Urban waterlogging will harm economic development and people’s life safety; however, the waterlogging risk zoning map provides the necessary decision support for the management of urban waterlogging, urban development and urban planning. This paper proposes an urban waterlogging risk assessment method that combines multi-criteria decision analysis (MCDA) with a geographic information system (GIS). The framework of urban waterlogging risk assessment includes four main elements: hazard, exposure, vulnerability, and emergency response and recovery capability. Therefore, we selected the urban area of Changchun City, Jilin Province as the study area. The Analytic Hierarchy Process (AHP) is a generally accepted MCDA method, it is used to calculate the weight and generate a result map of hazards, exposure, vulnerability, and emergency responses and recovery capability. Based to the principle of natural disaster risk formation, a total of 18 parameters, including spatial data and attribute data, were collected in this study. The model results are compared with the recorded waterlogging points, and the results show that the model is more reliable.
In this study, two districts, Erdaojiang District and Dongchang District, in Tonghua City, Jilin Province, were evaluated for their geological environment carrying capacity. A total of 14 evaluation indicators were selected from the three aspects of the geological environment, ecological environment, and social environment to make it more comprehensive to evaluate the carrying capacity of the geological environment. Using the AHP and CRITIC methods, the subjective weight and objective weight of each evaluation index are obtained, and the combined weight is calculated by game theory. When combined with the GIS and combined weights, the distribution map of the geological environment carrying capacity is obtained, and it is classified into four grades: excellent, good, medium, and poor. A comprehensive evaluation of the carrying capacity of the geological environment is carried out. The following conclusions are drawn: the overall carrying capacity of the geological environment in the study area is good, and the carrying capacity of individual areas is poor. The comparative analysis of the good and poor areas provides a scientific basis for future environmental governance and urban planning and provides a scientific basis for geological disasters and mines.
The urbanization rate in China has been increasing in recent years, and along with the increasing intensity of human engineering activities, ecological and geological (eco-geological) degradation have become key factors impeding sustainable urban development. Taking the concentrated mineral exploitation area of Tonghua City as an example, the distribution of mines in the area is concentrated and the spatial heterogeneity is significant. This paper includes 14 evaluation indicators in three aspects: eco-geological environment background, anthropogenic and mining engineering activities, and environmental pollution. Then, based on game theory combined with ANP-CV (Analytic Network Process and Coefficient of Variation), two empowerment methods, GIS spatial calculation is used to evaluate the eco-geological environment quality (EEQ). The results showed that the EEQ was divided into grades I–V from high to low, with areas of 21.13%, 30.35%, 27.00%, 14.30%, and 7.22%, respectively; the EEQ of the Hun River basin has a high spatial autocorrelation and low EEQ, and the EEQ grade of mines was divided on this basis; the hot spot analysis is useful for determining the EEQ, as well as for allocating mine restoration resources in a sensible manner. Finally, we propose countermeasures to improve EEQ, and this study can provide a scientific basis for ecological construction and geological environmental protection in Tonghua City.
Design of the Student Attendance Management System Based on the Internet of Things Technology: The IoT refers to the linking of items to a network through message-generating devices; in the connection process, communication and information circulation are carried out through the information dissemination medium to realize intelligent identification, tracking, supervision, and other functions. Attendance management is a system for assessing employee attendance, including being late, leaving early, and asking for leave. Student attendance refers to the attendance rate of students in class. This article aimed to study the design and research of the student attendance management system based on the Internet of things technology, and use this system to accurately record students attendance and develop good habits for students. An effective attendance management company has been developed to enhance the collection of information for student management in universities, to keep track of teachers and students teaching attendance in real time, and to connect teachers and students in real time using computer technology. Access to the Android version of the software speeds up the collection and processing of information and can play an important role in improving the efficiency of personnel management. On the basis of analysing the operation logic of the attendance system, matching programs and the attendance system software are designed. The experimental results of this article show that the attendance rate of students with utilitarian personality is the highest, as high as 70; the attendance rate of students with helpless personality is 13; the attendance rate of students who follow the current personality accounted for 10; and the attendance rate of nonmotivated students accounted for 7. It can be seen from this that personality is an important factor affecting students attendance rate. The attendance rate of positive psychology with goals is the highest, and the attendance rate of students without clear goals is the lowest. The student attendance management system of the Internet of things technology has been applied in practical work, but with the continuous construction and development of the school, the continuous improvement of new software and hardware, and the emergence of new needs in practical work, the student attendance management system is easy to crash when processing a large amount of data at the same time.