exposure

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exposure

1. Archit the position or outlook of a house, building, etc.; aspect
2. Mountaineering the degree to which a climb, etc. is exposed (see exposed (sense 4))
3. Photog
a. the act of exposing a photographic film or plate to light, X-rays, etc.
b. an area on a film or plate that has been exposed to light, etc.
c. (as modifier): exposure control
4. Photog
a. the intensity of light falling on a photographic film or plate multiplied by the time for which it is exposed
b. a combination of lens aperture and shutter speed used in taking a photograph

Exposure

The area on any roofing material that is left exposed to the elements.

Exposure

 

in photography, the quantity of illumination H (a photometric quantity), which serves as an evaluation of the surface density of the luminous energy Q. It determines the effect of optical radiation on the photographic material used.

In the general case, H = dQIdA = ∫Edt, where A is the illuminated area, E is the illuminance, and I is the duration of irradiation (exposure time). If E is a constant, then H = Et. In the SI system (seeINTERNATIONAL SYSTEM OF UNITS), exposure is expressed in lux-seconds (lx-s). Beyond the limits of the visible portion of the radiation spectrum, the quantity used is the energy exposure, which is the product of the irradiance and the duration of irradiation; it is expressed in joules per m2 (J/m2).

It is convenient to use the concept of exposure if the effect of radiation is cumulative over time (in photography as well as, for example, in photobiology). The concept is widely used in work with nonoptical and even corpuscular radiation, such as X rays and gamma rays (where the exposure is defined as the product of the surface density of the radiation flux and the duration (), as well as streams of electrons and other particles (where the exposure is equal to the product of the radiation dose rate and t). (See alsoSENSITOMETRY and CHARACTERISTIC CURVE.)

A. L. KARTUZHANSKH

exposure

[ik′spō·zhər]
(building construction)
The distance from the butt of one shingle to the butt of the shingle above it, or the amount of a shingle that is seen.
(graphic arts)
The act of permitting light to fall upon a photosensitive material.
(medicine)
The state of being open to some action or influence that may affect detrimentally, as cold, disease, or wetness.
(meteorology)
The general surroundings of a site, with special reference to its openness to winds and sunshine.
(nucleonics)
The total quantity of radiation at a given point, measured in air.
The cumulative amount of radiation exposure to which nuclear fuel has been subjected in a nuclear reactor; usually expressed in terms of the thermal energy produced by the reactor per ton of fuel initially present, as megawatt days per ton.

shake

A thick wood shingle, usually formed either by hand-splitting a short log into tapered radial sections or by sawing; usually attached in overlapping rows on wood sheathing, 1 as a covering for a roof or wall.

exposure

i. The total quantity of light received per unit area on a sensitized plate or film. It may be expressed as the product of the light intensity and the exposure time.
ii. The act of exposing a light-sensitive material to a light source.
iii. One individual picture of a strip of photographs, usually called a frame.

exposure

(1) The degree to which information can be accessed using authorized or unauthorized methods. See penetration test and risk analysis.

(2) In a camera, the amount of light that reaches the film (analog) or CCD or CMOS sensor (digital). The exposure is achieved by the sum of the shutter speed, aperture (f-stop) and ISO setting. See shutter speed, f-stop and ISO speed.
References in periodicals archive ?
Between-pollutant correlations of exposure error. The collinearity of exposure error was examined based on Pearson correlations between daily exposure error for local-local and regional-regional pollutant pairs (Figure 2B; see also Supplemental Material, Figure S3B, for local-regional pairs).
Variance of exposure error. For regional pollutants ([PM.sub.25], S[O.sub.4], and [O.sub.3]), variance across days of the normalized exposure error had very little spatial variability (i.e., box plots of the variance of normalized exposure error are narrow) and was < 0.20 for any type of error in any ZIP code (Figure 3A).
By compiling empirically determined parameters related to the between-pollutant relationships and their associated exposure error (Table 1), and utilizing Equation 3, we were able to quantify the potential attenuation of model coefficients in a bipollutant model.
Figure 4 presents the potential attenuation factors for single- and bipollutant epidemiologic models, based on empirical estimates of the relations hips between exposure metrics and their exposure error. The attenuation factors presented for bipollutant models were based on the assumption that one pollutant has a true effect on the health outcome and the other pollutant has no effect.
For comparison, the attenuation factors for a bipollutant model with one local (N[O.sub.x]) and one regional ([PM.sub.2.5]) pollutant are presented in Figure 4D, showing significant differences in the attenuation factor across types of exposure error but smaller differences between single- and bipollutant models.
An improved understanding of the degree of exposure error among pollutants and their dependent structure is needed to properly interpret results from epidemiologic models that include multiple pollutants.
where c is an attenuation factor between 0 and 1 given by c = var([x.sub.t]/|[var([x.sub.t]) + var([[Delta].sub.t])] where [[Delta].sub.t] = [z.sub.t] - [x.sub.t] is the exposure error. Again, a constant difference between the two exposure measures only changes the intercept.
To investigate the effects of exposure error in the log-linear regressions widely used to assess the pollutant-mortality association, consider the following model for an individual's risk of mortality:
We start with a personal risk model (Equation 5) and a decomposition of the exposure error (Equation 7) to obtain
Most exposure errors combine elements of each, but because the consequences on risk assessment of classical and Berkson errors differ, it is useful to consider each in turn.
In general, the effect of such exposure errors is intermediate between the two extreme models.
The first line of Table 1 refers to an example in which there is no correlation between [x.sub.1t] and [x.sub.2t] and there is equal variability of the two exposure errors [[Delta].sub.1t] and [[Delta].sub.2t], and these errors are not correlated; that is, the error in one predictor does not predict the error in the other.