bluuebunny/crossref_metadata_2025 huggingface dataset:
Gaya Komunikasi NonVerbal Gibran Rakabuming Raka pada Debat Cawapres 2024
Authors: Wijanarko Koko , Mashur Mohammad Said
Published: November 2024

Debat politik merupakan arena penting bagi para kandidat untuk menyampaikan ideologi, kebijakan, dan kualitas kepemimpinan mereka kepada para pemilih. Penelitian ini menganalisis penggunaan gestur yang dilakukan salah satu kandidat calon wakil presiden (cawapres) Gibran Rakabuming Raka pada debat cawapres keempat di Pilpres 2024. Analisis ini bertujuan untuk menjelaskan secara akademik bagaiamana Gibran Rakabuming mempengaruhi opini publik dan mendapatkan dukungan pemilih melalui gestur. Dengan menggunakan analisis konten rekaman video dari kanal YouTube Komisi Pemilihan Umum (KPU), penelitian ini mengkaji gestur spesifik yang dilakukan Gibran Rakabuming Raka saat berdebat. Hasil penelitian menunjukkan bahwa gestur-gestur tersebut berperan penting dalam memperkuat pesan verbal dan membentuk persepsi di kalangan pemirsa. Temuan ini berkontribusi memberikan pemahaman komunikasi nonverbal dalam debat politik, yang dapat membantu kandidat memaksimalkan strategi komunikasi mereka dalam kampanye. Studi ini menggarisbawahi pentingnya analisis isyarat dalam penelitian komunikasi politik, memberikan wawasan tentang bagaimana para kandidat secara strategis memanfaatkan isyarat nonverbal untuk meningkatkan kemampuan persuasif mereka dan mempengaruhi opini publik dalam lingkungan pemilu yang kompetitif.
Pengaruh Penambahan Abu Batubara Pltu Pulang Pisau terhadap Kuat Tekan Batako
Authors: Ganang Nuansa Mare Apui , Hutajulu Yossa Yonathan , Iashania Yunida , Betrio L Prayoga
Published: November 2024

Abu batubara hasil pembakaran pembangkit listrik tenaga uap terdiri atas fly ash dan bottom ash, keduanya merupakan limbah. Penyimpanan limbah memerlukan tempat khusus, tempat penyimpanan akan penuh apabila tidak dilakukan tindakan pengurangan jumlah limbah yang disimpan. Salah satu cara memanfaatkan limbah ini adalah dengan menambahankan limbah pada produk batako. Penelitian ini dilakukan untuk mengetahui pengaruh abu batubara terhadap kuat tekan batako. Metode yang digunakan dalam penelitian ini adalah metode kuantitatif, Batako diuji menggunakan alat kuat tekan digital. Hasil pengujian kuat tekan batako digunakan untuk melihat seberapa besar pengaruh penambahan abu batubara dengan komposisi tertentu. Berdasarkan hasil penelitian, didapatkan bahwa untuk komposisi awal semen 500 ml didapatkan penambahan kekuatan batako sebesar 55,96% saat diberikan penambahan fly ash 400 ml. Pada pencampuran bottom ash didapatkan bahwa terjadi penurunan kekuatan batako hingga 42,38% dengan perbandingan pasir dan bottom ash 1:1. Penambahan fly ash dapat meningkatkan nilai kuat tekan maksimal batako sehingga limbah dapat dimanfaatkan dan akan mengurangi keperluan untuk penyimpanan limbah hasil pembakaran.
Analisis Loyalitas Pasien dan Kepuasan Pasien: Pendekatan Kajian Literatur dengan Kualitas Pelayanan Rumah Sakit sebagai Variabel Intervening
Authors: Sitepu Michi , Kosasih Kosasih
Published: November 2024

Loyalitas dan kepuasan pasien merupakan indikator utama sebagai salah satu tolak ukur suatu keberhasilan dalam sistem perawatan dan pelayanan rumah sakit. Pasien yang loyal adalah pasien yang konsisten memilih dan menggunakan layanan kesehatan dari penyedia layanan kesehatan tertentu. Kepuasan pasien menggambarkan kualitas pelayanan kesehatan dalam memenuhi kebutuhan dari kepuasan pasien. Perkembangan moderenisasi meningkatkan persaingan rumah sakit untuk mencapai kepuasan dan loyaloitas pasien. Hal ini dapat diioptimalisasi dengan mengatahui aspek-aspek kualitas pelayanan, sehingga rumah sakit dapat segera melakukan evaluasi dan perbaikan. Metode yang digunakan adalah literature rivew dengan mengaji berbagai sumber pustaka. Kajian literatur ini bertujuan untuk menganalisis pengaruh loyalitas pasien yang ditinjau dari kepuasan pasien dengan kualitas pelayanan sebagai variabel intervening. Hasil penelitian menunjukkan penerapan kualitas pelayanan yang baik dan efektif akan berkontribusi terhadap kepuasan dan loyalitas pasien terhadap rumah sakit. Alih-alih hanya mengatakan bahwa pelayanan rumah sakit yang berkualitas mencakup aspek teknis medis, tetapi juga kenyamanan, perhatian, dan interaksi antara tenaga medis dengan pasien. Dengan demikian, rumah sakit harus memberikan kualitas pelayanan terbaik terhadap pasien, sehingga rumah sakit dapat meningkatkan inovasi layanan secara berkelanjutan. Kajian ini menyimpulkan bahwa loyalitas dan kepuasan pasien berperan penting sebagai indikator utama yang dapat memberikan masukan untuk memperbaiki kualitas pelayanan rumah sakit. Rekomendasi yang dihasilkan dari kajian ini mencakup pentingnya loyalitas pasien terhadap kepuasan pasien untuk mencapai kualitas layanan rumah sakit yang lebih baik.
Data Enablement: Construction of the “I-shaped” Business Pattern Supply Chain Finance Platform
Authors: Guo Hongyi , Liu Yanjun , Hu Ludong , Zhang Xuanbo
Published: November 2024

The article intends to tackle the financing issues for Small and Medium-sized Enterprises (SMEs), construct a supply chain finance platform, and implement risk control. By analyzing the current situation of SMEs and the role of supply chain finance, the platform is designed based on the “I-shaped” Empowerment Model. The platform possesses a variety of functions and advantages, including the ability to access production factors, information integration, risk management, and efficiency enhancement, and it adopts the microservice and distributed architecture. Through the “I-shaped” Empowerment Model and risk control measures, the platform effectively reduces various types of risks, provides reliable financial services for SMEs, and promotes the collaborative development of the supply chain. It will continue to be optimized and improved in the future to make greater contributions to economic development.
Research on automatic segmentation and recognition of single characters in original rubbings based on intelligent recognition of oracle bone inscriptions
Authors: Chen Guomin , Wen Guangjie
Published: November 2024

This paper proposes an effective segmentation and recognition method using YOLOv8 to solve the problem of segmentation and recognition of Oracle rubbings images. Draw sub-pixel edge contours through spot detection, corner detection, and edge detection (such as Canny and Sobel), and combine grayscale, opening operations, binarization, and Gaussian filtering to remove noise and repair contours, extract image features, and establish preprocessing Model. Use this model to preprocess the original oracle rubbing image and train it based on YOLOv8. The results show that this method can effectively segment and identify oracle bones characters.
Research on Innovative Strategies for Selling Rural Agricultural Products on the Internet
Authors: Cui Caizhou
Published: November 2024

At present, the majority of Chinese villages, especially the less developed areas of rural agricultural products to expand the market (i.e., selling, etc.) facing a series of problems, while the development of rural e-commerce has also come to some new opportunities. To this end, we need to innovate management strategies in the production, marketing and circulation of agricultural products to promote better access to markets for agricultural products. In terms of product supply, it is necessary to optimize and adjust the original breeding, planting, processing and manufacturing industries, i.e., the main industries supplying products to the network, and produce products more suitable for the needs of the masses. On the other hand, in terms of marketing, the new industry of “live streaming with goods” should have a sound supervision and constraint mechanism in product quality, live streaming technology, complaints and feedback, etc.; in terms of distribution of products for online shopping, based on the expansion of live streaming business, i.e., the massive growth of online shopping, it is necessary to accelerate the promotion of cold chain logistics for the seasonal, fresh and other essential products of the masses' life. The construction of relevant supporting facilities is needed to ensure that seasonal products are delivered with quality and freshness, and at the same time, some products can be guaranteed to be stored and transported across the seasons, so as to better satisfy the high-quality demand of the masses for online shopping of daily necessities.
Sedimentary Characteristics and Oil Control of Chang 7 Member in Zhidan Area, Ordos Basin
Authors: Ding Jingjing , Chen Shanshan
Published: November 2024

Deep-water gravity flow deposits are widely developed in the Chang 7 member of the Triassic Yanchang Formation in the Ordos Basin.Due to its complex formation mechanism and many types, it is a great challenge to predict its development scale and distribution law.Taking the Chang 7 Member in Zhidan area as an example, on the basis of fine core description, through sedimentary structure, grain size analysis and logging curve, the types and characteristics of sedimentary facies, logging facies and distribution of Chang 7 Member were studied.The results show that:(1)The Chang 7 member in Zhidan area develops delta front subfacies and semi-deep lake-deep lake subfacies, including underwater distributary channel, interdistributary bay, sliding-slump rock, sandy debris flow deposition, turbidite and semi-deep lake-deep lake mud.(2)The grain size probability accumulation curve of Chang 7 member develops one-stage, two-stage and three-stage. The one-stage mainly indicates turbidity current deposition, and the two-stage and three-stage mainly indicate underwater distributary channel deposition. (3)There are many types of sedimentary structures in the Chang 7 member. There are a large number of slump structures or heavy load molds in the sliding-slump rocks. The sandy debris flow deposits mainly develop massive bedding and mud-coated gravel structure. Turbidite common sand-mud frequent rhythmic interbedding, Bouma sequence and flame-like structure.(4)The delta front subfacies are distributed in the northeast, and the underwater distributary channel microfacies are developed. From Chang 73 to Chang 71, its distribution range gradually increases. The semi-deep lake-deep lake subfacies are distributed in the southwest, and the sandy debris flow is generally developed. From Chang 73 to Chang 71, its distribution range gradually decreases.This study can provide geological basis for the selection of sweet spot areas for shale oil exploration in the Chang 7 member of Zhidan area.
A Gas Well Production Prediction Model Based on Time-convolutional Neural Network
Authors: Zhang Long
Published: November 2024

This paper explores gas well production prediction, a crucial aspect of gas field development planning and analysis. Traditional methods like decline curve analysis and numerical simulation have limitations due to their reliance on simple mathematical models. In contrast, machine learning offers a more flexible approach. The study applies a Temporal Convolutional Network (TCN) model to predict production for two gas wells. The model's performance was evaluated using MSE, MAE, RMSE, and R², with results showing the TCN method achieving better accuracy. The TCN model presents a promising new approach for gas well production forecasting.
Emotional Resonance in Brand Innovation: An Examination of Emotion Recognition and Customized Music Services within the Shengchuan Poetry Brand Design Framework
Authors: Hu Mengwen
Published: November 2024

This research endeavors to delve into the intricate nexus of emotion recognition technologies and artistic design methodologies, examining their harmonious integration within the realm of brand design. Specifically, it investigates how these modalities can evoke multifaceted emotions, including anger, fear, excitement, and sadness, to forge profound emotional connections with consumers. By analyzing the innovative strategies employed by the hypothetical yet illustrative Shengchuan Poetry brand, particularly in its visual communication, user experience architecture, and customized music services, this study aims to elucidate the emotional underpinnings of its distinctive brand identity and the mechanisms that facilitate emotional resonance among its audience. It contributes to the scholarly discourse on brand innovation by proposing a conceptual framework that advocates for emotions as a strategic lever in designing memorable and impactful brand experiences.
Analysis of Lease Accounting Treatment Under ASC 842 and IFRS 16: A Case Study of Auto Inc. and Trans-Atlantic Inc. Contracts
Authors: Dai Yaoda , Mou Fanfan
Published: November 2024

This memorandum examines the application of ASC 842 and IFRS 16 lease accounting standards to contracts between Auto Inc. and Trans-Atlantic Inc. for the transportation of sedan and luxury cars. The analysis focuses on identifying whether these contracts contain leases by assessing the presence of identifiable assets and the right to control their use. The study concludes that the sedan car contract meets the criteria for a lease under both standards, with MV Manhattan as the identifiable asset and Auto Inc. having control over its use. Conversely, the luxury car contract does not qualify as a lease due to the absence of an identifiable asset and lack of control by Auto Inc. The memorandum also highlights key similarities and differences between ASC 842 and IFRS 16 in lease identification and classification, offering valuable insights for practitioners navigating these accounting frameworks.
The Artistic Expression and Aesthetic Value of the Artistic Conception of Tang Poetry on Landscape
Authors: Yi Ruijia
Published: November 2024

The landscape poetry of the Tang Dynasty holds a prominent place in the history of Chinese literature, especially the landscape poetry of the High Tang period, which represents the pinnacle of the development of Chinese landscape poetry. The inspiration and material for the creation of landscape poetry stem from natural landscapes. The texts of Tang Dynasty landscape poetry reflect the aesthetic consciousness of Tang poets. Through their contemplation of nature, poets discovered the inherent beauty of nature, experiencing the purification and cultivation of their souls during the aesthetic appreciation of nature, thus gaining a sense of beauty from these activities. One of the key reasons why Tang poetry became the peak of ancient Chinese poetic art is the epoch-making breakthroughs in the creation of artistic conception, particularly in landscape poetry, where the artistic conception presents new forms. This paper deeply analyzes the artistic expression and aesthetic value of the artistic conception in Tang poetry's landscape poetry, revealing its unique position in the history of Chinese literature and providing useful references for modern literary creation.
BrainSim: AI-Driven Brain MRI Simulation for Alzheimer’s Disease Diagnosis
Authors: Bao Yueyi
Published: November 2024

Alzheimer's Disease, a progressive neurodegenerative disorder with no cure, presents a formidable challenge to global healthcare. The simulation of brain states, encompassing both rejuvenation and aging, aids clinicians in understanding disease progression and early detection. Recent advances in deep adversarial neural networks, effective in generating age-varied facial images, are now applied to brain MRI simulations across different time states. However, existing methods for brain MRI synthesis predominantly focus on aging simulation, lacking rejuvenation capabilities, and relying heavily on longitudinal data. Access to rejuvenated brain scans is essential as it can help researchers track the structural changes and biomarkers in the early stage of AD, facilitating AD research and personalized treatments. Additionally, previous methods are often 2D-based, failing to capture complex 3D spatial information obtained by 3D scans. To overcome these limitations, I propose BrainSim, a novel longitudinal brain MRI synthesis framework. Specifically, BrainSim leverages a bidirectional cycle-consistent generative neural network to generate rejuvenated and aged MRI scans simultaneously using cross-sectional scans only. BrainSim incorporates a 3D conditional U-Net as its fundamental model, facilitating the direct generation of 3D MRI scans conditioned on the subject's health state and sex. BrainSim was evaluated against benchmark models using longitudinal data and a pre-trained age predictor to assess the quality of generated images. Experiments using the ADNI dataset show BrainSim's state-of-the-art performance in brain aging and rejuvenation tasks, marking significant advancements in MRI synthesis for Alzheimer's research and drug development.
Construction and Empirical Analysis of NFT Digital Art Market Value Prediction Model
Authors: Li Qizhan
Published: November 2024

The purpose of this article is to build and verify an effective market value prediction model of NFT digital art and make an empirical analysis to cope with the growing demand and uncertainty of NFT market. Through the comprehensive application of data collection, preprocessing, neural network model construction and optimization, the market value of NFT digital works of art is deeply explored in this article. In the research process, firstly, a large number of transaction data are collected from the open NFT trading platform, and strict data cleaning and feature selection are carried out; Then, a prediction model is built based on CNN (Convolutional Neural Network) model, and the model is optimized by cross-validation and parameter adjustment. The experimental results show that the model has high prediction accuracy and reliability, and can capture the key influencing factors of NFT digital art market value, such as artist reputation, scarcity of works and market demand, and point out the importance of the key influencing factors. At the same time, based on the research results, this article puts forward policy suggestions and practical enlightenment for NFT digital art market participants and regulators, with a view to promoting the healthy development of the market.
Thermodynamic and Economic Analysis of a High-efficiency System Integrating ORC Power Generation, CO2 Capture, and CO2 Storage Driven by Complementary LNG Cold Energy and Flue Gas Waste Heat.
Authors: Hu Tinglong , Li Yesai , Wang Jiajie , Fan Yi
Published: November 2024

Liquefied natural gas (LNG) is a clean primary energy source, and the large amount of cold energy stored in LNG provides an opportunity for sustainable technologies to recover and utilize this energy source. This can improve the energy efficiency of LNG regasification terminals and the economic viability of the LNG supply chain. In this paper, an efficient system integrating ORC power generation, CO2 capture, and CO2 storage driven by complementary LNG cold energy and flue gas waste heat is constructed. The exergy-efficiency of the system is 63.09%, the total round-trip efficiency η_(RTE-Overall) of the system was calculated to be 93.22% and the round-trip efficiency η_(RTE-LCES) of the LCES subsystem was 80.13%, and the total investment cost is 2.033 × 106, with a LCOS of 0.10 USD/ kW⋅h. Zero CO2 emission is realized, which contributes significantly to environmental protection.
Application of Data Science in Investment Decision and Its Influence on Market Forecast
Authors: Fu Yichen
Published: November 2024

Under the background of rapid development of data and information, financial investment decision-making is facing unprecedented challenges and opportunities. Traditional investment decision-making methods have obvious limitations in dealing with massive data and capturing market changes, while the rise of data science provides a new perspective and tool for investment decision-making. The purpose of this study is to explore the specific application of data science in investment decision-making and analyze its improvement and promotion of market forecasting ability. This article discusses the performance of data science forecasting model in market forecasting by combining theoretical analysis with empirical research. By selecting the historical data of the stock market as a sample, the data science model is applied to forecast, and the forecasting accuracy, yield and risk index are tested. The research results show that data science shows significant advantages in investment decision-making. Its powerful data processing ability and forecasting accuracy not only improve the accuracy and timeliness of market forecasting, but also provide investors with more scientific and accurate investment decision support.
Impact of the Global Financial Crisis on Emerging Markets
Authors: Chen Guanlin
Published: November 2024

This paper explores the impact of the 2007-2008 Global Financial Crisis on Brazil and India and analyzes their policy responses. Both countries used monetary policies and fiscal stimulus to mitigate the crisis, with Brazil focusing on interest rate cuts and infrastructure investment, while India emphasized social welfare and rural development. Structural reforms in both countries improved financial stability and economic diversification, contributing to their post-crisis recovery and demonstrating resilience. The paper underscores the importance of timely and targeted policy interventions for long-term stability in emerging markets.
Construction and Optimization Strategies for an Online Teaching Platform for College Students' Innovation and Entrepreneurship Education
Authors: Wu Lin , Yang Liu , Zhang Chunyan
Published: November 2024

With the advent of a new era, college student entrepreneurship education has garnered significant attention from universities and society at large. The aid of information technology brings new opportunities for the smooth execution of this work. Traditional education modes, affected by objective factors, have clear drawbacks. To enhance contemporary students' innovative abilities and core competitiveness, it is necessary to build a comprehensive online teaching platform for entrepreneurship education based on actual development conditions. This platform can leverage the advantages of the internet and information technology to accurately analyze students' learning abilities and needs, providing them with personalized educational resources. Moreover, incorporating virtual laboratories and simulated entrepreneurship into practical teaching can effectively cultivate students' problem-solving abilities, fostering the development of entrepreneurship education in universities and nurturing more well-rounded talents for society.
DC Arc Plasma Numerical Simulation Calculation Review
Authors: Li Shuangliang , Tao Jing
Published: November 2024

This study established a three-dimensional numerical model based on the Fluent software, listing the commonly used boundary conditions, physical models, and basic assumptions in the process of DC arc plasma numerical simulation. By combining multiple literature analyses, the influence of working gas flow rate, working current magnitude, degree of gas swirl, and non-swirling gas on the internal physical fields of the DC arc plasma torch was investigated. The research results indicate that the temperature, current density, plasma flow velocity, and pressure inside the plasma torch all increase with the increase of the working gas flow rate and working current. Under the same operating conditions, an increase in the degree of gas swirl leads to a decrease in the temperature and current density inside the plasma torch. This study provides theoretical support for the design, optimization, and control of plasma torches, which is helpful in improving the thermal efficiency and application effects of plasma torches.
A Data-Driven Approach to Tennis Player Performance Prediction and Evaluation
Authors: Zhang Jiabao
Published: November 2024

This study presents a comprehensive framework for evaluating and predicting tennis player performance using historical match data. First, to reduce the data dimension, principal component analysis is used to obtain seven principal components that capture more than 85% of the variance of the data. These principal components serve as inputs to a machine-learning model that is used to predict the outcome of tennis scores. Various machine learning algorithms are compared using ROC curves and evaluation metrics. The gradient gradient-enhanced decision tree (GBDT) model performs best. To evaluate athletes' performance comprehensively, an evaluation system based on the derived principal component was constructed by using the entropy weight method and the TOPSIS model. This comprehensive approach achieved 89.04% accuracy in predicting the outcome of tennis matches, demonstrating its effectiveness in capturing match dynamics. In addition, the study introduces a visualization method that combines macro-level score analysis with micro-level performance assessment. This allows a detailed understanding of how players perform at different stages of the game, enabling coaches and players to make informed decisions and optimize strategies.
Study on High-quality Development Strategy of Rural Economy Under the Strategy of Agriculture, Rural Areas and Farmers
Authors: Zhang Kaixian
Published: November 2024

With the in-depth implementation of the "three rural" strategy, the high-quality development of rural economy has become an important goal to achieve rural revitalization. This paper starts with the current situation of rural economic development, analyzes the main challenges facing rural economy, including infrastructure construction lag, unreasonable industrial structure and brain drain and innovation ability. On this basis, the core strategy of high-quality development of rural economy is put forward from three aspects: industrial revitalization, ecological revitalization and talent revitalization. By optimizing the industrial structure and promoting the integration of the primary, secondary and tertiary industries, the agricultural production efficiency is improved; Emphasizing green agriculture and environmental governance to promote sustainable development; Attention should be paid to attracting high-quality talents and improving rural education and training systems to promote innovation and entrepreneurship in rural areas. Through comprehensive measures, we will strive to provide systematic support for the high-quality development of the rural economy and help the smooth implementation of the rural revitalization strategy.
Corporate Ethics and Indigenous Rights: Analyzing the Impact of Vale S.A.'s Mining Operations in the Brazilian Amazon
Authors: Ou Mengxian
Published: November 2024

This work conducts a study on the ethical and cultural implications of the mining operations of Vale S.A. in the Brazilian Amazon with a special view on the indigenous communities. The major portion of this giant company’s work is done in ore production, which has caused mass deforestation, water pollution, and breach of land rights of the indigenous people. The company has failed to abide by international ethical mandates, including Free Prior Informed Consent (FPIC) and Corporate Social Responsibility (CSR). The work explained that the company has not abode by international ethical mandates as incorporated in United Nations Global Compact (UNGC) and United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP). The case study reports not exclusively the environmental hazards provoked by the mineral extractions of Vale but equally the socio-cultural devastation experienced by the native populations most notably the Yanomami. It also puts forward some actionable recommendations, which consist of implementing the FPIC, working with indigenous communities as stakeholders, and undertaking corporate governance reforms that zero in on more accountability. This case should practically serve as a wake-up call to businesses working in very sensitive areas to bring their practices in line with global ethical standards of ensuring that development is not achieved at the expense of marginalized communities.
Research on Sevengill Eel Population and Ecosystem Stability Based on Sex Ratio Changes
Authors: Li Chunsong
Published: November 2024

This study utilizes mathematical modeling, including difference and differential equations, to analyze the impact of gender ratio changes in seven-gill eels on ecosystem dynamics. The model incorporates population growth, gender ratio variations, and interactions with other ecosystem components. The findings reveal that a balanced sex ratio supports optimal population growth and ecosystem stability, while a male-dominated population reduces biodiversity and increases resource competition. Food availability and predator presence significantly affect the sex ratio, influencing the ecosystem's overall health. Using the TOPSIS method, the study determines that a higher proportion of females is most beneficial for ecosystem stability. Maintaining an optimal sex ratio is essential for ecosystem health, providing valuable insights for conservation and management efforts.
Research on Financial Systemic Risk Early Warning Based on Markov Regime Switching Model
Authors: Yang Jiaer
Published: November 2024

This paper discusses the early warning mechanism of financial systemic risk based on Markov regime switching model (MRSM). In view of the infectivity, widespread influence and serious consequences of systemic risk, traditional methods are often insufficient. In this paper, MRSM is used to improve the accuracy and timeliness of early warning, and an index system including macro-economy, policy changes, financial fragility and infectious risks is constructed. Principal component analysis (PCA) is used to integrate risk indexes of all dimensions to form financial stress index (FSI). Using a variety of economic and financial data, identify and predict the systemic risk state through MRSM. The results show that the model can effectively warn the high-risk period in advance, and its accuracy and timeliness are verified in practice, which provides an effective risk management tool for regulators.
Application and Prospect of Artificial Intelligence in Personalized Learning
Authors: Zhao Cong
Published: November 2024

With the rapid development of "big data, intelligence, cloud, things and mobile" technology, artificial intelligence has been widely used in the field of education, providing technical support for personalized learning. The traditional education model cannot meet the personalized needs of students. Education reform calls for the introduction of artificial intelligence technology to achieve the optimal allocation of educational resources and improve teaching effectiveness. The knowledge economy era has put forward higher requirements for talents' innovation ability and lifelong learning ability. Personalized learning is an important way to cultivate these abilities. This paper first takes the main application of artificial intelligence in personalized learning as the starting point, and then analyzes the advantages and challenges of artificial intelligence in personalized learning. It is concluded that artificial intelligence plays a positive role in innovating teaching methods, achieving educational equality, and giving new impetus to learning, but at the same time it also faces challenges in various aspects.
Current Situation and Thinking of Contemporary National Music Teaching
Authors: Shi Siyu
Published: November 2024

National music, as an important carrier for inheriting and promoting the excellent culture of the Chinese nation, has distinct, unique and profound national characteristics and aesthetic education value. National music teaching demonstrates the value concept of educating people with beauty and people-oriented, which is the concentrated embodiment of the core value of art courses. Based on the analysis of the current situation of national music teaching in my country, this paper proposes to focus on the cultural literacy of music teachers, improve the construction of national music teaching materials, and enhance the status of music education in school education, etc., to optimize the countermeasures of national music teaching in the new era, and provide a practical path for the widespread dissemination and popularization of national music in school education in my country.
Application and Optimization of Lightweight Convolutional Neural Network in Target Detection
Authors: Li Liangyuan
Published: November 2024

Due to its low computational complexity, minimal storage needs, and high real-time performance, lightweight convolutional neural networks (LCNN) have garnered significant attention amidst the swift advancement of deep learning technology. By automatically learning high-level feature representation, LCNN can capture key information in images more effectively. This paper aims to discuss the application and optimization of LCNN in target detection task. This paper discusses the key strategies such as network structure optimization, training method optimization and post-processing optimization to improve the performance of LCNN in target detection. The experimental results show that compared with the traditional SIFT-based target detection algorithm, LCNN has obvious advantages in detection success rate, time consumption and adaptability to different scenes. In addition, the lightweight design of LCNN makes it easier to deploy on equipment with limited resources. LCNN shows strong performance and wide application prospect in target detection, which is expected to provide new impetus for the innovation of target detection technology.
Educator’s Sentiments and Time Values of Zhang Jian
Authors: Xu Heng , Ma Bin
Published: November 2024

As a preeminent patriotic industrialist and educator in modern and contemporary Chinese history, Zhang Jian not only ventured into industrial enterprises to improve people's livelihood during the exploration and practice of early modernization in China but also initiated educational endeavors, holding profuse educational thoughts and concepts. Zhang Jian's educationalist sentiments are manifested in such aspects as his aspiration for enlightening and strengthening the nation, his advocacy of morality and culture, and his pragmatic and innovative demeanor. Propagating Zhang Jian's educationalist sentiments not only contributes to our comprehensive and profound understanding of the essence, essentials, undertones, and characteristics of the spirit of educationalists in the new era but also facilitates our steadfast establishment of the historical sense of mission and responsibility for educating talents for the Party and the country, and ultimately promotes the high-quality development of Chinese education and Chinese-style modernization.
The Communication Strategy of Xi'an City Image on Douyin based on the SWOT Analysis
Authors: Li Lei , Bolong Jusang Bin
Published: November 2024

With the rapid development of digitalization and globalization, the dissemination of city image has gradually become an important part of urban competitiveness. This article uses the SWOT analysis method to explore Xi'an's city image dissemination strategy on the Douyin platform and its strengths, weaknesses, opportunities and threats. This study points out that Xi'an has significant advantages in city image dissemination with its rich historical and cultural heritage and tourism resources. However, disadvantages such as content homogeneity and insufficient public services restrict the dissemination effect. At the same time, the implementation of new policies and the application of innovative technologies provide Xi'an with opportunities to further enhance its international reputation, but competition from other historical and cultural cities and changes in platform policies also pose potential threats. This article finally suggests that Xi'an should respond to external changes through content innovation, user participation and multi-platform cooperation, continuously optimize the city image dissemination strategy, and establish a more distinctive and attractive Xi'an city image.
Hidden Danger Detection and Identification System of Power Transmission Tower Based on YOLOV11
Authors: Zou Xin , Hu Yanru
Published: November 2024

This study proposed a hidden danger detection and identification system of power transmission tower based on YOLOv11, aiming to introduce an intelligent detection and identification system of hidden danger of power transmission tower based on YOLOv11 algorithm, which is committed to enhancing the safety and stability of power transmission tower. YOLOv11, the latest and most advanced object detection algorithm in the YOLO family, is known for its excellent detection efficiency and accuracy. In this system, YOLOv11 is specially trained to accurately identify four potential hazards on power pylons: bird's nests, balloons, garbage and kites. The accuracy of the system is as high as 93.8%, and the recall rate has reached an excellent level of 73.3%. In order to fully verify the actual utility of the model, we carefully built a user-friendly intuitive interface (UI) using PyQt5. The system integrates image detection, video detection and real-time camera monitoring and recognition functions, can accurately identify the above four types of hidden dangers, and comprehensively record all the detection results, which provides great convenience for subsequent data analysis and processing. This system is not only easy to operate, user-friendly user interface design, but also shows excellent performance in the process of real-time monitoring and recognition, ensuring a high degree of accuracy. These characteristics have laid a solid foundation for the subsequent related work.
Development Strategy of Carbon Finance in China Under the Low Carbon Economy Context
Authors: Xia Yezhi
Published: November 2024

As the concept of green development deepens, China actively promotes a low carbon economic development model, paying close attention to climate issue governance and carbon finance. Vigorously developing the carbon finance market and utilizing market mechanisms to optimize various resources, it provides industrial enterprises with carbon emission models that suit their own development. As the world's largest developing country, China should assume relevant responsibilities when facing global climate issues. Viewing the current development, countries worldwide have enhanced their focus on carbon trading markets and fully recognize the significant role of carbon finance in changing the future international financial landscape. From China's perspective, promoting the development of the carbon finance market and studying the current situation, issues, and strategies of carbon finance market development are crucial. This accelerates the construction of the carbon finance market in China, seeks the right to speak in the global carbon finance market, and thus, solidifies its standing in the international market.
Additive Exploration of Al/CuO Aluminium Thermite Systems
Authors: Lou Mingsong , Zhang Yongming , Zhang Yanfan , Xie Hangfei , Qiu Bozhi , Wang Jie
Published: November 2024

Aluminium thermite research has made significant progress in recent years, especially in the Al/CuO system to show its scientific value and application potential. Starting from the history of aluminothermite development, types of aluminothermite production methods, and exploration based on Al/CuO system. The development history of aluminothermics is briefly described. Advantages and disadvantages of various aluminothermic agent preparation methods, existing new methods. Overview of titanium-containing polymers, silicone-containing polymers, fluorine-containing polymers, and other additives based on the Al/CuO system to enhance the performance of aluminothermic agents.
Effect of coating Urea granules with Neem (Azadirachta indica) – Urea coat on the pattern of nitrogen release and microbial activity
Authors: Verma K. , Mishra V. , Kaushal R.
Published: November 2024

Influence of Neem Coated Urea on the release of NH4-N; NO2 + NO3-N, microbial activity and relative nitrification rate was determined in a laboratory incubation experiment. Five treatments, viz., soil + urea (T1), soil + urea coated with Neem coat-I (T2), soil + urea coated with urea coat-I & urea coat-II (T3), soil + urea coat-II (T4) and soil alone (T5). The ammonical and nitrate nitrogen release pattern in all the treatments was alike. Similar was the production of CO2 reflecting microbial activity. Relative rate of nitrification in treatment soil + urea coat-I (T2) was significantly less than even the soil alone treatment, i.e., control.
Turiyam a Co-ordinate Free Geometry and its exploration
Authors:   Department of Computer Science and Engineering, Gandhi Institute of Technology and Management-Visakhapatnam, Andhra Pradesh 530045, India, Prem Prem
Published: November 2024

Recent time data representation and visualization is considered as one of the major issues. It become more crucial when the data sets exists beyond the non-euclidean geometry and its hybridization also. There are several examples given by non-euclidean geometry by Lobachevsky, Bolyai, Riemannian which contains failure of Euclid postulates V and II, respectively. The problem arises when none of the Euclid Postulates exists. It might possible that the data sets contains unknown or co-ordinate free geometry. In this case the data can be explored based on a defined vector space rather than available co-ordinate geometry. It require human Turiyam consciousness to explore these types of unknown, undefined, co-ordinate free data. To understand this problem current paper explores the Turiyam geometry and its basic for exploring the unknown or undefined data with an example.
ОЦЕНКА РИСКОВ ВЫБОРА ВТОРИЧНОЙ НЕДВИЖИМОСТИ
Authors: Г.П. Фомин , И.В. Сухорукова , И.Ф. Алешина
Published: November 2024

Выявление и оценка рисков – один из ключевых аспектов рынка недвижимости. Данное обстоятельство связано с тем, что инвесторам и девелоперам необходимо принимать взвешенные решения в условиях неопределенности на рынке недвижимости. Статья посвящена анализу рисковых факторов, вероятности их возникновения и разработке математических алгоритмов снижения негативных последствий при выборе объектов для инвестирования в недвижимость на вторичном рынке. Математические методы анализа позволяют создать объективную основу для принятия решений за счет использования количественных данных и минимизации субъективных решений. Для достижения этой цели были использованы различные методы анализа: многокритериальный, матричный метод парного сравнения характеристик недвижимости, чтобы создать прочную основу для принятия решений, что и показано в работе вплоть до конкретных рекомендаций риэлторам. Кроме того, использование данных методик анализа можно легко адаптировать к различным рынкам и ситуациям.

Identifying and assessing risks is one of the key aspects of the real estate market. This circumstance is due to the fact that investors and developers need to make informed decisions in the face of uncertainty in the real estate market. The article is devoted to the analysis of risk factors, the likelihood of their occurrence and the development of mathematical algorithms for reducing negative consequences when choosing objects for investment in real estate on the secondary market. Mathematical methods of analysis allow you to create an objective basis for decision-making through the use of quantitative data and minimization of subjective decisions. To achieve this goal, various methods of analysis were used: multi-criteria, matrix method of pairwise comparison of real estate characteristics to create a solid basis for decision-making, which is shown in the work down to specific recommendations for realtors. In addition, the use of these analysis techniques can be easily adapted to different markets and situations
Pengaruh Model Pembelajaran Berbasis Masalah terhadap Kemampuan Literasi Sains Siswa pada Materi Sistem Ekskresi
Authors: Nabila Halim Nasution  , Hasruddin Hasruddin , Juliani Juliani
Published: November 2024

This study aimed to investigate the effect of problem-based learning on students' science literacy skills in the excretory system material for grade 11 science students at Madrasah Aliyah Negeri Binjai. This research was a quasi-experimental study using a pretest-posttest nonequivalent control group design. The population of this study was all grade 11 science students at Madrasah Aliyah Negeri Binjai in the 2023/2024 academic year. Cluster sampling was used to obtain two classes as samples, namely the experimental class (XI MIA 2) and the control class (XI MIA 5). Data was collected using a science literacy test instrument consisting of 20 multiple-choice questions, developed based on the Programme for International Student Assessment (PISA) framework, which measures three science literacy competencies: explaining phenomena scientifically, evaluating and designing scientific investigations, and interpreting data and evidence scientifically. The results showed that the average post-test score of the experimental class (using PBL) was higher (81.67) compared to the control class (61.06). The Independent Sample T-test showed a significant difference between the two groups, so the null hypothesis was rejected and the alternative hypothesis was accepted. Based on these results, it can be concluded that PBL has a positive effect on improving students' science literacy skills in the excretory system material.
Computing Awareness and Computational Thinking in Sri Lankan Street Vendor Communities: A Pilot Study
Authors:   Faculty of Applied Sciences, Wayamba University of Sri Lanka, Perera S.A.K.M , Munasinghe B ,   Faculty of Applied Sciences, Wayamba University of Sri Lanka
Published: November 2024

Although street market is a common and diverse form of informal economy in a country, the computing awareness and computational capacity of its contributing communities are largely understudied. This case study attempts to investigate the Computing awareness and Computational Thinking (CT) skills among street vendors in a Sri Lankan urban commercial area, using a mixed methods approach. It summarizes interviews, survey and observational findings about their digital literacy, digital awareness, problem solving skills and algorithmic thinking ability and the results are interpreted to understand their Computing awareness and CT skills. The findings reveal that Sri Lankan urban street vendors use digital devices, especially smartphones, for various purposes related to their vending activities, yet face concerns and challenges in accessing, affording, and trusting digital technologies. They seem to apply algorithmic thinking in planning, organizing, and optimizing their vending operations, and display problem-solving skills in coping with uncertainties, risks, and conflicts in their work environment, reflecting their resilience and adaptability. The study confirms that CT could be a valuable and relevant skill for street vendors and recognizing and nurturing these skills can enhance their socio-economic inclusion and resilience. The study also provides indicators for future research, such as exploring the gender and generational differences in both Computer awareness and Computational Thinking skills and evaluating the impact of educational interventions in those areas. Keywords: Algorithmic Thinking, Computational Thinking, Computer Science Social Topics, Societal Development, Computer Awareness