Results 141 to 150 of about 26,356,550 (281)
Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency
Advanced Science, EarlyView.This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun +9 more
wiley +1 more source
Research on Recognition Method of Driving Fatigue State Based on Sample Entropy and Kernel Principal Component Analysis. [PDF]
Entropy (Basel), 2018 Ye B, Qiu T, Bai X, Liu P.
europepmc +1 more source
Advanced Science, EarlyView.Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais +32 more
wiley +1 more source
Statistical properties of kernel principal component analysis [PDF]
Machine Learning, 2007 openaire +1 more source
Advanced Science, EarlyView.Mice can transfer the learned rule of spatial working memory to guide similar but novel tasks. Hippocampal CA3 populational activity dynamically reorganize during memory generalization, shifting from task‐specific to generalized coding over testing days. Sparse yet redundant neural representations of CA3 enable rule transfer and cognitive map formation,
Da Song +8 more
wiley +1 more source
Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet. [PDF]
Sci Rep, 2018 Shiokawa Y, Date Y, Kikuchi J.
europepmc +1 more source
Jurnal Ilmu Dasar, 2010 Principal component analysis (PCA) is a method used to reduce dimentionality of the dataset. However, the use of PCA failed to carry out the problem of non-linear and non-separable data. To overcome this problem such data is more appropriate to use PCA method with the kernel function, which is known as the kernel PCA (KPCA). In this paper, Iris dataset
Ismail Djakaria +2 more
openaire +1 more source
Cancer‐Associated BCL‐2 Mutants Reveal Mechanisms Towards Venetoclax Resistance
Advanced Science, EarlyView.Venetoclax (VEN) resistance in chronic lymphocytic leukemia arises from diverse BCL2 mutations. We map mechanisms contributing to VEN resistance across common BCL‐2 variants. G101V and D103Y reduce drug binding and increase sequestration of pro‐apoptotic proteins. V156D blocks VEN allosterically.
Jonas Aufdermauer +9 more
wiley +1 more source
Rainbow plots, Bagplots and Boxplots for Functional Data [PDF]
We propose new tools for visualizing large numbers of functional data in the form of smooth curves or surfaces. The proposed tools include functional versions of the bagplot and boxplot, and make use of the first two robust principal component scores ...
Rob J. Hyndman, Han Lin Shang
core
Advanced Science, EarlyView.Intrinsic phase toughening transforms a brittle B2 intermetallic into a plastically deformable, load‐bearing phase, while a heterogeneous laminated architecture suppresses strain localization and interface cracking. The synergy between ductile intermetallics and mesoscale heterogeneity establishes a general design strategy for breaking the long ...
Lu Yang +9 more
wiley +1 more source