Microsoft Word - 3 Zwischenbericht des Projektes Kommunale Bedarfserhebung_2014-07-15-MS mit SW!!.do

47,2 12,3 8,1 6,6 7,6 28,4 17,3 6,8 18,0 4,6 19,1 16,1 13,3 6,7 19,5 18,5 11,4 4,4 10,5 23,1 21,1 11,0 21,2 15,3 15,3 8,9 3,5 5,8 6,8 15,5 3,6 14,8 15,3 8,7 8,2 10,8 10,3 15,2 5,7 20,5 12,1 5,6 9,4 54,0 [...] 46,5 67,1 40,1  Grevenbroich  4,4 36,1 59,9 33,2  Heidenheim (Kreis)  2,8 29,1 51,0 27,3  Herdecke  5,9 37,9 67,9 36,9  Herford (Kreis)  6,4 41,4 64,6 37,5  Herzogtum Lauenburg (Kreis)  5,8 51,1 67,0 42 [...] 6  Lörrach (Kreis)  6,2 38,2 57,8 34,1  Mainz  7,1 54,3 73,6 45,6  Merzig‐Wadern (Kreis)  7,4 39,9 56,2 34,6  Monheim am Rhein   7,1 38,1 64,4 36,5  Mühlhausen   8,1 62,7 79,0 50,4  Münster  9,3 60,6 75 …

xvw + xwv ≤ 1 ∀{v, w} ∈ E (17) x(δ−(S)) ≥ 1 ∀S ⊆ V \ {r}, S ∩R′ 6= ∅ (18) x(δ+(S)) ≥ 1 ∀S ⊆ V \ {r}, S ∩R′2 6= ∅ (19) x(δ− Ḡw (S1)) + x(δ+ Ḡw (S2)) ≥ 1 ∀w ∈ V \ {r}, ∀S1, S2 ⊆ V \ {r, w}, S1 ∩ S2 ∩R′2 [...] Report TR07-1-008 November 2007 ISSN 1864-4503 Strong Formulations for 2-Node-Connected Steiner Network Problems (TR) Markus Chimani1, Maria Kandyba1?, Ivana Ljubić2??, and Petra Mutzel1 1 Faculty of Computer [...] to 1 if the corresponding edge is selected into N , and 0 otherwise. UCut : min ∑ e∈E ce · ze (23) z(δ(S)) ≥ 1 ∀S ⊆ V, ∅ 6= S ∩R1 6= R1 (24) z(δ(S)) ≥ 2 ∀S ⊆ V, ∅ 6= S ∩R2 6= R2 (25) z(δGw(S)) ≥ 1 ∀w ∈ …

KJH Report Extra 2021 (Korrigierte Fassung)

el 3.18.1 für Gruppen mit Kindern im Alter von unter 3 Jahren 1:4,5 2012 1:4,0 2017 1:3,9 2019 1:3,8 2020 3.18.2 für Gruppen mit Kindern im Alter zwischen 3 Jahren und Schuleintri 1:9,1 2012 1:8,5 2017 [...] rm 1.11.1 Unter 18-Jährige insgesamt 18,6% 2006 20,2% 2016 20,1% 2018 20,5% 2019 1.11.2 Alleinerziehende mit mindestens 1 Kind 37,0% 2006 43,6% 2016 41,5% 2018 42,7% 2019 1.11.3 Paarhaushalt mit 1 Kind [...] Einrichtungen in EUR 1,40 Mrd. 2010 1,70 Mrd. 2016 1,83 Mrd. 2018 1,94 Mrd. 2019 5.31 Ausgaben für heilpädagogische Leistungen für Kinder in EUR 0,91 Mrd. 2010 1,21 Mrd. 2016 1,32 Mrd. 2018 1,41 Mrd. 2019 5 …

which can be estimated by R(i) = n∑ k=1 [xk(i)− x̄(i)][yk − ȳ]√ n∑ k=1 [xk(i)− x̄(i)]2 √ n∑ k=1 [yk − ȳ]2 . (1) Here x̄(i) := 1 n ∑n k=1 xk(i) and ȳ := 1 n ∑n k=1 yk. The value of R(i)2 represents the [...] label y. Given samples Z = {(x1, y1), . . . , (xn, yn)}, an unbiased estimate of HSIC can be computed by HSIC(H,H′, Z) = 1 n(n− 3) [ tr(KL) + 1TK11TL1 (n− 1)(n− 2) − 2 n− 2 1TKL1 ] , where K and L are kernel [...] operators in RapidMiner. 1 Contents Page 1 Introduction 3 2 Filter Feature Selection Methods 6 2.1 Univariate Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.1 Pearson’s Correlation …

A PRACTICAL OVERVIEW OF QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP

/JPEG /ColorACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /ColorImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000ColorACSImageDict << /TileWidth 256 [...] /JPEG /GrayACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /GrayImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000GrayACSImageDict << /TileWidth 256 [...] formation at time (h) Percentage of inhibition at time (h) 1 h 2 h 3 h 4 h 5 h 6 h 5 mg/kg 5.8 9.0 30.1 30.9 35.1 44.5 10 mg/kg 8.7 15.2 33.5 46.0 49.1 78.9 20 mg/kg 7.7 18.4 48.5 62.7 68.4 84.4 Indomethacin …

Ghostscript wrapper for C:\Eldorado\Veroeffentlichungsbereiche\IUL\ICHSF08-High-Speed-Forming-2008-D

iterative way: 1 1 1 t t n nPk Da+ + + = (27) 1 1 1 1 01 1 1 1 1 1 [ ( ) ( )] ( ) ( )t t t t n nM dtS a M a dtD dtQkσ σ σ ϕ μ + + + + ++ = − + (28) Until convergence on both 1t nk + and 1t na + . The FEM [...] introduced the BEM matrices 1 1 , 10 ( ) ( ) 4 | |x y i j i j x yP V x V y d d x y μ π Γ Γ = • Γ Γ∫∫ − r r , 1 1 , ( ) ( ) x i j i j xD V x W x d Γ = • Γ∫ r r (24) 1 1 , 1 ( ) ( ) 2 x Si j i j xQ W x V [...] 0-form and 1-form basis functions: 0( ) 0S σ ϕ = (18) 1 1 011 ( ) ( ) ( ) da M S a D Sa dt σ σ ϕ μ + = − + (19) Where we introduced the 0-form stiffness matrix 0S , the 1-form mass matrix 1M , the 1-form stiffness …

Similar, but Different: Gender Differences in Working Time Arrangements and the Work–Life Interface

14) 0.78*** (0.07) 0.53*** (0.10) 0.55*** (0.12) 1.22* [1.05, 1.43] 1.05 [0.83, 1.34] 1.00 [0.76, 1.33] 2.19*** [1.93, 2.49] 1.70*** [1.39, 2.08] 1.73*** [1.35, 2.20] Married (vs. other) -0.28** (0.11) -0 [...] 1.21] 0.89 [0.66, 1.19] 1.79*** [1.56, 2.06] 1.40*** [1.13, 1.74] 1.46*** [1.13, 1.89] Married (vs. other) -0.24 (0.12) -0.42*** (0.10) 0.79 [0.62, 1.00] 0.65*** [0.53, 0.80] Female × married 0.19 (0 [...] 50, 8.07] 1.17 [0.38, 1.65] 2.07* [1.30, 3.30] 2.33** [1.36, 4.00] Married (vs. other) 0.66* (0.28) 0.43 (0.33) 1.94* [1.12, 3.38] 1.54 [0.81, 2.94] Female × married 0.11 (0.29) -1.13** (0.35) 1.11 [0.63 …

kernelDoE.dvi

algorithm: 1. Input: set of observations x1, . . . , xn, a kernel K and a desired number of instances k 2. Execute kPCA with kernel K on the x1, . . . , xn 3. Select the k−1 eigenvectors V1, . . . , Vk−1 with [...] called experimental design in observational data and has been introduced in [14, 15]. −2 −1 0 1 2 − 1 0 1 2 x1 x2 Figure 2: Data set (smaller dots) and optimal plan (larger dots) For special cases, such [...] corresponding y can be 1 obtained, where k << n. The question is which xi1 , . . . , xik to choose in or- der to learn the most accurate regression function from the completed sample (xi1 , yi1), . . . , (xik …