This PDF file contains the front matter associated with SPIE Proceedings Volume 12345, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

This paper will introduce two methods to calculate a quite complicated integral. This paper uses the answer of the former integral to calculate a more general integral which involves the arbitrary positive integer n. Back to the integral, the first method is quite traditional, the paper uses the property of the gamma function and the beta function. Through some basic transformations, this paper can induce it to the form, which uses some basic properties of this function to solve. The next method involves the residue formula. This paper will solve this problem in the complex plane and will select a suitable contour to solve this problem. To accomplish this task, it is also necessary to calculate the residue and use residue formula. Then it is not hard for us to generalize this proposition to an arbitrary positive integer n by a series of transformations. This paper wants to investigate this question in a totally different way, and show an accessible way to associate this powerful formula with the calculation of the integral.

In this paper, we introduce the almost average shadowing property(ALASP). Then, we prove that if an iterated function system IFS (𝑓₀, 𝑓₁) has ALASP, then F^k has ALASP for any K ε Z⁺. And we prove that if IFS (𝑓₀,𝑓₁) has ALASP and 𝑓_i is surjective for some 𝑖 ε {0,1}, then IFS (𝑓₀, 𝑓₁) is chain mixing.

Our project deals with the traveling salesman problem focusing on the distances between the most popular cities on the European continent under MTZ formulation. Currently, we have taken nine traveling spots into consideration and gotten the result of the optimal traveling route.

This paper mainly intends to integrate the multivalued function on the complex plane by using contour integral. The improper integral of a single-valued function on the real plane is often difficult to solve directly. In addition to solving the integral itself, we also need to judge its convergence and divergence. In order to solve integral of this kind, this paper extends its domain onto the complex plane. Then, we can find that this kind of function may become a complex multivalued function on the complex plane. However, if we use the contour integral, we can deal with the complex-valued function efficiently and then obtain the solution of the integral. Using contour integral to solve the integral in the complex field is applied in many fields. Contour integral can be used to solve partial differential equations, which can be applied in electrodynamics, quantum mechanics, hydrodynamics, and other fields.

When the classical Rosen’s method is applied to solving the dual of a convex programming problem, calculating the projection gradient direction at each iteration involves solving a minimization problem of Lagrangian function. By employing any parallel algorithms, an approximate solution can be obtained, which can approach any accuracy of the optimal solution. It is illustrated that, if the sequence of accuracies are properly chosen, the value of the dual variable at the -th iterate, generated by the modified Rosen’s method, converges to the optimal solution to the dual problem and the generated sequence also converges to the optimal solution to the original convex programming problem.

In this paper, the general concept of residue and general residue formulas are introduced. The general residue provides a method to study functions with infinite isolated singularities and the non-isolated singularities, which are the limits of sequences of isolated singularities. The general concept and residue theorem cover the shortage of the classical Cauchy residue theorem which can only deal with finite many isolated singularities. Then one uses the extended residue theorem on non-isolated singularities to calculate some infinite series. One can compute some classical series coming from different branches of mathematics, such as elliptic functions, number theory, and other examples. Using this method, one can see that it is a very useful method to deal with absolutely convergent series. More excitingly, this way is easy to use unlike most other methods for series. Thus, one can image that it has amazing applications in complex analysis and even other branches.

In this paper, we apply the perturbation theory on spectral radius and singular value of nonnegative diagonally dominant tridiagonal real matrix. It is found that if the off-diagonal elements and diagonally dominant vectors are bounded and form an inequality, then its spectral radius and singular value can be calculated with prescribed accuracies. In addition, our results can be applied to the problem of generalized eigenvalues.

This article is devoted to the numerical solution of the anomalous diffusion model governed by fractional diffusion equations using adaptive time stepping finite element method. We obtain a full discretization approximation by backward-Euler scheme in time direction and finite element discretization in space. An algorithm is given for the full discretization approximation by the adaptive time stepping method. The theoretical results is illustrated with numerical tests.

The analysis of complex variable function is mainly composed of two functions, two theorems and one series. They are holomorphic function, meromorphic function, Cauchy integral theorem, residue theorem and Laurent series. The theorems of meromorphic functions and complex analytic functions are the most important, especially complex analytic functions. These functions are defined on the complex plane, and their values are complex and differentiable. The commonly used theories, formulas and methods include Cauchy integral theorem, Cauchy integral formula, Residue theorem, Laurent series expansion and so on. As a research field of modern analysis, complex analysis was established in the 19th century. The main founders were Cauchy, Riemann and Weierstrass. This article mainly study and summarize holomorphic functions and Cauchy integral theorem. Cauchy's integral theory is the pioneer of complex analysis. It mainly describes the reason and extension of the independence of integral and path.

For solving nonlinear parabolic partial differential equations, some explicit methods have strict time step constraints and implicit methods have poor parallel scalability. So we propose a new explicit method for solving one-dimensional nonlinear parabolic problems. Taking advantage of its derivation mechanism, we put forward a simplified algorithm. This explicit RKL method adopts the s-stage strategy promoted by time to expand the time step, breaking the time limit of the previous explicit method in the parabolic problem, and it is easier to implement than the implicit method. Using shifted Legendre polynomials, we can intelligently obtain a scalable stable interval of the RKL method and the effective stable interval varies with s. We have designed some RKL schemes with a short recursive sequence and successfully implemented Burgers, Fisher equation, and other nonlinear problems. This fact has been verified.

The integral was introduced by Newton a hundred years ago. After that, Riemann gave a strict mathematical definition for integration. Integration has been widely applied in many fields. However, the Riemann integration has some limitations. Some integrals can be solved but they are not Riemann integrable. The most famous example is the Dirichlet function which is not Riemann integrable but Lebesgue integrable. We noticed that the Mellin transforms are closely connected to the theory of the Dirichlet series. Meanwhile, the Mellin transforms of some functions are not Riemann integrable, and they are difficult to be solved by some traditional methods but still can be solved in some other ways. Here, we will report a sample of solving one complicated integral of Mellin transform that has the form ∫∞0 t^s−1 f(t)dt by complex analysis. The result shows that some integrals of Mellin transform that are not Riemann integrable could be easily solved by the residue theorem.

This paper introduces a classic puzzle, the horse-in-pursuing problem, that N horses run in a counterclockwise direction to their neighboring houses with the same speed on an N-corners regular pentagon that has a side length of M. The problem will be simplified with a square case, that N=4 first, and then to the case of N-corners regular pentagon. This paper provides the solution using Complex Analysis and compares this solution with the classical solution in calculus, geometry, and mechanics.

During the past decades, the fractional differential equations (FDEs) have been widely used biology, stochastic dynamical system, and engineering to create the mathematical modeling of many complex phenomena. A great deal of effort has been extended by both mathematicians and physicists . As a result, various numerical and analytical methods for solving such FDEs have been established and developed such as Darboux transform method, the homotopy analysis method(HAM) fractional difference method, the Variational iteration method (VIM), the expansion method and so on.

For many centuries, people have done every possibility to find the number of prime numbers. During the 300 BC, Euclid had written a proof for there exist infinitely many prime numbers. However, the number of primes must be less than the number of integers. Hence, mathematicians started to consider precisely how many prime numbers are there comparing with all the integers. Until the end of 18th century, Gauss conjectured the total number of primes, and it was proven in the end of 19th century. The following paper will present a proof adapted from Ikehara in 1931. More precisely, the following paper converts the original problem into a better-behavior equation and then constructs another function to show the Prime Number Theorem with Function Theory and Fourier transforms. Notice that there are many more elegant proofs have been done during 20th century, and the following paper is for general understanding.

Many theories in complex analysis have their important applications in simplifying some problems in real analysis. There are many ways in applying the Residue theorem to compute real integrals. Gao Yuanyue gave specific examples of both real integrals and complex integrals to demonstrate the usage of this theorem. There used to be a hot topic toward the calculation of three kinds of integrals, which are respectively integrals of rational functions.

The way of Taylor’s series expansion is a kind of general operate and which are popularity in theory approximate in continuity functions . In fact , about the continuity random variable because of the vary of continuous , so it can use the way of continuity functions . this paper will be use the Taylor’s series expansion use in continuity random variable.

The aim of this paper is to introduce the notion of Interval-valued intuitionistic fuzzy (1,2)-ideals in semigroups and to investigate some of their properties. The characterizations of Interval-valued intuitionistic fuzzy (1,2)-ideals in semigroups are provided. It is shows that the intersection of two Interval-valued intuitionistic fuzzy (1,2)-ideals of semigroups is also an Interval-valued intuitionistic fuzzy (1,2)-ideal. These research results are helpful to enrich the fuzzy theory of semigroups.

The singular value decomposition (SVD) is broadly used in the dimensional reduction due to its universality for all matrices. We have deduced the mathematical formula of the SVD and logical thinking of SVD truncation. Dimensional reduction just uses the SVD truncation to select N biggest singular values. We have experimentally found that image compression used by SVD could greatly save memory without losing too much accuracy. The effectiveness of SVD could be directly shown in image recognition with complex data hierarchy. We also combined SVD with another useful dimensional reduction method named Principle Component Analysis (PCA). Our analysis indicates that the accuracy of both SVD and PCA could be guaranteed when processing a large number of data. Taken together with the data science and machine learning, SVD appears to be a fundamental tool of data processing. Our results establish a basic understanding of SVD in the application of dimensional reduction.

In this paper, we consider the phase field model by solving the nonlinear Cahn-Hilliard equation using a finite volume element method. A fully discrete approximation scheme is given and we obtain an algorithm for solving the discrete scheme based on the Newton-Raphson method. Numerical examples are provided to verify the theoretical results.

The report aims to analyse some differential equations qualitatively. Firstly, we examine some typical first-order autonomous differential equations like the logistic model. Then we discuss specifically about the behaviors of periodic solutions, in which we introduce Poincaré map as a strongly helpful tool. At last, the report respectively concludes the properties of different types of planar systems dependent on their eigenvalues.

Heterogeneity is an important issue in the study of causal reasoning.It is shown by whether or not individuals receive treatment and how they respond to treatment differently. In contrast to the conventional treatment effect, which ignores the effect of heterogeneity, a marginal treatment effect (MTE) was introduced to represent the marginal benefit of treatment, which is heterogeneously dependent on observed and unobserved factors. However, traditional methods prefer the curse of dimensionality in calculating MTE, leading to bias in empirical studies. In view of this, this paper proposes a nonparametric framework based on machine learning algorithms and theoretically validates the consistency of the approach. In our framework, we first consistently generate propensity scores from random forests, and then apply the propensity scores to the classical identification of MTEs. The innovative nonparametric MTE approach in this paper shows reliable consistency in the estimation of high-dimensional causal inferences and allows for a more efficient assessment of policy interventions.

Based on the perspective of Stackelberg game, this paper introduces the concept of fairness concerns into dual-channel supply chain research, and considers the factor of product return, and analyzes how the return rate and fairness concerns affect the optimal the pricing of supply chain members under three conditions: the supply chain members are fair and neutral, only the manufacturer is concerned about fairness and only the retailer is concerned fairness. When supply chain members feel unfair, they take steps to change the status quo, even at the expense of their own interests. This situation is known as fairness concerns. The numerical calculation software Matlab2021a was used to solve the game models under three different concerns, and finally the numerical simulation was carried out with the numerical calculation software Mathematica 12.1. The study found that with the increase of product return rate, the optimal direct price and retail price will gradually increase, while the wholesale price of the manufacturer gradually decreases. The optimal retail price will increase as the level of the manufacturer’s fairness concerns increases. The optimal online direct selling price of the manufacturer is not affected by the fairness concerns of supply chain members and the wholesale price will decrease as the level of the retailer’s fairness concerns increases.

There is always plenty of work for air-traffic controllers on control towers in airports. In addition to the busy air-traffic control for every plane, the air-traffic controllers also need to concentrate on taking off and landing process, which cost a lot of time and energy. As a result, the controllers have stressful work and the airport delay becomes normal. To relieve the controllers, we find out a way to select the best plane to land for an airport when the airport is busy. It can reduce their workload and help the airport improve the situation. By using this program, we can automate the process of landing. We used a method called greedy and genetic algorithm on this program to choose the best plane to land from a large number of aircraft. Also, we used ten sets of random data to test this method. The findings suggest that this program can choose the best plane one by one with an accuracy of 80 percent to 100 percent, which is about the same accuracy as human beings.

Based on the current situation that more and more people start to be interested in stock markets and try to earn some money through deliberate investments, the article would focus on helping people to make decisions on how to allocate money through the chosen industries so that they could obtain the lowest risk by receiving a combination which satisfies their need for return. The central problem shall be how to properly organize all the used methods and provide a visible chart to the audience; Therefore, the article will use Python to create a brief interface that could ultimately generate a webpage that shows both the specific efficient frontier and best weights of each chosen stock. In the calculation of the optimum weights in the efficient frontier, the paper is going to use quadratic programming to achieve that goal. The final result would be a brief program that could help people make decisions when they would like to invest in certain stocks.

The quartic generalized Ball basis functions of α, β, γ with three shape parameters are constructed, and the quartic αβγBall curve is defined.This curve can represent both the quartic Wang-Ball curve and the quartic Said-Ball curve. The properties of the quartic Ball curve and the geometrical meaning of the shape parameters are discussed, and the C¹, C², C³ continuity conditions between the two curves are analyzed, and an example of geometric modeling is given.

Taking 22 cities in the Long Hai-Lan Xin Economic Zone as the research object, this paper makes a statistical analysis of the regional, temporal, and spatial characteristics of the population distribution in each urban area and reveals the spatial evolution law of the Long Hai-Lan Xin Economic Zone. The results show that: (1) The spatial distribution of population density presents the characteristics of "low in the west and high in the east", and there are large differences between urban areas; (2) The temporal distribution of population density has obvious differences, which show an upward trend year by year; (3) The spatial distribution of population There is agglomeration in the layout, and the population "highhigh type" and the population "low-low type" are concentrated. (4) In the regression analysis of the influencing factors of the Long Hai-Lan Xin Economic Zone, the SDM model with individual fixed effects is determined as the best model. It shows that the regional GDP, average wages of employees, employees in the tertiary industry, and fixed asset investment in the whole society positively impact population distribution. Therefore, promoting the rational distribution of the population in the Long Hai-Lan Xin Economic Zone, it can be accomplished by adjusting the industrial structure, promoting the integrated development of the economic belt, and increasing infrastructure construction.

The health of the floating population is a weak link in the existing public service system. We sampled 3278 people from the floating population currently living in the four cities of Beijing, Shanghai, Tianjin and Chongqing. The number of years of residence of these populations was statistically compared by log-rank test, and univariate and multivariate Cox regression analysis were performed. The results showed that the difference in the number of years of residence of the floating population in the four municipalities was statistically significant (P <0.01). Age, city, health status, high blood pressure or type 2 diabetes, intra-year rash symptoms, and new rural cooperative medical insurance participation were the influencing factors (all P <0.05). Multi-factor analysis shows that age, place of residence, health status, and coverage of new rural cooperative medical insurance are independent influencing factors. The health coverage rate of the new rural cooperative medical insurance in Beijing, Shanghai and Tianjin is significantly different from that of Chongqing (all P <0.01). The number of years of residence of the floating population is highest in Tianjin, followed by Shanghai, Beijing, and Chongqing. The non-insurance of the new rural cooperative medical system is the risk factor and key reason for the minimum length of residence in Chongqing. Health status is a protective factor, indicating that disease is not a risk factor for the number of years the migrant population lives in the four municipalities.

With the continuous development of China's society, economic problems in various fields of society appear a trendofdiversification, and the methods of relevant researchers in the study of economic problems are also constantly updatedand changing. The vital superiority of the full application of probability theory and statistical methods to solve economicproblems in various industries has taken hold. Probability theory and applied statistics are both extremely important keypoints in mathematics. The branches of mathematics are mathematical statistics and mathematical probabilitytheory. The quantitative research and qualitative analysis of economic problems in various industries have become the most effective construction methods.

With the rapid development of network technology and social economy, the increasing number of non-litigious conflicts and disputes has stimulated the rapid development of online conflict and dispute mediation mechanisms in countries around the world. How to scientifically and efficiently improve the quality of conflict mediation and facilitate the parties to reach an agreement is crucial to effectively mediate conflicts and disputes, prevent them from escalating, and maintain social harmony and stability. In this paper, a fuzzy comprehensive evaluation method is used to evaluate the quality of conflict mediation based on the "online multi-conflict integration platform" in city H. The application of this evaluation method shows that it can better evaluate the quality of conflict mediation. The application practice shows that the evaluation can reflect the conflict mediation situation more objectively and multi-dimensionally, and provide data support for further improving social governance and implementing personalized conflict mediation guidance.

Saihanba ecological area is a concentrated distribution area of natural vegetation drawn from the forest land under the jurisdiction of Hebei Saihanba mechanical forest farm. Through the construction of ecological area, Saihanba has realized the transformation from yellow sand, no birds and trees to green development. Therefore, the study of Saihanba ecological area has deep academic significance. However, scholars mostly start from the qualitative point of view on the effect of Saihanba forest ecosystem Nature Reserve. This paper first uses the analytic hierarchy process model (AHP) based on entropy weight method (EWM) to analyze the impact of Saihanba ecological area construction on the local environment from the qualitative and quantitative point of view. Based on this model, this paper makes a qualitative and quantitative evaluation on the effect of the model extended to the whole country, and demonstrates its impact on China's carbon neutralization effect. The model data shows that the Saihanba for ecological area construction plays a positive role in promoting the environment. The score shows that the environmental score of Saihanba in 2020 is 32 times that of the year before the implementation of ecological area, which fully demonstrates the effectiveness and importance of the Saihanba ecological protection model and is an important measure of China's green mountain strategy. In order to explore whether the Saihanba ecological protection model has popularization significance for the whole country, the cluster model is used for research and analysis. The research shows that the Saihanba ecological protection model has a positive reference effect for other regions in the country. Through the model calculation and analysis, it is found that China is positive for the realization of carbon neutralization. However, if some cities in China implement carbon neutralization at the current speed, they may not be able to achieve the goal of carbon neutralization, Therefore, through the verification of linear regression equation model, this paper puts forward some suggestions to improve the planting rate and strengthen the implementation of carbon neutralization policy.

In order to further analyze the reasons and backgrounds of the implementation of the "Three -Child Policy", and find experience in the implementation of the "three -child policy" in the implementation of the "comprehensive two -child" policy. On the basis of the implementation of the implementation of the "comprehensive two -child" policy of Harbin City, the effects of the implementation of the "comprehensive two -child" policy implementation of the "comprehensive two -child" policy of Harbin City, which aims to promote the smoothness of the "three -child policy" of Harbin City Implement. This article uses SPSS to fully analyze statistical data, and uses a deck inspection method for scientific verification.

With the increasingly fierce competition in tourism industry, the service quality of tourist attractions must keep up if they are to develop, especially the current form of tourism gradually tends to quality and refinement, and tourists have higher expectations and requirements for tourism quality. Based on this, Zhaoxing Dong Village Scenic Area in Liping County, Qiandongnan Prefecture, Guizhou Province is selected as the research object, and the index evaluation system is constructed by using literature research method and interview method, etc. The data is obtained by issuing questionnaires through field research, using software SPSS analysis data，and the index data is analyzed by using modified IPA method. The study found that the scenic spot still needs to be improved mainly in the aspects of catering service, tour service and shopping service. In response to the research results, the following suggestions were put forward: to create "a theme of multiple forms, with a chain of pearls" form of catering development; to strengthen the "one center, multiple support" tourism route planning; to promote the realization of "shopping four Shopping services" and other recommendations.The proposed improvement countermeasures will help Zhaoxing Dong Village scenic spot to improve the quality of tourism services and promote the sustainable development of the scenic spot.

This paper presents an obstacle recognition algorithm for field road network, including obstacle element extraction based on digital elevation model (DEM), determination of traffic factors affecting path planning, rasterization of terrain environment, obstacle recognition algorithm, establishment of overlapping grid of traffic area, description of passable area and non-passable area, etc. Combined with the actual project, it has achieved good results.

Bridge is a worldwide intellectual sports activity. The playing method of bridge is inseparable from mathematical probability, especially the original probability and subsequent probability are widely used in bridge. This paper interprets the mathematical meaning of the original probability and subsequent probability, and analyzes in detail the impact of the changes of the original probability and subsequent probability on the winning chance of bridge through specific cases.

Aiming at the problem of UAV track evaluation, the main evaluation indexes related to it are analyzed from three aspects (performance, mission and defense) that affect the track quality. The target weight is determined by the entropy weight method, and the track evaluation model based on TOPSIS is established. Finally, the availability of the model is proved by an example.

This paper presents a global static planning algorithm for field road network. The algorithm is composed of obtaining or setting the starting point and key point model, setting the force type model, setting the planning mode model, global static planning model, etc. The global static planning model includes Astar path planning algorithm and the improvement of Astar path planning algorithm. Combined with the actual project, it has achieved good results.

In recent years, data mining algorithms have been widely recognized as an important way to predict diseases. In the medical field, we are often faced with massive data. How to choose a model and improve the model to obtain better results is a problem that researchers are committed to solving. This paper starts with the classification model of Support Vector Machine, and optimizes the its parameters by processing the data. We used the previous Genetic Algorithm for comparing, and proposed an improved Genetic Algorithm to optimize the prediction of Support Vector Machine on the Coronary Heart Disease dataset. The experimental results show that the improved Genetic Algorithm has better prediction accuracy than the previous Genetic Algorithm.

The integration of high-speed railway Internet of things(IoT) and it industry is deepening, new technologies emerge in endlessly, and security threats are also increasing. This paper introduces in detail the four threats to the equipment, data, network and application security of the high-speed railway IoT, summarizes the security characteristics of the high-speed railway IoT, puts forward the necessity of building a comprehensive security protection system covering the "Cloud, Management and Terminals" of the high-speed railway IoT, and finally designs a comprehensive security protection system of the "Cloud, Management and Terminals" of the high-speed railway Internet of things. This paper focuses on the comprehensive security protection system of "Cloud, Management and Terminals" of high-speed railway Internet of things, makes up for the lack of traditional railway IoT security protection system, and puts forward corresponding security protection strategies according to the main security threats of each security partition of high-speed railway IoT, so as to provide more thinking and direction for the security research in the field of high-speed railway IoT.

This paper presents a design method of radar jamming simulation software. The software is composed of radar jamming decision simulation model, radar jamming simulation master control model, radar automatic selection jamming simulation model, radar jamming simulation model, data transmission and integration model. Combined with the actual project, good results have been achieved.

This paper provides a method to assess the spread of an epidemic in a community using household data, first using a chain binomial model to elucidate the pattern of spread of the epidemic in households, fitting a series of chain binomial models to estimate escape probabilities and obtaining estimates of contact rates. The basic reproductive number was further estimated in combination with a deterministic compartment model SVEAI_QI_NR constructed based on an epidemiological dynamics approach including control measures to assess the spread of the epidemic in the community. The analysis reached the basic reproductive number of 5.2 in the community, with R₀<1 thus predicting the spread of the epidemic in the population during the period. Next, numerical simulations were conducted to investigate the effective reproductive number, an important parameter in the development trend of the epidemic, and to further evaluate the effectiveness of control strategies quarantine, antiviral drugs, and vaccines in controlling the epidemic. The simulation results show that isolation measures and vaccination play a very important role in controlling the spread of the epidemic when antiviral drugs are not sufficiently effective. Sensitivity analysis was performed to analyze the effect of parameters on the cumulative increase infected individuals, and it was concluded that it is also crucial to improve the effectiveness of vaccines when taking vaccination measures in the prevention and control of outbreaks.

In this paper, from the perspectives of enterprises, suppliers and transporters, the ordering and transportation of raw materials of production enterprises are modeled to research, mainly using intelligent algorithm, to solve the ordering and transportation of raw materials of production enterprises multi-objective optimization model, with comprehensive application of Matlab.The software solves the problem and draws a conclusion that meets the requirements of the topic. Apart from that,this article uses simulated annealing algorithm to solve the minimum number of suppliers, and establishes a multi-objective programming model about the balance of interests of enterprises,suppliers and transporters,and use particle swarm optimization algorithm (PSO) to determine the best procurement scheme of raw materials.

The construction of professional dynamic adjustment early warning evaluation model in higher vocational colleges is the need to promote and improve the construction and management of the national "double high plan", the need to complete the construction objectives and tasks of the "double high plan" with high quality, and the practical need to innovate and enrich the performance index evaluation system of higher vocational colleges. Based on AHP analytic hierarchy process, this paper designs the mathematical model of dynamic adjustment and early warning evaluation of Higher Vocational Majors, which is monitored from six first-class indicators: student source and scale, school enterprise cooperation, professional teaching guarantee conditions, professional teaching and construction, scientific research and social services, training quality and social reputation, and calculates the comprehensive ranking of Majors Based on the data of higher vocational talent training status, which is an important basis for professional dynamic adjustment. The model is used to measure the specialty of Chengdu Vocational and technical college. The calculation results are consistent with the actual situation of the University, which proves that the evaluation model is effective and can be popularized.

Since the outbreak of the novel Coronavirus in 2019, every country around the world has invested many resources in vaccine research and development. The goal of this paper is to investigate the current vaccination status around the world. And using the time series model to have a general grasp of the future vaccination trend. We used the Seasonal-ARIMA Model to predict the vaccination status in the next two years based on the collected data. Seasonal-ARIMA model, as a very commonly used model in time series forecasting, has a relatively good performance in forecasting. The data in this article comes from the OWID organization (our world in data), which is a non-profit organization based in the United Kingdom focusing on large global issues. And the data from this organization has high credibility. We have a prediction of future vaccination by writing this article, which can serve as a reference for the relevant departments to formulate vaccine production plans.

In 2021, the national economy gradually recovered from the epidemic. Under the development plan of "carbon peaking" and "carbon neutralization" mentioned in the meeting of the Political Bureau of the CPC Central Committee, driven by the leading stocks in the new energy sector, the A-share market environment has steadily improved and the market is expected to be repaired. In line with the central bank's RRR reduction policy in July, monetary liquidity has also been further relaxed. In this case, the Shanghai composite index was maintained at 3200 points throughout the year, although there were fluctuations caused by valuation deviations and events. But it is also an important sign of the overall improvement of China's economy. At the beginning of 2022, the central economic work conference proposed steady growth. The conference required that the economic work in 2022 should be stable, seek progress while maintaining stability, and the macro policies should be stable and effective. After setting this development tone, both the monetary policy of the central bank and the credit scale of commercial banks have been adjusted, and the stock of structural loans has increased, which has played an important role in the economic recovery under the prevention and control of the epidemic. Then, in the recent April of 2022, the A-share market was affected by the fluctuation of RMB exchange rate, and the RMB assets depreciated seriously. Coupled with the outbreak of the epidemic in Shanghai, the Shanghai stock index fell all the way below 3000 points. The previous high valuation sectors such as medicine, new energy, Internet and other industry leading stocks were also seriously damaged. The market sentiment is low and the trading volume shrinks, as if there was a signal of bull bear market conversion. In this regard, we have to think about where the future of Shanghai stock index is and whether we can make a reasonable prediction of the future situation with the help of existing data and models. The paper takes the daily closing price data from the SSE 50 index from 2004 to 2022 as the research sample, using the ARMA model to analyze the yield. Also, it conducts the thorough research on the stock index, which predicts the yield of 300 trading days in the future. According to the model, it is predicted that the yield rate will fluctuate between -0.03 and 0.03 in the next 300 trading days. Through predicting the data obtained from the model, we put forward related suggestions on current government policy and personal investment.

This paper mainly provides a method to evaluate the contribution rate of equipment system based on machine learning. Firstly, the index system of contribution rate evaluation of equipment system is established, the requirements of evaluation are clarified, and the normalized data is used as input. The evaluation model based on Principal Component Analysis (PCA) is built, and the contribution rate of the system is sorted by weight calculation. This paper uses experiments to verify the validity of our method.

As the world's first and by far the most important cryptocurrency, Bitcoin's price has a strong volatility, which in turn may bring huge profits to investors or return to the original point overnight. Coupled with the dominance of Bitcoin in the currency market and its innovative nature, in summary, both from the perspective of investors and from the perspective of the country as a whole, such research on Bitcoin value prediction will have important practical and practical value. This article selects the daily value of Bitcoin from NASDAQ from January 2021 to March 2021 as data, and will use the ARIMA model and SPSS software to predict prices for the next seven days. By finding the relative error between the predicted value and the actual value in the next seven days, it is found that the values are very small, indicating that the prediction effect of the model is good, and the ARIMA model can be selected as a short-term prediction of the value of Bitcoin.

This study focuses on the role of institutional investors in stock split using a unique dataset from Chinese A-share market. The empirical results of multiple regression analysis based on STATA software suggest that there is a positive announcement effect in Chinese stock market. We further find a significantly negative relation between the announcement effect of stock split and the shareholding ratio of institutional Investors, indicating that institutional investors may supervise and impact firms’ stock split decisions and market effect. Particularly, we find the attention of institutional investors have stronger impact on the abnormal return of stock split in volatile markets than in bull and bear markets.

In view of the complex and polymorphic structure of satellite networks, this paper proposes a K-Terminal communication reliability modeling method of satellite networks based on fault tree and Bayesian. Firstly, the fault tree is established according to the available path information that meets the QoS constraints, and then the corresponding relationship between the fault tree and Bayesian network is summarized. Finally, it is expressed with the help of Bayesian network. Combined with the conditional probability table, the two-way evaluation of satellite network is carried out by using Bayesian theorem, and the k-end path reliability of satellite link in different states is obtained. The results show that the model can not only improve the problem of multi-state network modeling, but also reduce the complexity of previous modeling.

Rainstorm and flood disasters caused by short-term heavy precipitation often lead to huge losses in the agriculture and animal husbandry in Xinjiang. In this study, the five disaster elements of rainstorms and floods in Xinjiang are used to construct the disaster loss index using the ratio method and the dimensionless linear combination method. The probability distribution function is used to classify the disaster loss index of counties and cities into four grades, mild (grade 1), moderate (grade 2), severe (grade 3), and extremely severe (grade 4). Further, the spatial and temporal distribution of disasters and their causes are analyzed. Results show that the five disaster elements exhibit significant geographical variability, with grade 4 disasters concentrated in the Yili River Valley and Kashgar Prefecture. There were frequent rainstorm disasters between April and August, with those in July being the most serious. The interannual variation of fatalities, collapsed houses, collapsed livestock shelters, livestock deaths, and the ratio between affected area and sown area all showed a significant linear decreasing trend between 1986 and 2019. When there was not much change in the hazard of short duration heavy rainfall, the enrichment projects and emergency relief systems implemented by the Xinjiang government have played an important role in disaster prevention and mitigation, ensuring a year-by-year disaster loss reduction.

With the continuous development of society and the continuous progress of the economy, computer technology has gradually penetrated into every corner of life. At the same time, scholars continue to apply computer technology to study the development of the new energy vehicle industry. developing and fostering new energy vehicles become the response to climate change and solve the problem of environment pollution and energy security multiple, one of the important ways of the government as a "one hand", how to effectively play a role of guiding, regulating, promote new energy upstream and downstream enterprise cooperative innovation, break the technical barriers, realize the transformation of scientific and technological achievements, Completing industrial upgrading is an urgent problem to be solved. Based on evolutionary game theory, this paper establishes an evolutionary game model of cooperative innovation involving vehicle enterprises, battery enterprises and government, and analyzes the process of continuous learning evolution of both sides from the perspective of government regulation. In order to verify the validity of the model, MATLAB software is used for numerical simulation to simulate the influence of the changes of various parameters on the evolution results. The results show that R&D subsidies and tax policies have more significant effects on cooperative innovation. Appropriate R&D subsidies and tax policies can improve the initiative of innovation subjects, and the effect of multiple policies is more obvious, and R&D subsidies still play a leading role in the incentive mechanism. The benefits of social reputation effect can improve the government's credibility and the enthusiasm of participating in cooperative innovation activities.

This article analyses the trends in viewership of four popular videos over approximately 500 samples in time on the bilibili, a video platform. According to the statistical law, it is found that the number of video views obeys a non-homogeneous Poisson distribution. To further explore the time-varying patterns of playback volume, describing the impact of changes in viewership and the growing Internet market on video views, we built a model for online video popularity, and verified it with actual data. This model reveals the dissemination mechanism of online video. The findings provide theoretical support for facilitating or inhibiting the dissemination of video.

Taking N service-oriented manufacturing enterprises as the research object, this paper analyzes the factors affecting the digitization level of service-oriented manufacturing enterprises through yahhp software and AHP method from the four aspects of innovation process, innovation environment, organizational factors and innovation benefits. The importance ranking of digital innovation mode in each link is obtained by TOPSIS method throughMATLAB software. It can not only promote the development of the digital innovation mode of N service-oriented manufacturing enterprises, but also have a certain reference significance for the improvement of the digital level of other service-oriented manufacturing enterprises.

Based on the grey prediction model, some data after GTD treatment of Guatemalan terrorist attacks are analyzed and predicted. Firstly, the grey prediction model is introduced. After understanding the principle of grey prediction model, python tool is used to calculate and accumulate the processed data to obtain the adjacent mean sequence, the application of least squares method, and the modeling. Finally, the prediction model is generated by using the obtained values of ' a ' and ' B '. According to the judgment standard of the prediction time of the model - far less than 0.3, the suitable prediction range of the model is ' suitable for medium and long-term prediction ', which provides a reference model for future data prediction.

Numerical solution of the Black-Scholes (referred to as the BS) equation is obtained by using semi-implicit EM method, and convergence of numerical solution is analyzed. The effectiveness of the method is verified by a specific example. The theoretical results are verified by numerical simulation.

In order to efficiently match and use the monitoring information obtained by the EMU fault detection robot, image registration technology can play a role. Facing the operation site of EMU fault detection robot, based on the original image data information of vehicle bottom fault collected by EMU fault detection robot, this paper carries out gamma transform and windowing preprocessing on the vehicle bottom image of EMU, puts forward the image registration algorithm of vehicle bottom fault detection of EMU based on Fourier transform, and gives the specific operation process of this algorithm. The experimental verification and comparative analysis show that compared with the image registration technology of EMU underbody fault detection based on Fourier transform, the image registration technology of EMU underbody fault detection based on conventional affine transform has obvious advantages, high effectiveness, strong robustness, accuracy and reliability, and can complete the high-precision, stable and reliable matching of images in a reasonable time, which meets the requirements of field practical application. The research of this paper provides theoretical support and technical basis for the intelligent identification of vehicle bottom fault defects of EMU, and has a good application prospect.

Taking the oil reservoir managed by an oil production plant as the main object, and mainly aiming at the problems existing in the current oil reservoir dynamic analysis, such as the heavy workload of data statistics, the incomplete function of drawing pictures, and the cumbersome filling of reports, we have fully investigated the current technical cadres of the whole plant. On the basis of understanding the current data requirements, functional requirements and operating habits, through the basic database, an intelligent management data platform for reservoir dynamic analysis is established. The system can meet the current reservoir dynamic analysis data statistical query, curve drawing, automatic report generation and other functions, provide convenience for development and analysis, and improve work efficiency and quality.

Bitcoin, as a new mean of circulation, has a great impact on gold market. The investment of Bitcoin and Gold has recently attracted intensive attention from financial institutions, and the capital markets. This paper proposes an investment strategy based on Title C of the 2022 Mathematical Contest. This paper establishes an LSTM time series forecasting model. After data processing and training with indicators such as MACD as features, a forecasting model and the predicted data are obtained. For the decision strategy, this paper builds a model that seeks the maximum return as well as the minimum risk based on Markowitz portfolio investment theory and Sharpe ratio. Calculated by genetic algorithm, the final return are calculated to be 207,612.96 USD.

COVID-19 disease, a new infectious disease that has emerged in recent years, poses a serious threat to humans. In this paper, a household epidemiological model was used to study the spread of COVID-19 in the community, using the viral load-based household model of infectious diseases proposed by Becker, combined with the chain binomial model, to derive the household reproduction number. The results of the sensitivity analysis showed that isolation and antiviral treatment were effective in controlling the spread of the disease; hospital isolation was more effective than home isolation in controlling the spread of the COVID-19 disease in the community; and the earlier the isolation, the more effective the prevention, suggesting that when faced with a serious outbreak of infectious disease, The rapid response of the government to ensure adequate health resources can effectively reduce the number of infections in households and effectively contained the rapid spread of the epidemic. The analysis of antiviral drugs shows that timely treatment of infected individuals with antiviral drugs is an effective way to control outbreaks, and that delayed use of antiviral drugs can lead to a reduction in the effectiveness of isolation measures. Therefore, researchers should accelerate their research to develop targeted antiviral drugs as soon as possible.

Under the constraints of carbon emission trading policy, can enterprises achieve environmental protection and economic growth at the same time? This paper selects heavy polluting enterprises listed in Shanghai and Shenzhen A-shares from 2008 to 2019 as research samples to empirically study the impact of carbon emission trading policies on the economic and environmental performance of heavy polluting enterprises. Then, the robustness of the results was tested by counterfactual tests, exclusion of other policy interference and falsified experiments. The results show that the carbon emission trading policy has a positive impact on the economic performance and environmental performance of heavy polluting enterprises, but the impact presents significant regional heterogeneity, on the other hand, due to the different nature of corporate equity, the impact of policies on corporate environmental performance is also different. Finally, green innovation does play a mediating role between carbon emission trading policies and corporate environmental performance, but the moderating effect of government subsidies is not significant. Therefore, the government should make rational use of modern information technology to guide the implementation of carbon trading policy and promote high-quality economic development.

Based on China's prefecture-level city data from 2002 to 2018, this study empirically analyzes the impact of high-speed rail (HSR) connection on international technology spillover. The results find that one new HSR train serving a city facilitates international technology spillover. Heterogeneous analyses show that the western in China is significantly affected by HSR connection, which the effect is not obvious in the eastern due to the original developed transportation network. Further examination shows that the effect of HSR connections is stronger for regions with lower initial human capital with regard to international knowledge flow.