Research Papers

["Tongxi Liu","Luyao Ye","Wei Yan"]

["Yu Bai"]

["Yuzhao Yang","Genlang Chen","Binhua He","Yan Zhao"]

Knowledge graphs represent real-world facts as structured triplets and underpin a wide range of applications, including question answering, recommendation, and retrieval-augmented generation. Automatically extracting such triplets from unstructured text is essential for scalable knowledge base const...

["Catalin Anghel","Emilia Pecheanu","A. Anghel","M. Craciun","A. Cocu"]

Reliable evaluation of large language models (LLMs) for educational use requires benchmarks that reflect exam constraints, instructor grading practices, and the operational consequences of thresholded decisions. This paper introduces ExamQ-Gen, an instructor-in-the-loop benchmark that couples two ta...

["José Fernández Cerero","José María Fernández Batanero","Daniel Fernández Cerero","Marta Montenegro Rueda"]

Artificial intelligence (AI) has established itself as a key technology in the context of Industry 4.0, with direct implications for university education, especially in engineering degrees. This study analyses the degree of adoption and the main educational uses of AI-based tools in higher education...

["Nyashadzashe Tamuka","T. Mathonsi","T. Olwal","Solly Maswikaneng","Tonderai Muchenje","T. Tshilongamulenzhe"]

Fog computing extends cloud services to the network edge to support low-latency IoT applications. However, since fog environments are distributed and resource-constrained, intrusion detection systems must be adapted to defend against cyberattacks while keeping computation and communication overhead ...

["Hebah Alquran","Shadi Banitaan"]

The integration of large language models (LLMs) such as GitHub Copilot, ChatGPT, and DeepSeek into programming education has introduced a new form of human–AI collaboration. These tools provide real-time code suggestions, debugging assistance, and design support, yet their effects on learning, trust...

["Madan Baduwal","Priyanka Paudel","Vini Chaudhary"]

Federated learning (FL) has emerged as a transformative distributed learning paradigm that enables collaborative model training without sharing raw data, thereby preserving privacy across large, diverse, and geographically dispersed clients. Despite its rapid adoption in mobile networks, Internet of...

["Natalya Maxutova","A. Kassymova","Kuanysh Kadirkulov","A. Ismailova","G. Zhidekulova","Zhanar Azhibekova","J. Tussupov","Q. Rakhimov","Z. Kenzhebayeva"]

Rare event detection in large tabular data remains a computationally challenging problem due to class imbalance, heterogeneous feature distributions, and unstable thresholds. Traditional machine learning approaches based on individual models and fixed thresholds often exhibit limited robustness and ...

["Eduardo Arguijo","Yenny Villuendas-Rey","Arturo Cruz-Jiménez","Jonatan Mireles-Hernández","O. Camacho-Nieto","Mario Aldape-Pérez"]

The rapid integration of artificial intelligence (AI) has heightened the need for evidence-based regulatory frameworks to effectively address its legal, ethical, and societal consequences. This research carefully analyzes the prevailing landscape of AI-related legislation in Mexico. The study conduc...

["Mireia Vendrell","Samantha-Kaye Johnston"]

["B. Althani"]

Automated legacy code modernization using Large Language Models lacks rigorous evaluation frameworks and multi-objective quality assessment methodologies. Existing research suffers from three critical deficiencies: single-metric evaluation paradigms creating pathological optimization incentives, sta...

["Lu Ding","Robert A. O’Berry","Hunter Tallent","Sanju Gharti Chhetri G C","A. Gapud"]

["Dimitrios Yiatas","A. Jimoyiannis"]

This paper presents the findings of a study on computer science teachers’ views regarding the reform of the computer science curriculum and its implementation in Greek model and experimental lower secondary schools (called Gymnasiums). Research data were collected through interviews with 19 computer...

["Tingting Wang","Shan Li","Shasha Li","Jianhua Zhang","Jie Gao"]

While generative artificial intelligence (GenAI) tools demonstrate potential for enhancing students' learning outcomes, little is known about how students use GenAI at the micro‐level, particularly regarding when and how they seek assistance during self‐regulated learning (SRL). This study exa...

["Zhen Xu","Xin Guan","Chenxi Shi","Qinhao Chen","Renzhe Yu"]

The growing emphasis on 21st-century competencies in postsecondary education, intensified by the transformative impact of generative artificial intelligence (GenAI) on the economy and society, underscores the urgent need to evaluate how they are embedded in curricula and how effectively academic pro...

["Gretchen Geng","Junyu Chen"]

["Marvin N. Wright","Lukas Burk","Pegah Golchian","Jan Kapar","Niklas Koenen","Sophie Hanna Langbein"]

In the age of digital epidemiology, epidemiologists are faced by an increasing amount of data of growing complexity and dimensionality. Machine learning is a set of powerful tools that can help to analyze such enormous amounts of data. This chapter lays the methodological foundations for successfull...

["Fabian Walke","Veronika Föller"]

This study investigates generative artificial intelligence (GenAI) usage of university students who study alongside their professional career. Previous literature has paid little attention to part-time students and the intersectional use of GenAI between education and business. This study examines w...

["Chih-Pu Dai","Fengfeng Ke"]