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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...

In recent years, large language models and agent systems based on them have been considered a promising tool for the digital transformation of public administration. However, the practical effectiveness of such systems i...

Nearly Zero Energy Buildings (NZEBs) are pivotal in addressing the escalating energy and environmental challenges of hot climates, where extreme cooling demands and reliance on fossil fuels intensify carbon footprints. T...

Domestic interiors have historically been organized through anthropocentric spatial logics in which architectural layouts, circulation systems, and spatial hierarchies are structured primarily around human needs and bodi...

Heterogeneous SoCs enhance system performance across various applications. However, managing and integrating components, interfacing hardware and software, and overseeing shared resources pose significant challenges for ...

Abstract This research is concerned with the innovative use of AI in cross-cultural music learning, more particularly in the creation of a multimodal learning model that combines audio identification, image analysis, and...

Immersive walkthroughs are increasingly used to document, interpret, and communicate heritage sites to remote audiences. This study presents a framework for designing and implementing a cross-platform WebVR walkthrough o...

Organotypic slice culture is a sophisticated technique historically used in cellular and developmental neurobiology to investigate three-dimensional architecture and cellular interactions. Maintaining thin tissue slices ...

Abstract Grid-connected renewable energy systems with high penetration rates exacerbate frequency fluctuations in microgrids, making traditional control methods ill-suited for random source-load variations. This paper pr...

Background: Cardiac complications arising from diabetes mellitus manifest as structural and functional myocardial alterations independent of traditional cardiovascular risk factors. The intricate molecular underpinnings ...

Abstract Early and reliable smoke detection is critical for preventing fire-related disasters, safeguarding human lives, and ensuring infrastructure safety. Conventional sensor-based systems, however, are often constrain...

Goal: Analysis of the glottal area during vocal fold vibration has gained increasing attention. However, traditional analysis requires manual, frame-by-frame glottal area annotation to compute the glottal area waveform, ...

In an era defined by the global transformation of the world order, characterized by a multitude of external and internal challenges, a new conceptual framework is advanced to steer the Russian economy toward a path of ba...

For the structural health monitoring of composite materials, data analysis technology must be very sophisticated, capable of detecting fault patterns that are multi-level and complicated. A comprehensive deep learning pa...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

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...

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 ...

Fast and accurate identification of skin lesions is important for the outcome of patients. The evaluation of lesions is subjective, and poor quality images may limit accuracy. Deep learning models can be an alternative; ...

The rapid proliferation of digital devices has generated vast amounts of data, presenting significant challenges in collection, processing, and analysis that traditional systems struggle to overcome. This study investiga...

The remarkable success of large language models (LLMs) in code generation has transformed software development, with systems like Codex, CodeGen, and StarCoder demonstrating strong capabilities in synthesizing functional...

Accurate identification of plant-parasitic nematodes is fundamental to effective crop protection and the maintenance of soil ecosystem integrity. This study integrates morphological characterization with deep learning-ba...

Reliable low-latency delivery over satellite downlinks remains fundamentally constrained by long propagation delays, burst-correlated packet loss, and the limited effectiveness of retransmission-based recovery. Although ...

Abstract Background Cumulus granulosa cells (CGCs) are essential for oocyte support, metabolic cooperation, and steroidogenesis, yet they deteriorate rapidly in conventional 2D culture, limiting long-term studies of thes...