Results 241 to 250 of about 2,525,472 (291)
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Mg–Zn composites with a thickness of 0.21 mm were fabricated using roll bonding of a kirigami‐patterned Mg alloy inlay within a Zn matrix. Thermal activation following this process led to the formation of tailored intermetallic structures, which provided the composite with enhanced flexural strength.
Yaroslav Frolov +4 more
wiley +1 more source
Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading
Advanced Engineering Materials, EarlyView.The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley +1 more source
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Consistency of incomplete data
Information Sciences, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Patrick G. Clark +2 more
openaire +2 more sources
Statistical Methods in Medical Research, 2007
The researcher collecting hierarchical data is frequently confronted with incompleteness. Since the processes governing missingness are often outside the investigator's control, no matter how well the experiment has been designed, careful attention is needed when analyzing such data.We sketch a standard framework and taxonomy largely based on Rubin's ...
Caroline, Beunckens +3 more
openaire +2 more sources
The researcher collecting hierarchical data is frequently confronted with incompleteness. Since the processes governing missingness are often outside the investigator's control, no matter how well the experiment has been designed, careful attention is needed when analyzing such data.We sketch a standard framework and taxonomy largely based on Rubin's ...
Caroline, Beunckens +3 more
openaire +2 more sources
Gaussian kernels for incomplete data
Applied Soft Computing, 2019Abstract This paper discusses a method to estimate the expected value of the Gaussian kernel in the presence of incomplete data. We show how, under the general assumption of a missing-at-random mechanism, the expected value of the Gaussian kernel function has a simple closed-form solution.
Mesquita, Diego P.P. +5 more
openaire +2 more sources
MISS: Analysis of Incomplete Data
Multivariate Behavioral Research, 1988MISS is a computer program written in the GAUSS programming language for the microcomputer (with DOS operating system and mathcoprocessor). It provides several options for incomplete data sets. First, it will produce maximum likelihood estimates of the covariance matrix and mean vector via the EM algorithm.
R, Schoenberg, G, Arminger
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2001
Database technology, as well as the bulk of data mining technology, is founded upon logic, with absolute notions of truth and falsehood, at least with respect to the data set. Patterns are discovered exhaustively, with carefully engineered algorithms devised to determine all patterns in a data set that belong to a certain class.
openaire +1 more source
Database technology, as well as the bulk of data mining technology, is founded upon logic, with absolute notions of truth and falsehood, at least with respect to the data set. Patterns are discovered exhaustively, with carefully engineered algorithms devised to determine all patterns in a data set that belong to a certain class.
openaire +1 more source
On Fuzzy Clustering for Incomplete Spherical Data and for Incomplete Multivariate Categorical Data
2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), 2018In this paper, six fuzzy clustering algorithms for incomplete data are proposed that use the optimal completion strategy, three of which are for incomplete spherical data and these of which are for incomplete categorical multivariate data. In numerical experiments using a real dataset, each of the proposed methods outperformed its counterpart method ...
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On Difference of Means with Incomplete Data
Biometrika, 1974SUMMARY An estimate of the difference of means is obtained when sampling from a bivariate normal distribution with variances o-2 and o- and correlation p, where some observations on either of the variables are missing. It is shown that this estimate has desirable properties.
Lin, Pi-Erh, Stivers, Lawrence E.
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