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This paper combines the actual situation of security management in colleges and universities, and analyzes the demand for security innovative management platform in colleges and universities to facilitate teachers and students to live happily and research in a comfortable and modernized campus. According to the different functionality, the innovative campus system can be divided into the 3D campus roaming navigation module based on VR technology, the intelligent attendance module based on the combination of convolutional neural network and face recognition, and the induced parking module based on ant colony algorithm. The structure of each module and the operation process are all described in detail. Simulation experiment analysis is used empirically to analyze the intelligent campus management platform. The results show that the method of this paper has an average pass rate of about 89.55% for a given number of vehicles, and compared with the pre-optimization period, the waiting time for parking has been reduced by 19.5%, with an optimization rate range of 72.37%. Even after the optimization of the method in this paper can not wholly avoid the parking wait, but it can reduce the parking wait time, which for the parking lot, can ease the parking congestion in the peak time. The theoretical guidance provided by this study is used to construct a more brilliant campus, promoting the development of security and intelligent management in colleges and universities.

By combining mining algorithms, this paper provides a new method for quantifying the characteristics of literary language, thereby reducing the subjectivity of the value and language discussion of ancient literature in Chinese. Firstly, the TF-IDF algorithm is improved, the methods of inter-class dispersion and intra-class dispersion are adopted, and the optimal number of topics K of the LDA topic model is determined by using the confusion degree, and the quantitative model of the value and language characteristics of ancient literary texts is constructed. Furthermore, the concept of maximum word-to-frequency ratio is introduced. It is integrated into the traditional information gain method, and an old academic text recognition algorithm based on XGBoost model is constructed. The model’s results were applied to the network corpus mining and analysis, and the results showed that the word “cherishing spring” ranked first with a frequency of 7085 occurrences, followed by “hurt autumn” with 4598 occurrences. Among the eight themes, “natural imagery” (Topic 3) accounted for the highest proportion, reaching 23.68%, followed by “landscape and pastoral” (Topic 7) and “euphemistic words” (Topic2), accounting for 16.29% and 14.54%, respectively. The method of this paper not only provides a new perspective and tool for the quantitative analysis of the linguistic characteristics of literary works, but also points out a new research direction for the in-depth discussion of textual value and linguistic characteristics in the future.

In this paper, the development of microgrid technology is discussed in close connection with the growing energy demand and the real needs of energy structure adjustment in the context of the times. Guided by green energy saving, the research focuses on constructing a hybrid energy storage DC microgrid model, especially the integrated photovoltaic power generation model and the related control strategy and power characteristics. The article further adopts a fuzzy PID control strategy to optimize the energy efficiency configuration of hybrid energy storage devices in DC microgrids. By carefully analyzing and optimizing the energy storage system in the DC microgrid, remarkable results are obtained: the optimized capacitive charge states range from 0.1 to 0.9, indicating a significant fluctuation of capacitive charge states, but at the same time avoiding the phenomenon of light abandonment and ensuring the reliability of power supply. More notably, during the increase of SOC (state of the energy storage system) from 0.40 to 0.70, the system can perform mode transitions under continuous load changes. This point shows the effectiveness of the optimization method in improving the energy storage efficiency and enhancing the system performance of the DC microgrid. Overall, the optimization method proposed in this paper provides a practical energy storage optimization scheme for developing microgrids, which is of great practical significance in promoting the research and application of microgrid technology. This not only helps to improve the efficiency of energy use, but also is a crucial step to realize sustainable energy development.

As China’s position in the international arena continues to rise, and its interaction with the rest of the world increases, Chinese language international education has received widespread attention and developed rapidly. Based on information fusion technology, this paper constructs a vocabulary frequency analysis model that combines Bayesian estimation and D-S evidential reasoning, specifically used to calculate the hotness value of Chinese language international education. In the in-depth analysis of the Chinese language international education field, high-frequency words reflect the core themes in teaching and learning. At the same time, centrality indicates the degree of interconnection among the research themes. In the in-depth analysis of the Chinese international Education field, high-frequency vocabulary reflects the core teaching and learning themes, and the centrality indicates the degree of interconnection among the research themes. The frequency of Chinese as a foreign language is as high as 170 times, with centrality reaching 0.33, and these high-frequency keywords constitute the cornerstone of the development of Chinese international Education in China. When analyzing the data of the foreign students coming to China, it is found that the Number of Asian students accounted for 59.29% of the total number of 274976 students by the end of the study period. By 2022, the number of colleges and universities enrolling international students in China will increase to 831, and the Chinese global education market will reach 7.56 billion yuan in 2022, showing a saturated market status. The information fusion technology adopted in this paper not only reveals the development trend of Chinese international Education, but also provides a powerful analytical tool to promote the high-quality development of this field. A powerful analyzing tool.

This paper examines the impact of media communication on the stock market in the context of the digital age, particularly its role in stock price volatility. With the significant increase in the speed, breadth and depth of media communication, the efficiency of stock market information transmission has been dramatically improved, significantly impacting stock price volatility. The article first explores the specific impact of media coverage characteristics and methods on stock price volatility by quantitatively analyzing media coverage’s breadth, manner and content. Then, the article utilizes multiple linear regression models to deeply explore the impact of various news texts on stock price volatility in different reporting modes (e.g., live reporting, television, and text reporting) in the Shanghai and Shenzhen stock markets. The findings show a significant association between the breadth of media coverage and stock prices at the 1% significance level. In addition, the regression coefficients of content and manner of coverage on stock price changes are 0.096 and 0.229, respectively, which are both significant at the 5% significance level. The research results of this paper not only reveal the close relationship between media communication and stock market volatility and provide theoretical support for predicting dramatic stock market volatility, which helps to promote the construction of a healthy and orderly capital market order.

The article takes the application of digital media technology in the spatial layout design of art exhibition halls as the entry point, and utilizes Web technology and the integrated simulation platform of urban VRGIS to establish the virtual space of immersive art exhibition halls. The article obtains binocular imaging data through binocular visual imaging model and solves the three-dimensional coordinate system by using the method of polar geometric constraints, and then reconstructs the three-dimensional space through the point cloud data to realize the design of the virtual space of the immersive art exhibition hall. The article evaluates the effectiveness of the immersive art gallery virtual space from three aspects: interactivity, DPI recovery value and eye movement data visualization. It is found that users are most effective with direct interaction within an interaction depth of 1.1 m to 1.7 m. In comparison, ray interaction is more appropriate when the interaction depth exceeds 2.3 m. Applying the method of this paper, the global DPI recovery value of the immersive art gallery can reach 89.67%, and the pupil diameter of the subjects can reach about 5.79 mm in the virtual space test over 160 seconds. In this paper, digital media technology can more effectively realize the immersive presentation of art theories, to better satisfy people’s growing spiritual needs and provide more diverse cultural experiences.

With the continuous development of blockchain technology and the capital market, asset management introduced by blockchain has become the focus of enterprises, and this paper studies the enterprise asset management accounting system based on blockchain technology. By using blockchain technology, an asset management accounting system can be built by combining the cost control and responsibility system. Even though the enterprise asset management mode is designed to be efficient, the evaluation index of blockchain is not accurate. The blockchain enterprise asset management mode is analyzed using the DEA effectiveness model combined with the entropy weight method. Combined with the measured data of blockchain technology, the election phase, throughput, and transaction delay are compared, in which the blockchain technology BFT-Raft has a significant improvement in the election phase, the throughput is increased by 101.2TPS, and the transaction delay is reduced by 200~250ms.Through the analysis of the enterprise asset management and the analysis of blockchain de-also asset management efficacy, in which the coverage rate of blockchain technology and the asset yield increase year by year from 2018 to 2021, and reach the highest value of 0.5785 and 0.3612 in 2021, respectively, indicating that M’s overall asset management efficiency of the company has gradually improved with the coverage application of blockchain technology. In summary, the enterprise asset management accounting system based on blockchain technology in this paper can effectively improve the efficiency of enterprise asset management and is of practical significance for the development of enterprise asset management.

In today’s big data-driven information technology development, the use of algorithms for platform management to achieve more accurate and efficient user services has become a trend. In this paper, from the two aspects of platform recommendation and route delivery of agricultural products wholesale, combining platform recommendation algorithms and delivery route optimization algorithms, the accurate management of the agricultural products wholesale platform is studied. Taking the dataset collected from the X agricultural products wholesale platform as the experimental sample, it can be seen by comparing the experimental results of this paper’s recommendation algorithm and the traditional collaborative filtering algorithm that this paper’s platform recommendation algorithm is more effective. Among them, the recommendation algorithm based on user similarity performs better than the recommendation algorithm based on user location in terms of accuracy, coverage, and recall, with optimal values of 36.42%, 50.84%, and 17.17%, respectively. Taking the route distribution study of 10 customers on the X agricultural products wholesale platform as an example, comparing the original planned distribution routes and the optimized routes, the total distance of the optimized routes is 84.97km, which is 21.29% less than that of the original planned routes under the condition of meeting the customer’s demand volume, distribution time and truck loading capacity, which verifies the effectiveness of the distribution route optimization algorithm. Effect validation shows that customer stickiness, relationship quality, and conversion cost are significantly correlated with platform recommendations and delivery route optimization.

In this paper, a 3D model based on semantic annotation is constructed with the goal of improving the efficiency of building interior design. By analyzing the basic methods of semantic annotation for building interiors, the method of positioning and map construction is selected to obtain the indoor point cloud data. The distance between 3D spatial lines is calculated using the frame line extraction algorithm, and the target area of the frame line candidate is divided according to the distance. According to the principle of detecting raster circles using the Hough transform, an interior design structure recognition method is proposed for recognizing windows, doors, and walls in building interiors. The results show that the modeling time of the semantically annotated 3D model is 10 seconds faster than the other models on the wall; 9 seconds are saved on the door modeling, and 7 seconds are saved on the window modeling. The visualization effect of semantically annotated 3D models is mostly concentrated in (0.5-1), and a large number of data points are distributed in (0.6-0.9), which indicates that the visualization effect of semantically annotated 3D models is better. The semantically annotated 3D model proposed in this paper can improve the visualization of architectural interior design, which can improve the efficiency of designers to a certain extent.

This paper first integrates the green concept into jewelry design from three aspects of jewelry materials, modeling and production process, and demonstrates the jewelry 3D printing technology in line with the green concept in the context of information technology and analyzes its technical process. Then, based on the PCA method and the point cloud data of space lattice, the three-dimensional normal estimation of jewelry is carried out, the three-dimensional reconstruction and cavity repair of jewelry is carried out through the triangular mesh model, and the complete output of the jewelry model in STL format is carried out, and the STL fast slicing is carried out. Finally, the effects of 3D modeling, slicing efficiency, and jewelry design are analyzed through numerical simulation experiments. The results show that the standard deviation of the error in the x-direction σ =0.16um, expectation μ =−0.007um, the standard deviation of the error in the y-direction σ =0.08um, expectation μ =0.003um, and the standard deviation of the error in the z-direction σ =0.28um, expectation μ =−0.001um, with a variation range of (−0.028, 0.028), in the three-dimensional modeling of jewelry. Compared with the traditional slicing algorithm, this paper’s slicing efficiency of jewelry is improved by (0.26, 0.45), when the production quantity is more than 500 pieces, in terms of the cost of the traditional production method is more advantageous.