bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on quality inspection model of spot welding of equal-thickness three-layer sheets based on ultrasonic A-scan
Authors: Liu Yali , Pan Yulong , Chen Haishan , Wang Wenzhe , An Tong , Chen Xu 
Published: April 2022

Abstract
To judge the spot welding quality automatically and effectively, this thesis uses the conventional ultrasonic A-scanning to study the mathematical model of nugget diameter for equal-thickness three-layer sheets. The finite element simulation model of the spot welding ultrasonic nondestructive (NDT) testing for equal-thickness three-layer low carbon sheets is established. The calculated values of the nugget diameter between different laminates are studied. Finally, the experiment of the spot welding ultrasonic nondestructive testing is carried out. This thesis verifies the correctness of the finite element simulation and the mathematical calculation model. The research results are of great significance to ultrasonic automatic inspection technology of spot welding.
Fingertip pulse rate variability extraction based on extreme-point symmetric mode decomposition
Authors: Wei Zijian , Li Min , Tang Youyuan 
Published: April 2022

Abstract
To solve shortcomings of being sensitive to noise and waveform when using threshold method to extract pulse rate variability (PRV) at this stage, a method using extreme-point symmetric mode decomposition to extract PRV signals from pulse waves with noise is proposed. A Butterworth filter is used to remove the baseline drift, the DC mode and power frequency noise, which can effectively avoid noise interference when identifying peak points. The pre-processed data is decomposed by extreme-point symmetric mode decomposition to select the corresponding mode of the main wave, thereby reducing the difficulty of feature point extraction. Compared with the threshold method, the extraction method proposed in this paper is more intuitive and can self-adaptively select the best decomposition layer. This method is suitable for the extraction of fingertip PRV under complex noise and some disease statuses.
Health evaluation methodology of remote maintenance control system of natural gas pipeline based on ACWGAN-GP algorithm
Authors: Zhang Shibin , Song Fei , Zhang Xiaojun , Jia Lidong , Shi Wei , Ai Yueqiao , Hei Weichun 
Published: April 2022

Abstract
The remote maintenance system of natural gas pipeline is of great significance to ensure the safe and stable operation of the pipeline network. The multi-classification method based on machine learning is more effective for the health evaluation of remote maintenance control system than the traditional evaluation method based on expert experience. In view of the sev ere imb alance i n the nu mber of s amples of f ive health levels, a health evaluation methodology of remote maintenance control system based on Wasserstein distance sand auxiliary classification generative adversarial network (ACWGAN-GP) is proposed. Firstly, the model stability is improved by introducing Wasserstein distance and gradient penalty. The generator generates balanced data, while the discriminator trains with generated and actual data. In this way, several ACWGAN-GP sub-models are trained. Then, the health levels of the sub-model are directly obtained by using the discriminator to classify the samples. Finally, according to the hierarchical relationship of the system, a parallel-serial combined evaluation method is adopted. By this means, the health evaluation model of remote maintenance control system including ACWGAN-GP sub-models is constructed. The experimental results based on 13 sets of KEEL and UCI multi-class imbalanced datasets and actual sampling data show that the effectiveness and advancement of the proposed method improved significantly compared with the existing similar typical algorithms.
Study on Dielectric and Thermal Properties of ABS / multilayer graphene Composites
Authors: Song Bo 
Published: April 2022

Abstract
ABS / multilayer graphene (MLGN) composites were prepared by melt blending ABS and multilayer graphene masterbatch,and their dielectric and thermal properties were studied. The results show that the dielectric constant, dielectric loss, conductivity, thermal decomposition temperature and thermal conductivity of ABS / MLGN composites increase with the increase of MLGN content. The content of MLGN in ABS / MLGN composites with conductive percolation is between 7-8%. When the mass content of MLGN increased to 7%, the dielectric constant of the composite increased from 3.01 to 103.23, the dielectric loss increased from 0.058 to 0.83 at 100Hz, the 5% mass loss temperature of the composite increased by 17.0°C and the thermal conductivity increased by 1.9 times. The research results can provide reference for the preparation of thermally conductive polymer dielectric composites.
Research on Short-term Wind Power Forecasting Based on Stacking Integrated Model
Authors: Wang Haoyue , Zhao Hongtao 
Published: April 2022

Abstract
With the large-scale use of wind farms, wind power has become an indispensable energy source. However, due to the influence of internal instability factors of wind, it poses a huge threat to the economic efficiency and reliability of power system operation. In order to solve this problem, according to the random volatility of wind power, this paper establishes a wavelet threshold noise reduction model to process wind speed characteristics. Because the wind power is very different when the wind speed is the same, many of the wind turbine’s own attributes are added to the input characteristics. Based on the strong generalization ability of decision tree models, the gradient descent tree, extreme gradient boost tree, and lightGBM algorithm are used as the base learner, and the multiple linear regression model is used as the meta-learner to construct a stacking integrated learning model. Compared with methods such as long and short-term memory neural networks, the performance and generalization ability of the cascading generalization algorithm combination model is relatively good.
Study on the influence of different thickness of armature structure on the emission performance of electromagnetic induction coil launcher
Authors: Zheng Fangzheng , Jiang Runxiang , Lu Mengkun , Qian Hanning , Yue Feihong 
Published: April 2022

Abstract
In the armature structure of traditional electromagnetic induction coil launcher, the armature tail melted due to heat accumulation. In this paper, three new armature structures are proposed. Based on the finite element software maxwell2D, the single-stage electromagnetic induction coil launcher, model is established. The performance indexes of traditional and new armature structures are compared, and the influence of the thickness of traditional armature structure and the side thickness of new structure on temperature rise and electromagnetic performance is studied. On the basis of Maxwell-thermal finite element, the correctness of the temperature field conclusion is verified. The simulation results show that the traditional armature structure has the optimal thickness and the armature performance remains unchanged when the weight ratio and the mechanical strength of the armature are considered. Structure 3 and Structure 4 of the new structure significantly improve the temperature rise of the armature and enhance its emission performance. Due to the eddy current, the optimum side thickness of the new structure 3 and structure 4 is slightly larger than 1/2 of the armature length.
Research and application of power system operation risk assessment method considering new energy grid connection
Authors: Mu Zhijun , Song Liang , Li Zhenkai , Mu Wanli , Geng Hongbin 
Published: April 2022

Abstract
The traditional distribution network operation risk assessment does not fully consider the intermittency and volatility of new energy sources, which has an adverse impact on the security management of the power grid. Therefore, combined with the probabilistic characteristics of new energy power generation, this paper establishes a distribution network operation risk assessment model and a comprehensive risk index system including new energy grid-connected, mainly including voltage over-limit, voltage collapse, line active power over-limit, system load loss, abandoning the wind and abandoning the light, exceeding the frequency limit, etc. On this basis, this paper formulates the weighting factors of each risk index, and comprehensively judges the weak points of the system. The example analysis shows that the risk assessment method proposed in this paper can quantitatively analyze the weak links after the new energy is connected to the distribution network. This verifies the effectiveness of the proposed method and provides a reference for the future development of new energy grid-connected security.
Research and Application of “Transparency” System for Sampling Inspection of Power Materials
Authors: Liu WenYe , Zhu Ting , Zhang Ting , Qin LiangLiang , Chen LingPin 
Published: April 2022

Abstract
Aiming at the problem of insufficient transparency in the process of sampling inspection of power materials, the research and application of transparency system for sampling inspection of power materials are proposed. Based on the browser / server mode, the “transparent” system architecture of power material sampling inspection is designed. This article is based on the working principle of the B/S architecture server. This paper analyzes the working mode of the power material sampling server, designs the power material sampling server, and completes the hardware design of the system. Based on the corresponding power material time weight and power material sampling data, this paper analyzes the historical quality of the system. According to the correlation between independent variables and dependent variables, the quality pass rate of power materials is predicted by calculating the sum of residual squares. Combined with the design of power material sampling process, the software design of the system is completed, and the power material sampling is realized. The test results show that the proposed “transparent” system has better sampling effect in the maximum completion time and the non sampling rate of the deadline.
Lightning Disturbance Analysis and Improvement Measures for “Generation-Grid-Load-Storage” Type Distribution Line
Authors: Huang Zhidu , Zhang Wei , Li Shan , Cui Zhimei , Tan Siyuan 
Published: April 2022

Abstract
For economy, the traditional lightning protection method is simple and the lightning protection effect is unsatisfactory. With China’s call and demand for energy transformation, a new distribution network based on “Generation-Grid-Load-Storage” will be the general direction of China’s distribution network development. The new distribution network puts forward higher requirements for the stability, and its lightning protection problem must be solved. In this paper, the overhead ground wire is proposed as the main lightning protection measure of the new distribution network, and the optimal erection range of the overhead ground wire of the distribution line is proposed through simulation, which can effectively reduce the amplitude of lightning overvoltage by 24.1%, which provides an application reference for the lightning protection concept of the new distribution line in the future.
Synthetic vascular graft with spatially distinct architecture for rapid biomimetic cell organisation in a perfusion bioreactor
Authors: Michael Praveesuda L , Yang Nianji , Moore Matthew , Santos Miguel , Lam Yuen Ting , Ward Annabelle , Hung Jui Chien , Tan Richard P , Wise Steven G 
Published: April 2022

Abstract
Access to lab-grown fully functional blood vessels would provide an invaluable resource to vascular medicine. The complex architecture and cellular makeup of native vessels, however, makes this extremely challenging to reproduce in vitro. Bioreactor systems have helped advanced research in this area by replicating many of the physiological conditions necessary for full-scale tissue growth outside of the body. A key element underpinning these technologies are 3D vascular graft templates which serve as temporary scaffolds to direct cell growth into similar cellular architectures observed in native vessels. Grafts further engineered with appropriate physical cues to accommodate the multiple cell types that reside within native vessels may help improve the production efficiency and physiological accuracy of bioreactor-grown vessel substitutes. Here, we engineered two distinct scaffold architectures into an electrospun vascular graft aiming to encourage the spatial organisation of human vascular endothelial cells (hCAECs) in a continuous luminal monolayer, co-cultured with human fibroblasts (hFBs) populating the graft wall. Using an electrospun composite of polycaprolactone and gelatin, we evaluated physical parameters including fibre diameter, fibre alignment, and porosity, that best mimicked the spatial composition and growth of hCAECs and hFBs in native vessels. Upon identifying the optimal scaffold architectures for each cell type, we constructed a custom-designed mandrel that combined these distinct architectures into a single vascular graft during a single electrospinning processing run. When connected to a perfusion bioreactor system, the dual architecture graft spatially oriented hCAECs and hFBs into the graft wall and lumen, respectively, directly from circulation. This biomimetic cell organisation was consistent with positive graft remodelling with significant collagen deposition in the graft wall. These findings demonstrate the influence of architectural cues to direct cell growth within vascular graft templates and the future potential of these approaches to more accurately and efficiency produce blood vessel substitutes in bioreactor systems.
Changing ocean seasonal cycle escalates destructive marine heatwaves in a warming climate
Authors: Wang Shengpeng , Jing Zhao , Wu Lixin , Wang Hong , Shi Jian , Chen Zhaohui , Ma Xiaohui , Gan Bolan , Yang Haiyuan , Liu Xin 
Published: April 2022

Abstract
Marine heatwaves (MHWs) can cause various adverse effects on marine ecosystems associated with complicated social ramifications. It has been well established that the gradually rising sea surface temperature (SST) due to anthropogenic carbon emission will cause an increase of the MHW duration and intensity. However, for species with strong adaptation capacity or mobility, MHW changes due to the altered SST variability under greenhouse warming are more crucial but so far remain poorly assessed. Under the high carbon emission scenario, we show that the cumulative duration (intensity) of MHWs, with the effect of secular SST increase excluded, is projected to be 60% (100%) higher by the end of this century than in the 1990s due to an amplified SST seasonal cycle. This increase becomes more evident for stronger MHWs, reaching up to 8 (30) folds for the extreme MHW category. The amplified SST seasonal cycle also causes pronounced seasonality of MHWs, making them more active in summer-autumn than winter-spring. Our results suggest that MHWs are likely to have increasingly devastating impacts on a wide range of marine species in the future without taking effective steps for carbon emission reduction.
An adaptive geographic meshing and coding method for remote sensing data
Authors: Huang Xiaohui , Li Jiabao , Yan Jining , Wang Lizhe 
Published: April 2022

Abstract
Spatial indexing techniques, inherently data structures, are generally used in portals opened by institutions or organizations to efficiently filter RS images according to their spatial extent, thus providing researchers with fast Remote Sensing (RS) image data discovery ability. Specifically, space-based spatial indexing approaches are widely adopted to index RS images in distributed environments by mapping RS images in two-dimensional space into several one-dimensional spatial codes. However, current spatial indexing approaches still suffer from the boundary objects problem, which leads to multiple spatial codes for a boundary-crossing RS image and thus alleviates the performance of spatial indexes built on top of these spatial codes. To solve this problem, we propose an adaptive geographic meshing and coding method (AGMD) by combining the famous subdivision model GeoSOT and XZ-ordering to generate only one spatial code for RS images with different spatial widths. Then, we implement our proposed method with a unified big data programming model, (i.e., Apache Beam), to enable its execution in various distributed computing engines (e.g., MapReduce, and Apache Spark, etc.) in distributed environments. Finally, we conduct a series of experiments on real datasets, the archived Landsat metadata collection in level 2. The results show that the proposed AGMD method performs well on metrics, including the following aspects: the effectiveness of the storage overhead and the time cost are up to 359.7% and 58.02 %, respectively.
Travel-mode classification based on GPS-trajectory data and geographic information using an XGBoost classifier
Authors: Jin Huiling , Wu Hangbin , Xu Zeran , Huang Wei , Liu Chun 
Published: April 2022

Abstract
Massive Global Positioning System (GPS) trajectory datasets are being produced owing to the advances in mobile sensors, the Internet, and GPS devices. Accurately inferring travel modes from GPS trajectory data can be helpful in transportation planning and modeling, infrastructure design, etc. However, adverse factors such as data noise, differences in sampling rate, and inadequate features have a negative impact on the results of travel mode classification. In this paper, to address such issues, we first propose a preprocessing workflow, which includes data cleaning, segmentation, and resampling, to preprocess raw trajectories. Then, we add new features related to the road and bus stop information for travel mode classification using an XGBoost (eXtreme Gradient Boosting) classifier, along with various basic features of the trajectories. We conducted a set of experiments on the GeoLife dataset using a group of state-of-the-art methods. The results showed that the proposed methods can improve the classification accuracy by using all the classifiers we compared and the classification accuracy using the XGBoost classifier can reach a maximum of 90.41%.
Urban forest canopy height modeling using spaceborne laser ICESAT-2 LIDAR
Authors: Shufan Wang , Chun Liu 
Published: April 2022

Abstract
Urban forests are an important part of urban ecosystems. Carbon sequestration in urban forests helps reduce the concentrations of greenhouse gases in the region where they are present. Forest height is an important structural parameter for calculating the forest carbon sequestration capacity. Based on this, our study proposes a space-borne laser fusion multi-source remote sensing inversion model of urban forest tree height based on urban space environmental characteristics. This paper mainly consists of three parts:
(1) First, a variety of highly correlated tree feature factors were extracted from ICESat2 satellite-borne laser data, LandSat8 multi-spectral data, and spatial environment auxiliary data, and a feature database was constructed. (2) The importance of the feature factors in the feature base was analyzed, and a large-scale forest height inversion model of Shanghai was constructed using a support vector machine (SVM), random forest (RF), and backward propagation neural network (BP-ANN). (3) The accuracy of the urban forest height inversion model was improved by introducing urban spatial environmental features such as texture features. Ablation experiments show that the texture features considered in this study can improve the accuracy of each model to varying degrees, and the accuracy of the BP neural network can reach
R2

=0.61, RMSE=3.6589. The accuracy of the urban tree height inversion model was
R2

=0.6433, RMSE=1.0967, which proves the effectiveness of the space-borne laser fusion multi-source remote sensing urban forest height inversion model considering the characteristics of the space environment.
Single-time power frequency modulation and peak -modulation market combined clearing method considering new energy absorption capacity
Authors: Jin Luosong , He Letian , Lv Ruiyang 
Published: April 2022

Abstract
In order to support the transaction clearing business of power frequency modulation and peak load modulation market in China and improve the absorption capacity of new energy, the coupling relationship between power frequency modulation and peak load modulation auxiliary service is studied, and the combined clearing method of single time period power frequency modulation and peak load modulation market considering the absorption of new energy is proposed. The coupling relationship between power frequency modulation and power peak modulation auxiliary services is reflected in that the two auxiliary services are mutually exclusive. Considering the important promoting effect of peak regulation capacity on new energy consumption, the index of residual depth peak regulation capacity was proposed as the evaluation basis of the clearance result on new energy consumption capacity. On this basis, a single time combined clearing model of power frequency modulation and peak-shaving market is constructed, which takes the minimum clearing cost as the main optimization objective and the maximum remaining peak-shaving capacity as the secondary optimization objective. Numerical examples show that the proposed method has significant advantages over the current sequential cleaning method and the combined cleaning method without considering the consumption of new energy in terms of transaction cost and residual depth peak-shaving capacity. The results show that the method proposed in this paper meets the requirements of promoting the construction of new power system with new energy as the main body in China, and has significant benefits in promoting the reform of power market and improving the consumption of new energy.
Analysis of food nitrogen footprint in Guangdong Province
Authors: Wang Senchao , Xu Meng 
Published: April 2022

Abstract
Global anthropogenic emissions of reactive nitrogen (Nr) from food production and consumption were regarded as main contributors to nitrogen-related pollution. Food nitrogen footprint analysis could help quantify the amount of Nr release to the environment during the processes of food production and consumption, which plays an important role in nitrogen emission management. In this study, the N-Calculator model was used to quantify the food nitrogen footprint in Guangdong province from 2013 to 2017. The results indicated that: nitrogen footprint of anaimal-sourced food was higher than that of others, and with the increase of animal-sourced food consumption in Guangdong province during the research period, the amount of per capita food nitrogen footprint increased from 19.22 to 21.33 kg N, nearly reaching to the amount of developed countries. Food nitrogen footprint of rural residents was larger than that of urban residents in Guangdong province. Exceeding the recommended amounts of animal-sourced food in the dietary guideline, recent dietary patterns in Guangdong province should be further optimized.