bluuebunny/crossref_metadata_2025 huggingface dataset:
Hierarchical feature similarity integration method for data sets based on deep learning
Authors: Xiaoli Yu
Published: August 2021

Under the background of the rapid rise of open-source software and the gradual popularization of various software development tools, a large amount of development activity data has been accumulated on the Internet. In the process of using these data to construct data sets, due to their poor traceability and narrow application scope, the quality of data in development activities is not high and the accuracy of analysis results is not high. The application of the hierarchical feature similarity integration method of data sets can make the multi-version and multi-level development smoother and more orderly. In this paper, a hierarchical feature similarity integration method based on hierarchical deep learning is proposed for data sets. Firstly, the dynamic mesh partitioning method is used to divide the sparse and dense regions in the space, which reduces the scale of data detection and shortens the execution time of detection. Then, through the hierarchical deep learning process, the professional knowledge and the distribution information of data attribute value are fused to realize the detection of discrete data in the database. Experimental results show that this method can accurately complete the detection of discrete data in the database in a relatively short time, and has more application advantages than traditional methods.
Research on Performance Monitoring System and Damage Identification Method of Civil Engineering Structure
Authors: Pan Haozhe , Yan Xingpei
Published: August 2021

In order to meet the increasing living needs of urban residents, China’s construction industry began to promote super high-rise buildings and long-span structures in an all-round way, and strengthened the research on performance monitoring and damage identification of civil engineering structures, so as to master the basic performance of structures and put forward effective solutions to the problems existing in their practical application. On the basis of understanding the current monitoring problems of civil engineering structures, according to the artificial neural network method of structural damage identification based on the statistical characteristics of structural dynamic response, this paper makes a concrete research from two aspects: single damage and multiple damage.
A double network structure anti-jamming algorithm based on deep reinforcement learning
Authors: Wang Yifan , Liu Xin , Wang Mei
Published: August 2021

At this stage, when dealing with intelligent jammer with environmental cognition, most anti-jamming methods only consider how to maximize avoidance of it. However, the user’s previous waveform and frequency actions have been leaked. As the intelligent jammer continues to learn, the performance of anti-jamming will decline. Existing literature has proposed the idea of hidden anti-jamming. The user uses rational communication action-making to prevent the jammer from obtaining the information of the user so that the jammer cannot target the user for jamming, but its model is relatively simple and cannot cope with complex jamming types. This paper designs a kind of decision related judgment module between jammer and user based on Generative Adversarial Networks (GAN), which uses the environment state received by the user to reversely infer the user’s decision whether to avoid jammer’s sense. Specifically, the neural network is used to fit the environment state under known user information, and calculate the loss between it and the real environment state to evaluate whether the user’s decision is to avoid jammer’s sense. Then, this paper proposes a deep reinforcement learning algorithm with double-network structure, which can deal with various types of complex jamming while ensuring anti-jamming performance. The final simulation results show that the improved deep reinforcement learning algorithm proposed in this paper can improve the anti-jamming performance, achieve hidden anti-jamming, and have a wider range of applications.
Parallel performance analysis of nonlinear equations algorithm based on hybrid genetic algorithm
Authors: Yang Yunwen
Published: August 2021

For a long time, people have done a lot of research on nonlinear equations in theory and numerical calculation. In this paper, the basic theories and methods of genetic algorithm and traditional algorithm are expounded, and the advantages of genetic algorithm and quasi-Newton algorithm are analyzed, thus a new hybrid genetic algorithm for solving nonlinear numerical problems is proposed, and the effectiveness of the algorithm is verified by numerical examples. The hybrid algorithm gives full play to the group search and global convergence of genetic algorithm, and effectively overcomes the initial point sensitivity problem of classical algorithm At the same time, the classical algorithm is introduced into genetic algorithm for local search, which overcomes the shortcomings of slow convergence speed and poor accuracy of genetic algorithm. The algorithm in this paper provides an effective way to solve nonlinear equations from another angle.
Research on Online Autonomous Learning Support System of Advanced Mathematics Based on Feature Extraction Algorithm
Authors: Su Li
Published: August 2021

One of the key problems in researching and developing online autonomous learning support system of advanced mathematics which adapts to learners’ personality characteristics is to acquire learners’ characteristics. According to the theory of teaching structure and network teaching mode, based on analyzing the syllabus and teaching materials of higher mathematics, this paper puts forward the overall goal and design principle of the system, redesigns the teaching expression form, and designs an online autonomous learning support system of higher mathematics based on feature extraction algorithm. In the design of the system, the teaching idea of taking teachers as the leading factor and students as the main body runs through, so that students can arrange their own study plans, actively explore knowledge, actively participate in interaction and get feedback in time, thus improving the learning effect.
Big data cloud platform server load balancing algorithm based on improved chaotic partition algorithm
Authors: Xiang Hao , Zhang Ting , Li Zhewen
Published: August 2021

Due to the heterogeneity of big data cloud platform and the uneven distribution of data between cloud servers, when cloud server cluster processes a large number of tasks, the node load is often uneven. To solve this problem, a load balancing algorithm based on improved chaotic partition algorithm for big data cloud platform server is proposed. According to the statistics of the average resource consumption of various services provided by the cluster, combined with the running time and resource occupation of tasks on the server, the total remaining task load of the server at a certain time point is predicted, so as to obtain the actual task load status of the node, and correct the task load in time. Experiments show that the load balancing algorithm of big data cloud platform server based on improved chaotic partition algorithm can effectively balance the load of multi task heterogeneous cloud servers, and has high feasibility, Then, based on this improved load balancing algorithm, we can also extend it to the application of multi-objective algorithm, such as robot path planning, target allocation scheduling algorithm and so on. There will be similar and reasonable performance compared with the same period last year.
Research on Network Intrusion Detection Method Based on Deep Learning Algorithm
Authors: Liao Xinhai , Xie Jianguo
Published: August 2021

Information security is very important in enterprises. Under the tide of modern network informationization, especially intrusion detection is facing great challenges. The rise of technologies such as big data and artificial intelligence, on the one hand, helps to strengthen information security, on the other hand, it also brings great challenges to information security. Everything has two sides, and the Internet is no exception. While the network has brought us a richer and faster life, the problem of network security has become increasingly prominent, and network security risks pose new challenges to the fields of politics, economy, culture, national defense, ecology and society. The active defense strategy using intrusion detection technology can actively discover attacks when they occur or attempt to attack, realize real-time response, and provide real-time protection for network systems. This paper starts from the field of intrusion detection and combines deep learning technology to design an efficient and intelligent intrusion detection model which can be used in the field of network intrusion detection.
Automatic keying algorithm for multi-category target recognition
Authors: Mao Liping
Published: August 2021

In this paper, through an in-depth study of the automatic keying algorithm for target recognition and using multi-class algorithms for its analysis, a saliency detection model based on the hypercomplex Fourier transform is proposed, which can quickly search for information related to the current task requirements. The problem of sample imbalance in deep neural network training exists, the module is used many times to fuse multi-scale features, the loss function uses weighted cross-entropy loss, and the weights are determined according to the proportion of samples in the training sample, which can solve the problem of the model tends to fit the category with more samples. After analysis, the proposed hyperspectral image fast feature enhancement algorithm based on guided filtering can effectively solve the problem of “the same object, different spectrum”, and the classification accuracy of small sample high-dimensional data is improved greatly. At the same time, the complexity of processing high-dimensional data such as hyperspectral remote sensing images is greatly reduced. The experimental results show that the processing time of the proposed fast feature enhancement process for hyperspectral remote sensing images in this paper decreases than that of the direct use of guided filtering.
Graph algorithm optimization techniques for high-throughput computers in weakly supervised scenarios
Authors: Mao Liping
Published: August 2021

In this paper, a weakly supervised recognition model is used to provide approximate position constraints for object transformation in the source and target domains, and to guide the generator to generate images that differ less from the real ones. The cross-modal synthesis technique is incorporated to take advantage of the data differences between different modalities to constrain the mapping functions, thus ensuring that the learned mapping functions are always performed on the paired data. The full version of the proposed method achieves a 3.6 % performance improvement compared to the benchmark network. Richly controlled experiments demonstrate the effectiveness of each improvement. It is found that the intrinsic correlation of query graphs provides complementary information for better performance of semantic segmentation with few samples, and the proposed network structure in this paper effectively exploits this information.
Design of Networked Intelligent Translation System Based on Machine Learning Algorithm
Authors: Hong Liu
Published: August 2021

China’s social and economic development is relatively rapid, and China’s opening to the outside world is further expanding. Under this background, the demand for foreign language professionals is also expanding. This paper designs a networked intelligent translation system based on machine learning algorithm, and proposes a cross-language information extraction method based on bilingual word representation. The learning of bilingual word representation can be divided into two stages: unsupervised and supervised. Capturing Chinese and English bilingual semantic information. The cross-language information extraction method based on machine learning algorithm reduces the impact of translation errors and language gaps on cross-language classification performance, obtains effective bilingual semantic information and annotation information, and improves the cross-language information extraction performance. The test results show that the designed automatic English translation system can effectively and quickly realize intelligent English translation of memory-assisted long characters, with high data recall rate, good accuracy and reliability, and good system compatibility, which is worthy of popularization and practical application.
Application of Computer Control System in Electrical Automation
Authors: Wang Xinxiang
Published: August 2021

With the improvement of information technology, China has continuously promoted the development of computer control system of electrical engineering and electrical automation in the current development process. In enterprise production, computer technology can be integrated into electrical engineering and electrical automation to realize real-time monitoring of controlled objects. Electrical engineering automation belongs to the field of modern electrical information, which is widely used in military, aerospace and industry. However, due to the late formation of China’s industrial system, there are still some problems in electrical engineering automation, resulting in serious energy consumption problems. In order to improve the application level of electrical automation control system and create greater benefits for enterprises and society, it is necessary to strengthen the application research of electrical engineering and automation computer control system. Based on the application status of computer control system in electrical automation, this paper discusses the application strategy of computer control system in electrical engineering and electrical automation to promote the further development of electrical engineering technology in China.
Research on Improvement of Computer Software Technology Based on Internet Technology
Authors: Luo Weizhang , Lin Jie
Published: August 2021

The rapid development of computer technology is an important symbol of human development and progress. With the continuous improvement of informatization, modern society has entered the era of big data. People’s daily life, work and study are inseparable from the assistance of computer software technology, and the social progress, the development of science and technology, and the trade of enterprises are also inseparable from the support of computer software technology. Based on the background of Internet era, this paper focuses on the analysis of the concept, classification and application of computer software technology in the current environment, and explores the development direction and positive influence of computer software technology. The application process of computer software development technology needs to find out the important factors that restrict the development of computer software development technology according to the actual situation, and constantly improve and innovate, so that computer software development technology can meet the needs of the development of the information age, and better provide safe and reliable technical support for China’s economic development and social progress.
Development and design of three-dimensional display system of visual design works based on virtual reality technology
Authors: Zhang Kai , Wang Yu
Published: August 2021

Exhibition design involves many fields, including many disciplines, such as design psychology, visual communication, ergonomics, etc. Therefore, there are many factors to be considered in the design process, that is, to transform ideological intentions, display information and design views into images that can be received visually. Virtual reality technology is a computer simulation technology that can create and experience a virtual world. It uses computers to generate an interactive 3D dynamic scene, and the simulation system of its physical behavior can immerse users in the environment. In this paper, the 3D model is combined with the physical image, and the visual design works are displayed in a virtual way by using Cult3D technology and virtual reality, so that the visual design works and their scene environment to be displayed can be better presented to users in 3D form, and the realism and visual beauty in the process of product browsing experience can be enhanced through humanized interactive design and artistic interface design. In the development process of the three-dimensional display system of visual design works, the cost accounting and the actual operation effect of the system have been considered, which has met the actual needs of users and has certain theoretical and practical value.
Construction and experimental research of multifunctional hybrid powertrain test bench
Authors: Yan Yi , Chen Bin , Liu Zhi Yang , Huang Bo
Published: August 2021

With the development of hybrid electric vehicles, the demand for test benches is becoming more and more vigorous. Based on the traditional engine test bench, this paper builds a multifunctional hybrid powertrain test bench by matching appropriate equipment such as battery simulators, power analyzers, fuel consumption meters, and air flow meters. The test bench has the characteristics of modularization, flexibility, and multi-function. It can be used for testing single engine, single generator and hybrid power system. Finally, the range extender produced by a domestic manufacturer was used as the test object, and the endurance test was carried out on the modified test bench. The test further verified the reliability and feasibility of the multifunctional hybrid powertrain test bench.
Research on Application of Computer Technology in the Optimization of Department Information System
Authors: Shen Haohui , Wang Juan
Published: August 2021

Aiming at the problems of weak financial management foundation, lack or failure of internal financial accounting management, etc., the characteristics of financial management of SMEs are analysed. The article develops a reasonable financial enterprise management system, which can promote the long-term development of the enterprise. The graphical user interface developed based on SWT realizes the main functions of enterprise financial management. Practice shows that the system is not only easy to operate, but also has a friendly interface. It is a flexible, reliable, fully functional, and practical information management system.
Research on Advantages and Difficulties of Implementing Full-cost Comprehensive Information System in Power Engineering
Authors: Wen Yanping , Su Xiaoxue , Zhang Rong , Wen Wei , Wang Zheng
Published: August 2021

The article analyses the current status and existing problems of the current pricing model of electric power projects in our country, introduces the advantages of the full-cost comprehensive unit price method, and demonstrates that the implementation of the full-cost comprehensive unit price method for project pricing is simple, operability, and meets market needs. The market pricing principle is more conducive to the reasonable determination and effective control of the project cost. Finally, it expounds the difficulties that need to be studied to solve the current implementation of this model, and proposes corresponding countermeasures. At the same time, we applied the full-cost comprehensive unit price to actual cases, and demonstrated the effectiveness of the full-cost comprehensive unit price in power engineering management through modelling and simulation.
Large-Scale Scientific Research Instrument Resource Information Sharing Platform through O2O Mode
Authors: Bao Jidong , Su Hailong , Yin Xinhong , Meng Jie , Liu Fei
Published: August 2021

Through the collection and integration of scientific instrument resources and scientific research services across the province, a scientific instrument public service system based on the O2O model will be constructed. The system takes the one-stop retrieval of scientific and technological resources as the hub, and provides accurate and convenient intelligent services for scientific and technological information for universities, scientific research institutes, key laboratories, high-tech enterprises, incubators and other units, realizing the co-construction and sharing of scientific instrument resources, Improve the utilization rate of scientific and technological resources, effectively improve the level of comprehensive sharing and efficient use of scientific instruments.
Design and Research of Wuhan Urban Railway Network Simulation Calculation Information System Utilizing Big Data
Authors: Zou Han , Liu Shujun
Published: August 2021

Based on the big data-assisted algorithm, the paper uses the dynamic relationship data of railway passenger flow as a research case, adopts the urban network chain model, and uses the mobility and agglomeration of railway passenger flow between cities as the research entry point to analyse the network connection strength of provincial cities and spatial organization structure characteristics. At the same time, it puts forward the idea of using Wuhan’s rich railway resources as the framework of urban railway network passenger flow intensity simulation calculation system, demonstrates the necessity and feasibility of its construction, and puts forward an implementation plan based on the characteristics of the railway network and urban development for the reference of relevant decision makers.
Systematic Research on Measuring Acceleration of Gravity by Laser Interferometry
Authors: Dang Chun , Li Jing , Tang Jie
Published: August 2021

Gravity acceleration is an important physical quantity, and its precise measurement results have important applications in practice. According to the principle of measuring gravity acceleration in college physics experiment, a scheme of measuring gravity acceleration by laser interferometry is designed, and the main sources and sizes of experimental errors are analyzed and calculated. Compared with the common simple pendulum method and falling body method, the theoretical results show that our measurement method has higher precision and is feasible to accurately measure the acceleration of gravity.
Grey Theory and AHP Applied in Performance Evaluation of Tactical Communication Network Information System
Authors: Chen Qi , Yi Maoxiang , Man Xin
Published: August 2021

The tactical communication network is the core technology of digital battlefield communication. Research on the interference effectiveness of tactical communication networks can ensure that the information services of tactical communication can be transmitted in real time and reliably. The article analyzes the interference effectiveness evaluation index system of tactical communication networks, uses indicators such as route discovery time, throughput, delay, and packet loss rate to evaluate network interference effectiveness, and proposes an effectiveness evaluation method based on AHP and gray theory. Finally, the networking software OPNET is used to conduct simulation experiments to obtain the experimental data before and after the interference, so as to obtain the effective evaluation results of the interference effectiveness of the tactical communication network. The research results have theoretical guiding significance for the evaluation of the interference effectiveness.
Research on Trend Forecasting System Utilizing Big Data Network and Information Technology
Authors: Xing An , Yan Shi , Yang Zang , Yan Lu , Yue Ren
Published: August 2021

In this paper, we take big data, the GDP of the United States from 1992 to 2020 as the research object. Through SPSS software analysis and descriptive statistics, we can compare the GDP of Biden and Trump during their tenure. Using big data’s analytical technology, the line chart we get visually shows that the election of different candidates will shape different strategic patterns of global economic and financial development. A new comprehensive factor W is obtained from the data that directly reflect the overall GDP of the United States. Finally, by establishing a forecasting model, we can find out the comprehensive event factors that will occur due to different political positions and policy plans between Biden and Trump in the future. In the end, we use the results of big data’s analysis to show that Biden’s economic plan may increase US GDP growth by 1.2 percentage points in 2021, push GDP growth to 4.9%, and help the US economy recover the economic losses caused by the epidemic in mid-2021.
Food Supply System Analysis Method and Information System Establishment with Quantitative Analysis
Authors: Chen Yu , Zeng Yanxi , Du Jiatao
Published: August 2021

Because a vast global system of national and international food producers and distributors controls the lifeblood of global food, our global food system is unstable even in well-functioning parts of the world. Therefore, it is particularly important to establish a food system that takes efficiency and profitability as the main considerations and allows for relatively cheap and efficient food production and distribution. In this paper, on the basis of the existing evaluation indicators of grain system, we establish a multi-level index system through principal component analysis. After that, we integrate the index into the grain system index through entropy weight method and coefficient of variation method, and establish a comprehensive evaluation model. On the basis of the evaluation model, the index is calculated twice, and the optimization model is established combined with the multi-objective programming algorithm. The simulation results show that the two weights of energy efficiency and per capita cultivated land area account for a large proportion in the optimized system.
The Systematical Solutions About Victoria’s “Fire Emergency Drones” Quantity and Location Solutions
Authors: Niu Zhe
Published: August 2021

For more than a year, there have been severe fires in almost all Australian states, with the eastern state of Victoria in particular. This paper aims to address three specific problems in “fighting wildfires” with three mathematical models. On the basis of analyzing the data, Model 1 obtains the specific fire situation of more than 5 months at the end of 2019. Since the occurrence of fire follows Poisson distribution, we use Monte Carlo method to generate random numbers that meet such distribution for simulation. Finally, the entropy weight method + Topsis method was used to determine the optimal combination: 13 SSA UAVs and 19 repeater UAVs, and the cost was $242,000. Model 2 needs to consider how equipment increases under extreme fires. To get the worst fire scenario in 10 years, we used cellular automata to simulate the occurrence, spread and extinction of fires. For Model 3, We use the improved genetic algorithm, by means of crossover, combination mutation, position mutation and displacement mutation of genes are carried out to select a certain number of excellent individuals. The algorithm balances the performance and accuracy, and finally obtains that the layout of the UAV should be concentrated in the east side of Victoria State as far as possible. In addition, we also analyzed the robustness and sensitivity of the model, it turns out that the model is robust.
Information System Construction and Research on Preference of Model by Multi-Class Decision Tree Regression
Authors: Mao Zhanpeng , Zheng Tingting , Lian Zongqiang
Published: August 2021

Through the construction of customer asset allocation decision preference model based on machine learning, the input variables are set as demographic variables, family economic conditions, personality psychological characteristics and risk attitude, and the output variables are customer asset allocation decision preference choices. machine learning algorithms such as decision tree and support vector machine are used to predict customers’ asset allocation decision preference, and compared with traditional prediction methods. The results show that the machine learning algorithm can predict customers’ asset allocation decision preference to a certain extent, and its performance is more effective than the traditional prediction method. Combined with the sample data, this paper analyzes the impact of venture capital on the growth ability of small and medium-sized enterprises, uses entropy method to evaluate corporate growth ability and corporate governance respectively, and further establishes a regression model to verify the intermediary role of corporate governance. The structured macro-prudential monetary policy rules with different response coefficients to the leverage ratio of different enterprises can effectively improve the level of social welfare, and the combination of optimal response coefficients is different under different kinds of shocks. Venture capital involvement in small and medium-sized enterprises can significantly improve the growth ability of small and medium-sized enterprises, and the support of venture capital can help enterprises improve the level of corporate governance. The experimental results show that the scorecard model constructed by the proposed method has good stability. The more obvious the improvement of the level of social welfare caused by the structural macroprudential monetary policy rules. The accurate prediction of asset allocation decision preference helps to improve customer decision-making efficiency and satisfaction, and reduce the labor costs of financial institutions..
Research on Opinion Target Extraction and System Information Collection Analysis for Reviews
Authors: Gao JianNan , Zhao Yanyan
Published: August 2021

Though the study of opinion target extraction of movie review, this paper proposed a method for opinion target extraction of movie review based on deep learning, and analyzed its emotional polarity. Finally, the experimental results were displayed in a visual manner to help users judge the details of the movie content. In this paper, by establishing a bidirectional short-term and short-term memory network model, the opinion target extraction task is translated into a sequence labeling task, which improved the accuracy of opinion object extraction. This paper crawled and organized the Chinese movie review corpus from the Internet and the experimental results proved the effectiveness of the proposed method.
Enhancing Data Applied in the Research of Partial Discharge Systematic Diagnosis
Authors: Yang Yi , Bai Demeng , Liu Meng , Dou Huiling
Published: August 2021

The existing problems in the current partial discharge PRPS sample enhancement method have been summarized in this artcle, and a GIS UHF partial discharge data enhancement method has been proposed which is based on noise coupling, Gaussian blur and so on. It solves the problem of unable to collect a large number of defect maps and form a sample set due to the lack of GIS partial discharge cases, which limits the application of intelligent algorithms such as deep neural networks. This partial discharge PRPS sample enhancement method has been proved through application that it can effectively enhance the partial discharge sample set, make the samples evenly distributed, and meet the training needs of intelligent algorithms such as deep neural networks. The intelligent diagnosis algorithm trained using the enhanced sample set has a high diagnostic accuracy rate of 95%, which has practical application value.
Review of data scraping and data mining research
Authors: Wang Yuguang , Zhu Dengyun , Zhang Bin , Guo Qi , Wan Fucheng , Ma Ning
Published: August 2021

In recent years, with the advent of the era of big data, the importance of data has also become more prominent. This article introduces the characteristics of today’s Internet data from the background of big data, and the main method of data scraping-crawlers. In addition, the concepts of data mining, as well as hotspots and trends are briefly introduced. Highlights the importance of data scraping and data mining in today’s Internet field.
Realization and optimization of Chinese syntactic analyzer based on PCFG
Authors: Zhu Dengyun , Zhang Bin , Guo Qi , Wang Shuang , Wan Fucheng , Ma Ning
Published: August 2021

As a basic research work, syntactic analysis is also a key technology in the field of natural language processing, and is the basis for deep understanding of language. The syntactic analyzer is an important tool for syntactic analysis. The Probabilistic Context Free Grammar (PCFG) model is the basic model of most parsers with excellent performance. Good effect. This article integrates named entity clues into PCFG-based Chinese syntax analysis models, completes joint learning and decoding of named entity recognition, syntactic analysis, and implements a fast and reliable decoding parser.
Simulation of non-motor vehicle and pedestrian mixed crossing behavior
Authors: Zhang Yi , Ge Jing
Published: August 2021

In order to study the mixed traffic of non-motor vehicles and pedestrians at urban intersections, a two-dimensional cellular automata model was established by analyzing the movement characteristics of non-motor vehicles and pedestrians, which included the field, cellular space, attributes, and forward decision-making of pedestrians and non-motor vehicles. This model can reflect the interweaving and interference behavior of non-motor vehicles and pedestrians in the time window of the intersection, and describe the behavior characteristics of non-motor vehicles and pedestrians in different stages of crossing the intersection.
An improved denoising model for convolutional neural network
Authors: Wang Wenjing
Published: August 2021

In recent years, computer vision and many other research fields have put forward higher and higher requirements for image quality, and image denoising has become an important research direction. Aiming at the problems of general image denoising effect and long algorithm convergence time, this paper makes an improvement on the original network structure of denoising convolutional neural network DnCNN model and adds channel attention mechanism in the penultimate layer. The channel attention mechanism further improves the signal-to-noise ratio (SNR) and optimizes the noise reduction effect through convolution and deconvolution neural networks. The experimental results show that, under the same noise reduction level of 25, the PSNR of the proposed DnCNN2 algorithm is 1.25dB and 1.62dB higher than that of the DnCNN algorithm after the verification of the BSD68 and SET12 test data sets. Structural similarity (SSLM) was increased by 0.0011 and 0.0103, respectively. Meanwhile, the convergence time of the algorithm becomes shorter. Compared with traditional deep learning image denoising algorithms, the noise reduction effect and operation efficiency of the proposed method are also improved, which has certain advantages.
Design of Risk Early Warning Model Based on Big Data
Authors: Shen Qi
Published: August 2021

With the development of China’s economy, pollution has become more and more serious, so total pollution control has become a priority for governments at all levels. The center of total pollutant emission reduction is to formulate scientific and reasonable pollutant emission reduction policies based on the forecast of pollutant emission in the next few years. According to the national requirements, the emissions of four pollutants, namely sulfur dioxide, nitrogen oxide, ammonia nitrogen and chemical oxygen demand, need to be counted. The research objective of this paper is to establish a combined model applicable to the emission prediction of sulfur dioxide, nitrogen oxide, ammonia nitrogen and chemical oxygen demand by analyzing the impact of population factors and industrial distribution on pollutant emissions and combining the grey system theory and neural network theory. According to the characteristics of pollutant discharge in a certain city, a pollutant discharge prediction model based on GM (1,1), GM (0,4) and BP neural network is proposed.
Design and Implementation of English Online Examination System Based on QT
Authors: Zhuo Wang
Published: August 2021

With the development of society, all fields will basically involve examinations. Nowadays, most of the papers in the form of paper media are used for examinations. The examination of paper media is heavily dependent on wasting natural resources and is difficult to improve effectiveness. For these reasons, the extensive use of test software is essential. The design and implementation of the text is based on the C/S mode exam management system. The system sets different permissions for each user category. People of different privileges use different functions. The system displays all the functions of the examination on the client, realizes the difference of information sharing and processing in real time, reduces the influence of human factors on the fairness of the examination, and greatly improves the efficiency of the examination.
A Virtual Modeling Method of Digital Media Image Synchronization Based on Motion Hybrid Algorithm
Authors: Yang Yanyan , Wang Zhiping , Yang Caixia , Zhu Huijun
Published: August 2021

In virtual reality digital media, motion capture system is used to build basic motion library. Then the basic motion is processed by motion editing technology. Motion blending is one of the most practical and complex editing techniques. This paper proposes a real-time synchronization algorithm based on motion blending, so as to better mix motion dynamically, avoid unexpected effects, and create complex virtual digital media animation. This paper adopts the strategy of data and model hybrid drive. The motion generation and control technology of virtual human is studied from the following aspects: Modeling and simulation method of motion system, grasping of virtual human considering the change of whole body posture, fast generation of operation action, automatic interactive generation of virtual human’s key frame posture, multi priority editing synthesis and interactive control of virtual human’s whole body motion. In this paper, the corresponding control strategy and model are proposed, and the traditional algorithm is improved. Experimental results show that the method improves the efficiency and accuracy of digital media generation. This method provides a reference for the research of digital media image synchronous virtual modeling method based on motion hybrid algorithm.
Design of Library Mobile User Behavior Analysis model for Personalized Information Service
Authors: Tang Miaoji
Published: August 2021

This paper summarizes the research status of Library mobile user behavior at home and abroad, and provides a reference for the design of Library mobile user behavior analysis model for personalized information service. Using the method of theoretical research and model analysis, the relationship between user behavior sequence and user behavior characteristics is studied from three aspects of data collection, data processing and data application. This paper defines and represents the invisible feedback behavior of Library mobile users on IOS app, android app and web page and product UI by combining the front-end operation behavior with the back-end business database, collects the data from three aspects: basic information field, user behavior related field and configuration flume of mobile users’ client, and introduces the time dimension, user dimension, Department dimension, resource dimension, resource dimension The data warehouse level modeling is carried out from six dimensions of behavior dimension and entrance channel, and the data application is realized from two steps of user behavior sequence prediction and user interest guidance.
Analysis of Big Data Embedded Mapping Model Oriented to Prediction of Subordinate Relationship
Authors: Xu Hui
Published: August 2021

With the rapid development of information technology, research on big data information has gone deep into all walks of life, and massive amounts of data spew out anytime and anywhere. This paper proposes a domain-subordinate relationship acquisition that combines multiple strategies and word representations. From semi-structured text and unstructured text, the candidate entity upper-lower relationship entity pairs are extracted, and then the obtained candidate upper-lower relationship entity pairs are verified by the support vector machine method to obtain high-quality candidate entity pairs. In the training phase, an exploratory method is designed to search for the optimal solution, and a greedy mechanism is introduced to evaluate the effectiveness of the reinforcement learning agent, so that the virtual node mapping scheme can continuously move towards higher system returns. Evolution has finally achieved the optimal virtual network mapping decision, so that large-scale tasks can be deployed to task processing nodes in the appropriate underlying network to achieve efficient task execution in a big data environment. The experimental results show that the Tard method can effectively avoid model overfitting and improve the task recognition processing ability in the actual application process under the premise of meeting large-scale task requests.
Design of 3D Scene Visual Communication Modeling Based on Virtual Reality Graphics Rendering Framework
Authors: Zheng Jintao , Liu Qian
Published: August 2021

Virtual reality is a kind of computer simulation system which can create virtual environment. People can interact with the three-dimensional environment generated by computer. In this paper, the real-time computer graphics technology, three-dimensional modeling technology and binocular stereo vision technology in virtual reality technology are studied, and the binocular stereo vision optical system is designed. This paper studies the visual communication modeling design of 3D scene under the framework of virtual reality graphics rendering. In this paper, we design and make a three-dimensional model, and develop a virtual indoor scene application. In this paper, the 3D model is used to build the scene, and several commonly used rendering technologies such as texture mapping, material, lighting calculation, transparent effect and shadow calculation in unity engine are used to render the scene. The experimental results show that this method can improve the design efficiency and the accuracy of design matching.
Research on Addressing Technology of Internet of Things Unique Resources Based on RFID
Authors: Huo Zhenxuan , Liu Tianjun , Li Tiannian , Zhong Hui
Published: August 2021

The global nature of the Internet of things obviously has the problem of cross domain communication, so the Internet of things also needs a set of perfect resource addressing technology to meet its resource addressing needs and promote the interconnection of the Internet of things. Through the analysis of five key elements of resource addressing, such as resource name, resource address, addressing mechanism, update mechanism and security mechanism, this paper summarizes the resource addressing characteristics of Internet of things, which is not only conducive to the design of resource addressing model of Internet of things that meets the demand of resource addressing, but also the necessary premise to solve the key technology of resource addressing of Internet of things. In order to solve the address conflict and addressing problem between different standards of radio frequency identification (RFID), a hierarchical addressing model based on RFID resource name space is proposed. This paper analyzes the characteristics of RFID resource addressing and the existing RFID addressing technology, finds out the defects of addressing technology based on domain name system, introduces the formal expression method of RFID resource namespace, and designs a hierarchical addressing model.
Design of IoT Sensor Terminal Based on RFID and Wi-Fi Technology
Authors: Li Meilian
Published: August 2021

The Internet of Things has penetrated into all aspects of human production and life. This article has developed an Internet of Things sensing terminal based on RFID and Wi-Fi technology. This article uses the information management function provided by RFID electronic tags and the convenient networking function provided by Wi-Fi to design. We introduced the system performance requirement analysis and system architecture design. Starting from the selection of the S5PV210 processor and each module, as well as the communication interface between each module and the processor, we design the overall terminal hardware architecture. According to the Android architecture, the porting and development of related hardware module drivers, the design of intermediate programs, and the design of the JNI communication interface of the information acquisition module are introduced. The design of the Android upper-level UI program of each module and the PC upper computer GUI program and the performance test of each information collection module have been completed.
Application of PLC in Variable Frequency Constant Pressure Control System for Mine Emulsion Pump Station
Authors: Tian Cong , Su Chang , Zhao Weiping
Published: August 2021

Programmable logic controller (PLC) is an automatic control device made of microcomputer technology. It is based on sequential control, supplemented by loop adaptive, can complete logical judgment, timing, memory and numerical functions. The application of PLC in the variable frequency and constant pressure control system of mine emulsion pump station is studied. The emulsion pump station for mine is introduced. Based on the practice of energy saving, safety and protection equipment, the application of variable frequency speed regulation and constant pressure technology in emulsion pump is described. The working principle and PLC control system of emulsion pump control system are introduced by means of PLC circuit control. The experimental results show that the design of variable frequency and constant pressure control system based on PLC can greatly save energy consumption. In the variable frequency state, the average temperature of the pump body does not exceed 45°, indicating that the variable frequency constant voltage control system can improve the service life of the equipment.
Key Technologies of Security Access Control in Fog Computing Environment
Authors: Bin Sun , Yongjie Wang
Published: August 2021

The rapid development of Internet technology has promoted the innovation of mobile communication technology. Following 2G, 3G, and 4G technology, mobile communication has entered the 5G era. At the same time, the trend of interconnection of all things is becoming more and more clear, and the simple cloud computing is gradually changing to more advanced and powerful fog computing. As a near-maturity edge computing model, fog computing is gradually popularized and applied. The security problem is always the most important thing in network technology. Therefore, it is necessary to think about the security access in fog computing environment. This work mainly discussed the security access control technology in fog computing environment, clarified its key parts, and analyzed its effective control technology from two aspects: extended access and hidden access. This work will give users more flexible access control options to thus achieve effective protection of data security and related factors.