--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/reference/ocr-new/status_messsage.cc Thu May 18 23:12:51 2006 +0200
@@ -0,0 +1,212 @@
+unknown mode: new
+.login: No such file or directory
+% ocrchie
+ocrchie
+
Done initializing new tcl commands
+Done initializing link variables
+Learning from train.tif and train.txt sych 0
+open succeeded on file train.tif. length = 300. width = 2400
+Extracting Components
+
+@@
+@
+Learning from 4.header.tif and 4.header.txt sych 1
+open succeeded on file 4.header.tif. length = 129. width = 1825
+Extracting Components
+
+Opening train.tif
+open succeeded on file train.tif. length = 300. width = 2400
+SCALE_FACTOR = 1.000000 Skip = 1.000000
+Starting deskew process: time = 0.000000
+Determining Line boundaries
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+abcdefghijklmnopqrstuvwxyz: ;\
+ABCDEFGHIJKLMNOPQRSTUVWXYZ
+0 1 234567890~ ! @#$%%^&* ()+=-,.<<>>/?'
+Error: Huh?Opening 4.col0.tif
+open succeeded on file 4.col0.tif. length = 2461. width = 877
+SCALE_FACTOR = 1.000000 Skip = 1.000000
+Starting deskew process: time = 0.000000
+Determining Line boundaries
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+dispersion and models of temporal price dis-
+persion. Most models of spatial price disper-
+sion, such as the Salop-Stiglitz model or the
+Wilde-Schwartz model, have equilibria with
+specific prices being charged with positive
+probability mass. The above argument shows
+that such strategies cannot be profit-max-
+iMzing Nash behavior in a temporal ran-
+domizing model.
+Since there are no point masses in the
+equilibrium density, the cumulative distribuM
+tion function will be a continuous function
+On (P*, T ). Let E(P ) be the cumuIative dis-
+tribution function for y( P ); thus y(P) =
+E^(P ) almost eveWhere.
+We can now construct the expected profit
+function for a representative store. When a
+store charges price P, exactIy two events are
+relevant. lt may be that P is the smallest
+price heing charged, in which case, the given
+store gets all of the informed customers.
+nis event happens only if all the other
+8tores charge prices higher than P, an event
+which has probability (l - F( P ))*- ' . On the
+other hand, there may be some store with a
+lower price, in which case the store in ques-
+tion only gets its share of the uninformed
+customers. This event happens with proba-
+bility l - (l - F( P))^ - '. (By Proposition 3
+we can neglect the prohahiIity of any ties.)
+Hence the expected profit of a representa-
+.
+tIve store Is
+/: ( N( P )( l - E( P ))^- '
+
++ @( P ) ( l - ( l - F( P ))^- ' ) 1/( P ) @
+where N( P ) =P( C+ I ) - C( C+ I )
+HI( P ) -P C- %( C )
+The maximization problem of the firm is
+to choose the density function y( P) so as to
+maximize expected profits su%ect to the
+constraInts:
+/V
+1( P ) ? 0 ; .y( P ) @ - l
+It is clear that all prices that are charged
+with positive density must yield the same
+Error: Huh?Opening hal4eqn.tif
+open succeeded on file hal4eqn.tif. length = 1349. width = 1753
+SCALE_FACTOR = 1.000000 Skip = 1.000000
+Starting deskew process: time = 0.000000
+Determining Line boundaries
+109.0 449.0 3 354 538
+109.0 449.0 0 61 89
+1622.0 719.0 4 641 780
+1622.0 719.0 3 354 538
+390.0 913.0 5 878 961
+390.0 913.0 4 641 780
+1450.0 919.0 5 878 961
+1450.0 919.0 5 878 961
+401.0 1108.0 6 1059 1154
+401.0 1108.0 5 878 961
+1095.0 1104.0 6 1059 1154
+1095.0 1104.0 6 1059 1154
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+we can neglect the probability ot any ties.)
+Hence the expected profit of a representa-
+tive store is
+/ P ^. ' ^ * ' ^ * ' ' - ^ ' ^ * * ^ - '
++ w 1 ( P ) ( l - ( l - E ( P ) ) ^ - ' ) ) y ( P ) d T
+where w S ( P ) - - P ( C + I ) - C ( C + I )
+E 1 ( P ) - - P G - C ( C )
+The maximization problem of the firm is
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+we can neglect the probability ot any ties.)
+Hence the expected profit of a representa-
+tive store is
+/ P ^. ' ^ * ' ^ * ' ' - ^ ' ^ * * ^ - '
++ w 1 ( P ) ( l - ( l - E ( P ) ) ^ - ' ) ) y ( P ) d T
+where w S ( P ) - - P ( C + I ) - C ( C + I )
+E 1 ( P ) - - P G - C ( C )
+The maximization problem of the firm is
+Calling interactive learn from Tcl
+Learning from recog.tmp and 1 sych 0
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+we can neglect the probability of any ties.)
+Hence the expected profit of a representa-
+tive store is
+<Int> P r* { <pi> s ( p ) ( 1 - F ( p ) ) n - 1
++ <pi> f ( p ) [ l - ( l - F ( P ) ) n - 1 ] } f ( p ) d p
+where <pi> s ( P ) = - P ( + + I ) - C ( + + I )
+<pi> f ( p ) = - U - c C ( ) )
+The maximization problem of the firm is
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+we can neglect the probability of any ties.)
+Hence the expected profit of a representa-
+tive store is
+<Int> P r* { <pi> s ( p ) ( 1 - F ( p ) ) n - 1
++ <pi> f ( p ) [ l - ( l - F ( P ) ) n - 1 ] } f ( p ) d p
+where <pi> s ( P ) = - P ( + + I ) - C ( + + I )
+<pi> f ( p ) = - U - c C ( ) )
+The maximization problem of the firm is
+436.9u 302.5s 14:08 87%
+% ocrchie
+ocrchie
+
Done initializing new tcl commands
+Done initializing link variables
+Learning from train.tif and train.txt sych 0
+open succeeded on file train.tif. length = 300. width = 2400
+Extracting Components
+
+@@
+@
+Learning from 4.header.tif and 4.header.txt sych 1
+open succeeded on file 4.header.tif. length = 129. width = 1825
+Extracting Components
+@ @
+Opening train.tif
+open succeeded on file train.tif. length = 300. width = 2400
+SCALE_FACTOR = 1.000000 Skip = 1.000000
+Starting deskew process: time = 0.000000
+Determining Line boundaries
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+Segmentation fault (core dumped)
+11.5u 4.7s 0:33 48%
+% Segmentation fault (core dumped)
+Segmentation fault (core dumped)
+
Badly placed ()'s.
+% rm core
+rm core
+
% run
+run
+
run: Command not found.
+% ocrchie
+ocrchie
+
Done initializing new tcl commands
+Done initializing link variables
+Learning from train.tif and train.txt sych 0
+open succeeded on file train.tif. length = 300. width = 2400
+Extracting Components
+
+@@
+@
+Learning from 4.header.tif and 4.header.txt sych 1
+open succeeded on file 4.header.tif. length = 129. width = 1825
+Extracting Components
+
+Opening int.tif
+open succeeded on file int.tif. length = 227. width = 277
+SCALE_FACTOR = 1.000000 Skip = 1.000000
+Starting deskew process: time = 0.000000
+Determining Line boundaries
+Calling recognize from Tcl
+Extracting Components
+Recognizing document
+/: ' ^
+Thank you for using OCRchie.
+16.0u 12.4s 0:35 81%
+% grep Extracting Components {*.cc *.tcl}
+grep Extracting Components {*.cc *.tcl}
+
Missing }.
+% grep Extracting Components *.cc
+grep Extracting Components *.cc
+
grep: can't open Components
+Page.cc: printf("Extracting Components\n");
+status_message.cc: set_string_status("Extracting Words", p, f);
+status_message.cc: set_string_status("Extracting Characters", p, f);
+%
\ No newline at end of file