Results 151 to 160 of about 283,589 (317)

Iterative Data Curation for Machine Learning‐Based Inverse Design of Active Composite Plates for Four‐Dimensional Printing

Advanced Intelligent Systems, EarlyView.
A machine learning framework is developed for the inverse design of 4D‐printed active composite plates. It utilizes a forward model to predict shapes from patterns and an inverse model to suggest initial patterns for desired shapes. This framework integrates a genetic algorithm to refine the predicted patterns, ensuring higher accuracy in achieving ...
Teerapong Poltue, Chao Zhang, Frédéric Demoly, Kun Zhou, H. Jerry Qi   +4 more
wiley   +1 more source

Neural Networks as Universal Finite-State Machines: A Constructive Deterministic Finite Automaton Theory [PDF]

Sahil Rajesh Dhayalkar
openalex   +1 more source

An nlogn algorithm for hyper-minimizing a (minimized) deterministic automaton

Theoretical Computer Science, 2010

semanticscholar   +1 more source

Microrobotic Catheterization of the Ophthalmic Artery for Targeted Treatment of Retinoblastoma

Advanced Intelligent Systems, EarlyView.
A microrobotic platform is presented that allows teleoperated and autonomous navigation of flow‐driven magnetic microcatheters, MagFlow, into the ophthalmic artery for superselective intra‐arterial infusion of chemotherapy to treat retinoblastoma. Extensive benchtop validations with patient‐derived biomimetic phantoms under optical and fluoroscopic ...
Artur Banach, Mehdi Krichen, Julian Raub, Christina Stathopoulos, Bruno Bartolini, Mahmut Selman Sakar   +5 more
wiley   +1 more source

Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions

Advanced Intelligent Systems, EarlyView.
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, Yingqian Xu, Caihua Wan, Ran Zhang, Meike Hindenberg, Raik Hoffmann, Shiqiang Liu, Tianyi Zhang, Shilong Xiong, Dehao Kong, Jihao Xia, Fangshuo Gao, Zhuyang Nie, Thomas Kämpfe, Guoqiang Yu, Xiufeng Han   +15 more
wiley   +1 more source

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

Advanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad, Solomon Amsalu Chekol, Julius Rasbach, Susanne Hoffmann‐Eifert, Stephan Menzel   +4 more
wiley   +1 more source

Cosmos Automaton: A Deterministic Fractal Automaton Generating Primes

Birke Heeren
  +5 more sources

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

Collaborative Multiagent Closed‐Loop Motion Planning for Multimanipulator Systems

Advanced Intelligent Systems, EarlyView.
This work presents a hierarchical multi‐manipulator planner, emphasizing highly overlapping space. The proposed method leverages an enhanced Dynamic Movement Primitive based planner along with an improvised Multi‐Agent Reinforcement Learning approach to ensure regulatory and mediatory control while ensuring low‐level autonomy. Experiments across varied
Tian Xu, Siddharth Singh, Qing Chang
wiley   +1 more source

Safe reinforcement learning under temporal logic with reward design and quantum action selection. [PDF]

Sci Rep, 2023
Cai M, Xiao S, Li J, Kan Z.
europepmc   +1 more source