2025 September - 44 articles
Cyberattacks, especially Advanced Persistent Threats (APTs), have become more complex. These evolving threats challenge traditional defense systems, which struggle to counter long-lasting and covert attacks. Cybersecurity Knowledge Graphs (CKGs), ena...
This paper explores how primary school teachers integrate digital technologies into their classroom practice, with a particular focus on the extent to which their stated intentions align with what actually takes place during lessons. Drawing on data...
Governments increasingly integrate artificial intelligence (AI) into digital public services, and understanding how citizens perceive and respond to these technologies has become essential. This systematic review analyzes 30 empirical studies publish...
In January 2023, Wikipedia introduced its most significant user interface (UI) redesign in over a decade, aiming to improve readability, accessibility, and navigation across devices. Despite the scale of this change, little empirical work has assesse...
This study explores the digital organization of cultural heritage knowledge across national GLAM institutions (galleries, libraries, archives, and museums) in the ten ASEAN countries. By employing a qualitative content analysis approach, this researc...
Emergency department (ED) overcrowding remains a major challenge for hospitals, resulting in worse outcomes, longer waits, elevated hospital operating costs, and greater strain on staff. Boarding count, the number of patients who have been admitted t...
Autonomous vehicles (AVs) are increasingly becoming a reality, enabled by advances in sensing technologies, intelligent control systems, and real-time data processing. For AVs to operate safely and effectively, they must maintain a reliable perceptio...
Traditional spam detection methodologies often neglect user privacy preservation, potentially incurring data leakage risks. Furthermore, current federated learning models for spam detection face several critical challenges: (1) data heterogeneity and...
This study introduces a novel informatics framework for assessing regional sustainability by integrating Twin Mean-Variance Two-Stage Data Envelopment Analysis (TMV-TSDEA) with a desirability-based decision analytics system. The model evaluates both...
Research indicates that perceived trust affects both behavioral intention to use chatbots and service satisfaction provided by chatbots in customer service contexts. However, it remains unclear whether perceived propensity to trust impacts service sa...
This research addresses the critical need for language preservation among the Higaonon indigenous community in Mindanao, Philippines, through the development of a culturally responsive mobile dictionary application. The Higaonon language faces signif...
Tourist flow prediction plays a crucial role in enhancing the efficiency of scenic area management, optimizing resource allocation, and promoting the sustainable development of the tourism industry. To improve the accuracy and real-time performance o...
This study presents preliminary design guidelines to support the evaluation of industrial safety training using immersive technologies, with a focus on high-risk work environments such as working at height. Although virtual reality has been widely ad...
The rapid rise of the prices of cryptocurrencies has intensified the need for robust forecasting models that can capture the irregular and volatile patterns. This study aims to forecast Bitcoin prices over a 15-day horizon by evaluating and comparing...
Background: Large language models (LLMs) such as ChatGPT have evolved rapidly, with notable improvements in coherence, factual accuracy, and contextual relevance. However, their academic and clinical applicability remains under scrutiny. This study e...
This study introduces the Human-AI Symbiotic Theory (HAIST), designed to guide authentic collaboration between human researchers and artificial intelligence in academic contexts, while pioneering a novel AI-assisted approach to theory validation that...
Unregulated herbal products marketed via digital platforms present escalating risks to consumer safety and regulatory effectiveness worldwide. This study positions the case of Jindamanee herbal powder—a banned substance under Thai law—as...
Human language comprehension relies on predictive processing; however, the computational mechanisms underlying this phenomenon remain unclear. This study investigates these mechanisms using large language models (LLMs), specifically GPT-3.5-turbo and...
Public transport agencies must triage thousands of multilingual complaints every day, yet the cost of training and serving fine-grained sentiment analysis models limits real-time deployment. The proposed “one encoder, any facet” framework...
Recommendation systems applied to tourism are widely recognized for improving the visitor’s experience in tourist destinations, thanks to their ability to personalize the trip. This paper presents a hybrid approach that combines Machine Learnin...
Deep-learning-based multiple label chest X-ray classification has achieved significant success, but existing models still have three main issues: fixed-scale convolutions fail to capture both large and small lesions, standard pooling is lacking in th...
Multi-behavior sequential recommendation (MBSRec) is a form of sequential recommendation. It leverages users’ historical interaction behavior types to better predict their next actions. This approach fits real-world scenarios better than tradit...
The modified Rankin Scale (mRS) is a widely used outcome measure for assessing disability in stroke care; however, its administration is often affected by subjectivity and variability, leading to poor inter-rater reliability and inconsistent scoring....
Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well...
(1) Background and objectives: Large language models (LLMs) such as GPT, Mistral, and LLaMA exhibit strong capabilities in text generation, yet assessing the quality of their reasoning—particularly in open-ended and argumentative contexts&mdash...
To address the high false alarm rate of intrusion detection systems based on distributed acoustic sensing (DAS) for power cables in complex underground environments, an innovative GRT-Transformer multimodal deep learning model is proposed. The core o...
Artificial intelligence (AI) has become an integral component of various sectors, including higher education. AI, particularly in the form of advanced chatbots like ChatGPT, is increasingly recognized as a valuable tool for engagement in higher educa...
Hard disk failure prediction is an important proactive maintenance method for storage systems. Recent years have seen significant progress in hard disk failure prediction using high-quality SMART datasets. However, in industrial applications, data lo...
Many breast cancer patients follow a self-managed treatment pathway, which may lead to gaps in the data available to healthcare professionals, such as information about patients’ everyday symptoms at home. Mobile apps have the potential to brid...
Data center virtualization has grown rapidly alongside the expansion of application-based services but continues to face significant challenges, such as downtime caused by suboptimal hardware selection, load balancing, power management, incident resp...
As artificial intelligence (AI) becomes ubiquitous across various fields, understanding people’s acceptance and trust in AI systems becomes essential. This review aims to identify quantitative measures used to measure trust in AI and the associ...
Technology roadmapping is conducted by systematic mapping of technological evolution through patent analytics to inform innovation strategies. This study proposes an integrated framework combining hierarchical Latent Dirichlet Allocation (LDA) modeli...
The selection of appropriate biomarkers in clinical practice aids in the early detection, treatment, and prevention of disease while also assisting in the development of targeted therapeutics. Recently, multi-omics data generated from advanced techno...
Firmware vulnerabilities in embedded devices have caused serious security incidents, necessitating similarity analysis of binary program instruction embeddings to identify vulnerabilities. However, existing instruction embedding methods neglect progr...
This study presents a comprehensive bibliometric analysis of the evolving landscape of data protection in medicine, examining research trends, thematic developments, and scholarly contributions from the 1960s to 2024. By analyzing 2159 publications i...
Lung cancer is one of the most prevalent and deadly forms of cancer, accounting for a significant portion of cancer-related deaths worldwide. It typically originates in the lung tissues, particularly in the cells lining the airways, and early detecti...
Background: In the medical field, various deep learning (DL) algorithms have been effectively used to extract valuable information from unstructured clinical text data, potentially leading to more effective outcomes. This study utilized clinical text...
Accessibility in web systems is essential to ensure everyone can obtain information equally. Based on the Web Content Accessibility Guidelines (WCAGs), the Electronic Government Accessibility Model (eMAG) was established in Brazil to guide the access...
This study offers a comprehensive examination of the scientific output related to the integration of Artificial Intelligence (AI) in education using qualitative research methods, which is an emerging intersection that reflects growing interest in und...
The rapid expansion of the Internet of Things (IoT) ecosystem has transformed industries but also exposed significant cybersecurity vulnerabilities. Traditional centralized methods for securing IoT networks struggle to balance privacy preservation wi...
Mental health disparities among those who self-identify as gay men in Peru remain a pressing public health concern, yet predictive models for early identification remain limited. This research aims to (1) develop machine learning and deep learning mo...
For the last decade, social networking services (SNS), such as X, Facebook, and Instagram, have become mainstream media for advertising and marketing. In SNS marketing, word-of-mouth among users can spread posted advertising information, which is kno...
The rapid development and deployment of artificial intelligence (AI) technologies have sparked intense public interest and debate. While these innovations promise to revolutionise various aspects of human life, it is crucial to understand the complex...
Traditional cattle health monitoring systems rely on centralized data collection, posing significant challenges related to data privacy, network connectivity, model reliability, and trust. This study introduces a novel, nature-inspired federated lear...
