Computers play a very important role in today's life. A large amount of personal information exists in computers, so it is very important to protect the information security on computer networks. The development o...
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Computers play a very important role in today's life. A large amount of personal information exists in computers, so it is very important to protect the information security on computer networks. The development of information technology has brought a huge impact on human society, and the information security of its computer network has attracted more and more attention. Aiming at the needs of computer network information management in the age of bigdata, this paper has developed a special computer network information protection system to deal with various threats and constantly improve the protection system. Based on this, the concept and advantages of the 5G network are first expounded, and the management technology of the 5G network is briefly analyzed. Then the information security problems of computer networks in the 5G era are considered, and effective solutions to the information security problems are proposed. Through research and calculation, the new computer network security system can improve network information security by 13.4%.
In recent years, new energy vehicles, as a high-tech industry, have developed rapidly. This paper uses "number of new energy project personnel" and "hours of R&D (research and development) personnel...
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In recent years, new energy vehicles, as a high-tech industry, have developed rapidly. This paper uses "number of new energy project personnel" and "hours of R&D (research and development) personnel" as design indicators to evaluate the investment of innovative talents in enterprises. This paper first introduces the supporting factors of the innovation environment in the input of innovation resources, and conducts research from four perspectives: human resources, innovation R&D, technology acquisition, and environmental support. In the construction of the innovation output index system, this paper outlines that the technological innovation (TI) achievements of enterprises are related to factors such as technological capabilities, profits, and market competitiveness of enterprises. Finally, this paper evaluates it from three aspects: the research and development achievements, the economic benefits obtained and the competitive benefits of the enterprise. The results show that from 2018 to 2022, the average technological innovation efficiency of new energy enterprises is 1.06;TI's efficiency indicators in the past five years are all above 1, and the overall improvement trend of TI is relatively stable. The new energy vehicle collaborative innovation system constructed in this paper will promote the overall development of the new energy vehicle industry.
With the rise of the era of bigdata, logistics distribution plays a crucial role in the development of enterprises. This paper makes an in-depth analysis and review of the research status of bigdata at home and abro...
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In the campus network billing system, in addition to online authentication, real-time monitoring of traffic and fees, network fee recharge is also an extremely important functional module. However, the traditional Int...
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ISBN:
(纸本)9781665416061
In the campus network billing system, in addition to online authentication, real-time monitoring of traffic and fees, network fee recharge is also an extremely important functional module. However, the traditional Internet fee recharge method has problems such as users need to line up at a designated place to recharge, the processing speed is slow, and the time for receiving the account is not timely. In response to the above problems, the article combines the actual network environment of colleges and universities with the specific needs of the campus integrated payment system model, and designs and develops a campus integrated payment system based on the blockchain architecture. The system uses blockchain technology based on the Fabric architecture, uses asymmetric encryption algorithms, Byzantine algorithms and other technologies to design and develop a campus-converged payment system with security, reliability, and decentralization. Practical application shows that this method has better feature resolution ability for blockchain distributed bigdata fusion. The high integration of campus payment and social payment is another practice of "Internet+" campus application, which will play a positive role in promoting the construction of campus informatization.
With the rapid development of the times, people have entered the era of intelligence, and the application of big data algorithms is becoming increasingly widespread. The satisfaction of consumers in online shopping is...
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With the rapid development of the times, people have entered the era of intelligence, and the application of big data algorithms is becoming increasingly widespread. The satisfaction of consumers in online shopping is closely related to communication and interaction during shopping. Based on this, this article studies the impact of online e-commerce interaction on consumer satisfaction based on big data algorithms. This article introduces the mediating variable of consumer satisfaction from the perspective of interaction, constructs a model between interaction and trust, and studies the internal impact mechanism of online interaction on consumer satisfaction in online shopping. This article takes the JD interactive shopping platform as the research object, and analyzes and explores the target consumer satisfaction of the women's clothing interactive shopping platform. Analyzed the impact of interaction on merchant qualifications and service satisfaction evaluations, store size, and logistics of purchased goods. The research results indicate that the normalization coefficients of the H1a and H1b pathways are 0.131 and 0.118, respectively, which are slightly smaller, indicating that the impact of perceived risk on consumer satisfaction is not significant. Meanwhile, the CR in H1 is a positive number and the direction of influence is positive, which is contrary to the assumption. Therefore, it is necessary to calibrate the initial model. After correction, the GFI value is 0.816, AGFI value is 0.825, RMSEA value is 0.042, TFI value is 0.930, CFI value is 0.955, PGFI value is 0.718, and PNFI value is 0.810. The degree is within an acceptable range. Therefore, when implementing interactive shopping, ecommerce companies need to create a good shopping environment for the implementation of interactive activities between sellers and customers. The impact of online e-commerce interaction based on big data algorithms on consumer satisfaction is a hot topic. Personalized recomme
In this paper, based on the research of the existing relevant results of teaching performance evaluation, referring to the information classroom performance evaluation system, the classroom teaching performance evalua...
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ISBN:
(纸本)9781728196190
In this paper, based on the research of the existing relevant results of teaching performance evaluation, referring to the information classroom performance evaluation system, the classroom teaching performance evaluation system in line with the characteristics of rural early childhood teaching classroom teaching. In this study, the Apriori analysis is adopted to analyze the data of classroom teaching performance evaluation of rural children teaching by using the big data algorithm method. Valuable knowledge of improving classroom teaching performance of rural children teaching is mined. First performance of education, teaching performance evaluation, rural children teaching classroom teaching and the analysis on the relevant situation do big data algorithm, mainly analyses the rural preschool education present situation of the application of classroom teaching, rural children education problems in classroom teaching, the demand of the rural preschool teaching classroom teaching evaluation, and on the basis of existing teaching performance evaluation research expounds the rural children teaching the basic content of the performance evaluation of classroom teaching, summed up the rural preschool teachers' performance evaluation model.
In the practice of financial management, the main links of financial and economic information processing include data collection, data integration, data analysis, and report preparation. Manually processing this type ...
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Since the current enterprise financial task allocation is difficult to adapt to the complex and changing business environment, it leads to low allocation efficiency, uneven resource utilization and insufficient except...
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Since the current enterprise financial task allocation is difficult to adapt to the complex and changing business environment, it leads to low allocation efficiency, uneven resource utilization and insufficient exception handling capabilities. This paper implements an intelligent task allocation method based on the combination of RPA (Robotic Process Automation) technology and big data algorithm. This method uses RPA technology to analyze task characteristics, adopts random forest algorithm to classify tasks, and uses support vector machine to predict task priorities. Then, the genetic algorithm is combined to optimize the task scheduling strategy to achieve dynamic task allocation. At the same time, the isolation forest algorithm is used to monitor the task execution status in real time and dynamically adjust the task allocation order. And the classification model, scheduling strategy and allocation rule base are continuously optimized through the feedback mechanism. In the four-week financial robot task allocation comparison experiment, the resource utilization rate of this method was improved from 85.4% to 90.4%, and the exception response time was kept between 4.5 and 6.4 minutes. The experimental results verify the effectiveness of this method in improving the efficiency of financial task allocation, optimizing resource utilization and enhancing the exception response capability, which has important academic value and application prospects.
Some recent studies have suggested that public opinions expressed in social media may be correlated with various social issues. To find out what actually can be discovered in social media data, we need data mining. Da...
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ISBN:
(纸本)9781479967193
Some recent studies have suggested that public opinions expressed in social media may be correlated with various social issues. To find out what actually can be discovered in social media data, we need data mining. data mining approaches that can handle massive amount of data have recently been referred to as big data algorithms. In this paper, we propose a big data algorithm to handling Twitter data mining. Furthermore, to ensure scalability, MapReduce framework is adopted to parallelize the proposed algorithm. Through the experiments, the potential of the proposed algorithm can be demonstrated. Computationally, the speed of execution can be shown to increase significantly despite increases in data set size. In fact, the acceleration ratio increases as the size of the dataset increases, and as the number of dataNodes increases.
We develop a human-machine interaction via dashboard for COVID-19 data visualization in the regions of Russia and the world. In particular, it includes an adaptive-compartmental multi-parametric model of the epidemic ...
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ISBN:
(纸本)9783031100475;9783031100468
We develop a human-machine interaction via dashboard for COVID-19 data visualization in the regions of Russia and the world. In particular, it includes an adaptive-compartmental multi-parametric model of the epidemic spread, which is a generalization of the classical SEIR models;and a module for visualizing and setting the parameters of this model according to epidemiological data, implemented in a dashboard. data for testing have been collected since March 2020 on a daily basis from open Internet sources and placed on a "data farm" (an automated system for collecting, storing and pre-processing data from heterogeneous sources) hosted on a remote server. The combination of the proposed approach and its implementation in the form of a dashboard with the ability to conduct visual numerical experiments and compare them with real data allows most accurately tune the model parameters thus turning it into an intelligent system to support a decision-making. That is a small step towards Industry 5.0.
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