§12 3 methods for estimating transport coefficients and interfacial area
Báo cáo sinh học: " Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance" ppsx
... a 16 23 ( 23) int QTL sc equal QTL variance high QTL low QTL sc int QTL sc sc high QTL sc 7210 (88) 141 93 (156) 158 (2) 767 (8) 1 538 (18) BM 890 (38 ) 2 537 (168) 2 032 (2 83) 81 (3) 32 7 ( 13) 575 ... 32 7 ( 13) 575 (24) LARS 914 (31 ) 39 37 (164) 7017 (2 93) 75 (4) 34 4 (15) 715 (29) PLSR 1249 (49) 52 63 (198) 10747 (39 3) 129 (5) 618 (21) 1150 (46) The methods BM, LARS and PLSR were used to calculate ... BM 659 (26) 4049 (108) 104 63 (34 3) 79 (2) 416 (6) 850 (12) LARS 707 (24) 4019 (71) 8 230 (124) 91 (2) 465 (6) 927 (12) PLSR 9 93 (24) 4242 ( 73) 8405 (1 23) Discussion and conclusions The accuracies...
- 11
- 379
- 0
Handbook of Residue Analytical Methods for Agrochemicals VOLUME 1 and VOLUME 2 doc
... 132 2 132 2 132 2 132 2 132 3 132 3 132 3 132 3 132 4 132 4 132 5 132 5 132 6 132 6 132 7 132 7 132 7 132 8 132 8 132 8 132 8 132 8 132 8 132 9 132 9 132 9 132 9 133 0 133 0 133 1 133 1 133 2 133 2 133 3 133 3 133 3 133 3 133 4 133 4 ... Instrumentation 32 7 32 7 32 7 32 7 32 9 33 6 33 6 33 6 33 9 33 9 33 9 34 2 34 4 34 4 34 7 34 7 34 7 34 7 34 8 34 8 34 9 35 0 35 0 35 1 35 1 35 2 35 4 35 5 35 9 35 9 36 0 36 1 36 1 36 1 36 2 36 3 36 3 36 6 Contents of Volume Calculation ... quantitation, and limit of detection Calculation of residues Important points Abbreviations and acronyms Index 133 5 133 5 133 5 133 5 133 6 133 6 133 6 133 7 133 7 133 7 133 7 133 7 133 7 133 8 133 8 133 8 133 8 133 9 133 9...
- 1,428
- 571
- 0
Nonlinear Stability of Finite Volume Methods for Hyperbolic Conservation Laws: and Well-Balanced Schemes for Sources ppt
... 13 14 15 15 16 19 22 24 24 25 26 29 30 32 33 36 40 45 47 48 50 53 58 58 Source terms 3. 1 Invariant domains and entropy 3. 2 Saint Venant system ... (2. 23) (2.24) Lemma 2.8 The left-hand side of (2. 23) and the right-hand side of (2.24) are nonincreasing functions of r and l respectively In particular, for (2. 23) and (2.24) to hold it is necessary ... invariant domains, see [35 ], [36 ] Finally, the Rusanov ux is obtained according to Remark 2.2 by optimizing (2.1 03) , and taking for c in (2. 93) c= sup U=Ul ,Ur sup |j (U )| j (2.104) 32 Chapter Conservative...
- 143
- 611
- 1
compact numerical methods for computers linear algebra and function minimisation 2ed - adam hilger
... If x = ak, then straightforward use of equations (3. 23) and (3. 24) or (3. 25) and (3. 26) gives XT X – x T x = (v – q)/2 > (3. 33) Using (3. 31) and (3. 22) in (3. 33) gives (3. 34) Thus, once columns ... for computers Singular values 3. 365840 731 1E+00 1.08127 630 36E+00 6.7 431 328720E-01 5 .36 27598567E-01 3. 365840 731 1E+00 1.08127 630 36E+00 6.7 431 328701E-01 5 .36 27598503E-01 Hilbert segment: Column orthogonality ... p/(v cos φ ) for q > sin φ = sgn(p)[(v – q)/(2v ) ] cos φ = p/(υ sin φ ) ½ for q < (3. 23) (3. 24) (3. 25) (3. 26) where } sgn (p) = –1 for p > for p < (3. 27) Note that having two forms for the calculation...
- 288
- 501
- 0
Báo cáo hóa học: " Research Article Some Iterative Methods for Solving Equilibrium Problems and Optimization Problems" potx
... and 3. 38 , we have that lim yn − ρn n→∞ 3. 43 18 Journal of Inequalities and Applications Observe that yn − Syn ≤ yn − xn xn − Sρn Sρn − Syn ≤ yn − xn xn − Sρn ρn − yn 3. 44 From 3. 27 , 3. 33 , and ... yn − p 2sn ν λ2 s2 Byn − Bp n 3. 34 s2 Byn − Bp n − 2sn ν yn − p 2 Byn − Bp Observe 3. 31 that xn −p ≤ − βn ρn − p βn xn − p 2αn λ2 3. 35 Substituting 3. 34 into 3. 35 , we have xn −p ≤ xn − p 2sn ... Trn xn and yn 1 rn η − yn , yn in 3. 12 and η F yn , yn 3. 11 η − yn , yn − xn ≥ 0, rn F yn , η yn − xn Trn xn , we have F yn , η Putting η 1 F yn , yn rn − xn ≥ 0, 3. 12 ∀η ∈ C 3. 13 yn in 3. 13 , we...
- 25
- 401
- 0
Báo cáo hóa học: " Research Article Hybrid Iterative Methods for Convex Feasibility Problems and Fixed Point Problems of Relatively Nonexpansive Mappings in Banach Spaces" docx
... T1 T and T2 S, then Theorem 3. 3 reduces to the following corollary Corollary 3. 5 Plubtieng and Ungchittrakool 22, Theorem 3. 1 Let E be a uniformly convex and uniformly smooth Banach space, and ... Kitahara and W Takahashi, “Image recovery by convex combinations of sunny nonexpansive retractions,” Topological Methods in Nonlinear Analysis, vol 2, no 2, pp 33 3 34 2, 19 93 13 W Takahashi and T ... problem: convergence of projection methods, ” Applied Mathematics and Optimization, vol 35 , no 3, pp 31 1 33 0, 1997 10 G Crombez, “Viewing parallel projection methods as sequential ones in convex...
- 19
- 287
- 0
Computational Methods for Protein Structure Prediction and Modeling Volume 1: Basic Characterization pot
... email: jliang@uic.edu Library of Congress Control Number: 2006929615 ISBN 10: 0 -38 7 -33 319 -3 ISBN 13: 978- 038 7 -33 319-9 Printed on acid-free paper C 2007 Springer Science+Business Media, LLC All ... six methods [three “human-expert methods —authors’ annotation, CATH, and SCOP and three “fully-automated methods —DALI (Holm and Sander 1994), DomainParser (Guo et al., 20 03) , and PDP (Alexandrov ... the forefront of the major areas of the field and bring extensive experience and insight into the central intellectual methods and ideas in the subdomain and its difficulties, accomplishments, and...
- 407
- 289
- 0
Variational Methods for Crystalline Microstructure - Analysis and Computation pptx
... curves between U1 and U3 and U2 and U3 are given by n3 and n5 , respectively Thus the semiconvex hulls of this threewell problem are described by Theorem 2.2 .3 with E3 = {n1 , n3 , n5 } In view ... solutions t 13 , s 13 and t 23 , s 23 of FtT Ft = GT Gs s and T FtT Ft = Hs Hs , respectively A short calculation shows that t 13 = ξ η 4− − , η ξ s 13 = ξ η 4− − , η ξ t 23 = η ξ + −1 , η ξ s 23 = ξ η 4− ... SO(2)Ui for i = 1, with rank(X1 − X2 ) = The minors relation and the expansion λi det Xi − det F = i=1 λ1 λ2 det(X2 − X1 ) − 3 − 3 (1 − 3 ) det λ1 λ2 X1 + X2 − X3 − 3 − 3 now imply that rank X3...
- 218
- 237
- 1
Báo cáo lâm nghiệp: "Evaluation of three methods for estimating the Weibull distribution parameters of Chinese pine (Pinus tabulaeformis)" pps
... 10 3 2.4 × 10 3 MLE 35 3 5 .3 × 10 4.6 × 10 3 LSM 69 3. 84 × 10 3 4.8 × 10 3 Method MOM RESULTS AND DISCUSSION because F(D) of the mean rank method [F(D) = i/(n + 1)] may be a larger value for ... 59 .3% , followed by the LSM 69 times (27.0%) and the MLE 35 times ( 13. 7%), respectively The mean MSEs from 152 times in MOM, 69 times in LSM and 35 times in MLE are 2.7 × 1 03, 3. 84 × 1 03 and 5 .3 ... stand and tree variables Tree variable (n = 15,676 trees) Stand variable (86 plots) dbh (cm) BA (m2/tree) 8.71 10.25 0.009 53 2.47 6. 13 4.06 0.00821 150 2.50 0.45 0.50 0.00196 2 ,35 4 19.50 33 .50 36 .80...
- 6
- 332
- 0
Báo cáo y học: "ISsaga is an ensemble of web-based methods for high throughput identification and semiautomatic annotation of insertion sequences in prokaryotic genomes" pdf
... FULL_IS_CANDIDATE 100 1 530 6267 83 625254 1 530 FULL_IS_CANDIDATE 100 1 530 37 54925 37 56454 1 530 FULL_IS_CANDIDATE 99. 93 1 530 39 15519 39 139 90 1 530 FULL_IS_CANDIDATE 99. 93 1 530 634 4996 634 6525 1 530 Insertion ... (NC_011891) Total IS ORF 15 33 35 35 Complete ORF - 18 24 - - 8 Unknown ORF - - 25 12 25 12 23 14 54 57 18 45 47 Partial ORF - 27 Pseudogene - 3 Unknown ORF Total IS - 38 39 36 - 18 19 18 The table ... 19 433 19 436 /note="target site duplication generated by insertion of ISAcma5“ /rpt_type=direct 19 437 2 033 4 /note="IS5 ssgr IS1 031 family“ /mobile-element="insertion sequence: ISAcma5“ 19 437 19453...
- 9
- 672
- 0
Level set methods for MRE image processing and analysis
... 33 3. 1.2 Complex Diffusion by Schrodinger Equation 34 3. 1 .3 Coherence Diffusion 35 3. 2 Level Set Segmentation 36 3. 2.1 Mathematical Modeling 38 3. 2.2 ... 21 2.2 .3 Elasticity Reconstruction 24 2 .3 LSM for MRE Image Processing 29 Chapter NEW LEVEL SET METHODS FOR MRE 31 3. 1 Level Set Diffusion 32 3. 1.1 Anisotropic ... 40 III 3. 3 Level Set Registration 42 3. 4 Experiments 43 3.4.1 On Level Set Diffusion 43 3.4.2 On the Unified Level Set Formulation 45 3. 5 Summary...
- 138
- 420
- 0
Nonrigid registration methods for myocardial perfusion mri and cerebral diffusion tensor mri 1
... 49 § 3. 2.5 Preliminary Results 52 § 3. 3 Registration of Myocardial Perfusion MRI 55 § 3. 3.1 Initial Alignment 55 § 3. 3.2 Heart Ventricle ... boundary between the LV and the myocardium 46 3. 3 Registration results for a renal perfusion sequence 53 3.4 Registration results for a myocardial perfusion ... dundant and difficult to process To simplify the processing, the diffusivity of each voxel is usually represented by a × matrix D11 D12 D 13 D = D21 D22 D 23 , D31 D32 D 33 (2.1)...
- 137
- 228
- 0
Nonrigid registration methods for myocardial perfusion mri and cerebral diffusion tensor mri 2
... Corr Sig 0.507 0.000 0.5 63 0.000 0. 533 0.000 0.646 0.000 Brain Stem Corr Sig 0.157 0.275 0.065 0.654 0.148 0 .31 5 0.052 0. 735 Whole Brain Corr Sig 0 .38 7 0.006 0 .39 6 0.004 0 .31 7 0.028 0.559 0.000 ... of pixels 3. 5 2.5 1.5 0.5 0 0.05 0.1 0.15 0.2 0.25 0 .3 0 .35 Pixel−wise standard deviation 0.4 0.45 0.5 Figure 5.14: The histograms of pixel-wise FA standard deviations within the brain area after ... 20 25 30 35 subjects 0.8 0.7 0.6 DTI measures 0.5 0.4 0 .3 0.2 0.1 Healthy subjects Patients 0 10 15 20 25 30 35 subjects Figure 5.15: Comparison of MR measurements between healthy subjects and...
- 34
- 334
- 0
Analytical methods for the performance evaluation and improvement of multiple part type manufacturing systems
... -0. 43 7. 43 Case CMT CD 7.02 -7.02 13. 69 -9. 23 11 .34 -15. 93 14.45 -19.86 5.75 -8. 83 4.62 - 13. 54 -6 .32 2 .35 -9 .31 5.64 12.95 3. 37 14.26 4.97 Case CMT 1. 53 1 .34 -12 .37 -10.16 -5. 13 -4.95 -1.14 -1 .31 ... -1.992 A 0.288 0.1 73 B 0 .35 8 0.412 A -0.297 -0 .36 3 B 0.128 0.161 A 0. 139 0.174 B Production rate error % CMT CD 0 .38 8 0 .36 8 0. 030 0.061 -0.224 -0.224 0.2 43 0.2 83 0.262 0 .33 3 0.052 0.105 Parttype ... CD CMT CD 0. 932 0.911 0 .37 1 -1.561 A 0.094 0.095 0.921 0.717 B 0.2 83 0.264 0.590 0. 631 A -0.595 -0.819 -0 .39 2 -0.5 43 B 0.649 0. 537 -0.246 -0 .33 9 A 0. 033 -0.795 -0.144 -0.165 B Table 3. 5: Errors...
- 218
- 351
- 0
Mathematical theory and numerical methods for gross pitaevskii equations and applications
... BEC for β = 0.20716N and λ = 0. 033 146N with different number of particles N λ β -0.5 -0.25 0.25 0.5 0.75 1.0 Eg 2.957 2.8 83 2.794 2.689 2.5 63 2.406 2.1 93 µg 3. 927 3. 817 3. 684 3. 525 3. 332 3. 084 ... 0.286 0 .30 3 0 .32 7 0 .36 4 0.4 43 g Epot 1.721 1.675 1.618 1.550 1.468 1 .36 3 1.217 g Eint 0. 839 0.8 53 0.890 0.950 1.047 1.212 1.575 g Edip 0. 131 0.081 0.000 -0.114 -0.278 -0. 534 -1.041 g σx 1.1 53 1.111 ... 36 3. 2 Results for the quasi-2D equation I 38 3. 2.1 3. 2.2 3. 3 Existence and uniqueness of ground state 39 Well-posedness for dynamics ...
- 222
- 332
- 0
Inexact interior point methods for large scale linear and convex quadratic semidefinite programming
... When ν = 0, (3. 3) gives the optimal conditions for (P 1) and (D1) For a nonzero ν, (3. 3) is the optimal condition for the log-det problems, that is, adding log barriers −ν log det x and ν log det ... 1) and (D1) are (strictly) feasible if there exists (x, y, z) satisfying the linear constraints in (3. 3) and (x, z ∈ int(K)) x, z ∈ K 3. 2 An infeasible central path and its neighborhood 3. 2 33 ... neighborhood 33 3. 3 An inexact infeasible interior-point algorithm 38 3. 4 Proof of Lemma 3. 7 44 Inexact primal-dual path-following methods for l1 -regularized...
- 146
- 557
- 0
Signal processing methods for mental fatigue measurement and monitoring using EEG
... Experimental Design and Data Collection 83 3 .3. 1 Mental-Fatigue EEG Experiments 83 3 .3. 1.1 Hardware and software environment 84 3. 3.1.2 Subjects ... the channel Fp1-F3 represents the voltage difference between the Fp1 electrode and the F3 electrode Next, the channel F3-C3 represents the voltage difference between F3 and C3, and so on through ... 84 3. 3.1 .3 Procedure 85 Labeling of Mental-Fatigue EEG 85 3. 3.2.1 Why AWVT? 85 3. 3.2.2 Characteristics of An Ideal Objective Performance...
- 254
- 507
- 0
Carbon emission allocation methods for aviation sector theory and experimental analysis
... Period_4 -3. 719 63 0.000 -0.820 -1.261 -0 .38 0 Period_5 -4.854 63 0.000 -1.025 -1.447 -0.6 03 Period_6 -3. 3 43 63 0.001 -0.841 -1 .34 3 -0 .33 8 Period_7 -3. 406 63 0.001 -0.7 83 -1.242 -0 .32 4 Period_8 -2 .33 2 ... 63 0.1 23 2.098 -0.586 4.7 83 Period_6 1.579 63 0.119 1 .38 9 -0 .36 9 3. 147 Period_7 1. 83 63 0.072 1.655 -0.152 3. 462 Period_8 2.142 63 0. 036 1.627 0.109 3. 144 Period_9 2.448 63 0.017 1.925 0 .35 4 3. 496 ... Period_10 3. 682 63 2.628 1.202 4.054 Period_11 2.847 63 0.006 1.881 0.561 3. 202 Period_12 3. 064 63 0.0 03 2 .38 8 0. 830 3. 945 Period_ 13 2.751 63 0.008 2.169 0.5 93 3.744 Period_14 2.401 63 0.019 1.755...
- 65
- 887
- 0
RESEARCH ARTICLE Parallel hybrid extragradient methods for pseudomonotone equilibrium problems and nonexpansive mappings
... Theorems 3. 6 and 3. 10, we obtain the corresponding result announced in [1, Theorem 3. 3] Numerical experiment Let H = R1 be a Hilbert space with the standart inner product x, y := xy and the norm ... as in the proof of Lemma 3. 2 and Theorem 3. 6, we conclude that F, Cn , Qn are closed and convex Besides, F ⊂ Cn ∩ Qn for all n ≥ Moreover, the sequence {xn } is bounded and lim ||xn+1 − xn || = ... ≥ (3) This algorithm was extended, modified and generelized by Anh and Hieu [3] for a finite family of asymptotically quasi φ-nonexpansive mappings in Banach spaces According to algorithm (3) ,...
- 19
- 319
- 0
Bayesian recursive algorithms for estimating free space and user intentions in a semi autonomous wheelchair with a stereoscopic camera system
... freespace 72 3. 33 Disparity map 73 3 .34 3D point map 73 3 .35 2D distance map with one freespace 73 3 .36 a Left image with one freespace 73 3 .36 b Right image ... Obstacle and Freespace Detection 62 3. 3.1 Distance Perception 63 3 .3. 2 Computation of 3D Point Map 63 3 .3. 3 Computation of 2D Distance Map 67 3. 3.4 Obstacle and Freespace ... 53 3.12a Colour rectified left image 53 3.12b Colour rectified right image 53 3.13a Edge left image 54 3. 13b Edge right image 54 3. 14 Correlation of two 3x3...
- 266
- 266
- 0
Tìm thêm: xác định các mục tiêu của chương trình khảo sát chương trình đào tạo gắn với các giáo trình cụ thể xác định thời lượng học về mặt lí thuyết và thực tế tiến hành xây dựng chương trình đào tạo dành cho đối tượng không chuyên ngữ tại việt nam điều tra với đối tượng sinh viên học tiếng nhật không chuyên ngữ1 khảo sát thực tế giảng dạy tiếng nhật không chuyên ngữ tại việt nam khảo sát các chương trình đào tạo theo những bộ giáo trình tiêu biểu xác định mức độ đáp ứng về văn hoá và chuyên môn trong ct phát huy những thành tựu công nghệ mới nhất được áp dụng vào công tác dạy và học ngoại ngữ mở máy động cơ lồng sóc hệ số công suất cosp fi p2 đặc tuyến hiệu suất h fi p2 đặc tuyến mômen quay m fi p2 đặc tuyến tốc độ rôto n fi p2 đặc tuyến dòng điện stato i1 fi p2 sự cần thiết phải đầu tư xây dựng nhà máy thông tin liên lạc và các dịch vụ phần 3 giới thiệu nguyên liệu chỉ tiêu chất lượng theo chất lượng phẩm chất sản phẩm khô từ gạo của bộ y tế năm 2008 chỉ tiêu chất lượng 9 tr 25