bluuebunny/crossref_metadata_2025 huggingface dataset:
Achievement Motivation and Job Performance of Township Cadres: The Mediating Role of Thinking Style and Professional Knowledge
Authors: Zhao Yuxuan
Published: August 2024

Achievement motivation, scientific thinking and knowledge skills are three levels of personal characteristic variables are an important part of human competence, they have a very important role in determining their own work performance. But in reality, people tend to ignore the achievement motivation, which is the most profound variable and the biggest influencing factor. At the same time, in the original theory, the intermediary path of how the achievement motivation affects the work performance is also very vague. Therefore, this paper adopts the method of empirical research to apply the theory in the field of public service work of township cadres, design a scale to measure these latent variables, and collect data from township cadres in Hebei Province by using questionnaire method. The research results show that the mediating effect between the achievement motivation of township cadres and their own work performance is a complete mediating effect. At the same time, there are three routes for its influence to be transmitted through scientific thinking and knowledge skills, which well proves the correctness of the theory and clarifies the ambiguous explanations of the theory.
A Study on Cargo Volume Prediction and Staff Scheduling Based on Support Vector Regression Model and Integer Planning
Authors: Wu Yishan
Published: August 2024

In pursuit of enhancing the management efficiency and reducing operational costs within the logistics network sorting centers, this research constructed a Particle Swarm Optimization (PSO)-Supported Vector Regression (SVR) model coupled with an Integer Programming staff scheduling model. Utilizing tools such as MATLAB, Excel, and Python, the study conducted processing and analysis of the cargo volume data, revealing the periodic trends of the cargo volume. After eliminating outliers, the optimized SVR model was employed for forecasting, and weights were established to adjust features and mitigate the impact of non-interactive sorting centers. The optimal staff allocation for each sorting center was determined through Integer Programming. This research provides an efficient set of strategies for cargo volume prediction and workforce scheduling, contributing to the optimization of cost-effectiveness in logistics management.
Research on the Recognition Method of Wheat Ears Based on Image Color and Classical Model
Authors: Liu Shugang , Chen Yihui
Published: August 2024

In this paper, we study wheat images during the grouting period, and construct a dataset by extracting wheat spike features through image preprocessing, color space conversion and edge detection. CNN and AlexNet models are used to train and optimize the parameters and structure to improve the recognition accuracy. By adjusting the batch size, learning rate and training rounds, CNN performs optimally with Batch size=64, Epoch=5, and learning rate=0.0001; AlexNet also performs well with similar settings, but the training cost is larger. This study verifies the effectiveness of image processing combined with the classical model CNN for recognizing wheat sheaves, providing data and theoretical support for wheat yield prediction.
Research on Housing Price Prediction Based on Machine Learning
Authors: Huang Zirui
Published: August 2024

The stability and long-term growth of the real estate industry depend heavily on the capacity to forecast house price trends with accuracy. The purpose of this research is to evaluate the benefits and drawbacks of several machine learning models for housing price prediction. First, the factors influencing housing prices in various ways are explained. Next, the multiple linear regression, backpropagation neural network, and random forest model, respectively, are introduced. In the meantime, the paper analyzes their forecasting shortcomings and provides examples of other scholars' optimization experiments on the aforementioned three models. The findings indicate that these three types of optimized models can obtain more stable and accurate prediction results when housing prices are predicted. Housing price forecasting can lower investment risks for real estate developers by assisting them in creating more effective project development plans and sales tactics. The government can better grasp the real estate market's development trend, create pertinent regulations and control measures, and support the stable and sustainable growth of the real estate market with the aid of home price prediction. Finding an appropriate way to predict the price of housing is therefore imperative.
Design And Research on Machining Orientation Control Based on Five Axis CNC Machine Tools
Authors: Li Hualiang
Published: August 2024

This article establishes a model for machining orientation control of a five axis CNC machine tool based on methods such as constructing translation matrix, rotation matrix, and composite matrix. Using the optimal path and rotation angle search algorithm based on rotation transformation and composite transformation, the displacement of the machining center relative to the initial state, the rotation angle of the rotation axis, and the drilling number under the minimum total displacement and total rotation angle are studied. For the given machining task and initial state, since the required holes (simplified as line segments) are all perpendicular to the X-axis, Bi=0 is obtained. This article first obtains the rotation angle Ai around the A-axis through the given angle conditions, and then establishes a composite transformation equation around the A-axis to solve for the new coordinates of each machining center, hole and plate intersection point after composite transformation. The displacement from the intersection point to the drill bit is the same as the displacement from the machining center to the drill bit, in order to determine the displacement of the machining center relative to the initial state. If the parameters of the first hole processed are (x1, y1, z1), , the displacement of the machining center relative to the initial state, and the required rotation angles . (A1, B1, X1, Y1, Z1)=(66, 0, −15, −159.732, 113.082) 1..
Analyzing Social Concerns in Contemporary Chinese Family Films: A Case Study of the Film Across the Furious Sea Directed by Cao Baoping
Authors: Zhao Yifei
Published: August 2024

Across the Furious Sea, directed by Cao Baoping and featuring Huang Bo and Zhou Xun, is a poignant exploration of familial dynamics and traditional Chinese values. Released on November 25, 2023, in mainland China, the film delves into the themes of revenge, loss, and the complexities of family relationships. This paper adopts a social sciences lens to analyze the film's narrative, emotional expressions, and character psychologies. By examining these elements, this study aims to shed light on prevalent social issues within Chinese families, offering insights into the intersection between film narratives and societal realities, and enhancing the connection between film and reality. Furthermore, it discusses how filmmakers can leverage such narratives to deepen the audience's understanding of social issues and enhance social cognition. Ultimately, this research contributes to the advancement of the film industry by encouraging a nuanced portrayal of social realities and fostering meaningful dialogue between filmmakers and society.
Business Valuation Method in Investment Decision-Making
Authors: Zhuo Runjia
Published: August 2024

In this thesis, valuation of Apple’s stock by employing three essential methods: Discounted Cash Flow, Free Cash Flow, and the Discounted Dividend Method. The aim is to project the future prices of Apple’s stock based on thorough analysis of the data provided in the company’s annual reports over the last decade, particularly focusing on factors like dividends. As per the recent stock market data, Apple’s stock is valued at $172.62 per share on March 18, 2024. However, through meticulous calculations using various valuation models, the author has determined that the intrinsic value of Apple’s stock stands at a higher value of $188.00 per share. This suggests that the stock is currently undervalued in the market. Given that the intrinsic value of the stock surpasses its current market price, so it is sensible for investors to consider buying Apple’s stock. By doing so, people may potentially benefit from the future expected growth and returns that the stock is projected to offer based on fundamental analysis. This analysis provides a suggestion for investors to have confidence in the long-term potential of Apple’s stock and consider it a wise investment choice.
Research on short-term passenger flow prediction of urban rail transit based on ARIMA algorithm
Authors: Liao Zhihan
Published: August 2024

The continuous growth of urban population has led to an increasing demand for urban public transport among citizens. In response, many cities have implemented urban rail transit systems to alleviate internal traffic congestion. Accurate short-term passenger flow prediction is crucial for the efficient operation of intelligent subway systems. Therefore, it is essential to establish or select a suitable model for predicting the short-term passenger flow of subways. This study utilizes ten days of travel data from the Beijing subway between May 1 and May 10, 2019. After conducting preliminary preprocessing on the 10-day subway appearance data, an ARIMA prediction model is established for initial forecasting. The accuracy of passenger volume forecast is evaluated by analyzing the variance between predicted values and actual values at specific time intervals, with results indicating that the ARIMA model demonstrates strong predictive capability.
The Effect of the Opening of Chengdu-Chongqing High-speed Rail on the Urbanization of Cities Along the Rail Line
Authors: Cao Ruizhe , Shen Xiaojing , Zu Bohan
Published: August 2024

With its benefits of high speed, high safety, and environmental friendliness, high-speed rail has emerged as a significant trend in the development of the modern transportation sector. It also plays a major role in boosting the economics and urbanization of China's metropolitan clusters. Taking the Chengdu-Chongqing region and its cities along the route as an example, this study examines the urbanization process of the Chengdu-Chongqing urban agglomeration both before and after the construction of high-speed rail by using data pertaining to the launch of the high-speed rail network in the region from 2012 to 2018. Using the difference in difference technique, this study examines and evaluates the real effects of the high-speed railway's opening on the urbanization process of Chengdu-Chongqing and the cities along its path. (DID). Based on empirical data, the Chengdu-Chongqing urban agglomeration's resident population's rate of urbanization has significantly increased since the high-speed railway opened, and can facilitate and support the Chengdu-Chongqing region's urbanization trend.
Applying Genetic Algorithms to Optimize Hybrid Flow Shop Scheduling in Disaster Response Logistics
Authors: Chen Zisen , Guo Yixuan , Ren Tianyi
Published: August 2024

This paper explains the hybrid flow shop problem and its occurrence in logistics. The paper introduced an example to explain the situation. The example problem is a condition involving different jobs, machines, and stages. The background is in a disaster area where people need supplies. The paper divided the whole process into two stages. The paper applies the genetic algorithm to solve this problem. Each schedule was represented in a form of an individual of the genetic algorithm. The paper narrows the range of the individuals by reintroducing a better individual to improve the fitness value of the individual. The result of the problem when the fitness value was nearly constant. The process of solving the problem is explained in detail. The final schedule was drawn in a graph approximately to scale. The paper explains the flaws of the genetic algorithm. In the code, the values were set to increase the efficiency to get the answer and reduce the flaw. At last, the paper discusses the future use of the hybrid flow shop problem in logistics.
Effects of Exchange Rate Changes on Real Estate Prices in Russia During the Russian-Ukrainian War
Authors: Han Zhengrong
Published: August 2024

As a result of the Russian-Ukrainian war which started at February 24, 2022, some of Russia's economic indicators have been affected, including the ruble's exchange rate, Russia's inflation rate, and GDP. With this in mind, this paper assumes that there is a linear relationship between real estate prices and the exchange rate, inflation rate, and GDP as follows: ln_repx = ß0 + ß1 ln_exr + ß2ln_inf + ß3ln_Y + c.c.. Based on the information collected, the StataSE 15.0 tool is used to perform regression operations to derive the correlation coefficients and to explore the relationship between house prices and each price factor. Afterwards, it was concluded that under the influence of the Russian-Ukrainian war, changes in the exchange rate of the Russian domestic currency against the US dollar would have some negative impact on real estate prices. Overall, these results shed light on guiding further exploration of continuous influence from war on Russia’s real estate market and pave a path for government to make efficient response.
The ESG Information Disclosure in Financial Market of China
Authors: Zhao Zhen
Published: August 2024

In recent years, ESG (Environmental, Social and Corporate Governance) has become an indispensable factor in investment decisions. ESG information disclosure of listed companies has played an important role in finance. Since companies with good ESG performance focus on long-term development and sustainable value creation. And they have better internal governance mechanisms which help to manage risks better. These companies would have stronger sustainable competitive advantages in the market. While in China’s ESG disclosure development, there still could be some issues that need to be addressed. This paper will from three perspectives to discuss the existing problems. Firstly, an official ESG disclosure framework and a regulatory force are needed to help standardize and legitimize the disclosed information. Secondly, there could be other ESG information besides the environmental problems that may also cause financial risks that need to be noticed during the disclosure. Lastly, to catch up the aggregated development of worldwide ESG disclosure, the supporting ESG infrastructure need to be improved. To solve these problems, this paper also gives relatively possible solutions: to construct a ESG management system and disclosure norms suitable for the Chinese market; to construct ESG-based bank credit facilities; to promote the development of digitalization and informatization of the disclosure.
The Marketing Strategy of Lululemon's Men's Shoe
Authors: Zhang Xidan
Published: August 2024

Following the epidemic, there has been a noteworthy movement among Chinese consumers toward valuing health and sustainability, which has had a big impact on the sports sector. This increase in health consciousness has forced firms to modify their strategies to match changing consumer demands. Lululemon, an international sports brand, recently entered the men's shoe sector as a strategic move to expand its consumer base. This paper investigates the market consequences of Lululemon's entry into men's footwear and discusses ideas for further penetration of the male sportswear sector. This study sheds light on the possible benefits and obstacles of Lululemon's expansion ambitions by conducting a thorough examination of market demand, brand image, and product strategy.
New Infrastructure Construction and High-quality Urban Development
Authors: Yi Jinyan
Published: August 2024

Infrastructure construction, as a solid foundation to support the city's comprehensive service function, plays an indispensable role in the city's economic prosperity, social progress and the improvement of environmental quality. It not only provides the necessary material conditions for the daily operation of the city, but also the key driving force for the outward expansion and internal optimization of the city. In view of its importance, an in-depth study of the relationship between China's infrastructure construction and urban development is of great guiding significance for us to accurately grasp the current situation of urban construction and scientifically plan the future path of urban economic and social development. This paper aims to deeply explore the core concept of new infrastructure construction and its unique advantages, and take this as a starting point to analyze the role of infrastructure construction in promoting urban economic vitality in detail. At the same time, combined with the actual situation of the current urban agglomeration, it reveals various problems and challenges that the new infrastructure may face in the process of promoting the high-quality development of urban agglomeration. On this basis, this paper puts forward the far-reaching impact of new infrastructure on high-quality urban development, to provide valuable reference and enlightenment for the sustainable, healthy and high-quality development of urban agglomerations.
Research on the Copyright Recognition of Artificial Intelligence Generated Content
Authors: Fang Zihao
Published: August 2024

Generative artificial intelligence undergoes statutory copyright licensing of pre-existing data and the training of models to input commands, execute algorithms, and output content. The constant involvement of human intelligence and the creative model of human-computer collaboration determine that artificial intelligence cannot be the subject of copyright. This gives rise to three categories of subjects: Artificial intelligence users, developers and investors. Artificial intelligence always involves human intelligence in the content creation process, and artificial intelligence-generated content has an original contribution as well as a minimum level of creativity from users, formally constituting works under the copyright law. The rules of copyright attribution for artificial intelligence-generated works should be prioritized according to the contractual agreement, If there is no contractual agreement, the copyright protection mode of the copyright law should only extended to AI users. The object of copyright protection should be limited to the artificial intelligence-generated works themselves, and the strength of copyright protection should be in line with the user's originality of the contribution to the work.
DRL For Battery Cycle Optimization: Theory and Practice
Authors: Hu Xinrui
Published: August 2024

In this paper, we investigate the use of Deep Reinforcement Learning (DRL) to optimize the charge/discharge cycles of batteries, aiming to improve their operational efficiency and lifespan. By casting the battery management problem within a Markov Decision Process framework, we apply a DRL algorithm to learn an effective policy for cycle optimization. Our empirical results demonstrate the superiority of the DRL approach over traditional methods in terms of energy efficiency and cycle life. We also provide a theoretical analysis of the algorithm's stability and convergence properties. The paper concludes with a discussion on the implications of our findings and potential directions for future research.
Quantifying Momentum in Tennis: A Case Study of the 2023 Wimbledon Gentlemen’s Final
Authors: Lyu Xin
Published: August 2024

In sports competitions, especially in famous sports like tennis, momentum has a very significant impact on the outcome of the competition. In the era of big data, research can predict the momentum changes in the game based on historical data, thereby providing players and coaches with reasonable strategies. This analysis can increase the player's winning rate. Explore the presence and changes of momentum in the game through a case study of the 2023 Wimbledon men's singles final. The research selected key moments in the game, including serve games, break games, and errors, to capture momentum through a series of quantifiable indicators, and applied random forest, support vector machine, and multi-layer perception models. Their accuracy rates are 0.6691, 0.6643, and 0.6479 respectively. The research aimed to predict scoring results and evaluate player performance. The research provides coaches and players with a new tool to quantify momentum in tennis matches, helping to better understand match flow, develop tactics, and improve match performance.
Exploration and Practice of Enterprise Transformation of Social Work Organisations: Paths, Challenges and Strategies
Authors: Yang Zhengyuanyi , Liu Xinyi , Xi Ruiyi , Li Haokai
Published: August 2024

With the development of social work in China and the gradual improvement of the market economic system, the entrepreneurial transformation of social work agencies has become an inevitable trend. In this context, this paper discusses in depth the path, challenges and strategies of the entrepreneurial transformation of social work agencies in China. Firstly, it elaborates the necessity of the entrepreneurial transformation of social work agencies from the theoretical level, and analyses its significance in improving the service quality, enhancing the vitality of the agencies, and optimizing the allocation of resources. Secondly, through practical cases, it demonstrates the specific paths of the entrepreneurial transformation of social work agencies, such as the introduction of market-oriented operation, the strengthening of human resource management, and the innovation of service models. At the same time, this paper also puts forward a series of coping strategies for the challenges that may be encountered in the process of transformation, such as conceptual change, policy environment, and talent drain. In addition, this paper also provides useful reference and inspiration for China's social work organisations by analysing the case studies of entrepreneurial transformation of outstanding social work organisations at home and abroad. In short, this paper aims to provide theoretical and practical support for the entrepreneurial transformation of China's social work agencies, with a view to promoting the healthy development of China's social work career.
Strategy Analysis for Transforming Low Loyalty and Spurious Loyalty Consumers: A Case Study of ANTA
Authors: Wang Xiaofei
Published: August 2024

In the context of the thriving sports sector, ANTA has made a notable impact on consumers by generously sponsoring the Olympic Games. Nevertheless, the primary focus of customers lies on the Chinese delegation rather than the ANTA brand itself, resulting in a diminished and misleading sense of devotion towards the company. The study aimed to investigate strategies for converting consumers with low and deceptive loyalty into highly loyal ones, focusing on the ANTA brand as a case study. Hence, the present study aims to accomplish the below objectives: To begin with, the objective is to examine the causes and attributes of consumer low and deceptive loyalty behaviors. Furthermore, a comprehensive examination of the brand image of ANTA is necessary to ascertain the crucial elements that contribute to the augmentation of client loyalty. To enhance customer loyalty towards the ANTA brand, it is necessary to devise and execute a range of marketing strategies and initiatives, such as brand promotion, product innovation, user experience, and long-term development. This will also involve offering recommendations for ANTA and other sports companies.
Time Measurement of People's Cultural Life Quality in China 's Provinces Based on Grey Prediction
Authors: Zeng Xiyu , Liang Ruikang , Shen Liancai , Zhong Yiwang
Published: August 2024

In order to better counter the quality of people's cultural life in various regions of China, based on the scientific and effective principles of data, this paper collects 33 secondary indicators for evaluating the quality of people 's cultural life from 31 provinces in China from 2014 to 2022. Then, the box plot and mean interpolation method are used to deal with outliers and missing values, and then the heat map is used to evaluate and screen the index system. In order to more accurately reflect the quality of cultural life, this paper uses the entropy weight method to integrate the second-level indicators into a more comprehensive first-level indicator, and obtains the specific scores of 31 provinces in ' cultural participation', 'cultural industrialization', 'cultural creativity', 'cultural richness' and 'cultural resources 'from 2014 to 2022, so as to do basic work for subsequent prediction and comprehensive evaluation. Finally, in order to enhance the innovation of the model, this paper studies the quality of cultural life of Chinese people in each province by 2025 under the grey prediction model from the time dimension, taking into account the scientific and effective. This method is conducive to China 's full understanding of the differences and convergence of the quality of cultural life in various provinces, providing a scientific basis for the cultural construction of the world 's people, and promoting social progress and civilization development.
Research on Trends in Illegal Wildlife Trade based on Comprehensive Growth Dynamic Model
Authors: Tang Runxuan
Published: August 2024

This paper presents an innovative Comprehensive Growth Dynamic Model (CGDM). CGDM is designed to simulate the temporal evolution of an event, incorporating economic and social factors. CGDM is a regression of logistic regression, power law regression, and Gaussian perturbation term. CGDM can effectively forecast the temporal evolution of an event, incorporating economic and social factors. The illicit trade in wildlife has a deleterious impact on the ecological environment. In this paper, we employ CGDM to forecast the trajectory of illegal wildlife trade from 2024 to 2034 in China. The mean square error is utilized as the loss function. The model illuminates the future trajectory of illegal wildlife trade, with a minimum point occurring in 2027 and a maximum point occurring in 2029. The stability of contemporary society can be inferred. CGDM's robust and generalizable nature is also evident.
Prediction of stock prices of Yuexiu REITs based on GARCH models
Authors: Jin Jia
Published: August 2024

As a new type of financial instrument, on the one hand, REITs can play the role of resource allocation in the securities market, enabling better coordination between project parties and funding parties, accelerating investment speed, and improving investment efficiency. On the other hand, they can also leverage high-quality infrastructure assets that were previously only available to some large infrastructure units. The income from some real estate projects allows ordinary institutions and investors to share this long-term stable cash flow return. Due to the initial exploration stage of REITs in mainland China and the relatively mature development of the Hong Kong REITs market, this article selects Yuexiu REITs, the first REITs fund in China with mainland property assets as the underlying asset, listed in Hong Kong, for specific empirical research. This article selects the closing prices of Yuexiu REITs from November 1, 2018 to November 1, 2022 as research data, and based on the GARCH model theory, establishes GARCH (1,1) model, EGARCH (1,1) model, IGARCH (1,1) model, and GARCH-M (1,1) model based on normal distribution, t-distribution, and GED distribution. According to the AIC criterion, the GARCH (1,1) model based on t-distribution and the IGARCH (1,1) model were selected to predict the future closing prices of Yuexiu REITs. The results showed that the GARCH (1,1) models under t-distribution had a narrower confidence interval range and higher accuracy.
Exploring the Effects of Automated Production Lines on Traditional Manufacturing Jobs
Authors: Luo Conghao
Published: August 2024

When famous companies such as BMW and Fast introduced fully automated production lines, some workers lost their jobs. This article mainly studies the impacts of automated production lines on labor market, including the job opportunities of high-skilled and low- skilled employees, worker’s wages and two important effects which are replacement effect and creative effects. In the research, I analyze the labor market situations of several economies and use some important data to show the current labor market trends. The result is that the introduction of automation will increase employment opportunities for high-skilled workers, but workers' wages may fall because the tasks of labor are smaller than those of machines. Meanwhile, the extent of impacts of replacement and creative effect on labour market might depends on time period and the relevant size between those. According to impacts, the policies for protecting labor force and increasing economic growth rates have been proposed. It is also expected that more job positions would be provided when the labor could adjust to the development of automated production lines in the future, and the productivity of firms will be improved dramatically.
Forest Cover Type Prediction Based Linear Regression
Authors: Gao Xiaoyu
Published: August 2024

Nowadays, the relentless exploitation of natural resources and the escalating deforestation have cast a dark shadow over the survival of forests worldwide.With the ever-growing demand for raw materials and the quest for economic growth, many industries have turned their sights on forests as a ready source of timber, minerals, and other valuable resources. Forests, repositories of biodiversity and crucial to our planet's ecological balance, are perilously close to disappearing, calling for urgent measures to ensure their sustainability. This study delves into the application of machine learning in predicting forest cover types, focusing on various methodologies, particularly linear regression. In this paper, the analysis mainly offers a thought-provoking assessment of the pros and cons of linear regression, unpacking its intricate strengths and weaknesses with clarity and wit. By examining this paper, individuals can gain a comprehensive understanding of how machine learning can aid in the planning and management of forest resources.
Copyright Regulation of Artificial Intelligence Generated Graphs
Authors: Ye Chenyu
Published: August 2024

With the profound advancement of AI algorithmic models, AI generators have progressively found applications across diverse industries. Nevertheless, this development has presented new challenges to legislation and judicial determinations concerning copyright and related matters. There remains no definitive conclusion on whether AI-generated works can be considered original or fall within the scope of copyright law, nor whether they are eligible for copyright protection. However, a thorough analysis of current domestic and international legislation and judicial precedents suggests that copyright protection should indeed be extended to AI-generated creations. This is supported by the fact that artificial intelligence models fundamentally serve as tools to aid human creativity, lacking autonomous will and primarily relying on human data analysis, compilation, and integration as a basis for creation. Therefore, even though the process of artificial intelligence creation may ultimately reflect the original thought and personalized expression of humans, it is essential to consider granting copyright protection to AI-generated content.
Futures Trading Security Based on Smart Contract Technology
Authors: Sun Lichen
Published: August 2024

With the development of blockchain technology and the increasing vitality of the world economy, the use of blockchain technology is expanding in the financial field gradually. Among all the financial derivatives, futures with their high-risk, high-return investment pattern have been popular to global investors, but their risks from leverage always lead to a disaster. Currently, there is no reasonable or appropriate safety net measure available to protect investors’ losses within acceptable limits. However, smart contracts at the blockchain contract layer with their properties of security, automation and strict adherence to contract terms, naturally align with the nature of futures trading. Therefore, this paper designs three types of smart contracts in trading access, risk aversion assessment and safety net protection respectively, to provide tailored safeguards for investors while promoting futures trading developing healthily and maintaining investor enthusiasm at the same time.
A Fitted Modeling Study of Past Weather Extremes in Canada
Authors: Zhang Danning
Published: August 2024

Extreme weather events have left deep imprints in the long history of humankind, and these imprints have formed historical landmarks of great value. These landmarks are not only records of natural phenomena, but also witnesses to the social, cultural and economic development of humankind. The study of these historical landmarks can provide a better understanding of the relationship between human beings and the natural environment, and provide a useful reference for future sustainable development. This paper analyzes and learns that these historical landmarks are records and warnings of natural disasters. Extreme weather events, such as floods, hurricanes, droughts and extreme heat, have wreaked havoc and impact on human societies. Therefore, this paper determines the past temperature trends by fitting past weather data, temperature data, and terrain data. The occurrence of these events reminds people of the power and unpredictability of natural forces. Through in-depth study of these historical landmarks, people can better understand the formation mechanism and scope of impact of natural disasters, so as to take effective preventive measures and reduce disaster losses.
Educational Anxiety and Willingness to Buy a School District House for Parents
Authors: Zhou Yibo
Published: August 2024

Children's education has always been one of the main topics in the family, and it has also caused anxiety to countless Chinese parents. This study aims to explore the influence of parent groups on the willingness to purchase houses in school districts in the context of educational anxiety. This research collected data from nearly four hundred parents through questionnaires and analyzed them using statistical analysis and content analysis techniques. According to the analysis, the study found that educational anxiety has a significant positive impact on parents' willingness to buy houses in school districts. These findings contribute to a deeper understanding of the behavior and decision-making of parent groups in situations of educational anxiety and provide a reference for relevant policy formulation. Although this study explores the psychological causes of home buying, it also has the problem of insufficient generalization. In the future, more psychological causes of housing in school districts can be explored.
Analysis on the influence of smart city construction on high-quality urban development
Authors: Lin Fanming
Published: August 2024

The focus of smart cities has shifted from the technical upgrade of basic city operation systems to the awareness and perception of urban residents. The idea of a "smart city" has emerged with the growth of urban informatization. A smart city is a crucial component in attaining high-quality development and is a prerequisite for urban digitalization to advance into intelligence. In the Communist Party of China's 20th National Congress report, General Secretary Xi Jinping emphasized the need to create a smart, resilient, and livable city. The people desire and the times demand that a new kind of city be built—one that is inventive, smart, safe, livable, resilient, and harmonious. High-quality urban development has gained fresh impetus from smart cities, an urban development paradigm that intimately combines the digital economy and modern urbanization. This article discusses the influencing factors of smart city construction on high-quality urban development, thereby providing important inspiration for the construction of smart cities to promote the macro goal of high-quality urban development.
Operational Efficiency through Machine Learning and Optimization in Supply Chain Management
Authors: Zou Jianke , Zhao Huayu , Li Ningxin
Published: August 2024

Supply chain management faces many challenges and opportunities in increasingly fierce global competition. The surge in data volume and the decline in data quality brought about by the era of big data has prompted enterprises to introduce advanced machine learning techniques to optimise supply chain management. This paper explores the application of machine learning in sensing supply risk, demand forecasting, inventory optimisation, and distribution and transportation planning to improve the ability of enterprises to predict and respond to market changes by automatically identifying and extracting patterns in data, thereby improving operational efficiency and customer satisfaction. While there are challenges such as data quality and availability when implementing machine learning solutions, these issues can be addressed with proper planning and deployment, and enterprises can stay ahead and grow sustainably in a competitive market.
Preface: 3rd International Conference on Applied Mathematics, Modeling Simulation and Automatic Control (AMMSAC 2024)
Authors: Haggai Emmanuel , Han Yingke
Published: August 2024

It is our honor to present the proceedings of the 2024 3rd International Conference on Applied Mathematics, Modeling Simulation and Automatic Control (AMMSAC 2024). This conference was successfully held in San Diego, USA during June 22-23, 2024.
AMMSAC 2024 aims to provide an ideal academic platform for researchers to present the latest research findings and describe emerging technologies, directions and developments in applied mathematics, modeling simulation, computer science, intelligent manufacturing, and automatic control. As these goals require the cooperation of people from different background, we hope that our research will help to achieve a better and more sustainable future for all.
During the conference, we were pleased to be joined by four knowledgeable keynote speakers. More than 60 participants were benefited through each of the 30-35 minutes keynote speech. The parallel sessions were arranged and carefully monitored by the organizing team.
We truly believe that AMMSAC 2024 is a great platform for researchers, academician, industry players, and student to brainstorm and exchange research idea, communicate their new research findings and eventually leading the world to meet the sustainable goals.
The AMMSAC Scientific Committee
San Diego, USA
Game Theory in Medical Aesthetics Industry: Evidence from Consultation and Plastic Surgery Department
Authors: Wan Chenwei
Published: August 2024

Currently, the medical aesthetic industry is experiencing rapid growth. On this basis, this study develops the potential usage of game theory in medical aesthetic industry. To be specific. This research mainly focuses on decision making processes in consultation and competition between public and private medical institutions. Based on the analysis of strategic interactions between doctors and patients during consultations, as well as the competitive dynamics between public and private institutions, this study reveals how game theory models, such as the Stackelberg competition, can evaluate pricing strategies and market behaviors. However, several limitations are worth noted during applications due to the variable real-life condition according to the analysis and suggestions for further exploration are proposed at the same time. Those external factors may influence the accuracy of the predictions and decisions made by the model. Overall, despite those uncertain factors existed, game theory is a valuable tool in medical aesthetic industry.
Seismic Response Characteristics of Complex Slope Terrain Based on FLAC3D Numerical Simulation
Authors: Yang Jiale , Jiang Yongchao
Published: August 2024

In the southwestern region of China, there are many natural slopes due to various factors such as terrain and landforms. Additionally, a large number of engineering projects are constructed in this region. When constructing highways, it is inevitable to build numerous cut slopes. Unfortunately, the seismic belt of China is mainly distributed in the southwestern region. Therefore, studying the dynamic response of cut slopes under seismic excitation is particularly important to reduce the occurrence of natural disasters such as landslides. This study utilizes numerical simulation methods to investigate the stability of different cut slopes. The results indicate that the acceleration dynamic response and displacement dynamic response exhibit elevation amplification effects. In the case of stepped cut slopes, the acceleration on the outer side of the steps is greater than that on the inner side, and the displacement on the outer side is larger as well. Additionally, the stress on the outer side is smaller compared to the inner side. As the platform width increases, the acceleration on the outer side decreases while the inner side accelerates. Similarly, the displacement on the outer side decreases while it increases on the inner side. Furthermore, the stress on the outer side increases while it decreases on the inner side. Consequently, as the slope angle of the slopes increases, the stability of the slopes deteriorates. Conversely, as the platform width increases, the stability of the slopes improves. The findings of this study can provide guidance for the construction and reinforcement of slope engineering, especially in the context of stepped slopes.
Exploring the Application of Remote Sensing Technology in Natural Disaster Monitoring
Authors: Ke Lingdi
Published: August 2024

The frequency of natural disasters is increasing annually, posing a significant threat to the social economy. Traditional methods of monitoring natural disasters are inefficient and can no longer meet monitoring needs. Remote sensing is economical, rapid, and data-rich. It has gradually been applied in natural disaster monitoring and has yielded positive results. This article explores the application of LiDAR and InSAR remote sensing technologies in three natural disasters: earthquakes, landslides, and floods. It concludes that in practical applications, selecting appropriate remote sensing technology methods or broadening the scope of remote sensing technology applications is necessary. Secondly, researchers should improve remote sensing data sharing, optimize algorithms, and develop better data processing systems and platforms. Finally, researchers can achieve better observation results only by improving observation accuracy. This paper aims to provide the public with relevant knowledge on the application of remote sensing in natural disaster monitoring. It also highlights flaws and deficiencies to provide references and ideas for related research.
Application of High-Resolution Remote Sensing Images in Urban Greening Rate Extraction
Authors: Chen Sirui
Published: August 2024

The urban greening rate is the ratio of the metropolitan green space area to the city’s total area, and it is an essential indicator for measuring the level of urban greening. High-resolution remote sensing images can provide detailed surface information, enabling people to monitor and understand the urban greening situation from a long distance, on a large scale and in real time. This paper investigates the performance and application of high-resolution remote sensing imagery in urban greening rate extraction. This paper concludes that selecting high-resolution remote sensing images, preprocessing the images, and adopting the visual interpretation method combined with automatic computer classification and field survey can improve the accuracy of greening rate extraction. Future research can improve extraction accuracy by combining different data sources and improving the classification method. This paper can provide some references for future research on urban greening rate extraction and enhancing the level and efficiency of urban greening management.
An Empirical Research on the Relationship Between Comprehensive Utilization of Waste Resources and Environmental Governance
Authors: Shao Yuhan
Published: August 2024

The development of comprehensive utilization of waste resources is an important part of the development of circular economy and the construction of a resource-cycling society. Using the empirical research method of multiple linear regression, this paper selects panel data from 30 provinces, autonomous regions, or municipalities directly under the central government of China from 2012 to 2021 to investigate the effects of the industry's development of comprehensive utilization of waste resources on the emission of pollutants in the environment. With common industrial solid wastes utilized and legal person capital as the main explanatory variables and total nitrogen oxide emissions as the explanatory variables, SPSSAU is utilized to empirically analyze the above factors. It concludes that the overall amount of nitrogen oxide emissions will increase by 51.356 tons for every 10,000 tons increase in the amount of common industrial solid wastes utilized extensively, which may be due to the imperfect technology of production and treatment facilities, mismanagement by the regulatory authorities, and the fact that solid wastes contain relevant substances and thus unavoidably produce emissions, resulting from the above three reasons. for every 1 unit increase in the square of legal person capital. The total amount of nitrogen oxides emission will be reduced by 66.75 tons, which can significantly reduce the emission of nitrogen oxides. In this paper, the model is considered robust by replacing the explanatory and interpreted variables in the robustness test.
Research on Business Performance of Shandong Province Based on Three-Stage Data Envelopment Analysis
Authors: Ren Ziyan , Wang Yushuo , Qiu Ziyi
Published: August 2024

Shandong Province ranks third in China in terms of economic output. The efficient operation of listed companies has contributed to the region's high economic growth to some extent. In order to improve the efficiency of enterprise operation, this paper takes 189 listed companies of various types in Shandong Province as the research object and constructs an efficiency evaluation index system through the three-stage data envelopment analysis to study the operational performance of enterprises from 2018 to 2022. Based on the research results, this paper puts forward suggestions for improving enterprise management. The research results show that only 2.12% of the sample enterprises have achieved the optimal efficient state in operation. The external environment has a significant constraint on the operation efficiency. Technical efficiency is the main factor affecting the operation efficiency of listed companies in Shandong Province, and enterprises have problems of waste and mismanagement in resource allocation and use. The operation efficiency of enterprises in different regions and industries is different. Based on the analysis results, this paper puts forward suggestions for the operation and management of listed enterprises in Shandong Province, improving their operational capabilities from both internal and external environment policies, promoting the balanced development of regional and industry economies.