Results 111 to 120 of about 8,432 (220)

Smart molecular design of NIR‐II organic fluorophores through self‐driven iterative evolution, deep learning, and fragment‐based assembly

open access: yesSmart Molecules, EarlyView.
A smart design strategy for NIR‐II organic fluorophores is proposed by combining self‐driven Iterative evolution, deep Learning, and fragment‐based assembly. This work establishes a broadly applicable approach for molecular design, accelerating the discovery of NIR‐II fluorophores and extending to optoelectronic materials and therapeutic compounds ...
Yu Zhang   +6 more
wiley   +1 more source

Distributed Karhunen-Loeve Transform With Nested Subspaces

open access: yes
A network in which sensors observe a common Gaussian source is analyzed. Using a fixed linear transform, each sensor compresses its high-dimensional observation into a low-dimensional representation.
Goela, Naveen, Gastpar, Michael
core   +1 more source

The Pier Luigi Nervi's concrete structure of Palazzetto dello Sport: Modeling and dynamic characterization

open access: yesStructural Concrete, EarlyView.
Abstract This paper presents a numerical and experimental study aimed at the modeling and dynamic characterization of the reinforced concrete structure of the Palazzetto dello Sport in Rome, designed and by Pier Luigi Nervi with Annibale Vitellozzi, and built by Nervi & Bartoli contractors in 1956‐57.
Jacopo Ciambella   +2 more
wiley   +1 more source

DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection

open access: yesIEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang   +5 more
wiley   +1 more source

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