Results 71 to 80 of about 5,834,158 (292)
Advanced Engineering Materials, EarlyView.Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn +5 more
wiley +1 more source
Computing the Wave-Kernel Matrix Functions [PDF]
SIAM Journal on Scientific Computing, 2018 Summary: We derive an algorithm for computing the wave-kernel functions \(\cosh\sqrt{A}\) and \(\mathrm{sinhc}\sqrt{A}\) for an arbitrary square matrix \(A\), where \(\mathrm{sinhc}z=\sinh(z)/z\). The algorithm is based on Padé approximation and the use of double angle formulas.
Nadukandi, Prashanth +1 more
openaire +2 more sources
A Kernel-Based Approach for Biomedical Named Entity Recognition
The Scientific World Journal, 2013 Support vector machine (SVM) is one of the popular machine learning techniques used in various text processing tasks including named entity recognition (NER).
Rakesh Patra, Sujan Kumar Saha
doaj +1 more source
Advanced Engineering Materials, EarlyView.This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji +3 more
wiley +1 more source
Journal of Applied Mathematics, 2011 We aimed to derive a kernel function that accounts for the interaction among moving particles within the framework of particle method. To predict a computationally more accurate moving particle solution for the Navier-Stokes equations, kernel function ...
Tony W. H. Sheu +2 more
doaj +1 more source
Support Vector Machines (SVMs) versus Multilayer Perception (MLP) in data classification
Egyptian Informatics Journal, 2012 In this paper, we introduce a new kernel function for improving the accuracy of the Support Vector Machines (SVMs) classification. The proposed kernel function is stated in general form and is called Gaussian Radial Basis Polynomials Function (GRPF) that
E.A. Zanaty
doaj +1 more source
Advanced Engineering Materials, EarlyView.This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
A forward-constrained regression algorithm for sparse kernel density estimation [PDF]
, 2008 Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward-constrained regression (FCR) manner. The proposed algorithm selects significant kernels one at a time, while the leave-
Harris, C. J. +8 more
core +1 more source
WLAN indoor positioning algorithm based on skewness-kurtosis testing
Tongxin xuebao, 2012 Focused on the issues that large positioning errors produced by the inconsistency of received signal strength (RSS)sample population distributions under indoor wireless local area network (WLAN),an indoor positioning algorithm based on skewness-kurtosis ...
Zhen-long SONG +4 more
doaj
Application of the multi-kernel non-negative matrix factorization on the mechanical fault diagnosis
Advances in Mechanical Engineering, 2015 Although the computation amount involved in the image processing is very large, image information which is very intuitive and easy to be understood has attracted great many attentions in the fault diagnosis of machines.
Yongsheng Yang +2 more
doaj +1 more source