Results 41 to 50 of about 761,172 (262)

Statistics of clustering of ultra-high energy cosmic rays and the number of their sources [PDF]

, 2000
Observation of clustering of ultra-high energy cosmic rays (UHECR) suggests that they are emitted by compact sources. Assuming small deflection of UHECR during the propagation, the statistical analysis of clustering allows to estimate the spatial density
E. Boldt, E. Waxman, E. Waxman, G. T. Zatsepin, G. T. Zatsepin, I. I. Tkachev, J. Loveday, J. P. Rachen, J. W. Cronin, K. Greisen, K. Mannheim, M. Takeda, P. G. Tinyakov, P. P. Kronberg, S. L. Dubovsky, S. Lee, S. Mao, Y. Uchihori   +17 more
core   +2 more sources

Hybrid Clustering Algorithm Based on Improved Density Peak Clustering

Applied Sciences
In the era of big data, unsupervised learning algorithms such as clustering are particularly prominent. In recent years, there have been significant advancements in clustering algorithm research.
Limin Guo, Weijia Qin, Zhi Cai, Xing Su
doaj   +1 more source

Negative Selection Algorithm Based on Antigen Density Clustering

IEEE Access, 2020
The negative selection algorithm (NSA) is one of the basic algorithms of the artificial immune system. In the traditional negative selection algorithm, candidate detectors are randomly generated without considering the uneven distributions of self ...
Chao Yang, Lin Jia, Bing-Qiu Chen, Hai-Yang Wen   +3 more
doaj   +1 more source

Density Gain-Rate Peaks for Spectral Clustering

IEEE Access, 2021
Clustering has been troubled by varying shapes of sample distributions, such as line and spiral shapes. Spectral clustering and density peak clustering are two feasible techniques to address this problem, and have attracted much attention from academic ...
Jiexing Liu, Chenggui Zhao
doaj   +1 more source

A Density-based Clustering Method [PDF]

Communications for Statistical Applications and Methods, 2002
This paper is to show a clustering application of a density estimation method that utilizes the Gaussian mixture model. We define "closeness measure" as a clustering criterion to see how close given two Gaussian components are. Closeness measure is defined as the ratio of log likelihood between two Gaussian components.
Sung Mahn Ahn, Sung Wook Baik
openaire   +1 more source

LeClair-Mussardo series for two-point functions in Integrable QFT [PDF]

, 2018
We develop a well-defined spectral representation for two-point functions in relativistic Integrable QFT in finite density situations, valid for space-like separations.
Pozsgay, B., Szécsényi, I. M.
core   +2 more sources

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source

A Distributed and Approximated Nearest Neighbors Algorithm for an Efficient Large Scale Mean Shift Clustering

, 2019
In this paper we target the class of modal clustering methods where clusters are defined in terms of the local modes of the probability density function which generates the data. The most well-known modal clustering method is the k-means clustering. Mean
Azzag, Hanane, Beck, Gaël, Cérin, Christophe, Duong, Tarn, Lebbah, Mustapha   +4 more
core   +2 more sources

Multi-step density-based clustering [PDF]

Knowledge and Information Systems, 2005
Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex distance measures are first choice but also simpler distance functions are available which can be computed much more efficiently.
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfeifle   +2 more
openaire   +1 more source

Reciprocal control of viral infection and phosphoinositide dynamics

FEBS Letters, EarlyView.
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley   +1 more source