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Nondestructive testing technology, as an indispensable part of modern industrial production, is of great significance for guaranteeing product quality, improving production efficiency, and ensuring production safety. This paper is based on nondestructive testing and electromagnetic sensing detection technology research. The study first adopts ACFM detection to analyze the sensitivity of the surface defect parameters of the material to be detected, and based on the analysis of the magnetic circuit of the electromagnetic sensing structure, to build a mathematical model of ACFM and electromagnetic coupling probe, and then through the magnetic method of non-destructive testing on the material cracks in the detection of the signal effect of the study. The results show that the amplitude of the response signal increases with the increase of the defect angle from 0 to 7 ms, reaching a maximum value of 0.24–0.26 around 6 ms. The amplitude of the response signal decreases with the decrease of the defect angle from 7 to 14 ms and reaches a minimum value of −0.16–0.18 around 14.5 ms. The amplitude of the detection signal is related to the depth of the crack and the length of the surface defect of the steel sheet specimen. The crack depth and surface defect length of the steel plate specimen influence the detection signal’s magnitude. When the defect depth and surface length of the steel plate specimen are 1.5 mm, the detection signal value is weak, and the noise on the surface of the steel plate specimen has a significant effect on the detection signal. Promoting the development and application of NDT technology is greatly aided by the results of this paper.

Relying on advanced technology, the financial shared management model realizes a breakthrough for the enhancement of enterprise financial management capability, and provides effective support for enterprise decision makers while mining financial risks. In this paper, the support vector machine algorithm (SVM) is used to construct a financial risk prediction model for e-commerce enterprises, and the radial basis kernel function (RBF) is selected among various kernel functions to enhance the discriminative ability of SVM. At the same time, the particle swarm algorithm (PSO) is introduced to optimize parameter γ and penalty factor C of the RBF kernel function, and the PSO-SVM fusion model is constructed, so as to improve the prediction accuracy of the e-commerce enterprise financial risk prediction model. After the experimental analysis of this paper on the various capabilities of enterprise financial management, it is found that the operating cash flow ratio of the e-commerce enterprise is less than 40% in 2017-2021, and reaches a minimum of 3% in 2020, which indicates that the Z e-commerce enterprise has insufficient ability to raise debt to operate, which may cause problems such as a decrease in the rate of return on assets. In addition, the cash flow of the e-commerce enterprise is highly variable, and the cash outflow from operating activities is significantly higher than the cash inflow in 2020, resulting in a negative net inflow of −111,451,575,000 yuan. It indicates that the Z e-commerce enterprise has a low degree of control over cash flow, and there is a financial risk of a sudden break in the capital chain. Therefore, the risk prediction model constructed in this paper can uncover potential hidden financial dangers and risks by analyzing the financial data of e-commerce enterprises.

Tantou woodblock prints are traditional Chinese woodblock prints with a long history. Adding modern information technology elements to the excellent traditional culture can better combine regional contemporary woodblock prints and realize the cultural heritage. In this paper, from the perspective of modern informatization inheritance, we propose a way of displaying Tantou woodblock prints with AR enhancement technology, which breaks the limitation of physical experience with the help of virtual technology and improves the immersive experience of Tantou woodblock prints by combining with visual SLAM spatial localization technology. Based on the KANO model, the inheritance effect of Tantou woodblock prints was empirically analyzed. The data of Q, A, I, R, M, and O of the satisfaction results of the experience effect of Tantou woodblock prints were 1.132, 3.034, 2.828, 1.422, 1.237, and 0.978, which belonged to the excitatory type of demand. The inheritance satisfaction could be improved by enhancing the natural experience effect. The percentage of experiencers’ satisfaction with the information acquisition rate of Tantou Wooden Plank New Year’s Paintings that reaches excellent and above is 82.35%, and this paper effectively captures the user’s experience point in the visual, which contributes to the inheritance of Tantou Wooden Plank New Year’s Paintings.

Aerobics is an internationally famous fitness and sports competition program. This paper aims to design an aerobics arm movement trajectory recognition method with the assistance of a sports computer to detect aerobics movements in real-time. The study first introduces the Gaussian kernel function based on the Kalman filter pose solution method to construct the aerobics arm GP-SUKF pose solution model. The acceleration data are then coordinate transformed to remove the gravity component of each axis, and the features of the aerobics action trajectory are extracted by combining the time-frequency domain integration method and eliminating the cumulative error. Finally, a support vector machine algorithm based on particle swarm optimization is constructed to classify and identify the features extracted from the trajectory of the extracted aerobics arm. In the simulation experiments, the algorithm in this paper provides more motion trajectory points for the aerobics arm movements. It is closer to the actual value of the wrist movements offered by the OptiTrack system, with the error ranging from 0.02m to 0.04m, and a better tracking effect can be obtained in the case of fast movements. This study can accurately track the trajectory of aerobics arm movements and provide more accurate posture and movement assistance for professional athletes and bodybuilders.

Due to the characteristics of clean and efficient hydrogen energy and its wide application, hydropower hydrogen production has become one of the potential technical means to reduce the new energy abandonment rate, and its economic benefits are analyzed in this paper. After exploring the operation characteristics of hydropower plants, the paper examines the characteristics of water and energy abandonment in combination with the calculation method of hydropower plant power abandonment, mathematically models the relevant equipment of hydropower hydrogen generation and consumption mode, and establishes a hydrogen storage and consumption model considering the capacity of storage. Based on the economic index of hydropower hydrogen production, the storage capacity of the hydropower hydrogen consumption mode is configured by combining the two-layer planning algorithm. Finally, a simulation experiment is carried out to analyze the hydropower hydrogen consumption model established in the paper and explore the optimal storage settings for hydropower hydrogen consumption. The results show that the optimal energy storage capacity of the demonstration base is 1MWh kWh cost of electricity is 0.113 yuan/kWh respectively, the whole life cycle NPV is the largest, is 7.39×106 yuan, the daily profit including hydrogen sales, electricity sales, and energy sales is about 463,110,000 yuan, and the incremental daily profit is about 144,980,000 yuan. Based on this study, we aim to promote the sustainable development of the new energy economy.

With the development of the social economy and the improvement of people’s living standards, the role of insurance in society has become increasingly important. The insurance industry’s growth is not in line with social demands. Insufficient insurance capacity or a mismatch between insurance products and demands in specific regions or industries can lead to increased social risks and unprotected interests. Taking Shanxi province as an example, it is a substantial industrial and energy base in China with abundant resources such as coal and power. Shanxi province is facing challenges of transformation and upgrading due to the transformation of economic structure and the increasing environmental awareness. The matching problem between social demands and insurance capacity becomes particularly important in this process. This paper aims to examine the issue of insurance demand and supply matching, using Shanxi province as a case study. The demand for insurance protection is increasing as social risks increase with rapid economic development and improvements in people’s living standards. However, there is a gap between insurance capacity and social demands, which limits the development of the insurance industry and the effective management of social risks. The characteristics of insurance demands and the current situation of insurance supply in Shanxi province are analyzed through a literature review and empirical research methods in this paper. It discusses the problems and shortcomings of the insurance industry in meeting social demands and proposes a series of policy recommendations to promote the matching of insurance demands and supply.

The information industry has increasingly become the dominant modern economy, and the introduction of informationization into enterprise management has become one of the necessary means for enterprises in various countries to improve their competitiveness and enhance their vitality. This paper is dedicated to studying the impact of information entropy and information gain ratio on enterprise management decision-making, which further confirms the necessity of modern enterprise management to implement informationization. This paper defines the relationship between information entropy and information gain ratio in enterprise management and establishes a comprehensive evaluation model that matches the two. The objective of indicator assignment improvement is improved by using weight determination based on information entropy to solve the issue of weighting between different indicators of two layers. According to the advantage that the information gain ratio can reflect the information orientation, the expert’s primary viewpoint assignment in the traditional enterprise management decision-making is replaced by the ratio of the information gain ratio of the sorted neighboring indicators to obtain the weights of each evaluation indicator. Taking enterprise Y as the research object to carry out empirical analysis, the entropy weight value of “consistency with the planned target” is 0.8599, which is an essential factor affecting the enterprise management decision. It can fully reflect the information orientation of the data itself and the subjective will of the experts or decision makers, which not only overcomes the shortcomings of the existing assignment methods that cannot objectively reflect the information orientation of the number or the subjective will of the experts or decision makers but also avoids the drawbacks of the existing combination assignment methods that cannot reasonably allocate the combination coefficients.

Labor education is a meaningful way to cultivate students’ comprehensive quality and a new requirement for education development in the context of the new era. This study aims to establish a labor education system for higher vocational colleges and universities, using the theoretical support of three-course parallelism and optimizing and integrating labor education resources through system dynamics. On this basis, the study uses a factor analysis model to explore the dynamic mechanisms of this education and a fuzzy comprehensive evaluation method to quantitatively analyze the quality of this labor education approach. In the empirical analysis of higher vocational colleges and universities, the effect of labor education in this paper improves by about 11 points compared with that of traditional education. The average scores of the six indicators of labor education based on the three parallel classes are all above 4 points, which is at the level of “excellent.” The optimization of labor education resources in this paper can effectively improve the utilization rate of resources and provide a guarantee for the labor education system based on three parallel classes, thus improving the overall effect of labor education, giving full play to the intrinsic value of labor education, and contributing to the overall development of students.

As a specific social group, the consumption behavior of college students not only reflects their economic ability but also contains deep-seated values and attitudes toward life. With the development of the social economy and the change in consumption concepts, the consumption patterns and psychology of college students have diversified. This paper deeply analyzes the characteristics of college students’ consumption behavior and the value of their ideological and political education. It also adopts the ADDIE model to systematically study college students’ consumption behavior. The improved K-means clustering algorithm allows us to classify the consumption behavior of 29,635 students and analyze their changing trends by collecting consumption data. The average monthly consumption of most students is approximately 800 to 1000 yuan, and the frequency of consumption is mainly 60-75 times per month. Students with different consumption levels have different needs and responses when it comes to ideological and political education. The paper proposes targeted strategies for ideological and political education to guide students in establishing correct consumption concepts and cultivating rational consumption behavior. The study effectively enhances the research on college students’ consumption behavior and the practical effect of ideological and political education through the application of the ADDIE model, providing support for the overall development of college students.

In this paper, we first establish the model of optimal allocation of water resources within the region and convert it into a dynamic planning problem. Then, under drought conditions, the models of optimal allocation of intra-regional water resources among industries and different crops are established, respectively, and the water production function model is established using sensitivity coefficients. Under the condition of satisfying the water quantity opportunity constraints and with the objective of ensuring obtaining a higher system return, the water resources optimal allocation model based on interval multi-stage stochastic opportunity constraint planning is established by combining multi-stage planning, interval planning and stochastic opportunity constraint planning. A hybrid intelligent algorithm combining stochastic simulation, multilayer neural networks, and genetic algorithms is used to solve the model. A case study of optimal water resource allocation is used to verify the feasibility and validity of the proposed model and algorithm. Under the traditional water resource allocation scheme, the total water supply and water shortage of Nandan County are 0.97 and 0.58 billion m3, and the water shortage rate is 37.55%. Under the optimized water resources allocation scheme of this paper, the water shortage of Nandan County is 0.05 billion m³, and the water shortage rate is 6.09%. The model of this paper’s allocation scheme can effectively meet the water demand.