2890 papers
This paper introduces Proximity-Preserving Neural Subdivision (PNS), a trainable refinement rule that augments Loop subdivision with a bounded, curvature-gated correction to adaptively capture local geometric features while strictly maintaining essential structural properties like rigid motion equivariance, planar reproduction, and spectral stability.
This paper presents a systematic literature review that synthesizes current governance requirements and identifies critical research gaps necessary to establish trustworthy, transparent, and accountable machine-to-machine communication within Autonomous Data Ecosystems.
This study employs a reproducible content analysis of a 50-record crosswalk to map ten higher-education cybersecurity maturity domains against ten authoritative frameworks, revealing that while NIST CSF 2.0 provides comprehensive coverage, a layered approach integrating general risk, operational, sector-specific, and AI standards is necessary for effective institutional governance.
This exploratory study analyzes 607 e-commerce phishing websites in Vietnam from 2022 to 2024 to reveal how attackers increasingly impersonate major platforms like Shopee and Tiki while continuously adapting technical tactics, such as URL structures and protocols, to evade detection.
This paper introduces ChainTrust-LLM, a novel framework that integrates expert feedback with a DAG-based blockchain ledger to detect and mitigate hallucinations in medical Large Language Models, achieving a 64.8% reduction in error rates while ensuring secure, auditable interactions with minimal latency.
This paper proposes a hybrid Siamese deep learning framework that fuses contextual BERT embeddings, lexical Glove-based CNN-BiLSTM features, and handcrafted linguistic metrics to effectively detect duplicate questions on Community Question Answering platforms, achieving 85.03% accuracy on the Quora Question Pairs dataset.
This paper proposes the Intelligent Emergency Decision-support Framework for Flight-deck Safety (IEDFS), a closed-loop system integrating dynamic reasoning, multi-agent cooperative decision-making, and hierarchical path planning to significantly enhance fire containment, casualty survival, and operational recovery in naval flight deck emergencies compared to conventional static approaches.
This scoping review identifies existing metadata-based methods for generating synthetic health data and highlights critical gaps in their standardized evaluation, ethical guidance, and specific applicability to code development in federated analysis contexts.
This paper empirically evaluates a drift-aware incremental clustering approach adapted from malware detection for identifying cryptocurrency rug pulls on Ethereum, finding that while it offers a lower false-positive rate in some instances, a periodically retrained supervised baseline ultimately achieves higher and more stable overall performance.
This paper systematizes the emerging field of hybrid neural modeling by establishing a unified mathematical framework that connects neural networks with mechanistic equations, clarifying their roles in inference and prediction while offering a manifold-learning perspective for uncertainty quantification.