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Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma

REFERENCES 1. Global Initiative for Asthma (GINA). Global Strategy for Asthma Management and Prevention. 2016. 2. Mileva Z, Popov T, Staneva M, et al. [Frequency and characteristics of the allergic diseases in Bulgaria.] Allergy and asthma, 2000;5 (Supl.1):3-32 [Bulgarian]. 3. Haldar P, Pavord I, Shaw D, et al. Cluster analysis and clinical asthma phenotypes. Am J Respir Crit Care Med 2008;178:218-24. 4. Moore W, Meyers D, Wenzel S, et al. Identification of asthma phenotypes using cluster analysis in the severe asthma research program. Am

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Computer recognition of data structures using cluster analysis and the theory of mathematical records

Abstract

The paper proposes a new approach to the agglomeration of data in cluster analysis. The new approach assumes that sets of similar events are attributed to the cumulative probability of their occurrence at the same time. Such approaches will not be found in probability. Thanks to the mathematical theory of records fairly accurate classification of the object can be provided. This is the method which can be used in the cluster analysis by agglomeration. Figure 1 has been drawn for the purposes of better illustration of the problem. It shows the problem of classifying an object to one of the two classes: suitable or unsuitable for further use. Thanks to the merger of two classifiers: KNN algorithm (k nearest neighbours) and belief function a model was created, which is pretty strong as it seems to discriminate against space objects. It therefore seems reasonable to discriminate space of objects. The paper also shows a possibility of applying the proposed model to classification and the correlation between cytokines and features related to the occurrence of lymphocytic leukaemia. It therefore seems justified to carry out tests on this new method as regards various scientific problems.

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Mapping Diversity of Publication Patterns in the Social Sciences and Humanities: An Approach Making Use of Fuzzy Cluster Analysis

, 2011 ) or in that of cognitive structure, mostly of a single discipline ( Lin & Kaid, 2000 ; Persson, 2015 ). In an effort to document intra-disciplinary diversity in a more systematic way, Verleysen and Weeren (2016) have performed a hard partitioning cluster analysis on the publication patterns of 1,828 individual authors belonging to 16 SSH disciplines and affiliated with the five universities in Flanders, Belgium. This analysis at the author level has demonstrated that intra-disciplinary diversity as regards publication patterns in Flanders is considerable, as

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Cluster Analysis in Research of Accident Rate in Construction Sector

Abstract

The construction site and its elements create circumstances that are conducive to the formation of risks to work safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This paper attempts to analyse the characteristics of the construction site to indicate their importance in defining the circumstances of an accident at work. The research was carried out on the basis of data from the register kept by the District Labour Inspectorate in Krakow, Poland. Main substantive tasks include isolating patterns of accidents on site and identifying those of the analysed characteristics that are important in defining these patterns. In terms of methodology, the paper presents a method of analysing data resources by using means of conceptual grouping in the form of cluster analysis.

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AMMI and GGE Biplot for genotype × environment interaction: a medoid–based hierarchical cluster analysis approach for high–dimensional data

: “Quantitative Genetics, Genomics and Plant Breeding”. CAB International, Wallingford, England: 221-243. Kaufman L., Rousseeuw P. (1990): Partitioning around medoids (program pam). Finding groups in data: an introduction to cluster analysis: 68-125. Mahalanobis P.C. (1936): On the generalised distance in statistics. Proceedings of the National Institute of Sciences of India: 49-55. Miranda G.V., Souza L.V., Guimarães L.J.M., Namorato H., Oliveira L.R., Soares M.O. (2009): Multivariate analyses of genotype x environment interaction of popcorn. Pesq. agropec

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Hemofiltration Romanian Registry – Typologies of patients identified by cluster analysis

References 1. E. Clark, A. O. Molnar, O. Joannes-Boyau, P. M. Honoré, L. Sikora, S. M. Bagshaw. High-volume hemofiltration for septic acute kidney injury: a systematic review and meta-analysis in Crit Care. 2014; 18(1): R7. 2. J. O. Friedrich, R. Wald, S. M. Bagshaw, K. E. A. Burns, N. K. J. Adhikari. Hemofiltration compared to hemodialysis for acute kidney injury: systematic review and meta-analysis, in Crit Care. 2012; 16(4): R146. 3. H. Dunn, L. Quinn, S. J. Corbridge, K. Eldeirawi, M. Kapella, E. G. Collins. Cluster Analysis in Nursing

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Use of functional cluster analysis of CPTU data for assessment of a subsoil rigidity

to the concept of functional data analysis. 3.2 Assumptions for the algorithm using functional data analysis In view of the indirect relationship of the values measured in the CPTU test (e.g. cone resistance) to the constrained modulus established in the subsoil, first of all, for the constructed algorithm, the value of modulus M as the function of depth has to be determined at each testing site (CPTU profile). This stage is based on a procedure for the identification of homogeneous geotechnical layers using cluster analysis, presented by Młynarek

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Transport Simulation Model Calibration with Two-Step Cluster Analysis Procedure

Abstract

The calibration results of transport simulation model depend on selected parameters and their values. The aim of the present paper is to calibrate a transport simulation model by a two-step cluster analysis procedure to improve the reliability of simulation model results. Two global parameters have been considered: headway and simulation step. Normal, uniform and exponential headway generation models have been selected for headway. Application of two-step cluster analysis procedure to the calibration procedure has allowed reducing time needed for simulation step and headway generation model value selection.

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Data clustering analysis in the assessment of wastes using in the sewage filtration

Technologie. T. 9. Z. 3 p. 1–21. StatSoft 2018. Cluster analysis [online]. [Access 15.11.2018]. Available at: http://www.statsoft.com/textbook/clusteranalysis W ąsik E., C hmielowski K. 2017. Ammonia and indicator bacteria removal from domestic sewage in a vertical flow filter filled with plastic material. Ecological Engineering. Vol. 106 p. 378−384. W ąsik E., C hmielowski K., S tudziński J., S zeląg B. 2018. Zastosowanie sztucznych sieci neuronowych do prognozowania zawartości azotu ogólnego w odpływie z oczyszczalni ścieków [Application of

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Cluster Analysis for the Determination of Innovative and Sustainable Oriented Regions in Europe

Abstract

In the past decades the preoccupation of decision-makers towards innovation and sustainable development has gained a major importance in the policy of most countries in Europe. On one hand, efficient innovation can differentiate a country or a region from another and make a difference in the intense increasing economic, technological and social competition. On the other hand, the orientation towards sustainable development assures a clean and unpolluted, social oriented and healthy environment as a framework for the growth of a country or a region. In many cases, innovation and sustainable development go hand in hand, as innovations contribute to the development of clean technologies, while sustainable societies assure the proper environment and background for stimulating the innovation research. The objective of this research is to determine the cluster of countries in Europe which are rather oriented to innovation or to sustainable development or both and to forecast their future developments and tendencies. In order to achieve this objective, the multivariate cluster analysis was applied with the help of the SPSS program, for data provided by the Eurostat for several innovation, sustainable development and contextual indicators. In a first step, for each of the analyzed countries, the values of the indicators have been collected for the same period and the correlations among them have been determined. In the second phase the number of clusters and the cluster membership of each country was determined, by running the Ward cluster analysis. Based on the results, the characteristics of each cluster of countries was defined.

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