Theory construction and data reconstruction are required for the evaluation of quality in China. Taking into consideration existing mature quality evaluation models (particularly the methods of evaluating customer satisfaction) and China's unique national conditions during its economic transition, four dimensions are proposed to evaluate quality in China: consumer satisfaction with quality, product safety, government regulations on quality, and citizen's concept of quality. Based on empirical investigation data in this framework, the overall evaluation of quality in China is summarized as quality in China has just reached a general standard, product safety remains steady as a whole, government quality regulations are ineffective, and Chinese citizens' concept of quality is poor. Correlation analyses show a positive relation between the effectiveness of government regulation on quality and Chinese citizens' concept of quality, consumer satisfaction with quality, and product safety. Finally, the paper proposes the implementation of an emphasis on product safety during quality elevation and quality improvement systems, such as the constant enhancement of quality regulation effects and Chinese citizens' concept of quality, to drive quality development.

According to forecast data from the State Grid Corporation of China, the number of terminal devices connected to the power grid is expected to reach the scale of 2 billion within the next five years. With the continuous growth in the number and variety of terminal devices in the smart grid, traditional cloud-edge-end architecture will face the increasing issue of response latency. In this context, in situ computing, as a paradigm for local or near-source data processing within cloud-edge-end architecture, is gradually becoming a key technological pathway in industrial systems. The in situ server system, by deploying servers near terminals, enables the near-data-source processing of terminal-generated in situ data, representing an important implementation of in situ computing. To enhance the processing efficiency and response capability of in situ data in smart grid scenarios, this study designs an in situ data processing mechanism and an access demand management framework. Due to the heterogeneity of in situ server performance, there are variations in response capabilities for access demands across rounds. This study introduces a double deep Q-network with prioritized experience replay to assist in response decision-making. Simulation experiments show that the proposed method reduces waiting latency and response latency by an average of 67.69% and 68.77%, respectively, compared to traditional algorithms and other reinforcement learning algorithms, verifying its effectiveness in in situ data management. This scheme can also be widely applied to in situ computing scenarios with low-latency data management, such as smart cities and industrial IoT.

This paper aims to solve the problem of food safety in catering O2O distribution link. We applied the system dynamics method to model the formation mechanism of food safety risk in the distribution link. The results of our experiment include identifying the risk factors that may be faced by food safety in the distribution link from five perspectives: O2O catering enterprise’s own risk, logistics distribution team’s distribution risk, O2O catering platform supervision risk, user-supervision risk, and government department supervision risk, and establishing a risk index evaluation system based on the Analytic Hierarchy Process. With the help of the system dynamics model, the corresponding risk formation mechanism system model flow diagram is established, and the model simulation analysis is carried out. Through this research, we concluded that we can use the risk model to understand the risks faced by different subjects so as to make targeted countermeasures.

Efficient integration of urban rail lines and buses can improve public transportation. However, current methods for connecting them are not effective or fast. This paper analyzes passenger travel data, including taxi tracks and road network information, to identify potential bus connection stations based on demand. The link growth probability model is then applied to determine the bus lines’ most connected directions based on demand. Finally, a constraint-based exhaustive tree view technique is proposed to speed up the convergence of results. The WEI QU NAN Station in Shaanxi Province is used as an example to evaluate the model’s efficacy. The study reveals 153 prospective stations and lays out the feeder bus network for the entire line, along with a route optimization strategy. Keywords include Feeder Bus, Route Optimization, Link Growth Probability, and Graph Theory.