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1

Liu, Jing, Fuyuan Cao, Xiao-Zhi Gao, Liqin Yu, and Jiye Liang. "A Cluster-Weighted Kernel K-Means Method for Multi-View Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 4860–67. http://dx.doi.org/10.1609/aaai.v34i04.5922.

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Анотація:
Clustering by jointly exploiting information from multiple views can yield better performance than clustering on one single view. Some existing multi-view clustering methods aim at learning a weight for each view to determine its contribution to the final solution. However, the view-weighted scheme can only indicate the overall importance of a view, which fails to recognize the importance of each inner cluster of a view. A view with higher weight cannot guarantee all clusters in this view have higher importance than them in other views. In this paper, we propose a cluster-weighted kernel k-mea
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2

Yin, Jun, Shiliang Sun, Lai Wei, and Pei Wang. "Discriminatively Fuzzy Multi-View K-means Clustering with Local Structure Preserving." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 15 (2024): 16478–85. http://dx.doi.org/10.1609/aaai.v38i15.29585.

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Анотація:
Multi-view K-means clustering successfully generalizes K-means from single-view to multi-view, and obtains excellent clustering performance. In every view, it makes each data point close to the center of the corresponding cluster. However, multi-view K-means only considers the compactness of each cluster, but ignores the separability of different clusters, which is of great importance to producing a good clustering result. In this paper, we propose Discriminatively Fuzzy Multi-view K-means clustering with Local Structure Preserving (DFMKLS). On the basis of minimizing the distance between each
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3

Zhang, Lixiang, Lin Lin, and Jia Li. "Multi-view clustering by CPS-merge analysis with application to multimodal single-cell data." PLOS Computational Biology 19, no. 4 (2023): e1011044. http://dx.doi.org/10.1371/journal.pcbi.1011044.

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Анотація:
Multi-view data can be generated from diverse sources, by different technologies, and in multiple modalities. In various fields, integrating information from multi-view data has pushed the frontier of discovery. In this paper, we develop a new approach for multi-view clustering, which overcomes the limitations of existing methods such as the need of pooling data across views, restrictions on the clustering algorithms allowed within each view, and the disregard for complementary information between views. Our new method, called CPS-merge analysis, merges clusters formed by the Cartesian product
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4

Wang, Xueyi, Lele Zhang, Zheng Fan, Yang Liu, Chen Chen, and Fang Deng. "From Coarse to Fine: A Matching and Alignment Framework for Unsupervised Cross-View Geo-Localization." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 8 (2025): 8024–32. https://doi.org/10.1609/aaai.v39i8.32865.

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Анотація:
Cross-view geo-localization aims at determining the geographic location of a query image by matching the reference images. The matching pairs can be captured from diverse perspectives, such as those from satellites and drones. Most existing methods are supervised that require input of location-labeled images or matched and unmatched image pairs for training, resulting in high labor costs. Moreover, current unsupervised methods perform instances matching directly between different perspectives with dramatic discrepancies, resulting in poor performance. To address these issues, this paper propos
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5

Su, Peng, Shudong Huang, Weihong Ma, Deng Xiong, and Jiancheng Lv. "Multi-view Granular-ball Contrastive Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 19 (2025): 20637–45. https://doi.org/10.1609/aaai.v39i19.34274.

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Анотація:
Previous multi-view contrastive learning methods typically operate at two scales: instance-level and cluster-level. The former generally constructs positive and negative pairs based on the correspondence between samples and view instances. These methods aim to bring positive pairs closer and push negative pairs further apart in the latent space. This kind of approaches has the drawback of inevitably introducing false negatives in an unsupervised setting, leading to reduced model discriminability. The latter usually involves calculating cluster assignments for samples under each view and maximi
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6

Lee, Seong-Kook, Myungshin Im, Eunhee Ko, et al. "Star-formation Property of High Redshift Galaxies in Clusters: Perceptive View from Observation and Simulation." Proceedings of the International Astronomical Union 17, S373 (2021): 260–63. http://dx.doi.org/10.1017/s1743921322004409.

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AbstractThe evolution of star formation properties of galaxies depends on the environment where galaxies reside, and generally star formation of galaxies in dense environment decreases more quickly. Interestingly, the star formation property of high-redshift galaxies clusters vary largely even though they are at similar redshift. We have found that the large-scale environment surrounding each galaxy cluster can contribute to make this cluster-by-cluster variation. This correlation is found in the results from observational data as well as in the simulations of galaxy formation. We suggest the
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7

Castellanos, Raúl, Francisco Najarro, Miriam Garcia, et al. "An infrared view of NGC3603." Proceedings of the International Astronomical Union 18, S361 (2022): 97–99. http://dx.doi.org/10.1017/s174392132200196x.

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AbstractNGC3603 is one of the youngest massive clusters of the Milky Way which uniquely enables studying the interplay between massive star feedback and the surrounding interstellar medium. Yet, a deep infrared (IR) view of the cluster is missing. We present guaranteed time observations of NGC3603 consisting of near infrared spectroscopy taken with VLT-KMOS. This data set will provide a first, rather complete IR census.
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8

Rines, Kenneth J., Jubee Sohn, Margaret J. Geller, and Antonaldo Diaferio. "A Spectroscopic View of the JWST/GTO Strong Lensing Cluster A1489." Astrophysical Journal 930, no. 2 (2022): 156. http://dx.doi.org/10.3847/1538-4357/ac67a8.

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Анотація:
Abstract We discuss a spectroscopic survey of the strong lensing cluster A1489 that includes redshifts for 195 cluster members along with central velocity dispersions for 188 cluster members. The caustic technique applied to the redshift survey gives the dynamical parameters M 200 = (1.25 ± 0.09) × 1015 M ⊙, R 200 = 1.97 ± 0.05 Mpc, and a cluster line-of-sight velocity dispersion of 1150 ± 72 km s−1 within R 200. These parameters are very similar to those of other strong lensing systems with comparably large Einstein radii. We use the spectroscopy and deep photometry to demonstrate that A1489
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9

Suprihadi, Suprihadi, Rini Kartika Hudiono, and Lina Sinatra Wijaya. "Rancang Bangun Sistem Jejaring Klaster Berbasis Web Menggunakan Metode Model View Controller." CCIT Journal 6, no. 3 (2013): 308–31. http://dx.doi.org/10.33050/ccit.v6i3.359.

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Анотація:
Cluster in Indonesia particularly in the area of Central Java in 2010 totaled 150. Based on the results of the survey in Demak, Wonosobo and Pemalang, most Clusters does not yet have a website as a media product promotion and Cluster communication. Some Cluster already leverages media Blog and facebook but the media still do not meet the expected needs because media Blog and Facebook are not a media for product promotion. This is because the limitations of cost and the scarcity of skilled human resources information technology owned by the Cluster. Therefore, this research was conducted on the
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10

Ragone-Figueroa, C., G. L. Granato, S. Borgani, et al. "Evolution and role of mergers in the BCG–cluster alignment. A view from cosmological hydrosimulations." Monthly Notices of the Royal Astronomical Society 495, no. 2 (2020): 2436–45. http://dx.doi.org/10.1093/mnras/staa1389.

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ABSTRACT Contradictory results have been reported on the time evolution of the alignment between clusters and their brightest cluster galaxy (BCG). We study this topic by analysing cosmological hydrosimulations of 24 massive clusters with $M_{200}|_{z=0} \gtrsim 10^{15}\, \rm {\, M_{\odot }}$, plus 5 less massive with $1 \times 10^{14} \lesssim M_{200}|_{z=0} \lesssim 7 \times 10^{14}\, \rm {\, M_{\odot }}$, which have already proven to produce realistic BCG masses. We compute the BCG alignment with both the distribution of cluster galaxies and the dark matter (DM) halo. At redshift z = 0, the
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11

POCHKIN, E. O. "ROLE OF CLUSTERS IN REGIONAL ECONOMIC DEVELOPMENT POLICIES." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 8 (2021): 175–78. http://dx.doi.org/10.36871/ek.up.p.r.2021.08.01.023.

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Анотація:
The article shows that regional economic development organizations often declare the presence of several clusters in the region; it is advisable to approach cluster practice from the point of view of an organization working with several clusters, rather than using a single (successful) cluster initiative.
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12

Feng, Wei, Guoshuai Sheng, Qianqian Wang, Quanxue Gao, Zhiqiang Tao, and Bo Dong. "Partial Multi-View Clustering via Self-Supervised Network." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 11 (2024): 11988–95. http://dx.doi.org/10.1609/aaai.v38i11.29086.

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Анотація:
Partial multi-view clustering is a challenging and practical research problem for data analysis in real-world applications, due to the potential data missing issue in different views. However, most existing methods have not fully explored the correlation information among various incomplete views. In addition, these existing clustering methods always ignore discovering discriminative features inside the data itself in this unsupervised task. To tackle these challenges, we propose Partial Multi-View Clustering via Self-Supervised \textbf{N}etwork (PVC-SSN) in this paper. Specifically, we employ
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13

Sabah, Ali, Sabrina Tiun, Nor Samsiah Sani, Masri Ayob, and Adil Yaseen Taha. "Enhancing web search result clustering model based on multiview multirepresentation consensus cluster ensemble (mmcc) approach." PLOS ONE 16, no. 1 (2021): e0245264. http://dx.doi.org/10.1371/journal.pone.0245264.

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Анотація:
Existing text clustering methods utilize only one representation at a time (single view), whereas multiple views can represent documents. The multiview multirepresentation method enhances clustering quality. Moreover, existing clustering methods that utilize more than one representation at a time (multiview) use representation with the same nature. Hence, using multiple views that represent data in a different representation with clustering methods is reasonable to create a diverse set of candidate clustering solutions. On this basis, an effective dynamic clustering method must consider combin
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14

Spirkova, Daniela, Dagmar Caganova, and Jana Sujanova. "Cluster Policy and its Influence on Economic Competitiveness." Applied Mechanics and Materials 718 (December 2014): 16–21. http://dx.doi.org/10.4028/www.scientific.net/amm.718.16.

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Анотація:
The paper deals with economic benefits of clusters connected to competitiveness and regional development. Hard and soft benefits of clusters are described in relationship to innovation environment. The main focus is put on cluster policy influence on competitiveness of economy from the point of view of advantages of cluster creation for SME ́s. However, cluster policy contributes to the increase of competitiveness of small and medium enterprises.
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15

Xu, Jie, Chao Li, Yazhou Ren, et al. "Deep Incomplete Multi-View Clustering via Mining Cluster Complementarity." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (2022): 8761–69. http://dx.doi.org/10.1609/aaai.v36i8.20856.

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Incomplete multi-view clustering (IMVC) is an important unsupervised approach to group the multi-view data containing missing data in some views. Previous IMVC methods suffer from the following issues: (1) the inaccurate imputation or padding for missing data negatively affects the clustering performance, (2) the quality of features after fusion might be interfered by the low-quality views, especially the inaccurate imputed views. To avoid these issues, this work presents an imputation-free and fusion-free deep IMVC framework. First, the proposed method builds a deep embedding feature learning
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16

WANG, Z. P., F. S. ZHANG, X. H. ZENG, F. WANG, S. F. ZHANG, and Y. P. ZHANG. "CLUSTER MATTER FORMATION IN CLUSTER COLLISIONS." International Journal of Modern Physics B 19, no. 15n17 (2005): 2465–70. http://dx.doi.org/10.1142/s0217979205031158.

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By using the tight-binding molecular dynamics simulations in cluster collisions, we give some evidences of the structures of ( Na 9)2 cluster dimer and ( Na 4)4 cluster tetramer from the dynamical point of view. We show that the ( Na 9)2 and ( Na 4)4 cluster matter may exist as intermediate states and finally decay to compact structure in real collision process. With a technique called "sharp cooling", the stable cluster structures ( Na 9)2 and ( Na 4)4 are brought into being to end. The eigen-mode frequencies of these clusters are obtained with Fourier transform of the velocity auto-correlati
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17

Clément, Benjamin, Johan Richard, Guillaume Mahler, Vera Patrício, and David Lagattuta. "Tightening the constraints on the mass distribution of the Frontier Fields MACSJ0416.1-2403 with VLT/MUSE spectroscopy." Proceedings of the International Astronomical Union 11, A29B (2015): 781–82. http://dx.doi.org/10.1017/s1743921316006803.

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AbstractWe have combined the performances of the VLT/MUSE spectrograph together with the power of gravitational lensing by Frontier Fields galaxy clusters to offer a unique magnified view of the distant universe. The large field of view over a wide optical wavelength domain enables redshift measurements of numerous lensed galaxies in the cluster core. Spectroscopically-confirmed multiple-imaged systems are further used as strong constraints to improve the cluster mass model. Here, we focus on the galaxy cluster MACSJ0416.1-2403 and compare the revised magnification map with results from previo
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18

Ryś, S., G. Siemieniec-Oziȩbło, M. Urbanik, M. Soida, and A. Kus. "ToPoS view of the Perseus cluster." Astronomische Nachrichten 330, no. 9-10 (2009): 928–30. http://dx.doi.org/10.1002/asna.200911265.

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19

Kim, Young Hyun, Kug Jin Jeon, Chena Lee, Yoon Joo Choi, Hoi-In Jung, and Sang-Sun Han. "Analysis of the mandibular canal course using unsupervised machine learning algorithm." PLOS ONE 16, no. 11 (2021): e0260194. http://dx.doi.org/10.1371/journal.pone.0260194.

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Анотація:
Objectives Anatomical structure classification is necessary task in medical field, but the inevitable variability of interpretation among experts makes reliable classification difficult. This study aims to introduce cluster analysis, unsupervised machine learning method, for classification of three-dimensional (3D) mandibular canal (MC) courses, and to visualize standard MC courses derived from cluster analysis in the Korean population. Materials and methods A total of 429 cone-beam computed tomography images were used. Four sites in the mandible were selected for the measurement of the MC cou
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20

Lodieu, N., A. Pérez-Garrido, R. L. Smart та R. Silvotti. "A 5D view of the α Per, Pleiades, and Praesepe clusters". Astronomy & Astrophysics 628 (серпень 2019): A66. http://dx.doi.org/10.1051/0004-6361/201935533.

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Aims. Our scientific goal is to provide revised membership lists of the α Per, Pleiades, and Praesepe clusters exploiting the second data release of Gaia and produce five-dimensional maps (α, δ, π, μα cos δ, μδ) of these clusters. Methods. We implemented the kinematic method combined with the statistical treatment of parallaxes and proper motions to identify astrometric member candidates of three of the most nearby and best studied open clusters in the sky. Results. We cross-correlated the Gaia catalogue with large-scale public surveys to complement the astrometry of Gaia with multi-band photo
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21

Zhang, Chao, Xiuyi Jia, Zechao Li, Chunlin Chen, and Huaxiong Li. "Learning Cluster-Wise Anchors for Multi-View Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 15 (2024): 16696–704. http://dx.doi.org/10.1609/aaai.v38i15.29609.

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Анотація:
Due to its effectiveness and efficiency, anchor based multi-view clustering (MVC) has recently attracted much attention. Most existing approaches try to adaptively learn anchors to construct an anchor graph for clustering. However, they generally focus on improving the diversity among anchors by using orthogonal constraint and ignore the underlying semantic relations, which may make the anchors not representative and discriminative enough. To address this problem, we propose an adaptive Cluster-wise Anchor learning based MVC method, CAMVC for short. We first make an anchor cluster assumption t
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22

Qin, Yalan, Guorui Feng, and Xinpeng Zhang. "Scalable One-Pass Incomplete Multi-View Clustering by Aligning Anchors." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 19 (2025): 20042–50. https://doi.org/10.1609/aaai.v39i19.34207.

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Анотація:
Multi-view clustering has gained increasing attention by utilizing the complementary and consensus information across views. To alleviate the computation cost for the existing multi-view clustering approaches on datasets with large scales, studies based on anchor have been presented. Although extensively adopted in the real scenarios, most of these works ignore to learn an integral subspace revealing the cluster structure with anchors from different views being aligned, where the centroid and cluster assignment matrix can be directly achieved based on the integral subspace. Moreover, these wor
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23

Franciosini, E., G. G. Sacco, R. D. Jeffries, et al. "The Gaia DR2 view of the Gamma Velorum cluster: resolving the 6D structure." Astronomy & Astrophysics 616 (August 2018): L12. http://dx.doi.org/10.1051/0004-6361/201833815.

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Gaia-ESO Survey observations of the young Gamma Velorum cluster led to the discovery of two kinematically distinct populations, Gamma Vel A and B, respectively, with population B extended over several square degrees in the Vela OB2 association. Using the Gaia DR2 data for a sample of high-probability cluster members, we find that the two populations differ not only kinematically, but are also located at different distances along the line of sight, with the main cluster Gamma Vel A being closer. A combined fit of the two populations yields ϖA = 2.895 ± 0.008 mas and ϖB = 2.608 ± 0.017 mas, with
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24

Omar, Z. Ali, Siti Rahayu Mohd Hashim, Justin Sentian, and Su Na Chin. "Application of K-Means Clustering and Calendar View Visualisation for Air Pollution Index Analysis." IOP Conference Series: Earth and Environmental Science 1103, no. 1 (2022): 012004. http://dx.doi.org/10.1088/1755-1315/1103/1/012004.

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Two years of diurnal concentration of particulate matter (PM10 ) and nitrogen dioxide with the addition of relative humidity measurement, collected from Putrajaya, Malaysia’s ground-based measurement station from January 2014 to December 2015, were analysed. K-means clustering was employed and optimal clusters of four were identified for each year based on the most suggested number of clusters from internal cluster validation measures of the total within sum of square, silhouette index and gap statistics. Each cluster was then profiled where each mean pollutant sub-indices were calculated and
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25

Lu, Han, Quanxue Gao, Qianqian Wang, Ming Yang, and Wei Xia. "Centerless Multi-View K-means Based on the Adjacency Matrix." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (2023): 8949–56. http://dx.doi.org/10.1609/aaai.v37i7.26075.

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Анотація:
Although K-Means clustering has been widely studied due to its simplicity, these methods still have the following fatal drawbacks. Firstly, they need to initialize the cluster centers, which causes unstable clustering performance. Secondly, they have poor performance on non-Gaussian datasets. Inspired by the affinity matrix, we propose a novel multi-view K-Means based on the adjacency matrix. It maps the affinity matrix to the distance matrix according to the principle that every sample has a small distance from the points in its neighborhood and a large distance from the points outside of the
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26

Terni de Gregory, B., B. Hugo, T. Venturi, et al. "A MeerKAT view on galaxy clusters: a radio–optical study of Abell 1300 and MACS J1931.8−2634." Monthly Notices of the Royal Astronomical Society 504, no. 2 (2021): 2924–39. http://dx.doi.org/10.1093/mnras/stab964.

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ABSTRACT In this paper, we present results from a radio–optical study of the galaxy populations of the galaxy clusters Abell 1300 and MACS J1931.8−2634, a merger and a relaxed system respectively both located at z ∼ 0.3, aimed at finding evidence of merger-induced radio emission. Radio observations are taken at 1.28 GHz with the MeerKAT interferometer during its early-stage commissioning phase, and combined with archive optical data. We generated catalogues containing 107 and 162 radio sources in the A 1300 and MACS J1931.8−2634 cluster fields, respectively, above a 0.2 mJy threshold and withi
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27

Kluender, R. A., and T. L. Walkingstick. "Rethinking How Nonindustrial Landowners View Their Lands." Southern Journal of Applied Forestry 24, no. 3 (2000): 150–58. http://dx.doi.org/10.1093/sjaf/24.3.150.

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Анотація:
Abstract Southwide nonindustrial landowners account for 70% of the commercial timber land and 69% of the total growing stock. These forests provide a diversity of benefits including solid wood products, wood fiber, wildlife habitat, recreation opportunities, water conservation, and scenic beauty. This study explores the diversity of landowner groups by developing landowner typologies (groups of individuals with similar characteristics) based on grouped responses to a mail questionnaire. Selected landowners were mailed a questionnaire that requested information about their land and their person
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28

NOZUE, Y., T. KODAIRA, S. OHWASHI, N. TOGASHI, and O. TERASAKI. "FERROMAGNETISM OF ALKALI-METAL CLUSTERS INCORPORATED IN THE PERIODIC SPACE OF ZEOLITE LTA." Surface Review and Letters 03, no. 01 (1996): 701–6. http://dx.doi.org/10.1142/s0218625x96001261.

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Анотація:
Magnetic properties are reported for rubidium and potassium clusters arrayed in a simple-cubic structure in zeolite LTA crystal. A ferromagnetism is observed, although no magnetic element is contained there. The result clearly indicates the intercluster interaction. The ferromagnetic properties vary depending on the average number of ns electrons of cluster. Optical properties reveal quantum electronic levels of cluster. The ferromagnetism is interpreted qualitatively in terms of the itinerant electron model based on the quantum levels of cluster. The magnetic properties of various clusters ob
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29

Chen, Man-Sheng, Ling Huang, Chang-Dong Wang, and Dong Huang. "Multi-View Clustering in Latent Embedding Space." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 3513–20. http://dx.doi.org/10.1609/aaai.v34i04.5756.

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Анотація:
Previous multi-view clustering algorithms mostly partition the multi-view data in their original feature space, the efficacy of which heavily and implicitly relies on the quality of the original feature presentation. In light of this, this paper proposes a novel approach termed Multi-view Clustering in Latent Embedding Space (MCLES), which is able to cluster the multi-view data in a learned latent embedding space while simultaneously learning the global structure and the cluster indicator matrix in a unified optimization framework. Specifically, in our framework, a latent embedding representat
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30

Pu, Jingyu, Chenhang Cui, Xinyue Chen, et al. "Adaptive Feature Imputation with Latent Graph for Deep Incomplete Multi-View Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 13 (2024): 14633–41. http://dx.doi.org/10.1609/aaai.v38i13.29380.

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Анотація:
In recent years, incomplete multi-view clustering (IMVC), which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Previous IMVC methods suffer from the following issues: (1) the inaccurate imputation for missing data, which leads to suboptimal clustering performance, and (2) most existing IMVC models merely consider the explicit presence of graph structure in data, ignoring the fact that latent graphs of different views also provide valuable information for the clustering task. To overcome such challenges, we present a novel method
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31

Saidov, Mukhammadali, and Ilhom Ochilov. "Theoretical analysis of agricultural clusters in innovative economy." BIO Web of Conferences 65 (2023): 03006. http://dx.doi.org/10.1051/bioconf/20236503006.

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Анотація:
This article analyzes the theoretical aspects of clusters in the innovative economy and their management, including the increase in economic efficiency of agro-clusters as a result of the organization of the agricultural sector on the basis of “production - service - production - storage - supply - processing - sales” development of cluster services, increase in production and diversification of exported finished products as a result of improvements, the authors have developed a unique, new definition of the term “cluster”. From a methodological point of view, the “face” of a cluster, its spec
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32

Chen, Yawei, Huibing Wang, Jinjia Peng, and Yang Wang. "Anchor Learning with Potential Cluster Constraints for Multi-view Clustering." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 15 (2025): 15939–47. https://doi.org/10.1609/aaai.v39i15.33750.

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Анотація:
Anchor-based multi-view clustering has received extensive attention due to its efficient performance. Existing methods only focus on how to dynamically learn anchors from the original data and simultaneously construct anchor graphs describing the relationships between samples and perform clustering, while ignoring the reality of anchors, i.e., high-quality anchors should be generated uniformly from different clusters of data rather than scattered outside the clusters. To deal with this problem, we propose a noval method termed Anchor Learning with Potential Cluster Constraints for Multi-view C
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33

Корепова and Valeriya Korepova. "PROBLEMS OF FORMATION SPORTS CLUSTERS IN RUSSIA." Clusters. Research and Development 2, no. 2 (2016): 35–38. http://dx.doi.org/10.12737/21443.

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Formation of sports clusters in Russia is an expedient solution to the problems of modern sports education. The organization will also allow the cluster to increase the competitiveness of the state sport. In the view of the authors to create a sports cluster, you must pay special attention to the establishment of diagnostic centers.
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34

Litvintseva, Galina, and Ekaterina Shits. "Territory Management in View of Cluster Potential." Procedia Economics and Finance 27 (2015): 216–23. http://dx.doi.org/10.1016/s2212-5671(15)00993-4.

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35

Molendi, S., S. De Grandi, and M. Guainazzi. "A BeppoSAX view of the Centaurus Cluster." Astronomy & Astrophysics 392, no. 1 (2002): 13–17. http://dx.doi.org/10.1051/0004-6361:20020696.

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36

Durret, F., E. Slezak, and C. Adami. "The cluster Abell 780: an optical view." Astronomy & Astrophysics 506, no. 2 (2009): 637–45. http://dx.doi.org/10.1051/0004-6361/200912264.

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37

Rawat, Vineet, M. R. Samal, D. K. Ojha, et al. "Peering into the Heart of the Giant Molecular Cloud G148.24+00.41: A Deep Near-infrared View of the Newly Hatched Cluster FSR 655." Astronomical Journal 168, no. 3 (2024): 136. http://dx.doi.org/10.3847/1538-3881/ad630d.

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Abstract We present a detailed near-infrared study of an embedded cluster located in the hub of the giant molecular cloud G148.24+00.41 of mass ∼105 M ⊙, with the TANSPEC instrument mounted on the 3.6 m Devasthal Optical Telescope. The hub is located near the geometric center of the cloud and represents its most massive clump. We studied the central 2 pc × 2 pc area of the hub with 5σ limiting magnitudes of 20.5, 20.1, and 18.6 mag in the J, H, and K s bands, respectively. Using the K s -band luminosity function and comparing it with the synthetic clusters, we obtained the age of the cluster a
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38

Jyoti, Davinder Singh, S. K. Dhankhar, et al. "Genetic Diversity among Brinjal Genotypes Grown in North-West India." Journal of Experimental Agriculture International 47, no. 5 (2025): 700–708. https://doi.org/10.9734/jeai/2025/v47i53458.

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Genetic diversity in brinjal (Solanum melongena L.) aim to explore the genetic differences among various genotypes. The primary goal is to identify valuable genetic material that can be utilized in breeding programs to develop superior brinjal varieties with improved yield. Keeping it in view, a field experiment was conducted at Research Farm, Department of Vegetable Science, CCSHAU, Hisar using thirty genotypes for twenty-two morphological characters to select diverse parents through multivariate analysis. Genetic divergence studies revealed that cluster I, accommodated a maximum number of ge
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39

Su, Y., Y. Zhang, G. Liang, et al. "A deep learning view of the census of galaxy clusters in IllustrisTNG." Monthly Notices of the Royal Astronomical Society 498, no. 4 (2020): 5620–28. http://dx.doi.org/10.1093/mnras/staa2690.

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ABSTRACT The origin of the diverse population of galaxy clusters remains an unexplained aspect of large-scale structure formation and cluster evolution. We present a novel method of using X-ray images to identify cool core (CC), weak cool core (WCC), and non-cool core (NCC) clusters of galaxies that are defined by their central cooling times. We employ a convolutional neural network, ResNet-18, which is commonly used for image analysis, to classify clusters. We produce mock Chandra X-ray observations for a sample of 318 massive clusters drawn from the IllustrisTNG simulations. The network is t
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40

Díez-Vial, Isabel, and Marta Fernández-Olmos. "Internal resources, local externalities and export performance: An application in the Iberian ham cluster." Journal of Management & Organization 19, no. 4 (2013): 478–97. http://dx.doi.org/10.1017/jmo.2013.32.

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AbstractThis research aims to complement resource-based view with a cluster approach in identifying which elements, both internal to the firm and locally available, improve firms’ export performance. While in the resource-based view exporting firms are contingent upon the development of intangible resources, from a cluster approach exporters exploit local externalities, mainly related to local information, knowledge and resource spillovers. We present empirical evidence from the Iberian ham cluster in Spain, which confirms the relevance of intangibles such as R&D and marketing promotion, b
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41

Masterson, Megan, Michael McDonald, Behzad Ansarinejad, et al. "Evidence for AGN-regulated Cooling in Clusters at z ∼ 1.4: A Multiwavelength View of SPT-CL J0607-4448." Astrophysical Journal 944, no. 2 (2023): 164. http://dx.doi.org/10.3847/1538-4357/acae9e.

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Abstract We present a multiwavelength analysis of the galaxy cluster SPT-CL J0607-4448 (SPT0607), which is one of the most distant clusters discovered by the South Pole Telescope at z = 1.4010 ± 0.0028. The high-redshift cluster shows clear signs of being relaxed with well-regulated feedback from the active galactic nucleus (AGN) in the brightest cluster galaxy (BCG). Using Chandra X-ray data, we construct thermodynamic profiles and determine the properties of the intracluster medium. The cool-core nature of the cluster is supported by a centrally peaked density profile and low central entropy
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42

Zhang, Jiadong, and Wei Wang. "VP-SOM: View-Planning Method for Indoor Active Sparse Object Mapping Based on Information Abundance and Observation Continuity." Sensors 23, no. 23 (2023): 9415. http://dx.doi.org/10.3390/s23239415.

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Active mapping is an important technique for mobile robots to autonomously explore and recognize indoor environments. View planning, as the core of active mapping, determines the quality of the map and the efficiency of exploration. However, most current view-planning methods focus on low-level geometric information like point clouds and neglect the indoor objects that are important for human–robot interaction. We propose a novel View-Planning method for indoor active Sparse Object Mapping (VP-SOM). VP-SOM takes into account for the first time the properties of object clusters in the coexistin
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43

Guan, Renxiang, Wenxuan Tu, Siwei Wang, et al. "Structure-Adaptive Multi-View Graph Clustering for Remote Sensing Data." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 16 (2025): 16933–41. https://doi.org/10.1609/aaai.v39i16.33861.

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Multi-view clustering (MVC) for remote sensing data is a critical and challenging task in Earth observation. Although recent advances in graph neural network (GNN)-based MVC have shown remarkable success, the most prevalent approaches have two major limitations: 1) heavily relying on a predefined yet fixed graph, which limits the performance of clustering because the large number of indistinguishable background samples contained in remote sensing data would introduce noise information and increase structure heterogeneity; 2) ignoring the effect of confusing samples on cluster structure compact
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44

De Almeida, Bibiana Skrebsky, Flávia Camargo Bernardi, Uiliam Hahn Biegelmeyer, et al. "VISÃO BASEADA EM RECURSOS NO CLUSTER VITIVINÍCOLA DA SERRA GAÚCHA." Revista Visão: Gestão Organizacional 7, no. 2 (2018): 104–20. http://dx.doi.org/10.33362/visao.v7i2.1625.

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O presente estudo foi realizado por meio de uma revisão da literatura sobre clusters e a Visão Baseada em Recursos (RBV). O artigo teve como objeto de estudo o cluster vitivinícola da Serra Gaúcha/RS. Com o referido estudo foi possível compreender como a RBV pode ser utilizada para criar vantagens competitivas. A metodologia utilizada foi uma pesquisa básica de revisão de literatura, exploratória, bibliográfica e documental. Averigou-se como resultado que o cluster apresenta potencial para se destacar internacionalmente, desde que analise seus recursos e a maneira como eles podem ser estratégi
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45

Gran, F., M. Zoccali, R. Contreras Ramos, et al. "Globular cluster candidates in the Galactic bulge: Gaia and VVV view of the latest discoveries." Astronomy & Astrophysics 628 (August 2019): A45. http://dx.doi.org/10.1051/0004-6361/201834986.

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Context. Thanks to the recent wide-area photometric surveys, the number of star cluster candidates have risen exponentially in the last few years. Most detections, however, are based only on the presence of an overdensity of stars in a given region or an overdensity of variable stars, regardless of their distance. As candidates, their detection has not been dynamically confirmed. Therefore, it is currently unknown how many and which of the published candidates are true clusters and which are chance alignments. Aims. We present a method to detect and confirm star clusters based on the spatial d
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46

Engelberg, Joseph, Arzu Ozoguz, and Sean Wang. "Know Thy Neighbor: Industry Clusters, Information Spillovers, and Market Efficiency." Journal of Financial and Quantitative Analysis 53, no. 5 (2018): 1937–61. http://dx.doi.org/10.1017/s0022109018000261.

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Firms in industry clusters have market prices that are more efficient than firms outside clusters. To establish causality, we analyze exogenous firm relocations and find that firms that relocate into industry clusters have higher levels of industry information in their prices. We argue that geographical proximity allows for information spillovers, reducing marginal cost to information producers. Our evidence supports this view: Analysts are more likely to cover stocks inside industry clusters, and when institutional investors have a large position in one stock in the industry cluster, they are
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47

Wang, Gicheol, Dongkyun Kim, and Gihwan Cho. "A Secure Cluster Formation Scheme in Wireless Sensor Networks." International Journal of Distributed Sensor Networks 8, no. 10 (2012): 301750. http://dx.doi.org/10.1155/2012/301750.

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In wireless sensor networks, clustering expedites many desirable functions such as load balancing, energy savings, and distributed key management. For secure clustering, it is very important to find compromised nodes and remove them during the initial cluster formation process. If some nodes are compromised and survive the censorship process, they can make some nodes have a different cluster view and can split a cluster into multiple clusters to deteriorate cluster quality as a whole. To resolve these problems, we propose a robust scheme against such attacks in this paper. First, our scheme ge
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48

Shah, Nevil, K. P. Singh, and Annapurni Subramaniam. "A multiwavelength view of the open cluster NGC 2527: discovery of active stars." Monthly Notices of the Royal Astronomical Society 493, no. 4 (2020): 5565–82. http://dx.doi.org/10.1093/mnras/staa636.

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ABSTRACT Star clusters are ideal platforms for categorizing X-ray emitting stars and to study X-ray emission as a function of stellar age and activity. We present a comprehensive study of an open star cluster, NGC 2527, by combining data from XMM-UVOT-Gaia. Cluster membership of stars and their photometry are taken from Gaia and cross-matched with XMM and UVOT detections. We estimate the age of NGC 2527 as ∼630 Myr, reddening as E(B − V) = 0.13 mag, and a distance of 642 ± 30 pc using PARSEC isochrones. We detect five sub-subgiants and five bandgap stars, which defy single star evolution. We e
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49

Gran, F., M. Zoccali, A. Rojas-Arriagada, et al. "APOGEE view of the globular cluster NGC 6544." Monthly Notices of the Royal Astronomical Society 504, no. 3 (2021): 3494–508. http://dx.doi.org/10.1093/mnras/stab1051.

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ABSTRACT The second phase of the APOGEE survey is providing near-infrared (near-IR), high-resolution, high signal-to-noise spectra of stars in the halo, disc, bar, and bulge of the Milky Way. The near-IR spectral window is especially important in the study of the Galactic bulge, where stars are obscured by the dust and gas of the disc in its line of sight. We present a chemical characterization of the globular cluster NGC 6544 with high-resolution spectroscopy. The characterization of the cluster chemical fingerprint, given its status of ‘interloper’ towards the Galactic bulge and clear signat
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50

Golova, Tat'yana, and Levon Mailyan. "Clustering of shotcrete technology from the position of a single system integrated approach." Construction and Architecture 10, no. 2 (2022): 41–45. http://dx.doi.org/10.29039/2308-0191-2022-10-2-41-45.

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Анотація:
The article proposes a unified structural approach to the use of shotcrete technology in construction from the point of view of cluster analysis. It is proposed to consider the shotcrete technology as a cluster with multilevel capabilities. A method of clustering the shotcrete technology has been developed, its main clusters and their parameters have been determined. The clustering algorithm of shotcrete technology is presented.
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