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Bibliographies thématiques / Intracluster Similarity

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Littérature scientifique sur le sujet « Intracluster Similarity »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 10 mars 2023

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Articles de revues sur le sujet "Intracluster Similarity"

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Boobalan, Parimala M. "Grouping of Nodes in Social Networks Based on Multiphase Approach." Recent Patents on Computer Science 12, no. 1 (2019): 25–33. http://dx.doi.org/10.2174/2213275911666181022111924.

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Background: Recent advances in the field of information and social network has led to the problem of community detection that has got much attention among the researchers. Objective: This paper focus on community discovery, a fundamental task in network analysis by balancing both attribute and structural similarity. The attribute similarity is evaluated using the Jaccard coefficient and Structural similarity is achieved through modularity. Methods: The proposed algorithm is designed for identifying communities in social networks by fusing attribute and structural similarity. The algorithm reta

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Yoo, Jaewon, Jongwan Ko, Cristiano G. Sabiu, et al. "Comparison of Spatial Distributions of Intracluster Light and Dark Matter." Astrophysical Journal Supplement Series 261, no. 2 (2022): 28. http://dx.doi.org/10.3847/1538-4365/ac7142.

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Abstract In a galaxy cluster, the relative spatial distributions of dark matter, member galaxies, gas, and intracluster light (ICL) may connote their mutual interactions over the cluster’s evolution. However, it is a challenging problem to provide a quantitative measure for matching the shapes between two multidimensional scalar distributions. We present a novel methodology, named the weighted overlap coefficient (WOC), to quantify the similarity of two-dimensional spatial distributions. We compare the WOC with a standard method known as the modified Hausdorff distance (MHD) method. We find th

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Raj, Aditya, and Sonajharia Minz. "A Scalable Unsupervised Classification Method Using Rough Set for Remote Sensing Imagery." International Journal of Software Science and Computational Intelligence 13, no. 2 (2021): 65–88. http://dx.doi.org/10.4018/ijssci.2021040104.

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Reference to geographic scale and geographic space representation are characteristics of geospatial data. This work has discussed two issues related to satellite image data, namely huge size and mixed pixels. In clustering, an unsupervised classification and a set of similar objects are grouped together based on the similarity measures. The similarity between intracluster objects is high, whereas the similarity between intercluster objects is low. This paper proposes a clustering technique called spatial rough k-means that classifies the mixed pixels based on their spatial neighbourhood relati

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Liew, ECY, DJ Maclean, JM Manners, D. Dawson, and JAG Irwin. "Use of Restriction Fragment Length Polymorphisms to Study Genetic Relationships Between Australian and Japanese Isolates of Phytophthora vignae." Australian Journal of Botany 39, no. 4 (1991): 335. http://dx.doi.org/10.1071/bt9910335.

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The genetic relationships among 10 Australian accessions of Phytophthora vignae (Pv) isolated from cowpea, two Japanese accessions of Pv isolated from adzuki bean and one accession of Phytophthora megasperma f. sp. glycinea (Pmg) isolated from soybean were assessed using Restriction Fragment Length Polymorphisms (RFLPs). Using five high-copy probes derived from genomic libraries of Pv and Pmg, RFLP banding patterns used to calculate the genetic distance, d, between isolates, showed that Pmg was very dissimilar to Pv (d = 0.102). In contrast, a close similarity among different isolates of Pv wa

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Dykhanov, Stanyslav, and Natalia Guk. "Analysis of the structure of web resources using the object model." Eastern-European Journal of Enterprise Technologies 5, no. 2(119) (2022): 6–13. http://dx.doi.org/10.15587/1729-4061.2022.265961.

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The methodology for analyzing the structure of a web resource using an object model, which is based on the description of the page in HTML and using style sheets, has been proposed. The object of research is a web resource page, the model of which is depicted as a DOM tree. Data on the structural elements of the tree are supplemented with information about the styles of the design of the pages. To determine the similarity of pages, it is proposed to apply a criterion that takes into account the structural and stylistic similarity of pages with the corresponding coefficients. To compare page mo

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Green, Sheridan B., Han Aung, Daisuke Nagai, and Frank C. van den Bosch. "Scatter in Sunyaev–Zel’dovich effect scaling relations explained by inter-cluster variance in mass accretion histories." Monthly Notices of the Royal Astronomical Society 496, no. 3 (2020): 2743–61. http://dx.doi.org/10.1093/mnras/staa1712.

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ABSTRACT X-ray and microwave cluster scaling relations are immensely valuable for cosmological analysis. However, their power is limited by astrophysical systematics that bias mass estimates and introduce additional scatter. Turbulence injected into the intracluster medium via mass assembly contributes substantially to cluster non-thermal pressure support, a significant source of such uncertainties. We use an analytical model to compute the assembly-driven non-thermal pressure profiles of haloes based on Monte Carlo-generated accretion histories. We introduce a fitting function for the average

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Wang, Fangshu, Shuai Wang, Xinzheng Niu, Jiahui Zhu, and Ting Chen. "Grid-Based Whole Trajectory Clustering in Road Networks Environment." Wireless Communications and Mobile Computing 2021 (November 24, 2021): 1–20. http://dx.doi.org/10.1155/2021/5295784.

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In the data mining of road networks, trajectory clustering of moving objects plays an important role in many applications. Most existing algorithms for this problem are based on every position point in a trajectory and face a significant challenge in dealing with complex and length-varying trajectories. This paper proposes a grid-based whole trajectory clustering model (GBWTC) in road networks, which regards the trajectory as a whole. In this model, we first propose a trajectory mapping algorithm based on grid estimation, which transforms the trajectories in road network space into grid sequen

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Chen, Haiyan, Linghui Zhang, Ligang Yuan, Weiqi Zhu, and Li Liu. "Air Traffic Complexity Assessment Based on Ordered Deep Metric." Aerospace 9, no. 12 (2022): 758. http://dx.doi.org/10.3390/aerospace9120758.

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Since air traffic complexity determines the workload of controllers, it is a popular topic in the research field. Benefiting from deep learning, this paper proposes an air traffic complexity assessment method based on the deep metric of air traffic images. An Ordered Deep Metric (ODM) is proposed to measure the similarity of the ordered samples. For each sample, its interclass loss is calculated to keep it close to the mean of the same class and far from the difference. Then, consecutive samples of the same class are considered as a cluster, and the intracluster loss is calculated to make the

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Fujita, Yutaka, Megan Donahue, Stefano Ettori, et al. "Halo Concentrations and the Fundamental Plane of Galaxy Clusters." Galaxies 7, no. 1 (2019): 8. http://dx.doi.org/10.3390/galaxies7010008.

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According to the standard cold dark matter (CDM) cosmology, the structure of dark halos including those of galaxy clusters reflects their mass accretion history. Older clusters tend to be more concentrated than younger clusters. Their structure, represented by the characteristic radius r s and mass M s of the Navarro–Frenk–White (NFW) density profile, is related to their formation time. In this study, we showed that r s , M s , and the X-ray temperature of the intracluster medium (ICM), T X , form a thin plane in the space of ( log r s , log M s , log T X ) . This tight correlation indicates t

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Thèses sur le sujet "Intracluster Similarity"

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PINARDI, STEFANO. "Movements recognition with intelligent multisensor analysis." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19297.

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In movement science with inertial sensor many different methodologies resolving specific aspects of movement recognition have been proposed. They are very interesting, and useful, but none of them are generally explicative of what is going on in the semantic sense. When we go down to the movement recognition/classification area (for example in Ambient Intelligence) we do not have a feasible model that can be considered generally predictive or usable for activity recognition. Also, in the field of movement recognition with inertial sensors many technological issues arise: technological div

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Chapitres de livres sur le sujet "Intracluster Similarity"

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Penikalapati, Pragathi, and A. Nagaraja Rao. "A Study on Efficient Clustering Techniques Involved in Dealing With Diverse Attribute Data." In Pattern Recognition Applications in Engineering. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1839-7.ch006.

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The compatibility issues among the characteristics of data involving numerical as well as categorical attributes (mixed) laid many challenges in pattern recognition field. Clustering is often used to group identical elements and to find structures out of data. However, clustering categorical data poses some notable challenges. Particularly clustering diversified (mixed) data constitute bigger challenges because of its range of attributes. Computations on such data are merely too complex to match the scales of numerical and categorical values due to its ranges and conversions. This chapter is intended to cover literature clustering algorithms in the context of mixed attribute unlabelled data. Further, this chapter will cover the types and state of the art methodologies that help in separating data by satisfying inter and intracluster similarity. This chapter further identifies challenges and Future research directions of state-of-the-art clustering algorithms with notable research gaps.

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