Results 31 to 40 of about 2,744,930 (320)
Application of Multivariate-Rank-Based Techniques in Clustering of Big Data
Vikalpa, 2018 Executive Summary Very large or complex data sets, which are difficult to process or analyse using traditional data handling techniques, are usually referred to as big data.
Pritha Guha
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Intra-cluster Globular Clusters in a Simulated Galaxy Cluster [PDF]
The Astrophysical Journal, 2018 Abstract Using a cosmological dark matter simulation of a galaxy-cluster halo, we follow the temporal evolution of its globular cluster population. To mimic the red and blue globular cluster populations, we select at high redshift two sets of particles from individual ...
Mario G. Abadi +6 more
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Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions
Frontiers in Neuroscience, 2019 Background: Amyotrophic Lateral Sclerosis (ALS) is a relentlessly progressive neurodegenerative condition with limited therapeutic options at present. Survival from symptom onset ranges from 3 to 5 years depending on genetic, demographic, and phenotypic ...
Vincent Grollemund +15 more
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Beilstein Journal of Organic Chemistry, 2019 We previously showed that the regio- and stereoselectivity in terpene-forming reactions are determined by the conformations of the carbocation intermediates, which reflect the initial conformation of the substrate, geranylfarnesyl diphosphate (GFPP ...
Hajime Sato +4 more
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Distributed Dynamic Cluster-Head Selection and Clustering for Massive IoT Access in 5G Networks
Applied Sciences, 2019 With the rapid growth of Internet-of-things (IoT) devices, IoT communication has become an increasingly crucial part of 5G wireless communication systems.
Yifeng Zhao +4 more
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The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings., 2003 We consider the following clustering problem: we have a complete graph on n vertices (items), where each edge (u, v) is labeled either + or – depending on whether u and v have been deemed to be similar or different. The goal is to produce a partition of the vertices (a clustering) that agrees as much as possible with the edge labels. That is, we want a
Shuchi Chawla, Avrim Blum, Nikhil Bansal
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Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering
Algorithms, 2017 We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online.
Xin Tian, Song Li
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Histology-informed automatic parcellation of white matter tracts in the rat spinal cord
Frontiers in Neuroanatomy, 2022 The white matter is organized into “tracts” or “bundles,” which connect different parts of the central nervous system. Knowing where these tracts are located in each individual is important for understanding the cause of potential sensorial, motor or ...
Harris Nami +4 more
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Combining multiple classifications of chemical structures using consensus clustering [PDF]
, 2012 Consensus clustering involves combining multiple clusterings of the same set of objects to achieve a single clustering that will, hopefully, provide a better picture of the groupings that are present in a dataset. This Letter reports the use of consensus
Adamson +43 more
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Sequence spaces M ( ϕ ) $M(\phi)$ and N ( ϕ ) $N(\phi)$ with application in clustering
Journal of Inequalities and Applications, 2017 Distance measures play a central role in evolving the clustering technique. Due to the rich mathematical background and natural implementation of l p $l_{p}$ distance measures, researchers were motivated to use them in almost every clustering process ...
Mohd Shoaib Khan +3 more
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