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Automatic movement recognition is often used to support various fields such as clinical, sports, and security. To date, there is a lack of a classification feature that is both interpretable and not movement-specific. Pr...

Abstract The increase in the scale and voltage level of urban power grids has made cable lines the main way of power transmission. However, their insulation systems are prone to Partial Discharge (PD) caused by local def...

Federated learning (FL) in mobile edge computing (MEC) operates over wireless links with time-varying bandwidth, latency, and packet loss, which makes conventional full-model synchronization inefficient and vulnerable to...

Digital Twin Networks (DTNs) are emerging as a key enabler for the robust optimization and lifecycle management of next-generation networks. However, current DTN approaches still rely heavily on manual design, implementa...

BackgroundArtificial intelligence (AI) has substantial potential to advance periodontal and peri- implant care through novel diagnostic, prognostic, and therapeutic opportunities. Nevertheless, the evidence is scattered ...

Abstract The Internet of Things (IoT) and emerging technologies have converged to drive the remarkable development of intelligent systems. The interconnection of physical objects, sensors, and tiny communication devices ...

Biotic and abiotic stresses reduce crop yields, yet existing image‑based diagnostic models are often crop‑specific, computationally intensive, and poorly interpretable. This study present: (i) a multi-crop diagnostic...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Abstract Traditional bridge structural condition assessments struggle to integrate the physical topological information of BIM models with the spatiotemporal evolution of long-term monitoring data, resulting in low asses...

The next-generation network technology is an intelligent information technology with the characteristics of collaborative perception, ubiquitous communication, and computer assistance. It is highly related to the industr...

Artificial intelligence (AI) has emerged as a transformative force in modern ophthalmology, enabling rapid advances in disease detection, clinical decision support, workflow optimization, and tele-ophthalmology. Ophthalm...

The next generation of tactical networks (TNs) is poised to further leverage the key enablers of 5G and beyond 5G (B5G) technology, such as radio access network (RAN) slicing and the open RAN (O-RAN) paradigm, to unlock ...

Thermoelectric generators offer a promising solution for sustainable, low-maintenance energy harvesting in smart agriculture, especially for powering off-grid sensor nodes and microgrid systems. However, their inherently...

The Link Women Indonesia initiative represents UN Women's pioneering artificial intelligence and digital technology training program designed to address gender disparities in Indonesia's technological workforce. Collabor...

Artificial Intelligence (AI) is playing an increasingly pivotal role in driving innovation and promoting sustainable development across various sectors amid the ongoing wave of industrial revolutions. However, the existi...

The integration of artificial intelligence (AI) into retinopathy of prematurity (ROP) screening represents an important advancement in neonatal ophthalmology, particularly in settings facing specialist shortages and scre...

Introduction and aims: Oral and maxillofacial surgery (OMFS) produces complex clinical data, while artificial intelligence (AI) applications in this field remain limited despite great potential. This study aimed to map t...

This study introduces a framework for cyber threat intelligence aimed at enhancing Türkiye’s proactive cybersecurity capabilities, specifically addressing security vulnerabilities. A geographic analysis involving 11,...

This study examines the role of artificial intelligence in improving the efficiency of photovoltaic (PV) systems through maximum power point tracking (MPPT) under dynamic operating conditions. A simulation-based model wa...

ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive me...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...

ABSTRACT This paper presents HealthNet, a novel framework for the dynamic optimisation of healthcare transportation networks using multi‐agent reinforcement learning. HealthNet leverages a spatiotemporal dependency mod...

IntroductionEarly and accurate diagnosis of skin cancer has a huge impact on the survival rate of patients and deep learning-based CNN and dermatologists' intelligence support can fasten the diagnosis not only within the...

ABSTRACT Background The COVID‐19 pandemic has caused massive devastation worldwide, and its effects still persist. Managing the early stages was difficult, but scientists worked tirelessly to control it. The emergence ...