bluuebunny/crossref_metadata_2025 huggingface dataset:
DEVELOPMENT OF A SCOUT MOVEMENT-BASED MENTAL HEALTH LITERACY MODULE TO PREVENT BULLYING
Authors: Ngoranubun Selestina Vilmas , Alfianto Ahmad Guntur , Rahmadhani Rahmaniah , Kurniyanti Mizam Ari
Published: June 2024

Bullying is a negative behavior that has an impact on mental health problems. Cases at school make bullying often carried out by students / adolescents. Scouting is one of the movements that exist in schools as agents of change and examples of leader values in schools. Literacy module as a health promotion media effort in bullying prevention. The purpose of this study was to develop a mental health literacy module based on the scout movement to prevent bullying. This research is a development research by testing modules. Design with a 4D model approach (defining, designing, developing, and disseminating). The respondents in this study were experts in the field of mental and community nursing, as well as 4 scout teachers. Assessment using content validity ratio (CVR) and Content Validity Index (CVI). The results at the defining stage were bullying problems in schools, the design stage with the creation of literacy modules based on the scout movement, stage three development with the results of CVR (20.5) and CVI (0.46) and stage three module dissemination. Analysis of module development through a series of 4 stages is carried out with the results of development by 4 experts in a ratio of 3 statements that are not accepted on the feasibility and accuracy indicators. However, from the overall results, the validity of the content is declared appropriate. The conclusion that the development of a mental health literacy module based on the scout movement to prevent bullying was stated to be appropriate by 4 experts.
Self-Awareness: Analysis of Nursing Management in Treating Patients with Type 2 Diabetes Mellitus
Authors: Rozani Leni , Ferasinta Ferasinta
Published: June 2024

Diabetes Mellitus type 2 is a disease with the largest number of sufferers of all existing diabetes diseases. Diabetes mellitus type 2 can be prevented by modifying lifestyle and lifestyle. This study aims to determine the self-awareness of groups at high risk of developing Diabetes Mellitus. This research uses a qualitative descriptive research method with a case study approach. Data was obtained by interviewing three high-risk participants who had a family history of Diabetes Mellitus. The interview results were analyzed using the Corbin and Strauss method which consists of three stages, namely open coding, axial coding and selective coding. The results of the research show that there is a similar pattern and produce selective coding, namely the lack of knowledge, attitudes and behavior in preventing Diabetes Mellitus which is not yet good in the community. Suggestions in the research are for health service providers to be more active in terms of prevention, such as providing education to residents so that residents can maintain their health. independently, especially in terms of a healthy lifestyle.
Overview of Self-Directed Learning Readiness (SDLR) in First-Year Nursing Students
Authors: Astuti Anggia Astuti , Wijaya Dodi , Abidin Zainal , Dwi Fibriansari Rizeki
Published: June 2024

Self-directed learning (SDL) solves learning challenges using various learning tools. Nursing requires lifelong learning, and SDL is an important skill for practitioners to stay current and effective. It is required of nursing students to embrace SDL and hone these abilities. Nevertheless, there is no indication of this novel procedure in Lumajang. This study aims to assess nursing students' preparation for SDL and its impact on learning outcomes. This quasi-experimental study purposefully included 91 students who carry out basic nursing clinical practice as participants. The instrument used in this study was the Self-Directed Learning Readiness Scale (SDLRS) questionnaire developed by Fisher. The results of this study showed that there was an increase in the SDLR level from 9 students (9.9%) having a high SDLR level to 78 students (85.8%) and 82 students (90.1%) having a moderate SDLR level to 13 students (14.2%). The nursing students' average SDL preparedness level has a substantial impact on learning outcomes. Nursing training institutes should give the resources required to adopt SDL as a primary teaching technique to ensure competent lifelong professionals.
Estado nutricional, tolerância alimentar e qualidade de vida de pacientes submetidos à cirurgia bariátrica
Authors: Chagas Shaiane Caetano , Santos Nathalia Maria Cavalcanti dos , Carvalho Ana Clara Lacerda Cervantes de , Souza Anderson Liberato de , Tomiya Marília Tokiko Oliveira , Sousa Bruno Soares de , Cruz Luana Carla Lacerda da , Cavalcanti Daniella Claudia de França
Published: June 2024

A cirurgia bariátrica (CB) e metabólica destaca-se no manejo da obesidade e na melhora da qualidade de vida. Porém, estudos demonstram que o desencadeamento de intolerância alimentar desfavorece o processo de continuidade da perda de peso, e acarretando o aumento do peso. Diante disso, o estudo objetiva avaliar a incidência de desenvolvimento de intolerância alimentar e a respectiva repercussão no estado nutricional e qualidade de vida em pacientes no pós-operatório de CB. Trata-se de um estudo observacional do tipo transversal, prospectivo, realizado em Recife/PE. Foi aplicado um questionário contendo dados socioeconômicos, presença de intolerância alimentar, identificação de alimentos propensos, sintomatologia desenvolvida e avaliação antropométrica. Por fim, foi avaliada a perda de peso e verificada a qualidade de vida através do questionário Bariatric Analysis and Reporting Outcome System. A amostra foi constituída por 64 pacientes, onde 76,6% foram submetidos ao Bypass Gástrico. Além disso, 67,2% possuíam intolerância alimentar. Em relação ao estado nutricional e intolerância alimentar, pacientes com ausência de intolerância a farinha de mandioca apresentaram um menor Índice de Massa Corporal (IMC) pré-CB quando comparado aos que não possuíam intolerância (p=0,014). Além disso, houve associação do estado nutricional e sintomas de intolerância alimentar na presença de diarreia e síndrome de dumping, com um menor média de IMC pós-bariátrica quando comparados com os que não tiveram esses sintomas. Já os que apresentavam distensão abdominal tiveram uma menor média de IMC pré-bariatrico. Quanto a intolerância alimentar e qualidade de vida, pacientes com ausência de intolerância à fritura apresentaram mediana de qualidade de vida classificada como “muito melhor”, enquanto os que apresentaram intolerância tiveram a mediana de qualidade de vida classificada como “melhor”, esta situação também foi encontrada com relação à farinha de trigo. Observou-se nesse estudo que os indivíduos submetidos à cirurgia bariátrica apresentaram alta prevalência de intolerância alimentar e baixa prevalência de diminuição da qualidade de vida associado a intolerância alimentar e sua sintomatologia.
Türk Tarih Kurumu Arşivinde Bulunan “Enver Paşa’nın Evrak-ı Metrukesi”
Authors: Nurdan Semiha
Published: June 2024

Türk Tarih Kurumu Atatürk’ün eseridir. Gazi Mustafa Kemal, Türk milleti tarihini yabancılardan değil, bizzat kendi tarihini, kendisinin araştırması için Türk Tarih Kurumunu kurmuştur. Türk tarihiyle ilgili bilgiyi dünya bilim insanları ile paylaşılması gerektiğini vurgulamıştır.

Türk Tarih Kurumu içerisinde yer alan arşiv ise neredeyse kurumun kuruluşuyla birlikte faaliyetlerine başlamıştır. Arşivde bulunan diğer koleksiyonlar gibi bu makaleye konu olan Enver Paşa evrakları da kuruma bağış yoluyla kazandırılmıştır.

Bu makalenin yazılış amacı, Osmanlı Devleti’nin en uzun yüzyılı olarak nitelendirilen 19. yüzyılın sonu ve 20. yüzyılın başlarında devletin içinde bulunduğu harp ortamında cepheden cepheye koşmuş bir komutanın geriye kalan evrak-ı metrukesini araştırmacılara tanıtmaktır. Analitik tasnif çerçevesinde gruplandırılan arşiv materyalleri sekiz başlık altında toplanmıştır. Evrakların belli başlıklar altında sınıflandırılması, araştırmacılar için kolay çalışma imkânı sağlaması açısından bu yönteme başvurulmuştur. Bu hususta Türk Tarih Kurumu Arşivinde Enver Paşa Koleksiyonu içerisinde bulunan belgelerin türünün ve içerik bilgilerinin ne olduğu bilgisi araştırmacılara sunulmuştur. Son olarak sekiz başlık altında toplanan evraklar ve içerikleri hakkında bilgi verilmiştir.
Integrating Complex Functions in Certain Situations by Two Methods
Authors: Zhu Runqiu
Published: June 2024

This article will mainly discuss several ways of integrating complex functions. In real field, the basic idea of integrating a function is to find its anti-derivative. However, it is challenging to find an anti-derivative of a complex function that is not differentiable at some points. This is because that in complex field, the derivative of a differentiable complex function must be also differentiable. Thus, finding the anti-derivative of non-differentiable function in complex plain is unapproachable. Moreover, even though a differentiable complex function is given, computing the anti-derivative will be very complicated or time-consuming. As a result, exclusive methods are required to calculate the integral of complex functions. Fortunately, Cauchy Residue Theorem and Cauchy-Goursat Theorem provide comprehensive ways for computing the integrals. It is crucial to realize their importance and they will be discussed in the following context. Additionally, the specific steps of application will also be shown. This study demonstrates clearly that the Residue theorem is a power method to handle with a series of complex integrals.
Study on insurance in earthquake-prone areas based on BP neural network and logistic regression model
Authors: Wang Bohong , Tao Xuanye , Min Yan
Published: June 2024

The frequent occurrence of extreme events poses major challenges to the insurance industry and affects its sustainable development. To provide insurance recommendations for extreme disaster areas, this paper combines BP neural network model, principal component analysis method and Logistic regression model to establish our insurance model. First, we processed the data. Then, the BP neural network mode used to correlate 33 kinds of earthquake correlation indexes with earthquake probability and make prediction. To make the data more representative, we conducted dimension reduction prediction through principal component analysis, screened out 8 important factors, and identified 3 principal components. We then performed Logistic regression analysis based on these three principal components and used the Logistic model to decide whether to conduct insurance. After the experiment, the accuracy of the model can reach 78.9%, which can provide a reliable prediction of the disaster in the region, to help the insurance company to make a decision whether to insure in the region.
Application and Impact Analysis of Intelligent Financial Systems in Small and Medium-Sized Manufacturing Industries
Authors: Ji Jiahao
Published: June 2024

This paper explores how smart financial systems can empower small and medium-sized manufacturing industries by integrating artificial intelligence, big data analytics and cloud computing technologies to provide customised financial service solutions for the sector. The study outlines the core challenges faced by small and medium-sized manufacturing industries, such as financing difficulties, lagging risk management and operational inefficiencies. The core components of the smart financial system are detailed, including functional modules such as automated credit assessment, supply chain finance optimisation, cost prediction models and personalised insurance product recommendations. This paper proposes strategies to address data security, technology acceptance, and regulatory compliance issues that may be encountered during the implementation process, and emphasises the importance of building a good ecosystem between the government, financial institutions, and technology enterprises to comprehensively support the intelligent transformation and sustainable development of the small and medium-sized manufacturing industry.
Economic Development Potential of Renewable Energy in China
Authors: Chen Danying
Published: June 2024

The economy is growing quickly, and the demand for energy is rising daily. The third energy transformation that human society is undergoing is only possible through fostering the growth of renewable energy sources. When it comes to the study, creation, and utilization of renewable resources, China's socioeconomic and geographic conditions are superior. This study examines the utilization rate and cost of renewable energy over various time periods and breaks down the growth of renewable energy in China into three stages. Finally, the author looks for a path that will best serve China's development and make use of renewable energy sources. Renewable energy will have enormous economic potential in China in the future as science and technology advance.
Solar Array Mechanism Based on Deployable Structure
Authors: Ma Shangyou
Published: June 2024

Spacecrafts such as satellites consume large amounts of electrical energy to carry out their missions in space. Due to the limited weight and space constraints, solar arrays become a top priority to meet the long-term operation of high-power loads. The widespread use of solar arrays is one of the necessary tools for sustainable development, which is not only related to the study of materials but also to explore more possibilities of utilization in conjunction with deployable structures. Based on the theoretical kinematic analysis and the scissor structure, this study puts forward a solar array mechanism of the scissor structure and revolute joints in the several regular polygons that connected each other. It comprises a sizeable octagonal loop and four medium-sized hexagonal rings. Because the simplified structure uses fewer rods, the failure rate is lower. A specific input angle can determine the configuration. A powerful and efficient solar array mechanism based on deployable structure was designed.
Analysis of Chaos of Chen Equation
Authors: Zhao Zhihui
Published: June 2024

As a matter of fact, chaos was first discovered by Poincaré. Then, the Edward Lorenz observed by chance the chaotic phenomenon when her predicted the weather. More powerful computers greatly aided chaos theory in recent years. With this in mind, this study analyses the chaos of Chen equations, the stability of Chen system, and the sensitive of parameters based on the staggered methods. The instability of the system is obtained by Routh-Hurwitz criterion. In addition, the numerical solution is obtained by Runge-Kutta method. Then, one draws the Chen attractors. Finally, the sensitive analysis in a new way implies that the solution is sensitive to the initial values, and the sensitivity relationship between the same component to different parameters is linear, but that between the different components to the same parameter is chaotic, and the different component to different parameters is also chaotic. This study is a multi-dimensional and comprehensive analysis of sensitivity analysis.
Sustainable Climate Action Plan for Haiti, focusing on renewable energy
Authors: Zhuo Julia
Published: June 2024

Haiti is one of the poorest and most vulnerable countries in the world that faces a multitude of challenges; its environmental conditions being one of its major concerns. There are many aspects regarding its climate problems, but the purpose of this report focuses on the adoption of pyrolysis, alternative materials for cookstoves in Haiti, as well as Haiti’s potential in renewable energy. The methods suggested above are mainly to address the areas of waste management, deforestation, carbon emission, and energy generation. In addition to these methods, this research also briefly examines some of Costa Rica’s sustainable climate policies and Haiti’s opportunity to adopt such policies. The ultimate purpose of this report is to also raise awareness for developing countries, such as Haiti, hoping to gain public effort to help improve the environmental quality of these countries.
Research on the Prediction of the Global Price of WTI Crude
Authors: Xie Fei
Published: June 2024

As the cornerstone of industrial development, crude oil prices have attracted international attention. However, due to the frequency of price fluctuations and the sensitivity to the international economic situation, crude oil prices are difficult to predict. Due to significant differences in prices before and after 2007, this will increase the difficulty of prediction and decrease its accuracy. The ARIMA model, as a typical prediction model, is highly favored by scholars from various countries due to its accuracy and adaptability. This article will use the ARIMA model to forecast the one-year future prices. The conclusion is as follows: in the two months, the prices will have a slight upward trend, while in the next year, the overall trend will show a relatively obvious downward trend. Therefore, this article believes that it is not recommended to invest in crude oil in the short term. At the same time, this article believes that ensuring domestic economic stability can reduce the impact of international economic shocks and thus gain an advantageous position in international trade.
Exploration and Applications of Carbon Utilization and Sequestration Technologies
Authors: Dong Fengjie , Zhu Xiyin
Published: June 2024

In recent years, the surge in global energy demand due to rapid technological advances has led to a significant increase in greenhouse gas emissions, resulting in a climate and energy crisis. Against this backdrop, the challenge for the global energy sector is to weigh the advantages and disadvantages of different carbon capture, utilization, and storage (CCUS) technologies in order to select the most appropriate method for each situation. This study focuses on Enhanced oil recovery (EOR) and ocean sequestration technologies and analyzes their theories, advantages, obstacles, and applications. EOR technology improves the efficiency of crude oil extraction by storing carbon dioxide (CO2) in deep strata and reducing the viscosity of the oil. This technology not only helps to reduce greenhouse gas emissions but also increases the rate of extraction of crude oil, providing a double benefit that makes it a commercially viable technology. However, the challenge with enhanced oil recovery technology is the high cost of facilities, which may limit its development prospects. Ocean sequestration refers to the storage of CO2 in the deep seabed to delay its contact with the atmosphere. The delay in the time of CO2 emissions brings a huge time value. However, ocean storage also has negative impacts, such as excessive CO2 in the ocean leading to acidification of seawater, disrupting the stability of ocean pH values, and ultimately leading to the extinction of deep-sea organisms.
Comprehensive Research on Vegetable Market Data Analysis and Strategy Formulation
Authors: Qiao Wu , Yang Kaijie , Liu Ziyu , Zhao Yuxiang , Chen Lei , Yang Lianxiang
Published: June 2024

In the current context of heightened public awareness of healthy eating, there is an increasing demand for high-quality fresh food products. This trend has brought fresh food supermarkets into the public spotlight. This study will primarily focus on vegetable products and aim to explore replenishment and pricing strategies for vegetable products under different conditions, to maximize the supermarket's revenue. The study will begin by checking whether the sales volume data for various vegetable categories conform to a normal distribution. After confirming normality, the Pearson correlation coefficient method will be used to analyze the relationships between sales volumes of different vegetable categories. Additionally, an ARIMA time series model will be employed to forecast vegetable sales data for the next seven days, and single-objective optimization will be utilized to obtain the best outcome. Finally, by constructing an optimal pricing and replenishment strategy hierarchy analysis system, decisions related to the sale of various vegetable products will be assessed and formulated.
The Severe Cold Air which Affected Qingdao during the 2022 National Holiday of China
Authors: Liu Yue
Published: June 2024

Under the background of global warming and climate change, the number of extreme weather is increasing, not only the extremely hot weather in summer but also record-breaking cold events. This paper uses synoptic maps and sounding graphs to analyze an unusual weather process of severe convection and sudden drop in temperature that happened in Qingdao between 2nd October 2022 and 4th October 2022. The weather process could be roughly divided into two parts. Before the cold front reached Qingdao, the precedent cold air came across with the strong west Pacific subtropical high and created severe convection like heavy rain, thunder, and lightning as well as strong wind, especially gusts, the characteristics resemble a typical summer severe convection. After the dusk of 3rd October 2022, the temperature began to fall rapidly, with the winds shifting to the north, this process is like a cold wave surging Qingdao in winter. The purpose of this paper is to study the impact of climate change on extreme weather using this weather event as an example. This study will help those concerned to better understand the evolution of weather events so that the necessary precautions can be taken to mitigate the damage they may cause to people, property and infrastructure.
Analysis on the Environmental Impact of Molten Salt Storage
Authors: Zhang Fengming
Published: June 2024

This research provides detailed background knowledge and basic concepts of molten salt technology in today's world. In addition, the impact of this technology on the environment is speculated. Molten salt is a thermal energy store. In the process of converting thermal energy, molten salt remains liquid, 60% sodium nitrate and 40% potassium nitrate, and the advantage of remaining liquid is that it collects the sun's energy and converts it into thermal energy. In short, molten salt storage (MSS) converts energy into heat. Under the current circumstances, MSS is still very important to the world. It has a strong thermal conductivity, because the molten salt is liquid form, so the energy, such as heat can be freely spread in the water. The container of MSS is also very large, it is a huge cylindrical container, so it can hold a lot of molten salt and conduct a lot of energy at once. MSS is relatively affordable because it is made of iron, copper, and other materials, so the raw materials are not so expensive. Moreover, these materials do not produce any carbon dioxide when they are used, thus MSS has a positive impact on the environment. Besides, the world has already put MSS into use today, such as the industrial steam supply field.
Discussion on the Importance of IT Technology to the Cultivation of "Three Highs" Talents in New Auto Time
Authors: Jian Haiyong
Published: June 2024

This paper discusses the importance of IT technology to the cultivation of "three highs" (high quality, high skill and high demand) talents in new auto time. By analyzing the current situation of the integration of IT technology and automobile industry, it is found that IT technology can improve the professional skills of talents, broaden international horizons and enhance innovation ability. This paper puts forward some training strategies, such as perfecting the education system, strengthening the construction of teachers and deepening the cooperation between schools and enterprises, in order to train more "three high" talents for the automobile industry to meet the needs of the times.
Analysis of the Principle and Applications of Sharping and Smoothing of Graphs Based on Fourier Transform
Authors: Guan Yuyi , Liu Yuxuan , Yuan Tianmin
Published: June 2024

As a matter of fact, Fourier transform is regarded as one of the most fundamental tools in image processing in recent years, which has been implemented in various applications including signal processing, acoustic generation and filtering as well as image processing. With this in mind, in this article, the principle of this transformation is introduced and discussed. At the same time, some related filter techniques is introduced to transform the image space into frequency space. The specific process of four different filters is shown in this study when applied in smoothing or sharping the graph. To demonstrate the significance of this technology, many real-world applications will be presented in the mean time. According to the analysis, the current limitations as well as future prospects are demonstrated. As the demand for digital image processing in various domains such as medical, telecommunication, and environment, the requirement for the Fourier transform has increased.
Research on Electric Vehicle Intelligent Parking Charging System
Authors: Gao Zihan
Published: June 2024

This article proposes an intelligent parking system in response to the current difficulties in charging electric vehicles in our country. The system integrates license plate recognition technology for vehicle identification and develops an intelligent system. It aims to prevent the occupation of charging station parking spaces by fuel-powered vehicles and the occurrence of the "short charging, long parking" phenomenon in electric vehicles while eliminating uncivilized parking behaviors. The system enhances the utilization efficiency of charging stations, thereby alleviating the challenges faced in charging electric vehicles. This paper provides an explanation and evaluation of the system through several sections, including technical introduction, application scenario selection, operational processes, practical significance, and feasibility analysis. Specifically, the operational processes propose corresponding mitigation measures for different scenarios. The conclusion presents prospects for this system, emphasizing its alignment with expected outcomes in terms of technology, economics, and feasibility. Furthermore, there is considerable potential for further development, contributing to the advancement of the electric vehicle industry in our country.
Analysis of Extreme Weather Events and Storm Systems and Their Impact on the Earth
Authors: Cao Zhenghui
Published: June 2024

Extreme weather events considerably impact our planet’s environment, challenging societies and ecosystems. This paper expansively examines their diverse effects and indicators. Defined by unmatched length, frequency, and power, extreme weather events entail floods, droughts, heatwaves, blizzards, tornadoes, and hurricanes. Their impacts reverberate profoundly, whereby tornadoes change the local landscape, while hurricanes bring habitat obliteration and coastal destruction. On the other hand, blizzards enhance vulnerability and freeze water bodies, and droughts interrupt water sources, endangering food chains. Moreover, heatwaves deepen stress on species, enhancing mortality risks. Also, floods, while vital for life, pose negative impacts, eroding habitats and soil. This paper indicates the complex relationship between our planet’s environment and extreme weather events through case studies and historical perspectives. With the growing frequency of climate change, comprehending their effects is critical for shaping adaptive approaches and developing resilience for human well-being and ecosystems.
Study of global illegal wildlife trade volume based on social network analysis and ARIMA model
Authors: Liu Fushuai
Published: June 2024

The illegal trade in wildlife and its products has become a global problem, and reducing the trade in illegal wildlife trade worldwide is important for the protection of biodiversity, social public safety and wildlife welfare. To explore ways to reduce illegal wildlife trade, the amount of wildlife trade needs to be integrated and predicted. Using CITES datasets and collected data, multiple linear regression was used to integrate the historical data of illegal wildlife trade, identify important factors, combine social network analysis and ARIMA time series analysis, build AR (2) model to fit the historical data, and forecast global trade records for the next five years. The results show that, the IWT will continue to rise globally over the next five years. At the same time, according to the influencing factors obtained by data integration, it provides the following suggestions and countermeasures to reduce illegal trade: strengthening legal effect, promoting national cooperation, etc.
Effects of Aerosols on Climate, Human Health, and Plant and Mitigation Strategies
Authors: Wei Zilin
Published: June 2024

With the increasing global air pollution, aerosols have received increased attention from researchers. Aerosols have been shown to have critical impacts on Earth’s climate, human health, and plant photosynthesis. In this context, this paper briefly introduces the composition of aerosols, the effects on Earth, and mitigation strategies. Aerosols scatter sunlight, as well as trap heat in the atmosphere, affecting Earth’s surface temperatures and reducing visibility. Besides, particulate matter can enter deeply into lungs, causing serious respiratory and cardiovascular diseases and spreading infective diseases. Meanwhile, by scattering sunlight, aerosols facilitate plant photosynthesis and protein expression. Because of the adverse effects of aerosols on climate and humans, several mitigation strategies, based on primary pollution sources, are proposed and discussed. To reduce vehicle aerosol emissions, implementing traffic restrictions is a potential strategy if practical and feasible for local communities. Encouraging the switch to electric vehicles is another strategy suggested and is more widely applied. For industry, a cap-and-trade system serves as another mitigation strategy to limit industrial emissions and provide incentives to reduce emissions.
Sustainable Marketing in Enhancing Customer Consumption in Tourism Industry in China
Authors: Li Jianhang
Published: June 2024

In China, there are many weaknesses related to the development of the hospitality and tourism market. Nevertheless, regarding to marketing, it is necessary to have more well prepared marketing practices in order to build some replaceable types of sustainable tourism following customer requirements and current trends at the time. The research is conducted with the purpose of making an intensive analysis of the importance of sustainable marketing in enhancing customer consumption in tourism industry in China. This paper also proposes some solutions to enhance sustainable tourism in China.
Research On the Application of Improved Models Based on Senet in Large-Scale Image Retrieval Algorithms
Authors: Ren Qize , Sun Aiguo
Published: June 2024

The proliferation of the Internet has led to a significant increase in image data, prompting a surge of interest in large-scale image retrieval technology. This study introduces an image retrieval algorithm leveraging SENet, incorporating data augmentation and regularization techniques to bolster model generalization capabilities, and employing transfer learning to enhance initial performance. Experimental findings demonstrate that this algorithm successfully enhances the accuracy and efficiency of image retrieval.
Research on the Prediction of Retail Car Sales in California
Authors: Yang Shuyi
Published: June 2024

Retail car sales are important because it is relevant to all the public including the government, market and consumer. With the influence of COVID-19 and many other factors, the change in retail car sales requires further research. Therefore, the prediction is in need of all sides to refer. Within all the models, the ARIMA model is more widely used, and the data satisfy the stationary required by the model, so it is chosen to be used in this research. The results of the forecast show that the retail car sales are going to decrease after the increase within the upper half of this year. However, whether the impact of the pandemic will last or it is a temporary factor remains a problem to solve. Conclusively, with the help of previous essays, the paper is expected to offer a forecast for retail car sales for the public to make decisions about retail car sales.
Risk Assessment of Terrorism in Asia based on K-Means Clustering Analysis
Authors: Jiang Lingzhi , Wu Qiwu , Xie Zhuoxu
Published: June 2024

This article obtains terrorist attack data from some regions of the global terrorism database, and uses Python language to preprocess and describe the data. Cluster analysis is performed on the preprocessed data using the K-means algorithm. During the analysis process, the focus is on the two key variables of casualties and economic losses, in order to find the patterns and trends behind the data. Based on the clustering results, the level of danger in each region was scientifically graded to assist counter-terrorism forces in gaining a deeper understanding of the core information of terrorist attacks in these areas, thereby enhancing their awareness of terrorist attacks and enhancing their ability to prevent them.
Research on Architecture of Smart Urban Rail Transit System
Authors: Duan Rong
Published: June 2024

By conducting a comprehensive review of domestic and international research findings, this study examines the data collection and utilization of smart city rail transit systems. It identifies the essential functional modules necessary for the overall architecture of such systems. The study also elucidates the establishment of processes within the perception and data collection layer, the data processing and analysis layer, and the control and management layer. Furthermore, it investigates the interrelationships among system components and the internal flow of information. The establishment of smart city rail transit system architecture helps to sort out and coordinate all kinds of information and data of the rail transit system, improve the efficiency of information collection and conversion, enhance the overall smoothness and safety of rail transit, and promote the establishment of a complete urban rail transit travel service system.
Big data climate prediction model based on linear regression
Authors: Wang Yuxing , Shi Yifan
Published: June 2024

This paper deeply studies the trends of climate change and ocean temperature change in British Columbia, which is of great significance for the prediction of climate change and the formulation of corresponding countermeasures. First, the paper obtained the historical temperature changes and ocean temperature data from 1981 to 2010 at 13 sites in British Columbia through the Canadian government website, and conducted data preprocessing. Then through linear fitting, we build a climate prediction model. Finally, through the analysis, we found that the temperature showed different trends with the change of latitude or longitude, and in the time dimension, we found that the temperature in British Columbia showed a rising trend from 1950 to 1999, and the temperature rising trend was roughly 1.5°C. In addition, it is found that the global sea surface temperature is on the rise.
Rnn-Ade-Based Multi-Product Replenishment-Pricing Modeling Study
Authors: He Hanglin , Jiang Juntian , Lai Yujie
Published: June 2024

Unscientific replenishment-pricing strategies can greatly reduce the sales profit of supermarkets, and choosing an appropriate decision model is crucial for supermarket operations. Therefore, this paper proposes a multi-product replenishment pricing model based on RNN-ADE, which fully utilizes the details of historical sales transactions with the help of recurrent neural networks to make the model results more credible, and also improves the DE algorithm to give the algorithm adaptability, so that the model has excellent global optimal solution search capability while having excellent solution efficiency. Then the model is tested practically based on the historical transaction flow detail data and historical product wholesale price of x superstore, and the replenishment and product pricing strategy for 2023-07-01 is formulated, the profit is predicted to be $741.44, and the sensitivity test is carried out. The results show that the model can effectively help supermarkets make more accurate and efficient replenishment and pricing decisions in a complex market environment.
Quantifying the Impact of the COVID-19 Pandemic on Copper Price Trends Using Time Series Analysis
Authors: Xu Qianqian
Published: June 2024

This paper explores the complex correlation between the COVID-19 epidemic and the price fluctuations of copper, an essential metal in multiple industries. The research seeks to analyze patterns and changes in copper pricing over a ten-year period using advanced time series analysis techniques. Historical data forms the basis for predicting the prices of copper. It allows for a comparison between pre-pandemic projections made using the ARIMA Model and the actual data observed after the pandemic. Such an evaluation allows for a nuanced understanding of the impact of this global health crisis on the copper market. By scrutinizing the discrepancies between projected and actual data, the study sheds light on the resilience and adaptability of the copper industry in the face of significant external disruptions. This deeper understanding not only contributes to the knowledge base surrounding the economics of copper but also provides insights into the broader capacity of industries to withstand and respond to unforeseen challenges. Acquiring a more profound comprehension of this subject not only enhances the existing information about the economics of copper, but also offers valuable insights into the overall ability of industries to endure and react to unexpected obstacles.
Efficiency Improvement and Key Opportunities of Stirling Engine
Authors: Luo Haoyan
Published: June 2024

Amidst the backdrop of an evolving societal landscape, the impending scarcity of energy resources has intensified the quest for innovative energy solutions. The Stirling engine, conceived by the Scottish clergyman Robert Stirling in 1816, emerges as a promising avenue to address contemporary energy challenges. This external combustion engine operates on the fundamental principle of harnessing work from heat transfer coupled with the expansion and contraction of gases. Its versatility lies in its capability to transmute diverse natural energy sources, ranging from wood and solar radiation to gases, into utilizable mechanical and electrical energy. The potential applications of Stirling engines are vast, encompassing roles as propulsion systems for space exploration, contributors to nuclear power generation, efficient refrigeration devices, and solar energy electricity generators. Nonetheless, the Stirling engine's Achilles' heel remains its suboptimal efficiency. This paper investigates diverse domains to optimize the performance of Stirling engines, shedding light on potential avenues for future research and development with the overarching aim of optimizing this venerable engine's contributions to sustainable energy solutions.
Research on the Stock prediction based on LSTM Algorithm
Authors: Mai Joleen
Published: June 2024

Predicting the value of a stock in the future is a widely recognized challenge. However, the Long Short-Term Memory (LSTM) network provides a distinctive solution as a specialized type of recurrent neural network proficient at tackling long-term dependency problems. Each time a new input is fed, the LSTM will first decide which previous memories to forget based on the new input and the output of the previous moment. This paper analyzes the LSTM algorithm for time series prediction in volume of stock. The dataset is initially split in a 7:3 ratio, with 70% allocated for the training set and 30% for the test set. This paper conducts data processing first, and then plots time series graphs to visualize the characteristics of volume of stock. Additionally, this paper conducts smoothness test together with white noise test, and makes time series predictions using LSTM. Values obtained from the experiments show that the training MSE of the LSTM algorithm is 28333951.7500 and the RMSE is 4722325.29. The final prediction comparison graph proves the potential of the LSTM algorithm to be used in market prediction.
Application and Benefit Assessment of Sustainable Building Materials in High-Rise Building Design
Authors: Chen Hanheng , Ji Qiang
Published: June 2024

With increasing environmental awareness, the use of sustainable building materials in modern high-rise architecture has become increasingly prominent. This paper provides a detailed analysis of Wood Chip Concrete Blocks (CBWC), exploring their application in high-rise building design, along with their environmental attributes, thermal performance, and structural integrity. Research indicates that CBWCs have a thermal resistance of R=5.26 m²K/W and fire resistance exceeding 180 minutes, significantly enhancing the building's energy efficiency and environmental friendliness. Simulation data reveals that the improved CBWC2 model, after partial filling and reinforcement, increased its peak horizontal force to 165.2 kN and reduced displacement to 9.99 mm, indicating enhanced structural stability. This study aims to use wood chip-reinforced concrete blocks to improve building energy efficiency and reduce carbon footprint while ensuring durability and safety, providing a sustainable material choice for future constructions.
Research Progress on the Effect of Unilateral Biportal Endoscopic on Lumbar Stability in the Treatment of Lumbar Disc Herniation
Authors: Long Keyi , Zhong Jiayun , Li Songlin
Published: June 2024

Lumbar disc herniation (LDH) is a common disease in spine surgery, characterized by typical symptoms of low back and leg pain, which can lead to sensory disturbances in the lower limbs, muscle weakness, and in severe cases, urinary and fecal dysfunction. For patients with poor response to conservative treatment, surgical treatment should be considered. Traditional open surgery causes large trauma and varying degrees of damage to the paravertebral muscles, facet joints, and surrounding ligaments, affecting the stability of the spine. With the development of the concept of minimally invasive surgery and the improvement of endoscopic surgical techniques, minimally invasive spine surgery has been widely used in the treatment of degenerative lumbar diseases. Unilateral biportal endoscopic (UBE) has been used in the treatment of various spinal disorders, causing minimal damage to the different structures. This article provides a review of the progress of UBE treatment on the impact of lumbar stability.
Predicting Mutual Fund Performance based on LSTM Models
Authors: Wang Yijin
Published: June 2024

Accurate prediction of mutual fund performance is becoming crucial for investors and fund managers to make informed investment decisions and earn profits. This paper utilized Long Short-Term Memory (LSTM) models to forecast the future performance of mutual funds in this research paper. This paper began by collecting a comprehensive dataset comprising historical fund prices and relevant financial indicators from Yahoo Finance. The dataset is preprocessed to handle missing values and format errors. LSTM models are known for their ability to retain and utilize information from earlier time steps in a sequence to make predictions or decisions at later time steps. This capability enables them to capture and understand long-term dependencies or relationships between elements in the sequential data, which are employed to understand and model the changes and trends in the performance of a mutual fund over time. The models are trained on a subset of the dataset, and hyperparameters are optimized to enhance their predictive capabilities. Evaluation metrics such as Mean Squared Error (MSE), the mean absolute error (MAE), root mean square error (RMSE), and R2 are employed to evaluate how accurately the models can predict future outcomes or events based on the available data. In conclusion, this research presents a robust methodology for predicting mutual fund performance using LSTM models. The findings highlight the potential of LSTM models as valuable tools for fund managers and investors, offering enhanced accuracy and providing valuable insights for informed decision-making in the dynamic and competitive mutual fund market.
Controlling Factors and Strategies of the Shared Bicycles in Jersey City, USA
Authors: Cao Hengyi
Published: June 2024

The emergence of shared bicycles provides a convenient low-carbon transportation option, which helps to reduce carbon emissions and traffic congestion, while promoting the development of low-carbon cities and the realization of sustainable mobility. This paper takes Jersey City in the United States as an example. Through the statistical analysis, it is concluded that Grove St RATH is the site with the largest number of shared bicycles, and the site is also located in the densely populated area, commercial center and public transportation hub of Jersey City. It indicates that the most used stations of shared bicycles in the city are related to the intensity of public transportation. The Grove Street stop is one of the busiest stops in Jersey City, located in the Grove Street area of downtown and also on the main thoroughfare to Manhattan in New York City. Jersey City's Hoboken Terminal station is an important transportation hub, serving NJ Transit trains, light rail, and the Hudson River Ferry. Located on the Hudson River, it offers a variety of transportation options for residents and visitors of Jersey City and the surrounding area. The delivery station of shared bicycles is near the transportation hub, which meets the travel needs of passengers going to or from the transportation hub by providing a convenient way to travel, so the station is used more. This location choice makes bike-sharing a convenient and fast alternative mode of transportation, enabling users to easily reach their destinations, especially in cases of traffic congestion or poor public transportation. However, shared bicycle parking spots in high-traffic areas may lead to parking congestion, affecting the convenience of users to park and borrow and return their cars. Therefore, it is necessary to increase the number of parking points and optimize the layout of parking points to ensure that the distribution of parking points is balanced and enough to accommodate the demand.
Big Data Analysis in Consumer Behavior
Authors: Zhou Qingyue
Published: June 2024

As a matter of fact, big data is an increasingly prevalent tool in contemporary society and has been shown to benefit numerous industries. Given the importance of consumer behavior as a market indicator, big data analysis of such behavior is of great significance in modern life as well as decision makings. With this in mind, based on these examples, this study will gain insight into the methods by which big data can be used to analyze consumer behavior. To be specific, this research will analyze and expound upon three examples of previous research that employ big data to study consumer behavior. On this basis, this paper will discuss the limitations and future developments of big data applications in this field. According to the analysis, this paper emphasizes the potential of big data in consumption to stimulate economic growth. Overall, these results shed light on guiding further exploration of consumer behavior analysis.