bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of wind turbine design parameters for power output in southern Nigerian states using response surface methodology
Authors: Onyekachi Marcel Egwuagu  , Vincent Anigbata  , Thomas Okechukwu Onah
Published: January 2024

Weather Risk Optimization of Vertical Wind Turbines when situated in Southern Nigeria was achieved using Response Surface Methodology. Wind speed at heights of 10m and 50m between the years of 1990 and 2020 was acquired for four sampled southern states of Imo, Delta, Edo, and Bayelsa states from the Nigerian Meteorological Agency. Parametric profiling in various locations in the country aided the selection of locations with low wind speeds in the region. Delta has the lowest wind speed of 1.81m/s. The model for determining the power output in the region shows 98% R squared value. Analysis shows that if offshore wind turbines must be sited in southern Nigeria, hub height will be 1125m and 827m for obtaining wind speeds of 10m/s and 5m/s respectively. The optimization plot shows a wind turbine of 114. 5m blade length, wind speed of 10 m/s, and hub height of 1125m can produce wind power of 8MW.
Histopathologic study of sinonasal lesions: A hospital based retrospective study, from January 2016 to August 2020
Authors: Ruth Abera Alemayehu  , Tufa Gemechu
Published: January 2024

Background: Sinonasal area is a host to various neoplastic and non- neoplastic lesions. The presenting symptoms of sinonasal lesions are similar and pose difficulty for diagnosis based on clinical features and advanced imaging modalities, which makes histopathology the principal diagnostic tool approach for these lesions. The aim of this study is to determine the various histopathologic types of Sinonasal lesions, their classification and relative distribution with regards to age and sex in our setting. Materials and Methods: A retrospective cross-sectional descriptive study conducted on 306 cases of sinonasal lesions over the period from January 2016 to August 2020. All the sinonasal tissues were received and diagnosed at histopathology section of Department of Pathology in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. The Pathology reports were collected from the pathology data archives; and the variables of study were extracted by using a data extraction sheet, and data analysis was done using SPSS version 26.0. Results: Most affected age group was 21-30 years 81(26.5%). Male predominance was observed with M: F ratio of 1.4:1.Nasal cavity was the commonest anatomical site involved 237(77.5%).There were 137(44.8%) Non-neoplastic lesions and 169(55.2%) Neoplastic lesions. Inflammatory Sinonasal Polyps 100(73.0%) were the most common among non-neoplastic lesions; inverted Sinonasal Papilloma 34(41%) the most common among the benign neoplastic and squamous cell carcinoma and nasopharyngeal carcinoma accounting for 21(25.6%) cases each, were the commonest malignant lesions. Conclusion: clinical findings and advanced image modalities can reach to a presumptive diagnosis for the sinonasal lesions but histopathology remains the gold standard for categorizing and diagnosis of non-neoplastic and neoplastic lesions of sinonasal tract.
State of play of odontophobia in the urban commune of Toliara
Authors: Hasina Menja ANDRIAMANJATO  , Njarasoa Charlette RANDRIAMALALA  , Honoria RAKOTOMALALA  , Mariette RAKOTOSON  , Léondre Sylvestre HAMINASON  , Andry Mampionona RIEL  , Bertille Hortense RAJAONARISON  , Adeline RAHARIVELO
Published: January 2024

Introduction: Dental anxiety is omnipresent in our society. “Fear of the dentist” often leads patients to let their teeth deteriorate rather than go to a dental office. The objective of this study was to evaluate odontophobia among dental consultants at University Hospital Toliara as well as associated factors Methods: This is a prospective, analytical study carried out with dental consultants at Antanambao Toliara University Hospital. The Modified Dental Anxiety Scale (MDAS) was used to determine the presence of dental phobia. Results: 96.92% of patients were included in the study, the age of the patients varied between 18 to 71 years, 39.68% were in the age group 18 to 25 years; 67.46% were of the feminine gender. The patients presented dental phobia in 39.68% of cases. Socio-professional status was associated with the occurrence of dental phobia (p=0.008). The anxiety-provoking factors observed were: anesthesia (p=0.000), fear of pain (p=0.001), noise from instruments (p=0.003), drilling (p=0.04), extraction dental (p=0.000) and view of instruments (p=0.000). A significant statistical difference was observed between avoidance of oral check-ups, avoidance of dental care, negative effects on oral health and the MDSA scale. Conclusion: Odontophobia is a reality. Identifying patients as early as possible as well as knowing the factors associated with its occurrence could improve the quality of care in the dental environment.
Empowering Rural Communities: Smart English Home Ignites Opportunities in Sungai Alam Village, Bengkalis Island
Authors: Putra Halim Dwi , Sukma Doris , Sabri Muhammad
Published: January 2024

This servitude 2023 explores the impact of the Smart English Home initiative in Sungai Alam Village, Bengkalis Island, aiming to empower rural communities through English language education. The study investigates the potential opportunities ignited by this program, focusing on the enhancement of educational access, economic prospects, and community development. By examining the implementation of the Smart English Home, the research aims to provide insights into the transformative effects of language empowerment in rural settings, contributing to the broader discourse on rural community development and empowerment initiatives. This abstract synthesizes the potential impact of the Smart English Home initiative in Sungai Alam Village, Bengkalis Island, emphasizing its role in empowering rural communities through English language education and its broader implications for community development and economic prospects.
ANALISIS DESKRIPTIF PERAN TAMAN BACA INOVATOR PADA KEGIATAN LITERASI BACA TULIS ANAK USIA DINI DI KECAMATAN BANTARGEBANG
Authors: Putri Choirunnisa
Published: January 2024

Penelitian ini bertujuan untuk mengetahui Peran Taman Baca Inovator dalam meningkatkan budaya literasi baca-tulis anak usia dini. Analisis data menggunakan data kualitatif dengan mendekripsikan data yang diperoleh dari hasil wawancara dan studi dokumentasi selanjutnya dianalisis dengan menggunakan analisis deskriptif dalam bentuk narasi. Hasil penelitian ini menunjukkan bahwa Taman Baca Inovator berperan penting dalam penanaman budaya baca-tulis maupun memberikan informasi minat dan budaya baca anak-anak usia dini Dalam pelaksanaannya, terdapat faktor pendukung dalam menjaga peran penting Taman Baca Inovator diantaranya sebagai tempat belajar bagi anak-anak dan masyarakat juga sebagai tempat wisata edukatif. Faktor penghambat dalam mempertahankan peran utama dari Taman Baca ini adalah mengoptimalkan strategi-strategi yang dimiliki dengan memaksimalkan perencanaan yang sesuai untuk membantu memenuhi kebutuhan literasi baca-tulis anak-anak usia dini. Keberadaan Taman Baca direspon dengan baik oleh para pengunjung diantaranya anak-anak usia dini, orang tua dan relawan.
Utilizing Asymmetric Cryptography and Advanced Hashing Algorithms for Securing Communication Channels in IoT Networks Against Cyber Espionage
Authors:   University of the Witwatersrand Johannesburg, South Africa, .. Anil Audumbar ,   Department of AI and Big data, Woosong University, Daejeon, South Korea,   School of Business, Woxsen University, Hyderabad, India,   Associate Engineer, TSYS Global Payments, Pune, India,   Senior Lecturer, Federal Polytechnic Bauchi, Nigeria,   Pune Institute of Computer Technology Pune, India,   University of  Prince Edward Island, Canada, .. Saurabh , .. Hemachandran. , Gadilkar Shraddhesh , Esther Zakka Benisemeni , Pise Ganesh Shivaji , Imuede Jude
Published: January 2024

This article describes a massive cryptographic scheme that can safeguard IoT communication paths. A combination of algorithms makes the technique operate. Communication security is handled differently by each algorithm. Elliptic Curve Cryptography (ECC), SHA-256 Secure Data Hashing, HMAC Message Authentication, and Merkle Tree Structures Decryption and Verification are used. Ablation is used to determine how each strategy increases security. The paper emphasizes that the algorithms function effectively together, demonstrating their importance for cyberdefense and surveillance. The recommended strategy is evaluated and found to operate better across key parameters.Top of Form
A Comprehensive Approach to Cyberattack Detection in Edge Computing Environments
Authors:   Department of Statistics and Programming, Faculty of Economics, University of Tishreen, Latakia, P.O. Box 2230, Syria, .. Khder ,   Department of Food and Biotechnology, South Ural State University, 454080 Chelyabinsk,   Electronic and Computer Center, University of Diyala, Baqubah MJJ2+R9G, Iraq,   Department of System Programming, South Ural State University, 454080 Chelyabinsk, Russia,   Department of System Programming, South Ural State University, 454080 Chelyabinsk, Russia,   Department of System Programming, South Ural State University, 454080 Chelyabinsk, Russia,   Electronic and Computer Center, University of Diyala, Baqubah MJJ2+R9G,,   Department of Communications and Electronics, Delta Higher Institute of Engineering and Technology, Mansoura 35111, Egypt, .. Alhumaima Ali , .. Hussein , .. Ammar , .. Artem , Potoroko Irina , .. Mostafa , El-kenawy El-Sayed M El
Published: January 2024

This research is concerned with the critical domain of cybersecurity in edge computing environments, which aims to strengthen defenses against increasing cyber threats that target interconnected Internet of Things (IoT) devices. The widespread adoption of edge computing introduces vulnerabilities that necessitate a strong framework for detecting cyberattacks. This study utilizes Long Short-Term Memory (LSTM) networks to present a comprehensive approach based on stacked LSTM layers for detecting and mitigating cyber threats in the dynamic landscape of edge networks. Using the NSL-KDD dataset and rigorous experimentation, this model demonstrates its ability to detect subtle anomalies in network traffic, which can be used to accurately classify malicious activities while minimizing false alarms. The findings highlight the potential of LSTM-based approaches to enhance security at the edge, providing promising avenues for strengthening IoT ecosystems’ integrity and resilience against emerging cyber threats.
The Role of the Real Economy in Resisting Dollar Hegemony
Authors: Chen Hongce
Published: January 2024

At present, the losses caused by COVID-19 have affected the economic construction of many countries, but the underlying essence is that the dollar hegemony uses weaponized currency to force other countries to participate in the process of financialization. The dollar's extracorporeal circulation has been affected by the external force of the new coronavirus, making the dollar's control weaker, and many single-industry countries have also derived the idea of getting rid of the dollar's control, which have been solved in countries with strong real economies. By exploring the role of the real economy in combating US dollar hegemony, this paper points out that a country with a strong real economy can make its internal supply chain more complete, create jobs and control inflation at the same time, reduce the possible damage caused by financial risks in the process of dollar hegemony, and play a positive role in the recovery of the economy after damage.
Research Advanced on the Influence of Green Credit Policy on Companies: A Case Study of Industrial Structure, Firm Performance, and Response Measures
Authors: Weng Yingbei
Published: January 2024

Nowadays, the traditional economic development mode and development power have caused a series of problems such as waste of factor input, serious environmental pollution, and low economic efficiency. Green finance is thus sprouting. With the rapid economic development, more and more companies at home and abroad have begun to use Green Credit Policy (GCP) to promote sustainable development. Based on official publication databases, we delve into a deep analysis of the impact of the Green Credit Policy on companies, focusing on their industrial structure, firm performance, and response measures. Through empirical analysis and theoretical discussions, we reveal that the Green Credit Policy positively influences industrial upgrading, enhances firms environmental performance, and stimulates strategic responses to Green Credit Policy. Additionally, empirical data substantiates the notion that GCP exerts a "detrimental impact" on companies exhibiting subpar environmental practices. These results underscore the importance of policies geared towards sustainability in fostering a more eco-friendly and robust economy.
Analysis of the Effect of Artificial Intelligence on the Labor Market in the United States
Authors: Fu Ruixuan
Published: January 2024

Artificial intelligence(AI) is facing rapid development, which presents both opportunities and risks. The Unities States, the worlds largest economy and a leading technological power, has witnessed significant advancements in AI. As an integral part of automated production, AI drives economic productivity, but it alters the demands and structure of the United States labor market. Increasing joblessness and a decrease in the number of people actively participating in the workforce imply that AI holds the capability to substitute human employment, thereby highlighting the importance of individuals adapting to changing labor demands. Research indicates that individuals with lower educational attainment and limited cultural proficiency face a greater likelihood of being replaced by artificial intelligence (AI). However, the evolving labor market demands a greater emphasis on AI-related skills. The potential of AI to foster the development of the United States labor market is evident, as it holds the capacity to drive further innovation and growth in the American economy. This research paper takes IBM, who officially announced the use of AI as a replacement for human labor, as a case study to examine the influence of AI on the labor market in the United States., exploring the opportunities and risks brought by AI development.
Application Analysis of Management Economics Theory in Enterprise Marketing Management Taking Apple and Huawei as Examples
Authors: Zheng Shiqi
Published: January 2024

Management economics, as a branch of economics, helps businesses and individuals systematically and logically formulate plans and decisions, and its application in management practice makes an indispensable contribution to society. This article takes Apple and Huawei as examples, and based on existing literature, analyzes the application of management economics theory in enterprise marketing management through case analysis and data analysis. This article finds that both Apple and Huawei cleverly and flexibly apply the four core theories of management economics. As excellent enterprises, both brands actively explore the potential needs of customers and help them seize the market faster. Apple actively collects user feedback, responds to and solves user issues and opinions in a timely manner, which helps them better understand consumer needs and expectations. Huawei has always been committed to deeply understanding customer needs. The results indicate that each company has its own unique operational approach, but it is worth noting that companies that want to succeed should start with organizational structure, optimize personnel management, clarify market goals, upgrade products targeted, capture customer groups, and establish good communication; All of these are key factors for the sustainable development of the company.
The Impact Study of Yield Curve Control on the Yen Exchange Rate and Japanese Inflation
Authors: Tian Xinyu , Zhu Zhihuan
Published: January 2024

Yield Curve Control (YCC) is fundamentally an interest rate tool that aims to maintain the yield curve at targeted levels across different maturities. The Bank of Japan (BOJ) initiated zero interest rates and quantitative easing in 2001, followed by qualitative and quantitative monetary easing policies starting in April 2013, and introduced negative interest rates in January 2016. It announced the implementation of Yield Curve Control policy as a policy objective for quantitative and qualitative easing. Amid the current global economic downturn, many Western countries have adopted interest rate hikes to ensure currency stability. However, Japan continues to implement Yield Curve Control policy to address the global economic slowdown. This paper, based on literature review and utilizing Japanese economic data from 2003 to 2022, employs correlation and regression analyses to delve into the impact of Yield Curve Control on the Japanese yens exchange rate and inflation. The study reveals that Japans Yield Curve Control policy has a certain positive impact on both the yens exchange rate and inflation, although this effect is relatively moderate. Therefore, the government should consider enhancing the use of other monetary policy tools and employing a comprehensive approach to influence exchange rates and inflation more effectively.
Research on the Impact of Supply Chain Concentration, and Financial Flexibility on Corporate Innovation: An Empirical Study in the New Energy Industry
Authors: Kong Yiyang
Published: January 2024

With the gradual formation of an international consensus on carbon peaking and neutrality, the new energy industry is a key focus for future development. Still, the industry also suffers from a fiercely competitive market environment. Therefore, the innovation performance of enterprises is crucial. This paper analyzes the impact of supply chain relationships and financial flexibility on corporate innovation from a resource-based viewpoint. Moreover, several variables are introduced to explore the optimal combination of innovation strategies. In the empirical part of the study, the study selects the panel data of listed companies in Chinas new energy industry. The fuzzy set qualitative comparative analysis approach investigates how supply chain concentration, and financial flexibility affect corporate innovation. The study shows that: corporate cash is the main internal resource for R&D, industrial clusters facilitate the acquisition of external resources, and the configuration of the two can promote corporate innovation; debt and supply chain risk inhibit corporate.
Taking BYD as an Example to Analyze New Energy Vehicles
Authors: Hu Zhaoqi
Published: January 2024

With the development of the times, the environmental problems brought by fuel powered vehicles have gradually attracted people's attention, and new energy vehicles have also received increasing social attention. People seem to attach more importance to and want to understand new energy vehicles, and the technology and marketing strategies of new energy vehicles have gradually become more mature. This article will take BYD Automobile as an example to analyze and propose some suggestions for the sales strategy and supply chain management of new energy vehicles. The full text study found that both BYD and other new energy vehicle brands have their own methods to attract customers for consumption, and the sales of new energy vehicles are also getting better with the attention of society. The research significance of this article lies in identifying some problems encountered in the development of new energy vehicles and proposing solutions, as well as expectations for the future of new energy vehicles.
Correlation Analysis Between Cereal Food Consumer Ratings and Nutritional Composition
Authors: Luan Rui
Published: January 2024

Since contemporary information-retrieval systems rely heavily on the content of titles and abstracts to identify relevant articles in literature searches, great care should be taken in constructing both. With the popularization of food safety and health knowledge, consumers are increasingly concerned about the nutritional value of food. Research has shown that when consumers purchase food products, the nutritional composition table on the food packaging can affect their purchasing intention. Therefore, it is important to explore the impact of various factors in the ingredient table on consumer ratings and purchase intentions. The paper takes nutritional data of cereal products as a sample to investigate customer ratings of different products and conduct regression analysis and correlation research between ratings and nutritional components of cereal products. Based on the obtained regression equation, the paper predicts the rating of cereal products on the market. The paper finds that there is a correlation between consumer ratings and nutritional composition in the cereal product. Using regression equations to predict the test set, the prediction accuracy is good, which indicates that we can refer to the nutritional composition table of cereal products to roughly predict the consumer ratings of products in the market. Based on research, cereal manufacturers can attract consumers to purchase products by optimizing brand promotion strategies, enhancing brand image, and other means. Also, manufacturers can also choose high protein and low fat cereal raw materials to meet consumer demand and expand market consumption of cereal products.
Comparative Study of Marketing Strategies Between Starbucks and Luckin Coffee in China
Authors: Hu Min
Published: January 2024

This paper examines the marketing strategies of Starbucks and Luckin Coffee in Chinas booming coffee market. It analyzes their key approaches, promotional tactics, pricing models, and target customer segments. The study aims to understand how these strategies have influenced each companys brand positioning and market share. A comprehensive understanding of their strategies and effectiveness is achieved by utilizing multiple sources, such as scholarly articles, industry reports, and marketing campaigns. While Starbucks emphasizes a high-end experience and loyalty, Luckin Coffee focuses on accessibility and affordability. Both companies face the challenge of maintaining profitability in a highly competitive market. They prioritize digital platforms but employ different strategies to stand out. Starbucks cultivates an upscale coffee culture, while Luckin Coffee rapidly expands through cost-effective measures. This review highlights the importance of adapting marketing strategies based on local market dynamics and audience preferences. Future market entrants can learn valuable lessons from the successes and challenges these major players face in Chinas coffee industry.
Google Stocks Prediction by Machine Learning of RNN and LSTM Techniques
Authors: Tian Ruimin
Published: January 2024

The objective of this study is to utilize a combined model of two algorithms, namely Long Short-Term Memory network and Recurrent Neural Network, to forecast the stock price of Google. Using Google stock price data from 2010 to 2022 as the training set and performed data preprocessing and feature engineering. This then build a deep neural network model consisting of multiple LSTM and RNN layers and train it by the backpropagation algorithm. During training, this paper employs an appropriate loss function and optimizer to minimize the prediction error. In conclusion, the performance of the model was assessed by employing Google stock price data from 2023 as a test set. By comparing the error between the actual stock price and the predicted value of the model, it can evaluate the accuracy and stability of the model. The experimental results show that the superposition model using LSTM and RNN algorithms can effectively predict the Google stock price with high accuracy and stability. This research presents a practical approach that can enhance the predictive capabilities of investors, financial institutions, and other related domains, enabling them to make well-informed investment decisions in the stock market.
Research on Business and Revenue Promotion Methods of Commercial Companies Based on Brand Marketing Planning Path - Take Nike's Marketing Strategy as an Example
Authors: Wei Jingyi
Published: January 2024

Marketing is a must for every brand, and brands can take publicity from various aspects, such as advertising, celebrity endorsement, and sponsorship. Nike as one of the world's largest and most well-known brands, has been the leader of the sports fast-fashion industry since its launch., Brand marketing means the world has been widely recognized. For example, Nike's Just Do It slogan, whether on social media or while walking on the street, is often seen in Nike ads. The success of Nike absolutely cannot be separated from its excellent marketing strategy. The rapid development of business means that new products and brands are constantly emerging, and emerging brands can learn from successful marketing cases to help them stand out in today's fierce market and win consumers' favour and loyalty. This paper examines three of Nike's famous marketing success cases. It analyzes how Nike has made marketing promotions successful from three perspectives: emotional marketing, celebrity collaborations, and the release of branded co-branded limited-edition items. This paper aims to determine the importance of promotion in today's market, calling on major brands to pay more attention to developing marketing strategies. Brands need to focus on consumers at the forefront, a good brand needs good marketing support.
Strategy Analysis of Health Care Products Advertising for the Aged: Optimization Suggestions Based on Appeal Presentation and Advertising Elements
Authors: Liang Yutao
Published: January 2024

With the increase in the elderly population, the advertising strategy of healthcare products for older people needs to be systematically analyzed and optimized. Through literature review, this study adopted the advertisements targeting the elderly of three famous Chinese health products brands as cases, analyzing the typical strategies of current advertising practices based on the expression of appeals including rational and perceptual appealing and advertising elements related to social power, then offering suggestions on needs, advertising content and media mix. The results showed that as the basis of perceptual appeal, rational appealing contained product information and health problems. Product information focused on communication at the core benefit level, while the description of health problems promoted purchasing behavior through negative reinforcement. Perceptual appeal mostly adopted the framing of family affection with the appeal objects were simultaneously the elderly and their children. Advertising elements were related to legitimate, reward, and referent power, corresponding to the use of uniform image, incentive enticement and upward social comparison related to the idealized self-image of the elderly. Recommendations involved broadening the appealing technique corresponding to alternative types and higher levels of needs, attempting heuristics including humor and celebrity endorsements, and considering social media-related touching points. This study provided mechanism clarification and theoretical support for health communication and advertising practice.
The Impact of Executive Compensation Stickiness on Stock Price Crash Risk
Authors: Zhang Xiaohan
Published: January 2024

Executive compensation stickiness is a compensation characteristic that links executive pay to company performance, reflecting a tendency among compensation setters to provide generous rewards to executives and relatively fewer penalties. It can be considered an effective incentive mechanism. This paper empirically examines the impact of executive compensation stickiness on stock price crash risk using data from all A-share listed companies from 2010 to 2021. The empirical results show that executive compensation stickiness significantly mitigates stock price crash risk. Further research reveals that in companies with female CEOs, non-financial backgrounds among top executives, and low information opacity, the inhibitory effect of executive compensation stickiness on stock price crash risk is more pronounced. Mechanism tests suggest that executive compensation stickiness reduces agency costs and, thereby, suppresses stock price crash risk. This study extends the understanding of the economic consequences of executive compensation stickiness and factors influencing stock price crash risk, providing practical insights for designing compensation incentive systems for listed companies and maintaining the stability of capital markets.
Application Research of ChatGPT in Enterprise Digital Transformation
Authors: Ding Wenting
Published: January 2024

This paper, from a narrow perspective, focuses on analyzing the advantages of ChatGPT in enterprise digital transformation, aiming to provide new insights and references for digital transformation in enterprises. By employing a case analysis method, specific application cases of ChatGPT in enterprise digital transformation are collected to explore its application scenarios and domains. Furthermore, the paper analyzes the advantages of ChatGPT in enterprise digital transformation in conjunction with its technical principles. The analysis concludes that the application of ChatGPT in enterprise digital transformation can enhance work efficiency and increase data collection and analysis accuracy. The innovation in this paper lies in the examination of representative enterprise cases in different fields to explore the application effects and advantages of ChatGPT in enterprise digital transformation from a broader perspective, providing new ideas and solutions for enterprise digital transformation.
Pioneer and Leader of the Gen-Z Entertainment Industry: Bilibilis Market Analysis and Strategy Based on the SWOT Analysis Framework
Authors: Sun Hanxiao , Yan Yan
Published: January 2024

Bilibili, as a leading Chinese online entertainment platform, boasts a distinctive community culture that has garnered significant attention. With approximately 315 million monthly active users in the first quarter of 2023, Bilibilis influence is undeniable, highlighting its commercial and social value. This research identifies critical challenges that Bilibili faces in the modern video market. These challenges encompass commercialization difficulties, content creator attrition, and struggles to redefine its identity while attempting to break boundaries. To address these issues, the research offers strategic recommendations. Firstly, Bilibili can enhance its commercialization by promoting its e-commerce function, fostering branded content partnerships, and implementing data-driven advertising to increase revenue. Secondly, reducing talent attrition among content creators can be achieved by addressing fan culture concerns and demonstrating a commitment to content creators. Finally, instead of unthinkingly pursuing boundary-breaking strategies, Bilibili should reaffirm its identity, emphasize long-form content, and focus on its profitable gaming segment. This research is significant as it guides Bilibilis strategic decision-making, ensuring it remains competitive and adaptable in the dynamic video content landscape. By implementing the recommendations, Bilibili can strengthen its position and remain the preferred platform for Chinas young generation, ensuring its long-term success in the online entertainment industry.
Analysis of the Interaction Between Bitcoin Price and Crude Oil Futures Price
Authors: Hu Haimei
Published: January 2024

The aim of this thesis is to analyze the interaction between Bitcoin price and crude oil futures price over the past seven years using the Ordinary Least Squares (OLS) method. Bitcoin, as a virtual currency, is characterized by high price volatility, while crude oil futures, as an important commodity, are also affected by a variety of factors. By collecting and analyzing data on the price of Bitcoin and crude oil futures in the past seven years, this research aims to investigate the interaction between Bitcoin price and crude oil futures price and explore their correlation and causation. The results of the study will provide investors and policymakers with important information about the bitcoin and crude oil futures markets in order to better understand market dynamics and formulate relevant strategies. Meanwhile, the time span of the study includes both the New Crown Epidemic period and the Post-Epidemic period, which is generalizable and more conducive to research and analysis under different era conditions.
Research on Brand Rejuvenation Strategy of Old Brands from the Perspective of Brand Marketing
Authors: Zhou Wanting
Published: January 2024

With the continuous development of the economy and the increasingly fierce market environment, the competition of brands in the consumer market is becoming increasingly fierce. In this situation, old brands are inevitably placed at a disadvantage and may even be gradually forgotten by consumers and eliminated from the market.To cope with rapid market changes and the developing situation of market competition, many old brands with weak competitiveness have chosen brand revitalization strategies to ensure a foothold in the consumer market. At present, although some old brands have successfully revived their brands through brand rejuvenation strategies, others have fallen into the trap of such strategies. When implementing brand rejuvenation strategies, many old brands have issues such as unclear brand awareness and positioning, superficial strategy implementation, and rapid strategy advancement. Therefore, it is suggested to emphasize the importance of individuation, adaptability, and conveying the brand's essence during the process of revitalization. This article analyzes various cases of old brands' rejuvenation, discusses and summarizes the potential problems commonly faced in the process of brand rejuvenation, and provides practical warnings and suggestions for old brands to implement brand rejuvenation strategies.
Chinas Accession to the Digital Economy Partnership Agreement: Assessing International and Domestic Prospects
Authors: Jiang Hailin
Published: January 2024

The COVID-19 pandemic has greatly affected the real economy. In contrast, the era of the digital economy has come. The global digital economy and trade are booming and in the ascendant. In order to respond to the needs of the times, China formally applied to join the Digital Economy Partnership Agreement (DEPA) in 2021. China should strongly advocate joining DEPA because it will help China gain more international discourse power and establish a tripartite pattern of international digital economic and trade rules. At the same time, it can also bring economic and international trade opportunities for the digital transformation of Chinese small and medium-sized enterprises (SMEs). Nonetheless, China faces a potential challenge in its journey toward DEPA endorsement due to its unique digital regulation framework, which could pose obstacles when bridging its national digital ecosystem with the international digital sphere. This article introduces the background of the current era of digital economy and trade and expounds on the reasons why China should join the DEPA from the perspectives of establishing a strong international digital economy and trade rules and facilitating the digital transformation of Chinese SMEs and analyzes the difficulties and solutions of joining the agreement at the current stage.
Relationship Between Financial Ratios and Stock Prices: Industry Disparities in Stable Economic Environment in China
Authors: Wang Ruoying
Published: January 2024

After the extensive and thorough cleanup and overhaul of the Chinese stock market in 1995, there followed a period of remarkable and noteworthy development, which was accompanied by an equally steady and stable growth of the Chinese economy. In the current economic climate, characterized by favorable conditions, shareholders' demand for energy conversion stock prices has become increasingly intense, thereby necessitating the intervention and involvement of financial ratios in regulating and modulating stock prices. This academic paper will employ a number of analytical tools and techniques, such as literature analysis and case studies, to examine the correlation between financial ratios and stock prices in China. The focus will be on the financial, pharmaceutical, and real estate industries, with particular attention paid to stable economic environments. The findings and results of this study have established that in a stable economic environment in China, the different financial ratios are highly adaptable and malleable to different industries when analyzing stock prices.
Modeling and Prediction of Birth Rate in China
Authors: Zhang Yunhan
Published: January 2024

Concerns about a persistent reduction are growing against the backdrop of large changes in Chinas birth rate during the last few decades. This paper explores this tendency via the lens of time series analysis, using birth rate records from 1964 through 2021 (particularly ignoring 1960-1963 due to Great Leap Forward distortions). The ARIMA and ETS models were extensively studied in our hunt for the best accurate forecasting device. The ARIMA (0,0,1) model was considered to be preferred based on comparison measures. The primary goal of this model was to predict the trend of Chinas fertility rates over the following five years. The ARIMA an1``d ETS models were rigorously applied to a selected training set after initial adjustments to ensure data stationarity, followed by an evaluation of their accuracy. Our findings, which are backed by the ARIMA model, imply a disturbing trend: a 0.117 percent annual fall in Chinas birth rate from 2022 to 2026. This suggests that a national fertility crisis is on the horizon. As a first step, we advise looking at the various socioeconomic reasons that may be driving this trend, as well as evaluating policy actions that could serve as potential cures.
Predicting Netflixs Future Success by Using SWOT Analysis
Authors: Luo Haochong
Published: January 2024

Netflix is a leader in media and entertainment in todays world, and this paper takes a comprehensive look at Netflix. This paper provides an in-depth study of Netflixs historical evolution, foundational underpinnings, and key business areas. The research in this paper utilizes a SWOT analysis to thoroughly assess and analyze Netflixs inherent strengths, weaknesses, emerging prospects, and looming challenges. The investigation scrutinizes the cornerstones of Netflixs success, including content innovation, savvy data utilization, efficient distribution network, and cutting-edge technology integration, which have ensured Netflixs success. By extrapolating and analyzing the extensive research and discussions, this paper offers sensible recommendations that offer possibilities for the future of Netflix and chart the trajectory of Netflixs growth. Based on the aforementioned insightful research and discourse, current projections suggest that Netflix is expected to prosper for a decade or more. This assessment emphasizes Netflixs enduring influence and potential for continued prosperity in the ever-changing media and entertainment landscape.
Future Markets in China and the U.S.: History, Current Situation and Improvement
Authors: Lu Yixiang
Published: January 2024

Given so much research on future markets in both America and China and their relationships, especially in commodities, such as oil and agricultural products, it was noticed that the researchers have done excellent research, which is, however, incomplete. This research is done in the belief that there is a lack of research on the comparison between Chinese and American future markets. This paper mainly focuses on three aspects of the two markets: (i)history and social factors (ii) types, duration, and transaction mechanism (iii) nature of regulatory structure study, and reach conclusions that after over a hundred years of development, the future markets in the United States have gone through much more challenges and more perfect. While learning from the experiences of the American future markets, China may need to pay more attention to improving the newly established laws on future markets, while considering the technological progress, as the future markets become more and more mature.
The Impact of the Federal Funds Rate Hike on Walmart Stock Price: A Short-term and Dynamic Perspective
Authors: Liu Yuqi
Published: January 2024

The relationship between interest rates and stock prices has been a topic of debate among scholars. Most scholars agree that interest rates are negatively correlated with stock prices in general, but there are differences in specific countries, industries, and stocks themselves. This paper take Wal-Mart's stock price before the Federal's interest rate hike on 17 March 2022 as a time series, and use ARIMA models to predict the future price, and test whether the interest rate hike affects Wal-Mart's stock price in the ultrashort term and the short term by examining the difference between the model's predicted price and the actual price. The finding of this paper is that interest rate hikes have a slight negative impact on Wal-Mart's stock price in the ultra-short term and no significant impact in the short term. Since previous studies on interest rates and stock prices have dealt less with short-term price changes of individual stocks, this paper provides direction for related research in this area and serves to fill this gap. The advice given to investors in this paper is that when interest rates rise, investors can go short on ultra-short investment period within a week, but if the investment period is longer than nine days, they should be careful to observe that other factors, because interest rate hike do not have a significant impact.
Portfolio Optimization Based on U.S. Stock
Authors: Gao Wenxiang
Published: January 2024

In the financial domain, portfolio optimization is of immense significance due to its potential for risk diversification and return enhancement. Particularly in today's society where inflation is on the rise, a well-constructed portfolio can effectively assist investors in maintaining or increasing real assets. This study selected 10 U.S. stocks and analyzed their data for the past decade. Utilizing Monte Carlo simulation, the study identified the efficient frontier and constructed three types of portfolios: equal-weighted (1/N) portfolio, global minimum variance portfolio (hereinafter referred to as GMVP), and maximum Sharpe ratio portfolio. The findings show that Microsoft and Nvidia have the greatest investment weights in the portfolio with the maximum Sharpe ratio. In the GMVP, JNJ and KO have the highest investment weights. By contrasting the three portfolios' combined performance with the S&P 500 index, both the maximum Sharpe ratio and the 1/N portfolios outperformed the benchmark index, while the GMVP performed below the benchmark. The findings of this study may offer insights into portfolio management for investors looking to increase their real assets.
Bicycle Sales Prediction Based on Ensemble Learning
Authors: Yu Bin
Published: January 2024

In the field of sales forecasting, there are still various challenges in conducting comprehensive analysis and accurate predictions for bicycle sales, including the diversity of sample data, the range of research scope, and the methods employed. This study aims to fill this research gap by applying a bicycle sales dataset and two ensemble learning methods to investigate the factors influencing bicycle sales and conduct sales predictions and analysis. The research findings indicate that cost, profit, and income are the most significant factors influencing bicycle profit predictions. Compared to the Random Forest model, the Gradient Boosting model performs better in predicting bicycle profits. This paper discusses the relevance and predictive performance of the bicycle sales dataset, providing opportunities for improvement and further optimization in future research to enhance the accuracy and reliability of bicycle sales predictions and offer valuable insights for decision-making and planning. Overall, these results shed light on guiding further exploration of sales prediction.
The Limitaitons and Alternatives of CAPM
Authors: Bin Yuxin
Published: January 2024

The Capital Asset Pricing Model (CAPM), a conventional financial model, has undergone extensive testing. This research critically examines the limitations of CAPM from four distinct perspectives and offers alternative frameworks. Specifically, this paper delves into these issues through the lens of the Conditional CAPM. Traditionally, CAPM has been viewed as a simplistic single-factor model. The limitations addressed here encompass temporal constraints, uniform expectations, the role of consumption factors, and underlying assumptions of rationality. This study employs a systematic literature review methodology to conduct its analysis. Through carefully selecting samples, our investigation reveals a correlation between the number of papers published and the years in question. Furthermore, certain keywords surface more frequently, indicating emerging phenomena and trends. However, our primary focus remains aligned with the research inquiry, leading us to select 12 samples for in-depth exploration. Ultimately, this paper argues that the Intertemporal CAPM (ICAPM) may ameliorate the time-related constraints inherent in traditional CAPM. Additionally, the Liquidity CAPM (LCAPM) factors in liquidity considerations, offering improvements to CAPM. The Consumption CAPM (CCAPM) augments CAPM's comprehensiveness by introducing consumption factors. Furthermore, the alpha-neutral CAPM and the sentiment-scaled model both acknowledge the influence of investor behaviour on asset pricing.
Literature Review on the Net Present Value Method of Project Investment Decision
Authors: Su Chen
Published: January 2024

Net present value method is one of the most commonly used evaluation methods in enterprise investment decision, which has great influence on the success of investment. Its research has important theoretical reference significance for enterprise investment decision. This article provides the current status of NPV in actual investment practice and decision making. This paper summarizes the similarities and differences of the definition of net present value from the related theories, concepts, formulas and economic significance. This paper further discusses the advantages and limitations of its application in theory and practice, and draws a relatively widely accepted conclusion about the advantages and limitations of net present value by elaborating the viewpoints of many scholars. Then, the potential optimization measures of net present value method are introduced. Finally, on the basis of summarizing the main viewpoints and contents of the existing research, the possible future research trends and directions of NPV are put forward.
Stock Price Prediction of GM Company: Comparison Based on KNN, Linear Regression and LSTM
Authors: Yin Congyan
Published: January 2024

Stock price prediction holds significant importance in the financial sector. It not only aids investors in making informed buy and sell decisions to achieve potential profits but also supports enterprises and financial institutions in risk assessment and management. This study utilized the stock prices of GM stocks spanning from 2013 to 2023 as dataset, with the goal of predicting their closing prices. This paper carefully identifies the parameters in the three model and one indicator of RMSE outcomes were computed. Visualizations of the results of the three model predictions are also provided. After comparing the indicator of the three models, it is found that the RMSE for LSTM is the smallest, indicating that the LSTM outperforms the KNN and linear regression from the perspective of forecast accuracy. The research highlights the application of the machine learning algorithm of LSTM in the prediction of the prices of financial assets and its practical value in financial market analysis.