### Table 1. Distribution of Distances from Pfatchable Points to their

in Classifying and Comparing Spatial Relations of Computerized Maps for Feature Matching Applications

### Table 2. Local-Distance Values

2002

"... In PAGE 2: ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Table2 . Local-Distance Values 9 .... In PAGE 8: ... This equation is a sum of the products of the received and expected values on a bit-by-bit basis. Table2 expands this equation for several coding rates. (3) (4)... ..."

### Table XI: Local and Global Heuristic Distances

### Table 1. Average number of moves and local search time as a function of the RCL parameter .

"... In PAGE 7: ... Very often, many GRASP solutions are generated in the same amount of time required for the local optimization procedure to converge from a single random start. These results are illustrated in Table1 and Figure 8, for another instance of MAXSAT where 1000 iterations were run. For each value of ranging from 0 (purely random construction) to 1 (purely greedy construction), we give in Table 1 the average Hamming distance between each solution built at the end of the con- struction phase and the corresponding local optimum obtained after local search, the average number of moves from the rst to the latter, the local search time in seconds, and the total processing time in seconds.... ..."

### Table 1. Average number of moves and local search time as a function of the RCL parameter .

"... In PAGE 7: ... Very often, many GRASP solutions are generated in the same amount of time required for the local optimization procedure to converge from a single random start. These results are illustrated in Table1 and Figure 8, for another instance of MAXSAT where 1000 iterations were run. For each value of ranging from 0 (purely random construction) to 1 (purely greedy construction), we give in Table 1 the average Hamming distance between each solution built at the end of the con- struction phase and the corresponding local optimum obtained after local search, the average number of moves from the rst to the latter, the local search time in seconds, and the total processing time in seconds.... ..."

### Table 1 Distance weighting functions

2006

"... In PAGE 2: ...01), is added to the expression. Model (0) stands for simplest RBF kernel; this one does not account for the kernel this A variety of models has been tested for the diagonal function M( C1 )( Table1 ). The traditional Gaussian of Eq.... ..."

### Table 1. The abilities of distance functions.

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### Table 1. The abilities of distance functions.

Cited by 1

### Table 5C - 95th% Translog IQUAIDS

1996

"... In PAGE 32: ... All calculations for the IQUAIDS model presented in this section are for this restricted sample of regular observations. Table5 computes the mean, 5th percentile, and 95th percentile of the predicted local and long-distance expenditures as a result of each of the four price change scenarios for the translog and IQUAIDS models. The predicted expenditures at current prices for both models are included in the first row.... In PAGE 51: ... Table5 -- Predicted Telephone Expenditure for Observed Prices and Four Price Change Scenarios (January 1988 Dollars) Table 5A - Means Translog IQUAIDS Local Long-Distance Local Long-Distance Scenario Observed Prices 51.23 64.... In PAGE 51: ...Table 5 -- Predicted Telephone Expenditure for Observed Prices and Four Price Change Scenarios (January 1988 Dollars) Table5 A - Means Translog IQUAIDS Local Long-Distance Local Long-Distance Scenario Observed Prices 51.23 64.... In PAGE 51: ...26 L P -40% D Note: P = Price of local service, P = Price of long-distance service. LD Table5 B - 5th% Translog IQUAIDS Local Long-Distance Local Long-Distance Scenario Observed Prices 37.91 18.... ..."

Cited by 2