bluuebunny/crossref_metadata_2025 huggingface dataset:
Re-visiting the Discursive Power of Chinas Generation Z: A Perspective on the Rise of New Populism in China Through Self-Media
Authors: Liu Zhiyan
Published: March 2024

While the authoritarian rule of China and its media censorship have been extensively researched, the emergence of self-media has introduced a dynamic new platform for political engagement, especially among Generation Z. This paper presents an innovative research perspective, examining the transformative role of self-media in reshaping and fragmenting discursive power, and its subsequent influence on the development of populism in China. It analyzes the Partys degree of tolerance towards self-media within its overarching media regulation policies, and studies how this emergent public sphere of politics catalyzed the transformation of populism along with broad discussions and critiques of societal issues. Focusing on Generation Zs extensive use of self-media for political engagement, the paper underscores the younger generations disillusionment with the current state of media-driven populism under the Party's regime. The paper highlights how the lack of discursive power has contributed to an excessive proliferation of nationalism, formalism, and disparities in wealth distribution. The study offers valuable insights for future research on discursive power in authoritarian settings and stimulates discourse on how self-media simultaneously constructs and deconstructs the frameworks and understanding of populist ideologies.
Analysis of Japan's Nuclear Sewage Discharge into the Sea from the Perspective of International Law
Authors: Xie Fok u
Published: March 2024

The Japanese government's proposed plan to release radioactive-contaminated water into the Pacific Ocean has raised global concerns. Consequently, this prompted extensive contemplation and discourse over Japan's obligations under international law. This study summarizes domestic and international nuclear-contaminated water studies. The assertion is made that Japan's action of releasing nuclear-contaminated water into the ocean can be classified as a state act, contravening pertinent international agreements and legal standards. The subsequent analysis delves into the legal foundation for Japan's state responsibility, highlighting the absence of any exemption from said responsibility. Furthermore, it explores the challenges associated with holding Japan accountable, encompassing varying standards of damage, the lack of regulatory oversight from the International Atomic Energy Agency (IAEA), the complexities surrounding evidence collection and acquisition, as well as the obstacles to transboundary implementation. This paper presents a set of strategies for China to address Japan's discharge of nuclear-contaminated water, focusing on the perspective of international law. These strategies encompass the formulation of explicit discharge standards and environmental damage criteria, and the establishment of a specialized organization for conducting investigations and gathering evidence. The primary objective of this study is to offer valuable insights into comprehending and addressing the intricacies of this multifaceted matter. Additionally, it seeks to furnish pertinent resources for effectively resolving transnational environmental conflicts within the context of international legal frameworks.
Comparison and Analysis of Multiple Machine Learning Algorithms for Predicting Student Adaptation Levels in Online Education
Authors: Li Yucong
Published: March 2024

With the rapid development and popularization of Internet technology, online education has become a new way of education. Compared with traditional classroom teaching, online education has a more flexible learning mode, a more convenient learning environment and a wider range of learning resources. However, at the same time, online education also faces some challenges, one of the most important challenges is the adaptability of students to online education. In this paper, we use machine learning techniques to predict students' adaptability in online classrooms. After using logistic regression model, k-neighborhood algorithm model, random forest model, XGBoost model and Cat Boost model to make predictions, it is found that random forest model is the best in predicting students' adaptability to online classroom, with a prediction accuracy of 89.6%. The XGBoost model and CatBoost model were also better in prediction, with prediction accuracies of 89.1% and 88.6%, respectively. In contrast, the logistic regression and KNN models have poorer prediction accuracy with 68.8% and 77.1%, respectively. The research in this article has important implications for the online education industry. By using machine learning techniques to predict students' adaptability in an online classroom, it can help educational institutions better understand students' learning and improve teaching effectiveness. Meanwhile, for students, knowing their adaptive ability in online classroom also helps them to better plan their study programs and improve their learning efficiency. This study uses machine learning techniques to predict students' adaptive ability in online classrooms, and the results show that the random forest model performs the best in terms of predictive effectiveness. This study provides a useful reference for the online education industry and also provides some ideas for future research.
Navigating Contradictions in Chinese Diplomacy: The Dual Narratives of Peaceful Rise and Class Struggle in Soft Power Discourse
Authors: Xiao Shiqing
Published: March 2024

This research paper explores the intricate and paradoxical nature of Chinas soft power, focusing on the dual narratives of peaceful rise (PR) and class struggle (CS) within its diplomacy and global strategy, The study contrasts Joseph Nyes concept of soft power with Chinas unique approach, highlighting the interplay between Chinas soft power ambitions and its global image. Critical discourse analysis, particularly Faircloughs three-step approach, is employed to dissect political language and narratives, offering a deeper understanding of the intersection of language, power, and ideology in Chinese diplomacy. The papers pivotal section analyzes Xi Jinpings rhetoric on PR and CS, revealing Chinas portrayal of a harmonious global emergence alongside a realist perspective on international power dynamics. The paper delves into the implications of these contrasting narratives for Chinas global image and diplomatic relations. It underscores the significance of understanding Chinas soft power in a connected and multipolar world, providing insights into Chinas rise as a global power and its interactions with the international community. In conclusion, the paper highlights Chinas struggle to balance its historical cultural identity with contemporary geopolitical realities.
The Resolution of Disputes Concerning the Protection of Civilians in Areas of Engagement in Armed Conflict: Based on the Additional Protocols to the Geneva Conventions
Authors: Ni Tianyu
Published: March 2024

Nowadays, with frequent local wars, the forms and means of armed conflicts are changing. So, when it comes to protecting civilians in war zones, there are often difficulties. These difficulties are caused by a variety of factors, which have often been seen in local wars in recent decades. On the question of who should bear the responsibility for protecting civilians and to what extent, people from different positions often have different answers. This article seeks to build on the Geneva Additional Protocol I to explain why warring parties should follow the principles of distinction and proportionality in conflict and how they can protect the fundamental rights of civilians. Through case analysis and legal analysis, this paper focuses on the changes in the forms and modes of war in recent decades and summarizes the main difficulties in protecting civilians in war zones in today's international environment. At the same time, by interpreting the provisions of Additional Protocol I to the Geneva Conventions, this paper draws a conclusion that the application of international law norms to implement the principle of distinction and proportionality in armed conflict can protect the basic rights of civilians in war zones in various ways.
Limitation of Religion Information Spread under Media Law
Authors: Li Chao
Published: March 2024

This article's research aims to let people better understand that freedom of speech needs to be controlled and has boundaries and limitations. Although the First Amendment of the Constitution seems to provide a very broad scope of free speech, a series of other bills have been established to restrict related harmful speech for the sake of public health and social morality. It is very necessary to understand this boundary, which can protect people from serious consequences of their speech due to an unclear understanding of the law. This article will focus on the legal definition of "freedom of speech" within the framework of media law and the First Amendment. Discuss the relationship between the Constitution, the First Amendment, and civil rights while elucidating the circumstances and restrictions on free speech and religious belief by government and religious institutions under media law and the First Amendment. Combining First Amendment-related sentencing bills and media law-related events, this research summarize the restrictions on religious freedom of expression. Although the First Amendment protects people's right to free speech, it cannot violate any laws, such as the Privacy Act and the Personal Reputation Act. Free speech itself cannot violate these other laws.
Research on Issues and Guidance Strategies of Peer Interactions During Area Activities in Senior Kindergarten Classes
Authors: Jing Ning
Published: March 2024

Area activities in a kindergarten setting are primarily child-centered, allowing children to make their own decisions, operate independently, and explore freely. These activities are crucial for enhancing childrens ability to interact with peers. During these self-directed area activities, children are not only able to reflect on their own behaviors but also respond to the actions of others. This cooperation and understanding foster improved peer interactions. This paper utilizes observational methods, interviews, and literature reviews, employing observation sheets for studying S Kindergarten. It focuses on three key issues in childrens peer interactions: aggressive behavior, egocentrism, and gender differences. The study analyzes the current state of teachers guidance strategies across three levels: linguistic, interactive, and environmental setup. It evaluates the existing practices in teachers guidance methods and concludes by offering improvements and recommendations for guiding peer interactions in senior kindergarten classes.
An Analysis of the Role and Impact of Teacher-Student Interaction on Establishing a Student-Centred Classroom Teaching Model
Authors: Zhao Ruohan
Published: March 2024

In the context of the new round of basic education curriculum reform, the status of the student-centered classroom teaching model is becoming more and more important, while teacher-student interaction promotes the development of this teaching model to a certain extent. By analyzing the student-centered classroom teaching model and teacher-student interaction from many perspectives, this paper aims to explore the role and impact of teacher-student interaction on this teaching model. This paper argues that teacher-student interaction in the classroom can improve classroom efficiency, enhance the quality of teaching, create a positive atmosphere, and motivate students. Based on this, the paper puts forward the following suggestions, teachers should fully explore the potential of students according to their differences and provide personalised guidance for students. It also promotes the construction of students' knowledge systems and the realization of their personal goals, promotes the development of students' critical thinking and independent learning abilities, and helps them to achieve better learning outcomes.
The Influence of Art Therapy on Adolescent Identity Development
Authors: Ding Yi
Published: March 2024

Art therapy is an approach aimed at promoting the mental health of individuals through creative expression and self-exploration. The method has been widely used in the field of education and child psychotherapy, and significant progress has been made. In particular, art therapy plays an important role in adolescent identity development. Adolescence is regarded as a critical period in the formation of an individual's identity and they are faced with identity challenges and exploration. By engaging in art therapy activities, adolescents can express emotions and thoughts in creative ways as a means of exploring and shaping their identity. This article aims to analyze the benefits of art therapy on adolescent identity development by reviewing existing research and providing insights. The article will provide an in-depth look at three perspectives: art therapy open studios, school-based art therapy, and digital technology art therapy. The findings clearly show that art therapy helps adolescents to shape their self-identity to a certain extent. Therefore, it is necessary to further promote and apply art therapy to provide more opportunities and support for the healthy growth of adolescents. By expanding the scope and implementation of art therapy, people can further improve its effectiveness in adolescents' identity development, thus making a greater contribution to the development of their mental health and social adaptability.
The Impact of Social Media on the Commercialization and Market Value of Visual Art
Authors: Yang Yuqi
Published: March 2024

With the rapid development of social media, every aspect of people's lives has been affected. The art field is also transforming under the influence of social media, which has changed the value of artworks in the market and the commercialization process. This study will delve into the impact of social media on the commercialization and market value of artworks, reveal the intricate relationship between social media and the art market, and provide suggestions for relevant personnel. This research will use a qualitative analysis method to analyze the case of Zhao Xiaoli, a famous TikTok artist. The research results show that social media has democratized information in the art field, thus changing the traditional art market regarding selection, promotion, and transaction. In addition, social media has altered aesthetics in the art field and created more added value for artworks. Faced with such an impact, artists and social media face new opportunities to think and change. Artists should seize the opportunities given by social media, and social media should also give artists enough support to realize the free trade of artworks on social media. Simultaneously, under the influence of technology and the preference for trending content on social media, the art domain may witness issues such as art plagiarism and a tendency for artworks to prioritize popularity over creativity. Social media platforms should increase moderation and support different types of artwork equally. Artists should also maintain their original intentions and create unique works.
Basic Education Development: Enlightment from Finnish Basic Education Reforms in Recent 50 Years
Authors: Liu Huanyu
Published: March 2024

Education reform has always been an important topic in the field of education. With the establishment of the United Nations Sustainable Development Goals, the quality and equality of education have become more attractive to educators. The curriculum reform of basic education in Finland has attracted widespread attention from scholars both domestically and internationally. Based on this, this article analyzes the characteristics of Finnish curriculum reform and the current situation of Finnish basic education, summarize the effectiveness and shortcomings of Finnish curriculum reform. The research in this paper shows that Finnish education emphasizes equity and high quality, so as to achieve a common education for the whole society. While ensuring the development of basic education, Finland emphasizes the internationalization of education and realizes the systematic and comprehensive development of education. However, Finland still faces the challenge of weakening students' basic skills. This paper argues that it is necessary to pay attention to improving the quality of teachers, ensuring educational fairness, and improving the quality of education.
Exploring the Differences of Manga Adaptations in Film and Television in the Context of the Era--Taking Slam Dunk as an Example
Authors: Wu You
Published: March 2024

With the progress of the times, the new media technology continues to develop, at the same time, the audience of the cartoon has also changed, and the content that the author wants to convey is also different from before. All these factors lead to the film and television adaptations of cartoons in today's era that have long been different from the past. The Slam Dunk movie, which will be released in 2023, is significantly different from the animated TV version of Slam Dunk, which aired nearly 30 years ago. The film version and the animated TV version have their own merits, and as far as audience evaluation is concerned, the film version is more controversial, and such a drastic adaptation has caused a lot of dissatisfaction among the audience. This paper will analyze the differences between the film version and the animated TV version from the two major directions of picture and narrative, compare the strengths and weaknesses of the author's trade-offs in the creation of the film, and discuss in depth the reasons behind the differences between the two. On this basis expand the vision to the general environment of the differences between manga film and television adaptations due to the changes of the times, and put forward relevant suggestions for the future path of manga film and television adaptations, exploring how to achieve a balance between the author's creativity and the audience's satisfaction through the method of improving or restoring the images and narratives.
The Impact of Digital Media on Language Styles and Communication Methods Based on Text, Image, and Video Forms
Authors: Han Yuxuan
Published: March 2024

In the era of digital media dominance, language and communication paradigms are undergoing transformative shifts, propelled by the widespread use of text, image, and video forms. With a focus on textual expressions, visual images, and video formats, the research explores the evolving dynamics of language in the digital age. It delves into the profound impact of digital media on language styles and communication methods. Digital platforms, including social media, online news, and blogs, have become integral to daily life, fundamentally altering how individuals communicate, socialize, and learn. Contractions, abbreviations, emoticons, kaomoji, emojis, memes, screenshots, short videos, and video calls have emerged as dynamic elements shaping language styles. While enhancing communication efficiency, immediacy, and emotional expression, these elements also raise concerns about the potential erosion of formality in digital communication. This study employs textual analysis to investigate the intricate interactions of multimedia forms on digital platforms and their impact on traditional communication styles. Insights aim to comprehensively understand the mechanisms driving language and communication evolution in the digital age. The findings offer valuable references for future technological and societal developments, emphasizing the importance of balancing innovation and preserving linguistic norms for responsible communication in the digital era.
A Study on the Selection and Development of English Education A Case Study of China and Belgium
Authors: Yao Dingning
Published: March 2024

The importance of foreign language education has been highlighted in the globalized state nowadays. Foreign language teaching is gradually entering the education curriculums of various countries. The current global trend can be analyzed by finding the similarities of foreign language teaching in different countries. This article chooses China in Asia and Belgium in Europe for comparison. This article focuses on the reasons for choosing to learn a foreign language in two countries and when education begins. Through analysis, this paper argues that the choice of language education should take into account the needs of social development and national development. As the world's common language, English plays an important role in realizing nationalization and promoting talent development, so foreign languages have become the first choice for second language education and learning in many countries. In addition, this paper argues that based on children's education and growth characteristics, starting to learn a foreign language as early as possible can effectively attract and master it. This paper suggests that people should fully understand the importance of English education, fully grasp the characteristics of students' age and stage, and improve the talent training plan.
Navigating the Uncertain Waters: An Analysis of the Near Future Profitability of the Russian Ruble
Authors: Li Jiahui
Published: March 2024

This paper aims to provide a comprehensive analysis of the near future of the Russian ruble, with a particular focus on its potential profitability as an investment asset. Amidst a backdrop of political tensions, economic sanctions, and ineffective forex interventions by the Russian Central Bank, the ruble has experienced significant volatility. The paper examines key factors influencing the rubles value, including political climate, inflation, interest rates, and main exports. The study analyzes the causes and solutions of Russias three major devaluations since the dissolution of the Soviet Union in 1992. By analyzing historical exchange rate and other economic indicators, the paper scrutinizes the internal and external indicators of rubles devaluation and evaluates the various policy measures taken by the Central Banks of Russia to stabilize the currency, including redenomination and shifts in exchange rate mechanisms. The paper concludes that, given the current political and economic landscape, the profitability of investing in the Russian ruble is questionable and unrecommended. Through this multi-faceted approach, this paper aims to provide a nuanced understanding of Rubles past and present, thereby offering valuable insights for policymakers, investors, and scholars interested in the foreign exchange market of Ruble.
Markovian Spatio-Temporal Pattern Variation and Prediction of Green Financial Development in China's Economic Belt Based on ADABOOST Algorithm
Authors: Yue Jiafei , Wu Zongnan
Published: March 2024

This paper constructs a comprehensive index system, measures Chinas provincial G-FINANCING INDEX using the VIKOR algorithm, explores the spatial and temporal distribution pattern of green financial development, hotspot regional migration and discrete trends by establishing a Markov spatial transfer matrix, and predicts the future pattern of green financial development in Chinas three major economic belts based on the machine-learning algorithm ADABOOST, which finds that: (1) the central region maintains a strong development momentum. The development of green finance in the region shows a scale effect, and there is a positive transmission trend of development momentum between cities. The right side of the nuclear density curve in the western region has a clear trailing trend, and the overall degree of improvement is high. The phenomenon of multi-polarisation exists among city clusters. The city clusters in the eastern region as a whole show extremely high development momentum. (2) Geographic background plays an important role in the process of transferring G-FINANCING INDEX in Chinese cities, and the level of regional G-FINANCING INDEX is the result of the joint action of desired outputs and non-desired outputs, which is dominated by the economic activities in the region, and is specifically expressed in the spatial spillover effect of regional G-FINANCING INDEX is the spatial spillover effect of regional economic activities. (3) The evolution of the G-FINANCING INDEX in the study region has obvious spatial spillover effects, and is synergistic with the type of regional G-FINANCING INDEX, showing the phenomenon of club convergence.
Marketing Strategy of Open AI
Authors: Ma Haoyuan
Published: March 2024

In the current society, the field of artificial intelligence is developing rapidly. In the field of artificial intelligence, OpenAI can be said to be one of the best, which promotes technological progress and market dynamic changes. This article discusses OpenAI's marketing strategy in depth, with the aim of understanding its formulation, evolution, and impact on the artificial intelligence industry. Through analysis, this paper examines the company's initial marketing efforts, branding and messaging strategies, and the role of collaborations and partnerships in expanding its market presence. The paper also discusses ethical considerations intertwined with OpenAI's marketing messages and statements, emphasizing the importance of transparency in this field. The findings of this paper highlight the importance of well-designed marketing strategies to shape industry perceptions, drive technology adoption, and promote ethical considerations in AI development. This research serves as a basis for looking at the complex relationship between marketing strategies and their wider implications for the AI industry.
The Relations Among Loose Monetary Policy and the Housing Bubble and the Financial Crisis of 2008
Authors: Li Xinlin
Published: March 2024

This paper examines whether the loose monetary policy was a key factor in the 2006 housing bubble and then led to the financial crisis of 2008. It analyses the situation of the US economy during the early 2000s. It presents how the role of the Federal Reserves Monetary strategies such as the Expansionary Monetary Policy created an easy credit environment and investors' overconfidence in the US. Furthermore, this paper delves into the Taylor rule and explores the principle for adjusting nominal interest rates based on economic fluctuation and inflation. This framework is crucial in understanding the policy decisions of that time. In addition, this paper outlines the different perspectives on the Monetary Policy from the John B. Taylor and Bernanke who was defend for the Federal Reserve that fears of deflation and the restrictions brought about by the liquidity trap during that time. The paper also reveals labour market, including unemployment and output gaps, indicated economic strength but also inflationary pressure. In conclusion, this paper emphasizes the importance of a multifaced approach to monetary policy analysis in understanding the intricate factors that led to this pivotal event in economic history.
Analysis of the Development and Financing of Small and Medium Enterprises
Authors: Shan Zhenting
Published: March 2024

The number of small and medium enterprises (smes) in a country is huge, their impact on national development is also incalculable, is an important component of the rapid growth of GDP and a strong foundation, but the financing problem has been restricting the development of small and medium-sized enterprises, the analysis of small and medium-sized enterprises in the era of economic downturn financing difficulties how to solve, We should upgrade our financing capacity while improving our own construction. The government should also increase support for financing projects of smes, and introduce certain policies to help smes provide financing services, so as to enhance the financial influence of smes and improve the social environment while developing the economy, through several practical examples, this paper analyzes some problems that small and medium-sized enterprises may encounter in financing in real life, so as to help small and medium-sized enterprises improve the success rate of financing,finally, analyze the future development trend of small and medium-sized enterprises.
Empirical Analysis of the Relationship Between Hospitalization and Mortality in Different Administrative Districts of New York City During the COVID-19 Pandemic
Authors: Pan Zhonghan
Published: March 2024

The COVID-19 pandemic has posed a severe threat to global public health, particularly in New York City, where the impact has been substantial. Against this backdrop, understanding the relationship between hospitalization and mortality, as well as how this relationship is influenced by the economic and healthcare conditions of different regions, becomes an urgent and important research topic. This study aims to explore the relationship between hospitalization and mortality in different administrative districts of New York City (Brooklyn, Bronx, Manhattan, Queens, and Staten Island) during the COVID-19 pandemic, and further analyze how economic development and healthcare conditions affect this relationship. Utilizing data provided by the New York City Department of Public Health, two differently configured regression models are employed for analysis. Model 1 solely considers the impact of hospitalization numbers on mortality numbers, while Model 2 further incorporates area and time as control variables. These findings not only provide significant insights into the geographical and socio-economic differences in the pandemic but also offer targeted suggestions for policy-making.
Economic Repercussions of COVID-19 in Japan and China
Authors: Hayashi Yoshiki
Published: March 2024

This study seeks to explore and elucidate the economic repercussions of the COVID-19 pandemic on Japan and China. By comparing these two prominent Asian economies, the paper aims to offer insights into how different economic structures, policies, and external relations can influence the economic impacts of a global health crisis and determine what each country should do in the post-pandemic era economy. This research delves into various economic indicators such as GDP growth, employment rates, number of bankruptcies, and sectoral analyses. Using quantitative analysis shown in graphs, the paper concludes that the COVID-19 pandemic significantly impacted Japan and China's economies, affecting SMEs, supply chains, unemployment, and government finances; the study suggests both nations need a multifaceted approach from government and society to boost their post-pandemic economies. The study found that Japan faced a surge in SME bankruptcies despite financial support measures; aggregate supply experienced disruptions, and aggregate demand declined due to service restrictions, exacerbating fiscal challenges. China, facing a supply-side shock, should prioritize domestic demand, SME support, digital transformation, and healthcare investment, leading to the study's conclusion that strengthening supply chains and aligning recovery with sustainability is vital for recovery and growth in the post-pandemic era.
An Analysis of the Enterprise Culture of the China Railway Fourth Bureau
Authors: Mi Yueyan
Published: March 2024

China Railway Fourth Bureau Group Co., Ltd. (hereinafter referred to as China Railway Fourth Bureau) is a large-scale construction enterprise with comprehensive construction capabilities and a "benchmark" member unit of China Railway Co., Ltd., a Fortune 500 enterprise in the world. This paper briefly sorts out the road of corporate culture construction at China Railway Fourth Bureau Group and finds that the unique culture of China Railway Fourth Bureau is different from other enterprises based on existing literature and data. The general summary is divided into four levels: material layer, system layer, spiritual layer, and behaviour layer, and it analyses the reasons for its success, mainly reflected in strategy, humanism, behaviour, and diversity.In short, these are all key factors for a company's success. Firstly, it establishes enterprise plans and goals that run through the top and bottom. Secondly, it strengthens employee training to improve productivity. In addition, it identifies the core of the company's goals and comes straight to the point.
Study on the Application of Big Data Technology in Inventory Audit - Taking Swertia Audit as an Example
Authors: Liu Jingyi
Published: March 2024

The arrival of the big data era provides new ideas for auditing to help transform traditional auditing into modern auditing. In this paper based on the existing literature, the basic data and application framework of big data auditing models are extensively reviewed, analyzed and summarized. The research and application of big data and its technology has become a domestic and foreign hot topic. In this paper, the application of big data technology in auditing is based on inventory analysis and auditing based on the analysis of the original auditing procedures and methods as well as the associated risks and difficulties. The case study of the Roe Deer Island scallop inventory audit event is used to study the possibility of applying big data auditing techniques in this area and the risk response in the case of the audit model, which provides a reference for the application of big data auditing in other inventory companies.
Research on the Influence Mechanism of Social Presence on Consumers Impulse Buying Behavior in Livestream ShoppingELM Model Perspective
Authors: Li Junyan
Published: March 2024

The immersive atmosphere created by livestream shopping enhances consumers' sense of immersion and immediacy. However, the high interactivity in livestream studios can lead to impulsive buying issues. This study identifies three core characteristics of social presence (visual attractiveness, immediate interactivity, clue multiplicity), flow experience (perceived pleasure, perceived arousal), and perceived trust as mediating variables, with impulsive buying behavior as the dependent variable. The model is constructed based on the Elaboration Likelihood Model (ELM) theory. Data analysis is conducted using SPSS 26.0 and AMOS 26.0. Results indicate that both visual attractiveness and immediate interactivity significantly influence consumers' flow experience and impulsive buying behavior, with flow experience mediating the relationship. Clue multiplicity significantly impacts consumers' perceived trust and impulsive buying behavior, with perceived trust acting as a mediator.
The Importance of Financial Statements in Corporate Management --Take Bright Dairy Co., Ltd. as an Example
Authors: Tong Yuxuan
Published: March 2024

As an old national brand, Bright Dairy Co., Ltd. (hereinafter referred to as Bright Dairy) is ranked among the top three in the industry after years of development and in 2023, the global food value is located 70th, which entering the top 100 list successfully. With the increase in the total revenue of the Chinese dairy industry, the competitive pressure on the development process of Bright Dairy is getting greater and it is easy to be hit by potential risks. This paper uses literature analysis, case analysis, data analysis, and this paper mainly studies the company's potential risks and the current situation of the company through financial statements. There are also show readers how the company continues to develop well when facing the risks and exerting its own advantages. The study of this paper concludes that in general, the development of the Bright Diary industry is relatively stable. Although it is affected by some major environmental effects of the epidemic, the potential risks are weak, so the company has a wonderful development prospect.
Achieving fairness in team-based FPS games: A skill-based matchmaking solution
Authors: Wu Ruotian , Meng Xiangcheng , Chen Haoshen , Zhu Zixuan , Wang Bo
Published: March 2024

Matchmaking is a critical part of online games which is often related to player satisfaction. To pursue a fair user experience, matchmaking mechanisms typically try to put players with similar skill levels into the same game. The traditional process relies heavily on the outcome of the game instead of the in-game performance of players. This paper proposes a new rating system to represent the skill level of both players and teams, along with a new definition to measure the degree of fairness of a matchmaking result. Three clustering methods (K-means, AGG and BKPP) are investigated to perform the matchmaking and the results are evaluated based on the newly-proposed definitions. The matchmaking results generated by the AGG method appear to reach the best degree of fairness. All source codes related to the project are available at https://github.com/WrtTZ/Achieving-Fairness-in-Team-Based-FPS-Games-A-Skill-Based-Matchmaking-Solution.
IoT based security and privacy implementation in smart home
Authors: Rajasekhar J. , Thanusha T. , Jyothi G. Naga , Tejaswi K. , Abualigah Laith
Published: March 2024

Internet-of-Things technology is being increasingly important in our daily lives. As IoT technology evolved, IoT devices face a data protection hazard, particularly smart home IoT gateway devices, which became evident. The demand for a low-cost, secure smart home gateway device or router among smart home users. The problem is that as the internet of things (IoT) becomes more ubiquitous, there is a growing need to simplify wireless network control mechanisms. Because data collecting and the process includes processes such as monitoring, judging, and controlling are all involved in IoT, the control mechanism is challenging to simplify. Many internets of things technology offer memory and communication capabilities, and are easily vulnerable to hacking, due to the mobile software available at the tip of one's fingers to operate the linked gadgets to the web. In the Internet of Things, secure data transfer is always a concern. To increase safety in IoT and wireless networks, the current study introduces a unique RSA-based method, as well as the AES algorithm and the lightweight protocol message queue telemetry transport (MQTT).
Sentiment analysis applied on Amazon reviews
Authors: Li Jiaqi , Pan Qi , Wang Yihao
Published: March 2024

With the rapid growth of e-commerce, accurately capturing buyers' sentiments through their reviews is increasingly vital for online marketplaces. In this paper, we aim to deal with sentiment analysis in these reviews by exploring effective methods to analyze them. We use a review dataset containing user ratings and comments on Amazon products. Applying the two-step methodology of data preprocessing and model building, we intend to employ models like LSTM and SVM to analyze Amazon customer reviews and gain insights into their performance. The findings of this study may also allow e-commerce platforms to provide better service to sellers and buyers.
Principal Component Analysis variants for Parkinson datasets
Authors: Cheng Chen
Published: March 2024

Principal Component Analysis (PCA) is one of the most fundamental dimension reduction methods that need further research. With the widespread popularity of machine learning and the arrival of the era of big data, dimension reduction has become a hot topic and principal component analysis is a hot topic. However, although there are a lot of researchers who focus on the methods of the PCA, few researches on Parkinson Datasets have been made. As a result, the aim of our work is to discuss the PCA variants for Parkinson Datasets. This paper first introduces the three most commonly used PCA methods: PCA, Sparse PCA and Kernel PCA, and then introduces the Support Vector Machine (SVM) used to measure the dimension reduction effect. After that, we introduced the Parkinson's dataset and the meanings of root mean square error (RMSE), overall accuracy, Cohens kappa (Kappa) and computational time, the indicators that are used to measure the dimensionality reduction effect. Finally, we identified the variants among different PCA methods on the Parkinson dataset by comparing the indicators of the data obtained after dimensionality reduction using different methods.
A new approach based on machine learning to certain diseases
Authors: Teng Ruyi , Zhu Tianqi , Qiao Shuyan
Published: March 2024

Never in history is the importance of data science so emphasized in modern society. Focusing on obtaining conclusive results from the implicit features concealed in a huge amount of data, data science plays a remarkable role in various fields, including modern medical practice. Although the fascinating performance of cutting-edge technology is capable of coping with numerous diseases, certain diseases, such as breast cancer and Parkinsons disease, still compromise peoples health since these diseases are difficult to predict and prone to exacerbate. In order to deal with that problem, we will introduce three different machine learning methods in our experiment to two different data sets to test the performance of classification. In the paper, we clarified the principle of each machine learning method (three different classifiers) at first. Then, we conducted our experiment, during which decisive parameters of classifiers were set by specific searching algorithms. Besides, we introduced metrics along with their principles for the evaluation of the numerical results, which were obtained by different classifiers. In the next step, we discussed the results by comparing the values of the metrics that represent the performance of a particular method. Therefore, we managed to obtain optimal classifiers for the two datasets. In the final stage of the paper, we discussed our experiments limitations as well as prospects, which includes further application in other fields.
Distributionally Robust Optimization methods on robust medical diagnosis systems
Authors: Tang Yumeng , Cui Ziming , Wang Xishi , Xiang Shuyu , Li Yifeng
Published: March 2024

In the medical field, modern recommendation systems face significant challenges due to distributional shifts in data. We propose utilizing Distributionally Robust Optimization (DRO) and Distributionally and Outlier Robust Optimization (DORO) methods to address this issue. This paper aims to develop suitable DRO and DORO frameworks for the medical domain and validate their effectiveness through extensive experiments. We employ the DDXPlus dataset for our investigations and cluster patients based on age, sex, and initial evidence to partition the data into distinct distributions. Using a simple three-layer neural network, we incorporate CVaR and CHISQ as DRO methods and their respective DORO forms. The experimental results show that the overall DRO approach demonstrates more significant enhancements while all four methods exhibit improvements over the original distributional scenarios. Our research contributes to optimizing deep learning models in the medical domain and enhancing their robustness. Furthermore, we intend to use these methods to estimate and provide best-fit patient therapies, addressing real-world medical challenges. The application of these approaches has the potential to enhance the performance and practicality of medical recommendation systems, offering improved medical services to patients.
DeepFoni: An Assistive Communication Innovation to Empower Individuals with Communication Difficulties
Authors: Hamrit Saida
Published: March 2024

This article delves into the transformative capabilities of DeepFoni innovation, a state-of-the-art voice assistant designed to champion seamless communication across linguistic and cultural boundaries. As a beacon of technological innovation, DeepFoni seeks to empower individuals with communication challenges, fostering a global environment of inclusivity, understanding, and equality. Also, we provide an overview of the application, its distinctive features, and its potential societal impact, emphasizing its role in shaping a more connected global community.
Climate risk vulnerability assessment on the production of heirloom rice (Oryza sativa L.) and Arabica coffee (Coffea arabica L.) in Mountain Province, Philippines
Authors: Daipan Levi Ezekiel , Lumbres Roscinto Ian , Lingaling Myra Nieves , Talkasen Lynn , Godio Quinerlyn , Mendoza Guillermo
Published: March 2024

Climate change has brought negative and adverse impacts to agricultural production in the Cordillera Administrative Region, including two of the most important agricultural crops, namely, Arabica coffee and heirloom rice. This study was conducted to assess the climate risk vulnerability on the production of these two agricultural products in the municipalities of Mountain Province, Philippines. The climate risk vulnerability was assessed based on the three general and most widely used climate impact factors as recommended by the Intergovernmental Panel on Climate Change (IPCC), namely, exposure to hazard, sensitivity, and adaptive capacity. The results show, based on the combined indices estimated for each of the three general factors and expected changes in temperature and precipitation as projected by IPCC, that there is high climate risk vulnerability of the two crops in the municipalities particularly in areas where there is high potential exposure to hazards, low climate suitability of key crops in the future, and low adaptive capacity. Findings from the climate risk vulnerability analysis (CRVA) developed in the study demonstrate that it, as described in this paper, can serve as a meaningful reference to inform and guide decision-makers from concerned government agencies and the private sector in crafting policies and potential interventions in highly vulnerable areas whose climate risk vulnerability can be estimated and determined using CRVA. It is recommended that the CRVA described in this paper be made part of the tools and potential guides used by the Department of Agriculture to help mainstream climate change adaptation and mitigation strategies.