Instrument Blood Current Measuring Instrument. Brain Wave Measuring Instrument. (frequency) f. log. 1/f

FM BS BS531ch 232ch 231ch

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Blood Pressure Instrument Temperature Measuring Instrument Blood Current Measuring Instrument Brain Wave Measuring Instrument (frequency) f log 1/f 2

1 Type [AA] 2 Type [RA] 3 Type [FA] 4 Type [AR] 5 Type [RR] 6 Type [FR] 7 Type [AF] 8 Type [RF] 9 Type [FF] 3

12 n x Range [ x min : xmax w [i ] x ] x x min max x Range : : : Range n : n (1) (2) w ( i 1) x w i (3) i n=10 1~10 t Bv(t) BpE (4) BpS BpS=1 110 [mmhg] Bp BpE Bv( t) 110 (4) def Bp t Bvt t1 BpE BpS t Bvs(t) BpsE BpsS BpsS BpsS=1 Bps (9) def BpS Bv : 3 t 1 (5) (6) 4

def BpsE Bvs( t) 70 (7) def def Bps t Bvst t BpsS Bvs : 3 BpsE BpsS 1 t 1 (8) (9) TR(t) TRK (10) TRK PF(t) PFS PFS PFI def (10) PFE PF ( t) 60 (11) def def PFI t PFt t PFS PF : 3 PFE PFS 1 t 1 (12) (13) TYPE [F,F] 1/f 5

80 75 70 1/f 刺激 血圧 [mmhg] 65 60 55 50 1/f 刺激 図 6.1 最高血圧 45 40 0 10 20 30 時間 [min] 図 6.2 最低血圧 1/f 刺激 105 100 95 脈拍 [ 回 /min] 90 85 80 75 図 6.3 脚部体温 70 65 0 10 20 30 時間 [min] 図 6.4 脚部脈拍 1/f 刺激 含有率 [%] 20 19 18 17 16 15 14 13 12 11 10 1/f 刺激 0 10 20 30 時間 [min] 図 6.5 α 波の含有率 振幅 [μv] 30 25 20 15 10 5 0 1/f 刺激 0 10 20 30 時間 [min] 図 6.6 α 波の振幅変化 (1) 最高血圧について血圧は時々刻々変化する生体信号である 図 6.1 を見ると 測定開始の 120から測定終了の30 分後までの変化が 1/f 刺激の場合はほぼ 120~130 の間に入っている 他の刺激信号の場合もほぼ同様な傾向にあり 特に 1/f の場合がベストという訳ではない (2) 最低血圧についてこれについては図 6.2にみられるように 1/f 刺激の場合が他の刺激振動に比較して変化が少なく 変 6

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Space Weather 10 30 1 2003 1 2003 10 (C)SOHOESA/NASA 3.1 12 12

1) 10km 10km NICTNational Institute of Information and Communications Technology Solar Flare CMECoronal Mass EjectionGeomagnetic Storm 8 30 CME 2 1989 3 Space Weather 2) 4) 20XX 2 11 1000 13 13

1 X X GOES X X 1858 100 X 30 4000mSv GPS 10 1859 9 1 19 1859 9 1 5) 1859 9 1 2 89 1770 9 17 6) 100 1 2012 7 CME 7) 2015 8) US Strategic National Risk Assessment 14 14

2003 1 10 25 1 10 8 8 1 1 27 3 2003 10 22 4 13 X X 100 X X M C GOESGeostationary Operational Environmental Satellite 24 365 M CME CME CME 1 5 km 100 1/100 2 150 km 1 1 ACE Advanced Composition ExplorerSolar Wind ACE 2003 10 24 15 10 25 0 CME 400km 600km 40 CME 800km Fedsat 9 N S S N 36 28 60 80 15 15

2003 10 24 15 50 10 25 0 50 800km ADEOSII 2 ADEOSII NASDA JAXA 2003 10 24 23 55 10 25 9 55 ADEOSII ADEOSII 3) ADEOSII NHK 2003 10 25 ADEOSII PLANET-B NOZOMIH2A 2005 10 2003 9) 16 16

2017 10 25 2003 14 1 2017 9 3 2017 9 4 9 11 3 CME 2003 10 24 7 23 10) 17 17

SF 1859 1).., 2017, vol.65, no5, p.123-128. 2).;.;.;.;.., 2000, 302p, ISBN978-4274078972. 3).ADEOS-II II..2004-07-28. http://www.mext.go.jp/b_menu/shingi/uchuu/reports/04080901.htm, 2017-06-16. 4).., 2013. 212p., ISBN978-4- 02-273507-2. 5) Carrington,R.C. Description of a Singular Appearance Seen in the Sun on September 1, 1895, Monthly Notice of the Royal Astronomical Society, 20(1859),pp.13-15. 6) Ryuho,Kataoka.; Kiyomi Iwahashi. Inclined zenith aurora over Kyoto on 17 September 1770: Graphical evidence of extreme magnetic storm. Space Weather AN AGU GOURNAL, 2017, DOI: 10.1002/2017SW001690. 7) D,N,Baker.; X,Li.; A,Pulkkinen.; C,M,Ngwira.; M,L,Mays.; A,B,Galvin. A major solar eruptive event in July 2012: Defining extreme space weather scenarios. SPACE WEATHER. 2013, vol.11, p.585-591. doi:10.1002/swe.20097. 8) National Science and Technology Council. National Space Weather Strategy. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/final_nationalspace weatherstrategy_20151028.pdf, (accessed 2017-04-18). 9).;.;.. 61. 2017, 3C07 JSASS-2017-4513. 10).;.. 62. 2018, 1K07JSASS-2018-4241. 18 18

1. 1950 1991 1995 1998 NPO 2010 2. (2015) 3. 19

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(o) (p) 10 Wi-Fi (o) SSL (p) 4 4 212018 9 p62 28

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1 40, n x 1, x 2,, x n x pdf f(x) 0 x f(x) = 1/ (1) x f(x) = 0 n y pdf f(y) 0 y f(y) = n(n 1)y n 2 ( y)/ n (2) y f(y) = 0 (n 1)/(n+1) 2 2(n 1) 2 /{(n + 2)(n + 1) 2 } 2 (1) 1 (2) white noise dt (1)(2) dy dy/dt = a(y K) + (3) K>0 y a>0 K K 1 35

K a K K a 3 = 0 3 K = 0 3 y t Y Y + Y 1. y g(y, t)dy dy/dt t = 0 y0 Prob{Y y(t) Y + Y} = g(y, t)dy dt t = 1 Prob g t pdf a(y0 K) 3 Kolmogorov y1 y0 + { a(y0 K)} Bharucha-Reid, 1960; Shigesada and Kawasaki, 1997 2 g( y, t) 2 2 t y 2 y 2 1 a( y K) g( y, t) g( y, t) (4) 4 y t 2 y g(y, t) 4 g(y, t)/t = 0 a(y K)g(y) + 1 2 d dy [ 2 g(y)] = 0 (5) g(y) t 5 a 00 K a 2 R exp ( y K) dy 0 2 6 : a 2 g(y) = exp ( y K) / R 2 (6) 6 g(y) y pdf y [0, ] 1 6 K 0 2 6 K 2 /(2a) 6 K K a 2 K a pdf 6 36

88 m 6 m 1 200 300 kg 6 6 m 2 6 = 100 88 m 2 m pdf 6 y pdfa: K = 30, a = 1.0, 2 = 250; B: K = 70, a = 1.0, 2 = 250; C: K = 30, 20 3 (1) (2) (3) 3 t t + t y t y y t+1 K a 0 3 7 y = a 0 (y t K) + 0 y t+1 = y t + y = (1 a 0 )y t + a 0 K + 0 (7) 0 0 2 0 a 0 0 t t0 a 0 a 0 3. 20 t y t = 20 y 3 y 20 y 3 3 37

7 1 y K a 0 â 0 = 1.090 Kˆ = 26.96 m K 3 K a 1. 7 â Kˆ 0 ˆ 2 sy 2 R 2 0 y = 1.09yt + 29.35 56.25 1.090 26.96 88.95 208.58 y = 1.47yt + 71.68 78.58 1.4739 48.63 194.59 933.53 y = 1.59yt + 112.00 73.80 1.5877 70.54 86.28 255.00 yt t yt = 20 0 ˆ 2 0 sy 2 â Kˆ s 2 y s 2 y 20 ˆ 2 0 = 194.59 s y 2 4 pdf 6 y pdf 2 y pdf 4 6 2 pdf pdf 38

* Shiyomi M, Tuiki M (1999) Model for the spatial pattern formed by a small herd in grazing cattle. Ecological Modelling 119: 231 238. : Bharucha-Reid AT (1960) Elements of the theory of Markov processes and their applications. McGraw-Hill, New York. Shigesada N, Kawasaki K (1997) Biological invasion: The theory and practice. Oxford University Press, London. 39

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