Results 51 to 60 of about 798,948 (275)
Minimum Density Hyperplanes [PDF]
, 2016 Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is central to many statistical and machine learning approaches to the classification of unlabelled data.
Hofmeyr, David P. +2 more
core +2 more sources
Quantum density peak clustering
Quantum Machine Intelligence, 2023 AbstractClustering algorithms are of fundamental importance when dealing with large unstructured datasets and discovering new patterns and correlations therein, with applications ranging from scientific research to medical imaging and marketing analysis. In this work, we introduce a quantum version of the density peak clustering algorithm, built upon a
Duarte Magano +2 more
openaire +2 more sources
FEBS Letters, EarlyView.Bifidobacterium bifidum establishes symbiosis with infants by metabolizing lacto‐N‐biose I (LNB) from human milk oligosaccharides (HMOs). The extracellular multidomain enzyme LnbB drives this process, releasing LNB via its catalytic glycoside hydrolase family 20 (GH20) lacto‐N‐biosidase domain.
Xinzhe Zhang +5 more
wiley +1 more source
A density clustering-based network performance failure big data analysis algorithm
Dianxin kexue, 2020 Facing frequent network security incidents,how to quickly find abnormal data in massive monitoring database and carry out network failure analysis becomes a research difficulty.A density-based network performance failure big data analysis algorithm was ...
Xiang LI, Yuan LI, Zifei ZHANG, Zhe YANG
doaj
Abnormal behaviour analysis algorithm for electricity consumption based on density clustering
The Journal of Engineering, 2019 How to effectively detect abnormal electricity consumption behaviour from a large-scale electrical load data is very important to smart grid. An abnormal electricity consumption analysis method based on density clustering is proposed.
Min Xiang +4 more
doaj +1 more source
Tangling clustering of inertial particles in stably stratified turbulence
, 2010 We have predicted theoretically and detected in laboratory experiments a new type of particle clustering (tangling clustering of inertial particles) in a stably stratified turbulence with imposed mean vertical temperature gradient.
A. Eidelman +15 more
core +1 more source
Molecular bases of circadian magnesium rhythms across eukaryotes
FEBS Letters, EarlyView.Circadian rhythms in intracellular [Mg2+] exist across eukaryotic kingdoms. Central roles for Mg2+ in metabolism suggest that Mg2+ rhythms could regulate daily cellular energy and metabolism. In this Perspective paper, we propose that ancestral prokaryotic transport proteins could be responsible for mediating Mg2+ rhythms and posit a feedback model ...
Helen K. Feord, Gerben van Ooijen
wiley +1 more source
Density-Based Clustering Validation [PDF]
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014 One of the most challenging aspects of clustering is validation, which is the objective and quantitative assessment of clustering results. A number of different relative validity criteria have been proposed for the validation of globular, clusters. Not all data, however, are composed of globular clusters.
Davoud Moulavi +4 more
openaire +1 more source
FEBS Letters, EarlyView.This perspective highlights emerging insights into how the circadian transcription factor CLOCK:BMAL1 regulates chromatin architecture, cooperates with other transcription factors, and coordinates enhancer dynamics. We propose an updated framework for how circadian transcription factors operate within dynamic and multifactorial chromatin landscapes ...
Xinyu Y. Nie, Jerome S. Menet
wiley +1 more source
Methods of Hierarchical Clustering [PDF]
, 2011 We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations that are available in R and other software environments. We look at hierarchical self-organizing maps, and mixture models.
Contreras, Pedro, Murtagh, Fionn
core +2 more sources