Results 141 to 150 of about 140,688 (313)
A new job priority rule for the NEH-based heuristic to minimize makespan in permutation flowshops
Jianghua Zhang +6 more
openalex +1 more source
Context‐Aware Semiautonomous Control for Upper‐Limb Prostheses
A semiautonomous prosthetic control strategy integrates electromyographic‐based intention with computer vision‐driven grasp adaptation and wrist orientation. Comparative experiments with functional tasks evaluate performance, usability, and cognitive workload.
Gianmarco Cirelli +7 more
wiley +1 more source
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 +3 more
wiley +1 more source
Do People Make Decisions Under Risk Based on Ignorance? An Empirical Test of the Priority Heuristic against Cumulative Prospect Theory [PDF]
Andreas Glöckner, Tilmann Betsch
openalex
: 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 +9 more
wiley +1 more source
Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza +2 more
wiley +1 more source
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 +2 more
wiley +1 more source
Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang +7 more
wiley +2 more sources
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
The Priority Heuristics for Concurrent Parsing of JavaScript
Myungsu Cha, Hyukwoo Park, Soo-Mook Moon
openaire +1 more source

