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Abstract To improve sketch recognition accuracy, this study proposes an enhanced sketch recognition model based on an improved CycleGAN network and a dual attention mechanism. The proposed model first incorporates multi-...

In this research, we address a critical problem for strawberry growers in Lima: the management of phytosanitary diseases. Traditionally, these farmers relied on time-consuming, imprecise, and error-prone visual observati...

Abstract Globally, shrimp aquaculture is a vital source of food, but disease outbreaks present serious economic challenges. Traditional diagnostic techniques, such as visual inspection and polymerase chain reaction (PCR)...

In this paper we describe the general architecture and the main structuring relations of the Portuguese WordNet, under construction within the WordNet.PT project*. We also present empirical and technical motivations for ...

Copper matrix composites face the inherent strength-conductivity trade-off, limiting their high-end applications. Inspired by bone and bamboo, a bioinspired oriented multicore composite (BOMC) was fabricated. Its dual-ne...

Abstract This paper presents a model for path-based growing network with preferential attachment motivated by the deployment of quantum key distribution networks. The model is based on a network constructed from path seg...

Abstract Automatic liver tumor segmentation using Single-Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) provides detailed insights that facilitate accurate tumor targeting and effective treatment plan...

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

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

The field of remote sensing change detection (RSCD) has witnessed remarkable progress. Most existing RSCD methods currently follow the encoder-feature interaction-decoder architecture. However, these methods often treat ...

Unmanned aerial vehicles (UAVs) are increasingly crucial across various fields. There is a growing interest in using federated learning (FL) methods to enhance the efficiency of UAV operations. Nevertheless, incumbent me...

Abstract Quantum Machine Learning (QML) is emerging as a promising technology for tackling complex computational challenges, although its practical implementation faces significant obstacles owed to the inherent noise in...

Mobile genetic elements (MGEs) such as bacteriophages and plasmids profoundly shape microbial community structure and drive horizontal gene transfer across ecosystems. Wastewater treatment systems, with their high cell d...

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...

Abstract Electric cable shovel (ECS) is a complex production equipment, which is widely utilized in open-pit mines. Rational valuations of load is the foundation for the development of intelligent or unmanned ECS, since ...

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...

Infrared dim and small target detection is crucial in fields, such as military reconnaissance and remote sensing. However, due to the extremely small target size, lack of texture, and low signal-to-noise ratio, the direc...

Abstract Smart home networks are a rapidly evolving part of the Internet of Things (IoT), where connected devices exchange information to automate energy use, enhance comfort, and improve user safety. Despite their benef...

Abstract This paper proposes a novel hybrid ensemble machine learning framework integrated with Explainable AI (XAI) to overcome the fundamental trade-off between non-detection zones (NDZ) and false positives in conventi...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

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...

Abstract The widespread adoption of the cloud continuum paradigm poses significant challenges such as the management of heterogeneous infrastructural devices, the strict security and privacy requirements, and the complex...

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...

An electromagnetic transient (EMT) simulation framework is developed by integrating the Parallel-in-Time algorithm with a data-oriented Entity–Component–System (ECS) architecture. The proposed method aims t...