scholarly journals Cluster analyses of two acoustic confusion matrices

1973 ◽  
Vol 13 (1) ◽  
pp. 13-24 ◽  
Author(s):  
B. J. T. Morgan
Keyword(s):  
Cluster Analyses ◽  
Acoustic Confusion ◽  
Confusion Matrices

Being Drunk to Have Fun or to Forget Problems?

2010 ◽  
Vol 26 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Emmanuel Kuntsche ◽  
Ronald Knibbe ◽  
Rutger Engels ◽  
Gerhard Gmel
Keyword(s):  
Social Relationships ◽  
Convergent Validity ◽  
Structural Equation ◽  
Risk Groups ◽  
Drinking Motives ◽  
Equation Modeling ◽  
Cluster Analyses ◽  
High Concordance ◽  
Nationally Representative ◽  
Risky Single Occasion Drinking

Prevention programs in adolescence are particularly effective if they target homogeneous risk groups of adolescents who share a combination of particular needs and problems. The present work aims to identify and classify risky single-occasion drinking (RSOD) adolescents according to their motivation to engage in drinking. An easy-to-use coding procedure was developed. It was validated by means of cluster analyses and structural equation modeling based on two randomly selected subsamples of a nationally representative sample of 2,449 12- to 18-year-old RSOD students in Switzerland. Results revealed that the coding procedure classified RSOD adolescents as either enhancement drinkers or coping drinkers. The high concordance (Sample A: κ = .88, Sample B: κ = .90) with the results of the cluster analyses demonstrated the convergent validity of the coding classification. The fact that enhancement drinkers in both subsamples were found to go out more frequently in the evenings and to have more satisfactory social relationships, as well as a higher proportion of drinking peers and a lower likelihood to drink at home than coping drinkers demonstrates the concurrent validity of the classification. To conclude, the coding procedure appears to be a valid, reliable, and easy-to-use tool that can help better adapt prevention activities to adolescent risky drinking motives.

Public finance flow in contemporary Russia

2020 ◽  
Vol 26 (11) ◽  
pp. 2501-2523
Author(s):  
V.V. Smirnov
Keyword(s):  
Neural Network ◽  
Public Finance ◽  
Systems Approach ◽  
Management Decisions ◽  
Public Authorities ◽  
Cluster Analyses ◽  
The Public ◽  
National Wealth ◽  
Economic Formation

Subject. This article discusses the issues related to public finance. Objectives. The article aims to identify the determinants, indicators, and priorities of the public finance flow in contemporary Russia. Methods. For the study, I used the methods of statistical, neural network, and cluster analyses, and the systems approach. Results. The article identifies and describes the determining indicators of the main aggregates and balances of public finance, sources, and the use of funds. It establishes a link between the main aggregates and balances of public finance, defining the form and content of Russian capitalism. Conclusions. Understanding the issue and problem of public finance flow in contemporary Russia helps identify the reasons for the inability to transit to a capitalist socio-economic formation. The provisions of the study expand the scope of knowledge and develop the competence of public authorities to make management decisions on the distribution and redistribution of the value of a public product and part of the national wealth.

Model of correlation between anticipatory consistency and intuitiveness in the development of neuroses

2020 ◽  
pp. 31-36
Author(s):  
Alexander Granitsa
Keyword(s):  
Significant Role ◽  
Defense Mechanisms ◽  
Somatoform Disorders ◽  
General System ◽  
Healthy People ◽  
Coping With Stress ◽  
Psychological Defense ◽  
Cluster Analyses ◽  
Neurotic Disorders

The aim of the study was to form the model of correlation between intuitiveness and anticipatory consistency in case of neurotic and somatoform disorders. The study included 197 patients with neurotic and somatoform disorders and 66 healthy people. We found a lower level of intuitiveness and anticipatory consistency in patients with neurotic disorders than in healthy people. Correlation and cluster analyses have shown that anticipatory inconsistency and a reduced intuitiveness play a significant role in the mechanisms of neurosis development. Intuitiveness in neurotic and somatoform disorders is the link between anticipatory consistency and psychological defense mechanisms in the general system of coping with stress.

Evaluation of soil quality under conservation tillage via factor and cluster analyses

2010 ◽  
Vol 18 (2) ◽  
pp. 223-228 ◽  
Author(s):  
Yu-Hong WU ◽  
Xiao-Hong TIAN ◽  
Xiong-Xiong NAN ◽  
Wen-Bo CHI ◽  
Xiao-Li YAN ◽  
...  
Keyword(s):  
Soil Quality ◽  
Conservation Tillage ◽  
Cluster Analyses

Fully automated contrast and non-contrast cardiac view detection in echocardiography a multi-centre, multi-vendor study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Gao ◽  
D Stojanovski ◽  
A Parker ◽  
P Marques ◽  
S Heitner ◽  
...  
Keyword(s):  
Neural Network ◽  
Training Data ◽  
Classification Model ◽  
Validation Dataset ◽  
Funding Source ◽  
Private Company ◽  
Validation Data ◽  
Independent Test ◽  
Model Training ◽  
Confusion Matrices

Abstract Background Correctly identifying views acquired in a 2D echocardiographic examination is paramount to post-processing and quantification steps often performed as part of most clinical workflows. In many exams, particularly in stress echocardiography, microbubble contrast is used which greatly affects the appearance of the cardiac views. Here we present a bespoke, fully automated convolutional neural network (CNN) which identifies apical 2, 3, and 4 chamber, and short axis (SAX) views acquired with and without contrast. The CNN was tested in a completely independent, external dataset with the data acquired in a different country than that used to train the neural network. Methods Training data comprised of 2D echocardiograms was taken from 1014 subjects from a prospective multisite, multi-vendor, UK trial with the number of frames in each view greater than 17,500. Prior to view classification model training, images were processed using standard techniques to ensure homogenous and normalised image inputs to the training pipeline. A bespoke CNN was built using the minimum number of convolutional layers required with batch normalisation, and including dropout for reducing overfitting. Before processing, the data was split into 90% for model training (211,958 frames), and 10% used as a validation dataset (23,946 frames). Image frames from different subjects were separated out entirely amongst the training and validation datasets. Further, a separate trial dataset of 240 studies acquired in the USA was used as an independent test dataset (39,401 frames). Results Figure 1 shows the confusion matrices for both validation data (left) and independent test data (right), with an overall accuracy of 96% and 95% for the validation and test datasets respectively. The accuracy for the non-contrast cardiac views of >99% exceeds that seen in other works. The combined datasets included images acquired across ultrasound manufacturers and models from 12 clinical sites. Conclusion We have developed a CNN capable of automatically accurately identifying all relevant cardiac views used in “real world” echo exams, including views acquired with contrast. Use of the CNN in a routine clinical workflow could improve efficiency of quantification steps performed after image acquisition. This was tested on an independent dataset acquired in a different country to that used to train the model and was found to perform similarly thus indicating the generalisability of the model. Figure 1. Confusion matrices Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Ultromics Ltd.

Visual Confusion Matrices: Fact or Artifact?

1969 ◽  
Vol 71 (1) ◽  
pp. 111-125 ◽  
Author(s):  
Dennis F. Fisher ◽  
Richard A. Monty ◽  
Sam Glucksberg
Keyword(s):  
Confusion Matrices
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