A systematic review of the effectiveness of occupational health and safety training 1

Size: px
Start display at page:

Download "A systematic review of the effectiveness of occupational health and safety training 1"

Transcription

1 Roson t l Sn J Work Envron Hlt. 2012;38(3): o: /sjw.3259 A systmt rvw t tvnss ouptonl lt n sty trnn 1 y Lyn S Roson, PD, 2 Crol M Stpnson, PD, Pul A Sult, PD, Bnjmn C Amk III, PD, Emm L Irvn, BA, Donl E Ert, PD, Stll Cn, MS, Amr R Blky, MS, Ann M Wn, BSN, Trr L Hottn, ED, Rort H Ptrs, MS, Jut A Clrk, MA, Kmrly Culln, MS, Cty J Rotun, ED, Pul L Gru, PD 1 Appnx Supplmntry tls A K 2 Corrsponn utor Insttut or Work & Hlt, 481 Unvrsty Av, Sut 800, Toronto, ON M5G 2E9, Cn. [E-ml: lroson@w.on.] Sn J Work Envron Hlt 2012 vol 38, no 3 1

2 Systmt rvw t tvnss OHS trnn Appnx: Fur A n Tls A K TRAINING FACTORS (.. lrnn prnpls, tmn, ormt, trnr) IMMEDIATE OUTCOMES (.. rton to trnn, knowl, ls, sklls, tttus, motvton to t, vorl ntnt) INTERMEDIATE OUTCOMES (.. vors, zr ontrols, zrs, xposurs) IMPACTS (.. njurs, llnsss, tlts, slts, osts) INDIVIDUAL FACTORS (.. morp tors, ontv lts, oupton, tnty, lnu lts, lrnn styl, prvous trnn, lt sttus, pr-trnn tttus, xptns, motvton to lrn) PRE-INTERVENTION WORKPLACE FACTORS (.. pr-trnn ns ssssmnt, mpowrmnt, sty ultur) POST-INTERVENTION WORKPLACE FACTORS (.. post-trnn mntnn ntrvntons, mpowrmnt, sty ultur) WORKPLACE Fur A. Conptul mol workpl trnn ntrvntons or prmry prvnton n OHS EXTERNAL ENVIRONMENT Tl A. Trms or ltrtur sr Trm Ctory Ext Sr Trms Work-rlt mploymnt/ ouptons work/ workr$.mp./ workpl$.mp. Euton n trnn ntrvnton ln trnn.mp. uton/ utonl msurmnt/ utonl sttus/ -trnn.mp. xtr trnn.mp. lt uton/ Hlt Euton/mt [Mtos] lt knowl, tttus, prt/ nsrv trnn/ Insrv Trnn/, o, mt ntrvnton?.mp. on mn trnn.mp. pr trnn.mp. trnn.mp. OHS outoms n tors tn tvnss Btwn-roup vluton sn sntsm/ nts/ nts, ouptonl/ nt prvnton/ rrrs.mp. vo?rl n.mp. lm$.mp. Costs n Cost Anlyss / umultv trum sorr/ onom vluton.mp. Evluton Stus/ lttors.mp. twn roups.mp. omprson.mp. k prours.mp. k/ zrous sustns/ zrous wst/ Hlt Knowl, Atttus, Prt/ lt protton.mp. KNOWLEDGE/ ml r.mp. ouptonl sss/ ouptonl xposur/ ouptonl lt/ Ouptonl Hlt Srvs/ prormn ntors.mp. prsntsm.mp. prmry prvnton/ prottv tors.mp. prt.mp. rnormnt.mp. rturn on nvstmnt.mp. Rsk Ftors/ sty/ sty ultur.mp. workrs ompnston/ wouns n njurs / rnom$.mp. T sr ws lmt to umns n (Enls or Frn) n yr= Trms wr lso us to xlu pultons: lt promoton, t, xrs, smokn, wt loss n ton. T trms r prsnt usn Mln syntx. Ts ws pt or otr tss. Sr trms wr omn usn t ollown Booln lo: trms wtn t sm tory wr omn usn OR n t trms n rnt tors wr omn usn AND. 2 Sn J Work Envron Hlt 2012 vol 38, no 3

3 Roson t l Tl B. Rlvn ssssmnt qustons, st 1. [OHS=ouptonl lt n sty.] Quston Exlusonry rspons 1 Is t stuy xmnn workr populton? No 2 Is t stuy onrn wt ny t ollown? No An ntrvnton stuy (wt pr- n post- msurs) ssssn t tvnss n OHS uton/trnn prorm Ftors tt my ltt or nt t tvnss OHS uton/trnn prorms A novl ppro to prov OHS uton/trnn prorms Splz tnqus/mtos (, omputr-s trnn) tt v n us to prov OHS uton/trnn prorms Ftors tt t ompln wt OHS uton/trnn prorms 3 Dos t stuy prsnt normton tt s st sr s onjtur or tstmonls wt no supportn vn? Ys 4 Dos t stuy ous on workrs urrnt stt knowl rrn n OHS ssu, w smply nts tt tr s urtr Ys n or uton/trnn on ts ssu? 5 Is t stuy puls n Enls or Frn? No Is t t pulton twn 199 n 2007? No Tl C. Et trnn on knowl (rltv to no-trnn ontrol). [ANCOVA=nlyss ovrn; =stnrz mn rn; NR=not rport;=stnr rror.] Gry t l (3) Grn t l (34) Hrrnton & Wlkr (45) Hrrnton & Wlkr (5) Rzzo t l (47) Intrvnton (lvl nmnt numr trnn sssons; zr typ ) Mult-omponnt lt trnn or nurss (H;5;E) Mult-omponnt ronoms (H;2;E) Computr-s om ronoms trnn (L;1;E) 1) Computr-s r sty trnn t l r lty (M;2;P) 2) Instrutor-l r sty trnn (L;2;P) 1) Instrutor-rt omputr ronoms (L;1;E) 2) Vo n pmplts; omputr ronoms (L;1;E) Mto lmttons sor N Tm Outom (mto msurmnt) Rsults, s rport n ornl pulton Drton t Sttstl snn (twn 8 NR 0 Knowl + P< wks Knowl n ls + P<0.01 or ntrton sln knowl n roup n ANCOVA Et sz Knowl + P< # ) 4 2) ) 45 2) 39 0 ) Knowl on zrs ) Knowl on sty vors 15 1( # 1( # 2( # 2( # Knowl 1) + 2) + ANCOVA 1() P<0.05 1() P<0.05 2() P<0.05 2() P<0.05 ANCOVA 1) P<0.05 2) P<0.05 1() () 1.0 2() () ) ) 0.78 Mor tls on t ntrvntons r n Tl 4. Lvl lrnr nmnt n t ntrvnton, s sr n mtos: low (L), mum (M), or (H). Hzr typ: olol (B), ml (C), ronom (E), pysl (P), sty (S). Mtoolol lmttons sor s sr n Mtos, wt rn 0 (no lmttons) to 8 (most lmttons). Totl numr sujts n t ntrvnton n ontrol roups n nlyss. Sujts r popl unlss nt otrws. Mto us to msur outom: mnstrtv rors (A), lnl xm (C), osrvtons (O), pysl proprty msurmnt (P), qustonnr/ry, voluntry rstry (R). Drton t, s rport y ornl utors or twn-roup rsults. Wn not rport y t ornl utors, t trmnton ws m y t rvwrs (nt y #), u y t utors ppro to nlyss. A postv vlu nts trnn mor tv tn ontrol. Sttstl snn, s rport y ornl utors or twn-roup tst. Wn not rport y t ornl utors, t ws trmn y rvwrs (nt y #) wn sln smlrty roups wt rspt to t outom oul stls (usn rtron p>0.05). Tsts wr onut on post-ntrvnton t only, unlss nt otrws. ws lult y rvwrs rom post-ntrvnton t wn sln smlrty t roups wt rspt to t outom oul stls (usn rtron P>0.05). A postv vlu nts trnn mor tv tn ontrol Sn J Work Envron Hlt 2012 vol 38, no 3 3

4 Systmt rvw t tvnss OHS trnn Tl D. Et trnn on tttus n ls (rltv to no-trnn ontrol). [ANCOVA=nlyss ovrn; = stnrz mn rn; NS=not sttstlly snnt; NC=not lult y rvwrs us sln ssmlrty roups wt rspt to outom msurs; =stnr rror] Grn t l (34) Hrrnton & Wlkr (45) Hrrnton & Wlkr (5) Intrvnton (lvl nmnt numr trnn sssons; zr typ ) Mult-omponnt ronoms (H;2;E) Computr-s om ronoms trnn (L;1;E) 1) Computr-s r sty trnn t l r lty (M;2;P) 2) Instrutor-l r sty trnn (L;2;P) Mto lmttons sor N Tm wks Outom (mto msurmnt) ) Sl-y ) Outom xpttons Rsults, s rport n ornl pulton Drton t )+ )+ Sttstl snn (twn ANCOVA: ) 0.82 ) P<0.01 or ) 0.87 ntrton sln sl-y n roup ) P=0.00 Et sz Atttus + P= # ) 4 2) 45 0 ) Atttus to zrs ) Atttus to sty vors 1() - 1( 2() - 2() - ANCOVA on roups 1,2 n ontrol 1() NS 1() NS 2() NS 2() NS 1() NC 1() () () Mor tls on t ntrvntons r n Tl 4. Lvl lrnr nmnt n t ntrvnton, s sr n mtos: low (L), mum (M), or (H). Hzr typ: olol (B), ml (C), ronom (E), pysl (P), sty (S). Mtoolol lmttons sor s sr n Mtos, wt rn 0 (no lmttons) to 8 (most lmttons). Totl numr sujts n t ntrvnton n ontrol roups n nlyss. Sujts r popl unlss nt otrws. Mto us to msur outom: mnstrtv rors (A), lnl xm (C), osrvtons (O), pysl proprty msurmnt (P), qustonnr/ry, voluntry rstry (R). Drton t, s rport y ornl utors or twn-roup rsults. Wn not rport y t ornl utors, t trmnton ws m y t rvwrs (nt y #), u y t utors ppro to nlyss. A postv vlu nts trnn mor tv tn ontrol. Sttstl snn, s rport y ornl utors or twn-roup tst. Wn not rport y t ornl utors, t ws trmn y rvwrs (nt y #) wn sln smlrty roups wt rspt to t outom oul stls (usn rtron p>0.05). Tsts wr onut on post-ntrvnton t only, unlss nt otrws. ws lult y rvwrs rom post-ntrvnton t wn sln smlrty t roups wt rspt to t outom oul stls (usn rtron P>0.05). A postv vlu nts trnn mor tv tn ontrol. Tl E. Et trnn on vors (rltv to no-trnn ontrol). [ANCOVA=nlyss ovrn; =stnrz mn rn; NC=not lult y rvwrs us sln ssmlrty roups wt rspt to outom msurs; NS=not sttstlly snnt; PPE=prsonl prottv qupmnt; PS=psyosol; RM ANOVA=rpt msurs nlyss vrn; =stnr rror; UP=unvrsl prutons.] Arntz & Arntz (50) Bor (53, 54) Brsson t l (31) Intrvnton (lvl nmnt numr trnn sssons; zr typ ) Group susson volnt nnts (ot roups wt volnt nnt orms) (M; multpl; S) 1) Mult-omponnt ronoms (H;1;E) 2) Ltur (L;1;E) Mult-omponnt ronoms (H;2;E) or : 1) <40 yrs 2) 40 yrs Mto lmttons sor N Tm Outom (mto msurmnt) Exposurs to volnt nnts 1) 103 2) ) 207 2) ) Workstton zrs (O) ) Posturl vors (O) ) 3 posturl vors (O) ) 10 workstton zrs (O) Rsults, s rport n ornl pulton Drton t Sttstl snn (twn Et sz - P= () - # 1() - # 2( # 2( # All # 1() NC, +, + 1(, NC, NC, NC, NC, +, -, NC, +, + 2(, NC, + 2() NC, +, +, +, +, +, NC, +, +, + P 0.05 (RM ANOVA on ll 3 roups) All # 1) P=NC, 0.00, ) P=0.02, NC, NC, NC, NC, 0.02, 0.15, NC,, () P=0.99, n, () P=NC, 0.00, 0.07, 0.15, 0.01, 0.00, NC, 0.01,, () NC, 0.49, () 0.34, NC, NC, NC, NC, 0.35, -, NC, 0.29, () 0.01, NC, () NC, 0.38, 0.19, 0.15, 0.2,, NC, 0.30, 0.14, () () () 2() 4 Sn J Work Envron Hlt 2012 vol 38, no 3

5 Roson t l Tl E. Contnu Eklö t l (40); Eklö & Hr (4) Grn t l (34) Hl t l (33) Jnsn t l (51) Rsmussn t l (49) Intrvnton (lvl nmnt numr trnn sssons; zr typ ) Mult-omponnt ronoms nlun PS tors (H;1;E) Tr stuy rms wt rnt trts or k: 1) nvul 2) suprvsors 3) roup Mult-omponnt ronoms (H;2;E) Formlz uton prorm on skn r (H;3;C) Trn-t-trnr prorm n ptnt ltn tnqus (H;2;E) Mto lmttons sor N 3 1) 18 2) 18 3) 18 (unt: work Tm wks ~4 9 Mult-omponnt rm sty (H;2;S) 1 ~171 rms Outom (mto msurmnt) ) % ronom motons ) Avr numr ronom motons Posturl xposurs (O) wt work vors ) Pysl xrton ) Hnln vor ) Rn moton (O) ) Atv sty vors ) PPE us Rsults, s rport n ornl pulton Drton t 1( 2( 3( 1( # 2( # 3( # Sttstl snn (twn 1() P=0.02 2() P=0.02 3() P=0.0 1,2,3 () P=0.24 n ovrll tst All s on n t. + P<0.01 or ntrton posturl xposurs n roup n ANCOVA ) v) v) + v # ) - ) ) Usn n t: ) P=0.02 ) P<0001 ) P=0.80 v) P=0.54 v) P=0.0 v) P= 0.11 ) NS ) NS ) NS Usn n t: ) P=0.035 ) P=0.005 Et sz 1() () (1.98 1() () () ) 0.51* ) 0.83 * ) 0.03 * v) 0.17 * v) 0.52 * v) 0.32 * ) ) ) 0.25 Rzzo t l (47) 1) Instrutor-rt omputr ronoms (L;1:E) 2) Vo n pmplts; omputr ronoms (L;1:E) 1) 45 2) Work ts 1) + 2) + ANCOVA: 1) P<0.05 2) P<0.05 1) NC 2) Wrt t l (52) Computr-ssst wt prolmsolvn; UP vors (M;1;B) UP vors (O) + Usn n t: P= Mor tls on t ntrvntons r n Tl 4. Lvl lrnr nmnt n t ntrvnton, s sr n mtos: low (L), mum (M), or (H). Hzr typ: olol (B), ml (C), ronom (E), pysl (P), sty (S). Mtoolol lmttons sor s sr n Mtos, wt rn 0 (no lmttons) to 8 (most lmttons). Totl numr sujts n t ntrvnton n ontrol roups n nlyss. Sujts r popl unlss nt otrws. Mto us to msur outom: mnstrtv rors (A), lnl xm (C), osrvtons (O), pysl proprty msurmnt (P), qustonnr/ry, voluntry rstry (R). Drton t, s rport y ornl utors or twn-roup rsults. Wn not rport y t ornl utors, t trmnton ws m y t rvwrs (nt y #), u y t utors ppro to nlyss. A postv vlu nts trnn mor tv tn ontrol. Sttstl snn, s rport y ornl utors or twn-roup tst. Wn not rport y t ornl utors, t ws trmn y rvwrs (nt y #) wn sln smlrty roups wt rspt to t outom oul stls (usn rtron P>0.05). Tsts wr onut on post-ntrvnton t only, unlss nt otrws. ws lult y rvwrs rom post-ntrvnton t wn sln smlrty t roups wt rspt to t outom oul stls (usn rtron P>0.05). A postv vlu nts trnn mor tv tn ontrol. In som ss, t wr stmt rom Fur (nt y*). Sn J Work Envron Hlt 2012 vol 38, no 3 5

6 Systmt rvw t tvnss OHS trnn Tl F. Et trnn on lt (rltv to no-trnn ontrol). [ANCOVA=nlyss ovrn; =stnrz mn rn; MSK=musuloskltl; NS=not sttstlly snnt; PS=psyosol; =stnr rror; UE=uppr xtrmty; US=uppr spn.] Intrvnton (lvl nmnt numr trnn sssons; zr typ ) Mto lmttons sor N Tm Outom (mto msurmnt) Rsults, s rport n ornl pulton Drton t Sttstl snn (twn Et sz Bno t l (55) Trnn on ol uttr us wt rtl mploys (H;1;S) Cuttr-rlt njury rt (A) - p = 0.8 # Rt rto: Bor (53, 54) 1) Mult-omponnt ronoms (H;1;E) 2) Ltur (L;1;E) 1) 85 2) 8 12 Uppr-oy MSK symptom sor 1) + # 1,2) P< ) + # (RM ANOVA on ll 3 roups) Brsson t l (31) Duy & Hzltt (32) Eklö t l (40); Eklö & Hr (4) Mult-omponnt ronoms (H;2;E) or : 1) <40 yrs 2) 40 yrs 1) Inormton on vo us or tn trns (L;1;E) 2) Prtl trnn on vo us or tn trns (H;2;E) Mult-omponnt ronoms nlun PS tors (H;1;E) Tr stuy rms wt rnt trts or k: 1) nvul 2) suprvsors 3) roup 4 1) 12 2) 328 1) 35 2) ) 18 2) 18 3) 18 (unt: work 2 MSK sorr prvln (C) Vo qulty sor (P) MSK or y symptom prvln 1) + 1) P=0.1 # 1) ) - # 2) P=0.4 # 2) ) + 2) + 1) - # 2) - # 3) - # P=0.18 (RM ANOVA on ll 3 roups) 1,2,3) P=0.90 n ovrll tst n t 1) 0.04 * 2) 0.30 * 1) ) ) Grn t l (34) Mult-omponnt ronoms (H;2;E) wks MSK symptom sor : ) UE ntnsty ) UE rquny ) UE urton v) US ntnsty v) US rquny v) US urton ) ) v) + v) + v ) P=0. ) P=0.9 ) P=0.7 v) P=0.8 v) P=0.4 v) P=0.7 ) - ) 0.03 ) v) 0.15 v) 0.27 v) 0.37 Hl t l (33) Formlz uton prorm on skn r (H;3;C) Skn symptom svrty (C + P= (s on n t) 0.05* Jnsn t l (51) Rsmussn t l (49) vn Poppl t l (58) Trn-t-trnr prorm n ptnt ltn tnqus (H;2;E) Mult-omponnt rm sty (H;2;S) 1 ~930 Ltn ronoms or mtrl nlrs (H;3;E) Low k pn : ) pst yr ) pst 3 Frm-rlt njury rts; ll njurs Low-k pn pst mont prvln ) ) Usn n t: ) P= ) P=0.1 ) 0.04 ) P=NS (Posson rrsson mol) Rt rto: P= Mor tls on t ntrvntons r n Tl 4. Lvl lrnr nmnt n t ntrvnton, s sr n mtos: low (L), mum (M), or (H). Hzr typ: olol (B), ml (C), ronom (E), pysl (P), sty (S). Mtoolol lmttons sor s sr n Mtos, wt rn 0 (no lmttons) to 8 (most lmttons). Totl numr sujts n t ntrvnton n ontrol roups n nlyss. Sujts r popl unlss nt otrws. Mto us to msur outom: mnstrtv rors (A), lnl xm (C), osrvtons (O), pysl proprty msurmnt (P), qustonnr/ ry, voluntry rstry (R). Drton t, s rport y ornl utors or twn-roup rsults. Wn not rport y t ornl utors, t trmnton ws m y t rvwrs (nt y #), u y t utors ppro to nlyss. A postv vlu nts trnn mor tv tn ontrol. Sttstl snn, s rport y ornl utors or twn-roup tst. Wn not rport y t ornl utors, t ws trmn y rvwrs (nt y #) wn sln smlrty roups wt rspt to t outom oul stls (usn rtron P>0.05). Tsts wr onut on post-ntrvnton t only, unlss nt otrws. ws lult y rvwrs rom post-ntrvnton t wn sln smlrty t roups wt rspt to t outom oul stls (usn rtron P>0.05). A postv vlu nts trnn mor tv tn ontrol. In som ss, t wr stmt rom Fur (nt y*). Sn J Work Envron Hlt 2012 vol 38, no 3

7 Roson t l Tl G. Rltv tvnss rn lvls nmnt on outoms. [ANCOVA=nlyss ovrn; =stnrz mn rn; HPD=rn protton v; I=ntrvnton; NC=not lult y rvwr us sln ssmlrty roups wt rspt to outom msur; NS=not sttstlly snnt; PPE=prsonl prottv qupmnt; Q&A=quston & nswr ssson; RM ANOVA=rpt msurs nlyss vrn; =stnr rror; UE MSK=uppr xtrmty musuloskltl ] Bor (53, 54) Duy & Hzltt (32) Hrrnton & Wlkr (5) Hon t l (2) Lölr t l (42) Lusk t l (5, ) Prry & Ly (57) Intrvnton (lvl nmnt numr trnn sssons; zr typ ) I1) Prtptory uton (ns-on mo, prolm solvn, pplton to work r) (H;1;E) I2) Trtonl uton (ltur, normtonl nout, Q&A ssson) (L;1;E) I1) Drt vo r trnn (volzton, postur, rsprton, rls tnson n vol pprtus, rsonn, n vo projton) (H;2;E) I2) Inrt vo r trnn (normton on vo prouton, tors ssot wt lty vo) (L;1;E) I1) Computr-s nstruton on r sty; srns ontn nrrton, ntrton, nmton or vo; som wt qustons n ntrtv ms (M;2;S) I2) Lturs & prnt mtrls (L;2;S) Mto lmttons sor I1) Computr w/ tlor k ) 2 nl. rn tst rsult; HPD prt ) 3 (H;1;P) I2) Commrl vo w/ rn tst rsult (M;1;P) I1) Ltur, prolm-solvn n prt rrn skn r (M;7;C) I2) Inormtonl ppr on skn r (L;1;C) I1) Tlor: Computr-s trnn tlor to workr s sl-rport prt. Us tul, ontv ppros, monstrton, rt prt, vrous xprn, prsuson n rol-moln tnqus. Prsnt n ntrtv ormt, wt k (H;1:P) I2) Non-tlor: As ov, ut lvr to ll prtpnts n unorm mnnr (H;1;P) I3) Vo (L;1;P) I1) Euton ntrvnton (ltur, sls, prsntton y rspt r rmr, monstrton n opportunty or ns-on prt) (H;1;C) I2) Stnr r-rtton mtn or pst ppltors (L;1;C) N Tm Outom (mto msurmnt) ) Workstton zrs (O) ) Posturl vors (O) ) UE MSK symptoms Vo qulty (Dyspon Svrty Inx) (P) Rsults, s rport n ornl pulton Drton t I1 vrsus I2: ) # ) # # I1 vrsus I2: Fr sty outoms : ) knowl on zrs I1 vrsus I2: # # ) knowl on sty # vors v) +# ) tttus on zrs v) tttus on sty vors 403 ) 0 wks ) yrs tr 1st ssson ) 2 ) 1 ) 1 v) 1 v) 1 v) ) Intnton to us HPDs ) Us HPDs Sttstl snn (twn RM ANOVA: ) NS ) NS ) NS 1, 2, ontrol: RM ANOVA: P=0.18 ) P=NS ) P=NS 1,2, ontrol: ANCOVA: ) P=NS v) P=NS RM ANOVA: ) P=0.001 ) NS Et sz Sn J Work Envron Hlt 2012 vol 38, no 3 7 ) ) ) ) 0.41 ) 0.2 ) 0.5 v) 0.21 ) 0.13 ) Drmtts (C) + Multpl lost rrsson: P= Us rn protton ) Sty knowl ) PPE us otr tn lovs ) Full PPE ompln v) Drml xposur v) Sty ntntons v) Rsk prptons I1 vrsus I3: + I2 vrsus I3: - I1 vrsus I2: v) + v) + v RM ANOVA: 1 vrsus 3: P=0.49 I2 vrsus 3: P=0.18 ) P<0.05 ) P<0.05 ) NS v) NS v) P<0.05 v) P<0.05 I1 vrsus I3: NC I2 vrsus I3: ) v) v) v) Mor tls on ntrvntons n Tl 4. Lvl nmnt, s sr n Mtos: low (L), mum (M) or (H). Lvl lrnr nmnt, s sr n Mtos: low (L), mum (M) or (H). Hzr typ: olol (B), ml (C), ronom (E), pysl (P), sty (S). Mtoolol lmttons sor, s sr n Mtos, wt rn 0 (no lmttons) to 8 (most lmttons). Totl numr sujts n t ntrvnton n ontrol roups n nlyss. Sujts r popl unlss nt otrws. Mto us to msur outom: lnl xm (C), osrvtons (O), pysl proprty msurmnt (P), qustonnr/ry. Drton t: + nts t r lvl nmnt trnn ws mor tv tn lowr, s rport y t ornl utors or twnroup rsults, wn vll. Wn not rport, t trmnton ws m y t rvwrs (nt y #), u y t utors ppro to nlyss. Sttstl snn: As rport y ornl utors or twn-roup tst, wn vll. Wn not rport, t ws lult y rvwrs (nt y #) wn sln smlrty oul stls (usn rtron P>0.5). Tsts wr onut on post-ntrvnton t only, unlss nt otrws. Et sz ws lult rom post-ntrvnton t wn sln smlrty t roups wt rspt to t outom oul stls, usn rtron P> nts trnn wt t r lvl nmnt ws mor tv tn low. 0.04

8 Systmt rvw t tvnss OHS trnn Tl H. Alortm ppl to r vrsus lowr nmnt trnn vn to trmn ts strnt. [=stnrz mn rn; IQR=ntrqurtl rn.] Strnt vn Mtoolol qulty Mnmum quntty Consstny ts Et sz rtron Stron Goo 2 stus IQR (or rn) os not nlu zro Sunt: Knowl = 0.25 Atttus & Bls = Bvors = Hlt = 0.04 Goo or Fr 5 stus IQR (or rn) os not nlu zro Mt mtoolol qulty, quntty n onsstny rtr or sunt ut not stron vn Sunt Goo Not ppll IQR (or rn) os not nlu zro Insunt Goo or Fr 3 stus IQR (or rn) os not nlu zro T rtron n ny on t our omns not mt Sunt: Knowl = 0.25 Atttus & Bls = Bvors = Hlt = 0.04 Lr: Knowl = 0.38 Atttus & Bls = 0.25 Bvors = 0.20 Hlt = 0.08 Sunt: Knowl = 0.25 Atttus & Bls = Bvors = Hlt = 0.04 Sunt: Knowl = 0.25 Atttus & Bls = Bvors = Hlt = 0.04 Mtoolol qulty tors or stus: Goo (0 1 lmttons sor), Fr (3 4), n Lmt ( 5). Intrqurtl rn ws trmn wn tr wr v or mor t szs n t oy vn; otrws t ull rn ws us. Crtr or sunt n lr t szs wr n y t rsr tm. Ts wr oprtonlz y rqurn t mn t sz or oy vn to qul to or rtr tn t rtron. Tl I. Fnl os vn on t rltv tvnss r vrsus lowr nmnt trnn, y outom. [=stnrz mn rn; FB=k; =stnr rror ; ntrvnton (sp lvls lrnr nmnt ; # sssons) Mtoolol qulty Clult t szs Knowl Atttus Bvors Hlt Hon t l (2); rn protton (H vrsus M;1) Fr Lölr t l (42); rmtts prvnton (M vrsus L;7 vrsus 1) Fr Lusk t l (5, ); rn protton (H vrsus L;1) Fr Prry & Ly (57); s pst us (H vrsus L;1) Fr + Prry & Ly (57); s pst us (H vrsus L;1) Goo ) 0.14 * v) Mor tls ntrvntons r n Tl 4. Sp lvls lrnr nmnt ontrst n t stuy, trmn s sr n Mtos: low (L), mum (M), or (H). Rrs to t ssss mtoolol qulty t sp outom t nlu n t tl: Goo, 0 1 mtoolol lmttons sor; Fr, 2 4. vlus n rom Tl G wr rr ovr to Tl I wn t mtoolol qulty t t ws r or oo. Wn stuy rport multpl msurs smlr onpt, only tr mn rport r (nt y *). T stnr rror or t ontrutn nvul msurs n oun n Tl G. A postv vlu or nts t r nmnt trnn s mor tv tn t lowr nmnt trnn. Numr ullts prn nvul t szs orrspon to tos us n Tl G. Et sz not lull, ut rton s nt. 8 Sn J Work Envron Hlt 2012 vol 38, no 3

9 Roson t l Tl J. Summry mtoolol qulty ssssmnts stus. [K=knowl; A=tttus n ls; B=vors; H=lt; CSG=omprlty stuy roups; II=ntrvnton mplmntton; OA=outom ssssmnt; SA=sttstl nlyss.] Intl stuy smpl sz Outoms ssss Mtoolol ssssmnts: our omns CSG II OA SA Mtoolol lmttons sor us n vn syntss Arntz & Arntz (50) *1500 B P P N P 5 Bno t l (55) *900 H P P P P 4 Bor (53, 54) 154 B, H N N Y N Brsson t l (31) *58 B, H P P Y N 4 Duy & Hzltt (32) 55 H N N Y N Eklö t l (40); 39 B, H P P P Y 3 Eklö & Hr (4) Gry t l (3) *250 K N N N N 8 Grn t l (34) 87 K, A, B, H P P P P 4 Hrrnton & Wlkr (45) 102 K, A P N P Y 4 Hrrnton & Wlkr (5) 141 K, A N P P P 5 Hl t l (33) 375 B, H Y Y Y Y 0 Hkmn & Gllr (44) 15 B Y P Y Y 1 Hon t l (2) 12 A, B P Y Y P 2 Jnsn t l (51) 210 B, H P P N N Lölr t l (42) 521 H P P Y P 3 Lusk t l (5, ) 2219 B P P P P 4 Prry & Ly (57) 400 K, B Y P Y Y 1 Rsmussn t l (49) 990 B,H Y Y P Y 1 Rzzo t l (47) *150 K N N Y P 5 Vn Poppl t l (58) 312 H P P P N 5 Wn t l (43) 10 K, B P P P P 4 Wrt t l (52) 0 B P P P Y 3 Intl stuy smpl sz rrs to t ntl sz t smpl wt rspt to nvul workrs. Wr t stnton ws prmtt, ts ws t sz t stuy smpl ollown xlusons on t ss llty, ntl nlty to ontt n ntl rusl to prtpt, ut or ny loss smpl or rsons non-rspons urn msurmnt or wtrwl. Astrsks (*) nt ss n w numrs wr tr stmt y t rvwrs or wr rport s pproxmt y t utors. E t ollown omns potntl s ws rst ssss y svrl tms n t mtoolol qulty ssssmnt orm: CSG, II, OA n SA. T rvwrs tn ssss wtr ty wr onnt tt t potntl or s n tt omn n mnmz: Ys (Y); Prtly (P); No (N). Sn outom ws ssss npnntly, t tl sows t stronst t ssssmnts mon ll outoms or stuy. Lmttons sor s rv rom t our omn-sp mtoolol ssssmnts (s Mtos) n rns rom 0 (no lmttons) to 8 (most lmttons). Tl K. Dtrmnton t strnt vn or outom n stus t rltv tvnss r vrsus lowr nmnt trnn [IQR=ntrqurtl rn; N=numr stus; NA=not ppll/not vll] Outom Goo Summry oy vn n tl G N IQR Mn t szs Fr Assssmnt oy vn usn vn syntss lortm Numr oo or r stus Consstny Mn t szs Strnt vn Knowl 0 1 NA NA Too w NA NA Insunt Atttus 0 1 NA Too w NA Sunt Insunt Bvors Enou Consstnt Lss tn Insunt sunt Hlt 0 1 NA 0.0 Too w NA Lr Insunt Dsrptors nt t rsult ssssn tur oy vn usn t vn syntss lortm sown n Tl H. T rsultn onluson out strnt vn ollown t ssssmnt oy vn nst t vn syntss lortm (tl H). Sn J Work Envron Hlt 2012 vol 38, no 3 9

In which direction do compass needles always align? Why?

In which direction do compass needles always align? Why? AQA Trloy Unt 6.7 Mntsm n Eltromntsm - Hr 1 Complt t p ll: Mnt or s typ o or n t s stronst t t o t mnt. Tr r two typs o mnt pol: n. Wrt wt woul ppn twn t pols n o t mnt ntrtons low: Drw t mnt l lns on

More information

Weighted Graphs. Weighted graphs may be either directed or undirected.

Weighted Graphs. Weighted graphs may be either directed or undirected. 1 In mny ppltons, o rp s n ssot numrl vlu, ll wt. Usully, t wts r nonntv ntrs. Wt rps my tr rt or unrt. T wt o n s otn rrr to s t "ost" o t. In ppltons, t wt my msur o t lnt o rout, t pty o ln, t nry rqur

More information

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees /1/018 W usully no strns y ssnn -lnt os to ll rtrs n t lpt (or mpl, 8-t on n ASCII). Howvr, rnt rtrs our wt rnt rquns, w n sv mmory n ru trnsmttl tm y usn vrl-lnt non. T s to ssn sortr os to rtrs tt our

More information

Lecture 20: Minimum Spanning Trees (CLRS 23)

Lecture 20: Minimum Spanning Trees (CLRS 23) Ltur 0: Mnmum Spnnn Trs (CLRS 3) Jun, 00 Grps Lst tm w n (wt) rps (unrt/rt) n ntrou s rp voulry (vrtx,, r, pt, onnt omponnts,... ) W lso suss jny lst n jny mtrx rprsntton W wll us jny lst rprsntton unlss

More information

Depth First Search. Yufei Tao. Department of Computer Science and Engineering Chinese University of Hong Kong

Depth First Search. Yufei Tao. Department of Computer Science and Engineering Chinese University of Hong Kong Dprtmnt o Computr Sn n Ennrn Cns Unvrsty o Hon Kon W v lry lrn rt rst sr (BFS). Toy, w wll suss ts sstr vrson : t pt rst sr (DFS) lortm. Our susson wll on n ous on rt rps, us t xtnson to unrt rps s strtorwr.

More information

The University of Sydney MATH 2009

The University of Sydney MATH 2009 T Unvrsty o Syny MATH 2009 APH THEOY Tutorl 7 Solutons 2004 1. Lt t sonnt plnr rp sown. Drw ts ul, n t ul o t ul ( ). Sow tt s sonnt plnr rp, tn s onnt. Du tt ( ) s not somorp to. ( ) A onnt rp s on n

More information

Divided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano

Divided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano RIGHT-ANGLE WEAVE Dv mons Mm t look o ts n rlt tt s ptvly p sn y Py Brnkmn Mttlno Dv your mons nto trnls o two or our olors. FCT-SCON0216_BNB66 2012 Klm Pulsn Co. Ts mtrl my not rprou n ny orm wtout prmsson

More information

4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling: Greedy Algorithms. Interval Scheduling. Interval scheduling.

4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling: Greedy Algorithms. Interval Scheduling. Interval scheduling. Cptr 4 4 Intrvl Suln Gry Alortms Sls y Kvn Wyn Copyrt 005 Prson-Ason Wsly All rts rsrv Intrvl Suln Intrvl Suln: Gry Alortms Intrvl suln! Jo strts t s n nss t! Two os omptl ty on't ovrlp! Gol: n mxmum sust

More information

Spanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1

Spanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1 Spnnn Trs BFS, DFS spnnn tr Mnmum spnnn tr Mr 28, 2018 Cn Hrn / Gory Tn 1 Dpt-rst sr Vsts vrts lon snl pt s r s t n o, n tn ktrks to t rst junton n rsums own notr pt Mr 28, 2018 Cn Hrn / Gory Tn 2 Dpt-rst

More information

CMSC 451: Lecture 4 Bridges and 2-Edge Connectivity Thursday, Sep 7, 2017

CMSC 451: Lecture 4 Bridges and 2-Edge Connectivity Thursday, Sep 7, 2017 Rn: Not ovr n or rns. CMSC 451: Ltr 4 Brs n 2-E Conntvty Trsy, Sp 7, 2017 Hr-Orr Grp Conntvty: (T ollown mtrl ppls only to nrt rps!) Lt G = (V, E) n onnt nrt rp. W otn ssm tt or rps r onnt, t somtms t

More information

(Minimum) Spanning Trees

(Minimum) Spanning Trees (Mnmum) Spnnn Trs Spnnn trs Kruskl's lortm Novmr 23, 2017 Cn Hrn / Gory Tn 1 Spnnn trs Gvn G = V, E, spnnn tr o G s onnt surp o G wt xtly V 1 s mnml sust o s tt onnts ll t vrts o G G = Spnnn trs Novmr

More information

Dental PBRN Study: Reasons for replacement or repair of dental restorations

Dental PBRN Study: Reasons for replacement or repair of dental restorations Dntl PBRN Stuy: Rsons or rplmnt or rpr o ntl rstortons Us ts Dt Collton Form wnvr stuy rstorton s rpl or rpr. For nrollmnt n t ollton you my rpl or rpr up to 4 rstortons, on t sm ptnt, urn snl vst. You

More information

Improving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e)

Improving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e) POW CSE 36: Dt Struturs Top #10 T Dynm (Equvln) Duo: Unon-y-Sz & Pt Comprsson Wk!! Luk MDowll Summr Qurtr 003 M! ZING Wt s Goo Mz? Mz Construton lortm Gvn: ollton o rooms V Conntons twn t rooms (ntlly

More information

MATERIAL SEE BOM ANGLES = 2 FINISH N/A

MATERIAL SEE BOM ANGLES = 2 FINISH N/A 9 NOTS:. SSML N NSPT PR SOP 0-9... NSTLL K STKR N X L STKR TO NS O SROU WT TP. 3. PR-PK LNR RNS WT P (XTRM PRSSUR NL R ) RS OR NNRN PPROV QUVLNT. 4. OLOR TT Y T SLS ORR. RRN T MNS OM OR OMPONNTS ONTNN

More information

DOCUMENT STATUS: RELEASE

DOCUMENT STATUS: RELEASE RVSON STORY RV T SRPTON O Y 0-4-0 RLS OR PROUTON 5 MM -04-0 NS TRU PLOT PROUTON -- S O O OR TLS 30 MM 03-3-0 3-044 N 3-45, TS S T TON O PROTTV RM OVR. 3 05--0 LT 3-004, NOT, 3-050 3 0//00 UPT ST ROM SN,

More information

New Biomaterials from Renewable Resources - Amphiphilic Block Copolymers from δ-decalactone. Figure S4 DSC plot of Propargyl PDL...

New Biomaterials from Renewable Resources - Amphiphilic Block Copolymers from δ-decalactone. Figure S4 DSC plot of Propargyl PDL... Eltron Supplmntry Mtrl (ESI) or Polymr Cmstry. Ts ournl s T Royl Soty o Cmstry 2015 Polymr Cmstry RSCPulsng Supportng Inormton Nw Bomtrls rom Rnwl Rsours - Amppl Blo Copolymrs rom δ-dlton Kulp K. Bnsl,

More information

Lecture II: Minimium Spanning Tree Algorithms

Lecture II: Minimium Spanning Tree Algorithms Ltur II: Mnmum Spnnn Tr Alortms Dr Krn T. Hrly Dprtmnt o Computr Sn Unvrsty Coll Cork Aprl 0 KH (/0/) Ltur II: Mnmum Spnnn Tr Alortms Aprl 0 / 5 Mnmum Spnnn Trs Mnmum Spnnn Trs Spnnn Tr tr orm rom rp s

More information

DOCUMENT STATUS: LA-S5302-XXXXS LA, SSS, TRICEPS EXTENSION VERY

DOCUMENT STATUS: LA-S5302-XXXXS LA, SSS, TRICEPS EXTENSION VERY RVSON STORY RV T SRPTON O Y //0 RLS OR PROUTON T LN MR ----- L /0/0 UPT SN N OMPONNTS US: S 3-03 (*N TWO PLS ONLY) WS 3-5, PRT 3-00 TO SSMLY. T OLLOWN UPT: 3-30, 3-403, 3-403, 3-40, 3-45, 3-4, 3-5. 30

More information

CMPS 2200 Fall Graphs. Carola Wenk. Slides courtesy of Charles Leiserson with changes and additions by Carola Wenk

CMPS 2200 Fall Graphs. Carola Wenk. Slides courtesy of Charles Leiserson with changes and additions by Carola Wenk CMPS 2200 Fll 2017 Grps Crol Wnk Sls ourtsy o Crls Lsrson wt ns n tons y Crol Wnk 10/23/17 CMPS 2200 Intro. to Alortms 1 Grps Dnton. A rt rp (rp) G = (V, E) s n orr pr onsstn o st V o vrts (snulr: vrtx),

More information

Theorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices.

Theorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices. Cptr 11: Trs 11.1 - Introuton to Trs Dnton 1 (Tr). A tr s onnt unrt rp wt no sp ruts. Tor 1. An unrt rp s tr n ony tr s unqu sp pt twn ny two o ts vrts. Dnton 2. A root tr s tr n w on vrtx s n snt s t

More information

Face Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction

Face Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction F Dtto Roto Lr Alr F Roto C Y I Ursty O solto: tto o l trs s s ys os ot. Dlt to t to ltpl ws. F Roto Aotr ppro: ort y rry s tor o so E.. 56 56 > pot 6556- stol sp A st o s t ps to ollto o pots ts sp. F

More information

Graph Search (6A) Young Won Lim 5/18/18

Graph Search (6A) Young Won Lim 5/18/18 Grp Sr (6A) Youn Won Lm Copyrt () 2015 2018 Youn W. Lm. Prmon rnt to opy, trut n/or moy t oumnt unr t trm o t GNU Fr Doumntton Ln, Vron 1.2 or ny ltr vron pul y t Fr Sotwr Founton; wt no Invrnt Ston, no

More information

Having a glimpse of some of the possibilities for solutions of linear systems, we move to methods of finding these solutions. The basic idea we shall

Having a glimpse of some of the possibilities for solutions of linear systems, we move to methods of finding these solutions. The basic idea we shall Hvn lps o so o t posslts or solutons o lnr systs, w ov to tos o nn ts solutons. T s w sll us s to try to sply t syst y lntn so o t vrls n so ts qutons. Tus, w rr to t to s lnton. T prry oprton nvolv s

More information

Strongly connected components. Finding strongly-connected components

Strongly connected components. Finding strongly-connected components Stronly onnt omponnts Fnn stronly-onnt omponnts Tylr Moor stronly onnt omponnt s t mxml sust o rp wt rt pt twn ny two vrts SE 3353, SMU, Dlls, TX Ltur 9 Som sls rt y or pt rom Dr. Kvn Wyn. For mor normton

More information

ELECTRONIC SUPPLEMENTARY INFORMATION

ELECTRONIC SUPPLEMENTARY INFORMATION Elctronc Supplmntry Mtrl (ESI) or Polymr Cmstry. Ts ournl s T Royl Socty o Cmstry 2015 ELECTRONIC SUPPLEMENTARY INFORMATION Poly(lyln tcont)s An ntrstn clss o polystrs wt proclly loct xo-cn oul ons suscptl

More information

Exam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms

Exam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms CS 542 Avn Dt Stutu n Alotm Exm 2 Soluton Jontn Tun 4/2/202. (5 ont) Con n oton on t tton t tutu n w t n t 2 no. Wt t mllt num o no tt t tton t tutu oul ontn. Exln you nw. Sn n mut n you o u t n t, t n

More information

Minimum Spanning Trees (CLRS 23)

Minimum Spanning Trees (CLRS 23) Mnmum Spnnn Trs (CLRS 3) T prolm Rll t nton o spnnn tr: Gvn onnt, unrt rp G = (V, E), sust o s o G su tt ty onnt ll vrts n G n orm no yls s ll spnnn tr (ST) o G. Any unrt, onnt rp s spnnn tr. Atully, rp

More information

Closed Monochromatic Bishops Tours

Closed Monochromatic Bishops Tours Cos Monoromt Bsops Tours Jo DMo Dprtmnt o Mtmts n Sttsts Knnsw Stt Unvrsty, Knnsw, Gor, 0, USA mo@nnsw.u My, 00 Astrt In ss, t sop s unqu s t s o to sn oor on t n wt or. Ts ms os tour n w t sop vsts vry

More information

Math 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4

Math 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4 Mt 166 WIR, Sprin 2012, Bnjmin urisp Mt 166 Wk in Rviw 2 Stions 1.1, 1.2, 1.3, & 1.4 1. S t pproprit rions in Vnn irm tt orrspon to o t ollowin sts. () (B ) B () ( ) B B () (B ) B 1 Mt 166 WIR, Sprin 2012,

More information

DOCUMENT STATUS: MINTP0 E-ST5080, BASE, NO DISPLAY VENDOR: 15.5 INCH MATERIAL SEE BOM FINISH REVISION HISTORY ITEM NO. PART NUMBER DESCRIPTION

DOCUMENT STATUS: MINTP0 E-ST5080, BASE, NO DISPLAY VENDOR: 15.5 INCH MATERIAL SEE BOM FINISH REVISION HISTORY ITEM NO. PART NUMBER DESCRIPTION RV T RVSON STORY SRPTON O Y 0-0-0 PROUTON RLS K. N NOTS:. SRL LL NORMTON: a) VOLTS: V b) MPS:.0 c) YLS: N/ d) WTTS: W e) PS: N/ f) PX #: PX. RTTON LOOS: S / / LN R WT SOPROPYL LOLOL PROR TO PLN.. PK M:

More information

46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l pp n nt n th

46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l pp n nt n th n r t d n 20 0 : T P bl D n, l d t z d http:.h th tr t. r pd l 46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l

More information

CSE 332. Data Structures and Parallelism

CSE 332. Data Structures and Parallelism Am Blnk Ltur 20 Wntr 2017 CSE 332 Dt Struturs n Prlllsm CSE 332: Dt Struturs n Prlllsm Grps 1: Wt s Grp? DFS n BFS LnkLsts r to Trs s Trs r to... 1 Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus,

More information

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2 Am Blnk Ltur 19 Summr 2015 CSE 332: Dt Astrtons CSE 332 Grps 1: Wt s Grp? DFS n BFS Dt Astrtons LnkLsts r to Trs s Trs r to... 1 A Grp s Tny... 2 Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus, Hps,

More information

Platform Controls. 1-1 Joystick Controllers. Boom Up/Down Controller Adjustments

Platform Controls. 1-1 Joystick Controllers. Boom Up/Down Controller Adjustments Ston 7 - Rpr Prours Srv Mnul - Son Eton Pltorm Controls 1-1 Joystk Controllrs Mntnn oystk ontrollrs t t propr sttns s ssntl to s mn oprton. Evry oystk ontrollr soul oprt smootly n prov proportonl sp ontrol

More information

MATERIAL SEE BOM ANGLES = 2 > 2000 DATE MEDIUM FINISH

MATERIAL SEE BOM ANGLES = 2 > 2000 DATE MEDIUM FINISH NOTS:. LN MTN SUR WT NTUR/SOPROPYL LOOL PROR TO RN L OR LOO. PPLY LOTT 4 ON TRS. TORQU TO. Nm / 00 lb-in 4. TORQU TO 45-50 Nm / - lb-ft 5. TORQU TO Nm / 4.5 lb-ft. TORQU TO 0 Nm / lb-in. TORQU TO 5.5 Nm

More information

The R-Tree. Yufei Tao. ITEE University of Queensland. INFS4205/7205, Uni of Queensland

The R-Tree. Yufei Tao. ITEE University of Queensland. INFS4205/7205, Uni of Queensland Yu To ITEE Unvrsty o Qunsln W wll stuy nw strutur ll t R-tr, w n tout o s mult-mnsonl xtnson o t B-tr. T R-tr supports ntly vrty o qurs (s w wll n out ltr n t ours), n s mplmnt n numrous ts systms. Our

More information

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology! Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik

More information

n r t d n :4 T P bl D n, l d t z d th tr t. r pd l

n r t d n :4 T P bl D n, l d t z d   th tr t. r pd l n r t d n 20 20 :4 T P bl D n, l d t z d http:.h th tr t. r pd l 2 0 x pt n f t v t, f f d, b th n nd th P r n h h, th r h v n t b n p d f r nt r. Th t v v d pr n, h v r, p n th pl v t r, d b p t r b R

More information

D t r l f r th n t d t t pr p r d b th t ff f th l t tt n N tr t n nd H n N d, n t d t t n t. n t d t t. h n t n :.. vt. Pr nt. ff.,. http://hdl.handle.net/2027/uiug.30112023368936 P bl D n, l d t z d

More information

DOCUMENT STATUS: CORE HEALTH & FITNESS, LLC IL-D2002-XXAAX IP,DUAL ADJUSTIBLE PULLEY MATERIAL SEE BOM FINISH N/A N/A SHEET SIZE: B SCALE: 1:33.

DOCUMENT STATUS: CORE HEALTH & FITNESS, LLC IL-D2002-XXAAX IP,DUAL ADJUSTIBLE PULLEY MATERIAL SEE BOM FINISH N/A N/A SHEET SIZE: B SCALE: 1:33. NOTS: RVSON STORY RV T SRPTON O Y //04 RLS OR PROUTON 433 P 34 55 033 OUMNT STTUS: NOT O PROPRTRY NORMTON TS OUMNT SLL NOT RPROU NOR SLL T NORMTON ONTN RN US Y OR SLOS TO OTR XPT S XPRSSLY UTORZ Y OR LT

More information

Sheet Title: Building Renderings M. AS SHOWN Status: A.R.H.P.B. SUBMITTAL August 9, :07 pm

Sheet Title: Building Renderings M. AS SHOWN Status: A.R.H.P.B. SUBMITTAL August 9, :07 pm 1 2 3 4 5 6 7 8 9 1 11 12 13 14 15 16 17 18 19 orthstar expressly reserves its common law copyright and other property rights for all ideas, provisions and plans represented or indicated by these drawings,

More information

Priority Search Trees - Part I

Priority Search Trees - Part I .S. 252 Pro. Rorto Taassa oputatoal otry S., 1992 1993 Ltur 9 at: ar 8, 1993 Sr: a Q ol aro Prorty Sar Trs - Part 1 trouto t last ltur, w loo at trval trs. or trval pot losur prols, ty us lar spa a optal

More information

Graphs Depth First Search

Graphs Depth First Search Grp Dpt Frt Sr SFO 337 LAX 1843 1743 1233 802 DFW ORD - 1 - Grp Sr Aort - 2 - Outo Ø By unrtnn t tur, you ou to: q L rp orn to t orr n w vrt r ovr, xpor ro n n n pt-rt r. q Cy o t pt-rt r tr,, orwr n ro

More information

COMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017

COMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017 COMP 250 Ltur 29 rp trvrsl Nov. 15/16, 2017 1 Toy Rursv rp trvrsl pt rst Non-rursv rp trvrsl pt rst rt rst 2 Hs up! Tr wr w mstks n t sls or S. 001 or toy s ltur. So you r ollown t ltur rorns n usn ts

More information

MINI POST SERIES BALUSTRADE SYSTEM INSTALLATION GUIDE PRODUCT CODE: MPS-RP

MINI POST SERIES BALUSTRADE SYSTEM INSTALLATION GUIDE PRODUCT CODE: MPS-RP MN POST SRS LUSTR SYSTM NSTLLTON U PROUT O: MPS-RP 0 R0 WLL LN 0 RONT LVTON VW R0 N P 0 T RUR LOK LOT ON LSS. SLON SL TYP. OT SS 000 LSS T 0 00 SRS LSS WT 00/00 (0mm NRMNTS VLL) MX. 000 00-0 (ROMMN) 00

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

Catalytic S N Ar of Unactivated Aryl Chlorides ESI

Catalytic S N Ar of Unactivated Aryl Chlorides ESI Eltron Supplmntry Mtrl (ESI) or CmComm. Ts journl s T Royl Soty o Cmstry 2014 Ctlyt S Ar o Untvt Aryl Clors ESI Tl o Contnts 1. Prour n Full Tl o Contons - Prour S1 - Intl solvnt srn (no tlyst) - Solvnt

More information

4 8 N v btr 20, 20 th r l f ff nt f l t. r t pl n f r th n tr t n f h h v lr d b n r d t, rd n t h h th t b t f l rd n t f th rld ll b n tr t d n R th

4 8 N v btr 20, 20 th r l f ff nt f l t. r t pl n f r th n tr t n f h h v lr d b n r d t, rd n t h h th t b t f l rd n t f th rld ll b n tr t d n R th n r t d n 20 2 :24 T P bl D n, l d t z d http:.h th tr t. r pd l 4 8 N v btr 20, 20 th r l f ff nt f l t. r t pl n f r th n tr t n f h h v lr d b n r d t, rd n t h h th t b t f l rd n t f th rld ll b n

More information

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2

CSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2 Am Blnk Ltur 0 Autumn 0 CSE 33: Dt Astrtons CSE 33 Grps : Wt s Grp? DFS n BFS Dt Astrtons LnkLsts r to Trs s Trs r to... A Grp s Tny... Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus, Hps, Vnll Trs,

More information

L.3922 M.C. L.3922 M.C. L.2996 M.C. L.3909 M.C. L.5632 M.C. L M.C. L.5632 M.C. L M.C. DRIVE STAR NORTH STAR NORTH NORTH DRIVE

L.3922 M.C. L.3922 M.C. L.2996 M.C. L.3909 M.C. L.5632 M.C. L M.C. L.5632 M.C. L M.C. DRIVE STAR NORTH STAR NORTH NORTH DRIVE N URY T NORTON PROV N RRONOUS NORTON NVRTNTY PROV. SPY S NY TY OR UT T TY RY OS NOT URNT T S TT T NORTON PROV S ORRT, NSR S POSS, VRY ORT S N ON N T S T TY RY. TS NORTON S N OP RO RORS RT SU "" YW No.

More information

PR D NT N n TR T F R 6 pr l 8 Th Pr d nt Th h t H h n t n, D D r r. Pr d nt: n J n r f th r d t r v th tr t d rn z t n pr r f th n t d t t. n

PR D NT N n TR T F R 6 pr l 8 Th Pr d nt Th h t H h n t n, D D r r. Pr d nt: n J n r f th r d t r v th tr t d rn z t n pr r f th n t d t t. n R P RT F TH PR D NT N N TR T F R N V R T F NN T V D 0 0 : R PR P R JT..P.. D 2 PR L 8 8 J PR D NT N n TR T F R 6 pr l 8 Th Pr d nt Th h t H h n t n, D.. 20 00 D r r. Pr d nt: n J n r f th r d t r v th

More information

22 t b r 2, 20 h r, th xp t d bl n nd t fr th b rd r t t. f r r z r t l n l th h r t rl T l t n b rd n n l h d, nd n nh rd f pp t t f r n. H v v d n f

22 t b r 2, 20 h r, th xp t d bl n nd t fr th b rd r t t. f r r z r t l n l th h r t rl T l t n b rd n n l h d, nd n nh rd f pp t t f r n. H v v d n f n r t d n 20 2 : 6 T P bl D n, l d t z d http:.h th tr t. r pd l 22 t b r 2, 20 h r, th xp t d bl n nd t fr th b rd r t t. f r r z r t l n l th h r t rl T l t n b rd n n l h d, nd n nh rd f pp t t f r

More information

4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n, h r th ff r d nd

4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n, h r th ff r d nd n r t d n 20 20 0 : 0 T P bl D n, l d t z d http:.h th tr t. r pd l 4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n,

More information

Fractions. Mathletics Instant Workbooks. Simplify. Copyright

Fractions. Mathletics Instant Workbooks. Simplify. Copyright Frctons Stunt Book - Srs H- Smplfy + Mthltcs Instnt Workbooks Copyrht Frctons Stunt Book - Srs H Contnts Topcs Topc - Equvlnt frctons Topc - Smplfyn frctons Topc - Propr frctons, mpropr frctons n mx numbrs

More information

Isomorphism In Kinematic Chains

Isomorphism In Kinematic Chains Intrntonl Journl o Rsr n Ennrn n Sn (IJRES) ISSN (Onln): 0-, ISSN (Prnt): 0- www.rs.or Volum Issu ǁ My. 0 ǁ PP.0- Isomorpsm In Knmt Cns Dr.Al Hsn Asstt.Prossor, Dprtmnt o Mnl Ennrn, F/O- Ennrn & Tnoloy,

More information

PRECAST APPROACH SLAB NOTES

PRECAST APPROACH SLAB NOTES ULNS TS ULN RWNS RPRSNT TYPL TLS OR T SN N TLN O PRST PPRO SLS. TS STS R NLU TO PROV N XMPL O T RTN LYOUT O TYPL PRST PPRO SL. TWO RNT PPRO SL SYSTMS R SOWN: SUR PPRO SLS: SLS TT R PL WT T TOP SUR T OR

More information

0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n. R v n n th r

0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n. R v n n th r n r t d n 20 22 0: T P bl D n, l d t z d http:.h th tr t. r pd l 0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n.

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

CHELOURANYAN CALENDAR FOR YEAR 3335 YEAR OF SAI RHAVË

CHELOURANYAN CALENDAR FOR YEAR 3335 YEAR OF SAI RHAVË CHELOURANYAN CALENDAR FOR YEAR YEAR OF SAI RHAVË I tou woust n unon wt our Motr, now tt tou st nvr t Hr. I tou woust sp t v o mttr, now tt tr s no mttr n no v. ~Cry Mry KEY TO CALENDAR T Dys o t W In t

More information

Using the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas

Using the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas SnNCutCnvs Using th Printl Stikr Funtion On-o--kin stikrs n sily rt y using your inkjt printr n th Dirt Cut untion o th SnNCut mhin. For inormtion on si oprtions o th SnNCutCnvs, rr to th Hlp. To viw th

More information

Tangram Fractions Overview: Students will analyze standard and nonstandard

Tangram Fractions Overview: Students will analyze standard and nonstandard ACTIVITY 1 Mtrils: Stunt opis o tnrm mstrs trnsprnis o tnrm mstrs sissors PROCEDURE Skills: Dsriin n nmin polyons Stuyin onrun Comprin rtions Tnrm Frtions Ovrviw: Stunts will nlyz stnr n nonstnr tnrms

More information

H NT Z N RT L 0 4 n f lt r h v d lt n r n, h p l," "Fl d nd fl d " ( n l d n l tr l t nt r t t n t nt t nt n fr n nl, th t l n r tr t nt. r d n f d rd n t th nd r nt r d t n th t th n r lth h v b n f

More information

BASIC CAGE DETAILS SHOWN 3D MODEL: PSM ASY INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY SPRING FINGERS CLOSED TOP

BASIC CAGE DETAILS SHOWN 3D MODEL: PSM ASY INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY SPRING FINGERS CLOSED TOP MO: PSM SY SI TIS SOWN SPRIN INRS OS TOP INNR W TS R OIN OVR S N OVR OR RIIITY. R TURS US WIT OPTION T SINS. R (UNOMPRSS) RR S OPTION (S T ON ST ) IMNSIONS O INNR SIN TO UNTION WIT QU SM ORM-TOR (zqsp+)

More information

24CKT POLARIZATION OPTIONS SHOWN BELOW ARE REPRESENTATIVE FOR 16 AND 20CKT

24CKT POLARIZATION OPTIONS SHOWN BELOW ARE REPRESENTATIVE FOR 16 AND 20CKT 0 NOTS: VI UNSS OTRWIS SPII IRUIT SMT USR R PORIZTION OPTION IRUIT SMT USR R PORIZTION OPTION IRUIT SMT USR R PORIZTION OPTION. NR: a. PPITION SPIITION S: S--00 b. PROUT SPIITION S: PS--00 c. PIN SPIITION

More information

( ) ( ) ( ) 0. Conservation of Energy & Poynting Theorem. From Maxwell s equations we have. M t. From above it can be shown (HW)

( ) ( ) ( ) 0. Conservation of Energy & Poynting Theorem. From Maxwell s equations we have. M t. From above it can be shown (HW) 8 Conson o n & Ponn To Fo wll s quons w D B σ σ Fo bo n b sown (W) o s W w bo on o s l us n su su ul ow ns [W/ ] [W] su P su B W W 4 444 s W A A s V A A : W W R o n o so n n: [/s W] W W 4 44 9 W : W F

More information

23 Minimum Spanning Trees

23 Minimum Spanning Trees 3 Mnmum Spnnn Trs Eltron rut sns otn n to mk t pns o svrl omponnts ltrlly quvlnt y wrn tm totr. To ntronnt st o n pns, w n us n rrnmnt o n wrs, onntn two pns. O ll su rrnmnts, t on tt uss t lst mount o

More information

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o

More information

Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v

Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v ll f x, h v nd d pr v n t fr tf l t th f nt r n r

More information

l f t n nd bj t nd x f r t l n nd rr n n th b nd p phl t f l br r. D, lv l, 8. h r t,., 8 6. http://hdl.handle.net/2027/miun.aey7382.0001.001 P bl D n http://www.hathitrust.org/access_use#pd Th r n th

More information

A ' / 1 6 " 5 ' / 4 " A4.2 48' - 0" 3 12' - 7" 13' - 11" 10' - 0" 9' - 0" 2' - 6" 1. 2: 12 INDICATES SHOW MELT TYP ABV ABV

A ' / 1 6  5 ' / 4  A4.2 48' - 0 3 12' - 7 13' - 11 10' - 0 9' - 0 2' - 6 1. 2: 12 INDICATES SHOW MELT TYP ABV ABV 4. 4. 4. K ' - / " ' - / 4 " 0 ' - / " ' - 0 " ' - 0 " ' - / " 4 ' - 0 " 4. M U PPR 48' - 0" ' - ' - " 0' - 0" ' - 0" ' - ". : WOM ' - 0 " OT: PROV URROU TR OUT SVS OR UTUR SP UTTY T OR QUSTR MPUS OTO

More information

SN54F280B, SN74F280B 9-BIT PARITY GENERATORS/CHECKERS

SN54F280B, SN74F280B 9-BIT PARITY GENERATORS/CHECKERS SN0, SN70 -T PRTY NRTORS/KRS SS00 3, PRL RVS OTOR 3 enerates ither Odd or ven Parity for Nine ata Lines ascadable for N-its Parity Package Options nclude Plastic Small-Outline Packages, eramic hip arriers,

More information

CEDAR ISLAND / KEATON BEACH TAYLOR COUNTY, FLORIDA POST-HURRICANE HERMINE EXAMINATION SURVEY FY16 4-FOOT PROJECT

CEDAR ISLAND / KEATON BEACH TAYLOR COUNTY, FLORIDA POST-HURRICANE HERMINE EXAMINATION SURVEY FY16 4-FOOT PROJECT 10 9 8 7 6 5 JUG ISLN R KL H R H R ROSMR LN W W HITTIL R JO MORGN R LRW TR RK R L M PNSOL GUL G O R G I TLLHSS JKSONVILL ORLNO OO TMP TLNTI ON N US rmy orps of ngineers Jacksonville istrict ST ON THIS

More information

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

,. *â â > V>V. â ND * 828.

,. *â â > V>V. â ND * 828. BL D,. *â â > V>V Z V L. XX. J N R â J N, 828. LL BL D, D NB R H â ND T. D LL, TR ND, L ND N. * 828. n r t d n 20 2 2 0 : 0 T http: hdl.h ndl.n t 202 dp. 0 02802 68 Th N : l nd r.. N > R, L X. Fn r f,

More information

16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am

16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am 16.unii Introution to Computrs n Prormmin SOLUTIONS to Exmintion /30/0 9:05m - 10:00m Pro. I. Kristin Lunqvist Sprin 00 Grin Stion: Qustion 1 (5) Qustion (15) Qustion 3 (10) Qustion (35) Qustion 5 (10)

More information

Minimum Spanning Trees (CLRS 23)

Minimum Spanning Trees (CLRS 23) Mnmum Spnnn Trs (CLRS 3) T prolm Gvn onnt, unrt rp G = (V, E), sust o s o G su tt ty onnt ll vrts n G n orm no yls s ll spnnn tr (ST) o G. Clm: Any unrt, onnt rp s spnnn tr (n nrl rp my v mny spnnn trs).

More information

BASIC CAGE DETAILS D C SHOWN CLOSED TOP SPRING FINGERS INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY

BASIC CAGE DETAILS D C SHOWN CLOSED TOP SPRING FINGERS INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY SI TIS SOWN OS TOP SPRIN INRS INNR W TS R OIN OVR S N OVR OR RIIITY. R IMNSIONS O INNR SIN TO UNTION WIT QU SM ORM-TOR (zqsp+) TRNSIVR. R. RR S OPTION (S T ON ST ) TURS US WIT OPTION T SINS. R (INSI TO

More information

OpenMx Matrices and Operators

OpenMx Matrices and Operators OpnMx Mtris n Oprtors Sr Mln Mtris: t uilin loks Mny typs? Dnots r lmnt mxmtrix( typ= Zro", nrow=, nol=, nm="" ) mxmtrix( typ= Unit", nrow=, nol=, nm="" ) mxmtrix( typ= Int", nrow=, nol=, nm="" ) mxmtrix(

More information

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely

(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely . DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,

More information

Data Mining in Bioinformatics Day 10: Graph Mining in Bioinformatics

Data Mining in Bioinformatics Day 10: Graph Mining in Bioinformatics Dt Mnn n Bonormts Dy 10: Grp Mnn n Bonormts Krstn Borwrt Frury 21 to Mr 4, 2011 Mn Lrnn & Computtonl Boloy Rsr Group MPIs Tünn wt prmsson rom Xn Yn n Xnon Jsmn Zou Krstn Borwrt: Dt Mnn n Bonormts, P 1

More information

SAMPLE LITANY OF THE SAINTS E/G. Dadd9/F. Aadd9. cy. Christ, have. Lord, have mer cy. Christ, have A/E. Dadd9. Aadd9/C Bm E. 1. Ma ry and. mer cy.

SAMPLE LITANY OF THE SAINTS E/G. Dadd9/F. Aadd9. cy. Christ, have. Lord, have mer cy. Christ, have A/E. Dadd9. Aadd9/C Bm E. 1. Ma ry and. mer cy. LTNY OF TH SNTS Cntrs Gnt flwng ( = c. 100) /G Ddd9/F ll Kybrd / hv Ddd9 hv hv Txt 1973, CL. ll rghts rsrvd. Usd wth prmssn. Musc: D. Bckr, b. 1953, 1987, D. Bckr. Publshd by OCP. ll rghts rsrvd. SMPL

More information

The Constrained Longest Common Subsequence Problem. Rotem.R and Rotem.H

The Constrained Longest Common Subsequence Problem. Rotem.R and Rotem.H T Constrn Lonst Common Susqun Prolm Rotm.R n Rotm.H Prsntton Outln. LCS Alortm Rmnr Uss o LCS Alortm T CLCS Prolm Introuton Motvton For CLCS Alortm T CLCS Prolm Nïv Alortm T CLCS Alortm A Dynm Prormmn

More information

Humanistic, and Particularly Classical, Studies as a Preparation for the Law

Humanistic, and Particularly Classical, Studies as a Preparation for the Law University of Michigan Law School University of Michigan Law School Scholarship Repository Articles Faculty Scholarship 1907 Humanistic, and Particularly Classical, Studies as a Preparation for the Law

More information

828.^ 2 F r, Br n, nd t h. n, v n lth h th n l nd h d n r d t n v l l n th f v r x t p th l ft. n ll n n n f lt ll th t p n nt r f d pp nt nt nd, th t

828.^ 2 F r, Br n, nd t h. n, v n lth h th n l nd h d n r d t n v l l n th f v r x t p th l ft. n ll n n n f lt ll th t p n nt r f d pp nt nt nd, th t 2Â F b. Th h ph rd l nd r. l X. TH H PH RD L ND R. L X. F r, Br n, nd t h. B th ttr h ph rd. n th l f p t r l l nd, t t d t, n n t n, nt r rl r th n th n r l t f th f th th r l, nd d r b t t f nn r r pr

More information

I N A C O M P L E X W O R L D

I N A C O M P L E X W O R L D IS L A M I C E C O N O M I C S I N A C O M P L E X W O R L D E x p l o r a t i o n s i n A g-b eanste d S i m u l a t i o n S a m i A l-s u w a i l e m 1 4 2 9 H 2 0 0 8 I s l a m i c D e v e l o p m e

More information

Applications of trees

Applications of trees Trs Apptons o trs Orgnzton rts Attk trs to syst Anyss o tr ntworks Prsng xprssons Trs (rtrv o norton) Don-n strutur Mutstng Dstnton-s orwrng Trnsprnt swts Forwrng ts o prxs t routrs Struturs or nt pntton

More information

d e c b a d c b a d e c b a a c a d c c e b

d e c b a d c b a d e c b a a c a d c c e b FLAT PEYOTE STITCH Bin y mkin stoppr -- sw trou n pull it lon t tr until it is out 6 rom t n. Sw trou t in witout splittin t tr. You soul l to sli it up n own t tr ut it will sty in pl wn lt lon. Evn-Count

More information

G-001 SACO SACO BAY BIDDEFORD INDEX OF NAVIGATION AIDS GENERAL NOTES: GENERAL PLAN A6 SCALE: 1" = 1000' CANADA MAINE STATE PLANE GEOGRAPHIC NO.

G-001 SACO SACO BAY BIDDEFORD INDEX OF NAVIGATION AIDS GENERAL NOTES: GENERAL PLAN A6 SCALE: 1 = 1000' CANADA MAINE STATE PLANE GEOGRAPHIC NO. 2 3 6 7 8 9 0 2 3 20000 230000 220000 ST TORY M 8-OOT W ST 2880000 2880000 L ROOK RL OTS: UKI OR TUR RKWTR (TYP) U O ROOK. SOUIS R I T TTS. T RR PL IS M LOWR LOW WTR (MLLW) IS S O T 983-200 TIL PO. SOUIS

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

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS

ECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS C 24 - COMBINATIONAL BUILDING BLOCKS - INVST 3 DCODS AND NCODS FALL 23 AP FLZ To o "wll" on this invstition you must not only t th riht nswrs ut must lso o nt, omplt n onis writups tht mk ovious wht h

More information

PLEASE DO NOT WRITE IN MARGINS. Part No. Specify Shipping Method:

PLEASE DO NOT WRITE IN MARGINS. Part No. Specify Shipping Method: ORR ORM USTOM PRSSUR GRMNTS SUMIT THIS ORM WITH LL ORRS, RORRS & LTRTIONS Numr ORR T PT N Y T SHIP TO Nw lty xstn Spy Sppn M: Grmnt(s) Orr Prt No. srpn Qty L Qty R Totl Qty MM//YYYY MM//YYYY RQUIR PTINT

More information

Appendix. In the absence of default risk, the benefit of the tax shield due to debt financing by the firm is 1 C E C

Appendix. In the absence of default risk, the benefit of the tax shield due to debt financing by the firm is 1 C E C nx. Dvon o h n wh In h sn o ul sk h n o h x shl u o nnng y h m s s h ol ouon s h num o ssus s h oo nom x s h sonl nom x n s h v x on quy whh s wgh vg o vn n l gns x s. In hs s h o sonl nom xs on h x shl

More information

FAMI-QS CODE VERSION 6

FAMI-QS CODE VERSION 6 Oprtor: FAMI-QS CODE VERSION 6 FAMI-QS Rstrton Numr: Dt o Aut: Autor: 4 Mnmnt Systm 4.1 Unrstnn t Oprtor n ts ontxt Ar xtrnl n ntrnl rsks trmn n oumnt? Ar xtrnl n ntrnl rsks rvw to nsur ontnul rlvn? Ar

More information

3V3 DECOUPLING DS90LV018A MCLKTON 4U7/10V +/-10% C196 +/-10% LCLK1IN+ NMCLKTON SK18 74LS123 MULTI +/-5% C N C94 10N

3V3 DECOUPLING DS90LV018A MCLKTON 4U7/10V +/-10% C196 +/-10% LCLK1IN+ NMCLKTON SK18 74LS123 MULTI +/-5% C N C94 10N 0 THIS RWG ONORMS TO.S. -T-0-00-0- U/0V +/-% 00N +/-0% 0N +/-0% U/0V +/-% 00N +/-0% 0 0N +/-0% R R 0R % P/0V +/-% K % U S YLLOW U 0 U U S0LV0 MLKTON /R S S R SK LS MULTI U/0V +/-% 00N +/-0% 0N +/-0% LLK+

More information

N V R T F L F RN P BL T N B ll t n f th D p rt nt f l V l., N., pp NDR. L N, d t r T N P F F L T RTL FR R N. B. P. H. Th t t d n t r n h r d r

N V R T F L F RN P BL T N B ll t n f th D p rt nt f l V l., N., pp NDR. L N, d t r T N P F F L T RTL FR R N. B. P. H. Th t t d n t r n h r d r n r t d n 20 2 04 2 :0 T http: hdl.h ndl.n t 202 dp. 0 02 000 N V R T F L F RN P BL T N B ll t n f th D p rt nt f l V l., N., pp. 2 24. NDR. L N, d t r T N P F F L T RTL FR R N. B. P. H. Th t t d n t r

More information

n

n p l p bl t n t t f Fl r d, D p rt nt f N t r l R r, D v n f nt r r R r, B r f l. n.24 80 T ll h, Fl. : Fl r d D p rt nt f N t r l R r, B r f l, 86. http://hdl.handle.net/2027/mdp.39015007497111 r t v n

More information

Decimals DECIMALS.

Decimals DECIMALS. Dimls DECIMALS www.mthltis.o.uk ow os it work? Solutions Dimls P qustions Pl vlu o imls 0 000 00 000 0 000 00 0 000 00 0 000 00 0 000 tnths or 0 thousnths or 000 hunrths or 00 hunrths or 00 0 tn thousnths

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

Telecommunications 1-1/4" RACEWAY WITH DOUBLE-GANG ADAPTER PLATE AND A/V CABLING.

Telecommunications 1-1/4 RACEWAY WITH DOUBLE-GANG ADAPTER PLATE AND A/V CABLING. 2 3 2 TNOOY SYMO ST NR TNOOY NOTS: NOT: This is a standard symbol list and not all items listed may be used. bbreviations () XSTN OV NS OOR NMW - UNRROUN ONUT T TORY ONTRTOR URNS ONTRTOR NST O ONTRTOR

More information