negative skewness and the power spectra of a fraction of light curves exhibit a knee. This can be explained as a result of the line-driven wind instability triggered by stochastic base perturbations.
Validation of the accuracy and precision ofGaiaEDR3 parallaxes with globular clusters
Authors: Maíz Apellániz J. , Pantaleoni González M. , Barbá R. H. 
Published: March 2021

Context.The recent early third data release (EDR3) from theGaiamission has produced parallaxes for 1.468 × 109sources with better quality than those reported in the previous data release. Nevertheless, there are calibration issues with the data that require corrections to the published values and uncertainties.Aims.We want to properly characterize the behavior of the random and systematic uncertainties of theGaiaEDR3 parallaxes in order to maximize the precision of the derived distances without compromising their accuracy. We also aim to provide a step-by-step procedure for the calculation of distances to stars and stellar clusters when using these parallaxes.Methods.We reanalyzed some of the data presented in the calibration papers for quasar and Large Magellanic Cloud (LMC) parallaxes and combine these results with measurements for six bright globular clusters. We calculated the angular covariance of EDR3 parallaxes at small separations (up to a few degrees) based on the LMC results and combined it with the results for larger angles using quasars to obtain an approximate analytical formula for the angular covariance over the whole sky. The results for the six globular clusters were used to validate the parallax bias correction as a function of magnitude, color, and ecliptic latitude and to determine the multiplicative constantkused to convert internal uncertainties to external ones.Results.The angular covariance at zero separation is estimated to be 106 μas2, yielding a minimum (systematic) uncertainty for EDR3 parallaxes of 10.3 μas for individual stars or compact stellar clusters. This value can be slightly reduced for globular clusters that span ≳30′ after considering the behavior of the angular covariance of the parallaxes for small separations. A recent parallax bias correction is found to work quite well, except perhaps for the brighter magnitudes, where improvements may be possible. The value ofkis found to be 1.1–1.7 and to depend onG. We find that stars with moderately large values of the renormalized unit weight error can still provide useful parallaxes, albeit with larger values ofk. We give accurate and preciseGaiaEDR3 distances to the six globular clusters, and for the specific case of 47 Tuc we are able to beat the angular covariance limit through the use of the background Small Magellanic Cloud as a reference and derive a high-precision distance of 4.53 ± 0.06 kpc. Finally, a recipe for the derivation of distances to stars and stellar clusters usingGaiaEDR3 parallaxes is given.
Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis
Authors: Ashat Munish , Klair Jagpal Singh , Singh Dhruv , Murali Arvind Rangarajan , Krishnamoorthi Rajesh 
Published: March 2021

Abstract
Background and study aims With the advent of deep neural networks (DNN) learning, the field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials (RCT) have investigated the influence of integrating AI in colonoscopy and its impact on adenoma detection rates (ADRs) and polyp detection rates (PDRs). We performed a systematic review and meta-analysis to reliably assess if the impact is statistically significant enough to warrant the adoption of AI -assisted colonoscopy (AIAC) in clinical practice.
Methods We conducted a comprehensive search of multiple electronic databases and conference proceedings to identify RCTs that compared outcomes between AIAC and conventional colonoscopy (CC). The primary outcome was ADR. The secondary outcomes were PDR and total withdrawal time (WT).
Results Six RCTs (comparing AIAC vs CC) with 5058 individuals undergoing average-risk screening colonoscopy were included in the meta-analysis. ADR was significantly higher with AIAC compared to CC (33.7 % versus 22.9 %; odds ratio (OR) 1.76, 95 % confidence interval (CI) 1.55–2.00; I2 = 28 %). Similarly, PDR was significantly higher with AIAC (45.6 % versus 30.6 %; OR 1.90, 95 %CI, 1.68–2.15, I2 = 0 %). The overall WT was higher for AIAC compared to CC (mean difference [MD] 0.46 (0.00–0.92) minutes, I2 = 94 %).
Conclusions There is an increase in adenoma and polyp detection with the utilization of AIAC.
Update der AWMF-S2k-Leitlinie „Diagnostik und Begutachtung asbestbedingter Erkrankungen“ – Was gibt es Neues?
Authors: Kraus T. , Teschler H. 
Published: March 2021

ZusammenfassungDie S2k-Leitlinie „Diagnostik und Begutachtung asbestbedingter Erkrankungen“ wurde im November 2020 aktualisiert. Dieser Beitrag fasst die wichtigsten Änderungen zusammen. Neu ist der Hinweis auf das Risiko einer potenziell hohen Exposition gegenüber Asbestfasern bei der Sanierung von asbesthaltigem Putz, Spachtelmassen und Klebern. Biomarker wie Mesothelin und Calretinin sollen aktuell nur im Rahmen der Forschung eingesetzt werden. Die „asbestos airways disease“, die nur histologisch diagnostiziert werden kann, wird als frühe Form der Asbestose in die Leitlinie aufgenommen. Da das UIP-Muster nicht charakteristisch ist für eine Asbestose, können computertomografische Fälle mit UIP-Muster ohne den gleichzeitigen Nachweis von Pleuraplaques alleine nicht sicher einer Asbestose zugeordnet werden. Bezüglich der Bewertung des funktionellen Schadens wird auf die große Bedeutung von Flussvolumenkurve, Ganzkörperplethysmografie, Diffusionskapazität und Belastungstests hingewiesen. Wenn verfügbar, sind die Referenzwerte nach GLI Grundlage der Bewertung. In der Leitlinie finden sich spezifische Hinweise zur Prävention, medizinischen Behandlung und erstmals zum Stellenwert der ambulanten Rehabilitation und Trainingstherapie. Ferner finden sich Hinweise auf die Begutachtung der neue Berufskrankheit Ovarialkarzinom nach beruflicher Asbestexposition.