Results 61 to 70 of about 26,484 (294)
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
Comprehensive review of dimensionality reduction algorithms: challenges, limitations, and innovative solutions [PDF]
PeerJ Computer ScienceDimensionality reduction (DR) simplifies complex data from genomics, imaging, sensors, and language into interpretable forms that support visualization, clustering, and modeling.
Aasim Ayaz Wani
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Advanced Engineering Materials, EarlyView.This article presents the design, modeling, and characterization of air‐pressure–actuated programmable vibroacoustic metamaterials (PVAMM). The study focuses on leveraging air pressure to dynamically tune resonance frequencies for effective noise attenuation.
William Kaal +2 more
wiley +1 more source
EFFECTIVENESS OF DIMENSIONALITY REDUCTION METHODS ON DATA WITH NON-LINEAR RELATIONSHIPS
BarekengThe phenomenon of big data presents distinct challenges in the analysis process, especially when the data contains a very large number of variables.
Lukmanul Hakim +4 more
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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
SensorsWith the rapid advancement of remote-sensing technology, the spectral information obtained from hyperspectral remote-sensing imagery has become increasingly rich, facilitating detailed spectral analysis of Earth’s surface objects.
Wenhui Song +5 more
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Principal Tensor Embedding for Unsupervised Tensor Learning
IEEE Access, 2020 Tensors and multiway analysis aim to explore the relationships between the variables used to represent the data and find a summarization of the data with models of reduced dimensionality. However, although in this context a great attention was devoted to
Claudio Turchetti +2 more
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IET Signal Processing, 2022 Isomap is a well‐known nonlinear dimensionality reduction method that highly suffers from computational complexity. Its computational complexity mainly arises from two stages; a) embedding a full graph on the data in the ambient space, and b) a complete ...
Eysan Mehrbani, Mohammad Hossein Kahaei
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Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Probabilistic Nonlinear Dimensionality Reduction
, 2022 High-dimensional datasets are present across scientific disciplines. In the analysis of such datasets, dimensionality reduction methods which provide clear interpretations of their model parameters are required. Principal components analysis (PCA) has long been a preferred method for linear dimensionality reduction, but is not recommended for data ...
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