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By keyword To identify photos by keyword, set a variable to the first keyword item that has the name you want Then use whose keywords contains and that keyword to identify the photos Here s an example:

E w(t1 )w( )

set FamilyKey to item 1 of (every keyword whose name is "Family") add (every photo in album "Photos" whose keywords contains FamilyKey) to album "Family Snaps"

Rw (t1 , )h(t2 ) d Rw (t1 , t2 )h( ) d (442)

By dimensions To identify photos by dimensions, use a statement such as whose dimensions is equal to followed by a list of the dimensions for example, {320, 480} for portrait-orientation photos taken on an iPhone:

Second, we derive the expression for the autocorrelation of y,

add (every photo whose dimensions is equal to {320, 480}) to album "iPhone Photos"

Ry (t1 , t2 ) = =

h(t1 )

By rating To identify photos by rating, use a statement such as whose rating is and the rating you want For example, the following script adds all the five-star photos to a variable named all_the_best and then uses a repeat loop to assign 20 of the photos to the album Best Photos:

E w( )w( )

| 45

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tell application "iPhoto" set all_the_best to every photo whose rating is 5 repeat with myCounter from 1 to 20 add item myCounter of all_the_best to the album "Best Photos" end repeat end tell

h(t1 )Rwy ( , t2 )d h( )Rwy (t1 , t2 )d (443)

To remove a photo from an album, use the remove command and specify the photo For example, the following statement removes the first photo from the album named Best Photos:

Rwy ( ) = Ry ( ) =

remove the first photo of album "Best Photos"

(444) (445)

The Fourier transforms of eqns (444-445) provide the cross power spectral density of y and w and the power spectral density of y Swy (j ) Sy (j ) = Sw (j )H(j ) = H(j )Swy (j ) = H(j )Sw (j )H(j ) (446) (447) (448)

The only property of the keyword object that s not inherited from the standard item class is the name property, which is the string assigned to the keyword

In the single-input, single-output case where y and w are both scalar random variables, eqn (448) reduces to Sy (j ) = |H(j )|2 Sw (j ) (449)

To find out which keywords are assigned to a photo, use a get every keyword command for the appropriate photo object For example, the following statement returns every keyword assigned to the first photo:

Eqns (448) and (449) are useful for nding a linear system realization H(j ) appropriate for producing a given colored noise process y from a white noise input w Example 414 A linear system with transfer function 2 H(s) = +s

This statement returns a list such as {keyword "Europe" of application "iPhoto", keyword "Vacations" of application "iPhoto"}

of keratinocytes and increased turnover of the stratum corneum leads to apparently smoother skin144 Dermal effects include increased synthesis of collagen and glycosaminoglycans145 In one study it was reported that 4 weeks of treatment with 12% lactic acid ammonium lactate lotion resulted in a 19% increase in epidermal thickness and increased amounts of glycosoaminoglycans146 Additionally, Smith noted increase in epidermal skin rmness and thickness as well as increase in dermal rmness and thickness with application of 12% lactic acid Clinically, this resulted in reports of improved smoothness147 Indications for alpha hydroxy acids include mild photodamage, ne wrinkling, hyperkeratosis (ie, icthyosis, xerotic eczema), acne, and actinic keratosis

2 is excited by white noise w(t) with PSD de ned by Sw (j ) = w , where w , > 0 The spectral density of the output y is calculated by eqn (449) as

To apply a keyword to a photo, use the assign keyword command This command requires you to select the photo or photos first, which you can do by using the select method For example, the following statements select the first photo in the album Industrial Decay and assign the existing keyword Urban to it:

Sy (j ) = = =

select the first photo in album "Industrial Decay" assign keyword string "Countryside"

(450)

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