Archives

  • Vol. 1 No. 1 (2024)

    Welcome to the latest issue of the International Journal of Emerging Technologies and Advanced Applications (IJETAA). Our newest edition showcases a collection of five exceptional articles at the forefront of technology and innovation. Each piece represents a significant contribution to the fields of knowledge graph construction, entity and relation extraction, automatic text labeling, network planning and design, and protocol entity extraction. These studies reflect the cutting-edge research and development efforts that define and drive the future of emerging technologies and their applications in various domains.

    In this issue, you will find insightful research on:

    • The construction of knowledge graphs for RFC protocols, offering a novel model that significantly improves the understanding and management of complex technical specifications.
    • Advanced techniques for the joint extraction of entities and relations, utilizing multi-feature fusion to enhance information extraction processes.
    • Innovative approaches to automatic text labeling with large language models, paving the way for more efficient and accurate data categorization.
    • Strategic planning and design of university campus networks using GPON technology, providing a blueprint for next-generation network infrastructure.
    • The application of few-shot learning in network protocol entity extraction, addressing the challenges of analyzing protocols with limited data.

    These articles embody our commitment to disseminating research that not only advances the theoretical landscape but also offers practical solutions to contemporary challenges. We invite academics, professionals, and enthusiasts alike to explore the insights and innovations presented in this issue. Join us in navigating the exciting possibilities that lie at the intersection of technology and application.

    Dive into our current issue to discover the latest contributions to the ever-evolving world of emerging technologies.

  • Vol. 1 No. 2 (2024)

    We are delighted to present to you the second issue of the IJETAA. This issue encapsulates a diverse range of research articles that delve into cutting-edge advancements in various domains of analytics and artificial intelligence.

    In this issue, we feature five insightful articles that contribute significantly to the advancement of analytical methodologies and applications:

    1. Spatial Distribution Analysis of Urban Retail Industry Using POI Big Data: This article explores the spatial distribution patterns of urban retail industries by leveraging Point of Interest (POI) big data. The research sheds light on the dynamics of retail establishments in urban environments, offering valuable insights for urban planners and businesses alike.

    2. YOLOLayout: Multi-Scale Cross Fusion Former for Document Layout Analysis: Presenting YOLOLayout, a novel approach for document layout analysis that utilizes a multi-scale cross fusion former. This research addresses the challenge of accurately extracting structural information from diverse document layouts, thereby facilitating automated document processing systems.

    3. Joint Information Extraction Model Based on Feature Sharing: Introducing a joint information extraction model that leverages feature sharing to enhance performance. This model demonstrates the efficacy of collaborative learning in information extraction tasks, paving the way for improved text mining and knowledge discovery.

    4. Interpretable DeepFake Detection Based on Frequency Spatial Transformer: Delving into the realm of deepfake detection, this article proposes an interpretable approach based on a frequency spatial transformer. By analyzing frequency-based features, the proposed method enhances the interpretability of deepfake detection models, thus bolstering trust and reliability in content authentication systems.

    5. Prompt Optimization Methods for Large Language Models with Long Text Input: Addressing the challenges associated with large language models and long text inputs, this research presents prompt optimization methods to improve model performance. By optimizing prompts for specific tasks and inputs, this approach enhances the effectiveness and efficiency of large language models in diverse applications.

    Each of these articles contributes to the growing body of knowledge in advanced analytics and artificial intelligence, offering innovative solutions to real-world challenges. We extend our gratitude to the authors for their valuable contributions and to our reviewers for their meticulous evaluation.

    We hope that the articles featured in this issue will inspire further research and spark meaningful discussions in the field of advanced analytics. We invite you to delve into the depth of knowledge presented in these articles and explore the possibilities they unfold.

  • Vol. 1 No. 3 (2024)

    In this third issue of the IJETAA, we present a diverse collection of research articles and reviews spanning robotics, computer vision, intelligent systems, blockchain technology, and warehouse management.

    In the research section, we explore an improved ant colony algorithm for mobile robot path planning, a multi-view approach to video object-level splicing localization, the development and application of a large model-based intelligent customer service system, and a case study on optimizing hotel financial processes using blockchain technology at T Group.

    Our review article delves into the latest advancements in warehouse management information system technology, providing valuable insights for professionals in the field.

    These articles showcase the breadth and depth of research being conducted in the areas of emerging technologies and their applications across various industries. We hope that this issue will inspire further research and innovation in these exciting fields.

  • Vol. 1 No. 4 (2024)

    We are pleased to present the fourth issue of our journal, which features two insightful research articles and one comprehensive review. These articles explore diverse topics, including the use of geographic information systems and clustering algorithms to understand spatial patterns of violence against women and children, the potential of emerging technologies to enhance health capital and promote common prosperity, and a survey of network security traffic analysis and anomaly detection techniques.

    In the first research article, titled "Spatial Patterns of Violence Against Women and Children using Geographic Information System and Density-Based Clustering Algorithm," the authors employ advanced geospatial analysis techniques to uncover patterns of violence against vulnerable populations. By leveraging geographic information systems and density-based clustering algorithms, the study provides valuable insights into the spatial distribution of these incidents, enabling policymakers and stakeholders to develop targeted interventions and support systems.

    The second research article, "Enhancing Health Capital and Promoting Common Prosperity from the Perspective of Emerging Technologies," explores the potential of cutting-edge technologies to improve health outcomes and promote social equity. The authors discuss how innovations such as artificial intelligence, telemedicine, and personalized medicine can contribute to building health capital and fostering inclusive growth. The article highlights the importance of harnessing these technologies responsibly to ensure that their benefits are accessible to all segments of society.

    In the review article, "A Survey on Network Security Traffic Analysis and Anomaly Detection Techniques," the authors provide a comprehensive overview of the latest approaches and methodologies used in network security. The survey covers various aspects of traffic analysis and anomaly detection, including machine learning-based techniques, statistical methods, and hybrid approaches. The article serves as a valuable resource for researchers and practitioners working in the field of network security, offering insights into the state-of-the-art techniques and future research directions.

    We hope that this issue of the journal will stimulate further research and discussion on these important topics. We invite our readers to explore these articles in depth and share their thoughts and perspectives with the research community.

  • Vol. 1 No. 5 (2024)

    Welcome to the 5th issue of the International Journal of Emerging Trends in Advanced Analytics (IJETAA). In this issue, we present groundbreaking research that explores innovative solutions and reviews in the realms of digital empowerment and simulation technology. These articles reflect our commitment to showcasing pioneering work that bridges technology and real-world applications.

    Innovative Paths for Digital Empowerment in Rural Revitalization of Ethnic Minority Areas

    Authors: Wen Ren, Feng Qi, Wei Tong
    DOI: 10.62677/IJETAA.2405118

    In this insightful article, Ren, Qi, and Tong delve into the transformative role of digital technologies in the revitalization of rural areas inhabited by ethnic minorities. The authors highlight how strategic digital interventions can empower these communities, fostering sustainable development and bridging the digital divide. The study provides a comprehensive analysis of various innovative paths and technologies that can drive socio-economic growth in underrepresented regions. By focusing on real-world applications and success stories, this research underscores the potential of digital empowerment as a catalyst for inclusive development.

    A Comprehensive Review of Simulation Technology: Development, Methods, Applications, Challenges, and Future Trends

    Author: Tao Luan
    DOI: 10.62677/IJETAA.2405119

    Tao Luan offers a thorough review of the evolution and impact of simulation technology across various sectors. This article provides a detailed examination of the development stages of simulation technology, the diverse methods employed, and its wide-ranging applications in industries from aerospace to healthcare. Luan also addresses the critical challenges faced by practitioners and researchers, such as computational limitations and the need for high-fidelity models. Looking ahead, the paper discusses emerging trends that are poised to shape the future of simulation, including advancements in AI integration and real-time processing capabilities. This review serves as an essential resource for understanding the past, present, and future landscape of simulation technology.