bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization and Innovation of SIFT Feature Matching Algorithm in Static Image Stitching Scheme
Authors: Jiao Yuan 
Published: April 2021

Abstract
With the development of computer technology, people can obtain electronic images by a variety of means, but these images often need to obtain a panoramic view of a large field of view from multiple limited field of view images because the field of view is smaller than that of humans, and image stitching technology can be very good Solve the contradiction between vision and resolution. This paper studies the extraction and registration of image feature points and its related technologies, including image feature detection and extraction, point feature-based matching, and image fusion. According to the requirements of matching and image splicing, the feature points with good robustness to image deformation and occlusion are used as image features to indicate that it meets the requirements of image splicing registration. This paper studies and designs an improved algorithm to improve the accuracy of feature points extraction. Further research and analysis of the SIFT operator based on the characteristics of the invariant technology realize that the feature points extracted from the image can be used for reliable matching of an object or scene from different perspectives.
Application of Fuzzy Clustering Maximum Tree Algorithm in Teaching Quality Evaluation
Authors: Xu Bo 
Published: April 2021

Abstract
The evaluation process of school teaching quality is more complicated. The traditional schemes mainly based on manual evaluation or expert evaluation. Due to the strong subjectivity, there is a big deviation between the evaluation results and the real results. To this end, a teaching quality evaluation program based on the largest tree of fuzzy clustering is proposed. After raw data collection, preprocessing, and data mining, accurate and objective evaluation results are finally obtained. Taking the original evaluation data set as the object, construct the fuzzy clustering maximum tree model, and obtain the importance matrix of the data set and the similarity coefficient between the input data variables. With the help of the fuzzy clustering maximum tree model, the importance of each factor in the evaluation of teaching quality can be objectively evaluated. Application examples also verify the superiority of the proposed evaluation algorithm.
Ceramic Molding Based on 3D Printing Technology
Authors: Deng Chao , Zhang Ting 
Published: April 2021

Abstract
3D printing technology can also be described as an increase in the manufacture of materials. In the forming process, no traditional machine tools, fixtures and cutting tools are required. Parts models of arbitrary complex shapes can be manufactured quickly and accurately. In the experimental process, small printers are modified in the extrusion part and printed with water-based alumina slurry as ink. The water-based oxide slurry is mainly water medium and contains only a small amount of organic binder. The influence of pH value, solid content, plasticizer, binder, lubricant and dispersant on the fluidity of slurry is studied. The results show that the slurry has the best stability when the amount of dispersant is 0.4 wt%, plasticizer is 1.0 wt%, lubricant is 4.0 wt%, binder is 1.0 wt%.
Construction of Rural Primary School Teachers’ Professional Ability Promotion System based on Cloud Platform
Authors: Zhou Junhui , Feng Xin , Li Weilong 
Published: April 2021

Abstract
At present, primary school teachers often face the problems of insufficient resources and guidance. Under the cloud platform learning, teaching and research are more efficient. In this paper, based on the cloud platform of rural primary school teachers’ professional ability improvement system as the research object, through the current situation of primary school teachers’ ability, combined with the current intelligent technology, the ability improvement of primary school teachers is studied. The results show that 75% of the respondents believe that their decision-making in the department actually relies on data analysis. 40% of the people think that using the results of data analysis to make decisions improves the importance of their work and their position in the enterprise. Decision making based on data has become the new normal, and the efficiency of primary school teachers’ ability improvement has increased by more than 45%. Similarly, education big data also has a profound impact on teaching decision-making. Cloud platform is the fundamental direction and key focus of teacher leadership in the new era. As a kind of dynamic leadership, teacher leadership has changed due to cloud platform learning. The impact of cloud platform learning on teachers’ leadership is omni-directional. Under cloud platform learning, teachers’ post requirements are higher, cooperation among teachers will be enhanced, teaching improvement will be strong, and teaching improvement and change behavior will be more active.
Intelligent Urban Rail Transit Based on Big Data Analysis and Application
Authors: Sun Wei 
Published: April 2021

Abstract
It is an intelligent information system developed in recent years to manage and control the traffic system with modern and intelligent technology. It plays an important role in alleviating traffic congestion, reducing traffic accidents and reducing energy consumption. This paper mainly studies the smart urban rail transit based on big data analysis and application. According to the characteristics of complex spatial correlation and time dependence of passenger flow, a deep learning model-temporal attention network is proposed, and multi-input multi-output multi-step forecasting strategy is used to solve the problem of error accumulation in long-term forecasting of passenger flow. Experimental results show that the prediction performance of our method in each time step is better than the traditional linear model, machine learning model and deep learning model, and the error is reduced by 7%-9% compared with the benchmark model. Moreover, the multi-input multi-output multi-step prediction strategy can effectively reduce the error accumulation of the traditional iteration strategy.
Network Subgraph Pattern Mining
Authors: Deng Wei 
Published: April 2021

Abstract
Mining local connection patterns in large-scale networks is of great significance for understanding the structure and function of biological networks and online social networks. In practical applications, there are many problems and challenges, such as unknown network structure, large network scale, large number of subgraphs, and large operation of subgraph pattern analysis, which make it very difficult to analyze the local connection patterns of large-scale network graph accurately and quickly. In order to solve this problem, this paper designs a method of crawler and sampling to obtain the topology of the unknown network. At the same time, the deviation introduced in the process of data acquisition is modeled and analyzed, which can be compensated and corrected. A sampling unbiased estimation method suitable for large-scale static graph and high-speed dynamic flow graph is designed. The research results of this paper can be used to accurately and quickly mine and estimate the eigenvalues of local connection patterns, and provide important technical means for computer network traffic monitoring, online social network analysis and biomolecular network information mining.
Analysis of Information Security Risk Defense in the Development of Big Data
Authors: He Yuexing , Ji Jingzhou 
Published: April 2021

Abstract
Big data plays an extremely important role in the development of social economy. The information security of big data is related to the security of people’s personal data and important information of governments and enterprises. This article analyzes the concept of big data and the information security risks under the development of big data, And from the social, technical supervision and other aspects, Discussed information security risk defense methods under the development of big data.
Community Detection Research Based on Line Graph
Authors: Gui Chun 
Published: April 2021

Abstract
Community structure is an important property of complex networks, in which network nodes are tightly split into different groups. In this paper, a new overlapping community detection algorithm based on line graph is proposed. Spectral analysis based on Normal Laplace Matrix of line graph is introduced. We not only make the spectral clustering to be an overlapping algorithm but also define a new similarity between edges by spectral analysis. We test our method on three-community network and Zachary karate club network. The experimental result shows that our method can detect community structure and overlapping nodes effectively. It is worth to note that our method is against undirected and unweighted graphs.
Design and Implementation of Macroeconomic Situation Analysis Application System Based on J2EE Technology
Authors: Yu Xiangjun , Gui Xuefei 
Published: April 2021

Abstract
It is of great significance to analyze the current economic situation, accurately implement policies, and make breakthroughs in key areas. Using advanced information technology, fully using shared economic data resources, using mature basic economic theories and analysis tools, the application system of macro-economic situation analysis is constructed, which can timely and accurately understand the changes of economic information, study and judge the current economic operation situation, crack down on the development constraints, improve the level of public services, and achieve efficient governance It provides real-time technical support. In this paper, combined with work practice, using J2EE technology, the economic situation analysis system construction process of demand analysis, functional design and development are briefly described, and the application prospects of the system are made for the next step.
Construction of University Governance Model Based on Microscope Algorithm
Authors: Bian Fei 
Published: April 2021

Abstract
The evaluation of university governance is a scientific and reasonable comprehensive evaluation to measure the economy, efficiency and efficiency of cultivating talents, which is an important part of the work of universities. With the rapid development of technology field, the method of artificial observation and analysis has been unable to adapt to the status quo of rapidly increasing information, and the automatic acquisition and analysis of microscope algorithm has become an inevitable trend. The purpose of this article is trying to solve the university governance theory and the practice topic, assessment and monitoring algorithm and combined with microscope compiled a set of characteristics of modern university, multi-level, three-dimensional governance performance evaluation index system, including personnel training performance, teaching, research, scientific research, social service performance, logistics support, the performance of five main dimensions, established the model of university governance evaluation algorithm based on microscope, and apply the model to assess the comprehensive performance of a university, a series of scientific conclusions and recommendations, to further improve the comprehensive performance of colleges and universities play an important role, also enriched the theory of university governance evaluation system, It expands the new direction of the comprehensive research in colleges and has important reference value for the future development of the university management mode from the traditional hierarchical management mode to the common governance mode.
Research and Application of Traffic Forecasting in Customer Service Center Based on ARIMA Model and LSTM Neural Network Model
Authors: Zhang Mingjie , Sheng Yan , Tian Nuo , Liu Wei , Wang Hui , Zhu Longzhu , Xu Qing 
Published: April 2021

Abstract
Traffic data is the premise of the number of call center seats. The corresponding agents can be arranged for different traffic volumes to achieve optimal configuration of call center human resources. In this paper, ARIMA model and LSTM neural network model based on time series are used to predict traffic. The traffic of the power call center in Hebei Province is taken as an example to conduct experiments on Python software. The results show that LSTM neural network model has higher prediction accuracy than ARIMA model.
Overall Design of Artificial Intelligence Applications Based on the Electric Power Big Data Platform
Authors: Li Yaodong 
Published: April 2021

Abstract
Electric power big data is a new cross-domain data that appears with the development of smart grid and big data technology, and it is a specific application of big data technology in modern smart grid. This article mainly introduces the overall design of artificial intelligence applications based on the electric power big data platform. This article will explain in detail the construction process of the electric power big data platform and the overall design of artificial intelligence applications. This article introduces the specific significance of power big data as the main technical department of artificial intelligence, from the main links of demand analysis, architecture design, detailed design, and system implementation to the overall process of artificial intelligence application design from demand to realization. First, the overall requirements of the system are analyzed in detail from two aspects: functional requirements and non-functional requirements, and then the business architecture, application architecture, data architecture and technical architecture of the system are designed. Taking the functional modules of the electric power big data platform as an example, the detailed design of the functions is explained from the point of view of the class diagram, sequence diagram, and data model. This paper uses a self-organizing patch antenna calculated based on the power big data platform to search for the lowest voltage standing wave ratio of 1.0068 and the corresponding return loss of 45dB. However, regarding the antenna bandwidth, the self-organizing patch antenna still has the characteristics of a traditional patch antenna with a relatively narrow working bandwidth, and the working bandwidth of 13dB is less than 12%.
Development of Distributed E-commerce System Based on Dubbo
Authors: Ni Yiran , Xie Nan , Huang Yingying , Huang Xin , Chen Weimin 
Published: April 2021

Abstract
China’s e-commerce is developing steadily towards intelligence, extension, standardization, division of labour, regionalization, popularization and internationalization. The competition of domestic e-commerce market has shifted from Tier 1-2 cities to tier 3-6 cities and to rural areas. Online e-commerce platform and offline stores begin to accelerate the industrial integration. This new retail mode will be close to consumers and provide operational efficiency. The technology of e-commerce development platform is also changing with each passing day. According to the idea of service-oriented, the system uses Dubbo, a distributed service framework based on Java, and uses zookeeper as the service registry to provide consistent coordination services for applications. Using the framework of Spring boot and the method provided by TkMybatis, the system realizes an e-commerce online shopping mall system with high concurrency, distribution and high availability e-commerce system - a comprehensive B2C shopping platform. In addition, the system also greatly reduces the coupling of the system, enhances the high availability, and has significant characteristics in maintainability and scalability.
Influence of Artificial Intelligence Technology on Animation Creation
Authors: Liu Qingke , Peng Hui 
Published: April 2021

Abstract
The advent of the era of artificial intelligence has brought unprecedentedly technological changes and breakthroughs to animation creation, which makes animation art creation gradually move towards the field of intelligence, and avoid the cumbersome and intensive work mode, thereby making the creation focus on the creative innovation. This paper deeply discusses the relationship between artificial intelligence and animation creation, and clarifies the advantages of artificial intelligence in improving the efficiency of animation creation. At the same time, it also analyses that the root of animation creation in this period is still human nature, so the creator should create animation based on human nature itself.
The Application of Big Data in the Intelligent Tourism Management Mode is Explored
Authors: Liu Yanshuang 
Published: April 2021

Abstract
In recent years, with the rapid development of the tourism industry and the application of the new tourism management model, the statistics of big data in the tourism industry and the improvement of the technical level of big data in the intelligent tourism management have gradually become the most important tasks and objectives in the intelligent tourism management model. The purpose of this paper is to analyze the current development of tourism management by using big data in the light of the development needs of the current era, and to explain the shortcomings of big data in the current smart tourism application. This paper mainly through the review of relevant literature at home and abroad and the use of multi-mark learning algorithms to carry out experiments to achieve our experimental goal - to study the application of intelligent tourism management model based on the background of big data. The experimental results show that the use of big data technology can effectively carry out the construction strategy of the new intelligent tourism management model in-depth research and analysis, and has defined reference significance.
Development and Application of Simulation Control System of Logistics Palletizing Robot Manipulator
Authors: Zheng Hong 
Published: April 2021

Abstract
Loading and unloading and handling is one of the important parts of logistics. It often occurs in the logistics system, which connects all links in the production process and plays a very important role. The purpose of this paper is to discuss the development and application of the simulation control system of the logistics palletizing robot manipulator. According to the control requirements and functions of the control system, the control system is planned, the PLC control mode and PLC model are selected, the communication system is set, and the I / 0 interface is allocated. The arm parallel mechanism is selected to be in a relatively dangerous position. The control system of the small arm and the rear arm of the palletizing robot is designed. The function modules in the PLC program have achieved the expected purpose. On the premise that the strength and stiffness of the two key components meet the design requirements, the weight of the two key components is reduced by 50% and 10kg respectively. The optimization effect is obvious, which is conducive to improving the structural performance of the palletizing robot, saving materials and reducing production costs.
Leakage Reduction of Water Distribution Network System Based on the Observation Data of Water Leakage and Pressure of Actual Water Distribution Network System
Authors: Cheng Peng 
Published: April 2021

Abstract
As the main way of urban water use, water supply system is an important urban infrastructure. It plays an important role in guaranteeing people’s life and economic construction. In recent years, it has an overall and guiding influence on the city. The monitoring and leak detection of water supply network system has become one of the most important problems in the water supply network system. The purpose of this paper is to explore the leakage reduction of the water distribution network system under the observation data of water leakage and pressure based on the actual water distribution network system. This paper analyzes the different pipe diameter of pressure change on the influence of water leakage, and the effect of different decompression interval to reduce water leakage results show that the leakage and pipeline pressure changes exponentially, it changes with reduced pressure pipe installation of pipe diameter and valve for high same diameter of pipeline, decompression and leakage effect is more effective, for the decompression range of basically the same pipeline, pipe diameter, the greater the effect is more obvious. In this paper, we study a kind of based on the pressure signal and traffic signal of the existing urban water supply pipe network leakage recognition and positioning method, and carries on the simulation of urban pipeline leakage simulation test platform through test analysis, probes into the key technology of this method and improvement, to improve the accuracy and positioning precision of the method to detect leaks. The research results show that the simplest method can be realized and the best effect can be achieved through the summary analysis of existing studies. When the leakage coefficient is set as 1, the water leakage is about 600%, and the pressure value of the leakage node and the pressure monitoring point for 24h is shown. It is obvious that when the lowest pressure is 10h, the pressure value is 300%. Through the analysis and improvement of this method, it can realize the timely identification and positioning of leakage events, reduce economic losses, and guarantee people’s normal life.
Industrial Detection Efficiency Based on Automatic Industrial CT Detection System
Authors: Xu Kai 
Published: April 2021

Abstract
With the rapid development of industrial technology, nondestructive testing technology has been widely used in industry. Automatic industrial CT testing is an effective method for nondestructive testing of internal defects of large workpieces. In the 1980s, China began to study industrial CT technology. However, due to the limited conditions and demand, the automatic industrial CT has not been put into use. In this regard, the purpose of this paper is to explore the efficiency of industrial detection under the automatic industrial CT detection system. In the actual X-ray CT inspection, for the small workpiece with complex internal structure, the best detection method is to detect along the section of the internal structure of the workpiece, so that the collected data can make CT imaging clearer. At the same time, with the acceleration of nondestructive testing automation process, the traditional rotary table X-ray CT detection system has been unable to meet the needs of actual production testing. According to the existing problems, a new automatic CT detection system is proposed in this paper. The system is a CT system based on 6-DOF Industrial robot. It has 6 spatial degrees of freedom, which can flexibly realize the clamping and spatial positioning of parts. It is an effective solution to replace the rotary table for radiographic inspection. And only according to the reasonable design of the clamping device according to the testing parts, it can be directly applied to industrial production, which speeds up the development process of nondestructive testing automation technology. Finally, this paper compares the CT detection system with the traditional industrial detection system, and studies the industrial detection efficiency of the two systems. The experimental results show that the efficiency of CT detection system proposed in this paper is 33% higher than that of traditional industrial detection system. At the same time, the proposed CT detection system provides a feasible solution for the automation of industrial X-ray CT detection.