3D-reconstruction and evaluation of MR images of children with juvenile idiopathic arthritis (JIA)
|
|
|
- Karin Glenn
- 5 years ago
- Views:
Transcription
1 Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich Year: D-reconstruction and evaluation of MR images of children with juvenile idiopathic arthritis (JIA) Hou, Mei-Yin Abstract: Objectives. 1) Virtual bilateral TMJ reconstruction from magnetic resonance (MR) imaging of 28 children (age range: ) with juvenile idiopathic arthritis (JIA) by means of state-of-theart software and 2) quantitative intra- and interindividual comparison of joint deformation. Methods. MR sections of all joints were assessed by two pediatric radiologists and reconstructed using Amira. Subjects were divided into three age groups and two diagnostic groups (no/mild vs. severe deformation). After ascertaining normal distribution, intra- and interindividual joint comparisons were performed with ANOVA and ttests at =0.05. Parameters not differing between sides and/or plane orientation were averaged intra-individually. Results. Significant differences among age groups were found for: steepness of the anterior fossa slope (p=0.003), condylar volume (p=0.007), intercondylar angle (p=0.008), direct and curvilinear length of the anterior fossa slope (p=0.047 resp ) and medio-lateral condylar diameter (left p=0.023, right p=0.017). Severely deformed TMJs had a smaller intercondylar angle (p=0.009) and a shallower anterior fossa slope (p=0.021) than normal or mildly deformed joints. Conclusion. Virtual 3D-reconstruction of TMJs of JIA children is feasible without ionizing radiation, but requires time and special skills. Across age groups and independent of radiological disease evidence, measurements on virtual models reflected morphological changes observed with conventional radiography during growth. Due to limited patient numbers in each age group, diagnostic (sub)groups could only be formed across all subjects. 3D-parameters of severely deformed joints seem to reflect altered joint growth and development. Future studies with larger cohorts may reveal further differences and should include healthy controls. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: Dissertation Originally published at: Hou, Mei-Yin. 3D-reconstruction and evaluation of MR images of children with juvenile idiopathic arthritis (JIA). 2012, University of Zurich, Faculty of Medicine.
2 ! #! %& % #!!! ( #! %&!!# %&& (!) & &+,, #! %&./
3 &( ) / /. 1& // 1 /67 // 1 8&9 // 1 00! : / /; ; /< ; /67 /< ;! =8&9=5 /< ; /25 /< ; >5 /? ; 0 = = Α /? ; 4&= 5. ; 02 = / 3! 4 <> <?8? /. 4. // ;/ / ) ;4 /0==Β ;1 /4>Χ 31 2
4 ( (+/ΑΧ8&9 &Α < 3/;?Α) 7 = 92Α5 ) Α: = 7 +& 7 ) 5)= 67 ) = ) = Ε Α 7= )=)ΦΓΧ ΗΙ..1 # ) Ε= ) 5 +6 = ) = = =Ι...0Α 5 =Ι...3Α5 =Ι...<Α = =Ι..43 =...?Α 5 =Ι.. 0=Ι../3Α 6 5 8&9 5 =Ι...?Α ) = =Ι.. /Α57 3
5 ) +Χ0! 8&9 92 ) : = = = = ) =5)! = = Α= 5 7 0!= 5 7 7) = ) 5 5 4
6 ,. +!7 = 92Α (! # )..3 4./ =/... ) & 92 ) 4 = < /. % 7 9 6== /3<3ϑ# ) )! Χ & = 6) 6 & )6 () == ) = (! 8=!! & = &8Α 6 = ) > 92# Φ8! ) 5 Κ & + Χ 1; & < 92 Κ )5 & = # 5
7 + &8 ) ) 8& ( ) == ) == Ε! )!Α Φ ) Χ ) ΦΓΧ ΗΙ..1 # ) 6 Ε 6) )!5 + 6 == )# 66 =Ι...0Α 5 =Ι...3Α 5 Λ =Ι...<Α % 6 =Ι..43 =...?Α! 5 =Ι.. 0 =Ι../3Α 6) 5Λ =Ι...?Α =Ι.. /Α +Χ0! 6 Μ == & = Χ = = Λ ) 6) Λ ) ) 6 ) 6
8 9 = 92Α : /??;Α! 92 /; Β) Β Α 92) 56/<?3 2 = ) = )..3 4./ = /... )../. 0=/... 5./.Α 8 5) )5 )5 /??0Α # 5 == Λ = =5= ) 5 =5 = 5 = = ) Β 6 = 7 ) = 5 Α ) 87 =5 92 = ) = =7 8&9Α /3 <3ϑ =Β ==== &5,/?;?Ν /?34Ν /??<Α ϑ ) = 7
9 2 )5 = 5= 92 == ) ΦΑ = 5 = 2 )= 5 3,% 3Α ) 8&9 /??0Ν, /??;Ν8)..4Α Γ== 8&95 57 &../Ν6..1Α 8&9 0.ϑΑ ;?ϑα /??0Ν #../Α Γ= = Ε 5=) == 7) 8 =7)= =)5 = &9 == ) 5 5 = (58&9 = = 5= 5= :5 >5 8&9 &2Α Γ ΕΒ Ε =&2 &..?Α 8 5 = = )7 = = ) 5 8 =8&9 5 = 8
10 # 5 ==7 = == Α ==5&2=5 5 ))!Α8&9 92= Φ) )5 8&9 =5 5 0!Α5 ) 7 5 =5 : Φ5 > >8 ==5Α&2 =)= = >5 =!5 5 ) = 5)5 >..<Ν>./.Α 2925) = =&2 8&90!.. Α 6 == ) 5 0! 8&9 > >8 ) >./.Ν./.Α Γ) Β= 8&90! &25 5= =7 : )
11 / ) /Α 5 &2 8&9 <92 1;7 5 = ) Α : 5 =7) ) 7 5== 0! 10
12 1 1+ ( &2) < /1/0Α)? /5 3Ο/;?Α ) 2 % 5 2%Α(../Α #5../Α 5 ) (Β = 8&9 Ε=&28&9)= ; Ε)= / == 5 2 ( ) ) = 55 Α 7 = =?8/ 1+,& &2 )/ 18 6&Ε8) =,!Β (&65 &)Λ2 6Α#, = 56) (Β )=) 8&9 = =58&9 ): 0! : 8Ε8(Ε= / Ε0? Ε.ΠΑ 2 = )/ =).Ο 4 2 )) 1;Θ/? Β /.. ) & ) 5 ) = )5 Γ 11
13 ) Α Β 7 Α Α55 Α 878 ) ) ) ) 7 ) 9 8/) ) ) 2) 8 ) 7 ) = 5 5= Ε ) >55) ) )5= ) )5) : )! = =5) ) 5)55 6 /?? Ν /??<Α = 7 ) % /?? Α =) =5 &2 )= 2 0? / 12
14 Λ9=Α 8 5 ) 7 0! ) 5 ) Χ 22 6!> 6Α 2= ) = :5) =5 7 ==Β 7)= Α) 4. &Φ6Λ 6Α 8 )5Β Α ) ) 5 Β 5= 1 0 /Α! # %& 8 ) Β=8& = ) = Β 5 )5==5 = 6 :5 ) == Β5 ) 5 5 ) = =Β 1 0 Α 13
15 y Α z x y y z x z x Α Α ( %& ) +%# &, & ) # &, &. # & 8 ) 5 ) = = ==5Β Α 8) 5 ) = 5 =) ) = =Α 14
16 # %& 8 ) 5 ) = = == 5Β Α ) == Α 8 ) ) ) = ) = = ) + # %& 15
17 5 ).. ) 1 0 1Ν= )Α.. # %& 1+/ 0!)55 = = ΒΑ! ) = Β= =Λ 2 ) ) = Α)55= ΦΓΧ= ) 5 = ) ) ) = ) 5 ) 5 ) 5 &Λ5 Λ 6 ) αι..1=ρ..1 Α../Σ=Τ..1 ) 16
18 5 ΥΑ.../Σ=Τ../ ) 5 5 ) ΥΥΑ=Τ.../ ) Β5 5 ΥΥΥΑ 5 ) =5 6#66 Λ) Χ /< 17
19 3 3+ ( 8? / ) = < /1/0Α= )? / 5 3Ο/;?Α &) /0<.?; 0Ο /;; 0Α)? 4 /4 ;Ο;/.Α & ) 15. /Ο/ Α = 8 0Β //=5 = 0 ) Α Φ) ΦΑ= Γ=,% 3Ν ),% 3 ) ) 3+, & 0 3+,+ 0 Χ 5 1 0Α 8? Β= /. / 85 )//? 3Π 7 <Α/1<.Π 7 //Α ) /4. 4Π 18
20 3+,+,) 0 >5 )= ) 5 5 8? Β= /. /. 0 Γ )50?ς 7 ;Α/0< ς 7 0Α ) ;?3 1ς 0?.Ο/0<.Α5 = 53/? 1ς 03;.Ο//.;.Α %5 )/; 7 5? 7 Ν 7 ) : 7 /./1/< Τ/.1Α & 7 ) / /1 /./Ο/ 41Α/.5 3+,+ 8? 4 = 7 8 /. 4 8 = = ) 1Π 4? 3Π )0/ ;Π /4 0Ο4; 1Α = 5 0/ 0Π /? Ο 4? 3Α = 0. ;Π 1Ο4 0Α = 50/ 1Π <?Ο43 Α 7 = ) 5 7? = 19
21 Ν ) ) ) 7 /< 1Α 8? 1 = 7 8 /. 1 8 =0? /; 4 8 ) = ) 7 /3 8 ) 7 < 8 = =8? ;7 ) /. ; 8 =4 < /3 0 8 ) 7 7 1Α 8 ) 7 Α /3 = Α 3+,+/ 0 8 = 5 8? 3 / /. 4 7 ;Α /< 4 7 0Α /1 ; /. 3Ο/< 4Α = 5/1 4 /. 4Ο/3 1Α 5 20
22 8. 1 / // < 3 3 1?Ο// /Α = /Ο// <Α5 8 5) 7 ; 7 / ) =.Ο;5 ; 7 Α = ;Ο/ 5 /< 7 Α= / Ο/<5 4 7 Α 1;7 )5)Β== ) & 7 75! 8? < >5 ) ) = =)7 7 =Α)7 = Α 8??8? /.Α 67 / 0) )5 8 7 Ω Ξ ) /. <Ο/. /4 7 = 5 ) )=5 4 7 Α 7ΑΒ 7 Α ) ΦΑ= Α ),% 3 Β=)Α 8) 7 ) ) = ) =Λ ) 21
23 = ) 5 5 ) Ε ) = 5 =Ι. 4.Α = = =Ι.?/?Α = 5= 5=Ι. 4/1 = =Ι. 4.Α 5 = 5 = Ι. <1 = = Ι. /..Α = ) ) = = /0 0/!!/!1 Α )8? // Β= ) /. /1Ο/. 1 6 = ) =Ι.. 1Α = =Ι..43Α =Ι.. 0=Ι../3Α Λ =Ι.../Α5 =Ι...<Α5 =Ι...3Α = == =Ι...0Α =Ι...?Α 5 5= 5 Β5 =Τ.../Α = 8? / Α ) )= 0 55 = = >5 5 )=/ /. ;Ο/. 0< )Β= = = 2 Α)= 2 Α = ) ) = )8? /
24 ) = 5 ) 5 =Ι...? = =Ι...0Α 8 = = 5))= = ) =Ι.. < = = Ι.. /Α Φ 5 = ) ) = =Ψ ) 5 = 23
25 4 8 5 )&2 = 5 =7 92 0! = ) + = = = & = ) 7 = 2 = = := 0!=5 7 ): 5 =) ) 7 5 &2 : 0!=592 8&9 8 5 ) =5 / ) 5 ) = 5! = = = = 5 ) 5 = 25 ) 5 5 = 5 ) 24
26 = = == 5 == == = 5= 5 8) ) ) )) 7 )7 7 ) 7! = 0! =7 5 = = 0! = 2 5 ) 5 = ) :5 )= = >= 8&9) =5 = 5 65) = 8&9 92 = > >8,7..<Ν./.Ν>./.Α 85 5 Ε 7 55 =5 ) ) 5 7 &2> >8 0! ) : 2 : 0! 5=8&9 & Γ5 = = 25
27 92=.. Α 0! 8&955= 7 =! &2 = => >8 = 5 2:5) = ) 7 : = : 5) = 7 = 5 ) 7=5,) &2 5 = = Ο =5 ) 7 ) 5 88&9 5 =5 8 5 : = Ζ5Ζ 8&9 =5 92) = ) = =7! = = ) 5 =50.1.ϑ =5 = 5 = = 5 7 & ;.ϑ!&! 26
28 5 Α)5Β 8 = 5 ) =)= = : >8 Ε =&2 5 = 6 :5=0! )= & 5 5 ) 9 = = 5 55 ) 5 5Α :7)..4Ν.....;Ν(..<Α 8 8&9)= 5) )= 5 8&9 )92)= = ) 27
29 5) 8 5 ) 0! & 8&9 )92 = : 7 =5 2 ) 5 5 ) = 5 ) = &9 ) )) 5 8 Β= 5 )= + = = = 5 = ) = = = = = 58&9 92= 28
30 6&( > Β ΒΑ 5,!32 67 Β [5 [5! [5,[ Λ[! Φ,% 3 / // / ; < 4 /43 43 < = ] = < 1 1 1? /0.?. =5 0 3? / <. 1 1 = = 4 ; ; ; 1. / //3 1 /? ;. / /.3. /3? = = ; / / /. / / =5 = 3? 3 /. < 3 / =5 < 3? 0 / 4 < / / ; 0 0 =5 =? / ?. /1. 1 0?? Β = /. ; 0 3 ; /.. /. =5 = = // < 0 ; < / 1 / 3. ; 4 =5 / 0 < /.?. /?. /0 // 1 //.. 1 /1. 44? = /4 // < 3 / 4 3 /4;? 0; / ( = /1 ;? 1 / ; //<.. /; // < // <. / /0<. 0/ =5 = /3 / /0? <? 3 = /< 4 4 / 3 3 /.4. /1 Β = = /? /;? /4 / < /;0. ;/. =5 =. 3 3 < 4? / ;. ;. = / /? ] /;. =5 = ] // ; < / ; Β = 0 /1 ; 0 4 / /;; 0 4; < =5 = 4 /. 4? 3. 3 /1/ ( 1 3 / / / ;?; 0 /4 ; ] ; //; =5 = 3 /. 3??.? /4 < 04 4 ( < // 4 < 4? /44. 00? = =? / /0<.? 4 6!? / 0 ; ;. 0 ; 0 / 0. /00 < /< < 0. 0 // 4 29
31 30, 4 67 [Π / /0< ; /1. ; 0 /40 < 4 /4. 1 /04 0 ; /0; 3 /1. < /4/ ;? /4. 0 /. /44 1 // /1< / /? / /0 /0? 1 /4 /4; ; /1 /1/? /; /1/ 1 /3 /4. 1 /< / 4 1 /? /0; <. /4? / / 3 4 /4; 3 0 /0< 4 /0? 3 1 /43 < ; / < / 3 /4; < < //? 3 /4. 4 6! /4. ; < <
32 , ( 67 Χ[ς Χ%[ς / ; /.< /./0?;1 /.1 0 /0< /.0; / ; ;.. / /? 1 ;/< 1;1 /.? ; 3. ;/. / /1 3 3<; <4? /.< < ;/; ;1. /.;??;< //.; / /4 /. ;4/ ;41 /./ // 3/< ;33 /.; / ;14 <.3 / 0 /0 <1? 3?< /.< /4 < 3 3/4 / /; / /./ /; ;/0 3.0 / /1 /3 3. 3?4 / /. /< /.0 /? <<? /.4 / /3. ;?0 3?; / /1 / 4</ 13 / /? 3<3?? / /< 0 /./< 3<3 /? 4 1 ; 1;4 / ?< / 0 ; 0? 4 1 /? 3 3<< /.<4 / 0< < 14; 03; / 41 ;?3 1 3/? 1 / /1 6! 3/1 3 /1 30; / /?4 4 / /;. // 31
33 , = = Α[Π 6= % = Α[Π 6= Α[Π 6= % Α[Π / / 0. / 0/ 4 < <? < < 0 0; / ; 0/ ; < ; ; / / 4. ; /1 < 4 1? < / < < ; ? 4; 1 4? /. 0? 4 0; 1 0? < 04 / // ? 04 ; / 3 / 1 0 / /< 4 /0 < /? / <. ; / /4?? 0; ; 0 1 0< / < ; 41. /; 0< ; 4< 1 0< /3 01? 04 < /< /4 0 /? /0 /? 1 /? / 0; < 0; / ? / < 3 /< ; /? 3? 4 4. / 0< / / /?? 4 0/ < /4 0 /4 / 1 <? ; 0 / < 0. < <? 0/? < / 0. / 1 1 /1? 0/ ; 0/ 0 0. ; 0/ 1 6! 0. < < 0 0/ /? ; < ;? 1 < 1 /. < 32
34 , 67 % = Α[ %% = Α[ % Α[ %% Α[ / < <? / // /. 1 /. 4 // 3 /. /1 3 0 /. 0? /. /? < 4? 3?.? 3? 1 1 /. 0 /. / /. 0? ; ;?? / 0?. /. 1 3 /. / 0 / / / 3 < /0 4 /0 / /; 4 /0? / < / 4 /0 3 / 3 /. // ; / 3 // 1 /0 // /. 4? 1 /. 1? 1 / ; / /0 <?? <? /. / /4 /. /.? // 0 /. < /1 /0 0 /. /4 1 / 0 /; /. <? < /. ; /. 1 /3 /1 4 /; /4 3 /4 ; /<? // 3 /. /. < /? / 1 //? /0? / 0. / /. < / 1 /? /? 3? 3? 1? 1 /0 < /0? /1 0 /4 < 0 //?? 0 // 3? / 4 // < / 0 / ; / / 1 ;. 3 0? 4 < ; / 1 /. ; /. 4?? 3 /. /? /0 3 /0. < // // ; //.? < // 4 // // /. ; 6! // /. //.. // 4 ; // / 4 33
35 , 0( 67 > = Α[ > % = Α[ > Α[ > % Α[ / /..? ; /0 1 // 4 // 4 /. / 0 /3 0 /. ; /.. /.? //. 4 /.? 4 /. 4 /. 1 /. < /. 0 /. 0 /. 1 ; /. ; /4 1? /. / 3 /0 3 /0 0 /? / < < /0 /0 1 /;? /0 3? /4 /4 /4 3 /4 4 /. /4 / /0 ; / /. // /. / /.. // // / / ; 0 3 ; < 3 3 /0 /. 4? 1? /? /4 // 3 // 3 / 0 /? /1 /0. /0 / /1 0 /4 1 /; /. // // 3 // 1 /3 /1 4 /3 0 /1? /; 4 /< /.? //? /. /? 0 /? / 4 /. /4 1 /0.. /0 < / / /0 3 /0 4 /? 0? <? ;?? /1? /1. /3. /1 1 0 /..? 4 //? /. 4 /0. /0 / /0 / / ; 1 4 < 3 ; / ;. ; /. / //. /. ; / 3 3 /0 ; /0 3 /4. / ; < /.. // < // // // //? / / /. 6! // 1 1 // 3 0 / / ; /. 1 34
36 , 5. #6. # 67 &%
41 78!!9)&!9)& 40
42 ! 9)&!+9)& 41
43 !9)&!09)& 42
44 !59)&.. 43
45 _/<Ν4 4 Β Α!132!1# >++ & _ /Ν1 0 =5 Α! 32! # > & & 44
46 _<Ν3? =5 Α!!32 1# >5 & _ <Ν// 4 Α!!!32 1# >!!+ & 45
47 _;Ν/ =5 Α!!32 0# >! & _?Ν/0 0 Β Α!! 32 # >! & 46
48 _ 0Ν/1 ; =5 Α!!+32 # >!0 & & 47
49 !!(!!0 48
50 !!5;!!14 49
51 !!(! ( 50
52 !!(!( 51
53 ! (!+ (. 52
54 !(.!0( Α & 2 & Β Χ Β# Β Β#9 53
55 !5 ( & 2 & Β Χ Β# Β Β#9!1 ( & 2 & Β Χ Β# Β Β#9 54
56 ! & 2 & Β Χ Β# Β Β#9! ; & 2 & Β Χ Β# Β Β#9 55
57 !! 4 & 2 & Χ Ε# Ε#9! ( & 2 & Χ Ε# Ε#9 56
58 ! ( & 2 & Χ Ε# Ε#9! +( & 2 & Χ Ε# Ε#9 57
59 ! & 2 & Χ Ε# Ε#9! 0( & 2 & Χ Ε# Ε#9 58
60 ! 5 (. & 2 & Χ Ε# Ε#9! 1(. & 2 & Χ Ε# Ε#9 59
61 > %,6,7# %# Λ! # Φ5 65&%)9,#= > Κ 5 ==7 Γ 65 Γ & Γ #5 Γ 5 (5./.Ν/ //.//3 > % + >% == 6 %= 6%# > >= &20! = 7 6..<Ν0. ;;0Ο;;3 (! &, > Χ # 6 %& 6 8&9 = 5 = 9!..<Ν<3 <33<</ > Χ > # & %! > 5 =5 7 = > & 6./.Ν1? 1/?04 %&> 2) %Φ9>#6 & ) 8&9 9!..;Ν<1 /..;/./. 60
62 %&Φ9>2) %#6 6 5=7 9!...Ν3? /34. /34; (=5 >Γ= /??;Ν< 44?14! %& (#6!5 = 8&9 9!..4Ν<0 4<.4<4,+66(!,=# 8=7 7 #22 =)= = #!/??;Ν/< 0/ 0/? 8+7,Γ &5 5= 7 /1 5 69! /??0Ν/./ 00 00< Φ6&6 && (! 8 8 =7 7 29#!.. Ν/ Α /.? /1 # 8,8 9 > 5 5 =7) 7 9/??<Ν 1 /4.;/ 61
63 %8 786,9 = 2 = 7 = ) >= ) Γ6 Γ&Γ#/?? Ν30 4?41./ & 8& &> 2 = 5 : = 7 = 9../Ν < /;<?? &59, 6 =7 9! /?;?Ν3? / 10. &%>9>((!68 2 #86 (5 = 7 7 = = 5 =Β 5 ΓΒΑ..?Ν4< ;Α ;<.1 # &, 8 = =5 5= 7 9../Ν < /.? //1 #5(6)8& # 9!Φ 9 Ν 2 % 5 2% 5 7 = (../ 9..4Ν0/ 0?. 62
64 Γ Χ &% % % 8 =77 69 /?34Ν0 <??; 6# 9: 6 = 7 7 = 9Γ&Β 6..1Ν;0 /0;<3/ 6,9%8 = =7 & 5/?? Ν/<1?04 6 Γ7 & 8 /<?3Ν<. 431? 8) & & 6& % 8= 7 = 9..4Ν0/ /4/</4 63
65 ,9 2) #! % & = = = ) #!!! ()5 =! % &! > = 5) & 6 ( == 55 == 64
66 : 2)5 7 =5 = 5) 5=92 / ) ΑΒ Α Α ) ) =Β ) 5 = _ 1Ν 3 Α _/ Ν0 < Α 65
67 _/<Ν4 4 Β Α _1Ν4 3 Α _ ;Ν4 < =5 Α 66
68 _ /Ν1 0 =5 Α _/.Ν; =5 Α _4Ν; ; Α 67
69 _/1Ν;? Α _.Ν3 3 Α _<Ν3? =5 Α 68
70 _0Ν3? = Α _//Ν< 0 =5 Α _ Ν< 1 =5 Α 69
71 _3Ν? 3 =5 Α _ 4Ν/. 4 ( Α _/3Ν/. 1 Α 70
72 _ 3Ν/. 3 ( Α _/Ν// / Α _ <Ν// 4 Α 71
73 _/0Ν// 1 Α _ Ν// ; Β Α _/4Ν// < ( Α 72
74 _/;Ν// < =5 Α _;Ν/ =5 Α _?Ν/0 0 Β Α 73
75 _ 0Ν/1 ; =5 Α _/?Ν/;? =5 Α 74
For personal use only
ACN: 062 284 084 ASX Code: SYS!! #! % &!! ( )!!!!&%!&!! + % % &! &! %,!% &%!!% &% &!%!! &!!% && &,!%! %, &%! & &&!%!! &!% &!! ( &!% &!!!!!!%. / 0 10 1 % 2! & &!,,, & ( & ! 3! (4&!! (!!% & &! &5 )!!!!4
Quick Start with CASSY Lab. Bi-05-05
Quick Start with CASSY Lab Bi-05-05 About this manual This manual helps you getting started with the CASSY system. The manual does provide you the information you need to start quickly a simple CASSY experiment
University Senate 6 May :30 PM Wang Lecture Hall 2
University Senate 6 May 2013 3:30 PM Wang Lecture Hall 2 I. Approval of the Agenda II. Approval of the Minutes from April III. Report from the President of the Senate IV. Report on D1 Athletics (J. Fiore)
Tracing Lineage Beyond Relational Operators
Tracing Lineage Beyond Relational Operators Mingwu Zhang 1 Xiangyu Zhang 1 Xiang Zhang 2 Sunil Prabhakar 1 1 Computer Science 2 Bindley Bioscience Center Purdue University Introduction Lineage (Data Provenance)
Tabella dei caratteri ASCII e UNICODE
Appendice 1: ausiliaria Tabella dei caratteri ASCII e UNICODE formato di stampa: A4 APP_1A_IT_R3.0.docx 1 di 9 Indice 1 TABELLE DEI CARATTERI... 3 Caratteri ASCII... 3 Lettere greche... -4 APP_1A_IT_R3.0.docx
BMC Evolutionary Biology 2008, 8:89
BMC Evolutionary Biology This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. Selection against
Kristoffer H. Rose. Version /01/07
Summary of qsymbols Kristoffer H. Rose Version 1.12 1997/01/07 Abstract qsymbols is a L A TEX [1] package defining systematic mnemonic abbreviations, starting with a single open quote for symbols, and
University of St Andrews Cardiff Business School!!! # % # &! (!#! ) +!!!,#!,! %,!! # 6!! 7.! % %788! 7 9 8! 8! (:0; <= (
Reid, Gavin C. and Smith, Julia A. (2005) Venture capital investor behaviour in the backing of UK high technology firms : financial reporting and the level of investment. Discussion paper. Centre for Research
r v i e w o f s o m e r e c e n t d e v e l o p m
O A D O 4 7 8 O - O O A D OA 4 7 8 / D O O 3 A 4 7 8 / S P O 3 A A S P - * A S P - S - P - A S P - - - - L S UM 5 8 - - 4 3 8 -F 69 - V - F U 98F L 69V S U L S UM58 P L- SA L 43 ˆ UéL;S;UéL;SAL; - - -
COLORPOP! User Guide
COLORPOP! User Guide Copyright 2018 Newell Rubbermaid Europe, LLC. All rights reserved. Rev. 6/18 No part of this document may be reproduced or transmitted in any form or by any means or translated into
Myriad Pro Light. Lining proportional. Latin capitals. Alphabetic. Oldstyle tabular. Oldstyle proportional. Superscript ⁰ ¹ ² ³ ⁴ ⁵ ⁶ ⁷ ⁸ ⁹,.
Myriad Pro Light Latin capitals A B C D E F G H I J K L M N O P Q R S T U V W X Y Z & Æ Ł Ø Œ Þ Ð Á Â Ä À Å Ã Ç É Ê Ë È Í Î Ï Ì İ Ñ Ó Ô Ö Ò Õ Š Ú Û Ü Ù Ý Ÿ Ž Ă Ā Ą Ć Č Ď Đ Ě Ė Ē Ę Ğ Ģ Ī Į Ķ Ĺ Ľ Ļ Ń Ň Ņ
2. Unlock the Customization Features: The Edit Button Click the "Edit" button on the Dashboard Home Page to unlock the customization features.
1. Introduction: Customize Content for Your Students The Garland Science Learning System (GSLS) is completely customizable. You can edit, delete, or add content to create a unique learning experience for
Palatino. Palatino. Linotype. Palatino. Linotype. Linotype. Palatino. Linotype. Palatino. Linotype. Palatino. Linotype
Copyright 2013 Johanna Corsini Arts 79 Typography 1 Sources: http://en.wikipedia.org/wiki/ http://en.wikipedia.org/wiki/typography By Johanna Corsini P a a P o l t a a n L P i l t n a i o a o y l t n n
News from the Wrapper
News from the Wrapper Gesellschaft für Schwerionenforschung mbh Darmstadt, Germany JACoW Team Meeting 2004 Knoxville, Tennessee November 7, 2004 What is still the same? What is still the same? What has
KbdKaz 500 layout tables
a ao a ao a o o o o o a a oo A o a a o a a oa ao oo A o a a o oa ao A a o a oa oa ao o a a a a o a A a a A ˆ a a A ˇ ao a a A a a A o Ao a a A Ao a o a a A ao a o a a A α a A a a a A o o a a A A a a A
Character Entity References in HTML 4 and XHTML 1.0
1 of 12 2/2/2009 2:55 PM Character References in HTML 4 and XHTML 1.0 Here is a set of tables containing the 252 allowed entities in HTML 4 and XHTML 1.0, as described in section 24 of the official HTML
The package paresse. Le TEXnicien de surface February 16, 2013
The package paresse Le TXnicien de surface le.texnicien.de.surface@wanadoo.fr February 16, 2013 Abstract This package implements an example from T. Lachand-Robert in [1]. It provides a means of typing
file:///export/home/apostolo/work/tex/mkindex/mkgrki...
The correct generation and typesetting of an index for a Greek document prepared with LaTeX is not a trivial task at all. First of all, the program makeindex cannot handle Greek letters, but even if the.idx
ALLEGRIA USER MANUAL. François Schiettekatte, Martin Chicoine Université de Montréal May 13, 2004
ALLEGRIA USER MANUAL François Schiettekatte, Martin Chicoine Université de Montréal May 13, 2004 1 Contents Introduction 3 I SpectrumExtractor 4 1 Data files format 4 2 Obtaining energy spectra with SpectrumExtractor
SharePoint Wiki Plus Getting Started
SharePoint Wiki Plus Getting Started Installation & User Guide Copyright 2005-2008 KWizCom Corporation. All rights reserved. Company Headquarters KWizCom 148 Castle Rock Dr. Richmond Hill, Ontario L4C
! " # $ % & ' ( ) * +, -. / : ; < =
! " # $ % & ' ( ) 32 33 34 35 36 37 38 39 40 41 * +, -. / 0 1 2 3 42 43 44 45 46 47 48 49 50 51 4 5 6 7 8 9 : ; < = 52 53 54 55 56 57 58 59 60 61 >? @ A B C D E F G 62 63 64 65 66 67 68 69 70 71 H I J
Ά η η 1 (30%): Sockets. socket () bind () listen () accept () connect () read () write () close ()
ΗΜΥ 316 - Ε α η ια ή Ά η η 5 Υ ο οίη η Π ω ο ό ο α η αι α α ο ή sockets Ά η η 1 (30%): Sockets π α α α α α π πα π α α ω sockets Unix/Linux. Γ α α α π π α π α Server α Client π π π α έ Α π, α α απ π ω.
Hur gör man för att skriva klassisk grekiska?
Hur gör man för att skriva klassisk grekiska? I operativsystemet Win10 byter man språk med en enkel knapptryckning i aktivitetsfeltet: SWE > ΕΛ Man kan ladda ner ett lämpligt typsnitt, SBL Bib Lit, på
The LibertinusT1 Math Package
The LibertinusT1 Math Package Michael Sharpe September 20, 2018 This package is a LATEX math package to accompany the LATEX Libertine text package, serving as an alternative to newtxmath with the libertine
DETERMINISTIC 3D RADIATION TRANSPORT SIMULATION FOR DOSE DISTRIBUTION AND ORGAN DOSE EVALUATION IN DIAGNOSTIC CT
DETERMINISTIC 3D RADIATION TRANSPORT SIMULATION FOR DOSE DISTRIBUTION AND ORGAN DOSE EVALUATION IN DIAGNOSTIC CT Monica Ghita,, Glenn Sjoden, Manuel Arreola, Ahmad Al-Basheer Basheer, Choonsik Lee, Wesley
Topic Training Engineering Report
Topic Training Engineering Report Topic Training Engineering Report All information in this document is subject to modification without prior notice. No part of this manual may be reproduced, stored in
Documentation for the betababel.sty package
Documentation for the betababel.sty package Felix G. Berkemeier 2005/07/10 Abstract The betababel package extends the polutonikogreek option of the babel package. It provides the possibility to directly
FREE. 3-in-1 Printer... Labeling, Bar Code, and Heat Shrink Tube Identification
3-in-1 Printer... Labeling, Bar Code, and Heat Shrink Tube Identificati 3 Year FREE Printer Warranty Industrial printer works like a Bee solving your labeling needs in the factory, warehouse, laboratory,
Multi-slice CT Image Reconstruction Jiang Hsieh, Ph.D.
Multi-slice CT Image Reconstruction Jiang Hsieh, Ph.D. Applied Science Laboratory, GE Healthcare Technologies 1 Image Generation Reconstruction of images from projections. textbook reconstruction advanced
Supplemental Material for Efficient MR Image Reconstruction for Compressed MR Imaging
Supplemental Material for Efficient MR Image Reconstruction for Compressed MR Imaging Paper ID: 1195 No Institute Given 1 More Experiment Results 1.1 Visual Comparisons We apply all methods on four 2D
Ternary Butterfly Subdivision
Ternary Butterfly Subdivision Ruotian Ling a,b Xiaonan Luo b Zhongxian Chen b,c a Department of Computer Science, The University of Hong Kong b Computer Application Institute, Sun Yat-sen University c
Charged Particle Reconstruction in HIC Detectors
Charged Particle Reconstruction in HIC Detectors Ralf-Arno Tripolt, Qiyan Li [http://de.wikipedia.org/wiki/marienburg_(mosel)] H-QM Lecture Week on Introduction to Heavy Ion Physics Kloster Marienburg/Mosel,
3D VISUALIZATION OF SEGMENTED CRUCIATE LIGAMENTS 1. INTRODUCTION
JOURNAL OF MEDICAL INFORMATICS & TECHNOLOGIES Vol. 10/006, ISSN 164-6037 Paweł BADURA * cruciate ligament, segmentation, fuzzy connectedness,3d visualization 3D VISUALIZATION OF SEGMENTED CRUCIATE LIGAMENTS
Nutthapat Kaewrattanapat. Lecture in Principle of Web Design
ASCII CODE (ASCII CHARACTERS) ls should display in files using charsets ISO 8859-1 or UTF-8. [ " ] quotation mark [name: "] [number: "] [ & ] ampersand [name: &] [number: &] [ < ] less than [name:
Predicting Tumour Location by Modelling the Deformation of the Breast using Nonlinear Elasticity
Predicting Tumour Location by Modelling the Deformation of the Breast using Nonlinear Elasticity November 8th, 2006 Outline Motivation Motivation Motivation for Modelling Breast Deformation Mesh Generation
SharePoint Wiki Plus User Guide
SharePoint Wiki Plus User Guide Installation & User Guide Copyright 2005-2008 KWizCom Corporation. All rights reserved. Company Headquarters KWizCom 148 Castle Rock Dr. Richmond Hill, Ontario L4C 5K5,
Always there to help you. Register your product and get support at M110. Question? Contact Philips.
Always there to help you Register your product and get support at www.philips.com/support Question? Contact Philips M110 User manual Contents 1 Important safety instructions 2 2 Your phone 3 What is in
MATH : EXAM 3 INFO/LOGISTICS/ADVICE
MATH 3342-004: EXAM 3 INFO/LOGISTICS/ADVICE INFO: WHEN: Friday (04/22) at 10:00am DURATION: 50 mins PROBLEM COUNT: Appropriate for a 50-min exam BONUS COUNT: At least one TOPICS CANDIDATE FOR THE EXAM:
Learning Algorithms for Medical Image Analysis. Matteo Santoro slipguru
Learning Algorithms for Medical Image Analysis Matteo Santoro slipguru santoro@disi.unige.it June 8, 2010 Outline 1. learning-based strategies for quantitative image analysis 2. automatic annotation of
mdput for mathematical typesetting with Adobe Utopia Paul Pichaureau January 29, 2006
mdput for mathematical typesetting with Adobe Utopia Paul Pichaureau January 29, 2006 Contents 1 Introduction 1 1.1 Requirements.................................................... 1 1.2 The name of the
CALIBRATION BETWEEN DEPTH AND COLOR SENSORS FOR COMMODITY DEPTH CAMERAS. Cha Zhang and Zhengyou Zhang
CALIBRATION BETWEEN DEPTH AND COLOR SENSORS FOR COMMODITY DEPTH CAMERAS Cha Zhang and Zhengyou Zhang Communication and Collaboration Systems Group, Microsoft Research {chazhang, zhang}@microsoft.com ABSTRACT
SharePoint Wiki Plus User Guide
SharePoint Wiki Plus User Guide Installation & User Guide Copyright 2005-2012 KWizCom Corporation. All rights reserved. Company Headquarters KWizCom 50 McIntosh Drive, Unit 109 Markham, Ontario ON L3R
PBSI: A symmetric probabilistic extension of the Boundary Shift Integral
PBSI: A symmetric probabilistic extension of the Boundary Shift Integral Christian Ledig 1, Robin Wolz 1, Paul Aljabar 1,2, Jyrki Lötjönen 3, Daniel Rueckert 1 1 Department of Computing, Imperial College
Convex hulls of spheres and convex hulls of convex polytopes lying on parallel hyperplanes
Convex hulls of spheres and convex hulls of convex polytopes lying on parallel hyperplanes Menelaos I. Karavelas joint work with Eleni Tzanaki University of Crete & FO.R.T.H. OrbiCG/ Workshop on Computational
Reconstruction in CT and relation to other imaging modalities
Reconstruction in CT and relation to other imaging modalities Jørgen Arendt Jensen November 16, 2015 Center for Fast Ultrasound Imaging, Build 349 Department of Electrical Engineering Center for Fast Ultrasound
Model-based Recursive Partitioning for Subgroup Analyses
EBPI Epidemiology, Biostatistics and Prevention Institute Model-based Recursive Partitioning for Subgroup Analyses Torsten Hothorn; joint work with Heidi Seibold and Achim Zeileis 2014-12-03 Subgroup analyses
IMPROVEMENT AND RESTORATION OF BIOMEDICAL IMAGES BLURRED BY BODY MOVEMENT
Proceedings 3rd Annual Conference IEEE/EBS Oct.5-8, 00, Istanbul, TURKEY IPROVEET AD RESTORATIO OF BIOEDICA IAGES BURRED BY BODY OVEET J. Hori, Y. Saitoh, T. Kiryu, K. Okamoto 3, K. Sakai 3 Faculty of
SharePoint Wiki Plus User Guide
SharePoint Wiki Plus User Guide Installation & User Guide Copyright 2005-2009 KWizCom Corporation. All rights reserved. Company Headquarters KWizCom 50 McIntosh Drive, Unit 109 Markham, Ontario ON L3R
11/18/ CPT Preauthorization Groupings Effective January 1, Computerized Tomography (CT) Abdomen 6. CPT Description SEGR CT01
Computerized Tomography (CT) 6 & 101 5 Upper Extremity 11 Lower Extremity 12 Head 3 Orbit 1 Sinus 2 Neck 4 7 Cervical Spine 8 Thoracic Spine 9 Lumbar Spine 10 Colon 13 CPT Description SEGR 74150 74160
STIC AmSud Project. Graph cut based segmentation of cardiac ventricles in MRI: a shape-prior based approach
STIC AmSud Project Graph cut based segmentation of cardiac ventricles in MRI: a shape-prior based approach Caroline Petitjean A joint work with Damien Grosgeorge, Pr Su Ruan, Pr JN Dacher, MD October 22,
A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions
Appeared in: G. F. Cooper & S. Moral (eds.), Uncertainty in Artificial Intelligence, Vol. 14, 1999, pp. 328--337, Morgan Kaufmann, San Francisco, CA. A Comparison of Lauritzen-Spiegelhalter, Hugin, and
A Family of Recompositions of the Penrose Aperiodic Protoset and its Dynamic Properties
Rose-Hulman Undergraduate Mathematics Journal Volume 12 Issue 2 Article 7 A Family of Recompositions of the Penrose Aperiodic Protoset and its Dynamic Properties Vivian Olsiewski Healey University of Notre
Spherical quadrilaterals with three non-integer angles
Spherical quadrilaterals with three non-integer angles Alexandre Eremenko, Andrei Gabrielov and Vitaly Tarasov July 7, 2015 Abstract A spherical quadrilateral is a bordered surface homeomorphic to a closed
Appendix A: An Alternative Estimation Procedure Dual Penalized Expansion
Supplemental Materials for Functional Linear Models for Zero-Inflated Count Data with Application to Modeling Hospitalizations in Patients on Dialysis by Şentürk, D., Dalrymple, L. S. and Nguyen, D. V.
ANALYSIS OF PULMONARY FIBROSIS IN MRI, USING AN ELASTIC REGISTRATION TECHNIQUE IN A MODEL OF FIBROSIS: Scleroderma
ANALYSIS OF PULMONARY FIBROSIS IN MRI, USING AN ELASTIC REGISTRATION TECHNIQUE IN A MODEL OF FIBROSIS: Scleroderma ORAL DEFENSE 8 th of September 2017 Charlotte MARTIN Supervisor: Pr. MP REVEL M2 Bio Medical
A more general model for the analysis of the rock slope stability
Sādhanā Vol. 33, Part 4, August 2008, pp. 433 441. Printed in India A more general model for the analysis of the rock slope stability MEHDI ZAMANI Department of Technology and Engineering, Yasouj University,
Proposed Catalog Changes TECH-PREP ENHANCED SKILLS CERTIFICATE RADIOLOGIC TECHNOLOGY (Computed Tomography) These courses will prepare Registered Radiographer, Radiation Therapist, or Nuclear Medicine Technologist
Mathematics of a Multiple Omni-Directional System
Mathematics of a Multiple Omni-Directional System A. Torii A. Sugimoto A. Imiya, School of Science and National Institute of Institute of Media and Technology, Informatics, Information Technology, Chiba
Experimental Analysis of the Temporomandibular Disc Movement During Mouth Opening
BULLETIN OF APPLIED MECHANICS 5(17), 18-22 (2009) 18 Experimental Analysis of the Temporomandibular Disc Movement During Mouth Opening Jan Krystufek, Zdenek Horak, Martina Fricova and Radek Jirman Abstract
Topic 4: Vectors Markscheme 4.6 Intersection of Lines and Planes Paper 2
Topic : Vectors Markscheme. Intersection of Lines and Planes Paper. Using an elimination method, x y + z x y z x y x + y 8 y Therefore x, y, z Using matrices, x y z x y z 5 (using a graphic display calculator)
Reconstruction in CT and relation to other imaging modalities
Reconstruction in CT and relation to other imaging modalities Jørgen Arendt Jensen November 1, 2017 Center for Fast Ultrasound Imaging, Build 349 Department of Electrical Engineering Center for Fast Ultrasound
Diffusion and Clustering on Large Graphs
Diffusion and Clustering on Large Graphs Alexander Tsiatas Final Defense 17 May 2012 Introduction Graphs are omnipresent in the real world both natural and man-made Examples of large graphs: The World
X-ray Diffraction from Materials
X-ray Diffraction from Materials 2008 Spring Semester Lecturer; Yang Mo Koo Monday and Wednesday 14:45~16:00 8. Experimental X-ray Diffraction Procedures 8.1 Diffraction Experiments using Films 8.1.1 Laue
Semantic Web write-enabling the Web of Data
Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2010 Semantic Web 2.0 - write-enabling the Web of Data Hert, M; Reif, G; Gall,
Quick Start Instructions on using MyOMLab with the JAWS Screen Reader*
Quick Start Instructions on using MyOMLab with the JAWS Screen Reader* To work on assignments in MyOMLab with JAWS, follow these steps to turn on the Automatically Detect for Accessibility Setting: 1.
2 CUTTING TOOL GEOMETRY PRODUCTION TECNOLOGY
2 CUTTING TOOL GEOMETRY PRODUCTION TECNOLOGY Instructional objectives At the end of this lesson, the student should be able to : (a) conceive rake angle and clearance angle of cutting tools (b) classify
F-ing Applicative Functors
F-ing Applicative Functors Andreas Rossberg, Google Claudio Russo, MSR Derek Dreyer, MPI-SWS ML Workshop, Copenhagen 2012/09/13 The Functor Schism The Functor Schism SML: generative functors return fresh
Advanced methods for the analysis of multispectral and multitemporal remote sensing images
Remote Sensing Laboratory Dept. of Information Engineering and Computer Science University of Trento Via Sommarive, 9, I-38123 Povo, Trento, Italy Thesis dissertation on Advanced methods for the analysis
Basic Trigonometry. Stephen Perencevich Department of Mathematics Montgomery College 3Π 4 Π 7Π 7Π 6 Π 2 0, 1 1,0 1,0 Π 3 5Π 3 Π 2
Basic Trigonometry Stephen Perencevich Department of Mathematics Montgomery College 4 0,,0,0 0 4 7 6 5 7 6 0, 5 i All firgures generated by Mathematica. R Revised July, 06 Typeset by L A TEX. Perencevich,
arxiv: v1 [cs.cv] 5 Aug 2015
![arxiv: v1 [cs.cv] 5 Aug 2015](/thumbs/81/84567167.jpg "arxiv: v1 [cs.cv] 5 Aug 2015")
Partitioned Shape Modeling with On-the-Fly Sparse Appearance Learning for Anterior Visual Pathway Segmentation arxiv:1508.01128v1 [cs.cv] 5 Aug 2015 Awais Mansoor, Juan J. Cerrolaza, Robert A. Avery, Marius
The Anatomical Equivalence Class Formulation and its Application to Shape-based Computational Neuroanatomy
The Anatomical Equivalence Class Formulation and its Application to Shape-based Computational Neuroanatomy Sokratis K. Makrogiannis, PhD From post-doctoral research at SBIA lab, Department of Radiology,
Robotics (Kinematics) Winter 1393 Bonab University
Robotics () Winter 1393 Bonab University : most basic study of how mechanical systems behave Introduction Need to understand the mechanical behavior for: Design Control Both: Manipulators, Mobile Robots
General theory of rectilinear ray systems
Allgemeine Theorie der gradlinigen Strahlensysteme J. f. reine u. angew. Math. 57 (860) 89-30. General theory of rectilinear ray systems (By E. E. Kummer in Berlin) Translated by D. H. Delphenich Up to
Diffraction and Interference of Plane Light Waves
PHY 92 Diffraction and Interference of Plane Light Waves Diffraction and Interference of Plane Light Waves Introduction In this experiment you will become familiar with diffraction patterns created when
Data Analysis, Persistent homology and Computational Morse-Novikov theory
Data Analysis, Persistent homology and Computational Morse-Novikov theory Dan Burghelea Department of mathematics Ohio State University, Columbuus, OH Bowling Green, November 2013 AMN theory (computational
Problem Solving 10: Double-Slit Interference
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of hysics roblem Solving 10: Double-Slit Interference OBJECTIVES 1. To introduce the concept of interference. 2. To find the conditions for constructive
Abbie M. Diak, PhD Loyola University Medical Center Dept. of Radiation Oncology
Abbie M. Diak, PhD Loyola University Medical Center Dept. of Radiation Oncology Outline High Spectral and Spatial Resolution MR Imaging (HiSS) What it is How to do it Ways to use it HiSS for Radiation
Journal of Theoretical and Applied Mechanics, Sofia, 2015, vol. 45, No. 2, pp
Journal of Theoretical and Applied Mechanics, Sofia, 2015, vol. 45, No. 2, pp. 59 74 SOLID MECHANICS WAVE PROPAGATION DUE TO AN EMBEDDED SEISMIC SOURCE IN A GRADED HALF-PLANE WITH RELIEF PECULIARITIES.
Image Processing - Lesson 10. Recognition. Correlation Features (geometric hashing) Moments Eigenfaces
Imae Processin - Lesson 0 Reconition Correlation Features (eometric hashin) Moments Eienaces Normalized Correlation - Example imae pattern Correlation Normalized Correlation Correspondence Problem match?
General Factorial Models
In Chapter 8 in Oehlert STAT:5201 Week 9 - Lecture 2 1 / 34 It is possible to have many factors in a factorial experiment. In DDD we saw an example of a 3-factor study with ball size, height, and surface
Greedy Routing with Guaranteed Delivery Using Ricci Flow
Greedy Routing with Guaranteed Delivery Using Ricci Flow Jie Gao Stony Brook University Joint work with Rik Sarkar, Xiaotian Yin, Wei Zeng, Feng Luo, Xianfeng David Gu Greedy Routing Assign coordinatesto
General Factorial Models
In Chapter 8 in Oehlert STAT:5201 Week 9 - Lecture 1 1 / 31 It is possible to have many factors in a factorial experiment. We saw some three-way factorials earlier in the DDD book (HW 1 with 3 factors:
Drawing Outer 1-planar Graphs with Few Slopes
Journal of Graph Algorithms and Applications http://jgaa.info/ vol. 19, no. 2, pp. 707 741 (2015) DOI: 10.7155/jgaa.00376 Drawing Outer 1-planar Graphs with Few Slopes Emilio Di Giacomo Giuseppe Liotta
Performance of the GlueX Detector Systems
Performance of the GlueX Detector Systems GlueX-doc-2775 Gluex Collaboration August 215 Abstract This document summarizes the status of calibration and performance of the GlueX detector as of summer 215.
Automatic Detection of Bone Contours in X-Ray Images
Automatic Detection of Bone Contours in X-Ray Images Alexey Mikhaylichenko 1, Yana Demyanenko 1, and Elena Grushko 2 1 Institute of Mathematics, Mechanics and Computer Science, Southern Federal University,
ARTIO SMS Services HTTP API Documentation
ARTIO SMS Services HTTP API Documentation David Jozefov Michal Unzeitig Copyright 2013 - ARTIO International Co. ARTIO SMS Services HTTP API Documentation ARTIO Publication date: 4.9.2013 Version: 1.0.1
Extreme Ultraviolet Radiation Spectrometer Design and Optimization
Extreme Ultraviolet Radiation Spectrometer Design and Optimization Shaun Pacheco Mentors: Dr. Guillaume Laurent & Wei Cao Project Description This summer project was dedicated to spectrally resolving the
d has a relationship with ψ
Principle of X-Ray Stress Analysis Metallic materials consist of innumerable crystal grains. Each grain usually faces in a random direction. When stress is applied on such materials, the interatomic distance
3D NURBS-ENHANCED FINITE ELEMENT METHOD
7th Workshop on Numerical Methods in Applied Science and Engineering (NMASE 8) Vall de Núria, 9 a 11 de enero de 28 c LaCàN, www.lacan-upc.es 3D NURBS-ENHANCED FINITE ELEMENT METHOD R. Sevilla, S. Fernández-Méndez
Multilevel Optimization for Multi-Modal X-ray Data Analysis
Multilevel Optimization for Multi-Modal X-ray Data Analysis Zichao (Wendy) Di Mathematics & Computer Science Division Argonne National Laboratory May 25, 2016 2 / 35 Outline Multi-Modality Imaging Example:
A fast algorithm for sparse reconstruction based on shrinkage, subspace optimization and continuation [Wen,Yin,Goldfarb,Zhang 2009]
![A fast algorithm for sparse reconstruction based on shrinkage, subspace optimization and continuation [Wen,Yin,Goldfarb,Zhang 2009]](/thumbs/81/83358288.jpg "A fast algorithm for sparse reconstruction based on shrinkage, subspace optimization and continuation [Wen,Yin,Goldfarb,Zhang 2009]")
A fast algorithm for sparse reconstruction based on shrinkage, subspace optimization and continuation [Wen,Yin,Goldfarb,Zhang 2009] Yongjia Song University of Wisconsin-Madison April 22, 2010 Yongjia Song
LECTURE 8: SMOOTH SUBMANIFOLDS
LECTURE 8: SMOOTH SUBMANIFOLDS 1. Smooth submanifolds Let M be a smooth manifold of dimension n. What object can be called a smooth submanifold of M? (Recall: what is a vector subspace W of a vector space
On the Latency-Accuracy Tradeoff in Approximate MapReduce Jobs
On the Latency-Accuracy Tradeoff in Approximate apreduce Jobs Juan F. Pérez Universidad del Rosario, Colombia Robert Birke and Lydia Chen IB Research Zurich, Switzerland IEEE INFOCO ay, 2017 J. F. Pérez,
4th of July
IDNs in Greece Segredakis Vaggelis Administrator Registry of [.gr] Domain Names Institute of Computer Science Foundation for Research and Technology Hellas Email: segred@ics.forth.gr IDN Facts The registration
Distributed and Centralized Hybrid CSMA/CA-TDMA Schemes for Single-Hop Wireless Networks
Distributed and Centralized Hybrid CSMA/CA-TDMA Schemes for Single-Hop Wireless Networks Bharat Shrestha, Ekram Hossain, and Kae Won Choi arxiv:40.5528v [cs.ni] 22 Jan 204 Abstract The strength of carrier-sense
Recognition. Normalized Correlation - Example. Normalized Correlation. Correlation. Image Processing - Lesson 10
Imae Processin - Lesson 0 Normalized Correlation - Eample Reconition Correlation Features (eometric hashin Moments Eienaces imae pattern Correlation Normalized Correlation model Correspondence Problem
CSE-321 Programming Languages 2014 Final
Name: Hemos ID: CSE-321 Programming Languages 2014 Final Problem 1 Problem 2 Problem 3 Problem 4 Problem 5 Problem 6 Total Score Max 15 12 14 14 30 15 100 There are six problems on 12 pages in this exam.
Progress on G4 FDIRC Simulation. Doug Roberts University of Maryland
Progress on G4 FDIRC Simulation Doug Roberts University of Maryland Since SLAC Workshop Spent some time trying to streamline and speed-up the reconstruction technique Needed quicker turnaround on resolution
Package UnivRNG. R topics documented: January 10, Type Package
Type Package Package UnivRNG January 10, 2018 Title Univariate Pseudo-Random Number Generation Version 1.1 Date 2018-01-10 Author Hakan Demirtas, Rawan Allozi Maintainer Rawan Allozi
Segmenting Glioma in Multi-Modal Images using a Generative Model for Brain Lesion Segmentation
Segmenting Glioma in Multi-Modal Images using a Generative Model for Brain Lesion Segmentation Bjoern H. Menze 1,2, Koen Van Leemput 3, Danial Lashkari 4 Marc-André Weber 5, Nicholas Ayache 2, and Polina