bluuebunny/crossref_metadata_2025_split huggingface dataset:
Examining the Concordance in the Documented Pressure Injury Site, Stage, and Count in Medical Information Mart for Intensive Care-III
Authors: Zhang Wenhui , Sotoodeh Mani , Ho Joyce C. , Simpson Roy L. , Hertzberg Vicki S. 
Published: September 2021

Abstract
Objectives This study aimed to compare the concordance of pressure injury (PI) site, stage, and count documented in electronic health records (EHRs); explore if PI count during each patient hospitalization is consistent based on PI site or stage count in the diagnosis or chart event records; and examine if discrepancies in PI count were associated with patient characteristics.
Methods Hospitalization records with the International Classification of Diseases ninth edition (ICD-9) codes, chart events from two systems (CareVue, MetaVision), and clinical notes on PI were extracted from the Medical Information Mart for Intensive Care (MIMIC)-III database. PI site and stage counts from individual hospitalization were computed. Hospitalizations with the same or different counts of site and stage according to ICD-9 codes (site and stage), CareVue (site and stage), or MetaVision (stage) charts were defined as consistent or discrepant reporting. Chi-squared, independent t-, and Kruskal–Wallis tests were examined if the count discrepancy was associated with patient characteristics. ICD-9 codes and charts were also compared for people with one site or stage.
Results A total of 31,918 hospitalizations had PI data. Within hospitalizations with ICD-9-coded sites and stages, 55.9% reported different counts. Within hospitalizations with CareVue charts on PI, 99.3% reported the same count. For hospitalizations with stages based on ICD-9 codes or MetaVision chart data, only 42.9% reported the same count. Discrepancies in counts were consistently and significantly associated with variables including PI recording in clinical notes, dead/hospice at discharge, more caregivers, longer hospitalization or intensive care unit stays, and more days to first transfer. Discrepancies between ICD-9 code and chart values on the site and stage were also reported.
Conclusion Patient characteristics associated with PI count discrepancies identified patients at risk of having discrepant PI counts or worse outcomes. PI documentation quality could be improved with better communication, care continuity, and integrity. Clinical research using EHRs should adopt systematic data quality analysis to inform limitations.
Low-temperature nucleation and growth of Zn on Au(111) and thermal stability toward (surface) alloy formation
Authors: Schüttler Konstantin M. , Bansmann Joachim , Engstfeld Albert K. , Behm R. Jürgen 
Published: September 2021

As part of an extensive study of the interaction between Zn and Au in Zn/Au(111) model systems, we have systematically investigated the low-temperature (LT) nucleation and growth behavior of Zn on the Au(111) surface as well as the thermal stability of the resulting structures toward sintering, intermixing, and dissolution by scanning tunneling microscopy (STM) and x-ray photoelectron spectroscopy (XPS). Zn deposition at LT, at 105 K (STM) or 80 K (XPS), leads to nucleation and two-dimensional growth of Zn islands mainly at the elbows of the Au(111) herringbone reconstruction, with a slight preference for island formation at pinched-in (pi) rather than bulged-out (bu) elbows. Local surface intermixing during LT Zn deposition leads to local perturbations of the Au(111) herringbone reconstruction, which results in the formation of additional nucleation sites (edge sites). At higher coverages (&gt;0.11 ML), island coalescence sets in. Testing the thermal stability by annealing experiments, we find the structures to be stable up to about 200 K, while at higher temperatures, 2D sintering, intermixing, and dissolution set in, with subtle differences between pi- and bu-elbow islands. This indicates largely comparable activation barriers for the underlying (surface-)diffusion and exchange processes. Upon annealing to 330 K, all island structures dissolved. Compared with previous reports on the growth of other metals on Au(111), Zn shows a rather high tendency for intermixing and can be considered to be typical of metal deposition systems with comparable barriers for 2D Zn detachment/sintering and intermixing/bulk diffusion.
Topological spin/structure couplings in layered chiral magnet Cr
1/3
TaS
2
: The discovery of spiral magnetic superstructure
Authors: Du Kai , Huang Fei-Ting , Kim Jaewook , Lim Seong Joon , Gamage Kasun , Yang Junjie , Mostovoy Maxim , Garlow Joseph , Han Myung-Geun , Zhu Yimei , Cheong Sang-Wook 
Published: September 2021

Significance
Magnets in which chirality of crystal lattice gives rise to noncollinear spin orders are ideal playgrounds for studies of novel physical phenomena originating from the nontrivial topology of magnetic textures. Most studies have been focused on homochiral materials, while topological magnetic states of heterochiral magnets have rarely been explored. Here, we report a layered chiral helimagnet with highly tunable topological heterochiral states. Tuning the chiral domain density, we have observed a topological magnetic texture that has the form of a spiral unfolding in the radial direction. In weak in-plane fields, this spiral magnetic superstructure transforms into a nonspiral array of concentric rings. Our results open a horizon for studies of tunable topological magnetic textures.
Research on Acoustic Emission Signal Denoising Based on Autoencoder
Authors: Zhou Jun , Yang mei , Yin Yue 
Published: September 2021

AbstractAcoustic emission signal denoising is the premise of acoustic emission signal identification. The traditional filter and wavelet analysis have the problems of relying on prior information and poor adaptability in acoustic emission signal denoising. Therefore, a noise denoising model of acoustic emission signal based on noise reduction autoencoder is proposed. By unsupervised learning training, the noise reduction autoencoder has more stable invariant characteristics, so that the error between the reconstructed signal and the original signal converges to a minimum, thus achieving the purpose of denoising. The denoising experiments are carried out on the basis of processing 3000 corrosive acoustic emission signal samples. The experimental results show that the model has better denoising effect when the number of hidden layer neurons is 400. The proposed DAE model has better performance and robustness than Donoho wavelet threshold denoising method.
Automatic bridge crack detection device based on quadrotor UAV
Authors: Song Xiangbo 
Published: September 2021

Abstract
For the bridge located in deep valley, with high tower and long span structure, the traditional artificial crack detection can not meet the needs of today. In order to solve this problem, a new bridge crack detection equipment is designed based on quadrocopter unmanned aerial vehicle. According to this equipment, the developed system contains: reconnaissance unmanned aerial vehicle system, acquisition and transmission system, crack positioning system, and graphics operations system. Reconnaissance UAV system is improved based on quadrocoper UAV to meet the requirements of flight power, flight control, flight safety and signal stability. In the integrated transmission system, the designed UAV equipped with Hawkeye 5S motion camera, and 4G communication is used to complete the real-time image transmission; The crack location system uses BDS / GPS dual-mode combined single-point positioning module to realize the accurate location of bridge surface cracks; Graphics operations system, based on C++ and python language, designed a superpotent actual-time video streaming graphics operations method, and used median filter, image grayscale, histogram equalization, threshold segmentation and other methods to process the crack image. The designed bridge crack detection equipment can effectively solve the problem of low crack detection efficiency, and realize the intelligence and automation of crack identification. It has practical engineering application value and promotes the development of bridge crack detection technology.
A methodology for removing biofouling of the hull based on ultrasonic guided waves
Authors: Han Cong , Qu Zhigang 
Published: September 2021

Abstract
Marine biofouling is considered as the undesired growth and accumulation of biological organisms on the surface of materials submerged in seawater. Marine biofouling could increase the resistance and fuel consumption of ships. In this paper, a novel method for removing biofouling on ship hull based on cavitation effect and ultrasonic guided waves (UGWs) is proposed, which is eco-friendly and could remove biofouling online. The simulation model is established by finite element method to study the sound pressure distribution on the steel plat. The biofouling removal experiment is designed, which reveals that it is feasible to remove biofouling efficiently with UGWs.
Research on Wavelet Transform Technology and Image Processing Performance Based on Matlab
Authors: Xie Wendi , Zhao Yurong , Wang Yang 
Published: September 2021

Abstract
This paper first introduces the basic concept, principle and application of wavelet transform. Then, the performance characteristics of Haar wavelet, dbN wavelet and symN wavelet, two different threshold shrinkage algorithms Visushrink and Bayesshrink, and two common threshold functions are described in detail. Finally, Matlab software programming is used to realize the simulation of the original image based on different wavelet bases in the influence of Gaussian noise, Poisson noise and salt and pepper noise, different threshold acquisition algorithm, different threshold function, and compare their peak signal to noise ratio (PSNR) value to complete the Image processing performance analysis.
Analysis on the Applicability of High-resolution Remote Sensing Images for Highway Construction
Authors: Li Sitao , Wang Zhaoming , Shao Shegang , Fang Liuyang , Wang Dan , Liu Zhiqiang 
Published: September 2021

Abstract
This paper first analyzes and determines the scope and contents of highway engineering environmental supervision from the aspects of highway engineering composition, construction stage division, impact environmental factors and their characteristics, environmental protection requirements, etc., combines with the characteristics of high-resolution remote sensing images, proposes the construction process and supervision precision requirements for the highway engineering in which environment protection control can be carried out by using satellite remote-sensing images and UAV (unmanned aerial vehicle) remote-sensing images. Through the environmental investigation experiment of high-resolution satellite remote sensing images commonly used in typical road sections, the satellite remote-sensing images meeting the highway engineering environmental supervision requirements are selected through comparative analysis from the perspectives of spatial resolution, revisit cycle, spectral waveband characteristics, environmental supervision precision requirements and image purchase cost rationality.
Infrared image detection of insulators based on Centernet model
Authors: Li Xiaogang , Ku Yongheng , Cui Yaohui , Tian Zhansheng , Sun Wukui 
Published: September 2021

Abstract
The infrared image can reflect the temperature information inside the insulator, which is helpful to realize the follow-up fault diagnosis. However, insulators are usually located in remote areas, and the complex background will affect the accuracy of the algorithm model. Therefore, we established an infrared dataset of insulators. We introduced the Centernet network to infrared detection of insulators, and conducted training and testing on the data set. The results show that our proposed model has a significant improvement of 4% to 5% compared with several mainstream detection models. This can meet the needs of insulator fault detection.
Feature Relation based Graph Convolution for 3D Point Cloud Analysis
Authors: Wang Yang , Xiao Shunping 
Published: September 2021

Abstract
3D point cloud recognition is still a challenge task since the shape implied in irregular points is difficult to capture. Standard convolution is inherently limited for these tasks due to its isotropy about features. In this paper, a novel graph convolutional network is introduced for point cloud classification and segmentation task. The proposed convolution adds an additional layer on the basis of relation-shape convolutional neural network, which can obtain more information and make the representation of point cloud more robust. At the same time, a feature relation method is proposed instead of the coordinate relation used in relation-shape convolutional neural network. The experimental results on challenging classification and segmentation datasets shows that the proposed method can learn discriminating features for recognition and semantic segmentation.
A CA-GCI Based Consensus Fusion Approach for Distributed Sensors with Different Fields of View
Authors: Ma Feng , Lu Huanzhang , Zhang Luping , Shen Xinglin 
Published: September 2021

Abstract
This paper is concerned with the distributed fusion problem of sensors with different fields of view (FoVs). The recently derived CA-GCI method provides solution to the fusion problem of sensors with different Fovs. However, it does not mention about the way that how to share information among more than 3 sensors. Consensus method is suitable for information sharing in distributed network, but it always based on the assumption that the sensors all have the same FoV. Thus the existing method cannot be applied directly. Based on the combination of the consensus method and the newly derived CA-GCI method, this paper proposes a consensus fusion approach for the sensors with different FoVs in a distributed network. Furthermore, this paper derives the minimum iteration steps required to ensure the network consensus is |풩| – 1, where |풩| represents the number of nodes in the networks. Simulation results demonstrate the effectiveness of the proposed approach.
Yolov5-based channel pruning is used for real-time detection of construction workers’ safety helmets and anti-slip shoes in informationalized construction sites
Authors: Shen Xuehui , Li Baojiang , Wang Xichao , Chen Guochu , Lu Junquan , Lin Bin , Zheng Jianming 
Published: September 2021

Abstract
In view of the problems that the application of target detection model in edge equipment occupied too much memory and the operation was slow, a lightweight model based on YoloV5 is proposed to detect the wearing condition of safety helmet and anti-slip shoes. The channel prunning is carried out on the basis of the original model, and the channel with low weight is deleted to reduce the parameters of the model and improve the detection speed. The experimental results show that the recognition accuracy of the network after channel pruning is 93.2%, which is basically the same as that before channel pruning. Meanwhile, the number of parameters is reduced by 63.9%, and the detection speed is 123.45fps. It provides technical support for the development of embedded detection equipment.
Kernel Function Based Mean Matrix Estimation and Its Application to Radar Target Detection
Authors: Cao Xingwei , Cheng Yongqiang , Wu Hao , Yang Zheng , Jing He , Wang Hongqiang 
Published: September 2021

Abstract
The estimation of mean matrix for a set of Hermitian positive definite (HPD) matrices is of fundamental importance to radar target CFAR detection, which can be considered based on a geometric framework. However, false targets can cause large errors in the estimation of the mean clutter matrix. In this paper, we consider the nonlinearity of kernel function and the mean matrix estimation method based on kernel function is designed. In order to reduce the influence of false targets in the estimation of mean matrix, we apply the kernel function to the nonlinear adjustment of the geometric distance. Then, the kernel function based constant false alarm rate (CFAR) detector is designed. Finally, numerical experiments based on simulated clutter data and measured sea clutter data are performed. We come to a conclusion that the method of matrix mean value estimation based on kernel function can restrain the false target in the reference cells effectively.
RETRACTED: Design strategy research on active interactive system for household appliances based on artificial intelligence
Authors: Dai Yiheng 
Published: September 2021

Abstract
In the era of artificial intelligence, active interaction has become an emerging design and development trend, bringing many opportunities and possibilities to the system innovation and experience upgrade of intelligent household appliances. This research firstly analyzed and sorted out documents in related fields such as human-agent active interaction, interaction design in intelligent household appliances and user-centered interaction design, combined with active interaction cases at home and abroad as well as other smart life fields. According to the system process and operating mode, the interaction stages of “perception-display-control-understanding” were divided. And the connotation, performance, valve and opportunity points of design intervention and opportunity points of active interaction in each stage were further analyzed. Finally, this research constructed a smart refrigerator active interaction strategy from the user’s perspective, from the four levels of user needs that are knowable, visible, controllable, and predictable, which could realize the trust relationship of man-machine collaboration and an orderly and active interaction system.
Research on character Action Control Method Based on Multi Phase-Functioned Neural Network and State Machine
Authors: Wang Zhe , Lei Xin , Li Jing 
Published: September 2021

Abstract
Aiming at the situation that the phase-functioned neural network can’t produce natural action or interact with the world poorly in some specific scenes, this paper proposes to divide different states according to the phase information of characters, and train several independent networks with different weights to predict the next frame state of characters. The experimental results show that, while the complexity of the model is reduced, the action generated by this method is more natural and fluent, which has good application value.
Wavelet Analysis-Based Simulation Study Of Small-Current Ground Fault System Routing
Authors: Cai Rui , Zhao Yuchen , Wang Qian , Liu Haorui 
Published: September 2021

Abstract
Small-current grounding is commonly used in medium-voltage distribution networks in China, including ungrounded neutral points, grounding via arc extinguishing coil and resistance grounding. In this paper, the power system modeling simulation of the grounding system via arc extinguishing coil and the transient characteristics when single-phase grounding occurs are studied. The principles and methods for selecting the wavelet basis function in transient component line selection are given. Wavelet analysis of the line current is carried out. It is verified by simulation that the wavelet analysis method in the small current ground fault selection can compare the difference of different lines.
A Joint Positioning Algorithm of TDOA and TOF Based on Ultra-wideband
Authors: Liu Chang , Bai Fengshan , Wu Chunsheng 
Published: September 2021

Abstract
Ultra-wideband (UWB) positioning is a mainstream positioning technology in recent years, and the main positioning algorithms used in UWB based positioning systems are TDOA and TOA. Aiming at the problem of unstable positioning accuracy of TDOA algorithm in traditional UWB positioning system, this paper proposes a joint positioning algorithm of TDOA and TOF based on UWB. The algorithm needs only one time of TOF ranging and combined with the TDOA algorithm, the distances between all base stations and a single tag in the positioning area can be obtained. Compared with the single TDOA algorithm, the algorithm has stable measurement accuracy and can achieve the same positioning accuracy whether the tag is inside or outside the triangle formed by the base station. The simulation results show that the average positioning error of the joint positioning algorithm of TDOA and TOF is less than 10 cm. The algorithm is effective and reliable, and meets the positioning requirements.
Research on the Application of the IPv6 Network Protocol
Authors: Xu Guan 
Published: September 2021

Abstract
With the rapid development of computer network technology, network applications have been very popular in people’s lives and work. The computer network technology includes many aspects, mainly including the communication technology and the computer technology. Although the network application has been relatively impeccable now, although people can contact anyone anywhere at any time through the network, it is still not perfect enough, and there are still great bottlenecks in the network technology. The network protocol plays an important role in the network technology. At present, the IPv4 protocol is more widely used in the Internet than others. Although the IPv6 protocol also has some applications, it is used less widely. For this reason, it is very necessary to research the application of the IPv6 network protocol. This paper mainly studies the main technical performance of the IPv6 network protocol, and introduces its application with specific examples. This paper analyzes the tunnel technology, network address translator technology and dual-stack technology of IPv6. And this paper introduces the basic configuration of the IPv6 address and of the static routing according to a specific type of router.
A sorting method of node based on Eigenvector and Closeness centrality
Authors: Zhu Jingcheng , Wang Lunwen , Wu Tao 
Published: September 2021

Abstract
Accurately identifying influential nodes in a complex network is of great significance to information dissemination. At present, researchers have put forward methods such as Degree centrality, Betweenness centrality, Closeness centrality and Eigenvector centrality, but these methods have certain limitations. There are many factors that affect the results of the node sorting, such as the number of neighbor nodes, node location information, etc. If multiple factors are combined, the proposed method can show more characteristics. First, closeness centrality of neighboring nodes is accumulated to reflect the influence of location information, and then integrated with Eigenvector centrality, the ECCN centrality is proposed to identify the network Influential nodes, this method integrates the path length and the number and quality of neighbor nodes. The SIR propagation model is used to simulate the influence of nodes on multiple real networks, and all centralities are compared with the results of the SIR model. Experimental analysis shows that the proposed method can more accurately identify influential nodes than other methods.
Hardware Circuit Design and Implementation of Digital IF Receiver
Authors: Wang Rui 
Published: September 2021

Abstract
At present, most of the digital IF receivers have bottlenecks in the acquisition and analysis of ultra-high frequency bandwidth signals. At the same time, they have the disadvantages of low resolution and low input bandwidth, which cannot meet the needs of ultra-high frequency signal measurement. In this paper, a high-resolution, high-bandwidth digital IF receiver hardware system is designed based on ADC + FPGA architecture. The front-end analog signal is discretized by two high-speed ADC chips and sent to FPGA to decode the sampling data, and the FFT IP core is called to calculate the power spectrum of the signal. The spectrum data are sent to the host computer through RS485 module and Ethernet chip to display the spectrum image of the original signal in real time, so as to analyze the temperature profile of the target atmosphere.