bluuebunny/crossref_metadata_2025 huggingface dataset:
Remilitarization and the struggle for an economic exploatation of Arctic as a reflection of war in Ukraine
Authors: Tučić Boris
Published: February 2025

Main goal of the paper is to analyze some of the most important implications of the contemporary international relations to the security of Arctic region. As a reflexion of the current state of the international relations and the revitalization of the "Cold war" interactions among key global players, Arctic region has been subject of relatively intensive (re)militarization from both - Russian and "Western" - sides, as well as of military reconfiguration, in a sense that NATO, through the admission of Finland and Sweden in its membership in April 2023 and March 2024, significantly strenghtened its Baltic, Nordic and Arctic flanks, as well as its presence at the Russian border. The analysis of the subject has been done within the theoretical framework of the science of international relations and by using the selected scientific methods, such as content analysis, inductive and deductive methods, as well as the comparative analysis. One of the conclusions of the analysis is that, as an implicitaion of its (re)militarization, military reconfiguration and of the state of contemporary international relations in general, military security of the Arctic region is by far predominant dimension of its security at the moment. Additional complicating moment regarding the complex situation in the Arctic comes with the "Chinese factor" and the strong intention of Beijing, primarily over Moscow, to gradually impose itself as a inevitable political, economic, as well as security "force" in the Arctic region. Western countries, led by the US, the intention of China see as a direct threat to their national interests, while the Russian Federation's long term best interests, no matter how important its partnership with Beijing is right now, is to keep its presence and influence in the region within the acceptable framework.
A systematic review of playing-related musculoskeletal disorders (PRMD) among tertiary-level professional music students: Exploring gender, psychological, and physiological determinants.
Authors: Fu Yu , Chiat Loo Fung , Chiat Loo Fung
Published: February 2025

Objective: The aim of this systematic review was to assess the methodological quality of articles on the prevalence of playing-related musculoskeletal disorders (PRMD) in music students tertiary, and to determine the prevalence rate and associated factors of PRMD.Methods: This review included crosssectional studies that described data on music students and were published in English between 1/1/2000 and 9/20/2024. Databases used in this study included, Web of Science (core collection), MEDLINE, sciELO, PubMed and Scopus. Reviewers used the Loney scale to assess methodological quality, and only studies that scored 5 were included.Results: A total of 479 articles have been identified, among which 11 cross - sectional studies were selected for methodological assessment. All of these studies achieved satisfactory scores regarding methodological quality. The prevalence rate of PRMD was remarkably high, varying from 28.9% to 80.7%. Female student musicians were more susceptible compared to those of other genders. Students lacking exercise habits were at higher risk. String and keyboard instrument players had the highest probabilities of PRMD. The traits of anxiety and perfectionism among music students were closely associated with PRMD.Conclusions: Music students are generally affected by PRMD. The gender, exercise habits and emotional traits of students are highly correlated with PRMD. Low response rates are a prevalent issue, and researchers from different continents tend to use different survey tools.
Investigation of Point Merge Utilization Worldwide Using Opensky Network Data
Authors: Hardell Henrik , Polishchuk Tatiana , Smetanová Lucie
Published: February 2025

Point Merge (PM) arrival procedures are currently in use at 44 airports across 20 countries worldwide. These procedures come in various design variants, including overlapping, partially overlapping, or separated sequencing legs. The positioning of sequencing legs within or outside of the Terminal Maneuvering Area (TMA) and the geometry of the arrival flows to PM or merging points impact the associated trade-offs between the PM system capacity and efficiency. In our study, we analyze the utilization of PM procedures at several airports implementing PM, using open-access ADS-B-based data from the Opensky Network. To identify flights that adhere to the PM procedures, we propose a catchment algorithm. The accuracy of the algorithm depends on the quality and completeness of the data, the specific design of the algorithm, and the complexity of the PM procedures. Generally, a well-designed catchment algorithm can achieve high accuracy by considering factors such as aircraft positions, speeds, and adherence to sequencing instructions. Then, we quantify PM utilization using performance indicators specifically tailored for this purpose.
This paper builds upon previous research presented at the 11th OpenSky Symposium in 2023. We introduce an additional step to enhance the accuracy of the catchment algorithm and conduct a comprehensive sensitivity analysis of the catchment area size employed in the initial stage. We quantify the algorithm’s accuracy by considering false-positive and false-negative filtered trajectories. Furthermore, we compare the results of our proposed approach with the PM identification tool available in the Traffic Library.
Exploring the Level of Satisfaction of Using Artificial Intelligence as to Having Romantic Relationship
Authors: Saga Michelle Angel , Cabugwason Jhemaree Pearl , Cabusas Maria Isabel , Camilo Aizee Grace , Daugdaug Vanessa , Rosales Maria Luz , Sacay Kaiser Kate , Batiancila Marian Joy
Published: February 2025

At this modernity, various applications have been innovated to entertain people and foster romantic connections, with one of the most notable being the increasing integration of artificial intelligence (AI) in romantic relationships. This study, conducted in the Philippines, aims to explore the relationship between relationship satisfaction from using AI in romantic relationships and the level of AI usage, while evaluating its significance in today’s generation. A total of 338 students ranging from Grade 11 to fourth-year college students, participated in this research, which employs a quantitative approach with a descriptive research design. The results revealed that participants were "satisfied" with their relationship satisfaction from using AI (M = 3.71, SD = 0.79), with 67% to 98% agreeing that AI positively influences their romantic relationship satisfaction. The overall AI usage in romantic relationships had a high mean score (M = 3.66, SD = 0.66), suggesting significant engagement with AI in this context. A moderately positive correlation (r = 0.585, p < 0.000, N = 338) was found between AI usage and relationship satisfaction, indicating that as AI usage increases, so does relationship satisfaction, underscoring the role of AI in enhancing emotional aspects of romantic relationships.
Perlindungan Hukum Tenaga Kerja Indonesia di Malaysia: Tantangan dan Upaya Diplomatik
Authors: Roji Rizki Pahrul , Nasrudin Nasrudin , Huda Uu Nurul
Published: February 2025

Penelitian ini bertujuan untuk menganalisis perlindungan hukum tenaga kerja Indonesia (TKI) di Malaysia dengan fokus pada tantangan hukum dan upaya diplomatik yang dilakukan pemerintah Indonesia. Penelitian ini menggunakan metode kualitatif dengan pendekatan yuridis normatif yang melibatkan studi literatur dan analisis dokumen. Hasil penelitian menunjukkan bahwa meskipun terdapat kerangka hukum dan perjanjian bilateral, TKI di Malaysia masih menghadapi berbagai masalah, seperti pelanggaran hak kerja, eksploitasi pekerja tanpa dokumen, serta keterbatasan akses bantuan hukum. Kebaruan penelitian ini terletak pada analisis yang mengintegrasikan aspek hukum dan diplomasi, dengan penekanan pada pentingnya kerangka kerja sama bilateral yang lebih proaktif dan sistem bantuan hukum yang lebih efektif. Penelitian ini berkontribusi dengan memberikan rekomendasi kebijakan untuk meningkatkan perlindungan hukum serta memperkuat strategi diplomatik Indonesia dalam melindungi hak-hak TKI di Malaysia.
Konsep Tarbiyah Rabbaniyah dalam Keluarga Menurut Al-Qur’an dan Relevansinya Terhadap Pola Asuh Anak Berlandaskan Ajaran Islam
Authors: Prasutia Putri Reginata , Nursari Nina
Published: February 2025

Pendidikan keluarga dalam Islam memiliki peran penting dalam membentuk karakter dan moral anak. Konsep tarbiyah rabbaniyah dalam Al-Qur’an menekankan pendidikan yang berlandaskan nilai-nilai ketuhanan, spiritualitas, dan akhlak mulia. Penelitian ini bertujuan untuk menganalisis konsep tarbiyah rabbaniyah dalam keluarga menurut Al-Qur’an serta bagaimana konsep ini berpengaruh terhadap pola asuh anak dalam Islam. Metode penelitian yang digunakan adalah kualitatif dengan pendekatan tafsir tematik, yaitu menganalisis ayat-ayat Al-Qur’an yang berkaitan dengan pendidikan keluarga dan pengasuhan anak. Hasil penelitian menunjukkan bahwa tarbiyah rabbaniyah menekankan tiga aspek utama: Pertama, tauhid sebagai fondasi utama pendidikan keluarga; Kedua, akhlak dan adab dalam membangun karakter anak, serta; Ketiga, pembinaan spiritualitas yang melibatkan hubungan harmonis dengan Allah dan sesama manusia. Studi ini memberikan kebaharuan dengan mengintegrasikan konsep tarbiyah rabbaniyah dengan teori pola asuh Islami dalam konteks modern. Kontribusi penelitian ini adalah menawarkan model pendidikan berbasis Al-Qur’an yang dapat diterapkan oleh keluarga Muslim dalam menghadapi tantangan zaman.
Business-to-Business (B2B) Marketing for Industrial Products in Google Ads: Strategies, Challenges, and Effectiveness
Authors: Ruvi Mohammad
Published: February 2025

This study explores the potential of Google Ads in Business-to-Business (B2B) marketing, focusing on its effectiveness, challenges, and success factors in the industrial sector, particularly for products such as pumps, valves, and compressors. The research originality lies in its comprehensive analysis of both the technical and socio-economic barriers to Google Ads adoption, filling gaps in the existing literature regarding long-term ROI and regional variations in campaign effectiveness. The study employs a mixed-methods approach, combining a systematic literature review, case studies of successful B2B Google Ads campaigns, and semi-structured interviews with industry experts. Empirical results reveal that Google Ads is highly effective for lead generation and brand awareness, with tailored campaigns achieving an average conversion rate of 8.5%. However, challenges such as high cost-per-click (CPC), complex buyer journeys, and ad fatigue hinder campaign success. Key success factors include data-driven optimization, integration with other marketing channels, and the use of industry-specific keywords. The findings have significant implications for B2B marketers, emphasizing the need for strategic budget allocation, continuous campaign optimization, and policy frameworks that support digital marketing adoption. This research provides actionable insights for businesses aiming to leverage Google Ads to enhance competitiveness in the digital marketplace.
ТЎҚИМАЧИЛИК САНОАТИ КОРХОНАЛАРИДА ИҚТИСОДИЙ БАРҚАРОРЛИКНИ ТАЪМИНЛАШНИ ТАШКИЛ ЭТУВЧИ РЕСУРСЛАР ТАРКИБИ
Authors: Абдуллаева Севарахон
Published: February 2025

Фаолият юритаётган тўқимачилик саноати корхоналарининг иқтисодий барқарорлигини таъминлаш ишлаб чиқариш жараёнларида бевосита ҳамда билвосита иштирок этувчи ҳамда фаолиятнинг асосий ташкил этувчи омилларидан ҳисобланган ресурсларга боғлиқдир. Мазкур мақола корхонада иқтисодий барқарорликни таъминловчи иқтисодий ресурсларнинг таркибий тузилмасини тадқиқ этишга қаратилган бўлиб, ҳар бир ресурснинг иқтисодий жараёнларга нисбатан таъсир доираси ёритилган.
СУҒУРТА БОЗОРИНИ РАҚАМЛАШТИРИШ УНИНГ РАҚОБАТБАРДОШЛИГИНИ ОШИРИШНИНГ ОМИЛИ СИФАТИДА
Authors: Турғунмирзаев Азмиддин
Published: February 2025

Мақолада суғурта соҳасининг рақамли трансформацияси натижасида юз бераётган ўзгаришлар, соҳани рақамлаштириш орқали компанияларнинг рақобатбардош омилларининг таҳлили атрофлича таҳлил этилган.
MAHALLA TIZIMIDA DAVLAT XIZMATLARI KOʻRSATISH MILLIY TIZIMINI TAKOMILLASHTIRISH YOʻLLARI
Authors: Sagdullayev Ulugʻbek
Published: February 2025

Maqolada mahalla tizimida davlat xizmatlari koʻrsatish milliy tizimining fuqarolarning shaxsiy ishtirokini qisqartirish “3 qadam”, “foydalanuvchi uchun moslashtirilgan” tamoyillari asosida takomillashtirilgan  mahalla tizimida davlat xizmatlariga boʻlgan talabni aniqlash, davlat xizmatlari koʻrsatish talablarini belgilash, davlat xizmatlari koʻrsatish standartlarini belgilash, davlat xizmatlari roʻyxatini shakllantirish, davlat xizmatlari koʻrsatishdagi ustuvorliklarni belgilash imkonini beruvchi tashkiliy-iqtisodiy mexanizmi va uning mahalla tizimida davlat xizmatlari koʻrsatishni tashkil qilish jarayoni yoritib berilgan. Ushbu tashkiliy-iqtisodiy mexanizm asosida mahalla tizimida davlat xizmatlari koʻrsatishning asosiy yoʻnalishlarini taklif qilingan.
Sibling Rivalry in the Perspective of Islamic Education
Authors: Sardi Mustaupa
Published: February 2025

This study aims to delve into the concept of sibling Rivalry in the Qur'an using a scientific approach. Siblinghood is a profound and essential value in Islamic teachings, serving as the foundation for interpersonal relationships within society. This research focuses on the analysis of Qur'anic verses that depict and discuss various aspects of siblinghood. The research methodology involves textual analysis of relevant verses, considering the historical and cultural context at the time of revelation. The findings indicate that the Qur'an emphasizes the significance of siblinghood as a basis for creating a just and harmonious society. Specific verses provide guidance on the rights and responsibilities among siblings, offering insights into the moral values that should be upheld in these relationships. This analysis also reveals that siblinghood in the Qur'an is not merely biological but encompasses spiritual and moral dimensions as well. The concept teaches solidarity, mutual assistance, and love among siblings as manifestations of devotion to Allah. Therefore, a profound understanding of the concept of siblinghood in the Qur'an can serve as a foundation for building a society characterized by compassion and justice. This research contributes to the scholarly understanding of the concept of siblinghood in the Qur'an and provides a new perspective on its practical implementation in daily life. The implications of this research can be used as a basis for developing educational and social programs aimed at strengthening the values of siblinghood in Muslim communities.
Keywords: sibling Rivalry, Islamic Values, Solidarity
Implementation of Character Education in the Independent Curriculum
Authors: Idham  , Rokimin  , Muchammad Ibnu Muzakir
Published: February 2025

This study analyzes the importance of character education within the framework of the independent curriculum, focusing on the integration of moral values in learning, the role of school leadership, and collaboration between teachers, parents, and the community. The method in this study uses a descriptive qualitative approach through literature studies from journals, books, and official documents. The results of the study show that the independent curriculum supports project-based learning, the flexibility of a holistic approach, and the role of transformational leadership in creating a school culture that supports character education. The challenges faced include limited teacher training, gaps in student backgrounds, and lack of program evaluation. The implication is the need to increase teacher training, strengthen the role of school principals, and integrate local values and digital technology to strengthen the effectiveness of character education. This research provides strategic recommendations for policymakers and educators in building a generation with character in the modern era
PŘEPLNĚNOST – CHRONICKÁ NEMOC ČESKÝCH VĚZNIC
Authors: Coufalová Bronislava
Published: February 2025

České vězeňství trpí několik let trvajícími chronickými problémy jako např. zaměstnávání odsouzených, samotné nadužívání trestu odnětí svobody justičním systémem, podfinancování potřeb Vězeňské služby, přítomnost drog ve věznicích apod. Nejpalčivějším problémem se však jeví býti přeplněnost věznic. Problematiku vězeňství je však třeba chápat komplexním způsobem, neboť se nejedná jen o problematiku vězeňství samotného, ale i vládních i nevládních institucí, dalších exekutivních a parlamentních orgánů, a v podstatě společnosti jako celku.
Estrategias Tecno Pedagógicas de Apoyo a la mejora del Proceso de Enseñanza-Aprendizaje en Bachillerato
Authors: Alonso Esquivel Francisco , Castro Aranda Cynthia Berenice , Lizeth de la Garza López Indira , Salazar Flores Víctor Alfonso , Nieto Claudio Jorge Luis
Published: February 2025

La educación media superior se encuentra en un punto de inflexión. La creciente demanda por profesionales capacitados para un mercado laboral en constante evolución exige una transformación de métodos de enseñanza.  La integración de plataformas tecnológicas es esencial para mejorar la calidad del aprendizaje, facilitando el acceso a la información y promoviendo un aprendizaje interactivo, colaborativo y personalizado. Plataformas virtuales como Moodle y Google Classroom entre otros, ofrecen entornos de aprendizaje flexibles a los estudiantes al acceder a materiales educativos en cualquier momento y lugar. Estas herramientas fomentan la autonomía, la colaboración y la personalización del aprendizaje, adaptándose a diferentes ritmos y estilos. La gamificación, a través de plataformas como Kahoot! y Quizizz, convierte el aprendizaje en una experiencia más atractiva y efectiva. Herramientas como Canva y Prezi, estimulan la creatividad y la comunicación visual, habilidades altamente valoradas en el mundo laboral. La incorporación de tecnologías digitales en la educación media superior no solo mejora la calidad del aprendizaje, sino que también prepara a los estudiantes para enfrentar los desafíos de un mundo laboral cada vez más digitalizado y competitivo.
Land Use and Land Cover changes in the Centre Region of Cameroon.
Authors: Mesmin Tchindjang , Frédéric Saha , Eric Voundi , Fendoung Philippes Mbevo , Makak Rose Ngo , Ismaël Issan , Frédéric Sédric Tchoumbou
Published: February 2025

Cameroon territory is experiencing significant land use and land cover (LULC) changes since its independence in 1960. But the main relevant impacts are recorded since 1990 due to intensification of agricultural activities and urbanization. LULC effects and dynamics vary from one region to another according to the type of vegetation cover and activities. Using remote sensing, GIS and subsidiary data, this paper attempted to model the land use and land cover (LULC) change in the Centre Region of Cameroon that host Yaoundé metropolis.  The rapid expansion of the city of Yaoundé drives to the land conversion with farmland intensification and forest depletion accelerating the rate at which land use and land cover (LULC) transformations take place.  This study aims at assessing the impacts of both agriculture and urbanization on the LULC change in the Centre Region of Cameroon. A detailed LULC map from MAPBOX high resolution images and three LULC maps were produced from Landsat TM-OLI images (1984-2015). A maximum likelihood classification techniques using ERDAS Imagine, showed forest decline with a total loss of 54% in thirty years.  Also, Landsat and MAPBOX images to which we added 1951 aerial photograph and SPOT 6 (2006) were used to analyse urban growth in the city of Yaoundé. The results show a remarkable urban spatial spread of the metropolis between 1951 and 2015, with a peak in 2000. Images processing enabled us to analyse the long term dynamics of LULC change since the 1950s in this Region using ArcGIS & QGIS software’s. Based on this dynamic, a LULC projection map was produced using Markov model on IDRISI Selva, demonstrating the decrease of the dense forest (45% in 2015 to 0.25% in 2050). It was estimated that by 2050, the entire dense forest can be depleted if nothing is done, while only 12.67% of the secondary forest would remain in the Region. Such a projected map is very useful to decision makers for council development and urban planning. This effective forest depletion ties with the hypothesis that urbanization of Yaoundé and its secondary surrounding satellite cities (within a radius of 30-100km) is a veritable driving force of deforestation.
Learning Language Beyond the Classroom: Reading English Newspapers in University Dormitories and Developing English Language Skills
Authors:   Education Professional and Humanitarian Worker, Bangladesh, Md Abu Nayeem , Abdul Alim ,   Secondary High School Teacher, Ministry of Education, Mohammod Moninoor Roshid ,   Institute of Education and Research (IER), University of Dhaka
Published: February 2025

Learning English as a foreign language (EFL) beyond the classroom is challenging in non-native English-speaking developing
countries with limited resources. However, learning English beyond the classroom occurs in an informal way to support language
learning for many autonomous or independent adult learners. This paper explores the habit of reading English newspapers
among residential students at a university as an autonomous English language learning process outside of the classroom.
Adopting a sequential explanatory mixed-method approach, data was collected from 150 residential students at the University
of Dhaka who participated in the survey, followed by interviews with 15 students. The findings show that most of the
participants read English newspapers as autonomous learners, considering the material value of English. They considered
developing English skills through the habit of reading English newspapers likely to help them in the future, particularly in career
preparation and getting the desired job and academic excellence. This reading habit and English language learning have been
interpreted through the theoretical lens of learning autonomy, Bourdieu’s habitus, and cultural capital. The study also identified
some challenges in developing the habits of reading English newspapers for residential learners and suggestions for overcoming
the obstacles and enabling their reading habits as an autonomous learning process for university learners.
Research on Personalized Recommendation Algorithm of E-Commerce Platform Based on Big Data
Authors: Gu Xupeng
Published: February 2025

This study aims to improve the accuracy and user satisfaction of personalized recommendation algorithms for e-commerce platforms. By analyzing the advantages and disadvantages of the existing recommendation algorithms, combined with big data and machine learning technology, this paper proposes an improvement method. During the research process, the parameter configurations of the two recommendation algorithms, SVD and NMF, are optimized using GridSearchCV. The experimental results show that the optimized SVD algorithm outperforms the NMF and the benchmark algorithm in terms of root mean square error (RMSE) and mean absolute error (MAE) indexes, and exhibits high recommendation accuracy. The study concludes that the optimized recommendation algorithm provides more accurate recommendations on e-commerce platforms, enhancing user satisfaction and platform conversion rates.
Application and Future Development of Big Data Technology in Intelligent Transportation Systems
Authors: Yang Yuhe
Published: February 2025

In this research plan, we employ a literature review approach to summarize the current state and development trends of big data technology in intelligent transportation systems. By collecting and analyzing relevant literature from both domestic and international sources, we organize case studies of big data applications in intelligent transportation systems. This allows us to analyze the shortcomings of existing research and identify the challenges that will be faced in future development. Additionally, we can propose future research directions and key focuses. Through this research, we hope to provide valuable assistance for future studies in this field.
Machine Learning in the Application of Fraudulent SMS Filtering
Authors: Huang Yihe
Published: February 2025

Electronic fraud SMS is a common network security threat, which brings huge economic and privacy risks to users. To effectively address this problem, this paper studies the electronic scam SMS filtering method based on machine learning. By analyzing and processing a large number of SMS datasets, we propose a classification model that comprehensively considers both textual and behavioral features to identify and filter e-scam text messages. The experimental results show that our method achieves significant improvements in accuracy and efficiency and provides better security for users.
Study on the Volatility of New Energy Index Based on ARMA-GARCH Model
Authors: Gao Yihan
Published: February 2025

New energy industry is an emerging industry in China with natural environmental protection attributes. However, new energy stock prices have fluctuated frequently in recent years, destabilising the market and affecting investment. Therefore, the article selects the daily closing prices of CSI New Energy Index from 1 August 2019 to 1 July 2024, and establishes a GARCH (1, 1) model through Eviews 13.0 to study the volatility of new energy stock prices in China. The results show that the new energy stock price return series has volatility aggregation and exhibits the characteristics of sharp peaks and thick tails.
Analysis of Parallel Optimisation Strategies Based on MapReduce Models
Authors: Wu Shuhang
Published: February 2025

The aim of this paper is to provide an in-depth analysis of parallel analysis strategies for MapReduce models, and to explore how to improve the overall performance by optimising task allocation and scheduling, improving data locality and increasing node utilisation. The research methodology includes an analysis and overview of existing MapReduce frameworks and proposes a series of improvement strategies. These strategies improve the utilisation of computing resources by adjusting the granularity of task division, optimising data slicing and distribution, and improving task scheduling algorithms. The results show that by reasonably optimising the parallel analysis strategy of the MapReduce model, its performance in large-scale dataset processing can be significantly improved, especially in resource-constrained distributed environments. Ultimately, this paper concludes that although the MapReduce model has been used in more mature applications, there is still much room for optimising its parallel strategy when facing larger scale and complex data processing tasks. In the future, further research should be devoted to finer-grained task scheduling, dynamic resource allocation, and more efficient fault-tolerance mechanisms to continuously improve the parallel processing capability of the MapReduce model.
Research on the Evaluation Model of Automotive Talents Based on Factor Analysis Method
Authors: Shi Yingqi , Guo Chao
Published: February 2025

With the rapid development of the automotive industry, the demand for high-quality talents is increasing day by day. This article uses factor analysis method to construct an automotive talent evaluation model, aiming to help enterprises select and cultivate talents more effectively through the analysis of talent characteristics. The research results indicate that professional basic theories, professional technical skills, innovative thinking ability, project management skills, and market & industry development awareness are key factors affecting the identification evaluation of automotive talents.
Artificial Intelligence Empowered Reforms in Economics Education
Authors: Wan Yingliang , Wan Xin , Huang Liqian , Zhao Yiheng
Published: February 2025

With the rapid development of Artificial Intelligence (AI) technologies, economics education is facing profound opportunities and challenges for transformation. The widespread application of AI not only provides new impetus for updating educational content and innovating teaching methods in economics but also drives a deep transformation of educational models. Traditional economics education models are gradually unable to meet the demands of contemporary development, particularly exhibiting significant shortcomings in personalized teaching, interdisciplinary integration, and the cultivation of practical skills. This paper conducts an in-depth analysis of the specific applications of AI technologies in economics courses, exploring their far-reaching impacts on updating teaching content, innovating teaching methods, professional development of educators, and the cultivation of student competencies. The article begins by reviewing the current state of economics education, highlighting deficiencies in traditional teaching methods, course content, and evaluation systems. Subsequently, leveraging the advantages of AI technologies, it proposes educational reform pathways, including the establishment of interdisciplinary curricula, personalized learning pathways, and the enhancement of practical components. Finally, the paper envisions potential future directions for economics education empowered by AI, particularly focusing on how technological means can facilitate the comprehensive improvement of students' data analysis and modeling abilities, innovative thinking, and practical skills. AI serves not only as a technological tool but also as a catalyst for the comprehensive reform of economics education, leading future educational models toward greater personalization, flexibility, and interactivity.
General Multi-modal Image Fusion Transformer Network
Authors: Dong Ao , Wang Zhi
Published: February 2025

In the field of image fusion, images obtained from multiple different sensors are fused into one image that contains more complementary information and fewer redundant features to produce a single image with enhanced information. In order to be accurate and concise for different Fusion tasks, this paper proposes a General end-to-end Multi-modal image fusion Transformer Network (GMTN). A two-branch feature extraction module is designed, which integrates the self-attention mechanism of the improved convolutional neural network CNN and Transformer to extract the short-range features and remote dependencies of the image respectively, and take into account various information of the fused image in a more comprehensive way. A large number of experimental results show that the proposed method achieves the same or even better performance than the existing image fusion on a variety of multi-modal medical image data sets, and also achieves good results on infrared and visible light, multi-focus and multi-exposure image fusion tasks.
Applications and Challenges of Artificial Intelligence in International Trade and Logistics: Current Status, Future Developments, and Policy Recommendations
Authors: Tao Hong , Wan Yingliang , Huang Liqian , Zhao Yiheng
Published: February 2025

With the rapid development of Artificial Intelligence (AI) technology, global economic models and market structures are undergoing profound transformations, particularly in the fields of international trade and logistics, where the application of AI is becoming a key driver for improving efficiency, reducing costs, and enhancing customer experience. Traditional international trade and logistics systems face multiple challenges such as supply chain opacity, high transportation costs, information asymmetry, and low operational efficiency. The introduction of AI technology, especially in areas such as big data analytics, machine learning, automation systems, and intelligent decision support, has gradually demonstrated its powerful potential in addressing these issues. This study aims to explore the specific applications of AI in international trade and logistics, as well as its role in driving the digital transformation of global supply chains. By analyzing the practical applications of AI in key areas such as supply chain management, trade data processing, and intelligent logistics, this paper seeks to provide valuable theoretical support and practical guidance for relevant enterprises and policymakers to promote industry development and enhance corporate competitiveness. To achieve this goal, the study adopts a case study approach, combining current industry data and AI technology development trends to comprehensively assess the current state and future potential of AI applications in international trade and logistics.
Research on Intelligent Diagnosis of Motion System Injuries Based on Gait and Kinematic Parameters of Multimodal Data
Authors: Cheng Dangwei , Zhuo Guangping , Miao Xinpeng , Ma Pengyuan , Ma Fei
Published: February 2025

This study aims to explore the use of the Transformer model for analyzing multimodal and multidimensional gait data, validating the effectiveness of the multi-head attention mechanism in case summarization and disease diagnosis. A retrospective case series design was adopted, involving 1200 samples collected from the Gait Laboratory of the Second Affiliated Hospital of Shanxi Medical University. The data include gait information from patients with osteoarthritis, anterior cruciate ligament injuries, and meniscus injuries, as well as healthy volunteers. Each sample encompasses foot pressure distribution, pressure intensity distribution, and motion data of the ankle, knee, and hip joints, along with labeled disease categories for model training and testing. Key data of clinical interest were curated into datasets to compare the performance of the Transformer model, based on the multi-head attention mechanism, with conventional convolutional neural networks in training and diagnosing conditions from gait data. The results demonstrate that the Transformer model achieves high diagnostic accuracy in gait analysis, with precision reaching approximately 95%. This study proves the feasibility of AI-based gait diagnosis using the Transformer model, providing valuable diagnostic references for orthopedic clinicians.
A Myopia Degree Prediction Model for Children and Adolescents Based on Follow-up Data with Different Time Intervals
Authors: Ma Pengyuan , Ma Shukui , Zhang Guowei , Ma Fei , Zhuo Guangping
Published: February 2025

Myopia has become a global public health issue, and existing research primarily focuses on predicting the future spherical equivalent (SE) of children and adolescents based on ocular optical data. However, electronic medical record (EMR) data often exhibit characteristics such as multi-dimensionality, irregular time series, missing values, and non-uniform time intervals, which present significant challenges for prediction. To address these issues, this paper proposes a prediction model named IST-xLSTM, which utilizes a temporal dense prediction module to handle missing data and overcome long-range dependencies and irregular time intervals. Additionally, a hierarchical temporal attention mechanism is introduced to extract both local and global features along the irregular time dimension, enhancing prediction accuracy. Experimental results show that the mean absolute error on the validation set is 0.216 ± 0.176 (D), which is significantly lower than the clinically acceptable prediction threshold of 0.50 (D).
Design of Channel Estimation and Channel Equalization Scheme for Massive MIMO-OFDM Communication System
Authors: Sun Jing , Md Johar Md Gapar , Tham Jacquline
Published: February 2025

The combination of massive MIMO (massive multiple input multiple output) technology and OFDM (orthogonal frequency division multiplexing) technology has become one of the key technologies in modern wireless communication systems. With the increase in the number of antennas and the complexity of communication channels, channel estimation and channel equalization have become important technical means to ensure system performance. In this paper, a channel estimation method and an adaptive equalization method based on the guide frequency signal are proposed to address the problems of channel distortion and inter-symbol interference (ISI) in massive MIMO-OFDM systems by designing an efficient channel estimation and equalization strategy in order to improve the system performance. In this paper, we first establish the channel model, design the system frame diagram, and analyze the data processing flow, then compare several channel estimation and equalization methods, propose a channel estimation method based on the guide signal, and select an adaptive equalization method for performance optimization. The proposed scheme has a large potential value in reducing the bit error rate (BER), improving the system capacity and anti-interference capability.
Application of Data Science and Machine Learning Algorithms in Intelligent Recommendation System
Authors: Wang Yuxuan
Published: February 2025

Intelligent recommender systems use data science and machine learning algorithms to significantly improve recommendation accuracy and personalization through preprocessing, feature engineering and user profile construction. The study proposes solutions for challenges such as data sparsity and cold start, and experimentally verifies the effectiveness of algorithms such as XGBoost. Meanwhile, the potential of deep learning models and integrated learning in recommendation systems is explored. The study shows that the integration of data science and machine learning algorithms strengthens the data processing and pattern recognition capabilities and promotes the optimization and innovation of recommendation algorithms.
Social Network Rumor Propagation Model Considering Blockchain Content Consensus
Authors: Zhang Can
Published: February 2025

In order to better explore the information dissemination characteristics of social networks, a trust evaluation mechanism is constructed based on the consensus mechanism and incentive mechanism of blockchain, and the participation consensus probability function is introduced, and a rumor propagation model of blockchain social networks is proposed. In the experimental simulation, the influence of trust degree on consensus participation probability and rumor acceptance probability is quantified, and the influence of this model on rumor propagation is explained through the analysis of consensus probability and propagation probability, and the comparison with the existing model is made. The experimental results show that the propagation range of the proposed model is reduced by 12%-41% compared with the classical model, which verifies that the proposed model can effectively suppress rumor propagation.
Sistem Pewarisan Hukum Adat Bali Terhadap Kedudukan Perempuan Pada Masyarakat Adat Bali
Authors: UDYTAMA I WAYAN WAHYU WIRA , DIANTI IDA AYU INDIRA SITA
Published: February 2025

Masyarakat adat Bali menganut sistem kekeluargaan patrilineal, yang berarti bahwa harta diwarisi oleh garis keturunan laki-laki. Dalam masyarakat Bali, terdapat sistem kekeluargaan patrilineal di mana hanya anak laki-laki yang diakui memiliki hak waris, sementara anak perempuan tidak mendapatkan hak yang sama. Penelitian ini bertujuan untuk menganalisis dan memahami secara mendalam kedudukan hak waris anak perempuan dalam hukum adat Bali. Metode Penelitian ini menggunakan metode penelitian normatif dengan pendekatan perundang-undangan dan pendekatan konseptual. Sistem ini menetapkan bahwa anak laki-laki memiliki hak utama untuk menerima warisan, sementara anak perempuan mungkin hanya menerima bagian kecil atau bahkan tidak sama sekali. Sehingga ahli waris dalam masyarakat hukum adat Bali ialah anak laki-laki saja, sedangkan anak perempuan tidak diperkenankan untuk mewaris.
IMPLIKASI PUTUSAN MAHKAMAH KONSTITUSI NOMOR 168/PUU-XXI/2023 TERHADAP PERJANJIAN KERJA WAKTU TERTENTU (PKWT)
Authors: WIRADHARMA SUMERTAJAYA I KETUT SATRIA , PURNAMA DEWI KADEK ARY , SWETASOMA COKORDA GDE , HUTAMA I DEWA MADE ADHI
Published: February 2025

Pengaturan mengenai PKWT dalam Undang-Undang Cipta Kerja oleh sebagian masyarakat dirasa tidak memberikan perlindungan kepada pekerja karena batas waktu PKWT menjadi lebih panjang dan adanya ketentuan bahwa jangka waktu PKWT didasarkan atas kesepakatan antara pekerja dan pemberi kerja. Undang-Undang Cipta Kerja tersebut dianggap bertentangan dengan konstitusi sehingga terhadapnya dilakukan pengujian. Permohonan pengujian terhadap ketentuan PKWT dalam Undang-Undang Cipta Kerja diajukan kepada Mahkamah Konstitusi pada tahun 2013 dengan Nomor Register 168/PUU-XXI/2023, yang kemudian diputusan oleh Mahkamah Konstitusi pada tanggal 31 Oktober tahun 2024. Putusan Mahkamah Konstitusi ini menyebabkan terjadinya perubahan terhadap mengaturan mengenai PKWT di Indonesia.
Dalam penelitian ini penulis menggunakan metode penelitian hukum normatif dengan pendekatan Perundang-undangan (statute approach) dan pendekatan kasus (Case Approach), selanjutnya hasil yang ditemukan dalam penilitian ini digambarkan secara deskriptif.
Undang-Undang Nomor 6 tahun 2023 Tentang Cipta Kerja mengatur ketentuan baru mengenai PKWT, pengaturan bersebut dimohonkan pengujian terhadap UUD NRI 1945 pada Mahkamah Konstitusi. Mahkamah Konstitusi dalam Putusan Nomor 168/PUU-XXI/2023, mengabulkan permohonan para pemohon untuk sebagian. Terkait dengan permohonan pasal-pasal yang mengatur mengenai PKWT Mahkamah Agung memutus Pasal 56 ayat (3) dan Pasal 57 ayat (1) dengan putusan inkonstitusional bersyarat. Pasca Putusan Mahkamah Konstitusi tersebut pengaturan mengenai jangka waktu PKWT menjadi lebih jelas, Mahkamah Agung memberikan pemaknaan terhadap ketentuan Pasal 56 ayat (3) bahwa jangka waktu PKWT paling lama 5 (lima) tahun termasuk jika terdapat perpanjangan PKWT, jangka waktu PKWT tidak dapat didasarkan pada perjanjian kerja yang disepakati oleh pekerja dengan pemberi kerja. Selain itu putusan Mahkamah Konstitusi menegaskan bahwa PKWT harus dibuat secara tertulis dengan menggunakan bahasa Indonesia dan huruf latin.
Impacto del consumo de cocaína en el síndrome coronario agudo
Authors: Saltos Ardila Julissa Andreina , Jaime Mendoza Marjorie Alexandra , García Calzadilla Anileisy , Ferrín Bravo Víctor Teófilo
Published: February 2025

El consumo de cocaína sigue siendo un problema de salud pública significativo a nivel mundial. Esta droga recreativa ilícita muy utilizada, está asociada con graves complicaciones cardiovasculares. Este estudio se centra en el impacto del consumo de cocaína en pacientes con Síndrome Coronario Agudo (SCA), y las intervenciones preventivas para reducir los riesgos asociados. El objetivo del estudio fue determinar si el consumo de cocaína asociado a un SCA tiene un impacto en el pronóstico de mortalidad del paciente en comparación con el SCA sin consumo de cocaína. Este estudio se realizó bajo un enfoque mixto, que utilizó una metodología descriptiva, observacional y ambispectivo, que realizó un muestreo no probabilístico por conveniencia debido a la naturaleza específica de la población y el contexto hospitalario con pacientes menores de 50 años tratados en el servicio de cardiología del Hospital Universitario de la UAI, internados en la Unidad Coronaria con diagnóstico de Síndrome Coronario Agudo (SCA) y consumo de cocaína desde diciembre de 2012 hasta diciembre de 2018. Se compararon las características clínicas y cardiológicas de 39 pacientes con SCA y antecedente de consumo de cocaína con las de 39 pacientes con SCA sin antecedente de consumo de cocaína. Los resultados mostraron una diferencia significativa del 11,54% en la mortalidad de los pacientes con SCA asociado al consumo de cocaína (SCA-ACC), con tres fallecimientos intrahospitalarios y seis extrahospitalarios y se identificaron factores de riesgo y complicaciones asociados con el consumo de cocaína.
Implementasi Pendidikan Demokrasi Melalui Musyawarah Besar (MUBES) Ormawa Politeknik Harapan Bersama 2024/2025
Authors: Prasetya Putra Nugraha  , Lourensius Hendra Putra
Published: February 2025

Demokrasi merupakan sistem kehidupan berbangsa dan bernegara yang dianut di Indonesia yang mana kekuasaan berada di tangan rakyat. Pelaksanaan Demokrasi juga berlaku pada dunia pendidikan tinggi dengan subjek pelaksana adalah mahasiswa. Salah satu bentuk penerapan pendidikan demokrasi di perguruan tinggi adalah Musyawarah Besar (Mubes) Organisasi Mahasiswa (Ormawa). Mubes Ormawa Politeknik Harapan Bersama 2024/2025 merupakan forum tertinggi lembaga kemahasiswaan selama satu periode tahun akademik. Metode penelitian yang digunakan adalah kualitatif dimana data tersebut akan dianalisis secara deskriptif. Mubes Ormawa Politeknik Harapan Bersama 2024/2025 yang diselenggarakan oleh BPM berfungsi untuk mengevaluasi serta memonitoring keberadaan unit-unit mahasiswa yang ada, sekaligus sebagai forum untuk menentukan arah kebijakan Ormawa ke depan. Oleh karenanya keberadaan Mubes Ormawa Politeknik Harapan Bersama 2024/2025 ini memberikan pembelajaran bagi para aktivis Ormawa Politeknik Harapan Bersama dalam mengambil langkah dan keputusan organisasi.
Study the impact of integrating blockchain and neural network technologies in predictive models: A survey
Authors:   Electrical and Electronic Department, Faculty of Engineering, University of Zawia - Libya, Marimi Rashed M
Published: February 2025

The integration of Blockchain technology with Artificial Neural Networks (ANNs) presents a promising advancement in predictive modeling by enhancing security, transparency, and accuracy. Blockchain ensures data integrity through decentralized and tamper-proof storage, while ANNs leverage deep learning algorithms for improved pattern recognition and decision-making. This paper explores the impact of combining these technologies, particularly in critical sectors such as healthcare, finance, and cybersecurity.Despite their advantages, several challenges hinder their seamless integration. Blockchain introduces computational overhead, scalability limitations, and regulatory concerns, while ANNs require vast datasets, making them vulnerable to adversarial attacks and biased learning. This study highlights solutions such as federated learning, hybrid blockchain architectures, and optimized cryptographic techniques to address these challenges. Future research should focus on enhancing computational efficiency, developing scalable frameworks, and establishing regulatory standards to facilitate broader adoption. By overcoming these barriers, Blockchain-ANN integration can revolutionize predictive analytics, providing secure, efficient, and intelligent decision-making systems across various industries.
Keywords: Blockchain, Artificial Neural Networks (ANNs), Predictive Modeling, Security, Scalability, AI Integration
Transformations of youth life in the digital age: work, knowledge and subaltern identities
Authors: González Estrada Yuleidys , Rosique Cárdenas Iramis , Manzano Castillo Yohandry
Published: February 2025

Introduction: The study examined the influence of digital technologies on the configuration of subjectivity and youth identities in Cuba. It started from the concept of “technologically encoded sociality” to analyze how digital capitalism transformed the perception of success and autonomy in youth. It addressed the relationship between the labor market, access to information, and the processes of domination/emancipation of subaltern identities.Development: The analysis included three main areas: the impact of digitization on youth employment, the circulation of knowledge and the transformation of subordinate identities. It became clear that young people faced job insecurity, despite the growth of digital opportunities. In terms of access to information, interaction on social networks and digital platforms changed the way young people consumed and generated knowledge, promoting new learning dynamics. The study also highlighted that self-help and entrepreneurship content influenced the perception of success, prioritizing economic growth and self-sufficiency over emotional stability.Conclusion: It was concluded that digital technologies reconfigured youth identity in Cuba, establishing new dynamics in the workplace, socially and affectively. However, it was noted that digitization did not operate neutrally, but was permeated by market logic, affecting the aspirations and behaviors of young people.