Factors affecting classification accuracy of attribute mastery in the rRUM and the DINA model

This paper proposes a method for classifying street lighting conditions after dark in order to share the collected data with the local community. Such information is important for the safety and security of residents, and can be used to discuss about anti-crime activities and nighttime route recommendations. However, it is difficult to ascertain the actual street lighting conditions because of insufficient street-lamp data and the effects of obstacles and other light sources. In order to tackle this problem, we propose a social approach by which local residents collaboratively collect street lighting conditions using their smartphones. The technology behind this approach is a classifier that places the street lighting conditions into one of three levels. It is based on three attributes that are calculated from the illuminance data collected by the smartphones. The results of experiments on 164 actual streets show a maximum classification accuracy of 88.4%. We also discuss performance differences between smartphones and the effect of walking speed during data collection, both of which are important factors affecting the classification accuracy.

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Factors Affecting the Classification Accuracy and Average Length of a Variable-Length Cognitive Diagnostic Computerized Test

Journal of Computerized Adaptive Testing ◽

10.7333/1802-060101 ◽

2018 ◽

Vol 6 (1) ◽

pp. 1-14 ◽

Cited By ~ 2

Author(s):

Alan Huebner ◽

Matthew Finkelman ◽

Alexander Weissman

Keyword(s):

Classification Accuracy ◽

Average Length ◽

Variable Length ◽

Factors Affecting

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Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100078614 ◽

1977 ◽

Vol 35 ◽

pp. 214-217

Author(s):

F. A. Heckman ◽

E. Redman ◽

J.E. Connolly

Keyword(s):

Image Analysis ◽

Image Quality ◽

Exposure Time ◽

Image Contrast ◽

Automated Image Analysis ◽

Practical Application ◽

Factors Affecting ◽

High Image Quality ◽

Qualitative Evidence ◽

Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

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