IDRstab(s, L) GBiCGSTAB(s, L) 2. AC-GBiCGSTAB(s, L) Ax = b (1) A R n n x R n b R n 2.1 IDR s L r k+1 r k+1 = b Ax k+1 IDR(s) r k+1 = (I ω k A)(r k dr

Size: px
Start display at page:

Download "IDRstab(s, L) GBiCGSTAB(s, L) 2. AC-GBiCGSTAB(s, L) Ax = b (1) A R n n x R n b R n 2.1 IDR s L r k+1 r k+1 = b Ax k+1 IDR(s) r k+1 = (I ω k A)(r k dr"

Transcription

1 1 2 IDR(s) GBiCGSTAB(s, L) IDR(s) IDRstab(s, L) GBiCGSTAB(s, L) Verification of effectiveness of Auto-Correction technique applied to preconditioned iterative methods Keiichi Murakami 1 Seiji Fujino 2 Abstract: Auto-Correction technique has been proposed by Sakurai et al. in order to avoid spurious convergence. Tukada et al. expanded the AC technique, and applied it to their GBiCGSTAB(s, L) method. In general, iterative methods are used together with preconditioning. Therefore, in this paper, we apply the AC technique to preconditioned iterative methods, and verify effectiveness of the AC technique. Keywords: Auto-Cerrection technique, IDR(s) method, IDRstab(s, L) method, GBiCGSTAB(s, L) method, preconditioning Sonneveld IDR(s) Induced Dimension Reduction [15] Sleijpen IDR(s) BiCGstab(l) [12] IDRstab(s, L) [13][14] IDRstab(s, L) GBiCGSTAB(s, L) [16] IDR(s) Bi-CGSTAB IDR(s) 1 Graduate School of Information Science and Electrical Engineering, Kyushu University 2 Research Institute for Information Technology, Kyushu University r k = b Ax k [11] IDR(s) GBiCGSTAB(s, L) [17] ILU(0) SSOR [2][3][4] IDR(s) 1

2 IDRstab(s, L) GBiCGSTAB(s, L) 2. AC-GBiCGSTAB(s, L) Ax = b (1) A R n n x R n b R n 2.1 IDR s L r k+1 r k+1 = b Ax k+1 IDR(s) r k+1 = (I ω k A)(r k dr k c). (2) ω k 0 c s dr k dr k = r k+1 r k dr k := (dr k 1,, dr k s ) dr k dr k = Adx k IDR I k = dr k b Range(c). (3) [11]3 Range(c) Range(c) = max 1 i s c(i) min 1 j s c(j). (4) I k I th dr k IDR(s) Set I k if I k < I th then Compute dr k recurcively else Compute dr k = Adx k end if r k+1 = r k + dr k GBiCGSTAB(s, L) I k [17] GBiCGSTAB(s, L) r k+1 = r k L k=1 γ k+1 U j k,1 U (j) k,1 αj k [rl k,1,, r L k,l]γ k+1 (5) γ k+1 = argmin γ r 0 [r 1,, r L ]γ, U j k,1 = AU j k (6) GBiCGSTAB(s, L) I k I k = r k r 0 max ( j Range(αj ) ) Range(γ) (7) 2.2 Eisenstat trick SSOR ILU SSOR [2] SSOR Eisenstat trick [6] [3][4][8][9] SSOR A = L A + D + U A K K = (L A + D/ω)(D/ω) 1 (U A + D/ω) (8) L A D U A ω SSOR Eisenstat trick [6] Ã = ((U A + D/ω) 1 + (L A + D/ω) 1 (I + (1 2/ω)D(U A + D/ω) 1 ))(D/ω) (9) Ãv [3][4] 1. y = (U A + D/ω) 1 (D/ω)v 2. z = (D/ω)v + (1 2/ω)Dy 3. w = (L A + D/ω) 1 z 4. Ãv = y + w Eisenstat trick SSOR 2

3 E-SSOR E-SSOR AC-GBiCGSTAB(s, L) E-SSOR AC-GBiCGSTAB(s, L) 1. Let x 0 be an initial guess, r 0 = b Ax 0, set R 0 R n s 2. Compute x 0 = (D/ω) 1 (U A + D/ω)x 0, r 0 = (L A + D/ω) 1 r 0 3. Set U 0, Compute U p, (p = 1) 4. Solve Mα = m 5. r 0 = r 0 U 1 α, x 0 = x 0 + U 0 α 6. while r k / r 0 ϵ do 7. {BiCG PART} 8. for j = 1... L do 9. if (k = 0) (j = 1) then 10. M 0 = R T 0 U 1, m 0 = R T 0 r Go to line end if 13. for i = 1... s do 14. if i = 1 then 15. Solve Mβ = m 16. U p e 1 = r p U p β, (p = 0, 1,, j 1) 17. else 18. Solve [ m, M[1 : i 2], M[i : s] ] β = Me i U p e i = U p+1 e i 1 [ r p, U p+1 [1 : i 2], U p [i : s] ] β 20. end if (p = 0, 1,, j 1) 21. y = (U A + D/ω) 1 (D/ω)e i 22. z = (D/ω)Ue i + (1 2 ω )Dy 23. w = (L A + D/ω) 1 z 24. Ue 1 = y + w 25. U p e i = U pe i, (p = 0, 1,, j) U j e i 26. Me i = R T 0 Ue i 27. end do 28. Solve Mα = m 29. r p = r p U p+1 α, (p = 0, 1,, j 1) 30. y = (U A + D/ω) 1 (D/ω) r j z = (D/ω) r j 1 + (1 2 ω )Dy 32. w = (L A + D/ω) 1 z 33. r j = y + w 34. end do 35. {MR PART} 36. γ = argmin γ r 0 [ r 1,, r L ]γ 37. I k = r k r 0 max ( j Range(αj ) ) Range(γ) 38. dx k = L U k α j + [ r 0,, r L 1 ]γ, x k+1 = x k + dx k j=1 39. if I k > θ then 40. y = (U A + D/ω) 1 (D/ω)dx k 41. z = (D/ω)dx k + (1 2 ω )Dy 42. w = (L A + D/ω) 1 z 43. r k+1 = r k (y + w) 44. else 45. r k+1 = r k [ r 1,, r L ]γ 46. end if 47. U k+1 = U k [U 1,, U L ]γ 48. M k+1 = γm k, m k = R T 0 r k, k = k Compute r k = (L A + D/ω) r k 50. end while 51. Compute x k = (U A + D/ω) 1 (D/ω) x k ( 1 ) ( 2 ) Dell PowerEdge R210II CPU: Intel Xeon E : 3.1GHz : 8Gbytes OS: Scientific Linux 6.0 ( 3 ) Intel Fortran Compiler version fast ( 4 ) cputime ( 1 ) 2 : r k+1 2 / r ( 2 ) x 0 0 ( 3 ) 1.0 ( 4 ) ( 5 ) s L ( 6 ) SSOR ILU(0) ω [5] 6. 2 dc3 TRRTrue Relative Residual b Ax k+1 / b NaN 3

4 1 Table 1 Characteristics of test matrices. air-cfl5 1,536,000 19,435, airfoil 2d 14, , poisson3db 85,623 2,374, sherman5 3,312 20, raefsky2 3, , watt 2 1,856 11, OK01 54,903 3,990, comsol 1,500 97, sme3dc 42,930 3,148, add20 2,395 17, dc3 116, , memplus 17, , epb3 84, , k3plates 11, , TRR -8 2 dc3 : (a) IDRstab(s, L) Table 2 Convergence rate of preconditioned iterative methods for matrix dc3: (a) non-preconditioned IDRstab(s, L) method , , , , , , , , , , , , , , , , , , , , , , , , , , , (b) ILU(0) IDRstab(s, L) (b) ILU(0) preconditioned IDRstab(s, L) method , , TRR 3 IDRstab(s, L) ( 1 ) AC TRR AC 7 ( 2 ) AC max ( 3 ) SSOR AC TRR -8 1 ( 4 ) AC TRR ILU(0) 136 SSOR 118 GBiCGSTAB(s, L) ( 1 ) AC TRR AC 31 ( 2 ) max AC AC ( 3 ) SSOR AC TRR -8 0 ( 4 ) AC TRR ILU(0) 86 SSOR 88 4

5 (c) E-SSOR IDRstab(s, L) (c) E-SSOR preconditioned IDRstab(s, L) method , , (d) GBiCGSTAB(s, L) (d) non-preconditioned GBiCGSTAB(s, L) method. [s] [s] 1 1 5, , , , , , , , , , , , , , , , , , , , , IDRstab(s, L) GBiCGSTAB(s, L) ( 1 ) AC IDRstab(s, L) TRR GBiCGSTAB(s, L) 103 ( 2 ) AC IDRstab(s, L) max 35 GBiCGSTAB(s, L) 63 ( 3 ) AC IDRstab(s, L) TRR GBiCGSTAB(s, L) 188 ( 4 ) AC SSOR IDRstab(s, L) TRR GBiCGSTAB(s, L) TRR 1 GBiCGSTAB(s, L) IDRstab(s, L) AC GBiCGSTAB(s, L) IDRstab(s, L) TRR IDRstab(s, L) GBiCGSTAB(s, L) (a) IDRstab(s, L) (b) GBiCGSTAB(s, L) 1 TRR Fig. 1 TRR distribution of preconditioned iterative method

6 (e) ILU(0) GBiCGSTAB(s, L) (e) ILU(0) preconditioned GBiCGSTAB(s, L) method (f) E-SSOR GBiCGSTAB(s, L) (f) E-SSOR preconditioned GBiCGSTAB(s, L) method , [1],, : IDRstab ( ),,, No.1791, pp (2012). [2] Axelsson, O.: A generalized SSOR method, BIT, Vol.12, pp (1972). [3] Chan, T. F., van der Vorst, H. A.: Approximate and Incomplete Factorizations, Parallel Numerical Algorithms, ICASE/LaRC Interdisciplinary Series in Sci. and Eng., Kluwer Academic, Vol.4, pp (1997). [4] Chen, X., Toh, K. C., Phoon, K. K.: A modified SSOR preconditioner for sparse symmetric indefinite linear systems of equations, Int. J. Numer. Meth. Engng, Vol.65, pp (2006). [5] Davis, T.:University of Florida Spares Matrix Collection: research/sparse/matrices/index.html [6] Eisenstat, S. C.: Efficient implementation of a class of preconditioned conjugate gradient methods, SIAM J. Sci. Stat. Compute., Vol.2, pp.1-4 (1981). [7], Sonneveld, P.,, van Gijzen, M.B.: IDR(s)-SOR,, Vol.20, No.4, pp (2010). [8],, : Eisenstat GS MRTR,, No.2011, (2011). [9] : Eisenstat, Table 3 3 Comparison of the accuracy between the preconditioned iterative methods. (a) IDRstab(s, L) AC TRR max (46%) (13) (12) (8) (12) (10) ILU(0) (46) (13) (12) (8) (12) (10) SSOR (34) (7) (9) (14) (29) (7) (2) (3) (9) (14) (61) (11) ILU(0) (5) (3) (8) (12) (67) (5) SSOR (0) (2) (7) (13) (69) (9), Vol.3, No.2, pp (2011). [10] Saad, Y., van der Vorst, H.A.: Iterative solution of linear systems in the 20th century, J. of Compute. Appl. Math., Vol.123, pp.1-33 (2000). [11] : AC-IDR(s) HPCS2009 pp.81-88, (2009) [12] Sleijpen, G.L.G., Fokkema, D.R.: BiCGstab(l) for equations involving unsymmetric matrices with complex spectrum, Electronic Transactions on Numerical Analysis, 6

7 (b) GBiCGSTAB(s, L) AC TRR max (32%) (5) (8) (7) (29) (18) ILU(0) (25) (8) (13) (8) (39) (9) SSOR (25) (6) (13) (8) (39) (9) (9) (3) (11) (6) (54) (18) ILU(0) (5) (2) (5) (13) (74) (2) SSOR (0) (1) (7) (13) (72) (7) Vol.1, pp (1993). [13] Sleijpen, G.L.G., Sonneveld, P., van Gijzen, M.B.: Bi- CGSTAB as an induced dimension reduction method, Appl. Numer. Math., Vol.60, pp (2010). [14] Sleijpen, G.L.G., van Gijzen, M.B.: Exploiting BiCGstab(l) strategies to induce dimension reduction, SIAM J. Sci. Comput., Vol.35, No.5, pp (2010). [15] Sonneveld, P., van Gijzen, M.B.: IDR(s): a family of simple and fast algorithms for solving large nonsymmetric linear systems, SIAM J. Sci. Stat. Comput., Vol.31, No.2, pp (2008). [16] Tanio,M., Sugihara, M.: Bi-CGSTAB(s, L)(= IDR(s, L),,, No.1638, pp (2009). [17],,, : GBiCGSTAB(s, L) ( ),,, No.1733, pp (2011). [18] : IDR, (2010). [19] van der Vorst, H.A.: Bi-CGSTAB: A fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems, SIAM Journal on Scientific and Statistical Computing, Vol.12, pp (1992). [20] Wesseling, P., Sonneveld, P.: Numerical Experiments with a Multiple Grid-and a Preconditioned Lanczos Type Methods, Lecture Notes in Math., Springer, No.771, pp (1980). 7

自動残差修正機能付き GBiCGSTAB$(s,L)$法 (科学技術計算アルゴリズムの数理的基盤と展開)

自動残差修正機能付き GBiCGSTAB$(s,L)$法 (科学技術計算アルゴリズムの数理的基盤と展開) 1733 2011 149-159 149 GBiCGSTAB $(s,l)$ GBiCGSTAB(s,L) with Auto-Correction of Residuals (Takeshi TSUKADA) NS Solutions Corporation (Kouki FUKAHORI) Graduate School of Information Science and Technology

More information

情報処理学会研究報告 IPSJ SIG Technical Report Vol.2014-HPC-144 No /5/ CRS 2 CRS Performance evaluation of exclusive version of preconditioned ite

情報処理学会研究報告 IPSJ SIG Technical Report Vol.2014-HPC-144 No /5/ CRS 2 CRS Performance evaluation of exclusive version of preconditioned ite 1 2 3 CRS 2 CRS Performance evaluation of exclusive version of preconditioned iterative method for dense matrix Abstract: As well known, only nonzero entries of a sparse matrix are stored in memory in

More information

untitled

untitled 1 1 Ax = b A R m m A b R m x R m A shift-and invert Lanczos - LU CG A = LU LU Ly = b Ux = y A LU A A = LL T 1 LU b,, Vol. 11, No. 4, pp. 14 18 (2006). x * x (0), x (1), x (2), A Ap A # x (n+1) = Cx (n)

More information

橡固有値セミナー2_棚橋改.PDF

橡固有値セミナー2_棚橋改.PDF 1 II. 2003 5 14 2... Arnoldi. Lanczos. Jacobi-Davidson . 3 4 Ax = x A A Ax = Mx M: M 5 Householder ln ln-1 0 l3 0 l2 l1 6 Lanczos Lanczos, 1950 Arnoldi Arnoldi, 1951 Hessenberg Jacobi-Davidson Sleijpen

More information

2012年度HPCサマーセミナー_多田野.pptx

2012年度HPCサマーセミナー_多田野.pptx ! CCS HPC! I " tadano@cs.tsukuba.ac.jp" " 1 " " " " " " " 2 3 " " Ax = b" " " 4 Ax = b" A = a 11 a 12... a 1n a 21 a 22... a 2n...... a n1 a n2... a nn, x = x 1 x 2. x n, b = b 1 b 2. b n " " 5 Gauss LU

More information

A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member

A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member A Feasibility Study of Direct-Mapping-Type Parallel Processing Method to Solve Linear Equations in Load Flow Calculations Hiroaki Inayoshi, Non-member (University of Tsukuba), Yasuharu Ohsawa, Member (Kobe

More information

IV (2)

IV (2) COMPUTATIONAL FLUID DYNAMICS (CFD) IV (2) The Analysis of Numerical Schemes (2) 11. Iterative methods for algebraic systems Reima Iwatsu, e-mail : iwatsu@cck.dendai.ac.jp Winter Semester 2007, Graduate

More information

第62巻 第1号 平成24年4月/石こうを用いた木材ペレット

第62巻 第1号 平成24年4月/石こうを用いた木材ペレット Bulletin of Japan Association for Fire Science and Engineering Vol. 62. No. 1 (2012) Development of Two-Dimensional Simple Simulation Model and Evaluation of Discharge Ability for Water Discharge of Firefighting

More information

4. C i k = 2 k-means C 1 i, C 2 i 5. C i x i p [ f(θ i ; x) = (2π) p 2 Vi 1 2 exp (x µ ] i) t V 1 i (x µ i ) 2 BIC BIC = 2 log L( ˆθ i ; x i C i ) + q

4. C i k = 2 k-means C 1 i, C 2 i 5. C i x i p [ f(θ i ; x) = (2π) p 2 Vi 1 2 exp (x µ ] i) t V 1 i (x µ i ) 2 BIC BIC = 2 log L( ˆθ i ; x i C i ) + q x-means 1 2 2 x-means, x-means k-means Bayesian Information Criterion BIC Watershed x-means Moving Object Extraction Using the Number of Clusters Determined by X-means Clustering Naoki Kubo, 1 Kousuke

More information

1 [1, 2, 3, 4, 5, 8, 9, 10, 12, 15] The Boston Public Schools system, BPS (Deferred Acceptance system, DA) (Top Trading Cycles system, TTC) cf. [13] [

1 [1, 2, 3, 4, 5, 8, 9, 10, 12, 15] The Boston Public Schools system, BPS (Deferred Acceptance system, DA) (Top Trading Cycles system, TTC) cf. [13] [ Vol.2, No.x, April 2015, pp.xx-xx ISSN xxxx-xxxx 2015 4 30 2015 5 25 253-8550 1100 Tel 0467-53-2111( ) Fax 0467-54-3734 http://www.bunkyo.ac.jp/faculty/business/ 1 [1, 2, 3, 4, 5, 8, 9, 10, 12, 15] The

More information

T rank A max{rank Q[R Q, J] t-rank T [R T, C \ J] J C} 2 ([1, p.138, Theorem 4.2.5]) A = ( ) Q rank A = min{ρ(j) γ(j) J J C} C, (5) ρ(j) = rank Q[R Q,

T rank A max{rank Q[R Q, J] t-rank T [R T, C \ J] J C} 2 ([1, p.138, Theorem 4.2.5]) A = ( ) Q rank A = min{ρ(j) γ(j) J J C} C, (5) ρ(j) = rank Q[R Q, (ver. 4:. 2005-07-27) 1 1.1 (mixed matrix) (layered mixed matrix, LM-matrix) m n A = Q T (2m) (m n) ( ) ( ) Q I m Q à = = (1) T diag [t 1,, t m ] T rank à = m rank A (2) 1.2 [ ] B rank [B C] rank B rank

More information

JFE.dvi

JFE.dvi ,, Department of Civil Engineering, Chuo University Kasuga 1-13-27, Bunkyo-ku, Tokyo 112 8551, JAPAN E-mail : atsu1005@kc.chuo-u.ac.jp E-mail : kawa@civil.chuo-u.ac.jp SATO KOGYO CO., LTD. 12-20, Nihonbashi-Honcho

More information

1 Fig. 1 Extraction of motion,.,,, 4,,, 3., 1, 2. 2.,. CHLAC,. 2.1,. (256 ).,., CHLAC. CHLAC, HLAC. 2.3 (HLAC ) r,.,. HLAC. N. 2 HLAC Fig. 2

1 Fig. 1 Extraction of motion,.,,, 4,,, 3., 1, 2. 2.,. CHLAC,. 2.1,. (256 ).,., CHLAC. CHLAC, HLAC. 2.3 (HLAC ) r,.,. HLAC. N. 2 HLAC Fig. 2 CHLAC 1 2 3 3,. (CHLAC), 1).,.,, CHLAC,.,. Suspicious Behavior Detection based on CHLAC Method Hideaki Imanishi, 1 Toyohiro Hayashi, 2 Shuichi Enokida 3 and Toshiaki Ejima 3 We have proposed a method for

More information

3. ( 1 ) Linear Congruential Generator:LCG 6) (Mersenne Twister:MT ), L 1 ( 2 ) 4 4 G (i,j) < G > < G 2 > < G > 2 g (ij) i= L j= N

3. ( 1 ) Linear Congruential Generator:LCG 6) (Mersenne Twister:MT ), L 1 ( 2 ) 4 4 G (i,j) < G > < G 2 > < G > 2 g (ij) i= L j= N RMT 1 1 1 N L Q=L/N (RMT), RMT,,,., Box-Muller, 3.,. Testing Randomness by Means of RMT Formula Xin Yang, 1 Ryota Itoi 1 and Mieko Tanaka-Yamawaki 1 Random matrix theory derives, at the limit of both dimension

More information

The 15th Game Programming Workshop 2010 Magic Bitboard Magic Bitboard Bitboard Magic Bitboard Bitboard Magic Bitboard Magic Bitboard Magic Bitbo

The 15th Game Programming Workshop 2010 Magic Bitboard Magic Bitboard Bitboard Magic Bitboard Bitboard Magic Bitboard Magic Bitboard Magic Bitbo Magic Bitboard Magic Bitboard Bitboard Magic Bitboard Bitboard Magic Bitboard 64 81 Magic Bitboard Magic Bitboard Bonanza Proposal and Implementation of Magic Bitboards in Shogi Issei Yamamoto, Shogo Takeuchi,

More information

Input image Initialize variables Loop for period of oscillation Update height map Make shade image Change property of image Output image Change time L

Input image Initialize variables Loop for period of oscillation Update height map Make shade image Change property of image Output image Change time L 1,a) 1,b) 1/f β Generation Method of Animation from Pictures with Natural Flicker Abstract: Some methods to create animation automatically from one picture have been proposed. There is a method that gives

More information

fiš„v8.dvi

fiš„v8.dvi (2001) 49 2 333 343 Java Jasp 1 2 3 4 2001 4 13 2001 9 17 Java Jasp (JAva based Statistical Processor) Jasp Jasp. Java. 1. Jasp CPU 1 106 8569 4 6 7; fuji@ism.ac.jp 2 106 8569 4 6 7; nakanoj@ism.ac.jp

More information

Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the imag

Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the imag 2004 RGB A STUDY OF RGB COLOR INFORMATION AND ITS APPLICATION 03R3237 Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One

More information

IPSJ SIG Technical Report Vol.2016-CE-137 No /12/ e β /α α β β / α A judgment method of difficulty of task for a learner using simple

IPSJ SIG Technical Report Vol.2016-CE-137 No /12/ e β /α α β β / α A judgment method of difficulty of task for a learner using simple 1 2 3 4 5 e β /α α β β / α A judgment method of difficulty of task for a learner using simple electroencephalograph Katsuyuki Umezawa 1 Takashi Ishida 2 Tomohiko Saito 3 Makoto Nakazawa 4 Shigeichi Hirasawa

More information

Q [4] 2. [3] [5] ϵ- Q Q CO CO [4] Q Q [1] i = X ln n i + C (1) n i i n n i i i n i = n X i i C exploration exploitation [4] Q Q Q ϵ 1 ϵ 3. [3] [5] [4]

Q [4] 2. [3] [5] ϵ- Q Q CO CO [4] Q Q [1] i = X ln n i + C (1) n i i n n i i i n i = n X i i C exploration exploitation [4] Q Q Q ϵ 1 ϵ 3. [3] [5] [4] 1,a) 2,3,b) Q ϵ- 3 4 Q greedy 3 ϵ- 4 ϵ- Comparation of Methods for Choosing Actions in Werewolf Game Agents Tianhe Wang 1,a) Tomoyuki Kaneko 2,3,b) Abstract: Werewolf, also known as Mafia, is a kind of

More information

28 Horizontal angle correction using straight line detection in an equirectangular image

28 Horizontal angle correction using straight line detection in an equirectangular image 28 Horizontal angle correction using straight line detection in an equirectangular image 1170283 2017 3 1 2 i Abstract Horizontal angle correction using straight line detection in an equirectangular image

More information

Keywords: corotational method, Rigid-Bodies-Spring model, accuracy, geometrical nonlinearity

Keywords: corotational method, Rigid-Bodies-Spring model, accuracy, geometrical nonlinearity Keywords: corotational method, Rigid-Bodies-Spring model, accuracy, geometrical nonlinearity vo2=voi+(sina1+sina2)l/2+{f1(sin2a1+sin2a2) +Fz1(sina1cosai+sina2cosa2)}l/(2EA) woe=w01-l+(cosai+cosa2)l/2+{fy1(sinaicosai

More information

三石貴志.indd

三石貴志.indd 流通科学大学論集 - 経済 情報 政策編 - 第 21 巻第 1 号,23-33(2012) SIRMs SIRMs Fuzzy fuzzyapproximate approximatereasoning reasoningusing using Lukasiewicz Łukasiewicz logical Logical operations Operations Takashi Mitsuishi

More information

GPGPU

GPGPU GPGPU 2013 1008 2015 1 23 Abstract In recent years, with the advance of microscope technology, the alive cells have been able to observe. On the other hand, from the standpoint of image processing, the

More information

IPSJ SIG Technical Report 1, Instrument Separation in Reverberant Environments Using Crystal Microphone Arrays Nobutaka ITO, 1, 2 Yu KITANO, 1

IPSJ SIG Technical Report 1, Instrument Separation in Reverberant Environments Using Crystal Microphone Arrays Nobutaka ITO, 1, 2 Yu KITANO, 1 1, 2 1 1 1 Instrument Separation in Reverberant Environments Using Crystal Microphone Arrays Nobutaka ITO, 1, 2 Yu KITANO, 1 Nobutaka ONO 1 and Shigeki SAGAYAMA 1 This paper deals with instrument separation

More information

untitled

untitled A = QΛQ T A n n Λ Q A = XΛX 1 A n n Λ X GPGPU A 3 T Q T AQ = T (Q: ) T u i = λ i u i T {λ i } {u i } QR MR 3 v i = Q u i A {v i } A n = 9000 Quad Core Xeon 2 LAPACK (4/3) n 3 O(n 2 ) O(n 3 ) A {v i }

More information

CPU Levels in the memory hierarchy Level 1 Level 2... Increasing distance from the CPU in access time Level n Size of the memory at each level 1: 2.2

CPU Levels in the memory hierarchy Level 1 Level 2... Increasing distance from the CPU in access time Level n Size of the memory at each level 1: 2.2 FFT 1 Fourier fast Fourier transform FFT FFT FFT 1 FFT FFT 2 Fourier 2.1 Fourier FFT Fourier discrete Fourier transform DFT DFT n 1 y k = j=0 x j ω jk n, 0 k n 1 (1) x j y k ω n = e 2πi/n i = 1 (1) n DFT

More information

2 (March 13, 2010) N Λ a = i,j=1 x i ( d (a) i,j x j ), Λ h = N i,j=1 x i ( d (h) i,j x j ) B a B h B a = N i,j=1 ν i d (a) i,j, B h = x j N i,j=1 ν i

2 (March 13, 2010) N Λ a = i,j=1 x i ( d (a) i,j x j ), Λ h = N i,j=1 x i ( d (h) i,j x j ) B a B h B a = N i,j=1 ν i d (a) i,j, B h = x j N i,j=1 ν i 1. A. M. Turing [18] 60 Turing A. Gierer H. Meinhardt [1] : (GM) ) a t = D a a xx µa + ρ (c a2 h + ρ 0 (0 < x < l, t > 0) h t = D h h xx νh + c ρ a 2 (0 < x < l, t > 0) a x = h x = 0 (x = 0, l) a = a(x,

More information

( ) a C n ( R n ) R a R C n. a C n (or R n ) a 0 2. α C( R ) a C n αa = α a 3. a, b C n a + b a + b ( ) p 8..2 (p ) a = [a a n ] T C n p n a

( ) a C n ( R n ) R a R C n. a C n (or R n ) a 0 2. α C( R ) a C n αa = α a 3. a, b C n a + b a + b ( ) p 8..2 (p ) a = [a a n ] T C n p n a 9 8 m n mn N.J.Nigham, Accuracy and Stability of Numerical Algorithms 2nd ed., (SIAM) x x = x2 + y 2 = x + y = max( x, y ) x y x () (norm) (condition number) 8. R C a, b C a b 0 a, b a = a 0 0 0 n C n

More information

& Vol.5 No (Oct. 2015) TV 1,2,a) , Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Ro

& Vol.5 No (Oct. 2015) TV 1,2,a) , Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Ro TV 1,2,a) 1 2 2015 1 26, 2015 5 21 Augmented TV TV AR Augmented Reality 3DCG TV Estimation of TV Screen Position and Rotation Using Mobile Device Hiroyuki Kawakita 1,2,a) Toshio Nakagawa 1 Makoto Sato

More information

FUJII, M. and KOSAKA, M. 2. J J [7] Fig. 1 J Fig. 2: Motivation and Skill improvement Model of J Orchestra Fig. 1: Motivating factors for a

FUJII, M. and KOSAKA, M. 2. J J [7] Fig. 1 J Fig. 2: Motivation and Skill improvement Model of J Orchestra Fig. 1: Motivating factors for a /Specially issued Original Paper QOL 1 1 A Proposal of Value Co-creation Model to Promote Elderly People s Community Activities Concerning QOL Improvement Case Studies of Successful Social Activities by

More information

EQUIVALENT TRANSFORMATION TECHNIQUE FOR ISLANDING DETECTION METHODS OF SYNCHRONOUS GENERATOR -REACTIVE POWER PERTURBATION METHODS USING AVR OR SVC- Ju

EQUIVALENT TRANSFORMATION TECHNIQUE FOR ISLANDING DETECTION METHODS OF SYNCHRONOUS GENERATOR -REACTIVE POWER PERTURBATION METHODS USING AVR OR SVC- Ju EQUIVALENT TRANSFORMATION TECHNIQUE FOR ISLANDING DETECTION METHODS OF SYNCHRONOUS GENERATOR -REACTIVE POWER PERTURBATION METHODS USING AVR OR SVC- Jun Motohashi, Member, Takashi Ichinose, Member (Tokyo

More information

4.1 % 7.5 %

4.1 % 7.5 % 2018 (412837) 4.1 % 7.5 % Abstract Recently, various methods for improving computial performance have been proposed. One of these various methods is Multi-core. Multi-core can execute processes in parallel

More information

磁気測定によるオーステンパ ダクタイル鋳鉄の残留オーステナイト定量

磁気測定によるオーステンパ ダクタイル鋳鉄の残留オーステナイト定量 33 Non-destructive Measurement of Retained Austenite Content in Austempered Ductile Iron Yoshio Kato, Sen-ichi Yamada, Takayuki Kato, Takeshi Uno Austempered Ductile Iron (ADI) 100kg/mm 2 10 ADI 10 X ADI

More information

1., 1 COOKPAD 2, Web.,,,,,,.,, [1]., 5.,, [2].,,.,.,, 5, [3].,,,.,, [4], 33,.,,.,,.. 2.,, 3.., 4., 5., ,. 1.,,., 2.,. 1,,

1., 1 COOKPAD 2, Web.,,,,,,.,, [1]., 5.,, [2].,,.,.,, 5, [3].,,,.,, [4], 33,.,,.,,.. 2.,, 3.., 4., 5., ,. 1.,,., 2.,. 1,, THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS TECHNICAL REPORT OF IEICE.,, 464 8601 470 0393 101 464 8601 E-mail: matsunagah@murase.m.is.nagoya-u.ac.jp, {ide,murase,hirayama}@is.nagoya-u.ac.jp,

More information

Vol. 42 No. SIG 8(TOD 10) July HTML 100 Development of Authoring and Delivery System for Synchronized Contents and Experiment on High Spe

Vol. 42 No. SIG 8(TOD 10) July HTML 100 Development of Authoring and Delivery System for Synchronized Contents and Experiment on High Spe Vol. 42 No. SIG 8(TOD 10) July 2001 1 2 3 4 HTML 100 Development of Authoring and Delivery System for Synchronized Contents and Experiment on High Speed Networks Yutaka Kidawara, 1 Tomoaki Kawaguchi, 2

More information

1_26.dvi

1_26.dvi C3PV 1,a) 2,b) 2,c) 3,d) 1,e) 2012 4 20, 2012 10 10 C3PV C3PV C3PV 1 Java C3PV 45 38 84% Programming Process Visualization for Supporting Students in Programming Exercise Hiroshi Igaki 1,a) Shun Saito

More information

Vol.54 No (May 2013) 7 1,a) , e e Factors and Strategies for Accelerating the Diffusion of Electronic Money Based

Vol.54 No (May 2013) 7 1,a) , e e Factors and Strategies for Accelerating the Diffusion of Electronic Money Based 7 1,a) 2 2012 7 4, 2013 2 1 7 5 8 e e Factors and Strategies for Accelerating the Diffusion of Electronic Money Based on a Consumer Survey in Seven Regions in Japan Kazuo Watabe 1,a) Kunihiko Iwasaki 2

More information

23 Study on Generation of Sudoku Problems with Fewer Clues

23 Study on Generation of Sudoku Problems with Fewer Clues 23 Study on Generation of Sudoku Problems with Fewer Clues 1120254 2012 3 1 9 9 21 18 i Abstract Study on Generation of Sudoku Problems with Fewer Clues Norimasa NASU Sudoku is puzzle a kind of pencil

More information

IIC Proposal of Range Extension Control System by Drive and Regeneration Distribution Based on Efficiency Characteristic of Motors for Electric

IIC Proposal of Range Extension Control System by Drive and Regeneration Distribution Based on Efficiency Characteristic of Motors for Electric IIC-1-19 Proposal of Range Extension Control System by Drive and Regeneration Distribution Based on Efficiency Characteristic of Motors for Electric Vehicle Toru Suzuki, Hiroshi Fujimoto (Yokohama National

More information

HP cafe HP of A A B of C C Map on N th Floor coupon A cafe coupon B Poster A Poster A Poster B Poster B Case 1 Show HP of each company on a user scree

HP cafe HP of A A B of C C Map on N th Floor coupon A cafe coupon B Poster A Poster A Poster B Poster B Case 1 Show HP of each company on a user scree LAN 1 2 3 2 LAN WiFiTag WiFiTag LAN LAN 100% WiFi Tag An Improved Determination Method with Multiple Access Points for Relative Position Estimation Using Wireless LAN Abstract: We have proposed a WiFiTag

More information

Vol.54 No (July 2013) [9] [10] [11] [12], [13] 1 Fig. 1 Flowchart of the proposed system. c 2013 Information

Vol.54 No (July 2013) [9] [10] [11] [12], [13] 1 Fig. 1 Flowchart of the proposed system. c 2013 Information Vol.54 No.7 1937 1950 (July 2013) 1,a) 2012 11 1, 2013 4 5 1 Similar Sounds Sentences Generator Based on Morphological Analysis Manner and Low Class Words Masaaki Kanakubo 1,a) Received: November 1, 2012,

More information

MDD PBL ET 9) 2) ET ET 2.2 2), 1 2 5) MDD PBL PBL MDD MDD MDD 10) MDD Executable UML 11) Executable UML MDD Executable UML

MDD PBL ET 9) 2) ET ET 2.2 2), 1 2 5) MDD PBL PBL MDD MDD MDD 10) MDD Executable UML 11) Executable UML MDD Executable UML PBL 1 2 3 4 (MDD) PBL Project Based Learning MDD PBL PBL PBL MDD PBL A Software Development PBL for Beginners using Project Facilitation Tools Seiko Akayama, 1 Shin Kuboaki, 2 Kenji Hisazumi 3 and Takao

More information

IPSJ SIG Technical Report Vol.2009-BIO-17 No /5/26 DNA 1 1 DNA DNA DNA DNA Correcting read errors on DNA sequences determined by Pyrosequencing

IPSJ SIG Technical Report Vol.2009-BIO-17 No /5/26 DNA 1 1 DNA DNA DNA DNA Correcting read errors on DNA sequences determined by Pyrosequencing DNA 1 1 DNA DNA DNA DNA Correcting read errors on DNA sequences determined by Pyrosequencing Youhei Namiki 1 and Yutaka Akiyama 1 Pyrosequencing, one of the DNA sequencing technologies, allows us to determine

More information

Studies of Foot Form for Footwear Design (Part 9) : Characteristics of the Foot Form of Young and Elder Women Based on their Sizes of Ball Joint Girth

Studies of Foot Form for Footwear Design (Part 9) : Characteristics of the Foot Form of Young and Elder Women Based on their Sizes of Ball Joint Girth Studies of Foot Form for Footwear Design (Part 9) : Characteristics of the Foot Form of Young and Elder Women Based on their Sizes of Ball Joint Girth and Foot Breadth Akiko Yamamoto Fukuoka Women's University,

More information

知能と情報, Vol.30, No.5, pp

知能と情報, Vol.30, No.5, pp 1, Adobe Illustrator Photoshop [1] [2] [3] Initital Values Assignment of Parameters Using Onomatopoieas for Interactive Design Tool Tsuyoshi NAKAMURA, Yuki SAWAMURA, Masayoshi KANOH, and Koji YAMADA Graduate

More information

Shonan Institute of Technology MEMOIRS OF SHONAN INSTITUTE OF TECHNOLOGY Vol. 41, No. 1, 2007 Ships1 * ** ** ** Development of a Small-Mid Range Paral

Shonan Institute of Technology MEMOIRS OF SHONAN INSTITUTE OF TECHNOLOGY Vol. 41, No. 1, 2007 Ships1 * ** ** ** Development of a Small-Mid Range Paral MEMOIRS OF SHONAN INSTITUTE OF TECHNOLOGY Vol. 41, No. 1, 2007 Ships1 * ** ** ** Development of a Small-Mid Range Parallel Computer Ships1 Makoto OYA*, Hiroto MATSUBARA**, Kazuyoshi SAKURAI** and Yu KATO**

More information

特-3.indd

特-3.indd Development of Automation Technology for Precision Finishing Works Employing a Robot Arm There is demand for the automation of finishing processes that require technical skills in the manufacturing of

More information

21 Key Exchange method for portable terminal with direct input by user

21 Key Exchange method for portable terminal with direct input by user 21 Key Exchange method for portable terminal with direct input by user 1110251 2011 3 17 Diffie-Hellman,..,,,,.,, 2.,.,..,,.,, Diffie-Hellman, i Abstract Key Exchange method for portable terminal with

More information

COE-RES Discussion Paper Series Center of Excellence Project The Normative Evaluation and Social Choice of Contemporary Economic Systems Graduate Scho

COE-RES Discussion Paper Series Center of Excellence Project The Normative Evaluation and Social Choice of Contemporary Economic Systems Graduate Scho COE-RES Discussion Paper Series Center of Excellence Project The Normative Evaluation and Social Choice of Contemporary Economic Systems Graduate School of Economics and Institute of Economic Research

More information

2. CABAC CABAC CABAC 1 1 CABAC Figure 1 Overview of CABAC 2 DCT 2 0/ /1 CABAC [3] 3. 2 値化部 コンテキスト計算部 2 値算術符号化部 CABAC CABAC

2. CABAC CABAC CABAC 1 1 CABAC Figure 1 Overview of CABAC 2 DCT 2 0/ /1 CABAC [3] 3. 2 値化部 コンテキスト計算部 2 値算術符号化部 CABAC CABAC H.264 CABAC 1 1 1 1 1 2, CABAC(Context-based Adaptive Binary Arithmetic Coding) H.264, CABAC, A Parallelization Technology of H.264 CABAC For Real Time Encoder of Moving Picture YUSUKE YATABE 1 HIRONORI

More information

IPSJ SIG Technical Report Vol.2010-SLDM-144 No.50 Vol.2010-EMB-16 No.50 Vol.2010-MBL-53 No.50 Vol.2010-UBI-25 No /3/27 Twitter IME Twitte

IPSJ SIG Technical Report Vol.2010-SLDM-144 No.50 Vol.2010-EMB-16 No.50 Vol.2010-MBL-53 No.50 Vol.2010-UBI-25 No /3/27 Twitter IME Twitte Twitter 1 1 1 IME Twitter 2009 12 15 2010 2 1 13590 4.83% 8.16% 2 3 Web 10 45% Relational Analysis between User Context and Input Word on Twitter Yutaka Arakawa, 1 Shigeaki Tagashira 1 and Akira Fukuda

More information

Krylov A04 October 8, 2010 T. Sakurai (Univ. Tsukuba) Krylov October 8, / 48

Krylov A04 October 8, 2010 T. Sakurai (Univ. Tsukuba) Krylov October 8, / 48 Krylov A04 October 8, 2010 T. Sakurai (Univ. Tsukuba) Krylov October 8, 2010 1 / 48 Krylov QCD, RSDFT, Shell model Block Krylov MATLAB Scilab T. Sakurai (Univ. Tsukuba) Krylov October 8, 2010 2 / 48 Krylov

More information

Bulletin of JSSAC(2014) Vol. 20, No. 2, pp (Received 2013/11/27 Revised 2014/3/27 Accepted 2014/5/26) It is known that some of number puzzles ca

Bulletin of JSSAC(2014) Vol. 20, No. 2, pp (Received 2013/11/27 Revised 2014/3/27 Accepted 2014/5/26) It is known that some of number puzzles ca Bulletin of JSSAC(2014) Vol. 20, No. 2, pp. 3-22 (Received 2013/11/27 Revised 2014/3/27 Accepted 2014/5/26) It is known that some of number puzzles can be solved by using Gröbner bases. In this paper,

More information

(MIRU2008) HOG Histograms of Oriented Gradients (HOG)

(MIRU2008) HOG Histograms of Oriented Gradients (HOG) (MIRU2008) 2008 7 HOG - - E-mail: katsu0920@me.cs.scitec.kobe-u.ac.jp, {takigu,ariki}@kobe-u.ac.jp Histograms of Oriented Gradients (HOG) HOG Shape Contexts HOG 5.5 Histograms of Oriented Gradients D Human

More information

MAC root Linux 1 OS Linux 2.6 Linux Security Modules LSM [1] Security-Enhanced Linux SELinux [2] AppArmor[3] OS OS OS LSM LSM Performance Monitor LSMP

MAC root Linux 1 OS Linux 2.6 Linux Security Modules LSM [1] Security-Enhanced Linux SELinux [2] AppArmor[3] OS OS OS LSM LSM Performance Monitor LSMP LSM OS 700-8530 3 1 1 matsuda@swlab.it.okayama-u.ac.jp tabata@cs.okayama-u.ac.jp 242-8502 1623 14 munetoh@jp.ibm.com OS Linux 2.6 Linux Security Modules LSM LSM Linux 4 OS OS LSM An Evaluation of Performance

More information

,,,,., C Java,,.,,.,., ,,.,, i

,,,,., C Java,,.,,.,., ,,.,, i 24 Development of the programming s learning tool for children be derived from maze 1130353 2013 3 1 ,,,,., C Java,,.,,.,., 1 6 1 2.,,.,, i Abstract Development of the programming s learning tool for children

More information

7,, i

7,, i 23 Research of the authentication method on the two dimensional code 1145111 2012 2 13 7,, i Abstract Research of the authentication method on the two dimensional code Karita Koichiro Recently, the two

More information

149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 :

149 (Newell [5]) Newell [5], [1], [1], [11] Li,Ryu, and Song [2], [11] Li,Ryu, and Song [2], [1] 1) 2) ( ) ( ) 3) T : 2 a : 3 a 1 : Transactions of the Operations Research Society of Japan Vol. 58, 215, pp. 148 165 c ( 215 1 2 ; 215 9 3 ) 1) 2) :,,,,, 1. [9] 3 12 Darroch,Newell, and Morris [1] Mcneil [3] Miller [4] Newell [5, 6], [1]

More information

1 (1997) (1997) 1974:Q3 1994:Q3 (i) (ii) ( ) ( ) 1 (iii) ( ( 1999 ) ( ) ( ) 1 ( ) ( 1995,pp ) 1

1 (1997) (1997) 1974:Q3 1994:Q3 (i) (ii) ( ) ( ) 1 (iii) ( ( 1999 ) ( ) ( ) 1 ( ) ( 1995,pp ) 1 1 (1997) (1997) 1974:Q3 1994:Q3 (i) (ii) ( ) ( ) 1 (iii) ( ( 1999 ) ( ) ( ) 1 ( ) ( 1995,pp.218 223 ) 1 2 ) (i) (ii) / (iii) ( ) (i ii) 1 2 1 ( ) 3 ( ) 2, 3 Dunning(1979) ( ) 1 2 ( ) ( ) ( ) (,p.218) (

More information

The 19th Game Programming Workshop 2014 SHOT 1,a) 2 UCT SHOT UCT SHOT UCT UCT SHOT UCT An Empirical Evaluation of the Effectiveness of the SHOT algori

The 19th Game Programming Workshop 2014 SHOT 1,a) 2 UCT SHOT UCT SHOT UCT UCT SHOT UCT An Empirical Evaluation of the Effectiveness of the SHOT algori SHOT 1,a) 2 UCT SHOT UCT SHOT UCT UCT SHOT UCT An Empirical Evaluation of the Effectiveness of the SHOT algorithm in Go and Gobang Masahiro Honjo 1,a) Yoshimasa Tsuruoka 2 Abstract: Today, UCT is the most

More information

29 jjencode JavaScript

29 jjencode JavaScript Kochi University of Technology Aca Title jjencode で難読化された JavaScript の検知 Author(s) 中村, 弘亮 Citation Date of 2018-03 issue URL http://hdl.handle.net/10173/1975 Rights Text version author Kochi, JAPAN http://kutarr.lib.kochi-tech.ac.jp/dspa

More information

untitled

untitled A = QΛQ T A n n Λ Q A = XΛX 1 A n n Λ X GPGPU A 3 T Q T AQ = T (Q: ) T u i = λ i u i T {λ i } {u i } QR MR 3 v i = Q u i A {v i } A n = 9000 Quad Core Xeon 2 LAPACK (4/3) n 3 O(n 2 ) O(n 3 ) A {v i }

More information

., White-Box, White-Box. White-Box.,, White-Box., Maple [11], 2. 1, QE, QE, 1 Redlog [7], QEPCAD [9], SyNRAC [8] 3 QE., 2 Brown White-Box. 3 White-Box

., White-Box, White-Box. White-Box.,, White-Box., Maple [11], 2. 1, QE, QE, 1 Redlog [7], QEPCAD [9], SyNRAC [8] 3 QE., 2 Brown White-Box. 3 White-Box White-Box Takayuki Kunihiro Graduate School of Pure and Applied Sciences, University of Tsukuba Hidenao Iwane ( ) / Fujitsu Laboratories Ltd. / National Institute of Informatics. Yumi Wada Graduate School

More information

IPSJ SIG Technical Report Vol.2012-CG-148 No /8/29 3DCG 1,a) On rigid body animation taking into account the 3D computer graphics came

IPSJ SIG Technical Report Vol.2012-CG-148 No /8/29 3DCG 1,a) On rigid body animation taking into account the 3D computer graphics came 3DCG 1,a) 2 2 2 2 3 On rigid body animation taking into account the 3D computer graphics camera viewpoint Abstract: In using computer graphics for making games or motion pictures, physics simulation is

More information

23 Fig. 2: hwmodulev2 3. Reconfigurable HPC 3.1 hw/sw hw/sw hw/sw FPGA PC FPGA PC FPGA HPC FPGA FPGA hw/sw hw/sw hw- Module FPGA hwmodule hw/sw FPGA h

23 Fig. 2: hwmodulev2 3. Reconfigurable HPC 3.1 hw/sw hw/sw hw/sw FPGA PC FPGA PC FPGA HPC FPGA FPGA hw/sw hw/sw hw- Module FPGA hwmodule hw/sw FPGA h 23 FPGA CUDA Performance Comparison of FPGA Array with CUDA on Poisson Equation (lijiang@sekine-lab.ei.tuat.ac.jp), (kazuki@sekine-lab.ei.tuat.ac.jp), (takahashi@sekine-lab.ei.tuat.ac.jp), (tamukoh@cc.tuat.ac.jp),

More information

浜松医科大学紀要

浜松医科大学紀要 On the Statistical Bias Found in the Horse Racing Data (1) Akio NODA Mathematics Abstract: The purpose of the present paper is to report what type of statistical bias the author has found in the horse

More information

SQUFOF NTT Shanks SQUFOF SQUFOF Pentium III Pentium 4 SQUFOF 2.03 (Pentium 4 2.0GHz Willamette) N UBASIC 50 / 200 [

SQUFOF NTT Shanks SQUFOF SQUFOF Pentium III Pentium 4 SQUFOF 2.03 (Pentium 4 2.0GHz Willamette) N UBASIC 50 / 200 [ SQUFOF SQUFOF NTT 2003 2 17 16 60 Shanks SQUFOF SQUFOF Pentium III Pentium 4 SQUFOF 2.03 (Pentium 4 2.0GHz Willamette) 60 1 1.1 N 62 16 24 UBASIC 50 / 200 [ 01] 4 large prime 943 2 1 (%) 57 146 146 15

More information

133 1.,,, [1] [2],,,,, $[3],[4]$,,,,,,,,, [5] [6],,,,,, [7], interface,,,, Navier-Stokes, $Petr\dot{o}$v-Galerkin [8], $(,)$ $()$,,

133 1.,,, [1] [2],,,,, $[3],[4]$,,,,,,,,, [5] [6],,,,,, [7], interface,,,, Navier-Stokes, $Petr\dot{o}$v-Galerkin [8], $(,)$ $()$,, 836 1993 132-146 132 Navier-Stokes Numerical Simulations for the Navier-Stokes Equations in Incompressible Viscous Fluid Flows (Nobuyoshi Tosaka) (Kazuhiko Kakuda) SUMMARY A coupling approach of the boundary

More information

第5章 偏微分方程式の境界値問題

第5章 偏微分方程式の境界値問題 October 5, 2018 1 / 113 4 ( ) 2 / 113 Poisson 5.1 Poisson ( A.7.1) Poisson Poisson 1 (A.6 ) Γ p p N u D Γ D b 5.1.1: = Γ D Γ N 3 / 113 Poisson 5.1.1 d {2, 3} Lipschitz (A.5 ) Γ D Γ N = \ Γ D Γ p Γ N Γ

More information

12) NP 2 MCI MCI 1 START Simple Triage And Rapid Treatment 3) START MCI c 2010 Information Processing Society of Japan

12) NP 2 MCI MCI 1 START Simple Triage And Rapid Treatment 3) START MCI c 2010 Information Processing Society of Japan 1 1, 2 1, 2 1 A Proposal of Ambulance Scheduling System Based on Electronic Triage Tag Teruhiro Mizumoto, 1 Weihua Sun, 1, 2 Keiichi Yasumoto 1, 2 and Minoru Ito 1 For effective life-saving in MCI (Mass

More information

,4) 1 P% P%P=2.5 5%!%! (1) = (2) l l Figure 1 A compilation flow of the proposing sampling based architecture simulation

,4) 1 P% P%P=2.5 5%!%! (1) = (2) l l Figure 1 A compilation flow of the proposing sampling based architecture simulation 1 1 1 1 SPEC CPU 2000 EQUAKE 1.6 50 500 A Parallelizing Compiler Cooperative Multicore Architecture Simulator with Changeover Mechanism of Simulation Modes GAKUHO TAGUCHI 1 YOUICHI ABE 1 KEIJI KIMURA 1

More information

Instability of Aerostatic Journal Bearings with Porous Floating Bush at High Speeds Masaaki MIYATAKE *4, Shigeka YOSHIMOTO, Tomoaki CHIBA and Akira CH

Instability of Aerostatic Journal Bearings with Porous Floating Bush at High Speeds Masaaki MIYATAKE *4, Shigeka YOSHIMOTO, Tomoaki CHIBA and Akira CH Instability of Aerostatic Journal Bearings with Porous Floating Bush at High Speeds Masaaki MIYATAKE *4, Shigeka YOSHIMOTO, Tomoaki CHIBA and Akira CHIBA Department of Mechanical Engineering, Tokyo University

More information

258 5) GPS 1 GPS 6) GPS DP 7) 8) 10) GPS GPS 2 3 4 5 2. 2.1 3 1) GPS Global Positioning System

258 5) GPS 1 GPS 6) GPS DP 7) 8) 10) GPS GPS 2 3 4 5 2. 2.1 3 1) GPS Global Positioning System Vol. 52 No. 1 257 268 (Jan. 2011) 1 2, 1 1 measurement. In this paper, a dynamic road map making system is proposed. The proposition system uses probe-cars which has an in-vehicle camera and a GPS receiver.

More information

1 1 tf-idf tf-idf i

1 1 tf-idf tf-idf i 14 A Method of Article Retrieval Utilizing Characteristics in Newspaper Articles 1055104 2003 1 31 1 1 tf-idf tf-idf i Abstract A Method of Article Retrieval Utilizing Characteristics in Newspaper Articles

More information

Study on Throw Accuracy for Baseball Pitching Machine with Roller (Study of Seam of Ball and Roller) Shinobu SAKAI*5, Juhachi ODA, Kengo KAWATA and Yu

Study on Throw Accuracy for Baseball Pitching Machine with Roller (Study of Seam of Ball and Roller) Shinobu SAKAI*5, Juhachi ODA, Kengo KAWATA and Yu Study on Throw Accuracy for Baseball Pitching Machine with Roller (Study of Seam of Ball and Roller) Shinobu SAKAI*5, Juhachi ODA, Kengo KAWATA and Yuichiro KITAGAWA Department of Human and Mechanical

More information

SEJulyMs更新V7

SEJulyMs更新V7 1 2 ( ) Quantitative Characteristics of Software Process (Is There any Myth, Mystery or Anomaly? No Silver Bullet?) Zenya Koono and Hui Chen A process creates a product. This paper reviews various samples

More information

IPSJ SIG Technical Report Secret Tap Secret Tap Secret Flick 1 An Examination of Icon-based User Authentication Method Using Flick Input for

IPSJ SIG Technical Report Secret Tap Secret Tap Secret Flick 1 An Examination of Icon-based User Authentication Method Using Flick Input for 1 2 3 3 1 Secret Tap Secret Tap Secret Flick 1 An Examination of Icon-based User Authentication Method Using Flick Input for Mobile Terminals Kaoru Wasai 1 Fumio Sugai 2 Yosihiro Kita 3 Mi RangPark 3 Naonobu

More information

1 DHT Fig. 1 Example of DHT 2 Successor Fig. 2 Example of Successor 2.1 Distributed Hash Table key key value O(1) DHT DHT 1 DHT 1 ID key ID IP value D

1 DHT Fig. 1 Example of DHT 2 Successor Fig. 2 Example of Successor 2.1 Distributed Hash Table key key value O(1) DHT DHT 1 DHT 1 ID key ID IP value D P2P 1,a) 1 1 Peer-to-Peer P2P P2P P2P Chord P2P Chord Consideration for Efficient Construction of Distributed Hash Trees on P2P Systems Taihei Higuchi 1,a) Masakazu Soshi 1 Tomoyuki Asaeda 1 Abstract:

More information

<95DB8C9288E397C389C88A E696E6462>

<95DB8C9288E397C389C88A E696E6462> 2011 Vol.60 No.2 p.138 147 Performance of the Japanese long-term care benefit: An International comparison based on OECD health data Mie MORIKAWA[1] Takako TSUTSUI[2] [1]National Institute of Public Health,

More information

19 Systematization of Problem Solving Strategy in High School Mathematics for Improving Metacognitive Ability

19 Systematization of Problem Solving Strategy in High School Mathematics for Improving Metacognitive Ability 19 Systematization of Problem Solving Strategy in High School Mathematics for Improving Metacognitive Ability 1105402 2008 2 4 2,, i Abstract Systematization of Problem Solving Strategy in High School

More information

yasi10.dvi

yasi10.dvi 2002 50 2 259 278 c 2002 1 2 2002 2 14 2002 6 17 73 PML 1. 1997 1998 Swiss Re 2001 Canabarro et al. 1998 2001 1 : 651 0073 1 5 1 IHD 3 2 110 0015 3 3 3 260 50 2 2002, 2. 1 1 2 10 1 1. 261 1. 3. 3.1 2 1

More information

情報処理学会研究報告 IPSJ SIG Technical Report Vol.2013-HPC-139 No /5/29 Gfarm/Pwrake NICT NICT 10TB 100TB CPU I/O HPC I/O NICT Gf

情報処理学会研究報告 IPSJ SIG Technical Report Vol.2013-HPC-139 No /5/29 Gfarm/Pwrake NICT NICT 10TB 100TB CPU I/O HPC I/O NICT Gf Gfarm/Pwrake NICT 1 1 1 1 2 2 3 4 5 5 5 6 NICT 10TB 100TB CPU I/O HPC I/O NICT Gfarm Gfarm Pwrake A Parallel Processing Technique on the NICT Science Cloud via Gfarm/Pwrake KEN T. MURATA 1 HIDENOBU WATANABE

More information

(a) 1 (b) 3. Gilbert Pernicka[2] Treibitz Schechner[3] Narasimhan [4] Kim [5] Nayar [6] [7][8][9] 2. X X X [10] [11] L L t L s L = L t + L s

(a) 1 (b) 3. Gilbert Pernicka[2] Treibitz Schechner[3] Narasimhan [4] Kim [5] Nayar [6] [7][8][9] 2. X X X [10] [11] L L t L s L = L t + L s 1 1 1, Extraction of Transmitted Light using Parallel High-frequency Illumination Kenichiro Tanaka 1 Yasuhiro Mukaigawa 1 Yasushi Yagi 1 Abstract: We propose a new sharpening method of transmitted scene

More information

[2] 2. [3 5] 3D [6 8] Morishima [9] N n 24 24FPS k k = 1, 2,..., N i i = 1, 2,..., n Algorithm 1 N io user-specified number of inbetween omis

[2] 2. [3 5] 3D [6 8] Morishima [9] N n 24 24FPS k k = 1, 2,..., N i i = 1, 2,..., n Algorithm 1 N io user-specified number of inbetween omis 1,a) 2 2 2 1 2 3 24 Motion Frame Omission for Cartoon-like Effects Abstract: Limited animation is a hand-drawn animation style that holds each drawing for two or three successive frames to make up 24 frames

More information

橡表紙参照.PDF

橡表紙参照.PDF CIRJE-J-58 X-12-ARIMA 2000 : 2001 6 How to use X-12-ARIMA2000 when you must: A Case Study of Hojinkigyo-Tokei Naoto Kunitomo Faculty of Economics, The University of Tokyo Abstract: We illustrate how to

More information

Fig. 3 3 Types considered when detecting pattern violations 9)12) 8)9) 2 5 methodx close C Java C Java 3 Java 1 JDT Core 7) ) S P S

Fig. 3 3 Types considered when detecting pattern violations 9)12) 8)9) 2 5 methodx close C Java C Java 3 Java 1 JDT Core 7) ) S P S 1 1 1 Fig. 1 1 Example of a sequential pattern that is exracted from a set of method definitions. A Defect Detection Method for Object-Oriented Programs using Sequential Pattern Mining Goro YAMADA, 1 Norihiro

More information

29 Short-time prediction of time series data for binary option trade

29 Short-time prediction of time series data for binary option trade 29 Short-time prediction of time series data for binary option trade 1180365 2018 2 28 RSI(Relative Strength Index) 3 USD/JPY 1 2001 1 2 4 10 2017 12 29 17 00 1 high low i Abstract Short-time prediction

More information

特集_03-07.Q3C

特集_03-07.Q3C 3-7 Error Detection and Authentication in Quantum Key Distribution YAMAMURA Akihiro and ISHIZUKA Hirokazu Detecting errors in a raw key and authenticating a private key are crucial for quantum key distribution

More information

2. Eades 1) Kamada-Kawai 7) Fruchterman 2) 6) ACE 8) HDE 9) Kruskal MDS 13) 11) Kruskal AGI Active Graph Interface 3) Kruskal 5) Kruskal 4) 3. Kruskal

2. Eades 1) Kamada-Kawai 7) Fruchterman 2) 6) ACE 8) HDE 9) Kruskal MDS 13) 11) Kruskal AGI Active Graph Interface 3) Kruskal 5) Kruskal 4) 3. Kruskal 1 2 3 A projection-based method for interactive 3D visualization of complex graphs Masanori Takami, 1 Hiroshi Hosobe 2 and Ken Wakita 3 Proposed is a new interaction technique to manipulate graph layouts

More information

第1章 微分方程式と近似解法

第1章 微分方程式と近似解法 April 12, 2018 1 / 52 1.1 ( ) 2 / 52 1.2 1.1 1.1: 3 / 52 1.3 Poisson Poisson Poisson 1 d {2, 3} 4 / 52 1 1.3.1 1 u,b b(t,x) u(t,x) x=0 1.1: 1 a x=l 1.1 1 (0, t T ) (0, l) 1 a b : (0, t T ) (0, l) R, u

More information

電子マネーと通信産業の戦略

電子マネーと通信産業の戦略 No.7, 55-65 (2006) Vision of Electronic Money Card Distribution Plans in Japan - Discussion of the and Credit Card Distribution Plans - OSHIMA Kazuchika Nihon University, Graduate School of Social and

More information

28 SAS-X Proposal of Multi Device Authenticable Password Management System using SAS-X 1195074 2017 2 3 SAS-X Web ID/ ID/ Web SAS-2 SAS-X i Abstract Proposal of Multi Device Authenticable Password Management

More information

ActionScript Flash Player 8 ActionScript3.0 ActionScript Flash Video ActionScript.swf swf FlashPlayer AVM(Actionscript Virtual Machine) Windows

ActionScript Flash Player 8 ActionScript3.0 ActionScript Flash Video ActionScript.swf swf FlashPlayer AVM(Actionscript Virtual Machine) Windows ActionScript3.0 1 1 YouTube Flash ActionScript3.0 Face detection and hiding using ActionScript3.0 for streaming video on the Internet Ryouta Tanaka 1 and Masanao Koeda 1 Recently, video streaming and video

More information

17 Proposal of an Algorithm of Image Extraction and Research on Improvement of a Man-machine Interface of Food Intake Measuring System

17 Proposal of an Algorithm of Image Extraction and Research on Improvement of a Man-machine Interface of Food Intake Measuring System 1. (1) ( MMI ) 2. 3. MMI Personal Computer(PC) MMI PC 1 1 2 (%) (%) 100.0 95.2 100.0 80.1 2 % 31.3% 2 PC (3 ) (2) MMI 2 ( ),,,, 49,,p531-532,2005 ( ),,,,,2005,p66-p67,2005 17 Proposal of an Algorithm of

More information

IPSJ SIG Technical Report Pitman-Yor 1 1 Pitman-Yor n-gram A proposal of the melody generation method using hierarchical pitman-yor language model Aki

IPSJ SIG Technical Report Pitman-Yor 1 1 Pitman-Yor n-gram A proposal of the melody generation method using hierarchical pitman-yor language model Aki Pitman-Yor Pitman-Yor n-gram A proposal of the melody generation method using hierarchical pitman-yor language model Akira Shirai and Tadahiro Taniguchi Although a lot of melody generation method has been

More information

Isogai, T., Building a dynamic correlation network for fat-tailed financial asset returns, Applied Network Science (7):-24, 206,

Isogai, T., Building a dynamic correlation network for fat-tailed financial asset returns, Applied Network Science (7):-24, 206, H28. (TMU) 206 8 29 / 34 2 3 4 5 6 Isogai, T., Building a dynamic correlation network for fat-tailed financial asset returns, Applied Network Science (7):-24, 206, http://link.springer.com/article/0.007/s409-06-0008-x

More information