Distributed Set Reachability

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Distributed Set Reachability"

Transcription

1 Dstt St Rty S Gj Mt T Mx-P Isttt Its, Usty U Gy SIGMOD 2016, S Fs, USA

2 Dstt St Rty Dstt St Rty (DSR) s zt ty xt t sts stt stt Dstt St Rty 2

3 Dstt St Rty Dstt St Rty (DSR) s zt ty xt t sts stt stt Dstt St Rty 2

4 Dstt St Rty Dstt St Rty (DSR) s zt ty xt t sts stt stt : T G G Rty. s t, t xsts t s t t G [SABW13, YCZ10] Dstt St Rty 2

5 Dstt St Rty Dstt St Rty (DSR) s zt ty xt t sts stt stt R s,,,,,,,,, G G Rty. s t, t xsts t s t t G [SABW13, YCZ10] St Rty. S T, s s s, t, s tt s S, t T s t G [TKC + 14, GA13] Dstt St Rty 2

6 Dstt St Rty Dstt St Rty (DSR) s zt ty xt t sts stt stt G 1 G 2 G 3 R s,,,,,,,,, G G s tt t G 1, G 2, G 3 Dstt Rty. s t, t xsts t s t t G [FWW12] Dstt St Rty. S T, s s s, t, s tt s S, t T s t G [?] Dstt St Rty 2

7 Ats At 1: SPARQL 1.1 ty ts ss w s Dstt St Rty 3

8 Ats At 1: SPARQL 1.1 ty ts ss w s Ex: F E w w N Pz SELECT?s WHERE {?s <I>?ty.?s <w> N Pz.?ty <ti>*?ty.?ty <to> E.} Dstt St Rty 3

9 Ats At 1: SPARQL 1.1 ty ts ss w s Ex: F E w w N Pz SELECT?s WHERE {?s <I>?ty.?s <w> N Pz.?ty <ti>*?ty.?ty <to> E.} Atw Cts = Sü U B ti Cts = F Gy Dstt St Rty 3

10 Ats At 1: SPARQL 1.1 ty ts ss w s Ex: F E w w N Pz SELECT?s WHERE {?s <I>?ty.?s <w> N Pz.?ty <ti>*?ty.?ty <to> E.} Atw Cts = Sü U B ti Cts = F Gy St Rty Qy: Cts Cts Dstt St Rty 3

11 Ats At 2: Cty tss s tws Dstt St Rty 4

12 Ats At 2: Cty tss s tws Ex: Hw s t zts t B Gts Bs = W Bt D J. T T G P Ozts = F Ft M Gts Ft Dstt St Rty 4

13 Ats At 2: Cty tss s tws Ex: Hw s t zts t B Gts Bs = W Bt D J. T T G P Ozts = F Ft M Gts Ft St Rty Qy: Bs Ozts Dstt St Rty 4

14 Hw t s DSR y? Qy: {,, } {, } Ssts G 1 G 2 G 3 Dstt St Rty 5

15 Hw t s DSR y? Vtx-Ct s: L P, G,... Ct( ) T Vtx sss Msss tx Msss ssss Sst ( 1) Sst Sst ( + 1) Qy: {,, } {, } Ssts G 1 G 2 G 3 Dstt St Rty 5

16 Hw t s DSR y? Vtx-Ct s: L P, G,... Ct( ) T Vtx sss Msss tx Msss ssss Sst ( 1) Sst Sst ( + 1) Qy: {,, } {, } Ssts 1 [] [] [] G 1 G 2 G 3 Dstt St Rty 5

17 Hw t s DSR y? Vtx-Ct s: L P, G,... Ct( ) T Vtx sss Msss tx Msss ssss Sst ( 1) Sst Sst ( + 1) Qy: {,, } {, } Ssts 1 2 [] [, ] [] [, ] [] [] [] [] G 1 [] G 2 G 3 Dstt St Rty 5

18 Hw t s DSR y? Vtx-Ct s: L P, G,... Ct( ) T Vtx sss Msss tx Msss ssss Sst ( 1) Sst Sst ( + 1) Qy: {,, } {, } Ssts 1 2. [,, ] [,, ] G 1 G 2 G 3 Dstt St Rty 5

19 Hw t s DSR y? Vtx-Ct s: L P, G,... Ct( ) T Vtx sss Msss tx Msss ssss Sst ( 1) Sst Sst ( + 1) Qy: {,, } {, } Ssts 1 2. [,, ] [,, ] G 1 G 2 G 3 P: O s s ( 10M s) y wt S = 10 T = 10 Dtst T( s) Ssts C. Sz(MB) NtD St Dstt St Rty 5

20 Hw t s DSR y? Vtx-Ct s: L P, G,... Ct( ) T Vtx sss Msss tx Msss ssss Sst ( 1) Sst Sst ( + 1) Qy: {,, } {, } Ssts 1 2. [,, ] [,, ] G 1 G 2 G 3 Cs: s tts & st xs t y tts ( t) ts t sts y ss ts Dstt St Rty 5

21 A t st DSR? Ojts: 1. z t sz sss x 2. t s & s tts s s ss s 3. s t s Dstt St Rty 6

22 A t st DSR? Ojts: 1. z t sz sss x ty s t tw ssts t & t t t ty.., ty y s By 2. t s & s tts s s ss s 3. s t s Dstt St Rty 6

23 A t st DSR? Ojts: 1. z t sz sss x ty s t tw ssts t & t t t ty.., ty y s By 2. t s & s tts s s ss s + y C t, xs tz (st) ty s [YCZ10, SABW13, GA13, TKC + 14] 3. s t s Dstt St Rty 6

24 A t st DSR? Ojts: 1. z t sz sss x ty s t tw ssts t & t t t ty.., ty y s By 2. t s & s tts s s ss s + y C t, xs tz (st) ty s [YCZ10, SABW13, GA13, TKC + 14] 3. s t s y ss sts s s y t SCCs Dstt St Rty 6

25 Ptt G1 G2 G3 Dstt St Rty 7

26 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } Dstt St Rty 7

27 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} Dstt St Rty 7

28 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} Dstt St Rty 7

29 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} St 1: Ct ty I O (st ty) (By G) By G Dstt St Rty 7

30 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} St 1: Ct ty I O (st ty) (By G) G B 1 G B 2 G B 3 Dstt St Rty 7

31 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} St 1: Ct ty I O (st ty) (By G) G B 1 G B 2 G B 3 Dstt St Rty 7

32 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} St 1: Ct ty I O (st ty) (By G) St 2: M y (C G) Dstt St Rty 7

33 Ptt G1 G2 G3 I 1 = {} I 2 = {,, } I 3 = {, } O 1 = {, } O 2 = {, } O 3 = {} St 1: Ct ty I O (st ty) (By G) St 2: M y (C G) St 3: Oty, xs t s tts s y ss Dstt St Rty 7

34 Qy ss Dstt St Rty 8

35 Qy ss Fw Lst: F 1 = {,,,, } Bw Lst: B 1 = {,, } F 2 = {,, } B 2 = {,, } F 3 = {,,, } B 3 = {,,, } Dstt St Rty 8

36 Qy ss Qy: Fw Lst: F 1 = {,,,, } Bw Lst: B 1 = {,, } F 2 = {,, } B 2 = {,, } F 3 = {,,, } B 3 = {,,, } I s t t, t y ss y Dstt St Rty 8

37 Qy ss Qy: Fw Lst: F 1 = {,,,, } Bw Lst: B 1 = {,, } F 2 = {,, } B 2 = {,, } F 3 = {,,, } B 3 = {,,, } Dstt St Rty 8

38 Qy ss Qy: Fw Lst: F 1 = {,,,, } Bw Lst: B 1 = {,, } F 2 = {,, } B 2 = {,, } F 3 = {,,, } B 3 = {,,, } I s t - st t, s tst tw tts Dstt St Rty 8

39 Qy ss Qy: {,, } {, } Fw Lst: F 1 = {,,,, } Bw Lst: B 1 = {,, } St1: F 2 = {,, } B 2 = {,, } {, } F 3 = {,,, } B 3 = {,,, } Dstt St Rty 8

40 Qy ss Qy: {,, } {, } Fw Lst: F 1 = {,,,, } Bw Lst: B 1 = {,, } St1: St2: F 2 = {,, } B 2 = {,, } {, } {,,, } F 3 = {,,, } B 3 = {,,, } {,,,, } Dstt St Rty 8

41 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G Dstt St Rty 9

42 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) Dstt St Rty 9

43 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) -s, s st ts G 3 w t Dstt St Rty 9

44 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) -s, s st ts G 3 w t t-s, s st ts G 1 w t Dstt St Rty 9

45 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) -s, s st ts G 3 w t t-s, s st ts G 1 w t Dstt St Rty 9

46 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) I1 = {} O1 = {, } I2 = {,, } O2 = {, } I3 = {, } O3 = {} Dstt St Rty 9

47 S t L Gs O t s sty s t sz y Sz: O( =1 ( I O ) + E C ) G: 43.6M (8.5 E ) LJ-20M: 861.4M (43.07 E ) By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) I1 = {} I2 = {,, } I3 = {, } O1 = {, } O2 = {, } O3 = {} υ1 = {} υ2 = {, }, υ3 = {} υ4 = {, } Fw sts (-t s) ν1 = {, } ν2 = {}, ν3 = {} ν4 = {} Bw sts (t-t s) Dstt St Rty 9

48 S t L Gs O t s sty s t sz y ν1, υ2 ν3 υ4 υ3 ν2 ν4 Sz: O( =1 ( N Υ ) + E C ) N : st -t s t Υ : st t-t s t N I, Υ O, E C E C By G Css By G F tt G = {G 1, G 2, G 3 }, w t y s ws. G1 G2 G3 Fw sts (-t s) I1 = {} I2 = {,, } I3 = {, } O1 = {, } O2 = {, } O3 = {} υ1 = {} υ2 = {, }, υ3 = {} υ4 = {, } Fw sts (-t s) ν1 = {, } ν2 = {}, ν3 = {} ν4 = {} Bw sts (t-t s) Dstt St Rty 9

49 S t L Gs O t s sty s t sz y ν1, υ2 ν3 υ4 υ3 ν2 ν4 Sz: O( =1 ( N Υ ) + E C ) N : st -t s t Υ : st t-t s t N I, Υ O, E C E C By G Css By G F tt G = {G 1, G 2, G 3 }, w t y s ws. υ2 υ3 ν3 ν2 υ4 ν1 υ4, ν1 υ2 ν2, υ1 υ3 ν3 ν4 υ1 ν4 w t sts, s t y s Dstt St Rty 9

50 Dtsts: Et S L Gs V E Gs V E Az 403,394 3,387,388 LJ-68M 4,847,571 68,993,773 BSt 685,230 7,600,595 Twtt-1.4B 41,652,230 1,468,364,884 G 875,713 5,105,039 Fs-500M 97,290, ,982,284 NtD 325,729 1,497,134 Fs-1B 156,595, ,965,047 St 281,903 2,312,497 LUBM-500M 115,561, ,002,176 LJ-20M 2,545,981 20,000,000 LUBM-1B 222,213, ,394,352 G tsts St: Mst:1, Ss:9, My:64 GB Dstt St Rty 10

51 Dtsts: Et S L Gs V E Gs V E Az 403,394 3,387,388 LJ-68M 4,847,571 68,993,773 BSt 685,230 7,600,595 Twtt-1.4B 41,652,230 1,468,364,884 G 875,713 5,105,039 Fs-500M 97,290, ,982,284 NtD 325,729 1,497,134 Fs-1B 156,595, ,965,047 St 281,903 2,312,497 LUBM-500M 115,561, ,002,176 LJ-20M 2,545,981 20,000,000 LUBM-1B 222,213, ,394,352 G tsts St: Mst:1, Ss:9, My:64 GB P: DSR DSR-F G G++ T (s) x x x x x Az BSt G NtD St LJ-20M LJ-68M Fs DSR s s t st t G, G++, DSR-F Dstt St Rty 10 Twtt LUBM

52 Dtsts: Et S L Gs V E Gs V E Az 403,394 3,387,388 LJ-68M 4,847,571 68,993,773 BSt 685,230 7,600,595 Twtt-1.4B 41,652,230 1,468,364,884 G 875,713 5,105,039 Fs-500M 97,290, ,982,284 NtD 325,729 1,497,134 Fs-1B 156,595, ,965,047 St 281,903 2,312,497 LUBM-500M 115,561, ,002,176 LJ-20M 2,545,981 20,000,000 LUBM-1B 222,213, ,394,352 G tsts St: Mst:1, Ss:9, My:64 GB Sty: DSR G++wE G++ G Qy T ( s) # Ptts # Ptts LJ-68 Fs-1B Dstt St Rty 10

53 Dtsts: Et S L Gs V E Gs V E Az 403,394 3,387,388 LJ-68M 4,847,571 68,993,773 BSt 685,230 7,600,595 Twtt-1.4B 41,652,230 1,468,364,884 G 875,713 5,105,039 Fs-500M 97,290, ,982,284 NtD 325,729 1,497,134 Fs-1B 156,595, ,965,047 St 281,903 2,312,497 LUBM-500M 115,561, ,002,176 LJ-20M 2,545,981 20,000,000 LUBM-1B 222,213, ,394,352 G tsts St: Mst:1, Ss:9, My:64 GB Sty: DSR G++wE G++ G DSR G++wE G++ G Qy T ( s) # Ptts # Ptts Qy T ( s) x10 50x50 100x100 Qy Szs x10 50x50 100x100 Qy Szs LJ-68 Fs-1B LJ-68 Fs-1B Dstt St Rty 10

54 Css W t stt t Dstt St Rty Dstt St Rty 11

55 Css W t stt t Dstt St Rty Ptt t ty t s xs sty t wtt t sty Dstt St Rty 11

56 Css W t stt t Dstt St Rty Ptt t ty t s xs sty t wtt t sty Css t sts s s t s Dstt St Rty 11

57 Css W t stt t Dstt St Rty Ptt t ty t s xs sty t wtt t sty Css t sts s s t s Exts t y s ( y tsts) Dstt St Rty 11

58 Css W t stt t Dstt St Rty Ptt t ty t s xs sty t wtt t sty Css t sts s s t s Exts t y s ( y tsts) T y y ttt Dstt St Rty 11

59 Rs I W F, X W, Y W, P ts stt ty s, PVLDB 5 (2012),. 11, S G K Ayw, PxS: ty s t-s t-stt t s RDF s y s sx tts, WWW, 2013, St St, As A, St J. Bt, G W, FERRARI: x t ty sst x, ICDE, 2013, M T, Mtz K, F Ct, T-A H-V, K P, As K, Ts N, Hy T. V, T t : Et t-s ts, PVLDB 8 (2014),. 4, H Y, Vt Cj, M J. Z, GRAIL: S Rty Ix L Gs, PVLDB 3 (2010),. 1-2, Qsts? F ts, s st y st: 84 Dstt St Rty 12

Differentiation of allergenic fungal spores by image analysis, with application to aerobiological counts

Differentiation of allergenic fungal spores by image analysis, with application to aerobiological counts 15: 211 223, 1999. 1999 Kuw Puss. Pt t ts. 211 tt u ss y yss, wt t t uts.. By 1, S. s 2,EuR.Tvy 2 St 3 1 tt Ss, R 407 Bu (05), Uvsty Syy, SW, 2006, ust; 2 st ty, v 4 Bu u (6), sttut Rsty, Uvsty Syy, SW,

More information

Housing Market Monitor

Housing Market Monitor M O O D Y È S A N A L Y T I C S H o u s i n g M a r k e t M o n i t o r I N C O R P O R A T I N G D A T A A S O F N O V E M B E R İ Ī Ĭ Ĭ E x e c u t i v e S u m m a r y E x e c u t i v e S u m m a r y

More information

Planar convex hulls (I)

Planar convex hulls (I) Covx Hu Covxty Gv st P o ots 2D, tr ovx u s t sst ovx oyo tt ots ots o P A oyo P s ovx or y, P, t st s try P. Pr ovx us (I) Coutto Gotry [s 3250] Lur To Bowo Co ovx o-ovx 1 2 3 Covx Hu Covx Hu Covx Hu

More information

Computer Graphics. Viewing & Projections

Computer Graphics. Viewing & Projections Vw & Ovrvw rr : rss r t -vw trsrt: st st, rr w.r.t. r rqurs r rr (rt syst) rt: 2 trsrt st, rt trsrt t 2D rqurs t r y rt rts ss Rr P usuy st try trsrt t wr rts t rs t surs trsrt t r rts u rt w.r.t. vw vu

More information

SPACE TYPES & REQUIREMENTS

SPACE TYPES & REQUIREMENTS SPACE TYPES & REQUIREENTS 2 Fby 2012 Gys Sh Typ: K E H 1 2 3 5 6 7 8 9 10 11 12 Ajy D (Hh Sh) F A Dsps Th fs f phys hs vv sps f h hhy fsy f vs. Phys s hf w fss wss hh vy hy-bs s f hhy fsy hs. Gy sps sh

More information

/99 $10.00 (c) 1999 IEEE

/99 $10.00 (c) 1999 IEEE P t Hw Itt C Syt S 999 P t Hw Itt C Syt S - 999 A Nw Atv C At At Cu M Syt Y ZHANG Ittut Py P S, Uvty Tuu, I 0-87, J Att I t, w tv t t u yt x wt y tty, t wt tv w (LBSB) t. T w t t x t tty t uy ; tt, t x

More information

CITY OF LAS CRUCES INFRASTRUCTURE/CIP POLICY REVIEW COMMITTEE

CITY OF LAS CRUCES INFRASTRUCTURE/CIP POLICY REVIEW COMMITTEE 1 5 6 7 8 9 11 1 1 1 15 16 17 18 19 0 1 6 7 8 9 0 1 5 6 7 8 9 0 1 ITY OF L U IFTUTU/I OLIY VI OITT T fwg f g f f L - If/I w f b 17, 018 :0.., f L,, bg (f 007-), 700, L, w x. B T: Gg,, G g, / T, 5 J, g,

More information

Available online Journal of Scientific and Engineering Research, 2016, 3(6): Research Article

Available online  Journal of Scientific and Engineering Research, 2016, 3(6): Research Article Av www.. Ju St E R, 2016, 3(6):131-138 R At ISSN: 2394-2630 CODEN(USA): JSERBR Cutvt R Au Su H Lv I y t Mt Btt M Zu H Ut, Su, W Hy Dtt Ay Futy Autu, Uvt Tw, J. Tw N. 9 P, 25136,Wt Sut, I, E-: 65@y. Att

More information

BACKFILLED 6" MIN TRENCH BOTT OF CONT FTG PROVIDE SLEEVE 1" CLR AROUND PIPE - TYP BOTTOM OF TRENCH PIPE SHALL NOT EXTEND BELOW THIS LINE

BACKFILLED 6 MIN TRENCH BOTT OF CONT FTG PROVIDE SLEEVE 1 CLR AROUND PIPE - TYP BOTTOM OF TRENCH PIPE SHALL NOT EXTEND BELOW THIS LINE TT T I I. VTS T T, SPIS. 0 MSY ITS MS /" = '-0" +' - " T /" d ' - 0" I SIGTI d d w/ " M I S IS M I d 0 T d T d w/ å" 0 K W TT I IS ITPT SM SIZ x 0'-0" I T T W PSSI d /" TY I SIGTI Y ' - 0" '-0" '-0" P

More information

BACKFILLED 6" MIN TRENCH BOTT OF CONT FTG PROVIDE SLEEVE 1" CLR AROUND PIPE - TYP BOTTOM OF TRENCH PIPE SHALL NOT EXTEND BELOW THIS LINE

BACKFILLED 6 MIN TRENCH BOTT OF CONT FTG PROVIDE SLEEVE 1 CLR AROUND PIPE - TYP BOTTOM OF TRENCH PIPE SHALL NOT EXTEND BELOW THIS LINE TT T I I. VTS T T, SPIS. 0 MSY ITS MS /" = '-0" +' - " T /" d ' - 0" I SIGTI d d w/ " M I S IS M I d 0 MI T d T d w/ å" 0 K W TT I IS ITPT SM SIZ x 0'-0" MI I T T W PSSI d /" TY I SIGTI Y ' - 0" MI '-0"

More information

o C *$ go ! b», S AT? g (i * ^ fc fa fa U - S 8 += C fl o.2h 2 fl 'fl O ' 0> fl l-h cvo *, &! 5 a o3 a; O g 02 QJ 01 fls g! r«'-fl O fl s- ccco

o C *$ go ! b», S AT? g (i * ^ fc fa fa U - S 8 += C fl o.2h 2 fl 'fl O ' 0> fl l-h cvo *, &! 5 a o3 a; O g 02 QJ 01 fls g! r«'-fl O fl s- ccco > p >>>> ft^. 2 Tble f Generl rdnes. t^-t - +«0 -P k*ph? -- i t t i S i-h l -H i-h -d. *- e Stf H2 t s - ^ d - 'Ct? "fi p= + V t r & ^ C d Si d n. M. s - W ^ m» H ft ^.2. S'Sll-pl e Cl h /~v S s, -P s'l

More information

- Prefixes 'mono', 'uni', 'bi' and 'du' - Why are there no asprins in the jungle? Because the parrots ate them all.

- Prefixes 'mono', 'uni', 'bi' and 'du' - Why are there no asprins in the jungle? Because the parrots ate them all. - Prfs '', '', 'b' a '' - Na: Wrsar 27 Dat: W ar tr asrs t? Bas t arrts at t a. At t btt f t a s a st f wrs. Ts wrs ar t. T wrs av b a rta (ra arss), vrta (ra w) r aa (fr rr t rr). W f a wr, raw a at r

More information

On Hamiltonian Tetrahedralizations Of Convex Polyhedra

On Hamiltonian Tetrahedralizations Of Convex Polyhedra O Ht Ttrrzts O Cvx Pyr Frs C 1 Q-Hu D 2 C A W 3 1 Dprtt Cputr S T Uvrsty H K, H K, C. E: @s.u. 2 R & TV Trsss Ctr, Hu, C. E: q@163.t 3 Dprtt Cputr S, Mr Uvrsty Nwu St. J s, Nwu, C A1B 35. E: w@r.s.u. Astrt

More information

and the ANAVETS Unit Portage Ave, Winnipeg, Manitoba, Canada May 23 to May E L IBSF

and the ANAVETS Unit Portage Ave, Winnipeg, Manitoba, Canada May 23 to May E L IBSF t NVET Uit 283 IR FO RE VET ER N N N I MY NVY & R 3584 Pt, Wii, Mitb, IN O RPORTE E IL L I GU VET IF N ENG R H LI E My 23 t My 28-2015 R LE YOUR ONE TOP HOP FOR QULITY POOL UE & ILLIR EORIE GMEROOM 204-783-2666

More information

Transform Solutions to LTI Systems Part 3

Transform Solutions to LTI Systems Part 3 Transform Solutions to LTI Systems Part 3 Example of second order system solution: Same example with increased damping: k=5 N/m, b=6 Ns/m, F=2 N, m=1 Kg Given x(0) = 0, x (0) = 0, find x(t). The revised

More information

Simulation of Natural Convection in a Complicated Enclosure with Two Wavy Vertical Walls

Simulation of Natural Convection in a Complicated Enclosure with Two Wavy Vertical Walls A Mtt S, V. 6, 2012,. 57, 2833-2842 Sut Ntu Cvt Ct Eu wt Tw Wvy Vt W P S Dtt Mtt, Futy S K K Uvty, K K 40002, T Ct E Mtt CHE, S Ayutty R., B 10400, T y 129@t. Sut Wtyu 1 Dtt Mtt, Futy S K K Uvty, K K 40002,

More information

Time Response Analysis (Part II)

Time Response Analysis (Part II) Time Response Analysis (Part II). A critically damped, continuous-time, second order system, when sampled, will have (in Z domain) (a) A simple pole (b) Double pole on real axis (c) Double pole on imaginary

More information

T H E S C I E N C E B E H I N D T H E A R T

T H E S C I E N C E B E H I N D T H E A R T A t t R u r s - L x C t I. xtr turs t Lx Ct Rurs. Rr qurtr s s r t surt strutur. Ts Att Rurs rv ut us, s srt t tr t rtt rt yur t w yu ru. T uqu Lx st ut rv ss ts ss t t y rt t tys t r ts w wr rtts. Atrx

More information

Infinite-dimensional methods for path-dependent equations

Infinite-dimensional methods for path-dependent equations Infinite-dimensional methods for path-dependent equations (Università di Pisa) 7th General AMaMeF and Swissquote Conference EPFL, Lausanne, 8 September 215 Based on Flandoli F., Zanco G. - An infinite-dimensional

More information

MASSALINA CONDO MARINA

MASSALINA CONDO MARINA p p p p p G.. HWY. p p.. HWY... HWY. : HG, 00 T. TY, 0 Y 0 T o. B WG T T 0 okia 0 icrosoft orporatio - VY - T - T - GG - HBT - TT - T - TT T - TWT T 0 - T TT T - T TT T T T - TTY T - - T VT - K T ( H ),±

More information

Optimal investment strategies for an index-linked insurance payment process with stochastic intensity

Optimal investment strategies for an index-linked insurance payment process with stochastic intensity for an index-linked insurance payment process with stochastic intensity Warsaw School of Economics Division of Probabilistic Methods Probability space ( Ω, F, P ) Filtration F = (F(t)) 0 t T satisfies

More information

Analysis Comprehensive Exam Questions Fall 2008

Analysis Comprehensive Exam Questions Fall 2008 Analysis Comprehensive xam Questions Fall 28. (a) Let R be measurable with finite Lebesgue measure. Suppose that {f n } n N is a bounded sequence in L 2 () and there exists a function f such that f n (x)

More information

i;\-'i frz q > R>? >tr E*+ [S I z> N g> F 'x sa :r> >,9 T F >= = = I Y E H H>tr iir- g-i I * s I!,i --' - = a trx - H tnz rqx o >.F g< s Ire tr () -s

i;\-'i frz q > R>? >tr E*+ [S I z> N g> F 'x sa :r> >,9 T F >= = = I Y E H H>tr iir- g-i I * s I!,i --' - = a trx - H tnz rqx o >.F g< s Ire tr () -s 5 C /? >9 T > ; '. ; J ' ' J. \ ;\' \.> ). L; c\ u ( (J ) \ 1 ) : C ) (... >\ > 9 e!) T C). '1!\ /_ \ '\ ' > 9 C > 9.' \( T Z > 9 > 5 P + 9 9 ) :> : + (. \ z : ) z cf C : u 9 ( :!z! Z c (! $ f 1 :.1 f.

More information

T T - PTV - PTV :\er\en utler.p\ektop\ VT \9- T\_ T.rvt T PT P ode aterial. Pattern / olor imenion omment PT T T ode aterial. Pattern / olor imenion omment W T ode aterial. Pattern / olor imenion omment

More information

CONTROLLABILITY OF NONLINEAR SYSTEMS WITH DELAYS IN BOTH STATE AND CONTROL VARIABLES

CONTROLLABILITY OF NONLINEAR SYSTEMS WITH DELAYS IN BOTH STATE AND CONTROL VARIABLES KYBERNETIKA VOLUME 22 (1986), NUMBER 4 CONTROLLABILITY OF NONLINEAR SYSTEMS WITH DELAYS IN BOTH STATE AND CONTROL VARIABLES K. BALACHANDRAN Relative controllability of nonlinear systems with distributed

More information

ADORO TE DEVOTE (Godhead Here in Hiding) te, stus bat mas, la te. in so non mor Je nunc. la in. tis. ne, su a. tum. tas: tur: tas: or: ni, ne, o:

ADORO TE DEVOTE (Godhead Here in Hiding) te, stus bat mas, la te. in so non mor Je nunc. la in. tis. ne, su a. tum. tas: tur: tas: or: ni, ne, o: R TE EVTE (dhd H Hdg) L / Mld Kbrd gú s v l m sl c m qu gs v nns V n P P rs l mul m d lud 7 súb Fí cón ví f f dó, cru gs,, j l f c r s m l qum t pr qud ct, us: ns,,,, cs, cut r l sns m / m fí hó sn sí

More information

0# E % D 0 D - C AB

0# E % D 0 D - C AB 5-70,- 393 %& 44 03& / / %0& / / 405 4 90//7-90/8/3 ) /7 0% 0 - @AB 5? 07 5 >0< 98 % =< < ; 98 07 &? % B % - G %0A 0@ % F0 % 08 403 08 M3 @ K0 J? F0 4< - G @ I 0 QR 4 @ 8 >5 5 % 08 OF0 80P 0O 0N 0@ 80SP

More information

Predicate Logic. 1 Predicate Logic Symbolization

Predicate Logic. 1 Predicate Logic Symbolization 1 Predicate Logic Symbolization innovation of predicate logic: analysis of simple statements into two parts: the subject and the predicate. E.g. 1: John is a giant. subject = John predicate =... is a giant

More information

Semi-Compatibility, Weak Compatibility and. Fixed Point Theorem in Fuzzy Metric Space

Semi-Compatibility, Weak Compatibility and. Fixed Point Theorem in Fuzzy Metric Space International Mathematical Forum, 5, 2010, no. 61, 3041-3051 Semi-Compatibility, Weak Compatibility and Fixed Point Theorem in Fuzzy Metric Space Bijendra Singh*, Arihant Jain** and Aijaz Ahmed Masoodi*

More information

Problem 1. CS205 Homework #2 Solutions. Solution

Problem 1. CS205 Homework #2 Solutions. Solution CS205 Homework #2 s Problem 1 [Heath 3.29, page 152] Let v be a nonzero n-vector. The hyperplane normal to v is the (n-1)-dimensional subspace of all vectors z such that v T z = 0. A reflector is a linear

More information

Risk-Averse Control of Partially Observable Markov Systems. Andrzej Ruszczyński. Workshop on Dynamic Multivariate Programming Vienna, March 2018

Risk-Averse Control of Partially Observable Markov Systems. Andrzej Ruszczyński. Workshop on Dynamic Multivariate Programming Vienna, March 2018 Risk-Averse Control of Partially Observable Markov Systems Workshop on Dynamic Multivariate Programming Vienna, March 2018 Partially Observable Discrete-Time Models Markov Process: fx t ; Y t g td1;:::;t

More information

Blues. G.S.P.T. Blue. U7233 Blue with a green face and slightly red flop. H.S. Indo Blue

Blues. G.S.P.T. Blue. U7233 Blue with a green face and slightly red flop. H.S. Indo Blue Bs C Bs C p.s.p.t. B U7233 B wh fc shy fp. H.S. I B U7235 O s sh b h fc fp. vs cs bh s mc cs. Apps vy y wh s mm k s bs. Occ B U7046 B wh fc fp. Az B U7048 B wh vy fc fp. L.S. B U7276 Us cs mx cccy whs,

More information

Daily Skill Practice

Daily Skill Practice G CD-0 Dily Skill Pti 00 Wkk ## W i t it Eh. gh y w m y il A ll? + = 8 Dy 8= 0. =. Nm. C h l lit tl k ty i g. I h hi ty w ig h, m y hw hi g w ig h?. W Wkk ##00 A A = t, >, = W it < t t m t m k t. Dy Dy

More information

EULER MARUYAMA APPROXIMATION FOR SDES WITH JUMPS AND NON-LIPSCHITZ COEFFICIENTS

EULER MARUYAMA APPROXIMATION FOR SDES WITH JUMPS AND NON-LIPSCHITZ COEFFICIENTS Qiao, H. Osaka J. Math. 51 (14), 47 66 EULER MARUYAMA APPROXIMATION FOR SDES WITH JUMPS AND NON-LIPSCHITZ COEFFICIENTS HUIJIE QIAO (Received May 6, 11, revised May 1, 1) Abstract In this paper we show

More information

MATH 4B Differential Equations, Fall 2016 Final Exam Study Guide

MATH 4B Differential Equations, Fall 2016 Final Exam Study Guide MATH 4B Differential Equations, Fall 2016 Final Exam Study Guide GENERAL INFORMATION AND FINAL EXAM RULES The exam will have a duration of 3 hours. No extra time will be given. Failing to submit your solutions

More information

The multidimensional Ito Integral and the multidimensional Ito Formula. Eric Mu ller June 1, 2015 Seminar on Stochastic Geometry and its applications

The multidimensional Ito Integral and the multidimensional Ito Formula. Eric Mu ller June 1, 2015 Seminar on Stochastic Geometry and its applications The multidimensional Ito Integral and the multidimensional Ito Formula Eric Mu ller June 1, 215 Seminar on Stochastic Geometry and its applications page 2 Seminar on Stochastic Geometry and its applications

More information

Future Self-Guides. E,.?, :0-..-.,0 Q., 5...q ',D5', 4,] 1-}., d-'.4.., _. ZoltAn Dbrnyei Introduction. u u rt 5,4) ,-,4, a. a aci,, u 4.

Future Self-Guides. E,.?, :0-..-.,0 Q., 5...q ',D5', 4,] 1-}., d-'.4.., _. ZoltAn Dbrnyei Introduction. u u rt 5,4) ,-,4, a. a aci,, u 4. te SelfGi ZltAn Dbnyei Intdtin ; ) Q) 4 t? ) t _ 4 73 y S _ E _ p p 4 t t 4) 1_ ::_ J 1 `i () L VI O I4 " " 1 D 4 L e Q) 1 k) QJ 7 j ZS _Le t 1 ej!2 i1 L 77 7 G (4) 4 6 t (1 ;7 bb F) t f; n (i M Q) 7S

More information

A TYP A-602 A-304 A-602 A-302 GRADE BEAM SEE 95% COMPACTED STRUCTURAL FILL A '-0"

A TYP A-602 A-304 A-602 A-302 GRADE BEAM SEE 95% COMPACTED STRUCTURAL FILL A '-0 W W/TITI -0 X U I I X TITI TY S W TYS TIS X W S SU XISTI -0-0 -0-0 -0-0 ' - " ' - " ' - " ' - " ' - " ' - /" ' - /" ' - " -STUTU I -0 ' - ' - " " ' - " " 0' - " ' - U I S STUT W'S TY UTI W S STUT W'S TY

More information

MA 201, Mathematics III, July-November 2018, Laplace Transform (Contd.)

MA 201, Mathematics III, July-November 2018, Laplace Transform (Contd.) MA 201, Mathematics III, July-November 2018, Laplace Transform (Contd.) Lecture 19 Lecture 19 MA 201, PDE (2018) 1 / 24 Application of Laplace transform in solving ODEs ODEs with constant coefficients

More information

SHORT WAY SYMMETRY/SYMMETRICAL SYNTHETIC TREAD TELEVISION VERTICAL VITREOUS VOLUME. 1 BID SET No. Revisions / Submissions Date CAR

SHORT WAY SYMMETRY/SYMMETRICAL SYNTHETIC TREAD TELEVISION VERTICAL VITREOUS VOLUME. 1 BID SET No. Revisions / Submissions Date CAR //0 :: T U 0 : /" = '-0" 0 0 0 View ame T W T U T UT 0 0 T T U 0 U T T TT TY V TT TY T. 00' - 0" T U T T U T T U U ( ) '-" T V V U T W T T U V T U U ( ) T T 0 T U XT W T WW Y TT T U U ( ) U WW00 T U W

More information

Exhibit 2-9/30/15 Invoice Filing Page 1841 of Page 3660 Docket No

Exhibit 2-9/30/15 Invoice Filing Page 1841 of Page 3660 Docket No xhibit 2-9/3/15 Invie Filing Pge 1841 f Pge 366 Dket. 44498 F u v 7? u ' 1 L ffi s xs L. s 91 S'.e q ; t w W yn S. s t = p '1 F? 5! 4 ` p V -', {} f6 3 j v > ; gl. li -. " F LL tfi = g us J 3 y 4 @" V)

More information

RELATIVE CONTROLLABILITY OF NONLINEAR SYSTEMS WITH TIME VARYING DELAYS IN CONTROL

RELATIVE CONTROLLABILITY OF NONLINEAR SYSTEMS WITH TIME VARYING DELAYS IN CONTROL KYBERNETIKA- VOLUME 21 (1985), NUMBER 1 RELATIVE CONTROLLABILITY OF NONLINEAR SYSTEMS WITH TIME VARYING DELAYS IN CONTROL K. BALACHANDRAN, D. SOMASUNDARAM Using the measure of noncompactness of a set and

More information

Dynamic Consistency for Stochastic Optimal Control Problems

Dynamic Consistency for Stochastic Optimal Control Problems Dynamic Consistency for Stochastic Optimal Control Problems Cadarache Summer School CEA/EDF/INRIA 2012 Pierre Carpentier Jean-Philippe Chancelier Michel De Lara SOWG June 2012 Lecture outline Introduction

More information

Convergence of Common Fixed Point Theorems in Fuzzy Metric Spaces

Convergence of Common Fixed Point Theorems in Fuzzy Metric Spaces Journal of mathematics and computer science 8 (2014), 93-97 Convergence of Common Fixed Point Theorems in Fuzzy Metric Spaces Virendra Singh Chouhan Department of Mathematics Lovely Professional University,

More information

Antibacterial effect assessment of ZnS: Ag nanoparticles

Antibacterial effect assessment of ZnS: Ag nanoparticles Nd. J., 3(3):191-195, S 2016 DOI: 10.7508/j.2016.03.007 Nd. J., 3(3):191-195, S 2016 ORIGINAL RSARCH PAPR Ab ff ssss f ZS: A ps Nj Pv; Gz A * ; Vj Kbszd Fvj B, Is Azd Uvsy, Isf, I ABSTRACT Objv(s): A f

More information

WHEREAS, the City Council has heretofore adopted a fee schedule for services rendered by the Anaheim Fire and Rescue Department; and

WHEREAS, the City Council has heretofore adopted a fee schedule for services rendered by the Anaheim Fire and Rescue Department; and RSTI. 18 - A RSTI F TH ITY I F TH ITY F AAHIM STABISHIG IF SAFTY DIISI FS T B HARGD BY TH FIR AD RS DPARTMT F TH ITY F AAHIM AD RSIDIG RSTI. 1-1. HRAS, the ity il hs heretfre dpted fee shedle fr series

More information

{nuy,l^, W%- TEXAS DEPARTMENT OT STATE HEALTH SERVICES

{nuy,l^, W%- TEXAS DEPARTMENT OT STATE HEALTH SERVICES TXAS DARTMT T STAT AT SRVS J RSTDT, M.D. MMSSR.. Bx 149347 Astn, T exs 7 87 4 93 47 18889371 1 TTY: l800732989 www.shs.stte.tx.s R: l nmtn n mps Webstes De Spentenent n Shl Amnsttn, eby 8,201 k 2007, the

More information

Inverted Input A to make routing easier fix in FPGA U2 ADS62P4X LVDS ADC

Inverted Input A to make routing easier fix in FPGA U2 ADS62P4X LVDS ADC 0 0 opyright 0 ttus Research. nverted nput to make routing easier fix in U SX VS V _0 0 p V_TX: R0 R R R S_ S_ S_ S_ V_TX: U TR T/ RST S 0 S S S R R S R0 S 0 % V_ 0 _ V V_ 0 _ in 00 R in _0 0 0 _0 0 0

More information

Lecture 15: H Control Synthesis

Lecture 15: H Control Synthesis c A. Shiriaev/L. Freidovich. March 12, 2010. Optimal Control for Linear Systems: Lecture 15 p. 1/14 Lecture 15: H Control Synthesis Example c A. Shiriaev/L. Freidovich. March 12, 2010. Optimal Control

More information

CBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane.

CBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane. CBSE CBSE SET- SECTION. Gv tht d W d to fd 7 7 Hc, 7 7 7. Lt,. W ow tht.. Thus,. Cosd th vcto quto of th pl.. z. - + z = - + z = Thus th Cts quto of th pl s - + z = Lt d th dstc tw th pot,, - to th pl.

More information

Bernardo D Auria Stochastic Processes /10. Notes. Abril 13 th, 2010

Bernardo D Auria Stochastic Processes /10. Notes. Abril 13 th, 2010 1 Stochastic Calculus Notes Abril 13 th, 1 As we have seen in previous lessons, the stochastic integral with respect to the Brownian motion shows a behavior different from the classical Riemann-Stieltjes

More information

c A c c vlr) (o (9 cci rj c4 c c t(f, e, rf) c.i c..i sc! ct J i J iut d(o (o cf) (f) cf) lr, o) e, t- I c c) (o (f) J) r) OJ -i sf N o) o) :!

c A c c vlr) (o (9 cci rj c4 c c t(f, e, rf) c.i c..i sc! ct J i J iut d(o (o cf) (f) cf) lr, o) e, t- I c c) (o (f) J) r) OJ -i sf N o) o) :! ) C v t(t) (L.( (U >,5 =!_ )(U ) = C (l) ( ':.9, 't ).9 F4 9 = t ;U) ' F = CL (= LL (u0 0 t F 5 t = ; p*5; HH... H ; t*f**'5!, FCF5FHHH FF#F _ z ( () t ) )! (9 00, l. ) C) ; t.. ( (9 t(,, t 4 l vl,.

More information

Exercise 2.2. Find (with proof) all rational points on the curve y = 2 x.

Exercise 2.2. Find (with proof) all rational points on the curve y = 2 x. Exercise 2.2. Find (with proof) all rational points on the curve y = 2 x. Exercise 2.4: Prove that for any integer n 0, e n is not a rational number. Exercise 2.5: Prove that the only rational point on

More information

ORDINANCE NO. 13,888

ORDINANCE NO. 13,888 ORDINANCE NO. 13,888 AN ORDINANCE d Mc Cd Cy Ds Ms, Iw, 2000, dd by Odc N. 13,827, ssd J 5, 2000, by g Sc 134-276 d cg w Sc 134-276, d by ddg d cg w Dvs 21A, cssg Scs 134-991 g 134-997, c w "C-3R" C Bsss

More information

Lecture 4 Continuous time linear quadratic regulator

Lecture 4 Continuous time linear quadratic regulator EE363 Winter 2008-09 Lecture 4 Continuous time linear quadratic regulator continuous-time LQR problem dynamic programming solution Hamiltonian system and two point boundary value problem infinite horizon

More information

Non-orthogonal Hilbert Projections in Trend Regression

Non-orthogonal Hilbert Projections in Trend Regression Non-orthogonal Hilbert Projections in Trend Regression Peter C. B. Phillips Cowles Foundation for Research in Economics Yale University, University of Auckland & University of York and Yixiao Sun Department

More information

- Prefix 'audi', 'photo' and 'phobia' - What's striped and bouncy? A zebra on a trampoline!

- Prefix 'audi', 'photo' and 'phobia' - What's striped and bouncy? A zebra on a trampoline! - Pf '', '' '' - Nm: Ws 11 D: W's s y? A m! A m f s s f ws. Ts ws. T ws y ( ss), y ( w) y (fm ). W y f, w. s m y m y m w q y q s q m w s k s w q w s y m s m m m y s s y y www.s..k s.s 2013 s www.sss.m

More information

129.00' Pond EXIST. TREES 100' WETLAND REVIEW LINE PROPOSED RESIDENCE EXIST. TREE TO REMAIN PROPOSED 4' HT. GATE 76'

129.00' Pond EXIST. TREES 100' WETLAND REVIEW LINE PROPOSED RESIDENCE EXIST. TREE TO REMAIN PROPOSED 4' HT. GATE 76' . W XST S S S SP T WY M P T S.. WTT MSS S PV- T S WS USS TWS T. V u.p.. S WS MSS T P V SM S WS. u.p.. MSS T UTS U WS, S PPS WS, S WS P ST SS XPS U USS TWS T.. MSS +/-, V..., 'VY' 'M' S MSU V WT TU TS.

More information

Emigration The movement of individuals out of an area The population decreases

Emigration The movement of individuals out of an area The population decreases Nm Clss D C 5 Puls S 5 1 Hw Puls Gw (s 119 123) Ts s fs ss us sb ul. I ls sbs fs ff ul sz xls w xl w ls w. Css f Puls ( 119) 1. W fu m ss f ul?. G sbu. Gw b. Ds. A suu 2. W s ul s sbu? I s b b ul. 3. A

More information

UCSD ECE250 Handout #27 Prof. Young-Han Kim Friday, June 8, Practice Final Examination (Winter 2017)

UCSD ECE250 Handout #27 Prof. Young-Han Kim Friday, June 8, Practice Final Examination (Winter 2017) UCSD ECE250 Handout #27 Prof. Young-Han Kim Friday, June 8, 208 Practice Final Examination (Winter 207) There are 6 problems, each problem with multiple parts. Your answer should be as clear and readable

More information

Problem Score Possible Points Total 150

Problem Score Possible Points Total 150 Math 250 Fall 2010 Final Exam NAME: ID No: SECTION: This exam contains 17 problems on 13 pages (including this title page) for a total of 150 points. There are 10 multiple-choice problems and 7 partial

More information

Digital Control & Digital Filters. Lectures 13 & 14

Digital Control & Digital Filters. Lectures 13 & 14 Digital Controls & Digital Filters Lectures 13 & 14, Professor Department of Electrical and Computer Engineering Colorado State University Spring 2017 Systems with Actual Time Delays-Application 2 Case

More information

Study on Structure Property of Cantilever Piezoelectric Vibration Generator

Study on Structure Property of Cantilever Piezoelectric Vibration Generator Sss & Tsds,. 177, Iss 8, As 14,. 46-5 Sss & Tsds 14 by IFSA Pbsh, S. L. h://www.sss.m Sdy S Py f C Pz b G 1,* Y Zh, Q, 1 L Jf 1 Mh & E C, A Usy f b, b Bd 711, Ch Sh f Ey Pw d Mh E, Nh Ch E Pw Usy, Bj 16,

More information

A Common Fixed Point Theorem for Compatible Mappings of Type (K) in Intuitionistic Fuzzy Metric space

A Common Fixed Point Theorem for Compatible Mappings of Type (K) in Intuitionistic Fuzzy Metric space Journal of Mathematics System Science 5 (205) 474-479 oi: 0.7265/259-529/205..004 D DAVID PUBLISHING A Common Fixe Point Theorem for Compatible Mappings of Type (K) in K.B. Manhar K. Jha Department of

More information

JUST THE MATHS UNIT NUMBER LAPLACE TRANSFORMS 3 (Differential equations) A.J.Hobson

JUST THE MATHS UNIT NUMBER LAPLACE TRANSFORMS 3 (Differential equations) A.J.Hobson JUST THE MATHS UNIT NUMBER 16.3 LAPLACE TRANSFORMS 3 (Differential equations) by A.J.Hobson 16.3.1 Examples of solving differential equations 16.3.2 The general solution of a differential equation 16.3.3

More information

ISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 5, Issue 1, July 2015

ISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 5, Issue 1, July 2015 Semi Compatibility and Weak Compatibility in Fuzzy Metric Space and Fixed Point Theorems Chandrajeet Singh Yadav Vadodara Institute of Engineering, Vadodara (Gujarat) For all x, y, zx and s, t 0, Abstract:

More information

20.6. Transfer Functions. Introduction. Prerequisites. Learning Outcomes

20.6. Transfer Functions. Introduction. Prerequisites. Learning Outcomes Transfer Functions 2.6 Introduction In this Section we introduce the concept of a transfer function and then use this to obtain a Laplace transform model of a linear engineering system. (A linear engineering

More information

Control system of unmanned aerial vehicle used for endurance autonomous monitoring

Control system of unmanned aerial vehicle used for endurance autonomous monitoring WSES NSIONS o SYSES ONOL oo-o h, s Nco osttsc, h oto sst o vhc s o c tooos oto EODO - IOEL EL, D vst othc o chst o Sc c, St. Ghoh o, o., 6,Scto, chst, ONI too.ch@.o htt:wwww.-cs.o SILE NIOLE ONSNINES,

More information

The Method of Laplace Transforms.

The Method of Laplace Transforms. The Method of Laplace Transforms. James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University May 25, 217 Outline 1 The Laplace Transform 2 Inverting

More information

Math 307 Lecture 19. Laplace Transforms of Discontinuous Functions. W.R. Casper. Department of Mathematics University of Washington.

Math 307 Lecture 19. Laplace Transforms of Discontinuous Functions. W.R. Casper. Department of Mathematics University of Washington. Math 307 Lecture 19 Laplace Transforms of Discontinuous Functions W.R. Casper Department of Mathematics University of Washington November 26, 2014 Today! Last time: Step Functions This time: Laplace Transforms

More information

principles of f ta f a rt.

principles of f ta f a rt. DD H L L H PDG D BB PBLH L 20 D PP 32 C B P L s BDWY s BGG M W C WDM DLL P M DC GL CP F BW Y BBY PMB 5 855 C WHL X 6 s L Y F H 5 L & 5 zzzl s s zz z s s» z sk??» szz zz s L ~Lk Bz ZzY Z? ~ s s sgss s z«f

More information

Stochastic Differential Equations.

Stochastic Differential Equations. Chapter 3 Stochastic Differential Equations. 3.1 Existence and Uniqueness. One of the ways of constructing a Diffusion process is to solve the stochastic differential equation dx(t) = σ(t, x(t)) dβ(t)

More information

FIXED POINT THEOREM USING COMPATIBILITY OF TYPE (A) AND WEAK COMPATIBILITY IN MENGER SPACE

FIXED POINT THEOREM USING COMPATIBILITY OF TYPE (A) AND WEAK COMPATIBILITY IN MENGER SPACE www.arpapress.com/volumes/vol10issue3/ijrras_10_3_11.pdf FIXED POINT THEOREM USING COMPATIBILITY OF TYPE (A) AND WEAK COMPATIBILITY IN MENGER SPACE Bijendra Singh 1, Arihant Jain 2 and Javaid Ahmad Shah

More information

Connecting Deer Creek and River des Peres Greenway

Connecting Deer Creek and River des Peres Greenway C D C Rv s s Gy ps D C Gy NORTH W Av Av Js Av E Av Su Av E Av Chy Av G Bv y Av. ps y h s G Bv, h h--y Cuy Av. ps C Rv s s Gy D C B B Bv Ox Av. Sussx Av. C Av. Ox Av. Ch Av. Ch Av. By E Av Mh Av. D C O-

More information

r R N S Hobbs P J Phelan B E A Edmeaes K D Boyce 2016 Membership ams A P Cowan D D J Robinson B J Hyam J S Foster A NAME MEMBERSHIP NUMBER

r R N S Hobbs P J Phelan B E A Edmeaes K D Boyce 2016 Membership ams A P Cowan D D J Robinson B J Hyam J S Foster A NAME MEMBERSHIP NUMBER ug bb K S bb h B E E ch Smth K t Sth E ugh m Cw b C w h T B ug bb K C t tch S bb h B E ch Smth K t Sth E ugh m Cw b S B C w Shh T ug bb K C tch S bb h ch Smth K t u Sth E m Cw b h S B C w O Shh T ug bb

More information

VANDERBILT UNIVERSITY. MATH 2610 ORDINARY DIFFERENTIAL EQUATIONS Practice for test 1 solutions

VANDERBILT UNIVERSITY. MATH 2610 ORDINARY DIFFERENTIAL EQUATIONS Practice for test 1 solutions VANDERBILT UNIVERSITY MATH 2610 ORDINARY DIFFERENTIAL EQUATIONS Practice for test 1 solutions The first test will cover all material discussed up to (including) section 4.5. Important: The solutions below

More information

Frequency Response of Linear Time Invariant Systems

Frequency Response of Linear Time Invariant Systems ME 328, Spring 203, Prof. Rajamani, University of Minnesota Frequency Response of Linear Time Invariant Systems Complex Numbers: Recall that every complex number has a magnitude and a phase. Example: z

More information

Half of Final Exam Name: Practice Problems October 28, 2014

Half of Final Exam Name: Practice Problems October 28, 2014 Math 54. Treibergs Half of Final Exam Name: Practice Problems October 28, 24 Half of the final will be over material since the last midterm exam, such as the practice problems given here. The other half

More information

3 Compact Operators, Generalized Inverse, Best- Approximate Solution

3 Compact Operators, Generalized Inverse, Best- Approximate Solution 3 Compact Operators, Generalized Inverse, Best- Approximate Solution As we have already heard in the lecture a mathematical problem is well - posed in the sense of Hadamard if the following properties

More information

Gary Callicoat Available All Day! Blue Plate Specials Monday: Gary s 3-Way Tuesday: Taco Salad Beef Stroganoff Wednesday: Spaghetti n Meatballs

Gary Callicoat Available All Day! Blue Plate Specials Monday: Gary s 3-Way Tuesday: Taco Salad Beef Stroganoff Wednesday: Spaghetti n Meatballs Wc f fs fy c c js. W f k xcs f vs f s sff s G Hsy Bck fs y f cf s s s y k. Ec vy y v y Rsy Bck I s y s ks s! Gy Cc Dy! A Av s c P B s c Txs s fs c 3-Wy s s y c s G s My: c c.89 s 10 c c v s s s f f s ss

More information

z E z *" I»! HI UJ LU Q t i G < Q UJ > UJ >- C/J o> o C/) X X UJ 5 UJ 0) te : < C/) < 2 H CD O O) </> UJ Ü QC < 4* P? K ll I I <% "fei 'Q f

z E z * I»! HI UJ LU Q t i G < Q UJ > UJ >- C/J o> o C/) X X UJ 5 UJ 0) te : < C/) < 2 H CD O O) </> UJ Ü QC < 4* P? K ll I I <% fei 'Q f I % 4*? ll I - ü z /) I J (5 /) 2 - / J z Q. J X X J 5 G Q J s J J /J z *" J - LL L Q t-i ' '," ; i-'i S": t : i ) Q "fi 'Q f I»! t i TIS NT IS BST QALITY AVAILABL. T Y FRNIS T TI NTAIN A SIGNIFIANT NBR

More information

Key: Town of Eastham - Fiscal Year :52 am

Key: Town of Eastham - Fiscal Year :52 am //7 SQ #:, RR WR PR SS SS SRP R Key: own of astham - Fiscal Year 8 : am S WY c/o SM RWR S WY SM, M 6 8-8- S WY M-S M of 7 RSFR SRY S WY SR W V & JY /SF/ bhd F F J S SF F P V R M J V S 97,, -.8,7,6 S 6/8/

More information

BIG TEX GRADE 5 SOCIAL STUDIES CELEBRATING SYMBOLS: BIG TEX & LADY LIBERTY UNITE

BIG TEX GRADE 5 SOCIAL STUDIES CELEBRATING SYMBOLS: BIG TEX & LADY LIBERTY UNITE GRA 5 SOCIA STUIS CBRATIG SYMBOS: & AY IBRTY UIT TACHR Cb Syb B Tx & y by U Fv G SOCIAIS STU I h w: x h fcc f yb k h Ac Tx bf c. c c h! A w Wh h c, y, Tx b c y w A h, x w y c f h, y cz. C c yb k h cb y.

More information

Control Systems. Laplace domain analysis

Control Systems. Laplace domain analysis Control Systems Laplace domain analysis L. Lanari outline introduce the Laplace unilateral transform define its properties show its advantages in turning ODEs to algebraic equations define an Input/Output

More information

Common Fixed Point Theorems for Generalisation of R-Weak Commutativity

Common Fixed Point Theorems for Generalisation of R-Weak Commutativity IOSR Journal of Mathematics (IOSR-JM) e-issn: 2278-5728,p-ISSN: 2319-765X, Volume 8, Issue 4 (Sep. - Oct. 2013), PP 09-13 Common Fixed Point Theorems for Generalisation of R-Weak Commutativity T. R. Vijayan,

More information

DERIVED CONES TO REACHABLE SETS OF A CLASS OF SECOND-ORDER DIFFERENTIAL INCLUSIONS

DERIVED CONES TO REACHABLE SETS OF A CLASS OF SECOND-ORDER DIFFERENTIAL INCLUSIONS DERIVED CONES TO REACHABLE SETS OF A CLASS OF SECOND-ORDER DIFFERENTIAL INCLUSIONS AURELIAN CERNEA We consider a second-order differential inclusion and we prove that the reachable set of a certain second-order

More information

Math Exam 3 Solutions

Math Exam 3 Solutions Math 6 - Exam 3 Solutions Thursday, July 3rd, 0 Recast the following higher-order differential equations into first order systems If the equation is linear, be sure to give the coefficient matrix At and

More information

CENTER POINT MEDICAL CENTER

CENTER POINT MEDICAL CENTER T TRI WTR / IR RISR S STR SRST I TT, SUIT SRST, RI () X () VUU T I Y R VU, SUIT 00 T, RI 0 () 00 X () RISTRTI UR 000 "/0 STY RR I URT VU RT STY RR, RI () 0 X () 00 "/0 STIR # '" TRV IST TRI UIIS UII S,

More information

SUBEXPONENTIAL SOLUTIONS OF LINEAR ITO-VOLTERRA EQUATIONS WITH A DAMPED PERTURBATION

SUBEXPONENTIAL SOLUTIONS OF LINEAR ITO-VOLTERRA EQUATIONS WITH A DAMPED PERTURBATION FUNCTIONAL DIFFERENTIAL EQUATIONS VOLUME 11 24, NO 1-2 PP. 5 10 SUBEXPONENTIAL SOLUTIONS OF LINEAR ITO-VOLTERRA EQUATIONS WITH A DAMPED PERTURBATION J. A. D. APPLEBY' Abstract. This paper studies the almost

More information

EE C128 / ME C134 Fall 2014 HW 8 - Solutions. HW 8 - Solutions

EE C128 / ME C134 Fall 2014 HW 8 - Solutions. HW 8 - Solutions EE C28 / ME C34 Fall 24 HW 8 - Solutions HW 8 - Solutions. Transient Response Design via Gain Adjustment For a transfer function G(s) = in negative feedback, find the gain to yield a 5% s(s+2)(s+85) overshoot

More information

Stability. X(s) Y(s) = (s + 2) 2 (s 2) System has 2 poles: points where Y(s) -> at s = +2 and s = -2. Y(s) 8X(s) G 1 G 2

Stability. X(s) Y(s) = (s + 2) 2 (s 2) System has 2 poles: points where Y(s) -> at s = +2 and s = -2. Y(s) 8X(s) G 1 G 2 Stability 8X(s) X(s) Y(s) = (s 2) 2 (s 2) System has 2 poles: points where Y(s) -> at s = 2 and s = -2 If all poles are in region where s < 0, system is stable in Fourier language s = jω G 0 - x3 x7 Y(s)

More information

(2) y' = A(t)y+ f C(t,s)y(s)ds,

(2) y' = A(t)y+ f C(t,s)y(s)ds, PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 100, Number 1, May 1987 BOUNDEDNESS PROPERTIES IN VOLTERRA INTEGRODIFFERENTIAL SYSTEMS W. E. MAHFOUD ABSTRACT. Sufficient conditions are given to

More information

ANSWER KEY. Page 1 Page 2 cake key pie boat glue cat sled pig fox sun dog fish zebra. Page 3. Page 7. Page 6

ANSWER KEY. Page 1 Page 2 cake key pie boat glue cat sled pig fox sun dog fish zebra. Page 3. Page 7. Page 6 P 1 P 2 y sd fx s d fsh z ys P 3 P 4 my, ms, m, m, m, m P 6 d d P 7 m y P 5 m m s P 10 y y y P 8 P 9 s sh, s, ss, sd sds, s, sh sv s s P 11 s P 12,, m, m, m,, dd P 13 m f m P 18 h m s P 22 f fx f fsh fm

More information

Chapter 3. Second Order Linear PDEs

Chapter 3. Second Order Linear PDEs Chapter 3. Second Order Linear PDEs 3.1 Introduction The general class of second order linear PDEs are of the form: ax, y)u xx + bx, y)u xy + cx, y)u yy + dx, y)u x + ex, y)u y + f x, y)u = gx, y). 3.1)

More information

t t t ér t rs r t ét q s

t t t ér t rs r t ét q s rés té t rs té s é té r t q r r ss r t t t ér t rs r t ét q s s t t t r2 sé t Pr ss r rs té P r s 2 t Pr ss r rs té r t r r ss s Pr ss r rs té P r q r Pr ss r t r t r r t r r Prés t r2 r t 2s Pr ss r rs

More information

Set-Valued Risk Measures and Bellman s Principle

Set-Valued Risk Measures and Bellman s Principle Set-Valued Risk Measures and Bellman s Principle Zach Feinstein Electrical and Systems Engineering, Washington University in St. Louis Joint work with Birgit Rudloff (Vienna University of Economics and

More information

e st f (t) dt = e st tf(t) dt = L {t f(t)} s

e st f (t) dt = e st tf(t) dt = L {t f(t)} s Additional operational properties How to find the Laplace transform of a function f (t) that is multiplied by a monomial t n, the transform of a special type of integral, and the transform of a periodic

More information

GENERALIZED TWISTED FIELDS

GENERALIZED TWISTED FIELDS GENERALIZED TWISTED FIELDS A A ALBERT 1 Introduction Consider a finite field $ If V is any automorphism of & we define v to be the fixed field of K under V Let S and T be any automorphism of $ and define

More information

< < or a. * or c w u. "* \, w * r? ««m * * Z * < -4 * if # * « * W * <r? # *» */>* - 2r 2 * j j. # w O <» x <» V X * M <2 * * * *

< < or a. * or c w u. * \, w * r? ««m * * Z * < -4 * if # * « * W * <r? # *» */>* - 2r 2 * j j. # w O <» x <» V X * M <2 * * * * - W # a a 2T. mj 5 a a s " V l UJ a > M tf U > n &. at M- ~ a f ^ 3 T N - H f Ml fn -> M - M. a w ma a Z a ~ - «2-5 - J «a -J -J Uk. D tm -5. U U # f # -J «vfl \ \ Q f\ \ y; - z «w W ^ z ~ ~ / 5 - - ^

More information

Conformal Mapping Lecture 20 Conformal Mapping

Conformal Mapping Lecture 20 Conformal Mapping Let γ : [a, b] C be a smooth curve in a domain D. Let f (z) be a function defined at all points z on γ. Let C denotes the image of γ under the transformation w = f (z). The parametric equation of C is

More information