### Table 4. Structural Equation Model of the Relationship Between Senior-Year Grades in Academic Courses and Employment in Grade 12

"... In PAGE 23: ... See the Appendix section for details about the specification and estimation of this model. In Table4 , we present the results of our model of the relationship between employment during high school and senior-year grades in academic courses.5 The table consists of three sections.... ..."

### Table 5: Times (minutes) for the text reading eval- uation.

2002

"... In PAGE 7: ... With the Shrink Wrap function, most users found it easy to read text by scrolling up and down. Times were reduced more than twice for all users ( Table5 ), with the exception of User 1. 8.... ..."

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### Table 5: Times (minutes) for the text reading eval- uation.

2002

"... In PAGE 7: ... With the Shrink Wrap function, most users found it easy to read text by scrolling up and down. Times were reduced more than twice for all users ( Table5 ), with the exception of User 1. 8.... ..."

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### Table 1: Percentage correct for each system SYSTEM SCORE

"... In PAGE 3: ...speaker distinction. There was a degree of variation on a per- system basis, as captured in Table1 . Additionally, as presented in Table 2, the number of words to determine that a text was human was nearly twice the closest system.... ..."

### Table 4: Average Number of Operations Per Character in English Text Searches few equality comparison operations on sequence elements|only about 1 per 100 elements for the longer patterns, no more than twice that for the shorter ones. They do access the elements substantially more often than that, in their respective skip loops, but still always sublinearly. With string matching, the comparisons and accesses are inexpensive, but in other applications of sequence matching they might cost substantially more than iterator or distance operations. In such applications the savings in execution time over SF or L could be even greater. For example, an appendix shows one experiment in which the text of Through the Looking Glass was stored as a sequence of words, each word being a character string, and the patterns were word sequences of di erent lengths chosen from evenly spaced positions in the target

1998

"... In PAGE 20: ... These counts are obtained without modifying the source code of the algorithms at all, by specializing their type parameters with classes whose operations have counters built into them. Table4 shows counts of data comparisons and other data accesses, iterator \big jumps quot; and other iterator operations, and distance oper- ations. In each case the counts are divided by the number of characters searched.... ..."

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### Table 3: Predicting the year, in the Address data set. L1 Error is the difference between predicted and true year. In the Accuracy column, we see that TOT predicts exactly the correct year nearly twice as often as LDA.

"... In PAGE 8: ... On the State-of-the-Union Address data set, we measure the ability to predict the year given the text of the address, as measured in accuracy, L1 error and average L1 distance to the correct year (number of years difference between pre- dicted and correct year). As shown in Table3 , TOT achieves double the accuracy of LDA, and provides an L1 relative er- ror reduction of 20%. 5.... ..."

### Table 1: Confusion matrix for the recognition results of 10 unoccluded views of each object.

"... In PAGE 4: ... The resolution of these views was 400 faces per view. Table1 shows the confusion matrix for our recognition results. Notice that there is only one false-positive i.... In PAGE 5: ... 5. Note that the recognition rate is 100% at zero occlusion because these tests were performed on a subsample of unoccluded views which were correctly recognized in Table1 . Fig.... In PAGE 5: ... After the addition of Gaussian noise with = 2:0cm. sample of noiseless views which were correctly recognized in Table1 . The recognition rate was 100% up to a noise with standard deviation of 2.... ..."

### Table 5.1: Basic functionality annotations for naming concept responsibilities

### Table 2 on page 5, do eliminate an occurrence of a point Y only if Y appears only one time in the geometric quantity (A,B,C and D must be di erent from Y ). If Y appears twice in S, this is not a problem because then the geometric quantity is zero, and so already eliminated by the simpli cation phase. But if Y appears twice in a ratio (for instance in AY BY ) this is a special case which needs to be treated apart. This is done in the implementation.

2004

"... In PAGE 3: ... Note that the de- pendency graph of the constructions must be cycle free. To eliminate a point from the goal we need to apply one of the elimination lem- mas shown on Table2 on page 5. This table can be read as follows: To eliminate a point Y , choose the line corresponding to the way Y has been constructed, and apply the formula given in the column corresponding to the geometric quantity in which Y is used.... In PAGE 4: ... We rst translate the goal (A0B0 k AB) into its equivalent using the signed area: SA0B0A = SA0B0B Then we eliminate compound points from the goal starting by the last point in the order of their construction. The geometric quantities containing an oc- currence of B0 are SA0B0B and SA0B0A, B0 has been constructed using the rst construction on Table2 with = 1 2: SA0B0A = SAA0B0 = 1 2SAA0A + 1 2SAA0C = 1 2SAA0C and SA0B0B = SBA0B0 = 1 2SBA0A + 1 2SBA0C The new goal is SAA0C = SBA0A + SBA0C Now we eliminate A0 using: SCAA0 = 1 2SCAB + 1 2SCAC = 1 2SCAB SABA0 = 1 2SABB + 1 2SABC = 1... In PAGE 5: ...Table2 . Elimination lemmas Construction Description Elimination formulas (Nondegeneracy condition) SABY = If AY k CD then AY CD = a0 a1 a2 Y P Q Take Y on line PQ such that PY PQ = .... In PAGE 11: ... This tactic (called eliminate_all) rst searches the con- text for a point which is not used to build another point (a leaf in the dependency graph). Then for each occurrence of the point in the goal, it applies the right lemma from Table2 by nding in the context how the point has been constructed and which geometric quantity it appears in. Finally it removes the hypotheses stating how the point has been constructed from the context.... ..."

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