Results 161 to 170 of about 353,794 (300)

Automation of Surgical Workflow Recognition: Unveiling the Surgical Instrument Kinematics that Underly Robot‐Assisted Prostatectomy Procedures

open access: yesAdvanced Intelligent Discovery, EarlyView.
Automated procedural analysis is recognized as one of the major game changers for robotic surgery. Meaning digital analysis needs to replace the manual assessments that set todays standard. Mechanical robotic‐instrument tracking enables the derivation of quantitative kinematic metrics that support behavior‐based workflow segmentation into distinct ...
Kateryna Pirkovets   +4 more
wiley   +1 more source

Electrothermally Controlled 3D‐Printed Shape Memory Polymers for Near‐Ambient Temperature Soft Robotic Applications

open access: yesAdvanced Intelligent Systems, EarlyView.
In this article, we develop bespoke resins for stereolithography 3D‐printing of soft‐robotic grippers that are controlled remotely by electrothermal stimulus near ambient temperatures. Turning on the electrical control, each finger can be actuated separately.
Kalyan Ghosh   +4 more
wiley   +1 more source

Design‐for‐Benchmarking in Soft Robotics: Navigating Component‐System Dichotomy

open access: yesAdvanced Intelligent Systems, EarlyView.
Soft robotics faces a profound evaluation challenge: the Component‐System Dichotomy, where isolated component tests fail to predict integrated performance. This article presents a systematic survey of critical reporting gaps across actuation, sensing, and control.
Matteo Lo Preti   +4 more
wiley   +1 more source

SiOx‐Based Probabilistic Bits Enabling Invertible Logic Gate for Cryptographic Applications

open access: yesAdvanced Intelligent Systems, EarlyView.
To enable lightweight hardware encryption and decryption, a Ti/SiOx/Ti threshold switching device is engineered to generate controllable stochastic oscillations. By tuning the input voltage, the device produces a programmable spike probability governed by intrinsic switching dynamics, enabling probabilistic bits that construct an invertible ...
Jihyun Kim, Hyeonsik Choi, Jiyong Woo
wiley   +1 more source

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

open access: yesAdvanced 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

Home - About - Disclaimer - Privacy