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Background and objectives: The multiple chest x-ray datasets released in the last years have ground-truth labels intended for different computer vision tasks, suggesting that performance in automated chest x-ray interpre...

Abstract Physical sciences are essential to the predictive modeling of complex environmental systems, particularly environmental monitoring and sustainability applications, as they provide the deterministic foundation re...

The field of artificial intelligence (AI), machine learning and intelligent automation has become pervasive in our modern digital world. It extends from business and public services to environmental management and even i...

Abstract Emotion recognition is fundamental to building socially intelligent robotic systems capable of effective and adaptive Human-Robot Interaction (HRI) and Collaboration (HRC). This literature review synthesizes rec...

Metal-organic coordination networks self-assembled on surfaces have emerged as functional low-dimensional architectures with potential applications ranging from the fabrication of functional nanodevices to electrocatalys...

Sixth-generation (6G) mobile networks are expected to be AI-native by design, with intelligence embedded directly into the Radio Access Network (RAN) control loop through architectures such as O-RAN, near-real-time RAN I...

IntroductionThe current paper suggests the conceptualisation of surveillance federalism as the theoretical framework to interrogate the recomposition of local and regional democratic autonomy in the context of multi-leve...

Global food security relies heavily on rice production, which is continuously threatened by crop diseases. Although deep learning (DL) models have demonstrated strong diagnostic performance, their high computational and ...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

With the rapid evolution of virtual reality technologies such as digital twins, industrial Internet of Things, edge intelligence, and metaverse, virtual‒reality integration has become a core driving force for the const...

High‐entropy alloys (HEAs) are emerging as promising candidates for advanced electrocatalysis due to their multi‐elemental compositions, tunable electronic structures, and remarkable stability. Recent advances in syn...

Abstract Two-dimensional (2D) semiconductors enable atomically thin channels and attractive electrostatics, but practical scaling increasingly hinges on gate-dielectric integration rather than channel performance. A key ...

Modern communication environments ranging from smart mobility infrastructures to digitally integrated health care systems demand adaptable and trustworthy network security. In this situation, software-defined networks (S...

En este trabajo se analizan diferentes arquitecturas de redes convolucionales sencillas para generar espectrogramas sintéticos correspondientes a registros de audio de ballenas barbadas. La sencillez en el modelo juega ...

Machine learning (ML) and neuromorphic computing have been enforcing problem-solving in many applications. Such approaches found fertile ground in optical communications, a technological field that is very demanding in t...

Abstract Modern broadband access networks increasingly carry heterogeneous, delay-sensitive traffic generated by cloud-assisted applications, real-time communication services, and short-form multimedia exchanges. These w...

Abstract Quantum networks (QNs) have been predominantly driven by discrete-variable (DV) architectures. Yet, optical platforms naturally generate Gaussian states—the common states of continuous-variable (CV) systems, m...

"Unmanned networked multirobot systems have the potential to accomplish complex field tasks with minimum human intervention. Motion coordination of vehicles that operate in different domains (land, sea, air) is one of th...

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory ...

This paper presents a proposal for an architecture that integrates knowledge discovery systems (automatic acquisition) and knowledge based systems (experts systems). This work formulates considerations over the viability...

"This thesis investigates the application of machine learning methods to the task of deforestation monitoring using time-series satellite data. The objective is to assess how different algorithmic approaches perform in d...

Object-oriented software development has proven effective for systems development, but the creation of reusable and changeable software architectures is still a challenging task. Design patterns capture the expertise for...

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological inte...