Large language models (LLMs) are increasingly being used in education, yet their correctness alone does not capture the quality, reliability, or pedagogical validity of their problem-solving behavior, especially in mathematics, where multi-step logic...
Selecting the appropriate academic track is a critical decision for students, as misalignment between program requirements and individual cognitive, personality, and competency profiles can significantly impact academic performance, persistence, and...
Obesity is a major public health concern because of its high prevalence and association with cardiometabolic comorbidities. This study compared nine ensemble and meta-ensemble learning models for multiclass obesity-status classification using the Obe...
The volume of daily email traffic continues to grow rapidly, creating challenges in efficiently distinguishing important from irrelevant messages. Beyond spam detection, modern email systems classify messages into categories such as promotions, socia...
Multimodal sentiment analysis (MSA) utilizes complementary information from different modalities to achieve a more thorough and fine-grained understanding of human sentiment. To address the issues of high modality redundancy and insufficient refined...
Emotion detection in social media remains challenging, particularly in polarized public debates where emotional expression is often imbalanced across categories. Addressing this challenge, this study compares the performance of multiple computational...
Governments worldwide are mandating digital tax platforms, yet little is understood about what sustains taxpayer engagement beyond legally compelled minimum use. This study extends the Technology Acceptance Model (TAM) with perceived compulsion and t...
In semi-supervised learning scenarios, the presence of limited labeled data and abundant unlabeled samples poses significant challenges to model robustness and generalization. Although the semi-supervised broad learning system (SSBLS) effectively exp...
Digital repositories have been an important gateway for the dissemination of information regarding objects of art and cultural heritage throughout the World Wide Web, but the vast number of available artifacts, both historical and modern, makes their...
Twitter/x has become a key platform for analyzing public opinion on a large scale; however, traditional centralized approaches raise significant concerns regarding privacy and data governance. To address these challenges, this paper presents an empir...
Email spam and phishing detection is typically evaluated using accuracy-centric metrics under implicitly unconstrained computational settings. However, in practical deployment scenarios—particularly in real-time and resource-constrained environ...
Blockchain technology has emerged as a foundational paradigm for building decentralized, transparent, and secure systems, particularly in environments that operate without centralized authority. At the core of these systems are consensus mechanisms t...
This paper investigates the problem of cross-lingual named entity recognition (NER), which involves automatically identifying entities such as persons, organizations, locations, and other structured elements in text. High-quality NER typically requir...
Accurate and efficient classification of hematological malignancies from peripheral blood smear (PBS) images remains challenging due to the scarcity of annotated datasets, staining variability, and subtle morphological differences among blood cancer...
Hyperspectral imaging (HSI) provides rich spectral information and serves as a non-destructive technique for forensic stain analysis. Conventional approaches often exhibit degraded performance due to the high dimensionality and spectral redundancy in...
Over the past three decades, artificial intelligence (AI) has substantially reshaped marketing research and practice, yet the discipline has not established a systematic understanding of its evolutionary trajectory and intellectual structure. A bibli...
The new energy vehicle (NEV) industry generates massive multi-source heterogeneous data. To overcome traditional database limitations in terminology disambiguation and multi-hop reasoning, this paper proposes a knowledge graph (KG)-based question-ans...
Bees are essential pollinators for agricultural systems, making accurate, automated monitoring of their behavior critical for assessing colony health and ecosystem stability. Recent advances in computer vision and artificial intelligence have enabled...
This research aimed to determine the influence of human–computer interaction usability on the behavioral intention and self-reported continued usage intentions of e-commerce applications. Moreover, it investigated the moderating role of trust i...
This paper presents SPARK_AI, a prompt-orchestrated system architecture for governing how large language models (LLMs) conduct structured and adaptive reasoning in human–AI interaction. The framework mitigates ad hoc LLM use by replacing direct...
With the rapid proliferation of large language models (LLMs), distinguishing machine-generated text from human-authored content has become increasingly critical for ensuring content authenticity, academic integrity, and trust in information systems....
The BiTemporal RDF (BiTRDF) model extends the standard RDF data model by integrating both valid time and transaction time, thus enabling the representation and querying of dynamic and historical knowledge. While the theoretical foundations of BiTRDF...
This study presents a deep learning-based framework for beam pattern synthesis in optimized uniform linear antenna arrays, combining Differential Evolution–based pre-optimization with recurrent neural network (RNN) modeling. Radiation patterns...
This study investigates how virtual reality systems can support inclusive access to culturally restricted sacred heritage sites. Two extended reality (XR) approaches were developed and deployed in a real-world setting: a VR360 virtual tour and an AI-...
The rapid advancement of digital and mobile technologies has reshaped the educational landscape, fostering the adoption of interactive and learner-centered methodologies. Among these, immersive technologies such as Augmented Reality (AR), when couple...
Urban waste management remains a significant challenge for achieving environmental sustainability and advancing smart city infrastructures. This study proposes a multimodal vision–language framework that integrates real-time object detection wi...
Universities play a dual role as sites of learning and as institutions that certify student competence through assessment. The rapid diffusion of generative artificial intelligence (GenAI) challenges this certification function by altering the condit...
The increasing digitalization of industrial ecosystems under the Industrial Revolution 4.0 has intensified the demand for fast, reliable, and inclusive broadband connectivity. The expansion of 5G technology led by data-driven services addresses the g...
The healthcare sector is undergoing a digital transformation that improves the quality of care, increases efficiency, and enhances connectivity. With digitalization comes an increase in cyber threats. Hospitals are among the primary targets of cyberc...
Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), is rapidly changing how higher education approaches teaching, learning, and assessment. In cybersecurity education, professional certification exams are key for me...
This study provides an early evaluation of the effectiveness of the Core Tax Administration System, a digital taxation platform introduced to integrate all tax administration processes in Indonesia into a single system. To conduct this evaluation, th...
Artificial Intelligence (AI) has transitioned from a specialized research area to a ubiquitous socio-technical infrastructure influencing sectors from healthcare and law to manufacturing and defense. In tandem with its transformative promise, AI has...
Student retention has become a major challenge for higher education institutions due to the influence that academic, socioeconomic, family, and motivational factors exert on students’ academic continuity. In this context, understanding the dete...
The discrete-form control of the Stewart platform is essential for digital implementation in intelligent manufacturing and robotic systems under the context of Industry 4.0, yet its performance is often degraded by unavoidable discrete disturbances....
This article presents a methodological framework for automating clinical data processing workflows using Generative Artificial Intelligence (AI) as an interactive co-developer. We demonstrate how Large Language Models (LLMs), specifically ChatGPT and...
Acute lymphoblastic leukemia (ALL) presents significant clinical challenges due to its genetic complexity and high relapse rates. While outcomes like length of stay (LOS), mortality, and total charges (TCs) are critical quality indicators, most exist...
Workspace digitalisation presents a transformative shift from traditional, physically bounded offices to virtual, technology-enabled environments. Digital technologies like cloud computing, artificial intelligence, and the Internet of Things enable r...
Russian-language resources for medical natural language processing (NLP) are expanding rapidly; however, their fragmentation, uneven curation, and limited clinical reliability hinder the development of safe machine learning systems for prognosis, pre...
Public organizations in Peru have committed substantial resources to artificial intelligence over recent years, yet evidence on whether these investments produce measurable returns has remained scarce. This study evaluated the causal impact of AI ado...
The integration of artificial intelligence (AI) in literature reviews aims to transform research by potentially automating processes, enhancing rigour, and improving quality. The study proposes a structured step-by-step approach to integrate AI tools...
Virtual museums delivered through immersive virtual reality (VR) function as information environments where users access interpretive content while navigating spatially. With the integration of generative artificial intelligence (AI), conversational...
The rapid adoption of generative artificial intelligence (AI) systems has transformed health information seeking, raising questions about their role as intermediaries in non-professional health self-consultation. This study compares Google Search and...
Background: The COVID-19 pandemic revealed persistent gaps in local health department (LHD) health informatics capacity. This study examines organizational characteristics of LHDs associated with the adoption of six health information systems: electr...
Automating ICD-10 coding from discharge summaries remains demanding because coders analyze clinical narratives while justifying decisions. This study compares three automation patterns: PLM-ICD as a standalone deep learning system emitting 15 codes p...
In 2023, in the wake of the launch of ChatGPT, based on GPT-3, we invited contributions on the Topic AI chatbots: threat or opportunity [...]
Causal inference in text data has been a demanding objective in the field of natural language processing, mainly due to the intrinsic ambiguity and context sensitivity inherent in data, inducing uncertainty. Diminishing this uncertainty is essential...
This paper evaluates the platform-mediated importance and impact of 3D cultural heritage models stored on Sketchfab by analyzing user engagement and retention metrics (views, likes, and comments), and provides a comparative assessment across other ma...
Traditional textile crafts face significant challenges in preserving and transferring knowledge due to the aging of expert artisans and declining community engagement. The Phum Riang silk-weaving tradition in Suratthani Province is a critical example...
The growing demand for customized pet diets highlights the shortcomings of commercial dog foods designed for all breeds, especially when it comes to addressing breed-specific diseases, metabolic disorders, and health risks. This research presents the...
Traumatic brain injury (TBI) is a leading cause of long-term disability worldwide, and each person’s recovery looks different. Artificial intelligence (AI) offers promising tools to project individual outcomes. However, these models are impacte...
