untitled

Size: px
Start display at page:

Download "untitled"

Transcription

1 c OR [1] OR Homeland Security (OR) [2] OR 1972 Chaiken and Larson [3] (1) (2) (3) (4) (5) OR 68 Olson and Wright [4] hozaki@nda.ac.jp Koopman [5] Homeland Security (Stackelberg game) Homeland Security Patrolling security game (PSG) Stackelberg security game (SSG) (Security game) PSG SSG Olson and Wright Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited.

2 Garnaev et al. [6] N x 1 =(x 1 1,...,x 1 N) y =(y 1,...,y N ) C i i v i(x 1, y) u 1 A(x 1, y) = N i=1 Civi(x1, y) x 2 y u 2 A(x 2, y) 1 2 q, 1 q u D(y, (x 1, x 2 )) = {qu 1 A(x 1, y)+(1 q)u 2 A(x 2, y)} x 1, x 2, y x 1, x 2, y u 1 A(x 1, y ) u 1 A(x 1, y ), u 2 A(x 2, y ) u 2 A(x 2, y ), U D(y, (x 1, x 2 )) U D(y, (x 1, x 2 )). u k A(x k, y) u 1 A(x 1, y) = N C ix 1 i (1 d iy i), (1) i=1 u 2 A(x 2, y) =D N x 2 i (1 d iy i), (2) i=1 C i = heipi g EjJ, d σe 2 i = σe 2 + geij P i i h Ei σ E J, g Ej D x k, y (1), (2) Yang et al. [7] SSG SSG Garnaev et al Yang et al 2 [8] Basilico et al. [9] PSG Olson and Wright SSG Tsai et al. [10] [11] [12 16] [1] 2007 ARMOR (Assistant for randomized monitoring over routes) 2009 IRIS (Intelligent randomization in scheduling) ARMOR DOBSS (Decomposed optimal Bayesian Stackelberg solver) Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited

3 400 GUARDS (Game-theoretic unpredictable and randomly deployed security) PROTECT (Port resilience operational/tactical enforcement to combat terrorism) Tambe [17] 3. 1 [18] Hohzaki et al. [19] 1 2 s t p s(t) j q j(i),i=1,...,l j (δ {1, 0}) (2) (d) (3) (α) δα/d 2 1 p s q j q j t j f j(t) f j 1( ) f j( ) { } f j(t) =min z f j 1(z)+D j 1(z)+E j (t) (3) D j 1(z) z j Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited.

4 j E j (t) j t CCD (3) f j(t) j t f j(t) =minmin i z f i(z)+d j i (z)+ej (t) { } D j i (z) j i z j f j(t) j t [20] E2C AWACS (Airborne warning and control system) (P TR) (G A) (λ) (σ) (R) P TRG 2 Aλ 2 σ/(4π) 3 R 4 3 (3) z 2 6 IR1 IR6 IR4 4 PR1 PR4 FR Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited

5 2 PR3 PR IR4 IR IR4 IR5 4. Hohzaki and Chiba [21] 2 2 (Attrition game) 2 [22] N A H h H R0 h e 1 d h e Ω h S s S B0 s s U(s) h f(h) e h s γe hs h x s y y f e(x, y) =max{0, x γ hs e y} (4) 0 (4) Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited.

6 2 h H l π h (l) π h = {π h (l),l Ω h } s e ye s y s = {ye,e s A} s g(s) E l l El e l e h l s y s e Rhs(l, I y s )= d h e max 0,Rh 0 γ hs e ys e (5) e E l e E e l g(s) h π h Rh(l, I (g,y)) = g(s)rhs(l, I y s ) s S Rh(π I h, (g,y)) = π h (l)rh(l, I (g,y)) l Ω h (g,y)={(g(s), y s ),s S} h max πh Rh(π I h, (g,y)) π h f(h) h H f(h)maxπ h RI h(π h, (g,y)) (g,y) {π h,h H} (g,y) R I (π,(g,y)) = f(h) π h (l) g(s)rhs(l, I y s ) h H l Ω h s S 2 (5) R II (π, (g,y)) = f(h) π h (l) h H l Ω h max dh e R0 h γ hs e g(s)ys e, e E l s S e E l e d h e R0 h γ hs e g(s)ys e s S e E e l d h e d h e e 3 [23] H = {1, 2} h =1 2 5, 6, 7, h = Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited

7 4 B B , 14, f(1) = 0.8, f(2) = 0.2 R0 1 =5,R0 2 =10 S = {1, 2} 2 s =1 s =2 U(2) = 0.3 γe hs s =2 γe hs B0,B s = 2 s = 1 2 g(s) s C g(1)b0 1 +2g(2)B0 2 1 s =1 B0 1 s =2 γe hs s =1 g(2) = 0.3 s =2 B0 1 B0 2 (C 0.7B0 1 )/(2 0.3) C = B0 1 ye s 4 s =1 2 B0 1 =9, B0 2 =22.8 C 5 s =1 1 s =2 B0 1 B , 13 C (1) (2) Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited.

8 (i) γe hs (ii) d h e (iii) (3) 5. 4 [1] 60, pp , [2] J. Herrmann (ed.), Handbook of Operations Research for Homeland Security, Springer Science & Business Media, [3]J.M.ChaikenandR.C.Larson, Methodsforallocating urban emergency units: A survey, Management Science, 19, pp , [4] D. G. Olson and G. P. Wright, Models for allocating police preventive patrol effort, Operational Research Quarterly, 26, pp , [5] B. O. Koopman, Search and screening, Operations Evaluation Group Report No. 56, [6] A. Garnaev, M. Baykal-Gursoy and H. V. Poor, Incorporating attack-type uncertainty into network protection, IEEE Transactions on Information Forensics and Security, 9, pp , [7] R. Yang, C. Kiekintveld, F. Ordonez, M. Tambe and R. John, Improving resource allocation strategies against human adversaries in security games: An extended study, Artificial Intelligence, 195, pp , [8] A. R. Washburn, TPZS applications: Blotto games, Wiley Encyclopedia of Operations Research and Management Science, 7, pp , [9] N. Basilico, N. Gatti and F. Amigoni, Patrolling security games: Definition and algorithms for solving large instances with single patroller and single intruder, Artificial Intelligence, 184, pp , [10] J. Tsai, Z. Yin, J. Y. Kwak, D. Kempe, C. Kiekintveld and M. Tambe, Urban security: Gametheoretic resource allocation in networked physical domains, In Proceedings of the 24th AAAI Conference on Artificial Intelligence, pp , [11] 2015 pp. 4 5, [12] J. Salmeron, R. K. Wood and R. Baldick, Analysis of electric grid security under terrorist threat, IEEE Transactions on Power Systems, 19, pp , [13] J. Pita, M. Jain, F. Ordonez, C. Portway, M. Tambe and C. Western, Using game theory for Los Angeles airport security, AI Magazine, pp , [14] M. Kodialam and T. V. Lakshman, Detecting network intrusions via sampling: A game theoretical approach, In Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications (IEEE INFOCOM), 3, pp , [15] F. Perea and J. Puerto, Revisiting a game theoretic framework for the robust railway network design against intentional attacks, European Journal of Operational Research, 226, pp , [16] M. Bell, U. Kanturska, J. Schmocker and A. Fonzone, Attacker-defender models and road network vulnerability, Philosophical Transactions of the Royal Society, 366, pp , [17] M. Tambe, Security and Game Theory-Algorithms, Deployed Systems, Lessons Learned, Cambridge University Press, [18] 4, pp , [19] R. Hohzaki, S. Morita and Y. Terashima, A patrol problem in a building by search theory, In Proceedings of 2013 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), pp , [20] 60, pp , [21] R. Hohzaki and T. Chiba, An attrition game on an acyclic network, Journal of the Operational Research Society, 66, pp , [22] pp , [23] co.jp/facility.html Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited

untitled

untitled c 816 Web 1. 30 [1] [2] [3, 4] [5] 10 [6] 185 8540 2 8 38 [5] [5, 7] [5] 3 (1) 608 18 Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited. (2) (3) 2. 2.1 Web 2014 1 2013 12 2.2

More information

untitled

untitled 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 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

untitled

untitled c OR 21 OR 1. 21 21 IoT OR OR OR 260 8672 1 8 1 OR 2. 2.1 public health [1] communicable (infectious) diseases vehicle burden HIV/AIDS (SARS) 258 60 Copyright c by ORSJ. Unauthorized reproduction of this

More information

untitled

untitled c 1. 2 2011 2012 0.248 0.252 1 Data Envelopment Analysis DEA 4 2 180 8633 3 3 1 IT DHARMA Ltd. 272 0122 1 14 12 13.10.7 14.5.27 DEA-AR (Assurance Region) 1 DEA 1 1 [1] 2011 2012 220 446 [2] 2. [2] 1 1

More information

untitled

untitled c Society5.0 Society5.0 Society5.0 Society5.0 2017 Society5.0 SDGs SIP PRISM Society5.0 2017 SIP ImPACT PRISM SDGs 1. Society5.0 2016 9 Society5.0 OR [1] Society5.0 2. Society5.0 2.1 Society5.0 Society5.0

More information

<30365F93C195CA8FDC5F88C092422E696E6464>

<30365F93C195CA8FDC5F88C092422E696E6464> 1 Sanders, G. B., William E. L., "Integration of In-Situ Resource Utilization into lunar/mars exploration through field analogs." Advances in Space Research 47, 1 2011, 20-29. 2 Sanders, G. B., William

More information

,398 4% 017,

,398 4% 017, 6 3 JEL Classification: D4; K39; L86,,., JSPS 34304, 47301.. 1 01301 79 1 7,398 4% 017,390 01 013 1 1 01 011 514 8 1 Novos and Waldman (1984) Johnson (1985) Chen and Png (003) Arai (011) 3 1 4 3 4 5 0

More information

1 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

通信容量制約を考慮したフィードバック制御 - 電子情報通信学会 情報理論研究会(IT) 若手研究者のための講演会

通信容量制約を考慮したフィードバック制御 -  電子情報通信学会 情報理論研究会(IT)  若手研究者のための講演会 IT 1 2 1 2 27 11 24 15:20 16:05 ( ) 27 11 24 1 / 49 1 1940 Witsenhausen 2 3 ( ) 27 11 24 2 / 49 1940 2 gun director Warren Weaver, NDRC (National Defence Research Committee) Final report D-2 project #2,

More information

or57_4_175.dvi

or57_4_175.dvi c Excel Excel Excel Excel Microsoft Excel 1. OR Microsoft Excel Excel 1 Excel Excel Excel or 2007 Excel OR Excel Excel LP Excel LP Excel 112 8551 1 13 27 1 Excel Excel Excel 2010 Excel OpenOffice Calc

More information

or58_11_651.dvi

or58_11_651.dvi c 1. 2. 480 1195 1 1 OECD 2010 [1] 33 OECD 2009 3,265 3,035 8,233 913 1 1 4 OECD 2 3 OECD 1,000 2.2 OECD 3.1 34 5 OECD 14 [2] 1 2013 11 Copyright c by ORSJ. Unauthorized reproduction of this article is

More information

Optical Flow t t + δt 1 Motion Field 3 3 1) 2) 3) Lucas-Kanade 4) 1 t (x, y) I(x, y, t)

Optical Flow t t + δt 1 Motion Field 3 3 1) 2) 3) Lucas-Kanade 4) 1 t (x, y) I(x, y, t) http://wwwieice-hbkborg/ 2 2 4 2 -- 2 4 2010 9 3 3 4-1 Lucas-Kanade 4-2 Mean Shift 3 4-3 2 c 2013 1/(18) http://wwwieice-hbkborg/ 2 2 4 2 -- 2 -- 4 4--1 2010 9 4--1--1 Optical Flow t t + δt 1 Motion Field

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

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

,.,. NP,., ,.,,.,.,,, (PCA)...,,. Tipping and Bishop (1999) PCA. (PPCA)., (Ilin and Raiko, 2010). PPCA EM., , tatsukaw

,.,. NP,., ,.,,.,.,,, (PCA)...,,. Tipping and Bishop (1999) PCA. (PPCA)., (Ilin and Raiko, 2010). PPCA EM., , tatsukaw ,.,. NP,.,. 1 1.1.,.,,.,.,,,. 2. 1.1.1 (PCA)...,,. Tipping and Bishop (1999) PCA. (PPCA)., (Ilin and Raiko, 2010). PPCA EM., 152-8552 2-12-1, tatsukawa.m.aa@m.titech.ac.jp, 190-8562 10-3, mirai@ism.ac.jp

More information

untitled

untitled c OR&SA OR&SA 2 OR&SA (Polarity) OR&SA 1. 1) 2) OR&SA 2 3) 2 OR&SA 2014 7 [1] 1) 2) 3) 153 8648 2 2 1 4) 5) 6) 1980 1990 2000 2. 234 36 Copyright c by ORSJ. Unauthorized reproduction of this article is

More information

\\ \Data_in4\TeX\OR\63-7\07\or63_7_401.dvi

\\ \Data_in4\TeX\OR\63-7\07\or63_7_401.dvi c CO 2 2 CO 2 CO 2 CO 2 IPCC 1. CO 2 2015 400 ppm CO 2 CO 2 2 2.5 16.2 8.2 [1] CO 2 305 0005 1 1 1 3F 1134 mamoru@sk.tsukuba.ac.jp 206 000 626 2 2 507 brother.hide10@gmail.com 305 005 1 1 1 IIIS 4F kojima.kazunori.ga@un.tsukuba.ac.jp

More information

or58_8_455.dvi

or58_8_455.dvi c Voice of CustomerVOC CS VOC Facebook Twitter SNS VOC SNS 1 VOC 1. WEB 2. 151 8583 2 2 1 VOC SNS 3. 3.1 4 (1) FAX (2) HP Twitter (3) (4) (1) (3) (4) 1 WEB 2013 8 Copyright c by ORSJ. Unauthorized reproduction

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

研究シリーズ第40号

研究シリーズ第40号 165 PEN WPI CPI WAGE IIP Feige and Pearce 166 167 168 169 Vector Autoregression n (z) z z p p p zt = φ1zt 1 + φ2zt 2 + + φ pzt p + t Cov( 0 ε t, ε t j )= Σ for for j 0 j = 0 Cov( ε t, zt j ) = 0 j = >

More information

3 2 2 (1) (2) (3) (4) 4 4 AdaBoost 2. [11] Onishi&Yoda [8] Iwashita&Stoica [5] 4 [3] 3. 3 (1) (2) (3)

3 2 2 (1) (2) (3) (4) 4 4 AdaBoost 2. [11] Onishi&Yoda [8] Iwashita&Stoica [5] 4 [3] 3. 3 (1) (2) (3) (MIRU2012) 2012 8 820-8502 680-4 E-mail: {d kouno,shimada,endo}@pluto.ai.kyutech.ac.jp (1) (2) (3) (4) 4 AdaBoost 1. Kanade [6] CLAFIC [12] EigenFace [10] 1 1 2 1 [7] 3 2 2 (1) (2) (3) (4) 4 4 AdaBoost

More information

JAPAN MARKETING JOURNAL 122 Vol.31 No.22011

JAPAN MARKETING JOURNAL 122 Vol.31 No.22011 Japan Marketing Academy JAPAN MARKETING JOURNAL 122 Vol.31 No.22011 JAPAN MARKETING JOURNAL 122 Vol.31 No.22011 JAPAN MARKETING JOURNAL 122 Vol.31 No.22011 JAPAN MARKETING JOURNAL 122 Vol.31 No.22011 JAPAN

More information

guideline_1_0.dvi

guideline_1_0.dvi Version 1.0 ( 22 5 ) cflkanta Matsuura Laboratory 2010, all rights reserved. I 3 1 3 2 3 3 4 II 8 4 8 5 9 5.1......................... 9 5.2......................... 10 5.3......................... 10

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

Abstract Gale-Shapley 2 (1) 2 (2) (1)

Abstract Gale-Shapley 2 (1) 2 (2) (1) ( ) 2011 3 Abstract Gale-Shapley 2 (1) 2 (2) (1) 1 1 1.1........................................... 1 1.2......................................... 2 2 4 2.1................................... 4 2.1.1 Gale-Shapley..........................

More information

01-._..

01-._.. Journal of the Faculty of Management and Information Systems, Prefectural University of Hiroshima 2014 No.6 pp.43 56 43 The risk measure for resilience in the inventory control system Nobuyuki UENO, Yu

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) 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

V 0 = + r pv (H) + qv (T ) = + r ps (H) + qs (T ) = S 0 X n+ (T ) = n S n+ (T ) + ( + r)(x n n S n ) = ( + r)x n + n (d r)s n = ( + r)v n + V n+(h) V

V 0 = + r pv (H) + qv (T ) = + r ps (H) + qs (T ) = S 0 X n+ (T ) = n S n+ (T ) + ( + r)(x n n S n ) = ( + r)x n + n (d r)s n = ( + r)v n + V n+(h) V I (..2) (0 < d < + r < u) X 0, X X = 0 S + ( + r)(x 0 0 S 0 ) () X 0 = 0, P (X 0) =, P (X > 0) > 0 0 H, T () X 0 = 0, X (H) = 0 us 0 ( + r) 0 S 0 = 0 S 0 (u r) X (T ) = 0 ds 0 ( + r) 0 S 0 = 0 S 0 (d r)

More information

ばらつき抑制のための確率最適制御

ばらつき抑制のための確率最適制御 ( ) http://wwwhayanuemnagoya-uacjp/ fujimoto/ 2011 3 9 11 ( ) 2011/03/09-11 1 / 46 Outline 1 2 3 4 5 ( ) 2011/03/09-11 2 / 46 Outline 1 2 3 4 5 ( ) 2011/03/09-11 3 / 46 (1/2) r + Controller - u Plant y

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

Change in Organization Mode and Asymmetric Personal Information via Corporate Group Management Resolution 1 asymmetric information,2003a symmetric ign

Change in Organization Mode and Asymmetric Personal Information via Corporate Group Management Resolution 1 asymmetric information,2003a symmetric ign ISSN 1347-5495 Business Research No. 50 2003 12 11 Change in Organization Mode and Asymmetric Personal Information via Corporate Group Management Resolution 1 asymmetric information,2003a symmetric ignorance

More information

IPSJ SIG Technical Report 1,a) 1,b) 1,c) 1,d) 2,e) 2,f) 2,g) 1. [1] [2] 2 [3] Osaka Prefecture University 1 1, Gakuencho, Naka, Sakai,

IPSJ SIG Technical Report 1,a) 1,b) 1,c) 1,d) 2,e) 2,f) 2,g) 1. [1] [2] 2 [3] Osaka Prefecture University 1 1, Gakuencho, Naka, Sakai, 1,a) 1,b) 1,c) 1,d) 2,e) 2,f) 2,g) 1. [1] [2] 2 [3] 1 599 8531 1 1 Osaka Prefecture University 1 1, Gakuencho, Naka, Sakai, Osaka 599 8531, Japan 2 565 0871 Osaka University 1 1, Yamadaoka, Suita, Osaka

More information

日立評論2007年3月号 : ソフトウェア開発への

日立評論2007年3月号 : ソフトウェア開発への Vol.89 No.3 298-299 Application of Statistical Process Control to Software Development Mutsumi Komuro 1 23 1985 ACM IEEE 1 195QC Quality Control 1 2 CMM Capability Maturity Model CMMI Capability Maturity

More information

A Study on Throw Simulation for Baseball Pitching Machine with Rollers and Its Optimization Shinobu SAKAI*5, Yuichiro KITAGAWA, Ryo KANAI and Juhachi

A Study on Throw Simulation for Baseball Pitching Machine with Rollers and Its Optimization Shinobu SAKAI*5, Yuichiro KITAGAWA, Ryo KANAI and Juhachi A Study on Throw Simulation for Baseball Pitching Machine with Rollers and Its Optimization Shinobu SAKAI*5, Yuichiro KITAGAWA, Ryo KANAI and Juhachi ODA Department of Human and Mechanical Systems Engineering,

More information

平成 19 年度 ( 第 29 回 ) 数学入門公開講座テキスト ( 京都大学数理解析研究所, 平成 19 ~8 年月 72 月日開催 30 日 ) 1 PCF (Programming language for Computable Functions) PCF adequacy adequacy

平成 19 年度 ( 第 29 回 ) 数学入門公開講座テキスト ( 京都大学数理解析研究所, 平成 19 ~8 年月 72 月日開催 30 日 ) 1 PCF (Programming language for Computable Functions) PCF adequacy adequacy 1 PCF (Programming language for Computable Functions) PCF adequacy adequacy 2 N X Y X Y f (x) f x f x y z (( f x) y) z = (( f (x))(y))(z) X Y x e X Y λx. e x x 2 + x + 1 λx. x 2 + x + 1 3 PCF 3.1 PCF PCF

More information

520

520 1319121211 1419 1910121918 19151712171412 11191712 1011 1119191911 191519181711 1912191714 1019 191214 10101915191911 13141917 121419191014 1912101011 191019191014126 1 19191912101911 19191217 1215161416

More information

, 1.,,,.,., (Lin, 1955).,.,.,.,. f, 2,. main.tex 2011/08/13( )

, 1.,,,.,., (Lin, 1955).,.,.,.,. f, 2,. main.tex 2011/08/13( ) 81 4 2 4.1, 1.,,,.,., (Lin, 1955).,.,.,.,. f, 2,. 82 4.2. ζ t + V (ζ + βy) = 0 (4.2.1), V = 0 (4.2.2). (4.2.1), (3.3.66) R 1 Φ / Z, Γ., F 1 ( 3.2 ). 7,., ( )., (4.2.1) 500 hpa., 500 hpa (4.2.1) 1949,.,

More information

CVaR

CVaR CVaR 20 4 24 3 24 1 31 ,.,.,. Markowitz,., (Value-at-Risk, VaR) (Conditional Value-at-Risk, CVaR). VaR, CVaR VaR. CVaR, CVaR. CVaR,,.,.,,,.,,. 1 5 2 VaR CVaR 6 2.1................................................

More information

9_18.dvi

9_18.dvi Vol. 49 No. 9 3180 3190 (Sep. 2008) 1, 2 3 1 1 1, 2 4 5 6 1 MRC 1 23 MRC Development and Applications of Multiple Risk Communicator Ryoichi Sasaki, 1, 2 Yuu Hidaka, 3 Takashi Moriya, 1 Katsuhiro Taniyama,

More information

An Interactive Visualization System of Human Network for Multi-User Hiroki Akehata 11N F

An Interactive Visualization System of Human Network for Multi-User Hiroki Akehata 11N F An Interactive Visualization System of Human Network for Multi-User Hiroki Akehata 11N8100002F 2013 3 ,.,.,.,,., (, )..,,,.,,.,, SPYSEE. SPYSEE,,., 2,,.,,.,,,,.,,,.,, Microsoft Microsoft PixelSense Samsung

More information

IPSJ SIG Technical Report Vol.2014-MBL-70 No.49 Vol.2014-UBI-41 No /3/15 2,a) 2,b) 2,c) 2,d),e) WiFi WiFi WiFi 1. SNS GPS Twitter Facebook Twit

IPSJ SIG Technical Report Vol.2014-MBL-70 No.49 Vol.2014-UBI-41 No /3/15 2,a) 2,b) 2,c) 2,d),e) WiFi WiFi WiFi 1. SNS GPS Twitter Facebook Twit 2,a) 2,b) 2,c) 2,d),e) WiFi WiFi WiFi 1. SNS GPS Twitter Facebook Twitter Ustream 1 Graduate School of Information Science and Technology, Osaka University, Japan 2 Cybermedia Center, Osaka University,

More information

1 Kinect for Windows M = [X Y Z] T M = [X Y Z ] T f (u,v) w 3.2 [11] [7] u = f X +u Z 0 δ u (X,Y,Z ) (5) v = f Y Z +v 0 δ v (X,Y,Z ) (6) w = Z +

1 Kinect for Windows M = [X Y Z] T M = [X Y Z ] T f (u,v) w 3.2 [11] [7] u = f X +u Z 0 δ u (X,Y,Z ) (5) v = f Y Z +v 0 δ v (X,Y,Z ) (6) w = Z + 3 3D 1,a) 1 1 Kinect (X, Y) 3D 3D 1. 2010 Microsoft Kinect for Windows SDK( (Kinect) SDK ) 3D [1], [2] [3] [4] [5] [10] 30fps [10] 3 Kinect 3 Kinect Kinect for Windows SDK 3 Microsoft 3 Kinect for Windows

More information

2003/9 Vol. J86 D I No. 9 GA GA [8] [10] GA GA GA SGA GA SGA2 SA TS GA C1: C2: C3: 1 C4: C5: 692

2003/9 Vol. J86 D I No. 9 GA GA [8] [10] GA GA GA SGA GA SGA2 SA TS GA C1: C2: C3: 1 C4: C5: 692 Comparisons of Genetic Algorithms for Timetabling Problems Hiroaki UEDA, Daisuke OUCHI, Kenichi TAKAHASHI, and Tetsuhiro MIYAHARA GA GA GA GA GA SGA GA SGA2SA TS 6 SGA2 GA GA SA 1. GA [1] [12] GA Faculty

More information

% 95% 2002, 2004, Dunkel 1986, p.100 1

% 95% 2002, 2004, Dunkel 1986, p.100 1 Blended Learning 要 旨 / Moodle Blended Learning Moodle キーワード:Blended Learning Moodle 1 2008 Moodle e Blended Learning 2009.. 1994 2005 1 2 93% 95% 2002, 2004, 2011 2011 1 Dunkel 1986, p.100 1 Blended Learning

More information

1 IDC Wo rldwide Business Analytics Technology and Services 2013-2017 Forecast 2 24 http://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h24/pdf/n2010000.pdf 3 Manyika, J., Chui, M., Brown, B., Bughin,

More information

_01野口.indd

_01野口.indd : NPO 83 4 2015 3 1. 1998 NPO NPO NPO NPO NPO 2.NPO 1 NPO 2007 12 2011 4 NPO NPO 2011 3 11 NPO NPO NPO 1 1998 NPO NPO 2 2 NPO NPO NPO NPO 3 83 4 1NPO NPO NPO https://www.npo - homepage.go.jp/portalsite/syokatsutyobetsu_ninshou.html12

More information

独立行政法人情報通信研究機構 Development of the Information Analysis System WISDOM KIDAWARA Yutaka NICT Knowledge Clustered Group researched and developed the infor

独立行政法人情報通信研究機構 Development of the Information Analysis System WISDOM KIDAWARA Yutaka NICT Knowledge Clustered Group researched and developed the infor 独立行政法人情報通信研究機構 KIDAWARA Yutaka NICT Knowledge Clustered Group researched and developed the information analysis system WISDOM as a research result of the second medium-term plan. WISDOM has functions that

More information

人工知能学会研究会資料 SIG-KBS-B Analysis of Voting Behavior in One Night Werewolf 1 2 Ema Nishizaki 1 Tomonobu Ozaki Graduate School of Integrated B

人工知能学会研究会資料 SIG-KBS-B Analysis of Voting Behavior in One Night Werewolf 1 2 Ema Nishizaki 1 Tomonobu Ozaki Graduate School of Integrated B 人工知能学会研究会資料 SIG-KBS-B508-09 Analysis of Voting Behavior in One Night Werewolf 1 2 Ema Nishizaki 1 Tomonobu Ozaki 2 1 1 Graduate School of Integrated Basic Sciences, Nihon University 2 2 College of Humanities

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

,,, 2 ( ), $[2, 4]$, $[21, 25]$, $V$,, 31, 2, $V$, $V$ $V$, 2, (b) $-$,,, (1) : (2) : (3) : $r$ $R$ $r/r$, (4) : 3

,,, 2 ( ), $[2, 4]$, $[21, 25]$, $V$,, 31, 2, $V$, $V$ $V$, 2, (b) $-$,,, (1) : (2) : (3) : $r$ $R$ $r/r$, (4) : 3 1084 1999 124-134 124 3 1 (SUGIHARA Kokichi),,,,, 1, [5, 11, 12, 13], (2, 3 ), -,,,, 2 [5], 3,, 3, 2 2, -, 3,, 1,, 3 2,,, 3 $R$ ( ), $R$ $R$ $V$, $V$ $R$,,,, 3 2 125 1 3,,, 2 ( ), $[2, 4]$, $[21, 25]$,

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

* *2 Russell et al. (2015) 2

* *2 Russell et al. (2015) 2 2017 6 1 1 2016 S 40 *1 1997 IBM 2011 IBM 2017 nishihara@hiroshima-u.ac.jp *1 NHTSA Investigation: PE 16-007 (Jan. 2017) 1 *2 1 2 3 4 *2 Russell et al. (2015) 2 6 8 Polinsky and Shavell (2010) Polinsky

More information

9.プレゼン資料(小泉)R1

9.プレゼン資料(小泉)R1 1 Me-DigIT 2 TRO, TMECH Interesting Readings IJMRCAS, TUFFC The Most 3., etc.. etc.. etc. 4 TRO09 5 J TRO09 The Most Interesting Readings J http://www.learner.org/interactives/renaissance/printing.html

More information

本文(横)  ※リュウミンL・カンマ使用/大扉●還暦記念論集用

本文(横)  ※リュウミンL・カンマ使用/大扉●還暦記念論集用 47 48 a 49 J.Piagetreflective thinkingr.skemp reflective intelligence A.H.SchoenfeldF.K.Lester J.Garofalo J.H.FlavellA.L.Brown 50 51 52 53 a b 54 SQSShared Questionnaire System PC G.Polya Schoenfild Polya

More information

TOP URL 1

TOP URL   1 TOP URL http://amonphys.web.fc.com/ 3.............................. 3.............................. 4.3 4................... 5.4........................ 6.5........................ 8.6...........................7

More information

10 2016 5 16 1 1 Lin, P. and Saggi, K. (2002) Product differentiation, process R&D, and the nature of market competition. European Economic Review 46(1), 201 211. Manasakis, C., Petrakis, E., and Zikos,

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

‰gficŒõ/’ÓŠ¹

‰gficŒõ/’ÓŠ¹ The relationship between creativity of Haiku and idea search space YOSHIDA Yasushi This research examined the relationship between experts' ranking of creative Haiku (a Japanese character poem including

More information

untitled

untitled IT E- IT http://www.ipa.go.jp/security/ CERT/CC http://www.cert.org/stats/#alerts IPA IPA 2004 52,151 IT 2003 12 Yahoo 451 40 2002 4 18 IT 1/14 2.1 DoS(Denial of Access) IDS(Intrusion Detection System)

More information

2 (S, C, R, p, q, S, C, ML ) S = {s 1, s 2,..., s n } C = {c 1, c 2,..., c m } n = S m = C R = {r 1, r 2,...} r r 2 C \ p = (p r ) r R q = (q r ) r R

2 (S, C, R, p, q, S, C, ML ) S = {s 1, s 2,..., s n } C = {c 1, c 2,..., c m } n = S m = C R = {r 1, r 2,...} r r 2 C \ p = (p r ) r R q = (q r ) r R RF-004 Hashimoto Naoyuki Suguru Ueda Atsushi Iwasaki Yosuke Yasuda Makoto Yokoo 1 [10] ( ). ( ) 1 ( ) 3 4 3 4 = 12 deferred acceptance (DA) [3, 7] [5] ( ) NP serial dictatorship with regional quotas (SDRQ)

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

On the Limited Sample Effect of the Optimum Classifier by Bayesian Approach he Case of Independent Sample Size for Each Class Xuexian HA, etsushi WAKA

On the Limited Sample Effect of the Optimum Classifier by Bayesian Approach he Case of Independent Sample Size for Each Class Xuexian HA, etsushi WAKA Journal Article / 学術雑誌論文 ベイズアプローチによる最適識別系の有限 標本効果に関する考察 : 学習標本の大きさ がクラス間で異なる場合 (< 論文小特集 > パ ターン認識のための学習 : 基礎と応用 On the limited sample effect of bayesian approach : the case of each class 韓, 雪仙 ; 若林, 哲史

More information

TA3-4 31st Fuzzy System Symposium (Chofu, September 2-4, 2015) Interactive Recommendation System LeonardoKen Orihara, 1 Tomonori Hashiyama, 1

TA3-4 31st Fuzzy System Symposium (Chofu, September 2-4, 2015) Interactive Recommendation System LeonardoKen Orihara, 1 Tomonori Hashiyama, 1 Interactive Recommendation System 1 1 1 1 LeonardoKen Orihara, 1 Tomonori Hashiyama, 1 Shun ichi Tano 1 1 Graduate School of Information Systems, The University of Electro-Communications Abstract: The

More information

IPSJ SIG Technical Report Vol.2010-NL-199 No /11/ treebank ( ) KWIC /MeCab / Morphological and Dependency Structure Annotated Corp

IPSJ SIG Technical Report Vol.2010-NL-199 No /11/ treebank ( ) KWIC /MeCab / Morphological and Dependency Structure Annotated Corp 1. 1 1 1 2 treebank ( ) KWIC /MeCab / Morphological and Dependency Structure Annotated Corpus Management Tool: ChaKi Yuji Matsumoto, 1 Masayuki Asahara, 1 Masakazu Iwatate 1 and Toshio Morita 2 This paper

More information

No. 3 Oct The person to the left of the stool carried the traffic-cone towards the trash-can. α α β α α β α α β α Track2 Track3 Track1 Track0 1

No. 3 Oct The person to the left of the stool carried the traffic-cone towards the trash-can. α α β α α β α α β α Track2 Track3 Track1 Track0 1 ACL2013 TACL 1 ACL2013 Grounded Language Learning from Video Described with Sentences (Yu and Siskind 2013) TACL Transactions of the Association for Computational Linguistics What Makes Writing Great?

More information

2

2 Copyright 2008 Nara Institute of Science and Technology / Osaka University 2 Copyright 2008 Nara Institute of Science and Technology / Osaka University CHAOS Report in US 1994 http://www.standishgroup.com/sample_research/

More information

or58_10_599.dvi

or58_10_599.dvi c 1. 450 m 14 26 1 =1.852 km/h 300 m 1 2 34 m 1933 2 30 m 135 8533 2 1 6 1 2009 12 29 m 1 (Weather Routing) [1] 2013 10 Copyright c by ORSJ. Unauthorized reproduction of this article is prohibited. 27

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

Vol. 23 No. 4 Oct. 2006 37 2 Kitchen of the Future 1 Kitchen of the Future 1 1 Kitchen of the Future LCD [7], [8] (Kitchen of the Future ) WWW [7], [3

Vol. 23 No. 4 Oct. 2006 37 2 Kitchen of the Future 1 Kitchen of the Future 1 1 Kitchen of the Future LCD [7], [8] (Kitchen of the Future ) WWW [7], [3 36 Kitchen of the Future: Kitchen of the Future Kitchen of the Future A kitchen is a place of food production, education, and communication. As it is more active place than other parts of a house, there

More information

emarketer SNS / SNS 2009 SNS 15 64

emarketer SNS / SNS 2009 SNS 15 64 Relationship of Creative Thinking and Feeling Shared Communication by Social media MORISAWA Yukihiro Social media has been shared content that is created by the CGM (consumer generated media) via the Internet.

More information

(1) (Karlan, 2004) (1) (1973) (1978) (1991) (1991) 1

(1) (Karlan, 2004) (1) (1973) (1978) (1991) (1991) 1 2004 1 8 2005 12 17 1 (1) (Karlan, 2004) 2 3 4 5 E-mail: aa37065@mail.ecc.u-tokyo.ac.jp (1) (1973) (1978) (1991) (1991) 1 2 2 2.1 (, 1978, 7 ) (2) (1988) 38 2 (3) (4) (2) (1986) 91 (1996) 2 1 (1993) 1

More information

Mantel-Haenszelの方法

Mantel-Haenszelの方法 Mantel-Haenszel 2008 6 12 ) 2008 6 12 1 / 39 Mantel & Haenzel 1959) Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J. Nat. Cancer Inst. 1959; 224):

More information

K 2 X = 4 MWG(f), X P 2 F, υ 0 : X P 2 2,, {f λ : X λ P 1 } λ Λ NS(X λ ), (υ 0 ) λ : X λ P 2 ( 1) X 6, f λ K X + F, f ( 1), n, n 1 (cf [10]) X, f : X

K 2 X = 4 MWG(f), X P 2 F, υ 0 : X P 2 2,, {f λ : X λ P 1 } λ Λ NS(X λ ), (υ 0 ) λ : X λ P 2 ( 1) X 6, f λ K X + F, f ( 1), n, n 1 (cf [10]) X, f : X 2 E 8 1, E 8, [6], II II, E 8, 2, E 8,,, 2 [14],, X/C, f : X P 1 2 3, f, (O), f X NS(X), (O) T ( 1), NS(X), T [15] : MWG(f) NS(X)/T, MWL(f) 0 (T ) NS(X), MWL(f) MWL(f) 0, : {f λ : X λ P 1 } λ Λ NS(X λ

More information

( 9 1 ) 1 2 1.1................................... 2 1.2................................................. 3 1.3............................................... 4 1.4...........................................

More information

zsj2017 (Toyama) program.pdf

zsj2017 (Toyama) program.pdf 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88

More information

88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88

More information

_170825_<52D5><7269><5B66><4F1A>_<6821><4E86><5F8C><4FEE><6B63>_<518A><5B50><4F53><FF08><5168><9801><FF09>.pdf

_170825_<52D5><7269><5B66><4F1A>_<6821><4E86><5F8C><4FEE><6B63>_<518A><5B50><4F53><FF08><5168><9801><FF09>.pdf 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88 th Annual Meeting of the Zoological Society of Japan Abstracts 88

More information

x (x, ) x y (, y) iy x y z = x + iy (x, y) (r, θ) r = x + y, θ = tan ( y ), π < θ π x r = z, θ = arg z z = x + iy = r cos θ + ir sin θ = r(cos θ + i s

x (x, ) x y (, y) iy x y z = x + iy (x, y) (r, θ) r = x + y, θ = tan ( y ), π < θ π x r = z, θ = arg z z = x + iy = r cos θ + ir sin θ = r(cos θ + i s ... x, y z = x + iy x z y z x = Rez, y = Imz z = x + iy x iy z z () z + z = (z + z )() z z = (z z )(3) z z = ( z z )(4)z z = z z = x + y z = x + iy ()Rez = (z + z), Imz = (z z) i () z z z + z z + z.. z

More information

1 Flores, D. (009) All you can drink: should we worry about quality? Journal of Regulatory Economics 35(1), Saggi, K., and Vettas, N. (00) On in

1 Flores, D. (009) All you can drink: should we worry about quality? Journal of Regulatory Economics 35(1), Saggi, K., and Vettas, N. (00) On in 6 016 4 6 1 1 Flores, D. (009) All you can drink: should we worry about quality? Journal of Regulatory Economics 35(1), 1 18. Saggi, K., and Vettas, N. (00) On intrabrand and interbrand competition: The

More information

新製品開発プロジェクトの評価手法

新製品開発プロジェクトの評価手法 CIRJE-J-60 2001 8 A note on new product project selection model: Empirical analysis in chemical industry Kenichi KuwashimaUniversity of Tokyo Junichi TomitaUniversity of Tokyo August, 2001 Abstract By

More information

main.dvi

main.dvi FDTD S A Study on FDTD Analysis based on S-Parameter 18 2 7 04GD168 FDTD FDTD S S FDTD S S S S FDTD FDTD i 1 1 1.1 FDTD.................................... 1 1.2 FDTD..................... 3 2 S 5 2.1 FDTD

More information

Lebesgue可測性に関するSoloayの定理と実数の集合の正則性=1This slide is available on ` `%%%`#`&12_`__~~~ౡ氀猀e

Lebesgue可測性に関するSoloayの定理と実数の集合の正則性=1This slide is available on ` `%%%`#`&12_`__~~~ౡ氀猀e Khomskii Lebesgue Soloay 1 Friday 27 th November 2015 1 This slide is available on http://slideshare.net/konn/lebesguesoloay 1 / 34 Khomskii 1 2 3 4 Khomskii 2 / 34 Khomskii Solovay 3 / 34 Khomskii Lebesgue

More information

42 3 u = (37) MeV/c 2 (3.4) [1] u amu m p m n [1] m H [2] m p = (4) MeV/c 2 = (13) u m n = (4) MeV/c 2 =

42 3 u = (37) MeV/c 2 (3.4) [1] u amu m p m n [1] m H [2] m p = (4) MeV/c 2 = (13) u m n = (4) MeV/c 2 = 3 3.1 3.1.1 kg m s J = kg m 2 s 2 MeV MeV [1] 1MeV=1 6 ev = 1.62 176 462 (63) 1 13 J (3.1) [1] 1MeV/c 2 =1.782 661 731 (7) 1 3 kg (3.2) c =1 MeV (atomic mass unit) 12 C u = 1 12 M(12 C) (3.3) 41 42 3 u

More information

[1], B0TB2053, 20014 3 31. i

[1], B0TB2053, 20014 3 31. i B0TB2053 20014 3 31 [1], B0TB2053, 20014 3 31. i 1 1 2 3 2.1........................ 3 2.2........................... 3 2.3............................. 4 2.3.1..................... 4 2.3.2....................

More information

[1] AI [2] Pac-Man Ms. Pac-Man Ms. Pac-Man Pac-Man Ms. Pac-Man IEEE AI Ms. Pac-Man AI [3] AI 2011 UCT[4] [5] 58,990 Ms. Pac-Man AI Ms. Pac-Man 921,360

[1] AI [2] Pac-Man Ms. Pac-Man Ms. Pac-Man Pac-Man Ms. Pac-Man IEEE AI Ms. Pac-Man AI [3] AI 2011 UCT[4] [5] 58,990 Ms. Pac-Man AI Ms. Pac-Man 921,360 TD(λ) Ms. Pac-Man AI 1,a) 2 3 3 Ms. Pac-Man AI Ms. Pac-Man UCT (Upper Confidence Bounds applied to Trees) TD(λ) UCT UCT Progressive bias Progressive bias UCT UCT Ms. Pac-Man UCT Progressive bias TD(λ)

More information

1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15. 1. 2. 3. 16 17 18 ( ) ( 19 ( ) CG PC 20 ) I want some rice. I want some lice. 21 22 23 24 2001 9 18 3 2000 4 21 3,. 13,. Science/Technology, Design, Experiments,

More information

A Japanese Word Dependency Corpus ÆüËܸì¤Îñ¸ì·¸¤ê¼õ¤±¥³¡¼¥Ñ¥¹

A Japanese Word Dependency Corpus   ÆüËܸì¤Îñ¸ì·¸¤ê¼õ¤±¥³¡¼¥Ñ¥¹ A Japanese Word Dependency Corpus 2015 3 18 Special thanks to NTT CS, 1 /27 Bunsetsu? What is it? ( ) Cf. CoNLL Multilingual Dependency Parsing [Buchholz+ 2006] (, Penn Treebank [Marcus 93]) 2 /27 1. 2.

More information

PFI

PFI PFI 23 3 3 PFI PFI 1 1 2 3 2.1................................. 3 2.2..................... 4 2.3.......................... 5 3 7 3.1................................ 7 3.2.................................

More information

2.R R R R Pan-Tompkins(PT) [8] R 2 SQRS[9] PT Q R WQRS[10] Quad Level Vector(QLV)[11] QRS R Continuous Wavelet Transform(CWT)[12] Mexican hat 4

2.R R R R Pan-Tompkins(PT) [8] R 2 SQRS[9] PT Q R WQRS[10] Quad Level Vector(QLV)[11] QRS R Continuous Wavelet Transform(CWT)[12] Mexican hat 4 G-002 R Database and R-Wave Detecting System for Utilizing ECG Data Takeshi Nagatomo Ikuko Shimizu Takeshi Ikeda Akio Sashima Koichi Kurumatani R R MIT-BIH R 90% 1. R R [1] 2 24 16 Tokyo University of

More information

johnny-paper2nd.dvi

johnny-paper2nd.dvi 13 The Rational Trading by Using Economic Fundamentals AOSHIMA Kentaro 14 2 26 ( ) : : : The Rational Trading by Using Economic Fundamentals AOSHIMA Kentaro abstract: Recently Artificial Markets on which

More information

24 201170068 1 4 2 6 2.1....................... 6 2.1.1................... 6 2.1.2................... 7 2.1.3................... 8 2.2..................... 8 2.3................. 9 2.3.1........... 12

More information

2019 1 5 0 3 1 4 1.1.................... 4 1.1.1......................... 4 1.1.2........................ 5 1.1.3................... 5 1.1.4........................ 6 1.1.5......................... 6 1.2..........................

More information

IPSJ SIG Technical Report Vol.2014-CG-155 No /6/28 1,a) 1,2,3 1 3,4 CG An Interpolation Method of Different Flow Fields using Polar Inter

IPSJ SIG Technical Report Vol.2014-CG-155 No /6/28 1,a) 1,2,3 1 3,4 CG An Interpolation Method of Different Flow Fields using Polar Inter ,a),2,3 3,4 CG 2 2 2 An Interpolation Method of Different Flow Fields using Polar Interpolation Syuhei Sato,a) Yoshinori Dobashi,2,3 Tsuyoshi Yamamoto Tomoyuki Nishita 3,4 Abstract: Recently, realistic

More information

(1.2) T D = 0 T = D = 30 kn 1.2 (1.4) 2F W = 0 F = W/2 = 300 kn/2 = 150 kn 1.3 (1.9) R = W 1 + W 2 = = 1100 N. (1.9) W 2 b W 1 a = 0

(1.2) T D = 0 T = D = 30 kn 1.2 (1.4) 2F W = 0 F = W/2 = 300 kn/2 = 150 kn 1.3 (1.9) R = W 1 + W 2 = = 1100 N. (1.9) W 2 b W 1 a = 0 1 1 1.1 1.) T D = T = D = kn 1. 1.4) F W = F = W/ = kn/ = 15 kn 1. 1.9) R = W 1 + W = 6 + 5 = 11 N. 1.9) W b W 1 a = a = W /W 1 )b = 5/6) = 5 cm 1.4 AB AC P 1, P x, y x, y y x 1.4.) P sin 6 + P 1 sin 45

More information