M-AMST: an automatic 3D neuron tracing method based on mean shift and adapted minimum spanning tree. [PDF]
BMC Bioinformatics, 2017 Wan Z +5 more
europepmc +1 more source
Multistable Composite Laminate Grids as a Design Tool for Soft Reconfigurable Multirotors
Advanced Intelligent Systems, EarlyView.Flexible, lightweight, stable: the reconfigurable multirotor combines stable flight in multiple shapes with low‐energy reconfiguration. Utilizing optimized multistable composites, it achieves self‐locking in open and folded configurations, cutting width‐span by 48% and allowing for safe gap traversal.
Luca Girardi +4 more
wiley +1 more source
Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network. [PDF]
Comput Math Methods Med, 2017 Guo H, Qin M, Chen J, Xu Y, Xiang J.
europepmc +1 more source
Robot‐Assisted Measurement of the Critical Micelle Concentration
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio +3 more
wiley +1 more source
Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Normal Controls With Subnetwork Selection and Graph Kernel Principal Component Analysis Based on Minimum Spanning Tree Brain Functional Network. [PDF]
Front Comput Neurosci, 2018 Cui X +6 more
europepmc +1 more source
Advancements in Machine Learning for Microrobotics in Biomedicine
Advanced Intelligent Systems, EarlyView.Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi +6 more
wiley +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source