scholarly journals Fluctuating environmental light limits number of surfaces visually recognizable by colour

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
David H. Foster

AbstractSmall changes in daylight in the environment can produce large changes in reflected light, even over short intervals of time. Do these changes limit the visual recognition of surfaces by their colour? To address this question, information-theoretic methods were used to estimate computationally the maximum number of surfaces in a sample that can be identified as the same after an interval. Scene data were taken from successive hyperspectral radiance images. With no illumination change, the average number of surfaces distinguishable by colour was of the order of 10,000. But with an illumination change, the average number still identifiable declined rapidly with change duration. In one condition, the number after two minutes was around 600, after 10 min around 200, and after an hour around 70. These limits on identification are much lower than with spectral changes in daylight. No recoding of the colour signal is likely to recover surface identity lost in this uncertain environment.

2010 ◽  
Vol 23 (6) ◽  
pp. 713-727 ◽  
Author(s):  
Robin A.A. Ince ◽  
Riccardo Senatore ◽  
Ehsan Arabzadeh ◽  
Fernando Montani ◽  
Mathew E. Diamond ◽  
...  

Author(s):  
Joanne Lee ◽  
Wendy K. Tam Cho ◽  
George Judge

This chapter examines and searches for evidence of fraud in two clinical data sets from a highly publicized case of scientific misconduct. In this case, data were falsified by Eric Poehlman, a faculty member at the University of Vermont, who pleaded guilty to fabricating more than a decade of data, some connected to federal grants from the National Institutes of Health. Poehlman had authored influential studies on many topics; including obesity, menopause, lipids, and aging. The chapter's classical Benford analysis along with a presentation of a more general class of Benford-like distributions highlights interesting insights into this and similar cases. In addition, this chapter demonstrates how information-theoretic methods and other data-adaptive methods are promising tools for generating benchmark distributions of first significant digits (FSDs) and examining data sets for departures from expectations.


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