Results 191 to 200 of about 8,808,141 (242)

Electrochemical Behavior of Flame‐Sprayed Sc‐Doped AlCoCrFeMo High‐Entropy Alloy Coatings in 3.5% Sodium Chloride Solution

Advanced Engineering Materials, EarlyView.
Scandium (Sc)‐doped AlCoCrFeMo HEA coatings are fabricated via flame spraying with 0.1, 0.3, and 0.5 wt% Sc additions. Among these, the HEA‐Sc0.3 coating exhibits the highest corrosion resistance, indicated by a more positive corrosion potential and lower current density.
Pankaj Kumar, Akash Vyas, Mohammad Aatif Qazi, Nashit Jalal, Maria Ophelia Jarligo, Mostafa Yakout, Jing Liu, André McDonald   +7 more
wiley   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Guest editorial: Total least squares and errors-in-variables modeling

, 2007
Van Huffel, S., Vaccaro, R., Markovsky, I., Soderstrom, T.   +3 more
core   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Collinearity and Total Least Squares

SIAM Journal on Matrix Analysis and Applications, 1994
The least squares (LS) and total least squares (TLS) methods are commonly used to solve the overdetermined system of equations \(Ax\approx b\). The main objective of this paper is to examine TLS when \(A\) is nearly rank deficient by outlining its differences and similarities to the well-known truncated LS method.
Ricardo D. Fierro, James R. Bunch
openaire   +2 more sources

On the equivalence of constrained total least squares and structured total least squares

IEEE Transactions on Signal Processing, 1996
Several extensions of the total least squares (TLS) method that are able to calculate a structured rank deficient approximation of a data matrix have been developed. The main result of this article is the demonstration of the equivalence of two of these approaches, namely, the constrained total least squares (CTLS) approach and the structured total ...
Philippe Lemmerling, Bart De Moor, Sabine Van Huffel   +2 more
openaire   +1 more source

Incomplete total least squares

Numerische Mathematik, 1999
Total least squares (TLS) are fitting data points with some model function such that the sum of squared orthogonal distances is minimized. The authors consider situations where the model is such that there might be no perpendiculars from certain data points onto the model function and where one has to replace certain orthogonal distances by shortest ...
K. Brüntjen, Helmuth Späth
openaire   +3 more sources

Constrained total least squares

ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
The Total Least Squares (TLS) method is a generalized least square technique to solve an overdetermined system of equations Ax\simeqb . The TLS solution differs from the usual Least Square (LS) in that it tries to compensate for arbitrary noise present in both A and b .
Theagenis J. Abatzoglou, Jerry M. Mendel
openaire   +2 more sources

On the recursive total least-squares

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
In this paper, by exploiting the total least-square (TLS) closed-form solution and using state-space structure in Krein space, we show that the solution of the TLS problems can be computed via the recursive Kalman filtering algorithm. This makes it possible to use the TLS for real-time applications.
Cuong Pham 0005, Tokunbo Ogunfunmi
openaire   +2 more sources