With the rapid development of online courses and continuous development of online courses, the content, functions, and forms of its teaching platform are becoming more and more diversified. Problem-based learning (PBL) is a kind of “problem,” “learner,” and “cooperative learning” as the center, creating a problem-solving learning environment and allowing students to carry out problem-based learning activities. The teaching method based on PBL is also suitable for the network teaching environment. Embedded design refers to the design of embedded application systems with real-time, specificity, and limited resources through different methods. This article primarily presents the investigation of the PBL showing method of inserted plan courses in light of the organization showing stage and means to give a few thoughts and headings to the examination of the organization showing stage under the PBL mode. This study proposes an exploration method for the PBL teaching mode of embedded design courses based on the network teaching platform, including literature research method, survey research method, experience summary method, and embedded system-related algorithms, which are used to carry out the embedded design course PBL based on the network teaching platform teaching mode exploration experiment. The exploratory aftereffects of this study show that 90.18% of understudies like the PBL show stage for implanted plan courses.

Personal information security plays fundamental and critical role in promotion of smart cities. By taking personal information, vulnerability and threat as basic elements for risk assessment, this article proposes a Markov method-based personal information security risk assessment model in smart cities with the core of threats (Li Hetian, 2007). Based on threat probability, threat consequence attribute and attribute value acquired through the Markov method, threat analysis, the multi-attribute decisionmaking theory and the expert grading method, this article calculates the objective threat indexes, which is then utilized for risk ranking, so as to provide scientific basis for formulating targeted personal information security risk management and control strategies.

With the rapid development of computer technology and network technology, it has become possible to build a large-scale networked video surveillance system. The video surveillance system has become a new type of infrastructure necessary for modern cities. In this paper, the problem of foreground extraction and motion recognition in intelligent video surveillance is studied. The three key sub-problems, namely the extraction of motion foreground in video, the deblurring of motion foreground and the recognition of human motion, are studied and corresponding solutions are proposed. A background modeling technique based on video block is proposed. The background is modeled at the block level, which greatly reduces the spatial complexity of the algorithm. It solves the problem that the traditional Gaussian model (GMM) moving target enters the static state and is integrated into the background process. The target starts to move for a long time and there are ghosts and other problems, which reduce the processing efficiency of the lifting algorithm. The test results on the Weizmann dataset show that the proposed algorithm can achieve high human motion recognition accuracy and recognition with low computational complexity. The rate can reach 100%; the local constrained group sparse representation classification (LGSRC) model is used to classify it. The experimental results on Weizmann, KTH, UCF sports and other test datasets confirm the validity of the algorithm in this chapter. KNN, SRC voting classification accuracy.

Urban rivers are the origin of civilizations, the source of water supply, and the center of recreational and sports activities. The role of rivers can be investigated from various political, cultural, security, drought, economic, and health aspects. This study was conducted in order to identify the influencing components of urban rivers on ecosystem sustainability. The weight coefficients of climatic, social, economic, and ecological components were evaluated through dynamic cluster analysis, and their role in ecosystem sustainability was quantified. In addition, the relationship between water-based factors and environmental components was determined in finding the best components of river ecosystem evaluation for future decisions. The provided analysis can increase the stability of the urban river ecosystem and can rank the priority of the impact factors. Ecological environment statistics, nature measures, economic parameters, and land cover rate substantially affected the visual influence of the urban river ecosystem. Results showed that the proposed evaluation provided a reasonable framework to evaluate the sustainability of the urban river ecosystem and visual perception to improve the design efficiency by decision-makers.