scholarly journals The Space and Terrestrial Weather Variations as Possible Factors for Ischemia Events in Saint Petersburg

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 8
Author(s):  
Olga M. Stupishina ◽  
Elena G. Golovina ◽  
Sergei N. Noskov ◽  
Gennady B. Eremin ◽  
Sergei A. Gorbanev
Keyword(s):  
Cluster Analysis ◽  
Hypothesis Test ◽  
Saint Petersburg ◽  
Data Treatment ◽  
Test Criterion ◽  
Gender Groups ◽  
Weather Variations

The Space and Terrestrial Weather (Weather Complex) impact on ischemia cases in Saint Petersburg is investigated. The results show the main feature of the Weather Complex when it was related to the days of the different ischemia situations in the different ischemia people gender groups. The data treatment was done with some elements of the Folder Epochs Method, Cluster Analysis and the Mann–Whitney hypothesis test criterion.

scholarly journals 33 Aplicação da análise exploratória de dados na discriminação geográfica do quiabo do Rio Grande do Norte e Pernambuco

2018 ◽  
Vol 34 (3) ◽  
pp. 33
Author(s):  
Francisco Dos Santos Panero ◽  
Maria de Fátima Pereira Vieira ◽  
Ângela Maria Paiva Cruz ◽  
Maria de Fátima Vitória De Moura ◽  
Henrique Eduardo Bezerra Da Silva
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Rio Grande ◽  
Component Analysis ◽  
The State ◽  
Data Treatment ◽  
Different Origins

Samples of okra from Caruaru and Vitória of Santo Antão, in the State of Pernambuco, and Ceará-Mirim, Macaíba and Extremoz in the State of Rio Grande do Norte have been analysed. Two different methods were applied in the data treatment allowing to geographically discriminate samples from different origins: Principal Component Analysis - PCA and Hierarquical Cluster Analysis - HCA.

scholarly journals Near earth space object detection using parallax as multi-hypothesis test criterion

2019 ◽  
Vol 27 (4) ◽  
pp. 5403
Author(s):  
Joseph Tompkins ◽  
Stephen Cain ◽  
David Becker
Keyword(s):  
Object Detection ◽  
Hypothesis Test ◽  
Space Object ◽  
Earth Space ◽  
Near Earth Space ◽  
Test Criterion

scholarly journals Characterizing Heterogeneity in Drivers’ Merging Maneuvers Using Two-Step Cluster Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Gen Li ◽  
Lu Sun
Keyword(s):  
Cluster Analysis ◽  
High Speed ◽  
Hypothesis Test ◽  
Simulation Software ◽  
Microscopic Simulation ◽  
Traffic Condition ◽  
Low Speed ◽  
Kolmogorov Smirnov ◽  
Log Normal ◽  
Behavior Models

In order to investigate the heterogeneity in merging behaviors on freeways, a novel data mining tool, called two-step cluster analysis, is applied to the merging maneuvers (namely, initial speed, merging speed, and merging position). Merging maneuvers of 370 drivers collected from the NGSIM dataset are automatically and optimally segmented into four clusters (Early Merging Drivers at High Speed, Early Merging Drivers at Low Speed, Late Merging Drivers at Low Speed, and Late Merging Drivers at High Speed) by the two-step cluster analysis. Hypothesis test confirms the significant differences in merging maneuvers between different clusters. The clustered data are used to find the best corresponding fitting distributions. Seven distributions (Normal, Log-normal, Student’s t, Logistic, Log-Logistic, Gamma, and Weibull) are considered for each cluster and the Kolmogorov-Smirnov test statics are used to select the best fitted distributions. It is found that merging drivers may merge either early or late, under congestion or uncongested traffic condition. Further analysis of merging durations shows that Late Merging Drivers use significantly shorter time than Early Merging Drivers to finish the merging maneuver, no matter if they are at high or at low speed. Hypothesis test of accepted lead gaps and lag gaps indicate that merging drivers are more sensitive to the lag gaps under congestion. The proposed method can automatically identify the heterogeneity in merging drivers and the results obtained in this paper can be used to enhance the accuracy of the merge behavior models in microscopic simulation software.

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

Measuring “Language Access Profiles” in Deaf and Hard-of-Hearing Children With the DHH Language Exposure Assessment Tool

2020 ◽  
pp. 1-25
Author(s):  
Matthew L. Hall ◽  
Stephanie De Anda
Keyword(s):  
Cluster Analysis ◽  
Exposure Assessment ◽  
Hard Of Hearing ◽  
Assessment Tool ◽  
Communication Mode ◽  
Developmental Potential ◽  
Language Access ◽  
Retest Reliability ◽  
Language Exposure ◽  
Test Retest Reliability

Purpose The purposes of this study were (a) to introduce “language access profiles” as a viable alternative construct to “communication mode” for describing experience with language input during early childhood for deaf and hard-of-hearing (DHH) children; (b) to describe the development of a new tool for measuring DHH children's language access profiles during infancy and toddlerhood; and (c) to evaluate the novelty, reliability, and validity of this tool. Method We adapted an existing retrospective parent report measure of early language experience (the Language Exposure Assessment Tool) to make it suitable for use with DHH populations. We administered the adapted instrument (DHH Language Exposure Assessment Tool [D-LEAT]) to the caregivers of 105 DHH children aged 12 years and younger. To measure convergent validity, we also administered another novel instrument: the Language Access Profile Tool. To measure test–retest reliability, half of the participants were interviewed again after 1 month. We identified groups of children with similar language access profiles by using hierarchical cluster analysis. Results The D-LEAT revealed DHH children's diverse experiences with access to language during infancy and toddlerhood. Cluster analysis groupings were markedly different from those derived from more traditional grouping rules (e.g., communication modes). Test–retest reliability was good, especially for the same-interviewer condition. Content, convergent, and face validity were strong. Conclusions To optimize DHH children's developmental potential, stakeholders who work at the individual and population levels would benefit from replacing communication mode with language access profiles. The D-LEAT is the first tool that aims to measure this novel construct. Despite limitations that future work aims to address, the present results demonstrate that the D-LEAT represents progress over the status quo.

Social representations of human rights violations: Further evidence

2001 ◽  
Vol 60 (2) ◽  
pp. 89-98 ◽  
Author(s):  
Alain Clémence ◽  
Thierry Devos ◽  
Willem Doise
Keyword(s):  
Cluster Analysis ◽  
Human Rights ◽  
Costa Rica ◽  
Young People ◽  
Social Representations ◽  
Social Reality ◽  
Questionnaire Study ◽  
Human Rights Violations ◽  
High Tolerance ◽  
Individual Actions

Social representations of human rights violations were investigated in a questionnaire study conducted in five countries (Costa Rica, France, Italy, Romania, and Switzerland) (N = 1239 young people). We were able to show that respondents organize their understanding of human rights violations in similar ways across nations. At the same time, systematic variations characterized opinions about human rights violations, and the structure of these variations was similar across national contexts. Differences in definitions of human rights violations were identified by a cluster analysis. A broader definition was related to critical attitudes toward governmental and institutional abuses of power, whereas a more restricted definition was rooted in a fatalistic conception of social reality, approval of social regulations, and greater tolerance for institutional infringements of privacy. An atypical definition was anchored either in a strong rejection of social regulations or in a strong condemnation of immoral individual actions linked with a high tolerance for governmental interference. These findings support the idea that contrasting definitions of human rights coexist and that these definitions are underpinned by a set of beliefs regarding the relationships between individuals and institutions.

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