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Related papers: Cluster Dynamics Modeling of Materials: Advantages…

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Clustering aims to group unlabeled objects based on similarity inherent among them into clusters. It is important for many tasks such as anomaly detection, database sharding, record linkage, and others. Some clustering methods are taken as…

Databases · Computer Science 2024-12-02 Binbin Gu , Saeed Kargar , Faisal Nawab

Many simple natural phenomena are characterized by complex motion that appears random at first glance, but that often displays underlying patterns and behavior that can be clustered in groups. The movement of small pieces of paper falling…

Data Analysis, Statistics and Probability · Physics 2022-10-10 Arthur A. B. Pessa , Matjaz Perc , Haroldo V. Ribeiro

Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datasets that contain either numeric or categorical attributes.…

Artificial Intelligence · Computer Science 2007-05-23 Zengyou He , Xiaofei Xu , Shengchun Deng

Mining Time Series data has a tremendous growth of interest in today's world. To provide an indication various implementations are studied and summarized to identify the different problems in existing applications. Clustering time series is…

Information Retrieval · Computer Science 2010-05-25 V. Kavitha , M. Punithavalli

Cross-section data unavailability for non-water materials in track structure simulation software necessitates nanodosimetric quantity transformation from water to other materials. Cluster dose calculation transformation initially employed…

Medical Physics · Physics 2025-10-28 Miriam Schwarze , Hui Khee Looe , Björn Poppe , Leo Thomas , Hans Rabus

Clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the process of grouping similar…

Data Structures and Algorithms · Computer Science 2012-05-08 T. Soni Madhulatha

An algorithm for Monte Carlo simulations is proposed in which the parameter controlling the strength of the transition becomes a dynamical variable and in which efficient transitions are achieved by cluster steps. It allows to avoid the…

High Energy Physics - Lattice · Physics 2009-10-22 W. Kerler , A. Weber

Multi-component polymer systems are of interest in organic photovoltaic and drug delivery applications, among others where diverse morphologies influence performance. An improved understanding of morphology classification, driven by…

Computational Engineering, Finance, and Science · Computer Science 2020-08-27 Pavan Inguva , Lachlan Mason , Indranil Pan , Miselle Hengardi , Omar K. Matar

We present a computational study of sliding between gold clusters and a highly oriented pyrolytic graphite substrate, a material system that exhibits ultra-low friction due to structural lubricity. By means of molecular dynamics, it is…

Computational Physics · Physics 2023-03-27 Wai H. Oo , Mehmet Z. Baykara , Hongyu Gao

We begin by reviewing some probabilistic results about the Dirichlet Process and its close relatives, focussing on their implications for statistical modelling and analysis. We then introduce a class of simple mixture models in which…

Methodology · Statistics 2010-03-23 Peter J. Green

Quantifying the population of nanoscale defects that are formed in metals and alloys exposed to extreme radiation environments remains a pressing challenge in materials science. These defects both fundamentally alter material properties and…

Materials Science · Physics 2022-04-26 Charles A. Hirst , Cody A. Dennett

Recently, clustering moving object trajectories kept gaining interest from both the data mining and machine learning communities. This problem, however, was studied mainly and extensively in the setting where moving objects can move freely…

Machine Learning · Statistics 2015-11-05 Mohamed Khalil El Mahrsi , Romain Guigourès , Fabrice Rossi , Marc Boullé

Scientists use imaging to identify objects of interest and infer properties of these objects. The locations of these objects are often measured with error, which when ignored leads to biased parameter estimates and inflated variance.…

We introduce a model for the dynamics of mud cracking in the limit of of extremely thin layers. In this model the growth of fracture proceeds by selecting the part of the material with the smallest (quenched) breaking threshold. In…

Condensed Matter · Physics 2009-10-31 A. Gabrielli , R. Cafiero , G. Caldarelli

A variety of problems in device and materials design require the rapid forward modeling of Maxwell's equations in complex micro-structured materials. By combining high-order accurate integral equation methods with classical multiple…

Numerical Analysis · Mathematics 2011-04-29 Zydrunas Gimbutas , Leslie Greengard

The theme of this contribution is the idea that the metals in the intracluster medium (ICM) may be inhomogeneously distributed on small scales. We focus on the possible interplay between this and the cooling flow process. We begin with a…

Astrophysics · Physics 2007-05-23 R. Glenn Morris , Andrew C. Fabian

The inclusion of a fragmentation mechanism in population balance equations introduces complex interactions that make the analytical or even computational treatment much more difficult than for the pure aggregation case. This is specially…

Disordered Systems and Neural Networks · Physics 2022-03-14 Arturo Berrones-Santos , Luis Benavides-Vázquez , Elisa Schaeffer , Javier Almaguer

Heterogeneous object design is an active research area in recent years. The conventional CAD modeling approaches only provide geometry and topology of the object, but do not contain any information with regard to the materials of the object…

Computational Engineering, Finance, and Science · Computer Science 2010-04-22 Vikas Gupta , K. S. Kasana , Puneet Tandon

In this paper, we review some recent work on amorphous materials using current "first principles" electronic structure/molecular dynamics techniques. The main theme of the paper is to emphasize new directions in the use of such ab initio…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. A. Drabold , P. Biswas , D. Tafen , R. Atta-Fynn

The analysis of the spatial distribution and kinematics of galaxies in clusters allows one to determine the cluster internal dynamics. In this paper, I review the state of the art of this topic. In particular, I summarize what we have…

Astrophysics · Physics 2007-05-23 Andrea Biviano
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