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Academic literature on the topic 'Cluster'

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Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Cluster"

1

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 (July 27, 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 are more. Less than ten clusters formation unable to yield distinguishable information. In this work each cluster is revealing quit important information about the diabetes, obesity, hypertension and their interrelation. Cluster 0: Diabetes ? Obesity ? Hypertension = Healthy patient, Cluster 1: Diabetes ? Obesity ? Hypertension = Healthy patient, Cluster2: Diabetes ? Obesity ? Hypertension = Obesity, Cluster3: Diabetes ? Obesity ? Hypertension = Patients with Obesity and Hypertension, Cluster4: Boarder line Diabetes ? Obesity ? Hypertension = Sever obesity, Cluster5: Obesity ? Hyper tension ? Diabetes = Hypertension, Cluster6: Border line obese ? Border line hypertension ? Diabetes = No serious complications, Cluster 7: Obesity ? Hypertension ? Diabetes= Healthy patients, Cluster 8: Obesity ? Hypertension ? Diabetes= Healthy patients, and Cluster 9: Diabetes ? Hyper tension ? Obesity = High risk unhealthy patients.
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2

Tri Gustiane, Indri, Martanto Martanto, and Tati Suprapti. "CLUSTERING HASIL CEK DARAH DIABETES LANSIA MENGGUNAKAN METODE K-MEANS DI POSBINDU KP. LEBAKJERO DESA CIHERANG." JATI (Jurnal Mahasiswa Teknik Informatika) 8, no. 2 (April 24, 2024): 2125–29. http://dx.doi.org/10.36040/jati.v8i2.9281.

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Penelitian ini bertujuan untuk menganalisis hasil cek darah lansia yang menderita diabetes menggunakan metode K-Means. Diabetes adalah penyakit metabolic yang ditandai dengan tingginya kadar gula darah (hiperglikemia) yang disebabkan oleh kekurangan insulin atau tidak efektif insulin dalam mengatur metabolisme glukosa. Selain itu terdapat faktor-faktor lain menjadi penyebab terjadinya diabetes diantaranya seperti faktor keturunan, berat badan, usia, tekanan darah dan sebagainya. Diabetes penyakit kronis yang umumnya terjadi pada lansia dan membutuhkan pemantauan berkala untuk mengelola kondisi mereka. Dengan metode K-Means untuk mengelompokan lansia ke dalam kategori yang berbeda berdasarkan karakteristik darah mereka. Metode K-Means Clustering merupakan metode yang digunakan dalam data mining yang cara kerjanya mencari dan mengelompokan data yang mempunyai kemiripan karakteristik antara data satu dengan data lain yang telah diperol eh data yang memiliki kesamaan bukan data yang sama tetapi memiliki karakteristik yang sama, Dengan menerapkan metode K-Means Clustering dapat membantu pihak Posbindu Kp.Lebakjero Desa Ciherang. Penelitian ini akan di cluster menjadi Lansia yang memiliki penyakit Diabetes paling tinggi di Posbindu Kp.Lebakjero Desa Ciherang. Dalam Cluster tersebut atribut yang dipakai adalah Nama, Jenis Kelamin, Usia, dan Hasil Cek Darah. Hasil analisis dapat membantu petugas kesehatan dalam merancang intervensi yang lebih spesifik dan efektif untuk mengelola diabetes pada populasi lansia. Hasil penelitian K-Means Clustering dibantu hasil nilai DBI dengan -0.597, menjadi 6 cluster dimana hasil cluster0 57, cluster1 24, cluster2 30, cluster3 23, cluster4 44, cluster5 25 dan hasil paling optimal di cluster0 yaitu 57. Cluster0 dengan 57 lansia dimana hasil cluster adalah kp.lebakjero mempunyai lansia paling banyak dan mempunyai diabetes paling tinggi. Selain itu, penelitian ini juga untuk mencapai sesuatu hasil yang akurat terhadap data yang di hasilkan di Posbindu Kp.Lebakjero Desa Ciherang.
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3

Frontera, Jennifer A., Lorna E. Thorpe, Naomi M. Simon, Adam de Havenon, Shadi Yaghi, Sakinah B. Sabadia, Dixon Yang, et al. "Post-acute sequelae of COVID-19 symptom phenotypes and therapeutic strategies: A prospective, observational study." PLOS ONE 17, no. 9 (September 29, 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 infection, and (2) similar therapeutic interventions. Logistic regression analyses were used to evaluate the association of these symptom and therapy clusters with quantitative 12-month outcome metrics (modified Rankin Scale, Barthel Index, NIH NeuroQoL). Results Among 242 patients, 122 (50%) reported ≥1 PASC symptom (median 3, IQR 1–5) lasting a median of 12-months (range 1–15) post-COVID diagnosis. Cluster analysis generated three symptom groups: Cluster1 had few symptoms (most commonly headache); Cluster2 had many symptoms including high levels of anxiety and depression; and Cluster3 primarily included shortness of breath, headache and cognitive symptoms. Cluster1 received few therapeutic interventions (OR 2.6, 95% CI 1.1–5.9), Cluster2 received several interventions, including antidepressants, anti-anxiety medications and psychological therapy (OR 15.7, 95% CI 4.1–59.7) and Cluster3 primarily received physical and occupational therapy (OR 3.1, 95%CI 1.3–7.1). The most severely affected patients (Symptom Cluster 2) had higher rates of disability (worse modified Rankin scores), worse NeuroQoL measures of anxiety, depression, fatigue and sleep disorder, and a higher number of stressors (all P<0.05). 100% of those who received a treatment strategy that included psychiatric therapies reported symptom improvement, compared to 97% who received primarily physical/occupational therapy, and 83% who received few interventions (P = 0.042). Conclusions We identified three clinically relevant PASC symptom-based phenotypes, which received different therapeutic interventions with varying response rates. These data may be helpful in tailoring individual treatment programs.
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4

Akter, F., MZ Islam, A. Akter, SK Debsharma, A. Shama, and M. Khatun. "Genetic Diversity of Bacterial Blight Resistant Rice (Oryza sativa L.) Genotypes from INGER." Bangladesh Rice Journal 23, no. 2 (July 17, 2020): 59–64. http://dx.doi.org/10.3329/brj.v23i2.48248.

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Genetic diversity of 65 rice genotypes was studied from IRBBN (International Rice Bacterial Blight Nursery) of INGER (International Network for Genetic Evaluation of Rice) materials through Mahalanobis D2 statistic for grain yield and yield contributing characters. The genotypes were grouped into five clusters. The inter-cluster distances were higher than intra-cluster distances indicating wider genetic diversity among the genotypes of different clusters. The intra-cluster distances were lower in all the cases reflecting homogeneity of the genotypes within the clusters. The cluster III contained the highest number of genotypes (23) and the clusterv contained the lowest (8). The highest intra-cluster distance was noticed for the cluster I and lowest for cluster III. The highest inter-cluster distance was observed between cluster I and V, followed by cluster IV and V, cluster II andV and the lowest between cluster I and IV. Regarding inter-cluster distance, the genotypes of cluster V showed high genetic distance from all other clusters. The genotypes from cluster V could be hybridized with the genotypes of other clusters for producing transgressive segregants. Based on canonical vector analysis, panicle number per plant had maximum contribution towards genetic divergence. The highest cluster means for yield, grain/panicle and spikelet fertility were obtained from cluster V. The highest means for 1000 grain weight, second higher yield and the lowest growth duration were found in cluster II, while the lowest mean value for yield and 1000 grain weight and higher mean value for growth duration were found in cluster IV. The crosses between the genotypes/parents of cluster V and cluster II, cluster V and cluster I would exhibit high heterosis as well as higher level of yield potential. Therefore, more emphasis should be given for selection of the genotypes from clusters II and V for future breeding programme. Bangladesh Rice j. 2019, 23(2): 59-64
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5

Altomare, Michele, Andrea Chierici, Francesco Virdis, Andrea Spota, Stefano Piero Bernardo Cioffi, Shir Sara Bekhor, Luca Del Prete, et al. "Centralization of Major Trauma Influences Liver Availability for Transplantation in Northern Italy: Lesson Learned from COVID-19 Pandemic." Journal of Clinical Medicine 11, no. 13 (June 24, 2022): 3658. http://dx.doi.org/10.3390/jcm11133658.

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Background: During the COVID-19 pandemic, the centralization of patients allowed trauma and transplants referral centers to continue their routine activity, ensuring the best access to health care. This study aims to analyze how the centralization of trauma is linked with liver allocation in Northern Italy. Methods: Cluster analysis was performed to generate patient phenotype according to trauma-related variables. Comparison between clusters was performed to evaluate differences in damage control strategy procedures (DCS) performed and the 30-day graft dysfunction. Results: During the pandemic period, the centralization of major trauma has deeply impaired the liver procurement and allocation between the transplant centers in the metropolitan area of Milan (Niguarda: 22 liver procurement; other transplant centers: 2 organ procurement). Two clusters were identified the in Niguarda’s series: cluster 1 is represented by 17 (27.4%) trauma donors, of which 13 (76.5%) were treated with DCS procedures, and 4 (23.5%) did not; cluster 2 is represented by 45 trauma donors (72.6%), of which 22 (48.8%) underwent DCS procedures. A significant difference was found in the number of DCS procedures performed between clusters (3.18 ± 2.255 vs. 1.11 ± 1.05, p = 0.0001). Comparative analysis did not significantly differ in the number of transplanted livers (cluster1/cluster2 94.1%/95.6% p = 0.84) and the 30-day graft dysfunction rate (cluster1/cluster2 0.0%/4.8% p = 0.34). Conclusions: The high level of care guaranteed by first-level trauma centers could reduce the loss of organs suitable for donation, maintaining the good outcomes of transplanted ones, even in case of multiple organ injuries. The pandemic period underlined that the centralization of major trauma impairs the liver allocation between transplant centers.
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6

Botet, R., and R. Jullien. "Intrinsic anisotropy of clusters in cluster-cluster aggregation." Journal of Physics A: Mathematical and General 19, no. 15 (October 21, 1986): L907—L912. http://dx.doi.org/10.1088/0305-4470/19/15/008.

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7

Knospe, O., R. Schmidt, E. Engel, U. R. Schmitt, R. M. Dreizler, and H. O. Lutz. "Cluster-cluster collisions. III. Potential energy between clusters." Physics Letters A 183, no. 4 (December 1993): 332–37. http://dx.doi.org/10.1016/0375-9601(93)90466-d.

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8

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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Baisya, Ritasman, Phani Kumar Devarasetti, Murthy G. S. R., and Liza Rajasekhar. "Autoantibody Clustering in Systemic Lupus Erythematosus–Associated Pulmonary Arterial Hypertension." Indian Journal of Cardiovascular Disease in Women - WINCARS 06, no. 02 (April 2021): 100–105. http://dx.doi.org/10.1055/s-0041-1732510.

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AbstractSystemic lupus erythematous–associated pulmonary arterial hypertension (SLE-PAH) is one of the important causes of mortality in lupus patients. Different autoantibodies are associated with SLE-PAH which can predict its future development. The objective of the study was to identify distinct autoantibody-based clusters in SLE-PAH patients and to compare demographic characters, clinical phenotypes, and therapeutic strategy across the clusters. Three distinct autoantibody clusters were identified using k-means cluster analysis in 71 SLE-PAH patients. Cluster1 had predominant Sm-RNP, Smith, SS-A association; cluster 2 had no definite autoantibody association; and cluster 3 was associated with nucleosome, histone, dsDNA, and ribosomal P protein. Patients in cluster 3 had a highly active disease while those in cluster 1 had significant cytopenia. Mean age and mean right ventricular systolic pressure (RVSP) were both high in cluster 2, indicating later-onset PAH in this group. This was the first autoantibody-based cluster analysis study in SLE-PAH patients in India which confirmed that autoantibodies did exist as clusters and the presence of definite autoantibodies can predict future development of pulmonary hypertension in these patients.
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Ramos-Almendares, Felipe, Mario Abadi, Hernán Muriel, and Valeria Coenda. "Intra-cluster Globular Clusters in a Simulated Galaxy Cluster." Astrophysical Journal 853, no. 1 (January 25, 2018): 91. http://dx.doi.org/10.3847/1538-4357/aaa1ef.

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Dissertations / Theses on the topic "Cluster"

1

Thompson, Bernard Robert. "Theory of cluster-cluster aggregation." Thesis, University of Cambridge, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238123.

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Warren, Patrick Bewick. "Scaling laws in cluster-cluster aggregation." Thesis, University of Cambridge, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386210.

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3

Saleh, Ibrahim A. "Cluster automorphisms and hyperbolic cluster algebras." Diss., Kansas State University, 2012. http://hdl.handle.net/2097/14195.

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Doctor of Philosophy
Department of Mathematics
Zongzhu Lin
Let A[subscript]n(S) be a coefficient free commutative cluster algebra over a field K. A cluster automorphism is an element of Aut.[subscript]KK(t[subscript]1,[dot, dot, dot],t[subscript]n) which leaves the set of all cluster variables, [chi][subscript]s invariant. In Chapter 2, the group of all such automorphisms is studied in terms of the orbits of the symmetric group action on the set of all seeds of the field K(t[subscript]1,[dot,dot, dot],t[subscript]n). In Chapter 3, we set up for a new class of non-commutative algebras that carry a non-commutative cluster structure. This structure is related naturally to some hyperbolic algebras such as, Weyl Algebras, classical and quantized universal enveloping algebras of sl[subscript]2 and the quantum coordinate algebra of SL(2). The cluster structure gives rise to some combinatorial data, called cluster strings, which are used to introduce a class of representations of Weyl algebras. Irreducible and indecomposable representations are also introduced from the same data. The last section of Chapter 3 is devoted to introduce a class of categories that carry a hyperbolic cluster structure. Examples of these categories are the categories of representations of certain algebras such as Weyl algebras, the coordinate algebra of the Lie algebra sl[subscript]2, and the quantum coordinate algebra of SL(2).
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4

Lublinski, Alf Erko. "Geographical business clusters concepts for cluster identification with an application to an alleged aeronautics cluster in Northern Germany /." [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=965586456.

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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 clusters and their real-world impact. The theoretical background is far from being consolidated and there is a variety of methodologies and approaches for studying and interpreting this phenomenon while at the same time little comparability among studies on actual cluster performances. The conceptual framework of clustering suggests that they affect performance but theory makes little prediction as to the ultimate distribution of the value being created by clusters. This thesis takes the case of Eastern European countries for two reasons. One is that clusters, as coopetitive environments, are a new phenomenon as the previous centrally-based system did not allow for such types of firm organizations. The other is that, as new EU member states, they have been subject to the increased popularization of the cluster policy approach by the European Commission, especially in the framework of the National Reform Programmes related to the Lisbon objectives. The originality of the work lays in the fact that starting from an overview of theoretical contributions on clustering, it offers a comparative empirical study of clusters in transition countries. There have been very few examples in the literature that attempt to examine cluster performance in a comparative cross-country perspective. It adds to this an analysis of cluster policies and their implementation or lack of such as a way to analyse the way the cluster concept has been introduced to transition economies. Our findings show that the implementation of cluster policies does vary across countries with some countries which have embraced it more than others. The specific modes of implementation, however, are very similar, based mostly on soft measures such as funding for cluster initiatives, usually directed towards the creation of cluster management structures or cluster facilitators. They are essentially founded on a common assumption that the added values of clusters is in the creation of linkages among firms, human capital, skills and knowledge at the local level, most often perceived as the regional level. Often times geographical proximity is not a necessary element in the application process and cluster application are very similar to network membership. Cluster mapping is rarely a factor in the selection of cluster initiatives for funding and the relative question about critical mass and expected outcomes is not considered. In fact, monitoring and evaluation are not elements of the cluster policy cycle which have received a lot of attention. Bulgaria and the Czech Republic are the countries which have implemented cluster policies most decisively, Hungary and Poland have made significant efforts, while Slovakia and Romania have only sporadically and not systematically used cluster initiatives. When examining whether, in fact, firms located within regional clusters perform better and are more efficient than similar firms outside clusters, we do find positive results across countries and across sectors. The only country with negative impact from being located in a cluster is the Czech Republic.
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6

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 clusters and their real-world impact. The theoretical background is far from being consolidated and there is a variety of methodologies and approaches for studying and interpreting this phenomenon while at the same time little comparability among studies on actual cluster performances. The conceptual framework of clustering suggests that they affect performance but theory makes little prediction as to the ultimate distribution of the value being created by clusters. This thesis takes the case of Eastern European countries for two reasons. One is that clusters, as coopetitive environments, are a new phenomenon as the previous centrally-based system did not allow for such types of firm organizations. The other is that, as new EU member states, they have been subject to the increased popularization of the cluster policy approach by the European Commission, especially in the framework of the National Reform Programmes related to the Lisbon objectives. The originality of the work lays in the fact that starting from an overview of theoretical contributions on clustering, it offers a comparative empirical study of clusters in transition countries. There have been very few examples in the literature that attempt to examine cluster performance in a comparative cross-country perspective. It adds to this an analysis of cluster policies and their implementation or lack of such as a way to analyse the way the cluster concept has been introduced to transition economies. Our findings show that the implementation of cluster policies does vary across countries with some countries which have embraced it more than others. The specific modes of implementation, however, are very similar, based mostly on soft measures such as funding for cluster initiatives, usually directed towards the creation of cluster management structures or cluster facilitators. They are essentially founded on a common assumption that the added values of clusters is in the creation of linkages among firms, human capital, skills and knowledge at the local level, most often perceived as the regional level. Often times geographical proximity is not a necessary element in the application process and cluster application are very similar to network membership. Cluster mapping is rarely a factor in the selection of cluster initiatives for funding and the relative question about critical mass and expected outcomes is not considered. In fact, monitoring and evaluation are not elements of the cluster policy cycle which have received a lot of attention. Bulgaria and the Czech Republic are the countries which have implemented cluster policies most decisively, Hungary and Poland have made significant efforts, while Slovakia and Romania have only sporadically and not systematically used cluster initiatives. When examining whether, in fact, firms located within regional clusters perform better and are more efficient than similar firms outside clusters, we do find positive results across countries and across sectors. The only country with negative impact from being located in a cluster is the Czech Republic.
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7

Jeltema, Tesla Erin. "Cosmology with clusters of galaxies : high-redshift clusters and the evolution of cluster substructure." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28372.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2004.
Includes bibliographical references (p. 85).
Clusters of galaxies have become an important cosmological tool, yet we do not un-erstand many aspects of their formation and development. In this thesis, I pursue two projects aimed at using clusters to constrain cosmology and better understanding cluster evolution. First, I examine the Chandra observation of MS1054-0321. MS1054-0321 is the highest redshift cluster in the Einstein Medium Sensitivity Survey (EMSS), and it was one of the first high-redshift clusters observed with Chandra. I confirm that this cluster is hot and massive, although its temperature is slightly lower than inferred previously. I also detected an iron line in this cluster, one of the first detections of iron in a cluster at these redshifts, with an abundance consistent with early enrichment of the ICM. MS1054-0321 exhibits significant substructure, which I study in detail for the first time. In X-rays, it appears to be a nearly equal mass double cluster in the process of merging. Both the cluster galaxies and mass associated with the western subclump are offset from the X-ray peak, possibly indicating that the gas in the subclump is being stripped off as it falls into the cluster. Despite the lower temperature, I find that the detection of this cluster in the EMSS constrains Qm to be less than one.
(cont.) In the second project, I investigate the evolution of cluster substructure with redshift, quantifying for the first time cluster structure out to z [approx.] 1. My sample includes 40 X-ray selected, luminous clusters from the Chandra archive, and I quantify cluster morphology using the power ratio method (Buote & Tsai 1995). I find that, as expected qualitatively from hierarchical models of structure formation, high-redshift clusters have more substructure and are dynamically more active than low-redshift clusters. Specifically, the clusters with z > 0.5 have significantly higher average third and fourth order power ratios than the lower redshift clusters. This observation of structure evolution indicates that dynamical state may be an important systematic effect in cluster studies seeking to constrain cosmology, and when calibrated against numerical simulations, structure evolution will itself provide interesting bounds on cosmological models.
by Tesla Erin Jeltema.
Ph.D.
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8

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. determining policy goals and designing policy instruments. In the literature review, a guide to the field study was developed by review of various approaches to cluster concept
common features of clusters and the competitive advantages these give rise to
various practices in cluster-based policy development, and various cluster analysis methods. The field study starts with the initial identification of need for policy intervention, at which stage the rationale for pursuing a cluster-based policy in the specific conditions of Samsun and Turkey was discussed. The &ldquo
clusters as sectors&rdquo
approach was utilized in the identification of region&rsquo
s (potential) clusters and selection of the cluster as the subject of analysis and policy development. The analysis of industrial sectors in Samsun&rsquo
s economy was followed by selection of the target sector via employing various criteria assessing the importance of these sectors in terms of value added to the regional economy, and the clustering potential. Accordingly, furniture sector was selected, and the agglomeration of furniture sector enterprises in Kutlukent locality was identified as the potential cluster to be the subject of analysis and policy development. Following the identification of the potential cluster, the descriptive part was completed by second-stage micro-level analysis of the identified potential cluster, by which detailed information about the potential cluster was presented. At that phase, cluster potential of the structure was assessed by examining the elements in cluster value and production chain
public and private business support infrastructure
the flow of materials and goods in the chain
untraded relationships between the elements
characteristics of enterprises and workforce
and innovation performance. This comprehensive in-depth analysis of the cluster provided the required information to identify the specific needs of the cluster for cluster-based policy intervention. In the last part of the thesis, i.e. prescriptive part, cluster-oriented policy recommendations were developed including the determination of policy goal and the design/selection of policy instruments. The necessary information was collected by two-stage expert interviews, and by overall scan of the enterprises involved in the cluster via enterprise survey, which was realized in interviews with all of the enterprises. Six experts and 283 enterprises participated in the study. The results of the analysis showed that, while Kutlukent furniture cluster had some features, which are common in effective cluster models, the cluster lacks some critical features, which are crucial for effective functioning of a successful cluster. Hence, Kutlukent furniture cluster was defined as a &ldquo
potential&rdquo
cluster, which should be promoted by utilizing the existing potentials and strengths, and by addressing the weaknesses and obstacles identified in the analysis of the cluster, via appropriate cluster-oriented policy measures, which were proposed in the prescriptive part of the policy-making process. By these measures, the elements of Kutlukent potential cluster would be able to realize competitive advantages associated with clustering as in successful cluster models.
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Terry, William David. "Cluster production in the matrix assembly cluster source." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7726/.

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This thesis focuses on the development of the Matrix Assembly Cluster Source (MACS). Firstly, a transmission mode MACS instrument has been upgraded and integrated with a Time-Of-Flight mass filter. An equivalent cluster beam current of 100 nA of silver nanoclusters has been achieved (previously several nA). Furthermore, an intrinsic size control has been demonstrated in the 1-5 nm range by varying the silver concentration in the matrix. The MACS has been demonstrated in a reflection regime, reaching a ~1% conversion of incident ions to clusters (~0.03% in transmission). The effect of the beam-plate geometry has been investigated and a new reflection mode system commissioned, producing a maximum equivalent silver cluster current of 170±16 nA. An average equivalent current of 40 nA has been deposited for 45 minutes. Nanocluster arrays have been demonstrated to preferentially immobilize dye molecules, the primary step towards label-free cluster-based biochips. Finally, visible range ion-induced light emission from the matrix was studied. Optical measurements demonstrate significant change in the ion-induced light emission spectra with the addition of O2, N2, or Ag to the matrix. By careful analysis of the emission spectra, the thickness, composition, and in certain cases, molecular composition of the matrix can be accessed.
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Hess, Cassiano Ricardo. "MDX-cc: ambiente de programação paralela aplicado a cluster de clusters." Pontifícia Universidade Católica do Rio Grande do Sul, 2003. http://hdl.handle.net/10923/1655.

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Due to the appearance of fast communication networks, such as Myrinet and SCI, it becames possible the construction of new architectures based on commodity, off-the-shelf machines (PCs and workstations) connected by this kind of network - which are been called clusters. Such architectures are becoming an alternative execution platform for complex parallel applications, mainly due to the cost/benefit relation they present. The diversity of fast networks leads to the interconnection of clusters, building an architecture called cluster of clusters. One of the main problems in the use of clusters of clusters is the programming software used for parallel application development, since this kind of architecture has some characteristics that must be addressed by the programming language or environment in order to provide high performance. This work describes the development of a message passing parallel programming environment for cluster of clusters, the MDX-cc. This environment was projected based on the MDX system [PRE98][HES01] and a first version has been implemented supporting communication over Fast-Ethernet, SCI and Myrinet networks. The main goal of MDX-cc is to provide communication and synchronization of processes that run on interconnected clusters. Thanks to its modular architecture and the use of specific communication protocols dedicated to each network interface, MDX-cc provides a simple programming interface, with a small set of primitives, and also provides a transparent communication among processes running on different network-based clusters.
Em razão do surgimento de redes de comunicação de alta velocidade, tais como Myrinet e SCI, a construção de arquiteturas baseadas em máquinas comuns (PCs e estações de trabalho) conectadas por esse tipo de rede - o que se denomina agregado (ou cluster) - tornou-se viável. Tais arquiteturas vêm se consolidando como plataformas alternativas para a execução de aplicações paralelas complexas, principalmente devido à relação custo/benefício que oferecem. Esse avanço das tecnologias de redes possibilita também a agregação de clusters, formando uma estrutura de cluster de clusters, como uma única máquina paralela. Um dos principais problemas no uso de cluster de clusters é o software utilizado para o desenvolvimento de aplicações paralelas, visto que cada agregado envolvido na estrutura possui certas características que precisam ser tratadas pela linguagem ou ambiente de programação, visando o alcance de alto desempenho. Esta dissertação tem como objetivo apresentar uma ferramenta de programação paralela por troca de mensagens que executa sobre uma estrutura de cluster de clusters: o MDX-cc. A ferramenta foi concebida tendo como base o sistema MDX [PRE98][HES01] e uma primeira versão foi implementada oferecendo suporte à comunicação em agregados com redes SCI, Myrinet e Fast-Ethernet. O principal objetivo do MDX-cc é oferecer recursos de comunicação e sincronização de processos que rodam em agregados interligados. Por sua arquitetura modular e abstração do uso de protocolos de comunicação dedicados a cada tecnologia de rede, o MDX-cc oferece uma interface de programação simples, com um conjunto reduzido de primitivas, e provê transparência total na comunicação entre processos que executam em nós de clusters com tecnologias de rede distintas.
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Books on the topic "Cluster"

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Rohmund, Frank. Cluster-Cluster-Stösse. [s.l.]: [s.n.], 1997.

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David, Deeths, and Bianco Joseph Ph D, eds. Sun Cluster environment: Sun Cluster 2.2. Palo Alto, Calif: Sun Microsystems Press, 2001.

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Byrne, David, and Emma Uprichard. Cluster Analysis. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: 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. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9780470977811.

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González-Moraga, Guillermo. Cluster Chemistry. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-85926-7.

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Social Science Research Council (Great Britain), ed. Cluster analysis. 2nd ed. Aldershot: 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. London: Arnold, 2001.

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1970-, Buyya Rajkumar, and Szyperski Clemens, eds. Cluster computing. Huntington, N.Y: Nova Science Publishers, 2001.

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

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A, Duncan Michael, ed. Cluster materials. Stamford, CT: JAI Press, Inc., 1998.

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Book chapters on the topic "Cluster"

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Jena, P., S. N. Khanna, and B. K. Rao. "Clusters and Cluster Reactions." In Density Functional Theory of Molecules, Clusters, and Solids, 123–51. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-011-0487-6_5.

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Kähler, Wolf-Michael. "Clusteranalysen (CLUSTER, QUICK CLUSTER)." In Statistische Datenanalyse mit SPSS/PC+, 332–52. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-92800-9_16.

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Kähler, Wolf-Michael. "Clusteranalysen (CLUSTER, QUICK CLUSTER)." In Statistische Datenanalyse mit SPSS/PC+, 332–51. Wiesbaden: Vieweg+Teubner Verlag, 1992. http://dx.doi.org/10.1007/978-3-322-86262-4_16.

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Joos, Thomas. "Cluster." In Exchange Server 2000: Installieren — Konfigurieren — Administrieren — Optimieren, 197–220. Wiesbaden: Vieweg+Teubner Verlag, 2003. http://dx.doi.org/10.1007/978-3-663-12109-1_4.

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Henckel, Dietrich, Kester von Kuczkowski, Petra Lau, Elke Pahl-Weber, and Florian Stellmacher. "CLUSTER." In Planen – Bauen –Umwelt, 94–120. Wiesbaden: VS Verlag für Sozialwissenschaften, 2010. http://dx.doi.org/10.1007/978-3-531-92288-1_3.

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Peroulis, Dimitrios, Prashant R. Waghmare, Sushanta K. Mitra, Supone Manakasettharn, J. Ashley Taylor, Tom N. Krupenkin, Wenguang Zhu, et al. "Cluster." In Encyclopedia of Nanotechnology, 433. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-90-481-9751-4_100140.

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Baun, Christian, Günther Bengel, Marcel Kunze, and Karl-Uwe Stucky. "Cluster." In Masterkurs Parallele und Verteilte Systeme, 429–45. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-8348-2151-5_10.

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Joos, Thomas. "Cluster." In Exchange Server 2000: Installieren — Konfigurieren — Administrieren — Optimieren, 201–24. Wiesbaden: Vieweg+Teubner Verlag, 2003. http://dx.doi.org/10.1007/978-3-322-91955-7_4.

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Gooch, Jan W. "Cluster." In Encyclopedic Dictionary of Polymers, 975. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15180.

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Malthe-Sørenssen, Anders. "Geometry of Clusters." In Percolation Theory Using Python, 63–84. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-59900-2_5.

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AbstractWe have seen how we can characterize clusters by their mass, s. As p approaches $$p:c$$ p c , the typical cluster size s increases as well as the characteristic cluster diameter. In this chapter we will discuss the geometry of clusters, and by geometry we will mean how the number of sites in a cluster is related to the linear size of the cluster. We will introduce several measures to characterize the spatial extent, the characteristic radius $$R:s$$ R s , of clusters of size s. We will measure $$R:s$$ R s to motivate that it is proportional to $$s^1/D$$ s 1 ∕ D , where D is a new exponent characterizing the dimension of clusters. We will demonstrate that the percolation system is characterized by two lengths, the system size L and a characteristic cluster size $$\xi $$ ξ , and that the system shows fractal, self-similar scaling when the characteristic length diverges. We develop scaling theories for $$P(s,L)$$ P ( s , L ) for $$p>p_c$$ p > p c and lay the foundations for a geometrical understanding and description of the spanning cluster.
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Conference papers on the topic "Cluster"

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Vormoor, O. "Reorganization of clusters in cluster-cluster-aggregation." In Sixth international conference on x-ray microscopy (XRM99). AIP, 2000. http://dx.doi.org/10.1063/1.1291152.

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Cosnita, Daniel alexandru, and Neculai eugen Seghedin. "CLUSTER COMPETITIVENESS PLATFORM." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-134.

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Clusters are regional agglomerations of enterprises (industry), universities and research organisations (RDI), regional/local public authorities and other catalyst institutions gathered around common objectives and goals. Cluster models are strictly linked to measuring their competitiveness based on innovation and internationalisation, as they are regional development instruments in the first place. Several platforms are currently in use at international level measuring cluster competitiveness, created and focused on the very objective they have been defined for. The Cluster Modelling Platform proposes an integrated approach harmonising theoretic considerations and practical aspects of utility aiming at becoming an useful tool for the generation of competitive clusters based on innovation and internationalisation (1); an instrument to measure cluster competitiveness and a consultancy tool (2); a way to evaluate performance of the cluster management team (3); a flexible method allowing assessments both at cluster level and at the level of each member. The evaluation methodology considers both quantitative and qualitative aspects, taking into considerations various indicators such as turnover, exports, employment, innovation (quantitative) and geographical concentration, labour force, strategy, internationalisation and cooperation (qualitative).Qualitative aspects play a validation role, after answers given by peers are being digitalised. In the end, an analogical cluster function is being calculated. As data flow in, the function autocorrects itself in order to give accurate results. Results are being interpreted and recommendations are being provided. The tool is embedded in a user-friendly web-platform. The end beneficiaries are mainly clusters and their members but policy makers can also make a good use of it.
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Tzou, D. Y., J. K. Chen, R. Roybal, and J. E. Beraun. "Cluster Dynamics for Multiscale Interactions." In ASME 2003 Heat Transfer Summer Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/ht2003-47560.

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A cluster approach has been proposed to describe the process of heat transport in microscale. Molecular clustering is described by integrating the Lennard-Jones potential over specific physical domains, forming cluster potentials that possess repulsive and attractive forces sensitively varying with the geometrical shapes of the molecular clusters. The cluster potentials thus developed provides a consistent approach for describing multi-scale heat transport, in that different shapes/dimensions of the clusters take different exponents in the repulsive and attractive forces. A one-dimensional example is given to illustrate the essence of the cluster dynamics simulation, emphasizing devious behavior from molecular motion and replacement of physical boundaries by cluster potentials of a larger scale.
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Baumert, T., R. Thalweiser, V. Weiss, E. Wiedenmann, and G. Gerber. "Femtosecond Dynamics of Nan and Hgn Metal-Cluster." In International Conference on Ultrafast Phenomena. Washington, D.C.: Optica Publishing Group, 1994. http://dx.doi.org/10.1364/up.1994.thb.4.

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In recent years clusters and in particular metal clusters have been the fascinating subject of many experimental and theoretical studies. Cluster physics bridge the gap between molecular physics and solid state physics. Metal clusters exhibit distinct features ranging from molecular properties seen in small particles to solid state like behaviour of large aggregates. We report cluster size dependent studies of physical and chemical properties such as absorption resonances, lifetimes, decay channels and ionisation processes of the one- and two electron metal clusters Nan and Hgn. For these studies we introduced a new experimental technique consisting of the combination of a cluster beam, ion- and electron spectroscopy and tunable femtosecond laser pump-probe techniques. A major result of our femtosecond experiments is that the conventional view of the optical response of metal cluster, e.g. absorption, ionisation and decay processes as well as the relevant time scale, had to be changed. Our results clearly show that for Nan and cluster sizes n≤21 molecular structure, excitations and properties prevail over collective excitations and surface plasmon-like properties.
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Buch, Amanda, Conor Liston, and Logan Grosenik. "Cluster-Aware Algorithms for AI-Enabled Precision Medicine." In LatinX in AI at Neural Information Processing Systems Conference 2023. Journal of LatinX in AI Research, 2023. http://dx.doi.org/10.52591/lxai2023121011.

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AI-enabled precision medicine promises a transformative improvement in healthcare outcomes. However, training on biomedical data presents a challenge: such data are often high dimensional, clustered, and of limited sample size. To overcome this, we propose a simple and scalable approach for cluster-aware embedding that augments embedding methods with a convex clustering penalty. This approach outperforms fourteen widely-used clustering methods on both highly underdetermined problems and on large sample datasets, yielding interpretable dendrograms of the embedded clusters. Our approach improves on existing methods and introduces a modular framework for interpretable biomarker discovery in precision medicine.
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Churchelauri, Mariam. "Maritime Transport Cluster Development in Georgia." In Challenges in Economics and Business in the Post-COVID Times. University of Maribor Press, 2022. http://dx.doi.org/10.18690/um.epf.5.2022.22.

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The geopolitical location in Georgia creates opportunities for maritime cluster development. The functioning of the international transport corridor depends on the ports and maritime transport. The country’s strategic location on the ‘One Belt One Road’ (OBOR) route, positioned along the shortest route between China and Europe. The development of maritime cluster gives Georgia the function of international importanceand provides more opportunities for sustainable development. The purpose of this paper relates to the possibilities of establishing maritime clusters in Georgia. Creating a cluster provides new opportunities for innovative handling of technological operations in port logistics. Creation of a maritime cluster on the basis of the Port of Batumi and the port of Poti, should increase the competitiveness of both the ports and other companies – as a cluster member. There are advantages of creating marine clusters in Georgia, such as it's: geopolitical location, attractive investment environment, regulated transportation infrastructure, vast seaport. The need to find solutions to the ongoing effects of the COVID-19 pandemic, strengthening Georgia’s transit function and transformation of the country’s ports into a maritime transport cluster will improve the competitiveness of the Georgian economy after the pandemic.
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Sekachev, Mikhail, Cheng-Xian Lin, Zhiyu Hu, and Don Dareing. "A Computational Study of Catalytic Platinum Nanoparticles With and Without OH Chemisorption During Reactions." In ASME 2008 3rd Energy Nanotechnology International Conference collocated with the Heat Transfer, Fluids Engineering, and Energy Sustainability Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/enic2008-53029.

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In this paper, various energies and geometries of pure platinum nanoparticles and those of platinum nanoparticles with adsorbed OH were investigated. Ten different platinum clusters of up to 28 atoms were studied using spin-unrestricted density functional theory (DFT) with a double numerical plus polarization basis set. Three different shapes were presented, and the effect of cluster size on binding energy, total energy, and HOMO-LUMO energy gap was investigated. The same set of calculations was performed for selected clusters with OH adsorbate on the Pt(111) surface. The results show that the stability of both the pure clusters and the clusters with adsorbed OH molecule increases with an increase of cluster size. This fact indicates that direct influence of the size of Pt cluster on the reaction rate is possible, and the understanding of how cluster size would affect binding energy is important. The effect of cluster size on total energy of molecule was shown to be a linear function independent of cluster type, as expected. We also found that optimized (stable) Pt clusters were bigger in size than that of the initial clusters, or clusters with bulk geometry.
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Ghasemi, Amin, and Max T. Stephens. "Development of Seismic Response Model for Wellington Building Inventory Using Indicator Buildings." In IABSE Symposium, Istanbul 2023: Long Span Bridges. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2023. http://dx.doi.org/10.2749/istanbul.2023.0198.

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<p>This paper is focused on regional building responses to earthquakes and the identification of broad vulnerability archetypes to increase resilience and limit human and economic loss. Wellington, New Zealand has been selected as the case study for this research due to the unique access to building data within the Central Business District (CBD), and the potential risk of seismic events. A database of reinforced concrete buildings with five or more stories in the Wellington CBD were clustered using a novel deep neural network architecture. The buildings in each cluster are similar in the seismic vulnerability and hence, the seismic response of the indicator buildings in each cluster can be used to quantify the seismic response of all buildings within the clusters. The building inventory was clustered into five clusters and eight indicator buildings were selected for detailed nonlinear response modeling based on their relative location to the cluster mean. The selected indicator buildings had different vulnerabilities based on their date of construction and lateral system; appropriate nonlinear models were generated using the most-detailed macro modeling approaches of buildings available in OpenSees. Next, the seismic response of selected buildings due to the input ground motions were quantified. Finally, results from the indicator buildings response models were utilized to predict the seismic response of all buildings within the same vulnerability cluster using linear regression models. The results of response prediction for the Wellington Building Inventory were verified by the measured response of some instrumented buildings for the 2016 Kaikoura earthquake.</p>
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Castleman, A. W., and R. G. Keesee. "Dynamics of cluster dissociation." In International Laser Science Conference. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/ils.1986.jfc1.

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Studies of cluster ionization and dissociation are of wide-ranging interest as they contribute to a further understanding of inter-molecular energy flow and energy disposal following multiphoton ionization, as well as on the changing properties of matter undergoing transitions from the gas to condensed phase. A major advance in the study of unimolecular dissociation and the spectroscopy of clusters has become available through the use of multi-photon ionization methods coupled with time-of-flight reflectron techniques. Using single and two-color pulsed lasers, the excess energy introduced into a cluster can be controlled. The power of the method is demonstrated by results of recent investigations of cluster fragmentation following internal ion-molecule reactions in hydrogen bonded cluster systems. The role of dissociation and the influence of the thermochemical stability of cluster ions in affecting the appearance of magic numbers in certain cluster distributions is discussed. The application of this method in studying spectral shifts and determining ionization potentials of probe molecules following successive clustering with a solvent species is also presented.
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Castleman, A. W., and R. G. Keesee. "Dynamics of cluster dissociation." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.fc1.

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Studies of cluster ionization and dissociation are of wide-ranging interest as they contribute to a further understanding of intermolecular energy flow and energy disposal following multiphoton ionization, as well as on the changing properties of matter undergoing transitions from the gas to condensed phase. A major advance in the study of unimolecular dissociation and the spectroscopy of clusters has become available through the use of multiphoton ionization methods coupled with time-of-flight reflectron techniques. Using single and two-color pulsed lasers, the excess energy introduced into a cluster can be controlled. The power of the method is demonstrated by results of recent investigations of cluster fragmentation following internal ion-molecule reactions in hydrogen bonded cluster systems. The role of dissociation and the influence of the thermochemical stability of cluster ions in affecting the appearance of magic numbers in certain cluster distributions is discussed. The application of this method in studying spectral shifts and determining ionization potentials of probe molecules following successive clustering with a solvent species is also presented.
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Reports on the topic "Cluster"

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Rabellotti, Roberta, and Elisa Conz. Mainstreaming the Cluster Approach in the Caribbean Region: The CCPF Cluster Capacity Building Initiative. Inter-American Development Bank, March 2023. http://dx.doi.org/10.18235/0004771.

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In the Caribbean region, clusters hold tremendous potential because of the predominance of small and micro enterprises, their weak link in value chains and the scarcity of specialized inputs. The Compete Caribbean Partnership Facility (CCPF) has backed a capacity-building campaign for the cluster approach with the aim of mainstreaming cluster interventions in the region. This report explores how the process of mainstreaming is taking shape among those business support organizations (BSOs) involved in the CCPF project, currently involved in the implementation of cluster projects. The study addressed these questions: (i) Have the BSOs improved their capacity to identify, design, and implement sustainable cluster initiatives? (ii) Is the cluster approach becoming mainstream in the Caribbean region? Based on primary evidence, the main findings are as follows. BSOs have played a key role by engendering a collaborative culture amongst clusters. One of the main achievements in implementing cluster programs is the increasing cooperation between clusters. Among the BSOs, there is general agreement over the usefulness of monitoring the cluster implementation when taking informed decisions, but the collection of information is also challenging. In the Caribbean region, cluster policies do not yet represent the core of industrial development policies; nonetheless, the potential for a more regional approach to cluster mainstreaming has surfaced in interviews. Policy recommendations for introducing and promoting the mainstreaming of a cluster approach in the Caribbean region should take a three-pronged approach that focuses on (i) cluster organizations, (ii) national ecosystems, and (iii) regional ecosystems.
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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.], October 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 the correct selection of clusters, a comparative analysis of several methods was performed: arithmetic mean ranks, hierarchical methods followed by dendrogram construction, K- means method, which refers to reference methods, in which the number of groups is specified by the user. The cluster analysis of forestries by twenty analytical grounds was not proved by analysis of variance, so the re-clustering of certain objects was carried out according to the nine most significant analytical features. As a result, the forestry was clustered into four clusters. The conducted cluster analysis with the use of different methods allows us to state that their combination helps to select reasonable groupings, clearly illustrate the clustering procedure and rank the obtained forestry clusters.
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Bowers, Michael T. Cluster Ions. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada282615.

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Bowers, Michael T. Cluster Ions. Fort Belvoir, VA: Defense Technical Information Center, August 1999. http://dx.doi.org/10.21236/ada376262.

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Owen, R. K. Quantum Monte Carlo methods and lithium cluster properties. [Atomic clusters]. Office of Scientific and Technical Information (OSTI), December 1990. http://dx.doi.org/10.2172/7204421.

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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, September 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 of the two experiences made it possible to draw some general conclusions concerning the similarities and differences between the two clusters in terms of the adoption and diffusion of exporting.
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Garrett, Charles Kristopher. The Darwin Cluster. Office of Scientific and Technical Information (OSTI), June 2018. http://dx.doi.org/10.2172/1441285.

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Moreland, Blythe. Measuring Cluster Relaxedness. Office of Scientific and Technical Information (OSTI), August 2012. http://dx.doi.org/10.2172/1049742.

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Bertsch, G. F., and K. Yabana. Cold cluster ferromagnetism. Office of Scientific and Technical Information (OSTI), December 1993. http://dx.doi.org/10.2172/10128221.

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Pacchioni, G., P. S. Bagus, and M. R. Philpott. Cluster-Model Study of the Interaction of Halogen Atoms with Ag Clusters. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada229749.

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