Results 101 to 110 of about 26,804 (294)
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 +5 more
wiley +1 more source
Nonlinear Dimensionality Reduction as Information Retrieval [PDF]
, 2008 Nonlinear dimensionality reduction has so far been treated either as a data representation problem or as a search for a lowerdimensional manifold embedded in the data space. A main application for both is in information visualization, to make visible the
core
Cross-modal Representation Learning with Nonlinear Dimensionality Reduction [PDF]
, 2019 In many problems in machine learning there exist relations between data collections from different modalities. The purpose of multi-modal learning algorithms is to efficiently use the information present in different modalities when solving multi-modal ...
Semih Kaya +3 more
core +1 more source
Advanced Engineering Materials, EarlyView.Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
wiley +1 more source
Dimensionality Reduction Nonlinear Partial Least Squares Method for Quality-Oriented Fault Detection
MathematicsUnlike traditional fault detection methods, quality-oriented fault detection further classifies the types of faults into quality-related and non-quality-related faults.
Jie Yuan, Hao Ma, Yan Wang
doaj +1 more source
Graph Embedding and Nonlinear Dimensionality Reduction
, 2011 Traditionally, spectral methods such as principal component analysis (PCA) have been applied to many graph embedding and dimensionality reduction tasks. These methods aim to find low-dimensional representations of data that preserve its inherent structure.
openaire +2 more sources
Advanced Engineering Materials, EarlyView.Deep‐UV (258 nm) femtosecond pulses enable uniform amorphous silicon writing on Si(100)/(111) with a six‐fold larger fluence amorphization window than NIR methods. Optimized fluence and overlap yield 20–45 nm uniform and continuous amorphous layers. Microscopy shows sharp interfaces, and real‐time reflectivity reveals nanosecond melt–resolidification ...
Wissal Benali +5 more
wiley +1 more source
Nonlinear dimensionality reduction and Bayesian optimization for accelerating design of materials
Scientific ReportsOptimizing biobased foam formulations is challenging because experiments are costly and fast-to-measure surrogate properties occupy high-dimensional spaces.
Muhammad Osman Nadeem Farooqui +4 more
doaj +1 more source
Spin Injection Of Exciton–Polaritons With Halide Perovskites At Room Temperature
Advanced Functional Materials, EarlyView.A monolithic Tamm‐plasmon microcavity embedding a two‐dimensional halide perovskite enables room‐temperature spin injection of exciton‐polaritons under quasi‐resonant optical excitation. Polarization‐resolved spectroscopy reveals partial preservation of the injected spin in the lower polariton branch, while bare excitons remain fully depolarized.
Elena Sendarrubias Arias‐Camisón +8 more
wiley +1 more source
Complexity, 2019 In this paper, a four-dimensional (4-D) memristor-based Colpitts system is reaped by employing an ideal memristor to substitute the exponential nonlinear term of original three-dimensional (3-D) Colpitts oscillator model, from which the initials ...
Yunzhen Zhang +5 more
doaj +1 more source