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Tablei326:i32Summaryi32ofi32constrainti32andi32costi32effects
Table 4: Household Investment Equations (c dv , c do ,andi h )
1996
Tablei321:i32Thei32differenti32perspectivesi32oni32componentsi32andi32theiri32promises
TABLEi323.i32Parietali32Regioni32Asymmetryi32ini32Malei32Patientsi32With Schizophreniai32andi32Healthyi32Malei32Comparisoni32Subjects
Tablei32 1.i32 Class-by-classi32 andi32 overalli32 accuraciesi32 oni32 thei32 testi32 set,i32 usingi32 differenti32 typesi32 ofi32 SVMs,i32 andi32 numberi32 ofi32 support vectors.
Tablei323.i32Class-by-classi32andi32overalli32accuraciesi32oni32thei32testi32set,i32usingi32thei32besti32MLPi32andi32thei32besti32k-NNi32classifier.
TABLEi324.i32Volumei32Correlationsi32Betweeni32thei32Lefti32andi32Righti32In- feriori32Parietali32Lobulesi32andi32Frontali32Lobei32Structuresi32ini3215i32Male Patientsi32Withi32Schizophrenia
TABLEi325.i32Volumei32Correlationsi32Betweeni32thei32Lefti32andi32Righti32In- feriori32Parietali32Lobulesi32andi32Temporali32Lobei32Structuresi32ini3214 Malei32Patientsi32Withi32Schizophrenia
Table 1: SR performance of several path selection algorithms (homogeneous case). ANDI for each range in Table 1 is given by 2.49, 2.63, 2.23, 1.61, and 1.21, respectively. The number of 18
2000
"... In PAGE 18: ... The same network topology, link weights, and constraints were used in [7]. For di erent ranges of c1 and c2, Table1 shows the SR of various algorithms based on twenty 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 00 00 11 11 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 00 00 00 11 11 11 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 00000000000000000 00000000000000000 00000000000000000 00000000000000000 11111111111111111 11111111111111111 11111111111111111 11111111111111111 0000000000000 0000000000000 0000000000000 1111111111111 1111111111111 1111111111111 000 000 000 000 000 000 111 111 111 111 111 111 00 00 00 00 00 11 11 11 11 11 000 000 000 000 000 000 111 111 111 111 111 111 000 000 000 000 000 000 000 000 000 000 111 111 111 111 111 111 111 111 111 111 00 00 00 00 00 00 00 11 11 11 11 11 11 11 0000 0000 0000 0000 1111 1111 1111 1111 000 000 000 000 000 000 000 000 000 111 111 111 111 111 111 111 111 111 000 000 000 000 000 111 111 111 111 111 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 000000000 111111111 111111111 111111111 111111111 111111111 111111111 111111111 111111111 111111111 111111111 111111111 00000 11111 00000 00000 00000 00000 00000 00000 00000 00000 00000 00000 11111 11111 11111 11111 11111 11111 11111 11111 11111 11111 00000000 00000000 00000000 00000000 00000000 00000000 11111111 11111111 11111111 11111111 11111111 11111111 000000000 000000000 000000000 000000000 111111111 111111111 111111111 111111111 00 00 00 00 00 00 00 00 00 00 11 11 11 11 11 11 11 11 11 11 000000 000000 000000 000000 111111 111111 111111 111111 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 0000000000 1111111111 1111111111 1111111111 1111111111 1111111111 1111111111 1111111111 1111111111 1111111111 1111111111 000 000 000 000 000 000 000 111 111 111 111 111 111 111 1 2 3 4 5 6 7 9 13 14 16 17 15 12 10 18 19 20 11 8 26 31 32 30 28 29 25 27 24 22 23 21 Figure 12: An irregular network topology.... In PAGE 19: ... Since the rst constraint is now tighter than before, the SR values for all algorithms, including the exact one, are smaller. Nonetheless, the same previously observed relative performance trends among di erent algorithms in Table1 are also observed here. Note that by making one constraint much tighter than the other, the problem almost reduces to that of nding the shortest path w.... ..."
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