bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dimensional Analysis on the Variation of Fault Parameters of Rod-shaped Object by using Π Theorem
Authors: Wang Tianxu 
Published: March 2021

Abstract
The calculation of the pressure difference remains an important challenge in engineering. Pressure difference analysis for a typical configuration is presented, which consists of two same cylinders connected with a small cylinder. ANSYS FLUENT is utilized to explore the relationship between pressure difference and several other variables based on the Π theorem by changing the configuration of the model and the initial velocity of the fluid. According to Π theorem, the ΔP/v2p and 1/v are related to each other, which can be fit pretty well with quadratic relation from simulation results. Simultaneously, the radius of the connected cylinder has the greatest influence on the pressure difference. Within a certain range, the smaller the radius, the greater the pressure difference. These results can be guidelines for appliances with such structures in engineering.
Vibration Mode Analysis of ANSYS WORKBENCH-Based Garden Blower Impeller
Authors: Zhao Yaping 
Published: March 2021

Abstract
This paper mainly takes the wind impeller, the main structural component of the blower and suction machine, as the research object, uses Solidworks software to model the blower and suction machine wind impeller, and then uses the finite element software, ANSYS WORKBENCH, to conduct a modal analysis, and obtain the natural frequencies and corresponding vibration modes of the impeller of the blower and suction machine at different speeds. Among them, for a non-zero speed, the corresponding centrifugal force will inevitably be generated when it rotates. Therefore, for the case of non-zero speed, first analyze the corresponding prestress, and then analyze the first five natural frequencies of the impeller at the corresponding speed under the influence of the prestress. Through the analysis, the excitation frequency and speed of the impeller resonance are obtained.
5G Technology-Based Smart Power Distribution Station Simulation Design Specifications and Applications
Authors: Liu Kelong , Jiao Yang , He Chunguang 
Published: March 2021

Abstract
The paper develops a 5G-based simulation design of a smart power distribution room. Through 5G’s large-capacity, high-reliability connection technology, various operating data of the distribution network are collected in real time, so as to achieve a complete overview of the power environment and operating status of various power distribution rooms. Process data collection effectively improves the operation of safe equipment. At the same time, it provides massive basic inversion data for the interactive design of smart power distribution rooms, enhances the ability to control the power distribution room system and its equipment, and enhance the overall reliability of the power distribution room system.
An Optimal Scheduling Method for Numerical Weather Model Assimilation with Dense Observations
Authors: Cheng Xingguo , Zhuang Yuxing , Zhang Jiaqing 
Published: March 2021

Abstract
In this paper, the scheduling problem of dense observation data in a numerical weather model assimilation system is studied and an algorithm of "deal-reveal" is proposed. The algorithm identifies the area where all dense observation stations are located, and then obtains a certain number of grid point on which the value represents the stations quantity overlaid on it. The algorithm selects the stations with maximum value corresponding to the dense observation data iteratively and make the amount of each batch of dense observation stations as more as possible to reduce the batch number, enhances the overall performance of the system finally.
Research on Intrusion Detection Method of Industrial Internet Based on Machine Learning
Authors: Xu Yanfa 
Published: March 2021

Abstract
The mobile Adhoc network (MANET) is being used more and more widely, and the related network security issues have also begun to receive widespread attention. Researching the MANET network’s possible attack methods, the paper proposes an intrusion detection performance evaluation model based on machine learning technology and proposes a comprehensive evaluation index. It compares seven machine learning algorithms’ performance in MANET network intrusion detection, sufficient for building security. The MANET network is of great significance. Use the GloMoSim simulation tool to simulate the MANET network’s normal behavior and the three intrusions of black hole, flood, and packet loss, and analyze the performance of seven machine learning algorithms in various attack situations in various attack situations detail. Our analysis results show that the evaluation model can better reflect the performance of various machine learning algorithms. Multilayer perceptrons, logistic regression, and support vector machines have higher detection rates and lower false alarm rates.
New Media User Behaviour Research Based on Big Data Analysis
Authors: Zhu Zhixuan 
Published: March 2021

Abstract
With the rapid development of diversified business models and market segments in the era of big data, many industries are facing the dual challenges of high customer acquisition costs and churn rates. How to accurately obtain user behavior data has become a top priority. This article uses big data technology to scientifically analyze the ratings and behavior data of new media users. Through new media user behavior analysis, we can accurately discover user behavior characteristics, optimize users’ personalized experience, and bring better new media business operations—basis for decision-making.
Research on Forecasting Volatility Rate of Financial Market based on GARCH and Neural Networks
Authors: Liu Yuanji , Zhang Boyang , Xu Fengchen 
Published: March 2021

Abstract
Aiming at the problem of irregular volatility in financial markets, this paper studies prediction algorithms based on GARCH class model and BP neural network model. In this paper, we compare the prediction accuracy between three kinds of GARCH base models and seven neural networks models. Results show that GARCH class model has a new neural network which can enhance volatility prediction accuracy; GARCH class model better, its variables as input value to neural network combination model help larger; additional introduction similar model variables reduce neural network combination model performance unless the new model variable brings information improvement advantages cover its data redundancy shortcomings.
Capsule Neural Network Based Error Correlation Potential Detection for EEG Topographies
Authors: Wang Qingyu , Wei Lan , Zhou Zhengkang , Wang Zhuoer 
Published: March 2021

Abstract
At present, the detection of error-related potentials is useful for the application of real-time error instruction correction techniques in brain-machine interface online systems. This paper, however, proposes a strategy for error-correlation potential detection based on EEG topographies, which translate the sequence of EEG topographies over time into a spatial position relationship between the features contained in different pictures. As the capsule network incorporates relative position relationships between features, i.e., positional information, a high classification accuracy can be achieved with a small dataset. Experimental evaluation has shown that the proposed method yields significant performance improvements compared to conventional processing methods.
Model to Predict Wartime Equipment Waste Based on Multiple Regression Analysis
Authors: Li Ziqi , Chen Guiming , Li Qiaoyang 
Published: March 2021

Abstract
Predicting wartime equipment waste has not only been a research topic at home and abroad but is also difficult. Traditional research methods emphasize the trend of wartime equipment waste but ignore the effects of influencing variables. This paper discusses the influencing factors of wartime equipment waste and proposes a model to predict wartime equipment waste based on multiple regression analysis. An ordinary least-squares approach is used to estimate the parameters of the model. The significance of the model and regression coefficient is evaluated by the complex correlation coefficient and the t-test, respectively. Ways to optimize and improve the model in future studies are discussed. Expressions to calculate the prediction value and prediction interval are given. This paper establishes three main factors that can be quantified and have a certain sample size: combat time, failure rate, and military input. First, a conventional multiple linear regression model is established. Based on the results of the significance test, the model is iteratively analyzed and optimized. Second, a stepwise regression method is used to screen the independent variables, and a weighted least- square estimation is used to evaluate the influence of changes in the automatic variables on the residual. Finally, a multivariate nonlinear regression approach using a weighted ternary quadratic polynomial model for statistical data is discussed and established. Results from testing indicate that the proposed model has good significance, feasibility, and practical application.
Research on the Construction of Highway Traffic Digital Twin System Based on 3D GIS Technology
Authors: Wang Songchun , Zhang Fa , Qin Ting 
Published: March 2021

Abstract
Under the background of smart city construction, modern information technology has been continuously innovated and developed, which has effectively promoted the development of highway transportation in China, and GIS technology has effectively promoted the development speed of highway transportation informationization in China. As an important geographic information system, GIS technology has obvious technical advantages in traffic information data collection, information data analysis and processing, and promotes the road traffic to develop towards informationization gradually. In order to accelerate the mature development of road transportation, with the support of GIS technology, the road transportation digital twin system is gradually constructed. As a revolutionary technology in the development of highway transportation, digital technology promotes the development of highway transportation in a green, open, and shared direction, laying a solid foundation for the quality of highway engineering construction. Based on this, this article analyzes the overview of GIS technology, explores the digital twin technology, and specifically discusses the modeling process of the road traffic digital twin system, in order to verify the feasibility of the practical application of the road traffic digital twin system.
Research on the Innovation Radiation of Shanghai Science and Technology Innovation Center to the Yangtze River Delta
Authors: Sun Xiaoyan 
Published: March 2021

Abstract
By constructing a regional innovation capability evaluation index system, comprehensively measuring the innovation capabilities of cities in the Yangtze River Delta region, and using the modified gravity model to construct the basic spatial radiation framework for innovation in the Yangtze River Delta region, it is important for Shanghai Science and Technology Innovation Center and 26 core cities in the Yangtze River Delta region. The innovative radiation intensity was measured and analyzed, and further visualized analysis was made with the help of ArcGIS10.5 software. The results show that Shanghai Science and Technology Innovation Center is at the core of the innovation spatial structure of the Yangtze River Delta, but the scope of innovation radiation is relatively small; the spatial distribution of urban innovation in the Yangtze River Delta region is obviously unbalanced; the innovation environment is in the development of urban innovation. The role is increasingly obvious. Based on this, a number of suggestions for the Shanghai Science and Technology Innovation Center to lead the realization of the coordinated development of innovation in the Yangtze River Delta are put forward.
Classificatory Analysis of Disputes on the Right of New Plant Varieties Based on LDA Model
Authors: Zhou Mingyue , Yang Yu 
Published: March 2021

Abstract
This paper takes the judgments between 2011 and 2020 on disputes on the right of new plant varieties from China Judgments Online as the object of research and uses LDA (Latent Dirichlet Allocation) subject model algorithm to analyze the causes and content of these infringement disputes with keyword extraction. With the help of LDA, it finds that China’s disputes over the right of new plant varieties are mainly concentrated in four aspects: the lack of consistent standards for the identification of "new varieties"; the difficulty in responsibility division between the stakeholders involved; the ambiguity in the identification of "propagating materials" and unclear causes of exemption system.
Design of English Translation System Based on Deep Learning
Authors: Ting Yang 
Published: March 2021

Abstract
Intelligent translation software is one of the important tools for people to learn, but the existing intelligent translation system usually needs to be further improved in terms of the flexible application of phrases and the accurate expression of professional vocabulary. The translation system based on deep learning designed in this paper mainly includes professional vocabulary database module, memory analysis module, English translation module and correction module. The professional vocabulary module accurately classifies words related to various disciplines. The memory analysis module compares the professional vocabulary usage in published documents on the Internet to analyze and memorize, so as to recommend relatively accurate professional vocabulary to enter the translation module. Need to enter the correction module to complete the correction of grammar and phrases, and finally complete the translation task with higher accuracy.
Coal Price Prediction based on LSTM
Authors: Pan Sitong 
Published: March 2021

Abstract
The price of coal has always been the focus of the government and is affected by various factors. This paper uses days, weeks and months as time units to establish a Long-Short Term Memory Recurrent Neural Network Model (LSTM RNN) to predict the change trend of coal prices. The accuracy and sensitivity of the model are tested, and the results show that the model is stable and has high accuracy
An Hotspot Prediction Approach of Scientific Research Based on Autonomously Evolutionary Learner
Authors: Ma Yan , Zou Lida , Han Yingkun , Ma Lei 
Published: March 2021

Abstract
Hotspot prediction of scientific research is a new application in information domain. Big-data analytics technique is a critical way of improving prediction efficiency. Scientific researching data have a high dimension and are from different domains. Just using a single learner is hard to solve the problem. In the paper we adopt several deep neural networks to find the proper data dimension and network structure. The genetic algorithm is introduced as well to fasten the whole prediction. The proposed approach performs well in accuracy ratio and recall ratio compared with the benchmark algorithms. The genetic algorithm and pruning method largely improve its performance as well.
A Review of Main Eye Movement Tracking Methods
Authors: Li Zhaowei , Guo Peiyuan , Song Chen 
Published: March 2021

Abstract
The study of eye movement has been last for centuries. Over the past decade, scientists have developed many new eye-tracking methods. During that same period, technological innovations have made eye-tracking units more affordable. The article provides a systematic review on some main eye-tracking methods. This paper also includes the factors that may influence the eye-gaze tracking and the application of gaze estimation in many areas. In this article, we provide information on eye tracking in hopes of improving the quality and reporting of eye-tracking research in communication.
Research on the Application of Computer Network Technology Under the Background of Artificial Intelligence Cloud Technology
Authors: Meng Qingwei 
Published: March 2021

Abstract
On the basis of timely processing of network situation information, effective responses to network attacks with dynamic evolution characteristics are the main problems faced by cyberspace security defines mechanisms. The application of artificial intelligence technology can strengthen the intelligent characteristics of this system. This article mainly starts with the related concepts of artificial intelligence technology and cyberspace defines, and explores the application measures and development trends of this technology in cyberspace security defines.
Research and Implementation of Network Security Management Based on Virtualization Technology
Authors: Ni Zhimin , Zhao Fan 
Published: March 2021

Abstract
With the rapid development of the Internet application, virtualization technology and network security management, combining the resources of science and technology information has become one of the network security management subject, because information system is becoming increasingly complex, software and hardware not compatible, the network security and the waste of resources seriously influence the efficiency of the information office, at the same time also increased the complexity of the network operation and maintenance and cost and energy consumption. This paper, by using virtualization technology to construct the virtual network, optimize the integration of existing server resources, saving operation and maintenance costs, reduce energy consumption, improve equipment utilization. Using the virtual firewall, virtual routing and virtual intrusion detection and other new technology was used to construct the network security system.
Research on lightweight web intrusion active defense key technology and visual measurement model based on dynamic ip black list
Authors: Zhao Fan , Ni Zhimin 
Published: March 2021

Abstract
In view of the existing passive detection and prevention methods and lack of commercial products are expensive and complex deployment problem of a simple and fast active defense technology of WEB dynamic real-time active defense, in order to solve the problem of attack and defense for WEB server. Firstly, based on reverse proxy massive WAF logs, the mathematical model of user access behavior is established, and the behavior characteristics of malicious WEB attacks are studied through data mining analysis. Then, a threat factor algorithm and a dynamic IP blacklist generation algorithm are designed based on these features and a custom rule base. Finally, based on visual measurement model, D3 WEB visualization technology is used to monitor and measure WEB intrusion. The technology reduces the false alarm and false positive rate of active defense, improves the defense effect and execution efficiency, and ensures the quality of normal network communication.
Design and Numerical Simulation of a Ball Cutting Type Energy Absorber Device
Authors: Hu Zhiqing , Guo Liming , Zhang Yuheng 
Published: March 2021

Abstract
This paper is verified by numerical simulation and experiment. Based on the principle of energy absorption in metal cutting process, this paper presents a new type of energy absorption structure, which can improve the collision performance of urban rail vehicles. The structure is composed of solid energy absorption tube, hard ball, anti-crawling board and mounting board. Based on the nonlinear dynamic simulation theory and the explicit algorithm of finite element software ABAQUS, the finite element model of the structure of the cutting type energy absorber was established, and the energy absorption process was simulated. Based on the verified simulation model, the influences of the design parameters such as the cutting depth and the number of balls on the energy absorption process are analyzed. It is found that the design parameters affect the cutting force and energy absorption, and the structure has a good energy absorption effect during the collision.
Establishmen of Real-time PCR for detecting Bibersteinia trehalosi for rpop gene
Authors: Wang Xiang , Luo Yilin , Zhou Lijun , Luo Zidan , Wang Yin , Yao Xueping , Luo Yan , Yang Zexiao 
Published: March 2021

Abstract
Bibersteinia trehalosi is a zoonosis bacterial species, There are few reports of the disease in our country, and there is no fast, sensitive and efficient detection method have been developded. Therefore, the Quantitative Real-time PCR (q-PCR) for detecting Bibersteinia trehalosi has been established, and the specific primers desigened based on the conserved sequence of Bibersteinia trehalosi rpoβ gene, the method was constucted by optimizing reaction conditions and then subjected the sensitivity, specificity, reproducibility, and clinical samples test. The results indicated a good linear relationship when the concentration of standard substance ranged between 1.20×101~1.20×105 copies/μL. Inaddition, the minimum detectable concentration was 1.20×10−2 copies/μL. There are no cross reaction with 20 kinds of bacteria and viruses. All of the CV values of intra-groups and intra-groups were less than 3%.The results showed that the method has the advantages of high sensitivity, strong specificity, good stability, high accuracy and rapid detection. It can be used for early diagnosis of infections in Bibersteinia trehalosi, as well as rapid detection and quantitative analysis of samples.
Comparisons of Subgrid-Scale Models for OpenFoam Large- Eddy Simulation
Authors: Feng Zhipeng , Qi Huanhuan , Huang Xuan , Liu Shuai , Liu Jian 
Published: March 2021

Abstract
OpenFOAM is a free, open-source software package that can be used for the solutions of computational fluid dynamics and simulation of various fluid flow processes. Nevertheless, OpenFOAM still lacks default settings and a large number of different numerical schemes and turbulent models should be validated. In this paper, the unsteady flow around a cylinder (Re=3900) is calculated by the large eddy simulation of OpenFOAM. The predictions include the drag and lift coefficient, the pressure distribution around the cylinder, the velocity distribution and Reynolds stress distribution in the wake region, as well as the prediction of the recirculation length and separation angle. Thanks to several simulations, these five subgrid-scale (SGS) models are compared and studied: The Smagorinsky SGS model, wall adaptive local eddy visibility SGS model, dynamic SGS model with Lagrangian averaging, dynamic one equation eddy visibility model, one equation eddy visibility model. The numerical results are verified with the published experimental data.
Prediction of the real estate industry economics based on LSTM model
Authors: Zhang Taoen , Fang Baojun 
Published: March 2021

Abstract
The economics of real estate industry has been seriously affected by the 2019-NcoV. Therefore, this study analyzed the changes of real estate industry and LSTM model was applied to predict the price of real estate industry. The error analysis was done to test the accuracy of model and the result indicated the model established in this paper has high accuracy and meaningful for practical application.
Research and Analysis on the Reliability of Smart Energy Mete
Authors: Chen Jintao , Zhao Fang , Zhu Wenjun , Huang Liang , Zhou Qiang , Shan Zhaoguo , Liu Liangtao 
Published: March 2021

Abstract
Analysis and study the reliability theory of smart electric energy meters, as well as reliability analysis indicators and fault distribution rules. Starting from the distribution law of fault data and reliability indicators of fault life, the reliability of electric energy meters is analyzed by collecting field maintenance data. The reliability model is used to study the failure modes, causes and effects of smart electric energy meters. The research and analysis of the reliability of the smart electric energy meter ensure the normal operation of the intelligent electric energy meter and improve the stability and reliability of the intelligent electric energy meter.