bluuebunny/crossref_metadata_2025 huggingface dataset:
A Psychological Perspective of Menopause: Sandplay Process as a Rite of Passage
Authors: Reece Sachiko Taki
Published: November 2024

Menopausal women face a change in identity and in individuality with the cessation of monthly blood flow and the loss of fertility. Women in menopause have no rites of passage to guide and sustain them while they undergo the ordeal of these huge physical and psychological alterations. Sandplay process functions as a rite of passage whereby women can experience, consciously and unconsciously the stages of transition; they can find their own center in the midst of the life-altering change. The article includes a clinical case.
Body, Image, Symbolic Thought and Sandplay
Authors: Castellana Franco
Published: November 2024

The purpose of this work is to shed light on the processes that mediate the passage from the space of the real to that of the symbolic within an analytical setting that includes sandplay.
The Frontier of Group Sandplay
Authors: Reece Sachiko Taki , Ford Christine
Published: November 2024

The authors respond to Lenore Steinhardt's "Group Sandplay and Visual Reality," which was a response to Christine Ford's and Sachiko Taki Reece's "All the Children: Can Group Sandplay Help the Growing Need?" published in Volume 15, Number 2 of this journal.
YOLOv9-SE: A Real-time Vehicle Detection Model Based on Improved YOLOv9
Authors: Gao Yangzi
Published: November 2024

With an increasing number of urban vehicles and complex road environments, real-time vehicle detection has become a key technology in autonomous driving, but it faces many challenges. Although traditional two-step target detection algorithms (such as the R-CNN series) have high detection accuracy, their real-time performance is poor, which makes it difficult to meet the needs of vehicle detection. In contrast, one-step detection algorithms such as YOLO stand out for their high speed and higher accuracy. However, the real-time detection of the latest YOLOv9 model in urban vehicle scenarios still needs to be improved. Therefore, this paper have improved the YOLOv9 model, specifically introducing the SENetV1 attention mechanism into the backbone extraction network. The experimental results show that the mAP value of the improved algorithm in vehicle detection is promoted by 5% under the same training conditions. Such an improvement not only enhances the ability to capture relationships between channels, but also improves feature expression capabilities and expands the application of YOLOv9 in autonomous driving.
Research on Operation Mechanism and Construction Path of Government Information Ecological Chain in Big Data Era
Authors: Wu Wenya , Zhu Simin , Yang Chuanjie
Published: November 2024

From "manual administration" to "information administration", the government constructs a new model of big data governance based on chain-dependent relations through the means of information technology and transmission and feedback of data information resources: Government Information Ecology Chain. It has the characteristics of information sharing, link diversity and information control, including the three components of node, chain and environment. Value-added mechanism, coordination and cooperation mechanism, dynamic balance mechanism is the operating mechanism of the government information ecological chain. The opening of government information, the self-organization ability of government information ecological chain and the ecological environment of government information affect the formation and development of the government information ecological chain. Therefore, it is necessary to build a government information ecological chain from fostering a scientific culture of government information ecological chain, enhancing the security of government information ecology chain, innovating the service mode of government information ecology chain, and building the platform of government information ecological chain.
Analysis of Influencing Factors of Urban Road Traffic Accidents Based on Association Rules
Authors: Yang Jiaqi
Published: November 2024

Urban road traffic conditions are complex and changeable. Affected by multiple factors, the mechanism and main influencing factors of traffic accidents are difficult to define. This paper aims to study the distribution characteristics and main factors influencing urban road traffic accidents. According to the collected data of urban traffic accidents in Britain, the basic characteristics including trunk road flap, weather conditions, time, maximum speed limit, first road classification and other factors are all analyzed, with association rules used to explore its influence mechanism. From aspects of vehicle, environment and road, this paper not only focuses on the influence mechanism of the interaction of two factors and three factors in urban road traffic accidents, but also puts forward targeted accident prevention measures accordingly.
Innovative Application of BIM Based Intelligent Prefabricated Buildings in Green and Low-carbon Design
Authors: Huang Kun
Published: November 2024

This article explores the innovative application of intelligent prefabricated buildings based on BIM technology in green and low-carbon design. By analyzing the combination of BIM technology and prefabricated buildings throughout their entire life cycle of design, construction, and operation, the enormous potential of BIM technology in energy conservation, emission reduction, resource utilization efficiency improvement, and optimization of building performance has been demonstrated. Research has shown that BIM technology can effectively improve the design accuracy and construction efficiency of prefabricated buildings, reduce material waste and carbon emissions, and promote the sustainable development of the construction industry. In addition, this article also combines practical application examples to illustrate the specific application effects of BIM in intelligent prefabricated buildings, and looks forward to future development directions.
Machine Learning-Based Profit Modeling for Credit Card Underwriting: Implications for Credit Risk
Authors: Xu Tianyi
Published: November 2024

Accurate profit modeling is crucial for effective credit risk management in credit card underwriting. This study explores how machine learning methods can improve profit models in credit card underwriting, using data from a major Chinese bank as a case study. We employed three primary machine learning algorithms—Random Forest, Gradient Boosting Trees, and Neural Networks—to analyze a credit card customer dataset comprising 500,000 customers and 8 million transaction records. Model performance was evaluated using 10-fold cross-validation. The results show that the Gradient Boosting Trees model outperformed the others across all evaluation metrics. Specifically, the Gradient Boosting Trees model achieved an accuracy of 89.2%, a recall of 85.3%, an F1 score of 87.1%, and an AUC of 0.927, significantly surpassing the other models. Furthermore, the confusion matrix results indicated that the Gradient Boosting Trees model had the highest true positive and true negative values, and the lowest false positive and false negative values, further validating its superior classification performance. In summary, the Gradient Boosting Trees model demonstrated higher accuracy and stability in predicting profit in credit card underwriting, providing a robust basis for financial institutions to select appropriate machine learning models for credit risk management.
Simulation of Medium Truck Frame Based on ANSYS
Authors: Xu Chang
Published: November 2024

The frame is the important part of the car, as the understructure of assemble. the important assembly and structure on the car are based on the frame, and fixed to corresponding position, such as, engine, transmission, steering system and cab and so on. Force situation of the frame is very complex, it supports various load from road and loading, a large proportion of vehicle performance lie on structure performance of the frame. Therefore, the frame must have adequate intensity assure its fatigue life, and adequate rigidity assure its requirement of assemble and use. The requirements of modern automobile development are not limited to traditional mechanical analysis methods. This paper takes the frame of a medium truck as the research object using the finite element analysis software ANSYS to carry on the static mechanics. In this paper, the three-dimensional model is made by SolidWorks as the carrier according to the parameters of a selected frame, and leading-in the ANSYS to carry on finite element analysis.
A Review of the Basic Principles and Methods of Signal Sampling Technology
Authors: Li Jiafeng
Published: November 2024

In modern life, communication is an essential human activity. In the process of communication, various information spreads around the world in the form of signals. In order to optimize the communication, the reasonable processing of the signal becomes an important research problem. Signal processing is an important step during signal processing. It is one of two processes that convert an analog signal into a digital equivalent signal. It can be considered that signal sampling transforms the time axis of the signal into a set of discrete time moments, that is, the process of converting a signal in a continuous time domain to a discrete time domain through a series of methods. It is used to convert continuous time signals into digital signals for relevant processing and storage of digital signals in subsequent operations. This paper will summarize the basic principles and methods of signal sampling technology, introduce the sampling theorem, sampling frequency, sampling depth, sampling method and sampling error, and finally discuss the future development of signal adoption technology.
Flight Trajectory Prediction Based on LSTM
Authors: Yang Songang
Published: November 2024

Track prediction is a key technology to avoid potential navigation dangers and provide reliable scheduling. Due to the insufficient processing ability of traditional neural networks for long sequence data such as track data, the prediction error of aircraft trajectories is relatively large. In this paper, the Long Short-Term Memory network (LSTM) is used for 4D track prediction, and the excessive dependence between adjacent data is reduced through the sliding window method. The ADS-B track data is standardized, outliers are processed using the 3σ Principle, and the smoothness of the time series is ensured through cubic spline interpolation. Four-dimensional track prediction and two-dimensional prediction of each feature of Height, Speed, Speed, Longitude, and Latitude are carried out for the standard data. Performance is judged by Root Mean Squared Error (RMSE) and the average prediction error of each feature. Through comparison, the track prediction effect of the LSTM neural network is better than the existing BP neural network prediction method.
Research on Deep Bomb Delivery Strategy Based on Monte Carlo Simulation and Adaptive Optimization Algorithm
Authors: Huang Lingkai
Published: November 2024

Aiming at the problem of insufficient precision of deep bomb delivery in traditional anti-submarine warfare, this paper proposes a novel algorithm combining Monte Carlo simulation and adaptive optimization [1]. The algorithm optimises the deep bomb delivery strategy by defining the probability distribution of the submarine position. Specifically, Monte Carlo simulation is used to generate samples of possible submarine positions, analyse the effect of the submarine's three-dimensional positional error underwater on the probability of hitting a single depth charge, and explore the role of the dual-fuse detonation mechanism [2]. On this basis, the submarine's orientation error in 3D space is further considered, and an optimisation model is used to determine the optimal fixed-depth fuse detonation depth to maximise the hit probability of a single deep bomb [3]. In addition, this paper extends to the case of multiple depth charges, and optimises the overall hit probability by designing the array of charges and plane spacing to ensure that at least one depth charge can hit the submarine [4]. The experimental results show that the algorithm significantly improves the hit probability of the deep bomb, effectively reduces the impact of positioning error on the combat effect and demonstrates its potential application in practical anti-submarine warfare.
Research on the Strain Prediction Method of High-Temperature Pressure Vessel Based on Finite Element and Deep Learning
Authors: Li Wenjie , Tang Yufeng , Zhang Siwei , Cao Rui
Published: November 2024

The stress and strain of metals under high-temperature operation have significant implications for the optimal design and safety assessment of high-temperature pressure vessels. However, it is challenging to efficiently evaluate the stress and strain in critical parts of high-temperature pressure vessels. To address these issues, a method combining deep learning and finite element analysis is proposed to predict the total strain of high-temperature pressure vessels. Firstly, finite element simulations are conducted under multiple working conditions and sizes to provide data support for deep learning prediction. Secondly, the WOA algorithm is used to optimize the number of hidden layer neurons and learning rate for LSTM, and the optimized hyperparameters are then assigned to the LSTM network to construct a prediction model that matches the data features more effectively.  Finally, the data obtained from the finite element simulations are fed into the prediction model, and the results show that the prediction accuracy reaches 98.6%, demonstrating good predictive performance. This achievement can provide efficient data support for the optimal design and safety assessment of high-temperature pressure vessels.
Fuel Tank Position Localization Based on Machine Vision
Authors: Song Changjiang
Published: November 2024

Refueling robots, as an important part of intelligent service systems, greatly enhance the safety and efficiency of the refueling process. This study focuses on the machine vision module in refueling robots, specifically exploring the application of high-resolution cameras and LiDAR in data acquisition. We used Convolutional Neural Networks (CNNs) such as ResNet and MobileNet for feature extraction, which ensured high-precision recognition and classification in a variety of environments. Meanwhile, the target detection module uses YOLOv4 and MobileNet3 with fast and accurate target localization capabilities to effectively identify and calibrate the location of fueling ports. In addition, we introduced Extended Kalman Filter (EKF) and Bayesian Filter algorithms for data fusion and state estimation, which improves the robustness and reliability of the system. By combining these advanced vision techniques and algorithms, the refueling robot realizes efficient and accurate automatic refueling operation. This research provides theoretical and technical support for the further development of intelligent refueling robots so that they can still operate stably in complex environments.
Application of Generative Artificial Intelligence Tool in Tourism in China
Authors: Su Hongxia , Liu Huifen , Sun Shan , Xu Mian
Published: November 2024

With the rapid progress of artificial intelligence and natural language processing technology, large-scale language models such as ChatGPT are increasingly widely used in the tourism industry, profoundly changing the traditional mode of tourism services. This paper discusses the application of Generative AI tools in tourism and its challenges and risks from both the supply side and the demand side. The research points out that travel agencies are faced with the loss of tourists, technical threshold and cost pressure, and tourists also have certain risks when using Generative AI tools for travel planning and decision-making. In order to cope with these challenges and risks, this paper puts forward corresponding countermeasures and suggestions. Travel agencies should get committed to improving information quality, strengthening technical updates and ensuring information security. At the same time, tourists should also be vigilant when using Generative AI tools and plan their travel itinerary properly. These strategies help travel agencies and tourists better adapt to the changes brought by new technologies and promote the sustainable development of the tourism industry.
Research on Intervention Strategies for Cognitive Dysfunction in the Elderly from the Perspective of Social Support Theory
Authors: Liu Liying
Published: November 2024

Based on the perspective of social support theory, this paper studies the influence of the social support system on cognitive dysfunction in the elderly, including the impact on the mental health of the elderly, ways to improve the quality of life of elderly patients with cognitive dysfunction, the promoting role in the integration and participation of the elderly in society, the importance of improving the social support system in the intervention and the management of cognitive dysfunction in the elderly. In addition, this paper also proposes the social intervention strategies for cognitive dysfunction in the elderly and evaluates the effect of social support intervention on cognitive dysfunction in the elderly.
A Brief Discussion on the Application of Financial Software in Higher Education Institutions
Authors: Ge Yan
Published: November 2024

With the arrival of a new management era and the digital age in higher education, the survival environment, operation, and management models of universities have undergone significant changes. Traditional financial software no longer meets the management needs of modern institutions. By selecting appropriate financial software, universities can accelerate the integration of internal information and the utilization of resources. Among these, cost control is a key financial aspect that universities are currently most concerned about. As the scale of operations expands and the total funding increases, the volume of reimbursement transactions has seen exponential growth. The diversification of financing methods has broadened the scope of economic activities in higher education, directly impacting the financial departments by expanding the scope and content of financial work and increasing the daily accounting tasks. Consequently, the workload has significantly increased. The complexity of financial work in universities has risen, leading to prominent issues such as low business approval efficiency, long wait times for employees, and high pressure on financial audits. The development of financial software has also driven an increasing demand for information technology in financial departments. The traditional reimbursement methods can no longer adapt to the current development status and management needs of universities, making the informatization of financial management an inevitable trend.
Impacting Factors of Default Risk of Personal Housing Loans in China: Based on MCLP Model
Authors: Zhao Li , He Guangrui
Published: November 2024

A large-scale default on personal housing loans will have a significant negative impact on the stability of the financial system and the smooth operation of the macro-economy. After the pandemic, preventing personal housing loan risks has become particularly important. Based on personal housing loans from commercial banks in China, a personal housing loan default risk model was constructed using the MCLP model, and the prediction results of the MCLP model were compared with those of the traditional logistic model to identify indicators that may affect default risk of personal housing loans. It was found that the MCLP had higher accuracy than the traditional logistic model. Empirical findings indicated that the education level, employment status, monthly household income, and census register of housing loan borrowers were primary factors influencing customer defaults.
A Study on the Placement Evaluation and Marketing Strategy of Shared Power Banks in Singapore
Authors: Wu Yanxi
Published: November 2024

The sharing economy, marked by collaborative consumption, has seen considerable growth globally. While prevalent in China, its popularity lags in other nations. This paper focuses on power bank sharing services in Singapore, a country embracing innovative sharing solutions. With rising mobile device usage, power bank sharing addresses the need for convenient, on-the-go charging. This paper employs a SWOT analysis, and evaluates a specific power bank sharing company in Singapore. Strengths lie in the app's convenience and growing electronic device reliance, while weaknesses encompass privacy and safety concerns. Opportunities arise from the city-state's tech-savvy and Chinese-dominated population and compact urban landscape, which makes them easily accept this new service. However, threats include regulatory uncertainties and single profit mode do need to be considered. In conclusion, Singapore's demographic and sharing-friendly environment positions power bank sharing as a potent manifestation of the sharing economy's innovation, catering to contemporary demands for accessible and sustainable energy solutions.
A Study on the Pricing of Convertible Bonds in the Chinese Market Based on the LSMC Model
Authors: Qiu Jiajie , Tao Xiangxin , Ji Yanting
Published: November 2024

Convertible bonds, which possess both stock and option characteristics, currently lack a sufficiently effective pricing method for the complex and specific clauses found in Chinese convertible bonds. This study employs structured model pricing and numerical experiment methods for the pricing of Chinese convertible bonds. The structured model selected is the Black-Scholes model, while the numerical experiment methods include the binomial tree pricing model and the Least Squares Monte Carlo (LSMC) model. A proposal is made to introduce an implied volatility model in the LSMC model pricing method, incorporating the Heston model to consider the impact of the implied volatility of the underlying stock in the real market, and further adjusting the LSMC model by estimating the volatility of the underlying stock using the implied volatility model. Empirical results indicate that numerical methods have higher pricing accuracy than structured models, with the LSMC model demonstrating the highest accuracy. It is also found that there is a certain premium phenomenon in the Chinese market for convertible bonds. Furthermore, the accuracy of the model improves after the volatility adjustment, indicating that implied volatility has explanatory power for the specific clauses contained in convertible bonds, and this influence is reflected in pricing.
Non-IFRS Applications: Financial Reporting Accuracy and Transparency challenges
Authors: Guo Ziang
Published: November 2024

In a globalized economy, many companies are increasingly adopting non-IFRS to enhance their financial disclosure and provide shareholders with a clearer view of business performance. The phenomenon has sparked a deep debate in academic circles about transparency and accuracy in financial reporting. In this way, this paper can further explore the application of non-IFRS in accounting records and its impact on the precision and clarity of financial disclosure. Through cross-industry empirical case studies and a careful review of the existing literature, we explore the motivations for adopting such unconventional accounting parameters, and identify potential comparative difficulties and normalization differences that may lead to loss of equivalence. The findings reveal that while non-IFRS can contribute to enhancing information content and enhancing insights into corporate management effectiveness, they can also mislead investors. In view of this, our research advocates promoting the harmonization of non-IFRS to enhance the quality of accounting reporting, and calls on regulators to strengthen the policy framework to further safeguard the interests of multiple stakeholders, including investors.
Research on the Economic Effect Model of Automobile Exhibition Based on Analytic Hierarchy Process
Authors: Guo Chao , Shi Yingqi , Jia Yunhui
Published: November 2024

With the continuous advancement of global economic integration, automobile exhibitions play an increasingly important role in promoting the integration of the automobile industry and regional economic growth due to their strong industrial driving effect. However, in the actual operation process, how to accurately quantify the specific impact of exhibition activities on local economy has become an urgent problem to be solved. Analytic Hierarchy Process (AHP) is a multi criteria decision-making method that combines qualitative and quantitative analysis. It can help decision-makers effectively handle multiple interrelated factors in complex decision-making environments. This article constructs a model framework for evaluating the economic effects of automobile exhibitions based on the Analytic Hierarchy Process, aiming to objectively and comprehensively reflect the economic benefits brought by exhibition activities. By applying the model to relevant data in Beijing from 2013 to 2022, the research results show that the model can not only accurately quantify the specific contribution of automobile exhibitions to the economy of Beijing, but also has more accurate and explanatory power compared to traditional evaluation methods. It can not only help government departments formulate exhibition related policies more scientifically, but also provide more targeted development strategy guidance for enterprises.
Study on the New Path of Chinese Commercial Banks' Globalization Development
Authors: Guo Xingwen
Published: November 2024

The globalization process of Chinese commercial banks stands at a significant historical juncture. With the increasing integration of global financial markets, China's economic power is progressively infiltrating the international arena. As vital agents of economic development, commercial banks must adapt to this trend and accelerate their internationalization efforts. However, amid the wave of globalization, Chinese commercial banks face unprecedented challenges and opportunities. On one hand, the intensifying competition in global markets and the growing complexity and uncertainty of the international financial system necessitate higher-level strategic planning. On the other hand, the rapid advancement of technology and the rise of the digital economy offer new avenues for development. Identifying an appropriate strategic position globally and achieving sustainable business growth has become a pressing issue for Chinese commercial banks. This study focuses on exploring how Chinese commercial banks can navigate the globalization process through innovative strategies, regional differentiation approaches, and multinational collaboration to find new paths that adapt to the global market, thereby securing a competitive edge in the international arena.
Intersecting Dynamics: Migration, State Control and Urban Expansion in Shenzhen’s Urban Villages
Authors: Wang Qingzheng
Published: November 2024

This essay explores the dynamic interplay between migration, state control, and urban expansion in Shenzhen's urban villages. With Shenzhen's designation as a special economic zone in 1978, the city experienced unprecedented economic and demographic growth, primarily driven by rural-to-urban migration and facilitated by the government's reform policies. This influx has led to the proliferation of urban villages, which are informal housing areas that have developed due to rapid urbanization and the state's uneven regulatory oversight. These urban villages have become focal points of social and economic activity, housing diverse populations including migrant workers and local entrepreneurs. The essay argues that migration and state control are crucial in shaping the urban landscape of Shenzhen, influencing the development and characteristics of urban villages. Through a detailed examination of these areas, the essay highlights the complexities of urban expansion in the context of China's broader socio-economic transformations.
Fundamental Causes and Recommendations for the Insufficient Effectiveness of China's 'Hierarchical Medical System' Policy Implementation
Authors: Yin Zihan
Published: November 2024

This paper analyzes sections of China's official government documents regarding the "hierarchical medical system" policy and compares the implementation of China's policy with the hierarchical medical policies of the United Kingdom's National Health Service (NHS). Using the detailed "strengthening the foundation" section in the policy documents as a starting point, the study examines why the issue of "overcrowded major hospitals and underutilized primary healthcare institutions" remains unresolved despite the implementation of the hierarchical medical system policy. One fundamental reason identified is the low competency level of primary care physicians. To address the issue of underqualified primary care physicians, this paper centers on promoting the standardization of primary healthcare and proposes two policy-level recommendations. First, establish a nationwide, objective, and quantitative evaluation standard for the accreditation of primary care physicians, along with a corresponding training system, to standardize the basic diagnostic capabilities of primary healthcare personnel. Second, leverage the medical consortium system to expand career prospects and enhance the professional attractiveness of primary care physicians.
“I Heard a Fly Buzz -- When I Died”: From Being-towards-Death to Existentialism
Authors: Song Jintao , Song Guofang
Published: November 2024

Emily Dickinson’s “I Heard a Fly Buzz -- When I Died” is one of the more renowned poems within her oeuvre that addresses the theme of death. Meanwhile, Heidegger’s concept of “being- towards-death” in Being and Time stands as a central pillar of his philosophy of death, offering a unique perspective on mortality. This paper aims to explore Dickinson’s poetry through the lens of Heidegger’s philosophy of death. Initially, it briefly outlines Heidegger’s views on death, distinguishing them from universal notions of mortality; subsequently, as the core content of this article, it specifically analyzes the construction of “being-towards-death” in “I Heard a Fly Buzz - When I Died” through the application of Heidegger’s philosophical insights.
An Innovative Thinking on the Effect Evaluation and System Improvement of Senile Monitoring
Authors: A Runa
Published: November 2024

China is preparing for its rapidly aging population and implementing an effective system of elder guardianship. Due to policies such as the one child policy and longer life expectancies, in combination with improved economic conditions, this demographic shift has put great pressures on social, legal and healthcare systems. In this paper, the authors investigate the development of elder guardianship in China, its present struggles as well as possible policy pathways.The current study aims to evaluate the efficacy of elder guardianship in China using an extensive literature review and incorporating theoretical discussions into legal analyses. Through comparisons with international guardianship models, foreign best guardianship practices to learn from the Chinese situation to find out. We reviewed case studies of efforts to reform elder care, both in community-based and governmental health strategies.The results presented in this article reinforce that although the Civil Code of PRC (2021) may be a significant step forward towards a more legal frameworking concerning elder guardianship, there are still challenges to be faced relating to the variety in law enforcement, oversight, and public awareness. Moreover, the transition to nephology nuclear living has also exacerbated the guardianship accommodate system. In addition to this, a key aspect relates to the reform required in pension and social security policies for the elderly population.The paper concludes that the guardianship system in China may improve by combining a family model with a public one, developing community-based elder care, and utilizing technology for monitoring. Suggestions also focus on strengthening legal frameworks, enhancing guardian oversight and encouraging elder care service innovation to better the quality of lives of those under guardianship.The authors of the study conclude that China's progress in elder guardianship has been commendable but there is still a long way to go, especially as far as legal issues are concerned and socio-administrative care services. Future studies in China need to explore more culturally distinctive and multifaceted modes of guardianship that are better fitted for the country's burgeoning older population.
Analysis of the Politicization of Media Coverage of the MeToo Movement in China and its Impact on Public Opinion
Authors: Li Leyi
Published: November 2024

In recent years, the Metoo movement has aroused widespread social concern, it has transcended being just a social movement and has integrated into a broader political and social context.  The study endeavors to investigate how the MeToo movement, originally a social movement focused on sexual harassment and sexual assault, has evolved into a phenomenon with a pronounced politicization tendency. To gain a deeper understanding of the politicization of the MeToo movement and its impact, by analyzing the media coverage of the MeToo movement in China, this study aims to reveal the key drivers of politicization of the movement and explore the impact of this politicization for the movement itself and society.
On International Law Protection of Child Sexual Assault
Authors: Wu Haonan , Wang Jun
Published: November 2024

The spate of child sexual abuse has raised awareness of the need and urgency to protect children from sexual abuse. In international law, sexuality is increasingly linked to human rights and is increasingly recognized as a fundamental human right, and the Convention on the Rights of the Child highlights the perspective of sexual human rights. We have ratified the Convention on the Rights of the Child and the Optional Protocol to the Convention on the Rights of the Child on the sale of children, child prostitution and child pornography. But let's face it, there are still many children in the world who are being sexually abused. To this end, we should sum up our experience, improve relevant laws in light of national conditions, and build a comprehensive and multi-level system for the protection of children's sexual rights, so as to provide a safe and harmless environment for children's growth.
Surface Chemistry-Enhanced Wearable Biosensors: A Novel Approach for Non-Invasive Continuous Health Monitoring
Authors: Chen Zhuo
Published: November 2024

With the rise of health concerns in recent years, wearable biosensors have gained widespread attention as an important technology for health monitoring. It can monitor human physiological indicators such as blood glucose and lactate. This type of monitoring does not require complex operations or frequent sampling and is non-invasive and capable of real-time monitoring. Chemically modified electrochemical biosensors have further improved the sensitivity and selectivity of monitoring and have the potential for a wider range of applications. In this paper, we will explore the application of surface chemically enhanced wearable sensors for non-invasive health monitoring and their future directions.
Research on the Application of AI Technologies in Computer Network Data Analysis
Authors: Ho Tsz Lok
Published: November 2024

In recent years, with the development of the Internet of Things and smart devices, the Future Internet project has driven innovation in network architecture by combining different models and resources. To manage complexity, creating abstract models has become a critical step in the field of computer networks. This study explores the application of AI techniques in network data analysis, demonstrating the possibilities of AI for real-time monitoring, anomaly detection, and the future development of AI. Despite the promising applications of AI technology, challenges such as privacy protection and dealing with cyber threats still need to be overcome. Future research should develop safer and more flexible AI algorithms to adapt to complex network environments.
Research on High-precision Algorithm for Flight Attitude Evaluation of Quadrotor Aircraft
Authors: Zhou Ruizhi
Published: November 2024

With the rapid development of UAV technology, quadrotor aircraft has shown wide application potential in many fields. In this paper, a high-precision algorithm based on multi-sensor data fusion and optimized extended Kalman filter (EKF) technology is designed and implemented for the flight attitude evaluation of quadrotor aircraft. By fusing the data of IMU (Inertial Measurement Unit), GPS (Global Positioning System) and magnetometer, the algorithm can effectively resist noise interference and reduce sensor errors, and realize real-time and high-precision estimation of aircraft attitude angle and position. The experimental results show that the algorithm performs well in a variety of flight trajectories, which is basically consistent with the real trajectory, especially in complex movements such as hovering and diving, and can still maintain high accuracy and robustness. Compared with the commonly used Mahony and Madgwick algorithms, the algorithm proposed in this study has obvious advantages in attitude estimation error fluctuation range, error stability and error average. This not only improves the maneuverability and safety of the aircraft, but also provides strong support for the autonomous flight and precise control of the UAV. This study provides an important reference for the field of flight attitude evaluation of quadrotor aircraft.
How Is AI Enhancing Investment Behavior in Today's Financial Markets
Authors: Yao Mengxiao
Published: November 2024

The present investigation delves intricately into AI's pivotal function in shaping contemporary financial market investment dynamics. Amidst surging data volumes and computational leaps, AI has emerged as a cornerstone in finance, particularly in enhancing investment efficacy, risk assessment, and tailored services. By scrutinizing AI's present adoption across domains like data analysis, algorithmic trading, risk mitigation, and advisory services through concrete case studies, we illustrate their tangible impact. Our study subsequently unfolds how AI bolsters investment activities by expediting decision-making, refining strategic investments, reinforcing risk controls, and enriching user experiences. Furthermore, we delve into the technological hurdles, ethical dilemmas, and regulatory challenges encountered in AI's financial sector integration. Lastly, we propose recommendations for financial institutions and regulators to foster AI's sustainable growth within the market. This research not only contributes to a profound comprehension of AI's role in financial applications but also furnishes valuable insights and future research directions.
Engineering Application of New Environmental Treatment Materials in Water Pollution Control
Authors: Li Junze
Published: November 2024

With the increasingly serious problem of water pollution, the application of new environmental governance materials in water pollution control has become a research hotspot. This paper systematically discusses the engineering applications of a variety of novel environmental governance materials in water pollution control, including nanomaterials, biomaterials and composites, and analyzes in detail the mechanisms of physical adsorption, chemical degradation, biodegradation and photocatalysis of these materials in practical applications. In addition, the practical effects of novel materials in water pollution control are demonstrated through cases of river training, industrial wastewater treatment and drinking water purification. Although these materials show remarkable pollutant removal ability, they still face challenges in practical applications such as material stability, economic cost and environmental safety. The paper concludes with an outlook on the future development direction of new environmental control materials and the need for further research, with a view to providing more effective solutions for water pollution control.
Tansen, the Court Singer: A Political Perspective (রাজদরবারের সভাগায়ক তানসেন: একটি রাজনৈতিক বীক্ষণ)
Authors: Kuheli Dr. Aklima Islam
Published: November 2024

হিন্দুস্তানি সংগীতের শ্রেষ্ঠ গুণী সংগীতজ্ঞ মিয়া তানসেনের নাম ভারতবর্ষ তথা বঙ্গদেশের সংগীতজ্ঞদের কাছে প্রবাদবাক্যের মত প্রচলিত। যদিও তাঁর সুদীর্ঘ সংগীত জীবনের ইতিবৃত্ত ‘আইনি আকবরী’ অথবা ‘পাদশানামা’ প্রভৃতি বিখ্যাত গ্রন্থ দুর্গের অভ্যন্তরে পাওয়া যায় তবে তা সাধারণ সংগীত বোদ্ধার কাছে দুর্ভেদ্য। আলোচ্য প্রবন্ধে মুঘল সম্রাট আকবরের রাজত্বকালে, তাঁর দরবারে তানসেনের অবস্থান ও তাঁর বর্ণাঢ্য সংগীত জীবন সম্বন্ধে আলোকপাত করার প্রয়াস থাকবে।
Kauṭilya’s Arthaśāstra in the Light of Civil Engineering and Architecture
Authors: Chowdhury Dr. Biva Sania
Published: November 2024

In this article entitled ‘Kautịlya’s Arthaśāstra in the light of Engineering and Architecture’ we have tried to forecast on Kautịlya’s thinking in the light of Engineering and Architecture of modern science. The Kautịlya’s Arthaśāstra as the name indicates is a treatise on Arthaśāstra. A definition of this śāstra is founding the concluding section of the work. There are many indications in the text that it has in view a comparatively small sized state. Similarly the book refers to ‘Janapada’s Or ‘vāstuka’. From these references vāstuvidyā or Engineering science has been choosen as topic of discussion. Janapada the territory with people settled on it, durga the fortified capital etc. play an important part in the administrative system.Arthaśāstra considered as a manual of statecraft and administration contains within it a wide spectrum of technological details by way of infrastructural adjunct to the various spheres of administration. The author injecting contentment and sense of security in the overall social fabric, would conceive that a strong superstructure can be built only on strong infrastructure. Various branches of Civil Engineering, as we understand today that technology, like town and country planning lay out plans for buildings architecture, design, construction materials, sanitation, irrigation etc. are to be found occupying appropriate place in the Arthaśāstra. In Arthaśāstra the sūtras, which are related to vāstuvidyā that is to the more comprehensive technology of Civil Engineering of today have been discussed in this article. Town planning architecture and civil Engineering, soil Mechanic
BANALATA SEN: THE FOUNDATION OF JIBANANANDA DASH’S LITERARY VISION (‘বনলতা সেন’ জীবনানন্দের কাব্যচিন্তার কোরক)
Authors: Nessa Dr. Nurunnaher Fayzer 
Published: November 2024

সকল শ্রেষ্ঠ ও মহৎ সৃষ্টিই যুগে যুগে পঠিত হয়, চর্চিত হয়, পাঠককে ভাবায়, আনন্দ দান করে। জীবনানন্দের ‘বনলতা সেন’ তেমনই একটি সৃষ্টি, যা বহুকাল ধরে পাঠক-সমালোচককে বর্ণনাতীত আনন্দ দান করে চলছে, তাদের কল্পনা ও সৌন্দর্যবোধকে তৃপ্ত করছে এবং নিশ্চিতভাবেই বলা যায় তা আরও বহুকাল অব্যাহত থাকবে। বনলতা সেন কাব্যগ্রন্থটি প্রকাশিত হয় ১৯৪২ সনে। ১৩৪৫ বঙ্গাব্দ থেকে ১৩৬০ বঙ্গাব্দ পর্যন্ত প্রকাশিত কবিতা – বিষয়ক পনেরোটি প্রবন্ধ নিয়ে ১৩৬২ সনে প্রকাশিত হয় কবিতার কথা শীর্ষক জীবনানন্দের মহামূল্যবান গ্রন্থটি। কবির অন্যান্য অনেক কবিতার মতোই বনলতা সেন গ্রন্থের প্রথম কবিতা ‘বনলতা সেন’ গভীর বিশ্লেষণে জীবনানন্দের কাব্যচিন্তার স্ফটিকস্বরূপ বলা যায়। বিশেষ করে ‘কবিতার কথা’, ‘কবিতা প্রসঙ্গে’, ‘কবিতার আত্মা ও শরীর’ প্রভৃতি প্রবন্ধে প্রকাশিত তাঁর কবিতা-বিষয়ক চিন্তাগুলো অপূর্ব দীপ্তি ছড়িয়ে আছে এই কবিতায়। বর্তমান আলোচনায় ‘বনলতা সেন’ কবিতাটিকে এই সিদ্ধান্তের আলোকেই আস্বাদনের চেষ্টা করা হবে।
Rendimiento de la cartera como componente satisfactor de la improductividad: evidencia estadística en Mutualistas
Authors: López-Núñez Henry Robert , Escobar-Ribadeneira Hugo Mateo , Ramírez-Albán Sammie Gabriela , Mejía-Cevallos Alvaro Javier
Published: November 2024

This study examines portfolio performance management as a strategy to mitigate unproductivity in mutual institutions. Using Spearman correlation models and decision trees, significant relationships between different types of loans and their impact on non-performing assets are identified. Findings reveal a strong correlation between refinanced and restructured loans, indicating their joint use in risk management. Additionally, microcredit and real estate loan portfolios emerge as key determinants of institutional financial health. Simplified decision tree models, while sacrificing some precision, aid in identifying critical factors. These results highlight the importance of integrated strategies and diversification in portfolio management to enhance financial stability and reduce risks.
Employing Convolutional Neural Network Model in Predicting Heart Diseases
Authors:   Biomeical Engineering Departmnet, Faculty of Engineering, Wadi Al-shati University, Alshreif Ahmed , Fadil Sana ,   Biomeical Engineering Departmnet, Faculty of Engineering, Wadi Al-shati University, Miskeen Guzlan ,   Biomeical Engineering Departmnet, Faculty of Engineering, Wadi Al-shati University
Published: November 2024

Heart disease is a global health challenge and one of the leading causes of death worldwide. Early diagnosis of heart disease allows for appropriate therapeutic intervention and necessary measures to prevent disease progression and prevent serious complications. The significance of ECG lies in its ability to detect heart disease and accurately diagnose various conditions. Many research studies have been conducted in the field of artificial intelligence techniques to analyze cardiac signals. This study aims to create a one-dimensional convolutional neural network (CNN) to process these ECG signals utilizing MIT-BHI database that contains 87554 samples of ECG signals was used. The database contains different cardiac signal classes, including normal signals, regular atrial contraction, premature ventricular contraction, combined beat, which results from the superposition of several waves in the presence of a cardiac pacemaker, and a class labeled as "unknown signals". Data were divided after processing into 80% training data, 15% test data, and 5% validation data. We processed the data and trained the CNN neural network model accordingly, and the results showed that the diagnostic accuracy reached 99.52% for training and 99.45% for testing. Keywords: Deep Learning, Covolutional Neural Network, Heart Disease Prediction, Healthcare.
Media Ajar Berbasis Digital dalam Pembelajaran IPS di SD/MI
Authors: Maharani Nurul Ain  , Asyifatun Muqaromah
Published: November 2024

The importance of utilizing digital learning resources for Social Studies (IPS) learning at Elementary School (SD) and Madrasah Ibtidaiyah (MI) levels is discussed in this article. The utilization of digital teaching materials is expected to improve IPS learning in a more interesting, dynamic, and efficient way along with technological advances. This study identifies various digital learning media, including web-based learning platforms, educational software, and instructional videos, that can be used in the context of IPS learning. The advantages and difficulties faced by teachers and students when incorporating digital media into the classroom are also discussed in this article. It is hoped that by using a digital approach, students will be able to better understand IPS content and develop 21st-century skills needed for everyday life. In addition, this article offers suggestions for the efficient use of digital learning resources that are appropriate to the needs of MI and elementary school students.