bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Food security Model of Rural Revitalization Based on Computer Artificial Intelligence Model
Authors: Lin Xiuli
Published: January 2024

In this paper, grain demand and supply models were established based on data collected from the China Statistical Yearbook and the website of the National Bureau of Statistics of China. This paper uses stepwise regression method to establish linear regression, residual autoregressive model and C-D production function, residual autoregressive model to analyze various factors that may affect grain yield. Then, R software was used to conduct collinearity test and residual analysis on the results, and cluster analysis method was used to conduct in-depth analysis on the causes of grain yield fluctuation. Finally, the regression equation of grain yield was obtained. Through MATLAB simulation curve, the values of the four main influencing factors are predicted respectively to get the future grain yield of China.
Path Planning Approaches for Unmanned Aerial Vehicle
Authors: Cao Han
Published: January 2024

The difficulty of finding the ideal path from the starting point to the destination site for a UAV is one of the most essential challenges related with the deployment of unmanned aerial vehicle (UAV). Path planning algorithms are classified into traditional and intelligent algorithms in this article based on the order of discovery of the path planning methods. Intelligent algorithms are algorithms that are inspired by nature and can efficiently tackle the complex path planning problem. In this article, by introducing the different advantages of traditional algorithms and intelligent algorithms, it proposes employing intelligent algorithms to address the inefficiencies of traditional algorithms in uncertain conditions. The essay also outlines three classical intelligent algorithms and proposes optimization algorithms for their respective deficiencies. The article also discusses the objectives and constraints of UAV path planning. This analysis will help define the outcomes of UAV path planning and suggest the future research directions.
Financial Analysis and Risk Study of Global Film Companies: A Case Study of Warner Bros. Entertainment, Inc
Authors: Zhu Siqi
Published: January 2024

The income of the film industry mainly depends on the box office, but the COVID-19 epidemic in the past three years has led to the suspension of cinemas in many regions, the postponement of films under production, and the postponement of the release of films, which has the most direct impact on the film industry. Therefore, this paper takes Warner Bros. Entertainment as an example, this paper introduces the reasons why the film industry is chosen and why Warner Bros. Entertainment is chosen. At the same time, through the introduction of Warner Bros. and the trend of its financial data in the past five years, we can analyze the possible crises and opportunities that the company may encounter. At the same time, we also conducted an industry analysis of the global film industry through this company and gave the specific crisis and the formation of opportunities.
Analysis of South West Airlines Management and Logistic Plan
Authors: Qi Zhouyang
Published: January 2024

Southwest Airlines has turned into a precursor in the competitive airline market, this is because of its novel management and operations procedure. Therefore, investigating its extraordinary strategies, benefits, difficulties, and impacts on the airline's operations gives substantial recommendations for its future development. Southwest Airlines is a spearheading low-cost airliner known for its obligation to client-centricity and functional proficiency, which is plentifully shown by its extraordinary administration and coordinated operations plan. The "Southwest Way" culture, which advances employee empowerment and outstanding client support, is at its core. The point-to-point route structure of the airline augments productivity by diminishing intricacy and working with fast airplane turnarounds. This procedure works on functional adaptability and cost viability and is upheld by a normalized Boeing 737 fleet. Furthermore, Southwest increases airplane usage and income creation by focusing on short-haul trips. Nonetheless, because of the restrictions of the point-to-point idea, significant distance and global extension face difficulties. However, the essay proposes strategic ideas, like worldwide market extension, state-of-the-art administrative procedures, environmentally friendly logistics, and computerized change. These actions ensure progressing thriving, ecologically dependable activities, and unrivaled client encounters. To introduce Southwest Airlines as an aeronautics pioneer, this paper explores its mind-blowing way, which was set apart by remarkable procedures, difficulties, and steadfast purpose.  In spite of difficulties, Southwest's beliefs, and employee-focused culture fueled the development and increased industry expectations. The paper examines how these components impact advancement and development.
Calculation of optical efficiency of the heliostat field based on Reverse Projection Box Counting Model
Authors: Chai Kexiang , Xiao Yundi , Xie Dun , Gao Wen
Published: January 2024

A more accurate and reasonable calculation model is proposed for the calculation of total optical efficiency, shadow blocking efficiency, cosine efficiency, atmospheric transmittance, collector truncation efficiency and output thermal power of heliostat field in tower solar photovoltaic power plant. In this paper, under the condition that the relevant parameters of heliostat field are determined, the Monte Carlo Ray Tracing method is used as the basis for the calculation of each optical efficiency. At the same time, the innovative Reverse Projection Box Counting Model is established to accurately identify whether there is a shadow blocking problem or not, and the differential idea is used to effectively solve the problem of repeated calculation of the blocking shadow area and the irregularity of the blocking area difficult to be calculated caused by one heliostat being blocked by multiple heliostats, so as to estimate the shadow blocking efficiency of the heliostat field more accurately. Finally, the heliostat field in Gansu, China, is taken as an example for calculation, and the results are compared with those of other scholars and the real value of the heliostat field to prove the superiority of the model constructed in this paper and the accuracy of the solution results.
Study of Optimal Portfolio Performance on Markowitz and Index Model
Authors: Dong Luke
Published: January 2024

The choice of a portfolio optimization of shares has been for so long a subject of major interest in the field of investment and financial mathematics. This article aims to create a portfolio optimization which follows the objective of maximized return and minimized risk under given constraint among S&P 500 and the ten stocks, utilizing data collected from Yahoo! Data. The article ought to elucidate the Markowitz Model and Single Index Model in terms of generating a better result via comparing their distinct mechanisms in calculating their return percentage, standard deviation and Sharpe ratio, alongside with the corresponding efficiency frontier to compare their sharp ratio to determine a better model for each scenario. The result illustrates a better performance of the Markowitz Model in the aspect of producing a better portfolio optimization contrasting the Index Model in all the constraint except constraint three. Eventually backtesting was utilized to verify the feasibility.
Triple-Disk Recovery RDP Coding: A Robust Solution for Data Storage in RAID Configurations
Authors: Wang Chuhan
Published: January 2024

Data-intensive technologies require reliable and efficient storage solutions to ensure the integrity and availability of vast amounts of generated data. Redundant Arrays of Independent Disks (RAID) technology has emerged as a popular choice, offering fault tolerance and improved performance. Among RAID configurations, RAID-6 stands out for its ability to tolerate up to two disk failures. This is achieved through algorithms like Row-Diagonal Parity (RDP) coding, which introduces redundancy and enables data recovery. In this paper, we propose an innovative approach, namely Triple-Disk Recovery RDP (TDR-RDP), to enhance reliability based on RDP coding by accommodating three disk failures. We review the RDP algorithm, introduce the TDR-RDP coding scheme, elaborate on encoding and decoding processes, and address diverse types of triple disk failures along with their recovery strategies. Furthermore, we evaluate and compare the computing efficiency of TDR-RDP with the RDP algorithm, showcasing its practical feasibility. Overall, the TDR-RDP algorithm offers a compelling solution to bolster data storage reliability in RAID configurations, surpassing traditional RDP coding by ensuring resilience against triple disk failures and augmenting data-intensive technologies.
Study of Interaction Design-Based Urban Architectural Space Optimization
Authors: Deng Qingxuan
Published: January 2024

In today's highly urbanized society, where science and technology are developing quickly, residents' quality of life has improved. Everyone is striving for a better life, and because urban residents must use and survive the urban space for a long time with a variety of defects brought on by the excessive process of urbanization, problems arising from the local context of on-demand optimization have become important. As a result, the primary area of research in this work is the study of interaction design-based spatial optimization of urban buildings. By analyzing the interactable scenarios in the city, the study methodology of this work summarizes the interaction method of space optimization. According to the study, the interactive aspects of urban space are primarily the ecological factors that change with the seasons, the material elements that deteriorate with usage and time, and the interactive technology elements brought on by technological advancement. Based on the interactive components of urban space that were summarized in the previous section, it is possible to draw the conclusion that the interaction of human behaviors, emotions, and senses with the interactivity of interaction design can be used to create a livable urban space.
A Comparison of Electric Vehicle Industry Policies Between China and The United States
Authors: Xiang Xinyi
Published: January 2024

Against the background of global vehicle market fluctuations, the annual sales of global electric vehicles continued to grow, showing a good development trend. In the global EV industry, China is the leader in the power battery supply chain, EV production, charger installation, etc. The U.S. is overall ranked third. After the background illustration and industry policy sorting, the paper illustrates the different top-level national EV industry strategy designs in China and the U.S., then compares the 2 countries’ policies from the dimensions of fiscal policies, R&D policies (focusing on battery development), and supporting infrastructure construction. The analysis shows that in the development of batteries and the construction of supporting infrastructure (charger), compared with China’s policies, the overall policy planning of the United States lacks coherence and central authority, and the development of its battery industry lacks the cooperation of enterprises under the leadership of the central government. The 2 countries have different preferences in fiscal and taxation policies, and the credit system represented by California Zero Emission Vehicle in the U.S. is more flexible and spontaneously guided than China's.
Stock Price Prediction based on Time Series Model and Long Short-term Memory Method
Authors: Song Dazhi , Song Dazhi
Published: January 2024

This study conducts a comparative analysis of two prominent methodologies, Time Series Analysis and Long Short-Term Memory Neural Networks (LSTM), for the prediction of stock prices, utilizing historical data from Netflix. The primary purpose of conducting this research is to evaluate their efficacy in terms of predictive accuracy. Time Series Analysis encompasses stationarity tests, rolling statistics, and the application of the Autoregressive Integrated Moving Average model. In contrast, LSTM Neural Networks involve data normalization, reshaping, and the development of LSTM-based models. Performance assessment metrics such as Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, and visual comparisons are utilized. The results prominently favor long short-term memory Neural Network, which consistently outperforms in predictive accuracy, yielding reduced forecasting errors. This study contributes significant insights into stock price prediction methodologies and offers implications for refining model parameters, bolstering adaptability to evolving market dynamics, and addressing computational efficiency concerns in both Time Series Analysis and LSTM Neural Networks. In summary, LSTM model emerges as the preferred approach, advancing understanding of effective strategies for stock price prediction in financial markets.
Recent Developments in Research on the Impact of ESG on Corporate Value
Authors: Zhang Qichen
Published: January 2024

ESG (Environmental, Social, and Governance) has become an increasingly prominent topic in the investment field. Questions such as whether ESG can create value for companies, the credibility of ESG investments, and whether ESG should be incorporated into my long-term investment plan are crucial considerations. Many scholars have conducted research from various perspectives to address these questions. This article summarizes relevant literature and answers the impact of ESG on corporate value and the factors influencing ESG's impact on corporate value. The research findings are as follows: 1.ESG has a generally positive impact on corporate value, with some factors showing inhibitory effects or no significant correlation.2.ESG primarily affects corporate value through aspects such as market valuation, financing costs, innovation capability, and reputation. 3. The impact of ESG on corporate value varies depending on the ownership structure and industry of the company. Based on these findings, companies should decide whether to enhance their ESG performance based on various factors such as their operational situation, industry composition, and ownership structure.
Prediction model of Wordle report based on GA-BP neural network
Authors: Wang Shiying , Wang Rui , Liu Peilin
Published: January 2024

Natural Language Processing (NLP) plays a vital role in artificial intelligence, enabling machines to understand and generate human language. This paper proposes a novel approach to improve NLP tasks by integrating a Genetic Algorithm-based BP neural network model. The model combines the strengths of genetic algorithms and neural networks. Genetic algorithms offer effective search capabilities, while the BP neural network provides a flexible learning framework. By integrating these techniques, the proposed model aims to overcome limitations of traditional NLP models. It effectively handles the complexity of natural language data, provides efficient training by avoiding local optima, and exhibits enhanced generalization capabilities for unseen data. Extensive experiments on benchmark NLP datasets validate the effectiveness of the proposed model. Results demonstrate its superiority over state-of-the-art NLP models in terms of accuracy, efficiency, and robustness. This paper presents a novel approach to enhance NLP tasks by integrating a genetic algorithm-based BP neural network model. The model shows promising results in various NLP applications and offers advantages over traditional approaches. This research contributes to the advancement of NLP techniques, facilitating more accurate and efficient language processing systems.
Research Status and Development Trend of EEG Technology for Deep Learning in Emotion Recognition
Authors: Yang Mu
Published: January 2024

EEG technology has made significant progress as people's attention to their emotions increases. This has also led to significant progress in various brain sciences, as well as their correlation with emotions. Nevertheless, based on the development of contemporary brain science, it is not possible to provide detailed cause analysis or draw accurate conclusions based on EEG information for a certain symptom or representation. The brain, as a complex organ of multiple entities, processes complex information by connecting multiple brain regions and clarifying the division of labor for each region. This creates a significant obstacle for the research method of brain computer interface, which uses computer algorithms to read information in the brain.  Recently, many solutions and research methods have emerged to address this issue, such as electroencephalography (EEG), Positive Positron Emission Computed Tomography (PET) and Functional Magnetic Resolution Imaging (fMRI), etc. However, with such a large number of technologies, a method that can provide precise data from both temporal and spatial angles has not yet been derived. So in-depth research in biology, continuous exploration of computer algorithms can make outstanding contributions to the refinement of brain computer data. In summary, this article aims to provide an overview of the relationship between emotions and EEG analysis, as well as the principles of machine recognition and other applied technologies.
Comparison Of Methods for Predicting Changes in Stock Trading Volume
Authors: Que Qinxuan
Published: January 2024

Stocks occupy an important place in the financial sector, while machine learning, which uses data to solve problems, has been applied in several fields. In this paper, three methods of multivariate linear model, BP neural network and ELMAN neural network are adopted to predict the transaction volume change value of ZTE and compare the evaluation. The study shows that, in the short-term prediction of BP neural network and multiple linear model, the two methods have good prediction effect, the BP neural network is stronger; ELMAN neural network is worse, it is not recommended to predict the trading volume change value.
Reflections on Asset Pricing Factors: A Machine Learning-Based Perspective
Authors: Yuan Ziding
Published: January 2024

In recent years, scholars have explored hundreds of asset pricing factors built upon the foundation of the Fama five-factor model, sparking widespread discussion in the academic community. Simultaneously, the advancement of machine learning techniques has brought innovation to asset pricing factors. This article provides an overview of typical asset pricing factors and the application of machine learning in pricing models. It begins by discussing the construction of new asset pricing factors and then delves into the innovations brought about by machine learning in asset pricing models. The diversity of factors increases the fit of asset pricing models but also presents corresponding challenges. The application of machine learning techniques addresses issues such as overfitting in pricing models, further enhancing model effectiveness. The primary value of this article lies in summarizing various perspectives on asset pricing factors in recent years, exploring the significant applications of machine learning in asset pricing models, and providing a forward-looking view on the development of asset pricing models.
Whether There Will Be Domestic Luxury Clothing Brands in China
Authors: Wong Cholaam
Published: January 2024

In recent years, with the improvement of China's overall economic level, China's luxury goods market has also been expanding, becoming a major consumer of luxury goods. However, the competition in the luxury goods market is fierce, but there are no local luxury brands in China. This paper analyzes whether domestic luxury brands will appear in China by studying the behavior of Chinese consumers and the current development status of Chinese luxury goods. While it is uncertain whether domestic luxury goods will emerge in China, the rapid growth of the Chinese luxury market and the rise of Chinese domestic brands suggest that the possibility is increasing. The inroads made by Chinese domestic brands in the luxury market are providing more choices for Chinese consumers and driving change in the global luxury market. In the future, as China's domestic brands continue to grow, we can expect to see more made-in-China luxury goods emerging in the international market.
Signal Enhancement Methods Based on Wavelet Transform, Fractional Fourier Transform and Short-time Fourier Transform
Authors: Zhang Xindan , Zheng Haoyuan
Published: January 2024

This review paper mainly focuses on different signal enhancement methods such as wavelet transform, fractional Fourier transform (FrFT) and short-time Fourier transform (STFT). First, this paper introduces the concept and importance of signal enhancement, as well as some current issues and challenges. Then, in recent years, the application of the three methods in wavelet transform, fractional Fourier transform and short-time Fourier transform is described. In terms of wavelet transform, this paper discusses the application of wavelet function to image enhancement and the specific steps, and analyzes its advantages and application in signal enhancement. In terms of fractional Fourier transform, this paper introduces its difference from traditional Fourier transform, and discusses its application in combination with adaptive filtering technology and the application of multi-level FrFT in the field of speech enhancement. Finally, in terms of short-time Fourier transform, this paper discusses its application in the fields of image enhancement and speech enhancement. The review paper finally discusses the characteristics, advantages and limitations of these three methods in signal enhancement, and looks forward to the future research directions. Through the research of this review paper, it can provide some reference and guidance for the research in the field of signal enhancement.
Inventory prediction based on CNN-LSTM Model
Authors: Zhang He , Tian Shaokai , Qin Jianfeng , Yu Zhengtian , Guo Huabo , Jia Xuefeng
Published: January 2024

Demand forecasting and inventory optimization are the core issues of e-commerce supply chain management, which are crucial for ensuring timely delivery of goods, reducing inventory costs, and improving inventory turnover efficiency. This paper is based on Python's merge function to merge table data and transcode text data. Then, by drawing a q-q diagram and K-S test to determine the distribution of the data columns, it was found that the shipment volume data follows a normal distribution. Adopting 3σ The principle is to determine outliers and manually determine that the two data with larger values in the edge values are considered outliers. Replace the above outliers with missing values and use Newton interpolation for linear filling to obtain the standard dataset after data preprocessing. We establish a prediction model based on attention mechanism for prediction, and ultimately obtain more accurate prediction results.
Predictive Analysis Based on Prophet Model: Evidence from the Number of Epidemic Infections
Authors: Pan Jiachen , Xu Zitong
Published: January 2024

This study makes a prediction of infection numbers in the future and investigates the correlation between the new cases and the stock price of companies in three different fields. In the first part of the prediction, we use three methods to make predictions of the future infected number, including the ETS, Auto-Regressive Moving Average (ARIMA), and Prophet model. In the next part, we use the GARCH model to discuss the correlation between infection numbers and stock prices. Considering the heterogeneity, we choose three different companies’ stocks to represent three industries respectively. They are Apple, Amazon and Pfizer. The result indicates that the stock price of Apple is negatively correlated to the infection number, the relationship between the infection number and the price of Amazon is inconspicuous, while the price of Pfizer is positively correlated with the development of the pandemic. Thus, we draw the conclusion that the impact of the epidemic is strong to manufacturing, is not obvious to the Internet industry, and boosts the development of the medical corporation.
The Impact of Social Media Marketing on the Mobile Game Industry--Take Glory of the Kings as an Example
Authors: Sun Ziming
Published: January 2024

Glory of the Kings is in a leading position in the mobile game industry, and its successful marketing strategy is worth learning from other mobile game manufacturers. This paper takes the marketing strategy of Glory of the Kings as an example to study how the mobile game industry should carry out more targeted marketing strategies according to the characteristics of different social media after the maturity of social media platforms. For social media with solid relationship characteristics, it is necessary to build a friend mechanism around the relationship link between users, strengthen the social attributes of games, enhance user stickiness, and carry out social marketing. For social media with weak relationship characteristics, marketing strategies closer to users should be adopted to stimulate users' interest and sense of participation, and interactive marketing should be conducted. Key opinion leaders should be utilized for content-heavy social media platforms to gain higher brand exposure and reach more target customers. It can also establish social media based on interest community, which can not only accumulate users but also feed back the game ontology and two-way drainage, complement each other to promote long-term operation and continue to expand the influence and possibility of game IP.
Research And Application Of 3D Collaborative Design in Oil and Gas Field Surface Engineering
Authors: Yan Dongyin , Wang Mincong , Tan Chuanjiang , Wang Chiyu , Sun Fengzhi , Feng Quan
Published: January 2024

With the constant development of major oil and gas fields at home and abroad towards the direction of digitalization and intelligent technologies, the traditional surface engineering process has encountered the challenges of limited professional collaborative design and poor data connection, etc. The advanced 3D collaborative design has gradually become the mainstream platform of oil and gas field surface engineering design due to its features of a higher degree of model reduction and its advantages of cross-discipline, cross-platform, and cross-region collaborative design. However, in the course of current station modeling and designing, due to the complexity of engineering and the limits of design software, etc., the problems of mutual transmission failure amongst models and the loss of attribute information are prone to occur, causing a bad impact on the work efficiency of 3D collaborative design. In this paper, the commonly used 3D collaborative design software in oil and gas fields has been systematically discussed along with the common issues and their solutions in aspects of 3D design analyzed. Moreover, the effective application of collaborative design in the stage of procurement and construction, and the stage of the operation and maintenance of the digital station shall be separately discussed. While improving the efficiency of 3D collaborative design, it also plays the role of guidance in strengthening the digital and intelligent construction foundation of oil and gas fields.
Study On the Impact of Input-Output Ratio of Chinese New Energy Enterprises
Authors: Tian Haoxuan
Published: January 2024

This essay will analyze and compare the relevant data of the leading companies in four industries: photovoltaic, wind power, hydrogen energy and new energy automobile. The first part is the brief description of the companies. The author selects two leading companies in each industry and analyzes their contribution to the industry. Next, the author collects the data on the research development investment and total turnover of each company and calculates the input-output ratio of each company by using the formula. Next is the comparison section, where in each industry, the authors compare the data of the net attributable profits of two companies from their annual reports for 2021 and 2022. The results of which can be seen as an increase or decrease in net profit for certain companies in both years and the author explains this result. In the Conclusion section, the authors first summarize the ranking of each industry. Secondly, the author compares the four industries to identify the two most profitable and promising companies in China's future and explains their characteristics and strengths.
Investing Decisions Based on Multiple Valuations - Case Study of Several Chosen Gaming Conglomerates
Authors: Song Jiuchuan
Published: January 2024

With the significant growth and transformation in the gaming industry, there is necessity to explore the complexities of investment decisions within several gaming conglomerates by employing multiple valuation methods as a case study and referring to recent data from 2019 to 2023 from U.S. Securities and Exchange Commission, based on stock prices on 12 August, 2023. Briefly introducing the background and the valuation tools, the analysis is mainly divided into two parts, market valuation, including P/E ratio, expected growth rates in EPS and gross revenue and PEG ratio, and profitability valuation, including GP/A ratio and annual and quarterly gross margin trends. In light of the above analysis, a best investing object is selected and the most significant risk factors of investing in the selected stock are listed. It is promising that investors and stakeholders will broaden more profound insights into the financial health, stability, and growth potential of ATVI, SONY, EA, and MSFT and the gaming industry.
Machine Learning in Tesla’s Stock Price Prediction
Authors: Kong Yalong
Published: January 2024

With the development of new energy battery technology and people's attention to environmental issues, new energy vehicles have gradually become one of the important choices for people to travel, and stock investors have also begun to keep an eye on the field of new energy vehicles. However, since the new energy industry is an emerging industry, the current stock market analysis in this regard is not complete. Machine learning is one of the important means of stock forecasting at present. This article will use 6 machine learning models such as linear regression, polynomial regression, XGBoost, ARIMA, Prophet and LSTM to analyze and predict the stock of Tesla, a leading company in the field of new energy vehicles, so as to judge the investment prospects of new energy vehicles. The outcomes demonstrate that LSTM has the lowest error in predicting the price of Tesla’s stock.
The Influence of Japanese Nuclear Sewage Pollution on China's Import and Export Trade
Authors: Huang Yini
Published: January 2024

The Fukushima Daiichi disaster occurred in 2011, leading to ongoing concerns about contaminated water. China and Japan have a complex trade relationship, which makes any disruption important. This background sets the stage for exploring potential trade implications. The research will discuss how Japan's nuclear and water pollution affect China's import and export trade. First, we will cover the background of the accident at the Fukushima nuclear power plant in Japan and the atomic sewage treatment plan. Next, we will analyze the potential impact of this incident on China's import and export trade, covering trade relations, seafood, and other aspects. Finally, we will discuss China's measures and proposals to address this impact. In short, it is concluded that Sino-Japanese trade will be subject to inevitable fluctuations in the short and medium term, but in the long run, its transaction will still show a steady upward trend.
Super-Resolution of Lightweight Images Based on Deep Learning
Authors: Wu Haozhe
Published: January 2024

As digital imaging technology advances, a significant breakthrough is the emergence of super-resolution technology, a method to enhance the quality of low-resolution images to high-resolution. When there are some developing of the newest digital camera's skills, the super-resolution technology is appearing and getting more and more importance. In the simplest terms, the image super-resolution skill is the technology of which one cover the process from low resolution images to high resolution images skills. This technology differs from the traditional approach in that it is attracting more and more attention from researchers and practitioners. This method is important in the future. With the passage of time, it will be more and more mature. In this paper, we focus on how to improve image resolution by using various technologies, and summarise the results obtained in recent years. Then, we briefly introduce the background and development of super resolution, then briefly introduce the technology. Finally, we come to a few conclusions regarding Deep Learning.
Analysis of Electric Sensor for Space Detectors: Mass Spectrometer, Particle Detector and CMOS/CCD Sensor
Authors: Lin Xinhang
Published: January 2024

As a matter of fact, with the participation of government agencies and the exploration of private enterprises, space exploration is undergoing rapid development as well as change in recent years. With this in mind, these trends will continue to promote human exploration and utilization of space, providing more opportunities for scientific research, commercial applications and exploration. In order to realize accuracy observation, high precision detectors are necessary to be developed and implemented. To be specific, a large number of electric sensors are applied on the space detectors, including mass spectrometer, particle detector as well as CMOS/CCD image sensor, etc. On this basis, this paper presents the principles, structures and applications of these three electric sensors in detail. According to the analysis, this study also analyzes the existing shortcomings of the state-of-art facilities as well as proposes future developments. Overall, these results shed light on guiding further exploration of space detectors.
Analysis of the effect of the application of the precision training model in the promotion of blood donation during public health emergencies
Authors: Han Zhi , Han Yujie
Published: January 2024

This study aimed to explore the impact of precision training on the promotion of blood donation during public health emergencies. The research focused on blood donation volunteers at the Wuwei Central Blood Station from 2018 to 2021. The data from 2018-2019 represented the period before precision training, while the data from 2020-2021 represented the period after precision training. The study observed the number of non-remunerated blood donations and group non-remunerated blood donations in the Wuwei Central Blood Station from 2013 to 2021. The success rate of blood donations, group blood donations, "turning back" of non-remunerated blood donations, and knowledge rate of non-remunerated blood donations were compared before and after precision training. The results showed that the actual values of blood donations were higher than the predicted values, indicating a positive influence of precision training. The success rate and group blood donation rate increased significantly after precision training. The rate of "returning" blood donation also increased significantly. Additionally, the knowledge rate of non-remunerated blood donation among different age groups increased significantly after precision training. In conclusion, precision training has a positive impact on blood donation during public health emergencies and can help alleviate blood shortage crises.
Characteristics, application fields, and future development and challenges of shock absorbers
Authors: Wang Jue
Published: January 2024

Vibrations potentially damage equipment and mechanical structures. To mitigate this potential harm, it is necessary to implement specialized vibration-damping equipment, engineering controls to minimize the transmission of vibrations, and the wearing of appropriate personal protective gear. These measures help safeguard the safety of both equipment and personnel while ensuring their normal operation and longevity. Nowadays, shock absorbers play a crucial role in various fields, mitigating external forces such as earthquakes and wind to protect equipment, structures, and individuals from the adverse effects of vibrations. This paper reviews the historical development of shock absorbers, spanning from the earliest friction dampers to the contemporary remotely controllable variants. This paper provides an overview of fundamental principles and diverse types of shock absorbers, including hydraulic shock absorbers, pneumatic shock absorbers, and magnetorheological shock absorbers. The applications of shock absorbers have been analyzed, emphasizing their significance in daily life. In addition, this paper underscores the future prospects of shock absorbers in environmental protection, sustainability, and their evolving role in safeguarding society.
A Statistical Study Based on the Top 50 Blockchain Companies Analyzing the Current Development of Blockchain Applications
Authors: Tang Yuchen
Published: January 2024

Nowadays, because of the Bitcoin and meta universe, blockchain wins a lot of attention from both the public and researchers, more and more people have started to work hard in this new area which has led the quick updates of the latest research progress and applications. This article tries to help other researchers have a clearer understanding of the current situation of blockchain applications. Chapter One first gives the historical background of blockchain's applications. It then comes out the research on the top popular applications in the blockchain field, how they become popular, and what improvements they can have. On the one hand, it aims to help researchers and entrepreneurs understand the market distribution and blockchain application development trends. On the other hand, it provides some ideas about existing problems of blockchain applications.
Will Virtual Currency Replace Classic Money in The Future
Authors: Li Siyao
Published: January 2024

Virtual currency is not an entirely new concept. As a special type of digital currency based on internet technology, virtual currencies are believed to have the potential to change the traditional monetary system. However, its applications lack the recognition of many countries. This study aims to explore whether virtual currencies can replace traditional currencies in order to provide theoretical support for the development and application of cryptocurrency. This article first reviews the characteristics of virtual currencies, and analyzes their comparison with traditional currencies in terms of value -formation mechanisms, levels of risk and the direction of currency circulation. Then, it discusses the impact of virtual currencies on monetary policy, including weakening the effectiveness of monetary policy and reducing the accuracy of currency indicators. Finally, measures and suggestions for regulating the issuance and development of virtual currencies are proposed. The study finally finds that virtual currency has both merits and demerits and that it may have some negative effect on classic money. Through in-depth analysis and research on virtual currencies, this article believes that virtual currencies have the potential to replace traditional currencies to a certain extent, but a comprehensive replacement is impossible.
Research On Supermarket Replenishment Decision Based on ARIMA Time Series Prediction and Combination Optimization Model
Authors: Fang Peng , Duan Xutao , Li Chengyuan
Published: January 2024

In order to maximize the daily profit of supermarkets, it is necessary to predict the sales volume of each category of vegetables in advance during replenishment to determine the variable cost of replenishment volume. This article uses the ARIMA time series prediction model and a nonlinear programming model with penalty functions to provide a combination optimization decision-making method. Under constraints such as supermarket space constraints and dish richness, it effectively solves the problem of specific daily replenishment total and maximum total profit per day for different products in supermarkets, as well as the problem of maximizing supermarket revenue.
The Executive Wage Disparity and Corporate Performance
Authors: Qiao Nannan
Published: January 2024

The connection between executive salary disparity and corporate yield has garnered a lot of attention since the continuous development of China's economic marketization, and some researchers have found a variety of economic consequence theories on the relationship between the two, however, there is still a lack of unified explanation between different theories. Therefore, by summarizing the three different theories on economic consequences in the existing stydies, this paper analyses the differences in their contradictory points, and accordingly explores the connection between the executive pay disparity and company success. The analysis finds that the "inverted U-shaped" theory is more supported from the point of overcoming the contradictions, i.e., the tournament theory and the behavioural theory have different scopes of application, so that both positive and adverse correlations between the executive wage difference and business performance exist, and the application of which should focus on the important moderating and intermediary variables in the relationship between the two to determine what stage it belongs to. This is a reminder that pay formulators need to work closely with the characteristics of the company to develop the pay gap that best suits them.
Short-term Passenger Flow Prediction for Hangzhou Metro based on Machine Learning Algorithms
Authors: Li Zhiyu
Published: January 2024

Subways have now reached an irreplaceable position in urban rail transportation. The aggregation of people choosing subway travel at the same time can easily lead to passenger congestion, so predicting passenger flow in advance is crucial. This study used LSTM (Long Short-Term Memory) as the data prediction model to forecast the card-swiping data of the Hangzhou subway for 10 consecutive days. The historical data was divided into intervals of 3 minutes, and the random forest was used to compare the correlation among features. The final prediction results showed that both the inbound and outbound flows exhibited a bimodal pattern on weekdays, while on holidays, the prediction results showed a bimodal pattern. Furthermore, by adjusting the parameters appropriately, the simulated trends closely matched the actual values, indicating the applicability of LSTM in simulating short-term passenger flow. Accurate prediction of passenger flow can enable more comprehensive management of the subway system and provide passengers with a higher-quality service experience and travel options.
Preface: 4th International Conference on Economic Development and Management Science (EDMS 2023)
Authors: Gallup Eleanore , Li Guopeng
Published: January 2024

2023 4th International Conference on Economic Development and Management Science (EDMS 2023) was held during November 18-19, 2023 at Cairo, Egypt. This conference aims to provide a platform for researchers and engineers to share their ideas, recent developments and successful practices in economic development, electronic commerce, financial investment, real estate, global business, and management science. The participants of the conference were from almost every part of the world, with background of either academia or industry, even well-known enterprise. The success and prosperity of the conference is reflected high level of the papers received.
The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. This book covers 2 chapters: 1. Economic Development; 2. Management Science. We would like to acknowledge all of those who supported EDMS 2023. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the Technical Program Committee for their valuable advices in the organization and helpful peer review of the papers.
Organizing Committee of EDMS
Cairo, Egypt
Prediction Of Vegetable Commodity Pricing Based on Machine Learning Algorithms
Authors: Yang Xiaoyu , Liu Zixuan
Published: January 2024

This paper is dedicated to improving the profit of vegetable category goods in superstores and optimizing how to make efficient pricing strategy for vegetable category so as to maximize the revenue of superstores. Therefore, a pricing strategy model based on genetic algorithm for vegetable category goods is proposed. First, we analyze and calculate the Pearson correlation of sales volume between categories, and obtain the positive correlation of leafy and cauliflower categories and the negative correlation of aquatic root and eggplant categories. Then, the cost, price and profit margin of each vegetable category are calculated in a weighted way, and Spearman's correlation coefficient is applied to reveal the relationship between total sales volume and cost. At the same time, we find out the linear relationship between the total sales volume and the weighted sales price of vegetable commodities, and finally, with the total profit as the objective function and the linear regression equation between the total sales volume and the weighted sales price of vegetable commodities as the constraints, we use genetic algorithms to search for the optimum, find out the sales price and sales volume under the maximal profit, and then realize the formulation of the pricing strategy for vegetable commodities.
Effect Of Magnetic Field on The Resistance of Magnetic Materials
Authors: Liu Jiangchuan
Published: January 2024

The effect of magnetic field on the resistance of magnetic materials is a topic of great interest in physics and engineering. Magnetic materials are those that exhibit magnetism. The resistance of a material is a measure of how much it opposes the flow of electric current. The resistance of a material can be influenced by various factors include external magnetic fields. The article will explore how magnetic fields affect the resistance of different types of magnetic materials, also what are the applications and explanation of this phenomenon. One of the methods to study the effect of magnetic field on the resistance of magnetic materials is to use Young’s modulus measurement device. This device is also known as a tensile tester or a universal testing machine. In this essay, it will include the review the theory of the effect of magnetic field on the resistance of magnetic materials using Young’s modulus measurement device. Article will also contain the advantages and limitations of this method. At the end of the essay, it will have the discussion of the future of magnetic material resistance measurement technology and more application.