bluuebunny/crossref_metadata_2025 huggingface dataset:
Legal Regulation of Artificial Intelligence Directors under the Background of the Revision of China's New Company Law
Authors: Xue Hao
Published: July 2024

With the rapid development of technology, artificial intelligence technology has gradually been valued by the public and applied in various industries. At the level of business and corporate governance, there are also examples of AI directors participating in corporate governance internationally, providing us with space to explore the application of AI directors in Chinese corporate governance and decision-making. In December 2023, China promulgated a newly revised Company Law, and this article aims to explore how China responds to the issue of artificial intelligence directors in the context of the new Company Law. Specifically, it manifests as the authorization of artificial intelligence directors as auxiliary functions, the expansion and modification of the obligations of natural person directors, and the issue of responsibility assumption caused by artificial intelligence directors.
The Essence of "Inversion" in Dialectics: From Hegel to Marx
Authors: Guan Kexin
Published: July 2024

The relationship between Marx's dialectics and Hegel's dialectics has always garnered significant attention. This relationship is not only a manifestation of their respective thoughts, but also an important link in the development of dialectics itself. "Inversion" is a significant philosophical concept proposed by Marx during the process of sublating Hegel's dialectics. A thorough analysis and understanding of "inversion" is a crucial link in fully grasping Marx's "critical nature". The dialectics of Marx's "critical nature" is rooted in idealism, and Marx believed that the consequence of this manifestation was the loss of the critical nature of dialectics. To correctly reveal the essence of dialectics, Marx centered on "human practice" as the fundamental method and completed the "inversion" of Hegel's dialectics. Marx inherited the "rational core" of the narrow sense dialectics, which is centered on negation, and discarded the "mystical shell" of the broad sense dialectics. At the same time, he re-inverted the relationship between spirit and reality that had been inverted in the "rational core", thereby highlighting human subjectivity and giving dialectics a revolutionary and critical nature.
The History of the Dissemination of Lifelong Education Thoughts in the UK and Its Implications for China
Authors: Li Yinghong
Published: July 2024

The concept of lifelong education is an important educational thought aimed at future education strategies. Modern lifelong education thoughts originated in the UK in the early 20th century, initially developed in Europe and the United States, and gradually spread to and influenced various countries in Asia. This paper reviews the history of the dissemination of lifelong education thoughts in the UK, utilizing historical-factor analysis to summarize the experiences and patterns of its historical development. It focuses on the pathways for the dissemination and absorption of lifelong education thoughts in China's adult education and higher education sectors in the near future, aiming to contribute to the goal of modernizing Chinese education.
The Relationship Between Stress and Greenspace Exposure
Authors: Zhao Leyi
Published: July 2024

This essay use literature review to explores the relationship between greenspace and stress, drawing on evidence from multiple studies that utilize cortisol measurements to indicate changes in stress levels. Greenspace refers to all natural green areas, including parks, woodlands, scrublands, and other natural environments. People's stress can be influenced by various factors such as the environment, family, friends, and work or study. Therefore, it is important to understand how much a green environment can reduce stress. The findings strongly suggest that greenspace has a beneficial impact on reducing mental stress. However, the influence of greenspace exposure varies by gender. For men, a moderate amount of greenspace is optimal for stress recovery, while more greenspace does not necessarily lead to greater improvement. In contrast, the effects on women require further investigation to be fully understood.
A Multimodal Discourse Analysis of Advertisements and Movie Posters
Authors: Zhao Haohao
Published: July 2024

Multimodal discourse analysis, grounded in Halliday's Systemic Functional Grammar, has been widely applied in advertising, movie posters, and e-commerce. Studies often use Kress and Van Leeuwen's visual grammar to understand how images convey meaning. It will compare the multimodal theoretical analysis of movie posters and ads, focusing on textual, color, and layout modalities, as well as stylistic features and internal modalities. Additionally, we will explore enhancing user experience in advertisements through multimodal analysis, aiming to increase impact, expressiveness, user engagement, and precise placement.
The Difference Between the Theory of Conformity and Neo-Confucianism in the View of Truth
Authors: Li Hui
Published: July 2024

In philosophical theory, the understanding of "truth" can be divided into axiological truth and epistemological truth. The truth in the axiological sense mainly involves the problem of meaning and value, while the truth in the epistemological sense involves the problem of the conformity between the subject of knowledge and the object of knowledge or the objective reality. From the epistemological point of view, we can clarify the difference between the coincidence theory and the Chinese Neo-Confucianism in the view of truth so that we can not only explain the truth of each theory but also understand the harmonious relationship between the two views of truth.
From Xenophon's Constitution of the Lacedaimonians to See the Instrumental Role of the Ideal Spartan Image in His Historical Writing
Authors: Guan Qichang
Published: July 2024

In 1933, French historian Olier raised the issue of the "Spartan Illusion" and believed that ancient historians' impressions of Sparta must have been artificially processed based on the author's writing purpose. Xenophon's The Constitution of Lacedaemonians is the crucial surviving material of a contemporary author who personally experienced and recorded the specific internal conditions of the Spartan city-state. It is also a concentrated expression of the Spartan illusion. As a historian of the Greek city-state crisis period, Xenophon not only paid more attention to Sparta in the process of writing "Greek Chronicles" due to his legendary personal experience, but also focused more on the image of ideal Sparta. Thinking about sex, theodicy, and political philosophy were integrated into historical writing, making the image of Sparta the focus of Xenophon's historical writing and philosophical thinking, and a tool for him to write history. Previous research has mainly focused on a series of subtle thoughts that Xenophon developed by borrowing the Spartan illusion. This article intends to formally explore and summarize the process of Xenophon manufacturing and using this writing instrument, and whether it achieves its expected results.
Motivating Chinese Students in UK Higher Education Through Constructivism to Help Improve Their Employability
Authors: Zuo Yinan
Published: July 2024

Many studies have shown the enhancement of competitive advantage is one of the main reasons Chinese students study in the UK, but most of them do not have clear career goals, and the demand of the labour market have become stringent. In this context, Chinese students need to be helped to carefully assess and reflect on their employability during their studies. The Graduate Capital Model, which categorises the skills that graduates need to acquire into five capitals; Constructivism, a theory that promotes student autonomous learning and co-operative learning, has been effective in helping Chinese students to develop a sense of reflection and improved employability. This study explores the importance of employability and Constructivism through a literature review and research comparison; and discusses the combined application of Constructivism and the Graduate Capital Model in practice. To provide Chinese students and UK universities and educators with the opportunity to think more creatively about learning and teaching, rather than continually following previous experiences.
The Study of Dissociative Identity Disorder: Etiology, Cognitive Ability and Treatment
Authors: Yang Aijia , Luo Shiyang , Liu Yihong , Wang Changqi
Published: July 2024

This paper provides an overview of Dissociative Identity Disorder (DID), its etiology, cognitive aspects, and treatment options. It explains the concept of dissociation and dissociative disorders, leading to the specific focus on DID. The etiology section discusses the multifaceted nature of DID, including biological factors like genetic vulnerabilities and neurobiological abnormalities. Psychological factors, particularly trauma and maladaptive schemas, and social factors, including societal influences and media portrayals, are also explored. This paper delves into cognitive abilities and their impact on individuals with the disorder. Like the relationship between sleep disturbances, trauma, dissociation, and cognitive abilities in individuals with DID and post-traumatic stress disorder (PTSD). The last part focuses on its treatment approaches, the holistic treatment approach that includes symptom reduction, engagement with traumatic memories, and integration and rehabilitation. Psychotherapy, such as cognitive behavioral therapy and eye movement desensitization and reprocessing, is the primary treatment modality, while medication may be used. This work also discusses the need for further research. It discusses potential connections between childhood trauma and cognitive strategies, the role of DID in enhancing aggression and self-protection abilities, and the impact of comorbid PTSD on treatment outcomes. By addressing these research gaps, more effective treatments for DID can be developed.
Audiovisual Books Have Better Effects Than Teacher-assisted Model in Second Language Acquisition for Preschool Children
Authors: Liu Shuqi
Published: July 2024

This study explores the impact of audiovisual books on second language acquisition in preschool children, addressing challenges related to bilingual teacher availability and high-quality resources in Chinese kindergartens. A comparative analysis between teacher-assisted and instructional audiovisual book methods was conducted in a teaching experiment involving 30 students from a kindergarten in Shenyang, China, who share similar educational backgrounds. The students were divided into two groups, and both groups underwent a pretest and posttest to assess their performance. The findings revealed that audiovisual books were more effective, resulting in significant improvements in letter acquisition for the experimental group. The literature review emphasizes the motivational and convenient aspects of audio-visual books. In the current context of limited teacher resources and the increasing prevalence of electronic devices, audiovisual books offer significant convenience and assistance for educators, parents, and students. This study supports the enhancement of language acquisition in young learners, positioning them for future academic success.
Can BDNF manipulate the overshoot-and-decline effect of adult neurogenesis during recovery from sleep deprivation?
Authors: Jiang Zhifeng
Published: July 2024

Sleep deprivation reduces an organisms ability to perform adult neurogenesis, the generation of new neurons in adulthood. Recently, researchers discovered that recovery in sleep deprivation causes the rate of adult neurogenesis to overshoot the normal rate, and then decline back to normal. This research focuses on brain-derived neurotrophic factor, and whether or not manipulating it and its related pathways could extend the overshoot effect to enhance adult neurogenesis in the long term. The conclusion that is expected from this research is that BDNF will be able to prolong the overshoot of adult neurogenesis that is induced by sleep deprivation. The work seeks to provide more control over the overshoot-and-decline effect of adult neurogenesis during recovery from sleep deprivation, opening new pathways to treatments involving the manipulation of adult neurogenesis.
Applications of machine learning to electronic health record data in liver-related disease
Authors: Luo Jie , Sun Yuqi , Liu Jiachen , Zhou Yu
Published: July 2024

Electronic Health Records (EHRs) has gained its increasing significance in modern healthcare as its promising prospects in the application of machine learning. The accumulation of vast clinical data holds potential for repurposing in clinical research such as prediction, diagnosis and prognosis. However, the collection and preparation of EHR data present challenges, primarily due to the inherent incompleteness of the data and the associated privacy and security concerns. To address the issue, text-mining tools based on domain-specific lexicons, data sharing and multiple de-identification methods have been suggested. In terms of methodologies, various machine learning models and algorithms used in EHR data analysis are analyzed, including logistic regression, decision trees, random forests, and natural language processing, each with its unique application scenarios in the healthcare domain. Liver related diseases, including HAV, HBV, HCV and especially Liver Cancer, has affected hundreds of millions of people around the world. The incidence and mortality rates for these diseases are still rising continually. With recent advancements of Machine Learning techniques, such as the attention mechanism and BERT-based embedding, which have shown exceptional results in EHR analysis when applying to liver diseases. While EHRs offer a treasure trove of data for clinical research, the challenges associated with their collection, processing, and analysis cannot be ignored. It underscores the need for robust methodologies and tools to harness the full potential of EHRs while ensuring data integrity and patient privacy. In this paper, we will gather and review the existing application in the realm of liver-related diseases.
Design and implementation of efficient distributed deep learning model inference architecture on serverless computation
Authors: Guo Xiaoyang , Yang Zhe , Yi Jie
Published: July 2024

Although the distributed algorithm and architecture have been widely used in the development of traditional large-scale machine model reasoning tasks, but it is unavoidable about the source waste caused by synchronization between learners and participants. However, serverless computing is charged based on usage, which makes it a popular alternative for model inference. This article mainly proposes the architecture and algorithm that can be used for the inference task of the distributed deep learning model and adopts coarse-grained parallelization strategy to solve the problem of high communication cost between Serverless platform functions. The paper tested the performance of the model on the deep learning model and found that the model reasoning based on the Serverless platform can better cope with the requirements and changes, and ensure the stability of the system. It is worth noting that both the data owner and the model owner can benefit from the process of carrying out the machine learning model inference task, but existing solutions cannot satisfied with them privacy requirements, which is a problem needs to think about in the field of machine learning inference tasksbased on the Serverless platform in the future.
Intelligence and safety: research progress and trends in multiphase flow separation technology and equipment
Authors: Wang Xiaoxuan
Published: July 2024

At present, with the rapid development of industrial automation and information technology, intelligence has become a key trend to improve the efficiency and safety of industrial equipment. Multiphase flow separation technology is an important link in the energy, chemical, and other industries, and the intelligent upgrade of its equipment and the study of safety technology are of great significance for improving the energy savings, environmental protection level, and production safety of the whole industry. This paper carries out a comprehensive study of domestic and foreign multiphase flow separation technology and equipment, combines the current scientific research background, future research trends, and the structural integrity and safety technology of pressurized equipment, analyzes the current challenges, and puts forward reasonable development suggestions for comprehensively upgrading the intelligence, stability, and reliability of separation equipment.
Metal-organic frameworks (MOFs) for photoreduction of CO2
Authors: Xiao Xinyu , Huang Shih-kai , Chen Hongming
Published: July 2024

In recent decades, human industrialisation has become increasingly advanced, and the quality of life has also improved. Subsequently, the excessive consumption of fossil fuels has caused a series of problems, for example, global environmental warming caused by excessive CO2 emissions. Among numerous CO2 reduction technologies, using solar energy as an energy source for the CO2 photoreduction is considered one of the most prospective technologies. This method not only reduces the amount of CO2, but also enables to converse CO2 into other valuable chemicals, thereby achieving carbon cycling. Metal-organic frameworks (MOFs) are composed of metal ions and organic ligands as three-dimensional porous materials. MOFs have many advantages, including sizeable specific surface area, excellent CO2 absorption capacity and modifiable pore structure, leading to broad application potential in photocatalytic reduction of CO2. This article mainly introduces three aspects: functionalisation and modification of pure MOFs, MOF-based composite materials, and MOF-derived materials, which further improve the CO2 photocatalytic efficiency of MOFs. Furthermore, it includes the analysis of reported examples, discussion and outlook on reaction mechanisms and challenges. At present, the main difficulties faced by MOFs-based photocatalysts lie in their economic feasibility and poor material stability. Therefore, this review aims to help stimulate in-depth research in this area as well as better exert the advantages of MOFs.
Comparative analysis of the impact in societies of silicon technology against that of steel
Authors: Ding Wei
Published: July 2024

This paper will first introduce silicon and steel then deeply discuss the impact to the society. Furthermore, I will also estimate the effect to the future about these two materials. Silicon is one of the most significant and useful elements which have been used in huge amounts of fields. For instant, silicon is the primary material to make semiconductor and optical fiber even to synthesize metal-cermet, which is a core material for the spacecraft. The central processing unit (CPU) is also made by silicon, so it is a common and important element now a day. Although silicon is discovered in early 18 centuries even earlier than steel, it doesnt have a big effect in the second industrial revolution. Difference with silicon, steel is the fundamental material of cars, rail and most of the machine invented in industrial revolution because the durability and plasticity. However, this valuable material cant be efficiently produced until Bessemer converter comes out. This machine developed the first process for manufacturing steel inexpensively.
A review on the effect of different advanced joinery applied on automobiles to reach fuel economy
Authors: He Siwei , Zeng Yuening , Chen Jiaqi , Xue Jieyou
Published: July 2024

Fuel economy has always been a key performance indicator of automobiles and an urgent issue to be addressed in environmental protection. Fuel economy is influenced by various factors such as car quality, driving resistance, transmission, engine, etc. To increase the fuel economy of automobiles, manufacturers are utilizing new materials for vehicle construction. therefore, it is necessary to investigate the most effective joinery method for constructing lightweight automobiles. In this article, the stages of joinery technology, including clinching, ultrasonic welding, riveting, bolting will be discussed. The authors have chosen to focus on the three most important aspects of these five methodologies, which are strength, bending, and fatigue. This paper will present a conclusion regarding these joining methods after discussing their properties.
Regions of the southern Atlantic Ocean: A study on the sea surface temperature and sea surface salinity of the southern Atlantic Ocean region
Authors: Li Bolun , Ni Zekai
Published: July 2024

Followed by the fast advancement of computer science and technology, studies involving massive datasets, especially environmental sciences, have been more accessible for researchers. Yet, with the completion of high-resolution data about the southern Atlantic Ocean region, there has not been sufficient academic research focusing on this specific area. In this regard, this paper investigates the connection between the Sea Surface Temperature (SST) and Sea Surface Salinity (SSS). The researchers chose South Atlantic as the research subject, and based on the visualization of the datasets from year 2010 to year 2014 to determine the number of clusters, the team applied k-means clustering to analyze the relation between SSS and SST by MATLAB. As a result, the research team found that the variation of the value of SSS and SST within the five years showed a stable tendency. The team classified the South Atlantic Ocean into four different oceanographical regions (based on the clusters acquired from the k-means technique), which each area showed a distinct feature in SSS and SST.
Ocean circulation response to rapid climate change
Authors: You Aming , Wang Mulun , Yu Yue
Published: July 2024

In recent years, the trend of global warming has been significant, with changes occurring in the atmosphere, oceans, wind fields, and other areas due to climate change. To predict the future response of ocean circulation to climate change under the influence of global warming trends, this work is based on the response of ocean circulation to ancient climate change. Through research and analysis of three factors, including The Atlantic Meridional Overturning Circulation(AMOC) index, salinity and temperature, combined with various data and chart analysis, the response mechanism of ocean circulation to climate change is explored. Explore the possibility of ocean circulation responding to future climate change. At the same time, fully analyze the advantages and disadvantages of this study to prepare for further research.
Research on multi-beam survey line system based on dynamic programming algorithm
Authors: Chen Xiaoya , Chen Xuanyu
Published: July 2024

This paper establishes a calculation model for the coverage width and overlap rate of a multi-beam survey line system [1], and optimizes the multi-beam bathymetric survey plan for marine areas. Through the dynamic programming algorithm, a reasonable survey line plan is designed based on the actual marine area depth. The research content includes:
Model Establishment: Construct a calculation model for coverage width and overlap rate, determining the coverage width and overlap rate at each position.
Three-Dimensional Space Model: Using the survey vessel as the origin and combining marine area information, solve for the coverage width at different angles.
Shortest Survey Line Plan: Using the dynamic programming algorithm, determine the shortest survey line plan, with the dynamic transfer equation determined by the overlap rate index. The total length of the survey line in this plan is calculated to be 114,824 meters.
Specific Survey Line Plan Design: Using sea depth data and cubic spline interpolation to complete the discrete point plane, construct approximate width and slope. Under the condition of relaxing the overlap rate to 5%-30%, the shortest survey line length is obtained as 398,059 meters, with a missing survey area ratio of 0%, and the total length of parts with an overlap rate exceeding 20% is 25,759 meters, accounting for 6.4%.
This study provides theoretical basis and calculation methods for optimizing multi-beam bathymetric survey plans.
A novel ensemble model for emotion classification in social media text
Authors: Jiang Xintong
Published: July 2024

Social media provides people with a platform to share their experiences and perspectives, and text is the most common way as either posts or comments. Much emotion-related information, such as mental state and attitude, can be revealed through texts. As a result, text-based emotion analysis plays an important role. This paper aims to propose a new classification model using the ensemble learning method, which can classify the emotions detected from the text into six classes, including joy, fear, surprise, love, sadness, and anger. Multiple base models are trained at the first stage, including traditional machine learning models (Multinomial Naive Bayes, SVM, and Decision Tree) and deep learning models (CNN, LSTM, and GRU). Then, a new ensemble model using the stacking method is developed. The stacking of deep learning models and SVM has achieved the best classification performance, where the accuracy and F1 score are 0.8875 and 0.8410, respectively. The evaluation metrics demonstrate the effectiveness and robustness of the new ensemble model for this emotion classification task.
Based on graph theory, design of distributed control system for multi-quadcopter UAVs
Authors: Gao Yuan
Published: July 2024

This paper addresses the formation control system for multi-quadcopter UAVs, proposing a control strategy based on finite-time stability theory. It designs position controllers with a dual power structure and attitude controllers combined with non-singular terminal sliding mode to achieve fast convergence and high-precision tracking. Through Lyapunov stability analysis, the paper proves the finite-time convergence of the control strategy. Simulation experiments validate the method's excellent performance in formation establishment, maintenance, and complex trajectory tracking, demonstrating rapid convergence, high precision, and strong disturbance rejection capabilities. This research provides theoretical and technical support for cooperative control of multi-quadcopters.
The advancements and future prospects of pedestrian action recognition based on machine learning algorithms
Authors: Wen Yi
Published: July 2024

This paper highlights the shift from classical machine learning to deep learning models and describes the fundamental methodology and developments in pedestrian activity recognition. The four main steps of the workflow are the gathering of datasets, pre-processing, designing and training the model, and evaluating the outcome. To extract pedestrian feature vectors, data must first be collected, cleaned, and processed from public or proprietary datasets. These vectors are used to train deep learning or machine learning models, which are subsequently assessed and fine-tuned for use in practical applications such as behaviour analysis and surveillance. For action recognition, conventional machine learning techniques like Random Forests (RF) and Support Vector Machines (SVM) have been used. SVMs, despite their potential for computing complexity, identify the best hyperplanes for classification. The categorization rates for a variety of human behaviours have been enhanced by a combination strategy utilizing SVMs and decision trees. As shown in a study that uses smartphone accelerometers to accurately identify everyday activities, RFs can manage enormous datasets. Deep learning models that automatically learn complicated feature representations, such as VA-fusion, AGC-LSTM, and LC-POSEGAIT, provide improved performance. These models capture minute differences in pedestrian behaviour using CNNs, RNNs, and LSTM architectures. Interpretability, generalization to new datasets, and computing demands are some of the difficulties they encounter. Future developments could include using transfer learning to improve performance in many circumstances, combining deep learning and expert systems for improved interpretability, and utilizing distributed computing for processing in an effective manner.
Comparative analysis of federated learning algorithms under non-IID data
Authors: Dai Jirui
Published: July 2024

With the increasing global attention to data privacy and security issues, how to effectively utilize distributed data while protecting personal privacy has become an important research topic. Federated learning (FL) aims to address data silos and privacy issues by enabling multiple devices or servers to train shared models in collaboration without submitting raw data to a central server. Although a variety of federated learning algorithms have been proposed, there is still a gap in the research on their performance differences under the same model. The goal of this study is to compare and analyze the performance differences of different federated learning algorithms on the same model through experiments. Based on the Fashion-MNIST dataset, this paper compares four commonly used federated learning algorithms in detail: Federal Averaging (FedAvg), Federated Stochastic Gradient Descent (FedSGD), Stochastic Controlled Averaging for Federated Learning (SCAFFOLD), and Federated Proximal (FedProx). The experimental results show that FedProx performs best in all evaluation indicators, followed by SCAFFOLD and FedAvg, while FedSGD performs the worst. These insights into algorithm performance with non-IID data inform practical application suitability and guide future research.
Federated learning: Impact of different algorithms and models on prediction results based on fashion-MNIST data set
Authors: Gao Yuan
Published: July 2024

The realm of federated learning is rapidly advancing amid the era of big data. Therefore, how to select a suitable federated learning algorithm to achieve realistic tasks has become particularly critical. In this study, we explore the impact of different algorithms and models on the prediction results of Federated Learning (FL) using the Fashion-MNIST data set. Federated Learning enhances data privacy and reduces latency by training models directly on local devices since it is a decentralized machine learning approach. We analyze the performance of several FL algorithms including Federated Averaging (FedAvg), Federated Stochastic Gradient Descent (FedSGD), Federated Proximal (FedProx), and SCAFFOLD. Our experiments reveal significant differences in accuracy and stability among these algorithms, highlighting their strengths and weaknesses in handling non-IID (Non-Independent and Identically Distributed) data. FedProx demonstrate superior performance in terms of accuracy and robustness, making them suitable for complex federated learning environments. These discoveries offer crucial insights for choosing suitable FL algorithms and models in practical applications.
Federated learning enhanced AR/VR integration in sleep wearable devices
Authors: Zhang Zhiruo
Published: July 2024

As a crucial aspect of human health, sleep remains a problem to many individuals. Many still struggle with going to sleep or poor sleeping quality. In terms of ways to interfere with this issue, traditional sleep measurement methods, such as polysomnography(PSG), are intrusive, expensive, and inconvenient for long-term monitoring. Wearable devices offer a practical alternative but often face challenges related to accuracy, comfort, and data privacy. Advances in technology present new opportunities to address these issues.This systematic review focuses on examining the drawbacks of current sleeping measurements and wearable devices, and further explores the integration of federated learning (FL) with AR, VR in sleep wearable devices in order to promote sleep facilitation. The study addresses key challenges in sleep research, including accurate and non-intrusive monitoring, data privacy, and personalized sleep coaching. Federated learning enables decentralized data analysis, enhancing model accuracy while preserving user privacy. AR and VR technologies offer immersive environments for sleep facilitation through tailored relaxation techniques. The combination of these technologies provides innovative solutions to improve sleep quality and intervention efficacy. Future research should focus on enhancing device comfort, accuracy, and the integration of FL algorithms for better user experiences.
Exploring the role of blockchain technology in enhancing data integrity and privacy protection
Authors: Meng Xianghui
Published: July 2024

This paper systematically builds a theoretical framework for enhancing data integrity and privacy protection by analyzing the fundamentals of blockchain technology and its inherent characteristics, such as decentralization, tamperability, and cryptographic algorithms. The study empirically examines the transparency and anonymity balance mechanism of blockchain in handling sensitive data using case studies and simulation experiments, and at the same time, designs smart contracts to automatically implement data protection strategies for different types of data security threats.
An analysis of risk control in the financial sector using big data technology
Authors: Lin Dalong
Published: July 2024

The rapid development of information technology has ushered in a new era of big data in the financial industry, which has provided financial institutions with a plethora of novel tools for risk management, while also playing a pivotal role in the industry's risk control landscape. This paper analyzes the public data of existing financial institutions, combines relevant literature, and employs big data technology to assess and identify risks, which aims to explore how big data technology can improve the risk management ability of the financial industry. In addition, the paper examines the challenges and problems faced by big data technology in the application of financial risk control, including data privacy and security, technology costs, and the demand for specialized talents. The research demonstrates that big data technology improves the speed and accuracy of risk identification, but also points out the challenges of data privacy and security management. Future risk control models need to better integrate big data analytics with traditional risk management methods, thus promoting the further development and application of big data technology in the field of risk control.
Research on the application of statistical methods based on big data in the medical and health field
Authors: Yang Wenyan
Published: July 2024

In the current era of information, the rise of big data technology has become a key force driving the development of the medical and health field. Statistical methods, as core tools for data analysis, have demonstrated unique advantages in processing vast medical datasets. This paper comprehensively analyzes the various applications of big data statistical methods in the medical and health field, focusing particularly on their practical effects and potential value in disease prediction, epidemiological research, medical resource optimization, and personalized medical services. Through a review of relevant literature and in-depth discussions of multiple cases, this paper reveals how statistical methods play a crucial role in improving diagnostic accuracy and medical service efficiency. It also addresses the challenges faced in actual applications, such as data privacy protection and technical standardization.
Applications and issues of artificial intelligence in the financial sector
Authors: Chen Yanyu
Published: July 2024

This paper investigates the application of artificial intelligence in the financial sector, analyzing the existing technical, ethical, and legal issues, and proposing corresponding solutions. The research background highlights the widespread use of AI technology in the financial industry and the efficiency and cost benefits it brings. The research focuses on challenges related to data quality, feature engineering, model complexity, real-time capability, computational resources, and data privacy protection. The research method includes literature review and case analysis, revealing the applications of AI technology in stock prediction, risk management, trading strategy optimization, and customer service. The results indicate that effective data cleaning, automated feature engineering, model simplification and regularization techniques, the use of interpretability tools like LIME and SHAP, and the introduction of fairness evaluation standards can significantly enhance AI model performance and transparency. The conclusion points out that these measures can not only solve the current technical and ethical issues of AI in the financial sector but also promote the widespread application and standardization of AI technology in other fields.
Relationship Between Technological Environment And The Effectiveness of Accredited Private Madrasah Aliyah in Riau Province
Authors: Tabi'in As'ad , Muntholib  , Hakim Lukman
Published: July 2024

This study aims to examine the relationship between the technological environment and the effectiveness of accredited Private Aliyah Madrasah A in Riau Province both partially and simultaneously. This research is a quantitative study with a survey method conducted at Private Aliyah Madrasahs in Riau Province. population of 79 people and samples using random sampling. The hypothesis in this study is: technological environment has a significant relationship both partially and simultaneously to the effectiveness of madrasah. Hypothesis testing uses Pearson Product Moment Correlation and multiple regression technique analysis, with a significance level of alpha 5 percent (α=0.05). This study results in findings, namely: technological environment has a significant relationship with madrasah effectiveness. Based on the research findings, it can be concluded that: the technological environment variable contributes significantly to the effectiveness of madrasah, namely the value of tcount (5.879) > ttabel (1.991) so that H0 is rejected and H1 is accepted, which means that the technological environment provides a significant relationship to the effectiveness of madrasah.
KONTRIBUSI PAJAK DAERAH TERHADAP PENDAPATAN DAERAH KABUPATEN BATU BARA TAHUN 2018-2021
Authors: Rumapea Masnida Elawati , Sembiring Yan Christin , Saragih Afni Eliana
Published: July 2024

This study aims to find out how big the contribution of local taxes is to the local revenue of Batu Bara Regency.  The population of this study is the realization of local taxes and the realization of local revenue at the Regional Revenue Agency of the Batu Bara Regency.  The sample for this research is Regional Tax data and Regional Original Revenue data for 2018-2021 at the Regional Revenue Agency of Batu Bara Regency.  The analytical method used is descriptive analysis with the contribution rate formula.
Based on the results of the research, it shows that the average contribution realization for 2018-2021 is Hotel Tax, Entertainment Tax, Street Lighting Tax, Parking Tax, Swallow's Nest Tax, Non-Metal Mineral Tax and Acquisition Tax is better than the average realized contribution in  2014-2017 while the Restaurant Tax, Advertising Tax, Land Water Tax and Land and Building Tax are not better.  For the average budget and realized contributions for 2018-2021 Entertainment Tax, Advertising Tax, Street Lighting Tax, Parking Tax, Groundwater Tax and Non-Metal and Rock Mineral Tax and Acquisition Tax fulfill the budget while Hotel Tax, Restaurant Tax, Sarang Tax  Swallow, Land and Building Tax do not meet the budget and of the eleven Regional Taxes that are classified as "good enough" is the Street Lighting Tax with an average realized contribution for 2018-2021 of 39.48%.
 
Kata Kunci: Regional Tax, Regional Original Revenue, Contribution
PENGARUH BUDAYA ORGANISASI, KOMITMEN ORGANISASI DAN AKUNTABILITAS PUBLIK TERHADAP KINERJA RSUD DJOELHAM BINJAI
Authors: Sitio Kezia Dominika , Parhusip Poltak Teodorus
Published: July 2024

This study aims to prove Organizational Culture, Organizational Commitment and Public Accountability affect performance. The sample in this study was obtained using the proportionate stratified random sampling method with a total sample of 77 respondents. The data analysis technique used is descriptive analysis, data quality test, classical assumption test, multiple linear regression analysis and hypothesis testing using t test and f test with a significance level of 5% using SPSS 26. From the results of research using SPSS, it is known that the value of the coefficient of determination (Adjustid R Square) is 0.730. Organizational Culture, Organizational Commitment and Public Accountability together affect Performance by 73%. Based on the results of multiple linear regression analysis, it can be concluded that organizational culture has a significant positive effect on performance, organizational commitment has a significant positive effect on performance and public accountability has a significant positive effect on performance at the Djoelham Binjai Regional General Hospital. From the results of the t test, it was obtained that tcount > ttable (2,936 > 1,993) and sig < 0.05 (0.004 < 0.05). This means that Ha1 is accepted and H01 is rejected or in other words, Organizational Culture partially has a positive and significant effect on Organizational Performance. For the second variable, the results obtained where the value of tcount > ttable (2,941 > 1,993) and the value of sig < 0.05 (0.004 < 0.05). This means that Ha2 is accepted and H02 is Rejected or in other words Organizational Commitment partially has a positive and significant effect on Organizational Performance and the third variable is obtained where the value of tcount > ttable (6.869 <1.993) and the value of sig <0.05 (0.000 > 0.05) . This means that Ha3 is accepted and H03 is rejected or in other words Public Accountability partially has a positive and significant effect on Organizational Performance. The higher the organizational culture, organizational commitment and public accountability, the better the performance in the hospital.
ANALISIS PENGARUH KEGIATAN SOSIALISASI PERPAJAKAN DAN PEMERIKSAAN PAJAK TERHADAP PENERIMAAN PPH PASAL 25/29 WAJIB PAJAK BADAN PADA KPP PRATAMA MEDAN PETISAH
Authors: Sihite Desima R. , Sembiring Yan Christin Br , Sitanggang Abdonsius
Published: July 2024

This study aims to find out how to analyze the influence of tax socialization activities and tax audits on income tax revenues article 25/29 for corporate taxpayers at KPP Pratama Medan Petisah. The population in this study is the number of taxpayers who are active and registered at KPP Pratama Medan Petisah from 2015-2022. This study uses primary and secondary data obtained by direct surveys to the field by distributing questionnaires to corporate taxpayers. The data analysis technique used in this study is a descriptive data analysis technique, namely describing and interpreting data according to existing facts.Based on the discussion of the research results obtained, it can be concluded that tax socialization activities at KPP Pratama Medan Petisah partially have a significant positive effect on tax revenues. Tax audit at KPP Pratama Medan Petisah has a significant positive effect on tax revenues. There is a positive influence on the receipt of income tax articles 25/29 for corporate taxpayers. simultaneously tax socialization and tax audit have a positive and significant effect on tax revenues. We can see that the three variables have a positive and significant influence. This means that the more often (positive) tax socialization and tax audit activities are carried out, the income tax revenue article 25/29 will also increase.
EVALUASI EFEKTIVITAS DAN KONTRIBUSI PENERIMAAN PAJAK BEA PEROLEHAN HAK ATAS TANAH DAN BANGUNAN TERHADAP PENDAPATAN ASLI DAERAH KOTA MEDAN
Authors: Sembiring Sabeth , Sinaga Ria Veronica , Sembiring Yogi Yovendra
Published: July 2024

This study aims to determine the level of effectiveness and contribution of Customs Tax on Land and Building Rights to the Regional Original Income of Medan City. The population of this study is the Medan City BPHTB tax and Medan City Original Revenue from 1978-2020. The sample of this research is the number of targets and realization of BPHTB tax revenues and realization of PAD in Medan City in 2016-2020. This study uses a descriptive method, the data collection technique in this study is a documentation technique obtained from the Medan City BPPRD office, and analyzes using the formula for the level of effectiveness and the level of contribution. Based on the results of the study, it shows that the level of effectiveness of the Tax on Acquisition of Rights on Land and Buildings has an average of 89.83% overall from 2016-2020 and is classified as "quite effective" and for the level of contribution of Taxes on the Acquisition of Rights on Land and Buildings. 2016-2020 with an average BPHTB tax contribution of 23.02% better than the Contribution Level of Tax Revenue from Land and Building Rights Acquisition in 2011-2015 with an average BPHTB tax contribution of 18.88%.
Perkuatan Pelat Lantai Dengan FRP (Fibre Reinforced Polimer) (Studi Kasus: Gedung Sekolah Siantar)
Authors: Siahaan Samuel , Tarigan Johannes
Published: July 2024

Perkuatan struktur diperlukan apabila struktur mengalami kerusakan yang berakibat tidak terpenuhinya lagi persyaratan teknis, seperti kekuatan, kekakuan dan daktilitas, kestabilan.. Penelitian ini menghitung perbaikan struktur pelat pada bangunan sekolah, yang mana perbaikan akan menggunakan FRP (Fibre Rainforced Polymer) sebagai bahan utama perbaikannya. Penelitian ini, menganalisis perkuatan pelat dengan cara menghitung momen pelat dengan menggunakan metode Konvensional, Teori Balok, dan juga dengan Teori Papan Catur dengan bantuan SAP2000. Perkuatan pada struktur ini direncanakan sebesar 30% dari kekuatan awal dari struktur pelat bangunan ini. Pelat yang ditinjau hanya pada pelat ruangan kelas. Dari hasil perhitungan diperoleh hasil perhitungan Teori Konvensional adalah Momen Tumpuan sebesar 2134,8 Kgf/m dan Momen Lapangan sebesar 1372,37 Kgf/m. hasil perhitungan Teori Balok adalah Momen Tumpuan sebesar 1174,5 Kgf/m dan Momen Lapangan sebesar 557,25 Kgf/m.Dan hasil perhitungan Papan Catur dengan Momen terbesarnya adalah Momen Tumpuan sebesar 1148,93 Kgf/m dan Momen Lapangan sebesar 485,86 Kgf/m. Momen yang dipakai dalam perhitungan FRP adalah momen konvensional. Berikut adalah perhitungan momen setelah penambahan FRP pada pelat lantai, CFRP 30,92 % atau sama dengan 6601194,61Nmm dengan banyak FRP 5 lembar, AFRP 48,43 % atau sama dengan 10339463.78Nmm dengan banyak FRP 8 lembar, FRP 31,27 % atau sama dengan 6676954.04Nmm dengan banyak FRP 10 lembar.
PENGARUH RETURN ON ASSET, DEBT TO EQUITY RATIO, DAN EARNING PER SHARE, TERHADAP RETURN SAHAM PADA PERUSAHAAN LQ45 DI BURSA EFEK INDONESIA PERIODE 2017-2020
Authors: Siregar Esra Rapma , Silalahi Donalson
Published: July 2024

This study aims to examine and explain the effect of return on assets, debt to equity ratio and earning per share on stock returns in companies including LQ-45 on the Indonesia Stock Exchange for the 2017-2020 period. The population in this study were 45 companies. The sampling technique used is purposive sampling, in order to obtain 9 manufacturing companies.  The data analysis technique used is multiple linear regression analysis and uses T test and F test with a significance level of 5 percent. The results showed that return on assets had a positive and significant effect on stock returns, debt to equity ratio had a positive and significant effect on stock returns, Earning per share had a positive and insignificant effect on stock returns. The ability of return on assets, debt to equity ratio and earning per share in explaining variations in stock returns is 31.6 percent