Articoli di riviste: "Post-clustering"

1

Im, Yeong-Hui. "A Post Web Document Clustering Algorithm". KIPS Transactions:PartB 9B, n. 1 (1 febbraio 2002): 7–16. http://dx.doi.org/10.3745/kipstb.2002.9b.1.007.

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Ong, S. H., e X. Zhao. "On post-clustering evaluation and modification". Pattern Recognition Letters 21, n. 5 (maggio 2000): 365–73. http://dx.doi.org/10.1016/s0167-8655(00)00003-9.

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Goyal, Poonam, N. Mehala, Divyansh Bhatia e Navneet Goyal. "Topical document clustering: two-stage post processing technique". International Journal of Data Mining, Modelling and Management 10, n. 2 (2018): 127. http://dx.doi.org/10.1504/ijdmmm.2018.092536.

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Bhatia, Divyansh, Navneet Goyal, Poonam Goyal e N. Mehala. "Topical document clustering: two-stage post processing technique". International Journal of Data Mining, Modelling and Management 10, n. 2 (2018): 127. http://dx.doi.org/10.1504/ijdmmm.2018.10013658.

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S, Shanmugapriyaa, Kuppusamy K.S e Aghila G. "Blosen: Blog Search Engine Based on Post Concept Clustering". International Journal of Ambient Systems and Applications 1, n. 3 (30 settembre 2013): 17–28. http://dx.doi.org/10.5121/ijasa.2013.1302.

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Lee, Ki-Jun, Kyung-Min Kim, Myung-Jin Lee, Woo-Ju Kim e June-S. Hong. "Post Clustering Method using Tag Hierarchy for Blog Search". Journal of Society for e-Business Studies 16, n. 4 (30 novembre 2011): 301–19. http://dx.doi.org/10.7838/jsebs.2011.16.4.301.

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Liu, Suyuan, Siwei Wang, Pei Zhang, Kai Xu, Xinwang Liu, Changwang Zhang e Feng Gao. "Efficient One-Pass Multi-View Subspace Clustering with Consensus Anchors". Proceedings of the AAAI Conference on Artificial Intelligence 36, n. 7 (28 giugno 2022): 7576–84. http://dx.doi.org/10.1609/aaai.v36i7.20723.

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Multi-view subspace clustering (MVSC) optimally integrates multiple graph structure information to improve clustering performance. Recently, many anchor-based variants are proposed to reduce the computational complexity of MVSC. Though achieving considerable acceleration, we observe that most of them adopt fixed anchor points separating from the subsequential anchor graph construction, which may adversely affect the clustering performance. In addition, post-processing is required to generate discrete clustering labels with additional time consumption. To address these issues, we propose a scalable and parameter-free MVSC method to directly output the clustering labels with optimal anchor graph, termed as Efficient One-pass Multi-view Subspace Clustering with Consensus Anchors (EOMSC-CA). Specially, we combine anchor learning and graph construction into a uniform framework to boost clustering performance. Meanwhile, by imposing a graph connectivity constraint, our algorithm directly outputs the clustering labels without any post-processing procedures as previous methods do. Our proposed EOMSC-CA is proven to be linear complexity respecting to the data size. The superiority of our EOMSC-CA over the effectiveness and efficiency is demonstrated by extensive experiments. Our code is publicly available at https://github.com/Tracesource/EOMSC-CA.

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DiCaprio, Christopher J., Mark Simons, Shelley J. Kenner e Charles A. Williams. "Post-seismic reloading and temporal clustering on a single fault". Geophysical Journal International 172, n. 2 (febbraio 2008): 581–92. http://dx.doi.org/10.1111/j.1365-246x.2007.03622.x.

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Balabaeva, Ksenia, e Sergey Kovalchuk. "Post-hoc Interpretation of Clinical Pathways Clustering using Bayesian Inference". Procedia Computer Science 178 (2020): 264–73. http://dx.doi.org/10.1016/j.procs.2020.11.028.

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Niemi, Arto, e Jukka Teuhola. "Burrows‐Wheeler post‐transformation with effective clustering and interpolative coding". Software: Practice and Experience 50, n. 9 (29 giugno 2020): 1858–74. http://dx.doi.org/10.1002/spe.2873.

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Zhang, Jesse M., Govinda M. Kamath e David N. Tse. "Valid Post-clustering Differential Analysis for Single-Cell RNA-Seq". Cell Systems 9, n. 4 (ottobre 2019): 383–92. http://dx.doi.org/10.1016/j.cels.2019.07.012.

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İnkaya, Tülin, Sinan Kayalıgil e Nur Evin Özdemirel. "Extracting the Boundaries of Clusters: A Post-Clustering Tool for Spatial Datasets". International Journal of Pattern Recognition and Artificial Intelligence 34, n. 04 (1 agosto 2019): 2050008. http://dx.doi.org/10.1142/s0218001420500081.

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Boundary extraction is a fundamental post-clustering problem. It facilitates interpretability and usability of clustering results. Also, it provides visualization and dataset reduction. However, it has not attracted much attention compared to the clustering problem itself. In this work, we address the boundary extraction of clusters in 2- and 3-dimensional spatial datasets. We propose two algorithms based on Delaunay Triangulation (DT). Numerical experiments show that the proposed algorithms generate the cluster boundaries effectively. Also, they yield significant amounts of dataset reduction.

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Chen, Lin Chih. "Building a Post-Search Academic Search Engine Based on a Serial of Clustering Methods". Applied Mechanics and Materials 284-287 (gennaio 2013): 3051–55. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3051.

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Academic search engines, such as Google Scholar and Scirus, provide a Web-based interface to effectively find relevant scientific articles to researchers. However, current academic search engines are lacking the ability to cluster the search results into a hierarchical tree structure. In this paper, we develop a post-search academic search engine by using a mixed clustering method. In this method, we first adopt a suffix tree clustering and a two-way hash mechanism to generate all meaningful labels. We then develop a divisive hierarchical clustering algorithm to organize the labels into a hierarchical tree. According to the results of experiments, we conclude that using our mixed clustering method to cluster the search results can give significant performance gains than current academic search engines. In this paper, we make two contributions. First, we present a high performance academic search engine based on our mixed clustering method. Second, we develop a divisive hierarchical clustering algorithm to organize all returned search results into a hierarchical tree structure.

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Röhrl, Jennifer M., Rouven Arnold e Karima Djabali. "Nuclear Pore Complexes Cluster in Dysmorphic Nuclei of Normal and Progeria Cells during Replicative Senescence". Cells 10, n. 1 (14 gennaio 2021): 153. http://dx.doi.org/10.3390/cells10010153.

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Hutchinson-Gilford progeria syndrome (HGPS) is a rare premature aging disease caused by a mutation in LMNA. A G608G mutation in exon 11 of LMNA is responsible for most HGPS cases, generating a truncated protein called “progerin”. Progerin is permanently farnesylated and accumulates in HGPS cells, causing multiple cellular defects such as nuclear dysmorphism, a thickened lamina, loss of heterochromatin, premature senescence, and clustering of Nuclear Pore Complexes (NPC). To identify the mechanism of NPC clustering in HGPS cells, we evaluated post-mitotic NPC assembly in control and HGPS cells and found no defects. Next, we examined the occurrence of NPC clustering in control and HGPS cells during replicative senescence. We reported that NPC clustering occurs solely in the dysmorphic nuclei of control and HGPS cells. Hence, NPC clustering occurred at a higher frequency in HGPS cells compared to control cells at early passages; however, in late cultures with similar senescence index, NPCs clustering occurred at a similar rate in both control and HGPS. Our results show that progerin does not disrupt post-mitotic reassembly of NPCs. However, NPCs frequently cluster in dysmorphic nuclei with a high progerin content. Additionally, nuclear envelope defects that arise during replicative senescence cause NPC clustering in senescent cells with dysmorphic nuclei.

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Kim, Hyungtai, Yun-Hee Kim, Seung-Jong Kim e Mun-Taek Choi. "Pathological gait clustering in post-stroke patients using motion capture data". Gait & Posture 94 (maggio 2022): 210–16. http://dx.doi.org/10.1016/j.gaitpost.2022.03.007.

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Meshram, Shubhangi P., Anuradha D. Thakare e Santwana Gudadhe. "Hybrid Swarm Intelligence Method for Post Clustering Content Based Image Retrieval". Procedia Computer Science 79 (2016): 509–15. http://dx.doi.org/10.1016/j.procs.2016.03.065.

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Yamauchi, Futoshi. "School quality, clustering and government subsidy in post-apartheid South Africa". Economics of Education Review 30, n. 1 (febbraio 2011): 146–56. http://dx.doi.org/10.1016/j.econedurev.2010.08.002.

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Still, Evan, e Peter Hosemann. "Alpha Shape Analysis: Extracting Composition, Surface Area, and Volume Post Clustering". Microscopy and Microanalysis 26, S2 (30 luglio 2020): 2080–82. http://dx.doi.org/10.1017/s1431927620020371.

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Nagda, Riddhi, Pratik Shah, Chang Seop Lee, Sooyeon Park e Seong Wook Yang. "Structural Influence on the Post-Clustering Stability of DNA/AgNCs Fluorescence". Nanomaterials 9, n. 5 (28 aprile 2019): 667. http://dx.doi.org/10.3390/nano9050667.

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DNA-encapsulated Silver Nanoclusters (DNA/AgNCs) based sensors have gained increasing attention in past years due to their diverse applications in bioimaging, biosensing, and enzymatic assays. Given the potential of DNA/AgNCs for practical applications, the systematic studies of the fluorescent stability over an extended period is necessary. However, the correlation between nucleic acid properties and the long-term stability of DNA/AgNCs is less known. With locking-to-unlocking sensors, in which the secondary structure of DNA template is standardized, we investigated the correlation between the DNA structure and the fluorescence stability of AgNCs. Post-synthesis of DNA/AgNCs, the fluorescence, and structures of templates were monitored over three weeks. By combining the fluorescence spectroscopy with the in-gel fluorescent assay, we found that AgNCs encapsulated by dimer-structured DNA/AgNCs templates were more stable than those of hairpin-structured DNA/AgNCs templates. While the orange fluorescence from the dimer templates increased over three weeks, the red fluorescence from the hairpin templates was diminished by >80% within two days at room temperature. Further tests revealed that hairpin-encapsulated red-emissive AgNCs is more sensitive to oxidation by atmospheric oxygen compared to dimer encapsulated orange AgNCs. Our observations may provide an important clue in encapsulating photophysically more stable AgNCs by tuning the DNA secondary structures. The proposed strategy here can be essential for pragmatic applications of DNA/AgNCs templates.

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Arbez, Nicolas, Tamara Ratovitski, Elaine Roby, Ekaterine Chighladze, Jacqueline C. Stewart, Mark Ren, Xiaofang Wang, Daniel J. Lavery e Christopher A. Ross. "Post-translational modifications clustering within proteolytic domains decrease mutant huntingtin toxicity". Journal of Biological Chemistry 292, n. 47 (27 settembre 2017): 19238–49. http://dx.doi.org/10.1074/jbc.m117.782300.

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de Groot, Joost C. W., Mark W. E. J. Fiers, Roeland C. H. J. van Ham e Antoine H. P. America. "Post alignment clustering procedure for comparative quantitative proteomics LC-MS Data". PROTEOMICS 8, n. 1 (gennaio 2008): 32–36. http://dx.doi.org/10.1002/pmic.200700707.

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Hidayatur Rohmah. "Collaboration of Clustering Technique and Picture in Teaching Vocabulary". EDUVELOP 3, n. 1 (3 ottobre 2019): 21–26. http://dx.doi.org/10.31605/eduvelop.v3i1.394.

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This research was aimed to know the empirical evidence about the improvement of the studentsâ€™ English vocabulary through Clustering technique and picture as a media at the First Grade Students of Madrasah Muâ€™alliminn Muâ€™allimat Bahrul â€˜Ulum Tambakberas Jombang. The problem of the study was how to improve studentâ€™s English vocabulary through Clustering Technique and Picture as a media. This pre-experimental research is quantitative and the data taken from the pre-test and post-test and test sheet is used as the instrumentation. The result showed that the use of clustering technique and picture as a media in teaching vocabulary mastery increased. It can be seen from the studentsâ€™ score of pre-test is 46.73, meanwhile the mean score of post-test is 73.67. The effectiveness of using this technique and media is implemented from studentsâ€™ scores which are increased after learning vocabulary by using collaboration between clustering technique and picture as a media.

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Abed, Ban Kadhim. "Developing the Writing Skill of the University of Technology' Students by using Clustering Technique". Al-Adab Journal, n. 131 (15 dicembre 2019): 55–70. http://dx.doi.org/10.31973/aj.v1i131.718.

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The difficulties in writing are considered one of the most significant problems that have an effect on non-native English speakers. This study aims at developing the writing skills by using clustering technique to the University of Technology' students, then making a comparison between students' performance in writing in a per and post-test. A pre-test was made to the students to know their level in writing an essay then a course of study in teaching writing by using clustering technique was delivered to the students then a post-test is taken by students. The study aims at showing the influence using clustering technique in students' performance in writing. So the results have shown that there is a great development in students’ performance in writing after their involvement in the course

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Baig, Ahmed S., Omair Haroon e Nasim Sabah. "Price Clustering After the Introduction of Bitcoin Futures". Applied Finance Letters 9 (23 aprile 2020): 36–42. http://dx.doi.org/10.24135/afl.v9i0.200.

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Economic theory suggests that introduction of derivative contracts can improve the informational efficiency of the underlying asset prices (Danthine, 1978). In this study, we examine the impact of the introduction of Bitcoin futures on price clustering in Bitcoin. Our findings suggest that price clustering in Bitcoin meaningfully decreases post the introduction of its futures contracts.

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V, Bindhu, e Ranganathan G. "Hyperspectral Image Processing in Internet of Things model using Clustering Algorithm". June 2021 3, n. 2 (21 giugno 2021): 163–75. http://dx.doi.org/10.36548/jismac.2021.2.008.

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With the advent of technology, several domains have b on Internet of Things (IoT). The hyper spectral sensors present in earth observation system sends hyper spectral images (HSIs) to the cloud for further processing. Artificial intelligence (AI) models are used to analyse data in edge servers, resulting in a faster response time and reduced cost. Hyperspectral images and other high-dimensional image data may be analysed by using a core AI model called subspace clustering. The existing subspace clustering algorithms are easily affected by noise since they are constructed based on a single model. The representation coefficient matrix connectivity and sparsity is hardly balanced. In this paper, connectivity and sparsity factors are considered while proposing the subspace clustering algorithm with post-process strategy. A non-dominated sorting algorithm is used for that selection of close neighbours that are defined as neighbours with high coefficient and common neighbours. Further, pruning of useless, incorrect or reserved connections based on the coefficients between the close and sample neighbours are performed. Lastly, inter and intra subspace connections are reserved by the post-process strategy. In the field of IoT and image recognition, the conventional techniques are compared with the proposed post-processing strategies to verify its effectiveness and universality. The clustering accuracy may be improved in the IoT environment while processing the noise data using the proposed strategy as observed in the experimental results.

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Capobianco-Uriarte, María de las Mercedes, Juan Carlos Gázquez-Abad, Jaime De Pablo-Valenciano e María del Pilar Casado-Belmonte. "INFLUENCE OF THE ECONOMIC CRISIS ON THE IDENTIFICATION OF COUNTRY PROFILES WITHIN THE EUROPEAN TOMATO MARKET". Journal of Business Economics and Management 22, n. 3 (7 maggio 2021): 823–46. http://dx.doi.org/10.3846/jbem.2021.14468.

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The objectives of this work are to determine the profiles of the countries that make up the European tomato consuming market and to observe if the economic-financial crisis (2007/2008) has influenced them. Both Lafay’s economic indicators were applied and country profiles and subprofiles were identified through a multilevel two-stage cluster analysis. The empirical analysis covers the period from 2005 to 2016, separated into two periods, pre-crisis (2005–2010) and post-crisis (2011–2016). Most countries obtained import and export profiles that coincide in both indices, Except in Italy. Only one post-crisis profile change was detected, this being for Greece, from an importer to an exporter. As a result of the initial two-stage clustering analysis (both in the pre-crisis and post-crisis period), three clusters were obtained. At the first level of clustering, Italy is identified with a producer profile and Spain and the Netherlands with an exporter profile. At the second level of clustering of the initial larger group, two clusters were identified, Germany and the United Kingdom with an importing sub-profile, and France and Belgium with an exporting sub-profile. In the transition from the pre-crisis to the post-crisis period, Portugal changed from a producer sub-profile to an exporter sub-profile.

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Bangun, Monica Natalia, Open Darnius e Sutarman Sutarman. "OPTIMIZATION MODEL IN CLUSTERING THE HAZARD ZONE AFTER AN EARTHQUAKE DISASTER". SinkrOn 7, n. 3 (13 agosto 2022): 2089–95. http://dx.doi.org/10.33395/sinkron.v7i3.11598.

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There are a large number of approaches to clustering problems, including optimization-based methods involving mathematical programming models to develop efficient and meaningful clustering schemes. Clustering is one of the data labeling techniques. K-means clustering is a partition clustering algorithm that starts by selecting k representative points as the initial centroid. Each point is then assigned to the nearest centroid based on the selected specific proximity measure. This writing is focused on the grouping of post-earthquake hazard zones based on grouping with regard to certain characteristics which aim to describe the process of partitioning the N-dimensional population into K-sets based on the sample. This research consists of three steps, namely standardization, data clustering using K-means and data interpolation using the K-means clustering algorithm and zoning of 7 variables, namely magnitude, depth, victim died, the victim didn’t die, public facilities were heavily damage, public facilities were slightly damage, and affected areas.

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Saki, Azadeh, Hamed Tabesh, Razieh Yousefi e Sanaz Khalili. "Clustering the Attitudes towards Statistics and Technology among Medical Post Graduate Students". British Journal of Applied Science & Technology 18, n. 4 (10 gennaio 2016): 1–11. http://dx.doi.org/10.9734/bjast/2016/29673.

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Torkzadeh, R., J. B. M. van Waes, V. Cuk e J. F. G. Cobben. "Clustering Technique for Scenario Reduction in Post-Energy Transition Voltage Dips Assessment". Renewable Energy and Power Quality Journal 19 (settembre 2021): 241–45. http://dx.doi.org/10.24084/repqj19.267.

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The Dutch transmission system operator makes multiple scenarios to predict the future developments. These scenarios will help to define the risk factors and constraints in the grid, for which reinforcement planning is necessary. The developed grid after these reinforcements should continue to fulfil the power quality assessment criteria specified in the Dutch grid code. The reduction in system strength due to partial phase out of the conventional generation may have an adverse impact on the PQ, especially the voltage dips. Precise assessment criteria for voltage dips have been stipulated by the Dutch grid code that also need to be met after the energy transition. Evaluating all possible grid future scenarios can provide insight in possible future operating conditions. In practice, due to various combinations of network configurations, loading scenarios and dispatch scenarios, it is not possible to analyze all operating scenarios in detail. This paper presents a method to determine the most important scenarios for voltage dip assessments using a clustering technique. The proposed clustering technique reduces the number of scenarios that are needed to be assessed that makes the whole process doable in practice.

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KIMURA, Shuta, Masanori HASHIMOTO e Takao ONOYE. "A Body Bias Clustering Method for Low Test-Cost Post-Silicon Tuning". IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E95.A, n. 12 (2012): 2292–300. http://dx.doi.org/10.1587/transfun.e95.a.2292.

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Kumara, Banage T. G. S., Incheon Paik, Koswatte R. C. Koswatte e Wuhui Chen. "IMPROVING WEB SERVICE CLUSTERING THROUGH POST FILTERING TO BOOTSTRAP THE SERVICE DISCOVERY". Services Transactions on Services Computing 2, n. 3 (luglio 2014): 1–13. http://dx.doi.org/10.29268/stsc.2014.2.3.1.

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Falkner, Jayson A., Jarret W. Falkner, Anastasia K. Yocum e Philip C. Andrews. "A Spectral Clustering Approach to MS/MS Identification of Post-Translational Modifications". Journal of Proteome Research 7, n. 11 (7 novembre 2008): 4614–22. http://dx.doi.org/10.1021/pr800226w.

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Shibasaki, Koji, Makoto Tominaga e Yasuki Ishizaki. "Hippocampal neuronal maturation triggers post-synaptic clustering of brain temperature-sensor TRPV4". Biochemical and Biophysical Research Communications 458, n. 1 (febbraio 2015): 168–73. http://dx.doi.org/10.1016/j.bbrc.2015.01.087.

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Park, Gunhan, Yunju Baek e Heung-Kyu Lee. "Re-ranking algorithm using post-retrieval clustering for content-based image retrieval". Information Processing & Management 41, n. 2 (marzo 2005): 177–94. http://dx.doi.org/10.1016/j.ipm.2003.08.002.

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Kurkure, Manasee, Anuradha Thakare e Santvana Gudadhe. "Genetic Candidate Group Search Approach for Post Clustering Content based Image Retrieval". International Journal of Computer Applications 132, n. 16 (17 dicembre 2015): 6–9. http://dx.doi.org/10.5120/ijca2015907677.

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Chen, Chun-Hao, Ji-Syuan He, Tzung-Pei Hong e Subbaiya Rammohan Kannan. "Post-Analysis Framework for Mining Actionable Patterns Using Clustering and Genetic Algorithms". IEEE Access 7 (2019): 108101–15. http://dx.doi.org/10.1109/access.2019.2933505.

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Siegler, R. L., J. R. Sherbotie, N. D. Denkers e A. T. Pavia. "Clustering of post-diarrheal (Shiga toxin-mediated) hemolytic uremic syndrome in families". Clinical Nephrology 60, n. 08 (1 agosto 2003): 74–79. http://dx.doi.org/10.5414/cnp60074.

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Reistetter, Timothy, Karl Eschbach, Daniel Jupiter, John Prochaska, Amol Karmarkar e Kenneth Ottenbacher. "Developing Rehabilitation Service Areas: Exploring Geographic Clustering in Post-Acute Care Services". Archives of Physical Medicine and Rehabilitation 97, n. 12 (dicembre 2016): e28. http://dx.doi.org/10.1016/j.apmr.2016.09.076.

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N Sujatha, Latha Narayanan Valli, A Prema, SK Rathiha e V Raja. "Initial centroid selection for K- means clustering algorithm using the statistical method". International Journal of Science and Research Archive 7, n. 2 (30 dicembre 2022): 474–78. http://dx.doi.org/10.30574/ijsra.2022.7.2.0309.

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An iterative process that converges to one of the many local minima is used in practical clustering methods. K-means clustering is one of the most well-liked clustering methods. It is well known that these iterative methods are very susceptible to the initial beginning circumstances. In order to improve K-means clustering's performance, this research suggests a novel method for choosing initial centroids. The suggested approach is evaluated with online access records, and the results demonstrate that better initial starting points and post-processing cluster refinement result in better solutions.

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Risma Rahajeng Lestari e Neny Triana Dewi. "THE EFFECTIVENESS OF USING CLUSTERING TECHNIQUE TOWARD WRITING PROCEDURE TEXT". Jurnal Ilmu Pendidikan Muhammadiyah Kramat Jati 3, n. 1 (1 giugno 2022): 1–9. http://dx.doi.org/10.55943/jipmukjt.v3i1.22.

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This research was conducted to measure the effectiveness of cluster techniques in writing text procedures from students as students of Roudlotun Nasyiin Mojokerto. The researcher uses quasi experimental research for design. This design involves two classes as research subjects, the experimental class and the control class. These classes have similar abilities in English achievement. The researcher gave experimental treatment in treatment class and the researcher gave control treatment in control class. After doing the treatments in each class, the researcher gave post-test. The post-test scores in each class will be compared to measure the impact of doing these treatments. There are two variables in this research, independent variable and dependent variable. Independent variable is clustering technique and dependent variable is writing achievement. This treatment is given during some meeting before taking the data. The research result students’ ability in writing after taught by using clustering technique was very good. In short, clustering technique was an appropriate strategy to write a text, especially procedure text. The writing students’ ability taught by using non- clustering technique was lower than the students were taught by using clustering technique. The result of t-test was 7,153. After got the score, the researcher compared it with t- table (df = n1 + n2 – 2 = 72 ; significance 5% = 0.05). The value of t-table was 1.666. It signed that Ha was accepted and H0 was refused.

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Chen, Shi-Fan, Martin White, Joseph DeRose e Nickolas Kokron. "Cosmological analysis of three-dimensional BOSS galaxy clustering and Planck CMB lensing cross correlations via Lagrangian perturbation theory". Journal of Cosmology and Astroparticle Physics 2022, n. 07 (1 luglio 2022): 041. http://dx.doi.org/10.1088/1475-7516/2022/07/041.

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Abstract We present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.78 and σ 8 = 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ωm = 0.303 ± 0.008, H 0 = 69.21 ± 0.77 and σ 8 = 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of Ωm and H 0 are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The low σ 8 value are driven by cross correlations with CMB lensing in the low redshift bin (z ≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.

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Lorimer, Tom, Jenny Held e Ruedi Stoop. "Clustering: how much bias do we need?" Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 375, n. 2096 (15 maggio 2017): 20160293. http://dx.doi.org/10.1098/rsta.2016.0293.

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Scientific investigations in medicine and beyond increasingly require observations to be described by more features than can be simultaneously visualized. Simply reducing the dimensionality by projections destroys essential relationships in the data. Similarly, traditional clustering algorithms introduce data bias that prevents detection of natural structures expected from generic nonlinear processes. We examine how these problems can best be addressed, where in particular we focus on two recent clustering approaches, Phenograph and Hebbian learning clustering, applied to synthetic and natural data examples. Our results reveal that already for very basic questions, minimizing clustering bias is essential, but that results can benefit further from biased post-processing. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’.

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Heyer, Geoffrey L., Julie A. Young, Sean C. Rose, Kelly A. McNally e Anastasia N. Fischer. "Post-traumatic headaches correlate with migraine symptoms in youth with concussion". Cephalalgia 36, n. 4 (8 giugno 2015): 309–16. http://dx.doi.org/10.1177/0333102415590240.

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Objective The term “post-traumatic migraine” (PTM) has been used to describe post-traumatic headaches (PTHs) that have associated migraine features, but studies of this relationship are lacking. The objective of the present study was to determine whether PTH correlates strongly with migraine symptoms among youth with concussion. Methods Twenty-three symptoms were analyzed from a retrospective cohort of 1953 pediatric patients with concussion. A principal component analysis (PCA) with oblique Promax rotation was conducted to explore underlying symptom relationships in the full cohort and in subcohorts stratified by the presence ( n = 414) or absence ( n = 1526) of premorbid headache. Results The mean patient age was 14.1 years; 63% were male. Headache was the most common postconcussion symptom, acknowledged by 69.4% of patients. When considering the full cohort, the PCA demonstrated clustering of headache with photophobia, phonophobia, nausea, dizziness, and neck pain. Similar clustering was present among patients without premorbid headaches. Repeating the analysis in the patients with preconcussion headaches led to elimination of neck pain from the cluster. Conclusions PTH correlates strongly with other migraine symptoms among youth with concussion, regardless of premorbid headaches. This clustering of migraine symptoms supports the existence of PTM as a distinct clinical entity in some patients.

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Amri, Samsul. "TEACHING HORTATORY EXPOSITION TEXT THROUGH CLUSTERING TECHNIQUE". Wiralodra English Journal 2, n. 2 (1 settembre 2018): 163–75. http://dx.doi.org/10.31943/wej.v2i2.358.

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Having writing problems was faced by students. This research purposed to describe the teaching process how Clustering Technique improves the students' writing skill of hortatory exposition text, and what influenced factors of their writing improvement. This is a Classroom Action Research. The participants of the research were the students of grade XI AB-3 of MA Darul Hikmah Pekanbaru. The data were collected in each cycle from observation checklists, field notes, interviews, and writing tests. Then the researcher found that Clustering Technique enables to improve better the students' writing skill of hortatory exposition text through the process of socializing, reviewing, controlling, monitoring, assisting, motivating, and practicing. Consequently, the students could improve their writing skill which involved the mean score improvement of writing indicators; grammar, vocabulary, mechanics, fluency, and organization. It could be seen from the improvement of the base score mean score (56.32), post-test I (64.23), and post-test II (73.85). Furthermore, the factors that influenced the improvement of their writing skill involved creative thinking, students' motivation, amount of writing practices, students' prior knowledge, and the teacher's role. To sum up, the implementation of Clustering Technique in teaching writing of hortatory exposition text could provide positive results on their writing skill.

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Fernsel, Pascal. "Spatially Coherent Clustering Based on Orthogonal Nonnegative Matrix Factorization". Journal of Imaging 7, n. 10 (28 settembre 2021): 194. http://dx.doi.org/10.3390/jimaging7100194.

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Classical approaches in cluster analysis are typically based on a feature space analysis. However, many applications lead to datasets with additional spatial information and a ground truth with spatially coherent classes, which will not necessarily be reconstructed well by standard clustering methods. Motivated by applications in hyperspectral imaging, we introduce in this work clustering models based on Orthogonal Nonnegative Matrix Factorization (ONMF), which include an additional Total Variation (TV) regularization procedure on the cluster membership matrix to enforce the needed spatial coherence in the clusters. We propose several approaches with different optimization techniques, where the TV regularization is either performed as a subsequent post-processing step or included into the clustering algorithm. Finally, we provide a numerical evaluation of 12 different TV regularized ONMF methods on a hyperspectral dataset obtained from a matrix-assisted laser desorption/ionization imaging measurement, which leads to significantly better clustering results compared to classical clustering models.

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Mulky Haris, Suci Ma'alikul, Nur Qalbi e Herlina Daddi. "THE EFFECTIVENESS OF CLUSTERING TECHNIQUE IN IMPROVING STUDENTS’ WRITING SKILL IN NARRATIVE TEXT AT SMA NEGERI 21 MAKASSAR". English Language Teaching Methodology 2, n. 3 (15 dicembre 2022): 192–98. http://dx.doi.org/10.56983/eltm.v2i3.83.

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This research aims to find out The Effectiveness of Clustering Technique in Improving Students’ Writing Skill In Narrative Text. This research was conducted at SMA Negeri 21 Makassar. The design of this research is Pre-Experimental Design. The population of this study was the first-grade students in academic years 2020/2021 in SMAN 21 Makassar, which was selected by using cluster random sampling technique, while the sample of this study was 30 students. The instrument of this study was a test that used pre-test and post-test.The mean score of the pre-test in content 71,1 was lower than post-test 80,6. From the t-test, the study found that the value of t-test in generic structure pre-test 20,62 was fair than t-table 1.538, and the value of t-test in generic structure post-test 38,71 was greater than t-table 1.538. There was a difference between the students’ writing before and after applying the clustering technique in the class. It shows that the Null Hypothesis (H0) was rejected and the alternative hypothesis (H1) was accepted. The result of the data shows that writing in terms of the generic structure of narrative text through the clustering technique was a fairly effective method to improving students' writing skills in narrative text.

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Silva, Ricardo, João Moura-Pires e Maribel Yasmina Santos. "Spatial Clustering in SOLAP Systems to Enhance Map Visualization". International Journal of Data Warehousing and Mining 8, n. 2 (aprile 2012): 23–43. http://dx.doi.org/10.4018/jdwm.2012040102.

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The emergence of the SOLAP concept supports map visualization for improving data analysis, enhancing the decision making process. However, in this environment, maps can easily become cluttered losing the benefits that triggered the appearance of this concept. In order to overcome this problem, a post-processing model is proposed, which relies on Geovisual Analytics principles. Namely, it takes advantage from the user interaction and the spatial clustering approach in order to reduce the number of elements to be visualized when this number is inadequate to a proper map analysis. Moreover, a novel heuristic to identify the threshold value from which the clusters must be generated was developed. The proposed post-processing model takes into account the query performed, i.e., the number of spatial attributes, the number of spatial dimensions, and the type of spatial objects selected from dimensions. The results obtained so far show: (i) the novel approach to support queries with two spatial attributes from different dimensions allows useful analysis; (ii) the proposed post-processing model is very effective in maintaining a map suitable to the user’s cognitive process; and, (iii) the heuristic proposed provide the user participation in the clustering process, in a user-friendly way.

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Guisado, Daniela, Sayali Talware, Shishir Singh, Stephanie Gold, Moutasem Mansi, Elbek Fozilov, Aaron Etra, Judy Cho e Louis Cohen. "REPOGRAMING OF THE INTESTINAL IMMUNE CELL COMPARTMENT DEFINES THE RESPONSE TO AUTOLOGOUS STEM CELL TRANSPLANTATION IN CROHNS DISEASE". Inflammatory Bowel Diseases 29, Supplement_1 (26 gennaio 2023): S51—S52. http://dx.doi.org/10.1093/ibd/izac247.101.

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Abstract INTRODUCTION For the treatment of refractory Crohn’s disease (CD) autologous stem cell transplant (auto-SCT) is unparalleled in its ability to induce clinical and endoscopic remission.(1, 2) Auto-SCT is unique as a cellular therapy aimed to reset immune pathophysiology to a pre-disease state using hematopoietic stem cells. As such, the study of how the immune system responds to auto-SCT will provide unique insight into CD pathogenesis and treatment. To date, no studies in any cohort have defined the mucosal and peripheral immune response to auto-SCT. Here we report initial studies of high dimensional immune phenotyping of patients with CD during auto-SCT. METHODS Patients with CD were enrolled in a Phase IIa study of auto-SCT (NCT03219359). 14 patients were transplanted (2018-2022). Paired blood and intestinal samples were taken prior to transplant and 6 months post-transplant. Fresh leukocytes were isolated and analyzed by mass cytometry (CyTOF). Supervised clustering of immune cell populations using canonical markers was performed in parallel with unsupervised clustering by FlowSOM.(3) RESULTS After 6 months post-transplant,12/13 patients had an endoscopic response (↓SES-CD by 50%) and 10/13 patients were in endoscopic remission (SES-CD<4). Supervised clustering of major immune cell subsets demonstrated distinct site-specific responses to transplant in myeloid and lymphoid cell populations (Fig 1). Naïve CD4+ and CD8+ T cells universally decrease in number at 6 months post-transplant whereas all other B and T cell populations have discordant changes in the blood and intestine, especially naïve and transitional CD27- B cell populations which significantly increase in blood and decrease in the intestine. CD14+ populations are universally increased in number post-transplant with a specific increase in CD14+ CD206+ macrophages in the intestine. Unsupervised clustering of blood and intestinal immune cells resolve 100 cell clusters that correlate with canonical immune cell markers (Fig 2). Unsupervised analysis further highlights a significant increase in multiple intestinal CD14+CD206+ immune cell populations reflecting newly arrived and/or differentiating and mature monocyte derived macrophages. Principal component and hierarchical clustering analyses of immune cell clusters suggest a reprograming of the intestinal immune compartment post-transplant whereas changes in circulating immune cells populations fail to separate the pre and post-transplant states. CONCLUSION We demonstrate for the first time differences in the intestinal and peripheral immune response to auto-SCT. These studies highlight the changes in intestinal immune cell networks that define the transplant response perhaps through CD14+ cells.

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Camacho-Hernández, Diego A., Victor E. Nieto-Caballero, José E. León-Burguete e Julio A. Freyre-González. "Partition Quantitative Assessment (PQA): A Quantitative Methodology to Assess the Embedded Noise in Clustered Omics and Systems Biology Data". Applied Sciences 11, n. 13 (28 giugno 2021): 5999. http://dx.doi.org/10.3390/app11135999.

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Identifying groups that share common features among datasets through clustering analysis is a typical problem in many fields of science, particularly in post-omics and systems biology research. In respect of this, quantifying how a measure can cluster or organize intrinsic groups is important since currently there is no statistical evaluation of how ordered is, or how much noise is embedded in the resulting clustered vector. Much of the literature focuses on how well the clustering algorithm orders the data, with several measures regarding external and internal statistical validation; but no score has been developed to quantify statistically the noise in an arranged vector posterior to a clustering algorithm, i.e., how much of the clustering is due to randomness. Here, we present a quantitative methodology, based on autocorrelation, in order to assess this problem.

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Hamzah, Almed, e Ahmad Fathan Hidayatullah. "Clustering on Twitter: case study Twitter account of higher education institution in Indonesia". MATEC Web of Conferences 154 (2018): 03010. http://dx.doi.org/10.1051/matecconf/201815403010.

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Recently, higher education institutions have been using Twitter as one of tools to enhance their communication network. This paper aims to cluster Twitter data retrieved from the official Twitter account of higher education institutions in Indonesia. We expect to obtain a valuable information from the tweet posted. Furthermore, we use Twitter’s hashtag as a basis of clustering. We collect data from n=10 institutions that have an official account on Twitter. The Affinity Propagation algorithm was employed to perform the clustering task. According to the clustering results, we conclude that higher education in Indonesia mostly utilize Twitter to post general information, news, agenda, announcement, information to the new students, and achievement.

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