Results 101 to 110 of about 5,579,561 (370)
MARRT: Medial Axis biased rapidly-exploring random trees
IEEE International Conference on Robotics and Automation, 2014 Motion planning is a difficult and widely studied problem in robotics. Current research aims not only to find feasible paths, but to ensure paths have certain properties, e.g., shortest or safest paths.
Jory Denny +3 more
semanticscholar +1 more source
On the tree-depth of random graphs
Discrete Applied Mathematics, 2014 The tree-depth is a parameter introduced under several names as a measure of sparsity of a graph. We compute asymptotic values of the tree-depth of random graphs. For dense graphs, p>> 1/n, the tree-depth of a random graph G is a.a.s. td(G)=n-O(sqrt(n/p)). Random graphs with p=c/n, have a.a.s.
Perarnau Llobet, Guillem +1 more
openaire +3 more sources
Flexible Leaf‐Like Fuel Cell From Plasmonic Janus Nanosheet
Advanced Functional Materials, EarlyView.A flexible leaf‐like fuel cell is fabricated by conductive gold nanowire sponge‐supported plasmonic Janus nanosheet, which can generate a power of 8.93 mW cm⁻2 with less than 10% performance deterioration even being bent or twisted. Further assembly in a tree‐like layout demonstrates omnidirectional light harvesting capability and wind resistance ...
Yifeng Huang +3 more
wiley +1 more source
Classification of Alpine Skiing Styles Using GNSS and Inertial Measurement Units
Sensors, 2020 In alpine skiing, four commonly used turning styles are snowplow, snowplow-steering, drifting and carving. They differ significantly in speed, directional control and difficulty to execute.
Christina Neuwirth +5 more
doaj +1 more source
On Random Tree Structures, Their Entropy, and Compression [PDF]
arXiv, 2023 Measuring the complexity of tree structures can be beneficial in areas that use tree data structures for storage, communication, and processing purposes. This complexity can then be used to compress tree data structures to their information-theoretic limit.
arxiv
Carbon Nanotube 3D Integrated Circuits: From Design to Applications
Advanced Functional Materials, EarlyView.As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu +3 more
wiley +1 more source
Active Learning‐Driven Discovery of Sub‐2 Nm High‐Entropy Nanocatalysts for Alkaline Water Splitting
Advanced Functional Materials, EarlyView.High‐entropy nanoparticles (HENPs) hold great promise for electrocatalysis, yet optimizing their compositions remains challenging. This study employs active learning and Bayesian Optimization to accelerate the discovery of octonary HENPs for hydrogen and oxygen evolution reactions.
Sakthivel Perumal +5 more
wiley +1 more source
Parallel Quantum Rapidly-Exploring Random Trees
IEEE AccessIn this paper, we present the Parallel Quantum Rapidly-Exploring Random Tree (Pq-RRT) algorithm, a parallel version of the Quantum Rapidly-Exploring Random Trees (q-RRT) algorithm.
Paul Lathrop +2 more
doaj +1 more source
Monochromatic trees in random tournaments [PDF]
Combinatorics, Probability and Computing, 2019 AbstractWe prove that, with high probability, in every 2-edge-colouring of the random tournament on n vertices there is a monochromatic copy of every oriented tree of order $O(n{\rm{/}}\sqrt {{\rm{log}} \ n} )$. This generalizes a result of the first, third and fourth authors, who proved the same statement for paths, and is tight up to a constant ...
Bucić, M +3 more
openaire +6 more sources
Advanced Functional Materials, EarlyView.Herein, a comprehensive framework that enabled the optimization of colloidal solubility within a high‐dimensional parameter space and study of reversible assembly processes is developed. This data‐driven workflow integrated innovations including the robotic platform for automated AuNPs functionalization, machine learning for predicting and revealing ...
Yueyang Gao +5 more
wiley +1 more source