Results 41 to 50 of about 22,366 (265)

GrSrNMF: dynamic community detection with graph and symmetry bi-regularized non-negative matrix factorization

Scientific Reports
Community detection in dynamic networks has become an interesting and popular research direction in recent years, widely used in electronic commerce, social media, and other fields.
Wei Yu, Shihong Wu, Shigen Shen, Hongyan Li, Weiyan Yang, Xiaoming Li, Lei Wang   +6 more
doaj   +1 more source

On extension of regular graphs [PDF]

Journal of Discrete Mathematical Sciences and Cryptography, 2018
arXiv admin note: substantial text overlap with arXiv:1407 ...
Banerjee, Anirban, Bej, Saptarshi
openaire   +2 more sources

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Bearing Faults Diagnosis Method Based on Stacked Auto-Encoder With Graph Regularization for Wind Turbines

发电技术
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, LIU Jianxun, BAO Yanyang, LI Dazi   +3 more
doaj   +1 more source

Double regularized matrix factorization for image classification and clustering

EURASIP Journal on Image and Video Processing, 2018
Feature selection, which aims to select an optimal feature subset to avoid the “curse of dimensionality,” is an important research topic in many real-world applications.
Wei Zhou, Chengdong Wu, Jianzhong Wang, Xiaosheng Yu, Yugen Yi   +4 more
doaj   +1 more source

Regular embeddings of a graph [PDF]

Pacific Journal of Mathematics, 1983
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

Patient‐Derived 3D Heart‐On‐a‐Chip Model of Dilated Cardiomyopathy With Embedded Bead‐Based Mapping of Tissue Contractility

Advanced Healthcare Materials, EarlyView.
A heart‐on‐a‐chip model of dilated cardiomyopathy is developed from patient‐derived induced pluripotent stem cells. The model recapitulates key disease phenotypes and enables functional assessment through integrated bead‐based tracking and pillar deflection measurements.
Ali Mousavi, Ludovic Mouttet, Shihao Cui, Yasaman Hekmatnia, Mehran Mottahedi, Ida Derish, Naimeh Rafatian, Mark Aurousseau, Gregor Andelfinger, Renzo Cecere, Houman Savoji   +10 more
wiley   +1 more source

Anticancer Drug Response Prediction in Cell Lines Using Weighted Graph Regularized Matrix Factorization

Molecular Therapy: Nucleic Acids, 2019
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, Yan Zhao, Chun-Chun Wang, Jian-Qiang Li, Xing Chen, Xue Piao   +5 more
doaj   +1 more source

Building a Graph Signal Processing Model Using Dynamic Time Warping for Load Disaggregation

Sensors, 2020
Building on recent unsupervised Non-intrusive load monitoring (NILM) algorithms that use graph Laplacian regularization (GLR) and achieve state-of-the-art performance, in this paper, we propose a novel unsupervised approach to design an underlying graph ...
Kanghang He, Vladimir Stankovic, Lina Stankovic   +2 more
doaj   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source