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This study investigates the long-term aging effects and structural degradation mechanisms of photovoltaic (PV) modules integrated into smart city furniture, with a particular focus on panels of 10 W, 25 W, and 40 W nomin...

Due to error sources arising from undersampling of target signals and imperfections in background models, the single-pair satellite gravity missions equipped with the low-low satellite-to-satellite tracking technology ar...

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...

Real-time streaming pipelines are increasingly central to data-driven product decisions, yet the data quality literature has focused predominantly on batch systems. We present ADQM (Adaptive Data Quality Monitor), a fram...

In this study, an Entropy Transformed Pareto Distribution (EnTrPD) was proposed to provide improved flexibility in modelling heavy-tailed behavior observed in data, and was subsequently applied to assess wealth inequalit...

Manual monitoring of intravenous (IV) therapy is labor-intensive and susceptible to human error, posing risks to patient safety. Existing computer vision-based approaches have addressed either drip rate estimation or flu...

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...

Lipoprotein(a) [Lp(a)] is a useful marker for cardiovascular risk stratification. Previous studies have shown higher Lp(a) levels in women than in men and sex differences in its association with atherosclerosis. The aim ...

This study compares seven quantum algorithms—Variational Quantum Eigensolver (VQE), Variational Quantum Deflation (VQD), Quantum Approximate Optimization Algorithm (QAOA), Quantum Amplitude Estimation (QAE), Quant...

The increasing integration of inverter-interfaced renewable energy sources has significantly changed the dynamic characteristics of modern power systems, resulting in a substantial decline in effective system inertia and...

Customer churn prediction is essential across data-driven industries such as insurance, digital banking, e-commerce, and subscription platforms, where retaining existing customers is typically more cost-effective than ac...

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...

This paper presents an inductorless design methodology for compact single-pole double-throw (SPDT) switches in Sub-6 GHz applications. To achieve compactness and meet key performance metrics below 5.0 GHz, the methodolog...

Abstract Vascularized submental lymph node (VSLN) flap transfer is a promising treatment for lymphedema, yet its venous anatomy remains underexplored. This study investigated variations of the submental artery and vein a...

Understanding how semantic information flow reorganizes market topology remains an open challenge in financial network analysis. Prior work typically emphasizes price correlations or sentiment polarity, but rarely quanti...

Cybersecurity education often struggles to engage learners while effectively conveying complex web vulnerabilities. This challenge is particularly evident in topics such as cross-site scripting (XSS), where understanding...

Terrestrial evaporation ($E$) plays a crucial role in the water, energy, and carbon cycles and modulates climate change through multiple feedback mechanisms. While process-based models estimate $E$ using satellite-derive...

Zernike moments are well-suited for unmanned aerial vehicle scene matching because of their rotation invariance and robustness to noise. However, their high computational complexity poses challenges for meeting the real-...

Mobility-as-a-Service (MaaS) orchestration faces critical challenges in managing the Service Quality Index (SQI), Fleet Utilization Ratio (FUR), and Dynamic Pricing Index (DPI) under uncertain and time-varying urban dema...

Federated Prompt Learning (FPL) enables efficient collaborative adaptation of large-scale models, but it remains vulnerable to data heterogeneity: locally optimized prompts may become biased, thereby weakening the aggreg...

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...

This article explores the impact of electromagnetic interference from consumer electronics and common household appliance on the performance of Global Navigation Satellite System (GNSS) receivers in smartphones. As GNSS ...

Emergency evasive maneuvers unfold in short near-limit windows in which combined-slip saturation, load transfer, and rapidly varying friction make onset-computation budget and model mismatch critical to collision-avoidan...

A compact $64\times 64$ magnetic RAM (MRAM)-based analog computing-in-memory (ACIM) macro is presented, co-optimizing in-memory techniques to overcome the inherently small read margin of MRAM-based ACIM. Based on a sin...