bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Complex Data Mining Analysis and Pattern Recognition Based on Deep Learning
Authors: Lian Jieting , Chen Taiying
Published: June 2024

This paper systematically investigates and discusses the application of deep learning in complex data mining analysis and pattern recognition. Firstly, it introduces the basic concepts of deep learning and commonly used models, including artificial neural networks, convolutional neural networks, and recurrent neural networks. Then, it elaborates on the application methods and techniques of deep learning in mining different types of complex data (such as images, text, time series, etc.), and explores the latest research progress in the field of pattern recognition. Furthermore, it analyzes the challenges faced by deep learning in practical applications, such as data scarcity and model generalization capabilities, and proposes future development trends and research directions. Finally, it summarizes the research content and significance of this paper, emphasizing the importance and application prospects of deep learning in the field of complex data mining and pattern recognition.
Face Age Prediction Based on Machine Learning
Authors: Hu Yuting
Published: June 2024

Age recognition, an essential attribute of human identity, plays a pivotal role in various social and medical applications. Due to the influences of photography equipment, lighting, and angles, age recognition based on facial images has always been a challenging topic. Fortunately, with the development of machine learning, especially the breakthroughs achieved by neural network models in image-related fields, researchers have applied machine learning to age recognition. From the perspective of research methodologies, age prediction can be regarded as either a regression or classification task. Therefore, this article analyzes from both regression and classification perspectives. Firstly, it introduces the commonly used datasets in the field of facial recognition. Then, it discusses the commonly used regression models, classification models, and optimization methods in age recognition tasks. Finally, the article summarizes the entire text and proposes future research ideas, providing references for researchers in related fields.
New Era Business Administration Major Student Innovation Ability Training Model Exploration and Practice
Authors: Gao Wen , Hashinm Raemah Binti Abdullah
Published: June 2024

This article explores and practices the cultivation model of innovation ability for business administration students in the new era. It first analyzes the development trends of business administration major in the new era, the importance of innovation ability in the major, and the basic composition of the cultivation model of innovation ability. It points out the existing problems in current business administration education, such as the disconnection between curriculum setting and actual needs, the lack of practical teaching links, and the mismatch between individual differences of students and the cultivation model. In response to these issues, this article proposes optimization strategies, including the construction of an innovation ability-oriented curriculum system, the strengthening of practical teaching, and the focus on the individual development of students. It summarizes the research findings and provides insights for the cultivation of innovative business administration professionals in the future.
Comparative Evaluation, Challenges, and Diverse Applications of Multi-Armed Bandit Algorithms
Authors: Han Yunmeng
Published: June 2024

This manuscript offers an exhaustive comparative study of key Multi-Armed Bandits (MAB) algorithms, exploring their challenges, potential resolutions, and varied applications in today's context. It concentrates on at least three principal algorithms: the Upper Confidence Bound (UCB), Thompson Sampling, and ε-greedy. The analysis critically assesses their performance, focusing on convergence rate, precision, and computational demands. Key challenges in non-static environments and large-scale deployments are identified, including the complexities of multi-objective optimization. The paper proposes innovative solutions such as adaptive algorithmic approaches and the integration of parallel computing frameworks to address these challenges. It further delves into a range of application domains, from online advertising and recommendation systems to clinical trial methodologies, drawing comparisons between traditional and novel applications. The discussion also encompasses critical issues like data scarcity, cold start problems, ethical considerations in algorithm design, and the intricacies of processing real-time data. In its concluding sections, the study sheds light on recent successful deployments of MAB algorithms, identifying core factors contributing to their effectiveness and forecasting future developmental trajectories. This comprehensive analysis provides a detailed overview of the MAB field, highlighting its significance and practical impact in various sectors.
Revealing the Close Connection Between Tennis Match Momentum and Victory Through Machine Learning Methods
Authors: Yu Guolin , Wang Xinyu , Dong Bohan
Published: June 2024

In competitive sports, especially in tennis matches, momentum is considered a key factor influencing the outcome. However, there is widespread controversy surrounding the definition of momentum, its quantification methods, and its impact on match results. We compared different models (LightGBM, SVM, XGBoost, MLP, logistic regression) using five-fold cross-validation to predict changes in momentum in tennis matches based on a given dataset. The results showed that LightGBM performed best with an accuracy of 77.6%. We selected LightGBM to predict the momentum score for each point of player 1 in the final match. It was found that the average momentum scores in the second, third, and fifth sets were greater than 0.5, which aligned with the actual outcomes. Furthermore, through Pearson correlation analysis and OLS validation of the relationship between momentum changes and match results, we obtained a p-value below 0.05, a Pearson correlation coefficient of 0.59, and an F-statistic of 376.6 in the OLS model, indicating a strong positive correlation between the two.
The Progress in the Occurrence and Treatment of NLRP3 Inflammasome in Bone and Joint Diseases
Authors: Duan Kunsheng
Published: June 2024

Inflammasomes play a pivotal role in the innate immune system, which regulates the activation and expression of inflammatory factors, has a profound impact on the occurrence and expression of various inflammatory diseases. In recent years, studies have demonstrated that the NLRP3 inflammasome is closely associated with many fields, such as cardiovascular diseases, metabolic disorders, and chronic diseases. Moreover, inflammatory diseases of bone and joints, which are more prevalent in the population, such as osteoarthritis and rheumatoid arthritis, can cause substantial damage to bone and cartilage, trigger pain and even dysfunction, and reduce the quality of life. Numerous studies have shown that the pathogenesis of multiple bone diseases and arthritic diseases, including osteoarthritis and rheumatoid arthritis, is closely associated with the NLRP3 inflammasome. Some progress has been made in the targeted treatment of the NLRP3 inflammasome, especially for small-molecule inhibitors. These inhibitors have potential therapeutic value by inhibiting the activation of the NLRP3 inflammasome, thereby reducing the inflammatory response. However, the research on the feasibility, safety, and drug metabolism of these small-molecule inhibitors in clinical application is still in the exploratory stage, and further research is urgently needed. This paper aims to review the NLRP3 inflammasome structure, function and its progress in bone-related diseases and treatment. Through this paper, we hope to improve the understanding of the NLRP3 inflammasome in the development and treatment of bone diseases, so as to provide a theoretical basis for clinical practice.
A Review of Research on The Reliability Assessment of Fresh Product Distribution Networks Considering Product Perishability Constraint
Authors: Zhang Yuanyuan
Published: June 2024

A reliable and stable distribution network is fundamental for the effective operation of fresh agricultural product logistics, and network reliability is a crucial metric for determining whether fresh agricultural product logistics can complete specified tasks promptly and smoothly. To further clarify the current research status on the reliability of fresh agricultural product distribution networks considering transportation losses, this study reviews the literature from three aspects: research on transportation losses of fresh agricultural products, reliability of stochastic distribution networks, and methods for assessing the reliability of stochastic distribution networks considering transportation losses. The studies indicate that few documents introduce both quantity deterioration and quality deterioration simultaneously into network reliability research, which tends to overlook the market demand under reduced freshness, and seldom considers the dynamic changes of deterioration factors in complex environments.
Biogeochemical Cycle of Acid Mine Drainage from Pyrite Mines and Its Environmental Impact
Authors: Zhang Zhouyuan
Published: June 2024

Acid wastewater from pyrite mines is a serious environmental pollutant, whose formation and evolution is a complex microbial ecology and biogeochemical cycle process. This paper reviews the research progress on the microbial classification and distribution, microbial diversity and abundance, biogeochemical cycle process of acid wastewater, etc., reveals the key role of microorganisms in the formation mechanism, environmental impact and utilization and treatment of acid wastewater, and provides theoretical basis and technical support for the monitoring, assessment and management of acid wastewater. The sustainable and ecological study of acid wastewater, etc., hoping to provide more scientific evidence and innovative ideas for the sustainable management and utilization of acid wastewater.
Research on the Exploration of China's Financial Supervision Based on the Smoke Index
Authors: Wang Senpei , Zhu Jieliang , Qi Chenyang , Cai Xiaoyu
Published: June 2024

In recent years, with the rapid development of China's economy and the continuous development of Internet technology, China has ushered in a "financial boom". At the same time, the financial risks of illegal fund-raising such as P2P online loan platforms have gradually been exposed. In order to effectively warn and prevent these risks, the Beijing Leading Group for the Fight against Illegal Fund-raising and the Technology Company jointly developed the "Smoke Index", and with the establishment of the General Administration of Financial Supervision, financial supervision has increasingly become an important measure to protect financial security in China. This article aims to explore its promoting role in China's financial supervision with the help of the smoke index, and take this as an entry point to provide a new direction for the steady development of China's economy.
Analysis of the Utility Tunnel Joint's Stress Characteristics Under Well Point Precipitation Conditions
Authors: Li Ben , Zhang Xinsheng
Published: June 2024

The method by which groundwater influences subsurface buildings is relatively complex in the groundwater-rich regions of southern China. Notably, it substantially affects the pipe corridor junctions, which are crucial to impermeability. In order to analyze the forces on the utility tunnel joints during well-point precipitation, numerical modeling of the utility tunnel joints using the well-point precipitation method based on Finite element software was carried out, and a precipitation model tank was made to verify the model parameters and boundary restrictions. The results indicate that under well-point precipitation, the force variation of the bottom plate is more significant than that of the top plate at the same port and that in the joint section close to the precipitation point, the force variation of the bottom plate can reach 2-3 times that of the top plate. The spigot joint's bottom plate has a maximum tensile stress of 319.52 kPa, which raises the possibility of tensile damage. The well-point dewatering method has a higher likelihood of bottom plate cracks, which makes it a critical component to be watched during construction and operation.
Vibrational Analysis of Mounting Base for a Winch
Authors: Wang Peng , Wu Gang , Zhao Zhigao , Qian Jiachang
Published: June 2024

Mounting base will help to give better layout for equipment, and the vibrational performance is very important for vibration isolation design of equipment. The statics, modal and impedance analysis are conducted for mounting base of a winch in an experiment, the effect of gravity is also considered. Numerical results show that, the effect of gravity on modal frequency of mounting bases here is very small and could be ignored, the impedance is about 106 Ns/m, and it will change especially for amplitudes of resonance peaks with the change of location of external load force. Conclusions here will help to support the vibration isolation design for equipment.
An Overview of Data Contribution Evaluation Methods for Federated Learning
Authors: Ding Chenxi , Zhang Mingchuan
Published: June 2024

With the rapid development of artificial intelligence, especially machine learning technology, the demand for data is also increasing. As a distributed learning method, federated learning (FL) allows total multiple parties to co-train models locally while protecting data privacy. Due to heterogeneity in data, devices, and other factors, the contribution of participants to model quality also varies. If these differences are ignored, it poses a challenge to achieving a fair FL environment. Therefore, fairly assessing the contribution levels of each data provider becomes a critical issue in FL. This plays a significant role in fairly motivating participants and promoting the sustainable development of FL. This paper reviews existing evaluation methods from the perspective of data contribution assessment in FL, discusses ongoing challenges in this area, and explores future research directions.
Sustainable Urban Development in the Post-Pandemic Era: Smart Shenzhen based on the 15-Minute City Concept
Authors: Peng Chuxuan
Published: June 2024

In the face of the pandemic, there has been a global focus on urban planning and sustainability. These have attracted attention in innovative cities. The 15-Minute City approach aims to address the COVID-19 pandemic, enhance urban sustainability, and encourage citizen involvement in urban planning and management. In 2018, the municipality of Milan launched the Fifteen Minute City project. The project aims to redefine the use of streets and public spaces, encourage cycling and walking, and reshape neighborhoods. By studying the success of Milan's 15-minute City, this paper aims to deeply analyze the necessary factors for the successful implementation of the 15-minute plan based on the Notice of Shenzhen Municipal Bureau of Commerce on printing and distributing the Implementation Plan for the Pilot City Construction of Shenzhen Quarter Hour Convenient Living Circle. This paper will establish causal connections between the variables within the plan and propose strategies for mitigating the identified risks. Additionally, the document will present a fair and objective evaluation of the plan's consequences, along with practical suggestions for future execution. The paper highlights the importance of community involvement in urban planning and emergency management by examining key initiatives in Shenzhen, such as the implementation of digital technologies, green transport policies, community support, and public education. The research provides valuable lessons for both Shenzhen and other cities on sustainable development and infection management and highlights the need for community collaboration and public participation.
A study on commodity pricing and sales optimization based on linear programming model: a case of vegetable category
Authors: Chen Yutong
Published: June 2024

In the fresh food retail industry, vegetable commodities require daily replenishment decisions based on historical sales and demand due to their short freshness period and susceptibility to quality. In this paper, the sales volume, wholesale price and unit price of each category are first extracted, and the cost-plus ratio and related data are calculated. The relationship between the sales volume of each category and the cost markup rate is analyzed through linear regression, and it is concluded that the sales volume of most categories decreases with the increase of the markup rate, and through the distribution of the scatter plot of the total sales volume of the vegetable category and the markup rate, it can be seen that there is a negative correlation between the total sales volume of the vegetable category and the cost markup pricing, and then through the establishment of the optimization model and the prediction of the sales volume of each category for the coming week, the wholesale price and the related data, and the profits are used to Pricing to ensure revenue at the maximum markup rate to develop the total daily capture and pricing strategy for the coming week.
The Application of Artificial Intelligence in Global Supply Chain Financing and Its Implications for Multinational Corporations Subtitle as Needed
Authors: Wang Shuo , Zhang Yuanbo
Published: June 2024

Starting from the year 2023, the world has entered a new phase of explosive growth in artificial intelligence development, bringing forth a myriad of opportunities and challenges for multinational enterprises in the realm of global supply chain financing. This study systematically analyzes the current state and impact of artificial intelligence technology in global supply chain financing. Furthermore, it identifies and assesses potential technological, legal, ethical, and security challenges that may arise in this process, proposing corresponding strategies to address them. The research findings indicate that despite the challenges associated with adopting AI technology in supply chain financing, the opportunities far outweigh the risks. Through judicious strategies and management measures, multinational corporations can effectively leverage AI technology to optimize supply chain financing and achieve sustainable development.
The Impact of Artificial Intelligence on Environmental Protection
Authors: Qi Yukai
Published: June 2024

In the face of escalating global environmental issues, the role of artificial intelligence (AI) in environmental protection has become increasingly significant. One of the key areas of focus is water quality monitoring in sewage treatment. AI has been instrumental in predicting and identifying potential contaminants, thus ensuring the safety and cleanliness of water resources. This not only aids in maintaining public health but also contributes to the preservation of aquatic ecosystems. Another crucial aspect is the prediction of air pollution. AI algorithms have been developed to forecast air quality, enabling timely measures to mitigate the adverse effects of air pollution. This is particularly beneficial in urban areas where air pollution levels are typically high. The paper also explores AI's role in soil protection, specifically in detecting soil quality. AI can help identify nutrient deficiencies, monitor moisture levels, and detect the presence of harmful substances, thereby promoting sustainable agriculture and preserving soil health. Furthermore, the paper extends its scope to specific applications of AI in other areas of environmental protection. These include wildlife conservation, waste management, and climate change mitigation, among others. Finally, the paper looks forward to the future impact and development of AI in the field of environmental protection. It discusses the potential challenges and opportunities, and how AI can be leveraged to create a more sustainable and environmentally-friendly future. The paper underscores the importance of continued research, and development in AI to fully harness its potential in environmental protection.
Examining the Impact of Resistance to Innovation on New Product Adoption Behavior: The Role of Purchase Intention
Authors: Malate Loren Absalão Vaz
Published: June 2024

Innovation resistance is an emerging area of research in marketing. Despite the high rate of market introduction failures that businesses encounter, there is surprisingly little research into a key cause of these failures: the resistance of customers to innovation. This study explores the complex relationship between resistance to innovation, purchase intention, and new product adoption behavior. The conceptual framework was inspired by various theories, such as Kotler's Decision-Making Process, Innovation Resistance Theory and Theory of Planned Behavior (TPB). Through a descriptive research approach utilizing an online survey, the study examines how Resistance to Innovation influences various aspects of New Product Adoption Behavior such as New product Buying Behavior, New Product Information Searching Behavior in the lens of New Product Purchase Intention. This research uses SPSS 26.0 software to analyse the survey data. As expected, resistance to innovation exerts some influence on new product purchase intention. Purchase intention is found to partially mediate the relationship between resistance to innovation and new product adoption behavior.
The Intersection of Plastic Electronics and Medical Innovation
Authors: Xie Yanxi
Published: June 2024

The aging global population has catalyzed a paradigm shift in healthcare, emphasizing disease prevention over treatment and underscoring the need for large-scale, long-term monitoring of physiological parameters. Wearable health monitoring devices have emerged as a pivotal solution, offering real-time physiological data collection across prevention, treatment, and rehabilitation phases, thus revolutionizing traditional health monitoring approaches. This paper explores the integration of advanced materials—conductive polymers, flexible carbon nanomaterial electrodes, and metal foil substrates—into wearable health technologies. These materials enhance device flexibility, biocompatibility, and non-intrusive monitoring capabilities, providing medical-grade data crucial for early diagnosis and treatment guidance. With the wearable device market projected to expand significantly, fueled by the Internet of Things (IoT) and device miniaturization, this study delves into the technological advancements in detection technologies for electrophysiological, physical, biochemical, and photoelectric signals. It also examines the challenges and future directions in wearable health devices, focusing on material innovation, device miniaturization, and the integration of plastic electronics to improve wearability, sustainability, and interactivity. Through systematic analysis, this paper aims to highlight the transformative impact of wearable health technologies on enhancing patient care, facilitating early disease detection, and offering personalized health management solutions.
Applications of 2D semiconductor materials in electronics and optoelectronics
Authors: Luo Xianqi
Published: June 2024

Due to the demand for the higher performance of electronic and optoelectronic devices, the research of 2D semiconductor materials is very important nowadays. Because of the excellent electronic and optoelectronic properties of 2D semiconductor materials can be applied in many fields. This article mainly introduced the preparation, properties and applications of 2D semiconductor materials. The applications in electronics and optoelectronics are mainly discussed, such logic gates, field effect transistors light emitting diodes and high responsivity photodetectors. Compared to traditional semiconductor materials, 2D semiconductor materials have higher mobility and energy efficiency, leading to higher responding speed and lower energy loss. The flexibility of these materials also makes wearable electronic devices possible. However, they are still short in stability and immature in preparation. Future studies should focus more on the stability and preparation of 2D semiconductor materials and9 make the massive production and application of such high-performance materials plausible.
An Analysis of Optimal Decision on Capital Structure
Authors: Li An
Published: June 2024

Achieving optimal financial performance is the ultimate objective for enterprises when crafting their capital structure. This pursuit, however, is far from one-size-fits-all, as the intricacies of various industries and the idiosyncrasies of host countries contribute to the diversity in capital structure configurations. Leveraging the foundational concepts of the Modigliani and Miller (M&M) theorem, this article delves into a comprehensive exploration of the intricacies surrounding capital structures in distinct industry segments. Capital-intensive industries, labor-intensive industries, and research and development (R&D) sectors are scrutinized under the analytical lens to decipher the unique considerations at play. Moreover, this study extends its purview to encompass the dichotomy between the financial markets of developing and developed nations. By doing so, it unveils key distinctions in capital market dynamics, risk profiles, and financing opportunities. These insights offer enterprises a roadmap for making well-informed decisions pertaining to their optimal capital structure. In essence, this article provides a valuable reference point, enabling companies to align their financial strategies with the precise needs of their industry and the nuances of their operating environment.
Preliminary Exploration of the Construction of the Great Site Museum in Jingzhou
Authors: Li Li
Published: June 2024

Jingzhou is the main part of the National Great Site Protection Zone in the Central China region of the Yangtze River Basin. In 2010, the National Cultural Heritage Administration and the Hubei Provincial People’s Government signed a joint agreement on the protection of the Great Site in Jingzhou, marking a milestone event in the protection of Chu culture heritage and cultural relics in Hubei. The major sites in the Jingzhou area are located within the Jinan Ecological Cultural Tourism Area, giving the construction and development of the site museum in Jingzhou’s Jinan Ecological Cultural Tourism Area a unique advantage. By analyzing the exhibition concepts, architectural concepts, interpretation concepts, and talent development concepts of the three major sites in the jurisdiction area, this paper explores some ideas for the construction of the Great Site Museum.
The Analysis on the Management of Charlotte Hornets
Authors: He Haoze
Published: June 2024

This paper focuses on the topic of team management and uses the case of an NBA team, Charlotte Hornets as an example. The research wants to discover the relationship between the successful operation of a sports team and its actions as well as the management system. In the body part, it analyzes the team’s current situation, evaluates the actions it has taken and makes plans for the future of the team. It turns out that the team has almost got rid of the difficult situation and it is on the right track right now. The research applies qualitative approaches and specifically utilizes the methods of observation. It turns out that though Charlotte Hornets used to struggle with their performance in the league, it is on the right track towards the playoffs now. The result shows that whether a team can be successful is closely associated with the team’s management and planning.
Research And Impact of Bioremediation on Soil Cadmium
Authors: Xu Mingting
Published: June 2024

There are many studies on the interaction between Cd pollution and bioremediation at home and abroad, mainly local and short-term toxicological effects, and there is a lack of systematic reviews. The purpose of this report is to provide a summary of the research on several bioremediation methods through specific experiments and mechanisms. and a summary and report on the principles and mechanisms of phytoremediation technology and animal remediation technology. In the future, bioremediation technology should focus on further exploration in the treatment cycle and final treatment of materials, avoid secondary pollution, strengthen the prevention and control of soil cadmium pollution, master more scientific soil cadmium pollution prevention and control technology, and expand more experiments and research on bioremediation If necessary, researchers can comprehensively apply and match a variety of different control technologies to enhance the control effect of soil cadmium pollution. It is also hoped that more attention will be paid to some potential future research on remediation methods for soil cadmium pollution, and that bioremediation is not only for the further exploration and discovery of cadmium and other heavy metal pollution in soil.
Study on Damage Inference of Parker Trusses Based on Bayesian Principles
Authors: Deng Zhifang , Wang Qianfan
Published: June 2024

The assessment of the health condition and safety of engineering structures is currently a research focus in the field of civil engineering. The traditional deterministic model for damage recognition is limited by the fine reading of field inspections and the accuracy of experts, resulting in a low recognition rate. Structural damage identification methods that consider uncertainty have been developed due to modelling errors, observation noise, system time variability, and other factors that lead to uncertainty. This study focuses on the Parker truss structure, and a two-dimensional planar finite element model is established by setting various key parameters such as prior distribution, stiffness, modulus of elasticity, node distribution, and external loading. The model is updated using the Bayesian updating principle. This principle is then combined with the finite element model. Opensees software is used for programming, and the Monte Carlo random sampling technique is used for structural damage inference. The study results demonstrate that the method can accurately identify the damage level of Parker truss structures with high robustness. The method can be of reference significance and practical value for identifying damage in truss structures.
Evaluation of Safety and Therapeutic Efficacy of CAR-T Therapy
Authors: Sheng Xinyi
Published: June 2024

Chimeric antigen receptor (CAR)-T therapy has been developed as revolutionary treatment in cancer treatment. It has been clinically proven to be effective and durable towards certain subtypes of blood cancer especially in B-cell leukemia or lymphoma. CARs are synthetic receptor which are designed to redirect T lymphocytes to eliminate cancer cells with a specific antigen on the surface. However, limited therapeutic efficacy and safety concern of CAR-T therapy present as obstacles to its application in both solid and hematological cancer. Hence more research is being conducted to study the mechanism behind therapeutic limitation and how to improve its therapeutic effectiveness. Furthermore, innovative strategies should be investigated to limit its toxicities. This review firstly explains the process of CAR-T therapy and its current milestone. Then the review discusses its current challenges and characterize some reasons for its limited therapeutic applications and strategies to improve its efficacy and safety in clinical settings.
Impact of Sunscreen on Preventing Each Type of Facial Skin Cancer
Authors: Xing Shengyan
Published: June 2024

The most frequent cancer in the US is skin cancer, around 5.4 million cases of Basal Cell Carcinoma (BCC) and Squamous Cell Carcinoma (SCC) are treated every year, while BCC is more common. Exposure to ultraviolet rays is the source of four varieties of skin cancer: BCC, SCC, Melanoma, and Merkel Cell Carcinoma (MCC). Since there are several experiments done on the influence of sunscreen on skin cancer, this paper aims to offer a comprehensive and symmetric conclusion to existing research. This paper summarizes the current studies finished for each type of skin cancer that might be caused by high levels of UV exposure. This study cites 4 experiments for melanoma, and three of them show a reduction in the rate of melanoma if sun blockers were used. This paper also uses three research for SCC and BCC to analyze the relationship between sun cream application and the probability of having SCC and BCC. None of them found that sunscreen will decrease the rate of SCC and one of them contends that sun lotion can prevent some of SCC. There is no current research about MCC, as the difficulty of holding this kind of experiment. This study will provide a reference for the medical field and the general public to analyze if sun lotion should be employed to prevent skin cancers.
Multi-scale image recognition strategy based on convolutional neural network
Authors: Zhang Huajun , Diao Su , Yang Yining , Zhong Jiachen , Yan Yafeng
Published: June 2024

The accurate recognition and interpretation of multi-scale visual information is a critical focus within contemporary computer vision research. To this end, this study explores and innovatively constructs a multi-scale image recognition strategy based on a Convolutional Neural Network (CNN) with a multi-level and multi-resolution perception domain. This strategy is embedded with an advanced multi-level convolutional operation mechanism, which enables the model to intelligently explore and learn the multi-scale feature representation space of images from tiny texture to grand structure, from shallow simple features to deep semantic abstraction. The core technology path of this paper is to design a deep separable convolutional architecture and combine pyramid pool technology to form a unique network module. This modular design not only ensures the computational efficiency of the model but also improves the ability of extracting and integrating multi-scale image features. Following intensive experimentation on an array of extensively recognized and substantial image datasets, the multi-scale image recognition approach introduced in our study has demonstrated marked enhancements in both recognition capability and stability, manifesting clear superiority compared to conventional, single-scale image recognition methodologies. This research not only enriches the theoretical framework of image recognition, but also provides a new and efficient solution for dealing with complex multi-scale image recognition challenges in practical applications, and further promotes the development of image understanding and recognition technology.
Design of Car Control Algorithm Based on Deep Reinforcement Learning
Authors: Lei Yu
Published: June 2024

Reinforcement learning algorithm is widely used in the field of agent control because of its high robustness and strong adaptability. The problem of Mountain-Car-v0 is a classic control problem, which attracts the attention of many researchers. Traditional control methods, for example, PID control, are widely used in industrial and robot control fields, but they show obvious limitations in the face of such highly nonlinear and unknown environments. Therefore, this paper proposes a car control algorithm based on deep reinforcement learning, aiming at overcoming the shortcomings of traditional methods and realizing efficient control of complex dynamic systems. By combining the automatic extraction of high-dimensional features of deep learning with the dynamic decision-making mechanism of reinforcement learning, an adaptive control algorithm is designed, which can continuously learn and optimize in the interaction with the environment without establishing an accurate system model in advance. The experimental results show that compared with traditional control methods and other intelligent control strategies, the proposed algorithm shows higher efficiency and better adaptability in the task of Mountain-car-V0, and obviously improves the success rate of the Mountain-Car-v0.
Survey on Indoor Positioning and Navigation Technologies Based on Sensors Fusion
Authors: Shao Yuxuan
Published: June 2024

Due to the growth of productivity and the development of min-sensors, relevant localization and navigation algorithms are better suited today. However, indoor localization still faces many new problems, and with the popularity of usage scenarios, the variable and complex environmental information brings many new challenges to indoor localization and navigation. Currently, the widely used sensors on the market are vision sensors, ToF sensors and wireless sensors. These three types of sensors are used under different conditions and also have different accuracies and measurement ranges. Through sensors fusion algorithms can complement the strengths and weaknesses of different sensors to achieve better performance in complex using situations. The paper presents a survey on indoor positioning and navigation technologies based on sensor fusion from different sensors and relevant applications. We demonstrate the benefits of sensor fusion algorithms in practical applications by performing sensor fusion based on and single type of sensors and different types of sensors.
Challenges and Opportunities for Sustainable Supply Chain Management
Authors: Li Fangxi
Published: June 2024

Green supply chain management (GSCM) is an advanced management approach that comprehensively considers the environmental impact, resource utilization efficiency, and enterprise income throughout the entire supply chain process. Compared to traditional supply chain management, GSCM exhibits higher complexity in terms of management and network characteristics. It emphasizes sustainable development for both society and enterprises, incorporating ecological and environmental protection design principles from raw material sourcing to waste material recycling, thereby achieving optimized environmental outcomes through enhanced cooperation within and between organizations. In essence, green supply chain management practices encompass green design, green procurement, green manufacturing, green packaging, green materials usage, and green recycling initiatives. The critical distinction between a green supply chain and a traditional one lies in the former's consideration not only of optimizing and coordinating the supply chain under conventional economic cost constraints but also recognizing the negative impacts of economic activities on the environment as significant factors warranting investigation. By embedding environmental awareness into supply chain management processes, it seeks to achieve a balanced approach that harmonizes the economy with environmental concerns. The proposition of adopting a green supply chain aligns with the developmental trajectory of economic globalization and free trade while meeting demands for environmentally friendly products and promoting greener trade.
Green Bond Issuance and Corporate Investment and Financing Level: Evidence from Chinese Listed Companies
Authors: Yu Wansheng
Published: June 2024

After the formation of the Chinese green bond market in 2016, it rapidly developed. However, there have been relatively few studies in academia on the financial performance of enterprises after issuing green bonds. In order to promote the development of the green bond market and guide enterprises to improve their investment and financing decisions, this paper uses panel data of A-share listed companies and green bond issuing companies from 2012 to 2022 as samples to study the impact and mechanism of green bond issuance on the investment and financing behavior and maturity mismatch of enterprises. The conclusion drawn is that green bond issuance significantly promotes the improvement of enterprises' investment and financing capabilities, and it also reduces the degree of maturity mismatch for enterprises. This conclusion passes the parallel trends test and remains robust after controlling for the effects of corporate financial asset allocation, industry time trends, and excluding competitive hypotheses. Through mechanism research, it is found that green bonds can improve the level of enterprise investment and financing and the degree of maturity mismatch by reducing the degree of financing constraints on enterprises. They can also enhance enterprise investment and financing capabilities by changing market sentiment and alleviate the maturity mismatch of investment and financing.
Impact of Human Factors on Nature and Corresponding Measures
Authors: Li Chengzhe
Published: June 2024

As people in nowadays are paying more and more attention on environmental problems, we have noticed that human factors are great contributors to many problems on nature. This essay mainly discusses about the effects of human factors on nature in the aspects of atmosphere, rivers, oceans, and soil. In the paper, various of human factors including burning fossil fuels, sewage disposal, etc. are studied. Industrial processes emit significant greenhouse gases, disrupting Earth's balance and contributing to global warming and acid rain. Sewage and improper waste disposal in rivers and oceans turn once-pristine waters toxic, imperiling marine life. The urgency to address disposal habits is evident in cases like turtles ingesting plastic bags. Plant life is also affected as sewage laden with nitrogen, phosphorus, and potassium leads to ecological degradation, causing algal blooms and creating "dead lakes" or "dead seas." On land, human activities like desertification, deforestation, and urbanization have degraded soil health. Additionally, past imprudent infrastructure development has left scars of mudslides, emphasizing the vulnerability of ecosystems to human disregard. Lastly, the paper discusses some possible solutions due to this situation. This paper hopes to find out ways to solve environmental problems caused by human factors.
Analysis of Huawei's Financial Risk Management from the Perspective of Financial Indicators
Authors: Zhu Yangdan , Liu He
Published: June 2024

With the continuous development of China's socio-economy, overall enterprise growth faces certain limitations; deeper economic reforms and market opening create a more challenging external environment for businesses. This implies that companies will encounter more challenges. To ensure that enterprises can operate normally and successfully achieve their business objectives, it is necessary to correctly understand financial risks and adopt rational risk management methods to avoid or reduce potential losses. This paper takes Huawei Technologies Co., Ltd. (hereinafter referred to as "Huawei") as an example and analyzes its financial indicators. Through financial data, it identifies the issues and causes of the company's financial risk management, and discusses how to prevent financial risks in enterprises, aiming to assist companies in achieving sustainable development in a fiercely competitive environment.
Practice of Progressive Training System for Innovative Talents in Research Units
Authors: Zheng Deyao , Zhang Biao , Kou Yumin
Published: June 2024

Young employees, as the reserve force of an enterprise, are crucial for its future and have always been valued and cared for by senior management. Talent cultivation follows the process of "establishing standards-building application systems-formulating plans-implementing training," and through digitalization, scientific evaluation, and visualization, it comprehensively connects the talent chain of "selection, cultivation, utilization, and management." This transforms past innovative talents from "I have to learn" to "I want to learn," effectively enhancing employees' work enthusiasm and management efficiency.
"The Role of Coach-Athlete Relationship in Enhancing Team Sport Performance: A Multi-Sport Perspective"
Authors: Yuan Xiang
Published: June 2024

This research provides useful insights on the coach-athlete relationship in college sports by analyzing the characteristics of the participants, evaluating players' perspectives on this relationship, and revealing the difficulties encountered by student-athletes. A heterogeneous group of primarily male athletes participated in a variety of team sports, with soccer, basketball, and volleyball being the most prevalent. Athletes often had favorable opinions on their interactions with coaches, demonstrating exceptional performance in areas such as communication, motivation, guidance, empathy, openness, understanding of roles, and ethical conduct. Nevertheless, significant gender-based disparities arose, as men athletes reported more positive connections compared to their female counterparts. Furthermore, student-athletes have pinpointed significant obstacles, such as difficulties in communicating, incongruity in coaching styles, resolving conflicts, obtaining mental health assistance, ensuring ethical conduct, and addressing concerns about criticism.
ARIMA-based Freight Forecasting and Network Optimization in E-commerce Logistics
Authors: Wu Tianyou , Deng Jinkai , Chu Chengxi , Luo Jinghao
Published: June 2024

Considering the proliferation of e-commerce platforms exemplified by Taobao and JD, the paradigm of online shopping has evolved into an integral facet of contemporary societal existence. To enhance network transport performance, it is essential to predict freight volume, assess existing capacity, and establish new sites to alleviate network pressure. This study focuses on a logistics transportation network, utilizing daily freight turnover data from January 1, 2021, to December 31, 2022. The ARIMA time series method is employed to forecast freight volumes at different sites within the e-commerce logistics network. Taking three logistics site route combinations, namely DC14→DC10, DC20→DC35, and DC25→DC62, as examples, two differencing operations are applied to meet the stationarity requirement of the ARIMA model. Autocorrelation and partial autocorrelation coefficients are used for preliminary model order determination. By minimizing the Akaike Information Criterion (AIC) value, an ARIMA (5) model is established. Single and multiple-step predictions are conducted, resulting in forecast curves for future freight volumes. Subsequently, an evaluation of the transportation network is performed, considering the importance of nodes and routes. The entropy weight method is applied to determine the weights of evaluation indicators. Importance indices for nodes and routes are calculated, leading to a ranking. For the assessment and selection of new site capabilities, Fisher's discriminant function is employed to classify different sites. The valuation level for site selection is determined, providing a scientific basis for the systematic choice of new sites.
Research on the Correlation between Economic Factors and Quality of Life
Authors: Li Renzhi
Published: June 2024

This study is a pivotal examination of the intricate link between economic factors and residents' quality of life, underscoring its critical implications for policy-making and societal advancement. It delves into the multifaceted relationship between economic indicators like GDP, unemployment, income distribution, and quality of life elements such as health, education, and subjective well-being, particularly focusing on Qingdao, China from 2008 to 2018. Employing a hybrid methodology of quantitative and qualitative analysis, including secondary data and case studies, the research unveils a positive correlation between economic growth and improved living standards, while also highlighting the complexities and multidimensional aspects of this relationship. The findings suggest that while economic growth contributes to better quality of life, aspects like job creation, social equity, and public services are equally vital, advocating a balanced approach in policy-making to ensure equitable and sustainable societal development.