Different types of Domination in Intuitionistic Fuzzy Graph

Size: px
Start display at page:

Download "Different types of Domination in Intuitionistic Fuzzy Graph"

Transcription

1 Aals of Pur ad Appld Mathmatcs Vol, No, 07, 87-0 ISSN: X P, ol Publshd o July 07 wwwrsarchmathscorg DOI: Aals of Dffrt typs of Domato Itutostc Fuzzy Graph MGaruambga, SSasakar ad Palal 3 Dpartmt of Mathmatcs, Sr Vasa Collg Erod , Tamladu, Ida -mal:karusc@yahoo Dpartmt of Scc ad Humats, PES Ursty Bagalor , arataka, Ida 3 Dpartmt of Mathmatcs, Th Oxford Collg of Egrg Bagalor , arataka, Ida -mal: skars@gmalcom Corrspodg author -mal: sshakar@gmalcom Rcd Ju 07; accptd July 07 Abstract I ths papr, w troducd a dfto of dg domato st usg strog dgs ad dg dpdt sts of tutostc fuzzy graphs W dtrm th domato umbr γ G ad dg domato umbr γ G for sral classs of tutostc fuzzy graphs ad th rlato btw thm ar dscussd Also w troduc a rgular domatg st ad rgular dpdt st tutostc fuzzy graphs wth sutabl llustratos ywords: Edg domatg st IFG, dg domato umbr, dg dpdt st, rgular domato st AMS Mathmatcs Subct Classfcato 00: 05C7, 03E7, 03F55 Itroducto Th study of domatg sts graph was troducd by Or ad Brg 96 Th dg domato was troducd by Arumugam ad Vlammal [] Th dg domato problm has may applcatos rsourc allocato, twork routg ad codg thory problms [, 3] Somasudaram ad Somasudaram [7] troducd th cocpt of domato fuzzy graphs ad obta sral bouds for th domato umbr Domato fuzzy graphs usg strog dgs was dscussd by Nagoorga ad Chadraskara [8] Parath ad Thamzhdh [] troducd domatg st, domato umbr, dpdt st, total domatg ad total domato umbr tutostc fuzzy graphs Rsarch work of sral stgators [, 5, 6, 9, 3, 5, 6] ha motatd us to dlop th dffrt typs of domato tutostc fuzzy graphs Ths papr s orgazd as follows Scto cotas prlmars ad scto 3, a dg domato umbr ad dg dpdt umbr of a IFG s dfd usg 87

2 MGaruambga, SSasakar ad Palal strog dgs Scto dals wth proprts of dg domato IFGs ad th rlato btw domato umbr γ G ad dg domato umbr γ G Fally, w troducd rgular domatg st ad rgular dpdt st IFG scto 5 Prlmars Dfto [0] A tutostc fuzzy graph IFG s of th form 88 G V, E sad to b a mmax IFG f V {, } such that : V [0,] ad ν : V [0,], dot th dgr of mmbrshp ad o-mmbrshp of th lmt 0 + ν, for ry V,,,,, V rspctly ad E V V whr : V V [0,] ad ν : V V [0,], ar such that m[, ], ν max[ ν, ν ], dots th dgr of mmbrshp ad o-mmbrshp of th dg rspctly, whr + ν, for ry E 0 E For ach tutostc fuzzy graph G, th dgr of hstachstato dgr of th rtx V G s π ν ad th dgr of hstac hstato dgr of a dg E G s π ν Dfto [] A IFG, G V, E s sad to b complt IFG I m, ad ν max ν, ν for ry V Dfto 3 [] A IFG, G V, E s sad to b strog IFG f m, ad ν max ν, ν for ry E Dfto [] Th complmt of a IFG, G V, E s a IFG, G V, E, whr V V, ad ν ν, for all,,,, 3 m, ad ν max ν, ν ν for all,,,, Dfto 5 [7] Th ghbourhood dgr of a rtx s dfd as d d, d ν whr N N N d N ν w N w N w ad d N ν w

3 Dffrt typs of Domato Itutostc Fuzzy Graph Dfto 6 [8] Lt G V, E b a IFG Th th dgr of a rtx s dfd by d d, d, G ν whr d ad dν ν Dfto 7 [8] A tutostc fuzzy graph G V, E s sad to b a, -rgular f d, G for all V ad also G s sad to b a rgular tutostc fuzzy graph of dgr, Dfto 8 [] A tutostc fuzzy graph G V, E s sad to b a bpartt f th rtx st V ca b parttod to two o mpty sts V ad V such that 0 ad ν 0 f V or V > 0, ν < 0 f V or V, for som ad, or 0, ν < 0 f V or V, for som ad, or > 0, ν 0 f V or V, for som ad Dfto 9 [] A bpartt tutostc fuzzy graph G V, E s sad to b complt f m, ad ν max ν, ν for all V ad V ad s dotd by Dfto 0 [] If ad btw V, V V G, th -strgth of coctdss btw k s sup{ k,, } ad ν -strgth of coctdss ad k s ν f{ ν k,, } k If u ar coctd by mas of paths of lgth k th u, s dfd as sup u, u, } ad { 3 k k V k u, f { ν u, ν, ν, 3 ν k, u,, k, V ν s dfd as Dfto [] A dg u s sad to b a strog dg f u, u, ad ν u, ν u, } Dfto [] Lt G V, E b a IFG o V Lt u V, w say that u domats G f thr xsts a strog dg btw thm Dfto 3 [] A subst S of V s calld domatg st G f for ry V S, thr xsts u S such that u domats Dfto [] A domatg st S of a IFG s sad to b mmal domatg st f o propr subst of S s a domatg st 89

4 MGaruambga, SSasakar ad Palal Dfto 5 [] Mmum cardalty amog all mmal domatg st s calld rtx domato umbr of G ad s dotd by γ G Dfto 6 [] Lt G V, E b a IFG, th th rtx cardalty of V s dfd by + γ V for all V V Dfto 7 [] Lt G V, E b a IFG, th th dg cardalty of E s + γ dfd by E for all E E 3 Edg domato tutostc fuzzy graphs Th cocpt of dg domato graphs was troducd by Arumugam ad Vlammal 988 ad furthr dg domato ad dpdc fuzzy graphs s studd by Nagoorga ad Prasaa d W rfr to [] for th trmology of domato tutostc fuzzy graphs Dfto 3 Lt G V, E b a IFG Lt ad W say that domats f s a strog dg G b two adact dgs of G Dfto 3 A subst S of E s calld a dg domatg st G f for ry E S, thr xsts S such that domats Dfto 33 A dg domatg st S of a IFG s sad to b mmal dg domatg st f o propr subst of S s a dg domatg st Dfto 3 Mmum cardalty amog all mmal dg domatg st s calld dg domato umbr of G ad s dotd by γ G Dfto 35 Th strog ghbourhood of a dg a IFG G s N { E G s strog dg ad adact to G } s Exampl 3 Cosdr a IFG, G V, E, such that V {, } ad E {,,, 3, 3,, 3, 5,, 5,, 6, 6, } Fgur : 90

5 Dffrt typs of Domato Itutostc Fuzzy Graph Hr, },,, },, },,, },, } ar mmal dg domatg { { 5 sts of G ad γ G 07 { 5 { 7 { 6 7 Dfto 36 Lt E b a subst of dg st E Th th od cor of as th st of all rtcs cdt to ach dg E E s dfd Dfto 37 Two dgs ad G V, E f N ad s ar sad to b dg dpdt a IFG N s Dfto 38 A subst S of E s sad to b a tutostc fuzzy dg dpdt st of a IFG G f ay two dgs S ar dg dpdt Dfto 39 A dg dpdt st S of G a IFG s sad to b maxmal dpdt f for ry dg E S, th st S {} s ot dpdt Dfto 30 Th mmum cardalty amog all maxmal dg dpdt st s calld dg dpdc umbr of G ad t s dotd by β G Dfto 3 A dg IFG G s calld a solatd dg f t s ot adact to ay strog dg G Exampl 3 Cosdr a IFG, G V, E, such that V {, } ad E {,,, 3, 3,,,, 5,,, 5, } 3 5 Fgur : Hr, },, },, },, },, },, },, } ar maxmal { 3 { { { 5 9 { 3 5 dg dpdt sts of G ad β G 075 { 5 7 { 6 Dfto 3 If all th dgs ar strog dg a IFG th t s calld strgthd IFG Thorm 3 Nod cor of a dg domatg st of a IFG G s a domatg st of G Proof: Lt V b th od cor of a dg domatg st D of G W ha to pro that V s a domatg st of G Suppos V s ot a domatg st Th thr xsts atlast o rtx u whch

6 s ot domatg by th lmts of MGaruambga, SSasakar ad Palal V V dos ot cota ay rtx from N s u u for all Th D dos ot cota ay strog dg whch domats N s u Hc D s ot a dg domatg st of G Ths s a cotradcto Thrfor od cor of a dg domatg st of a IFG s a domatg st of G Thorm 3 Lt G b a IFG wthout solatd dgs ad thr xsts o dg E such that N s D If D s a mmal dg domatg st, th S D s a dg domatg st, whr S s th st of all strog dg G Proof: Lt D b a mmal dg domatg st of a IFG G Suppos S D s ot a dg domatg st Th thr xsts atlast o dg D whch s ot domatd by S D Sc G has o solatd dgs ad thr s o dg E such that N s D, s adact to atlast o strog dg dg domatg st of G, S D Hc D 9 S Sc S D s ot a Thrfor D { } s a dg domatg st whch s cotradcto to th fact that D s mmal dg domatg st Thus, ry dg E S s domatd by a dg S D Thrfor S D s a dg domatg st Thorm 33 A dg dpdt st of a IFG hag oly strog dgs s a maxmal dg dpdt st f ad oly f t s dg dpdt ad dg domatg st Proof: Lt S b a dg dpdt st of a IFG hag oly strog dgs Suppos S s a maxmal dg dpdt st of G Th for ry E S, th st S } s ot a dg dpdt st, for ry E S, thr s a dg { such that N Thus, S s a dg domatg st of G ad also t s a dg s dpdt st ofg Corsly, Suppos S s both dg dpdt ad dg domatg st of G W ha to pro that S s maxmal dg dpdt st hag oly strog dgs Sc S s a dg domatg st of G, t has oly strog dgs Assum that S s ot a maxmal dg dpdt st Th thr xsts a dg S such that S { } s a dg dpdt st, thr s o dg S blogg to N ad thrfor s ot domatd by S Hc S caot b a dg domatg st of G, whch s a cotradcto Hc S s a maxmal dg dpdt st ofg hag oly strog dgs Thorm 3 Ery maxmal dg dpdt st a IFG G hag oly strog dgs s a mmal dg domatg st of G Proof: Lt S b a maxmal dg dpdt st hag oly strog dgs of a IFG G s

7 Dffrt typs of Domato Itutostc Fuzzy Graph By Thorm 33, S s a dg domatg st of G Suppos S s ot a mmal dg domatg st of G Th thr xsts a dg S such that S { } s a dg domatg st Th atlast o dg S { } s N Ths cotradcts th fact that S s a dg dpdt st of G s Hc S s a mmal dg domatg st of G Thorm 35 Nod cor of a maxmal dg dpdt st of a IFG hag oly strog dgs s a domatg st of G Proof: Lt S b a maxmal dg dpdt st of a IFG G hag oly strog dgs Lt V b th od cor of S By Thorm 3, Ery maxmal dg dpdt st hag oly strog dgs s a mmal domatg st of G Th V s a od cor of a dg domatg st of a IFG G By Thorm 3, od cor of a dg domatg st of a IFG G s domatg st of G Hc V s a domatg st of G Thorm 36 Ery complt IFG s strgthd IFG Proof: Lt G V, E b a complt IFG By dfto of complt IFG u m u, ad ν u, max ν u, ν, for all u, V Suppos G has atlast o o strog u dg th u < u, ad ν u < ν u, whch mpls that u < m u, ad ν u, < max ν u, ν, for som u V Ths cotradcts our assumpto that G s complt IFG Thus, ry dg complt IFG s a strog dg Hc ry complt IFG s strgthd IFG Corollary 37 Ery strog IFG s a strgthd IFG Corollary 38 Ery slf complmtary IFG s a strgthd IFG Corollary 39 Ery complt bpartt IFG, s a strgthd IFG Thorm 30 Lt G V, E s a IFG ad f G s both rgular ad dg rgular IFG th, s a costat fucto ν Proof: Assum that G s both rgular ad dg rgular IFG By dfto of rgular IFG, d d, d, G ν V By dg rgular IFG, dg d, dν l, l E whr d d + d E l + 93

8 MGaruambga, SSasakar ad Palal l E ad d d + d ν E ν ν ν l + ν l ν E Hc, s a costat fucto ν Not Lt G V, E b a complt IFG wth, ν as a costat fucto ad f G s, rgular IFG th ad ν E Thorm 3 Lt G V, E b a slf complmtary IFG Th G s a, dg rgular IFG f ad oly f G s also, dg rgular IFG Proof: Sc G V, E s a slf complmtary IFG m, / ad ν max ν, ν / V By th dfto of complmt, m, ad ν max ν, ν ν V Thrfor m, / ad ν max ν, ν / V Hc ad ν ν Now d d, d G ν E k k E k + k k k d k k E k k E + k k d d Smlarly d d ν ν Thrfor d d E G G Hc G s, dg rgular IFG f ad oly f G s also, dg rgular IFG 9

9 Dffrt typs of Domato Itutostc Fuzzy Graph Rlato btw domato umbr γ G ad dg domato umbr γ G of a IFG Notato Lt P b th umbr of dgs mmum dg domatg st of Lmma P, wh s Proof: It ca b asly rfd that P ad P Wh 6, cosdr 6 Lt E 6 {,, 5} ad f P 6 th N ad N costtut 9 dgs ad sc E 6 5 th rmag 6 dgs ar ducd graph of G [ 3,, 5, 6] whch s clarly But P P 6 + P + + P tms Wh 8, cosdr 8 Lt E 8 {,, 8} ad f P 8 th N ad N costtut 3 dgs ad sc E 8 8 th rmag 5 dgs ar ducd graph of G [ 3,, 5, 6, 7, 8 ] whch s clarly 6 But P 6 3 P + P + + P tms 8 6 Smlarly, cosdr E {,, Lt } ad f P th N ad N costtut 3 dgs ad sc E th rmag dgs ar ducd graph of G, ] whch s [ clarly P + P [+ P [+ + P ] + [+ + + tms] + 6 P + Hc P, wh s Lmma P, wh s odd Proof: It ca b asly rfd that P 0 ad P 3 Wh 5, cosdr 5 Lt E 5 {,, 0} ad f P 5 th N ad N costtut 7 dgs ad sc E 5 0 th rmag 3 dgs ar ducd graph of G [ 3,, 5] whch s clarly 3 But P 3 P 5 + P P + tms Wh 7, cosdr 7 Lt E 7 {,, } ad f P 7 th N ad N costtut dgs ad sc E 7 th rmag 0 ] 95

10 MGaruambga, SSasakar ad Palal dgs ar ducd graph of G [ 3,, 5, 6, 7 ] whch s clarly 5 But P 5 P + P + + P tms Smlarly, cosdr Lt E {,, } ad f P th N ad N costtut 5 dgs ad sc E 3 th rmag dgs ar ducd graph of + G [,,, 3] whch s clarly 3 P P [+ + 7 P Hc P ] + [+ + + tms] P, wh s odd Lmma 3 If G V, E s a complt IFG th P m P m + P Proof: Cas Wh m ad s m + m P m+ + P m + P Cas Wh m s odd ad s m + m P m + P m + P + Rmark Th abo rsult s ot tru whr m ad s both odd + + Lmma For ay complt IFG, P + Proof: To pro P, w us th mthod of ducto Cas wh s odd For, P 0 s a sgl rtx Assum that th rsult s tru for all m +, w ha to pro for m + 3 m+ m + + P m + m P m + 3 P m+ + P By Lmma 3 P m + + m + Hc P m+ 3 s tru Cas wh s

11 Dffrt typs of Domato Itutostc Fuzzy Graph For, P s a dg Assum that th rsult s tru for m, w ha to pro for m + m m + P m m P m + P m + P By Lmma 3 m m + + P + + m + Hc P m+ s tru Hc th proof m + Lmma 5 If P dot th umbr of dgs mmal dg domatg st of complt graph th P + P, wh s P + P +, wh s odd Proof: Wh s P + P Hc P + P, wh s Wh s odd + P P + Hc P P +, wh s odd Thorm 6 For a complt IFG G wth rtcs, s, s odd whr γ G ad γ G s th mmum cardalty of th rtx ad dg domatg st +

12 MGaruambga, SSasakar ad Palal Proof: Lt G V, E b a complt IFG wth By Thorm 36, G s strgthd IFG If w choos a dg u th t wll domat all th dgs cdt to u ad Th st of dgs u whr o two of thm has a rtx commo forms a mmal dg domatg st Mmum cardalty of dg domatg st s γ G Sc G s complt IFG, mmum cardalty of rtx domatg st wll b oly o rtx ad t s γ G If s, th P cotas dgs By Lmma γ G s th sum of mmum cardalty of dgs ad γ G s a mmum cardalty of a rtx Sc G s complt IFG, th dgs assocatd wth γ G wll ha mmum cardalty Hc th sum of mmum cardalty of dg domatg st γ G γ G Smlarly, f s odd, th P cotas dgs By Lmma ad γ G γ G Hc th rsult Thorm 7 If G V, E s a complt IFG th γ G < γ G f > 3 Proof: Assum that G V, E s a complt IFG Th ry dg G s strog dg γ G s th mmum cardalty of a rtx + By Lmma, P cotas dgs + γ G s th sum of mmum cardalty of If > 3 th γ G cotas mor tha o dg Hc γ G < γ G dgs Not Lt G V, E s a complt IFG wth, as costat fucto ad 3 th γ G γ G ν Not 3 If G s dg rgular IFG wth, ν as costat fucto th G s dg rgular IFG Rmark If γ G ad γ G s domato umbr ad dg domato umbr of a IFG wth > 3 th 98

13 Dffrt typs of Domato Itutostc Fuzzy Graph γ G γ G < γ G, s γ G γ G < γ G, s odd Thorm 8 Lt G V, E b a slf complmtary IFG th γ G γ G Proof: Sc G s slf complmtary IFG Ery dg slf complmtary IFG s a strog dg ad ad ν ν Also G s somorphc to G Thrfor mmum cardalty of dg domatg st of G ad G rmas sam Hc γ G γ G Thorm 9 Lt G V, E b a complt bpartt IFG, ad f G s both rgular ad dg rgular IFG th γ G γ G Proof: G G V, E b a complt bpartt IFG, th ry dg G s a strog dg Assum that G s both rgular ad dg rgular IFG By Thorm 30,, s a costat fucto th th rtx domato umbr γ G u, ν ad th dg domato umbr γ G u, Hc γ G γ G 5 Rgular domato tutostc fuzzy graphs Dfto 5 Lt G V, E b a IFG A st S subst of V s calld rgular tutostc fuzzy domatg st f ry rtx V S s adact to som rtx S all th rtcs S has th sam dgr Exampl 5 Cosdr a IFG, G V, E, such that V {, } ad E {,,, 3, 3, 6,,, 5, 5, 6} Fgur 3: 99

14 MGaruambga, SSasakar ad Palal Dfto 5 Th mmum cardalty of rgular tutostc fuzzy domatg st s calld rgular tutostc fuzzy domatg umbr ad dotd by γ G 08 Dfto 53 A st S subst of V s calld mmal rgular tutostc fuzzy domatg st f Ay subst of S s ot a tutostc fuzzy domatg st all th rtcs of S ha th sam dgr Dfto 5 A dpdt st S of a IFG G V, E s sad to b rgular dpdt IFG f all th rtcs of S has th sam dgr Dfto 55 A st S s maxmal rgular dpdt st f for ry rtx th st S {} s ot rgular dpdt st Exampl 5 Cosdr a IFG, G V, E, such that V {, } ad E {,, 3, 3,,, } rf 3 V S Fgur : Hr, }, } s a rgular dpdt st { 3 { Thorm 5 A rgular dpdt st s a rgular maxmal dpdt st of a IFG f ad oly f t s rgular dpdt ad rgular domatg st Proof: Lt S b a rgular maxmal dpdt st a IFG, th for ry u V S, th st S {u} s ot a dpdt st, for ry u V S, thr s a rtx S such that u s adact to Thus, S s domatg st of G ad also rgular dpdt st of G Hc S s rgular dpdt ad rgular domatg st Corsly, Suppos S s both rgular dpdt ad rgular domatg st of G W ha to pro that S s rgular mxmal dpdt st Assum that S s ot a maxmal dpdt st Th thr xsts a rtx u S such that S {u} s a dpdt st, thr s o rtx S adact to u ad thrfor u s ot domatd by S Hc S caot b a domatg st of G, whch s cotradcto Hc S s maxmal dpdt Thus S s rgular maxmal dpdt st Thorm 5 Ery rgular maxmal dpdt st a IFG G s a rgular mmal domatg st of G Proof: Lt S b a rgular maxmal dpdt st a IFG By Thorm 5, S s 00

15 Dffrt typs of Domato Itutostc Fuzzy Graph rgular domatg st of G Suppos S s ot a mmal domatg st of G Th thr xsts atlast o rtx S such that S {} s domatg st Th atlast o rtx S {} s adact to Ths cotradcts th fact that S s rgular dpdt st of G Hc S s rgular mmal domatg st of G REFERENCES SArumugam ad SVlammal, Edg domato graphs, Tawas Joural of Mathmatcs, Ataasso, Itutostc fuzzy sts: Thory ad applcatos, studs fuzzss ad soft computg, Hdlbrg, Nw York, Physca-Vrl, GJChag, Algorthmc aspcts of domato graphs, : DZ Du, PM Pardalos Eds, Hadbook of Combatoral Optmzato, Vol 3, luwr, Bosto, MA, 998, MGaruambga, SSasakar ad Palal, Som proprts of a rgular tutostc fuzzy graph, Itratoal Joural of Mathmatcs ad Computato, MGaruambga, Palal ad SSasakar, Edg rgular tutostc fuzzy graph, Adacs Fuzzy Sts ad Systms, OTMausha ad MSSutha, Strog domato fuzzy graphs, Fuzzy Iformato ad Egrg, ANagoorga ad S Shatha Bgum, Dgr, ordr ad sz tutostc fuzzy graphs, Itratoal Joural of Algorthms, Computg ad Mathmatcs, ANagoorga ad VTChadraskara, Domato fuzzy graph, Adacs Fuzzy Sts ad Systm, ANagoorga ad Prasaa D, Edg domato ad dpdc fuzzy graphs, Adacs Fuzzy Sts ad Systms, RParath ad MGaruambga, Itutostc fuzzy graphs, Computatoal Itllgc, Thory ad applcatos, RParath, MGaruambga ad Ataasso, Opratos o tutostc fuzzy graphs, Procdgs of IEEE Itratoal Cofrc Fuzzy Systms FUZZ-IEEE, RParath ad GThamzhdh, Domato tutostc fuzzy graphs, Nots o Itutostc Fuzzy Sts, Radha ad Numaral, O dg rgular fuzzy graphs, Itratoal Joural of Mathmatcal Arch, ARosfld, Fuzzy graphs, I Fuzzy Sts ad Thr Applcatos to Cogt ad Dcso Procsss, Acadmc Prss, SSahoo ad MPal, Itutostc fuzzy comptto graphs, Joural of Appld Mathmatcs ad Computg, SSahoo ad MPal, Product of tutostc fuzzy graphs ad dgr, Joural of Itllgt ad Fuzzy Systms, ASomasudaram ad SSomasudaram, Domato fuzzy graphs-i, Pattr Rcogto Lttrs,

Independent Domination in Line Graphs

Independent Domination in Line Graphs Itratoal Joural of Sctfc & Egrg Rsarch Volum 3 Issu 6 Ju-1 1 ISSN 9-5518 Iddt Domato L Grahs M H Muddbhal ad D Basavarajaa Abstract - For ay grah G th l grah L G H s th trscto grah Thus th vrtcs of LG

More information

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are

Total Prime Graph. Abstract: We introduce a new type of labeling known as Total Prime Labeling. Graphs which admit a Total Prime labeling are Itratoal Joural Of Computatoal Egrg Rsarch (crol.com) Vol. Issu. 5 Total Prm Graph M.Rav (a) Ramasubramaa 1, R.Kala 1 Dpt.of Mathmatcs, Sr Shakth Isttut of Egrg & Tchology, Combator 641 06. Dpt. of Mathmatcs,

More information

Reliability of time dependent stress-strength system for various distributions

Reliability of time dependent stress-strength system for various distributions IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,

More information

Almost all Cayley Graphs Are Hamiltonian

Almost all Cayley Graphs Are Hamiltonian Acta Mathmatca Sca, Nw Srs 199, Vol1, No, pp 151 155 Almost all Cayly Graphs Ar Hamltoa Mg Jxag & Huag Qogxag Abstract It has b cocturd that thr s a hamltoa cycl vry ft coctd Cayly graph I spt of th dffculty

More information

ON THE COMPLEXITY OF K-STEP AND K-HOP DOMINATING SETS IN GRAPHS

ON THE COMPLEXITY OF K-STEP AND K-HOP DOMINATING SETS IN GRAPHS MATEMATICA MONTISNIRI Vol XL (2017) MATEMATICS ON TE COMPLEXITY OF K-STEP AN K-OP OMINATIN SETS IN RAPS M FARAI JALALVAN AN N JAFARI RA partmnt of Mathmatcs Shahrood Unrsty of Tchnology Shahrood Iran Emals:

More information

A Measure of Inaccuracy between Two Fuzzy Sets

A Measure of Inaccuracy between Two Fuzzy Sets LGRN DEMY OF SENES YERNETS ND NFORMTON TEHNOLOGES Volum No 2 Sofa 20 Masur of accuracy btw Two Fuzzy Sts Rajkumar Vrma hu Dv Sharma Dpartmt of Mathmatcs Jayp sttut of formato Tchoy (Dmd vrsty) Noda (.P.)

More information

Chiang Mai J. Sci. 2014; 41(2) 457 ( 2) ( ) ( ) forms a simply periodic Proof. Let q be a positive integer. Since

Chiang Mai J. Sci. 2014; 41(2) 457 ( 2) ( ) ( ) forms a simply periodic Proof. Let q be a positive integer. Since 56 Chag Ma J Sc 0; () Chag Ma J Sc 0; () : 56-6 http://pgscccmuacth/joural/ Cotrbutd Papr Th Padova Sucs Ft Groups Sat Taș* ad Erdal Karaduma Dpartmt of Mathmatcs, Faculty of Scc, Atatürk Uvrsty, 50 Erzurum,

More information

Bayesian Shrinkage Estimator for the Scale Parameter of Exponential Distribution under Improper Prior Distribution

Bayesian Shrinkage Estimator for the Scale Parameter of Exponential Distribution under Improper Prior Distribution Itratoal Joural of Statstcs ad Applcatos, (3): 35-3 DOI:.593/j.statstcs.3. Baysa Shrkag Estmator for th Scal Paramtr of Expotal Dstrbuto udr Impropr Pror Dstrbuto Abbas Najm Salma *, Rada Al Sharf Dpartmt

More information

In 1991 Fermat s Last Theorem Has Been Proved

In 1991 Fermat s Last Theorem Has Been Proved I 99 Frmat s Last Thorm Has B Provd Chu-Xua Jag P.O.Box 94Bg 00854Cha Jcxua00@s.com;cxxxx@6.com bstract I 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES

COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES COMPLEX NUMBERS AND ELEMENTARY FUNCTIONS OF COMPLEX VARIABLES DEFINITION OF A COMPLEX NUMBER: A umbr of th form, whr = (, ad & ar ral umbrs s calld a compl umbr Th ral umbr, s calld ral part of whl s calld

More information

International Journal of Mathematical Archive-6(5), 2015, Available online through ISSN

International Journal of Mathematical Archive-6(5), 2015, Available online through  ISSN Itratoal Joural of Mathmatal Arhv-6), 0, 07- Avalabl ol through wwwjmafo ISSN 9 06 ON THE LINE-CUT TRANSFORMATION RAPHS B BASAVANAOUD*, VEENA R DESAI Dartmt of Mathmats, Karatak Uvrsty, Dharwad - 80 003,

More information

Aotomorphic Functions And Fermat s Last Theorem(4)

Aotomorphic Functions And Fermat s Last Theorem(4) otomorphc Fuctos d Frmat s Last Thorm(4) Chu-Xua Jag P. O. Box 94 Bg 00854 P. R. Cha agchuxua@sohu.com bsract 67 Frmat wrot: It s mpossbl to sparat a cub to two cubs or a bquadrat to two bquadrats or gral

More information

The Equitable Dominating Graph

The Equitable Dominating Graph Intrnational Journal of Enginring Rsarch and Tchnology. ISSN 0974-3154 Volum 8, Numbr 1 (015), pp. 35-4 Intrnational Rsarch Publication Hous http://www.irphous.com Th Equitabl Dominating Graph P.N. Vinay

More information

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis

Department of Mathematics and Statistics Indian Institute of Technology Kanpur MSO202A/MSO202 Assignment 3 Solutions Introduction To Complex Analysis Dpartmt of Mathmatcs ad Statstcs Ida Isttut of Tchology Kapur MSOA/MSO Assgmt 3 Solutos Itroducto To omplx Aalyss Th problms markd (T) d a xplct dscusso th tutoral class. Othr problms ar for hacd practc..

More information

3.4 Properties of the Stress Tensor

3.4 Properties of the Stress Tensor cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato

More information

Repeated Trials: We perform both experiments. Our space now is: Hence: We now can define a Cartesian Product Space.

Repeated Trials: We perform both experiments. Our space now is: Hence: We now can define a Cartesian Product Space. Rpatd Trals: As w hav lood at t, th thory of probablty dals wth outcoms of sgl xprmts. I th applcatos o s usually trstd two or mor xprmts or rpatd prformac or th sam xprmt. I ordr to aalyz such problms

More information

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays

Group Consensus of Second-Order Multi-agent Networks with Multiple Time Delays Itratoal Cofrc o Appld Mathmatcs, Smulato ad Modllg (AMSM 6) Group Cossus of Scod-Ordr Mult-agt Ntworks wth Multpl Tm Dlays Laghao J* ad Xyu Zhao Chogqg Ky Laboratory of Computatoal Itllgc, Chogqg Uvrsty

More information

Counting the compositions of a positive integer n using Generating Functions Start with, 1. x = 3 ), the number of compositions of 4.

Counting the compositions of a positive integer n using Generating Functions Start with, 1. x = 3 ), the number of compositions of 4. Coutg th compostos of a postv tgr usg Gratg Fuctos Start wth,... - Whr, for ampl, th co-ff of s, for o summad composto of aml,. To obta umbr of compostos of, w d th co-ff of (...) ( ) ( ) Hr for stac w

More information

Iranian Journal of Mathematical Chemistry, Vol. 2, No. 2, December 2011, pp (Received September 10, 2011) ABSTRACT

Iranian Journal of Mathematical Chemistry, Vol. 2, No. 2, December 2011, pp (Received September 10, 2011) ABSTRACT Iraa Joral of Mathatcal Chstry Vol No Dcbr 0 09 7 IJMC Two Tys of Gotrc Arthtc dx of V hylc Naotb S MORADI S BABARAHIM AND M GHORBANI Dartt of Mathatcs Faclty of Scc Arak Ursty Arak 856-8-89 I R Ira Dartt

More information

Introduction to logistic regression

Introduction to logistic regression Itroducto to logstc rgrsso Gv: datast D { 2 2... } whr s a k-dmsoal vctor of ral-valud faturs or attrbuts ad s a bar class labl or targt. hus w ca sa that R k ad {0 }. For ampl f k 4 a datast of 3 data

More information

Lecture 1: Empirical economic relations

Lecture 1: Empirical economic relations Ecoomcs 53 Lctur : Emprcal coomc rlatos What s coomtrcs? Ecoomtrcs s masurmt of coomc rlatos. W d to kow What s a coomc rlato? How do w masur such a rlato? Dfto: A coomc rlato s a rlato btw coomc varabls.

More information

Numerical Method: Finite difference scheme

Numerical Method: Finite difference scheme Numrcal Mthod: Ft dffrc schm Taylor s srs f(x 3 f(x f '(x f ''(x f '''(x...(1! 3! f(x 3 f(x f '(x f ''(x f '''(x...(! 3! whr > 0 from (1, f(x f(x f '(x R Droppg R, f(x f(x f '(x Forward dffrcg O ( x from

More information

On the Possible Coding Principles of DNA & I Ching

On the Possible Coding Principles of DNA & I Ching Sctfc GOD Joural May 015 Volum 6 Issu 4 pp. 161-166 Hu, H. & Wu, M., O th Possbl Codg Prcpls of DNA & I Chg 161 O th Possbl Codg Prcpls of DNA & I Chg Hupg Hu * & Maox Wu Rvw Artcl ABSTRACT I ths rvw artcl,

More information

Adagba O Henry /International Journal Of Computational Engineering Research / ISSN: OPERATION ON IDEALS

Adagba O Henry /International Journal Of Computational Engineering Research / ISSN: OPERATION ON IDEALS Adagba O Hry /Itratoal Joural Of Computatoal Egrg Rsarh / ISSN 50 3005 OPERATION ON IDEALS Adagba O Hry, Dpt of Idustral Mathmats & Appld Statsts, Eboy Stat Uvrsty, Abakalk Abstrat W provd bas opratos

More information

Advances of Clar's Aromatic Sextet Theory and Randic 's Conjugated Circuit Model

Advances of Clar's Aromatic Sextet Theory and Randic 's Conjugated Circuit Model Th Op Orgac hmstry Joural 0 5 (Suppl -M6) 87-87 Op Accss Advacs of lar's Aromatc Sxtt Thory ad Radc 's ougatd rcut Modl Fu Zhag a Xaofg Guo a ad Hpg Zhag b a School of Mathmatcal Sccs Xam Uvrsty Xam Fua

More information

Second Handout: The Measurement of Income Inequality: Basic Concepts

Second Handout: The Measurement of Income Inequality: Basic Concepts Scod Hadout: Th Masurmt of Icom Iqualty: Basc Cocpts O th ormatv approach to qualty masurmt ad th cocpt of "qually dstrbutd quvalt lvl of com" Suppos that that thr ar oly two dvduals socty, Rachl ad Mart

More information

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1

The probability of Riemann's hypothesis being true is. equal to 1. Yuyang Zhu 1 Th robablty of Ra's hyothss bg tru s ual to Yuyag Zhu Abstract Lt P b th st of all r ubrs P b th -th ( ) lt of P ascdg ordr of sz b ostv tgrs ad s a rutato of wth Th followg rsults ar gv ths ar: () Th

More information

Further Results on Pair Sum Graphs

Further Results on Pair Sum Graphs Applid Mathmatis, 0,, 67-75 http://dx.doi.org/0.46/am.0.04 Publishd Oli Marh 0 (http://www.sirp.org/joural/am) Furthr Rsults o Pair Sum Graphs Raja Poraj, Jyaraj Vijaya Xavir Parthipa, Rukhmoi Kala Dpartmt

More information

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data

On Estimation of Unknown Parameters of Exponential- Logarithmic Distribution by Censored Data saqartvlos mcrbata rovul akadms moamb, t 9, #2, 2015 BULLETIN OF THE GEORGIAN NATIONAL ACADEMY OF SCIENCES, vol 9, o 2, 2015 Mathmatcs O Estmato of Ukow Paramtrs of Epotal- Logarthmc Dstrbuto by Csord

More information

The real E-k diagram of Si is more complicated (indirect semiconductor). The bottom of E C and top of E V appear for different values of k.

The real E-k diagram of Si is more complicated (indirect semiconductor). The bottom of E C and top of E V appear for different values of k. Modr Smcoductor Dvcs for Itgratd rcuts haptr. lctros ad Hols Smcoductors or a bad ctrd at k=0, th -k rlatoshp ar th mmum s usually parabolc: m = k * m* d / dk d / dk gatv gatv ffctv mass Wdr small d /

More information

Basic Polyhedral theory

Basic Polyhedral theory Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist

More information

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca**

ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca** ERDO-MARANDACHE NUMBER b Tbrc* Tt Tbrc** *Trslv Uvrsty of Brsov, Computr cc Dprtmt **Uvrsty of Mchstr, Computr cc Dprtmt Th strtg pot of ths rtcl s rprstd by rct work of Fch []. Bsd o two symptotc rsults

More information

Section 6.1. Question: 2. Let H be a subgroup of a group G. Then H operates on G by left multiplication. Describe the orbits for this operation.

Section 6.1. Question: 2. Let H be a subgroup of a group G. Then H operates on G by left multiplication. Describe the orbits for this operation. MAT 444 H Barclo Spring 004 Homwork 6 Solutions Sction 6 Lt H b a subgroup of a group G Thn H oprats on G by lft multiplication Dscrib th orbits for this opration Th orbits of G ar th right costs of H

More information

Statistical Thermodynamics Essential Concepts. (Boltzmann Population, Partition Functions, Entropy, Enthalpy, Free Energy) - lecture 5 -

Statistical Thermodynamics Essential Concepts. (Boltzmann Population, Partition Functions, Entropy, Enthalpy, Free Energy) - lecture 5 - Statstcal Thrmodyamcs sstal Cocpts (Boltzma Populato, Partto Fuctos, tropy, thalpy, Fr rgy) - lctur 5 - uatum mchacs of atoms ad molculs STATISTICAL MCHANICS ulbrum Proprts: Thrmodyamcs MACROSCOPIC Proprts

More information

ASYMPTOTIC AND TOLERANCE 2D-MODELLING IN ELASTODYNAMICS OF CERTAIN THIN-WALLED STRUCTURES

ASYMPTOTIC AND TOLERANCE 2D-MODELLING IN ELASTODYNAMICS OF CERTAIN THIN-WALLED STRUCTURES AYMPTOTIC AD TOLERACE D-MODELLIG I ELATODYAMIC OF CERTAI THI-WALLED TRUCTURE B. MICHALAK Cz. WOŹIAK Dpartmt of tructural Mchacs Lodz Uvrsty of Tchology Al. Poltrchk 6 90-94 Łódź Polad Th objct of aalyss

More information

On Approximation Lower Bounds for TSP with Bounded Metrics

On Approximation Lower Bounds for TSP with Bounded Metrics O Approxmato Lowr Bouds for TSP wth Boudd Mtrcs Mark Karpsk Rchard Schmd Abstract W dvlop a w mthod for provg xplct approxmato lowr bouds for TSP problms wth boudd mtrcs mprovg o th bst up to ow kow bouds.

More information

Frequency hopping sequences with optimal partial Hamming correlation

Frequency hopping sequences with optimal partial Hamming correlation 1 Frqucy hoppg squcs wth optmal partal Hammg corrlato Jgju Bao ad ju J arxv:1511.02924v2 [cs.it] 11 Nov 2015 Abstract Frqucy hoppg squcs (FHSs) wth favorabl partal Hammg corrlato proprts hav mportat applcatos

More information

Strongly Connected Components

Strongly Connected Components Strongly Connctd Componnts Lt G = (V, E) b a dirctd graph Writ if thr is a path from to in G Writ if and is an quivalnc rlation: implis and implis s quivalnc classs ar calld th strongly connctd componnts

More information

ON RIGHT(LEFT) DUO PO-SEMIGROUPS. S. K. Lee and K. Y. Park

ON RIGHT(LEFT) DUO PO-SEMIGROUPS. S. K. Lee and K. Y. Park Kangwon-Kyungki Math. Jour. 11 (2003), No. 2, pp. 147 153 ON RIGHT(LEFT) DUO PO-SEMIGROUPS S. K. L and K. Y. Park Abstract. W invstigat som proprtis on right(rsp. lft) duo po-smigroups. 1. Introduction

More information

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt

More information

Suzan Mahmoud Mohammed Faculty of science, Helwan University

Suzan Mahmoud Mohammed Faculty of science, Helwan University Europa Joural of Statstcs ad Probablty Vol.3, No., pp.4-37, Ju 015 Publshd by Europa Ctr for Rsarch Trag ad Dvlopmt UK (www.ajourals.org ESTIMATION OF PARAMETERS OF THE MARSHALL-OLKIN WEIBULL DISTRIBUTION

More information

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP)

Complex Numbers. Prepared by: Prof. Sunil Department of Mathematics NIT Hamirpur (HP) th Topc Compl Nmbrs Hyprbolc fctos ad Ivrs hyprbolc fctos, Rlato btw hyprbolc ad crclar fctos, Formla of hyprbolc fctos, Ivrs hyprbolc fctos Prpard by: Prof Sl Dpartmt of Mathmatcs NIT Hamrpr (HP) Hyprbolc

More information

Unbalanced Panel Data Models

Unbalanced Panel Data Models Ubalacd Pal Data odls Chaptr 9 from Baltag: Ecoomtrc Aalyss of Pal Data 5 by Adrás alascs 4448 troducto balacd or complt pals: a pal data st whr data/obsrvatos ar avalabl for all crosssctoal uts th tr

More information

JOURNAL OF COLLEGE OF EDUCATION NO

JOURNAL OF COLLEGE OF EDUCATION NO NO.3...... 07 Ivrt S-bst Copproxmto -ormd Spcs Slw Slm bd Dprtmt of Mthmtcs Collg of ducto For Pur scc, Ib l-hthm, Uvrsty of Bghdd slwlbud@yhoo.com l Musddk Dlph Dprtmt of Mthmtcs,Collg of Bsc ducto, Uvrsty

More information

Washington State University

Washington State University he 3 Ktics ad Ractor Dsig Sprg, 00 Washgto Stat Uivrsity Dpartmt of hmical Egrg Richard L. Zollars Exam # You will hav o hour (60 muts) to complt this xam which cosists of four (4) problms. You may us

More information

SOME PARAMETERS ON EQUITABLE COLORING OF PRISM AND CIRCULANT GRAPH.

SOME PARAMETERS ON EQUITABLE COLORING OF PRISM AND CIRCULANT GRAPH. SOME PARAMETERS ON EQUITABLE COLORING OF PRISM AND CIRCULANT GRAPH. K VASUDEVAN, K. SWATHY AND K. MANIKANDAN 1 Dpartmnt of Mathmatics, Prsidncy Collg, Chnnai-05, India. E-Mail:vasu k dvan@yahoo.com. 2,

More information

Non-uniform Turán-type problems

Non-uniform Turán-type problems Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at

More information

Combinatorial Networks Week 1, March 11-12

Combinatorial Networks Week 1, March 11-12 1 Nots on March 11 Combinatorial Ntwors W 1, March 11-1 11 Th Pigonhol Principl Th Pigonhol Principl If n objcts ar placd in hols, whr n >, thr xists a box with mor than on objcts 11 Thorm Givn a simpl

More information

NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES

NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES Digst Joural of Naomatrials ad Biostructurs Vol 4, No, March 009, p 67-76 NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES A IRANMANESH a*, O KHORMALI b, I NAJAFI KHALILSARAEE c, B SOLEIMANI

More information

Some Results on E - Cordial Graphs

Some Results on E - Cordial Graphs Intrnational Journal of Mathmatics Trnds and Tchnology Volum 7 Numbr 2 March 24 Som Rsults on E - Cordial Graphs S.Vnkatsh, Jamal Salah 2, G.Sthuraman 3 Corrsponding author, Dpartmnt of Basic Scincs, Collg

More information

Channel Capacity Course - Information Theory - Tetsuo Asano and Tad matsumoto {t-asano,

Channel Capacity Course - Information Theory - Tetsuo Asano and Tad matsumoto   {t-asano, School of Iformato Scc Chal Capacty 009 - Cours - Iformato Thory - Ttsuo Asao ad Tad matsumoto Emal: {t-asao matumoto}@jast.ac.jp Japa Advacd Isttut of Scc ad Tchology Asahda - Nom Ishkawa 93-9 Japa http://www.jast.ac.jp

More information

Correlation in tree The (ferromagnetic) Ising model

Correlation in tree The (ferromagnetic) Ising model 5/3/00 :\ jh\slf\nots.oc\7 Chaptr 7 Blf propagato corrlato tr Corrlato tr Th (frromagtc) Isg mol Th Isg mol s a graphcal mol or par ws raom Markov fl cosstg of a urct graph wth varabls assocat wth th vrtcs.

More information

PURE MATHEMATICS A-LEVEL PAPER 1

PURE MATHEMATICS A-LEVEL PAPER 1 -AL P MATH PAPER HONG KONG EXAMINATIONS AUTHORITY HONG KONG ADVANCED LEVEL EXAMINATION PURE MATHEMATICS A-LEVEL PAPER 8 am am ( hours) This papr must b aswrd i Eglish This papr cosists of Sctio A ad Sctio

More information

International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.8, No.3, May Amin Ghodousian *

International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.8, No.3, May Amin Ghodousian * AN ALGORIHM OR SOLVING LINEAR OPIMIZAION PROBLEMS SUBJECE O HE INERSECION O WO UZZY RELAIONAL INEQUALIIES EINE BY RANK AMILY O -NORMS Am Ghodoua aculty of Egrg Scc, Collg of Egrg, Uvrty of hra, POBox 365-4563,

More information

FOURIER SERIES. Series expansions are a ubiquitous tool of science and engineering. The kinds of

FOURIER SERIES. Series expansions are a ubiquitous tool of science and engineering. The kinds of Do Bgyoko () FOURIER SERIES I. INTRODUCTION Srs psos r ubqutous too o scc d grg. Th kds o pso to utz dpd o () th proprts o th uctos to b studd d (b) th proprts or chrctrstcs o th systm udr vstgto. Powr

More information

Section 5.1/5.2: Areas and Distances the Definite Integral

Section 5.1/5.2: Areas and Distances the Definite Integral Scto./.: Ars d Dstcs th Dt Itgrl Sgm Notto Prctc HW rom Stwrt Ttook ot to hd p. #,, 9 p. 6 #,, 9- odd, - odd Th sum o trms,,, s wrtt s, whr th d o summto Empl : Fd th sum. Soluto: Th Dt Itgrl Suppos w

More information

MODEL QUESTION. Statistics (Theory) (New Syllabus) dx OR, If M is the mode of a discrete probability distribution with mass function f

MODEL QUESTION. Statistics (Theory) (New Syllabus) dx OR, If M is the mode of a discrete probability distribution with mass function f MODEL QUESTION Statstcs (Thory) (Nw Syllabus) GROUP A d θ. ) Wrt dow th rsult of ( ) ) d OR, If M s th mod of a dscrt robablty dstrbuto wth mass fucto f th f().. at M. d d ( θ ) θ θ OR, f() mamum valu

More information

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 7, July-25 64 ISSN 2229-558 HARATERISTIS OF EDGE UTSET MATRIX OF PETERSON GRAPH WITH ALGEBRAI GRAPH THEORY Dr. G. Nirmala M. Murugan

More information

Chapter 6. pn-junction diode: I-V characteristics

Chapter 6. pn-junction diode: I-V characteristics Chatr 6. -jucto dod: -V charactrstcs Tocs: stady stat rsos of th jucto dod udr ald d.c. voltag. ucto udr bas qualtatv dscusso dal dod quato Dvatos from th dal dod Charg-cotrol aroach Prof. Yo-S M Elctroc

More information

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem Mahmacal ascs 8 Chapr VIII amplg Dsrbos ad h Cral Lm Thorm Fcos of radom arabls ar sall of rs sascal applcao Cosdr a s of obsrabl radom arabls L For ampl sppos h arabls ar a radom sampl of s from a poplao

More information

Week 3: Connected Subgraphs

Week 3: Connected Subgraphs Wk 3: Connctd Subgraphs Sptmbr 19, 2016 1 Connctd Graphs Path, Distanc: A path from a vrtx x to a vrtx y in a graph G is rfrrd to an xy-path. Lt X, Y V (G). An (X, Y )-path is an xy-path with x X and y

More information

A Multi-granular Linguistic Promethee Model

A Multi-granular Linguistic Promethee Model A Mult-graular Lgustc Promth Modl Nsr Haloua, Lus Martíz, Habb Chabchoub, Ja-Marc Martl, Ju Lu 4 Uvrsty of Ecoomc Sccs ad Maagmt, Sfax, Tusa, Uvrsty of Jaé, Spa, Uvrsty of Laval, Caada, 4 Uvrsty of Ulstr,

More information

Control Systems (Lecture note #6)

Control Systems (Lecture note #6) 6.5 Corol Sysms (Lcur o #6 Las Tm: Lar algbra rw Lar algbrac quaos soluos Paramrzao of all soluos Smlary rasformao: compao form Egalus ad gcors dagoal form bg pcur: o brach of h cours Vcor spacs marcs

More information

On Eccentricity Sum Eigenvalue and Eccentricity Sum Energy of a Graph

On Eccentricity Sum Eigenvalue and Eccentricity Sum Energy of a Graph Aals of Pure ad Appled Mathematcs Vol. 3, No., 7, -3 ISSN: 79-87X (P, 79-888(ole Publshed o 3 March 7 www.researchmathsc.org DOI: http://dx.do.org/.7/apam.3a Aals of O Eccetrcty Sum Egealue ad Eccetrcty

More information

Chapter 5 Special Discrete Distributions. Wen-Guey Tzeng Computer Science Department National Chiao University

Chapter 5 Special Discrete Distributions. Wen-Guey Tzeng Computer Science Department National Chiao University Chatr 5 Scal Dscrt Dstrbutos W-Guy Tzg Comutr Scc Dartmt Natoal Chao Uvrsty Why study scal radom varabls Thy aar frqutly thory, alcatos, statstcs, scc, grg, fac, tc. For aml, Th umbr of customrs a rod

More information

THE BALANCED CREDIBILITY ESTIMATORS WITH MULTITUDE CONTRACTS OBTAINED UNDER LINEX LOSS FUNCTION

THE BALANCED CREDIBILITY ESTIMATORS WITH MULTITUDE CONTRACTS OBTAINED UNDER LINEX LOSS FUNCTION Joural of Stattc: Advac Thory ad Applcato Volum 4 Numbr 5 Pag - Avalabl at http://ctfcadvac.co. DOI: http://dx.do.org/.864/jata_746 THE BALANCED CREDIBILITY ESTIMATORS WITH MULTITUDE CONTRACTS OBTAINED

More information

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.

More information

Odd Generalized Exponential Flexible Weibull Extension Distribution

Odd Generalized Exponential Flexible Weibull Extension Distribution Odd Gralzd Epotal Flbl Wbull Etso Dstrbuto Abdlfattah Mustafa Mathmatcs Dpartmt Faculty of Scc Masoura Uvrsty Masoura Egypt abdlfatah mustafa@yahoo.com Bh S. El-Dsouy Mathmatcs Dpartmt Faculty of Scc Masoura

More information

Introduction to logistic regression

Introduction to logistic regression Itroducto to logstc rgrsso Gv: datast D {... } whr s a k-dmsoal vctor of ral-valud faturs or attrbuts ad s a bar class labl or targt. hus w ca sa that R k ad {0 }. For ampl f k 4 a datast of 3 data pots

More information

Saw-Dmss Model For Intuitionistic Fuzzy Multi Attribute Decision Making Problems

Saw-Dmss Model For Intuitionistic Fuzzy Multi Attribute Decision Making Problems Itratoal Joural o Rct ad Iovato Trds Computg ad Commucato ISSN: 232-869 Saw-Dmss Modl For Itutostc Fuzzy Mult ttrbut Dcso Mag Problms V. Thagarasu ssocat Profssor of Computr Scc Gob rts & Scc Collg Gobchttpalayam,

More information

Estimation of the Present Values of Life Annuities for the Different Actuarial Models

Estimation of the Present Values of Life Annuities for the Different Actuarial Models h Scod Itratoal Symposum o Stochastc Modls Rlablty Egrg, Lf Scc ad Opratos Maagmt Estmato of th Prst Valus of Lf Auts for th Dffrt Actuaral Modls Gady M Koshk, Oaa V Guba omsk Stat Uvrsty Dpartmt of Appld

More information

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013 18.782 Introduction to Arithmtic Gomtry Fall 2013 Lctur #20 11/14/2013 20.1 Dgr thorm for morphisms of curvs Lt us rstat th thorm givn at th nd of th last lctur, which w will now prov. Thorm 20.1. Lt φ:

More information

Course 10 Shading. 1. Basic Concepts: Radiance: the light energy. Light Source:

Course 10 Shading. 1. Basic Concepts: Radiance: the light energy. Light Source: Cour 0 Shadg Cour 0 Shadg. Bac Coct: Lght Sourc: adac: th lght rg radatd from a ut ara of lght ourc or urfac a ut old agl. Sold agl: $ # r f lght ourc a ot ourc th ut ara omttd abov dfto. llumato: lght

More information

More Statistics tutorial at 1. Introduction to mathematical Statistics

More Statistics tutorial at   1. Introduction to mathematical Statistics Mor Sttstcs tutorl t wwwdumblttldoctorcom Itroducto to mthmtcl Sttstcs Fl Soluto A Gllup survy portrys US trprurs s " th mvrcks, drmrs, d lors whos rough dgs d ucompromsg d to do t thr ow wy st thm shrp

More information

07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n

07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n 07 - SEQUENCES AND SERIES Pag ( Aswrs at h d of all qustios ) ( ) If = a, y = b, z = c, whr a, b, c ar i A.P. ad = 0 = 0 = 0 l a l

More information

Folding of Hyperbolic Manifolds

Folding of Hyperbolic Manifolds It. J. Cotmp. Math. Scics, Vol. 7, 0, o. 6, 79-799 Foldig of Hyprbolic Maifolds H. I. Attiya Basic Scic Dpartmt, Collg of Idustrial Educatio BANE - SUEF Uivrsity, Egypt hala_attiya005@yahoo.com Abstract

More information

Hardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R.

Hardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R. Hardy-Littlwood Conjctur and Excptional ral Zro JinHua Fi ChangLing Company of Elctronic Tchnology Baoji Shannxi P.R.China E-mail: fijinhuayoujian@msn.com Abstract. In this papr, w assum that Hardy-Littlwood

More information

APPENDIX: STATISTICAL TOOLS

APPENDIX: STATISTICAL TOOLS I. Nots o radom samplig Why do you d to sampl radomly? APPENDI: STATISTICAL TOOLS I ordr to masur som valu o a populatio of orgaisms, you usually caot masur all orgaisms, so you sampl a subst of th populatio.

More information

Tolerance Interval for Exponentiated Exponential Distribution Based on Grouped Data

Tolerance Interval for Exponentiated Exponential Distribution Based on Grouped Data Itratoal Rfrd Joural of Egrg ad Scc (IRJES) ISSN (Ol) 319-183X, (Prt) 319-181 Volum, Issu 10 (Octobr 013), PP. 6-30 Tolrac Itrval for Expotatd Expotal Dstrbuto Basd o Groupd Data C. S. Kaad 1, D. T. Shr

More information

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity BULLETIN of the MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Bull. Malays. Math. Sc. Soc. () 7 (004), 5 35 Strog Covergece of Weghted Averaged Appromats of Asymptotcally Noepasve Mappgs Baach Spaces wthout

More information

and one unit cell contains 8 silicon atoms. The atomic density of silicon is

and one unit cell contains 8 silicon atoms. The atomic density of silicon is Chaptr Vsualzato o th Slo Crystal (a) Plas rr to Fgur - Th 8 orr atoms ar shar by 8 ut lls a thror otrbut atom Smlarly, th 6 a atoms ar ah shar by ut lls a otrbut atoms A, 4 atoms ar loat s th ut ll H,

More information

Graphs of q-exponentials and q-trigonometric functions

Graphs of q-exponentials and q-trigonometric functions Grahs of -otals ad -trgoomtrc fuctos Amla Carola Saravga To ct ths vrso: Amla Carola Saravga. Grahs of -otals ad -trgoomtrc fuctos. 26. HAL Id: hal-377262 htts://hal.archvs-ouvrts.fr/hal-377262

More information

The Interplay between l-max, l-min, p-max and p-min Stable Distributions

The Interplay between l-max, l-min, p-max and p-min Stable Distributions DOI: 0.545/mjis.05.4006 Th Itrplay btw lma lmi pma ad pmi Stabl Distributios S Ravi ad TS Mavitha Dpartmt of Studis i Statistics Uivrsity of Mysor Maasagagotri Mysuru 570006 Idia. Email:ravi@statistics.uimysor.ac.i

More information

Bayesian Test for Lifetime Performance Index of Ailamujia Distribution Under Squared Error Loss Function

Bayesian Test for Lifetime Performance Index of Ailamujia Distribution Under Squared Error Loss Function Pur ad Appld Mathmatcs Joural 6; 5(6): 8-85 http://www.sccpublshggroup.com/j/pamj do:.648/j.pamj.656. ISSN: 36-979 (Prt); ISSN: 36-98 (Ol) Baysa Tst for ftm Prformac Idx of Alamuja Dstrbuto Udr Squard

More information

On spanning trees and cycles of multicolored point sets with few intersections

On spanning trees and cycles of multicolored point sets with few intersections On spanning trs and cycls of multicolord point sts with fw intrsctions M. Kano, C. Mrino, and J. Urrutia April, 00 Abstract Lt P 1,..., P k b a collction of disjoint point sts in R in gnral position. W

More information

Further Results on Pair Sum Labeling of Trees

Further Results on Pair Sum Labeling of Trees Appled Mathematcs 0 70-7 do:046/am0077 Publshed Ole October 0 (http://wwwscrporg/joural/am) Further Results o Par Sum Labelg of Trees Abstract Raja Poraj Jeyaraj Vjaya Xaver Parthpa Departmet of Mathematcs

More information

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit

Binary Choice. Multiple Choice. LPM logit logistic regresion probit. Multinomial Logit (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty (c Pogsa Porchawssul, Faculty of Ecoomcs, Chulalogor Uvrsty 3 Bary Choc LPM logt logstc rgrso probt Multpl Choc Multomal Logt (c Pogsa Porchawssul,

More information

β-spline Estimation in a Semiparametric Regression Model with Nonlinear Time Series Errors

β-spline Estimation in a Semiparametric Regression Model with Nonlinear Time Series Errors Amrca Joural of Appld Sccs, (9): 343-349, 005 ISSN 546-939 005 Scc Publcatos β-spl Estmato a Smparamtrc Rgrsso Modl wth Nolar Tm Srs Errors Jhog You, ma Ch ad 3 Xa Zhou Dpartmt of ostatstcs, Uvrsty of

More information

Irregular Boundary Area Computation. by Quantic Hermite Polynomial

Irregular Boundary Area Computation. by Quantic Hermite Polynomial It. J. Cotmp. Mat. Sccs, Vol. 6,, o., - Irrgular Boudar Ara Computato b Quatc Hrmt Polomal J. Karwa Hama Faraj, H.-S. Faradu Kadr ad A. Jamal Muamad Uvrst of Sulama-Collg of Scc Dpartmt of Matmatcs, Sualma,

More information

Searching Linked Lists. Perfect Skip List. Building a Skip List. Skip List Analysis (1) Assume the list is sorted, but is stored in a linked list.

Searching Linked Lists. Perfect Skip List. Building a Skip List. Skip List Analysis (1) Assume the list is sorted, but is stored in a linked list. 3 3 4 8 6 3 3 4 8 6 3 3 4 8 6 () (d) 3 Sarching Linkd Lists Sarching Linkd Lists Sarching Linkd Lists ssum th list is sortd, but is stord in a linkd list. an w us binary sarch? omparisons? Work? What if

More information

Perfect Constant-Weight Codes

Perfect Constant-Weight Codes 56 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 50, NO. 9, SEPTEMBER 004 Prfct Costat-Wght Cods Tuv Etzo, Fllo, IEEE, ad Mosh Schartz, Mmbr, IEEE Abstract I hs porg or from 973, Dlsart cocturd that thr

More information

11/13/17. directed graphs. CS 220: Discrete Structures and their Applications. relations and directed graphs; transitive closure zybooks

11/13/17. directed graphs. CS 220: Discrete Structures and their Applications. relations and directed graphs; transitive closure zybooks dirctd graphs CS 220: Discrt Strctrs and thir Applications rlations and dirctd graphs; transiti closr zybooks 9.3-9.6 G=(V, E) rtics dgs dgs rtics/ nods Edg (, ) gos from rtx to rtx. in-dgr of a rtx: th

More information

PROOF OF FIRST STANDARD FORM OF NONELEMENTARY FUNCTIONS

PROOF OF FIRST STANDARD FORM OF NONELEMENTARY FUNCTIONS Intrnational Journal Of Advanc Rsarch In Scinc And Enginring http://www.ijars.com IJARSE, Vol. No., Issu No., Fbruary, 013 ISSN-319-8354(E) PROOF OF FIRST STANDARD FORM OF NONELEMENTARY FUNCTIONS 1 Dharmndra

More information

Three-Dimensional Theory of Nonlinear-Elastic. Bodies Stability under Finite Deformations

Three-Dimensional Theory of Nonlinear-Elastic. Bodies Stability under Finite Deformations Appld Mathmatcal Sccs ol. 9 5 o. 43 75-73 HKAR Ltd www.m-hkar.com http://dx.do.org/.988/ams.5.567 Thr-Dmsoal Thory of Nolar-Elastc Bods Stablty udr Ft Dformatos Yu.. Dmtrko Computatoal Mathmatcs ad Mathmatcal

More information

A Stochastic Approximation Iterative Least Squares Estimation Procedure

A Stochastic Approximation Iterative Least Squares Estimation Procedure Joural of Al Azhar Uvrst-Gaza Natural Sccs, 00, : 35-54 A Stochastc Appromato Itratv Last Squars Estmato Procdur Shahaz Ezald Abu- Qamar Dpartmt of Appld Statstcs Facult of Ecoomcs ad Admstrato Sccs Al-Azhar

More information

Double Dominating Energy of Some Graphs

Double Dominating Energy of Some Graphs Iter. J. Fuzzy Mathematcal Archve Vol. 4, No., 04, -7 ISSN: 30 34 (P), 30 350 (ole) Publshed o 5 March 04 www.researchmathsc.org Iteratoal Joural of V.Kaladev ad G.Sharmla Dev P.G & Research Departmet

More information

Derangements and Applications

Derangements and Applications 2 3 47 6 23 Journal of Intgr Squncs, Vol. 6 (2003), Articl 03..2 Drangmnts and Applications Mhdi Hassani Dpartmnt of Mathmatics Institut for Advancd Studis in Basic Scincs Zanjan, Iran mhassani@iasbs.ac.ir

More information

Network reliability importance measures : combinatorics and Monte Carlo based computations

Network reliability importance measures : combinatorics and Monte Carlo based computations 7th WSEAS Itratoal Cofrc o APPLIED COMPUTER SCIENCE, Vc, Italy, Novmr 2-2, 2007 88 Ntwork rlalty mportac maur : comatorc ad Mot Carlo ad computato ILYA GERTSAKH Dpartmt of Mathmatc Guro Uvrty PO 65 r Shva

More information

Pion Production via Proton Synchrotron Radiation in Strong Magnetic Fields in Relativistic Quantum Approach

Pion Production via Proton Synchrotron Radiation in Strong Magnetic Fields in Relativistic Quantum Approach Po Producto va Proto Sychrotro Radato Strog Magtc Flds Rlatvstc Quatum Approach Partcl Productos TV Ergy Rgo Collaborators Toshtaka Kajo Myog-K Chou Grad. J. MATHEWS Tomoyuk Maruyama BRS. Nho Uvrsty NaO,

More information

Consistency of the Maximum Likelihood Estimator in Logistic Regression Model: A Different Approach

Consistency of the Maximum Likelihood Estimator in Logistic Regression Model: A Different Approach ISSN 168-8 Joural of Statstcs Volum 16, 9,. 1-11 Cosstcy of th Mamum Lklhood Estmator Logstc Rgrsso Modl: A Dffrt Aroach Abstract Mamuur Rashd 1 ad Nama Shfa hs artcl vstgats th cosstcy of mamum lklhood

More information