Results 61 to 70 of about 9,194 (262)
Advanced Materials, EarlyView.Rapid thiol‐maleimide addition frequently outpaces mixing, resulting in heterogeneous hydrogels. S‐nitrosothiols act as thiol‐protecting groups, allowing uniform mixing with maleimide‐functionalized polymers before gelation. Sodium thiosulfate or sodium ascorbate then regenerates thiols on demand, triggering controlled thiol‐maleimide crosslinking ...
Julian A. Serna +7 more
wiley +1 more source
Fuzzy Logic Based Teaching/Learning of a Foreign Language in Multilingual Situations
Acta Linguistica Asiatica, 2017 The concept of Fuzzy Logic (FL) has gained momentum in areas of artificial intelligence and allied researches because of its absolute ability to present efficient solutions to real life problems.
Sweta SINHA
doaj +1 more source
Advanced Materials Technologies, EarlyView.Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim +6 more
wiley +1 more source
On‐Chip Photonic Neural Network Architectures
Advanced Optical Materials, EarlyView.This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Why is “not infrequent” not always “frequent”? Double negation in political discourse
ExELL (Explorations in English Language and Linguistics), 2015 The aim of this paper is to view double negation in the light of its semantic and pragmatic meaning. While double negation in logic gives a positive value, in natural languages, besides having positive entailment, it can have a range of different ...
Osmankadić Merima
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Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
Advanced Robotics Research, EarlyView.A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
Natural language processing and logic programming
The Journal of Logic Programming, 1994 AbstractThis paper examines the main points of contact between logic programming and natural language processing, and covers some of the important issues that arise using logic programming techniques in natural language processing. It emphasizes the importance of taking into account the most general analyses from linguistic theory in building NLP ...
openaire +2 more sources
LLM‐Integrated Human–Robot Interaction System for Microrobots
Advanced Robotics Research, EarlyView.This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source
Advanced Robotics Research, EarlyView.DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano +3 more
wiley +1 more source