bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence and Applications in Structural and Material Engineering
Authors: Zhang Shengzhe
Published: January 2024

The integration of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) has become a vital tool attributed to Structural and Material Engineering and developed the way engineers approach design analysis and optimization. This paper explores the principal models of ML and DL, such as the generative adversarial network (GAN) and the artificial neural networks (ANN) and, and discusses their impacts on the applications of material design, structure damage detection (SDD), and archtecture design. It indicates that the high-quality of database is the essential key to training the model. Thus, the data preprocessing is required for expanding the data source and improving the quality of data. In material design process, ML and DL models reduce the time to predict the properties of construction materials, which makes SDD realistic as well. For architecture design, GAN is used to generate image data, such as drawing of the floor plan and this could be helpful to reduce the labor resources. However, some challenges of ML and DL are found while applying the algorithms to real-life applications. For example, sufficient data is needed to train the DL models and the ethic aspect is also a concern when thinking of AI.
An Analysis of the Artistic Marketing Strategies of the Aranya Community in Qinhuangdao, China
Authors: Sun Jiadai
Published: January 2024

In recent years, consumer scenarios have been continuously evolving and iterating. Along with the changes in historical and cultural contexts, people's consumption behaviors and psychology have also been constantly transformed. This article comprehensively analyzes the historical changes and developments in consumer society and explores the challenges of urban consumption spaces in the post-pandemic era. The successful creation of the aranya community, and its activation pathway, will be the primary focus of this article. By combining with other typical brand cases, delve into changes in consumer psychology and behaviors, seeking to understand the emotional expectations consumers place on post-pandemic-era consumption spaces. Architectural spaces and consumption scenes are not merely physical structures but also places consumers rely on to release their spiritual and emotional needs. This article will explore and summarize the aranya brand's construction methods, as well as the significance of creating atmospheric experiential feelings for consumers. It will analyze the cultural dissemination of art education in situational consumer spaces and underline the necessity of constructing situational experiential feelings in consumption spaces. This will enable designers and space creators to conduct more in-depth research on the design and cultural dissemination of consumption spaces, providing a more solid theoretical foundation for future urban consumption space development.
Application and Limitation of Fisher Model
Authors: Han Yulun
Published: January 2024

This essay explores the Fisher Effect hypothesis, which posits a direct relationship between nominal interest rates and expected inflation. It delves into the Fisher model's concept, its implications, and its significance in economics. The research question of the model's validity and applicability is examined through a review of current research findings, revealing mixed results. The essay highlights the diverse applications of the Fisher model in monetary policy, finance, and decision-making across various economic sectors. However, it also discusses the model's limitations, including its assumptions, data quality concerns, short-term focus, and neglect of risk premiums. Future research directions are proposed to enhance the model's accuracy and applicability. In conclusion, this essay emphasizes the importance of recognizing both the strengths and weaknesses of the Fisher Effect and the need for ongoing refinement in its application to navigate the complexities of the economic landscape.
Enhancing High-Speed Data Transfer in Fpga-Based Systems: An Innovative Usb 3.0 Communication Interface Design
Authors: Liao Cailin , Liu Yuhao , Zhu Yanzhe
Published: January 2024

This study introduces an innovative design for a USB 3.0 communication interface, specifically tailored for Field-Programmable Gate Arrays (FPGAs). Given the escalating requirements for rapid data transmission in contemporary computer applications, USB 3.0 provides substantial enhancements over its antecedents. Nonetheless, extant USB communication interfaces inadequately cater to FPGA development, leading to diminished productivity for developers. To reconcile this discrepancy, this paper advocate for an Intellectual Property (IP) core interface that capitalizes on the concurrent data transmission proficiency of FPGAs, in conjunction with the superior speed transfer of USB 3.0. This design employs the CYUSB3014 chip, amalgamating the Physical Layer (PHY), Serial Interface Engine (SIE), and driver software into a singular entity. Herein, the FPGA serves as the nexus of control, streamlining data interchange and interface coordination among diverse modules within the system. The design put forth not only enables expeditious data communication in FPGA-centric systems, thereby surmounting the constraints of conventional USB interfaces, but also promotes accelerated data conveyance and augmented development efficiency. Consequently, this design harbors extensive applicability across spheres of digital system design and communications.
The Role of TRIM Proteins in Antiviral Defense
Authors: Liu Yilin
Published: January 2024

The Tripartite motif (TRIM) protein family is classified among a cohort of E3 ubiquitin ligase families. A large percentage of TRIM proteins are E3 ubiquitin ligase active and take part in a number of cellular functions. By adding ubiquitin molecules to target proteins via a variety of techniques, it can change those proteins. The important role of the TRIM protein in controlling pattern recognition receptor signaling pathways and the defense mechanisms of mammals against viruses, with a focus on protecting the host from viral infections, has been clarified by recent study. In addition to triggering crucial cell-intrinsic defense mechanisms like autophagy and transcription-dependent antiviral responses, TRIM proteins can also exhibit direct antiviral effects by obstructing particular viral components via a variety of mechanisms. Regrettably, certain viruses have developed efficient mechanisms to evade the antiviral activities exerted by specific TRIM proteins, including SARS-CoV-2. Viruses has the capacity to exploit TRIMs and the ubiquitination process directly, hence enhancing the viral replication cycle and inducing heightened pathogenicity. In this article, I have delved into research that explores the molecular mechanisms responsible for the antiviral effects of TRIM proteins. Additionally, I have examined how TRIM proteins exert their influence on various viral entities, shedding light on their crucial role in the immune response against viral infections.
Analysis Of House Price Bubbles and Macroeconomic Policy Regulation
Authors: Yan Weilun , Zhou Youchen
Published: January 2024

House prices are a reflection of a country's economic growth and a city's overall competitiveness, and are determined by supply and demand after integrating various factors. Real estate is an important pillar industry all over the world, and almost everyone sees property as an important reflection of economic property. Real estate includes residential and commercial property. In 2023 real estate will remain an important and large industry. House prices are something that is closely watched in people's lives. When there is a change in house prices it can have an impact on the whole society and economy. This study focuses on the impact of macroeconomic policies on the house price bubble economy and the causes of the house price bubble economy. The study will adopt an objective perspective and a formulaic approach to analyze the house price bubble economy. This study will use the example of Japan during the bubble economy to explain this. It is found that different macroeconomic policies will lead to different economic effects that will trigger the strength of the house price bubble, such as macroeconomic policies that lead to inflation and then lead to the strengthening of the house price bubble.
Research On Pruning Methods for Mobilenet Convolutional Neural Network
Authors: Zou Yunhuan
Published: January 2024

This paper comprehensively reviews pruning methods for MobileNet convolutional neural networks. MobileNet is a lightweight convolutional neural network suitable for resource-constrained environments such as mobile devices.Various pruning methods can be applied to reduce the model's storage space and computational complexity, including channel pruning, kernel pruning, and weight pruning. Channel pruning removes unimportant channels to reduce redundant parameters and computations in the model, while kernel pruning reduces redundant calculations by pruning convolutional kernels. Weight pruning involves setting small-weighted elements to zero to remove unimportant weights. These pruning methods can be used individually or in combination. After pruning, fine-tuning is necessary to restore the model's performance. Factors such as pruning rate, pruning order, and pruning location need to be considered to achieve a balance between reducing model size and computational complexity while minimizing performance loss. Pruning methods based on MobileNet convolutional neural networks reduce the parameter count and computational complexity, improving model lightweightness and inference efficiency. These methods are of significant value in resource-constrained environments such as mobile devices. This review provides insights into pruning methods for MobileNet convolutional neural networks and their applications in lightweight and efficient model deployment. Further advancements such as automated pruning methods driven by reinforcement learning algorithms can enhance the pruning process to achieve optimal model compression effects. Future research should focus on adapting and optimizing these pruning methods for specific problem domains and achieving even higher compression ratios and computational speedups.
Navigating Economic Recovery in the Post-COVID Era: Lessons and Implications from the New Deal
Authors: Yang Caiqing
Published: January 2024

The COVID-19 pandemics, have sparked unprecedent crises worldwide, reminding the governments of the economic turmoil of the 1930s Great Depression. Effective government interventions are required urgently to combat the severe volatility and initiate recovery. How could the lessons from the historical policies provide crucial insights for the contemporary challenge of the US economy? This paper examines the efficacy of the New Deal and fiscal and monetary responses of the US government following the COVID-19 pandemic through comparative analysis of several macroeconomic variables including GDP growth, Unemployment rate and Consumer Price Index. By assessing the successes, limitations and long-term implications between the stimulus measures for addressing distinct challenges of the two periods, this research emphasizes the significance of New Deal’s ideas in promoting the comprehensive, flexible and equitable initiatives under the contemporary context. Furthermore, this study attempts to convey informative policy recommendations for addressing the subsequent concerns arising in the post-covid economy, as well as provide feasible guidance for future policy improvements.
Current Situation and Optimization Suggestions for Ageing-Appropriate Development of Urban Public Rest Facilities
Authors: Xu Ruisi
Published: January 2024

With the increasing proportion of elderly people, China has long since entered an aging society, and the development of aging has continued to deepen. In the construction of the humanization level of the city, the development of age-appropriate public rest facilities has attracted much attention. This study will take the current aging society as the background and meet the physiological and psychological needs of the elderly group as the starting point to investigate in depth the current situation of the construction of urban public open space facilities. Based on the degree of aging, the level of urban construction, and social concern, this study selects the public rest facilities in Changning District, Shanghai, as the research object, and conducts a comprehensive analysis of the level of construction of aging-appropriate rest facilities. The study found that the construction of existing urban public rest facilities is still characterized by a variety of problems such as scarcity, single type, poor comfort, safety hazards, and lack of consideration for the physical scale of the elderly population and suggested corresponding improvements. Public rest facilities must follow the people-oriented principle, be based on the many different needs of the elderly, fully integrate the living habits of China's elderly population, and comprehensively improve the quality of life of the elderly population. This study is of great significance for the subsequent promotion of the construction of public rest facilities and the implementation of the construction of the humanization level of the city.
A Study on the Differences in Economic Development between East and West China
Authors: Cheng Hongji
Published: January 2024

This study probes into the root cause of the economic development gap between East and West China. In the background, China's vast geographical conditions, historical investment patterns, and policy support have led to significant differences in development between the eastern and western regions. The objective of this paper is to analyze in depth how these factors interact and affect the economic development of the two regions. The research focuses on geographical factors, industrial structure, productivity, and education level. The study found that the eastern region's geographical advantages, policy support, and industrial diversity promoted its economic prosperity, while the western region's geographical barriers, resource dependence, and educational shortcomings restricted its development. In the future, comprehensive measures, including infrastructure construction, policy support, innovation promotion, and education reform, are needed to close this gap. Balanced and sustainable economic growth in China requires the coordinated development of the eastern and western regions, which will also help improve the living standards of the people throughout the country and promote the overall prosperity of the country.
Smartphone Fast Charger Analysis Based on RLC Circuit Transient Process
Authors: Wang Junxiang
Published: January 2024

In today's era, the widespread adoption of mobile terminals, particularly smartphones, has been facilitated by the rapid advancements in information and communication technology. However, a notable drawback of smartphones is their high-power consumption, necessitating faster charging solutions to enhance user convenience. This paper focuses on the RLC circuit of fast chargers. Initially, it introduces the fundamental principles and associated protocols of fast charging technology, elucidating the operation of integrated circuits within fast chargers and highlighting the advantages of fast charging compared to conventional slow charging methods. Moreover, the paper conducts an in-depth analysis of the transient processes within the pivotal series RLC circuit in fast chargers, encompassing zero-input responses and sinusoidal AC excitation responses. The transient processes are categorized into overdamped, critically damped, or underdamped states based on circuit element parameters, with initial conditions and power supply phase determining whether the circuit transitions directly into a steady-state process when stimulated by sinusoidal AC. This research contributes to a deeper understanding of the RLC circuit within smartphone fast chargers and serves as a valuable reference for advancing the development of fast charging solutions.
Research on Vegetable Pricing and Replenishment Strategy Based on TOPSIS Method and Simulated Annealing Algorithm
Authors: Cong Fanpu , Luan Qi , Xu Peng
Published: January 2024

By mining the relationship between categories and individual products, this paper puts forward enterprise replenishment and pricing strategies under different conditions. First of all, from the 49 kinds of vegetables sold, the TOPSIS method based on entropy weight is used to select the top 20 important items by taking the market demand and excess income as the first-level index, and taking the historical sales rate, average daily sales volume, variance of sales volume, vegetable loss rate and unit profit as the second-level index. Then, based on the concept of complementary and alternative goods, through the Spearman correlation coefficient, and using the weighted correlation coefficient method, select the top 9 items, such as ginger, garlic, millet pepper combination and so on. Using these selected items, taking the profit maximization of fresh merchants as the objective function and the demand of each category as constraints, a 0-1 integer nonlinear programming model is established. Then, the simulated annealing algorithm is used to simulate the planning for 1000000 times, and the pricing strategy and supply plan of the enterprise on July 1st are obtained, and the maximum profit on that day is 2098.17 yuan.
Research on multi-beam problems based on geometric modeling and underwater detection
Authors: Guo Huaijian , Song Hanshuo , Zhou Zhengyu , Lv Lingrui , Zang Chang
Published: January 2024

This paper aims to establish and solve the mathematical model of coverage width under multi-beam bathymetry, rising from a one-dimensional sea area measurement problem to a two-dimensional sea area measurement problem. First, this paper takes the center of the sea area as the coordinate origin, establishes a one-dimensional coordinate system, and derives the functional relationship between the coordinate position of the measured ship axis and the angle of the seabed slope through the triangle edge relationship. At the same time, the mathematical relationship between the depth of the water body and the position of the measuring ship is constructed, and the relationship between the single coverage width of the detection system and the depth of the water body is found using the sine theorem. Subsequently, this paper established a two-dimensional sea area measurement model. Taking the center point of the sea area to be measured as the coordinate origin, a three-dimensional coordinate system was constructed. The normal vector projection direction was taken into account to obtain the new slope angle, and the two-dimensional sea area measurement was converted into a one-dimensional sea area. Measurement. Finally, this article uses MATLAB to conduct simulation experiments and gives the relationship between the coverage width and the position of the survey ship at different angles between survey line directions, providing an effective reference for the multi-beam sounding strategy.
Research on Computational Mechanics Construction of Bridge Civil Engineering Construction Based on Computer Big Data Technology
Authors: Wei Junyi
Published: January 2024

In this paper, a 3D visualization system for bridge construction management is established based on VRP virtual platform. The bridge construction monitoring data management system is designed on the platform of Access database and the object processing technology of VRP. Starting from the basic theory of construction monitoring of cable-stayed bridge, the system realizes the problem of construction error identification in the monitoring process and using the recognition results to compensate and modify the finite element model. The system mainly realizes the functions of data editing, query, data analysis, data visualization, bridge information introduction and so on. It solves the key problem of using relational database to form various reports quickly and intelligently.
Research on Multibeam Bathymetry Based on Geometric Analysis Models and Brute Force Search Algorithm
Authors: Liu Ziyu , Zhao Yuxiang , Wang Pu , Ju Jinli , Lu Weiquan , Zhang Jiarong , Zheng Wei , Li Ni
Published: January 2024

In recent years, multibeam sonar systems have gradually replaced single-beam sonar systems. They have become widely accepted and extensively used in the field of seabed depth detection because they overcome the lack of data between survey lines inherent to single-beam systems. The issue of high redundancy in seabed depth data has been a long-standing and challenging problem to solve. To minimize the redundancy rate of seabed depth data as much as possible, this paper conducts a study on the redundancy rate of multibeam sonar systems using different depth measurement methods based on geometric analysis and brute-force search algorithms. This paper establishes a geometric analysis model that utilizes a brute-force search algorithm to enumerate all possible outcomes and selects the optimal solution. The results, upon comparison, show that the redundancy rate of the equidistant uniform survey line method is one-sixth of that of the traditional grid measurement method, indicating good practicality and significantly improving the data space utilization of seabed depth measurement systems.
Application Scenarios of Edge Computing in Conjunction with Cloud Computing and Artificial Intelligence
Authors: Li Zehao
Published: January 2024

The proliferation of mobile technology products and the development of wireless communication networks have given rise to numerous application scenarios that prioritize higher computing power, better privacy protection, lower latency, and lower energy consumption. Given these requirements, edge cloud computing has emerged as a critical component of computing platforms and a key enabler for communication technology. In this paper, the concept of edge computing and its synergies with cloud computing and artificial intelligence are explored. This paper outlines the various advantages that can be obtained through the collaboration of edge computing and cloud computing. Specifically, it focuses on existing and potential scenarios where this collaboration can be beneficial. These include the Internet of Things, mobile gaming, metaverse and extended reality. The potential for innovation in these fields is immense and the possibilities are vast. The paper also presents the definition of artificial intelligence and its opportunities in the field of communication networks. Particularly, a discussion of feasible models for integrating artificial intelligence with edge computing concludes the paper.
Enterprise Value Assessment Based on Real Option Approach: The Case of SEMCORP
Authors: Li Wenrui
Published: January 2024

As the core power source of new energy vehicles, the lithium battery industry has ushered in a high-speed development, and has become the most widely used battery technology system. Due to the industry's high technical barriers, imperfect system, high volatility risk and other characteristics of the lithium battery enterprise value the overall assessment of the difficulty of ordinary investors to make a more accurate judgment. As an important representative of the lithium new energy materials industry, SEMCORP is in a golden development period. Based on the research results of previous researchers on enterprise value assessment, this paper examines the value assessment of n SEMCORP. Specifically, this paper applies a two-stage growth model to calculate the present value and evaluates the potential value separately with the help of an option pricing model to obtain its overall value. After analyzing, conclude that SEMCORP 's shares are overvalued. This paper can provide decision-making references for the investment and financing of Chinese lithium new energy materials enterprises, as well as further enriching the application of enterprise value assessment methods.
Can CAR T Cell Therapy Be a Good Way of Treating Other Diseases
Authors: Liu Xuze
Published: January 2024

CAR T-cells (CARs) have been used to treat a variety of cancers since their discovery in the late 1980s. Because of its efficacy, it has been used as a focus of research and a breakthrough point in cancer treatment, and its principles can also be a way to treat other types of diseases. Therapeutic trials focusing on different diseases and proving its effectiveness in treating different diseases or having been put into medical trials have shown that it works as part of the immune system to treat diseases other than cancer. The ability of CARs therapy to treat other diseases has been successful in different clinical and other trials, and in the future it may be possible to combine it with other therapies or immunotherapies (such as immune checkpoint inhibitors or chemotherapy) to treat other The ability of CARs to treat other diseases may contribute to space exploration and other important steps in human history.
Result of Human-induced Hybridization--Cat Born with Genetic Defect
Authors: Hu Jintian , Zhao Runbing
Published: January 2024

Advancements in genetic science have facilitated the creation of popular cat breeds like the Scottish Fold and Munchkin, often admired for their distinct physical features and affable personalities. While these innovations mark a significant stride in the domain of genetic manipulation, they are not devoid of controversy, often giving rise to pressing ethical concerns. This arises primarily due to the potential health issues that such breeds might inadvertently inherit, coupled with diminished survival skills should they find themselves in the wild. Moreover, this pursuit of desired traits sometimes overshadows the imperative of ensuring robust animal welfare standards. As humanity delves deeper into the realms of genetic science, striking a harmonious balance between technological progression and safeguarding the intrinsic rights and well-being of these animals becomes increasingly pivotal. This underscores the compelling need for ethical responsibility in steering genetic advancements, fostering a future where technology serves as a boon rather than a bane in the evolutionary narrative of these beloved feline companions.
Digital Intelligence Analysis for the "First Mile" of Agricultural Product E-commerce Supply Chain
Authors: Du Yulin
Published: January 2024

At present, with the continuous development of Internet technology, the development trend of "Internet plus agriculture" is increasingly obvious. With the increasing attention of the academic community to rural e-commerce, the supply chain management of agricultural product e-commerce has become one of the key research topics today. However, there is still a research gap on how to achieve efficient and precise integration of the "first mile" of agricultural product e-commerce supply chain, lacking a unified understanding and solution. Therefore, this article focuses on the digital intelligent countermeasures for the e-commerce supply chain of agricultural products in the "first mile". Firstly, analyze the current development status of agricultural product e-commerce and the specific reasons that affect the precise integration of smallholders and e-commerce enterprises, and then conduct strategic research to provide digital solutions for achieving the "first mile" e-commerce supply chain of agricultural products. The research results of this paper can provide decision-making guidance for the digital and intelligent development of agricultural product e-commerce supply chain, and promote the continuous development of "Internet plus agriculture".
Yellow River Water and Sand Monitoring Data Model based on SARIMAX Rediction
Authors: Li Xingyu
Published: January 2024

With the evolution of history, the problems faced by the Yellow River Basin have been an important research topic in hydrology. In this paper, for the problems in the monitoring of water and sand in the Yellow River, a seasonal time series model of the monitoring data is established based on the time series prediction model, and the CUSUM algorithm is used to test the model. First, the data are processed to calculate the spearman correlation for each pair of categories. Then, for analyzing the description of single dimensional data, data descriptive analysis was used. Next, the data were forecasted using a seasonal time series forecasting model. Finally, the seasonal time series prediction model was used to predict water fluxes and solved using double interpolation to obtain the predicted effect plots for the next ten years. The proposed model is close to the reality, can reasonably solve the proposed problem, and is characterized by high practicality and high efficiency of the algorithm.
The Treatment for Athletic Pubalgia
Authors: Yang Zihao
Published: January 2024

Athletic Pubalgia injury is a common sports injury that troubles the sports life of ordinary people and the performance of athletes. This paper aims to help everyone briefly understand the anatomical mechanism of injury, treatment methods, and precautions. Also, the most important part of this paper is that the treatment of Athletic Pubalgia. It divided in two parts, one is on surgical grounds, and other one is on conservation treatment grounds. This paper shows the correlation between the two treatments. At last, this paper shows the prognosis of this injury. Also, it shows the different effects of ordinary people and athletes. Through this paper, it will be more evidence-based when dealing with Athletic Pubalgia injuries in daily life, enabling people to have a clearer understanding of the ways to recover from injuries and illnesses, and to recover their health as soon as possible.
The Impact of External Events on the Industry: Taking the Pharmaceutical and Chip Industries as Examples
Authors: Wang Yiao
Published: January 2024

The Covid-19 pandemic and the Sino US trade war have been the focus of the international community in recent years. By using the methods of literature review and data analysis, this paper analyzes the short-term fluctuations and long-term development trends of medical devices, chemical pharmaceuticals, Chinese patent medicines and biopharmaceuticals in China under the pandemic situation. It also studies the impact of the measures taken by China and the United States in the chip game, as well as the political significance of the relaxation of chip restrictions in the United States: it seems to be courting China, but in fact it is to suppress Chinese chips more forcefully. The research results of this paper can provide reference suggestions for the policy authorities: there is a large development space for Chinese patent medicine and biopharmaceutical, and information technology also has broad application prospects in the pharmaceutical industry. China should continue to strengthen the research and development of chips to cope with the new round of offensive of the United States.
Prediction of Electric Load Neural Network Prediction Model for Big Data
Authors: Huang Zifan , Zhong Hongkui , Chen Wenyu , Wang Jianhong
Published: January 2024

Firstly, this article analyzes the distribution patterns and interrelationships of sales volume among different categories of vegetables and individual products. Based on the results of the stability test of the daily sales volume of six types of vegetables, the data of each type of vegetables is divided into 7 sub-data sets according to the week to explore the distribution patterns of vegetable sales volume and time. Subsequently, this article conducts a distribution test on 42 sub-data sets of the six types of vegetables, and finds that the Weibull distribution is the optimal fitting distribution. Spearman correlation coefficients are used to judge the correlation between the six types of vegetables based on scatter plots. The results show that there is weak correlation among different categories of vegetable products. An Apriori algorithm is used to analyze the correlation of 246 individual products, and 24 frequent itemsets are found. Then, a heatmap analysis is conducted on the individual products in each set, which shows strong correlation within the set. Finally, this article divides the daily sales volume of each vegetable category into two time scales, and uses the ARIMA(p,d,q) model and the ARIMA-LSTM model to predict the sales volume for the following week, which facilitates the construction of a sales volume-price model based on future predicted sales volume to predict the price of vegetables for the following week, and further analysis can be conducted.
Driverless Planning and Decision-Making based on GRU
Authors: Li Jiaqi , Ouyang Zhixin , Ren Haojing
Published: January 2024

In the wake of the swift advancement of artificial intelligence, driverless technology has progressively emerged as a revolutionary technology. The existing driverless technology primarily relies on advanced sensors, artificial intelligence and machine learning algorithms, with a view to perceiving and analyzing the surrounding environment in real time, and making driving decisions accordingly. At the present time, despite the fact that driverless technology has introduced a lot of convenience to human travel, it still encompasses a significant number of challenges, such as safety, perception technology, vehicle control, road planning, cost and other issues. In a similar vein, the safety issue is an unavoidable part of the discussion on the driverless. Driverless vehicles require robust system safety and protection mechanisms. This paper is designed to establish a data model by analyzing the NGSIM dataset, and to probe the driverless perception capability and decision-making on intelligence in behavior-aware motion perspective with GRU approach. Eventually, it was concluded that neither too many nor too few neighboring vehicles should be taken into account when forecasting the trajectory of each vehicle in the coming years, while the appropriate neighboring vehicles should be selected to achieve the best prediction results.
Problems of ESG that Prevent Its Integration in Investment Decision-Making: Evidence from Investors
Authors: Chen Kaiting
Published: January 2024

The growing importance of ESG considerations in investment decisions reflects a transformative shift in how investors evaluate the sustainability and ethical impact of firms. As ESG integration becomes increasingly popular among investo rs, it is important to analyze how such an integration can affect investment decisions. While previous articles discussed reasons why investors integrate or not integrate ESG in making investment decisions, they did not probe into the question of how problems of ESG itself affect its integration in investment decision-making. This essay explores this topic by analyzing previous articles about ESG, its traits, and investors’ views on taking into account ESG factors in investment decision-making. It is concluded that some problems of ESG, including the absence of agreed criteria and lack of transparency in the rating process, can prevent ESG integration from being effective in making investment decisions.
Fluctuation of Exchange Rates Caused by Monetary Policy Divergence: Empirical Analysis between China and USA
Authors: Gao Runjia
Published: January 2024

In the past ten years, because of the differences in economic history and social political scenarios between China and the US, the two countries have already experienced a divergence in monetary policy. Asides the domestic macroeconomic implications, the divergence would potentially cause changes and fluctuations between the exchange rates of the two currencies. Through theoretical analysis on macro and international economics as well as econometrics modelling utilizing Python and Stata-17, this research constructed a time series vector autoregression model quantifying the relationship between the USD/CNY exchange rate and monetary policy changes of both the US and China. This research found that the monetary policy changes in the two countries would not fundamentally change the USD/CNY exchange rate level but would cause fluctuations. Based on the findings, the article made recommendations for both central bankers and investors participating in the foreign exchange market to deal with the monetary policy divergence of the two major global economic entities.
Energy Management System: The Engine for Sustainable Development and Resource Optimization
Authors: Zhang Jiayi
Published: January 2024

In the background of traditional energy sources, people primarily rely on fossil fuels for electricity generation, but this leads to environmental issues and energy dependency. Therefore, the introduction of the Energy Management System (EMS) becomes crucial, which helps optimize electricity distribution and management to integrate new energy sources effectively, achieving a more sustainable, stable, and efficient electricity supply. It is not just a simple technical solution, but is a strategic approach aimed at optimizing the use and allocation of energy resources to maximize efficiency as well. The intelligent management provided by the EMS enables collaboration between new energy sources and the traditional power grid, reducing electricity costs and decreasing carbon emissions. This overview aims to delve into the core concepts, technological applications, and future trends of the EMS. It will comprehensively analyze the practical applications of the EMS in various fields from various perspectives, including system architecture and data analysis methods, and provide an in-depth understanding of their positive impact on energy efficiency, environmental sustainability, and economic development.
Analysis of Investors' Investment Choices for Oil Companies
Authors: Zhang Junxi
Published: January 2024

This paper delves into the significance of oil within the realms of energy supply, transportation, and the chemical industry, all while exploring the unique challenges encountered by diverse categories of investors. Employing a multifaceted approach encompassing risk analysis, profitability assessment, and market ratio analysis, this study meticulously dissects the financial records of select oil companies. Consequently, it formulates insightful recommendations aimed at enhancing investor decision-making processes and fostering stronger corporate investor relations. The primary findings of this research emphasize the intricate interplay of numerous factors that sway investors' choices, necessitating a comprehensive evaluation that takes into account risk, profitability, and prevailing market conditions. This study not only identifies these influences but also offers specific, actionable guidance to navigate them effectively. The implications of this research extend to the practical domains of investment decision-making and corporate strategic planning, thus underscoring its intrinsic value in shaping both individual investment portfolios and the strategic directions of oil enterprises.
A Study of Controlling Shareholds' Tunneling Behavior
Authors: Ou Zhuohuang
Published: January 2024

Since the establishment of the Shanghai Stock Exchange and the Shenzhen Stock Exchange in the 1990s, China's capital market has emerged. Over the years, the domestic capital market has achieved certain results, but negative phenomena have gradually emerged, and the problem of tunneling is one of the representative issues. A concentrated ownership structure is prone to breed tunneling behavior, which results in a decrease in company value, damage to the interests of minority shareholders, and a reduction in market efficiency. This paper, through the study of relevant literature, summarized the behaviors of controlling shareholders' asset-stripping companies that harmed people's interests, listed different methods used by controlling shareholders for asset stripping, explored the causes of controlling shareholders' asset-stripping behavior, and examined the consequences of controlling shareholders' asset stripping methods.
The Application of Artificial Intelligence in Game
Authors: Pan Ziyu
Published: January 2024

AI has been extensively applied in various aspects of game development over the past few decades. One critical application is the use of AI algorithms to simulate intelligent decision-making processes for non-player character behavior. Another application is procedural content generation, where AI algorithms generate game content such as level designs or missions to enhance gameplay diversity. This paper aims to explore the application of AI in game development by analyzing specific cases and discussing the current state of the field. The paper also focuses on related topics such as motion and physics simulation, as well as dynamic adaptation. The current state of using AI to enhance realistic motion and physics simulation in game development is further examined. In summary, this paper provides a comprehensive overview of the application of AI in game development, highlighting its significance. The paper concludes with a summary and future outlook of the entire study.
Analysis of the Acquisition of Blizzard by Microsoft
Authors: Bao Jie , Wang Ziyi , Zhang Zhuoxuan
Published: January 2024

As matter of fact, Microsoft, the world's leading technology company, has been looking for opportunities to expand its business in various fields in order to enhance the overall performances and build the ecology. In recent years, Microsoft has always been one of the major players in the gaming industry. With this in mind, it has begun the steps for acquisition of Blizzard. On this basis, this study will analyze the cases of the acquisition. To be specific, the balance sheets and financial statements variation during the processes will be analytically evaluated. In addition, the market proportion change of the company will also be analyzed. Based on the estimations, the impacts as well as overall evaluation for the M&A will be discussed. According to the analysis, the suggestions of the industry will be proposed at the same time. Overall, these results shed light on guiding further exploration of M&A expanding strategy.
Principle and application of amplifier of fiber on fiber communication
Authors: Wang Jinda
Published: January 2024

As the most widely used and the most reliable way of communication in the world today, the development of optical fiber communication will inevitably affect the world. As an important component of fiber communication system, the development of fiber amplifier directly affects the development of fiber communication. The fiber amplifier is divided into semiconductor fiber amplifier, mixed with rare earth element fiber amplifier and nonlinear fiber amplifier. This paper aims to study the principle, function and equipment of the fiber optic amplifier. Some limitations and prospects for the future are also proposed.The principle, function and limitation of erbium-doped fiber amplifier are emphasized. It is a summary of the development of fiber amplifier in recent years, and it is convenient for other scholars to find and study the data of fiber amplifier. This paper summarizes the development of fiber amplifier in recent years, and explains the basic principles of fiber amplifier, so that other scholars to find the data of fiber amplifier, convenient for other scholars to study.
Research on the analysis of Yellow River water and sand monitoring data based on ARIMA model
Authors: Liu Yan , Bai Xue , Shi Qian , Liu Sijia
Published: January 2024

The article uses hydrological data from a hydropothe paperr station in Xiaolangdi Reservoir spanning six years. the paper use mutability analysis, seasonal decomposition method, and ARIMA model to reveal hydrological change trends and cyclic characteristics. the paper also use the CUSUM algorithm to identify the water-sand flux mutation points. The study's findings demonstrate that ARIMA(1,2,1) can be used to predict trends in total water flux and total sand content. It also reveals that there is significant seasonality and periodicity in the water-sand fluxes. These results offer a solid scientific foundation for decision-making and have substantial implications for the management and control of the region's water resources.
Research on 2D SDE Method of Fluid Field Effect above Airfoil at Transonic Speed
Authors: Li Xinhao
Published: January 2024

In this research, a Python-centric approach is proposed for simulating fluid dynamics over transonic airfoils. The study employs the finite difference method to solve the small disturbance equation (SDE), incorporating Newman boundary conditions. Iterative computations are adeptly managed using the successive over-relaxation (SOR) method. These methodologies, as validated through rigorous code testing, enable precise calculations of velocity distributions and vivid visualizations of fluid velocity streamlines. For this investigation, the airfoil is conceptualized as a minor obstruction and is abstracted into a trigonometric function. A pivotal aspect of this study is the exploration of the interplay between the Mach number and the 'shark angle'—a critical determinant in aerodynamic performance. Simulation outcomes reveal an inverse relationship between the Mach number and the airfoil's shark angle; a surge in the Mach number corresponds to a reduction in the shark angle. These findings, encapsulated in flow field diagrams, offer invaluable insights for the strategic design and optimization of airfoils, aiming to maximize lift while concurrently curtailing drag, thereby enhancing overall aerodynamic efficiency.
Optimization of vegetable commodity replenishment and sales strategy based on time series model and multiple linear regression model
Authors: Xu Ke , Chen Wenqin , Wang Chengzhi
Published: January 2024

Vegetable commodities have a short freshness period and their quality can change from good to bad. So the study of automatic pricing and replenishment decision of vegetable commodities is of great significance for the superstore itself. In this paper, we first discuss the total sales volume of each vegetable category (cost-plus pricing by single product selling price, wholesale selling price and wastage rate), and use the construction of multiple linear regression model to discuss the relationship between the total sales volume and the above three indicators. Next, the least squares estimation algorithm and Matlab were used to simulate and analyse the correlation between the cauliflower and foliage categories. In order to formulate the total daily replenishment and pricing strategy for the vegetable category in the coming week, a time series model was built to predict the total sales volume for the next 7 days by using 30 days of data changes. Finally, a moving average method is used to forecast the total daily replenishment amount, which maximises the supermarket's profitability.
Analysis and Research on Load Behavior of H-shaped Steel Concrete
Authors: Qin Yi
Published: January 2024

Steel-reinforced concrete (SRC) possesses excellent strength and numerous advantages over traditional concrete, making it extensively used in high-rise buildings and large-span bridge structures. This paper commences with the constitutive relationship of steel reinforcement in SRC, the nominal stress-strain conversion, and real stress-strain transformation. It employs Abaqus for nonlinear finite element analysis to study the stress variations in compressed SRC columns subjected to reciprocating loads and examines load-displacement curves. The paper analyzes the hysteresis loops of SRC columns under reciprocating loads, the trends in skeleton curves, energy dissipation, and stiffness degradation. Consequently, it concludes that the variation of compressive stress along the axis of SRC columns is consistent with the change in bearing capacity. Under reciprocating loads, the stress at the lower end of the SRC column is greater than that at the upper end, suggesting the need for reinforcement in the lower portion. The hysteresis loop of SRC columns exhibits a rich characteristic, with increasing energy absorption as displacement increases.