scholarly journals Discussion on the Design of Food Safety Subject Database Based on Big Data Testing

2021 ◽  
Vol 292 ◽  
pp. 02052
Author(s):  
Kai Chen ◽  
Heng Tao ◽  
Jie Yu ◽  
Miao Hao ◽  
Hong Yang ◽  
...  

Food safety is a matter of national importance, and it is important to establish and improve a whole process food safety supervision system with high standard. Along with the advent of the era of big data, to achieve this goal requires not only the reform and optimization of the old regulatory approach needs to establish the idea of information-based supervision, and actively apply big data technology to food safety testing. In this paper, we introduce the current situation of food safety in society, analyse the shortcomings of current food safety supervision and the challenges faced in the era of big data, discuss the feasibility of using big data for food safety testing with big data technology as the core, and give the design idea of establishing a corresponding food safety subject database. This paper takes food safety testing as the foothold and innovatively combines big data with food safety testing, with a view to providing reference for food safety regulatory authorities and promoting the healthy development of the food industry.

2021 ◽  
Vol 292 ◽  
pp. 02053
Author(s):  
Kai Chen ◽  
Miao Hao ◽  
Hong Tan ◽  
Wei Huang ◽  
Fangjian Xin ◽  
...  

Food safety testing is of great significance for building a harmonious society. With the advent of the Internet era, the number of data indicators to be considered in food safety testing has gradually increased, and traditional food testing cannot adapt to the fast pace of today’s times. In order to meet the current challenges of food testing, this paper analyses the advantages of “Internet +” in building a food testing laboratory based on the challenges of food safety testing in the Internet era, and discusses the advantages of “Internet +” in the era of food testing. The paper discusses the intelligent working mode of food testing laboratories in the “Internet +” era, and combines big data technology to build an intelligent and comprehensive laboratory management platform, so as to build a new era of food testing intelligent laboratory, which improves the efficiency of food testing managers, reduces the workload, improves the accuracy of food safety testing, and helps the healthy development of the food industry.


2020 ◽  
Vol 13 (4) ◽  
pp. 340-351
Author(s):  
Yin Huang ◽  
Shumin Huang ◽  
Yichen Zhang ◽  
Xue Yang ◽  
Runda Liu

Background: Big data technology has been widely used in manufacturing supply chain management. However, traditional big data technology has some limitations, and it cannot achieve the continuous improvement of whole-process product quality tracing. Objective : The purpose of this study is to overcome the limitations by patents analysis and provide new big data technology and technical modes to make the continuous improvements of whole-process product quality tracing for achieving effective product lifecycle management based on big data technology. Methods: The research method, patent analysis, and comparative analysis are employed in this study to analyze product quality tracing in the manufacturing supply chain based on big data technology. Moreover, the procedure and steps of the new big data technology - Product Digital Twin (PDT), and its technical modes are designed by process design methods. Its key technologies are also analyzed and compared with traditional big data technology by the comparative study. Results: The research achieves the continuous improvements of whole-process product quality tracing based on new big data technology - PDT by patent analysis. The formation process and behavior of manufactured products in the realistic environment are simulated, monitored, diagnosed, predicted, and controlled. In this way, the high-efficient coordination in various stages of the product lifecycle is propelled fundamentally and the continuous improvements of the whole-process product quality tracing based on big data technology is analyzed. Conclusion: Three new technical modes based on big data technology are predicted for future researches and patents, namely, the immersive development mode integrating big data and the virtual reality technology, the knowledge-based multivariant coordinated development mode, and the lifecycle extended development model based on multi-domain interoperability.


2021 ◽  
Vol 5 (4) ◽  
pp. 1-3
Author(s):  
Yanan Song

Under the background of national development strategy in the new era, cross-border e-commerce with the help of Internet platform can realize the interconnection between producers and consumers, and gradually expand the influence of international trade. Based on big data technology, this paper builds an industry chain with cross-border e-commerce members' participation, and analyzes the specific application of big data in the product support, internal operation, external marketing, logistics service and service evaluation of cross-border e-commerce industry chain. The purpose is to effectively promote the healthy development of cross-border e-commerce and improve China's trade and economic level.


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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