bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of mathematical model in the field of financial investment
Authors: Liu Ruyun
Published: July 2024

With the vigorous development of the international financial industry, more and more new financial products and investment strategies have emerged. Mathematical models with their rigorous logic and accuracy, through in-depth analysis of various data in the financial market, can reveal the laws hidden behind the data and help investors make more intelligent decisions. The wide application of mathematical models not only enriches the theoretical system of finance, but also plays an important role in the actual financial market. It is increasingly recognized that the study of mathematical model has become a key technology in the study of finance, and has played a positive role in promoting the stability and development of financial market. This paper will analyze the classical mathematical model and its application in the field of financial investment.
The Impact of Global Digital Trade Governance on Multinational Corporations
Authors: Yu Yinglin
Published: July 2024

With the strengthening of global digital trend, digital trade has become a crucial part of international business. By integrating the theoretical framework of global digital trade governance with the practical operations of multinational corporations, we can more accurately grasp the actual effects of digital trade governance and how these effects specifically act on the business strategies, market layout, and operating models of multinational corporations. This paper delves into the compliance challenges, business opportunities, and innovation drivers faced by multinational corporations in the context of digital trade governance, and analyzes core issues such as network security and corporate social responsibility in detail. The research results show that digital trade governance has multi-dimensional impacts on multinational corporations. To cope with these impacts, multinational corporations need to build a comprehensive compliance system to address the diversity of regulations and inconsistent standards while seizing the business opportunities brought about by digital trade governance to promote globalization and technological innovation. However, this also brings new challenges such as network security risks and uncertainties in trade policy, requiring companies to strengthen network security protection and closely monitor changes in trade policies. This paper reveals the impact of digital trade governance on multinational corporations, providing strategies and suggestions for enterprises to ensure they maintain a leading position in global digital trade.
The application and development of CRISPR Cas9
Authors: Wang Jingyi
Published: July 2024

This comprehensive review paper thoroughly explores the developmental background, basic principles, application examples, and the current challenges and ethical issues associated with CRISPR-Cas9 technology, and provides an in-depth forecast and outlook on its future directions. Originating from a natural immune mechanism in bacteria, CRISPR-Cas9 technology can precisely identify and cut targeted DNA sequences to achieve gene editing. Characterized by its ease of operation, low cost, and high efficiency, it has been widely applied in biological research, medical treatment, agricultural improvement, and other areas, bringing an unprecedented ability to transform life. This paper extensively introduces various application examples of CRISPR-Cas9 technology, including but not limited to the study of gene functions, treatment of genetic diseases, development of antiviral therapies, and enhancement of crop traits. These applications showcase the enormous potential of CRISPR-Cas9 technology in driving scientific advancement and solving practical problems. However, with the widespread application of the technology, a series of challenges and ethical concerns have arisen. The paper delves into issues such as potential off-target effects of gene editing, ecological risks associated with gene drives, and the ethical boundaries of human embryonic gene editing. The paper anticipates the future development of CRISPR-Cas9, suggesting that with a deeper understanding and continuous refinement of the technology, it may play an even greater role in precision medicine, biopharmaceuticals, bioenergy, and other fields [1].
Construction of core literacy index system for tennis majors in sports colleges and universities in China
Authors: Zhang Hao
Published: July 2024

The study aimed to index core literacies of tennis major students in sports colleges and universities in China using the quantitative methods of research. With perspectives from teacher-respondents and tennis major students, the researcher through review of literature and studies identified three (3) categories of literacies of tennis majors inclusive of healthy behavior, sport ability and sport morality. The indicators of these literacies were assessed by both groups of respondents. In the analysis of the collected data, results revealed that both groups assessed the core literacies positively showing no significant difference in their rating. Such result further showed that the respondents relatively exhibit positive valuation of the core literacies. It was further revealed in the data that there are significant relationships identified among the core literacies included in the study. With these results, the research concluded of the significance of traditional skills and cultural heritage in training for tennis as sport and provide for indexes on the core literacies included in the study.
Research on the issues of digital currency from the perspective of international tax system
Authors: Ran Xiangdong , Jin Tianhao
Published: July 2024

Unlike traditional currencies, the international taxation of digital currencies has unique characteristics. This article takes digital currency as the research object and examines its development trend from the perspective of international taxation. In summary, digital currency is of great research significance because of its unique characteristics, which are different from other currencies in the conventional sense. Because of sorting out the experience of relevant foreign countries in regulating digital currency, this article analyzes that digital currency has caused problems such as tax evasion facilitation, excessive taxation, and technical or political barriers under the current international tax system. It is urgent to improve relevant legislation and strengthen departments. Only through inter-regional supervision and international exchanges and cooperation can we finally respond.
Learning Goal Formulation Strategies in the Teaching-learning-assessment Alignment
Authors: Liu Mengxia , Yun Hong
Published: July 2024

The new curriculum standard proposes integrating teaching and evaluation to promote the realization of the education function. Teaching-learning-evaluation integration involves the integration of teacher teaching, student learning, and assessment effect, with shared learning objectives playing a core role within this framework. These objectives are derived from curriculum standards, teaching materials, and the learning situation and are matched with the actual learning situation to ensure the depth and effectiveness of learning. A dynamic adjustment mechanism for learning objectives is crucial in achieving classroom integration, with timely adjustments made according to students' learning progress and needs to enhance the educational process's flexibility and adaptability.
Overview of Improvement Methods for Three Evaluation Indicators of Path Planning A * Algorithm
Authors: Li Xiwen
Published: July 2024

In the era of rapid development of industrial automation in the 21st century, robots are currently the focus of global technological development. The efficiency and safety of robot work are indicators that people evaluate their work, and most robots need to move during work, so it is necessary to study the problem of robot movement. The key to robot movement problem is route planning, and the research topic of this article is three improvement methods according to the conventional A * algorithm. This article first introduces the conventional A * algorithm, and then analyzes three evaluation indicators of path search time, amount of turning points, and turning flatness of the traditional A * algorithm. It is found that these indicators are the main factors affecting the efficiency of car search. Thus, several typical improvement methods were demonstrated, such as dynamically adjusting the cost estimation function method, dynamically adjusting the search domain method, and geometric optimization method. After mathematical modeling and formula analysis of these three methods, this article concludes that the traditional A * algorithm is not suitable for working in actual working conditions with randomly distributed obstacles. After improving the above methods, the improved A * algorithm has significant implications for path search efficiency and safety.
Potential Application of Mediterranean Diet and DASH Diet and Plant-Based Diet in Solving the Problem of Hypertension in Women
Authors: Liu Yuan
Published: July 2024

The food industry is thriving due to economic prosperity. People's food requirements have expanded beyond mere sustenance to include a desire for diversity. However, long-term pressure from heavy work or family responsibilities may cause women to develop irregular dietary habits, leading to obesity and related health issues. As hypertension is a significant contributor to cardiovascular disease, this paper compares the advantages and disadvantages of three popular diets: the Mediterranean diet, the DASH diet, and the plant- based diet. The paper discusses the pros and cons of each diet to determine which one is more suitable for the female to prevent and alleviate hypertension symptoms. By comparing the regional, quantitative, nutritional value and public acceptance of three different diets, it is concluded that the plant-based diet which consists of fruits and vegetables in addition to nuts, seeds, whole grains, and legumes, is more suitable as a daily diet for women to alleviate hypertension symptoms.
Research on cargo volume prediction and personnel arrangement based on logistics network sorting centers
Authors: Zheng Hao
Published: July 2024

In today's increasingly competitive e-commerce logistics industry, various levels of sorting centers on the logistics chain serve as the core nodes and capillaries of the logistics network, bearing the increasingly heavy sorting and transportation functions. Therefore, using the cargo volume of sorting centers to statistically predict future cargo volume and based on this, plan personnel arrangements for each station. This significantly improves the operational efficiency and economic benefits of each station, thereby more reasonably allocating resources, improving service quality, reducing labor waste, improving employee job satisfaction, and achieving the optimization and sustainable development of the logistics industry. This article uses the cargo volume statistics data of 57 sorting centers in a logistics network to analyze the temporal changes of cargo volume at each station on different dates and different time periods on the same day. Starting from the flow of goods within the network and considering the mutual influence of goods volume between stations, machine learning is used to extract the inherent changes in various sorting centers. Regression algorithms based on time series are used to predict the future goods volume for a period. Then, based on the predicted goods volume at each station, a linear optimization is established by considering the constraints of formal and temporary workers to solve the scheduling problem, to achieve a relatively balanced number of personnel for different shifts and minimize the total number of workers and labor costs.
Analysis of the Problem of “Multi-Party Cooperation” in Solving Elderly Care and Suggestions for Elderly Care in China Under the Model of Integrated Elderly Care and Medical Services
Authors: Cai Yuxi , Chen Yifan , Jiang Jiayi
Published: July 2024

Integrated Elderly Care and Medical Services is a multi-faceted combination of medical institutions and elderly care institutions and is an important form of elderly care both domestically and internationally. In recent years, a large amount of literature has shown that research on Integrated Elderly Care and Medical Services is of great significance. This article starts from the perspective of “multi-party cooperation”, points out the development difficulties and shortcomings by listing the relevant practices of the interaction between state-owned enterprises, other related enterprises, and the government, and proposes corresponding countermeasures and suggestions for their future development from different aspects so that all parties in society can better fulfill their social responsibilities. Ultimately, it is possible to sort out and interpret the model of Integrated Elderly Care and Medical Services. The aim is to provide suggestions for improving the quality of elderly care, reducing medical costs, and achieving the long-term goal of healthy aging.
Research on User Churn Prediction of Traditional Supermarket Digital Platform
Authors: Yin Honglei , Pei Yilei
Published: July 2024

This paper uses the advantages of machine learning algorithms to conduct empirical research on classification prediction to explore the user churn prediction model of traditional supermarket digital platform. User reviews on the online platform of Wumart were used as the data source, and user information of Ehime Orange purchased was used as the research object. Starting from the two dimensions of user value characteristics and evaluation characteristics, the user's purchase information is collected, and five characteristic data such as the latest consumption time, consumption times, consumption amount, rating and review text are obtained by calculating the information. Later, a predictive model was built based on XGBoost, a machine learning algorithm, to predict the trend of user churn. By comparing and analyzing the contribution of characteristic variables in user churn prediction, the types of lost users are divided according to key characteristic variables such as average monthly consumption times and average consumption amount, and corresponding retention strategies are proposed. The validation found that the sentiment of the score and review text had a significant impact on user churn prediction. By analyzing the important variables affecting the prediction of user churn, this paper summarizes two types of churn users, and formulates corresponding retention strategies for users with less demand and no demand. This is of great significance for reducing the loss of digital platform users, maintaining old users, improving the profits of supermarkets, and achieving the goals of healthy and sustainable development of supermarkets.
Investment In Infrastructure Construction of the "Belt and Road" And Its Influencing Factors
Authors: Wang Qinyu
Published: July 2024

In 2013, after visiting Kazakhstan and Indonesia, General Secretary Xi Jinping threw a new issue to the world -- "the Belt and Road" initiative (including “the 21st-Century Maritime Silk Road” and “the Silk Road Economic Belt”, abbreviated as BRI), intending to build a new model of international relations and building a community with a shared future for mankind. Transportation infrastructure investment, as an important component of this initiative, has always been of great concern. This article introduces the basic situation of infrastructure construction since the proposal was put forward, and sorted out the reasons for China's investment in infrastructure construction of the BRI, including factors, for example, adapting to “the new normal of China's economy ,and bringing markets and resources to China; Summarize the impact on co-building countries from the perspectives of economy and trade. This paper also sorted out the factors that affect China's investment, including the improvement of labor force in countries participating the BRI, the improvement of infrastructure quality and co-build country’s system. Finally, briefly point out the current challenges and challenges faced.
The Nationalization of Western Opera in China
Authors: Jiang Ruizi
Published: July 2024

After the May Fourth Movement in 1919, Western opera, along with other Western cultures, entered China with little response. However, after a century of development, the collision and integration of these two cultures eventually led to the incorporation of traditional Chinese music elements into opera. The Chinese opera was gradually becoming an important part of Chinese music culture. How is the traditional Chinese music fused into the Chinese opera? What is the status of this music culture? This paper is going to explore the integration of traditional Chinese music elements and investigate the problems encountered in the process of nationalization of Western opera in China. Through the analysis of Chinese operatic works and the status of the musical form within its cultural context, the author concludes that the nationalization of Chinese opera is still an ongoing process.
Wearable Biosensors for Non-invasive Sweat Analysis
Authors: Cao Shuyang
Published: July 2024

Wearable biosensors, especially sweat sensors have drawn significant attention in recent years. Sweat is of importance for its wealth of biomarkers about physiological states. It is therefore utilized for health monitoring, exercise monitoring and so on. Physiological states of individuals can be analyzed through non-invasive wearable sweat biosensors. This paper introduces progress made in sweat sensing technology, including soft materials and microfluidic networks that achieved sweat collection without evaporation. Recent research improved sweat capture of rest individuals and led to robust biosensing assays involving the integration of biosensing arrays and flexible substrates. Novel non-invasive wearable sweat biosensors for the analysis of glucose, alcohol, lactate, and urea were also proposed recently, as well as a sweat sensor capable of analyzing these biomarkers simultaneously. These biosensors all had outstanding sensitivity, selectivity, and stability. While existing wearable sweat sensors have multiple challenges, the future of non-invasive sweat sensing is still promising.
Use a Brain-Computer Interface to Treat Depression
Authors: Li Qiguang
Published: July 2024

Brain-computer interface to treat depression is a very important new therapy that is highly effective without side effects. Depression is an growing mental health problem that affects the quality of life of hundreds of millions of people worldwide. Traditional treatments for depression, such as medication and psychotherapy, although effective to some extent, are accompanied by a range of side effects and limitations. In recent years, the brain-computer interface (BCI), as an emerging treatment method, has brought unprecedented hope for patients with depression. This article will explore in depth the mechanisms and methods of BCI treatment for depression and the advantages over conventional therapies. Compared with traditional depression therapy, treating depression with brain-computer interface has the advantage of noninvasive, painless and no side effects. The three main treatments for depression include transcranial direct current stimulation, transcranial alternating current stimulation, and transcranial magnetic stimulation. This paper explores the therapeutic mechanism and basic treatment of the three methods, comparing their advantages and disadvantages with those of conventional drugs. Overall, transcranial direct current stimulation, rTMS, and transcranial AC stimulation are all highly efficient and non-side-effective BCI treatments for depression.
Analysis Of Deep Learning-Based Visual Perception Technology for Picking Robots
Authors: Jiang Xinyue , Zeng Hao
Published: July 2024

With global population growth and rising labor costs, the development of agricultural picking robots is crucial to improving agricultural productivity and reducing costs. A combination of deep learning technology and traditional vision technology has revolutionized the visual perception capability of agricultural picking robots. This has enabled robots to achieve more accurate fruit identification and localization in complex environments. In this paper, we review the visual perception technology of picking robots based on deep learning, which is primarily divided into two core technologies for fruit recognition and 3D reconstruction and localization during fruit picking. Firstly, we analyze the application of deep learning models in fruit recognition. We discuss how to integrate and process the feature information of fruits through deep learning neural networks to improve recognition accuracy and review the development of more typical deep learning models in the past three years. Secondly, we discuss the advantages and disadvantages of several types of traditional stereo vision technology. We synthesize the advantages and disadvantages of several types of current stereo vision technology that are more widely used. We also analyze how deep learning technology has optimized the model and combined it with traditional stereo vision technology in recent years to achieve the three-dimensional reconstruction and precise positioning of fruits. Finally, we summarize the main challenges of current picking robots, mainly the accuracy of the deep learning network, the difficulty of acquiring and calibrating the original image set, and the generality of the models carried by the picking robots. Additionally, we look forward to the future development direction.
Cancer Treatment Response Differences in Pediatric and Adult Cancers
Authors: Huang Ruoxun
Published: July 2024

There are significant differences between childhood and adult cancers in a number of ways, including causes, treatments, and response to treatment. Childhood cancers are often associated with factors such as germline predisposition, genetic mutations, viral infections, and exposure to toxic substances. In contrast, adult cancers may be more influenced by factors such as family history, long-term exposure to radiation, and poor lifestyle habits. Although both childhood and adult cancers may be treated with chemotherapy, radiotherapy, and immunotherapy, treatment for children requires special attention to dose optimization and minimization of long-term side effects. In addition, the treatment of pediatric cancers presents some special challenges. The relatively low incidence of childhood cancers, the large tumor heterogeneity, and the fact that the needs and responses of each child may be different have led to relatively slow progress in pediatric oncology research. At the same time, due to the immature functioning of body systems in children during development, treatment requires more careful consideration of various possible side effects and implications. Therefore, this article first analyzes the differences in the causes of cancer between children and adults, then, explores the differences in cancer treatment between the two, and finally, emphasizes the need for collaborative efforts to address these challenges, improve access to care, and increase survival rates for pediatric patients with cancer.
Application Of Gene Detection Technology in Diagnosis and Dreatment of Chronic Diseases
Authors: Zhang Tianyao
Published: July 2024

This study uses the method of literature review and case analysis to sort out and evaluate the relevant literature, and discusses the specific application of gene detection technology in the diagnosis, treatment and prevention of chronic diseases combined with actual cases. By analyzing the application of gene detection technology in the field of chronic diseases, the role of gene detection technology in early diagnosis, personalized treatment and prevention strategy is discussed. The results show that the gene detection technology has a broad application prospect in the diagnosis and treatment of chronic diseases, which is of great significance to improve the diagnosis and treatment efficiency and the level of personalized medicine, and provides a useful reference for clinicians and researchers.
Research on Information Security Management and Protection Measures of Financial Enterprises in the Era of Big Data---Take the USA of Industrial and Commercial Bank of China
Authors: Sun Chuhan
Published: July 2024

The Internet is changing the way people live all the time. With the development of the country’s information technology, the transmission and sharing of data information is more and more convenient, which has completely changed the way people live, work, and study. In the era of big data, data has become an important element of enterprise development, and those who have mastered the data have the key conditions for development. But at the same time, information security has become a common concern. Especially for banks in the digital era, the information security of banks will face many security risks. Suppose the information security management system of the bank is not perfect. In that case, the leakage and loss of important information and data will cause very serious consequences and even bring greater risks to the bank’s operation and management. Therefore, the protection of information security is particularly important. In view of this, this topic will take the USA of Industrial and Commercial Bank of China (ICBC, USA) as a case study to study its information security management and protection.
Analysis Of Deep Learning-Based Anti-Jamming Method for UAV Communication
Authors: Yang Shuhan
Published: July 2024

With the increasing popularity of Unmanned Aerial Vehicle(UAV) in both military and civilian applications , it is crucial to ensure the reliability and safety of their signals. In recent years, deep reinforcement learning has proven to be a powerful tool for meeting this challenge. This paper aims to analyze the potential of deep learning in signal jamming countermeasures for UAV communication systems. Traditional jamming countermeasures, such as frequency hopping and Direct Sequence Spread Spectrum (DSSS), are effective to a certain extent. Still, it is difficult to cope with dynamically changing jamming environments due to single mode and low spectrum utilization. On the other hand, deep learning has powerful automatic feature extraction and pattern recognition capabilities, especially the reinforcement learning method based on deep learning, which can realize real-time adaptation of UAVs to environmental changes and automatic optimization of communication strategies. The article focuses on anti-jamming methods based on reinforcement learning and deep reinforcement learning algorithms and proposes a new anti-jamming strategy for UAV communication based on generative adversarial networks (GANs). Although the deep learning method opens up a new way for anti-jamming of UAV communication signals, it still faces the challenges of high demand for computational resources and complex model training in practical applications.
Research on the Formation of Children's Personality
Authors: Wu Shu
Published: July 2024

This paper aims to explore the diverse reasons and influencing factors behind the formation of children's personality, delving into the significant roles played by genetic factors, environmental influences, and the process of socialization in children's personality development. Firstly, by analyzing genetic theories, it reveals the potential influence of genes on the formation of children's personality and explores the complex interaction between genes and the environment. Secondly, it analyzes the shaping role of environmental factors on children's personality from various perspectives such as family, society, and culture, including parenting styles, school environment, peer relationships, and media influences. Lastly, from the perspective of socialization theory, it delves into the impact mechanism of the socialization process on the formation of children's personality, emphasizing the close connection between children's self-identity, emotional regulation, behavioral expression, and socialization. Through comprehensive analysis, it is found that the formation of children's personality is a complex process influenced by multiple factors, involving the integrated effects of genetics, environment, and socialization. Future research should further explore the interactions between different factors and how to better promote healthy development of children's personality.
Research And Strategic Analysis of Project Client Selection Based on Client Assessment System
Authors: Zheng Jianshu , Wang Weihan , Jinqiu Zhang
Published: July 2024

The aim of this study is to select the most suitable clients for the project by establishing a client assessment system, and to conduct a comprehensive assessment and future relevance analysis of the clients through the RSR assessment model and the Granger causality analysis model. First, by analyzing the project conditions and predicted clients, the conditions required for the project were listed, and the performance of past clients on each of the assessment factors was captured and comprehensively evaluated in order to select the highest rated clients. Second, the specific interests and resources of the client were analyzed by analyzing their reports and publicity. Finally, the high correlation with clients is demonstrated by analyzing the program-related factors in the case of China, and the Granger causality test shows a high Granger causality, suggesting that the program is appropriate for the selected clients in the present and the future. In addition, the establishment of a client assessment system, the application of the client ranking and RSR assessment model, and the related strategies against illegal wildlife trade and the findings of the Granger causality analysis are discussed.
Identity, Emotions, and Death: Interpreting Letter from an Woman from the Perspective of Biographical Criticism
Authors: Lang Cuo
Published: July 2024

Stephen Zweig's Letter from an Woman focuses on a long letter sent by a woman to unfold the story plot. Death is the prominent theme of the work, and highlighting the psychological activities of the characters is the author's realistic writing style. This work is set against the backdrop of the Nazi regime in 20th century Europe, and through imaginative reconstruction, it shapes the author's identity embodiment, emotional projection, and the world of yesterday; Completed the dialectical relationship between the author and oneself, with the group, with history and the era, between reality and illusion. This plays a role in rediscovering the author's subjectivity in biographical literature, providing valuable examples for its further development in the process of transformation.
The Analysis of Drone Track Planning Based on Machine-visual.
Authors: Zhong Qi
Published: July 2024

With the proliferation of drones, there has been a surge in demand for highly efficient navigation systems. This article delves deep into the evolution of machine vision-based drone trajectory planning to meet this demand. By harnessing machine vision technology, including visual SLAM, three-dimensional vision, depth cameras, convolutional neural networks, and other methods, drones have significantly enhanced their operational capabilities in complex environments. Through case studies, this article illustrates how machine vision technology optimizes trajectory planning by facilitating obstacle detection, target recognition, and tracking. Furthermore, it underscores the challenges posed by computing resource constraints, deep learning model training, and optimization. Addressing these challenges is crucial for the continued advancement of machine vision-based navigation systems for drones. Additionally, the article proposes future research directions such as improving environmental perception, integrating multiple sensors, and optimizing algorithms and hardware to further enhance drone navigation systems. By exploring these avenues, researchers can pave the way for more efficient, reliable, and adaptable drone navigation systems capable of operating seamlessly in diverse environments and scenarios.
Research of Wearable Triboelectric Nanogenerator for Powering and Monitoring Movements
Authors: Xu Nuoqian
Published: July 2024

Precise tracking of physical activity and sleep habits is essential for evaluating people's health, particularly in relation to upholding a healthy lifestyle, identifying illnesses early, and providing medical care. A novel technique for gathering energy is the Triboelectric Nanogenerator (TENG) characterized by high efficiency, low cost and low energy consumption, which is famous as a novel and efficient electric energy harvesting technology under different condition. This essay suggests a design that uses TENG technology to generate energy for wearable biosensor which can monitor the health condition. Subsequently, the advantages, usage and method of applications are introduced in this review. For example, TENG can be worn on different place on bodies like ankles, arms, feet, chests etc to get body system health condition monitored. Also, the essential material of the product is important. TENGs can deal with the inconvenient problem with independent energy generator using triboelectric textiles (TETs). Triboelectric textiles are synthetic materials which are thought as a unique source of energy that harvests energy from human motion. Finally, the essay suggests the working principle. Charge transfer occurs between the skin and the triboelectric textile. Electric charge transfer occurs between skin and triboelectric textiles due to the triboelectric effect.
A study on the Ecosystem of the Lampreys Based on Lotka-Volterra Modeling
Authors: Cao Yisen , Li Zihao , Ma Xiaoyi
Published: July 2024

This study provides insights into the ecosystem impacts of adaptive sex ratio variation in lampreys through mathematical and ecological modeling. The predator-prey relationship between prey, lampreys and indigenous populations was simulated using the Lotka-Volterra model, revealing the effect of increasing male sex ratio on the significant increase in prey population size and the variation in the three population cycles. The model was further linearized to determine the stability of the ecosystem under different sex ratios by calculating Jacobi matrices and eigenvalues and found that the ecosystem tends to be stable when the male ratio is within a specific range. Analysis of the model with the addition of parasites showed that an increase in male ratio promotes an increase in prey population size, has a smaller effect on competitors, and slightly reduces parasite numbers. These findings provide an important reference for understanding the effects of adaptive sex ratio variation on ecosystems and population interactions.
Application Research Based on Finite Difference Algorithm
Authors: Tong Ruojing , Qian Xinyu , Xiang Xinlan
Published: July 2024

This paper discusses the importance of finite difference algorithms in the field of science and engineering and focuses on methods for both optimization of algorithm efficiency and numerical stability improvement. For algorithm efficiency, optimization methods such as parallel computing techniques, optimized mesh partitioning, selection of appropriate difference formats, adaptive mesh methods, use of high-performance computing platforms, and pre-processing and post-processing techniques are introduced. And for numerical stability, methods to improve the numerical stability of the algorithm are discussed. Through these optimization and improvement methods, the finite difference algorithm can respond to the challenges of complex problems more efficiently and reliably, and provide a more reliable and efficient numerical computation method for scientific research and engineering practice.
Research on High-Precision Positioning Technology for Deep-Sea Submersibles Based on Kalman Filtering
Authors: Huang Weidan
Published: July 2024

As an important tool for deep-sea missions, the position precision of the submersible is directly related to the success of the mission and the safety of deep-sea operations. High-precision positioning technology is urgently needed for deep-sea exploration to cope with the challenges of complex ocean currents, uneven seawater density and complex topography. Based on the Kalman filter method and fitting algorithm, a prediction model of submersible position in deep sea is established considering whether the submersible can keep communication with the main ship or not. In order to make the prediction model more convenient to use and more accurate. In this paper, the 3D coordinate system used in the prediction model is given, and the force acting on the submersible is analyzed. In addition, this paper also gives the uncertainty factors that affect the prediction model, and proposes that special equipment can be added to the submersible to reduce the interference of uncertainty factors.
study of caring behaviors in the classroom of higher education teachers
Authors: Wang Yifan
Published: July 2024

This study uses interview method, observation method and questionnaire method to study the caring behavior of teachers in colleges and universities. The study randomly distributes questionnaires, interviews students of different majors and interviews and observes teachers of a college in Jilin Province to conduct the study and draw conclusions. The study found that some teachers' caring behavior in the classroom is insufficient and lack of attention to students' wishes and students' acceptance, and analyzed the main reasons from the three aspects of teachers, students and the environment. Finally, three strategies are proposed to deal with the above situation: (1). improve teachers' understanding of caring and strengthen the relationship between teachers and students; (2). innovate the form of education and teaching to improve the attractiveness of the classroom; (3). establish a fair educational evaluation mechanism to promote the fairness of caring.
A Study of the Relationship Between Monetary Policies and Financial Crises
Authors: Wu Keyu
Published: July 2024

In the process of the financial crisis evolving into a global crisis, the Federal Reserve has diligently applied the lessons gleaned from historical financial upheavals, including the Great Depression of 1929, the Stagflation Crisis of 1970, and the Subprime Crisis of 2008. Through a proactive approach to crisis management via monetary policy, the Federal Reserve has endeavored to mitigate the impact of such crises. This paper conducts a comprehensive analysis, drawing upon a brief retrospective examination of relevant literature and historical experiences in monetary policy during crisis periods. It delves into the operational strategies employed by the Federal Reserve Bank to respond to crises, along with the development of novel monetary policy instruments aimed at sustaining liquidity within the financial system. Additionally, the paper explores the dynamics of international monetary policy cooperation amidst crises. Ultimately, within the framework of heightened economic globalization, it underscores the imperative for central banks to wield monetary policy with precision in addressing financial crises.
Research on Insurance Cost Prediction Model Based on Linear Regression
Authors: Liu Xinyang , Wang Siyu , Fang Xu , Zhang Senyao , Lin Bohan
Published: July 2024

The insurance industry is experiencing a crisis due to the frequent occurrence of extreme weather worldwide, resulting in significant losses across all sectors. This paper aims to mitigate the impact of extreme weather on the insurance industry by using Harbin and Haikou as case studies. The study employs linear regression (least square method) and Pearson correlation coefficient analysis to simulate the insurance cost of the two cities over the next ten years. The results offer insights into the potential profits and losses of insurance costs during different periods. Additionally, this section presents the management mode of urban insurance companies, taking into account local conditions. The model method responds to national policies, but further data is required to support in-depth research and improvement.
Advancements and Integration of CMOS Phase Detectors in Modern Communication Systems and Imaging Technologies
Authors: Yao Jinchen
Published: July 2024

CMOS phase detectors play a crucial role in generating high-precision clocks, synchronizing data communication, and enabling autofocus systems in imaging. These devices can measure and adjust the phase of signals with remarkable accuracy, thereby ensuring signal stability and optimizing system performance. With the increasing complexity of communication systems, designers have focused on developing phase detectors capable of handling various communication standards and modes. This article will first explore the recent advancements in CMOS phase detector designs. It will then investigate the innovative approaches to integrating CMOS phase detectors with other components. Lastly, it will showcase the novel applications of CMOS phase detectors in Phase-Locked Loops (PLLs). The research presented in this article is expected to contribute significantly to the study and application of CMOS phase detectors in the fields of communication systems and integrated circuits, providing valuable insights for future developments.
Health Monitoring Based on Bone Conduction Headphones
Authors: An Xu
Published: July 2024

With the continuous expansion of the headphone market size, headphones have already been combined with other functions, such as health monitoring and massage. In existing technology, air conduction headphones have already been linked with biosensors as a kind of in-ear device to monitor health. However, there are some problems when using this kind of headphones. There will be many discomforts when wearing this headphone for a long time. What is more, detected data will not be higher than out-ear device. Therefore, bone conduction headphones are proposed to be combined with biosensors for health monitoring for more comforts and higher accuracy. This article mainly compares existing device (in-ear device) with imagined device to verify the rationality of using bone conduction headphones. In addition, the principles of biosensors and anatomical mechanism are listed aiming to illustrate why there is more accurate data when using bone conduction headphones for health monitoring. A new kind of algorithm used for signal processing is also listed for eliminating external noise. Finally, a kind of bone conduction headphone which is combined with biosensors to monitor health is proposed. At the same time, the schematic diagram of sensor system that is composed of integrated sensor and integrated circuit is given. Then, the application scenario of this device is discussed and this headphone is advised to be applied in medical field and long-time monitoring field. Eventually, the perspective of materials is discussed to further improve the accuracy and comfort in the future.
Preface: 3rd International Conference on Education Technology, Economic Management and Social Sciences (ETEMSS 2024)
Authors: Clapham Annabelle , Zheng Zihan
Published: July 2024

The 2024 3rd International Conference on Education Technology, Economic Management and Social Sciences (ETEMSS 2024) was held in Amsterdam, Netherlands during June 01-02, 2024. This conference aims to bring together researchers, scientists, engineers, and scholar students to exchange and share their experiences, new ideas, and research results about all aspects of education technology, psychological science, economic management, cultural studies, and social sciences, and discuss the practical challenges encountered and the solutions adopted.
ETEMSS 2024 will bring you an unexpected harvest. The conference program covered invited, oral, and poster presentations from scientists working in similar areas to establish platforms for collaborative research projects. This conference provided delegates with a good opportunity to exchange new ideas, establish research and/or business contacts, and establish potential partnerships for global partnerships. We hope that the outcome of this conference will lead to significant contributions towards creation of new knowledge.
Scientific Committee of ETEMSS
Amsterdam, Netherlands
Employment Willingness and Suggestions for Normal College Students in the Post-pandemic Era
Authors: Li Siyao , Wang Jixian , Huang Saiqiong , Yu Haoxuan , Li Chuanming
Published: July 2024

This article aims to investigate the employment willingness of normal school students through questionnaires and interviews. Focusing on the school and the students, it explores methods to enhance the employment management level of normal school graduates, thereby helping the school achieve the strategic goal of stable employment for graduates. The research results show that the employment willingness of normal school students is strong, accompanied by anxiety. Their employment willingness is influenced by various factors, exhibiting instability, with competitive pressure being the primary influencing factor during the employment process. Moreover, the employment willingness is closely related to the school's employment courses and employment management services. In conclusion, the employment willingness of normal school students in the post-pandemic era is characterized by strong desire and instability. Formulating corresponding recommendations and measures for their employment willingness is of great significance for the school's employment management work in the post-pandemic era, and provides a certain reference value for employment research and practice at normal schools in the region.
Research On Software Performance Optimization Strategy Based on Machine Learning
Authors: Mao Ning
Published: July 2024

This paper discusses the core content and practical application of designing software performance optimization strategies based on machine learning. The paper also covers the collection and processing of performance data, as well as feature extraction and selection, which provide a solid foundation for training machine learning models. It emphasizes the importance of model selection and training, and outlines the key steps for constructing an optimal decision model. The practical application case demonstrates that a machine learning-based performance optimization strategy can effectively enhance the operational efficiency and stability of software systems, thereby improving the user experience. Additionally, the challenges of data quality and model stability that may arise in practical machine learning applications are also highlighted. In the future, as technology continues to advance, the potential applications of machine learning in software performance optimization will expand.