Results 51 to 60 of about 117,362 (280)
ObjectivesIn order to solve the problems of low efficiency of fault feature extraction, inaccurate feature representation, and difficulty in adapting existing methods to complex signal requirements in wind turbine bearing fault diagnosis, a fault ...
LIU Zhan +3 more
doaj +1 more source
Zero Shot Learning with the Isoperimetric Loss
We introduce the isoperimetric loss as a regularization criterion for learning the map from a visual representation to a semantic embedding, to be used to transfer knowledge to unknown classes in a zero-shot learning setting.
Bertozzi, Andrea +2 more
core +1 more source
A Scalable Perovskite Platform With Multi‐State Photoresponsivity for In‐Sensor Saliency Detection
A scalable in‐sensor computing platform (32 × 32 array) with ultra‐low variability is developed by incorporating ferroelectric copolymers into halide perovskite thin films. These devices achieve 1000 programmable photoresponsivity states and high thermal reliability.
Xuechao Xing +10 more
wiley +1 more source
Graph Neural Networks have emerged as powerful tools for analyzing graph-structured data. However, their performance often varies across datasets due to challenges such as noisy edges, sparse connectivity, and over-smoothing in deep layers.
Vinay Santhosh Chitla +3 more
doaj +1 more source
Precision medicine has become a novel and rising concept, which depends much on the identification of individual genomic signatures for different patients.
Na-Na Guan +5 more
doaj +1 more source
Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao +3 more
wiley +1 more source
Graph-Based Clustering via Group Sparsity and Manifold Regularization
Clustering refers to the problem of partitioning data into several groups according to the predefined criterion. Graph-based method is one of main clustering approaches and has been shown impressive performance in many literatures.
Jianyu Miao +3 more
doaj +1 more source
Vacuum Polarization and Chiral Lattice Fermions
The vacuum polarization due to chiral fermions on a 4--dimensional Euclidean lattice is calculated according to the overlap prescription. The fermions are coupled to weak and slowly varying background gauge and Higgs fields, and the polarization tensor ...
't Hooft +52 more
core +1 more source
Regular embeddings of a graph [PDF]
In this paper we study embeddings of a graph G in Euclidean space R" that are 'regular' in the following sense: given any two distinct vertices u and v of G, the distance between the corresponding points in R" equals a if u and v are adjacent, and equals β otherwise.
openaire +3 more sources
Aldosterone‐producing adenomas (APAs) develop via two distinct paths: directly from adrenal zona glomerulosa (zG) cells, or stepwise from zG cells through aldosterone‐producing micronodules (APMs) before progressing to APAs. Advanced single‐cell and spatial analyses identified distinct cell states linked to oxidative stress and cell–cell interactions ...
Zhuolun Sun +7 more
wiley +1 more source

