Assessment of Power Plant Based on Unsafe Behavior of Workers through Backpropagation Neural Network Model

Safety is an essential topic for electric power plants. In recent years, accidents caused by unsafe behaviors of electric power plant employees are frequent. To promote the sustainable development and safety of electric power plants, studies on the assessment of unsafe behavior are becoming increasingly important and urgent. In this study, accident statistical analysis, literature review, and expert survey are adopted to select more comprehensive and accurate assessment indicators of unsafe behavior of the workers in electric power plants. Data about indicator and unsafe behavior were obtained through a questionnaire survey, and 27 indicators were used as inputs, and the unsafe behavior was taken as the output of a backpropagation (BP) neural network based unsafe behavior assessment model. An assessment indicator system about power plant workers’ unsafe behavior composed of 4 first-level indicators and 27 second-level indicators was established and the weights of the assessment indicators were determined. A three-layer feedforward BP neural network assessment model of “27-13-1” layers was found to be a suitable model. The proposed model can demonstrate the nonlinear complex relationship between the assessment indicator and the unsafe behavior of power plant workers. The model can be helpful to evaluate, predict, and monitor the safety performance of electric power plants.

Risk Analysis of Textile Industry Foreign Investment Based on Deep Learning

With the decline of China’s economic growth rate and the uproar of antiglobalization, the textile industry, one of the business cards of China’s globalization, is facing a huge impact. When the economic model is undergoing transformation, it is more important to prevent enterprises from falling into financial distress. So, the financial risk early warning is one of the important means to prevent enterprises from falling into financial distress. Aiming at the risk analysis of the textile industry’s foreign investment, this paper proposes an analysis method based on deep learning. This method combines residual network (ResNet) and long short-term memory (LSTM) risk prediction model. This method first establishes a risk indicator system for the textile industry and then uses ResNet to complete deep feature extraction, which are further used for LSTM training and testing. The performance of the proposed method is tested based on part of the measured data, and the results show the effectiveness of the proposed method.

Assessment of Aesthetic Quality of Urban Landscapes by Integrating Objective and Subjective Factors: A Case Study for Riparian Landscapes

To improve human well-being, there is increasing awareness of elevating aesthetic benefits by landscape design, planning, and management. However, which landscape features and attributes may be associated with aesthetic value of an urban landscape, human aesthetic preference, and landscape practices is still not clear yet. We proposed a comprehensive aesthetic assessment approach to realise the determination of landscape aesthetic indicators, integration of objective indicators and subjective preferences, and validation of estimations. The approach was based on a four-level landscape aesthetic indicator system from the bottom features up to attributes (landscape naturalness, landscape complexity, plant species diversity, water surface, water clarity, and bank naturalness), component qualities, and finally overall quality. Fourteen metrics that could provide objective visual and spatial characters and ecological implications were identified and quantified to indicate landscape aesthetic features. Landscape aesthetic attributes, vegetation and waterbody component qualities, and overall quality were estimated by integrating objective indicators and human subjective preferences. The approach was applied to a case study of four subareas along an artificially restored riparian buffer in Beijing, China. The results showed that the modelled overall aesthetic quality was determined by both vegetation (accounting for 53%) and waterbody. The higher vegetation quality depended on the higher plant abundance, more vegetation patches, and more vegetation patch types; the higher waterbody quality depended on the clearer water and larger water surface. Compared with other features, vertical vegetation configuration, diversity of patch type and patch shape, and shrub species diversity had greater contribution to the attributes of naturalness, complexity, and plant species diversity, respectively. The modelled vegetation aesthetic attributes were directly validated using the surveyed perceptions, and the modelled vegetation and waterbody aesthetic qualities were indirectly validated by correlating with the main recreational activities. The approach is confirmed to be able to address the questions on determination, integration, and validation of landscape aesthetic indicators in some way. Thus, the approach is expected to be used for other landscapes to offer a framework for landscape practices to improve aesthetic value and cultural service.

Construction and Application of the Evaluation System of Natural Resources Asset Accountability Audit of Officials: A Case Study of Jiangxi, China

At the Third Plenary Session of the 18th Central Committee of the Communist Party of China, the Central Committee first proposed the establishment of the Natural Resources Asset Accountability Audit of Officials, which not only marked a new stage in China’s ecological construction, but also triggered many scholars’ discussion on the accountability audit evaluation indicator system of natural resources assets. In this paper, the combination of entropy weight method and TOPSIS method is introduced into the natural resource asset accountability audit evaluation system for the first time, and a system based on energy subsystem, economy subsystem and environment subsystem is constructed. The system is used to evaluate the performance of leading officials of Jiangxi Province, one of the first batch of national pilot zones for ecological conservation in China, in the responsibility of natural resource asset management from 2015 to 2019. The evaluation result indicates that the overall situation of natural resource assets in Jiangxi Province shows a steady upward trend, and the overall performance should be affirmed. The practical application of this evaluation system in the national pilot zone for ecological conservation will enlighten other provinces in China to improve the leading officials’ accountability audit of natural resource assets.

Evaluation on Risk Factors of Elderly Services From the Perspective of Integrated SCOR Model

Analysing and identifying the risk factors of elderly services is conducive to improving the risk management capabilities of the elderly care industry and maintaining the safety and stability of the elderly care service industry chain. Based on the integrated Supply Chain Operations Reference (SCOR) model, a risk indicator system for elderly services supply chain was established from plan, design, supply, implementation, and customer service. The DEA method with Entropy-AHP mixed constraint was introduced to deal with the weight freedom of traditional DEA method. Taking the likelihood, exposure and consequence of risk occurrence as decision variables, the risk evaluation and ranking of the indicators were carried out. According to the empirical analysis based on the data of elderly care institutions in the Pearl River Delta of China, the biggest Pareto risk factors in the first-level and second-level indicators, the risk growth and reduction ratios of the first-level indicators were obtained.

Research on the Reform Direction of Ideological and Political Course Teaching Based on Online Open Courses

In the context of the “Internet +” era, educational information has become an inevitable trend in educational development. The successive introduction of relevant policies has laid the foundation for the steady development of educational information. Online open courses are an important means to expand teaching space and time, and this article aims to open up a new direction for the teaching reform and development of ideological and political courses through the combination of ideological and political courses and online open courses. This article proposes the analytic hierarchy process and the Delphi method. First, the Delphi method is used to revise the initially constructed indicator system; then, the analytic hierarchy process is used to design the weights of the indicator system; finally, we try to apply the established index system. The experimental results of this paper show that teacher expression and curriculum content have a greater impact on classroom teaching. The weight of teacher expression is 0.25, and the weight of curriculum content is 0.26.

Reducing the Environmental Impact of Sterilization Packaging for Surgical Instruments in the Operating Room: A Comparative Life Cycle Assessment of Disposable versus Reusable Systems

The widespread use of single-use polypropylene packaging for sterilization of surgical instruments (blue wrap) results in enormous environmental pollution and plastic waste, estimated at 115 million kilograms on a yearly basis in the United States alone. Rigid sterilization containers (RSCs) are a well-known alternative in terms of quality and price. This paper deals with two research questions investigating the following aspects: (A) the environmental advantage of RCS for high volumes (5000 use cycles) in big hospitals, and (B) the environmental break-even point of use-cycles for small hospitals. An in-depth life cycle assessment was used to benchmark the two systems. As such a benchmark is influenced by the indicator system, three indicator systems were applied: (a) carbon footprint, (b) ReCiPe, and (c) eco-costs. The results are as follows: (1) the analyzed RSC has 85% less environmental impact in carbon footprint, 52% in ReCiPe, and 84.5% in eco-costs; and (2) an ecological advantage already occurs after 98, 228, and 67 out of 5000 use cycles, respectively. Given these two alternative packaging systems with comparable costs and quality, our results show that there are potentially large environmental gains to be made when RSC is preferred to blue wrap as a packaging system for sterile surgical instruments on a global scale.

Research on a Dynamic Evaluation of Financial Risks of Intellectual Property Pledge Financing of High-Tech Enterprises

Intellectual property pledge financing is effective in alleviating the financing problems of scientific and technological enterprises to a certain extent. However, compared with traditional loans, intellectual property pledge financing is at greater risk with an eye to the particularity of intellectual property pledges. Therefore, it is very important to evaluate the risk of intellectual property pledge financing. This article first outlines the information entropy method, functionalizing indicator data and weight data, and applies the combination of the weight function and indicator function in dynamic evaluation function, to get the final evaluation result. Second, taking four high-tech listed companies on the growth enterprises market (GEM) as example, an evaluation indicator system has been constructed with 16 relevant financial indicators from 2015 to 2019. Then, based on the dynamic function method, we can construct the evaluation function to describe the change trend of the financial indicators of enterprises with a comparison of the advantages and disadvantages of the financial indicators of enterprises. Finally, this article has made a comprehensively comparative analysis on the dynamic evaluation, and the financial risk of intellectual property pledge financing of high-tech enterprises has been done with the combination of the dynamic evaluation curve with the optimal time weight determined by the maximum entropy method.

Spatial–Temporal Features of Coordination Relationship between Regional Urbanization and Rail Transit—A Case Study of Beijing

Urban rail transit is an important transportation infrastructure that mitigates the congestion of the central city and realizes compact city space development. However, the literature on the spatiotemporal coupling of urbanization and rail transit from the urban scale and its influencing factors is still uncommon. Taking Beijing as an example, based on the theory of coupling coordination, we have constructed a comprehensive indicator system for regional urbanization (hereafter RU) (including population, economy, and spatial urbanization) and rail transit (hereafter RT). On this basis, we use the entropy method, coupling coordination degree model, and spatial autocorrelation analysis method to explore the spatiotemporal characteristics of the overall and pairwise coupling coordination between population, economy, spatial urbanization, and rail transit. Finally, we analyze the spatial correlation and standard deviational ellipse analysis of the coupling coordination degree between RU and RT. The results indicate the following: (1) In addition to population urbanization, the other urbanization indicators and the RT level all show a downward–rising–falling trend from 2006 to 2017, among which the level of economic urbanization is the highest. The degree of coupling coordination between RU and RT is unbalanced development and shows a trend of first rising and then falling. (2) The degree of coupling coordination between RU and RT presents an imbalanced distribution in various regions, and the coupling coordination degree in the central urban areas is significantly higher than that in the outer suburbs. (3) From 2006 to 2017, the spatial correlation of the coupling coordination degree between the various systems has a similar changing trend. Moreover, the distribution of the spatial agglomeration points of the coupling coordination degree between RU and the RT is similar, showing a decreasing trend from the central urban area to the surrounding urban area. Therefore, relevant departments can rationally plan the construction of urban rail transit according to the coordination relationship between RU and RT and the spatial aggregation degree to realize the benign and sustainable development between urban especially suburbanization and rail transit.

Spatial Pattern of Underground Space Development in Major Cities in China: Evaluation and Analysis

Underground space development has gradually become an organic part of China’s urban development and construction. Comprehensively developing underground space scientifically and rationally to give full play to its comprehensive benefits is the main problem faced by China’s underground space development at this stage. This research starts with the measurement of the level of urban underground space (UUS) development. This paper constructs a UUS development level measurement indicator system, which is composed of Construction of UUS (D1), urban economic development indicators (D2), and urban population development indicators (D3), which has 12 secondary indicators, and then we use entropy-TOPSIS method to quantitatively evaluate the development level of underground public space in 39 prefecture-level cities and above in my country and analyze its spatial differentiation. The results show that the urban agglomeration has the characteristics of “high-high” cluster distribution with the development level of underground space. However, the overall level of underground space development in China’s major cities is not high and there are apparent differences in the level of UUS development. In terms of spatial distribution, the sustainable development level of cities in the eastern coastal regions of China is relatively high, with towns in the central and northeastern areas ranking second and western towns and northeastern cities ranking the lowest. At the same time, we found that there is a mismatch between the underground space development index and the economic population development index in the evaluation index. Finally, some suggestions are put forward to realize the balanced development of UUS development in our country.