Results 191 to 200 of about 211,113 (260)

Identification of Missing Knowledge in MBSE System Models Using Graph‐Based Machine Learning

Systems Engineering, EarlyView.
ABSTRACT The design and development of complex aerospace systems pose significant challenges due to their growing complexity. Iterative design processes, guided by formal specifications, strive to refine initially vague characteristics through multiple stages.
Esma Karagoz, Olivia J. Pinon Fischer, Dimitri Mavris   +2 more
wiley   +1 more source

Revisiting Volterra defects: geometrical relation between edge dislocations and wedge disclinations. [PDF]

R Soc Open Sci
Kobayashi S, Takemasa K, Tarumi R.
europepmc   +1 more source

Quantifying Structural Complexity, Effort, and Performance: An Early Experiment Using Network Design Tasks

Systems Engineering, EarlyView.
ABSTRACT Structural Complexity is perceived as driving cost in system development, yet managing it effectively requires empirical understanding. This study investigates human decision‐making using a toy transportation‐style network design task, focusing on how Structural Complexity, Effort, and Performance interact. Seventy‐four participants (primarily
Alfonso Lanza, Joshua Sutherland, Marc‐Andre Chavy‐Macdonald, Olivier L. de Weck   +3 more
wiley   +1 more source

Age-related constraints on the spatial geometry of the brain. [PDF]

Nat Commun
Escalante YY, Adams JN, Yassa MA, Janssen N.   +3 more
europepmc   +1 more source

Stochastic geometry analysis of UAV-assisted networks with probabilistic UAV activation. [PDF]

Sci Rep
Selim MM.
europepmc   +1 more source

An improved tortuosity measurement method combining curvature-based, breadth-first search and Euclidean distance for retinal image analysis. [PDF]

PeerJ
Amir Hamzah NA, Wan Zaki WMD, Ali A.
europepmc   +1 more source

Physics‐Driven Deep Neural Networks for Solving the Optimal Transport Problem Associated With the Monge–Ampère Equation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Monge–Ampère equations (MAEs) are fully nonlinear second‐order partial differential equations (PDEs), which are closely related to various fields including optimal transport (OT) theory, geometrical optics and affine geometry. Despite their significance, MAEs are extremely challenging to solve.
Xinghua Pan, Zexin Feng, Kang Yang
wiley   +1 more source

High-resolution dataset (2017-2023) of physical-geographical predictors for machine learning modelling of fluvial flooding: the Gidra river case, Slovakia. [PDF]

Data Brief
Vojtek M, Benko Ľ, Kapusta J, Držík D, Munk M, Munková D, Drlík M, Vojteková J.   +7 more
europepmc   +1 more source

AVCLNet: Multimodal Multispeaker Tracking Network Using Audio‐Visual Contrastive Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Audio‐visual speaker tracking aims to determine the locations of multiple speakers in the scene by leveraging signals captured from multisensor platforms. Multimodal fusion methods can improve both the accuracy and robustness of speaker tracking.
Yihan Li, Yidi Li, Zhenhuan Xu, Hao Guo, Mengyuan Liu, Weiwei Wan   +5 more
wiley   +1 more source