scholarly journals Based on the Software Complexity Measurement of Complex Networks under Big Data Technology

2021 ◽  
Vol 2066 (1) ◽  
pp. 012014
Author(s):  
Xiaobin Hong

Abstract With the development of the times, computer technology is booming, so the network is becoming more and more complex, software design is becoming more and more complex, because of the protection against a variety of internal or external risks. The internal risk is that the traffic carried by the system is too large to cause the system to crash or the system to crash caused by the code operation error, and the external threat is that hackers use computer technology to break into the system according to security vulnerabilities, so the purpose of this paper is based on big data technology, the software complexity of complex networks is measured and studied. With the consent of the school, we used the school’s internal network data, and after consulting the literature on the complex construction and analysis of complex networks and software, modeled and analyzed it using the improved particle group algorithm. The experimental results show that there is a certain correlation between complex network and software complexity. Because complex networks determine that software requires complex construction to withstand potential risks to keep the software running properly.

Author(s):  
Yu Zhang ◽  
Yan-Ge Wang ◽  
Yan-Ping Bai ◽  
Yong-Zhen Li ◽  
Zhao-Yong Lv ◽  
...  

2020 ◽  
Vol 12 (13) ◽  
pp. 5470 ◽  
Author(s):  
Antonio Matas-Terrón ◽  
Juan José Leiva-Olivencia ◽  
Pablo Daniel Franco-Caballero ◽  
Francisco José García-Aguilera

Big Data technology can be a great resource for achieving the Sustainable Development Goals in a fair and inclusive manner; however, only recently have we begun to analyse its impact on education. This research goal was to analyse the psychometric characteristics of a scale to assess opinions that educators in training have about Big Data besides their related emotions. This is important, as it will be the educators of the future who will have to manage with Big Data at school. A nonprobability sample of 337 education students from Peru and Spain was counted. Internal consistency, as well as validity, were analysed through exploratory and confirmatory factorial analysis. The results show good psychometric values, highlighting as relevant a latent structure of six factors that includes emotional and cognitive dimensions. As a result, the profile defining the participants in relation to Big Data was identified. Finally, the implications of the Big Data for Inclusive Education in a sustainable society are discussed.


2021 ◽  
Vol 1881 (4) ◽  
pp. 042036
Author(s):  
Jiao Tan ◽  
Yonghong Ma ◽  
Ke Men ◽  
Jing Lei ◽  
Hairui Zhang ◽  
...  

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