bluuebunny/crossref_metadata_2025 huggingface dataset:
Adherencia al tratamiento antihipertensivo y calidad de vida en instituciones de segundo nivel de atención
Authors: Sahury Sara , Castellanos Ulloa Andrea Poleth , Díaz Valle Deysi Julissa , Bonilla Sinthia , Maradiaga Ramón , Maradiaga Edna J.
Published: January 2025

Introducción: La adherencia al tratamiento es un problema de salud pública, con importancia en las terapias de enfermedades crónicas. La adherencia deficiente a tratamientos a largo plazo compromete la efectividad del tratamiento e influye directamente en la calidad de vida. Objetivo: Establecer la relación que existe entre adherencia al tratamiento y la calidad de vida de pacientes adultos hipertensos en dos hospitales de segundo nivel. Métodos: Estudio descriptivo transversal, con análisis de asociación, muestreo no probabilístico a conveniencia, se seleccionó muestra utilizando programa Open Epi en línea, resultando 206 pacientes que cumplieron criterios de inclusión. La adherencia se midió con test de Morisky- Green-Levine y la calidad de vida con MINICHAL. Los datos fueron analizados en SPSS Statistic 21.0; análisis univariado, calculando frecuencias, porcentajes y el bivariado (asociación entre adherencia/factores de adherencia y calidad de vida), se aplicó prueba del chi cuadrado y modelo de regresión logística binaria. Contó con aprobación ética. Resultados: La población estudiada fue de predominio femenino, entre 51-60 años, alfabeta, casados, pobres. El 71.4% (147) eran adherentes al tratamiento. La calidad de vida fue media-alta en 80.1% (165). Se presentó asociación entre la variable adherencia y escolaridad (p<0.01), nivel de pobreza (p<0.01), uso de otros fármacos (p<0.01). No se encontró asociación entre adherencia y calidad de vida. (p <0.1) Discusión: La adherencia al tratamiento fue alta. Los adherentes al tratamiento tenían calidad de vida media-alta, los no adherentes calidad de vida baja; los pacientes con polifarmacia, mayor escolaridad y nivel socioeconómico tienen mejor adherencia al tratamiento.
EcoResponsive Environments
Authors: Odeleye NezHapi-Dellé
Published: January 2025

This review looks at ‘EcoResponsive Environments: A Framework for Settlement Design’ which proposes an exciting new integration of design thinking and skills across scales – extending the lucidity of the ‘Responsive Environments’ urban design approach beyond cities – to the design of wider settlements and going beyond human needs to embrace the topographical and ecological features of natural systems.
Concentrated growth factor scaffold-based pulpotomy of permanent molars with symptomatic irreversible pulpitis
Authors: Harith Arthi K. , Koteeswaran Vishnupriya , Kowsky Dinesh , Velmurugan Natanasabapathy , Nandini Suresh
Published: January 2025

Objectives: Pulpotomy is a minimally invasive procedure that aims to retain the vitality of the radicular pulp by removing the inflamed coronal pulp tissue. This case series presents the successful management of symptomatic irreversible pulpitis by pulpotomy with concentrated growth factor (CGF) scaffolds.Methods: Six permanent mandibular molars with a diagnosis of symptomatic irreversible pulpitis were included. Under Local anesthesia and rubber dam isolation, caries were excavated using high-speed bur under coolant. Full coronal pulpotomy was done and hemostasis was achieved. CGF membrane was prepared and placed over the radicular pulp and layered with Biodentine (Septodont). Final restoration of type IX glass ionomer cement and bulk fill composite resin was placed. Patients were assessed for various clinical and radiographic parameters at intervals of 1 week and 3, 6, and 12 months. Five patients fulfilled the success criteria at the end of 1 year.Results: Pulpotomy is considered an alternative treatment modality for root canal treatment in symptomatic irreversible pulpitis aiming at alleviating symptoms and maintaining vitality. CGF scaffold when used as a capping material acts as a reservoir for growth factors with anti-inflammatory properties and enhances healing.Conclusions: Scaffold-based pulpotomy can be considered a biological approach to healing inflamed pulp.
Shall We Discuss “The Thing” that is not Supposed to be Discussed? Toward a Rational Approach to National Education in Hong Kong
Authors: Lin Jason Cong
Published: January 2025

Objective: Since the implementation of the National Security Law in Hong Kong in 2020, national education that aims to cultivate Hongkongers’ sense of belonging to the Chinese nation has been widely promoted, yet remains controversial. This study aims to examine how textbooks in Hong Kong promote different elements of national education.

Methods: This study uses summative content analysis to examine how textbooks for the newly created subject of Citizenship and Education Development in Hong Kong promote different elements of national education.

Results: Findings show that four elements of national education are promoted as non-controversial, have a correct answer, and are essential for the nation's rejuvenation and for being a good citizen.

Conclusion: the paper discusses the limitations of this way of teaching national education and argues for adopting a rational approach in Hong Kong.
Research on the Construction and Teaching Application of the STEP Engineering Education Model in Cultivating Excellent Engineers
Authors: Hong Siyao
Published: January 2025

Objective: To address the urgent demand for high-level engineering talents in the new era, and in response to engineering education reform trends and accreditation requirements, this paper focuses on the educational philosophies of world-class universities, particularly drawing from the globally recognized CDIO (Conceive, Design, Implement, Operate) framework. Based on the characteristics and practical experiences of a university’s engineering education, we propose the STEP education model (i.e., Software, Theory, Experiment, Project) to achieve systematic enhancement in engineering education and effectively cultivate the comprehensive abilities of engineers.

Methods: The STEP model is structured around project-driven learning, seamless integration of theoretical and experimental teaching, and a curriculum structure supported by software tools. It aims to enhance students’ learning outcomes through innovative teaching approaches, including science-education integration, virtual-real fusion, and competition-driven learning.

Results: Practical applications of the STEP education model in several course systems at the university demonstrate its effectiveness in enhancing students' engineering practice abilities and innovative thinking.

Conclusion: Providing strong support for the cultivation of excellent engineering talent, the STEP education model has proven effective in enhancing students' engineering practice abilities and innovative thinking, which are essential for meeting the demands of the new era and the trends in engineering education reform and accreditation requirements.
TINJAUAN HUKUM ISLAM TERHADAP METODE BIBIT BEBET BOBOT DALAM MEMILIH PASANGAN SUAMI ISTRI DI DESA PLUMBON KECAMATAN MOJOLABAN KABUPATEN SUKOHARJO
Authors: Khoiruddin Dzikri , Syamsuddin S , Baehaqi B
Published: January 2025

Marriage is a sacred worship for muslims, in its implementation have rules that have been described in Al-Qur’an and Hadits. To achieve a harmonious marriage and not against islamic law, then there is a need for good marriage knowledge. One of the science of marriage is to choose a good partner, among them by choosing lineage, rank, beauty, partner’s religion. Islam regulates marriage not only for the satisfaction of sex relations, but aim to make a family that is sakinah,  mawaddah, warahmah. In creating a harmonious and ideal family, javanese people have a bibit bebet bobot method in order to choose his life partner. In this research the author uses Qualitative Research. By using Descriptive Qualitative method by explaining the conditions in the field with data obtained through interviews, observation and documentation. Data analysis using data reduction method, data presentation and conclutions from research result. The result of the author’s research indicate that (1)The bibit bebet bobot method already existed in the days of Kartasura kingdom. Bibit means the origin of the partner, bebet comes from the word “bebetan” in javanese means clothing (economic and social caste), bobot means self-quality (education). (2)Islamic law reviews that the bibit bebet bobot method is in accordance with islamic sharia, as in islamic law there is kafa’ah. (3)The bibit bebet bobot method in modern times is still considered relevant but with the development of new languages or terms but with the same purpose.
PENYEBAB MENINGKATNYA PERKAWINAN DI BAWAH UMUR DI KANTOR URUSAN AGAMA KECAMATAN KEBAKKRAMAT TAHUN 2019-2021
Authors: Widiyati Wahyu , Syamsuddin S , Baehaqi B
Published: January 2025

Underage marriage is a marriage or contract that can guarantee that a man and a woman have each other and can have husband-wife relations and that marriage is carried out by a person (potential husband, prospective wife) who has not reached the age specified by law. The current law in Indonesia that has been determined by the government. Namely under the age of 19 for men and women in accordance with Law Number 16 of 2019. This study uses a qualitative descriptive method, namely research conducted to examine an object, a condition or phenomenon, a group of people, with natural or real conditions. Trying to tell the current problem solving based on the data. The right data needs to be determined by informants who have competence and are in accordance with data needs (purposive). This study aims to describe in full and in detail the events or various phenomena studied regarding underage marriages. The results showed that the cause of the increase in underage marriages in the Religious Affairs Office of the Kebakkramat District was the concern of the parents because the child's relationship with the boyfriend was too close for fear that an act prohibited by the provisions of Islamic law would occur, namely adultery and other disgraceful acts. Another cause is because they are already pregnant, the parents marry off because their children are already working, they are considered ready to become husbands or heads of families or conversely ready to become wives or housewives. For couples who are not married, they should think more carefully about getting married, avoiding underage marriages. In order to realize the purpose of marriage, namely to form a happy and eternal family or household based on Belief in the One and Only God.
PERAN KEPALA KANTOR URUSAN AGAMA KECAMATAN TASIKMADU KABUPATEN KARANGANYAR DALAM MENANGGULANGI PERKAWINAN DIBAWAH UMUR
Authors: Abubakar Kirana , Wibowo Muhammad Kurniawan Budi , Baehaqi B
Published: January 2025

The main problem in this study is related to underage marriage that occurs in the Tasikmadu sub-district, along with how to overcome it carried out by the Head of KUA in minimizing underage marriage. This study aims to determine (1) the condition of underage marriage in Tasikmadu District, Karanganyar Regency, (2) The Role of the Head of the Office of Religious Affairs in preventing underage marriage. This research uses qualitative methods. Qualitative research is a continuous research process so that the data collection and data analysis stages are carried out simultaneously during the research process. Data collection was carried out by interview method to the Head of KUA Tasikmadu. The location of the research was carried out at the Office of Religious Affairs in Tasikmadu District, Karanganyar Regency. The results of research conducted at the Office of Religious Affairs of Tasikmadu District, Karanganyar Regency are factors that cause underage marriage to occur, there are also reasons that cause underage marriage that often occurs in the community of Tasikmadu District, Karanganyar Regency are economic factors, factors that have loved each other, parental factors and the most important factor is pregnancy out of wedlock. The role of the Office of Religious Affairs in tackling underage marriage has been carried out in accordance with the procedure, namely by conducting socialization to the community through routine studies related to marriage, besides that the KUA also conducts socialization through premarital guidance for teenagers how to build a good household. Implementation of the marriage law regarding the age limit for marriage and in cooperation with youth leaders and village officials or other agencies.
PENAFSIRAN PEMBERIAN DISPENSASI PERKAWINAN DI BAWAH UMUR DI PENGADILAN AGAMA KABUPATEN SUKOHARJO TAHUN 2019 - 2021
Authors: Munawir M , Wibowo Muhammad Kurniawan Budi , Baehaqi B
Published: January 2025

Interpretation is a method of legal interpretation that provides an easy-to-understand explanation of the text of the law so that the scope of the rule can be determined in relation to certain events. Judge's  interpretation or interpretation is one of the processes that must be taken by the court in order to obtain certainty regarding the meaning of statutory law. Marriage dispensation is an exception to the rule or law that is given to applicants to get married but are not old enough in accordance with the terms and conditions of the applicable law. The author in this study used a qualitative descriptive method, the data collection method is original data from the Religious Courts of  Sukoharjo Regency, both about annual reports and direct interviews from existing judges in dealing with the problem of interpreting the dispensation of underage marriages. The data was then analyzed descriptively qualitatively, namely to describe what was happening at that time. To test the validity of the data is done through Editing and Classifying. The results of the study show that the interpretation of the granting of underage marriage dispensation in Sukoharjo Regency in 2019-2021 is carried out by submitting a marriage dispensation application stating that the marriage must still be carried out due to an urgent and emergency situation that must be married or handled immediately. The factors that led to the interpretation of the granting of dispensation for underage marriages, namely pregnancy out of wedlock, parental factors, educational factors, economic factors and of course the Covid 19 factor in 2020 which stopped all forms of human activity or what are known to be restrictions within the scope all sectors of human life.
Advancements in Ultrasound Imaging for Assessing the biological behavior of Hepatocellular Carcinoma
Authors: Shi Di , Li Li
Published: January 2025

Since the advent of contrast-enhanced ultrasound technology in 1968, with the continuous innovation of contrast agents, the increasing refinement of the resolution of ultrasound equipment, and the vigorous development of new imaging technologies, this technology has gradually demonstrated its irreplaceable unique advantages in many fields such as the diagnosis, treatment, and efficacy evaluation of hepatocellular carcinoma (HCC). It can not only provide more accurate medical imaging support, but also is expected to reveal more biological characteristics of HCC, providing a solid basis for personalized treatment decisions in the era of precision medicine.
Changes in Female Labor Supply, Fertility, and Employment Trends
Authors: Chen Yutong
Published: January 2025

Along with the changes of the times, there are different development trends in demographics, labor supply, and employment opportunities in various industries. The serious aging of the population, the lack of labor in the market, and the decline of the fertility rate have been social topics with serious impact. The female employment rate is also deeply related to it. However, the participation of women in various industries is closely related to their biological and social characteristics, which leads to different trends in the future development of each sector. Gender differences are unavoidable in the social selection process for employment, where family structure, aging population, socio-demographic structure, and salary distribution are all issues that cannot be ignored. On the other hand, the decline of the fertility rate and the female employment rate are closely related, and this relationship will have a profound impact on labor productivity, consumption, industry, and the demographic structure of society.
Teaching Design of Who Says Women Enjoy Leisure from the Perspective of Ideological and Political Education
Authors: Jiang Huanru
Published: January 2025

Compulsory Education Art Curriculum Standards (2022 edition) emphasizes that art curriculum should be based on moral education as the fundamental task, and junior high school music education as an important gateway to moral education in middle school, exploring the ideological and political elements of music curriculum is a far-reaching and significant work. Through research, it is advantageous to promote ideological and political education in the opera art course. The opera art contains excellent traditional music culture, condenses the traditional virtues of the Chinese nation, and integrates the aesthetic spirit of Chinese art. Taking the drama course Who Says Women enjoy Leisure in junior high school as an example, this paper analyzes and excavates the ideological and political elements of "Moderation and harmony", "freedom and equality", "family and country feelings" and "cultural confidence" contained in the work from multiple perspectives, designs a variety of practical activities to guide students to participate, and proposes the feasible methods to practice curriculum ideological and political teaching in junior high school drama as follows: Teachers should strengthen their own moral cultivation, broaden professional knowledge, be good at exploring ideological and political elements to enrich teaching content, use a variety of teaching methods to stimulate students' interest in learning, and build a subtle and humane teaching process.
The Impact of Building Material Modeling on Enhancing Building Sustainability (Carbon Emissions): A Case Study of a Residential Building in Basilia
Authors:   MSc. in Building Information Modeling and Management, Syrian Virtual University, Damascus, Syria, Mary Mary ,   Lecturer Professor, Building Information Modeling and Management Master, Syrian Virtual University, Damascus, Syria,   Lecturer Professor, Al-Rasheed International Private University, Damascus, Syria, Khalil Naoras , Kadi Alaa J
Published: January 2025

This study addresses the impact of modeling building materials on improving building sustainability by analyzing a case study of a residential building in the Baselia area of Damascus, which has experienced the removal of orchards, leading to negative environmental impacts. The research focuses on evaluating the carbon footprint of the building materials used in the structure and cladding, utilizing Autodesk Forma to analyze life cycle and energy efficiency. The study includes an analysis of the impact of five different building materials on carbon emissions during the stages of production, transportation, installation, use, and disposal. Results show that composite steel has the highest carbon emissions compared to other materials, while wood materials, such as timber frame and mass timber, have the lowest emissions. For internal cladding, the differences between materials were relatively minor. The study recommends selecting building materials with lower environmental impact and enhancing energy efficiency, which contributes to reducing carbon emissions in the construction sector and supports achieving sustainability goals.
The Impact of Building Material Modeling on Enhancing Building Sustainability (Shadow and Lighting): A Case Study of a Residential Building in Basilia
Authors:   MSc. in Building Information Modeling and Management, Syrian Virtual University, Damascus, Syria, Mary Mary ,   Lecturer Professor, Building Information Modeling and Management Master, Syrian Virtual University, Damascus, Syria,   Lecturer Professor, Al-Rasheed International Private University, Damascus, Syria, Khalil Naoras , Kadi Alaa J.
Published: January 2025

This study examines the impact of building material modeling on enhancing building sustainability through a case study of a residential building in the city of Basilia. The focus is on using Revit 2023 to model the building and analyze how building materials affect its sustainability. The modeling process includes analyzing the shadows cast by architectural elements and studying their impact on the performance of the building materials. Shadow reflections on energy and material efficiency are measured to determine how building sustainability can be improved through material design and distribution adjustments. Additionally, Revit Insight 2025 is used to evaluate the extent to which natural lighting is achieved through the building envelope and to study the impact of materials on lighting quality and energy efficiency. The research addresses how the building benefits from natural lighting and how this can be optimized with appropriate materials to achieve maximum energy efficiency and reduce environmental impact. The study aims to provide a comprehensive model demonstrating how building sustainability can be enhanced through improved modeling of building materials and analysis of their environmental performance. Through these analyses, the research seeks to offer strategies and recommendations for designing more sustainable and energy-efficient buildings.
THE SPECIFIC PRINCIPLES OF FORMATION OF FUTURE TEACHERS’ PROFESSIONAL-SPEECH CULTURE
Authors: Abdizhahankyzy А. Abdizhahankyzy
Published: January 2025

This article is considered the necessary to use the listed principles reflect features ­ of construction of the educational process developing integrative quality of the future teacher personality in the process of foreign language learning.
The significant purposes induce, direct a behavior of people. Thus the person puts before itself the purposes on the basis of requirements, interests or comprehension and acceptance of tasks which are put forward by other people or ­ a society owing to social communication and dependences.                           
Educational function is that maintenance of the future teachers with necessary general and special professionally - pedagogical knowledge, skills inseparably linked with ­ development in students of professional-significant qualities of the person. In the process of ­ studying of the pedagogical theory and school practice future teachers are­ is brought up interest in pedagogical activity, ­ his relation to the subject of pedagogical activity is formed,­  professional ­ activity, such qualities, as communicativity , diligence, a pedagogical step develop.
The Effects of Parenting Styles on Children's Emotional and Social Skill Development: The Mediating Role of Emotion Regulation Skills
Authors: Zheng Jie
Published: January 2025

Children's emotional and social skill development plays a crucial role in their social adjustment and mental health. Studies show that parenting style strongly influences this process, not only directly on the child's behaviour, but also indirectly on their emotional and social skills through emotion regulation. In recent years, scholars have increasingly focused on the mediating role of emotion regulation in parenting styles and children's social skill development, in an attempt to further reveal how parenting styles facilitate or hinder the formation and development of children's social skills by influencing emotion regulation. Therefore, with a particular focus on the mediating role of emotion regulation skills, this study will examine the effects of parenting styles on the development of children's emotional and social skills. Analyzing the effects of various parenting styles on emotion regulation can deepen our understanding of how effective parenting strategies can promote the healthy development of children's emotional and social skills. The study found that authoritative parenting, characterized by warmth and support, positively influenced children's emotional and social skills by enhancing their emotion regulation abilities. On the other hand, authoritarian and neglectful parenting styles were linked to poorer emotion regulation, hindering the development of children's social skills.
Research on Music Therapy for Dementia Patients
Authors: Liu Ziyu
Published: January 2025

Music therapy is a new and mature frontier discipline. Based on the theory and method of psychotherapy, it employs the special physical and mental function of music to help patients, under the guidance of a music therapist, overcome psychological obstacles and improve mental and physical well-being. With the ongoing aging of the population, the number of Alzheimer's disease diagnoses is expected to rise. In the management of dementia among the elderly, music therapy stands out as a valuable non-pharmacological approach, impacting cognition, emotion, and behavior positively. Currently, the application of musical interventions for alleviating cognitive and behavioral symptoms in dementia patients has gained widespread acceptance as an alternative treatment method, with many positive results being achieved. This study explores the therapeutic development of music therapy in treating Alzheimers disease. The main reason music can regulate emotions is that it can trigger emotional reactions and affect an individual's emotional state through various physiological and psychological mechanisms. This article synthesizes existing literature to find that music therapy has specific therapeutic effects on patients, including memory improvement, enhanced cognitive function, and emotional restoration, and presents practical examples of its implementation.
Identification and Disclosure of TPF in International Investment Arbitration: A Perspective from ICSID Jurisdiction
Authors: Zhou ManSing
Published: January 2025

This article delves into the multifaceted role of third-party funding (TPF) in international investment arbitration (ISA), scrutinizing its burgeoning influence and the attendant risks to the arbitration process's integrity. The paper underscores the imperative for legal reforms within the ICSID framework to bolster transparency and fairness by advocating for a more precise definition of TPF, enhancing evidence standards, and emphasizing the transparency of non-profit TPF. It tackles the practical challenges arising from the current ambiguities in TPF definitions and proposes reforms to mitigate the risks of conflicts of interest. The paper's objective is to ensure that arbitration processes remain efficient, fair, and free from undue influence, thereby upholding the integrity and legitimacy of international dispute resolution mechanisms and maintaining public trust in the arbitration's outcomes. This analysis is crucial for understanding the evolving landscape of TPF in ISA and for shaping the future of legal reforms that will safeguard the fairness and efficiency of arbitration proceedings in the international arena.
Tropical Cyclone Trajectory Prediction with Integration of Shallow Convolutional Layer and Bi-LSTM
Authors: Wu Keliang , Zhao Bohan , Yang Yujie , Ouyang Yumo
Published: January 2025

Tropical cyclones are calamitous natural disasters that frequently result in severe economic losses. In order to enhance disaster response and management, as well as to reduce economic and humanitarian losses, it is imperative to forecast cyclones. This paper presents a deep learning approach using a Conv-Bi-LSTM model to forecast cyclone trajectories utilizing the HURDAT2 dataset. By integrating Convolutional layers with Bidirectional LSTM networks, the model effectively captures both spatial and temporal patterns in the data. After comparing with basic RNN, LSTM and GRU, proposed model illustrates better accuracy in trajectory predictions, even with relative complex routes. And thus, the proposed solution possesses potential in cyclone prediction so as to reinforce disaster responsiveness and further management.
Survey of Context-Sensitive Processing on Dialogue Generation Model
Authors: Zhang Qichen , Lei Zhiting
Published: January 2025

In recent years, dialogue generation models have emerged as a prominent area of research, as a crucial role in the domain of natural language processing, garner significant attention from the academic community. Existing dialogue generation models predominantly emphasize human-computer interaction, however, various context-sensitive issues should not be overlooked inherent to the process. Consequently, this paper aims to summarize and categorize these context-sensitive processing issues. Firstly, based on extant literature, an overview of the current landscape of dialogue generation models is provided. Secondly, the definition of "sensitive" is clarified, and relevant scholarly works are briefly reviewed following the definition. Thirdly, previous methods addressing context-sensitive processing within dialogue generation models are directly categorized and their specific methodologies are briefly analyzed regarding this issue. Finally, pertinent research gaps and limitations are identified while future directions for research in dialogue generation models are proposed.
Book Recommendation System
Authors: Yu Zekai , Zhan Yiyan , Liu Daiyang
Published: January 2025

This study presents a personalized book recommendation system designed to assist students in selecting appropriate study materials based on their grade levels and subject preferences. Unlike general AI models such as ChatGPT, our system tailors book recommendations by integrating user feedback and leveraging targeted personalization. The development process consisted of multiple iterations involving user-centered design and evaluation, including surveys, low-fidelity prototype testing, and high-fidelity prototype evaluation. Findings show that the system effectively meets the unique needs of students by providing accessible, relevant, and customized recommendations. The results indicate that our personalized approach improves user satisfaction and addresses challenges that traditional book recommendation systems face, such as lack of relevance and complexity in navigation.
User Experience Improvement Through Personalized Travel Planning: A Study of AI Travel Customization
Authors: Chen Boke , Liu Jingwan
Published: January 2025

The article explores the integration of artificial intelligence (AI) with personalized travel planning, focusing on how AI can enhance the user experience by providing customized itineraries. Travelers today often have many options when planning a vacation, which can lead to situations such as inefficiency or decision overload. We created a prototype for personalized travel planning to help users by using AI to assess user preferences and provide customized travel plans to reduce the load before a trip. User testing, low-fidelity prototypes, and research were all part of the development process. We looked at how AI may expedite trip planning and increase customer happiness by processing user data and offering tailored recommendations in real-time. The results show that the integration of AI in travel planning provides a more intuitive, efficient, and enjoyable experience, allowing users to seamlessly explore destinations that match their interests.
Develop Intelligent Travel Assistant Using OpenAI API to Provide Personalized Services
Authors: Wang Shiqing , Wang Chenjie , Wu Jiahao
Published: January 2025

This article discusses the application of the ChatGPT Model in a travel assistant application. Nowadays, as the world has recovered from the pandemic, demand for tourism has recovered worldwide, whether domestic or international. However, one of the significant dilemmas for travelers before a trip is how to outline a trip formation and plan when it is challenging to know the local area, while travel agencies might be another unnecessary expense. By this chance, we are developing a travel agency application powered by OpenAI that incorporates ChatGPTs functionality inside, providing real-time guidance, destination insights, and highly customized and organized itineraries to help users plan their trips with more convenience and less expenses. This essay will discuss the app's design, AI features, and how ChatGPT enhances the travel planning experience.
Sports Betting: An Application of Machine Learning to the Game Prediction
Authors: Wang Eryi , Yin Xinyi , Li Yao , Wang Tianyu
Published: January 2025

The study investigates the use of machine learning to predict the results of football matches, with its main goal being to enhance the effectiveness of sports betting techniques.An assessment of diverse machine learning methods was carried out by analyzing a comprehensive dataset that included European league games spanning 2008 to 2016, such as Random Forest, Gaussian Process Regression, Logistic Regression, K-Nearest Neighbors, AdaBoost, XGBoost, and LightGBM. Our results revealed that the LightGBM and Ada model exhibited great performance, achieving an accuracy of 52.6% and 52.8% in predicting match outcomes.Moreover, we incorporated the concept of double chances into our analysis and a simulation-based betting strategy was used in our model, demonstrating a 3% profit margin. This study demonstrates a hopeful potential of machine learning. It is very useful in sports analysis and betting. At the same time, the study talks about some limitations. It also suggests directions for future research.
Music Genre Classification: A Comprehensive Study on Feature Fusion with CNN and MLP Architectures
Authors: Li Xiang , Li Fan , Lu Zhi Peng , Yang Zi yue
Published: January 2025

The classification of music genres has been a key focus in the field of music information retrieval (MIR), many researchers are also looking for a number of ways to solve this problem. Early approach Feature-based methods such as Support Vector Machines (SVMs) and K-nearest Neighbors (k-NN) are mainly used for handcrafted features such as Mel frequency cepstrum coefficients (MFCC). As convolutional neural networks (CNNs) are increasingly used to capture complex time-frequency patterns in audio data, the performance and accuracy of music genre classification has been dramatically improved.Recent research advances have been made in integrating attention mechanisms and mixing mechanisms, which further improves the accuracy of the genre classification model. But that's it. Methods often rely on a single type of input data, such as spectrograms or raw audio data, and are therefore limited. They are able to fully capture the multifaceted nature of music.In this research, we propose a novel multi-input neural network architecture that uniquely integrates a CNN for Mel spectrogram processing with a Multilayer Perceptron (MLP) for handling additional feature data extracted from CSV files. This two-branch approach can effectively help us understand music data more comprehensively while processing spectral and feature-based information. The GTZAN dataset was a great help for our experiments, and the details of this part will be explained later. In addition, our model effectively combines the advantages of both CNN and MLP methods, thereby improving the classification accuracy of multiple music genres. And finally, our results show that the system achieves [0.77] accuracy, support [10], recall [0.67], and F1 score [0.65].
MESAVERSE: A Metaverse Enterprise Social Applications Platform
Authors: Liu Luyao , Tsang Lihong , Luo Wenxi , Ouyang Yao , Huang Yue
Published: January 2025

Enterprise Social Computing (ESC) refers to using social networking tools within an organization to facilitate communication, collaboration, and information sharing among employees. While ESC has become a key component in modern enterprises, it still faces several challenges such as privacy and security concerns, integration issues, etc. At the same time, the emergence of technologies such as Artificial Intelligence (AI), Blockchain, Virtual Reality (VR), and Augmented Reality (AR) is revolutionizing the form of enterprises. Enterprises are actively embracing the new trends to remain competitive in the market. This paper focuses on the integration of these technologies within the Metaverse context to enhance ESC while addressing its challenges. This paper introduces various Metaverse Enterprise Social Applications (MESAs) such as mesaConnect, mesaFind, mesaMeet, mesaSolv, and mesaTrain. These applications support social connections, expert matching, private meetings, problem-solving, and personalized training, respectively. The MESAVERSE platform is proposed as an extensible platform that includes various modules, referred to as MESAs, and aims at integrating these modules into a cohesive system and facilitating their future development. MESAVERSE also demonstrates the concept of Enterprise 5.0 by creating an innovative workplace that is focused on the user experience.
An Interdisciplinary Exploration of Concept and Application of Large Language Models
Authors: Ji Zechen
Published: January 2025

Large Language Models (LLMs) have emerged as transformative tools in Artificial Intelligence (AI), fueled by advancements in deep learning. Notably, OpenAI's Generative Pretrained Transformer (GPT) series has showcased their capacity to comprehend and generate human-like text, making them indispensable across various domains. This paper provides a comprehensive exploration of LLMs, encompassing their foundational principles, technical advantages, and multifaceted applications spanning agriculture, medicine, and information security. By elucidating how LLMs revolutionize these sectors through heightened efficiency, accuracy, and innovation, this work unveils their potential to reshape industries and drive technological progress. Additionally, this work delves into forthcoming prospects and potential challenges in LLM development and deployment, concluding with a synopsis of pivotal insights. As LLMs continue to evolve, their integration into diverse fields promises profound implications for human-computer interaction and societal advancement. This paper illuminates the trajectory of LLMs, from their inception to their current prominence, underscoring their pivotal role in shaping the future of AI and fostering responsible innovation.
Research on Industrial Internet Intrusion Detection Based on Deep Learning Algorithms
Authors: Jia Chengbo
Published: January 2025

With the rapid popularization of the Industrial Internet, the connection between industrial control systems and enterprise networks has become increasingly tight, making them primary targets for cyberattacks. This trend not only intensifies the security risks of industrial control systems but also presents new challenges for cybersecurity protection. Deep learning technology in artificial intelligence, with its capability to learn complex problems from unsupervised data, is a powerful tool for protecting the cybersecurity of industrial control systems. This paper explores the foundational theories of Industrial Internet security and intrusion detection, covering basic concepts, major characteristics, and various security threats and risks faced by the Industrial Internet. It further analyzes the limitations of traditional security technologies in the context of the Industrial Internet, including their inadequacies in responding to new threats, particularly their vulnerability to system vulnerabilities and virus attacks. Moreover, the paper introduces the specific applications of three deep learning algorithmsConvolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs)in the security of the Industrial Internet. Through systematic analysis and research, the paper reveals specific cybersecurity issues present in the Industrial Internet and proposes effective methods to address these issues using deep learning algorithms. These findings not only provide new ideas and technical support for contemporary Industrial Internet security protection but also offer valuable insights and a theoretical foundation for future research directions.
Gesture Object Detection and Recognition Based on YOLOv11
Authors: Xu Jian , Chen Heyao , Xiao Xingpeng , Zhao Mengyuan , Liu Bo
Published: January 2025

This article explores the application of YOLOv11 algorithm in gesture recognition field to evaluate its performance in human-computer interaction (HCI). By introducing the YOLOv8 model and corresponding dataset for training, we obtained the confusion matrix predicted by the model, which shows that the model can accurately recognize most gestures, although there are a few cases of misidentification. When the IoU threshold is 0.5, the average accuracy (mAP) of the model steadily improves with the progress of training, indicating that the overall performance of the model in gesture detection tasks has been enhanced. In addition, even under stricter evaluation conditions where the IoU threshold was increased from 0.5 to 0.95, mAP still showed an upward trend, although the growth rate was not as significant as mAP50, which still demonstrated the improvement in model performance. Through the detection of the test set images, we found that the YOLOv11 model can effectively recognize gestures and accurately interpret their meanings, demonstrating high accuracy. This study not only demonstrates the potential of YOLOv11 in gesture recognition tasks, but also provides a new technological path for the future development of HCI field. Overall, the YOLOv11 algorithm has demonstrated strong performance and accuracy in gesture recognition, providing a more natural and intuitive way for interaction between smart devices and humans.
A CT Image Classification Network Framework for Lung Tumors Based on Pre-trained MobileNetV2 Model and Transfer learning, And Its Application and Market Analysis in the Medical Field
Authors: Gao Ziyang , Tian Yong , Lin Shih-Chi , Lin Junghua
Published: January 2025

In the medical field, accurate diagnosis of lung cancer is crucial for treatment. Traditional manual analysis methods have significant limitations in terms of accuracy and efficiency. To address this issue, this paper proposes a deep learning network framework based on the pre-trained MobileNetV2 model, initialized with weights from the ImageNet-1K dataset (version 2). The last layer of the model (the fully connected layer) is replaced with a new fully connected layer, and a softmax activation function is added to efficiently classify three types of lung cancer CT scan images. Experimental results show that the model achieves an accuracy of 95.2% on the test set, with significant improvements in feature extraction compared to traditional models. With the rapid development of artificial intelligence technologies, deep learning applications in medical image processing are bringing revolutionary changes to the healthcare industry. AI-based lung cancer detection systems can significantly improve diagnostic efficiency, reduce the workload of doctors, and occupy an important position in the global healthcare market. The potential of AI to improve diagnostic accuracy, reduce medical costs, and promote precision medicine will have a profound impact on the future development of the healthcare industry.
Defect Detection Network In PCB Circuit Devices Based on GAN Enhanced YOLOv11
Authors: Huang Jiayi , Zhao Feiyun , Chen Lieyang
Published: January 2025

This study proposes an advanced method for surface defect detection in printed circuit boards (PCBs) using an improved YOLOv11 model enhanced with a generative adversarial network (GAN). The approach focuses on identifying six common defect types: missing hole, rat bite, open circuit, short circuit, burr, and virtual welding. By employing GAN to generate synthetic defect images, the dataset is augmented with diverse and realistic patterns, improving the models ability to generalize, particularly for complex and infrequent defects like burrs. The enhanced YOLOv11 model is evaluated on a PCB defect dataset, demonstrating significant improvements in accuracy, recall, and robustness, especially when dealing with defects in complex environments or small targets. This research contributes to the broader field of electronic design automation (EDA), where efficient defect detection is a crucial step in ensuring high-quality PCB manufacturing. By integrating advanced deep learning techniques, this approach enhances the automation and precision of defect detection, reducing reliance on manual inspection and accelerating design-to-production workflows. The findings underscore the importance of incorporating GAN-based data augmentation and optimized detection architectures in EDA processes, providing valuable insights for improving reliability and efficiency in PCB defect detection within industrial applications.
新课标背景下 第三学段颜色词词义教学 研究——以 “绿” 为例
Authors: 盛 宇涵
Published: January 2025

新课标指出，第三学段处于过渡衔接阶段，词义的教学尤为重要。本文以颜色词“绿”为例，探讨颜色词词义教学的方法。首先剖析“绿”的词义内涵及在部编版教材中的使用情况；其次提出基于日常生活、语境和运用多媒体手段对“绿”的词义教学的实践探索；最后总结出“1+n”教学模式，并指出未来研究可拓展至整体语文教学领域。研究旨在为语文词义教学提供创新路径，推动新课标理念落地，促进学生核心素养的长足发展。
五四浪潮中女子教育的觉醒：性别平等追求与文化认同重构
Authors: 许 艳丽
Published: January 2025

五四运动作为中国现代化进程中的关键事件，对女性教育和文化认同产生了深远影响。其不仅推动了女性教育权的普及，还促进了女性角色认同的转型，尤其是在教育领域，从传统的“女德”教育到现代学术与职业教育的转型，为女性自我认知和社会地位的提升提供了基础。在历史发展进程中，性别平等思想的传播并非一帆风顺，与传统儒家文化中对女性的角色期待存在激烈对立。在教育内容与形式的改革过程中，如何平衡现代性与传统性之间的张力成为关键问题。五四运动期间的文化冲突，不仅表现在教育政策和课程设置上，也影响了社会对女性教育的接受度与认同。其中性别平等理念与传统文化观念的冲突，对于揭示女性教育在这一历史转型中的文化认同变迁具有重要作用。五四运动对女性教育的推动不仅改变了教育体系本身，还为女性社会地位的提升、文化身份的重塑铺平了道路。
Evaluating the Performance of Large Language Models on Arabic Lexical Ambiguities: A Comparative Study with Traditional Machine Translation Systems
Authors: H Aldawsari Hamad Abdullah
Published: January 2025

The rapid advancement in natural language processing (NLP) has led to the development of large language models (LLMs) with impressive capabilities in various tasks, including machine translation. However, the effectiveness of these new systems in handling linguistic complexities, such as Arabic lexical ambiguity, remains underexplored. This study investigates whether LLMs can outperform traditional machine translation (MT) systems in translating Arabic lexical ambiguities, characterized by homonyms, heteronyms, and polysemes. The evaluation involves two prominent LLMs, OpenAI's GPT and Google's Gemini, and compares their performance with traditional MT systems, Google Translate and SYSTRAN. The results indicate that GPT and Gemini offer substantial improvements in translation accuracy and intelligibility over traditional MT systems and highlight the advanced capabilities of LLMs in handling the complexities of Arabic, suggesting a significant step forward in machine translation technologies. This study highlights the potential of LLMs to overcome the limitations of traditional MT systems and provides a foundation for future research. The results contribute to the ongoing development of more effective and accurate translation systems, emphasizing the importance of adopting advanced AI technologies in the field of machine translation.