Results 151 to 160 of about 2,583,502 (287)

A Case Study to Monitor Parallel‐Connected Ni–Cd Batteries on EMU Trains Through Compositional Data Control Charts

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Electric multiple unit (EMU) trains, widely used in modern railway transportation, use Nickel–Cadmium (Ni–Cd) batteries to power auxiliary systems on board, including lighting, ventilation, control electronics, and emergency systems. These batteries are often connected in parallel to ensure a wider power supply range for electrical loads that ...
Christian Capezza, Guido Cesaro, Antonio Lepore, Biagio Palumbo, Emanuele Rossi   +4 more
wiley   +1 more source

Sliding Motions on Non‐Euclidean State Spaces: A Differential‐Geometric Perspective

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper extends sliding‐mode control theory to nonlinear systems evolving on smooth manifolds. Building on differential geometric methods, we reformulate Filippov's notion of solutions, characterize well‐defined vector fields on quotient spaces, and provide a consistent geometric definition of higher‐order sliding modes.
Fernando Castaños
wiley   +1 more source

Privacy‐Preserving Data‐Driven Distributed MPC for Heterogeneous Nonlinear Multi‐Agent Systems

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Distributed model predictive control (DMPC) is a cornerstone for coordinating multi‐agent systems, yet simultaneously ensuring data privacy, handling unknown nonlinear dynamics, and managing heterogeneous constraints remains an open challenge.
Mahmood Mazare, Hossein Ramezani
wiley   +1 more source

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

Smart 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, Zhubin Hu, Xinyuan Wang, Zhenrong Sun, Yongye Liang, Cheng Zhong, Haitao Sun   +6 more
wiley   +1 more source

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

IEEJ 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

Constructing mesoscale functionomics by neural dynamics subspace clustering. [PDF]

Natl Sci Rev
Cai Y, Xu X, Xiao G, Ling H, Shi Z, Wang M, Wang M, Chen F, Wu J, Dai Q.   +9 more
europepmc   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Adaptive behavior is guided by integrated representations of controlled and non-controlled information. [PDF]

Elife
Huang B, Ritz H, Jiang J.
europepmc   +1 more source

Dissecting Glioma Heterogeneity: A Deep Hybrid Graph Convolutional Network With Hinge Attention for Causal‐Effect Explainability

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumour classification is a critical task in medical imaging that requires accurate and interpretable solutions to assist in clinical decision‐making. In this paper, we present GraphConvNet‐X, a novel hybrid model that integrates convolutional neural networks (CNNs) for spatial feature extraction with graph neural networks (GNNs) that ...
Sultanul Arifeen Hamim, Mubasshar U. I. Tamim, S. M. Hasan Mahmud, M. F. Mridha, Zeyar Aung   +4 more
wiley   +1 more source

Developmentally defined subcircuits in the hippocampus support spatial learning. [PDF]

Neuron
Huszár R, Kirsanov A, Henze G, Huilgol D, Valero M, Huang ZJ, Buzsáki G.   +6 more
europepmc   +1 more source