bluuebunny/crossref_metadata_2025 huggingface dataset:
Mustafa Kemal Paşa’nın İstiklal Savaşı’ndan Cumhuriyet’e Geleceğin Türkiye’sine Daire Türk ve Yabancı Basına Mesajları
Authors: Sürmeli Serpil
Published: June 2024

Mondros Mütarekesi’nin ardından İtilaf Devletlerinin Türk toprakları üzerindeki işgal siyaseti Türk milletini en ağır ve en acı gerçek olan beka sorunuyla karşı karşıya bıraktı. Ancak Türk milleti yüzyıllarca bağımsız yaşadığı topraklarda milli varlığına tehdit oluşturan bu büyük tehlikeyi sineye çekecek bir karaktere sahip değildi. Mücadele edecek üstelik bunu gayet medeni bir yolla yapacak yöntemleri biliyordu. ABD Başkanı Wilson’un dünyada ses getiren barış ilkelerinden 12. maddesine ki mütareke de bu maddeye vurgu yapılarak talep edildiğine göre tekrar dikkat çekmek suretiyle kendisine yapılan haksızlığın giderileceği düşüncesindeydi. Böylece bölgelerinin Türklüğünü 12. madde üzerinden ispatlamak üzere Müdafaa-i Hukuk Cemiyetleri kurarak harekete geçtiler ve umutlarını Başkan Wilson’un da katılacağı Paris Barış Konferansı’na bağladılar. Ancak haksızlığı gidermek bir yana yeni manda rejimleri adı altında eski sömürge anlayışlarının devamı ve İzmir’e Yunan işgalinin davet edilmesi medeni mücadele yolunda bütün umutları yok etti.

İzmir’in işgali, Türk Milleti’nin hayatında bir kırılma noktası oldu ve bu olay ülkeyi istila eden işgalcilere karşı silahla mücadele etmekten başka tutulacak meşru bir yol bırakmadı. Şehrin kurtuluşu milletçe kurtuluşun simgesi ve Mustafa Kemal Paşa’nın önderliğinde yürütülecek bağımsızlık mücadelesinin de meşalesi oldu.

Türk milletinin hür ve bağımsız yaşama arzusunu ve bu arzuyla ayağa kalkmaya çalışan mücadeleci ruhu aynı milletin bir ferdi olarak çok iyi bilen Mustafa Kemal Paşa, ülkenin kaderini tayinde verdiği tarihî kararı, zaman ve şartların bir önder olarak çıkaracağı fırsatlar önüne geldiğinde, derhâl hayata geçirirdi. Bağımsızlık yolunda başladığı Anadolu yolculuğunda öncelik verdiği ilk iş, milletin meşru haklarının anlaşılması idi. İç ve dış kamuoyuna verilen mücadelenin gerekçelerini anlatmak, dikkat ve desteğini çekmek oldukça önemliydi ve basın bu amaç için en etkili araçtı. Millî teşkilatlanma ve temel ilkeleriyle ses getiren bu mücadeleye basının ilgi göstermesi kaçınılmazdı. Nitekim Mustafa Kemal Paşa önce Türk basınının, TBMM Hükümeti’nin kurulmasıyla da yabancı basının artan ilgisini Türk millî davasını dünyaya anlatmak ve anlaşılmasını sağlamak adına oldukça etkin kullandı ve dünya, Türk Milleti’nin İstiklal Mücadelesi’nden Cumhuriyet Türkiye’sine uzanan zorlu yolculuğundaki başarı öyküsüne, bizzat onun ağzından tarihe mal olan mesajlarıyla tanıklık etti.
Research on deep-sea submarine distress positioning prediction based on hydrodynamics and numerical simulation techniques
Authors: Jiang Xiaoyi
Published: June 2024

The purpose of this paper is to study the problem of positioning prediction of deep-sea submarines after distress. Firstly, the kinematic equations of a deep-sea submarine in seawater are established, and the motion characteristics of a deep-sea submarine under the action of water current are analysed. Subsequently, a computational model of the current velocity in the Mediterranean Sea was established, and the positioning prediction of the submarine was carried out based on this computational model. In addition, the article proposes a search device selection method based on decision tree and TOPSIS algorithm, and a search path planning method based on happiness search algorithm. Ultimately, the research results show that the method is effective and reliable in submarine distress positioning prediction.
Impacts of Conservation Reserve Programs on Maize’ Acres Planted: Evidence from Iowa, Maine, and Wisconsin
Authors: Pan Yufei
Published: June 2024

As a matter of fact, the Conservation Reserve Programs has widely affected various issues, which has great impacts on the environment and agriculturea. With this in mind, this study delves into the multifaceted impacts of Conservation Reserve Programs (CRP) on maize acres planted in Iowa, Wisconsin, as well as Maine. To be specific, spanning the years 1984, 1985, 1986, 2000, 2010, as well as 2023, the comparative analysis presented in this research provides insights into the evolving relationship between CRP initiatives and maize cultivation in diverse agricultural landscapes. Based on the evaluations and according to the analysis, in a world grappling with climate change and the imperative of sustainable land management, the insights garnered from the diverse experiences in Iowa, Wisconsin, as well as Maine continue to guide efforts to cultivate a future where agricultural production harmonizes seamlessly with environmental stewardship. Overall, these results shed light on guiding further exploration of maize’s planting.
A Study on Vegetable Commodity Selling Price and Sales Forecasting Based on ARIMA-Differential Evolutionary Algorithm
Authors: Liu Chengcheng , Zhou Guangyin , Zhong Caiying
Published: June 2024

Fresh food superstores need to develop accurate replenishment plans to cope with the pricing challenges caused by the short freshness period, many varieties, and large differences in origins of vegetables, to meet customer demand and to protect the sales program. In this paper, we firstly draw bar charts to show the distribution of sales among the top 10 best-selling and least-selling vegetable items in each vegetable category, and draw correlation coefficients heat maps to show the correlation of sales among the six vegetable categories. Since there are too many vegetable categories, only the 10 best-selling individual items are selected to draw the heat map of correlation coefficient, and hierarchical clustering is performed to study the correlation. Then a cost-plus pricing model is established to represent the recommended selling price through the total cost per unit and profit margin, while the total sales volume of each category is obtained by accumulating the sales volume of each individual item. In this paper, K-means clustering was used to aggregate the six vegetable categories into three broad categories, and it was found that the sales volume and the recommended selling price were negatively correlated. In order to predict the daily replenishment volume of each category from July 1-7, 2023, this paper screens the daily sales volume of the categories in June and July in the past two years, and predicts it with the ARIMA model in time series analysis, and draws line graphs to show the prediction results, and gives the daily replenishment volume strategy at the same time. Finally, differential evolutionary algorithm is used to introduce the optimal selling price, which is 39 yuan/kg for aquatic roots and tubers, 24 yuan/kg for flowers and leaves, 17 yuan/kg for cauliflower, 3 yuan/kg for eggplant, 26 yuan/kg for chili peppers, and 37 yuan/kg for edible mushrooms. The maximum gain was 73,525.45 yuan.
Comparison Between Elementary Network Structure and Prophet Model for Time-Series Forecasting: Merchandise Sales
Authors: Zhang Xu , Zhang Lixian , Yang Ziang
Published: June 2024

In order to maximize the profits of supermarkets, this article discusses different models in relation to time series prediction, based on previous time points, to help with setting the merchandise price. In detailed, we compared 2 deep learning methods(BiLSTM and Transformer) and Prophet model for predicting the future sales information. The overall dataset comes from certain information in the cost unit price of each category in a certain market within continuous 61 days. We evaluated these models based on the gaps bewteen their predictions and actual values, as well as the model’s Interpretability. Our results indicate that the BiLSTM model could predict smoothly, while the Transformer excels in short-term prediction accuracy. The Prophet model, though less precise, offers valuable insights into seasonal patterns. We find that no single model is universally superior; instead, their efficacy varies with the nature of the sales data. A combined approach, utilizing the strengths of each model, may provide the most comprehensive forecasting strategy. This study underscores the importance of model selection in enhancing retail pricing strategies through accurate sales forecasting.
Research on the Legal Liability of the Third Party for Infringement of Spouse Rights
Authors: Fang Ziying
Published: June 2024

In today's society, with the increasing economic level and the continuous expansion of people's openness, people's sexual consciousness is more pursuit of self-satisfaction, but the concept of chastity gradually collapsed. In recent years, the divorce rate in our country is getting higher and higher, one of the most important reasons is the intrusion of the third party. At present, China lacks the relevant legislation of spousal rights and the accountability mechanism for the third party's infringement of spousal rights. Therefore, it is increasingly urgent to perfect the relevant laws to regulate the increasingly rampant extramarital sex. First of all, through the comprehensive analysis of the theories of the third party in different academic circles, this paper defines the concept of the third party and the related contents of the spousal rights. At the same time, this paper makes a concrete analysis of the behavior and characteristics of the third party's infringement of spouse rights. Secondly, this paper analyzes the legal problems and practical dilemmas in our country in the third party's infringement of spouse's right. Finally, this paper puts forward specific suggestions for the problems mentioned above in China. In a word, only by filling and perfecting the relevant legal gaps of third party's infringement of spouse's rights can we better protect the legitimate rights and interests of no-fault spouses, and maintain judicial justice and social fairness.
Research on the Impact of Digital Finance on the High-Quality Development of Regional Economy: An Empirical Analysis Based on Provincial Panel Data
Authors: Li Jiafeng
Published: June 2024

As a product of the combination of digital technology and traditional finance, the vigorous development of digital finance in the context of the digital economy era will certainly have a great impact on the high-quality development of the economy. Based on the panel data of 31 provinces from 2011 to 2020, this paper adopts the entropy value method to determine the economic development index of the region, and applies the two-way fixed effect model to explore the impact of the development of digital finance on the regional economic development. It is found that the rapid development of digital finance has a positive role in promoting the economic development of the region and changes with the level of openness to the outside world as well as the level of human capital, and that the innovation effect update of the region plays an intermediary role as an intermediary variable in the impact of digital finance on the economic development of the region. There is significant heterogeneity in the economic development of digital finance on different regions, with the highest in the east and the lowest in the center. Reasonable suggestions are made for the better development of the economy of each region, thus promoting the high-quality development of the economy of each region.
Analysis of the Principle and Simulations for Re-ionization of THESAN
Authors: Xu Zihou
Published: June 2024

The re-ionization era was always mysterious to humans, because of its great time distance. It is the period when galaxies form due to dark matter congregating and emit high energy photons ionizing the surrounding (entire) universe. The THESAN simulation is a successful program that uses computers and models that simulates what happened in the re-ionization era. However, this is a complex program that contains multiple research directions, the aim of this paper is to summarize the work of the THESAN team giving first a background information about simulations, the re-ionization era, and certain models for re-ionization era. Then, this study introduces the THESAN model which contains three important parts of radiation, galaxy formation, and cosmic dust. Afterwards the results of the simulation such as Lyman alpha emission will be summarized and observation methods such as 21 cm line will be illustrated. At last, there will be discussion of the limitations of the THESAN study and its future outlooks majorly focusing on the use of JWST detection abilities on the THESAN simulation.
Athlete Momentum Visualization Based on Logit Regression Model and LSTM Prediction Model
Authors: Jiang Jinhao , Li Yuqian
Published: June 2024

With the development of information technology, big data analytics predicts the likelihood of a player's victory by capturing the game situation, thus providing the player with a timely and appropriate strategy to win the game. In order to investigate whether the player's "momentum" has an impact on the game results, this paper extracts four indicators, namely, the player difference, the number of consecutive wins, the number of breaks of serve, and the number of successful breaks of serve based on the data of the Wimbledon Men's Tennis Championships in 2023, in order to quantify the impact of the "momentum" on the game results.  Logit regression models were then developed to find strong correlations between these metrics and the number of wins. Therefore, in order to further investigate the influence of these metrics on the game process, an LSTM prediction model was built to predict the outcome of the game. The training results of the final model show that the MSE is 0.316 and the MA is 0.387, with low prediction errors. Based on the prediction results of LSTM, this paper provides appropriate suggestions for players by analyzing the turning points of win/loss tilts and changes in players' status.
A study on the influence factors of athletes' momentum based on RF model and BP neural network
Authors: Lan Rongqi , Chen Youzhen , Lin Chengbin
Published: June 2024

Momentum is used in the dictionary to mean "the acquisition of power through motion or a series of events". In sports, a team or a player may feel that they have momentum in the sport they are competing in. Athletes with "momentum" are often considered to have an advantage. To study the influencing factors of athletes' momentum, this paper uses the data of the men's match of Wimbledon Open 2023, adopts the Random Forest Model to filter the features affecting momentum, and obtains the five most important factors affecting the momentum of tennis players; and adopts the BP neural network to fit the athletes' movement state, and predicts the fluctuation of the situation. Studying the characteristics of momentum influence, understanding the development of momentum and the timing of its formation can provide a clearer understanding of the reality of the athlete's situation, which can allow the athlete and the coach to analyze and train in a more targeted way to achieve the effect of improving sports performance.
Wordle game prediction study based on ARIMA and grey correlation analysis model
Authors: Zhang Qiansong
Published: June 2024

The puzzle game Wordle is a huge hit and has attracted a lot of users on Twitter. In the era of big data, this study is dedicated to mining meaningful information from the data thus building a predictive model of the game, which can be used to assess its impact on human choices and behavioral outcomes. This experiment hopes that by predicting trends in multiple aspects of player behaviour, it will lead to more interesting and innovative improvements in puzzle games. By building an ARIMA model, it is possible to predict the number of people who will give feedback on the results each day. A grey correlation analysis model was developed to analyse the effect of three different factors on the percentage of people choosing the difficult mode in the game.
Analysis of the Observations for Three Telescopes: EHT, FAST and LBTI
Authors: Zhou Weimin
Published: June 2024

As technology continuously advances, the telescope technologies available to humans are becoming increasingly refined, leading to the discovery of an ever-growing number of phenomena using these telescopes. This allows for a deeper understanding of the universe one inhabits, with more astronomical phenomena receiving scientific explanations. This article primarily seeks to broaden our knowledge in this area by describing three distinct astronomical telescopes. It introduces the components and detection principles of the Event Horizon Telescope (EHT), FAST, and the Large Binocular Telescope Interferometer (LBTI). Additionally, this study delves into the primary research objectives, pivotal scientific domains, and ongoing projects of these three telescopes. Moreover, at the conclusion of each section, this study discusses their recent observational results or some noteworthy astronomical phenomena. According to the three examples presented in this article, the aim is to enhance people's understanding of astronomical telescopes and to inspire more individuals to take an interest in the advancements of astrophysics.
Combining Kinematic Modeling and TOPSIS For Enhanced Submarine Rescue Missions: Path Prediction and Equipment Assessment
Authors: Yao Siyu
Published: June 2024

With the growing interest in exploring the unknown underwater world, underwater tourism has become an emerging trend, which also brings about new demands for tourism safety and underwater exploration technologies. In this context, this paper aims to investigate path prediction modeling for submarine failure scenarios with an example in the Ionian Sea. In this paper, a prediction model based on kinematics and dynamics equations is used and combined with a Gaussian Markov process to simulate the current velocity, while an uncertainty perturbation term is introduced to improve the model's realism. To ensure that the submarine can be found in the shortest possible time, this paper establishes the weights of the dimensional and indicator layers based on the analysis hierarchy process (AHP) and entropy weighting method (EWM) and then calculates the scores of the required devices using the TOPSIS method. It was finally determined that the most suitable equipment is the magnetometer, followed by equipment such as a sonar system. This study provides a framework for improving search and rescue efficiency in submarine malfunction situations.
Mitigating PM2.5 Pollution in Shijiazhuang: Strategies and Solutions
Authors: Hou Guanlin
Published: June 2024

Air pollution, particularly PM2.5 pollution, has been a pressing issue in Shijiazhuang, a city in Hebei Province, China, characterized by high levels of PM2.5 concentration over the past years. This research paper delineates the historical trends and various factors influencing PM2.5 concentration in Shijiazhuang, including meteorological, geographical, and human factors. The paper further explores a range of strategies to mitigate PM2.5 pollution, focusing on policy interventions and technological solutions. Policy interventions encompass stricter emission standards for industries, promotion of green transportation, and sustainable agricultural practices. Technological solutions highlight the introduction of air purifiers in public spaces, development of cleaner industrial technologies, and the promotion of electric vehicles and public transportation systems. Grounded in recent research findings, the paper offers a comprehensive approach to reducing PM2.5 environmental pollution in Shijiazhuang, aiming to foster a healthier and more sustainable habitat for its residents.
A QUBO model-based approach for solving the computational resource allocation problem and its application analysis
Authors: Chi Ming
Published: June 2024

This paper discusses the solution method of the computational resource allocation problem based on the QUBO model, and analyzes the application in combination with the simulated annealing algorithm and the CIM simulator. The reasons for choosing the QUBO model and its advantages in logical reasoning are first introduced, and then the core principles of the QUBO model are analyzed, including its relationship with quadratic unconstrained optimization problems. Then the principles of simulated annealing algorithm and CIM simulator and their applications in problem solving are discussed in detail. In terms of specific problem solving, taking the optimal position of base station setting and the optimal path of overhauling as examples, the problem definition, decision variables, the establishment of QUBO model, and the solving process are described respectively, and the solving process is demonstrated through flowcharts. Finally, the solution results of the base station setup and maintenance path problems are given and the model is evaluated.
Investigation of Electron Beam Depth-dose Curve Using EGSnrc
Authors: Huang Zhuoyun
Published: June 2024

As a matter of fact, electron beam therapy is fundamental in cancer treatment, with advantage of precise dose deposition and shallow penetration, making it ideal for targeting superficial tumors in recent years. Accurate modelling of electron beam characteristics is important for safe and effective radiation therapy. On this basis, this research looks at the electron beam depth dose curve, and its behaviour under different field size using EGSnrc (Electron Gamma Shower National Research Council) as well as discusses its validity by compare simulation results with other researchers’ work. According to the analysis, this study has proved the validity of DOSXYZnrc since the simulation data is consistent with the agreed data despite some other unmentioned parameters should be rechosen at the same time. To ensure the safe and effective delivery of radiation therapy, accurate electron beam information and dosimetry are indispensable for radiation oncologists and medical physicists. These results shed light on guiding further exploration of electron beam therapy.
Critique of Oil Sand Exploitation in Indigenous Community from a Perspective of Political Ecology
Authors: Zhang Qinghui
Published: June 2024

The high demand of energy and the goal of reducing energy-related pollution emission are both urgent needs in contemporary global discussion, and the topic of sustainable development and the concept of sustainability are integrated through the discussions. Canada is one of the largest oil-producing states due to its large oil sands deposits in Northern regions where is also important reservoir for indigenous communities. The large-scale oil sand extraction by energy corporations and the promotion from governments along with the colonial heritage has caused degradation in vulnerable indigenous communities environmentally, socially, and culturally. This paper adopts a political ecology approach and integrates the study of extractivism and the concepts of consumption and metabolic rift into the case analysis on the power structure underlying the oil sands exploitation in McMurray Metis indigenous community, which provides an insight into unequal and asymmetric power structure among the oil industry, the government, the indigenous community, and the public.
Analysis of Lithium Battery Industry in Northwest China
Authors: Bi Sheng
Published: June 2024

The purpose of this paper is to study and analyze whether northwest China meets the development needs of lithium battery industry and its impact on local economic development, and draw general conclusions. Compared with batteries, lithium-ion battery packs have natural advantages in environmental protection. The materials used in lithium-ion battery packs do not contain polluting metals such as cadmium, lead, mercury and other harmful heavy metals. There are no pollutants in the processing and use of lithium-ion batteries, which ensures human health. There is no pollution of water and soil in the recycling process of waste batteries. Lithium batteries have relatively high energy storage density and long service life, making them the most promising energy storage technology at present. Northwest China has a high demand for energy storage, and its unique geographical conditions have great advantages for the development of lithium batteries. The lithium battery industry can help the local economy to a certain extent through the financial advantages brought by the recycling of lithium batteries.
The Impacts of the Pandemic on Employment in the United States
Authors: Li Qinyun
Published: June 2024

Amid the pandemic's stringent public health measures, which triggered widespread layoffs, business closures, and job losses, the labor landscape in the United States underwent a profound transformation. an effort to gain diverse perspectives on the impact of the pandemic on the United States, this research employs robust data collection and rigorous statistical analysis to investigate the pandemic's ramifications across diverse U.S. industries. Utilizing a comparative approach, it juxtaposes pre- and post-pandemic employment data, employing quantitative methods to unveil the pandemic's palpable influence on employment rates. Furthermore, this study extends its purview to the quest for post-pandemic recovery. Its findings not only offer evidence-based insights for bolstering workforce resilience but also cultivating inclusive growth. By systematically unraveling the intricacies of the pandemic's employment impact, this research lays a sturdy foundation. It paves the way for the development of a resilient, equitable labor market—a key element in sustaining prosperity in our ever-evolving and unpredictable world.
Replenishment Strategy Model Based on Cost-plus Pricing
Authors: Huang Xiaoyun , Zhang Ziwei
Published: June 2024

To formulate the commodity pricing replenishment strategy to meet the short-term profit demand of merchants, we established a pricing replenishment prediction model based on the sales-cost-plus pricing correlation. It integrates four-dimensional profit factors, taking the maximization of total profit as the core guidance and considering the objective impact of date. With ARIMA and random forest algorithm, the commodity cost and sales volume are predicted from the perspective of sales cyclical fluctuation. Finally, we constructed the optimal pricing linear function based on the goal programming problem. The optimal pricing replenishment strategy can be determined by adjusting the commodity pricing. The calculation results show that the prediction accuracy of the model is higher than 0.71, which can provide merchants with pricing and replenishment strategies with high reliability.
Modeling Historical Volatility of 10-year Chinese Treasury Bond Futures: A Comparative Analysis of MLE and MCMC Approaches
Authors: Zhao Shujun
Published: June 2024

Chinese treasury bond futures are gaining significance in the market. Volatility is an important metric for measuring the fluctuations in asset prices. This paper provides historical volatility modeling for 10-year Chinese treasury bond futures through the Student-t distribution GARCH (1,1) model. The data encompasses the entire historical daily prices, which are used for calculating logarithmic returns. Before modeling, plots and hypothesis tests such as Augmented Dickey-Fuller testing and Lagrange Multiplier testing, are performed to assess the underlying assumptions. In pursuit of better outcomes, a comparative analysis is conducted on parameter estimation, by using both the Maximum Likelihood Estimator (MLE) and Markov Chain Monte Carlo (MCMC) with the Metropolis-Hasting algorithm. The results are performed by “fGarch” and “bayesGARCH” packages in RStudio. Two methods give different estimates, but both accurately fit the dataset. The forecast errors show the MLE is better. However, a generalizable conclusion remains elusive, primarily due to disparities in data sources, model configurations, and the default settings in R packages.
Analysis of the Formation Mechanisms of Various AGNs
Authors: Xiao Zengwei
Published: June 2024

As a matter of fact, investigation of Active Galactic Nuclei (AGNs) is quite important in analysis of galaxy formation in cosmology and astrophysics. On this basis, in this paper, the intricate world of AGNs and their profound implications for the understanding of galaxy formation and universe evolution has been shown. AGNs, fueled by gas accretion produced by stars clashing with central supermassive black holes (SBH), stand as some of the most luminous objects in the night sky, emitting energy surpassing the ordinary galaxies. This paper underscores the vital role of AGNs in unraveling the cosmic models. The cosmological evolution of AGN luminosity functions offers a historical perspective on SBH formation, intimately tied to the universe's history. The paper conducts a comprehensive analysis of diverse AGN types, with particular emphasis on Type I AGNs such as Quasars, Type II AGNs, and Radio Galaxies. Underscoring profound connection between AGN activity, galaxy morphology, and star formation dynamics.
Comparison and Integration of BRT and Railway Development
Authors: Su Hao
Published: June 2024

This paper investigates the comparative analysis of Bus Rapid Transit (BRT) and Railway Development as urban transportation solutions. Integrating Bus Rapid Transit and railways within urban planning is also explored, highlighting the role of feeder systems, accessibility enhancement, and land-use considerations. The paper also examines the effects of economics on both transportation modes. While BRT positively impacts local economies through reduced congestion and improved accessibility, railways, especially high-capacity systems, yield more substantial economic benefits. It can help some developing and building cities choose their priority public transportation. Both modes offer unique advantages, with BRT catering to immediate transit needs and railways contributing to enduring urban development. Integrating these modes in urban planning demands careful consideration of accessibility, sustainability, and land use, leading to efficient and sustainable transportation networks. Considering growing urbanization and transportation challenges, this study examines the background, advantages, challenges, and integration potential of these systems. The research emphasizes the need for further investigation to guide urban planners, policymakers, and transportation authorities in making informed decisions and creating well-connected and environmentally friendly urban transportation systems.
Applications of Residue Theorem to Some Selected Integrals
Authors: Xie Chanyu
Published: June 2024

A complex variable is a quantity that contains both a real part and an imaginary part. Complex analysis is an application of mathematics that analyzes the features of functions of complex variables. Physics, engineering, and computer science are just a few of the scientific disciplines that benefit from complex analysis. In order to tackle issues that are challenging or impossible to resolve using only real variables, complex analysis is crucial. This paper introduces an important theorem in complex analysis, which is Cauchy’s residue theorem. A relative general expression for a complex integral along a simple closed contour is provided by Cauchy's residue theorem. Cauchy's residue theorem can be used to select an acceptable closed contour for the calculation of some unusual definite integrals that may be highly complex and challenging to solve using traditional methods. The residue at the function's isolated singularities is then established. In the formula that is subtracted in Cauchy's residue theorem, the values of the residues are extracted. The integral along a simple closed contour can then be represented in two pieces, in which one along the real axis and the other along the circle.
Validity Investigation and Temperature Prediction of Global Warming Based on Random Forest Algorithm
Authors: He Shikang
Published: June 2024

This study initially examined the validity of the global warming argument through normal distribution test and one-sample t-test, and conducted a data perspective analysis to determine whether the increase of global temperature in March 2022 was larger than any previous 10-year period. Subsequently, based on the data collection and processing of global temperature impact factors and correlation analysis, three prediction models were established: multiple regression prediction model, ARIMA time series prediction model, and random forest-based nonlinear prediction model. These models collaborated to complete a forecast of future global temperatures. After accuracy assessment and sensitivity analysis with confidence intervals ranging from 95% to 105%, the nonlinear prediction model based on the Random Forest algorithm was selected to further study the future global temperature. The results showed that the global average temperature would reach 20 degrees in 2055, 19.96 degrees in 2050, and 20.07 degrees in 2100.
Thai Film and Television Development and its Impact on the Economy
Authors: Wang Mingping , Su Wei
Published: June 2024

Film and television are regarded as the media carrying cultural communication, that is, one of the key carriers of cross-cultural communication. In recent years, Thai films and television have gained more and more popularity among audiences all over the world, which not only has far-reaching significance for studying the phenomenon of cross-cultural communication, but also its contribution to the economy is worth analyzing. As a non-traditional film and television power in Asia, there are many places worthy of our attention and research on how Thailand makes film and television develop rapidly and drive its economy.
Methods to Reduce Building Energy Consumption
Authors: Ren Shangyuan
Published: June 2024

With the development of science and technology, the density of modern buildings in urban areas has increased to a large extent, giving rise to a sharp increase in building energy consumption. Therefore, it’s of great significance to reduce the energy consumption in buildings. The paper discussed the factors of energy consumption in industrial, residential, and commercial buildings, which can be divided into space heating, cooling, water heating, and lighting. There are also several methods of cutting down on wasted energy in buildings in this paper, including the heat pump system, the green roof, and the use of the pyroelectric effect. The heat pump system is an equipment which can transfer heat from a cooler space to a warmer space. It transfers heat instead of generating it to save energy costs in an evaporation and condensation cycle. The cool roof is designed to reflect and absorb heat from the sun. As the roof temperature decreases, the urban heat island (UHI) is mitigated and it’s relatively easier to cool the inner temperature. The green roof, roof with vegetation, soil, and drainage layers, works similarly but it also produces fresh fruits. In addition, the thermoelectric effect can convert heat into electricity to produce energy based on the temperature difference. It can take advantage of electricity to create temperature differences as well. The essay introduced several methods to reduce building energy consumption, which can be useful in developing countries such as China to solve the problem caused by industrialization and mitigate carbon emissions.
Analysis of Principle and Applications of Fourier Transform for Acoustics
Authors: Qian Zhiwei
Published: June 2024

As a matter of fact, since the invention of Fourier transform has been invented, various fields have used the measure to extract signals and eliminate the noise. In recent years, with the rapid development of computer fields, the fast Fourier transform (FFT) is pretty simple to implement. On this basis, numerical solutions and dealing approaches are proposed in lots of fields including optics and acoustics. With this in mind, this paper will detailly analyze and discuss the implementation of Fourier analysis into acoustic. To be specific, this study will demonstrate the principle for FFT analysis as well as the situations of using FFT. At the same time, the applications in the acoustic field will be systematically estimated. Acc7ording to the analysis, the current limitations will be proposed, and the future prospects will be presented. Overall, these results shed light on guiding further exploration of FFT analysis in different subjects and fields.
Progress and Perspective of Single-atom Catalysts for the Electrochemical CO2 Reduction Reaction for Fuels and Chemicals
Authors: Liu Benjamin
Published: June 2024

Electrochemical CO2 Reduction Reaction (CO2RR) presents a transformative approach for the sustainable synthesis of fuels and chemicals to address pressing environmental challenges. The efficiency and selectivity of the CO2RR largely depend on the catalyst. Among which, Single-Atom Catalysts (SACs) have surfaced as a prominent design for this reaction, offering exceptional activity and selectivity. This paper delves into the progress and perspectives of SACs in CO2RR, tracing their historical evolution, unique advantages, and underlying mechanisms. The superior atomic utilization, distinct electronic configurations, and enhanced product specificity of SACs over traditional catalysts have opened novel pathways for more efficient conversion of CO2 to potent resources. However, challenges particularly concerning the stability, scalability, and product diversity of these catalysts constitutes as major impediments. Recent innovations, from advanced characterization techniques to novel synthesis methods, are spotlighted, showcasing the strides the scientific community has made. Looking forward, this paper underscores the potential of SACs in bridging sustainable energy sources with green chemical production and discuss prospective strategies to overcome existing limitations.
Extreme Weather Based Insurance Underwriting Decision Modeling and Solutions
Authors: Li Haoruo , Luo Weiru
Published: June 2024

This paper addresses the problem of insurance companies' underwriting decisions under extreme weather conditions. Firstly, the data were preprocessed, including identifying and processing missing data and outlier analysis. Then an underwriting decision-making model based on the extreme weather hazard model and the insurance insolvency factor model is established, and the corresponding solutions are proposed. Finally, through model validation and empirical analysis, the underwriting strategies of insurance companies under different risk levels are derived, and corresponding suggestions are given.
A Study on the Dynamic Relationship between Performance Scoring and Outcomes in Sports Competitions
Authors: Li Haitao , Li Zhijun , Jin Yuqi
Published: June 2024

In this paper, the relationship between kinetic energy and match results in tennis matches was explored by using principal component analysis (PCA) and the entropy weighting method. By analyzing the match data of Wimbledon 2023, the paper describes the data processing methods in detail, including the processing of missing data and the application of the MICE algorithm. It was found that there is a correlation between changes in kinetic energy during matches and match success, thus providing practical guidance for tennis coaches and players in adjusting their strategies. In addition, the role of kinetic energy in determining sports outcomes was analyzed, demonstrating the validity of the methodology employed. This study provides a new research idea and framework for the field of sports science.
Optimal Investment in Electricity Generation under Mean-Variacne Criteria
Authors: Wang Qingyue
Published: June 2024

This study introduces an application of mean-variance optimization, a common risk management technique in financial markets, to the New England area electricity market. The research optimizes portfolio selection in energy markets, treating 24 hourly intervals as distinct assets, and utilizes historical data from ISO New England hourly locational prices from 2022 to 2023. The study demonstrates the application of mean-variance optimization model across cases for hydroelectric and gas turbine combined power plants, providing generation companies with strategies to optimize their portfolio selection. This approach allows companies to make informed decisions about when and how to sell their power, aligning with their risk and return preferences. The research findings suggest that this optimization method can offer a systematic framework for generation companies to navigate the volatile electricity market and manage the risk and return.
A Study on the Decision of Insurance Order Quantity in Disaster-prone Areas Based on Grey Prediction and Multivariate Linear Regression
Authors: Du Zhuohang
Published: June 2024

In recent years, earthquakes, floods, sandstorms, extreme heat and other natural disasters have occurred with increasing frequency in all corners of the Earth, and these disasters have caused huge economic losses. In this paper, the data of the disaster-prone state of Florida is taken as an example. In order to make the local insurance companies better make insurance decisions, the article first estimate the disaster frequency of the region in the next five years based on Grey Prediction, and then obtain the average expected weather-related disaster frequency of Sky and Land disasters (431.24 and 428.86). At the same time, the article carries out Multivariate Linear Regression on insurance sales (dependent variable) and disaster frequency (independent variable), obtaining the linear regression equation of the state, and calculates the expected value of insurance sales in the next five years (14.2372 million). Then, paper uses the concept of marginal benefit in economics and curve fitting toolbox to fit the marginal insurance cost curve and marginal insurance revenue curve, and take the intersection point of the curve (20.2692 million) as the number of underwriting orders that make the insurance company most profitable. Through comparison, it is found that the underwriters in Florida should continue to conduct business.
Multidimensional linear regression analysis to predict the change in one-day video views on Bilibili website
Authors: Lu Jixing , Xia Yifan
Published: June 2024

This paper utilizes a multidimensional linear regression analysis model to investigate video playback volume changes within Bilibili's film, cartoon, anime, auto-tune remix-themed content, game, and entertainment partitions. We employ crawler software and a webpage loop with a nested collection of video links to extract and sequence titles. Technical abbreviations are defined when first presented. We utilize crawler software to extract various data sets from online video links. We establish a web page cycle and collected video links within nested collections to accomplish this. Subsequently, they systematically accessed each link to extract information such as titles, playback, likes, coins, favorites, and video synopses. Finally, the data 6,075 are obtained and filtered down to 1,691 representative data points using playback, likes, coins, favorites, and other data sets from the previous day. The previous day's playback, likes coins, favorites, and other data are also collected. After conducting a multidimensional linear analysis, we evaluate the Durbin-Watson test, VIF, and R^2 to determine the accuracy of fit. Our findings indicate that collecting videos and playback from the previous day positively impacts playback for the following day. However, pursuing likes andcoins excessively is susceptible to restriction by the system.
Cooling and Heating Load Calculation and Energy Consumption Analysis for Single-family Residences in New York
Authors: Ding Qianyu
Published: June 2024

Building energy consumption analysis is a crucial component of sustainable design, allowing for efficient planning of energy use and effective control of energy consumption. This paper focuses on a single-family residence located in Brooklyn, New York. Utilizing Revit software, and primarily analyzes the impact of geographic location and building orientation on energy consumption, ultimately selecting the most suitable architectural design. The total site energy consumption of the building is 203907.34 kBtu, and the total source energy consumption is 523300.15 kBtu according to the simulation. Overall, the climate of the building's location significantly influences energy consumption. Therefore, it is advisable to enhance the building's thermo control capabilities to effectively reduce energy consumption.
Research on Digital Transformation and System Reconstruction of AIGC-Enabled Landscape Architecture
Authors: Yan Jiayi
Published: June 2024

Landscape architecture is a huge and complex discipline with strong cross-fertilization, which needs to be supported by massive resource databases and strong Analysis and processing capabilities. The traditional design methods need help. The digital landscape has become an important method of landscape architecture, and the development of Artificial Intelligence Generated Content (AIGC) provides new opportunities for the digitalization process. Through the introduction of related concepts, the article takes the dilemma faced by traditional landscape architecture as the main entry point, explores the application form of AIGC in landscape architecture workflow from three aspects: information analysis, design assistance, and innovation demand, and identifies that AIGC-enabled development is the road to the future of landscape architecture. Finally, it discusses the possible misconceptions of the process, aiming to provide new ideas for landscape architecture digital transformation and system restructuring.
An Ecological Network Analysis Based on The Lotka-Volterra Model
Authors: Huang Qi , Huang Jia
Published: June 2024

Changes in adaptive sex ratio is a phenomenon in ecology and evolutionary biology, and the growth rate of the lampreys is affected by food availability, which directly affects the sex ratio of the lampreys. In order to investigate the effects of changes in the sex ratio of lampreys on the stability of the ecosystem, this paper takes phytoplankton, lampreys and their predators as the objects of study, and assesses the stability of the ecosystem by measuring the Shannon diversity index. The results shows that an increase in male sex ratio contributed to the stability of the ecosystem under specific parameters. In addition, this paper investigated the potential effects of changes in the sex ratio of lampreys on their parasite populations and introduced the parasites into an ecological network model. In this paper, this paper found that changes in parasite abundance may give certain parasites an advantage. These findings contribute to a better understanding of the effects of sex ratio changes on ecosystem stability and provide an important reference for ecological conservation and management.
Influencing Factors of NBA Player’s Salary Based on Mixed Linear Model
Authors: Qian Li’ao
Published: June 2024

With the intensification of the global commercial influence of NBA, the salary of its player has always been a hot topic. This paper aims to offer a more practical insight for stakeholders within NBA ecosystem and provide a reference for the revolution and development of China’s professional basketball league by further analyzing the main factors that impact the salary level of NBA player based on previous study. Although many of the influencing factors considered in this paper have been mentioned in previous literature, they have not been systematically sorted out and analyzed based on data. A total of 8626 valid datasets of 454 NBA players in 2017-2018 season are selected as the research object for the study. By constructing a mixed linear model, which considers both fixed effects and random effects in NBA player’s salary influencing factors, two conclusions are drawn. Firstly, there are multiple factors that affect the salary of NBA players, among which age, morphology, draft ranking, game experience and usage have obvious influence on the salary of players. On the other hand, nationality, education and efficiency (related to team performance) have no significant correlation with player’s salary.