Dynamic blockchain adoption for freshness-keeping in the fresh agricultural product supply chain

During COVID-19, the explosive growth of demand for fresh agricultural products on E-commerce platform has increased the difficulty of maintaining the greenness and freshness in delivery. The traditional cold chain delivery is effective in keeping greenness, but its information asymmetry makes the freshness-keeping activities unable to be regulated, which may lead to the supply chain members giving up their freshness-keeping efforts. Can the blockchain technology effectively solve these problems? We consider a fresh agricultural product supply chain consisting of a supplier and an E-commerce platform (retailer). The retailer is responsible for the wholesale and sales of fresh agricultural products, and determines the blockchain adoption degree and advertising effort. The supplier is responsible for delivering fresh agricultural products to consumers, and determines the greenness investment and freshness-keeping effort. Based on the traditional and blockchain-based fresh agricultural product supply chain, we discuss the dynamic optimization of freshness-keeping effort, advertising effort, and blockchain adoption degree. Results show that the supplier will give up the freshness-keeping effort after receiving the wholesale funds in the traditional fresh agricultural product supply chain, which will naturally worsen the fresh agricultural products. When adopting blockchain technology, the supplier continues to make the freshness-keeping effort in delivery. And five specific settings are proved that blockchain is effective in maintaining freshness. But two other specific settings are determined that it is not suited for adopting blockchain. In addition, compared with the traditional fresh agricultural product supply chain, blockchain adoption can effectively reduce the freshness-keeping effort, advertising investment and goodwill for achieving the same profit margin level, and will not affect the greenness investment decision of the supplier. Our research can provide some insights into the cold chain logistics management of fresh blockchain. © 2022

Online Learning of Embedded Technology Course in the Post-Epidemic Era: A Case Study of Chinese Institute

The Covid-19 pandemic has altered the way people view online learning, which has experienced explosive growth since the pandemic and quickly cultivated the habit of online learning among the students. Online learning is not limited by time or space, and students can learn the courses repeatedly. Despite these advantages, it still has serious limitations in face of hardware-related courses like embedded technology, because it is not likely to provide opportunities for close-up observation of the real objects or any hands-on experience. Therefore, the learning effect will be greatly compromised. This paper proposed a solution for online learning of embedded technology course. It introduced the objective and content design of the course, the integration of ideological and political elements into the course, the teaching platforms that have been used as well as the concrete implementation process of online learning of the course, and it also statistically examined the effect of online learning. © 2022 ACM.

Research on the Construction Method of Knowledge Graph

With the continuous innovation of Internet technology, the explosive growth of information has become one of its most obvious characteristics, and how to break through the problem of data storage has become an urgent challenge to be solved. The knowledge graph proposed by Google can intuitively describe the relationship between entities in the objective world in the form of a graph, which is of great help in solving this problem. Firstly, the basic concept of knowledge graph is expounded, and include the key steps of knowledge extraction, knowledge fusion, knowledge storage, etc. Taking the relationship between confirmed cases of the coronavirus disease 2019(COVID-19) in a certain city over the recent period as an example, a knowledge graph of case relationship is constructed. The results indicated that the knowledge graph intuitively shows the transmission path of the epidemic, which can provide certain help for the effective prevention and control of the epidemic. © VDE VERLAG GMBH - Berlin - Offenbach.

Power grid data intelligent management and application under the background of big data

With the popularization of new technologies such as big data, cloud computing and the Internet of things in the construction of smart grid, power data is showing explosive growth. Traditional power enterprises rely on manpower to collect data and recover arrears. During the period of COVID-19, the closed management of government departments, the arrears of electricity customers and no power outages made the recovery work more difficult. In this paper, through the mining and analysis of customers' historical payment data, historical electricity and other data, using the deep learning algorithm in the field of artificial intelligence, this paper constructs a mathematical model and formulates the prevention and control strategy of electricity charge recovery risk of business travel alienation. The application results show that the new strategy can effectively reduce the amount of customer arrears and comprehensively improve the lean, digital and intelligent management level of power supply enterprises. © 2022 IEEE.