8 OR (a) A A 3 1 B 7 B (game theory) (a) (b) 8.1: 8.1(a) (b) strategic form game extensive form game 1
|
|
- ああす このえ
- 5 years ago
- Views:
Transcription
1 8 OR (a) A A 3 1 B 7 B (game theory) (a) (b) 8.1: 8.1(a) (b) strategic form game extensive form game 1
2 2 [5] player 2 1 noncooperative game 2 cooperative game ( ). A B A B B A 1, 1 8,, 8 4, 4 2 A B A B A B prisoners dilemma B A ( 1, 1) ( 8, 0) (0, 8) ( 4, 4) bimatrix 2 A B payoff payoff matrix A B 2 (a) A (b) B B B 1 8 A 1 < 0 A Λ Λ 8 < 4 0 4
3 Excel OR 8 3 A (a)b A A B A B A (b)a A B ( 4, 4) ( 1, 1) A B A, B =, Nash equilibrium A B A B B A B A, B =, A B 3 A, B =, () B F A I M B D5:E6 A K5:L6 B B5:B6 A B5 B6 =1-B5 D3:E3 B F5:F6 B A F5 =SUMPRODUCT(D5:E5,K$3:L$3) F6 D3 E3 B =K3 =L3 B3 A =SUMPRODUCT(B5:B6,F5:F6) B I5 I6 A =B5 =B6 K7:L7 A B K7 =SUMPRODUCT($I5:$I6,K5:K6) L7 I3 B =SUMPRODUCT(K3:L3,K7:L7) B5 0 K3 L3 0 1 A B J.F.Nash
4 4 8.2: A Excel B3 B5 GRG 2 B3 0-1 LP LP GRG 3. A B B 4. B5 1 K3, L A 5. 50%B5 K3 L best response strategy pure strategy 50% mixed strategy
5 Excel OR willingness to pay; WTPA WTP B 2 8.1(a) (a) A B B A A A B B 0 A (a) A A B A 1 A,B, 8.1: (a) (b) WTP B WTP (1, 1) (8, 0) A ( 1, 1) ( 1, 0) WTP B WTP (3, 1) (10 0) A ( 1, 3) ( 1, 0)
6 6 A B (b) (a) A A B (b) A B 8.1(a) (b) A B (a) A B (b) A B A B A B 8 4 W.S.Vickrey mechanism design Yahoo! second price auction max-min Excel 2
7 Excel OR () %, 40%, 20% Nash (0,0) (3,-3) (-6,6) (-3,3) (0,0) (6,-6) (6,-6) (-6,6) (0,0) zero-sum two-person game (p g, p c, p p ) (q g, q c, q p ) g c p p g q c ) p g + p c + p p = 1, p g, p c, p p 0; q g + q c + q p = 1, q g, q c, q p 0 2 (p g, p c, p p ) = ( 1 3, 1 3, 1 3 ) 1 3 (p g, p c, p p ) = (0, 1, 0) Π Π (p g, p p, p c q g, q p, q c ) = ( 0 q g +3 q c 6 q p )p g +( 3 q g +0 q c +6 q p )p c +( 6 q g 6 q c +0 q p )p c (q g, q c, q p ) (p g, p c, p p ) LP P (q g, q c, q p ) max p g,p c,p p Π (p g, p c, p p q g, q c, q p ) s.t. p g + p c + p p = 1, p g, p c, p p 0
8 8 (q g, q c, q p ) Π (p g, p c, p p ) (q g, q c, q p ) Π (p g, p c, p p ) LP P (p g, p c, p p ) max q g,q c,q p Π (q g, q c, q p p g, p c, p p ) s.t. q g + q c + q p = 1, q g, q c, q p 0 ((p g, p c, p p), (qg, qc, qp)) (p g, p c, p p) LP P (qg, qc, qp) (qg, qc, qp) LP P (p g, p c, p p) 1 ((p g, p c, p p), (q g, q c, q p)) (q g, q c, q p) ((p g, p c, p p), (q g, q c, q p)) Excel B G J N D5:F7 L5:N7 B5:B B8 =SUM(B5:B7) D3:F3 G5:G7 G5 =SUMPRODUCT(D5:F5,L$3:N$3) G6:G7 D3;F3 L3:N3 D3 =L3 M3:N3 B3 =SUMPRODUCT(B5:B6,F5:F6) J5:J7 A J5 =B5 J6:J7 L8:N8 L8 =SUMPRODUCT($J5:$J7,L5:L7) M9:N8 J3 =SUMPRODUCT(L3:N3,L8:N8) 2. (p g, p c, p p) = (q g, q c, q p) = (0, 1, 0) B5:B7 L3:N3 0,1,0 B3 J B3 B5:B7
9 Excel OR : Excel B8 = 1 GRG LP LP GRG (p g, p c, p p) = (q g, q c, q p) = ( 1 3, 1 3, 1 3 ) B5:B7 L3:N3 =1/ %,40%,20%(p g, p c, p p) = (q g, q c, q p) = (0.4, 0.4, 0.2)? B5:B7 L3:N3 0.4,0.4,0.2 40%,40%,20% %,40%,20% max-min max-min J.C.Harsanyi R.Selten Nash
10 ( ). A B A 2 B 5 A B 1 A 4 B 5 A B 2 q 1 q 2 q 3 q 4 q 5 q 6 q 7 q 8 q 9 q p 1 1 (0, 0) ( 2, 2) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) p 2 2 (2, 2) (0, 0) ( 2, 2) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) p 3 3 ( 1, 1) (2, 2) (0, 0) ( 2, 2) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) p 4 4 ( 1, 1) ( 1, 1) (2, 2) (0, 0) ( 2, 2) (1, 1) (1, 1) (1, 1) (1, 1) (1, 1) p 5 5 ( 1, 1) ( 1, 1) ( 1, 1) (2, 2) (0, 0) ( 2, 2) (1, 1) (1, 1) (1, 1) (1, 1) p 6 6 ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) (2, 2) (0, 0) ( 2, 2) (1, 1) (1, 1) (1, 1) p 7 7 ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) (2, 2) (0, 0) ( 2, 2) (1, 1) (1, 1) p 8 8 ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) (2, 2) (0, 0) ( 2, 2) (1, 1) p 9 9 ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) (2, 2) (0, 0) ( 2, 2) p ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) ( 1, 1) (2, 2) (0, 0) A k p k A (p 1,..., p 10 ) p p 10 = 1, p 1,..., p 10 0 p 2 = 1, p 1 = p 3 = = p 10 = 0 A 2?? B (q 1,..., q 10 ) q q 10 = 1, q 1,..., q 10 0 A Π A Π A (p 1,..., p 10, q 1,..., q 10 ) := (2p 2 p 3 p 4 p 10 )q 1 +( 2p 1 + 2p 3 p 4 p 10 )q 2 + +(p 1 + p p 8 2p 9 )q 10 B (q 1,..., q 10 ) A Π A (q 1,..., q 10 ) B A
11 Excel OR 8 11 (q 1,..., q 10 ) A max-min max-min strategy { { } } q q 10 = 1, p p 10 = 1, max min Π A (p 1,..., p 10, q 1,..., q 10 ) : : (p i) (q j) q j 0, j = 1,..., 10 p j 0, j = 1,..., 10 A min (qj) Π A (p 1,..., p 10, q 1,..., q 10 ) A Π A A B B A (p 1,..., p 10 ) Π A (p 1,..., p 10, q 1,..., q 10 ) (q 1,..., q 10 ) a 1 := 2p 2 p 3 p 4 p 10, a 2 := 2p 1 +2p 3 p 4 p 10,..., a 10 := p 1 +p 2 + +p 8 2p 9 min (q j) Π A (p 1,..., p 10, q 1,..., q 10 ) = min (q j) a 1 q a 10 q 10 s.t. q q 10 = 1 q 1,..., q 10 0 LP LP min{a 1,..., a 10 } (8.1) max (p i ) min{2p 2 p 3 p 4 p 10, 2p 1 + 2p 3 p 4 p 10,..., p 1 + p p 8 2p 9 } s LP (8.1) max s,(p i) s s.t. s 2p 2 p 3 p 4 p 10 s 2p 1 + 2p 3 p 4 p 10. s p 1 + p p 8 2p 9 p 1 + p p 10 = 1 p 1, p 2,..., p 10 0 Excel s 2 s +, s s = s + s, s +, s 0 max-min LP max s +,s,(p i ) s + s s.t. s + s 2p 2 p 3 p 4 p 8 p 9 p 10 s + s 2p 1 +2p 3 p 4 p 8 p 9 p s + s p 1 +p 2 +p 3 +p 4 + 2p 8 +2p 10 s + s p 1 +p 2 +p 3 +p 4 + +p 8 2p 9 p 1 +p 2 +p 3 +p 4 + +p 8 +p 9 +p 10 = 1 s +, s, p 1, p 2,..., p Excel LP(8.2) A max-min (8.2)
12 12 1. LP(8.2) 8.4 Excel B2:M2 s +, s, p 1, p 2,..., p 10 B3 =B2-C2 C3:C12 (8.2) C3 =SUMPRODUCT(D$2:M$2,D3:M3) C4:C12 N2 =SUM(D2:M2) p 1 + p p B3 B2:M2 C3:C12 >= B3 N2 = 1 LP (a) Excel (b) 8.4: max-min [1] 1 LP A maxmin B B max-min 2 max-min (p 1, p 2, p 3, p 4, p 5, p 6,..., p 10, s +, s ) = (0.0625, , 0.25, , , 0,..., 0, 0, 0) 0 max-min max-min ( ) maxmin ((p g, p c, p p), (q g, q c, q p)) = ((0.4, 0.4, 0.2), (0.4, 0.4, 0.2)) (p g, p c, p p ), (q g, q c, q p ) max-min { { } } q g + q c + q p = 1 p g + p c + p p = 1 max min Π (p i) (q j) (p g, p c, p p, q g, q c, q p ) : : q g, q c, q p 0 p g, p c, p p 0
13 Excel OR 8 13 LP max s +,s,(p i ) s.t. s + s s + s 3p c + 6p p s + s 3p g 6p p s + s 6p g + 6p c p g + p c + p p = 1 s +, s, p g, p c, p p 0 (p g, p c, p p ) = (0.4, 0.4, 0.2) max-min (q g, q c, q p ) = (0.4, 0.4, 0.2) min (PK ). PK or or or 6 or or 3 PK max-min (0,1 ) (1,0 ) (1,0 ) (0.3,0.7) (0.9,0.1) (0.9,0.1) (0.8,0.2) (0,1 ) (0.9,0.1) (0.8,0.2) (0.1,0.9) (0.9,0.1) (1,0 ) (1,0 ) (0,1 ) (0.8,0.2) (0.7,0.3) (0.6,0.4) max-min max-min max-min max-min PK
14 A B 2 B (1) (2) A (1) (4, 4) (0, 8) (2) (8, 0) (2, 2) (1) 2. (2) 3. - (1) 4.- (2) 5. (1) % 50%
15 Excel OR : (a) F3:G4 A K3:L4 B 6. B11:C210 U(0, 1) 8.5(b) (a) E C vs. 6 E 1 tt E11 1 F 6 F11 =IF($B11<0.5,1,2) 4. A G11 =INDEX($F$3:$G$4,E11,F11) B H11 =INDEX($K$3:$L$4,E11,F11) E11:H11 E12:H vs. 6 J M J 2 1 K M (a) (b) 2 8.5: vs O11 1 O12 =IF(P11=1,1,2) O13:O210 O12 P R 2 K N 11
16 vs T vs Y Y12 =IF(PRODUCT(Z$11:Z11)=1,1,2) Y12:210 PRODUCT( ) PRODUCT(Z$11:Z11) : AVERAGE 8.7:
17 Excel OR !? : 8.4 cooperative game
18 ε ( ) coalition characteristic function 3 L J I {L}{L,J} 3 x L, x J, x I 3 10 x L + x J + x I = 10 (8.3) 1 x J 0.8 x J < x L x L + x J x L 1.0 x J 0.8 x I 0.7 x L + x J x L + x I x J + x I S {L, J, I} (x L, x J, x I ) x j v(s) j S v S v(s) (x L, x J, x I ) x L + x J + x I = v({l, J, I}) (= 10) S {L, J, I} x j v(s) j S
19 Excel OR 8 19 (x L, x J, x I ) core : 3 v 8.8 ε- ε-core ε x L + x J + x I = v({l, J, I}) (= 10) C(ε) := (x L, x J, x I ) : S {L, J, I} ε + x j v(s) j S ε = 0 C(0) ε- ε C(ε) ε C(ε) ε C(ε) ε- least ε-core LP min. x,ε ε s.t. ε + j S x j v(s) S N j N x j = v(n) (8.4) N := {L, J, I} 3 LP min x max S v(s) x j : S N : x j = v(n) j S j N e(s) := v(s) j S x j S excess demand, regret x S S N LP 8.4 x N ε-
20 (a) Excel A S B v(s) D8:F8 x L, x J, x I G8 ε D2:G7 LP 2. C2:C8 LP(8.4) C2 =SUMPRODUCT(D$8:G$8,D2:G2) C3:C7 ε + j S x j C8 =SUM(D8:F8) j N x j 3. H2:H7 e(s) H2 =B2-C2+G$8 H3:H7 4. G8 D8:G8 B2:B7 <= C2:C7 B8 = C8 LP (a) Excel (b) 8.9: 5. (a), (b) S e(s)
21 Excel OR 8 21 (a) ε- L J I (b) S L J I LJ JI IL e(s) ε (4 ). T Y K A Jay-G J 4 S v(s) S v(s) S v(s) S v(s) T 0 Y 3 A 1 J 0.5 T,Y 4 T,A 1.5 T,J 5 Y,A 2 Y,J 2.5 A,J 3 T,Y,A 7 T,Y,J 8 T,A,J 8.5 Y,A,J 6 T,Y,A,J 10 T, Y, A, J x T, x Y, x A, x J ε- LP min. x,ε ε s.t. ε + x T 0.0 (= v({t})) ε + x Y 3.0 (= v({y})) ε + x A 1.0 (= v({a})) ε + x J 0.5 (= v({j})) ε + x T + x Y 4.0 (= v({t, Y})) ε + x T + x A 1.5 (= v({t, A})) ε + x T + x J 5.0 (= v({t, J})) ε + x Y + x A 2.0 (= v({y, A})) ε + x Y + x J 2.5 (= v({y, J})) ε + x A + x J 3.0 (= v({a, J})) ε + x T + x Y + x A 7.0 (= v({t, Y, A})) ε + x T + x Y + x J 8.0 (= v({t, Y, J})) ε + x T + x A + x J 8.5 (= v({t, A, J})) ε + x Y + x A + x J 6.0 (= v({y, A, J})) x T + x Y + x A + x J = 10.0 (= v({t, Y, A, J})) ε- (x T, x Y, x A, x J ) = (4.75, 2.25, 0.25, 2.75) 0.75 H ε-
22 ( ). Akiko Bob Cecile A 3,500 B 5,000 C 10,000 A,B 8,000 B,C 12,000 C,A 12,000 A,B,C 14,000 ε- A, B 2 {A,B} v({a, B}) A B 3, 500+5, 000 = 8, , S v(s) S v(s) S v(s) A 0 B 0 C 0 A,B 500 B,C 3000 C,A 1500 A,B,C x A, x B, x C ε- LP min. x,ε ε s.t. ε + x A 0 ε + x B 0 ε + x C 0 ε + x A + x B 500 ε + x B + x C 3000 ε + x A + x C 1500 x A + x B + x C = (x A, x B, x C ) = (750, 750, 3000) A 2750 B 4250 C 7000
23 Excel OR 8 23 Shapley Shapley Shapley value Shapley L J I 3 L J I3 {L, I, J} {L} {L, I} {L, I, J} L = 1.0 J = 0.8 I = 8.2 I L J S {I} {L, I} {L, I, J} +I +L +J v(s) v(s) ! = = 6 n n! L J I L J I L I J J L I J I L I L J I J L Shapley
24 24 Shapley Shapley 3 99 A B C Shapley A, B A B C Shapley-Shubik A B C A B C A C B B A C B C A C A B C B A Shapley-Shubik
25 [1] M. I [2] [3], [4] [5] [6] Vol.54, pp ,
PSCHG000.PS
a b c a ac bc ab bc a b c a c a b bc a b c a ac bc ab bc a b c a ac bc ab bc a b c a ac bc ab bc de df d d d d df d d d d d d d a a b c a b b a b c a b c b a a a a b a b a
More information取扱説明書 [F-02F]
F-02F 4. 2 3 4 5 6 7 8 9 0 2 3 4 5 6 7 8 a b c d a b c d a b cd 9 e a b c d e 20 2 22 ab a b 23 a b 24 c d e 25 26 o a b c p q r s t u v w d h i j k l e f g d m n a b c d e f g h i j k l m n x 27 o
More information2 Excel =sum( ) =average( ) B15:D20 : $E$26 E26 $ =A26*$E$26 $ $E26 E$26 E$26 $G34 $ E26 F4
1234567 0.1234567 = 2 3 =2+3 =2-3 =2*3 =2/3 =2^3 1:^, 2:*/, 3:+- () =2+3*4 =(2+3)*4 =3*2^2 =(3*2)^2 =(3+6)^0.5 A12 =A12+B12 ( ) ( )0.4 ( 100)0.9 % 1 2 Excel =sum( ) =average( ) B15:D20 : $E$26 E26 $ =A26*$E$26
More informationTaro10-名張1審無罪判決.PDF
-------------------------------------------------------------------------------- -------------------------------------------------------------------------------- -1- 39 12 23 36 4 11 36 47 15 5 13 14318-2-
More information1 1 2 (game theory)
11 6 1 1 2 (game theory) 1 2.1........................................ 1 2.2...................................... 3 3 2 3 3.1........................................ 3 3.2...................................
More informationExcel97関数編
Excel97 SUM Microsoft Excel 97... 1... 1... 1... 2... 3... 3... 4... 5... 6... 6... 7 SUM... 8... 11 Microsoft Excel 97 AVERAGE MIN MAX SUM IF 2 RANK TODAY ROUND COUNT INT VLOOKUP 1/15 Excel A B C A B
More informationkoji07-01.dvi
2007 I II III 1, 2, 3, 4, 5, 6, 7 5 10 19 (!) 1938 70 21? 1 1 2 1 2 2 1! 4, 5 1? 50 1 2 1 1 2 2 1?? 2 1 1, 2 1, 2 1, 2, 3,... 3 1, 2 1, 3? 2 1 3 1 2 1 1, 2 2, 3? 2 1 3 2 3 2 k,l m, n k,l m, n kn > ml...?
More information0226_ぱどMD表1-ol前
No. MEDIA DATA 0 B O O K 00-090-0 0 000900 000 00 00 00 0000 0900 000900 AREA MAP 0,000 0,000 0,000 0,000 00,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 0,000 00,000 0,000
More information31 33
17 3 31 33 36 38 42 45 47 50 52 54 57 60 74 80 82 88 89 92 98 101 104 106 94 1 252 37 1 2 2 1 252 38 1 15 3 16 6 24 17 2 10 252 29 15 21 20 15 4 15 467,555 14 11 25 15 1 6 15 5 ( ) 41 2 634 640 1 5 252
More informationuntitled
0. =. =. (999). 3(983). (980). (985). (966). 3. := :=. A A. A A. := := 4 5 A B A B A B. A = B A B A B B A. A B A B, A B, B. AP { A, P } = { : A, P } = { A P }. A = {0, }, A, {0, }, {0}, {}, A {0}, {}.
More information2002.N.x.h.L.......g9/20
1 2 3 4 5 6 1 2 3 4 5 8 9 1 11 11 12 13 k 14 l 16 m 17 n 18 o 19 k 2 l 2 m 21 n 21 o 22 p 23 q 23 r 24 24 25 26 27 28 k 28 l 29 m 29 3 31 34 42 44 1, 8, 6, 4, 2, 1,2 1, 8 6 4 2 1, 8, 6, 4, 2, 1,2 1, 8
More information76 3 B m n AB P m n AP : PB = m : n A P B P AB m : n m < n n AB Q Q m A B AQ : QB = m : n (m n) m > n m n Q AB m : n A B Q P AB Q AB 3. 3 A(1) B(3) C(
3 3.1 3.1.1 1 1 A P a 1 a P a P P(a) a P(a) a P(a) a a 0 a = a a < 0 a = a a < b a > b A a b a B b B b a b A a 3.1 A() B(5) AB = 5 = 3 A(3) B(1) AB = 3 1 = A(a) B(b) AB AB = b a 3.1 (1) A(6) B(1) () A(
More informationLINEAR ALGEBRA I Hiroshi SUZUKI Department of Mathematics International Christian University
LINEAR ALGEBRA I Hiroshi SUZUKI Department of Mathematics International Christian University 2002 2 2 2 2 22 2 3 3 3 3 3 4 4 5 5 6 6 7 7 8 8 9 Cramer 9 0 0 E-mail:hsuzuki@icuacjp 0 3x + y + 2z 4 x + y
More information1. 2 P 2 (x, y) 2 x y (0, 0) R 2 = {(x, y) x, y R} x, y R P = (x, y) O = (0, 0) OP ( ) OP x x, y y ( ) x v = y ( ) x 2 1 v = P = (x, y) y ( x y ) 2 (x
. P (, (0, 0 R {(,, R}, R P (, O (0, 0 OP OP, v v P (, ( (, (, { R, R} v (, (, (,, z 3 w z R 3,, z R z n R n.,..., n R n n w, t w ( z z Ke Words:. A P 3 0 B P 0 a. A P b B P 3. A π/90 B a + b c π/ 3. +
More information1. 2. 3. 2 (90, 90) (86, 92) (92, 86) (88, 88) Figure 1 Exam or presentation? a (players) k N = (1, 2,..., k) 2 k = 2 b (strategies) i S i, i = 1, 2 1
2014 11 in progress 1 1 2 2 2.1................................... 2 2.2........................................ 4 3 Nash Equilibrium 6 3.1........................................ 6 3.2..........................................
More information70 : 20 : A B (20 ) (30 ) 50 1
70 : 0 : A B (0 ) (30 ) 50 1 1 4 1.1................................................ 5 1. A............................................... 6 1.3 B............................................... 7 8.1 A...............................................
More information欧州特許庁米国特許商標庁との共通特許分類 CPC (Cooperative Patent Classification) 日本パテントデータサービス ( 株 ) 国際部 2019 年 1 月 17 日 CPC 版のプレ リリースが公開されました 原文及び詳細はCPCホームページの C
欧州特許庁米国特許商標庁との共通特許分類 CPC (Cooperative Patent Classification) 日本パテントデータサービス ( 株 ) 国際部 2019 年 1 月 17 日 CPC 2019.02 版のプレ リリースが公開されました 原文及び詳細はCPCホームページの CPC Revisions(CPCの改訂 ) 内のPre-releaseをご覧ください http://www.cooperativepatentclassification.org/cpcrevisions/prereleases.html
More information) 9 81
4 4.0 2000 ) 9 81 10 4.1 natural numbers 1, 2, 3, 4, 4.2, 3, 2, 1, 0, 1, 2, 3, integral numbers integers 1, 2, 3,, 3, 2, 1 1 4.3 4.3.1 ( ) m, n m 0 n m 82 rational numbers m 1 ( ) 3 = 3 1 4.3.2 3 5 = 2
More informationMicrosoft Word - 倫理 第40,43,45,46講 テキスト.docx
6 538 ( 552 ) (1) () (2) () ( )( ) 1 vs () (1) (2) () () () ) ()() (3) () ( () 2 () () () ()( ) () (7) (8) () 3 4 5 abc b c 6 a (a) b b ()() 7 c (c) ()() 8 9 10 () 1 ()()() 2 () 3 1 1052 1051 () 1053 11
More information00 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.... 0........ 0 0 0 0 0 0 0 0 0 0..0..........0 0 0 0 0 0 0 0 0 0 0.... 0........ 0 0 0 0 0 0 0 0 0 0... 0...... 0... 0 0 0 0 0 0..0 0... 0 0 0 0 0.0.....0.
More information6.1号4c-03
6.1 0 1 1 1 1 BF 1 C DB C 1* F E C 1 F 1 E C 1 E D 1 D 1 BF C G 1 DF 1 E 1 BF 1 BF 1 BF 1 BG 1 BG 1 BG 1 BF 1 BG 1 E 1 D F BF 1 BF 1 F 1 BF 1 F C 1 d 0 1 A 0 1 14 A G 0 1 A 1 G 0 1 1 1 E A 01 B 1 1 1 1
More information140 120 100 80 60 40 20 0 115 107 102 99 95 97 95 97 98 100 64 72 37 60 50 53 50 36 32 18 H18 H19 H20 H21 H22 H23 H24 H25 H26 H27 1 100 () 80 60 40 20 0 1 19 16 10 11 6 8 9 5 10 35 76 83 73 68 46 44 H11
More information取扱説明書 -詳細版- 液晶プロジェクター CP-AW3019WNJ
B A C D E F K I M L J H G N O Q P Y CB/PB CR/PR COMPONENT VIDEO OUT RS-232C LAN RS-232C LAN LAN BE EF 03 06 00 2A D3 01 00 00 60 00 00 BE EF 03 06 00 BA D2 01 00 00 60 01 00 BE EF 03 06 00 19 D3 02 00
More information151021slide.dvi
: Mac I 1 ( 5 Windows (Mac Excel : Excel 2007 9 10 1 4 http://asakura.co.jp/ books/isbn/978-4-254-12172-8/ (1 1 9 1/29 (,,... (,,,... (,,, (3 3/29 (, (F7, Ctrl + i, (Shift +, Shift + Ctrl (, a i (, Enter,
More information熊本県数学問題正解
00 y O x Typed by L A TEX ε ( ) (00 ) 5 4 4 ( ) http://www.ocn.ne.jp/ oboetene/plan/. ( ) (009 ) ( ).. http://www.ocn.ne.jp/ oboetene/plan/eng.html 8 i i..................................... ( )0... (
More informationuntitled
Excel A D-2 B-2 D-2 B2 C-2 D-2 C2-23 - Enter D-2 B2(1000) C2(5) 5000 D-2 (D-2) (D-2) (D-3) (D-6) - 24 - (D-3) (D-6) D (D-2) =B2*C2 (D-3) =B3*C3 (D-4) =B4*C4 Excel - 25 - $A$1 1000 A-1 (B-1) =$A$1 (B-1)
More informationOR 2 Excel 2 3.. 4. OK. 1a: Excel2007 Office. Excel2003 1.. 1b. 2.. 3. OK. 2.,,. ツール アドイン 1b: Excel2003 :,.,.,.,,,.,,. 1. Excel2003.
OR 2 Excel 1 2 2.1 Excel.,. 2.2, x mathematical programming optimization problem, OR 1., 1 : f(x) h i (x) = 0, i = 1,..., m, g j (x) 0, j = 1,..., l, f(x) h i (x) = 0, i = 1,..., m, g j (x) 0, j = 1,...,
More information(1) θ a = 5(cm) θ c = 4(cm) b = 3(cm) (2) ABC A A BC AD 10cm BC B D C 99 (1) A B 10m O AOB 37 sin 37 = cos 37 = tan 37
4. 98 () θ a = 5(cm) θ c = 4(cm) b = (cm) () D 0cm 0 60 D 99 () 0m O O 7 sin 7 = 0.60 cos 7 = 0.799 tan 7 = 0.754 () xkm km R km 00 () θ cos θ = sin θ = () θ sin θ = 4 tan θ = () 0 < x < 90 tan x = 4 sin
More informationr d 2r d l d (a) (b) (c) 1: I(x,t) I(x+ x,t) I(0,t) I(l,t) V in V(x,t) V(x+ x,t) V(0,t) l V(l,t) 2: 0 x x+ x 3: V in 3 V in x V (x, t) I(x, t
1 1 2 2 2r d 2r d l d (a) (b) (c) 1: I(x,t) I(x+ x,t) I(0,t) I(l,t) V in V(x,t) V(x+ x,t) V(0,t) l V(l,t) 2: 0 x x+ x 3: V in 3 V in x V (x, t) I(x, t) V (x, t) I(x, t) V in x t 3 4 1 L R 2 C G L 0 R 0
More informationall.dvi
5,, Euclid.,..,... Euclid,.,.,, e i (i =,, ). 6 x a x e e e x.:,,. a,,. a a = a e + a e + a e = {e, e, e } a (.) = a i e i = a i e i (.) i= {a,a,a } T ( T ),.,,,,. (.),.,...,,. a 0 0 a = a 0 + a + a 0
More informationall.dvi
38 5 Cauchy.,,,,., σ.,, 3,,. 5.1 Cauchy (a) (b) (a) (b) 5.1: 5.1. Cauchy 39 F Q Newton F F F Q F Q 5.2: n n ds df n ( 5.1). df n n df(n) df n, t n. t n = df n (5.1) ds 40 5 Cauchy t l n mds df n 5.3: t
More information0 = m 2p 1 p = 1/2 p y = 1 m = 1 2 d ( + 1)2 d ( + 1) 2 = d d ( + 1)2 = = 2( + 1) 2 g() 2 f() f() = [g()] 2 = g()g() f f () = [g()g()]
8. 2 1 2 1 2 ma,y u(, y) s.t. p + p y y = m u y y p p y y m u(, y) = y p + p y y = m y ( ) 1 y = (m p ) p y = m p y p p y 2 0 m/p U U() = m p y p p y 2 2 du() d = m p y 2p p y 1 0 = m 2p 1 p = 1/2 p y
More information行列代数2010A
a ij i j 1) i +j i, j) ij ij 1 j a i1 a ij a i a 1 a j a ij 1) i +j 1,j 1,j +1 a i1,1 a i1,j 1 a i1,j +1 a i1, a i +1,1 a i +1.j 1 a i +1,j +1 a i +1, a 1 a,j 1 a,j +1 a, ij i j 1,j 1,j +1 ij 1) i +j a
More informationuntitled
c 645 2 1. GM 1959 Lindsey [1] 1960 Howard [2] Howard 1 25 (Markov Decision Process) 3 3 2 3 +1=25 9 Bellman [3] 1 Bellman 1 k 980 8576 27 1 015 0055 84 4 1977 D Esopo and Lefkowitz [4] 1 (SI) Cover and
More information1/68 A. 電気所 ( 発電所, 変電所, 配電塔 ) における変圧器の空き容量一覧 平成 31 年 3 月 6 日現在 < 留意事項 > (1) 空容量は目安であり 系統接続の前には 接続検討のお申込みによる詳細検討が必要となります その結果 空容量が変更となる場合があります (2) 特に記載
1/68 A. 電気所 ( 発電所, 変電所, 配電塔 ) における変圧器の空き容量一覧 平成 31 年 3 月 6 日現在 < 留意事項 > (1) 空容量は目安であり 系統接続の前には 接続検討のお申込みによる詳細検討が必要となります その結果 空容量が変更となる場合があります (2) 特に記載のない限り 熱容量を考慮した空き容量を記載しております その他の要因 ( 電圧や系統安定度など ) で連系制約が発生する場合があります
More informationP.1P.3 P.4P.7 P.8P.12 P.13P.25 P.26P.32 P.33
: : P.1P.3 P.4P.7 P.8P.12 P.13P.25 P.26P.32 P.33 27 26 10 26 10 25 10 0.7% 331 % 26 10 25 10 287,018 280,446 6,572 30,236 32,708 2,472 317,254 313,154 4,100 172,724 168,173 4,551 6,420 6,579 159 179,144
More information合併後の交付税について
(1) (2) 1 0.9 0.7 0.5 0.3 0.1 2 3 (1) (a), 4 (b) (a), (c) (a) 0.9 0.7 0.5 0.3 0.1 (b) (d),(e) (f) (g) (h) (a) (i) (g) (h) (j) (i) 5 (2) 6 (3) (A) (B) (A)+(B) n 1,000 1,000 2,000 n+1 970 970 1,940 3.0%
More information1009.\1.\4.ai
- 1 - E O O O O O O - 2 - E O O O - 3 - O N N N N N N N N N N N N N N N N N N N N N N N E e N N N N N N N N N N N N N N N N N N N N N N N D O O O - 4 - O O O O O O O O N N N N N N N N N N N N N N N N N
More information(1) (2) 27 7 15 (1) (2), E-mail: bessho@econ.keio.ac.jp 1 2 1.1......................................... 2 1.2............................... 2 1.3............................... 3 1.4............................
More information2/50 Auction: Theory and Practice 3 / 50 (WTO) 10 SDR ,600 Auction: Theory and Practice 4 / 50 2
stakagi@econ.hokudai.ac.jp June 24, 2011 2.... 3... 4... 7 8... 9.... 10... 11... 12 IPV 13 SPSB... 15 SPSB.... 17 SPSB.... 19 FPSB... 20 FPSB.... 22 FPSB.... 23... 24 Low Price Auction.... 27 APV 29...
More informations s U s L e A = P A l l + dl dε = dl l l
P (ε) A o B s= P A s B o Y l o s Y l e = l l 0.% o 0. s e s B 1 s (e) s Y s s U s L e A = P A l l + dl dε = dl l l ε = dε = l dl o + l lo l = log l o + l =log(1+ e) l o Β F Α E YA C Ο D ε YF B YA A YA
More information29
9 .,,, 3 () C k k C k C + C + C + + C 8 + C 9 + C k C + C + C + C 3 + C 4 + C 5 + + 45 + + + 5 + + 9 + 4 + 4 + 5 4 C k k k ( + ) 4 C k k ( k) 3 n( ) n n n ( ) n ( ) n 3 ( ) 3 3 3 n 4 ( ) 4 4 4 ( ) n n
More information(2 X Poisso P (λ ϕ X (t = E[e itx ] = k= itk λk e k! e λ = (e it λ k e λ = e eitλ e λ = e λ(eit 1. k! k= 6.7 X N(, 1 ϕ X (t = e 1 2 t2 : Cauchy ϕ X (t
6 6.1 6.1 (1 Z ( X = e Z, Y = Im Z ( Z = X + iy, i = 1 (2 Z E[ e Z ] < E[ Im Z ] < Z E[Z] = E[e Z] + ie[im Z] 6.2 Z E[Z] E[ Z ] : E[ Z ] < e Z Z, Im Z Z E[Z] α = E[Z], Z = Z Z 1 {Z } E[Z] = α = α [ α ]
More information福岡大学人文論叢47-3
679 pp. 1 680 2 681 pp. 3 682 4 683 5 684 pp. 6 685 7 686 8 687 9 688 pp. b 10 689 11 690 12 691 13 692 pp. 14 693 15 694 a b 16 695 a b 17 696 a 18 697 B 19 698 A B B B A B B A A 20 699 pp. 21 700 pp.
More information1 (1) vs. (2) (2) (a)(c) (a) (b) (c) 31 2 (a) (b) (c) LENCHAR
() 601 1 () 265 OK 36.11.16 20 604 266 601 30.4.5 (1) 91621 3037 (2) 20-12.2 20-13 (3) ex. 2540-64 - LENCHAR 1 (1) vs. (2) (2) 605 50.2.13 41.4.27 10 10 40.3.17 (a)(c) 2 1 10 (a) (b) (c) 31 2 (a) (b) (c)
More informationHITACHI 液晶プロジェクター CP-EX301NJ/CP-EW301NJ 取扱説明書 -詳細版- 【技術情報編】 日本語
A B C D E F G H I 1 3 5 7 9 11 13 15 17 19 2 4 6 8 10 12 14 16 18 K L J Y CB/PB CR/PR COMPONENT VIDEO OUT RS-232C RS-232C RS-232C Cable (cross) LAN cable (CAT-5 or greater) LAN LAN LAN LAN RS-232C BE
More information(, Goo Ishikawa, Go-o Ishikawa) ( ) 1
(, Goo Ishikawa, Go-o Ishikawa) ( ) 1 ( ) ( ) ( ) G7( ) ( ) ( ) () ( ) BD = 1 DC CE EA AF FB 0 0 BD DC CE EA AF FB =1 ( ) 2 (geometry) ( ) ( ) 3 (?) (Topology) ( ) DNA ( ) 4 ( ) ( ) 5 ( ) H. 1 : 1+ 5 2
More information1990 IMO 1990/1/15 1:00-4:00 1 N N N 1, N 1 N 2, N 2 N 3 N 3 2 x x + 52 = 3 x x , A, B, C 3,, A B, C 2,,,, 7, A, B, C
0 9 (1990 1999 ) 10 (2000 ) 1900 1994 1995 1999 2 SAT ACT 1 1990 IMO 1990/1/15 1:00-4:00 1 N 1990 9 N N 1, N 1 N 2, N 2 N 3 N 3 2 x 2 + 25x + 52 = 3 x 2 + 25x + 80 3 2, 3 0 4 A, B, C 3,, A B, C 2,,,, 7,
More information0 (18) /12/13 (19) n Z (n Z ) 5 30 (5 30 ) (mod 5) (20) ( ) (12, 8) = 4
0 http://homepage3.nifty.com/yakuikei (18) 1 99 3 2014/12/13 (19) 1 100 3 n Z (n Z ) 5 30 (5 30 ) 37 22 (mod 5) (20) 201 300 3 (37 22 5 ) (12, 8) = 4 (21) 16! 2 (12 8 4) (22) (3 n )! 3 (23) 100! 0 1 (1)
More information.5 z = a + b + c n.6 = a sin t y = b cos t dy d a e e b e + e c e e e + e 3 s36 3 a + y = a, b > b 3 s363.7 y = + 3 y = + 3 s364.8 cos a 3 s365.9 y =,
[ ] IC. r, θ r, θ π, y y = 3 3 = r cos θ r sin θ D D = {, y ; y }, y D r, θ ep y yddy D D 9 s96. d y dt + 3dy + y = cos t dt t = y = e π + e π +. t = π y =.9 s6.3 d y d + dy d + y = y =, dy d = 3 a, b
More informationベンチャーと戦略ゲーム
2015 5 23 ( ) M&A IPO 2018 1. 60 (John von Neumann) (John F. Nash, Jr.) (Oskar Morgenstern) Theory of games and economic behavior 1) strategic-form game extensive-form game normal-form game non-cooperative
More information1 Excel 1. [Standard] (call [Call Standard]) Excel [ ] [E ] Excel m 1 ( ) (
1 Excel 1. [Standard] (call [Call Standard]) Excel [] [E ] Excel 2. 2 2.1 50m 1 ( ) 30 1. 2019 (http://news.fukuoka-edu.ac.jp/form/guide/navi2019.pdf), p.7 8 2. Excel 2019 4 Excel 2019 Excel 2013 [] [R]
More informationiii 1 1 1 1................................ 1 2.......................... 3 3.............................. 5 4................................ 7 5................................ 9 6............................
More information, 1. x 2 1 = (x 1)(x + 1) x 3 1 = (x 1)(x 2 + x + 1). a 2 b 2 = (a b)(a + b) a 3 b 3 = (a b)(a 2 + ab + b 2 ) 2 2, 2.. x a b b 2. b {( 2 a } b )2 1 =
x n 1 1.,,.,. 2..... 4 = 2 2 12 = 2 2 3 6 = 2 3 14 = 2 7 8 = 2 2 2 15 = 3 5 9 = 3 3 16 = 2 2 2 2 10 = 2 5 18 = 2 3 3 2, 3, 5, 7, 11, 13, 17, 19.,, 2,.,.,.,?.,,. 1 , 1. x 2 1 = (x 1)(x + 1) x 3 1 = (x 1)(x
More informationu = u(t, x 1,..., x d ) : R R d C λ i = 1 := x 2 1 x 2 d d Euclid Laplace Schrödinger N := {1, 2, 3,... } Z := {..., 3, 2, 1,, 1, 2, 3
2 2 1 5 5 Schrödinger i u t + u = λ u 2 u. u = u(t, x 1,..., x d ) : R R d C λ i = 1 := 2 + + 2 x 2 1 x 2 d d Euclid Laplace Schrödinger 3 1 1.1 N := {1, 2, 3,... } Z := {..., 3, 2, 1,, 1, 2, 3,... } Q
More informationHITACHI 液晶プロジェクター CP-AX3505J/CP-AW3005J 取扱説明書 -詳細版- 【技術情報編】
B A C E D 1 3 5 7 9 11 13 15 17 19 2 4 6 8 10 12 14 16 18 H G I F J M N L K Y CB/PB CR/PR COMPONENT VIDEO OUT RS-232C LAN RS-232C LAN LAN BE EF 03 06 00 2A D3 01 00 00 60 00 00 BE EF 03 06 00 BA D2 01
More informationGame Theory( 0) Masato Shimura 2006 4 22 1 7 1.1......................................... 7 1.2 MAXMIN.......................... 9 1.3.................................... 11 2 21 2.1...................................
More information2001 Mg-Zn-Y LPSO(Long Period Stacking Order) Mg,,,. LPSO ( ), Mg, Zn,Y. Mg Zn, Y fcc( ) L1 2. LPSO Mg,., Mg L1 2, Zn,Y,, Y.,, Zn, Y Mg. Zn,Y., 926, 1
Mg-LPSO 2566 2016 3 2001 Mg-Zn-Y LPSO(Long Period Stacking Order) Mg,,,. LPSO ( ), Mg, Zn,Y. Mg Zn, Y fcc( ) L1 2. LPSO Mg,., Mg L1 2, Zn,Y,, Y.,, Zn, Y Mg. Zn,Y., 926, 1 1,.,,., 1 C 8, 2 A 9.., Zn,Y,.
More informationExcel 2007 Excel 2007 Excel 2007
Excel 2007 Excel 2007 Excel 2007 Excel 2007 Excel Excel Excel Book1 Sheet1 Excel Excel Excel 2002OSWindows XP Excel Excel Excel Excel Office Excel Excel Excel Excel Excel A A5 CtrlC B3 B3 B3 B3 Excel A1
More information~nabe/lecture/index.html 2
2001 12 13 1 http://www.sml.k.u-tokyo.ac.jp/ ~nabe/lecture/index.html nabe@sml.k.u-tokyo.ac.jp 2 1. 10/ 4 2. 10/11 3. 10/18 1 4. 10/25 2 5. 11/ 1 6. 11/ 8 7. 11/15 8. 11/22 9. 11/29 10. 12/ 6 1 11. 12/13
More informationB ver B
B ver. 2017.02.24 B Contents 1 11 1.1....................... 11 1.1.1............. 11 1.1.2.......................... 12 1.2............................. 14 1.2.1................ 14 1.2.2.......................
More information17 18 2
17 18 2 18 2 8 17 4 1 8 1 2 16 16 4 1 17 3 31 16 2 1 2 3 17 6 16 18 1 11 4 1 5 21 26 2 6 37 43 11 58 69 5 252 28 3 1 1 3 1 3 2 3 3 4 4 4 5 5 6 5 2 6 1 6 2 16 28 3 29 3 30 30 1 30 2 32 3 36 4 38 5 43 6
More informationB. 41 II: 2 ;; 4 B [ ] S 1 S 2 S 1 S O S 1 S P 2 3 P P : 2.13:
B. 41 II: ;; 4 B [] S 1 S S 1 S.1 O S 1 S 1.13 P 3 P 5 7 P.1:.13: 4 4.14 C d A B x l l d C B 1 l.14: AB A 1 B 0 AB 0 O OP = x P l AP BP AB AP BP 1 (.4)(.5) x l x sin = p l + x x l (.4)(.5) m d A x P O
More information目次
00D80020G 2004 3 ID POS 30 40 0 RFM i ... 2...2 2. ID POS...2 2.2...3 3...5 3....5 3.2...6 4...9 4....9 4.2...9 4.3...0 4.4...4 4.3....4 4.3.2...6 4.3.3...7 4.3.4...9 4.3.5...2 5...23 5....23 5.....23
More information20 9 19 1 3 11 1 3 111 3 112 1 4 12 6 121 6 122 7 13 7 131 8 132 10 133 10 134 12 14 13 141 13 142 13 143 15 144 16 145 17 15 19 151 1 19 152 20 2 21 21 21 211 21 212 1 23 213 1 23 214 25 215 31 22 33
More information行列代数2010A
(,) A (,) B C = AB a 11 a 1 a 1 b 11 b 1 b 1 c 11 c 1 c a A = 1 a a, B = b 1 b b, C = AB = c 1 c c a 1 a a b 1 b b c 1 c c i j ij a i1 a i a i b 1j b j b j c ij = a ik b kj b 1j b j AB = a i1 a i a ik
More informationi I Excel iii Excel Excel Excel
Excel i I Excel iii 1 1 2 Excel 2 2.1..................................... 2 2.2 Excel................................................ 2 2.3 Excel................................................ 4 2.4..............................................
More information1007.\1.ai
- 1 - B - 2 - e - 3 - F O f g e f - 4 - O O N N N N N N N N N N N N N N N N N N N N N N N F C - 5 - N N N N N N N N N N N N N N N N N N N N N N N F - 6 - D - 7 - - 8 - - 9 - - 10 - - 11 - - 12 - - 13 -
More information橡早川ゼミ卒業論文 棟安.PDF
4 1998 J J 3 6 1 J J J J 3 1 1993 1 5 1993 1997 3 3 10 J CP 3 3 CP J 10 300 J 300 J 13 9000 J 2 5 10 25 1978 100 J 1994 pp105106 pp118121 1 J CATEGORY CP 92 10 J CATEGORY 1000 2 CATEGORY J CP CATEGORY
More information05秋案内.indd
1 2 3 4 5 6 7 R01a U01a Q01a L01a M01b - M03b Y01a R02a U02a Q02a L02a M04b - M06b Y02a R03a U03a Q03a L03a M08a Y03a R04a U04a Q04a L04a M09a Y04a A01a L05b, L07b, R05a U05a Q05a M10a Y05b - Y07b L08b
More information( ) 2002 1 1 1 1.1....................................... 1 1.1.1................................. 1 1.1.2................................. 1 1.1.3................... 3 1.1.4......................................
More informationPart () () Γ Part ,
Contents a 6 6 6 6 6 6 6 7 7. 8.. 8.. 8.3. 8 Part. 9. 9.. 9.. 3. 3.. 3.. 3 4. 5 4.. 5 4.. 9 4.3. 3 Part. 6 5. () 6 5.. () 7 5.. 9 5.3. Γ 3 6. 3 6.. 3 6.. 3 6.3. 33 Part 3. 34 7. 34 7.. 34 7.. 34 8. 35
More informationJanuary 16, (a) (b) 1. (a) Villani f : R R f 2 f 0 x, y R t [0, 1] f((1 t)x + ty) (1 t)f(x) + tf(y) f 2 f 0 x, y R t [0, 1] f((1 t)x + ty) (1 t
January 16, 2017 1 1. Villani f : R R f 2 f 0 x, y R t [0, 1] f((1 t)x + ty) (1 t)f(x) + tf(y) f 2 f 0 x, y R t [0, 1] f((1 t)x + ty) (1 t)f(x) + tf(y) (simple) (general) (stable) f((1 t)x + ty) (1 t)f(x)
More informationA(6, 13) B(1, 1) 65 y C 2 A(2, 1) B( 3, 2) C 66 x + 2y 1 = 0 2 A(1, 1) B(3, 0) P 67 3 A(3, 3) B(1, 2) C(4, 0) (1) ABC G (2) 3 A B C P 6
1 1 1.1 64 A6, 1) B1, 1) 65 C A, 1) B, ) C 66 + 1 = 0 A1, 1) B, 0) P 67 A, ) B1, ) C4, 0) 1) ABC G ) A B C P 64 A 1, 1) B, ) AB AB = 1) + 1) A 1, 1) 1 B, ) 1 65 66 65 C0, k) 66 1 p, p) 1 1 A B AB A 67
More information入試の軌跡
4 y O x 4 Typed by L A TEX ε ) ) ) 6 4 ) 4 75 ) http://kumamoto.s.xrea.com/plan/.. PDF) Ctrl +L) Ctrl +) Ctrl + Ctrl + ) ) Alt + ) Alt + ) ESC. http://kumamoto.s.xrea.com/nyusi/kumadai kiseki ri i.pdf
More information05‚å™J“LŁñfi~P01-06_12/27
2005 164 FFFFFFFFF FFFFFFFFF 2 3 4 5 6 7 8 g a 9 f a 10 g e g 11 f g g 12 a g g 1 13 d d f f d 14 a 15 16 17 18 r r 19 20 21 ce eb c b c bd c bd c e c gf cb ed ed fe ed g b cd c b 22 bc ff bf f c f cg
More information欧州特許庁米国特許商標庁との共通特許分類 CPC (Cooperative Patent Classification) 日本パテントデータサービス ( 株 ) 国際部 2019 年 7 月 31 日 CPC 版が発効します 原文及び詳細はCPCホームページのCPC Revision
欧州特許庁米国特許商標庁との共通特許分類 CPC (Cooperative Patent Classification) 日本パテントデータサービス ( 株 ) 国際部 2019 年 7 月 31 日 CPC 2019.08 版が発効します 原文及び詳細はCPCホームページのCPC Revisions(CPCの改訂 ) をご覧ください https://www.cooperativepatentclassification.org/cpcrevisions/noticeofchanges.html
More informationŁ½’¬24flNfix+3mm-‡½‡¹724
571 0.0 31,583 2.0 139,335 8.9 310,727 19.7 1,576,352 100.0 820 0.1 160,247 10.2 38,5012.4 5,7830.4 9,5020.6 41,7592.7 77,8174.9 46,425 2.9 381,410 24.2 1,576,352 100.0 219,332 13.9 132,444 8.4 173,450
More informationx x x 2, A 4 2 Ax.4 A A A A λ λ 4 λ 2 A λe λ λ2 5λ + 6 0,...λ 2, λ 2 3 E 0 E 0 p p Ap λp λ 2 p 4 2 p p 2 p { 4p 2 2p p + 2 p, p 2 λ {
K E N Z OU 2008 8. 4x 2x 2 2 2 x + x 2. x 2 2x 2, 2 2 d 2 x 2 2.2 2 3x 2... d 2 x 2 5 + 6x 0 2 2 d 2 x 2 + P t + P 2tx Qx x x, x 2 2 2 x 2 P 2 tx P tx 2 + Qx x, x 2. d x 4 2 x 2 x x 2.3 x x x 2, A 4 2
More information28
y i = Z i δ i +ε i ε i δ X y i = X Z i δ i + X ε i [ ] 1 δ ˆ i = Z i X( X X) 1 X Z i [ ] 1 σ ˆ 2 Z i X( X X) 1 X Z i Z i X( X X) 1 X y i σ ˆ 2 ˆ σ 2 = [ ] y i Z ˆ [ i δ i ] 1 y N p i Z i δ ˆ i i RSTAT
More information2 / 5 Auction: Theory and Practice 3 / 5 (WTO) 1 SDR 27 1,6 Auction: Theory and Practice 4 / 5 2
stakagi@econ.hokudai.ac.jp June 22, 212 2................................................................ 3...................................................... 4............................................................
More information2000年度『数学展望 I』講義録
2000 I I IV I II 2000 I I IV I-IV. i ii 3.10 (http://www.math.nagoya-u.ac.jp/ kanai/) 2000 A....1 B....4 C....10 D....13 E....17 Brouwer A....21 B....26 C....33 D....39 E. Sperner...45 F....48 A....53
More information2012 A, N, Z, Q, R, C
2012 A, N, Z, Q, R, C 1 2009 9 2 2011 2 3 2012 9 1 2 2 5 3 11 4 16 5 22 6 25 7 29 8 32 1 1 1.1 3 1 1 1 1 1 1? 3 3 3 3 3 3 3 1 1, 1 1 + 1 1 1+1 2 2 1 2+1 3 2 N 1.2 N (i) 2 a b a 1 b a < b a b b a a b (ii)
More information(2016 2Q H) [ ] R 2 2 P = (a, b), Q = (c, d) Q P QP = ( ) a c b d (a c, b d) P = (a, b) O P ( ) a p = b P = (a, b) p = ( ) a b R 2 {( ) } R 2 x = x, y
(2016 2Q H) [ ] R 2 2 P = (a, b), Q = (c, d) Q P QP = a c b d (a c, b d) P = (a, b) O P a p = b P = (a, b) p = a b R 2 { } R 2 x = x, y R y 2 a p =, c q = b d p + a + c q = b + d q p P q a p = c R c b
More information1 (utility) 1.1 x u(x) x i x j u(x i ) u(x j ) u (x) 0, u (x) 0 u (x) x u(x) (Marginal Utility) 1.2 Cobb-Daglas 2 x 1, x 2 u(x 1, x 2 ) max x 1,x 2 u(
1 (utilit) 1.1 x u(x) x i x j u(x i ) u(x j ) u (x) 0, u (x) 0 u (x) x u(x) (Marginal Utilit) 1.2 Cobb-Daglas 2 x 1, x 2 u(x 1, x 2 ) x 1,x 2 u(x 1, x 2 ) s.t. P 1 x 1 + P 2 x 2 (1) (P i :, : ) u(x 1,
More informationEP760取扱説明書
D D D # % ' ) * +, B - B / 1 Q&A B 2 B 5 B 6 Q & A 7 8 $ % & ' B B B ( B B B B B B B B B B B ) B B B A # $ A B B * 1 2 # $ % # B B % $ # $ % + B B 1 B 2 B B B B B B B B B B , B B B - 1 3 2 2 B B B B B
More information/02/18
3 09/0/8 i III,,,, III,?,,,,,,,,,,,,,,,,,,,,?,?,,,,,,,,,,,,,,!!!,? 3,,,, ii,,,!,,,, OK! :!,,,, :!,,,,,, 3:!,, 4:!,,,, 5:!,,! 7:!,,,,, 8:!,! 9:!,,,,,,,,, ( ),, :, ( ), ( ), 6:!,,, :... : 3 ( )... iii,,
More information( [1]) (1) ( ) 1: ( ) 2 2.1,,, X Y f X Y (a mapping, a map) X ( ) x Y f(x) X Y, f X Y f : X Y, X f Y f : X Y X Y f f 1 : X 1 Y 1 f 2 : X 2 Y 2 2 (X 1
2013 5 11, 2014 11 29 WWW ( ) ( ) (2014/7/6) 1 (a mapping, a map) (function) ( ) ( ) 1.1 ( ) X = {,, }, Y = {, } f( ) =, f( ) =, f( ) = f : X Y 1.1 ( ) (1) ( ) ( 1 ) (2) 1 function 1 ( [1]) (1) ( ) 1:
More information( ) ( )
20 21 2 8 1 2 2 3 21 3 22 3 23 4 24 5 25 5 26 6 27 8 28 ( ) 9 3 10 31 10 32 ( ) 12 4 13 41 0 13 42 14 43 0 15 44 17 5 18 6 18 1 1 2 2 1 2 1 0 2 0 3 0 4 0 2 2 21 t (x(t) y(t)) 2 x(t) y(t) γ(t) (x(t) y(t))
More information.3. (x, x = (, u = = 4 (, x x = 4 x, x 0 x = 0 x = 4 x.4. ( z + z = 8 z, z 0 (z, z = (0, 8, (,, (8, 0 3 (0, 8, (,, (8, 0 z = z 4 z (g f(x = g(
06 5.. ( y = x x y 5 y 5 = (x y = x + ( y = x + y = x y.. ( Y = C + I = 50 + 0.5Y + 50 r r = 00 0.5Y ( L = M Y r = 00 r = 0.5Y 50 (3 00 0.5Y = 0.5Y 50 Y = 50, r = 5 .3. (x, x = (, u = = 4 (, x x = 4 x,
More information007 0 ue ue 6 67 090 b 6666 D 666 0 6 6 0 0 0 4 0 6 7 6 6706 00000 00000 69 000040 000040 0040 0040 000040 000040 0040 0040 674 00000 70 00000 0 00000
EDOGAWA ITY Y @ Y 60 7 66997 00 00 00 00 600 000 000 4900 900 700 000 f 004000 00 000 7f 70g 0 0 007 0 ue ue 6 67 090 b 6666 D 666 0 6 6 0 0 0 4 0 6 7 6 6706 00000 00000 69 000040 000040 0040 0040 000040
More information3 m = [n, n1, n 2,..., n r, 2n] p q = [n, n 1, n 2,..., n r ] p 2 mq 2 = ±1 1 1 6 1.1................................. 6 1.2......................... 8 1.3......................... 13 2 15 2.1.............................
More information1 n 1 1 2 2 3 3 3.1............................ 3 3.2............................. 6 3.2.1.............. 6 3.2.2................. 7 3.2.3........................... 10 4 11 4.1..........................
More information空き容量一覧表(154kV以上)
1/3 A. 電気所 ( 発電所, 変電所, 配電塔 ) における変圧器の空き容量 覧 < 留意事項 > (1) 空容量は 安であり 系統接続の前には 接続検討のお申込みによる詳細検討が必要となります その結果 空容量が変更となる場合があります (2) 熱容量を考慮した空き容量を記載しております その他の要因 ( や系統安定度など ) で連系制約が発 する場合があります (3) 表 は 既に空容量がないため
More informationBasic Math. 1 0 [ N Z Q Q c R C] 1, 2, 3,... natural numbers, N Def.(Definition) N (1) 1 N, (2) n N = n +1 N, (3) N (1), (2), n N n N (element). n/ N.
Basic Mathematics 16 4 16 3-4 (10:40-12:10) 0 1 1 2 2 2 3 (mapping) 5 4 ε-δ (ε-δ Logic) 6 5 (Potency) 9 6 (Equivalence Relation and Order) 13 7 Zorn (Axiom of Choice, Zorn s Lemma) 14 8 (Set and Topology)
More information