Results 181 to 190 of about 237,968 (367)
Advanced Intelligent Systems, EarlyView.This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer +2 more
wiley +1 more source
Multicomponent Stapling of Glucagon‐Like Peptide‐1 Enables Receptor‐Guided PROTAC Delivery
Angewandte Chemie, EarlyView.We report a stapled glucagon‐like peptide‐1 (GLP‐1) analogue created via multicomponent tryptophan‐mediated Petasis reaction (TMPR). This strategy yields a stabilised peptide with superior helicity and improved potency. Conjugation to a bromodomain‐containing protein 4 (BRD4) degrader creates the first GLP‐1‐guided targeted protein degrader (PROTAC ...
Jan L. Venne +5 more
wiley +2 more sources
Spatial association and modeling of road traffic deaths in Thailand, 2022. [PDF]
Popul Health MetrOo YH +3 more
europepmc +1 more source
A Study of Road Traffic Accident (RTA) Deaths in a Teaching Hospital in Ahmedabad from January 2014 to June 2014 classified according to ICD-10 [PDF]
, 2015 Rakesh Vahoniya +2 more
openalex
Road Traffic Accidents and Injuries Among Form 6 Students in Muar [PDF]
, 2016 Roy Rillera Marzo
openalex +1 more source
, 2014 Fifty percent of drives have been found to frequently violate speed limits (OECD/ECMT, 2006), and speed limit compliance appears to depend on the perceived credibility of a road’s speed limit (Goldenbeld & van Schagen, 2007). Credibility of speed limits,
Ahie, Liv Marit
core
Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning
Advanced Intelligent Systems, EarlyView.A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang +6 more
wiley +1 more source
Road Traffic Anomaly Detection by Human-Attention-Assisted Text-Vision Learning. [PDF]
Sensors (Basel)Chai Y, Silamu W.
europepmc +1 more source
Automated driving: the legal hurdles for road traffic laws on the road ahead
, 2020 Nynke Vellinga
openalex +1 more source