In order to explore the deficiencies in the teaching process of marketing majors in higher vocational colleges and further improve the teaching quality of marketing majors in higher vocational colleges. This paper utilizes the improved ID3 algorithm to construct the SLIQ data mining algorithm to improve the teaching quality of teachers of marketing majors in higher vocational colleges and universities. Using ID3 algorithm to build a decision tree to get the portraits of teachers and students, at the same time, in order to reduce the computational complexity of ID3 algorithm and the problem of multi-value bias, the concept of sample structure vector similarity is introduced, and the degree of information gain is optimized to get a more reasonable decision tree. On this basis, based on the improved ID3 data mining algorithm, a teaching quality assessment system for senior marketing majors based on SLIQ algorithm is designed, which identifies important factors affecting teachers’ teaching quality by mining a large amount of data in the teaching process.The AUC value of the SLIQ data mining algorithm is 0.98, which can effectively improve the algorithm’s generalization ability, and it has an excellent performance in the teaching quality assessment task. The performance is excellent. In this paper, we systematically identify “the principles of marketing” and “the degree of seriousness of teachers’ homework correction” as the key factors to improve the teaching quality of marketing teachers. It provides a scientific basis for improving the quality of teachers’ teaching.

Visual communication design requires that feeling information and exchange of information must be conveyed efficiently and accurately. In this paper, we design a robust principal component sub-analysis visual enhancement algorithm based on improved Retinex. The algorithm transforms the image to the logarithmic domain so that it satisfies the decomposition condition of RPCA. After the RPCA decomposition model to get the low-rank component and sparse component, and will use adaptive gamma correction algorithm for the low-rank component for contrast enhancement, the two components are combined and then inverse transformed in the logarithmic domain to get the enhancement results. To avoid color distortion, the input image is converted to HSV color space to separate illumination information from noise. The model uses the inexact augmented Lagrange multiplier method (IALM) to solve the optimization problem, which leads to a significant improvement in the decomposition speed. The performance of the designed algorithm is verified on the dataset, and it is found that after the color equalization process for overexposed images, the gray value distribution is more uniform, and the image shows a better sense of brightness and visual effect after the contrast is increased. The algorithm scores 0.4648 and 0.7577 in UCIQE and UIQM respectively, which are ranked first among all algorithms and have better visual effect and information communication efficiency.

In recent years, China’s research investment in colleges and universities has gradually increased, but not much research and exploration has been done on the construction of the evaluation index system for the integration of industry and education. The state, society, industry and so on have brought rare opportunities for the implementation of in-depth integration of industry and education, which also indicates the imperative of the development of integration of industry and education. Based on the practical significance of educational evaluation, this paper applies the CIPP model to the construction of the quality evaluation system for collaborative education and training in university modern industrial colleges in view of the high degree of fit between the CIPP model and the process of university-industry-industry fusion activities in university modern industrial colleges. The recursive hierarchical structure is established according to the established index system, and the weights of the index system are calculated through the consistency test. The factor loading matrix of the first three principal components is constructed, and the modern industrial colleges are evaluated according to the principal components, and the mean values of the principal components 1, 2, and 3 are 0.27, 0.096, and -0.0186, respectively.In the calculated quality evaluation results of the integration of industry and education in modern industrial colleges, the score of educational and teaching achievements of the modern industrial colleges in Zhejiang Province is relatively low at 85.8439, which indicates that there is a gap in educational and teaching achievements, and there is a need to further improve the education and teaching achievements of modern industrial colleges. In addition, there are differences in the evaluation of the quality of industry-education integration in different modern industrial colleges in Zhejiang Province.The results of this study indicate that it is necessary to further optimize the construction path to meet the actual needs of industry-teaching integration in Zhejiang Province.

Lung cancer is the most common malignant tumor in humans and the leading cause of cancer-related deaths worldwide. In this study, we focused on the immune cells in the microenvironment of lung cancer at the protein expression level by IHC as well as mIHC techniques to explore the spatial distribution characteristics of immune cells within the tumor. To predict the prognosis of NSCLC patients and their potential response to immunotherapy, a machine learning-based immune-related prognostic model for lung cancer was constructed by combining Cox regression analysis, random survival forest and XGBoost algorithm, and the effect of the prognostic model was verified on the relevant dataset. The results showed that there were some differences in the immune cells between lung adenocarcinoma and lung squamous carcinoma in the lung cancer microenvironment, and the spatial distribution heterogeneity of CD3+ T cells and MHC class II antigen-presenting cells was higher in lung adenocarcinoma (P<0.05).The overall survival of high-risk patients was lower than that of the low-risk group in both LUAD and LUSC (P<0.01), and the immuno-associated prognostic model of lung cancer had a stable performance in the AUC value in multiple independent cohorts with stable performance, and the IRS model maintained high accuracy and stable performance in the training set and test set, which indicates that IRS has great potential for clinical application.

Rhythm matching of music and dance is an important research area in cross-modal analysis. In this paper, a music and dance rhythm matching algorithm based on time series analysis is proposed to extract the time series features of music and dance, and a genetic algorithm is used to determine the correspondence between music and dance movements to reflect the degree of correlation between changes in music and dance rhythm movements. In order to improve the matching and smoothing degree between the dance movement time series and the music time series, a constraint-based dynamic programming algorithm is introduced. The experimental results show that the model performs well in the matching degree and matching efficiency enhancement between dance movement time series and music time series, and its matching efficiency is 2-3 times of the traditional method. It shows high practicality in dance choreography and music matching, and can match any music clip with smooth and beautiful dance movements. The research in this paper provides new technical means for dance choreography and music matching, which will further optimize the transition harmony between music time series and dance movement time series.

This study takes the physical properties of high temperature devices as a starting point and the experimental apparatus used to obtain the study samples. The heat transfer process can be categorized into heat conduction, heat convection and heat radiation depending on the mode of contact. Under the theoretical support of the first law of thermodynamics, the nonlinear partial differential equations of the heat transfer characteristics of the high temperature devices are determined, and the above equations are analyzed by numerical simulation with the help of ANSYS software. When the thickness of the device is 1um, 8um and 15um, the heat transfer temperature and the power of the heat source show a monotonically increasing trend, in addition, when the thickness of the device is a fixed value, the spacing of the heat source and the heat transfer temperature show a nonlinear monotonically decreasing, and the present study has an important practical significance for improving the heat transfer performance of high temperature devices.

In order to explore the relationship between multi-source terrain features and lightning activity in Inner Mongolia, monitoring data and digital terrain elevation data of thunderstorm activity in Inner Mongolia from 2014 to 2025 were collected, and the spatio-temporal data mining method of mathematical and statistical analysis was used to analyze the distribution characteristics of lightning activity in Inner Mongolia. Based on the selected terrain feature factors, the machine learning method of multiple regression analysis is used to establish a research model of multi-source terrain features and lightning activity for quantitative analysis. The results show that the frequency of ground flashes in Inner Mongolia is mainly concentrated in May-October, accounting for more than 92% of the whole year, and the seasonal characteristics of its ground flash activities are significant, and the current intensity is mainly concentrated in the range of 20-40 kA. Correlation analysis reveals that multiple features of multi-sourced terrain are positively and negatively correlated with the frequency of lightning ground flashes and the current intensity (p < 0.05), and the prediction error of the constructed regression model for the ground flashes' frequency and the current intensity is 7.31%. The prediction errors of the constructed regression model on ground flash frequency and current intensity are 7.31% and 5.08%, which can provide a reference for lightning disaster prevention and mitigation in Inner Mongolia.

In response to the rapidly developing market demand, this paper proposes the use of genetic algorithms in industrial product design optimization under simulation environment. Design the product base gene coding, use the fitness function to determine the fitness value of different individuals, the genetic operator to support the optimization of industrial product design, by clarifying the optimal individual in the population in order to determine the optimization of industrial product design to meet the conditions. Then build up the industrial product design system based on genetic algorithm, plan the functional modules such as product information collection and coding, genetic generation of product solutions, and formulate the system process and function realization method. Exploring the performance of this paper’s industrial product design model in the simulation environment, this paper’s model in the operation efficiency, convergence speed and other aspects of performance are better than its other comparison model, in the iteration to about 300 times to achieve convergence. In the application practice of this paper’s design system, the values of this paper’s system are close to 1, and the RMSE values of each design parameter are lower than 0.5, and the average product quality score reaches 0.157, which is excellent in real-world applications.

The double bass, as the instrument with the lowest timbre and the largest volume in the string section of a symphony orchestra, is the “mainstay” of the orchestra’s acoustic effect, and grasping the bass performance mode in double bass performance is a problem that all double bass players need to explore in depth. A cluster-weighted multi-view kernel k-means clustering model (CWK2M) is proposed to study the local quality differences of the bass performance score views at the cluster level. The proposed weighted multiview clustering algorithm is then compared with several multiview clustering algorithms on several real multiview data for experiments and analysis of pitch change patterns. The experimental results show that, on the whole, the proposed algorithm in this paper obtains a relatively good clustering effect on each multiview data, especially on the Sens IT dataset of bass performance scores, the performance of each metrics is significantly improved, and the precision, recall, F1 value and NMI metrics are 0.632, 0.653, 0.687, and 0.713, respectively.In addition, the algorithm of this paper is utilized for the three bass playing patterns such as TaS1, Py11 and Mla1 are further analyzed, which further validates the universality and performance effect of the improved weighted clustering algorithm proposed in this paper for the analysis of pitch change patterns in bass playing.

The energy consumption problem of building complexes has become increasingly prominent along with the acceleration of urbanization. In order to achieve efficient energy saving in building complexes, this study proposes a Bayesian network-based uncertainty modeling in decision-making system for energy consumption management. By analyzing the uncertainty factors in the energy consumption data, a Bayesian network model is constructed to predict and analyze the energy consumption. And the uncertainty factors are used as decision variables to construct the energy consumption management decision-making system based on Bayesian network. The experimental results show that the uncertainty model and decision-making system constructed in this paper have more favorable performance compared with other benchmark methods, and exhibit smaller measurement errors in experimental tests. At the same time, the application of this paper’s decision-making system for energy consumption management of building complexes can significantly reduce management costs, and obtain the double benefits of reducing energy consumption and saving costs.