Results 61 to 70 of about 1,585 (209)

Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity

Arthritis Care &Research, EarlyView.
Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley   +1 more source

Neuro-Fuzzy control for four Wheels electric vehicle safety

Revue des Énergies Renouvelables, 2017
This paper present novel approach for traction control of four wheel electric propulsion system for each wheel. This algorithm is necessary to improve the vehicle safety, the independent Machine Control philosophy is employed using an intelligent ...
A. Nasri, B. Gasbaoui
doaj  

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Multi-task collaborative recognition technology for intelligent driving vehicles driven by computer vision

Frontiers in Mechanical Engineering
IntroductionTo develop a multi-task collaborative intelligent driving perception system enabling high-precision integrated recognition of pedestrians, roads, and vehicles, this study proposes a corresponding recognition technology.MethodsFor pedestrian ...
Huandong Wang, Jiayu Yang, Ruomiao Wang, Haozuo Su, Xuanzheng Wang   +4 more
doaj   +1 more source

Beyond Visual Scoring: Computational CT‐analysis for HRCT based quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, Accepted Article.
Interstitial lung disease (IRD‐ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRD). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the non‐invasive assessment of ILD; however, its interpretation is constrained by substantial inter‐observer variability and ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source

Self-Powered Sensing System for Electric Vehicle Drive Condition Monitoring and Driving Condition Identification in Intelligent Electric Vehicles

Research
It is crucial to monitor the real-time and accurate status of an electric drive system and understand its interaction with driving behavior in order to meet the higher requirements for vehicle safety and reliability in the era of autonomous driving ...
Jianfeng Tang, Haoyuan Li, Yong Hu, Yinglong Shang, Hengyu Li, Hailong Tian, Peng Liu, Liming Zhou, Jianhai Zhang, Hongwei Zhao   +9 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

An Autonomous Vehicle Behavior Decision Method Based on Deep Reinforcement Learning with Hybrid State Space and Driving Risk

Sensors
Behavioral decision-making is an important part of the high-level intelligent driving system of intelligent vehicles, and efficient and safe behavioral decision-making plays an important role in the deployment of intelligent transportation system, which ...
Xu Wang, Bo Qian, Junchao Zhuo, Weiqun Liu   +3 more
doaj   +1 more source