Unsupervised change detection in satellite images using fuzzy c-means clustering and principal component analysis [PDF]
, 2013 Mustafa Hayri Kesikoğlu +2 more
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Retraction Note to: Rough fuzzy region based bounded support fuzzy C-means clustering for brain MR image segmentation [PDF]
, 2022 A. Srinivasan, S Sadagopan
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Clickable Microgel Inks Enable Spatioselective, Multi‐Stimuli Programmable Assembly of Materials
Advanced Science, EarlyView.Clickable microgel inks enable direct ink writing of hydrogel architectures with intrinsic spatioselective and programmable multi‐responsiveness. By combining pH‐responsive and temperature‐responsive microgel building blocks through Diels‐Alder interparticle crosslinking, the assemblies exhibit controllable swelling and shape changes.
Junho Moon +3 more
wiley +1 more source
Abstract and Applied Analysis, 2014 Owing to the increase and the complexity of data caused by the uncertain environment, the water environment monitoring system in Three Gorges Reservoir Area faces much pressure in data handling.
Yuanchang Zhong +4 more
doaj +1 more source
Scalable clustering by truncated fuzzy $c$-means
Big Data and Information Analytics, 2016 Most existing clustering algorithms are slow for dividing a large dataset into a large number of clusters. In this paper, we propose a truncated FCM algorithm to address this problem. The main idea behind our proposed algorithm is to keep only a small number of cluster centers during the iterative process of the FCM algorithm. Our numerical experiments
Guojun Gan, Qiujun Lan, Shiyang Sima
openaire +1 more source
Advanced Science, EarlyView.In this study, the orange‐muscle giant abalone (Haliotis gigantea) is used as a model to identify a non‐coding SNP that disrupts the interaction between ITGA8 pre‐mRNA and the splicing factor ILF2, leading to altered ITGA8 splicing. These splicing changes promote carotenoid accumulation in abalone muscle through the regulation of tissue remodeling ...
Xiaohui Wei +17 more
wiley +1 more source
Clustering of COVID-19 data for knowledge discovery using c-means and fuzzy c-means
, 2021 Asif Afzal +6 more
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A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application
Advanced Science, EarlyView.This review presents a strategy‐centric framework for spatial omics technologies, organizing methods by how spatial information is experimentally encoded. It compares key performance trade‐offs across sequencing‐ and imaging‐based approaches, examines computational and practical limitations, and highlights biomedical applications. The analysis provides
Xiaofeng Wu +5 more
wiley +1 more source
Clusters of medical specialties around patients with multimorbidity - employing fuzzy c-means clustering to explore multidisciplinary collaboration. [PDF]
BMC Health Serv Res, 2023 Verhoeff M +8 more
europepmc +1 more source
SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
Advanced Science, EarlyView.ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao +11 more
wiley +1 more source