On the Numerical Solutions of Two Dimensional Maxwell s Equations
|
|
- Stuart Casey
- 5 years ago
- Views:
Transcription
1 ues oea ceces : 8-88 I -9 IOI Pubcaos O e umeca ouos of Two mesoa Mawe s uaos.. weam M.M. Kae a.t. Moame epame of Maemacs acu of ceces Cao Uves Ga gp epame of Maemacs acu of ceces Bea Uves Bea gp epame of Basc ceces Moe Acaem fo geeg a Tecoog Cao gp Absac: I s pape wo ffee meos ae sue o sove umeca me epee Mawe s euaos wo mesos. Te meos ae e scouous Gae Meo GM a e Vaaoa Ieao Meo VIM. scouous Gae meo s ese fo ffee umbe of aguao eemes ffee me evas a ffee oes of bass fucos. Compasos bewee e souos of Mawe s euaos usg GM a VIM ae pesee. I s fou a VIM s va fo age me bu GM ovecome s pobem. Ke wos: scouous Gae meo me-oma mawe s euaos wo mesos vaaoa eao meo ITROUCTIO Mawe s euaos ae oe of e mpoa moes ffee fes; escbes eecomagec peomea suc as cues mco ao a aa waves. I s we ow a Mawe s euaos ae a o sove aaca ca be sove aaca o fo smpe omas suc as a spee a a fe ccua ce []. umeca meos fo e Mawe s euaos ae usua efee o as Compuaoa ecomagec CM. Te moeg of ssems ae vovg eecomagec waves s ow we oe oug e souo of e me oma Mawe euao o space g. uc sems wee sove w ma ffee meos e fs meo fo e umeca smuao of me epee eecomagec waves e e ffeece Tme oma Meo TM was popose []. I s cea a TM ow ue s smpc a effcec bu s ffcu o geeae o usucue o-caesa gs a suffe fom e accuae epeseao of e souo o cuve bouaes []. Moeove TM as accuac mao fo seco oe accuac sevee ms e ab o coec epese wave moo ove og saces uess e g s pobve fe []. Ma ffee pes of meos ave bee popose wc ae base o usucue gs a ca ea w compe geomees e e eme Tme oma Meos TMs [4 5]. Tee ae wo ffcues appea we usg e saa e eme Meo M. s e meo geea use o a goba cofomg mes a mea a mes wou agg coecg oes o msmac of mes pos aog ea bouaes. eco ow we ca epese coe sguaes [4 6]. Te scouous Gae Meos GM meos [7-] ae base o scouous fe eeme spaces. I s eas ae eemes of vaous pes a sapes egua o-cofomg meses a eve oca vag pooma egee. Moeove cou s wea efoce acoss mes efaces b ag suabe bea foms e so-cae umeca fues o e saa vaaoa fomuaos []. e o eaea meses usg Lagage poomas [ ] o o eaea meses usg poucs of Lagage poomas []. O e oe a Vaaoa Ieao Meo VIM [4-] s popose b J.. e [6 7] as a mofcao of a geea Lagage mupe meo. Ts ecue poves a seuece of fucos wc coveges o e eac souo of e pobem. I as bee sow a s poceue s a powefu oo fo sovg vaous s of pobems. Ts ecue soves e pobem wou a ee o sceao of e vaabes eefoe s o affece b comp uao ou off eos a oe s o face w ecess of age compue memo a me. Aso s ecue poves e souo of e pobem a cose fom we e mes po ecues suc as e fe ffeece meo pove e appomao a mes pos o. Ts pape s ogae as foows: I seco e moe pobem a e agom of souo ae Coespog Auo:... weam epame of Maemacs acu of ceces Cao Uves Ga gp 8
2 ues oea c. : 8-88 ouce. I seco VIM s ouce o oba e appomae souo of Mawe s euaos. Te as seco 4 gves a scusso of ou esus. GM OR T MOL PROBLM Le us cose e wo mesoa vacuum Mawe s euaos; wc s ow as Tasvese Magec fom TM [9]; efe Ω [ ] [ ] [ T]. wee ae e compoes of e magec fe a s e eecc fe -eco. uemoe s cae magec pemeab a s cae eecc pemv. o e boua coos assume a e wa of e cav s pefec eecca coucg suc a e agea compoe of e eecc fe vases a e wa.e. a e was aso e a coos of e pobem ae pace sceao: a Assume a e compuaoa oma Ω s compose of K ooveappg -smpces o eemes. Ω Ω K wee s a sag se age a e aguao s assume o be geomeca cofomg; fo eampe Ω s appomae b a pecewse ea pogo w eac e segme beg a face of age. b Assume a e oca souo of e veco of e fe [] T a e oca fu ca be efe: p. wee p s e mumesoa Lagage poomas efe b some g pos a efe as P p spa j ; j p s m s wee m ae aba cosas. o smpc e us we Mawe s euao e fu fom [9]: w a Q.. T [ ] Q e e I e foowg we epa bef e basc ea of GM o sove. e fs pa we pese e space sceao a e seco pa we pese e me sceao. 8 c To mpeme e umeca appomao mup euao. w es fuco e egag b pas wce s ea us o. * [ ] ˆ..4 wc epese e sog fom of GM fo pobem.. Assume a e oca souo s epesse as p p ˆ ψ.5
3 ψ p wee { } ues oea c. : 8-88 s a geue wo mesoa pooma bass of oe a p s e umbe of ems e oca epaso wc eae o e oe of e pooma w e eao p. e Te we ave..4 a.5 a afe some eaageme we ge: p p j. j j j p * ˆ.6 j j wc s e sem scee fom of Mawe s euaos wee e mass ma M j j a ca be we as M J I T J v v j.7 wee suc a a j j j j j j j j a e eeme of ege egao ma j ˆ j J I j j.8.9 a w be cacuae e same wa e e sffess ma fo moe eaes fo asfomao a cacuao see [7 ]. Aso o compue e suabe fu we efe Z ± ± Z ± ± w bouaes ˆ ˆ Aso e sffess ma ˆ ˆ Z Z Te e peag boua em ow efe as; ˆ [[ ]] ˆ ˆ [[ ]]. ˆ Z Z ˆ [[ ]] αˆ ˆ [[ ]] ˆ α. f ow e oca semscee sceme of Mawe s euaos geg afe sovg usg GM a fom. a. ae gve b:.a JM ˆ [ ] α ˆ [[ ]] [ ] [[ ]] [ ] JM [ ] ˆ α ˆ [ ] [ ] α JM ˆ ˆ.b.c Tme sceao: To compee e semscee fomuao..a-..c use a epc aw soage Rug- Kua meo o egae me w p sages p s e oe of e pooma of e bass fucos. Te me sep use e compuao s ae eusca o be CL p m ma c wee c 84
4 ues oea c. : 8-88 Tabe : Te mamum eo of e umeca souo a ffee vaues of p a ffee mes T p 4 p 8 p p A e e-6.4e e-4.4e e e e e e e-6.98e-7 A e-8.768e-.85e e e-.4e-..586e e-.6e-.8.74e-7.596e e- A e e e-.445e e-4.97e e-.4656e-.56e e-.666e e- 9.65e e- 5.e-.7e Appomae Appomae g. : umeca souo fo usg GM a p a g. : umeca souo fo usg GM a p a 8 s e wave spee e - eeme; s e eg mamum amee of e eeme; a CLp coo pca aes vaues of /p. Te umeca esus fo sovg Mawe s euao usg e GM ae sow Tabe. Ts abe peses e mamum eo of e souo fo ffee mes umbe of eemes K a e oe of pooma p. UMRICAL IMPLMTATIO O VIM I s seco we app VIM o oba e appomae souo of. w e a a coos. Accog o VIM [6] we ca cosuc e foowg eao fomua: Appomae g. : umeca souo fo usg GM a 5 p a
5 ues oea c. : Appomae ac Z g. 4: Te umeca souo usg VIM a.4 afe 6 eao ef. ac souo fo g ~. ~ ~ wee a ae geea Lagage mupes wc ca be efe opma va vaaoa eo. Te seco em o e g-a se. s cae e coeco a e subscp eoes e - oe appomao. Ue a suabe esce vaaoa assumpo.e. ~ ~ a ~ s cosee as a esce vaao we ca assume a e above coecoa fucoa ae saoa.e. ~ δ ~ δ a ~ δ e e Lagage mupes ca be efe []. Te successve appomaos a of e souo w be ea obae upo usg e obae Lagage mupes a suabe seecve fucos a. Cacuag vaao w espec o a we ca oba e foowg ffeea euaos:. Te Lagage mupes eefoe ca be efe as:. ubsug e efe mupe. o. esus e foowg eao fomua.4 We ca sa w e gve a appomao usg a coos a b e fomua.4 some appomae souos ae se beow:
6 ues oea c. : 8-88 Tabe : Te mamum eo of e umeca souo a ffee vaues of mes T Ma eo T Ma eo s ms m m m m s ms s m s s m s 87 s m s s m s s m s m s m s s m s ece e souo s ma be obae usg: m s ms s m s s m s m.5 Te beavo of e appomae souo of e VIM a e eac souo s gve g. 4 a.4. Te umeca esus fo sovg Mawe s euao usg e VIM ae sow Tabe. Ts abe peses e mamum eo of e souo fo ffee mes. COCLUIO A RMARK I s wo e scouous Gae me oma meo a VIM ae use o su e umeca souo of Mawe s euaos womesos. Te GM s appe fo ffee umbe of eemes ffee me a ffee oe of poomas. ee we e moes mus be sma eoug fo eas souo f beg age gve moe oscaos fo sma moes gve ve goo accuac aso mus be ege o fco. Aoug VIM s a ve smpe meo a as ma avaages suc as ees o sceao space a me vaabes o ee o sove ea o oea ssem of euaos bu fom e obae umeca esus Tabe we fou a VIM s va fo age me a GM ovecome suc s pobem. RRC. Aesso U.. Tme oma Meos fo e Mawe uaos. ocoa sseao Roa Isue of Tecoog ocom.. Tafove A Compuaoa ecoamcs: Te e-ffeece Tme- oma Meo Aec ouse Boso.. ee K umeca souo of a boua vaue pobems vovg Mawe s euao soopc mea. I Tas. Aeas Popagae 4: mes A. a P. Jo 997. e eemes a mass umpg fo Mawe s euaos: Te case umeca Aass C.R. Aca c. Pas 4: Moma. a. Abuasa 5. Appcao of e s vaaoa eao meo o emo euao. Caos oos a acas 7: Mo P.. e eme Meo fo Mawe s uao. Ofo Uves ew o.
7 ues oea c. : Cocbu B. G.. Kaaas a C.W. u. s couous Gae Meos. Teo Compuao a Appcaos. Vo. of Lecue oes Compuaoa cece a geeg pge-veag Be. 8. Kög M. K. Busc a J. egema. Te scouous Gae me-oma meo fo Mawe s euaos w asoopc maeas. Poocs a aosucues-uameas a 9. Goe M.J. A.. Be a. coa 6. Ieo pea scouous Gae meo fo Mawe s euaos: L-om eo esmaes. Pep o. 6- ovembe 6. eave J.. a T. Wabuo 8. oa scouous Gae Meos: Agom Aass a Appcaos pge.. Wabuo T. a J. esave. oa g-oe meos o usucue gs. I: Tme oma souo of Mawe's euaos. J. Compu. Ps. 8 : as. a. Lae. A g-oe ocofomg scouous Gae meo fo me-oma eecomagec. Joua of Compuaoa a Appe Maemacs 4: Wabuo T. a J. esave 4. g-oe oa scouous Gae meos fo e Mawe egevaue pobem. Pos. Tas. Ro. oc. Loo e. A 6: Abass T.A. M.A. -Taw a. Zoe 7. ovg o-ea paa ffeea euaos usg e mofe vaaoa eao Paé ecue. Joua of Compuaoa a Appe Maemacs 7: Abou M.A. a A.A. oma 4. Vaaoa eao meo fo sovg Buge s a coupe Buge s euaos. J. of Compuaoa a Appe Maemacs : e J Vaaoa eao meo-a of o-ea aaca ecue: some ea mpes. Ieaoa Joua of o-lea Mecacs 4: e J Vaaoa eao meo fo ea ffeea euaos. Comm. o-lea c. ume. muao : weam.. a M.M. Kae 7. Vaaoa eao meo fo oe mesoa o-ea emo -easc Caos oos a acas : weam.. a M.M. Kae. Covegece of vaaoa eao meo appe o o-ea coupe ssem of paa ffeea euaos. I. J. of Compue Ma. 87 5: -.. weam.. M.M. Kae a R.. A-Ba 8. o-ea focusg Maaov ssems b vaaoa eao meo a Aoma ecomposo meo. Joua of Pscs: Cofeece ees 96: -7.. as.. Lae a. Rape 8. eveopme of a o-cofomg scouous Gae meo o smpe meses fo eecomagec wave popagao. ou Ieaoa Cofeece o Avace Compuaoa Meos geeg ACOM.. sgos L ffeea uaos a e Cacuus of Vaaos. Tasae fom e Russa b G. aovs M Moscow. Appcaos 8:
Increasing the Image Quality of Atomic Force Microscope by Using Improved Double Tapered Micro Cantilever
Rece Reseaces Teecocaos foacs Eecocs a Sga Pocessg ceasg e age Qa of oc Foce Mcope Usg pove oe Tapee Mco aeve Saeg epae of Mecaca Egeeg aava Bac sac za Uves aava Tea a a_saeg@aavaa.ac. sac: Te esoa feqec
More informationChapter 5. Long Waves
ape 5. Lo Waes Wae e s o compaed ae dep: < < L π Fom ea ae eo o s s ; amos ozoa moo z p s ; dosac pesse Dep-aeaed coseao o mass
More informationINDUCTIVE PULSED THRUSTER WITH SUPERCONDUCTING ACCELERATING ELEMENTS
DTVE PSED THRSTER WTH SPERODTG AEERATG EEMETS Vas Rashova¹, a Poomaova¹, Oma JRamez, Ae Dashov² ¹suo Poécco acoa e Méco, ESME-HAA,Av Saa Aa,, P, Méoco DFFAX:6-6--8, E-ma: vas@camecacesmecupm ²aoa Aeospace
More information. The second term denotes the transition [n 1, n 2-1] [n 1, n 2 ] and leads to an increased p ( n1,
. THE MSTE EQUTION OCH Te mase euao oesos o e saeme a e obab of beg a gve sae ages eeg o e obabes of aso o a fom a oe sae e ssem. I oves e fu obab sbuo we a be e sove. Ufouae s s o ofe e ase so we mus
More informationOn Probability Density Function of the Quotient of Generalized Order Statistics from the Weibull Distribution
ISSN 684-843 Joua of Sac Voue 5 8 pp. 7-5 O Pobaby Dey Fuco of he Quoe of Geeaed Ode Sac fo he Webu Dbuo Abac The pobaby dey fuco of Muhaad Aee X k Y k Z whee k X ad Y k ae h ad h geeaed ode ac fo Webu
More informationLagrangian & Hamiltonian Mechanics:
XII AGRANGIAN & HAMITONIAN DYNAMICS Iouco Hamlo aaoal Pcple Geealze Cooaes Geealze Foces agaga s Euao Geealze Momea Foces of Cosa, agage Mulples Hamloa Fucos, Cosevao aws Hamloa Dyamcs: Hamlo s Euaos agaga
More informationTHIS PAGE DECLASSIFIED IAW E
THS PAGE DECLASSFED AW E0 2958 BL K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW E0 2958 B L K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW EO 2958 THS PAGE DECLASSFED AW EO 2958 THS
More informationTechnical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.
Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so
More informationP 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 informationA L A BA M A L A W R E V IE W
A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N
More informationc- : r - C ' ',. A a \ V
HS PAGE DECLASSFED AW EO 2958 c C \ V A A a HS PAGE DECLASSFED AW EO 2958 HS PAGE DECLASSFED AW EO 2958 = N! [! D!! * J!! [ c 9 c 6 j C v C! ( «! Y y Y ^ L! J ( ) J! J ~ n + ~ L a Y C + J " J 7 = [ " S!
More information-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL
UPB Sc B See A Vo 72 I 3 2 ISSN 223-727 MUTIPE -HYBRID APACE TRANSORM AND APPICATIONS TO MUTIDIMENSIONA HYBRID SYSTEMS PART II: DETERMININ THE ORIINA Ve PREPEIŢĂ Te VASIACHE 2 Ace co copeeă oă - pce he
More informationEMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions
EMA5 Lecue 3 Seady Sae & Noseady Sae ffuso - Fck s d Law & Soluos EMA 5 Physcal Popees of Maeals Zhe heg (6) 3 Noseady Sae ff Fck s d Law Seady-Sae ffuso Seady Sae Seady Sae = Equlbum? No! Smlay: Sae fuco
More informationON THE EXTENSION OF WEAK ARMENDARIZ RINGS RELATIVE TO A MONOID
wwweo/voue/vo9iue/ijas_9 9f ON THE EXTENSION OF WEAK AENDAIZ INGS ELATIVE TO A ONOID Eye A & Ayou Eoy Dee of e Nowe No Uvey Lzou 77 C Dee of e Uvey of Kou Ou Su E-: eye76@o; you975@yooo ABSTACT Fo oo we
More informationT T V e g em D e j ) a S D } a o "m ek j g ed b m "d mq m [ d, )
. ) 6 3 ; 6 ;, G E E W T S W X D ^ L J R Y [ _ ` E ) '" " " -, 7 4-4 4-4 ; ; 7 4 4 4 4 4 ;= : " B C CA BA " ) 3D H E V U T T V e g em D e j ) a S D } a o "m ek j g ed b m "d mq m [ d, ) W X 6 G.. 6 [ X
More informationDYNAMICAL NEAR OPTIMAL TRAINING FOR INTERVAL TYPE-2 FUZZY NEURAL NETWORK (T2FNN) WITH GENETIC ALGORITHM
DYNAICAL NAR OPIAL RAINING FOR INRVAL YP- FUZZY NURAL NWORK FNN WIH GNIC ALGORIH A hess Submed Fume o he Requemes o he Degee o ase o Phosoph B a Chu-Sheg Cheg Schoo o coeecoc geeg Fau o geeg ad Iomao echoog
More informationAnouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent
oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps
More informationAPPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS
Joa of Aed Mahema ad Comaoa Meha 4 3( 6-73 APPLCATON OF A Z-TRANSFORMS METHOD FOR NVESTGATON OF MARKOV G-NETWORKS Mha Maay Vo Nameo e of Mahema Ceohowa Uey of Tehoogy Cęohowa Poad Fay of Mahema ad Come
More informationTHIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.
T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson
More informationNonlocal Boundary Value Problem for Nonlinear Impulsive q k Symmetric Integrodifference Equation
OSR ol o Mec OSR-M e-ssn: 78-578 -SSN: 9-765X Vole e Ve M - A 7 PP 95- wwwojolog Nolocl Bo Vle Poble o Nole lve - Sec egoeece Eo Log Ceg Ceg Ho * Yeg He ee o Mec Yb Uve Yj PR C Abc: A oe ole lve egoeece
More informationGeneralized Entropy of Kumaraswamy Distribution Based on Order Statistics
Geeaed Eop o Kumaawam Dbuo Baed o Ode Sac Ra Na M.A.K Bag 2 Javd Ga Da 3 Reeach Schoa Depame o Sac Uve o Kahm Saga Ida 2 Aocae Poeo Depame o Sac Uve o Kahm Saga Ida 3 Depame o Mahemac Iamc Uve o Scece
More informationTHIS PAGE DECLASSIFIED IAW E
THS PAGE DECLASSFED AW E0 2958 BL K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW E0 2958 B L K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW E0 2958 BL K THS PAGE DECLASSFED AW E0 2958
More informationIV. STATICS AND DYNAMICS OF DEFORMABLE MEDIA.
V. TT ND DYNM OF DEFOMLE MED. 48. Defoabe eu. Naua sae a efoe sae. The heoes of he efoabe e a he efoabe suface ha we scusse ea a ve aua ae o evsog a oe geea efoabe eu ha he oe ha s habua cosee he heo of
More informationMODELING AND IDENTIFICATION OF A TWO-LINK FLEXIBLE MANIPULATOR
ABC Sosu Ss caocs - Vo. 5 Cog b ABC Sco VII - Robocs Pag 9 ODELIN AND IDENIFICAION OF A WO-LINK FLEXIBLE ANIPULAOR og Auguso Bof jog.g@ga.co Fábo L.. Saos fsaos@a.b Cao Rogus Bao caob@ga.co Luz Caos Saova
More informationH STO RY OF TH E SA NT
O RY OF E N G L R R VER ritten for the entennial of th e Foundin g of t lair oun t y on ay 8 82 Y EEL N E JEN K RP O N! R ENJ F ] jun E 3 1 92! Ph in t ed b y h e t l a i r R ep u b l i c a n O 4 1922
More informationP a g e 3 6 of R e p o r t P B 4 / 0 9
P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J
More information3D UNIFIED CFD APPROACH TO MODELING OF BUBBLE PHENOMENA
e Ieaoa oca eeg o Nucea aco ema-hyaucs (NUREH- Pae: 47 Poes Paace Cofeece Cee Ago Face Ocobe -6 5 3D UNIFIED CFD APPROACH O ODELING OF BUBBLE PHENOENA am Cuao A E Akseoa ae A Pecko Nucea Safey Isue (IBRAE
More informationG OUP S 5 TH TE 5 DN 5. / E/ ' l / DECE 'I E THIS PAGE DECLASSIFIED IAW EO ', - , --,. . ` : - =.. r .
= ; D p a 0 + 5 TH TE 5 DN 5 506 T F/ GH T G OUP S / E/ 9 4 4 / DECE E = / v c H S T 0 R Y 45 8 TH F HTE S DR N S ) 50 c c o s ) DECE 9 3 DLCE E 9 a L ON J E R E 2 d L Cope s H aca SS L 9/ soca e O 0 THS
More informationSuppose we have observed values t 1, t 2, t n of a random variable T.
Sppose we have obseved vales, 2, of a adom vaable T. The dsbo of T s ow o belog o a cea ype (e.g., expoeal, omal, ec.) b he veco θ ( θ, θ2, θp ) of ow paamees assocaed wh s ow (whee p s he mbe of ow paamees).
More information1. INTRODUCTION In this paper, we consider a general ninth order linear boundary value problem (1) subject to boundary conditions
NUMERICAL SOLUTION OF NINTH ORDER BOUNDARY VALUE PROBLEMS BY PETROV-GALERKIN METHOD WITH QUINTIC B-SPLINES AS BASIS FUNCTIONS AND SEXTIC B-SPLINES AS WEIGHT FUNCTIONS K. N. S. Kas Vswaaham a S. V. Kamay
More informationT 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 informationMATHEMATICAL DERIVATION OF THE FARADAY INDUCTION LAW AND EXPLANATION OF ITS LORENTZ NON-INVARIANCE
MTHEMTICL DERIVTION OF THE FRDY INDUCTION LW ND EXPLNTION OF ITS LORENTZ NON-INVRINCE.L. Kholmesk Depame of Phscs Belausa Sae Ues 4 F. Skoa eue 0080 Msk Belaus E-mal: kholm@bsu.b The pese pape ees he Faaa
More informationAn Interactive Intuitionistic Fuzzy Non-Linear Fractional Programming Problem
o ou of pp gg R SSN - Voum Num pp - R uo p:wwwpuoom v uo uzz No- o ogmmg om zz m pm of Mm u of S w v o gp O : --- T pp vop w v mo fo ovg o fo pogmmg pom o uo fuzz o v mo f o m M pf g of - v m-m pom ov
More informationDensity estimation III. Linear regression.
Lecure 6 Mlos Hauskrec mlos@cs.p.eu 539 Seo Square Des esmao III. Lear regresso. Daa: Des esmao D { D D.. D} D a vecor of arbue values Obecve: r o esmae e uerlg rue probabl srbuo over varables X px usg
More informationParameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data
Avlble ole wwwsceceeccom Physcs Poce 0 475 480 0 Ieol Cofeece o Mecl Physcs Bomecl ee Pmee smo Hyohess es of wo Neve Boml Dsbuo Poulo wh Mss D Zhwe Zho Collee of MhemcsJl Noml UvesyS Ch zhozhwe@6com Absc
More informationExistence of Nonoscillatory Solutions for a Class of N-order Neutral Differential Systems
Vo 3 No Mod Appd Scc Exsc of Nooscaoy Souos fo a Cass of N-od Nua Dffa Sysms Zhb Ch & Apg Zhag Dpam of Ifomao Egg Hua Uvsy of Tchoogy Hua 4 Cha E-ma: chzhbb@63com Th sach s facd by Hua Povc aua sccs fud
More informationPosterior analysis of the compound truncated Weibull under different loss functions for censored data.
INRNAIONA JOURNA OF MAHMAIC AND COMUR IN IMUAION Vou 6 oso yss of h oou u Wu u ff oss fuos fo so. Khw BOUDJRDA Ass CHADI Ho FAG. As I hs h Bys yss of gh u Wu suo s os u y II so. Bys sos osog ss hv v usg
More informationReliability Equivalence of a Parallel System with Non-Identical Components
Ieraoa Mahemaca Forum 3 8 o. 34 693-7 Reaby Equvaece of a Parae Syem wh No-Ideca ompoe M. Moaer ad mmar M. Sarha Deparme of Sac & O.R. oege of Scece Kg Saud Uvery P.O.ox 455 Ryadh 45 Saud raba aarha@yahoo.com
More informationβ A Constant-G m Biasing
p 2002 EE 532 Anal IC Des II Pae 73 Cnsan-G Bas ecall ha us a PTAT cuen efeence (see p f p. 66 he nes) bas a bpla anss pes cnsan anscnucance e epeaue (an als epenen f supply lae an pcess). Hw h we achee
More informationSummary of Grade 1 and 2 Braille
Sa of Gade 1 ad 2 Baie Wiia Pa Seebe 1998, Ai 1999 1 Baie Aabe Te fooig i i of TEX aco ad Baie bo coaied i baie Te e coad \baie{} cove eece of ag o Baie bo A ag ca be oe caace ic aea a i, o i caace ic
More informationHyperbolic Heat Equation as Mathematical Model for Steel Quenching of L-shape and T-shape Samples, Direct and Inverse Problems
SEAS RANSACIONS o HEA MASS RANSER Bos M Be As Bs Hpeo He Eo s Me Moe o See Qe o L-spe -spe Spes De Iese Poes ABIA BOBINSKA o Pss Mes es o L Ze See 8 L R LAIA e@o MARARIA BIKE ANDRIS BIKIS Ise o Mes Cope
More informationViewing in 3D. Viewing in 3D. Planar Geometric Projections. Taxonomy of Projections. How to specify which part of the 3D world is to be viewed?
Viewig i 3D Viewig i 3D How o speci which pa o he 3D wo is o e viewe? 3D viewig voume How o asom 3D wo cooiaes o D ispa cooiae? Pojecios Cocepua viewig pipeie: Xom o ee coos 3D cippig Pojec Xom o viewpo
More information(1) Cov(, ) E[( E( ))( E( ))]
Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )
More informationLecture 3 summary. C4 Lecture 3 - Jim Libby 1
Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch
More information_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9
C C A 55NED n R 5 0 9 b c c \ { s AS EC 2 5? 9 Con 0 \ 0265 o + s ^! 4 y!! {! w Y n < R > s s = ~ C c [ + * c n j R c C / e A / = + j ) d /! Y 6 ] s v * ^ / ) v } > { ± n S = S w c s y c C { ~! > R = n
More information176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s
A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps
More informationOrder Statistics. 1 n. Example Four measurements are taken on a random variable, x, which take on values.
Oe Sascs e be couous epee.v. wh sbuo a es (. We eoe K be he oee aom vaable whee < < K < a because he ae couous we ca goe equal sg. m ma ( K ( K The pobabl es uco o a ae easl ou: e be a couous.v. ha has
More informationContinuous Time Markov Chains
Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,
More informationAlgebraic Properties of Modular Addition Modulo a Power of Two
Agebac Popees of Moda Addo Modo a Powe of Two S M Dehav Aeza Rahmpo Facy of Mahemaca ad Compe Sceces Khaazm Uvesy Teha Ia sd_dehavsm@hac Facy of Sceces Qom Uvesy Qom Ia aahmpo@sqomac Absac; Moda addo modo
More informationCopyright Birkin Cars (Pty) Ltd
E GROU TWO STEERING AND EDAS - R.H.D Aemble clue : K360 043AD STEERING OUMN I u: - : K360 04A STEERING RAK :3 K360 045A EDA OX K360043AD STEERING O UMN Tl eque f embl f u: - mm Alle Ke 3mm Se 6mm Alle
More informationAnalytical Evaluation of Multicenter Nuclear Attraction Integrals for Slater-Type Orbitals Using Guseinov Rotation-Angular Function
I. J. Cop. Mh. S Vo. 5 o. 7 39-3 Ay Evuo of Mu u Ao Ig fo S-yp O Ug Guov Roo-Agu uo Rz Y M Ag Dp of Mh uy of uo fo g A-Khj Uvy Kgo of Su A Dp of Mh uy of S o B Auh Uvy Kgo of Su A A. Ug h Guov oo-gu fuo
More informationChapter 3: Maximum-Likelihood & Bayesian Parameter Estimation (part 1)
Aoucemes Reags o E-reserves Proec roosal ue oay Parameer Esmao Bomercs CSE 9-a Lecure 6 CSE9a Fall 6 CSE9a Fall 6 Paer Classfcao Chaer 3: Mamum-Lelhoo & Bayesa Parameer Esmao ar All maerals hese sles were
More information4.1 Schrödinger Equation in Spherical Coordinates
Phs 34 Quu Mehs D 9 9 Mo./ Wed./ Thus /3 F./4 Mo., /7 Tues. / Wed., /9 F., /3 4.. -. Shodge Sphe: Sepo & gu (Q9.) 4..-.3 Shodge Sphe: gu & d(q9.) Copuo: Sphe Shodge s 4. Hdoge o (Q9.) 4.3 gu Moeu 4.4.-.
More informationDensity estimation III.
Lecure 6 esy esmao III. Mlos Hausrec mlos@cs..eu 539 Seo Square Oule Oule: esy esmao: Bomal srbuo Mulomal srbuo ormal srbuo Eoeal famly aa: esy esmao {.. } a vecor of arbue values Objecve: ry o esmae e
More information( ) ( ) Weibull Distribution: k ti. u u. Suppose t 1, t 2, t n are times to failure of a group of n mechanisms. The likelihood function is
Webll Dsbo: Des Bce Dep of Mechacal & Idsal Egeeg The Uvesy of Iowa pdf: f () exp Sppose, 2, ae mes o fale of a gop of mechasms. The lelhood fco s L ( ;, ) exp exp MLE: Webll 3//2002 page MLE: Webll 3//2002
More informationInstruction Sheet COOL SERIES DUCT COOL LISTED H NK O. PR D C FE - Re ove r fro e c sed rea. I Page 1 Rev A
Instruction Sheet COOL SERIES DUCT COOL C UL R US LISTED H NK O you or urc s g t e D C t oroug y e ore s g / as e OL P ea e rea g product PR D C FE RES - Re ove r fro e c sed rea t m a o se e x o duct
More information11/8/2002 CS 258 HW 2
/8/ CS 58 HW. G o a a qc of aa h < fo a I o goa o co a C cc c F ch ha F fo a I A If cc - c a co h aoa coo o ho o choo h o qc? I o g o -coa o o-coa? W ca choo h o qc o h a a h aa a. Tha f o o a h o h a:.
More informationBy Joonghoe Dho. The irradiance at P is given by
CH. 9 c CH. 9 c By Joogo Do 9 Gal Coao 9. Gal Coao L co wo po ouc, S & S, mg moocomac wav o am qucy. L paao a b muc ga a. Loca am qucy. L paao a b muc ga a. Loca po obvao P a oug away om ouc o a a P wavo
More informationVARIED SIZED FLOOR PLATE S O N - S I T E B U I L D I N G A M E N I T I E S
VAIED SIZED FLOO PLAE S O - S I E B U I L D I G A E I I E S AVAILABILIIES HIGH-ISE EIE 29H FLOO 16,584 SF LEASE OU ID-ISE PAIAL 18H FLOO 12,459 SF 08/2019 ID-ISE PAIAL 14H FLOO 7,232 SF 08/2019 LOW-ISE
More informationThe calculation of the characteristic and non-characteristic harmonic current of the rectifying system
The calculato of the chaactestc a o-chaactestc hamoc cuet of the ectfyg system Zhag Ruhua, u Shagag, a Luguag, u Zhegguo The sttute of Electcal Egeeg, Chese Acaemy of Sceces, ejg, 00080, Cha. Zhag Ruhua,
More informationANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2
Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads
More informationX-Ray Notes, Part III
oll 6 X-y oe 3: Pe X-Ry oe, P III oe Deeo Coe oupu o x-y ye h look lke h: We efe ue of que lhly ffee efo h ue y ovk: Co: C ΔS S Sl o oe Ro: SR S Co o oe Ro: CR ΔS C SR Pevouly, we ee he SR fo ye hv pxel
More informationRAKE Receiver with Adaptive Interference Cancellers for a DS-CDMA System in Multipath Fading Channels
AKE v wh Apv f Cs fo DS-CDMA Ss Muph Fg Chs JooHu Y Su M EEE JHog M EEE Shoo of E Egg Sou o Uvs Sh-og Gw-gu Sou 5-74 Ko E-: ohu@su As hs pp pv AKE v wh vs og s popos fo DS-CDMA ss uph fg hs h popos pv
More informationMathematical Formulation
Mahemacal Formulao The purpose of a fe fferece equao s o appromae he paral ffereal equao (PE) whle maag he physcal meag. Eample PE: p c k FEs are usually formulae by Taylor Seres Epaso abou a po a eglecg
More information1.050 Engineering Mechanics I. Summary of variables/concepts. Lecture 27-37
.5 Engneeng Mechancs I Summa of vaabes/concepts Lectue 7-37 Vaabe Defnton Notes & ments f secant f tangent f a b a f b f a Convet of a functon a b W v W F v R Etena wok N N δ δ N Fee eneg an pementa fee
More information( ) ( ) Last Time. 3-D particle in box: summary. Modified Bohr model. 3-dimensional Hydrogen atom. Orbital magnetic dipole moment
Last Time 3-dimensional quantum states and wave functions Couse evaluations Tuesday, Dec. 9 in class Deceasing paticle size Quantum dots paticle in box) Optional exta class: eview of mateial since Exam
More informationA Method for Group Decision-making with Uncertain Preference Ordinals Based on Probability Matrix
65 A pubcao of CHEMICA ENGINEERINGTRANSACTIONS VO. 51, 016 Gue Edo:Tcu Wag, Hogyag Zag, e Ta Copyg 016, AIDIC Sevz S..., ISBN978-88-95608-43-3; ISSN 83-916 Te Iaa Aocao of Ceca Egeeg Oe a www.adc./ce DOI:
More informationOH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9
OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at
More informationA NEW FORMULAE OF VARIABLE STEP 3-POINT BLOCK BDF METHOD FOR SOLVING STIFF ODES
Joual of Pue ad Appled Maemac: Advace ad Applcao Volume Numbe Page 9-7 A NEW ORMULAE O VARIABLE STEP -POINT BLOCK BD METHOD OR SOLVING STI ODES NAGHMEH ABASI MOHAMED BIN SULEIMAN UDZIAH ISMAIL ZARINA BIBI
More informationOptimization Method for Interval Portfolio Selection Based on. Satisfaction Index of Interval inequality Relation
Opmzao Meho fo Ieval Pofolo Seleco Base o Sasfaco Ie of Ieval equal Relao Yuchol Jog a a Cee of Naual Scece Uves of Sceces Pogag DPR Koea E-mal: ucholog@ahoo.com Absac: I hs pape e cose a eval pofolo seleco
More informationOverview. Splay trees. Balanced binary search trees. Inge Li Gørtz. Self-adjusting BST (Sleator-Tarjan 1983).
Ovrvw B r rh r: R-k r -3-4 r 00 Ig L Gør Amor Dm rogrmmg Nwork fow Srg mhg Srg g Comuo gomr Irouo o NP-om Rom gorhm B r rh r -3-4 r Aow,, or 3 k r o Prf Evr h from roo o f h m gh mr h E w E R E R rgr h
More informationDensity estimation. Density estimations. CS 2750 Machine Learning. Lecture 5. Milos Hauskrecht 5329 Sennott Square
Lecure 5 esy esmao Mlos Hauskrec mlos@cs..edu 539 Seo Square esy esmaos ocs: esy esmao: Mamum lkelood ML Bayesa arameer esmaes M Beroull dsrbuo. Bomal dsrbuo Mulomal dsrbuo Normal dsrbuo Eoeal famly Noaramerc
More informationI M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o
I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o u l d a l w a y s b e t a k e n, i n c l u d f o l
More informationLeast Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters
Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo
More informationOn the hydrogen wave function in Momentum-space, Clifford algebra and the Generating function of Gegenbauer polynomial
O he hoge we fco Moe-sce ffo geb he eeg fco of egebe oo Meh Hge Hss To ce hs eso: Meh Hge Hss O he hoge we fco Moe-sce ffo geb he eeg fco of egebe oo 8 HL I: h- hs://hches-oeesf/h- Sbe o J 8 HL s
More informationA PATRA CONFERINŢĂ A HIDROENERGETICIENILOR DIN ROMÂNIA,
A PATRA ONFERINŢĂ A HIDROENERGETIIENILOR DIN ROMÂNIA, Do Pael MODELLING OF SEDIMENTATION PROESS IN LONGITUDINAL HORIZONTAL TANK MODELAREA PROESELOR DE SEPARARE A FAZELOR ÎN DEANTOARE LONGITUDINALE Da ROBESU,
More informationThe far field calculation: Approximate and exact solutions. Persa Kyritsi November 10th, 2005 B2-109
Th fa fl calculao: Appoa a ac oluo Pa K Novb 0h 005 B-09 Oul Novb 0h 005 Pa K Iouco Appoa oluo flco fo h gou ac oluo Cocluo Pla wav fo Ic fl: pla wav k ( ) jk H ( ) λ λ ( ) Polaao fo η 0 0 Hooal polaao
More informationF l a s h-b a s e d S S D s i n E n t e r p r i s e F l a s h-b a s e d S S D s ( S o-s ltiad t e D r i v e s ) a r e b e c o m i n g a n a t t r a c
L i f e t i m e M a n a g e m e n t o f F l a-b s ah s e d S S D s U s i n g R e c o v e r-a y w a r e D y n a m i c T h r o t t l i n g S u n g j i n L e, e T a e j i n K i m, K y u n g h o, Kainmd J
More informationON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT
V M Chacko E CONVE AND INCREASIN CONVE OAL IME ON ES RANSORM ORDER R&A # 4 9 Vol. Decembe ON OAL IME ON ES RANSORM ORDER V. M. Chacko Depame of Sascs S. homas Collee hss eala-68 Emal: chackovm@mal.com
More informationFun and Fascinating Bible Reference for Kids Ages 8 to 12. starts on page 3! starts on page 163!
F a Faa R K 8 12 a a 3! a a 163! 2013 a P, I. ISN 978-1-62416-216-9. N a a a a a, a,. C a a a a P, a 500 a a aa a. W, : F G: K Fa a Q &, a P, I. U. L aa a a a Fa a Q & a. C a 2 (M) Ta H P M (K) Wa P a
More informationAC 2-3 AC 1-1 AC 1-2 CO2 AC 1-3 T CO2 CO2 F ES S I O N RY WO M No.
SHEE OES. OVE PCE HOSS SSOCE PPUCES. VE EW CORO WR. S SE EEVO S EXS. 2. EW SSORS CCOS. S SE EEVO S HOSS. C 2-3 C - C -2 C 2- C -3 C 4- C 2-2 P SUB pproved Filename: :\\2669 RP Performing rts Center HVC\6-C\s\2669-3.dwg
More informationIn order to ensure that an overall development in service by those. of total. rel:rtins lo the wapris are
AhAY ggkhu e evue he eve us wch my be eese s esu eucs ese mbes buges hve bee ke cvu vs. Css e vse e' he w m ceges cec ec css. Dec Dgqs_1q W qge5ee.pe_s_ v V cuss ke ecy 1 hc huse ees. bse cu wc esb shmes.
More informationCptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1
ps 57 Machne Leann School of EES Washnon Sae Unves ps 57 - Machne Leann Assume nsances of classes ae lneal sepaable Esmae paamees of lnea dscmnan If ( - -) > hen + Else - ps 57 - Machne Leann lassfcaon
More informationSoftware Process Models there are many process model s in th e li t e ra t u re, s om e a r e prescriptions and some are descriptions you need to mode
Unit 2 : Software Process O b j ec t i ve This unit introduces software systems engineering through a discussion of software processes and their principal characteristics. In order to achieve the desireable
More information-Z ONGRE::IONAL ACTION ON FY 1987 SUPPLEMENTAL 1/1
-Z-433 6 --OGRE::OA ATO O FY 987 SUPPEMETA / APPR)PRATO RfQUEST PAY AD PROGRAM(U) DE ARTMET OF DEES AS O' D 9J8,:A:SF ED DEFS! WA-H ODM U 7 / A 25 MRGOPf RESOUTO TEST HART / / AD-A 83 96 (~Go w - %A uj
More informationConvexity Preserving C 2 Rational Quadratic Trigonometric Spline
Ieraoal Joural of Scefc a Researc Publcaos, Volume 3, Issue 3, Marc 3 ISSN 5-353 Covexy Preservg C Raoal Quarac Trgoomerc Sple Mrula Dube, Pree Twar Deparme of Maemacs a Compuer Scece, R. D. Uversy, Jabalpur,
More informationFI 2201 Electromagnetism
F Eectomagnetism exane. skana, Ph.D. Physics of Magnetism an Photonics Reseach Goup Magnetostatics MGNET VETOR POTENTL, MULTPOLE EXPNSON Vecto Potentia Just as E pemitte us to intouce a scaa potentia V
More informationA stopping criterion for Richardson s extrapolation scheme. under finite digit arithmetic.
A stoppg crtero for cardso s extrapoato sceme uder fte dgt artmetc MAKOO MUOFUSHI ad HIEKO NAGASAKA epartmet of Lbera Arts ad Sceces Poytecc Uversty 4-1-1 Hasmotoda,Sagamara,Kaagawa 229-1196 JAPAN Abstract:
More informationChapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I
CEE49b Chaper - Free Vbrao of M-Degree-of-Freedo Syses - I Free Udaped Vbrao The basc ype of respose of -degree-of-freedo syses s free daped vbrao Aaogos o sge degree of freedo syses he aayss of free vbrao
More informationParameters Estimation in a General Failure Rate Semi-Markov Reliability Model
Joura of Saca Theory ad Appcao Vo. No. (Sepember ) - Parameer Emao a Geera Faure Rae Sem-Marov Reaby Mode M. Fahzadeh ad K. Khorhda Deparme of Sac Facuy of Mahemaca Scece Va-e-Ar Uvery of Rafaja Rafaja
More informationUpper Bound For Matrix Operators On Some Sequence Spaces
Suama Uer Bou formar Oeraors Uer Bou For Mar Oeraors O Some Sequece Saces Suama Dearme of Mahemacs Gaah Maa Uersy Yogyaara 558 INDONESIA Emal: suama@ugmac masomo@yahoocom Isar D alam aer aa susa masalah
More informationdm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v
Mg: Pcess Aalyss: Reac ae s defed as whee eac ae elcy lue M les ( ccea) e. dm he ube f les ay lue s M, whee ccea M/L les. he he eac ae beces f a hgeeus eac, ( ) d Usually s csa aqueus eeal pcesses eac,
More informationRadioactive Decay and Half Life Simulation 2/17 Integrated Science 2 Redwood High School Name: Period:
Radioactive Decay and Half Life Simulation 2/17 Integrated Science 2 Redwood High School Name: Period: Background I t was not until the end of the 1800 s that scientists found a method for determining
More informationK E L LY T H O M P S O N
K E L LY T H O M P S O N S E A O LO G Y C R E ATO R, F O U N D E R, A N D PA R T N E R K e l l y T h o m p s o n i s t h e c r e a t o r, f o u n d e r, a n d p a r t n e r o f S e a o l o g y, a n e x
More information1. Experimental Methodology
Supporting Information Combining in situ NEXAFS spectroscopy and CO 2 methanation kinetics to study Pt and Co nanoparticle catalysts reveals key insights into the role of platinum in promoted cobalt catalysis.
More informationThe Poisson Process Properties of the Poisson Process
Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad
More informationNon-Equidistant Multi-Variable Optimum Model with Fractional Order Accumulation Based on Vector Continued Fractions Theory and its Application
QIYUN IU NON-EQUIDISN MUI-VRIE OPIMUM MODE WIH FRCION ORDER... No-Equds Mu-V Ou Mod w Fco Od ccuuo sd o Vco Coud Fcos o d s co Qu IU * D YU. S oo o dcd Dsg d Mucu o Vc od Hu Us Cgs Hu 8 C. Cog o Mcc Egg
More informationDangote Flour Mills Plc
SUMMARY OF OFFER Opening Date 6 th September 27 Closing Date 27 th September 27 Shares on Offer 1.25bn Ord. Shares of 5k each Offer Price Offer Size Market Cap (Post Offer) Minimum Offer N15. per share
More informationA DUAL-RECIPROCITY BOUNDARY ELEMENT METHOD FOR ANISOTROPIC HEAT CONDUCTION IN INHOMOGENEOUS SOLIDS
s Ieo ofeece Fo Scefc ou o ouo Eee s I-SE Ahes 8- Seebe 4 I-SE A DUA-REIPROIY BOUDARY EEE EHOD FOR AISOROPI HEA ODUIO I IHOOGEEOUS SOIDS W.. A K. K. hoo Dvso of Eee echcs Schoo of echc Pouco Eee y echooc
More informationSOLUTION TO THE PROBLEM CONTROL OF A DISTRIBUTED PARAMETER PROCESS
DAAA INTERNATIONAL SIENTII BOO pp. 69-86 HAPTER 5 SOLUTION TO THE PROBLE ONTROL O A DISTRIBUTED PARAETER PROESS JADLOVSA A.; ATALINI B.; HRUBINA.; AUROVA A. & WESSELY E. Absrac: The chaper eas wh he ssues
More information