Kinematics Modeling of a 4-DOF Robotic Arm

Size: px
Start display at page:

Download "Kinematics Modeling of a 4-DOF Robotic Arm"

Transcription

1 5 Iteatoal Cofeece o Cotol, Automato ad Robotcs Kematcs Model of a -DOF Robotc Am Am A. Mohammed ad M. Sua Mechacal Eee Depatmet K Fahd Uvey of Petoleum & Meals Dhaha, Saud Aaba e-mal: mehmets@kfupm.edu.sa Abact Ths wok pesets the kematcs model of a RA (a DOF) obotc am. The dect kematc poblem s addessed us both the Deavt-Hatebe (DH) coveto ad the poduct of expoetal fomula, whch s based o the scew theoy. By compa the esults of both appoaches, t tus out that they povde detcal solutos fo the mapulato kematcs. Futhemoe, a alebac soluto of the vese kematcs poblem based o toometc fomulas s also povded. Fally, smulato esults fo the kematcs model us the Matlab poam based o the DH coveto ae peseted. Sce the two appoaches ae detcal, the poduct of expoetal fomula s supposed to poduce same smulato esults o the obotc am uded. Keywods-Robotcs; DH coveto; poduct of expoetals; kematcs; smulatos I. INTRODUCTION Nowadays, obotcs s a ch aea of eseach, tems of the kematcs, dyamcs ad cotol. Kematcs, patcula, plays a sfcat ole obotcs ad especally fo the udy of dual mapulatos' behavo. Theefoe, a decsve ep ay obotcs syem s the aalyss ad model of the mapulato kematcs []. It ca be dvded eeally to fowad ad vese kematcs. The fome efes to dect fd of the ed effecto (EE) poo ad poue fo the ve jot coodates, o the cotay, the latte s the detemato of jot vaables tems of the EE poo ad poue []. I othe wods, t s the pocess of obta a cofuato space that coespods to a ve wok space. It has seveal dscples of applcatos clud the compute aphcs []. Whle the fowad kematcs s ahtfowad, the vese kematcs s ot a easy task ad t usually has multple solutos. Numeous techques ad the combatos could be used fo solv ad aalyz the vese kematcs poblem. Howeve each method besde ts advataes possesses some hadcaps. Theefoe, t s advataeous to apply moe tha oe method ad to teate them wth addtoal pocedues []. Seveal appoaches have bee veated ad compaed by Ades et al []. Jasjt Kau et al [5] have aalyzed ad smulated a obotc am hav thee lks-mapulato, whee the vese kematcs esults two solutos, out of whch the be oe has bee chose wth the usae of the eetc alothm. They have cocluded that the obotc am movemet optmzato ca be acheved by the eetc alothms a pactcal ad effectve way. A eometc appoach to solve the uspecfed jot ales eeded fo the autoomous poo of a obot am s peseted []. Based o few assumptos coce the wok evomet of the mapulato ad the kd of mapulato equed, addto to the basc toomety, a ease soluto has bee poposed. The toduced methodoloy has bee teed us fve deees of feedom obotc am compouded to a -Robot. By cay out the mechacal des, all compoets have bee assembled toethe addto to two faed sesos to detect the object ad to fd ts poo. Fally, the electcal des was doe, ad the poposed method was teed ad jufed. Howeve, ths appoach lacks ts eealty due to the abudat assumptos cosdeed, ad what s moe s that the la lk s ected to ju two oetatos. I what we toduce hee s that the la lk could have ay abtay oetato, whch makes the aalyss moe eeal to dffeet cofuatos. Ge ad J [6] poposed a alothm of a edudat obot kematcs based o poduct of expoetals (PE), whee the fowad ad vese kematcs poblems wee addessed. The vese kematcs poblem was decomposed to seveal sub poblems ad by udy them sepaately, a soluto of the vese kematc poblem was poposed. Kematcs ad teactve smulato syem model fo obot mapulatos s ve [7], whee the fowad ad vese kematcs of a obotc am called Kataa5 ae uded by the expoetal poduct method, the a teactve smulato syem s bult based o thee-met vtual scee model techques poposed fo obot mapulatos. These techques ae OpeGL, VRML ad aothe oe based o Vsual C, Lab Vew ad Matlab platfom. A obot smulato, whch s toduced by Lodes [8] ad s based o Matlab, eables the model of ay obotc am povded that the coespod DH paametes ae kow. Lks vsualzato tems of shape ad sze was made afte some cosdeatos. The poam was show to adequately model seveal example obots. Ths pape focuses o model ad smulato of the RA- obotc am, a small specal obot wth evolute jots [9]. A excellet suvey of obotcs kts fo posecoday educato s ve []. The e of ths pape s oazed as follows: Secto II below pesets the kematcs aalyss based o the DH coveto ad expoetals fomulato. The vese kematcs soluto /5/$. 5 IEEE 87

2 based o the alebac method s ve secto III. I secto IV, the mapulato smulato pocedue ad esults ae peseted. Secto V cocludes ths wok. II. MANIPULATOR KINEMATICS The DH coveto ad poduct of expoetals ofte used kematcs aalyss of obot mapulatos ad othe mechacal uctues. The below secto utlzes both methods to dve the kematcs model of the obot. To smplfy the aalyss, the effect of the ppe s oed mak the obotc am a fou deee of feedom, a fou-jot spatal mapulato. The teatmet of ths mapulato s aaloue to that of PUMA 56 afte emov the w ad add oe moe evolute jot. A. DH Coveto. Deavt-Hatebe (DH) coveto s commoly used the kematcs aalyss of the obotc mapulato []. It s based o attach a coodate fame at each jot ad specfy fou paametes kow as DH paametes fo each lk, ad utlz these paametes to couct a DH table. Fally, a tasfomato matx betwee dffeet coodate fames s obtaed. The majo objectve s to cotol both the poo ad oetato of the EE o the ppe ts wok space. We wll f deve the elatoshp betwee the jot vaables ad the poo, ad oetato of the ppe, us the DH method []. The obotc am ude udy s show below F. (RA-A of Imaes SI Ic [9] ) ad DH paametes F.. Vaous otay ad lea motos of the obotc am ae show below F. Each moto s made possble by a sevomoto (o ju a sevo) at the coespod locato. Fue. Robotc am wth 5 depedet motos [9]. B. Fowad Kematcs As F. depcts a coodate fame attached to evey lk ode to fd ts cofuato the ehbo fames us the d moto fomula. To do so a DH table s eeded as follows: Fame( ) TABLE I. a DH PARAMETERS. a d 9 l l l l Fue. The obot am. By apply the Deavt-Hatebe (DH) otatos [] fo the jots coodates, the DH-table ca be coucted as led above Table II. The lk leths as show F. ae l =.5 cm, l = cm, ad l = l = 9 c m. C. Fowad Tasfomato Matces Oce the DH table s eady, the tasfomato matces ae easy to fd. Geeally, the matx of tasfomato fom the fame B to the fame B fo the adad DH method s ve by []: cos s cos s s a cos s cos cos cos s a s T = s cos d () Fue. DH paametes. The the dvdual tasfomato matces fo =,,, a d ca be easly obtaed. Theeafte, the complete tasfomato T s foud fom: T = T T T T () Upo the detemato of, T we ca fd the lobal coodates of the ed effecto. The tp pot of the am s at the o of fame B (F. ),.e. t s at [ ] T. So, ts poo the lobal fame becomes: 88

3 d x d y p = T p = T = = d z Obvously, ths s the la colum of the tasfomato matx T. Afte smplfcatos us toometc fomulas, the pevous equato becomes: ( ) ( ) () dx = c l c l c l c c ( ) ( ) (5) dy = s l c l c l s c ( ) ( ) (6) dz = l l s l s l s whee s ads fo s () ad c ads fo c o s. I addto, dx, dy ad dz ae the lobal ed effecto coodates. Moeove, the ed effecto oetato s: = (7) The DH paametes ae ak to the cofuato of the obot. Fo dffeet mapulato uctues, the kematcs equatos ae ot uque. Moeove, kematcs equatos of the mapulato based o the DH coveto povde some sulaty mak the equatos dffcult to solve o usolvable some cases. I addto, the DH coveto, the commo omal s ot defed popely whe axes of two jots ae paallel. I ths case, the DH method has a sulaty, whee a lttle chae the spatal coodates of the paallel jot axes ca ceate a hue mscofuato epesetato of the DH coodates of the elatve poo. I the follow secto, a alteatve to the DH coveto, the PE s peseted. D. Poduct of Expoetals Asde fom the DH coveto, aothe method s the socalled poduct of expoetals (PE). Us the ealty that the moto of each jot s eeated by a tw accompaed wth the jot axs, a moe eometc epesetato of the kematcs ca be acqued. Remembe that f ξ s a tw, accod to efeece [], the fowad kematcs s ve by: ˆ ˆ ˆ ( ) = e e... e ( ) (8) The above equato s called the poduct of expoetal fomula fo the obot fowad kematcs, whee ( ) s the fal cofuato of the obot ad expoetal ve by [7]: T ˆ e ( I e )( v ) e = ˆ e s a matx (9) Fo a psmatc jot the tw s ve by: v =, ad fo a evolute jot by: q, = whee R s a ut vecto the decto of the axs of the tw, q R s ay pot o the axs, ad v R s a ut vecto dect the taslato decto. I ths case, the tw ξ s fo dffeet lks of the obot ae ve by: = L = L L = L ( L L ) = Moeove, ( ) s the tal cofuato of the obot ve by s t ( ) l l l = l The fowad kematcs map of the mapulato has the fom: ˆ ( ) ( ) ( ) ( ) ˆ ˆ ˆ R p e e e e = = By expad tems the poduct of expoetals fomula, Eq. yelds R cos( ) cos s s ( ) cos ( ) = cos( ) s cos s ( ) s s ( ) cos( ) ( ( ) L ( )) ( ( ) L ( )) L s ( ) L s L s ( ) cos L cos L cos cos p( ) = s L cos L cos cos L It s clea that the above equato () s detcal to those equatos () thouh (6). Thus, the kematcs model us the DH coveto ad poduct of expoetals aees wth each othe. III. INVERSE KINEMATICS We ed up wth a set of fou olea equatos wth fou ukows. Solv these equatos alebacally, kow as the vese kematcs, eques that we eed to kow the jot vaables,,, a d fo a ve EE poo [ dx, dy, dz ] ad oetato. We et fom equatos () to (7), by dvd, squa, add ad us some toometc fomulas: () () () 89

4 d y = ta () d x ( c c ) ( a b ) = ± () ta, ta, [ / / ] ad [ / / / ] depcted Fs. 6 ad 7, espectvely., whch ae A B C l l = c o s l l (5) whee a = l b = l l c = dz l l ad = a b s, cos, s,. I addto A = ( dx l c c ), B = ( dy l s c ), adc = ( dz l l s ) Hav detemed,, a d, we ca the fd fom the EE oetato of as follows: Fue. Home poo. = (6) IV. SIMULATION OF THE ROBOTIC ARM Sce obotcs s a multdscplay subject, ts udy eques sklls fom dffeet felds of kowlede, ot easly avalable. Thus, smulato has bee ecozed as a sutable tool that combes all these featues toethe eabl the use of a dect vsualzato of dffeet kds of moto that a obot may pefom, mak the ole of smulato vey mpotat obotcs []. Us the obotcs toolbox toethe wth the Matlab softwae []-[5], the kematcs of a obotc am ca be smulated ad aalyzed based o the DH coveto descbed befoe. The toolbox takes a covetoal appoach to epeset the kematcs ad dyamcs of seal-lk obotc ams. Besdes, t povdes seveal fuctos ad outes, whch ae hady fo the smulato ad scuty of obotc mapulatos, lke kematcs, dyamcs ad tajectoy ceato. Based o the afoemetoed toolbox, may cofuatos of the obot mapulato ae easly vsualzed. I ode to smulate the obotc mapulato, f we eect a vecto of Lk objects ad set ou fou oups of DH paametes as Table I. The, these ae passed to the coucto SealLk, whch s the key ep to utlze the toolbox. A detaled pocedue ca be foud [5]. I ode to eeate the plot fou jot vaables ae eeded. I the f case all jot vaables ae eteed the fom of zeos (ow vecto), such as [ ] = [ ]. F. shows e o home poo of the obot, whee all jots vaables ae zeos. I the toolbox, each evolute jot s esembled by a small cylde. Sce we have fou evolute jots, fou cyldes ca be see Fs. -7. A secod tee cofuato s that whe all lks ae ad upht as F. 5 shows. The coespod put ths case s ve by: [ / ], whee all the ales ae defed ada by default. To te the fuctoalty of all the jots, othe two cofuatos ae selected as ve by the vectos of jot vaables Fue 5. Fue 6. Fue 7. Upht poo. Left-dow poo. All jots ae ve ales. V. CONCLUSION Kematcs model of a deee-of-feedom obotc am s peseted us both the DH method ad poduct of expoetals fomula. It s pove that both appoaches povde the same soluto fo the obot mapulato ude udy. I addto, the smulato of the obot mapulato s caed out us the Matlab softwae va the obotcs toolbox, thouh whch seveal poos of the mapulato ae ealzed based o the DH coveto. Althouh esults of the poduct of expoetals fomula ae ot ve, they ae expected to be same as those of the DH coveto. 9

5 ACKNOWLEDGMENT Authos atefully ackowlede the suppot povded by K Fahd Uvey of Petoleum & Meals thouh the NSTIP poject 9-ELE786-. REFERENCES [] K. E. Clothe ad Y. Sha, A Geometc Appoach fo Robotc Am Kematcs wth Hadwae Des, Electcal Des, ad Implemetato, J. Robot.,. [] R. N. Jaza, Theoy of Appled Robotcs. Boo, MA: Spe US,. [] Baka, Lukas, ad Roma Beka. Ivese kematcs-basc methods. Web.< cesc. o/cescg- /LBaka/pape. pdf (). [] A. Adou ad J. Laseby. "Ivese kematcs: a evew of ex techques ad toducto of a ew fa teatve solve," 9. [5] J. Kau ad V. K. Baa, "Smulato of Robotc Am hav thee lk Mapulato," Iteatoal Joual of Reseach Eee ad Techoloy (IJRET), vol., o., Mach,, ISSN: 77-78,. [6] X. F. Ge ad J. T. J, The alothm of edudat obotc kematcs based o expoetal poduct, Appl. Mech. Mate., vol. 58-6, pp. 9-97, Ju.. [7] X. Xao, Y. L, ad H. Ta, Depatmet of electomechacal eee, uvey of Macau, Macao SAR, Cha, IEEE Iteatoal Cofeece o Ifomato ad Automato (ICIA),, pp [8] A. Lodes, Robot Smulato MATLAB, upublshed. [9] [] M. Ruzzeete, M. Koo, K. Nelse, L. Gespa, ad P. Fo, A evew of obotcs kts fo tetay educato, Poceeds of Iteatoal Wokshop Teach Robotcs Teach wth Robotcs: Iteat Robotcs School Cuculum,, pp [] R. M. Muay, Z. L, S. S. Say, ad S. S. Say, A Mathematcal Itoducto to Robotc Mapulato, CRC pess, 99. [] L. Žlajpah, Smulato obotcs, Math. Comput. Smul., vol. 79, o., pp , Dec. 8. [] P. I. Coke ad othes, A compute tool fo smulato ad aalyss: the Robotcs Toolbox fo MATLAB, Poc. Natoal Cof. Auala Robot Assocato, 995, pp. 9-. [] P. I. Coke, Robotcs, Vso ad Cotol: Fudametal Alothms MATLAB. Bel: Spe,. [5] P. Coke, Robotcs, Vso ad Cotol, vol. 7. Bel, Hedelbe: Spe Bel Hedelbe,. 9

Professor Wei Zhu. 1. Sampling from the Normal Population

Professor Wei Zhu. 1. Sampling from the Normal Population AMS570 Pofesso We Zhu. Samplg fom the Nomal Populato *Example: We wsh to estmate the dstbuto of heghts of adult US male. It s beleved that the heght of adult US male follows a omal dstbuto N(, ) Def. Smple

More information

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi Assgmet /MATH 47/Wte Due: Thusday Jauay The poblems to solve ae umbeed [] to [] below Fst some explaatoy otes Fdg a bass of the colum-space of a max ad povg that the colum ak (dmeso of the colum space)

More information

Kinematics. Redundancy. Task Redundancy. Operational Coordinates. Generalized Coordinates. m task. Manipulator. Operational point

Kinematics. Redundancy. Task Redundancy. Operational Coordinates. Generalized Coordinates. m task. Manipulator. Operational point Mapulato smatc Jot Revolute Jot Kematcs Base Lks: movg lk fed lk Ed-Effecto Jots: Revolute ( DOF) smatc ( DOF) Geealzed Coodates Opeatoal Coodates O : Opeatoal pot 5 costats 6 paametes { postos oetatos

More information

The Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof

The Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof MATEC Web of Cofeeces ICIEA 06 600 (06) DOI: 0.05/mateccof/0668600 The ea Pobablty Desty Fucto of Cotuous Radom Vaables the Real Numbe Feld ad Its Estece Poof Yya Che ad Ye Collee of Softwae, Taj Uvesty,

More information

On EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx

On EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx Iteatoal Joual of Mathematcs ad Statstcs Iveto (IJMSI) E-ISSN: 3 4767 P-ISSN: 3-4759 www.jms.og Volume Issue 5 May. 4 PP-44-5 O EP matces.ramesh, N.baas ssocate Pofesso of Mathematcs, ovt. ts College(utoomous),Kumbakoam.

More information

Minimum Hyper-Wiener Index of Molecular Graph and Some Results on Szeged Related Index

Minimum Hyper-Wiener Index of Molecular Graph and Some Results on Szeged Related Index Joual of Multdscplay Egeeg Scece ad Techology (JMEST) ISSN: 359-0040 Vol Issue, Febuay - 05 Mmum Hype-Wee Idex of Molecula Gaph ad Some Results o eged Related Idex We Gao School of Ifomato Scece ad Techology,

More information

Fairing of Parametric Quintic Splines

Fairing of Parametric Quintic Splines ISSN 46-69 Eglad UK Joual of Ifomato ad omputg Scece Vol No 6 pp -8 Fag of Paametc Qutc Sples Yuau Wag Shagha Isttute of Spots Shagha 48 ha School of Mathematcal Scece Fuda Uvesty Shagha 4 ha { P t )}

More information

VECTOR MECHANICS FOR ENGINEERS: Vector Mechanics for Engineers: Dynamics. In the current chapter, you will study the motion of systems of particles.

VECTOR MECHANICS FOR ENGINEERS: Vector Mechanics for Engineers: Dynamics. In the current chapter, you will study the motion of systems of particles. Seeth Edto CHPTER 4 VECTOR MECHNICS FOR ENINEERS: DYNMICS Fedad P. ee E. Russell Johsto, J. Systems of Patcles Lectue Notes: J. Walt Ole Texas Tech Uesty 003 The Mcaw-Hll Compaes, Ic. ll ghts eseed. Seeth

More information

XII. Addition of many identical spins

XII. Addition of many identical spins XII. Addto of may detcal sps XII.. ymmetc goup ymmetc goup s the goup of all possble pemutatos of obects. I total! elemets cludg detty opeato. Each pemutato s a poduct of a ceta fte umbe of pawse taspostos.

More information

The Exponentiated Lomax Distribution: Different Estimation Methods

The Exponentiated Lomax Distribution: Different Estimation Methods Ameca Joual of Appled Mathematcs ad Statstcs 4 Vol. No. 6 364-368 Avalable ole at http://pubs.scepub.com/ajams//6/ Scece ad Educato Publshg DOI:.69/ajams--6- The Expoetated Lomax Dstbuto: Dffeet Estmato

More information

= y and Normed Linear Spaces

= y and Normed Linear Spaces 304-50 LINER SYSTEMS Lectue 8: Solutos to = ad Nomed Lea Spaces 73 Fdg N To fd N, we eed to chaacteze all solutos to = 0 Recall that ow opeatos peseve N, so that = 0 = 0 We ca solve = 0 ecusvel backwads

More information

Minimizing spherical aberrations Exploiting the existence of conjugate points in spherical lenses

Minimizing spherical aberrations Exploiting the existence of conjugate points in spherical lenses Mmzg sphecal abeatos Explotg the exstece of cojugate pots sphecal leses Let s ecall that whe usg asphecal leses, abeato fee magg occus oly fo a couple of, so called, cojugate pots ( ad the fgue below)

More information

Non-axial symmetric loading on axial symmetric. Final Report of AFEM

Non-axial symmetric loading on axial symmetric. Final Report of AFEM No-axal symmetc loadg o axal symmetc body Fal Repot of AFEM Ths poject does hamoc aalyss of o-axal symmetc loadg o axal symmetc body. Shuagxg Da, Musket Kamtokat 5//009 No-axal symmetc loadg o axal symmetc

More information

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1 Scholas Joual of Egeeg ad Techology (SJET) Sch. J. Eg. Tech. 0; (C):669-67 Scholas Academc ad Scetfc Publshe (A Iteatoal Publshe fo Academc ad Scetfc Resouces) www.saspublshe.com ISSN -X (Ole) ISSN 7-9

More information

GREEN S FUNCTION FOR HEAT CONDUCTION PROBLEMS IN A MULTI-LAYERED HOLLOW CYLINDER

GREEN S FUNCTION FOR HEAT CONDUCTION PROBLEMS IN A MULTI-LAYERED HOLLOW CYLINDER Joual of ppled Mathematcs ad Computatoal Mechacs 4, 3(3), 5- GREE S FUCTIO FOR HET CODUCTIO PROBLEMS I MULTI-LYERED HOLLOW CYLIDER Stasław Kukla, Uszula Sedlecka Isttute of Mathematcs, Czestochowa Uvesty

More information

University of Pavia, Pavia, Italy. North Andover MA 01845, USA

University of Pavia, Pavia, Italy. North Andover MA 01845, USA Iteatoal Joual of Optmzato: heoy, Method ad Applcato 27-5565(Pt) 27-6839(Ole) wwwgph/otma 29 Global Ifomato Publhe (HK) Co, Ltd 29, Vol, No 2, 55-59 η -Peudoleaty ad Effcecy Gogo Gog, Noma G Rueda 2 *

More information

An Unconstrained Q - G Programming Problem and its Application

An Unconstrained Q - G Programming Problem and its Application Joual of Ifomato Egeeg ad Applcatos ISS 4-578 (pt) ISS 5-0506 (ole) Vol.5, o., 05 www.ste.og A Ucostaed Q - G Pogammg Poblem ad ts Applcato M. He Dosh D. Chag Tved.Assocate Pofesso, H L College of Commece,

More information

Trace of Positive Integer Power of Adjacency Matrix

Trace of Positive Integer Power of Adjacency Matrix Global Joual of Pue ad Appled Mathematcs. IN 097-78 Volume, Numbe 07), pp. 079-087 Reseach Ida Publcatos http://www.publcato.com Tace of Postve Itege Powe of Adacecy Matx Jagdsh Kuma Pahade * ad Mao Jha

More information

Atomic units The atomic units have been chosen such that the fundamental electron properties are all equal to one atomic unit.

Atomic units The atomic units have been chosen such that the fundamental electron properties are all equal to one atomic unit. tomc uts The atomc uts have bee chose such that the fudametal electo popetes ae all equal to oe atomc ut. m e, e, h/, a o, ad the potetal eegy the hydoge atom e /a o. D3.33564 0-30 Cm The use of atomc

More information

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures.

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures. Lectue 4 8. MRAC Desg fo Affe--Cotol MIMO Systes I ths secto, we cosde MRAC desg fo a class of ult-ut-ult-outut (MIMO) olea systes, whose lat dyacs ae lealy aaetezed, the ucetates satsfy the so-called

More information

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S Fomulae Fo u Pobablty By OP Gupta [Ida Awad We, +91-9650 350 480] Impotat Tems, Deftos & Fomulae 01 Bascs Of Pobablty: Let S ad E be the sample space ad a evet a expemet espectvely Numbe of favouable evets

More information

Exponential Generating Functions - J. T. Butler

Exponential Generating Functions - J. T. Butler Epoetal Geeatg Fuctos - J. T. Butle Epoetal Geeatg Fuctos Geeatg fuctos fo pemutatos. Defto: a +a +a 2 2 + a + s the oday geeatg fucto fo the sequece of teges (a, a, a 2, a, ). Ep. Ge. Fuc.- J. T. Butle

More information

Council for Innovative Research

Council for Innovative Research Geometc-athmetc Idex ad Zageb Idces of Ceta Specal Molecula Gaphs efe X, e Gao School of Tousm ad Geogaphc Sceces, Yua Nomal Uesty Kumg 650500, Cha School of Ifomato Scece ad Techology, Yua Nomal Uesty

More information

The Geometric Proof of the Hecke Conjecture

The Geometric Proof of the Hecke Conjecture The Geometc Poof of the Hecke Cojectue Kada Sh Depatmet of Mathematc Zhejag Ocea Uvety Zhouha Cty 6 Zhejag Povce Cha Atact Begg fom the eoluto of Dchlet fucto ug the e poduct fomula of two fte-dmeoal vecto

More information

This may involve sweep, revolution, deformation, expansion and forming joints with other curves.

This may involve sweep, revolution, deformation, expansion and forming joints with other curves. 5--8 Shapes ae ceated by cves that a sface sch as ooftop of a ca o fselage of a acaft ca be ceated by the moto of cves space a specfed mae. Ths may volve sweep, evolto, defomato, expaso ad fomg jots wth

More information

FIBONACCI-LIKE SEQUENCE ASSOCIATED WITH K-PELL, K-PELL-LUCAS AND MODIFIED K-PELL SEQUENCES

FIBONACCI-LIKE SEQUENCE ASSOCIATED WITH K-PELL, K-PELL-LUCAS AND MODIFIED K-PELL SEQUENCES Joual of Appled Matheatcs ad Coputatoal Mechacs 7, 6(), 59-7 www.ac.pcz.pl p-issn 99-9965 DOI:.75/jac.7..3 e-issn 353-588 FIBONACCI-LIKE SEQUENCE ASSOCIATED WITH K-PELL, K-PELL-LUCAS AND MODIFIED K-PELL

More information

CHAPTER 5 : SERIES. 5.2 The Sum of a Series Sum of Power of n Positive Integers Sum of Series of Partial Fraction Difference Method

CHAPTER 5 : SERIES. 5.2 The Sum of a Series Sum of Power of n Positive Integers Sum of Series of Partial Fraction Difference Method CHAPTER 5 : SERIES 5.1 Seies 5. The Sum of a Seies 5..1 Sum of Powe of Positive Iteges 5.. Sum of Seies of Patial Factio 5..3 Diffeece Method 5.3 Test of covegece 5.3.1 Divegece Test 5.3. Itegal Test 5.3.3

More information

Best Linear Unbiased Estimators of the Three Parameter Gamma Distribution using doubly Type-II censoring

Best Linear Unbiased Estimators of the Three Parameter Gamma Distribution using doubly Type-II censoring Best Lea Ubased Estmatos of the hee Paamete Gamma Dstbuto usg doubly ype-ii cesog Amal S. Hassa Salwa Abd El-Aty Abstact Recetly ode statstcs ad the momets have assumed cosdeable teest may applcatos volvg

More information

Motion and Flow II. Structure from Motion. Passive Navigation and Structure from Motion. rot

Motion and Flow II. Structure from Motion. Passive Navigation and Structure from Motion. rot Moto ad Flow II Sce fom Moto Passve Navgato ad Sce fom Moto = + t, w F = zˆ t ( zˆ ( ([ ] =? hesystemmoveswth a gd moto wth aslat oal velocty t = ( U, V, W ad atoalvelocty w = ( α, β, γ. Scee pots R =

More information

Lecture 10: Condensed matter systems

Lecture 10: Condensed matter systems Lectue 0: Codesed matte systems Itoducg matte ts codesed state.! Ams: " Idstgushable patcles ad the quatum atue of matte: # Cosequeces # Revew of deal gas etopy # Femos ad Bosos " Quatum statstcs. # Occupato

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

By the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences

By the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences Chapte : Theoy of Modula Aithmetic 8 Sectio D Chiese Remaide Theoem By the ed of this sectio you will be able to pove the Chiese Remaide Theoem apply this theoem to solve simultaeous liea cogueces The

More information

APPROXIMATE ANALYTIC WAVE FUNCTION METHOD IN ELECTRON ATOM SCATTERING CALCULATIONS. Budi Santoso

APPROXIMATE ANALYTIC WAVE FUNCTION METHOD IN ELECTRON ATOM SCATTERING CALCULATIONS. Budi Santoso APPROXIMATE ANALYTIC WAVE FUNCTION METHOD IN ELECTRON ATOM SCATTERING CALCULATIONS Bud Satoso ABSTRACT APPROXIMATE ANALYTIC WAVE FUNCTION METHOD IN ELECTRON ATOM SCATTERING CALCULATIONS. Appoxmate aalytc

More information

Harmonic Curvatures in Lorentzian Space

Harmonic Curvatures in Lorentzian Space BULLETIN of the Bull Malaya Math Sc Soc Secod See 7-79 MALAYSIAN MATEMATICAL SCIENCES SOCIETY amoc Cuvatue Loetza Space NEJAT EKMEKÇI ILMI ACISALIOĞLU AND KĀZIM İLARSLAN Aaa Uvety Faculty of Scece Depatmet

More information

The calculation of the characteristic and non-characteristic harmonic current of the rectifying system

The 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 information

Multivector Functions

Multivector Functions I: J. Math. Aal. ad Appl., ol. 24, No. 3, c Academic Pess (968) 467 473. Multivecto Fuctios David Hestees I a pevious pape [], the fudametals of diffeetial ad itegal calculus o Euclidea -space wee expessed

More information

Lecture 9 Multiple Class Models

Lecture 9 Multiple Class Models Lectue 9 Multple Class Models Multclass MVA Appoxmate MVA 8.4.2002 Copyght Teemu Keola 2002 1 Aval Theoem fo Multple Classes Wth jobs the system, a job class avg to ay seve sees the seve as equlbum wth

More information

Inequalities for Dual Orlicz Mixed Quermassintegrals.

Inequalities for Dual Orlicz Mixed Quermassintegrals. Advaces Pue Mathematcs 206 6 894-902 http://wwwscpog/joual/apm IN Ole: 260-0384 IN Pt: 260-0368 Iequaltes fo Dual Olcz Mxed Quemasstegals jua u chool of Mathematcs ad Computatoal cece Hua Uvesty of cece

More information

THREE-PARAMETRIC LOGNORMAL DISTRIBUTION AND ESTIMATING ITS PARAMETERS USING THE METHOD OF L-MOMENTS

THREE-PARAMETRIC LOGNORMAL DISTRIBUTION AND ESTIMATING ITS PARAMETERS USING THE METHOD OF L-MOMENTS RELIK ; Paha 5. a 6.. THREE-PARAMETRIC LOGNORMAL DISTRIBUTION AND ESTIMATING ITS PARAMETERS USING THE METHOD OF L-MOMENTS Daa Bílová Abstact Commo statstcal methodology fo descpto of the statstcal samples

More information

Phys 2310 Fri. Oct. 23, 2017 Today s Topics. Begin Chapter 6: More on Geometric Optics Reading for Next Time

Phys 2310 Fri. Oct. 23, 2017 Today s Topics. Begin Chapter 6: More on Geometric Optics Reading for Next Time Py F. Oct., 7 Today Topc Beg Capte 6: Moe o Geometc Optc eadg fo Next Tme Homewok t Week HW # Homewok t week due Mo., Oct. : Capte 4: #47, 57, 59, 6, 6, 6, 6, 67, 7 Supplemetal: Tck ee ad e Sytem Pcple

More information

A. Thicknesses and Densities

A. Thicknesses and Densities 10 Lab0 The Eath s Shells A. Thcknesses and Denstes Any theoy of the nteo of the Eath must be consstent wth the fact that ts aggegate densty s 5.5 g/cm (ecall we calculated ths densty last tme). In othe

More information

Chapter 2: Descriptive Statistics

Chapter 2: Descriptive Statistics Chapte : Decptve Stattc Peequte: Chapte. Revew of Uvaate Stattc The cetal teecy of a oe o le yetc tbuto of a et of teval, o hghe, cale coe, ofte uaze by the athetc ea, whch efe a We ca ue the ea to ceate

More information

MATH Midterm Solutions

MATH Midterm Solutions MATH 2113 - Midtem Solutios Febuay 18 1. A bag of mables cotais 4 which ae ed, 4 which ae blue ad 4 which ae gee. a How may mables must be chose fom the bag to guaatee that thee ae the same colou? We ca

More information

Multistage Median Ranked Set Sampling for Estimating the Population Median

Multistage Median Ranked Set Sampling for Estimating the Population Median Jounal of Mathematcs and Statstcs 3 (: 58-64 007 ISSN 549-3644 007 Scence Publcatons Multstage Medan Ranked Set Samplng fo Estmatng the Populaton Medan Abdul Azz Jeman Ame Al-Oma and Kamaulzaman Ibahm

More information

Application Of Alternating Group Explicit Method For Parabolic Equations

Application Of Alternating Group Explicit Method For Parabolic Equations WSEAS RANSACIONS o INFORMAION SCIENCE ad APPLICAIONS Qghua Feg Applcato Of Alteatg oup Explct Method Fo Paabolc Equatos Qghua Feg School of Scece Shadog uvesty of techology Zhagzhou Road # Zbo Shadog 09

More information

Recent Advances in Computers, Communications, Applied Social Science and Mathematics

Recent Advances in Computers, Communications, Applied Social Science and Mathematics Recet Advaces Computes, Commucatos, Appled ocal cece ad athematcs Coutg Roots of Radom Polyomal Equatos mall Itevals EFRAI HERIG epatmet of Compute cece ad athematcs Ael Uvesty Cete of amaa cece Pa,Ael,4487

More information

ON THE CONVERGENCE THEOREMS OF THE McSHANE INTEGRAL FOR RIESZ-SPACES-VALUED FUNCTIONS DEFINED ON REAL LINE

ON THE CONVERGENCE THEOREMS OF THE McSHANE INTEGRAL FOR RIESZ-SPACES-VALUED FUNCTIONS DEFINED ON REAL LINE O The Covegece Theoems... (Muslm Aso) ON THE CONVERGENCE THEOREMS OF THE McSHANE INTEGRAL FOR RIESZ-SPACES-VALUED FUNCTIONS DEFINED ON REAL LINE Muslm Aso, Yosephus D. Sumato, Nov Rustaa Dew 3 ) Mathematcs

More information

NUMERICAL SIMULATION OF TSUNAMI CURRENTS AROUND MOVING STRUCTURES

NUMERICAL SIMULATION OF TSUNAMI CURRENTS AROUND MOVING STRUCTURES NUMERICAL SIMULATION OF TSUNAMI CURRENTS AROUND MOVING STRUCTURES Ezo Nakaza 1, Tsuakyo Ibe ad Muhammad Abdu Rouf 1 The pape ams to smulate Tsuam cuets aoud movg ad fxed stuctues usg the movg-patcle semmplct

More information

A DATA DRIVEN PARAMETER ESTIMATION FOR THE THREE- PARAMETER WEIBULL POPULATION FROM CENSORED SAMPLES

A DATA DRIVEN PARAMETER ESTIMATION FOR THE THREE- PARAMETER WEIBULL POPULATION FROM CENSORED SAMPLES Mathematcal ad Computatoal Applcatos, Vol. 3, No., pp. 9-36 008. Assocato fo Scetfc Reseach A DATA DRIVEN PARAMETER ESTIMATION FOR THE THREE- PARAMETER WEIBULL POPULATION FROM CENSORED SAMPLES Ahmed M.

More information

Chapter 5 Force and Motion

Chapter 5 Force and Motion Chapte 5 Foce and Motion In chaptes 2 and 4 we have studied kinematics i.e. descibed the motion of objects using paametes such as the position vecto, velocity and acceleation without any insights as to

More information

χ be any function of X and Y then

χ be any function of X and Y then We have show that whe we ae gve Y g(), the [ ] [ g() ] g() f () Y o all g ()() f d fo dscete case Ths ca be eteded to clude fuctos of ay ube of ado vaables. Fo eaple, suppose ad Y ae.v. wth jot desty fucto,

More information

SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES

SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES #A17 INTEGERS 9 2009), 181-190 SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES Deick M. Keiste Depatmet of Mathematics, Pe State Uivesity, Uivesity Pak, PA 16802 dmk5075@psu.edu James A. Selles Depatmet

More information

Distribution of Geometrically Weighted Sum of Bernoulli Random Variables

Distribution of Geometrically Weighted Sum of Bernoulli Random Variables Appled Mathematc, 0,, 8-86 do:046/am095 Publhed Ole Novembe 0 (http://wwwscrpog/oual/am) Dtbuto of Geometcally Weghted Sum of Beoull Radom Vaable Abtact Deepeh Bhat, Phazamle Kgo, Ragaath Naayaachaya Ratthall

More information

Using Counting Techniques to Determine Probabilities

Using Counting Techniques to Determine Probabilities Kowledge ticle: obability ad Statistics Usig outig Techiques to Detemie obabilities Tee Diagams ad the Fudametal outig iciple impotat aspect of pobability theoy is the ability to detemie the total umbe

More information

Learning Bayesian belief networks

Learning Bayesian belief networks Lectue 6 Leag Bayesa belef etwoks Mlos Hauskecht mlos@cs.ptt.edu 5329 Seott Squae Admstato Mdtem: Wedesday, Mach 7, 2004 I class Closed book Mateal coveed by Spg beak, cludg ths lectue Last yea mdtem o

More information

FUZZY MULTINOMIAL CONTROL CHART WITH VARIABLE SAMPLE SIZE

FUZZY MULTINOMIAL CONTROL CHART WITH VARIABLE SAMPLE SIZE A. Paduaga et al. / Iteatoal Joual of Egeeg Scece ad Techology (IJEST) FUZZY MUTINOMIA CONTRO CHART WITH VARIABE SAMPE SIZE A. PANDURANGAN Pofesso ad Head Depatmet of Compute Applcatos Vallamma Egeeg College,

More information

Objectives. Learning Outcome. 7.1 Centre of Gravity (C.G.) 7. Statics. Determine the C.G of a lamina (Experimental method)

Objectives. Learning Outcome. 7.1 Centre of Gravity (C.G.) 7. Statics. Determine the C.G of a lamina (Experimental method) Ojectves 7 Statcs 7. Cete of Gavty 7. Equlum of patcles 7.3 Equlum of g oes y Lew Sau oh Leag Outcome (a) efe cete of gavty () state the coto whch the cete of mass s the cete of gavty (c) state the coto

More information

New Vector Description of Kinetic Pressures on Shaft Bearings of a Rigid Body Nonlinear Dynamics with Coupled Rotations around No Intersecting Axes

New Vector Description of Kinetic Pressures on Shaft Bearings of a Rigid Body Nonlinear Dynamics with Coupled Rotations around No Intersecting Axes Acta Polytechca Hugaca Vol. No. 7 3 New Vecto escpto of Ketc Pessues o haft eags of a gd ody Nolea yamcs wth oupled otatos aoud No Itesectg Axes Katca. tevaovć Hedh* Ljljaa Veljovć** *Mathematcal Isttute

More information

Range Symmetric Matrices in Minkowski Space

Range Symmetric Matrices in Minkowski Space BULLETIN of the Bull. alaysia ath. Sc. Soc. (Secod Seies) 3 (000) 45-5 LYSIN THETICL SCIENCES SOCIETY Rae Symmetic atices i ikowski Space.R. EENKSHI Depatmet of athematics, amalai Uivesity, amalaiaa 608

More information

Chapter 5 Force and Motion

Chapter 5 Force and Motion Chapte 5 Foce and Motion In Chaptes 2 and 4 we have studied kinematics, i.e., we descibed the motion of objects using paametes such as the position vecto, velocity, and acceleation without any insights

More information

Lecture 11: Introduction to nonlinear optics I.

Lecture 11: Introduction to nonlinear optics I. Lectue : Itoducto to olea optcs I. Pet Kužel Fomulato of the olea optcs: olea polazato Classfcato of the olea pheomea Popagato of wea optc sgals stog quas-statc felds (descpto usg eomalzed lea paametes)!

More information

Chapter 7 Varying Probability Sampling

Chapter 7 Varying Probability Sampling Chapte 7 Vayg Pobablty Samplg The smple adom samplg scheme povdes a adom sample whee evey ut the populato has equal pobablty of selecto. Ude ceta ccumstaces, moe effcet estmatos ae obtaed by assgg uequal

More information

φ (x,y,z) in the direction of a is given by

φ (x,y,z) in the direction of a is given by UNIT-II VECTOR CALCULUS Dectoal devatve The devatve o a pot ucto (scala o vecto) a patcula decto s called ts dectoal devatve alo the decto. The dectoal devatve o a scala pot ucto a ve decto s the ate o

More information

VIII Dynamics of Systems of Particles

VIII Dynamics of Systems of Particles VIII Dyacs of Systes of Patcles Cete of ass: Cete of ass Lea oetu of a Syste Agula oetu of a syste Ketc & Potetal Eegy of a Syste oto of Two Iteactg Bodes: The Reduced ass Collsos: o Elastc Collsos R whee:

More information

Sensorless A.C. Drive with Vector Controlled Synchronous Motor

Sensorless A.C. Drive with Vector Controlled Synchronous Motor Seole A.C. Dve wth Vecto Cotolle Sychoo Moto Ořej Fše VŠB-echcal Uvety of Otava, Faclty of Electcal Egeeg a Ifomatc, Deatmet of Powe Electoc a Electcal Dve, 17.ltoa 15, 78 33 Otava-Poba, Czech eblc oej.fe@vb.cz

More information

Hyper-wiener index of gear fan and gear wheel related graph

Hyper-wiener index of gear fan and gear wheel related graph Iteatoal Joual of Chemcal Studes 015; (5): 5-58 P-ISSN 49 858 E-ISSN 1 490 IJCS 015; (5): 5-58 014 JEZS Receed: 1-0-015 Accepted: 15-0-015 We Gao School of Ifomato Scece ad Techology, Yua Nomal Uesty,

More information

CHAPTER 4 RADICAL EXPRESSIONS

CHAPTER 4 RADICAL EXPRESSIONS 6 CHAPTER RADICAL EXPRESSIONS. The th Root of a Real Number A real umber a s called the th root of a real umber b f Thus, for example: s a square root of sce. s also a square root of sce ( ). s a cube

More information

Estimation of Parameters of the Exponential Geometric Distribution with Presence of Outliers Generated from Uniform Distribution

Estimation of Parameters of the Exponential Geometric Distribution with Presence of Outliers Generated from Uniform Distribution ustala Joual of Basc ad ppled Sceces, 6(: 98-6, ISSN 99-878 Estmato of Paametes of the Epoetal Geometc Dstbuto wth Pesece of Outles Geeated fom Ufom Dstbuto Pavz Nas, l Shadoh ad Hassa Paza Depatmet of

More information

AIRCRAFT EQUIVALENT VULNERABLE AREA CALCULATION METHODS

AIRCRAFT EQUIVALENT VULNERABLE AREA CALCULATION METHODS 4 TH ITERATIOAL COGRESS OF THE AEROAUTICAL SCIECES AIRCRAFT EQUIVALET VULERABLE AREA CALCULATIO METHODS PEI Yag*, SOG B-Feg*, QI Yg ** *College of Aeoautcs, othweste Polytechcal Uvesty, X a, Cha, ** Depatmet

More information

1 Solution to Problem 6.40

1 Solution to Problem 6.40 1 Soluto to Problem 6.40 (a We wll wrte T τ (X 1,...,X where the X s are..d. wth PDF f(x µ, σ 1 ( x µ σ g, σ where the locato parameter µ s ay real umber ad the scale parameter σ s > 0. Lettg Z X µ σ we

More information

2012 GCE A Level H2 Maths Solution Paper Let x,

2012 GCE A Level H2 Maths Solution Paper Let x, GCE A Level H Maths Solutio Pape. Let, y ad z be the cost of a ticet fo ude yeas, betwee ad 5 yeas, ad ove 5 yeas categoies espectively. 9 + y + 4z =. 7 + 5y + z = 8. + 4y + 5z = 58.5 Fo ude, ticet costs

More information

Journal of Engineering Science and Technology Review 7 (2) (2014) Research Article

Journal of Engineering Science and Technology Review 7 (2) (2014) Research Article Jest Joual of Egeeg Scece ad echology Revew 7 () (4) 75 8 Reseach Atcle JOURNAL OF Egeeg Scece ad echology Revew www.jest.og Fuzzy Backsteppg Sldg Mode Cotol fo Msmatched Uceta System H. Q. Hou,*, Q. Mao,

More information

Lecture 12: Spiral: Domain Specific HLS. Housekeeping

Lecture 12: Spiral: Domain Specific HLS. Housekeeping 8 643 ectue : Spal: Doma Specfc HS James C. Hoe Depatmet of ECE Caege Mello Uvesty 8 643 F7 S, James C. Hoe, CMU/ECE/CACM, 7 Houseeepg You goal today: see a eample of eally hghlevel sythess (ths lectue

More information

Chapter 3: Theory of Modular Arithmetic 38

Chapter 3: Theory of Modular Arithmetic 38 Chapte 3: Theoy of Modula Aithmetic 38 Section D Chinese Remainde Theoem By the end of this section you will be able to pove the Chinese Remainde Theoem apply this theoem to solve simultaneous linea conguences

More information

ASYMPTOTICS OF THE GENERALIZED STATISTICS FOR TESTING THE HYPOTHESIS UNDER RANDOM CENSORING

ASYMPTOTICS OF THE GENERALIZED STATISTICS FOR TESTING THE HYPOTHESIS UNDER RANDOM CENSORING IJRRAS 3 () Novembe www.apape.com/volume/vol3iue/ijrras_3.pdf ASYMPOICS OF HE GENERALIZE SAISICS FOR ESING HE HYPOHESIS UNER RANOM CENSORING A.A. Abduhukuov & N.S. Numuhamedova Natoal Uvety of Uzbekta

More information

Auchmuty High School Mathematics Department Sequences & Series Notes Teacher Version

Auchmuty High School Mathematics Department Sequences & Series Notes Teacher Version equeces ad eies Auchmuty High chool Mathematics Depatmet equeces & eies Notes Teache Vesio A sequece takes the fom,,7,0,, while 7 0 is a seies. Thee ae two types of sequece/seies aithmetic ad geometic.

More information

CE 561 Lecture Notes. Optimal Timing of Investment. Set 3. Case A- C is const. cost in 1 st yr, benefits start at the end of 1 st yr

CE 561 Lecture Notes. Optimal Timing of Investment. Set 3. Case A- C is const. cost in 1 st yr, benefits start at the end of 1 st yr CE 56 Letue otes Set 3 Optmal Tmg of Ivestmet Case A- C s ost. ost st y, beefts stat at the ed of st y C b b b3 0 3 Case B- Cost. s postpoed by oe yea C b b3 0 3 (B-A C s saved st yea C C, b b 0 3 Savg

More information

A New Approach to Moments Inequalities for NRBU and RNBU Classes With Hypothesis Testing Applications

A New Approach to Moments Inequalities for NRBU and RNBU Classes With Hypothesis Testing Applications Iteatoal Joual of Basc & Appled Sceces IJBAS-IJENS Vol: No:6 7 A New Appoach to Momets Iequaltes fo NRBU ad RNBU Classes Wth Hypothess Testg Applcatos L S Dab Depatmet of Mathematcs aculty of Scece Al-Azha

More information

Ch 3.4 Binomial Coefficients. Pascal's Identit y and Triangle. Chapter 3.2 & 3.4. South China University of Technology

Ch 3.4 Binomial Coefficients. Pascal's Identit y and Triangle. Chapter 3.2 & 3.4. South China University of Technology Disc ete Mathem atic Chapte 3: Coutig 3. The Pigeohole Piciple 3.4 Biomial Coefficiets D Patic Cha School of Compute Sciece ad Egieeig South Chia Uivesity of Techology Pigeohole Piciple Suppose that a

More information

Counting Functions and Subsets

Counting Functions and Subsets CHAPTER 1 Coutig Fuctios ad Subsets This chapte of the otes is based o Chapte 12 of PJE See PJE p144 Hee ad below, the efeeces to the PJEccles book ae give as PJE The goal of this shot chapte is to itoduce

More information

Multivariate Transformation of Variables and Maximum Likelihood Estimation

Multivariate Transformation of Variables and Maximum Likelihood Estimation Marquette Uversty Multvarate Trasformato of Varables ad Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Assocate Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 03 by Marquette Uversty

More information

PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM

PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM Joual o Mathematcal Sceces: Advaces ad Applcatos Volume 6 Numbe 00 Pages 77-9 PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM DAU XUAN LUONG ad TRAN VAN AN Depatmet o Natual Sceces Quag Nh

More information

Numerical Solution of Non-equilibrium Hypersonic Flows of Diatomic Gases Using the Generalized Boltzmann Equation

Numerical Solution of Non-equilibrium Hypersonic Flows of Diatomic Gases Using the Generalized Boltzmann Equation Recet Advaces Flud Mechacs, Heat & Mass asfe ad Bology Numecal Soluto of No-equlbum Hypesoc Flows of Datomc Gases Usg the Geealzed Boltzma Equato RAMESH K. AGARWAL Depatmet of Mechacal Egeeg ad Mateals

More information

L-MOMENTS EVALUATION FOR IDENTICALLY AND NONIDENTICALLY WEIBULL DISTRIBUTED RANDOM VARIABLES

L-MOMENTS EVALUATION FOR IDENTICALLY AND NONIDENTICALLY WEIBULL DISTRIBUTED RANDOM VARIABLES THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Sees A, OF THE ROMANIAN ACADEMY Volume 8, Numbe 3/27,. - L-MOMENTS EVALUATION FOR IDENTICALLY AND NONIDENTICALLY WEIBULL DISTRIBUTED RANDOM VARIABLES

More information

The Pigeonhole Principle 3.4 Binomial Coefficients

The Pigeonhole Principle 3.4 Binomial Coefficients Discete M athematic Chapte 3: Coutig 3. The Pigeohole Piciple 3.4 Biomial Coefficiets D Patic Cha School of Compute Sciece ad Egieeig South Chia Uivesity of Techology Ageda Ch 3. The Pigeohole Piciple

More information

SUPPLEMENTARY MATERIAL CHAPTER 7 A (2 ) B. a x + bx + c dx

SUPPLEMENTARY MATERIAL CHAPTER 7 A (2 ) B. a x + bx + c dx SUPPLEMENTARY MATERIAL 613 7.6.3 CHAPTER 7 ( px + q) a x + bx + c dx. We choose constants A and B such that d px + q A ( ax + bx + c) + B dx A(ax + b) + B Compaing the coefficients of x and the constant

More information

2.1.1 The Art of Estimation Examples of Estimators Properties of Estimators Deriving Estimators Interval Estimators

2.1.1 The Art of Estimation Examples of Estimators Properties of Estimators Deriving Estimators Interval Estimators . ploatoy Statstcs. Itoducto to stmato.. The At of stmato.. amples of stmatos..3 Popetes of stmatos..4 Devg stmatos..5 Iteval stmatos . Itoducto to stmato Samplg - The samplg eecse ca be epeseted by a

More information

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT

ON 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 information

Part V: Velocity and Acceleration Analysis of Mechanisms

Part V: Velocity and Acceleration Analysis of Mechanisms Pat V: Velocty an Acceleaton Analyss of Mechansms Ths secton wll evew the most common an cuently pactce methos fo completng the knematcs analyss of mechansms; escbng moton though velocty an acceleaton.

More information

A New Approach to General Relativity

A New Approach to General Relativity Apeion, Vol. 14, No. 3, July 7 7 A New Appoach to Geneal Relativity Ali Rıza Şahin Gaziosmanpaşa, Istanbul Tukey E-mail: aizasahin@gmail.com Hee we pesent a new point of view fo geneal elativity and/o

More information

FULLY RIGHT PURE GROUP RINGS (Gelanggang Kumpulan Tulen Kanan Penuh)

FULLY RIGHT PURE GROUP RINGS (Gelanggang Kumpulan Tulen Kanan Penuh) Joual of Qualty Measuemet ad Aalyss JQMA 3(), 07, 5-34 Jual Pegukua Kualt da Aalss FULLY IGHT PUE GOUP INGS (Gelaggag Kumpula Tule Kaa Peuh) MIKHLED ALSAAHEAD & MOHAMED KHEI AHMAD ABSTACT I ths pape, we

More information

Statics. Consider the free body diagram of link i, which is connected to link i-1 and link i+1 by joint i and joint i-1, respectively. = r r r.

Statics. Consider the free body diagram of link i, which is connected to link i-1 and link i+1 by joint i and joint i-1, respectively. = r r r. Statcs Th cotact btw a mapulato ad ts vomt sults tactv ocs ad momts at th mapulato/vomt tac. Statcs ams at aalyzg th latoshp btw th actuato dv tous ad th sultat oc ad momt appld at th mapulato dpot wh

More information

Scalars and Vectors Scalar

Scalars and Vectors Scalar Scalas and ectos Scala A phscal quantt that s completel chaacteed b a eal numbe (o b ts numecal value) s called a scala. In othe wods a scala possesses onl a magntude. Mass denst volume tempeatue tme eneg

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

More information

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

Railroad vehicle modelling in probabilistic vibration analysis of a railway bridge with randomly fluctuating track ballast stiffness

Railroad vehicle modelling in probabilistic vibration analysis of a railway bridge with randomly fluctuating track ballast stiffness oceeds of the 9th Iteatoal ofeece o Stuctual Dyamcs EUODY 4 oto otual 3 Jue - July 4 A. uha E. aetao. beo G. Mülle eds.) ISS: 3-9; IS: 978-97-75-65-4 aload ehcle modell pobablstc bato aalyss of a alway

More information

Overview. Review Superposition Solution. Review Superposition. Review x and y Swap. Review General Superposition

Overview. Review Superposition Solution. Review Superposition. Review x and y Swap. Review General Superposition ylcal aplace Soltos ebay 6 9 aplace Eqato Soltos ylcal Geoety ay aetto Mechacal Egeeg 5B Sea Egeeg Aalyss ebay 6 9 Ovevew evew last class Speposto soltos tocto to aal cooates Atoal soltos of aplace s eqato

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

Lecture 24: Observability and Constructibility

Lecture 24: Observability and Constructibility ectue 24: Obsevability ad Costuctibility 7 Obsevability ad Costuctibility Motivatio: State feedback laws deped o a kowledge of the cuet state. I some systems, xt () ca be measued diectly, e.g., positio

More information