bluuebunny/crossref_metadata_2025 huggingface dataset:
Wordle word difficulty classification based on K-means
Authors: Xiong Chen , Yang Xinbo , Zhang Jiahui
Published: January 2024

Wordle is a popular word-guessing game, and the analysis of Wordle games will play an important role in updating its iterations. In this paper, a word difficulty classification model based on K-means cluster analysis is developed. Clustering the dataset of the number of times required for word guessing, the words can be classified into three categories according to their difficulty: hard, medium and easy, with the corresponding labels of 3, 2 and 1. The attributes of the words in each category were counted and analyzed to arrive at the following: 1) The more common the word, the less difficult it was. 2) The more repeated letters in the word, the more difficult it was. 3) The experiment substitutes the example word EERIE into the model and the difficulty classification result is medium. The profile coefficient index of the model is 0.372. The cluster analysis method applied in this paper has good training results and is suitable as technical support for Wordle game analysis.
The Reasons on The Worse Situation of Canon Cameras
Authors: Huang Junyi
Published: January 2024

Canon cameras have gained appeal as a result of the popularity of social media. However, the declining camera market during the epidemic has had an impact on Canon due to a decrease in non-essential purchases. The purpose of this study is to analyze why Canon's market performance has been less than stellar since the epidemic. Using Canon's global camera market as an example, market sales and segmentation data from 2020 will be analyzed. Existing academic research and papers will also be quoted to demonstrate Canon's market evaluation. Canon should incorporate more of its brand identity to address its innovation challenges. In order to address Canon's brand loyalty issue, it is proposed that Canon re-launch fresh marketing strategies and invite professionals to promote the products. To attract this customer segment, it is advised that Canon continue production of point-and-shoot cameras or expand the experience of unprofessional young people. This study's research value is to fill an academic void in the analysis of Canon's market performance, which is not as good as it once was, and to make recommendations for Canon's future development.
Brand Rejuvenation: How Do Traditional Brands Maintain Stable and Sustainable Marketing Effectiveness - Take Holland as An Example
Authors: Li Shuaiying
Published: January 2024

Due to the background that traditional brand now having trouble operating and young people have become the purchasing power, this study explores the reason for brand rejuvenation, determining factors of brand rejuvenation, ways to perform brand rejuvenation properly, and problems of brand rejuvenation in cake industry context and set Hollyland as an example to analysis brand rejuvenation. The 4P model is used in the research to analyse the case. In the case of Hollyland, product is designed to be of appealing appearance, place is set to be convenient for consumers, while the price is relatively higher than brands with similar market share. Among all marketing strategies of Hollyland, co-branding method and the taste stand out, which contribute to Hollyland’s development in the consumer’s purchasing experience aspect. Purchasing experience is found to be the most important factor affecting consuming behavior. The findings provide greater insights into consuming behavior and brand development, giving traditional brands ideas of better developing novel products. The findings also suggest that traditional brands should dive deep into ways of improving younger consumers’ purchasing experience, such as introducing co-branding, designing novel packaging and so on.
Impact of Pesticides on Food Quality and Human Health
Authors: Leng Bo
Published: January 2024

This research explores the impact of pesticides on crop quality and food safety. The widespread use of pesticides is a fundamental practice in modern agriculture, aimed at protecting crops from the perils of pests and diseases. However, pesticide usage goes beyond pest control, affecting both crop quality and food safety. Studies indicate that prolonged exposure to specific pesticides, such as organophosphates, can lead to adverse changes in the aroma, taste, and nutrient content of crops, raising concerns about the nutritional value of pesticide-treated produce. Factors influencing pesticide residues, including application timing and soil characteristics, add complexity to managing residue levels in crops. Public awareness and education initiatives are crucial in addressing the potential risks associated with pesticide residues, emphasizing safe food handling practices. A critical worry is how pesticides affect people's health, with chronic health effects including neurotoxicity, carcinogenicity, and reproductive issues. Acute pesticide poisoning remains a pressing global issue, especially in regions with intensive pesticide use. Children, due to their vulnerability, are at higher risk of cognitive development issues linked to pesticide exposure. Regulatory measures play a crucial role in minimizing health impacts. Protecting vulnerable populations, monitoring long-term health effects, and promoting sustainable agricultural practices are essential steps in mitigating the adverse effects of pesticide use.
The Application of AI in Social Development And A Survey of The Stock Market of Leading Companies
Authors: Dong Yinqiao , Fan Haoxing , Zheng Kaihao
Published: January 2024

The AI craze that started in the mid-20th century has reached its peak now, and people's lives are increasingly dependent on AI technology, ranging from surgical treatment to helping people with multiple-choice questions. It is foreseeable that the future trend of artificial intelligence technology will move in the direction of intelligence, efficiency and convenience. Therefore, it is necessary to have an in-depth understanding of the operation of the industry and the development of the leading companies in the industry. This paper mainly adopts the comparative research method. First of all, the development status and existing problems of the artificial intelligence chip industry are analyzed. Then, compare and analyze the development of NVIDIA and AMD and the advantages and disadvantages of their products. Finally, suggestions are put forward for the problems existing in the artificial intelligence chip industry. After a period of research, this article found that exclusivity is particularly sought after in this industry. For example, NVIDIA's H100 tablet helped NVIDIA in the AIGC industry.
The Impact of Digital Financial Inclusion on Green Innovation in the Yangtze River Delta
Authors: Shen Xingyue
Published: January 2024

Digital financial inclusion is developing rapidly, and studies have confirmed that it has brought great impact on science and technology innovation. Taking green innovation as a new perspective, this paper explores the impact of digital inclusive finance on green innovation in the Yangtze River Delta from 2011 to 2020 based on the use of Eviews software, and concludes that digital inclusive finance has a significant positive effect on green innovation in the YRD region. It is further analyzed to conclude that both the sub-dimensions of breadth of coverage and depth of use of digital financial inclusion play a significant positive effect on green innovation.
Research on the Impact of Monetary Policies on Economic Development: Perspective from the United States
Authors: Chen Tszching
Published: January 2024

During COVID-19, the Fed applied several policies to boost the economy, including tax cuts and lower interest rates. In March of 2022, the Fed began raising the interest rates as a response to the inflationary economy, which put a full stop to the COVID-19 period economically. The series of monetary policies used by the Fed have captured widespread attention since it influences different markets and sectors. This essay examines the effects of monetary policies used by the Fed on different markets by looking at the data published by the Fed and the banks, and also include evaluation made by experts in news and essays. This paper can conclude that expansionary monetary policies to some extent, are considered helpful for lowering the inflation rate, however, they will cause some destruction to the housing market, banks, investors, and the whole global economy, the author can see this through criticism and data from the housing market, the bankruptcy of some banks and different industries. This essay includes both the positive and negative effects of a few common monetary policies and makes an overall suggestion.
Application Of The CRISPR-Cas9 System to Drug Discovery in Breast Cancer
Authors: Zhang Yifei
Published: January 2024

To elucidate the functioning of the CRISPR-Cas9 system in the realm of drug discovery, a series of experiments were undertaken. Firstly, CRISPR-Cas9 was employed to facilitate both positive and negative selection screening within human cells. Subsequently, an exploration of genes vital for pluripotent stem cell and cancer cell viability was conducted. Following this, in a melanoma model, a screen was performed to identify genes whose loss contributes to resistance against vemurafenib, a therapeutic agent targeting the mutant protein kinase BRAF. Notably, the top-ranking candidate genes included previously verified genes such as NF1 and MED12, alongside novel discoveries in the form of CUL3, NF2, TADA1, and TADA2B. This investigation revealed a remarkable consistency among distinct guide RNAs directed at the same gene, with an elevated rate of successful hit confirmation. These findings underscore the potential of genome-scale screening employing Cas9, thus substantiating CRISPR-Cas9 as a potent methodology for large-scale sequencing and the selection of target sites.
The Impact for the Countries Joined the Ancient Silk Road
Authors: Xu Ruize
Published: January 2024

The Silk Road may have had an impact on the countries through which it sailed, but theoretical analysis as well as facilitated cultural exchanges among diverse populations from various nations and ethnicities. The ancient Silk Road, as the first commercial passage connecting the East and the West, the establishment of an extensive transportation network had a profound impact on the culture and economy of multiple countries. Whether there is an effect, however, remains to be seen. This paper will conduct research through the literature research method, and correctly understand its influence on the country by investigating the literature about the Silk Road. The study unveiled that the ancient Silk Road exerted a substantial impact on the culture and economy of various nations. Language, religion, music, and other cultural elements were disseminated to countries participating in the ancient Silk Road through books or musical instruments. Serving as an exemplary model of ancient international trade, the ancient Silk Road greatly facilitated the exchange of goods and pioneered commercial connections between the East and West. It not only facilitated extensive exports of silk and porcelain for many countries but also introduced locally unavailable commodities.
The Impact of China's Introduction of Tesla on Itself and The Chinese Economy
Authors: Chen Zexi
Published: January 2024

Tesla's steadfast commitment to minimizing pollution while delivering exhilarating performance has catapulted it to the forefront of the electric vehicle revolution. Its strides toward reshaping the automobile industry align seamlessly with the burgeoning global call for environmentally conscious travel options. Within China, Tesla's trajectory has been nothing short of remarkable. The brand has captured the imagination of Chinese consumers, who perceive it as a symbol of the transition towards a cleaner and greener future. Tesla's presence has mirrored the rising awareness of the imperative to reduce carbon footprints and embrace clean energy alternatives. The Gigafactory in Shanghai, a testament to Tesla's commitment, stands as a manifestation of its dedication to the Chinese market, fostering local production and bolstering the country's electric vehicle ecosystem. However, this journey has not been devoid of challenges. As Tesla navigates China's complex business landscape, it must contend with regulatory intricacies, competition, and the evolving preferences of consumers. Ensuring a seamless charging infrastructure, addressing range anxiety, and adhering to local regulations have posed hurdles for Tesla's expansion. The brand's ability to overcome these challenges and maintain its position as a market leader will be pivotal in shaping the future trajectory of electric vehicles in China. In conclusion, Tesla's ascent in China underscores its global prominence as a torchbearer for electric mobility. Its dedication to pollution-free performance and the changing preferences of environmentally conscious consumers have solidified its stature.
Impact of the Russian-Ukrainian Conflict on the International Situation in Russia
Authors: Hu Qican
Published: January 2024

The complex Russo-Ukrainian conflict, rooted in historical, political, and territorial contentions, has far-reaching implications that extend beyond regional boundaries. This ongoing conflict has fundamentally reshaped Russia's global stance through its multifaceted impact on Western relations, economic repercussions, security recalibrations, and strategic use of propaganda. In navigating a way forward, diplomatic negotiations, leveraging multilateral forums, and addressing core grievances emerge as promising avenues. Diplomacy, facilitated by impartial mediators, emerges as a pivotal instrument for mutual comprehension and conflict resolution. Embracing multilateralism and active participation in international organizations not only fosters open dialogues but also facilitates collaborative solutions. An essential component of lasting tranquility involves addressing underlying issues, encompassing concerns over minority rights and disputed territories. Successfully resolving these foundational matters holds the potential to restore Russia's credibility, cultivate cross-border collaboration, and bolster the stability of the region. By embracing productive diplomatic initiatives, Russia can look forward to fortifying its global relations, fostering economic progress, and strengthening the foundations of international security. In the midst of these challenges, the quest for peaceful resolutions underscores the potential for broader international cooperation, ultimately contributing to a more stable and prosperous global landscape.
Lagrange's mean value theorem in hyperbolic number plane
Authors: Zhao Yukang , Xia Yiqiang , Qiu Yu
Published: January 2024

Hyperbolic number is a generalization of real number, it is a commutative ring of zero factor, and has been widely used in many fields such as mathematics, physics and engineering. In this paper, we first review the basic concepts and properties of hyperbolic numbers, and then study the Lagrange's mean value theorem on the hyperbolic numbers plane, and get a more general theorem. This not only provides impetus for the development of hyperbolic analysis, but also further injects energy into the development of applied mathematics.
A Study on Measuring the Efficiency of Digital Inclusive Finance Enabling High-Quality Fiscal Development in Provinces
Authors: Zhu Xiaoqian , Xiao Xingru , Bo Yating
Published: January 2024

With the rapid development of the global economy, digital inclusive finance as a new innovative model directly affects the real economy, which also has a boost for local government finance. In order to realize digital inclusive finance empowering local financial development, this paper takes 31 provinces' financial development as the research object, selects digital inclusive finance data and 31 provinces' panel data during 2015-2021, and applies DEA three-stage data envelopment analysis to construct the evaluation index system of the efficiency of each province's financial development based on the environmental indicators, which contains input indicators, output indicators and environmental variables and combines with the Malmquist index for dynamic analysis, found that South China has the highest efficiency after empowerment, while Northwest China has the lowest, at the same time, need to pay more attention to the environment in East China and North China, and the total factor productivity is affected by the epidemic in 2021 and the trade friction between China and the United States, showing a decreasing trend. Accordingly, this paper proposes to deepen the depth of the use of digital inclusive finance by strengthening the cooperation between relevant technology and financial companies and other suggestions to emphasize the development of digital inclusive finance, pay attention to the impact of environmental factors, and appropriately increase the scale of implementation and other countermeasures.
A Study of the Impact of China's Internet Economy on the Agricultural Industry
Authors: Wu Yongyi
Published: January 2024

In recent years, China has faced the challenge of economic transformation and the triple pressure of contracting demand, supply shocks and weakening expectations. In the past, China's economic growth was mainly driven by trade and investment. Nevertheless, the share of consumption in the economy has been increasing, becoming one of the most critical factors in China's economic development. The rapid development of Internet technology has promoted online consumption, thus providing a good opportunity and a platform for selling agricultural products online in remote areas. This paper focuses on the impact of the development of China's Internet economy on the agricultural industry. It is found that the development of China's Internet economy has a positive impact on the development of the agricultural industry and the sale of agricultural products. Whether in the pre-epidemic, epidemic, or post-epidemic period, online sales of agricultural products show a continuous growth trend. This paper also presents the problems of selling agricultural products online and provides reasonable solutions.
Study on Prestressed Steel Dome Structure
Authors: Zhang Jiayi
Published: January 2024

With the rapid development of new materials, new processes, and new structures in recent years, the application of prestressed steel structures has been increasingly used, especially for long-span spatial structures. Among the commonly used prestressed steel structural systems, the suspend-dome structures and cable-dome structures can effectively resist loads through prestress distribution. This article explains and demonstrates the features and development of the suspend-dome structure and the cable-dome structure based on the background and characteristics of the prestressed steel structure. Some engineering projects based on these two systems are introduced. Due to their great properties and stress distributions, suspend-dome structures and cable-dome structures can adjust their shapes to meet different architectural requirements, especially shown in many public venues like sports centers. It is expected that prestressed steel structure has bright prospects in the future and the development of prestressing disciplines can be increasingly more significant. This article may offer a reference for the development of prestressed steel structures.
Applicability Analysis of Cryptocurrency Market Based on Capital Asset Pricing Model
Authors: Liu Yuhan
Published: January 2024

At present, there are approximately 9300 types of cryptocurrencies in the cryptocurrency market, with Bitcoin, Ethereum, and other representative cryptocurrencies receiving widespread attention. Currently, scholars have conducted a lot of research on stock pricing using the Capital Asset Pricing Model (CAPM), but there is little research on the application of CAPM in the emerging cryptocurrency market. This article uses the CAPM to conduct an applicability analysis of CAPM of the top 10 cryptocurrencies in the cryptocurrency market from August 1 2021 to July 31 2023. The analysis process involves first conducting a mathematical analysis of the returns and coefficient  of cryptocurrencies, and then using the OLS regression model to fit the cryptocurrency data and CAPM formula with analyses of the OLS regression results. The research conclusion of this article is that in most cases, CAPM is not applicable in the cryptocurrency market. This article demonstrates an applicability analysis of CAPM in the cryptocurrency field, providing reference value for scholars conducting research in this field and investors in cryptocurrencies.
A Comparative Analysis of Petrochemical Industry Development in China and The United States.
Authors: Han Kaibo , Sun Kexin
Published: January 2024

Concurrently, the petrochemical industry serves as a catalyst for scientific and technological innovation, propelling the frontiers of knowledge while spearheading societal progress. This symbiotic relationship between industry and innovation has been pivotal in shaping the trajectory of scientific development, technological advancement, and the broader societal landscape. This discourse endeavors to undertake a comparative analysis of the petrochemical landscapes in both China and the United States. Through such an examination, the aim is to galvanize mutual progress in technological innovation, enhance competitiveness, facilitate resource synergy, and foster bilateral cooperation. By emulating sustainable practices from both nations, the petrochemical sector can chart a course toward harmonious and ecologically-conscious growth. The ramifications of this collaboration hold the potential to catalyze growth within the petrochemical industry of both countries. Not only will it serve to bolster their economic development, but it will also be instrumental in underpinning their strides towards sustainable development. Ultimately, this harmonized approach stands to amplify the progress of the petrochemical domain, acting as a catalyst for economic growth while championing a sustainable and balanced future.
Opportunities and Challenges of New Energy Vehicles in Carbon Neutrality and Financial Investment Banking
Authors: Lin Li
Published: January 2024

One of the biggest problems the world is currently experiencing is global climate change, requiring all industries to work together to mitigate its adverse effects on the environment and society. In this context, carbon neutrality has become a topic of widespread concern and discussion. This article focuses on the role that financial investment banks play in initiatives for carbon neutrality and their function in the area of alternative fuel vehicles. This study will go into the history and difficulties of creating new energy vehicles, highlighting the critical function of market-based carbon pricing in achieving emissions reduction targets. The research results show that the new energy vehicle field has good development prospects, but there are also development challenges. Financial investment banks play a crucial role in advancing the carbon neutrality strategy and provide important support for enterprises to achieve sustainable development by providing services such as financial support, risk management and market analysis. Finally, the research significance of this article lies in an in-depth discussion of the role of financial investment banks in carbon neutrality strategies, which provides useful reference and guidance for achieving sustainable development goals.
Comparative Analysis of Machine Learning Algorithms for Sentiment Classification in Amazon Reviews
Authors: Yu Bole
Published: January 2024

Sentiment analysis serves as a crucial approach for gauging public opinion across various sectors, including the realm of product reviews. This study focuses on the evaluation of customer sentiments in Amazon reviews using an array of machine learning algorithms—Logistic Regression, Random Forest, Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks. The methodology employed is robust, characterized by meticulous parameter tuning based on both theoretical and empirical considerations. Comparative analysis of these algorithms, grounded in accuracy and other performance metrics, offers valuable insights into their respective efficacies and limitations for sentiment analysis tasks. The findings of this study contribute to an enhanced understanding of the performance of different machine learning algorithms in sentiment classification and provide a foundation for future research in this domain.
Traffic flow simulation study under large gathering activities based on VISSIM
Authors: Li Xiangcheng
Published: January 2024

Based on the above background, this paper starts from the theory of traffic flow and the macro-basic diagram, and simulates and researches the traffic congestion problems generated in the period of large-scale gathering activities during festivals. First of all, this paper summarizes the time correlation and spatial correlation of traffic flow, analyses the judgement method and rating index of traffic congestion, and completes the macroscopic basic map; after defining the simulation parameters of each road segment and signal intersection in the road network, it is implemented by using the VISSIM simulation software; finally, it carries out the simulation analysis with the example of the New Year's Eve firework display at the Chaotianmen Gate in Chongqing, and calculates and analyses the traffic flow state of the road network with output data, and then compares the output data with that of the road network. Finally, we use the output data to calculate and analyses the traffic flow status of the road network, compare it with the traffic flow data under the smooth period, judge the congestion characteristics, draw the macroscopic basic map of the road network under each period, simulate the changes of the macroscopic basic map, analyses the impact of traffic congestion on the traffic flow of the road network, calculate the degree of improvement of the traffic status of the network, and put forward the reasonable optimization scheme to provide a decision-making basis for the evacuation of the traffic under the festival and large-scale gathering activities.
Research on Detecting Auto Insurance Fraud
Authors: Quan Yuexin
Published: January 2024

With the expansion of the insurance sector has come an increasing concern about insurance fraud. This issue has grown in prominence over time, necessitating the implementation of appropriate countermeasures. In response, this work conducts a thorough analysis of the available literature, with an emphasis on the incorporation of machine learning approaches for detecting fraudulent actions in the field of automobile insurance. By delving into the intricacies of the vehicle insurance fraud landscape, the research investigates the strategic deployment of expert systems and machine learning models to enhance fraud identification processes. Drawing from the wealth of high-quality auto insurance data spanning the last five years, this work explores the implementation of diverse machine learning algorithms, including Logistic Regression, Decision Tree, and Discriminative Analysis, in order to construct comprehensive predictive models. After the modeling was completed, comprehensive testing and analysis were conducted, and the results showed that the logistic regression model had the highest accuracy among these three models. Finally, the future research direction of automobile insurance fraud detection technology is discussed, and how to reasonably prevent automobile insurance fraud is proposed.
A Study on the Comparative Advantages and Disadvantages of Different Options
Authors: Li Xiang
Published: January 2024

This paper delves into the world of options, a type of derivative financial product that provides the right to buy or sell a specified asset at a predetermined price by a specified date. The historical evolution of options, from informal agreements among farmers to structured contracts in medieval Europe, is explored. The study highlights the versatility of options, including the creation of new options through combinations and constraints. It also critiques existing options pricing models, such as the Black-Scholes model, pointing out their limitations in capturing real market data. The paper categorizes options into call and put options, emphasizing their distinct purposes and risk profiles. It also examines American and European options, focusing on their differences and the factors influencing their suitability. The use of options in hedging strategies is discussed through various real-world cases, showcasing their effectiveness in managing risks, particularly in volatile markets. While options offer diverse opportunities for risk management and profit, they also come with challenges, including the cost of monitoring the options market and the potential pitfalls for retail investors. The paper concludes by highlighting the ongoing evolution of the options market and its potential to become more accessible and comprehensible in the future.
Stock Volatility Prediction Analysis Based on Different Models
Authors: Yang Boao
Published: January 2024

Stock volatility prediction is an important method for making the correct financial decision in modern stock market. Additionally, traditional method of stock indices prediction has been proved by modern scholars to be ineffective. This review focuses on the volatility prediction performance of various models, aiming to figure out the most effective volatility prediction model for modern stock market. The four models discussed in this review are ARIMA, XGBOOST, GARCH, and LSTM. Concluding the effectiveness of different models in volatility prediction can be helpful for practical applications of these models in modern stock markets, which can improve the profitability of stock investors under certain situations. Among all four models discussed in this review, LSTM model shows the best performance among all four models in stock volatility prediction. The unique machine learning ability of LSTM has great potential value in future science field research. Since this study is only a general review of stock volatility prediction models, additional research and analysis are essential in order to further conduct this topic for better accuracy and credibility.
The Structure and Application of a Flexible Manipulator Based on Octopus Biomimetics
Authors: Tian Yuchen
Published: January 2024

With the gradual development of modern science and technology, robotic arms have become increasingly important equipment, which can replace humans to complete various tasks. It has played an important role in many fields such as science, military, and industry. But the traditional rigid manipulator is often limited in some special working environments. With the development of Bionics, people find that flexible manipulator has better performance in the special working environment. This article studies the mechanical structure, driving mode, control mode, and bionic suction cup of the octopus’s biomimetic robotic arm, and conducts application analysis in three aspects: underwater rescue, narrow space operation, and fire rescue. It has been proven that flexible robotic arms have higher flexibility and larger motion space than rigid robotic arms. The octopus’s biomimetic robotic arm has high flexibility and large load-bearing capacity, which has great research significance in dealing with special working environments such as narrow spaces.
Examining the Application of Immune Checkpoint Inhibitors in Cancer Immunotherapeutic: A Systematic Review
Authors: Liu Xiaoxi
Published: January 2024

To define the clinical utilizations, effectiveness, and challenges of immune checkpoint inhibitors (ICIs) in cancer treatments. A systematic review of the literatures regarding the efficacy of ICI therapy in the management of advanced melanoma, non-small cell lung cancer (NSCLC), and hepatocellular carcinoma (HCC) was performed. The effectiveness and safety profile of anti-PD-1 (Nivolumab, Pembrolizumab, and Cemiplimab /PD-L1 (Atezolizumab, Durvalumab, and Avelumab), anti-CTLA-4 (Ipilimumab) drugs were measured and evaluated in several clinical trials via treatment-related indicators (response rate, survival rate, progression-free survival, overall survival, median overall survival, and treatment-related adverse events). Considering the increasing use of ICI therapy in days to come due to its great potential, this review can be valuable in assisting professional students or even oncologists to have a general overview of the role of ICIs in cancer immunotherapeutic, particularly targets the advanced melanoma, NSCLC, and HCC.
Revolutionizing The Automotive Industry: Tesla's Innovative Marketing Strategies in The Face of Changes
Authors: Liu Yuhao , Wei Yule , Wu Zixuan , Yi Jinpeng , Zhao Yufei
Published: January 2024

In the current era that prioritizes low carbon emissions, Tesla has emerged as a dominant player in the electric vehicle market, defying challenges and odds through its unwavering commitment to sustainability. This study delves into the intricate web of marketing strategies deployed by Tesla, a pioneering force in the rapidly expanding electric vehicle sector. Against the backdrop of varying circumstances, including shifts in national policies, market dynamics, supply and demand, and technical advancements, Tesla has adeptly navigated its course. The focal points of these strategies encompass pricing adjustments, strategic advertising campaigns, continuous technological innovation, and strategic partnerships recalibrations. Tesla's discerning choices in these diverse scenarios have been instrumental in sustaining and augmenting its market performance. By adroitly adapting its approach, the company has managed to maintain a formidable competitive edge. This paper intricately examines the ramifications of Tesla's multifaceted marketing strategies on its performance, elucidating how these decisions have influenced its growth trajectory. The study also ventures to forecast Tesla's future growth trajectory. Given the company's successful track record in maneuvering within the dynamic electric vehicle landscape, informed insights are gleaned into the avenues that may drive Tesla's continued expansion and influence. By fusing comprehensive analyses of the strategies undertaken, this research aims to offer valuable insights into the symbiotic relationship between strategic marketing decisions and Tesla's remarkable success in the current market.
Digital Operational Strategies in The Post-Pandemic Era for Travel Companies: A Case Study of Ctrip
Authors: Zhang Zihan
Published: January 2024

The epidemic’s impact has caused the tourism industry to face major challenges and changes in the post-epidemic era, in which the digital operation model has become the key to driving recovery and innovation. Taking Ctrip as an example, this study provides an in-depth analysis of the changes in the digital operation mode of tourism enterprises in the post-epidemic era. Firstly, the context and situation of Ctrip’s activities have changed in the digital environment, expanding the online business space and strengthening the interaction between the company and consumers. Second, the digital environment has changed corporate and consumer behavior from competition to cooperative symbiosis while triggering the socialization and personalization of consumer behavior. In addition, Ctrip’s travel products have changed in the digital environment, with data analysis to tailor travel products for consumers. Practical applications of Ctrip’s digital operations, including user demand forecasting and product design optimization, are further discussed. It is concluded that digital operations are important in improving management efficiency, meeting consumer demand, pricing strategy, and risk control. However, digital operations face legal, protection, and risk issues that require further research and solutions. This study provides useful experiences and insights for developing digital operation modes in tourism enterprises.
Big Data Analytics for Supply Chain Mass Customization: Prospects, Challenges, and Opportunities
Authors: Tian Guangchun
Published: January 2024

In today's world, the topic of economic globalization is still on the rise, and trade between countries is becoming more and more frequent. At the same time of economic prosperity, customers' demand for products is clearer and more perfect, which brings more intense competition between countries and enterprises. As one of the four most important strategic resources in the 21st century, the supply chain also shows increasingly important positions in the wave of international competition. More accurate customization of customer demand has become particularly important to save resources, create better revenue, and accurately meet customer demand. Mass customization is built through big data analysis; supply chain management is mass customization's basis and starting point. Nowadays, flexible and changeable customer demand greatly improves the risk and pressure of enterprises, standing on the tip of the wind of digitalization, intelligence, and the use of information technology to improve the enterprise organizational structure and operational processes to become a problem for enterprises to change their problems, the use of big data for customization in the supply company to analyze the point of focus.
The Impact of China-US Trade Conflict on Foreign Investment in China
Authors: Wang Yibo
Published: January 2024

The trade war between China and the United States, as the two largest global economies, has had a profound impact on both countries. However, China, being a developing nation that has attracted significant interest from investment companies worldwide, has been particularly affected by this conflict. The trade war has presented numerous challenges for companies looking to invest in China, but there have been notable improvements in recent years. This study aims to delve into the examination of the influence of objective changes and subjective changes experienced by investors on the ultimate outcomes of their investments. By analyzing both the tangible and intangible factors affecting investment decisions and outcomes, a comprehensive understanding of the trade war's impact on investment in China can be gained. Objective changes refer to the concrete alterations in trade policies, tariffs, and regulations that have been implemented as a result of the trade war. These changes may include increased tariffs on certain products, revised import and export regulations, or modifications to investment laws. These objective changes can directly impact the costs, profitability, and feasibility of investments in China. On the other hand, subjective changes pertain to the perceptions, attitudes, and sentiments of investors toward investing in China amid the trade war. These subjective changes can be influenced by factors such as geopolitical tensions, market uncertainty, and the perceived risks associated with investing in a country engaged in a trade war.
The Investigation of Prediction for Stroke Using Multiple Machine Learning Models
Authors: Wen Jingrui
Published: January 2024

The primary objective of this research is to forecast stroke occurrence on an individual patient level. Through exploratory data analysis, the study has brought to light noteworthy disparities in the distribution of stroke and non-stroke cases, shedding light on the influence of diverse health and lifestyle factors on stroke susceptibility. This project underscores the immense potential of machine learning in the realm of medical prediction, serving to aid patients in risk assessment and aiding medical practitioners in devising treatment strategies. Concerning the predictive models employed, this research leveraged two distinct models, namely RandomForest and DecisionTree. Additionally, it utilized evaluation metrics such as the Confusion Matrix, Receiver Operator Characteristic (ROC) curve, and Precision-Recall curve, each of which provided comprehensive insights into the performance of the prediction models. One noteworthy aspect of this study is the presence of missing data within certain features, underscoring the challenges posed by data gaps in medical prediction and the imperative need for effective methods to handle missing data. The experimental outcomes unveiled an Area Under the Curve (AUC) of 95% for RandomForest and 92% for DecisionTree, indicating robust predictive capabilities. Future endeavors may concentrate on refining prediction models, achieving greater balance, and expanding the dataset to enhance prediction precision.
Comparison Of the Electric Vehicle Industry in China and The United States - In Terms of Sales Volume, Policies, And Technology
Authors: Diao Chenfeng
Published: January 2024

In today's global warming environment, countries are trying to reduce their carbon emissions. One of the most accepted and effective ways around the world is to develop the electric vehicle industry. China and the United States, as the two largest economies in the world, the development of the electric vehicle industry in the two countries can be a reference for the world, especially in the context of China's first electric vehicle sales. In the United States, as an automobile power, the electric vehicle industry is also developing rapidly, and gradually catching up with the pace of China. Therefore, by comparing the sales volume, technology and policies of the two countries, this study analyzes the similarities and differences between the industry in the two countries, aiming to find ways to develop the electric vehicle industry in the two countries and even the whole world, and jointly contribute to solving the global climate problem.
Impact Of Corporate Green Technology Innovation from An ESG Perspective
Authors: Liu Fangyu
Published: January 2024

This paper discusses the impact of green innovation on firms in the chemical, manufacturing, high-tech and power generation industries from an Environmental, Social, and Governance (ESG) perspective. Through case studies of representative firms in the industries, it summarizes the common features of the impacts in the industries by focusing on the impacts of green innovation on firms from an ESG perspective. By examining leading chemical companies, AkzoNobel, DuPont and The Dow Chemical Company, it demonstrates how green innovation can significantly improve economic performance. In the high-tech sector, Google, Intel and NVIDIA utilize technology to expand and streamline their businesses. In the manufacturing industry, Siemens, Apple and Tesla represent companies optimized across the board to reduce the CO2 produced during manufacturing. Finally, in the energy sector, Tesla Energy, Vestas, and ANDRITZ Hydro are capitalizing on booming market opportunities for rapid expansion and growth. This paper provides a useful reference and outlook for understanding the growth strategies and profiles of these four industries.
Analysis of Abnormal Phenomena in China Securities Market Based on Behavioral Finance
Authors: Wang Ziqi
Published: January 2024

Compared with western mature markets, China securities market started late and has some obvious deficiencies, which leads to traders, especially individual investors, easy to make irrational investment decisions which cannot be explained by traditional finance. Based on the relevant facts and references, this paper believes that there are overtrade and exceptional open-style fund redemption in the fund market, dramatic fluctuation, and Irrational reaction in the stock market. The main reasons based on behavioral finance are: noise trading, herd behavior, prospect theory and disposal effect and overreaction. Finding out the typical anomalies and reasons of the two markets is conducive to study how to improve the efficiency and stability of China security market. This paper innovatively puts forward the background reasons and gives three suggestions in the conclusion: imitating trading, avoiding duplication of decision-making, and increasing the development of financial derivatives, which also has a certain reference significance for the improvement of policies and systems.
Study on the Methods of Strengthening Reinforced Concrete Beams with CFRP
Authors: Teng Congyang , Zhu Zhicheng
Published: January 2024

After the long-term use of reinforced concrete structures, there may be structural aging and structural damage, these common engineering problems. As a result, the performance is reduced, so it is necessary to strengthen to meet the corresponding safety requirements. Carbon Fiber Reinforced Polymer (CFRP) has the advantages of lightweight, strong, high tensile strength and tensile degree. Therefore, CFRP is widely used in reinforcement. Based on CFRP reinforcement of reinforced concrete beams, this paper analyzes its reinforcement methods. The paper mainly analyzes the influence of different pasting methods of CFRP on the performance of beams and the influence of material pasting thickness on beams. Through the analysis and research, it can be concluded that CFRP has certain advantages compared with traditional reinforcement materials. Therefore, it can be used to reinforce reinforced concrete beams. This study can provide some reference value for some related projects of reinforced concrete beams reinforced by CFRP.
How to Become Rich Using Quantitative Trading?
Authors: Jiang Chengkai
Published: January 2024

Bitcoin has become a very common investment product, also known as 'digital gold' because of its global discussion and rising prices. This paper develops a model that can only rely on these data to predict future price fluctuations and plan trading decisions. The trading decision planning model consists of three sub-models that are mutually undertaken. For model 1, in order to judge the price trend reliably, this paper uses the Long Short-Term Memory (LSTM) neural network, which is sensitive to the time series, to learn all the time series price data up to the trading day, and to predict the future price data of them respectively, which is provided to another sub-models for subsequent work. For Model 2, after obtaining the follow-up price data, all the technical indicators needed are calculated in this model, and then the moving average convergence divergence (MACD) rule is used to determine whether the transaction is carried out for the first time, and then the predicted price trend is used for the second judgment. For model 3, the model begins to make decision- making planning. This model mainly solves the bi-objective programming problem with the goal of maximizing returns and minimizing risks. In the range of controllable risks, the model will give the optimal solution of maximizing returns. Finally, using the model, the sensitivity of the model to transaction cost is studied by changing the transaction commission, and it is found that the final investment income is more sensitive to the transaction commission of bitcoin.
How has machine learning advanced the field of artificial intelligence for vehicles?
Authors: Yu Xinyang
Published: January 2024

The purpose of this review is to highlight recent advancements in autonomous vehicles (AVs) and related infrastructure, primarily from artificial intelligence (AI), which makes AVs more appealing to consumers. It is critically analyzed and reviewed how AI can benefit AVs, structure of AVs, and automotive innovation techniques. The paper provides a quick reference for researchers interested in understanding the use of AI in AV research.