Results 21 to 30 of about 13,526 (126)

Universal Gripper for Industrial Manipulation With Enhanced Rigid Mechanics and Self‐Adaptable Fingers

Advanced Robotics Research, EarlyView.
An enhanced universal gripper combining rigid mechanics with self‐adaptable fingers is presented for industrial automation. The novel six‐bar linkage with integrated compliant pad eliminates mechanical interference while enabling passive shape adaptation.
Muhammad Usman Khalid, Nirmal Kumar Ravikumar, Mattia Frascio, Sumanth Nagalakunta, Alessandro Seitone, Benoît Lévesque, Alessandro Zanella, Matteo Zoppi   +7 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns

Advanced Intelligent Discovery, EarlyView.
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer, André Orth, Robert Wang, Ben Breitung, Simon Schweidler, Jasmin Aghassi‐Hagmann, Markus Reischl   +6 more
wiley   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

Fourier series and Chebyshev polynomials applied to real-time water demand forecasting

, 2017
Relevance of water demand forecasting increases with complexity of water supply systems. Several methods for water demand forecasting have been proposed in literature, mostly based on time-series analysis and machine learning, the later needing more ...
B. Brentan, E. Luvizotto, J. Izquierdo, R. Pérez-García   +3 more
semanticscholar   +1 more source

Beyond Directions: Symmetry‐Aware Rotation Sets for Triaxial Diffusion Encoding by Geometric Filter Optimization

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To improve the accuracy of diffusion‐weighted powder average signals for diffusion encoding with arbitrary b‐tensors. Methods We identify an intrinsic dihedral (D2$$ {D}_2 $$) symmetry of diffusion signals for arbitrary diffusion encoding, which defines their natural signal space (a quotient of 3D rotations).
Sune Nørhøj Jespersen, Filip Szczepankiewicz   +1 more
wiley   +1 more source

Pickin' up good vibrations: a systematic review of footfall detection and analysis in the realm of wildlife surveying

Wildlife Biology, EarlyView.
Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge, Luigi La Spada, Robert A. Briers, Niamh M. McHugh, Patrick J. C. White   +4 more
wiley   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

Parallel Vectors Extraction using Bézier Clipping

Computer Graphics Forum, EarlyView.
Abstract In this paper, we propose a novel local feature extraction algorithm for the parallel vectors (PV) operator. Our method is based on Bézier clipping, which is a bracketing‐based root finding method that is commonly‐used in computer‐aided geometric design.
Nico Daßler, Tobias Günther
wiley   +1 more source

Fast Nodal Hessian Computation for Peridynamic Fracture Simulation

Computer Graphics Forum, EarlyView.
A fast, exact nodal Hessian computation for Non‐Ordinary State‐Based Peridynamics is introduced through analytical simplification and a warp‐centric GPU strategy. The method accelerates preconditioned solvers and Vertex Block Descent, enabling interactive fracture simulation with physical accuracy.
Yuxiong Qin, Qingfu Zhang, Zhongkai Zhang   +2 more
wiley   +1 more source