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Applied Sciences, Vol. 16, Pages 9093: Security and Safety of Large Language Models—A Use Case for Extended Reality Environments
45+ min ago (361+ words) This research investigates the security of large language models (LLMs) with the aim of identifying key security and safety threats, control measures, and governance considerations that are relevant to their trustworthy adoption in the Extended Reality (XR) domain. To achieve…...
Applied Sciences, Vol. 16, Pages 9083: PV-STAM: Velocity-Aware Attention for Mapless Deep Reinforcement Learning Navigation in Dynamic Environments
4+ hour, 21+ min ago (678+ words) Mapless deep reinforcement learning (DRL) navigation in dynamic indoor environments is difficult under single-frame 2D LiDAR, which reports where an obstacle is but not whether it is approaching. We introduce the Positional-Velocity Spatio-Temporal Attention Module (PV-STAM), a compact perception block (19,968 trainable…...
Applied Sciences, Vol. 16, Pages 9075: An Investigative Study of Widely Used Ergonomic Risk Assessment Methods Based on Machine Learning and MCDM Approaches
23+ hour, 51+ min ago (512+ words) REBA, RULA, and OWAS are widely used observational ergonomic risk assessment methods based on predefined ordinal scoring rules. The final risk scores generated by these methods play a critical role in determining and prioritizing ergonomic interventions under limited resources to…...
Applied Sciences, Vol. 16, Pages 9065: Bayesian Biaffine Variational Graph Convolutional Network for Aspect-Based Sentiment Analysis
1+ day, 3+ hour ago (496+ words) Aspect-based sentiment analysis (ABSA) aims to identify the sentiment polarity expressed toward a specific aspect in a sentence. Existing sequential and Transformer-based methods can effectively capture contextual semantics, but they often lack explicit modeling of aspect–opinion relations. Graph-based approaches…...
Applied Sciences, Vol. 16, Pages 9003: A Knowledge Graph-Augmented Large Language Model Framework for Context-Aware Question-Answering and Intelligent Feedback Generation
2+ day, 22+ hour ago (533+ words) This study proposes EQAS (Empowered Question-Answering System), a hybrid framework designed to support context-aware question-answering and intelligent feedback generation in domain-specific knowledge environments. EQAS integrates fine-tuned transformer-based models, instruction-guided large language models, domain-specific knowledge graphs, and LangChain-based vector retrieval to…...
Applied Sciences, Vol. 16, Pages 9005: DWAT: Density-Weighted Adversarial Training for Robustness Beyond the Training Perturbation Budget
2+ day, 22+ hour ago (571+ words) Deep neural networks (DNNs) are widely deployed in safety-critical applications such as medical diagnosis and autonomous driving. Adversarial training (AT) is among the most effective defenses, casting robust optimization as a min–max problem over a defender-specified ℓp-ball of fixed…...
Applied Sciences, Vol. 16, Pages 9001: Agentic AI-Enabled Digital Twins for Intelligent Non-Destructive Testing of 3D-Printed Rehabilitation Equipment—A Narrative Review
2+ day, 23+ hour ago (688+ words) Digital twins (DTs) based on agent-based artificial intelligence (Agentic AI) provide a transformative framework for streamlining nondestructive testing (NDT) of 3D-printed rehabilitation equipment. This study applies a conceptual research methodology based on the integration and analysis of recent advances in…...
Applied Sciences, Vol. 16, Pages 8991: Early Prediction of Epileptic Seizures Based on Multifractal Analysis and Optimized Graph Neural Networks Using Scalp EEG Data
3+ day ago (452+ words) Early prediction of epileptic seizures remains an active research area in scalp electroencephalography (EEG) analysis. Current methods focused on this topic often rely on handcrafted features that insufficiently capture the multiscale nonlinear dynamics of preictal activity, process EEG channels independently…...
Applied Sciences, Vol. 16, Pages 8993: CDTS2: Causal Downstreamer with Causally Disentangled Trend and Seasonality Time-Series Representations
3+ day, 1+ hour ago (411+ words) Time-series representation learning decomposes signals into interpretable factors such as trend and seasonality, and disentangled representation learning assigns these factors to distinct latent dimensions, enhancing interpretability and forecasting accuracy. However, existing methods achieve only statistical disentanglement: an intervention on one…...
Applied Sciences, Vol. 16, Pages 8987: Hierarchical Point Cloud Analysis for 3D Defect Detection of Annular Welds
3+ day, 2+ hour ago (329+ words) Annular fillet welds on guide rods lie in stress concentration zones and are susceptible to fatigue failure under dynamic suspension loads, necessitating accurate quality inspection. However, their complex three-dimensional topography makes it difficult for conventional methods to balance detection accuracy…...