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Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots). Our approach leverages on Artificial Intelligence (AI) to differentia...

Abstract Using biomedical foundation models (FMs) for inference on small cohorts, represents a promising and practical route to advance drug response biomarker discovery and target identification. Here, we demonstrate th...

Abstract Bunker fuel prices constitute a major component of maritime transport costs, representing 30–70% of total operating expenses and critically influencing competitiveness, planning, and regulatory compliance in g...

Abstract Accurate prediction of bio-oil yield from pyrolysis of organic solid waste is still the main problem in the field of biomass valorization, mostly because of high variability in the composition and the heterogene...

Plant disease diagnosis in field settings is challenged by subtle symptomology, high inter-class visual similarity, and class imbalance, making automated detection particularly difficult. While deep learning models achie...

To address the sensitivity of traditional Two-Dimensional Principal Component Analysis (2DPCA) to outliers and the breakdown of variance-reconstruction equivalence under noise, we propose an Angle-Aware Weighted 2DPCA (A...

Intelligent mining area detection is fundamental for ecological monitoring and sustainable development of mining areas. However, current remote sensing detection lacks high-quality multimineral rotated object detection d...

In this study, a novel Quantum Self-Attention Neural Network for Multi-Model Aerial Image Classification (QSANN-MAIC) is proposed. The objective of this paper is to develop a high-performance learning framework capable o...

Degradation of images in ocean remote sensing is primarily due to light scattering, chromatic aberration, and stochastic noise. As a result, the quality of the image content has been significantly compromised. Most ocean...

Fine-grained remote sensing ship detection plays an important role in maritime traffic management and the security guarantee system. Despite considerable research advances have been achieved via elaborately designed deep...

Reliable trajectory similarity estimation underpins applications such as map matching, mobility anomaly detection, and travel behavior analysis. However, traditional distance-based methods are computationally expensive a...

Abstract Preterm birth (PTB) affects an estimated 15 million infants worldwide each year, raising an enormous challenge in the field of maternal-fetal medicine. This work explores machine learning approaches for disting...

In the context of the rapid evolution of digital finance, artificial intelligence (AI) models are deeply integrated into critical business processes such as risk assessment, asset pricing, and anti-fraud. The resultant l...

Floating offshore wind turbines (FOWTs) raise concerns among coastal communities due to their potential impacts on marine biodiversity and fisheries. This issue is particularly striking in France, where the government is...

"Left Bundle Branch Block (LBBB) diagnosis is crucial for patient stratification and the selection of individuals who are likely to respond to Cardiac Resynchronization Therapy (CRT). The pathophysiological distinction b...

As a key element of human settlements and fundamental features in maps, buildings play a critical role in urban planning and environmental monitoring. Automatically extracting buildings from remote sensing images is of s...

Flood disasters, with high suddenness, wide impact and severe consequences, severely threaten ecological security, human lives, property and socioeconomic development. Optical remote sensing, though advantageous in spati...

Recently, a three-terminal interface dipole modulation field-effect transistor (IDM FET) memory device has been proposed that leverages electric-field-induced dipole modulation at oxide/oxide interfaces. This device has ...

Artificial intelligence (AI) models developed for Global Navigation Satellite System Reflectometry (GNSS-R) observations have demonstrated competitive performance in estimating geophysical parameters, especially ocean su...

The analysis and modeling of educational data are of great significance to the evaluation of teaching quality and personalized learning guidance. However, the acquisition of academic data is often limited by the costs of...

Spark detection in distribution line videos remains challenging due to weak visual saliency, multi-scale variation, and complex environmental interference. To address these issues, this paper presents an enhanced Swin Tr...

With the proposal of the national dual-carbon strategic goal, distributed photovoltaic (PV) ushers in new development opportunities, and the management of voltage quality for photovoltaic power stations becomes a key cha...

The detection of transmission towers in remote sensing images presents significant challenges due to insufficient feature representation and significant object size variations, particularly at low spatial resolutions whe...

Unmanned aerial vehicle (UAV) aerial photography technology is crucial in various fields, including daily life, production, and security. However, it faces challenges in small object detection, such as extremely small ob...