Enhancement of DoD Related Research Through Acquisition of Impact Testing Equipment

1998 ◽  
Author(s):  
Samuel I. Ibekwe
Keyword(s):  
Impact Testing ◽  
Testing Equipment ◽  
Related Research

Disaster-Related Research and Consultation: Lessons Learned From Two Events

2011 ◽  
Author(s):  
Stephanie W. Campbell ◽  
A. Brooke Walters ◽  
Brandy J. Baczwaski ◽  
Stefan E. Schulenberg
Keyword(s):  
Lessons Learned ◽  
Related Research

Discussion on “Production testing equipment” at the Birmingham Section of the Institution

1932 ◽  
Vol 11 (1) ◽  
pp. 46
Author(s):  
R.H. Youngash ◽  
E.W. Field ◽  
I.H. Wright ◽  
J.H. Garnett ◽  
H.C. Armitage ◽  
...  
Keyword(s):  
Testing Equipment ◽  
Production Testing

Analysis of athletes’ stadium stress source based on improved layered K-means algorithm

2020 ◽  
Vol 39 (4) ◽  
pp. 5905-5914
Author(s):  
Chen Gong
Keyword(s):  
Experimental Data ◽  
Machine Learning Algorithms ◽  
User Preference ◽  
Experimental Comparison ◽  
Actual Situation ◽  
Medical Field ◽  
Pressure Source ◽  
Preference Model ◽  
Related Research ◽  
Analysis System

Most of the research on stressors is in the medical field, and there are few analysis of athletes’ stressors, so it can not provide reference for the analysis of athletes’ stressors. Based on this, this study combines machine learning algorithms to analyze the pressure source of athletes’ stadium. In terms of data collection, it is mainly obtained through questionnaire survey and interview form, and it is used as experimental data after passing the test. In order to improve the performance of the algorithm, this paper combines the known K-Means algorithm with the layering algorithm to form a new improved layered K-Means algorithm. At the same time, this paper analyzes the performance of the improved hierarchical K-Means algorithm through experimental comparison and compares the clustering results. In addition, the analysis system corresponding to the algorithm is constructed based on the actual situation, the algorithm is applied to practice, and the user preference model is constructed. Finally, this article helps athletes find stressors and find ways to reduce stressors through personalized recommendations. The research shows that the algorithm of this study is reliable and has certain practical effects and can provide theoretical reference for subsequent related research.

Educational Transformation through Online Learning: To Be or Not to Be

2010 ◽  
Vol 14 (4) ◽  
Author(s):  
Anthony G Picciano ◽  
Jeff Seaman ◽  
I. Elaine Allen
Keyword(s):  
Online Learning ◽  
Student Satisfaction ◽  
Instructional Quality ◽  
The United States ◽  
American Education ◽  
Institutional Mission ◽  
Educational Transformation ◽  
Related Research ◽  
Student Access ◽  
K 12

The purpose of this article is to examine online learning at the macro level in terms of its impact on American K-12 and higher education. The authors draw on six years of data that they have collected through national studies of online learning in American education as well as related research to do a critical and balanced analysis of the evolution of online learning in the United States and to speculate where it is going. Their collection of data represents some of the most extensive research examining online learning in the totality of K-20 education. Issues related to the growth of online learning, institutional mission, student access, faculty acceptance, instructional quality, and student satisfaction are explored. Of particular importance is an attempt to determine if online learning is in fact transforming American education in its essence and to speculate on the future.

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