Buscar recursos académicos

INTRODUCTION: Accurate power quality disturbances (PQDs) classification is critical for maintaining grid stability and reliability in modern power systems. However, existing deep learning methods predominantly rely on si...

With advances in aerospace technology, high-resolution optical imagery from satellites, such as China’s Gaofen series, is vital for climate monitoring and agriculture. However, cloud cover significantly impedes th...

Abstract Accurate classification of phonocardiogram (PCG) signals is vital for the early detection of cardiovascular diseases (CVDs), a leading cause of global mortality. However, conventional machine learning and deep l...

Early detection of Parkinson’s disease (PD) through speech analysis offers significant clinical advantages, yet no validated tools exist for Arabic-speaking populations, representing a critical gap in global healthcare...

Introduction and aims: Automated dental report generation faces significant challenges in multimodal fusion, often resulting in suboptimal semantic quality and risks of hallucination, where AI generates clinically unsupp...

To address the challenges of aviation safety information overload in Pre-flight Information Bulletin (PIB) systems, this study proposes an intelligent classification framework (ERNIE-DPCNN) that integrates knowledge-enha...

The increasing frequency and severity of wildfires necessitates advanced methods for effective surveillance and management, as traditional ground-based techniques often struggle to adapt to rapidly changing fire behavior...

Buildings serve as a key indicator of human land use, and building change detection plays a crucial role in urban growth and shrinkage monitoring, land use planning, and urban development assessment and management. Curre...

Abstract Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe ...

An Optical Character Recognition (OCR) approach for printed Arabic script is presented in this paper, Which is one of the most popular scripts in the world. Development of an OCR system. For Arabic script it is difficult...

Sleep plays an important role in physical health, cognition, and emotional well-being. Since sleep disorders can affect all these aspects, accurately detecting sleep stages is key to proper diagnosis and monitoring. Auto...

Accurate traffic flow prediction is of great significance for urban planning and traffic management. Among existing methods, researchers have shown remarkable progress by utilizing spatiotemporal networks. Unfortunately,...

The need for early and precise identification of abnormalities has made the detection and classification of brain tumours essential components of medical diagnosis. Because brain tumours are naturally complex and can hav...

Ethylene is an important raw material, and ethylene cracking furnaces (ECFs) are the core equipment sources of ethylene plants. The quality of the operation of the ECF directly affects the overall economic benefits of th...

Abstract Accurate prediction of cascading faults in power grids can ensure system stability and prevent large-scale outages. Existing methods typically require learning effective statistical information from datasets wit...

Abstract This study presents a Quantum-Enhanced Firefly Algorithm (QFA)-based multi-level image annotation framework that integrates advanced Otsu thresholding, region-based feature extraction, and Bayesian multi-label c...

Abstract Accurate and reliable wind power forecasting models are essential for the optimal dispatch of power systems. However, existing methods still face several challenges, including ineffective signal decomposition, l...

Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases, such as hypertension. The assessment of cardiorespiratory function and biometric identification (ID...

The inherent non-stationarity, weak periodicity, and abrupt transient mutations of wind turbine gearbox vibration signals present substantial challenges to traditional diagnostic frameworks. To improve diagnostic accurac...

To address the difficulty of blasthole detection during the charging phase of drill-and-blast tunnelling, which is aggravated by dust interference and insufficient illumination, this study proposes an intelligent blastho...

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with strong invasiveness, limited treatment options, and poor prognosis. Its early accurate diagnosis and individualized treatment are major challenges f...

The dynamic range limitation is intrinsic to conventional RGB cameras, which reduces global contrast and causes the loss of high-frequency details such as textures and edges in complex, dynamic traffic environments (e.g....

Abstract Objective This study aims to evaluate the clinical features, efficacy of endoscopic therapy, and long-term prognosis in patients with ectopic papilla of Vater (EPV) located in the duodenal bulb. Methods A retros...

Solar iron production from H2-based direct reduction of iron ore was investigated in a continuously particle-fed reactor for performance analysis. Concentrated solar energy was used as the external source of high-tempera...