Results 231 to 240 of about 53,776 (298)

Transfer of Episodic Self-Referential Memory across Amnesic Identities in Dissociative Identity Disorder using the Autobiographical Implicit Association Test

, 2018
Bruno Verschuère, Rosie Marsh, Rafaële J. C. Huntjens, Martin J. Dorahy, Warwick, chandele Butler   +5 more
openalex   +2 more sources

Contact Force Estimation of Continuum Robots without Embedded Sensors: A Review

Advanced Intelligent Systems, EarlyView.
This review surveys methods for estimating contact forces in continuum robots without embedded sensors. It explains why contact force matters, classifies force patterns, and groups existing methods into three approaches based on actuation, deformation, and environment information.
An Hu, Yu Sun
wiley   +1 more source

Nosek & Hansen (2008a, 2008b): Attitudes and Knowledge in the Implicit Association Test

, 2009
Brian A. Nosek
openalex   +1 more source

Neuromorphic Photonic Processing and Memory With Spiking Resonant Tunneling Diode Neurons and Neural Networks

Advanced Intelligent Systems, EarlyView.
This work shows resonant tunneling diode‐based opto‐electronic spiking neurons enabling fast edge detection in time series, a two‐layer photonic spiking neural network for complex classification, and a depth‐tunable photonic spiking memory system. Neuromorphic computing—modeled after the functionality and efficiency of biological neural systems—offers ...
Dafydd Owen‐Newns, Joshua Robertson, Giovanni Donati, Qusay Al‐Taai, José Figueiredo, Edward Wasige, Kathy Lüdge, Bruno Romeira, Antonio Hurtado   +8 more
wiley   +1 more source

Predicting Materials Thermodynamics Enabled by Large Language Model‐Driven Dataset Building and Machine Learning

Advanced Intelligent Systems, EarlyView.
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu, Haydn Anderson, Noah I. Waxman, Vsevolod Kovalev, Byron Fisher, Elizabeth Li, Xiaofeng Guo   +6 more
wiley   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Voxel‐SLAM: A Complete, Accurate, and Versatile Light Detection and Ranging‐Inertial Simultaneous Localization and Mapping System

Advanced Intelligent Systems, EarlyView.
: In this work, Voxel‐SLAM (simultaneous localization and mapping) is introduced: a complete, accurate, and versatile LiDAR (light detection and ranging) ‐inertial SLAM system consisting of five modules: initialization, odometry, local mapping (LM), loop closure (LC), and global mapping (GM), all employing the same map representation, an adaptive voxel
Zheng Liu, Haotian Li, Chongjian Yuan, Xiyuan Liu, Jiarong Lin, Rundong Li, Chunran Zheng, Bingyang Zhou, Wenyi Liu, Fu Zhang   +9 more
wiley   +1 more source

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

Advanced Intelligent Systems, EarlyView.
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty, Antonis Vamvakeros, Samuel J. Cooper   +2 more
wiley   +1 more source

Using the Implicit Association Test to Investigate the Strength of Synesthetic Associations

, 2019
Margaret Martinez, Nicole Steiner, Simon Lacey, Lynne C. Nygaard, K. Sathian   +4 more
openalex   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source