Results 21 to 30 of about 1,103 (151)

On structural controllability in complex networks with periodic switching topologies

Asian Journal of Control, EarlyView.
Abstract This paper investigates the structural controllability of complex networks with periodic switching topologies. First, several graph transformations that preserve structural controllability are demonstrated. Based on the n‐walk theory, a criterion is derived that determines structural controllability by analyzing only the joint graph within a ...
Jingrui Hou, Zhaohui Liu, Xinghuo Yu, Mahdi Jalili   +3 more
wiley   +1 more source

Cross‐Entropy of Power Spectral Density Function: A Modal Identification Framework

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT The power spectral density (PSD) function of measured structural response contains a significant amount of information, including the modal parameters (natural frequencies, damping ratios). Output‐only system identification or modal identification technique can be used for extracting such modal parameters from the measured response or its ...
Su‐Hong Kim, Jae‐Seung Hwang, Dae‐Kun Kwon, Ahsan Kareem   +3 more
wiley   +1 more source

Endohedral fullerenes as qubits: From synthesis to quantum computing applications

InfoMat, EarlyView.
Endohedral fullerenes emerge as promising platforms for qubits and qudits. This review surveys the primary synthesis routes, from arc‐discharge to high‐yield molecular surgery. It then details spin manipulation and readout in key systems, including metal‐based, cluster, and nitrogen‐containing fullerenes.
Jeong‐Seok Nam, Jiye Han, Jin‐Myung Choi, Franklin H. Cho, Daniel K. Park, Seunghee Park, Yoshifumi Hashikawa, Yasujiro Murata, Eunsang Kwon, Dong‐Hwan Kim, Junki Kim, Il Jeon   +11 more
wiley   +1 more source

Intrinsically Design‐Rule‐Compliant Nanophotonic Inverse Design via Learned Generative Manifolds

Laser &Photonics Reviews, EarlyView.
A generative reparameterization framework for nanophotonic inverse design is introduced, restricting optimization to a learned manifold of design‐rule‐compliant geometries. Unlike conventional penalty‐based approaches, fabrication constraints are encoded intrinsically within the design representation.
Bahrem Serhat Danis, Demet Baldan Desdemir, Enes Akcakoca, Zeynep Ipek Yanmaz, Gulzade Polat, Ahmet Onur Dasdemir, Aytug Aydogan, Abdullah Magden, Emir Salih Magden   +8 more
wiley   +1 more source

Diffraction‐Free Natural Optical Skyrmions and Their Subwavelength Confinement Around Vortices

Laser &Photonics Reviews, EarlyView.
ABSTRACT Diffraction causes waves to spread out as they propagate freely. The tighter the lateral confinement, the faster the spreading. Past research on how to suppress diffraction has been based on wave engineering and has led so far to idealized waves that, in real settings, eventually diffract.
Nilo Mata‐Cervera, Deepak K. Sharma, Ramon Paniagua‐Dominguez, Yijie Shen, Miguel A. Porras   +4 more
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

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

Recognition of Spatiotemporal Feature Images of Zero‐Sequence Voltage for Single‐Phase High‐Impedance Ground Faults Under Complex Conditions

High Voltage, EarlyView.
ABSTRACT Diagnosing high‐impedance ground faults (HIGFs) in distribution networks is extremely challenging because high transition resistance significantly reduces electrical signal strength and unpredictable initial fault phase angles coupled with asymmetric voltage disturbances often lead to misclassification.
Zhengyang Li, Yijia Cao, Chun Chen, Weiyu Wang, Yansha Li, Jinglu Li   +5 more
wiley   +1 more source

Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation

Computer Graphics Forum, EarlyView.
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley   +1 more source

Interpolated Adaptive Linear Reduced Order Modeling for Deformation Dynamics

Computer Graphics Forum, EarlyView.
Abstract Linear reduced‐order modeling (ROM) is widely used for efficient simulation of deformation dynamics, but its accuracy is often limited by the fixed linearization of the reduced mapping. We propose a new adaptive strategy for linear ROM that allows the reduced mapping to vary dynamically in response to the evolving deformation state ...
Y. Tao, M. Chiaramonte, P. Fernandez
wiley   +1 more source