bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Green GDP Revolution Neural Network Prediction Model
Authors: Li Xinyi
Published: June 2024

In recent decades, GDP, the core indicator of the national economy, has played a key role in measuring the state of the economy and the level of development. However, GDP falls short as a measure of economic health, failing to fully account for the interrelationships between resources, the environment and the economy. In order to more comprehensively reflect the balance between the economy and the environment, we have introduced green GDP as an important indicator to measure the degree of social and economic health. This paper discusses in depth the differences in the definition, understanding and calculation methods of GGDP. An in-depth comparison of GDP and GGDP is made based on the grey forecast model to analyze their differences in measuring socio-economic health. At the same time, in order to measure social and economic health status more accurately, this paper classifies green GDP based on feedforward neural network model theory and clustering algorithm, builds a neural network prediction model, analyzes the correlation degree between different factors and GGDP, and analyzes the influence degree of different factors in resources and environment on social and economic status and development level. Through reasonable summary and analysis of the research results, considering the state of social and economic health, this study provides useful reference suggestions for the future government to implement economic measures and policies, and has positive significance for promoting the innovation and sustainable development of economic indicators.
Advancements in Filter Technology: Evolution and Applications
Authors: Mao Hongquan
Published: June 2024

This paper explores the historical trajectory and contemporary applications of signal processing filters. From the early days of analog filters to the current digital era, the paper traces their evolution, emphasizing key developments in active RC filters, monolithic integrated op amps, and the transition to switched-capacitor and continuous-time filters. Fundamentals of analog and digital filters are outlined, distinguishing their processing of continuous-time and discrete-time signals. The classification of filters, including low-pass, high-pass, band-pass, and band-stop, is discussed with insights into their specific applications. The paper delves into crucial applications in audio processing, video processing, communication systems, power management, and sensor signal processing, showcasing filters' pivotal role in enhancing signal quality across diverse fields. Addressing emerging technologies, the paper highlights adaptive and deep learning filters, projecting the future trends in filter technology. It anticipates developments in analog integrated filters, emphasizing the growing significance of integrated circuits technology. This comprehensive review aims to deepen readers' understanding and inspire continued innovation in signal processing.
Current Study on A* Algorithm in Autonomous Obstacle Avoidance
Authors: Zhu Chengyue
Published: June 2024

The A* algorithm is a heuristic search algorithm widely used in the fields of path planning and graph search. This paper aims to delve deeply into the principles, implementation, and performance optimization of the A* algorithm in practical applications. Firstly, we elaborate on the basic principles of the A* algorithm, including the definitions of cost function and heuristic function, as well as how to achieve efficient search by maintaining open lists and closed lists. Secondly, we analyze the application of the A* algorithm in path planning problems. By constructing environmental models and designing appropriate heuristic functions, we achieve optimal path search from the start point to the end point. Additionally, we explore the performance optimization methods of the A* algorithm, including strategies such as utilizing priority queues to manage nodes to be searched and dynamically adjusting heuristic functions, to improve the execution efficiency and search accuracy of the algorithm. Finally, through a series of experiments and case studies, we verify the effectiveness and superiority of the A* algorithm in path planning problems. The research results of this paper provide beneficial references and insights for the application of the A* algorithm in related fields.
A Multidimensional Exploration of the Visual Arts: History, Impact and Future Trends
Authors: Li Zhendi
Published: June 2024

This article explores the multidimensional nature of the visual arts, tracing their trends and challenges from antiquity to the present day. The article begins by defining the visual arts and emphasising their importance in reflecting and shaping human culture and society. The study aims to analyse the historical development of the visual arts, examining the origins and characteristics of ancient art, the artistic changes from the Middle Ages to the Renaissance, and the progress of modern art movements such as Impressionism and Expressionism. The research delves into key elements and techniques in the visual arts, including the use of colour, shape and line, and how these are used in different media such as painting, sculpture and digital art. The article discusses how style and subject matter express the artist's unique perspective and emotions, contributing to the richness of visual expression. In addition, the article analyses the far-reaching impact of visual art on society and culture, showing how art reflects and influences social change, as well as its role in education and social ideology, and explores the intersection of art and politics through examples of propaganda art and protest art. The article also examines contemporary trends and challenges facing the visual arts, in particular the integration of digital technologies and new media, the impact of globalization on artistic style and expression, and the continuing struggle in the contemporary art market between commercialisation and artistic values. In the concluding section, the article outlines the historical course of the visual arts and their importance in contemporary society, as well as providing an outlook on future trends in the visual arts. This comprehensive exploration underscores the enduring value and dynamism of the visual arts as a fundamental part of human history and an important channel for cultural and social evolution.
On the inspiration of Lin-Manur-Miranda musical Hamilton
Authors: Feng Yizhang , Chen Kexu
Published: June 2024

Lin-manuel-Miranda's musical "Hamilton" as the fastest in the history of Broadway music costs and began to profitable musical with its pioneer music style and the core values of drama structure in the world stage, the success of the Broadway musical is not only in the history, also for the development of world musical provides unprecedented possibilities.the success of Lin-Manuel Miranda's musical "Hamilton" has had a profound impact on the world of theater, particularly in the realm of musicals. Its pioneering music style and the core values of drama structure have opened up new possibilities for the development of musicals worldwide. The widespread appeal and profitability of "Hamilton" have inspired artists to experiment with different genres and storytelling techniques, pushing the boundaries of what is considered traditional musical theater. Furthermore, the global interest in historical and biographical musicals that "Hamilton" has generated has enriched the cultural landscape of musical theater, offering audiences a diverse range of stories and perspectives. Overall, "Hamilton" has left an indelible mark on the world stage, paving the way for future innovations in the field of musical theater.
Literature Review on Decision-Making and Coordination of Closed-loop Supply Chain
Authors: Sun Yuqi
Published: June 2024

Effective treatment and recycling of waste products in the operation of closed-loop supply chain can not only save resources and energy, reduce environmental pollution, but also reduce costs and increase profits for enterprises. All participants in closed-loop supply chain often make decisions with the goal of maximizing overall benefits. This paper aims at summarizing the research progress of decision-making and coordination of closed-loop supply chain, summarizing the factors that affect the decision-making of closed-loop supply chain from the non-economic behavior of decision-makers, green investment, uncertainty, government and policy, and summarizing the commonly used coordination mechanism of closed-loop supply chain, so as to explore the future research direction.
Making The Best Investment Strategy for Insurance Companies Under The Background of Extreme Weather
Authors: Li Meng , Han Xinke , Qi Huixin , Liu Ruiyun , Zhang Yan , Wei Zeji
Published: June 2024

In the face of the negative impacts of the frequent occurrence of extreme weather disasters around the world, we have developed natural disaster risk prediction and analysis models for insurance companies to maximize their benefits. This paper first selects six risk indicators, such as flood, cold wave, drought and other disasters, and combines the analytic hierarchy process (AHP) and grey prediction model (GM) to calculate the impact weights of six kinds of natural disasters, and predicts the probability of future occurrence, so as to realize the comprehensive assessment of natural disaster risk. This paper also analyzes the effect of the owner's intention to buy insurance on the insurance strategy through the function model, and solves the optimal insurance strategy through the technique for order preferenceby similarity to ideal solution (TOPSIS) and neural network. We define the ratio of the total profit of natural disaster insurance to the total cost as the decision coefficient K. When K is greater than 35%, the insurance company chooses to write the policy, and when K is greater than 5% and less than 35%, the insurance company chooses to bear the risk. Finally, this paper collected the data of Florida and Kyushu, Japan. Through the insurance model, it calculated that the total profit of natural disaster insurance in Florida was 635.8 million US dollars, while that in Kyushu was -61.51 million US dollars. Therefore, insurance companies should invest in Florida.
Assessing Refereeing Proficiency in Chinese University Basketball Leagues
Authors: Feng Jiahao
Published: June 2024

This research examines the perspectives of athletes and coaches on the competence of basketball referees, with a specific emphasis on important aspects such as understanding the rules, making decisions, communicating, managing the game, maintaining consistency, and resolving conflicts. By conducting an extensive survey that incorporates both quantitative and qualitative data-gathering methods, this study aims to provide a thorough understanding of the existing difficulties encountered by those involved in the field of basketball officiating. The results indicate that there is a general discontent with the level of officiating, as both players and coaches evaluated officials' performance low across all measured categories. In addition, the research reveals recurring obstacles that substantially influence the integrity and fairness of basketball tournaments. These issues encompass uneven officiating, communication hurdles, difficulty in game management, concerns over transparency and accountability, and subjective judgment calls. The research highlights the pressing necessity for focused development programs that aim to enhance the abilities of referees and tackle the highlighted obstacles in order to enhance the overall quality of basketball officiating.
Texture Classification Method Based on Local Enhancement and Non-local Median Patterns
Authors: Lian Yaxin , Dong Yongsheng
Published: June 2024

Local binary pattern (LBP) serves as a highly powerful method for texture classification. LBP and its variant methods are extensively applied across various domains of image processing.In increasingly complex imaging environments, LBP faces two issues: (1) Loss of detail information during feature extraction. (2) Sensitivity to noise. To mitigate these issues, this paper proposes a method called Local Enhancement and Non-local Median Pattern (LENMP). It consists of two operators: Local Adaptive Contrast Enhancement Pattern (LEP) and Non-local Median Binary Pattern (NMBP). The LEP operator captures the sign and magnitude details of local image characteristics, while the NMBP operator captures the global information of image features. First, the image is processed using the threshold ACE (thACE) algorithm to enhance the contrast of high-frequency information in the image, extracting image contour edge information. Then, median extraction is performed separately on the two operators to capture larger spatial texture detail information. Finally, comparative experiments are conducted on multiple datasets (Outex, CUReT, Brodatz, KTH-TIPS, and Kylberg) with representative texture classification methods. The results indicate that our proposed LENMP texture classification method exhibits good classification performance and remains competitive compared to the latest descriptors.
Expanding the Horizon: Diverse Applications and Insights from Multi-Armed Bandit Algorithms
Authors: Li Haoyang
Published: June 2024

In an era marked by the ever-increasing convergence of applications and algorithms, the imperative to maximize efficiency while mitigating the adverse effects of uncertainty has emerged as a critical objective for application developers. Despite this, a significant body of research on Multi-Armed Bandit (MAB) algorithms has predominantly focused on the comparative analysis of their performance, often overlooking their tangible impact on diverse applications. This study builds upon the data and findings of several preceding investigations that examine the application of MAB algorithms across various domains, including e-commerce, clinical trials, and dynamic pricing strategies. Our findings underscore the versatility and adaptability of MAB algorithms in enhancing the performance of applications across these varied fields. Notably, certain MAB algorithms demonstrate a higher suitability for specific scenarios compared to others. Consequently, this research posits that achieving an optimal balance between exploration and exploitation, and thereby maximizing rewards in uncertain environments, necessitates not just the application of MAB algorithms but also the strategic selection of the most effective algorithm tailored to each unique context. Overall, this study aims to showcase the wide-ranging applicability of MAB algorithms, offering a comprehensive exploration of their capabilities and impact across multiple sectors.
Intelligent Metro Passenger Flow Monitoring and Guidance System
Authors: Liu Jiangjun
Published: June 2024

With the rapid development of big data, image analysis technology, and artificial intelligence, the related businesses of smart subways have been gradually realized. Facing the huge passenger flow during peak hours, how to guide passengers to relatively spacious compartments has become a hot issue of concern. This article utilizes big data processing and existing image analysis technology in combination with the original subway system to develop an intelligent subway passenger flow monitoring and guidance system. This system consists of three parts: multi-terminal collection, data analysis, and intuitive guidance. The system has the advantages of high reliability, low cost, and real-time guidance, which is expected to help improve passengers' ride experience and ensure the normal operation of the subway.
The Intersection of Gender, Migration, and Urbanisation in Shaping Community Identities and Social Structures
Authors: Wu Yujia
Published: June 2024

This paper explores in depth the cross influence of three factors, gender, migration and urbanization, in shaping community identity and social structure. As the basic element of social composition, gender not only affects the self-perception of individuals, but also shapes the collective identity at the community level. As an important driving force of community development, the cultural diversity and social dynamics brought about by immigration have had a profound impact on community identity. However, urbanization, as an important feature of modern society, has had a significant impact on community identity and social structure by changing the physical and social environment of communities. In terms of community identity, the adjustment and remodeling of gender roles and gender relationships are an important part of community development.Simultaneously, the integration of immigrants involves the reshaping and rediscovery of identity, enhancing the complexity of community identity through interactions and contrasts with native residents. Moreover, urbanization-induced community shifts and population movements further complicate and diversify this identity. In terms of social structure, the promotion of gender equality awareness helps to break the shackles of traditional social structure and promote the community to a more equitable and inclusive direction. The influx of immigrants brings new social classes and interest groups and have an important impact on the social structure of the community. The rapid advancement of urbanization intensifies the differentiation and reorganization of social structure, which makes the class differences and conflicts of interest within the community more obvious. Gender, immigration, and urbanization have close intersections in shaping community identity and social structure. These three factors interact and influence each other to jointly promote the development and change of the community.
Study on the reduction of illegal wildlife trade based on data prediction
Authors: Wang Zishu
Published: June 2024

Wildlife is an important part of all life and natural ecosystem on earth, and their living conditions are closely related to the sustainable development of human beings. The current disorderly use has made the illegal wildlife trade become the third largest crime in the world, seriously affecting biodiversity, ecosystem service function, global social order and public security, and wildlife welfare. In recent years, the illegal wildlife trade involves as much as $26.5 billion a year and is considered the fourth largest illegal trade in the world, protection of wildlife has become a top priority. In order to obtain the method to effectively reduce the illegal wildlife trade and predict the change trend of illegal wildlife trade in the next five years,based on this background, this paper uses the collected data and the AHP hierarchical analysis, GM (1,1) model to construct the model of illegal wildlife trade research in the next five years.
The Transformative Role of Group Theory in Physics
Authors: Qin Mu
Published: June 2024

This article investigates the significant impact of Group Theory within the field of physics, having a particular focus on its application in comprehending difficult physical systems and phenomena. This report centers on the application of Lie groups, rotational groups, the Poincaré and Lorentz groups in order explain complicated features of physics. The report methodically discusses the role of the SU (2) group in Lie groups, the exploration of the rotational symmetries of the SO(3) group, and the significance of Lorentz transformations in special relativity with results demonstrate how Group Theory explains the nature of angular momentum in quantum mechanics and the limitations of the Schrödinger equation under Lorentz transformations. In addition, how the Poincaré group in special relativity is utilized. However, the scope of Group Theory's applications in physics is vast and multifaceted, making it challenging to encapsulate all its facets in a single report. This expansive field continues to evolve, promising further insights and innovations in the understanding of the physical universe.
Unveiling the Deep Connection Between Athlete Momentum and Match Scoring through Statistics Analysis
Authors: Zhang Boya , He Yifan , Shi Yiyu
Published: June 2024

The concept of momentum in ball sports is characterized by significant changes in-game performance and mental states, which play a key role in determining the outcome of a match. This study takes the 2023 Wimbledon men's final as an example and constructs a model for assessing athletes' performance during tennis matches based on binary logistic regression. It also constructs a tennis match momentum assessment algorithm to explore the relationship between the momentum change among match players and the performance change (score difference) of both players. It was found that the momentum change of match players was closely related to the score difference. This study is not only conducive to improving the athletes' competitive level but also has a profound impact on the scientific and professional development of tennis.
Research on the Application of Machine Learning Algorithms in Green Economy Indicator Modeling and Sustainable Development Evaluation
Authors: Zhang Ziqi
Published: June 2024

This study presents a comprehensive modeling and analysis framework for investigating the impact of green GDP on climate factors and its potential for promoting sustainable development. Our model utilizes the entropy weight method (EWM) and grey correlation analysis (GRA) to optimize and process data, while employing a BP neural network for model training. Results indicate that green GDP leads to smaller global climate damage compared to traditional GDP, indicating its potential to alleviate the global climate crisis and promote green development.Furthermore, we built a green GDP prediction model using LSTM to forecast future changes. From the perspective of economy and management, the results indicate that transitioning from GDP to green GDP initially leads to a decrease in the index, followed by an increase. This suggests that green GDP development has short-term drawbacks but long-term benefits, including reduced resource consumption, improved economic conditions, and contribution to sustainable development. Finally, we analyzed the learning rate, number of iterations, and thresholds of related parameters through Logistic binary classification. Results demonstrate that our model is relatively stable, highlighting how green GDP addresses ecological challenges while promoting economic prosperity. These findings underscore the urgency of adopting the concept of green GDP in the contemporary era for achieving sustainable development goals.Overall, this research provides critical insights on the potential benefits and feasibility of green GDP as a crucial tool for mitigating climate risks and enhancing global prosperity.
Advances in Radar Signal Processing: Integrating Deep Learning Approaches
Authors: Li Bangrui
Published: June 2024

In the military, in daily life, and in scientific research, radar technology is widely used. Radar signal processing has long been an essential component in target detection and imaging. The development of deep learning technology in recent years has given radar signal processing new approaches and resources. With its exceptional feature extraction and pattern recognition skills, deep learning has made amazing strides and has been applied to radar signal processing to enhance tasks like target detection, tracking, and recognition. Traditional radar signal processing is based on models. It mainly uses the prior information of the model and related signal processing criteria to design signal processing methods. It uses Gaussian, linear, and stationary assumptions. The deep learning method is a data-based method that does not require prior knowledge of the model and can spontaneously find the relationship between the input of the algorithm and the expected output. This article will review traditional methods and deep learning methods in radar signal processing, focusing on the application and future development direction of deep learning methods in radar signal processing, briefly sorting out the research progress in recent years, and analyze some existing problems or shortcomings of existing methods.
The Effect of Childhood Maltreatment on Violent Behavior in Adulthood
Authors: Zhao Chenyu
Published: June 2024

Childhood is the fastest and most critical developmental period for individuals to develop emotional and cognitive abilities. If children are abused, neglected, or raised in a family with traumatic experiences and dysfunctional dynamics during childhood, it is very likely to have an impact on their future development during adulthood. This review mainly discusses the contribution of childhood maltreatment to adult violent behavior. Previous studies on different aspects in the same direction were analyzed. It was found that with the trajectory, the negative impact of childhood maltreatment will not be reduced. Severity of maltreatment and later violent behavior, gender, experiences of different types of abuse, shame, personality disorder and some protective factors serve as mediators to varying degrees. Among them, psychopathy is a controversial intermediary factor. One study indicated that it could function as an intermediary factor, while another article only found it as a factor leading to violent behavior, and there was no evidence to prove the impact of maltreatment on it. This review can provide some guidance to the design of intervention programs for children in need.
Phonetic Learning Strategies for Chinese as a Second Language
Authors: Jiao Bingyang
Published: June 2024

In the process of international Chinese teaching, pronunciation is the key and difficult point of second language learners, due to the lack of real language environment, learners are affected by factors such as negative transfer of their mother tongue, and the phenomenon of foreign accents is common when learning pronunciation. Based on the characteristics of modern Chinese pronunciation, this paper aims to explore the factors influencing foreign learners' acquisition of Chinese phonetics, and to find ways to improve learners' pronunciation accuracy and fluency.
Business Model Analysis and Evaluation of Hotpot Catering Industry ——Taking Haidilao and Xiabu Group as examples
Authors: Zhou Qunfeng
Published: June 2024

Hotpot is a form of catering that has existed for thousands of years in China. Under the background of rapid development in China, the hot pot industry has created a solid market with traditional cooking technology and rich innovation mode and has become one of the important forces in China's catering industry. In the face of fierce market competition, the correctness of the business model often determines the development path of enterprises. To evaluate the impact of different business models on the development of the food and beverage industry, this paper compares the business models of Haidilao and Xiabu Group, analyzes their business models, feedback data, operation strategies, and marketing methods, and evaluates the development prospects of the two models according to the analysis results.
A Mobile AD Hoc Network Relay Method based on OLSR Protocol
Authors: Du Hongwei
Published: June 2024

Aiming at the reliability and performance problems of data transmission in the complex mobile AD hoc network environment, a relay method is designed and implemented in the unstable network environment with complex dynamics such as mobile, multi-hop and no center according to practical needs. By introducing a prior link-state routing protocol, OLSR is introduced. Using range value judgment, sliding window statistics and improved multi-point relay selection technology, it can effectively reduce the redundancy of relay node set, reduce the forwarding frequency of service data in the network, save the network overhead, and ensure the data transmission delay and quality in the large scale and dense mobile AD hoc network.
Analysis of College English Acquisition Strategies
Authors: Li Ruizhen
Published: June 2024

The second language acquisition theory proposed by Krashen in the 1980s is a relatively complete theoretical system of second language acquisition at present. Among them, the most influential is the acquisition-learning hypothesis. He believes that acquisition is the most important. Learners can successfully communicate, mainly the acquired knowledge. College English is the language that all college students in China must learn, and it is also the second language of students. This article takes the acquisition strategy analysis of college students as an observation point and discusses it in five parts. First of all, the introduction introduces the research background. Secondly, briefly introduce the second language acquisition strategy. The third part analyzes the current situation and existing problems of college English acquisition. The fourth part analyzes the strategic factors that affect students' English acquisition. The fifth part analyzes the implications of second language acquisition strategy factors for learners to learn English. Finally, let's summarize.
Vegetable Merchandise Analysis from a Quarterly Sales Data Perspective
Authors: Sang Yuxin , Li Peiyan , Yin Ziliang
Published: June 2024

In the field of fresh vegetable retailing, the category diversity and time-sensitive characteristics of commodities pose unique challenges to inventory management and pricing decisions. Comprehensively analyzing the distribution pattern of sales volume of different categories and individual items of vegetable commodities and their interrelationships is of great significance to retailers' scientific replenishment and pricing decisions. By categorizing vegetable sales every quarter, a comprehensive analysis is carried out on a category and individual item basis. Visualization was used to show the distribution pattern of sales volume by category and individual item. Subsequently, Kendall correlation analysis was utilized to explore the relationship between the sales volume of different vegetable categories. In addition, the interrelationships between the sales volumes of different vegetable individual items were investigated in conjunction with waterfall diagrams. Through in-depth analysis of sales data, understanding the sales relationship between different vegetable categories can help retailers develop a more refined pricing strategy, make pricing adjustments based on the relative sales of goods, and improve sales revenue and profit levels. Such scientific inventory management and pricing strategies not only help meet customer demand and enhance customer experience, but also strengthen customer loyalty and promote long-term stable business development.
A Capacitive Transparent Liquid Concentration Detecting System Based on LabVIEW
Authors: Shangguan Fuze , Cui Wenmin , Liang Shuoyi , Lin Xihan , Wang Kuilong
Published: June 2024

The accurate detection of transparent liquid concentrations holds widespread applications in production and daily life, making the design and development of novel detection systems crucial. In this study, a capacitance-based detection system for measuring the concentration of transparent liquids was successfully designed and implemented. The system utilized a cylindrical capacitive sensor and FDC2214 module for capacitance measurement, with data acquisition, processing, and display accomplished through an Arduino microcontroller and a LabVIEW program. The results of practical detections demonstrate that the developed system exhibits advantages such as non-contact operation, low cost, high accuracy, minimal sample requirement, and rapid detection speed. This system effectively meets the demands for transparent liquid concentration detection.
The Effects of the AIGC Software on English Majors: Professional Competence, Individual Perceptions, and Career Planning
Authors: Wei Qianjun
Published: June 2024

In recent years, the application of AIGC-type software in the teaching of English majors has become more and more widespread and attracted much attention. This study aims to investigate the application value and use satisfaction of AIGC-type software in teaching English majors, as well as the effects on students' individual ability and cognition. The study adopts a natural experimental method to collect data through questionnaires and interviews with ten English majors as research subjects. The study shows that AIGC-type software can effectively improve students' translation ability and self-confidence, but there are differences in the demand and acceptance of AIGC among students of different academic and ability levels; students' willingness to use AIGC is generally on the rise and their satisfaction is high, but there are still some questions and concerns; AIGC-type software can help students clarify their career planning, but their future roles may not be a replacement for human translators, but an aid for translators.
Portrayal of Autism in Film and Television: Discrepancies with Real Life and Their Impact
Authors: Gong Ke
Published: June 2024

Movies and television, with their influential power, shape societal perceptions of individuals with autism, a multifaceted neurodevelopmental disorder. This study examines how the media portrays autism spectrum disorder (ASD), using the TV show "The Good Doctor" as a case study. Through a comparison between the show's portrayal and actual experiences, the research identifies both correct and potentially misinterpreted representations. It highlights how the media shapes how the general public views people with ASD and advocates for a reasonable strategy that takes into account the condition's complexity. The study notes potential preconceptions regarding genius talents while highlighting sections where the show accurately depicts social obstacles. In an effort to debunk misunderstandings and lessen stigma, it promotes responsible storytelling as a means of fostering compassion, understanding, and awareness of autism. For a more thorough understanding of the impact of media on perceptions of ASD, empirical data should be incorporated into future research.
Research on the Preferences of U.S. Venture Funding Deals in 2023 for the Industry in Which the Company Operates
Authors: Lei Xianyang
Published: June 2024

Since the effects of geopolitics and recession, venture capital deals have become more cautious and companies' access to capital has become more difficult. Therefore, this research will analyze 2023 U.S. venture capital deal data to explore venture capitalists' preference for the corporate industry. In previous similar studies, visual graphics were essential, which was also applied in this study. At the same time, OLS regression model was also used for verification in this research. The results show that in 2023, U.S. venture capital deals favor the technology industry, especially the two hot spots of artificial intelligence and biotechnology. There is a positive linear relationship between venture capital investment and corporate hot spots. When the company industry moves closer to the technology industry, the amount of venture capital investment increases significantly. However, the November-December data is still to be added. Forecasting the future preferences of the venture capital trading industry is also an issue that needs to be addressed. Finally, on the basis of previous studies, this paper also provides some meaningful results for venture capital market participants, hoping to help improve the efficiency of venture capital market.
Research on public policy plan of unemployment risk caused by artificial intelligence
Authors: Cheng Rui
Published: June 2024

At present, artificial intelligence has been widely used in many fields of economy and society. The development of artificial intelligence has rich implications for the times and is closely related to unemployment. Technical unemployment, structural unemployment, asymmetric unemployment, and sudden unemployment are the realistic forms of unemployment caused by the development of artificial intelligence. With the rapid development of artificial intelligence (AI) technology, unemployment risk has become a problem that cannot be ignored. In order to meet this challenge, the supply path of public policy is particularly important. This paper will discuss how to effectively alleviate the unemployment risk caused by artificial intelligence through the supply of public policies from five aspects: policy support, education and training, employment service, social security, and regulatory supervision.
Prediction on the Prices of Laboratory-Grown Diamonds based on Multiple Linear Regression Model
Authors: Xu Jingru
Published: June 2024

Diamond as emotional investment, in recent years, the market price of it is going through rising and falling, and drastic fluctuating, more is the decline in price. The diamond industry has also been challenged, there is happening oversupply and weak demand in diamond market. The impact of lab-grown diamonds on natural diamonds has also changed the price of diamonds across the diamond industry. However, the market of diamond is still at the forefront of the jewelry industry. In order to ensure that consumers have more understanding of diamond choices, this paper adopts multiple linear regression model to forecast diamond prices, collects a large amount of data, and uses 4c criteria as the standard for diamond price prediction to explore the relationship between diamond prices and diamond measurement standards. Through the calculation, the diamond buyers will explore ways to realize diamond price, the diamond industry will be rationalized production, and balance the relationship between diamond supply and demand to provide a method.
Design of heliostat field based on ray tracing
Authors: Deng Hao , Chen Haiwen , Wang Xinxiang
Published: June 2024

In the tower solar thermal power generation system, the optical efficiency of mirror field is the primary factor that determines the power generation efficiency of the whole system. Given the size and installation height of heliostat, in order to meet the requirements of rated Power 60MW, the parameters of heliostat field are designed and the model of tower solar thermal power generation system is established. Considering the cosine loss, shadow occlusion loss and truncation efficiency, and knowing that these three points are closely related to the position of the Sun, a method of ray tracing is proposed to calculate the sunshine accurately, the optimum parameters of helioscope field were determined by simulation. The simulation results show that the average thermal power output per unit mirror area can be increased by reducing the shadow occlusion between the heliostats.
Trends and Dynamics of China's Lodging and Catering Industry: A Comparative Analysis
Authors: Wang Ziyan
Published: June 2024

This article mainly writes about the trends and development of China's catering and lodging industry in recent years, and by analyzing the collected data, this research can give suggestions for development in the next few years. This article mainly uses the comparison method, after collecting the data, by comparing the change of data in different years, through the comparison method, this paper can more intuitively feel the change of different years, which can help us to analyze better. The rigor of this study is very high because all data and conclusions are collected from official data. The research in this article will have an important impact on those who want to work in the food and beverage industry in China. Those who want to work in the industry, can use the article to find out whether the industry will be stable in the future. Those who want to start their own business in this field can use the article to know whether they are ready to enter the market now.
The Pink World of Prudence Flint
Authors: Qi Xue , Wang Runxin
Published: June 2024

Prudence Flint is a female painter living and working in Melbourne, whose paintings are characterized by extremely bright pastel shades and slightly exaggerated female nudes. The gentle serenity that is unique to women from a female perspective is brought out in her images. She portrays ordinary women in a variety of interior spaces, showing the beauty of their bodies deliberately reshaped and sculpted, while the backgrounds are rendered with transcendent simplicity and comforting colors. This paper takes several key works of Flint's since her career and her oral interviews as references and explores how Flint's attitude towards patriarchal society is expressed through the manifestation of "femininity" in her paintings, in combination with the theories related to Western dualism and feminist thinking.
Research on the Application and Prospect of Digital Currency in International Trade Settlement
Authors: Gao Xiaoyan
Published: June 2024

With the increasing integration of the global economy, the international trade settlement method is also constantly evolving. As an emerging means of payment, the application of digital currency in international trade settlement has gradually attracted more attention. This paper aims to discuss the application status, advantages, challenges and future development prospects of digital currency in international trade settlement. Through research, it is found that digital currency shows the advantages of high efficiency and low cost in international trade settlement, but it also faces challenges such as technical security and lack of regulation. Looking ahead, digital currencies are expected to play a bigger role in international trade settlement, but the government, enterprises and technology providers need to work together to overcome existing problems, improve the regulatory system and promote the healthy development of digital currencies.
The Role of Lamprey Sex Ratios in Ecosystem Dynamics: An Analysis Using Lotka-Volterra Models
Authors: Ke Xue , Cheng Ruilin , Li Yahui
Published: June 2024

With global ecological changes, studying the sex ratio of lampreys in ecosystems and their impact on the food chain and ecological stability has become a key topic in ecology and environmental science. Lampreys are found mainly in the North Pacific region and are considered to be parasites that have a significant impact on the ecosystem. The sex ratio of lampreys is not as 1:1 as in most species, depending on how quickly they grow during the larval stage. In response to this, this study started with the living habits of lampreys and studied the impact of different years in different watersheds on the sex ratio of lampreys, as well as the relationship between water temperature and catch quantity. Subsequently, the Lotka-Volterra model theory was applied to prove that the sex ratio of lampreys has a greater impact on ecosystems in simpler food chains, but a smaller impact in more complex food chains. This study successfully revealed when the population of lamps can alter its sex ratio, lampreys have a certain impact on the quantity and structure of species in ecosystems.
China's A-share Crash in 2015- -Based on the Perspective of the Liquidity Barrier Lake Caused by the "Targeted Easing" Policy
Authors: Pan Weixin , Yu Linze
Published: June 2024

This paper is based on the theory of liquidity effect, that the 2015 crash is formed by directional easing liquidity of the lake, namely the central bank directional loose monetary policy derived monetary is not through monetary policy transmission channel to the entity neighborhood, but deposited in the financial system, pushing up the rising asset prices, and cause industrial "real to virtual", further boost the financial asset prices and the real economy fundamentals mismatch. Small and medium-sized enterprises and state-owned enterprises local government "hidden guarantee" of real estate, city investment companies in financing credit discrimination, and commercial Banks to lend behavior, also led to the liquidity of the formation of the lake finally, this paper summarizes a series of Suggestions, such as accelerating the marketization of interest rate reform, improve the monetary policy management, improve the macro-prudential monetary policy framework, establish and improve the multi-level capital market measures, to prevent such problems from happening again, make the central bank's monetary policy can more powerful through the financial system to the real economy, promote the development of our country economy with high quality.
Introduction Remote-operated Underwater Vehicle for Inspection of Underwater Structure
Authors: He Jianghai
Published: June 2024

Since many dams and bridges constructed in last century are facing serious safety issue resulting from leakage, erosion, and crack, it is increasingly urgent to develop more inspection and repair technologies that can be used for the maintenance operation. This essay introduces the practical application of underwater structure inspection conducted by remote-operated underwater vehicle. The applications include Mullaperiyar dam, Amagase dam, Aqua bridege, and Shorenji dam. And the application skills are summarized in inspecting small leaks of dam in clean water, inspection in turbid water, conducting survey in easy-entangled environment, and operation in flowing water. The advantages of remote-operated underwater vehicle compared with traditional divers are accumulated, and the remaining problem of existing remote-operated underwater vehicle are also summarized. This paper further provides experience of its operation in low-visibility water and stabilizing its position in turbulence, as well as solving the difficulties of getting the cables entangled in easy-winding water. Besides, an outlook is provided for remote-operated underwater vehicle’s development tendency in the field of underwater detection and reinforcement, with the purpose of addressing more critical problem in maintaining underwater structure in the future.
Creativity in Translation: A Study on Apple’s English-Chinese Advertising Translation based on Communicative Translation Approach
Authors: Wu Chen
Published: June 2024

With a focus on creativity, this study investigates the translation of Apple’s English-to-Chinese advertisements in light of Peter Newmark’s Communicative Translation approach. Detailed analysis reveals that Apple’s creative use of translation techniques such as idioms, puns, and network catchphrases, instead of literal translation, effectively produces an equivalent effect on the target audience. This research highlights the significance of creativity in tech product advertising translation, offering insights for advertisers seeking to create compelling and engaging translations.
The Effect of Aerobic Exercise among Obese College Students: Towards an Intervention Program
Authors: Zhou Huimin , Dr. Hazel
Published: June 2024

Due to the improvement of the quality of life, people's intake of excess nutrition, the temptation of electronic and other technological products make people sit for a long time without exercise. With the intensification of urbanization, these problems directly lead to the emergence of a large number of chronic metabolic diseases such as obesity, which seriously threatens human physical and mental health. As a pilot study, U1 University, with more than 20,000 students, obtained their BMI from the results of physical health tests organized by the school for all college students. According to the health standards of the World Health Organization (WHO), 28≤BMI≤32 is considered to be obese, and BMI≥32 is considered to be very obese. According to the physical health test of the school once a semester, students with BMI≥28 were screened and aerobic exercise intervention was conducted for 8 weeks to explore the feasibility of exercise intervention program for obese college students to reduce weight and fat.