Results 131 to 140 of about 845,204 (303)

Mapping the Social Network Structure and Composition of Black Individuals With Rheumatic and Musculoskeletal Conditions

Arthritis Care &Research, EarlyView.
Objective Our objective was to describe the social networks of Black individuals with rheumatic and musculoskeletal conditions and understand the clustering of health‐related behaviors to inform future community‐based, peer‐led interventions. Methods We used an adapted Personal Network Survey for Clinical Research (PERSNET) to map the personal social ...
Taussia Boadi, Amar Dhand, Leah Santacroce, Neil Pillai, Komel Safdar, Mia T. Chandler, Ariel Childs, Monica Crespo‐Bosque, Gina Curry, Mary Dollear, Alice Eggleston, Daniel Erickson, Dieufort Fleurissaint, Denice Garrett, Gail Granville, Tyler Green, Magdalena Hamielec, Elena Losina, Karen Mancera‐Cuevas, Mary Ann Nelson, Chisa Nosamiefan, Bisola Ojikutu, Tonya S. Roberson, Mary Beth Son, Marie Jacques Toussaint, Michael York, Rosalind Ramsey‐Goldman, Candace H. Feldman   +27 more
wiley   +1 more source

Box Representations of Embedded Graphs [PDF]

Discrete & Computational Geometry, 2016
A $d$-box is the cartesian product of $d$ intervals of $\mathbb{R}$ and a $d$-box representation of a graph $G$ is a representation of $G$ as the intersection graph of a set of $d$-boxes in $\mathbb{R}^d$. It was proved by Thomassen in 1986 that every planar graph has a 3-box representation.
openaire   +4 more sources

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Predicting biomedical relationships using the knowledge and graph embedding cascade model.

PLoS ONE, 2019
Advances in machine learning and deep learning methods, together with the increasing availability of large-scale pharmacological, genomic, and chemical datasets, have created opportunities for identifying potentially useful relationships within ...
Xiaomin Liang, Daifeng Li, Min Song, Andrew Madden, Ying Ding, Yi Bu   +5 more
doaj   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Neural-based inexact graph de-anonymization

High-Confidence Computing
Graph de-anonymization is a technique used to reveal connections between entities in anonymized graphs, which is crucial in detecting malicious activities, network analysis, social network analysis, and more.
Guangxi Lu, Kaiyang Li, Xiaotong Wang, Ziyue Liu, Zhipeng Cai, Wei Li   +5 more
doaj   +1 more source

Embedded-Graph Theory

CoRR, 2017
In this paper, we propose a new type of graph, denoted as "embedded-graph", and its theory, which employs a distributed representation to describe the relations on the graph edges. Embedded-graphs can express linguistic and complicated relations, which cannot be expressed by the existing edge-graphs or weighted-graphs.
openaire   +2 more sources

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Network community detection via neural embeddings

Nature Communications
Recent advances in machine learning research have produced powerful neural graph embedding methods, which learn useful, low-dimensional vector representations of network data. These neural methods for graph embedding excel in graph machine learning tasks
Sadamori Kojaku, Filippo Radicchi, Yong-Yeol Ahn, Santo Fortunato   +3 more
doaj   +1 more source

Anomalous behavior detection based on optimized graph embedding representation in social networks

Journal of King Saud University: Computer and Information Sciences
Anomalous behaviors in social networks can lead to privacy leaks and the spread of false information. In this paper, we propose an anomalous behavior detection method based on optimized graph embedding representation. Specifically, the user behavior logs
Ling Xing, Shiyu Li, Qi Zhang, Honghai Wu, Huahong Ma, Xiaohui Zhang   +5 more
doaj   +1 more source