A STUDY ON QUANTIFICATION OF COMPONENT FACTORS TO EXPLAIN THE SOFTNESS OF LIGHT ON INDOOR DAYLIGHTING ENVIRONMENT OF A ROOM PASSING THROUGH WINDOWS : ANALYSIS OF LATENT VARIABLES GRADUAL CHANGE AND ANNOYANCE OF LIGHT

In this study, two latent variables were quantified to predict softness based on the evaluation structure of light softness derived in a previous study. First, we conducted subject evaluation experiments and luminance distribution measurements to discover physical indicators that were highly related to the five observed variables (brightness darkness boundary, brightness darkness contrast, glare, window surface luminosity, and flicker). Next, we examine ho w to quantify the latent variables from the observed variables. Finally, using latent variables quantified from physical indicators, we predicted the apparent softness of light from the evaluation structure and found that we could predict softness (R2=0.663).

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Journal
Journal of Environmental Engineering (Transactions of AIJ)
Published
2025-02-28
DOI
https://doi.org/10.3130/aije.90.129
Primary Topic
Visual perception and processing mechanisms
Type
article
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article

A STUDY ON QUANTIFICATION OF COMPONENT FACTORS TO EXPLAIN THE SOFTNESS OF LIGHT ON INDOOR DAYLIGHTING ENVIRONMENT OF A ROOM PASSING THROUGH WINDOWS : ANALYSIS OF LATENT VARIABLES GRADUAL CHANGE AND ANNOYANCE OF LIGHT

Nozomu Yoshizawa, Yukie SASAJIMA
1 links
Journal of Environmental Engineering (Transactions of AIJ)
Visual perception and processing mechanisms
article

A STUDY ON QUANTIFICATION OF COMPONENT FACTORS TO EXPLAIN THE SOFTNESS OF LIGHT ON INDOOR DAYLIGHTING ENVIRONMENT OF A ROOM PASSING THROUGH WINDOWS : ANALYSIS OF LATENT VARIABLES GRADUAL CHANGE AND ANNOYANCE OF LIGHT

Nozomu Yoshizawa, Yukie SASAJIMA
article en

Abstract

In this study, two latent variables were quantified to predict softness based on the evaluation structure of light softness derived in a previous study. First, we conducted subject evaluation experiments and luminance distribution measurements to discover physical indicators that were highly related to the five observed variables (brightness darkness boundary, brightness darkness contrast, glare, window surface luminosity, and flicker). Next, we examine ho w to quantify the latent variables from the observed variables. Finally, using latent variables quantified from physical indicators, we predicted the apparent softness of light from the evaluation structure and found that we could predict softness (R2=0.663).

Journal of Environmental Engineering (Transactions of AIJ)Vol. 90(829)
Tokyo University of Science (JP)
Sustainable cities and communities
Openalex Percentile: Top 96%
Visual perception and processing mechanisms
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