Traditional manufacturing industry is in the early stages of transition to low-carbon innovative production, and is in urgent need of a low-carbon innovation system to achieve the goal of carbon neutrality. In order to realize the effective supervision of enterprise carbon emissions, this paper constructs a tripartite evolutionary game model among the corporate, government and public from the perspective of dynamic subsidies and taxes. The main results are as follows. First, the increase in government subsidies to a certain extent will help encourage companies to choose low-carbon innovative production strategies, but more subsidies are not always better. Excessive subsidies will increase the cost of government regulation and reduce the probability of government regulation. Second, the tripartite evolutionary game system does not converge under the static subsidies and taxes mechanism. But the system could quickly converges to the stable condition under dynamic subsidies and taxes. The stable point is the situation of corporate low-carbon innovation, government regulation, and public supervision. Third, the public intervention and supervision can effectively prevent the phenomenon of government misconduct and enterprises over-emission production. And the influence of public reward and punishment is more effective for the government than for enterprises.

Inspired by the biological visual attention mechanism, we propose a visual attention convolutional neural network to solve the problem of identifying aircraft skin, but showing that the aircraft s kin image collected by the camera is rarely illuminated, and the contrast between defects and background is low and difficult to identify. Firstly, the U-Net with the encoder-decoder structure is used to initially segment the skin image that are provided by Airlines. Then, the residual block is introduced into the U-Net to enhance the propagation ability of the features and extract more defect detail feature information. Finally, the visual attention mechanism is used to increase the weight of the defect area to reduce the influence of uneven illumination on the model. The experimental results show that the proposed model has better defect segmentation effects in both visual effects and objective evaluation indexes. Our algorithm not only enhances the accuracy and effectiveness of skin defect identification but also provides management personnel with a more relevant tool, promoting the intelligence and information of air maintenance. This contributes to excellent management support for aviation companies and related industries.

Abstract Taxi services have a rapid development in sharing economy, especially Uber. And how to retain users and develop continuous usage is crucial for the development of sharing economy. The post-adoption of mobile services has been studied from different perspectives, but most researches focus on the effect of perceived usefulness, ease of use and satisfaction on continued usage, overlooking the important role of user value perceptions and habit. So we develop a model focusing on the cognitive process involved in the decision-making: cognitive beliefs (value perceptions including context value and in-use value beliefs) and an automatic process (habit process usage). We also examine the antecedents of habit. In this study, a survey sample of 305 responses is used to test the model in the context of Uber (taxi-calling mobile application). We find that context value has a significant impact on in-use value (represented by functional, convenience, monetary value) and then in-use value positively influences the overall evaluation (satisfaction). Satisfaction and habit positively influence users’ continuance intention. Additionally, the data also shows that in-use value and satisfaction are important to habitual behavior. And we use the decision tree algorithm to verify its effectiveness, the results show that the user's willingness to continue to use is affected by the above factors.

With the development of mobile technology, location-based mobile advertising has become worldwide. The development of effective advertising strategies is critical. Extant researches mainly focus on attitude and behaviour intention as the measures of advertising effectiveness, overlooking the important role of individual perceived value which is related to trade-off between benefits and sacrifices. So this study proposes a model to measure LBA effectiveness from the perspective of value and the relationship with user responses. This research model is empirically tested using survey data collected from 301 receivers of LBA in China. The results show that perceived LBA value is positively related to purchasing intention on advertised brands. In addition, perceived benefits including entertainment, convenience, and personalisation have direct positive effects on consumers' perceived LBA value. Privacy risk and irritation, as perceived sacrifices, have negative effects on consumers' perceived LBA value.

The Wireless Sensor Networks (WSNs) are composed of sensor nodes and sink nodes, and the network of sensor nodes is energy constrained, so the reliability of the WSNs is closely related to the energy of the nodes. According to the characteristics of the WSNs, this paper gives the concepts of the reliability and transmission reliability in WSNs, and analyses the energy consumption of sensor nodes in cases of data fusion and no data fusion. Additionally, we get the function relationship between reliability probability and time when WSN nodes are in normal working condition. Furthermore, by the simulation technology, we evaluate the reliability of the WSNs and the transmission reliability method of the entire network associated with the different level of energy. Finally, we propose the algorithm of transmission reliability model in the process of wireless transmission with energy restrictions.