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When voyage report data is utilized as the main data source for ship fuel efficiency analysis, its information on weather and sea conditions is often regarded as unreliable. To solve this issue, this study approaches AIS...

BackgroundIn the field of geological exploration of coal mines, methods such as in-seam seismic exploration, the transient electromagnetic method, and audio-frequency electrical penetration offer unique technical advanta...

Abstract The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system. Bench test data are easily obtained, but it is challenging to emulate...

Remote sensing-derived building footprint data has been widely applied in population mapping. However, nonresidential buildings typically occupy larger areas or volumes, and obtaining building footprint data with type in...

Abstract Long-read transcriptome sequencing (long-RNA-seq) revolutionizes transcriptome research by enabling full-length transcript analysis for comprehensive exploration of isoform diversity. We developed IFDlong, a pro...

Abstract The rapid development of China’s financial markets, particularly the expansion of the ETF ecosystem, has made dynamic sector rotation strategies increasingly feasible and cost-effective for investors. At the s...

Category: Hindfoot, Ankle Arthritis Keywords: Wound Complications, Total Ankle Arthroplasty, Revision Ankle Arthroplasty Introduction/Purpose: Total ankle arthroplasty (TAA) preserves motion, while ankle arthrodesis (AF)...

To fully exploit the advantages of GNSS-R small satellites (large quantity, short revisit cycle) and address key challenges of multisource GNSS-R data—track-wise distribution, uneven spatial coverage, and observat...

ABSTRACT This paper presents an event‐triggered pinning observer‐based control of unknown large‐scale interconnected systems under false data injection attacks using distributed noisy data without any system identi...

System-level remaining useful life (RUL) prediction is challenging because multisensor data fusion requires an integrated representation of multicomponent degradation, and the uncertainty of model parameters is often ove...

Abstract Air-conditioning load forecasting is important for building energy scheduling and control. The task is difficult because load data show clear periodic patterns, and sudden changes caused by events such as holida...

Abstract For a single-structure deep learning fault diagnosis model, its disadvantages are an insufficient feature extraction and weak fault classification capability. This paper proposes a multi-scale deep feature fusio...

Abstract In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) play a vital role in enabling seamless communication between connected devices. In a WSN data prediction system based, clustering and...

The dynamic range limitation is intrinsic to conventional RGB cameras, which reduces global contrast and causes the loss of high-frequency details such as textures and edges in complex, dynamic traffic environments (e.g....

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 ...

Abstract Background Super-enhancers are critical cis-regulatory elements that play a central role in modulating gene expression and driving cellular identity. Their dysregulation is closely associated with the developmen...

Abstract Unmanned Aerial Vehicles (UAVs) are pivotal in tasks such as traffic monitoring and rescue operations, yet detecting small objects in UAV images remains challenging due to their diminutive size, low resolution, ...

Abstract Facial Expression Recognition (FER) demonstrates significant value in practical scenarios such as intelligent human–computer interaction. However, conventional FER methods often struggle to balance performance...

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...

Autonomous underwater vehicles (AUVs) operating in harsh, communication-limited underwater environments require robust fault diagnosis systems to ensure mission success and safety. Existing model-based approaches suffer ...

Tropical dry forests and savannas provide important ecosystem services and harbor high biodiversity, yet are globally under pressure from land-use change. Mapping changes in the condition of dry forests and savannas is t...

Plant-scale industrial carbon accounting is critical for developing targeted emission-reduction policies. However, most assessments of carbon-intensive sectors rely on aggregate statistics, which obscure significant hete...

This article presents an innovative technique for remote sensing-based mapping and predicting land degradation in the European frontier regions. The mapping is carried out by geospatial data fusion of relevant biophysica...

Accurate detection of pediatric fractures in radiographs remains challenging due to subtle visual cues and the high prevalence of false-positive detections produced by automated systems. To address this limitation, we pr...