Buscar recursos académicos

Brain–computer interfaces (BCIs) based on motor imagery (MI) provide a transformative direct communication pathway for patients with severe motor disabilities. However, the high inter-subject variability and non-statio...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Complex interactions between seawater and freshwater govern intrusion and stabilization in coastal aquifers. Previous studies have primarily relied on interface-based analyses, limiting full-field spatial quantification ...

ABSTRACT Bio‐inspired optimisation methods have been widely applied to complex real‐world problems, particularly in low‐carbon power and energy systems, where optimisation tasks often involve high‐dimensional, co...

ABSTRACT With the advancement of brain–computer interfaces (BCI), motor imagery (MI) electroencephalogram (EEG) decoding can greatly benefit from spatial filtering features derived from common spatial patterns (CSP). H...

ABSTRACT With the development of unmanned aerial vehicle and satellite technology, the application of tiny object detection in remote sensing images is becoming increasingly widespread. Although significant progress has ...

Topicality of comparative study in Foreign Direct Investments (FDI) is determined by the need to deepen analysis of economic activity challenges and opportunities related to cross-border investments. Research in FDI tren...

Background: Recent years have witnessed a surge in the integration of digital intelligence within dental education, with various technologies increasingly supporting clinical skill training and educational applications. ...

Introduction and aims: This article aims to answer how emerging technologies, education, and governance can be strategically integrated to improve oral health in Latin America and the Caribbean (LAC). By focusing on Vene...

Hate speech is pervasive across most social media platforms, profoundly impacting users' lives and wellbeing. To address this critical issue, researchers are exploring explainable AI (XAI), which helps users understand A...

Abstract Efficiently and accurately extracting key information from videos has become a core challenge in the current computer vision. Traditional methods rely on manual features and shallow models, making it difficult t...

The effect of imbalanced data on the optical character recognition of Braille text is investigated by applying two techniques to a set of convolutional neural network image classification models. A multilabel classificat...

Abstract Facial expressions exhibit a wide range of emotions. They are regulated by neural mechanisms in the brain that are beyond one’s control. Facial expressions are largely involuntary. The term “micro facial exp...

IntroductionWe address moral uncertainty in reinforcement learning (RL) by proposing a framework that integrates multiple ethical theories into decision-making. Existing approaches rely on single moral frameworks or hand...

Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

Federated learning (FL) is a decentralized machine learning (ML) approach that can be used for intrusion detection in Internet of Things (IoT) devices. It involves the local training of AI models and their aggregation at...

To solve the problem of lack of market insight and insufficient innovation creativity in entrepreneurship of college students, this paper aims to explore the application of data mining and predictive analysis technology ...

Abstract Early small fires in coal mines are of critical importance for mine safety, as most incidents begin as small fire sources. These fires essentially constitute a task of small-object detection. Detecting such targ...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

Abstract Recently, numerous lightweight image super-resolution methods with low computational complexity have been proposed, achieving a promising trade-off between reconstruction quality and efficiency. However, most ex...

Autism Spectrum Disorder is a neurodevelopmental disorder with onset in early childhood and its diagnosis often requires clinical processes based on long, subjective observations. Although early diagnosis and interventio...

Background Identifying priority projects in industry–education integration is critical for optimizing policy support and resource allocation. While prior studies have primarily relied on qualitative assessments, there ...

he orchestration of microservices in distributed cloud environments poses significant challenges due to the heterogeneous nature of cluster nodes and dynamic workload patterns. Traditional scheduling strategies in Kubern...

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...