Markov Basis for No-Three-Factor Interaction Models and Some Other Hierarchical Models

2012 ◽  
pp. 129-157
Author(s):  
Satoshi Aoki ◽  
Hisayuki Hara ◽  
Akimichi Takemura
Keyword(s):  
Hierarchical Models ◽  
Markov Basis ◽  
Interaction Models ◽  
Factor Interaction ◽  
Three Factor

Calculation of Chi-Square to Test the No Three-Factor Interaction Hypothesis

Biometrics ◽  
1959 ◽  
Vol 15 (1) ◽  
pp. 107 ◽  
Author(s):  
Marvin A. Kastenbaum ◽  
Donald E. Lamphiear
Keyword(s):  
Chi Square ◽  
Interaction Hypothesis ◽  
Factor Interaction ◽  
Three Factor

scholarly journals Evaluation of a Mathematical Model for Digital Image Enhancement

2015 ◽  
Vol 9 (1) ◽  
pp. 292-296
Author(s):  
Hassem Geha ◽  
Ibrahim Nasseh ◽  
Marcel Noujeim
Keyword(s):  
Mathematical Model ◽  
Digital Image ◽  
Histogram Equalization ◽  
Polynomial Model ◽  
The Other ◽  
Degree Polynomial ◽  
Significant Difference ◽  
Digital Image Enhancement ◽  
Factor Interaction ◽  
Three Factor

Objective : The purpose of this study is to compare the detected number of holes on a stepwedge on images resulting from the application of the 5th degree polynomial model compared to the images resulting from the application of linear enhancement. Material and Methods : A 10-step aluminum step wedge with holes randomly drilled on each step was exposed with three different kVp and five exposure times per kVp on a Schick33® sensor. The images were enhanced by brightness/contrast adjustment, histogram equalization and with the 5th degree polynomial model and compared to the original non-enhanced images by six observers in two separate readings. Results : There was no significant difference between the readers and between the first and second reading. There was a significant three-factor interaction among Method, Exposure time, and kVp in detecting holes. The overall pattern was: “Poly” results in the highest counts, “Original” in the lowest counts, with “B/C” and “Equalized” intermediate. Conclusion : The 5th degree polynomial model showed more holes when compared to the other modalities.

Increasing Visitor Engagement during Interpretive Walking Tours

2018 ◽  
Vol 23 (2) ◽  
pp. 31-48
Author(s):  
David Douglas ◽  
Gary Ellis ◽  
Andrew Lacanienta
Keyword(s):  
Interaction Effect ◽  
Question Type ◽  
Living History ◽  
First Person ◽  
Walking Tour ◽  
Heritage Site ◽  
Third Person ◽  
Factor Interaction ◽  
Three Factor ◽  
Walking Tours

This study examined the effect of living-history interpretation (i.e., first-person, third-person, no living history) and question type (i.e., relevant, dissonant, customary) on engagement of visitors during walking tours at a heritage site. One hundred seventy-six visitors participated in the study. Visitors completed a measure of engagement immediately following each of six stops during the walking tour. A measure of guest familiarity of the context of the site was also taken. Results from linear mixed-modeling revealed a three-factor interaction effect, familiarity by question type by living-history interpretation. Engagement of visitors is impacted by guest familiarity with the context, the living-history interpretation type, and the question type posed. Results might guide interpretation professionals in customizing interpretation experiences to stage more engaging interpretation experiences.

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