Sensitivity analysis of unsafe behaviors in the spinning and weaving factories: Exploring the association with burnout and resilience using Bayesian networks. [PDF]
Azimi R +5 more
europepmc +1 more source
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim +4 more
wiley +1 more source
Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li +15 more
wiley +1 more source
Causal mapping of psychological and occupational risk factors for suicidal ideation in psychiatric nurses using Bayesian networks: A multicenter cross-sectional study. [PDF]
Wang M +9 more
europepmc +1 more source
Metalearning‐based inverse optimization enables precise microscale three‐dimensional printing using a DLP system. Distorted structures from conventional printing are analyzed via neural network regression, which predicts optimal exposure time and mask design.
Jae Won Choi +3 more
wiley +1 more source
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong +4 more
wiley +1 more source
Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin +4 more
wiley +1 more source
Forecasting Subjective Cognitive Decline: AI Approach Using Dynamic Bayesian Networks.
Etholén A +7 more
europepmc +1 more source
Behavioral Analysis of Postgraduate Education Satisfaction: Unveiling Key Influencing Factors with Bayesian Networks and Feature Importance. [PDF]
Li S, Wang T, Yin H, Ding S, Cai Z.
europepmc +1 more source
A modular eight‐legged robot exploits anisotropically oriented soft I‐beam backbones to transmit vibration from a single unbalanced‐mass actuator, producing frequency‐dependent multimodal gaits. A pseudo‐rigid‐body model enables high‐fidelity MuJoCo simulation, while Bayesian parameter identification and reinforcement learning yield robust control ...
Yiğit Yaman +4 more
wiley +1 more source

