Emergency Information Sharing Mechanism and Efficiency Measurement in Coastal Cities, China

To establish and improve the theoretical framework and operation mechanism of emergency information sharing, and to establish the index system and evaluation method of the efficiency of emergency information sharing are the key work to improve the disaster prevention and mitigation capacity of coastal cities in China. In this paper, the synergetic theory is introduced into the construction of emergency information sharing framework. By clarifying the operation relationship between the participants and the information transmission, the framework and operation mechanism of emergency information sharing are constructed. Around the 3 dimensions of emergency information sharing mechanism construction, resource guarantee ability and collaborative driving force of emergency information sharing, the evaluation index system of emergency information sharing collaborative efficiency in coastal cities is proposed, and the evaluation method of emergency information sharing collaborative efficiency based on coupling degree model is proposed. The empirical results show that the efficiency of emergency information sharing in coastal cities in China is generally on the rise, and the contribution rate of the construction level of emergency information sharing mechanism is higher than that of the resource guarantee ability and the collaborative driving force of emergency information sharing, but the efficiency of emergency information sharing in coastal cities in China is still at the bottom level. The research results provide theoretical basis and methods for the emergency management departments of coastal cities in China.

Explore the Conflict and Resolution of Pollution NIMBY Facility Construction in the Context of New Media: An Evolutionary Game Theoretical Approach

The rapid urbanization process has brought many pollution NIMBY facilities, and the associated pollution NIMBY conflicts have become one of the important factors restricting social stability. With the advent of the media era, new media has become the main channel for the public to recognize risks and master information, which greatly aggravates the social amplification effect of NIMBY conflict risk. In this case, it is of great significance to explore the interest relationship among the local government, the new media, and the local people and their roles in the NIMBY conflict. Based on the stakeholder theory, this paper constructs a three-party evolutionary game model of the local government, the new media, and the local people and carries out numerical simulation on the evolutionary model using MATLAB. The results show that the local government adopts a certain degree of regulatory strategy for the new media, the new media adopts the strategy of publicizing facts, and the local people adopts the strategy of nonresistance, which are the stable strategy points of the evolutionary game among the three stakeholders in the NIMBY conflict. The local government’s intervention in rumors to a certain extent is conducive to promoting the new media to publicize facts of the pollution NIMBY facilities and to restrain the local people’s choice of resistance strategies. The local government’s punishment to the new media spreading rumors should be kept above a certain level to restrain the new media spreading rumors. When the local people’s resistance reaches a certain level, the local government’s intervention will break down and the new media will become hyperactive. The results of this paper can provide some enlightenment for the stakeholders in pollution NIMBY conflicts and deepen the understanding of multiple interest conflicts and their resolution. Finally, this study proposes to build information sharing mechanism, information communication mechanism, trust mechanism, network governance mechanism, and public participation mechanism, so as to resolve the construction risk of pollution NIMBY facilities and improve the overall social welfare level.

Bayesian assessment of utility tunnel risk based on information sharing mechanism

The main body of the utility tunnel is all kinds of pipelines, so the normal operation of the pipelines is very important for the operation benefit of the comprehensive utility tunnel; meanwhile, identifying the potential risks of the pipelines in time can reduce the losses caused by the uncertain risks to the comprehensive utility tunnel. This paper uses the Stackelberg game model to analyze the risk information sharing among utility tunnel institutions which concludes in utility tunnel company and pipeline company, which is helpful for understanding the decision-making process in the game and its equilibrium results can guide utility tunnel company’s decision-making behavior in seeking utility tunnel risk treatment. On this basis, this paper analyzes the potential disaster risk factors in the operation process of utility tunnel, and constructs the risk early warning model of integrated pipeline corridor based on Bayesian network. The results show that the potential disaster risk during the operation of utility tunnel is evaluated, and the overall risk probability level, the key path and key risk factors of the occurrence of disaster risk events are obtained.

Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways

A wide variety of 1) parametric regression models and 2) co-expression networks have been developed for finding gene-by-gene interactions underlying complex traits from expression data. While both methodological schemes have their own well-known benefits, little is known about their synergistic potential. Our study introduces their methodological fusion that cross-exploits the strengths of individual approaches via a built-in information-sharing mechanism. This fusion is theoretically based on certain trait-conditioned dependency patterns between two genes depending on their role in the underlying parametric model. Resulting trait-specific co-expression network estimation method 1) serves to enhance the interpretation of biological networks in a parametric sense, and 2) exploits the underlying parametric model itself in the estimation process. To also account for the substantial amount of intrinsic noise and collinearities, often entailed by expression data, a tailored co-expression measure is introduced along with this framework to alleviate related computational problems. A remarkable advance over the reference methods in simulated scenarios substantiate the method’s high-efficiency. As proof-of-concept, this synergistic approach is successfully applied in survival analysis, with acute myeloid leukemia data, further highlighting the framework’s versatility and broad practical relevance.

Adaptive Information Sharing with Ontological Relevance Computation for Decentralized Self-Organization Systems

Decentralization is a peculiar characteristic of self-organizing systems such as swarm intelligence systems, which function as complex collective responsive systems without central control and operates based on contextual local coordination among relatively simple individual systems. The decentralized particularity of self-organizing systems lies in their capacity to spontaneously respond to accommodate environmental changes in a cooperative manner without external control. However, if members cannot obtain observations of the state of the whole team and environment, they have to share their knowledge and policies with each other through communication in order to adapt to the environment appropriately. In this paper, we propose an information sharing mechanism as an independent decision phase to improve individual members’ joint adaption to the world to fulfill an optimal self-organization in general. We design the information sharing decision analogous to human information sharing mechanisms. In this case, information can be shared among individual members by evaluating the semantic relationship of information based on ontology graph and their local knowledge. That is, if individual member collects more relevant information, the information will be used to update its local knowledge and improve sharing relevant information by measuring the ontological relevance. This will enable more related information to be acquired so that their models will be reinforced for more precise information sharing. Our simulations and experimental results show that this design can share information efficiently to achieve optimal adaptive self-organizing systems.

Supply Chain Inventory Collaborative Management and Information Sharing Mechanism Based on Cloud Computing and 5G Internet of Things

With the development of economic globalization, the competition among enterprises is increasingly fierce. Therefore, companies need close information sharing to realize the integration of supply chain. This article aims to study the collaborative management and information sharing mechanism of supply chain inventory based on cloud computing and 5G Internet of Things. This article first introduces the theory and methods of collaborative supply chain management and the information exchange mechanism and then discusses the problem of information sharing in the supply chain, that is, the bullwhip phenomenon, and then from the demand forecast, supply chain structure, time lag, and shortage game, six aspects are analyzed. The cause of the bullwhip phenomenon is analyzed. Secondly, this article proposes a quantitative analysis of the bullwhip effect, establishes a mathematical model of the bullwhip effect in the supply chain, and uses quantitative analysis to analyze the value of information sharing in the supply chain. Finally, this article uses cloud computing technology to build a supply chain information collaboration system architecture and uses EPC Internet of Things to build a supply chain information sharing model and describes the entire operation process of the supply chain. The experimental results of this paper show that the application of cloud computing technology to supply chain management establishes a system platform for supply chain information sharing, improves the overall operational efficiency of supply chain management, and realizes supply chain information sharing and business collaboration. In addition, the operating costs and risks of each node enterprise in the supply chain are reduced by 12% compared with the nonsharing situation, which also shows that the overall benefits of the supply chain have been correspondingly improved and market competitiveness has been enhanced.

Research on accounting information sharing mechanism from the perspective of national governance

Accounting information sharing plays an important role in giving full play to the resource allocation effect of accounting information and promoting the modernization of national governance. It is one of the main tasks of the 13th five year plan for accounting reform and development of the Ministry of finance to establish a public service platform for social accounting information based on the disclosure of financial report data. In view of a series of problems brought about by the current accounting information multi submission, different caliber, mutual independence and non sharing, this paper discusses the mechanism and implementation path of accounting information sharing from the perspective of national governance, and puts forward a vertical through, horizontal interaction, internal integration and national unified accounting information sharing service system. Through the establishment of accounting information platform, accounting information can be “Count one, share resources”.

Intelligent English writing system based on fusion of herding effect and artificial intelligence

The use of intelligent college English writing training system will certainly promote the traditional teaching structure and realize a new and efficient English writing teaching mode. On the basis of machine learning and the herd effect algorithm, this article constructs an artificial intelligence-based English intelligent writing system. Moreover, in view of the shortcomings of traditional models and the characteristics of intelligent English writing, this paper proposes an improved algorithm for optimization of swarm particle walking paths. In addition, this article proposes a relative attractiveness to initialize the formation of small-scale groups based on the herd effect. Then, in the process of intelligent writing, by establishing an information sharing mechanism between groups, each group is continuously updated and reorganized according to the relative attractiveness of the group, so that the writing process can be simulated more realistically. From the experimental research, it can be seen that the model constructed in this paper has a certain degree of intelligence.