bluuebunny/crossref_metadata_2025 huggingface dataset:
Teachers' Utilization of Mobile Learning Applications for Instruction and The Students’ Classroom Performance Towards Strategic Guidelines in The Classroom
Authors: Wang Peiwei
Published: June 2024

This paper is in order to determine the situation of teachers' utilization of mobile learning applications for instruction and the students’ classroom performance on classroom strategy, this paper investigates the strategies of students in Yulin University of Shaanxi Province for teachers' use of mobile learning applications in teaching evaluation. The interviewed students' assessment of the relationship between their teachers' use of mobile learning applications in teaching and classroom performance was identified. In this study, structured survey and quantitative analysis were used to collect and compare data. At least 375 students were randomly selected as the study sample. The results are as follows: 1). Majority of the student respondents are male of not more than nineteen years of age representing Grade 1. 2). Students believe that their teachers frequently use the mobile learning applications in the classroom resulting to an effective utilization of the application in the teaching-learning process.3). Female students have better assessed the utilization of mobile learning applications in their classrooms than the male students. On the other hand, students’ age and grade level did not make significant differences in their perceptions on how their teachers utilized the applications. 4). Students generally exhibited fair to good classroom performance based on their recent evaluation. 5). The use of mobile learning applications in the teaching-learning process did not make significant impact on the classroom performance of the students. This paper is of great significance in improve teaching practices, improve learning outcomes, and promote responsible and effective technology integration. It empowers educators, provides information to administrators, addresses data privacy concerns, and promotes the overall advancement of educational technology and its impact on society.
Research on Tax Collection and Administration Efficiency in the Context of “Governing Taxation by Numbers”
Authors: Tang Yining , Li Wanjun , Peng Wending , Guo Dan
Published: June 2024

In modern national governance systems, tax collection and administration efficiency is a key indicator to measure the performance of the tax system. With the proposal and implementation of the concept of “governing taxation through numbers”, how to use digital technology to improve tax collection and administration efficiency has become an important issue. Focusing on the background of the policy of “governing taxation by numbers”, this article selects Anhui Province as a case area to conduct an in-depth analysis of the impact of the policy of “governing taxation by numbers” on the efficiency of tax collection and administration in practical applications, and explores strategies to improve tax collection and administration efficiency, aiming to optimize Provide theoretical and practical reference for tax management, improving tax compliance and reducing collection costs.
Investigating Enhanced YOLOv8 Model Applications for Large-Scale Security Risk Management and Drone-Based Low-Altitude Law Enforcement
Authors: Chen Guancheng , Du Wenzhuo , Xu Tong , Wang Siyuan , Qi Xiang , Wang Yuxin
Published: June 2024

Urban expansion and complex environments are escalating security challenges. This research presents a drone-based risk assessment approach, significantly enhanced by the YOLOv8 algorithm. Through continuous iterations, the algorithm's performance has improved approximately fourfold, greatly boosting detection accuracy for low-altitude law enforcement and overcoming the constraints of existing surveillance technologies. Furthermore, the algorithm was applied to five major marathon events, conducting security risk assessments based on EWM-TOPSIS and FCM clustering. The final risk ranking of the events was Zhanjiang, Shanghai, Qingdao, Jiangsu, and Tianjin, with the Zhanjiang Marathon showing a people risk index of 72.12, indicating a need for strengthened security measures. This research applies artificial intelligence to public safety, delivering a scalable solution for a variety of security challenges.
Impact of the Development of a Low-Carbon Economy on Global International Trade
Authors: Ma Yiling
Published: June 2024

With the continuous development of human society, the high intensity of energy use has caused serious damage to the environment. Due to the aggravation of ecological problems, governments have gradually set their eyes on balancing economic development and environmental protection. In this context, the "low-carbon economy" emerged and became the keyword in the new policies introduced by governments around the world. However, along with the introduction of low-carbon policies in various countries, its significant impact on international trade has also begun to emerge. Due to the different national conditions and backgrounds of various countries, how to develop a low-carbon economy and how to develop international trade under the background of a low-carbon economy has become one of the key research topics of all countries in the world. By discussing the development of a low-carbon economy and its relationship with international trade, a feasible new strategy of international trade development under the background of low low-carbon economy is proposed.
Research on the Value Distribution of China's Emerging Industries under the Background of "Double Carbon"
Authors: Hu Yaling , Wang Lei , Wang Xueshan , Yang Luyuan
Published: June 2024

China's emerging industries have developed rapidly in recent years, still have significant growth, high added value, is the economic low-carbon environmental protection development of the positive driving force. Sanger algorithm is used to analyze the examples of emerging industries in China, explore efficient and scientific value distribution methods of emerging industries, promote rapid economic development, and summarize the specific construction paths of transforming traditional economic industries and developing emerging industries in various places, so as to provide reference for relevant departments to formulate and improve the healthy development of value distribution of developing emerging industries.
Dynamic Analysis of Street Trees in Vehicle-mounted LiDAR Point Clouds
Authors: Wang Zhiyao , Hao Daoqian , Li Kanghong
Published: June 2024

Street trees, as key elements of urban road scenes, play a significant role in the overall ecological environment and aesthetics of city roads through their dynamic growth and changes. With the continuous development of urban roads, the growth conditions of street trees are also constantly changing. Therefore, studying how to infer the dynamic changes of roads through the variations in street trees is a highly valuable technical issue. This paper delves into several critical parameters of street trees, including diameter at breast height (DBH), tree height, trunk height, crown volume, and crown spread. By updating these parameters, determining transplantation and replanting decisions, and analyzing growth states, we comprehensively analyze the dynamic changes of street trees. To achieve this goal, we integrated multiple parameters into the analysis process of street trees and established a comprehensive analysis system centered on the DBH parameter. Combining this with data visualization technology, we provide an intuitive dynamic analysis method. Experimental results indicate that, compared to single-parameter analysis methods, the multi-parameter comprehensive analysis method demonstrates higher accuracy and stronger persuasive power in the study of dynamic changes in street trees, thereby validating the superiority and practicality of the proposed research algorithm. This research can provide more scientific and reliable references for urban road planning and management.
Assessment of the Teaching Strategies in Macro Motor Learning and Skill Display of the Primary Physical Education Curriculum
Authors: Yang Bo
Published: June 2024

Instructional methods in physical education (PE) tend to be conceptualized in different approaches. This paper attempted to describe the level of academic achievement of third graders in the macro skills of motor learning and skill display and assumes significant differences in variables to propose some teaching strategies for improving motor learning and skill display skills. The results of the National Motor Learning and Skill Display Test revealed that 58.90% of students scored within the 81% to 90% range. The assessment of teaching strategies showed that overall, the strategies had a mean of 3.05 and a standard deviation of 0.83. The chi-square test for association between gross motor learning and teaching strategies was significant (Χ2 = 89.22, p = 0.00). The "Enhanced Motor Skills through Strategic Teaching (EMST) Program" is recommended to improve motor skills through effective teaching strategies.
The Impact of Digital Economy on Entrepreneurial Activity in Chinese Cities: Theoretical Mechanisms and Policy Recommendations
Authors: Chen Deqin , Liu Si , Zheng Haiqin , Du Xiangyu
Published: June 2024

This study delves into the mechanism of the digital economy's impact on entrepreneurial activity in Chinese cities, and analyzes the role of the digital economy in enhancing entrepreneurial activity with empirical data. It is found that the digital economy significantly promotes the enhancement of urban entrepreneurial activity by reducing entrepreneurial costs, improving market efficiency, and optimizing resource allocation. Meanwhile, this study also puts forward targeted policy recommendations with a view to further utilizing the role of digital economy in promoting urban entrepreneurship development.
IoT Sensor-Based Big Data and Information Systems in Smart Healthcare
Authors: Zhou Xiang
Published: June 2024

With the increasing maturity of the Internet of Things (IoT) technology, a new development trend of smart healthcare has been born. This paper, based on the introduction of the current development status, application, and prospects of smart healthcare, mainly focuses on the use of IoT sensors and big data and information systems in smart healthcare and then introduces the relevant technologies involved in wearable devices based on IoT sensors and home environment sensors, as well as the overall operational framework. It also analyzes the case studies of two smart healthcare companies, Sense care and Tencent Cloud, and introduces the smart healthcare technologies they are currently mainly applying. In addition, this report also analyzes the prospects of IoT sensor-based, big data and information systems in the development of smart healthcare, describes some of the current application scenarios and possible areas of application in the future and evaluates the benefits and challenges of their application in the field of smart healthcare.
Research Status and Application of Supercapacitors
Authors: Gao Yuxiang
Published: June 2024

Research and development of new green and sustainable energy storage technologies is urgent due to the severity of the energy crisis and environmental pollution, as well as the need for sustainable development. Supercapacitors are a new type of energy storage device that has a higher power density and a longer service life than other energy storage devices. Thanks to its superior characteristics with extended use and quick rate of charge and discharge, it has attracted widespread attention from researchers. This paper reviews the structure, classification, and working principle of supercapacitors. Besides, utilizing electrode materials is summarized in this article, such as materials with a carbon basis and conductive polymers in supercapacitors, and expounds the application status of supercapacitors in industries, power, transportation, and daily life. In addition, this paper also analyzes the shortcomings and challenges faced by current supercapacitors, and finally summarizes the new potential application fields (such as hydrogel electrolyte and flexible capacitor) and research directions of supercapacitors.
Review of Semi-Supervised Medical Image Segmentation based on the U-Net
Authors: Dai Lina , Md Gapar Md Johar  , Mohammed Hazim Alkawaz
Published: June 2024

Medical image segmentation is a core task in the field of medical image processing. It aims to separate areas of interest such as organs, tissues, and lesions from the background in medical images to facilitate further analysis, diagnosis, and treatment planning. Accurate image segmentation is crucial for improving the accuracy of disease diagnosis, assessing disease progression, and developing personalized treatment plans. However, fully supervised segmentation methods face the challenge of high annotation costs. With the emergence of the U-Net architecture, semi-supervised medical image segmentation based on U-Net is receiving increasing attention. This article reviews semi-supervised segmentation methods, the design concept and structure of the U-Net network, how it has been extended, and its application in semi-supervised medical image segmentation. The article also identifies the challenges faced by semi-supervised medical image segmentation techniques based on U-Net and speculates on possible future research directions. In conclusion, the article summarizes the potential of semi-supervised medical image segmentation technology based on U-Net as an accurate and efficient tool for medical diagnosis and treatment.
Analysis of the Fate of Literati in Qing Dynasty Who did not Meet the Imperial Examination: Life Dilemma and Spiritual Pursuit
Authors: Feng Jiayin
Published: June 2024

The Qing Dynasty was the last period of Chinese feudal society, during which the imperial examination system played an important role. The purpose of this paper is to discuss the fate of literati who failed to pass the imperial examination in Qing Dynasty, focusing on the analysis of their life difficulties and the spiritual realm they pursued. Firstly, it introduces the historical background and structure of the imperial examination system in Qing Dynasty, and its influence on social mobility and literati status. It then discusses the economic challenges, career opportunities limitations and psychological difficulties faced by literati who failed to pass the exam. At the same time, it analyzes how these literati seek spiritual satisfaction and contribution by cultivating personal interest, engaging in literary and artistic creation, and participating in knowledge exchange and cultural activities. Through case studies of well-known literati who failed the exam, their life paths, dilemmas, and achievements are explored, as well as their philosophical and spiritual legacies. Finally, compare with the literati who passed the examination, reflect on the diversity of literati life in Qing Dynasty. The purpose of this study is to provide a new perspective for understanding the fate of literati in Qing Dynasty, and to provide inspiration and suggestions for future research.
Convolutional Neural Networks Applied to Lung Image Detection: Model Comparison and Optimal Selection
Authors: Xuan Lifan
Published: June 2024

The topic of pulmonary health has become a prevalent concern among the public, making monitoring lung health a crucial subject. Numerous researchers have proposed models or methods for detecting pulmonary images, and their effectiveness has been confirmed. However, in the domain of pulmonary image detection, there is a systematic comparison to identify the most suitable and efficient method. Therefore, the theme of this study is to discover, through comparative analysis, the model method most fitting for current pulmonary image detection. The research methodology is outlined as follows: firstly, introduce popular model methods in the current context; secondly, summarize and record the accuracy of each model in pulmonary image recognition; and finally, conduct a horizontal comparison to derive conclusions regarding the optimal model method. This study reveals that Feature Fusion exhibits an outstanding accuracy of 97.79% in pulmonary image recognition, securing the top position. In contrast, Transformer has the lowest accuracy, yet it still reaches 78.9%. Therefore, Feature Fusion emerges as the most promising model method currently deserving widespread promotion in the field of pulmonary image detection.
Preface: 5th International Symposium on Economic Development and Management Innovation (EDMI 2023)
Authors: Chen Yuanyuan , Ali Hesham H.
Published: June 2024

This proceeding includes original and peer-reviewed research papers from the 5th International Symposium on Economic Development and Management Innovation (EDMI 2026), held in New York, United States during May 20-21, 2023.
The aim of EDMI 2023 is to provide a platform for accountants, financial industry practitioners, scholars, managers and graduate students from different cultural backgrounds to present and discuss research, developments and innovations in all fields of Economic Development and Management Innovation. It provides opportunities for the delegates to exchange new ideas and application experiences, to establish business or research relations and to find global partners for future collaboration.
EDMI 2023 received 174 manuscripts. By submitting a paper to this EDMI, the authors agreed to the review process and understood that papers undergo a peer-review process. Manuscripts were reviewed by appropriately qualified experts in the field selected by the Conference Committee, who gave detailed comments and-if the submission was accepted the authors would submit a revised version that considered this feedback. All papers were reviewed using a double-blind review process: authors declared their names and affiliations in the manuscript for the reviewers to see, but reviewers did not know each other’s identities, nor did the authors receive information about who had reviewed their manuscript. The Committees of EDMI 2023 invested great efforts in reviewing the papers submitted to the conference and organizing the sessions to enable the participants to gain maximum benefit.
With our warmest regards,
Yuanyuan Chen
Hesham H. Ali
Conference Organizing Committee
Stock Market Liberalization and Earnings Management
Authors: Song Zirui , Song Yinxuan
Published: June 2024

Using the Shanghai-Hong Kong Stock Connect (SHHKConnect) as an exogenous shock, this paper investigates the impact of stock market liberalization on earnings management in China. By employing the propensity score matching difference-in-difference (PSM-DID) method, we find that the implementation of the SHHKConnect could lower the extent of earnings management for connected firms. The robustness check is conducted and valid. Our study contributes to a deeper understanding of the economic consequences of stock market liberalization and thereby providing implications for policymakers.
Research on the Intrinsic Influencing Factors of Individual Irrational Buying Behavior under Public Health Emergencies
Authors: Han Zihui
Published: June 2024

After the outbreak of New Crown Pneumonia, the rush shopping triggered by the epidemic continued, which brought shocks and challenges to the epidemic prevention and control order and public crisis management. Based on the individual behavioral decision-making model, this paper empirically investigated the intrinsic influencing factors of individual rush behavior under the epidemic using binary logistic analysis, and concluded that individual irrational rush behavior under the public health emergencies was associated with individual's gender, age, education level, satisfaction with community epidemic prevention and control work, individual's sensitivity to media reports, individual's response to surrounding The study concluded that individuals' irrational rush behavior was related to seven factors: gender, age, education level, satisfaction with community epidemic prevention, individual's sensitivity to media reports, individual's reaction to the nervous behavior of the surrounding people, and individual's knowledge about the epidemic, and finally proposed new people-oriented public crisis response strategies.
Smart City Construction Policy and Firm Performance: Empirical Evidence from Shanghai and Shenzhen A-share Listed Companies
Authors: Su Chenyu
Published: June 2024

I examine the effects of digitalization and informatization on firm performance (ROE). I employed a multistage DID model, using smart city development as a natural experiment. Using a sample of Shanghai and Shenzhen listed companies, I discover that firms affected by smart city policy are more likely to have better performance. This finding is robust to a series of robustness checks. Cross-section analysis indicates that nonstate-owned firms, firms with lower power levels concentration and western firms are more likely to benefit from smart city construction. These findings can help managers and policymakers to better understand the mechanisms underlying the relationship between smart city development and firm performance and to develop tailored strategies to leverage the benefits of smart city development.
Enterprise Digital Transformation and Accounting Information Transparency
Authors: Wang Zexi
Published: June 2024

Based on the data of listed companies from 2010 to 2021, this paper discusses the impact of digital transformation of enterprises on accounting information transparency. The results show that digital transformation can improve the transparency of accounting information; The positive relationship between the two is more significant in the diversified business environment. The digital transformation of non-state-owned enterprises has a more significant effect on improving transparency. Digital transformation improves the transparency of accounting information, which in turn enables enterprises to reduce financing constraints and improve future growth prospects. The results of this study provide strong evidence that digital transformation has a positive impact on improving the transparency of accounting information, and can be used as a valuable reference to reduce the information asymmetry between companies and the capital market. The study of this paper provides evidence that digital transformation has positive significance to improve the transparency of accounting information and has reference value to reduce the information asymmetry between companies and the capital market.
How does Sci-tech Finance Affect the Structural Upgrading of China's Service Industry?
Authors: Shi Xiangru
Published: June 2024

Combined with the rise of science and technology finance(sci-tech fin) in the current digital age, this paper selects panel data of 30 provinces and cities from 2011 to 2020 to build a two-way fixed effect model, and empirically analyzes the influence of fintech on the structural upgrading of Chinese service industry. The results show that sci-tech finance significantly positively pushes forward the structural upgrading of the service sector with regional heterogeneity, which is specifically manifested in the positive promoting effect on the central and western areas. Additionally, the level of financial regulation and government expenditure can enhance the influence of sci-tech finance on the service industry structure promoting. Based on this, the paper puts forward some policy suggestions on developing sci-tech finance and deepening the combination of technology finance and service industry.
Coupling Coordination Analysis of Green Tourism - Regional Economy - Regional Logistics
Authors: Kang Yixin
Published: June 2024

By using the panel data of 30 provinces and cities in China from 2011 to 2021, the entropy weight method, coupled coordination model and obstacle degree model are used to construct the coupled coordination index system of green tourism, regional economy and regional logistics, and explore the spatio-temporal evolution, coupled coordination evolution characteristics and impact factors of different regions. The results showed that: (1) Green tourism and regional economic system showed an overall upward trend, while regional logistics system showed a trend of first increase and then decrease. (2) The coupling coordination degree showed an upward trend, from moderate imbalance to mild imbalance, but the overall coupling coordination degree in the country was not high enough. (3) Total investment of foreign-invested enterprises, express delivery volume, total import and export volume of business units, and total postal business are the main obstacle factors. They are the main obstacle factors of economic development module, regional logistics scale module, economic development scale and logistics infrastructure module respectively.
The Impact of Straw Burning on Mortality Rate: A Case Study of Northeast China
Authors: Fang Taoce
Published: June 2024

Northeast is one of the main grain producing areas in China and also has a large number of straw resources. However, due to the high cost of recycling and the limited level of science and technology, most of the straw resources are not recycled and are directly burned in the open. Straw burning produces large quantities of toxic gases and some suspended particles, which have a serious impact on human health and the environment. This report analyses straw burning data, air quality indices, particulate matter concentrations, and mortality rates in the Northeast, and finds that straw burning is serious in many of the more populous cities in the Northeast, and that these cities also have poorer air quality. At the same time declining air quality increases people's mortality rates. Therefore, this paper argues that straw burning can have negative externalities on the environment, thus affecting mortality rates. Government incentives can be introduced to reduce straw burning, thereby increasing social benefits.
A Survey of Sinological Literacy of College English Majors Under the Background of New Liberal Arts
Authors: Yang Liyuan
Published: June 2024

Under the new circumstances, the world development pattern has undergone rapid changes, and China is playing an increasingly important role on the international stage. To establish a good national image under the background of globalization, higher requirements are put forward for English majors to improve their Sinological literacy. Based on the background of the new liberal arts, the author takes English majors in Chongqing Normal University as the research subject. And combines domestic and foreign research results to study the current situation of Sinological literacy through questionnaires, interviews, and literature research. The questions consists of 4 dimensions (Sinological knowledge, Sinological competence, Sinological spirits, and Sinological emotions.) and 53 questions. The research questions are: (1) What is the status quo and problems of English majors' Sinological literacy in Chongqing Normal University? (2) What are the causes leading to students' lack of Sinological literacy? (3) What measures are offered to improve Sinological literacy? The paper founds that students majoring in English lack knowledge related to sinology. They are confused about the Sinological spirit and have weak competencies. By interviewing, the paper found 4 reasons that may explained it: (1) Students lack interest and incentive to learn Sinology. (2) There are few qualified teachers who are equipped with abundant Sinology. (3)Students prefer fragmented knowledge than Sinology due to the era of multimedia. (4) English majors are more likely to be influenced by Western culture if they`re not guided correctly. Through literature research, the paper also raises some measures:(1) Establish the correct concept, the school should add the corresponding subjects. (2) Strengthen teachers' character. (3)Make full use of the rich activities in the second classroom .(4)Build campus culture full of Sinological elements. The author analyzes the result of the investigation case and gives some corresponding countermeasures to solve the problem, in order to provide suggestions for the Sinological literacy cultivation of college English majors and hopes that schools can train more talents for English majors to communicate with other cultures.
Status and Development of Cathode Materials for Lithium-Ion Batteries
Authors: Yu Yicheng
Published: June 2024

Driven by the energy transition and the wave of electrification, efficient battery technology is a core requirement in today's society. Lithium-ion batteries, with their high energy density and long lifespan, occupy an important place in sustainable energy storage solutions. However, the overall performance and economics of the batteries greatly depend on the cathode materials used in them, and innovations in this area are critical to the advancement of battery technology. This study focuses on the latest research findings on cathode materials for lithium-ion batteries, providing an in-depth analysis of key materials such as lithium cobalt oxide, lithium manganese oxide, lithium nickel oxide, lithium iron phosphate, and ternary materials. The article details the chemical properties and performance optimisation of these materials. Through a comparative analysis, this paper aims to reveal the comprehensive performance of different cathode materials and explore their potential for improving battery energy density, reducing cost, and enhancing safety. The importance of this research lies in the fact that it provides an in-depth understanding of cathode materials for lithium-ion batteries, offering a key guide to the innovation and development of future battery technologies. This is not only of practical significance for the advancement of efficient, economical, and environmentally friendly battery technologies but also provides a valuable reference for related industries and academia.
Human Metabolism's Reaction to a Low-Carbohydrate Diet
Authors: Guo Yihan
Published: June 2024

In recent years, as the quality of life has improved, the obesity problem has become more serious, affecting adults and children around the world, reaching epidemic proportions. Low-carbohydrate diets (LCDs) are widely popular among people and used by a wide range of patient groups for weight management. This review examines the complex interactions between human metabolism and LCDs, focusing on the effects on metabolism and personal health. Part One discusses the importance of carbohydrates in metabolism. The second part examines the metabolic effects of a low-carbohydrate diet. Part Three analyses the therapeutic implications of low-carbohydrate diets, highlighting their potential applications in weight loss and management, disease control and treatment, and supplementation for endurance athletes. Despite the remarkable results achieved so far, this paper finds that there are still many shortcomings. Although the impact of LCD on metabolism has been studied, the risk of long-term health effects needs to be further explored. Therefore, larger-scale, multi-center trials targeting different populations are needed to further evaluate the impact of LCD. Based on these conclusions, this article has important implications for healthcare professionals in providing personalized guidance that takes into account individual responses and circumstances.
An Exploration of Sensor-Based Target Localization for Automated Driving
Authors: Kang Jialiang
Published: June 2024

With the continuous advancement of artificial intelligence and meas-urement technology, autonomous driving technology has emerged as a significant challenge for human research. Autonomous driving, as a crucial aspect facilitating convenience in human life, demands substan-tial technological advancements. Target localization stands as a pivotal element in the perception layer of autonomous driving technology. This paper provides a detailed overview of fundamental techniques and sce-narios associated with target localization in autonomous driving. It co-vers aspects such as ultrasonic sensors, visual sensors, LIDAR, and comprehensively summarizes research and applications in autonomous driving technology. Specifically, the author emphasizes the application of sensors in reverse radar systems. Furthermore, the author provides a detailed description of the basic operations of a reverse radar through simulation and emulation using Keil and Proteus software. The author conducted extensive data collection and analysis during the simulation experiments, validating that the simulated circuit can achieve the prima-ry functions of a reverse radar. Finally, the author offers an analysis and outlook on future research in the field of autonomous driving.
Analysis of LSTM and Derivative Models for Bitcoin Prediction Research
Authors: Ren Boyu
Published: June 2024

Bitcoin, the first cryptocurrency, has attracted much attention in the digital currency market, and its price volatility is affected by a variety of factors, posing a challenge to investors. For the sake of analytical feasibility, many studies have adopted simplified modeling assumptions. This may overlook certain key nonlinear features of the market, such as the complexity of investor behavior and the volatility of market sentiment.  This study explores the application of Long Short-Term Memory (LSTM) networks and their derivative models in predicting Bitcoin prices. Recognizing the complex nature of Bitcoin’s market dynamics, the research delves into the effectiveness of LSTM in capturing the nonlinear patterns of cryptocurrency prices. Furthermore, it extends the analysis to derivative models like MSM-LSTM and Empirical Mode Decomposition (EMD) LSTM, evaluating their ability to enhance prediction accuracy by addressing the limitations of the standard LSTM. This study provides an in-depth analysis of the effectiveness of LSTM and its derived models in the practical application of Bitcoin price prediction, with a special focus on their ability to capture non-linear patterns in the market. In Bitcoin price prediction, LSTM models have limitations but also great potential in capturing nonlinear patterns in the market. Extended models based on their own can perform well in Bitcoin price prediction. This study contributes to the field by suggesting strategies to improve the accuracy of the model and by providing ideas for developing trading strategies based on the results of the analysis.
A Review of Point Cloud Alignment Methods and Their Applications
Authors: Wu Jing , Zhang Mingchuan
Published: June 2024

Point cloud alignment is a key technique in the field of computer vision, which involves estimating the transformation between two-point clouds. With the development of optimization methods and deep learning techniques, the robustness and efficiency of point cloud alignment have been significantly improved. Recent studies have combined these two methods to further optimize the performance. Meanwhile, advances in 3D sensing and 3D reconstruction techniques have given rise to the new research field of cross-source point cloud alignment. This paper reviews recent advances in point cloud alignment, including both homologous and cross-source alignment techniques, and explores the interconnection of optimization and deep learning techniques. In addition, the paper reviews relevant benchmark datasets and explores their applications in different domains. Finally, future research directions for point cloud alignment are also described.
The Application of Internet Technology in Enhancing the Efficiency of the Gig Economy
Authors: Ma Jiashuo
Published: June 2024

As our country's overall strength continues to grow, internet technology has rapidly developed, giving rise to the gig economy as a new economic form. The gig economy is characterized by its strong flexibility and intelligence, becoming the choice of many, while providing businesses with a broader range of human resource options. Traditionally, the gig economy has been limited by geographical and informational constraints, making it difficult for supply and demand to match effectively. However, with the widespread adoption of internet technology, gig workers and demanders can easily post and search for information online, achieving precise matches. This efficient circulation of information not only reduces search costs but also improves matching efficiency, making the gig economy more flexible and efficient. Additionally, internet technology enhances the efficiency of the gig economy by optimizing organizational management and processes. With tools such as project management software, automation, and intelligent processes, teams within the gig economy can better coordinate work and improve work efficiency. These technologies reduce error rates, ensure the quality and effectiveness of work, and promote the sustainable development of the gig economy.
Analysis of Huawei's New Energy Vehicle Business Marketing Strategy--Based on the AITO Askworld Sub-brand
Authors: Sun Haowen
Published: June 2024

China's new energy automobile market is booming, Huawei as a communication giant, it crosses into the automobile industry, which has a lot of uniqueness compared with traditional car companies and is even more innovative in its marketing strategy, The success of a car brand depends not only on product quality, but also on effective brand marketing strategies. By cleverly positioning the market, communicating brand values, and enhancing brand awareness, automobile manufacturers can stand out in the fierce market competition and attract and retain more consumers. This paper firstly introduces the background and development history of Huawei's automotive business and analyzes its main competitors; then based on 4P marketing theory, it replaces the traditional promotional strategy with the analysis of digital marketing innovation, i.e., from the four aspects of product strategy, pricing strategy, digital marketing innovation, and channel strategy, it comprehensively analyzes Huawei's new energy automotive business marketing strategy; then it evaluates and gives an explanation of its product strategy and channel strategy; then it evaluates and explains its new energy automotive business marketing strategy. strategy and channel strategy and give relevant suggestions.
The recycling and utilization of new energy batteries
Authors: Chu Chengfeng , Yu Zetong
Published: June 2024

As the main energy storage component of new energy vehicles, the retirement tide of power batteries is coming. The large-scale retirement of power batteries has brought huge benefits to the treatment of power batteries challenge. From the aspects of environment, resources and economy, the significance of power battery recycling is expounded, and the current status of power battery recycling is analyzed. It is aimed at strengthening new energy vehicles power battery recycling, from the aspects of improving laws and regulations, improving the recycling system and improving recycling technology, put forward countermeasures and suggestions. At present, the main technologies are mechanical separation technology, pyrolysis technology and wet extraction technology. Mechanical separation technology mainly uses vibration separation, eddy current separation and electrostatic separation methods to separate different substances in the battery. Pyrolysis technology refers to the heating of waste to a certain temperature in an oxygen-free or low-oxygen environment to decompose organic matter, gas, liquid and solid products. The pyrolysis technology method mainly recovers heavy metals such as nickel and zinc, and the recovery efficiency is high. However, air participation in the operation is easy to cause secondary pollution. Wet extraction technology mainly extracts valuable materials and valuable heavy metals through sorting and sorting, shelling, dissolving in acid and alkali solutions, extraction and ion exchange methods. This technology has a wide range of applications, high recycling rate and little impact on the environment, and is currently one of the mainstream technologies in the field of new energy vehicle battery recycling. However, the process is complex and lengthy, and the recovery of electrolyte and leaching residue is easy to cause secondary pollution, and the recovery cost is high.
Amap - Innovation Based on the Aggregation Model
Authors: Ji Yuling , Song Yueheng , Zhao Xuanqing , Zhou Hang
Published: June 2024

With the rapid growth of online car booking and the widespread adoption of the aggregation model, the momentum behind its implementation in this industry seems unstoppable. This study focuses on Autonaud Taxi, examining its business model innovation, service model innovation, and product innovation resulting from the aggregation model. By employing Porter's Five Forces analysis and SWOT analysis, its comparative advantage highlight the unique competitiveness fostered by this mode. The research emphasizes Autonauer Taxi's significant innovations and developments within the framework of the aggregation model in the online ride-hailing industry. Both its business and service models have a positive impact on regional economies, while product innovation expands its audience reach and enhances overall competitiveness. This analysis provides valuable insights into the dynamic landscape of online ride-hailing services, showcasing Autonauer Taxi as a noteworthy player with distinctive strengths in implementing an effective aggregation model paradigm. The innovative potential of the ride-hailing industry in the aggregation mode is further amplified, which has a positive impact on the development of the consumer economy.
Research on Narrative Strategies in Korean Variety Shows and Youth Self-identification: A Case Study of 'Biong Biong Planet Game Room'
Authors: Lei Shiyu
Published: June 2024

Korean variety shows, with their distinctive entertainment style and gamification, have become a widely disseminated part of Korean pop culture, creating a unique cultural landscape. "Biong Biong Planet Game Room," a variety show produced in South Korea in 2022, combines travel reality shows with competitive games, enriching the emotional expression of variety shows through the construction of multiple spaces. This paper, based on the analysis of the narrative strategies of "Biong Biong Planet Game Room," explores the narrative paths of the show. It also examines how contemporary youths seek self-identification within such shows and project their self-awareness into them. Through this analysis, the paper identifies three ways in which young people construct their self-identity: resonating with the narrative subjects, immersing in the narrative space, and being attracted and engaged by the diverse and intertwined narrative structures. This research also provides insights into the development path for Chinese variety shows.
Analysis on tax management and risk control of enterprise management decision
Authors: Rong Xiaoya , Wang Haoran
Published: June 2024

In today's complex and changeable business environment, enterprises are faced with many business decision-making problems. As an important part of enterprise management, tax plays a key role in enterprise management decision-making. Tax management involves tax planning, tax compliance and tax risk management of enterprises, which directly affects the operating results and profits of enterprises. At the same time, risk control is a factor that can not be ignored in business decision-making, and enterprises must make a balance between risk and return. Therefore, it is of great significance to study the relationship between tax management and risk control for improving the effect of enterprise management decision.
Walmart Sales Forecasting using Different Models
Authors: Yu Chenghao
Published: June 2024

This research study compares three regression models, namely Random Forest, Linear Regression, and Lasso Regression, to determine which model has better performance on predicting Walmart sales. Through the analysis of historical sales data, including factors such as time, unemployment rate, CPI, and temperature, the dataset have training and testing sets. Random Forest is implemented and compared with Linear Regression, a traditional statistical method, as well as Lasso Regression, which includes a regularization term for feature selection and prediction accuracy improvement. Performance evaluation is conducted using mean squared error,and R-squared score. The results consistently show that Random Forest outperforms both Linear Regression and Lasso Regression in predicting Walmart sales, demonstrating its accuracy and robustness. This research offers insights into predictive modeling in retail sales forecasting and highlights the potential for using Random Forest as a reliable tool for inventory control, demand forecasting, and strategic planning at Walmart and similar retailers. Overall, this study contributes to the understanding of sales prediction in the retail industry, suggesting avenues for future research in exploring advanced machine learning algorithms and data preprocessing techniques to further improve accuracy.
Synthesis And Application of Partial Block Polymers in Drug Delivery
Authors: Yue Lishang
Published: June 2024

With the rapid development of modern medicine, the application of biodegradable polymers in drug delivery systems has received increasing attention. Due to their good biocompatibility and biodegradability, they can effectively deliver drugs to target sites while avoiding damage to other tissues. As a functional drug carrier, they have brought revolutionary changes to the field of drug development. Biodegradable polymers play a crucial role in drug delivery systems. Many drugs have excellent anti-cancer or other disease treatment effects, but cannot be directly applied in clinical practice due to low absorption rates or toxic side effects. Drug carriers can provide an effective delivery method for these drugs, achieving synergistic effects of multiple drugs and reducing toxic side effects in the human body. This article introduces four polymers, PLA, PEG, PCL, PEO, and the synthesis, modification, and application of three block copolymers of PLA-PEG, PCL-PEG, and PEO-PEG. It also summarizes the new progress of block copolymers in drug delivery and proposes some new issues and prospects for the synthesis of new drug carriers and the construction of drug delivery platforms.
Research on superstore vegetable replenishment decision-making based on time series and PSO particle swarm algorithm
Authors: Li Zijian , Li Chengyu , Zhang Yongcheng
Published: June 2024

Because vegetables are easy to wear and tear and not easy to store, supermarkets will replenish vegetables every day. In order to make reasonable replenishment and pricing decisions, this paper firstly correlates the total sales data with other data, and finds that the total sales data is negatively correlated with the average purchase price and average selling price, and positively correlated with the number of discounts, and then adopts the Feedforward Neural Network model, the Evenberg-Marquardt training algorithm, and the time series analysis prediction to predict the total daily replenishment and pricing policy of each vegetable in the coming week. Marquardt training algorithm, time series analysis and forecasting, predicting the total daily replenishment and pricing strategy of each vegetable in the coming week, and at the same time, adopting the method of dynamic planning, through the use of particle swarm algorithm of PSO to solve the total replenishment of each category and pricing strategy, and then iterated to get the total daily replenishment of each category of commodities and pricing strategy in the coming week.