Relevant bibliographies by topics / Cluster analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Cluster analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Cluster analysis"

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Ahamad, Mohammed Gulam, Mohammed Faisal Ahmed, and Mohammed Yousuf Uddin. "Clustering as Data Mining Technique in Risk Factors Analysis of Diabetes, Hypertension and Obesity." European Journal of Engineering and Technology Research 1, no. 6 (2018): 88–93. http://dx.doi.org/10.24018/ejeng.2016.1.6.202.

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This investigation explores data mining using open source software WEKA in health care application. The cluster analysis technique is utilized to study the effects of diabetes, obesity and hypertension from the database obtained from Virginia school of Medicine. The simple k-means cluster techniques are adopted to form ten clusters which are clearly discernible to distinguish the differences among the risk factors such as diabetes, obesity and hypertension. Cluster formation was tried by trial and error method and also kept the SSE as low as possible. The SSE is low when numbers of clusters ar
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D. Shashibhushan, C. V. Sameer Kumar, and Ravi Kiran Reddy Kondi. "Genetic diversity analysis of Pearl Millet germplasm by cluster analysis." emergent Life Sciences Research 08, no. 01 (2022): 70–74. http://dx.doi.org/10.31783/elsr.2022.817074.

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There are 40 genotypes of pearl millet that were gathered from ICRISAT in Hyderabad for the study. The experiment was performed in triplicate using Randomized Block Design. With an average D2 value of 398.08, the experimental material was divided into seven clusters, indicating the presence of diversity across the lines for the attributes being studied. Among different clusters the maximum cluster lines i.e., ten lines were observed in cluster V followed by cluster IV, cluster III, cluster I, cluster II, cluster VII, and cluster VI. Cluster V has the greatest intra cluster distance, followed b
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Klyuchko, O. M. "CLUSTER ANALYSIS IN BIOTECHNOLOGY." Biotechnologia Acta 10, no. 5 (2017): 5–18. http://dx.doi.org/10.15407/biotech10.05.005.

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KUMAWAT, ANAND. "Genetic divergence analysis of soybean (Glycine Max L.) genotypes using mahalanobis multivariate analysis." Annals of Plant and Soil Research 26, no. 1 (2024): 172–74. http://dx.doi.org/10.47815/apsr.2024.10348.

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Wilk's criterion was used to group the 25 genotypes into three different clusters based on the D2 values. Cluster III was the biggest with 11 genotypes, followed by cluster II with 8 genotypes and cluster I with 6 genotypes. Cluster mean was the highest for days to maturity in cluster II (92.96) and lowest for number of primary branches/plant in cluster III (3.45). Using cluster means genetic diversity analysis reveals genetic backgrounds and interactions of germplasm and manages crop primary pools. The highest inter-cluster distance was observed between cluster II and I, followed by cluster I
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Godara, Poonam, Shrawan Kumar, and Darvinder Kumar. "Evaluation of Genetic Variation in Indian mustard (Brassica Juncea L Czern and Coss) Using Multivariate Techniques." Journal of Agriculture Research and Technology 47, no. 03 (2022): 344–48. http://dx.doi.org/10.56228/jart.2022.47315.

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A set of 310 lines of Indian mustard (Brassica juncea L Czern and Coss) were analysed for cluster and principal component analysis (PCA). PCA identified four principal components which explained 65.13% of total variability among the 310 genotypes. Hierarchical cluster analysis grouped 310 genotypes into 3 clusters. Cluster1 included maximum number of 155 genotypes and clusters 3 had the lowest number of 43 genotypes. The grouping pattern of genotypes obtained by cluster analysis and PCA plots was almost similar.
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Zhang, Xiaoli, Qiang Liu, Shengyang Niu, et al. "Varietal Differences Among the Fruit Quality Characteristic of 15 Spine Grapes (Vitis davidii Foëx)." HortScience 57, no. 10 (2022): 1282–88. http://dx.doi.org/10.21273/hortsci16702-22.

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Spine grape (Vitis davidii Foëx), an important wild grape species in South China, has gained attention because of its health-promoting effects and use in the wine industry. Fruit quality plays an important role in determining the quality of wine; however, a suitable evaluation system to monitor its fruit quality has not been established. The fruit quality characteristics (phenolics and aromas) of 15 spine grapes grown in China were evaluated using a combination of principal component and cluster analyses. The total sugar, organic acid, and phenolic content ranged from 81.80 to 154.89 mg·g−1, 8
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Frontera, Jennifer A., Lorna E. Thorpe, Naomi M. Simon, et al. "Post-acute sequelae of COVID-19 symptom phenotypes and therapeutic strategies: A prospective, observational study." PLOS ONE 17, no. 9 (2022): e0275274. http://dx.doi.org/10.1371/journal.pone.0275274.

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Background Post-acute sequelae of COVID-19 (PASC) includes a heterogeneous group of patients with variable symptomatology, who may respond to different therapeutic interventions. Identifying phenotypes of PASC and therapeutic strategies for different subgroups would be a major step forward in management. Methods In a prospective cohort study of patients hospitalized with COVID-19, 12-month symptoms and quantitative outcome metrics were collected. Unsupervised hierarchical cluster analyses were performed to identify patients with: (1) similar symptoms lasting ≥4 weeks after acute SARS-CoV-2 inf
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Kundu, Anirban, Guanxiong Xu, and Chunlin Ji. "Analysis on Cloud Classification using Accessibility." International Journal of Cloud Applications and Computing 4, no. 3 (2014): 44–53. http://dx.doi.org/10.4018/ijcac.2014070103.

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In this paper, Cloud classification has been demonstrated using accessibility factor of distinct Cloud clusters. Group and non-group Cloud structures have been classified using its direction of scope of activities. Each type of Cloud is further divided into different clusters based on its unique status, such as reachable cluster, non-reachable cluster, basin cluster, momentary cluster, and initiation cluster. Set theory has been applied to realize our proposed Cloud system.
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Talekar, S. C., M. Vani Praveena, and R. G. Satish. "Genetic diversity using principal component analysis and hierarchical cluster analysis in rice." INTERNATIONAL JOURNAL OF PLANT SCIENCES 17, no. 2 (2022): 191–96. http://dx.doi.org/10.15740/has/ijps/17.2/191-196.

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A set of 100 germplasm lines with four checks viz., BPT-5204, PSB-68, Siri1253 and MGD-101 were evaluated in augmented block design during Kharif 2020. The observations were documented for 5 quantitative traits viz., days to 50% flowering, panicle length, number of panicles per square meter, 1000 grain weight and grain yield by principal component analysis and cluster analysis to determine the relationship and genetic divergence among the individuals. The cumulative variance of 55.60% was explained by 1st two principal components (PC1 and PC2) with eigen values greater than 1. Component 1 with
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Al Jauhar, Hafizh Syihabuddin, Solimun Solimun, and Rahma Fitriani. "Integration of DBSCAN Cluster Analysis with Multigroup Moderation Path Analysis." CAUCHY: Jurnal Matematika Murni dan Aplikasi 10, no. 1 (2025): 72–81. https://doi.org/10.18860/cauchy.v10i1.29847.

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This study examines the application of integration between DBSCAN cluster analysis and multigroup moderation path analysis to analyse patterns of waste management behaviour in Batu City. DBSCAN was used to cluster the data based on density, resulting in two main clusters as well as some noise data. The first cluster consisted of 189 respondents, while the second cluster included 196 respondents, with the remaining 10 data identified as noise. The DBSCAN clustering results showed a silhouette index of 0.664, indicating good clustering quality in terms of compactness and separation between clust
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Dissertations / Theses on the topic "Cluster analysis"

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Kozovska, Kornelia <1981&gt. "Business Clusters in Eastern Europe: Policy Analysis and Cluster Performance." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1611/2/Tesi_Kornelia_Kozovska.pdf.

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Clusters have increasingly become an essential part of policy discourses at all levels, EU, national, regional, dealing with regional development, competitiveness, innovation, entrepreneurship, SMEs. These impressive efforts in promoting the concept of clusters on the policy-making arena have been accompanied by much less academic and scientific research work investigating the actual economic performance of firms in clusters, the design and execution of cluster policies and going beyond singular case studies to a more methodologically integrated and comparative approach to the study of cluster
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Kozovska, Kornelia <1981&gt. "Business Clusters in Eastern Europe: Policy Analysis and Cluster Performance." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1611/.

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Clusters have increasingly become an essential part of policy discourses at all levels, EU, national, regional, dealing with regional development, competitiveness, innovation, entrepreneurship, SMEs. These impressive efforts in promoting the concept of clusters on the policy-making arena have been accompanied by much less academic and scientific research work investigating the actual economic performance of firms in clusters, the design and execution of cluster policies and going beyond singular case studies to a more methodologically integrated and comparative approach to the study of cluster
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Pavlou, M. "Analysis of clustered data when the cluster size is informative." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1357842/.

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Clustered data arise in many scenarios. We may wish to fit a marginal regression model relating outcome measurements to covariates for cluster members. Often the cluster size, the number of members, varies. Informative cluster size (ICS) has been defined to arise when the outcome depends on the cluster size conditional on covariates. If the clusters are considered complete then the population of all cluster members and the population of typical cluster members have been proposed as suitable targets for inference, which will differ between these populations under ICS. However if the variation i
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Ngai, Wang-kay, and 倪宏基. "Cluster analysis on uncertain data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B4218261X.

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Dufour, Alyssa Beth. "Cluster analysis of longitudinal trajectories." Thesis, Boston University, 2013. https://hdl.handle.net/2144/12751.

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Thesis (Ph.D.)--Boston University<br>Cluster analysis is widely used in many disciplines including biology, psychology, archaeology, geography, and marketing. Methods have been developed to extend cluster analysis to longitudinal data, clustering subject trajectories rather than single time points. Here, I examine 2 methods of longitudinal cluster analysis: k-means and model-based (implemented using FlexMix in R) cluster analysis. I compare these two methods based on the Correct Classification Rate, the ability of the method to correctly classify subject trajectories into groups, using a simul
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Ngai, Wang-kay. "Cluster analysis on uncertain data." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B4218261X.

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Takahashi, Atsushi. "Hierarchical Cluster Analysis of Dense GNSS Data and Interpretation of Cluster Characteristics." Kyoto University, 2019. http://hdl.handle.net/2433/244510.

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Popescu, Bogdan. "MASSCLEAN - MASSive CLuster Evolution and ANalysis Package - A New Tool for Stellar Clusters." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1276526207.

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Cuciti, Virginia <1989&gt. "Cluster-scale radio emission: analysis of a mass-selected sample of galaxy clusters." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amsdottorato.unibo.it/8540/1/Tesi_PhD.pdf.

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Radio halos are Mpc scale diffuse sources located at the center of a fraction of galaxy clusters. In the current theoretical picture, they form via the re-acceleration of electrons in the ICM by means of turbulence, injected during cluster mergers. This scenario allows basic predictions on the formation history of radio halos that can only be tested by analysing large samples of galaxy clusters with adequate radio and X-ray data. The main goal of this Thesis is to study the first complete large sample of mass-selected galaxy clusters to obtain solid statistical constraints on the connectio
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Bozkirlioglu, Ali. "Cluster Potential In Industrial Sectors Of Samsun: Kutlukent Furniture Cluster Study." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605603/index.pdf.

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The present study investigated whether cluster potentials could be identified in the geographical area within the boundaries of Samsun province, and if identified, how such a potential could be promoted through corresponding support measures. Development of policy recommendations for promotion of identified cluster potential was the principal goal of the study. The course of the study was characterized by a cluster-based policy-making process in the policy environment, i.e. Samsun province. The process includes a descriptive part, i.e. cluster analysis, and a prescriptive part, i.e. determinin
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Books on the topic "Cluster analysis"

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Byrne, David, and Emma Uprichard. Cluster Analysis. SAGE Publications Ltd, 2012. http://dx.doi.org/10.4135/9781446261033.

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Everitt, Brian S., Sabine Landau, Morven Leese, and Daniel Stahl. Cluster Analysis. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9780470977811.

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Social Science Research Council (Great Britain), ed. Cluster analysis. 2nd ed. Published on behalf of the Social Science Research Council by Gower, 1986.

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Sabine, Landau, and Leese Morven, eds. Cluster analysis. 4th ed. Arnold, 2001.

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library, Wiley online, ed. Cluster Analysis. 5th ed. Wiley, 2011.

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Everitt, Brian. Cluster analysis. 3rd ed. E. Arnold, 1993.

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Murtagh, Fionn. Handbook of cluster analysis. Edited by Meilă Marina 1962 editor. Taylor & Francis, 2016.

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Andrew, Lawson, and Denison David G. T, eds. Spatial cluster modelling. Chapman & Hall/CRC, 2002.

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Scitovski, Rudolf, Kristian Sabo, Francisco Martínez-Álvarez, and Šime Ungar. Cluster Analysis and Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74552-3.

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D, Hovee Eric, Oregon Forest Resources Institute, and E.D. Hovee & Company., eds. Oregon forest cluster analysis. E.D. Hovee & Company, 2005.

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Book chapters on the topic "Cluster analysis"

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Tay, Dennis. "Cluster analysis." In Data Analytics for Discourse Analysis with Python. Routledge, 2024. http://dx.doi.org/10.4324/9781003360292-3.

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Backhaus, Klaus, Bernd Erichson, Sonja Gensler, Rolf Weiber, and Thomas Weiber. "Cluster Analysis." In Multivariate Analysis. Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-40411-6_8.

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Backhaus, Klaus, Bernd Erichson, Sonja Gensler, Rolf Weiber, and Thomas Weiber. "Cluster Analysis." In Multivariate Analysis. Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-32589-3_8.

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Sarstedt, Marko, and Erik Mooi. "Cluster Analysis." In Springer Texts in Business and Economics. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-53965-7_9.

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Gatignon, Hubert. "Cluster Analysis." In Statistical Analysis of Management Data. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-8594-0_12.

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Cleff, Thomas. "Cluster Analysis." In Applied Statistics and Multivariate Data Analysis for Business and Economics. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17767-6_12.

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Baragona, Roberto, Francesco Battaglia, and Irene Poli. "Cluster Analysis." In Evolutionary Statistical Procedures. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16218-3_7.

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Filzmoser, Peter, Karel Hron, and Matthias Templ. "Cluster Analysis." In Springer Series in Statistics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96422-5_6.

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Olson, David L. "Cluster Analysis." In Computational Risk Management. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3340-7_6.

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Härdle, Wolfgang Karl, and Zdeněk Hlávka. "Cluster Analysis." In Multivariate Statistics. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-36005-3_13.

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Conference papers on the topic "Cluster analysis"

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Mor, Omri, George Bosilca, and Marc Snir. "Holistic Performance Analysis for Asynchronous Many-Task Runtimes." In 2024 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2024. http://dx.doi.org/10.1109/cluster59578.2024.00015.

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Martin, M. Z., S. R. Desai, C. S. Feigerle, and J. C. Miller. "Laser-Induced Chemistry within Clusters." In Laser Applications to Chemical and Environmental Analysis. Optica Publishing Group, 1996. http://dx.doi.org/10.1364/lacea.1996.lfa.6.

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Clusters comprise an interesting environment for the study of chemical reactions. Binary cluster complexes can be produced which combine a variety of potential reactant partners in various proportions in an intimate, yet controlled arrangement. Molecules or ions within such a cluster (i.e. solvated) have properties which are intermediate between those of isolated species and of species in solution or in bulk. Furthermore as the cluster size increases their properties may smoothly change until the condensed-phase regime is reached. But, since clusters are generated and interrogated in the gas p
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Gudipaty, Tarun, Luthur S. L. Cheung, Linan Jiang, and Yitshak Zohar. "Cluster Formation and Growth in Flow of Dilute Particle Suspension in Microchannels." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59602.

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Microchannels are susceptible to blockage by solid particles. The lifetime of microfluidic devices depends on their ability to maintain flow without interruption, while certain applications require microdevices for transport of liquids containing particles. In this work, the phenomenon of interest is the formation and growth of clusters in the flow of a dilute suspension of hard spheres. Based on the present experiments, aggregation of clusters was observed for particle-laden flow in a microchannel with particle void fraction as low as 0.001 and particle diameter to channel height ratio as low
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Steadman, J., E. W. Fournier, and J. A. Syage. "Detection and Differentiation of Neutral and Ionic Reaction Mechanisms in Molecular Clusters." In Laser Applications to Chemical Analysis. Optica Publishing Group, 1990. http://dx.doi.org/10.1364/laca.1990.pd4.

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A longstanding goal in the chemical analysis of reaction mechanisms is understanding the role of the solvent. We have been involved in work that addresses this issue on a single molecule basis by studying reactions in molecular clusters.1–3 In this report we describe a means for detecting and measuring rapid intermolecular cluster chemistry using mass-selective picosecond resonance-enhanced multiphoton ionization (REMPI). Molecular beam mass spectrometry offers a powerful means for identifying a variety of product species and distinguishing precursor cluster size. However, such investigations
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Popchev, I., and V. Peneva. "CLUSTER-a package for cluster analysis." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1988. http://dx.doi.org/10.1109/iembs.1988.95330.

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Das, Sunanda, Shreya Chaudhuri, and Asit K. Das. "Cluster analysis for overlapping clusters using genetic algorithm." In 2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN). IEEE, 2016. http://dx.doi.org/10.1109/icrcicn.2016.7813542.

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Kaur, Sandy, and Eun Kyung Lee. "Diagnostic Analysis: Directional Relation Graph." In 2019 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2019. http://dx.doi.org/10.1109/cluster.2019.8891032.

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Laros, James H., Lee Ward, Ruth Klundt, Sue Kelly, James L. Tomkins, and Brian R. Kellogg. "Red storm IO performance analysis." In 2007 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2007. http://dx.doi.org/10.1109/clustr.2007.4629216.

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Duplyakin, Dmitry, Jed Brown, and Robert Ricci. "Active Learning in Performance Analysis." In 2016 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2016. http://dx.doi.org/10.1109/cluster.2016.63.

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Brunst, Nagel, and Malony. "A distributed performance analysis architecture for clusters." In Proceedings IEEE International Conference on Cluster Computing CLUSTR-03. IEEE, 2003. http://dx.doi.org/10.1109/clustr.2003.1253301.

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Reports on the topic "Cluster analysis"

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Kryzhanivs'kyi, Evstakhii, Liliana Horal, Iryna Perevozova, Vira Shyiko, Nataliia Mykytiuk, and Maria Berlous. Fuzzy cluster analysis of indicators for assessing the potential of recreational forest use. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4470.

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Cluster analysis of the efficiency of the recreational forest use of the region by separate components of the recreational forest use potential is provided in the article. The main stages of the cluster analysis of the recreational forest use level based on the predetermined components were determined. Among the agglomerative methods of cluster analysis, intended for grouping and combining the objects of study, it is common to distinguish the three most common types: the hierarchical method or the method of tree clustering; the K-means Clustering Method and the two-step aggregation method. For
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Choudhary, Akok. Cluster-Based Repositories and Analysis. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada420002.

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Monteiro, Joana, Beatriz Kury, and Angela Da Rocha. The Role of Flagship Firms, External Actors and Support Institutions in the Emergence of Successful Export Activities in Brazil: Two Industrial Cluster Studies. Inter-American Development Bank, 2009. http://dx.doi.org/10.18235/0011331.

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This paper examines the process by which firms in a cluster start to export based on systemic interactions and the process of diffusion of exporting as a business strategy within the cluster. Two Brazilian manufacturing industries are studied, and within each one a geographic cluster was identified as the origin of dynamic export growth. Players in each industrial cluster, as well as other significant players, were interviewed or identified using secondary sources, and extensive secondary data research was undertaken to study clusters' historical development. Detailed analysis and a comparison
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Wachtel, Amanda, Darryl Melander, and Olga Hart. ReNCAT: The Resilient Node Cluster Analysis Tool. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1880920.

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Weijters, Bert. Cluster Analysis in R: From Theory to Practice. Instats Inc., 2023. http://dx.doi.org/10.61700/3xjho79mx2fc0706.

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This Cluster Analysis in R workshop, led by professor Bert Weijters from Ghent University, provides participants with a comprehensive understanding of the theory and practice of cluster analysis, a crucial tool in academic research for identifying patterns within datasets, including datasets with large numbers of cases and/or variables. This hands-on workshop covers topics from a very brief introduction to RStudio and cluster analysis, to mastering different clustering techniques, and provides practical exercises on simulated and real-world datasets, equipping participants with valuable skills
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Anderson, Sandra. Eutamias minimus and E. amoenus : morphological cluster analysis. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.2262.

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Leland, Robert W. Dual mode use requirements analysis for the institutional cluster. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/918226.

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Kumar, Prabhat, Melvin Felton, David Ligon, Sandra Collier, and Deryck James. Machine-Learning Groundwork and Cluster Analysis for Vortex Detection. DEVCOM Army Research Laboratory, 2022. http://dx.doi.org/10.21236/ad1165710.

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Hair. L52003 Application of the Crack Layer Theory for Understanding and Modeling of SCC in High Pressure. Pipeline Research Council International, Inc. (PRCI), 2003. http://dx.doi.org/10.55274/r0010893.

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A stochastic features of SCC colony, such as corrosion pit distribution, SC crack initiation from the pits and SC crack aspect ratio, SC crack cluster formation, SC cluster interaction and instability, are observed and characterized. A concept of a single crack equivalent to a cluster of cracks is introduced to simplify computational work on clusters evolution and instability. Various criteria of equivalence for different stages of clusters evolution are discussed. An accelerated test with a number of accelerating factors has been designed and performed for simulation of individual SC crack gr
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Raykov, Tenko. Latent Class Analysis and Mixture Modeling. Instats Inc., 2023. http://dx.doi.org/10.61700/tkd5fah8evykd469.

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Latent class analysis (LCA) and mixture models (MM) are an applied statistical method for examining heterogeneity in studied populations. The method can be used to evaluate whether a studied population consists of an initially unknown number of several subpopulations (latent classes, types, clusters) that differ in important ways. This workshop introduces participants to the general field of classification (clustering), using LCA as a model-based version of cluster analysis and moving on to more general mixture modeling with latent variables. Hands-on examples with best practices for analysis
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