Results 121 to 130 of about 22,663 (297)
Constrained projection approximation algorithms for principal component analysis
, 2019 In this paper, we introduce a new error measure, integrated reconstruction error (IRE) and show that the minimization of IRE leads to principal eigenvectors (without rotational ambiguity) of the data covariance matrix.
Cichocki, A, Choi, S, Ahn, JH
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Advanced Materials, EarlyView.This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao +8 more
wiley +1 more source
Forward Projection for Use with Iterative Reconstruction
Modelling the forward projection or reprojection, that is defined as the operation that transforms a 3D volume into series of 2D set of line integrals, is of interest in several medical imaging applications as iterative tomographic reconstruction (X-ray,
Raja Guedouar, Boubaker Zarrad
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Algorithms for projection methods for solving linear systems of equations
, 1977 The solution of linear systems of equations using various projection algorithms is considered. Since nonsingularity of the coefficient matrix is the only requirement for convergence, techniques for increasing the rate of convergence are presented ...
Keller, R.F., Wainwright, Roger L.
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Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, EarlyView.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
Advanced Materials, EarlyView.A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong +11 more
wiley +1 more source
Evaluation model and its iterative algorithm by alternating projection
Mathematical and Computer Modelling, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Xenes for Sustainable Energy: A Roadmap From First‐Principles Design to Practical Deployment
Advanced Materials Interfaces, EarlyView.Emerging 2D Xenes are advancing from theoretical predictions toward practical energy‐storage and conversion technologies through the integration of first‐principles modelling, experimental synthesis, electrochemical validation, and AI‐assisted materials design, enabling accelerated discovery of high‐performance and sustainable electrochemical systems ...
Onur Karaman, Ceren Karaman
wiley +1 more source
A New Variational Inequality with its Application
, 2009 In this paper, we suggest the iterative algorithm for a variational inequality by using the auxiliary principle technique, which is closely related to the optimal boundary control of time-varying population system with age-dependence and spatial ...
Shi, Chao-Feng
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Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source