I. INTRODUCTION. 1 IRCCyN: UMR CNRS 6596, Ecole Centrale de Nantes, Université de Nantes, Ecole des Mines de Nantes


 Camron Glenn
 2 years ago
 Views:
Transcription
1 he Knematc Analyss of a Symmetrcal hreedegreeoffreedom lanar arallel Manpulator Damen Chablat and hlppe Wenger Insttut de Recherche en Communcatons et Cybernétque de Nantes, rue de la Noë, 442 Nantes, France Abstract resented n ths paper s the knematc analyss of a symmetrcal threedegreeoffreedom planar parallel manpulator. In opposte to seral manpulators, parallel manpulators can admt not only multple nverse knematc solutons, but also multple drect knematc solutons. hs property produces more complcated knematc models but allows more flexblty n trajectory plannng. o take nto account ths property, the noton of aspects,.e. the maxmal sngulartyfree domans, was ntroduced, based on the noton of workng modes, whch makes t possble to separate the nverse knematc solutons. he am of ths paper s to show that a nonsngular assemblymode changng trajectory exst for a symmetrcal planar parallel manpulator, wth equlateral base and platform trangle. Index erms arallel manpulator, Sngularty, Aspect, Assembly modes, Workng modes. F I. INRODUCION OR two decades, parallel manpulators have attracted the attenton of more and more researchers who consder them as valuable alternatve for robotc mechansms []. As stated by a number of authors [4], conventonal seral knematc machnes have already reached ther dynamc performance lmts, whch are bounded by hgh stffness of the machne components requred to support sequental jonts, lnks and actuators. hus, whle havng good operatng characterstcs (large workspace, hgh flexblty and manoeuvrablty), seral manpulators have dsadvantages of low precson, low stffness and low power. Also, they are generally operated at low speed to avod excessve vbraton and deflecton. Conversely, parallel knematc machnes offer essental advantages over ther seral counterparts (lower movng masses, hgher rgdty and payloadtoweght rato, hgher natural frequences, better accuracy, smpler modular mechancal constructon, possblty to locate actuators on the fxed base) that should lead to hgher dynamc capabltes. However, most exstng parallel manpulators have lmted and complcated workspace wth sngulartes, and hghly nonsotropc nput/output relatons [5]. Hence, the performances may sgnfcantly vary over the workspace and depend on the drecton of the moton. A wellknown feature of parallel manpulators s the exstence of multple drect knematc solutons (or assembly modes). hat s, the moble platform can admt several postons and orentatons (or confguratons) n the workspace for one gven set of nput jont values [6]. he dual problem arses n seral manpulators, where several nput jont values correspond to one gven confguraton of the endeffector. o cope wth the exstence of multple nverse knematc solutons n seral manpulators, the noton of aspects was ntroduced [7]. he aspects were defned as the maxmal sngulartyfree domans n the jont space. For usual ndustral seral manpulators, the aspects were found to be the maxmal sets n the jont space where there s only one nverse knematc soluton. Many other seral manpulators, referred to as cuspdal manpulators, were shown to be able to change soluton wthout passng through a sngularty, thus meanng that there s more than one nverse knematc soluton n one aspect. New unqueness domans have been characterzed for cuspdal manpulators [8], [9]. A defnton of the noton of aspect was gven by [0] for parallel manpulators wth only one nverse knematc soluton. hese aspects were defned as the maxmal sngulartyfree domans n the workspace. A second defnton was gven by [] for parallel manpulators wth several nverse knematc solutons. hese aspects were defned as the maxmal sngulartyfree domans n the Cartesan product of the workspace wth the jont space. However, t was shown n [2] that t s possble to lnk several drect knematc solutons wthout meetng a sngularty, thus meanng that there exsts cuspdal parallel manpulators. hs property was found for partcular lnks lengths. However, [] conjectured that such propertes cannot exst for symmetrcal parallel manpulator. he am of ths paper s to show that a symmetrcal DOF planar parallel manpulator can change assembly mode wthout meetng a sngularty. We mean by symmetrcal, a manpulator wth equlateral base and platform trangles. hs paper s organzed as follows. Secton II descrbes the planar RRR parallel manpulator studed, whch s used all along ths paper. Secton III recalls the noton of aspect for parallel manpulators. A nonsngular assemblymode changng trajectory s shown for the symmetrcal planar parallel manpulator. he workspace and the generalzed IRCCyN: UMR CNRS 6596, Ecole Centrale de Nantes, Unversté de Nantes, Ecole des Mnes de Nantes
2 2 aspects are calculated usng octree models. II. RELIMINARIES A. arallel manpulator studed he manpulator under study s a planar threedof manpulator comprsng three parallel RRR chans shown n Fg.. hs manpulator s used to llustrate the example n ths paper. hs manpulator has frequently studed, n partcular n [65]. l m O m nverseknematcs matrces of the manpulator, defned as ( c b) ( c b) E( p c) A ( c2 b2) ( c2 b2) E( p c2) (4a) ( ) ( ) ( ) c b c b E p c ( c b) E( b a) ( c2 b2) E( b2 a2) ( ) ( ) c b E b a (4b) C. Sngulartes For the planar manpulator studed, such confguratons are reached whenever the axes C, 2 and ntersect (possbly at nfnty), as depcted n Fg. 2. In the presence of such confguratons, the manpulator cannot resst any torque appled at the ntersecton pont I. y C l 2 2 A x m l Fgure : he RRR parallel manpulator studed he actuated jont varables are the rotaton of the three revolute jonts located on the base (, 2, ). he Cartesan varables are the coordnate ( xy, ) of the operaton pont and the orentaton of the platform. he passve and actuated jonts wll always be assumed unlmted n ths study. onts A, and, (respectvely C, and ) le at the corners of an equlateral trangle, whose geometrc center s 0 (respectvely ). Moreover, l l l2 l 6, wth l denotng the length of A, m m m2 m 6, wth m denotng the length of C, r r r2 r 0, wth r denotng the length of A O and s s s2 s 5, wth s denotng the length of C, n unts of length that need not be specfed n the paper.. Knematc Relatons he velocty p of pont can be obtaned n three dfferent forms, dependng on whch leg s traversed, namely, p = E( b a ) + E( c b ) E( p c ), [,] () wth matrx E, 0 E 0 We would lke to elmnate the three dle jont rates, 2 and from eq. (), whch we do by dotmultplyng eq. () by ( c ) b, thus obtanng ( c b ) p =( c b ) E( b a )+( c b ) E( p c ), (2) [,] Equaton (2) can now be cast n vector form, namely, At ρ wth t p and ρ 2 () wth ρ thus beng the vector of actuated jont rates. Moreover, A and are, respectvely, the drectknematcs and the I C A Fgure 2: Example of parallel sngularty For the manpulator under study, the seral sngulartes occur whenever ( b a ) ( c b ) lm for at least one value of, as depcted n Fg. for =,.e. whenever the ponts A,, and C are algned. D. Workng modes he noton of workng modes was ntroduced n [] for parallel manpulators wth several solutons to the nverse knematc problem and whose matrx s dagonal. A workng mode, denoted Mf, s the set of mechansm confguratons for whch the sgn of ( j,, n for a parallel manpulator wth n degrees of freedom) does not change and does not vansh. A mechansm confguraton s represented by the vector (X, q), whch permts us to locate the moble platform as well as all the lnks.. ( X, q) W Q such that sgn( )=cst for j,, n Mf and det( ) 0 herefore, the set of workng modes ( Mf, j I ) s obtaned whle usng all permutatons of sgn of each term. he manpulator under study has eght workng modes, as depcted n Fg. 4, that we call now (a), (b),..., (h). Each workng mode s defned accordng to the sgn of as s gven s n table. 2
3 ablty of a parallel manpulator to change ts nverse knematc soluton depends on the bounds n the passve and actuated jonts. hs problem s not taken nto account n our study snce unlmted jonts are assumed. C A 2 Fgure : Example of seral sngularty when A, and C are algned 2 A C (a) (b) (c) (d) 2 A C (e) (g) Fgure 4: he eght workng modes (f) (h) Fgure 4 (a) (b) (c) (d) (e) (f) (g) (h) N N N N N N N N N N N N able : he eght workng modes of the manpulators studed wth N (resp. ) denoted negatve values of (resp. postve values) Accordng to each workng mode, the parallel sngularty locus changes n the workspace, as shown n Fg. 5. In generally, the Fgure 5: he same platform confguraton wth two jont confguratons (sngular on the left and none sngular on the rght) E. Octree Models Octree models are herarchcal data structures based on recursve subdvson of the space, respectvely [6]. hey are useful for representng complex dmensonal shapes lke workspaces [0]. A close method s used n [7] that dvdes the workspace nto boxes. hs method does not use recursve subdvson but nterval analyss methods [8] to buld the dextrous workspace. However, t does not make t possble to perform oolean operatons or to make pathconnectvty analyss easly. he frst method permts us to calculate easly all knd of space and the computng tme s lmted as a functon of the accuracy. he second one s more exact but requres more ablty to be mplemented. In both cases, we can characterze spaces whose dmensons are ether lengths or angles. Snce the structure of the octree model has an mplct adjacency graph, pathconnectvty analyses and trajectory
4 4 plannng can be carred out naturally. he optmal constructon method of a 2 k tree s derved from the shape, whch recalls the tree. he most nterestng approach conssts n testng successvely all the nodes present n the maxmal depth, followng an order of numberng whch quckly allows nodes to be grouped and thus, smplfes the 2 k tree. he order of numberng for ths algorthm s based on Morton's sweepng [9]. he nverse or drect knematc model s used to calculate 2 k tree. he fgure 6 represents the octree model of ts Cartesan workspace where the frst and the second axs represent the poston and the thrd axs the orentaton of the moble platform. QA Q ; QA s connected. he seral aspects are the maxmal sngulartyfree domans n the jont space for one gven workng mode. For each workng mode, there exsts, at least, one aspect where det( A ) s postve and another one where det( A ) s negatve. However, such regons can be dsjont. In table 2, we assocated the aspects wth a workng mode for whch det( A ) s postve. For the workng mode (a), there exst four aspects and for the other ones, there s only one aspect. Due to the symmetrcal propertes of the mechansm, there exst also aspects where det( A ) s negatve. Workng modes (a) (b) (c) (d) (e) (f) (g) (h) N fgure able 2: he projecton of the generalzed aspects on the workspace when det( A ) 0 for each workng mode x y Fgure 6: he Cartesan workspace III. WORKSACE ANALYSIS A. Aspect defntons he noton of aspect was ntroduced by [7] to cope wth the exstence of multple nverse knematc solutons n seral manpulators. Recently, the noton of aspect was defned for parallel manpulators wth only one nverse knematc soluton to cope wth the exstence of multple drect knematc solutons [0] and for parallel manpulators wth multple nverse and drect knematc solutons (the generalzed aspects []). For the manpulator studed, we use the second defnton. he generalzed aspects A are defned as the maxmal sets n W Q so that A W Q ; A s connected; A ( X, q) Mf such that det( A ) 0 In other words, the generalzed aspects A are the maxmal sngulartyfree domans of the Cartesan product of the reachable workspace (called W) wth the reachable jont space (called Q). he projecton of the generalzed aspects onto the workspace yelds the parallel aspects WA so that, WA W ; WA s connected. he parallel aspects are the maxmal sngulartyfree domans n the workspace for one gven workng mode. he projecton of the generalzed aspects onto the jont space yelds the seral aspects QA so that, Fgure 7: he four parallel aspects for the workng mode (a) and det( A ) 0 Fgure 8: he parallel aspect for the workng mode (b) and det( A ) 0 Fgure 0: he parallel aspect for the workng mode (d) and det( A ) 0 Fgure 9: he parallel aspect for the workng mode (c) and det( A ) 0 Fgure : he parallel aspect for the workng mode (e) and det( A ) 0
5 5 Fgure 2: he parallel aspect for the workng mode (f) and det( A ) 0 Fgure : he parallel aspect for the workng mode (g) and det( A ) 0 osture () osture (2) Fgure 4: he parallel aspect for the workng mode (h) and det( A ) 0 he calculaton of the generalzed aspects can be performed by 6 usng a 2 octree model or two octree models. We use the second method. he frst one s the projecton of the generalzed aspect onto the reachable workspace and the second one the projecton onto the reachable jont space for a gven workng mode and a gven sgn of det( A) constant. o obtan these results wth an accuracy of 0.09 for the poston and,4 degrees for the orentaton, the computng tmes s 90 seconds wth an AMD Athlon X processor and the maxmum memory used s 80 Mb. he connectvty analyss of each doman requres 20 seconds.. Nonsngular posture changng trajectores In [2], a nonsngular posture changng trajectory was found for a RR planar manpulator. However, t appears that ths trajectory passes close to a sngular confguraton. hs property was confrmed n [0] for the same manpulator and for a RRR planar manpulator wth nonsymmetrcal geometry [20]. Accordng to the assumpton n [], we can thnk that such propertes may not exst for the mechansm studed. However, we shown that a nonsngular confguraton changng trajectores exsts. For the followng nput jont values: = , 2 = , = Four drect knematc solutons are found (Fgure 5 and able ). We notce that solutons and 4 are n the same generalzed aspect (he parallel aspect assocated s depcted n the fgure 8). osture () osture (4) Fgure 5: he four drect knematc solutons for = , 2= , = osture N x y n degrees () (2) () (4) able : Four drect knematc solutons for the same jont values A frst method to confrm ths property s to evaluate the determnant of A and (able 4) and to fnd out a trajectory between these two postures. det(a) osture () osture (4) able 4: Evaluaton of det( A ) and generalzed aspect for the two pose n the same We fnd a nonsngular contnuous trajectory between postures () and (4) by passng through an ntermedate posture (5) (Fgure 6) whose poston s (0.987;.90) and orentaton s 2.5 degrees. etween these three postures, a lnear nterpolaton s defned to stay n the same generalzed aspect. he values of det(a),, and are evaluated and each value of these ndces s normalzed by ts maxmum value as t s shown n fgure 7.
6 6 Fgure 6: he ntermedate posture (5) for the nonsngular changng trajectory Wth ths result, we have proofed that a nonsngular assembly mode trajectory s possble for a symmetrcal planar RRR parallel manpulator. Insde such trajectory, not any knematc ndex, derved from the Jacoban matrces, permts us to recognze such property det( ) A 2 0 t osture () osture (5) osture (4) Fgure 7: Varatons of the normalzed values of det(a),, and along the trajectory (t) between postures () and (4) C. Characterstc surfaces o separate the drect and nverse knematc solutons, the unqueness domans are determned for the parallel manpulator wth one nverse knematc soluton n [0] and for parallel manpulator wth several nverse knematc solutons n [20]. he boundares of the unqueness domans are defned by the characterstc surfaces [20]. For the generalzed aspect (b), we can compute the characterstc surface that permts us to solate the assembly modes where t s possble to realze nonsngular assembly mode changng trajectores (Fgure 8). Fgure 8: he parallel sngulartes and the characterstc surfaces assocated wth the generalzed aspect (b) IV. SUMMARY AND CONCLUSIONS A knematc analyss of a planar RRR parallel manpulator wth symmetrcal propertes was presented n ths paper. he eght workng modes have been characterzed and generalzed aspects have been found out. Insde such domans, any contnuous trajectores are possble. In such domans, there are nonsngular changng trajectores but not any knematc ndex can recognze such property. An example of nonsngular changng trajectory s gven and the characterstc surface are computed whch permt, n a future works, to defne closely the unqueness domans of the manpulator studed. REFERENCES [] H. Asada and J.J. Slotne, Robot Analyss and Control, John Wley & Sons, (986). [2] K.S. Fu, R. Gonzalez and C.S.G. Lee, Robotcs: Control, Sensng, Vson, and Intellgence, McGrawHll, (987). [] J.J. Crag, Introducton to Robotcs: Mechancs and Control, Addson Wesley, (989). [4] L.W. sa, Robot Analyss, he Mechancs of Seral and arallel Manpulators, John Wley & Sons, (999). [5] D. Stewart, A latform wth Sx Degrees of freedom, roceedngs of the Insttuton of Mechancal Engnners Vol. 80, art, No. 5, 786, (965). [6] J. Merlet, arallel robots, Kluwer Academc ubl., Dordrecht, he Netherland, (2000). [7]. orrel, A study of manpulator nverse knematc solutons wth applcaton to trajectory plannng and workspace determnaton, roc. IEEE Int. Conf on Rob. And Aut., pp 8085, (986). [8] h. Wenger, A new general formalsm for the knematc analyss of all nonredundant manpulators, IEEE Robotcs and Automaton, pp , (992). [9] J. El Omr, Analyse Géométrque et Cnématque des Mécansmes de ype Manpulateur, hèse, Nantes, (996). [0] h. Wenger and D. Chablat, Unqueness Domans n the Workspace of arallel Manpulators, IFACSYROCO, Vol. 2, pp. 446, 5 Sept., Nantes, (997).
7 7 [] D. Chablat and h. Wenger, Workng Modes and Aspects n Fullyarallel Manpulator, IEEE Internatonal Conference on Robotcs and Automaton, pp , May, (998). [2] C. Innocent and V. arentcastell, Sngulartyfree evoluton from one confguraton to another n seral and fullyparallel manpulators, Robotcs, Spatal Mechansms and Mechancal Systems, ASME, (992). [].R. McAree, R. W. Danel, An explanaton of Never Specal Assembly Changng Moton for  arallel Manpulators, Int. Journal of Robotcs research, Vol. 8/6, June (999). [4] J. Angeles, Fundamentals of Robotc Mechancal Systems, SprngerVerlag, (2002). [5] C. Gosseln, and J. Angeles, he Optmum Knematc Desgn of a lanar hreedegreeoffreedom arallel Manpulator, ASME, Journal of Mechansms, ransmssons, and Automaton n Desgn, Vol. 0, March (988). [6] D. Meagher, Geometrc Modellng usng Octree Encodng, echncal Report ILR8005, Image rocessng Laboratory, Rensselaer olytechnc Insttute, roy, New York 28 (98). [7] D. Chablat, h. Wenger and J. Merlet, Workspace Analyss of the Orthoglde usng Interval Analyss, 8th Internatonal Symposum on Advances n Robot Knematcs, Kluwer Academc ublshers, Caldes de Malavella, Espagne, June (2002). [8] J. Merlet, ALIAS: an nterval analyss based lbrary for solvng and analyzng system of equatons, Sémnare Systèmes et équatons algébrques, oulouse, pp , June (2002). [9] G. Morton, A Computer Orented Geodetc Data ase and a new echnque n Fle Sequencng, IM Ltd, Ottawa, Canada (966). [20] D. Chablat and h. Wenger, Les Domanes d Uncté des Manpulateurs lenement arallèles, Journal of Mechansm and Machne heory, Vol 6/6, pp , (200).
where the coordinates are related to those in the old frame as follows.
Chapter 2  Cartesan Vectors and Tensors: Ther Algebra Defnton of a vector Examples of vectors Scalar multplcaton Addton of vectors coplanar vectors Unt vectors A bass of noncoplanar vectors Scalar product
More informationRecurrence. 1 Definitions and main statements
Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.
More informationDEXTERITY INDICES OF 6UPS PARALLEL MANIPULATOR
Internatonal Journal of Mechancal Engneerng and echnology (IJME) Volume 6, Issue 12, Dec 2015, pp. 0108, Artcle ID: IJME_06_12_001 Avalable onlne at http://www.aeme.com/ijme/ssues.asp?jype=ijme&vype=6&iype=12
More informationInterIng 2007. INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 1516 November 2007.
InterIng 2007 INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 1516 November 2007. UNCERTAINTY REGION SIMULATION FOR A SERIAL ROBOT STRUCTURE MARIUS SEBASTIAN
More informationv a 1 b 1 i, a 2 b 2 i,..., a n b n i.
SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 455 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces we have studed thus far n the text are real vector spaces snce the scalars are
More information8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by
6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationThe eigenvalue derivatives of linear damped systems
Control and Cybernetcs vol. 32 (2003) No. 4 The egenvalue dervatves of lnear damped systems by YeongJeu Sun Department of Electrcal Engneerng IShou Unversty Kaohsung, Tawan 840, R.O.C emal: yjsun@su.edu.tw
More informationNMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING. Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582
NMT EE 589 & UNM ME 482/582 ROBOT ENGINEERING Dr. Stephen Bruder NMT EE 589 & UNM ME 482/582 7. Root Dynamcs 7.2 Intro to Root Dynamcs We now look at the forces requred to cause moton of the root.e. dynamcs!!
More informationPolitecnico di Torino. Porto Institutional Repository
Poltecnco d orno Porto Insttutonal Repostory [Proceedng] rbt dynamcs and knematcs wth full quaternons rgnal Ctaton: Andres D; Canuto E. (5). rbt dynamcs and knematcs wth full quaternons. In: 16th IFAC
More informationSCALAR A physical quantity that is completely characterized by a real number (or by its numerical value) is called a scalar. In other words, a scalar
SCALAR A phscal quantt that s completel charactered b a real number (or b ts numercal value) s called a scalar. In other words, a scalar possesses onl a magntude. Mass, denst, volume, temperature, tme,
More informationON THE ACCURACY, REPEATABILITY, AND DEGREE OF INFLUENCE OF KINEMATICS PARAMETERS FOR INDUSTRIAL ROBOTS
Internatonal Journal of Modellng and Smulaton, Vol. 22, No. 3, 2002 ON THE ACCURACY, REPEATABILITY, AND DEGREE OF INFLUENCE OF KINEMATICS PARAMETERS FOR INDUSTRIAL ROBOTS P.S. Shakolas, K.L. Conrad, and
More informationConversion between the vector and raster data structures using Fuzzy Geographical Entities
Converson between the vector and raster data structures usng Fuzzy Geographcal Enttes Cdála Fonte Department of Mathematcs Faculty of Scences and Technology Unversty of Combra, Apartado 38, 3 454 Combra,
More informationLoop Parallelization
  Loop Parallelzaton C52 Complaton steps: nested loops operatng on arrays, sequentell executon of teraton space DECLARE B[..,..+] FOR I :=.. FOR J :=.. I B[I,J] := B[I,J]+B[I,J] ED FOR ED FOR analyze
More informationSupport Vector Machines
Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.
More informationCausal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting
Causal, Explanatory Forecastng Assumes causeandeffect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of
More informationDamage detection in composite laminates using cointap method
Damage detecton n composte lamnates usng contap method S.J. Km Korea Aerospace Research Insttute, 45 EoeunDong, YouseongGu, 35333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The contap test has the
More informationFace Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching)
Face Recognton Problem Face Verfcaton Problem Face Verfcaton (1:1 matchng) Querymage face query Face Recognton (1:N matchng) database Applcaton: Access Control www.vsage.com www.vsoncs.com Bometrc Authentcaton
More informationThe Magnetic Field. Concepts and Principles. Moving Charges. Permanent Magnets
. The Magnetc Feld Concepts and Prncples Movng Charges All charged partcles create electrc felds, and these felds can be detected by other charged partcles resultng n electrc force. However, a completely
More informationGoals Rotational quantities as vectors. Math: Cross Product. Angular momentum
Physcs 106 Week 5 Torque and Angular Momentum as Vectors SJ 7thEd.: Chap 11.2 to 3 Rotatonal quanttes as vectors Cross product Torque expressed as a vector Angular momentum defned Angular momentum as a
More informationSMOOTH TRAJECTORY PLANNING ALGORITHMS FOR INDUSTRIAL ROBOTS: AN EXPERIMENTAL EVALUATION
1. Albano LANZUTTI SMOOTH TRAJECTORY PLANNING ALGORITHMS FOR INDUSTRIAL ROBOTS: AN EXPERIMENTAL EVALUATION 1. DIPARTIMENTO DI INGEGNERIA ELETTRICA, GESTIONALE E MECCANICA UNIVERSITA' DI UDINE, UDINE ITALY
More informationComparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions
Comparson of Control Strateges for Shunt Actve Power Flter under Dfferent Load Condtons Sanjay C. Patel 1, Tushar A. Patel 2 Lecturer, Electrcal Department, Government Polytechnc, alsad, Gujarat, Inda
More informationEfficient Project Portfolio as a tool for Enterprise Risk Management
Effcent Proect Portfolo as a tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company January 5, 27 Effcent Proect Portfolo as a tool for Enterprse
More informationRing structure of splines on triangulations
www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAMReport 201448 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon
More informationBERNSTEIN POLYNOMIALS
OnLne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful
More information1 Example 1: Axisaligned rectangles
COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture # 6 Scrbe: Aaron Schld February 21, 2013 Last class, we dscussed an analogue for Occam s Razor for nfnte hypothess spaces that, n conjuncton
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationPowerofTwo Policies for Single Warehouse MultiRetailer Inventory Systems with Order Frequency Discounts
Powerofwo Polces for Sngle Warehouse MultRetaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
More informationOn the Optimal Control of a Cascade of HydroElectric Power Stations
On the Optmal Control of a Cascade of HydroElectrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More information21 Vectors: The Cross Product & Torque
21 Vectors: The Cross Product & Torque Do not use our left hand when applng ether the rghthand rule for the cross product of two vectors dscussed n ths chapter or the rghthand rule for somethng curl
More informationMAPP. MERIS level 3 cloud and water vapour products. Issue: 1. Revision: 0. Date: 9.12.1998. Function Name Organisation Signature Date
Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPPATBDClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller
More informationBrigid Mullany, Ph.D University of North Carolina, Charlotte
Evaluaton And Comparson Of The Dfferent Standards Used To Defne The Postonal Accuracy And Repeatablty Of Numercally Controlled Machnng Center Axes Brgd Mullany, Ph.D Unversty of North Carolna, Charlotte
More informationCan Auto Liability Insurance Purchases Signal Risk Attitude?
Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? ChuShu L Department of Internatonal Busness, Asa Unversty, Tawan ShengChang
More information6. EIGENVALUES AND EIGENVECTORS 3 = 3 2
EIGENVALUES AND EIGENVECTORS The Characterstc Polynomal If A s a square matrx and v s a nonzero vector such that Av v we say that v s an egenvector of A and s the correspondng egenvalue Av v Example :
More informationL10: Linear discriminants analysis
L0: Lnear dscrmnants analyss Lnear dscrmnant analyss, two classes Lnear dscrmnant analyss, C classes LDA vs. PCA Lmtatons of LDA Varants of LDA Other dmensonalty reducton methods CSCE 666 Pattern Analyss
More informationProject Networks With MixedTime Constraints
Project Networs Wth MxedTme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationA MultiCamera System on PCCluster for Realtime 3D Tracking
The 23 rd Conference of the Mechancal Engneerng Network of Thaland November 4 7, 2009, Chang Ma A MultCamera System on PCCluster for Realtme 3D Trackng Vboon Sangveraphunsr*, Krtsana Uttamang, and
More informationFORCED CONVECTION HEAT TRANSFER IN A DOUBLE PIPE HEAT EXCHANGER
FORCED CONVECION HEA RANSFER IN A DOUBLE PIPE HEA EXCHANGER Dr. J. Mchael Doster Department of Nuclear Engneerng Box 7909 North Carolna State Unversty Ralegh, NC 276957909 Introducton he convectve heat
More informationPSYCHOLOGICAL RESEARCH (PYC 304C) Lecture 12
14 The Chsquared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed
More informationQUANTUM MECHANICS, BRAS AND KETS
PH575 SPRING QUANTUM MECHANICS, BRAS AND KETS The followng summares the man relatons and defntons from quantum mechancs that we wll be usng. State of a phscal sstem: The state of a phscal sstem s represented
More informationVision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION
Vson Mouse Saurabh Sarkar a* a Unversty of Cncnnat, Cncnnat, USA ABSTRACT The report dscusses a vson based approach towards trackng of eyes and fngers. The report descrbes the process of locatng the possble
More informationMultiRobot Tracking of a Moving Object Using Directional Sensors
MultRobot Trackng of a Movng Object Usng Drectonal Sensors Xaomng Hu, Karl H. Johansson, Manuel Mazo Jr., Alberto Speranzon Dept. of Sgnals, Sensors & Systems Royal Insttute of Technology, SE 44 Stockholm,
More information+ + +   This circuit than can be reduced to a planar circuit
MeshCurrent Method The meshcurrent s analog of the nodeoltage method. We sole for a new set of arables, mesh currents, that automatcally satsfy KCLs. As such, meshcurrent method reduces crcut soluton to
More information行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告
行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告 畫 類 別 : 個 別 型 計 畫 半 導 體 產 業 大 型 廠 房 之 設 施 規 劃 計 畫 編 號 :NSC 962628E009026MY3 執 行 期 間 : 2007 年 8 月 1 日 至 2010 年 7 月 31 日 計 畫 主 持 人 : 巫 木 誠 共 同
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):18841889 Research Artcle ISSN : 09757384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationRobotics and ComputerIntegrated Manufacturing
Robotcs and ComputerIntegrated Manufacturng 27 (2) 977 98 Contents lsts avalable at ScenceDrect Robotcs and ComputerIntegrated Manufacturng journal homepage: www.elsever.com/locate/rcm Optmal desgn of
More informationPOLYSA: A Polynomial Algorithm for Nonbinary Constraint Satisfaction Problems with and
POLYSA: A Polynomal Algorthm for Nonbnary Constrant Satsfacton Problems wth and Mguel A. Saldo, Federco Barber Dpto. Sstemas Informátcos y Computacón Unversdad Poltécnca de Valenca, Camno de Vera s/n
More informationJ. Parallel Distrib. Comput.
J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n
More informationAPPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT
APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedocho
More informationForecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract  Stock market s one of the most complcated systems
More informationEnhancing Parallel Robots Accuracy with Redundant Sensors
Enhancng Parallel obots Accuracy wth edundant ensors Frédérc Marquet, Olver Company, ébasten Krut, Franços Perrot LIMM  UM 556 CN Unversté Montpeller 2 161 rue Ada, 34392 Montpeller Cede 5, France
More informationwww.engineerspress.com Neural Network Solutions for Forward Kinematics Problem of Hybrid SerialParallel Manipulator
www.engneersress.com World of Scences Journal ISSN: 307307 Year: 03 Volume: Issue: 8 Pages: 4858 Aahmad Ghanbar,, Arash ahman Deartment of Mechancal Engneerng, Unversty of Tabrz, Tabrz, Iran School of
More informationSIMPLE LINEAR CORRELATION
SIMPLE LINEAR CORRELATION Smple lnear correlaton s a measure of the degree to whch two varables vary together, or a measure of the ntensty of the assocaton between two varables. Correlaton often s abused.
More informationWhen Network Effect Meets Congestion Effect: Leveraging Social Services for Wireless Services
When Network Effect Meets Congeston Effect: Leveragng Socal Servces for Wreless Servces aowen Gong School of Electrcal, Computer and Energy Engeerng Arzona State Unversty Tempe, AZ 8587, USA xgong9@asuedu
More informationIDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS
IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS Chrs Deeley* Last revsed: September 22, 200 * Chrs Deeley s a Senor Lecturer n the School of Accountng, Charles Sturt Unversty,
More informationLinear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits
Lnear Crcuts Analyss. Superposton, Theenn /Norton Equalent crcuts So far we hae explored tmendependent (resste) elements that are also lnear. A tmendependent elements s one for whch we can plot an / cure.
More informationA machine vision approach for detecting and inspecting circular parts
A machne vson approach for detectng and nspectng crcular parts DuMng Tsa Machne Vson Lab. Department of Industral Engneerng and Management YuanZe Unversty, ChungL, Tawan, R.O.C. Emal: edmtsa@saturn.yzu.edu.tw
More informationImplementation of Deutsch's Algorithm Using Mathcad
Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages  n "Machnes, Logc and Quantum Physcs"
More information2.5 1.5 0.5. I(λ ) 0.5 1.5
NONCOLOCATION EFFECTS ON THE RIGID BODY ROTORDYNAMICS OF ROTORS ON AMB Gancarlo Genta Department of Mechancs, Poltecnco d Torno, Torno, Italy, genta@polto.t Stefano Carabell Department of Automatc Control,
More informationAn Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch
An Integrated Semantcally Correct 2.5D Object Orented TIN Andreas Koch Unverstät Hannover Insttut für Photogrammetre und GeoInformaton Contents Introducton Integraton of a DTM and 2D GIS data Semantcs
More informationDistributed MultiTarget Tracking In A SelfConfiguring Camera Network
Dstrbuted MultTarget Trackng In A SelfConfgurng Camera Network Crstan Soto, B Song, Amt K. RoyChowdhury Department of Electrcal Engneerng Unversty of Calforna, Rversde {cwlder,bsong,amtrc}@ee.ucr.edu
More informationThe Development of Web Log Mining Based on ImproveKMeans Clustering Analysis
The Development of Web Log Mnng Based on ImproveKMeans Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationA DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATIONBASED OPTIMIZATION. Michael E. Kuhl Radhamés A. TolentinoPeña
Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATIONBASED OPTIMIZATION
More informationANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING
ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 6105194390,
More informationLecture 2: Single Layer Perceptrons Kevin Swingler
Lecture 2: Sngle Layer Perceptrons Kevn Sngler kms@cs.str.ac.uk Recap: McCullochPtts Neuron Ths vastly smplfed model of real neurons s also knon as a Threshold Logc Unt: W 2 A Y 3 n W n. A set of synapses
More informationS 5 S 3 S 4 S 1 S 2 P 6 P 5 P 3 TCP
A BODYORIENTED METHOD FOR DYNAMIC MODELING AND ADAPTIVE CONTROL OF FULLY PARALLEL ROBOTS Alan Codourey, Marcel Honegger, Etenne Burdet Insttute of Robotcs, ETHZurch ETHZentrum, CLA, CH89 Zurch, Swtzerland
More informationFaraday's Law of Induction
Introducton Faraday's Law o Inducton In ths lab, you wll study Faraday's Law o nducton usng a wand wth col whch swngs through a magnetc eld. You wll also examne converson o mechanc energy nto electrc energy
More informationAn Alternative Way to Measure Private Equity Performance
An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate
More informationEnergy Conserving Routing in Wireless Adhoc Networks
Energy Conservng Routng n Wreless Adhoc Networks JaeHwan Chang and Leandros Tassulas Department of Electrcal and Computer Engneerng & Insttute for Systems Research Unversty of Maryland at College ark
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationThe Virtual Movable Human Upper Body for Palpatory Diagnostic Training
Paper Number 261232 Sesson DHM5 The Vrtual Movable Human Upper Body for Palpatory Dagnostc Tranng MengYun Chen, Robert L. Wllams II, Robert R. Conatser Jr. and John N. Howell Interdscplnary Insttute
More informationbenefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
More informationHow Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence
1 st Internatonal Symposum on Imprecse Probabltes and Ther Applcatons, Ghent, Belgum, 29 June 2 July 1999 How Sets of Coherent Probabltes May Serve as Models for Degrees of Incoherence Mar J. Schervsh
More informationgreatest common divisor
4. GCD 1 The greatest common dvsor of two ntegers a and b (not both zero) s the largest nteger whch s a common factor of both a and b. We denote ths number by gcd(a, b), or smply (a, b) when there s no
More informationElastic Systems for Static Balancing of Robot Arms
. th World ongress n Mechans and Machne Scence, Guanajuato, Méco, 9 June, 0 _ lastc Sstes for Statc alancng of Robot rs I.Sonescu L. uptu Lucana Ionta I.Ion M. ne Poltehnca Unverst Poltehnca Unverst Poltehnca
More information1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)
6.3 /  Communcaton Networks II (Görg) SS20  www.comnets.unbremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes
More informationAn InterestOriented Network Evolution Mechanism for Online Communities
An InterestOrented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne
More informationFORMAL ANALYSIS FOR REALTIME SCHEDULING
FORMAL ANALYSIS FOR REALTIME SCHEDULING Bruno Dutertre and Vctora Stavrdou, SRI Internatonal, Menlo Park, CA Introducton In modern avoncs archtectures, applcaton software ncreasngly reles on servces provded
More informationOnLine Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features
OnLne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com
More informationGRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 NORM
GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 NORM BARRIOT JeanPerre, SARRAILH Mchel BGI/CNES 18.av.E.Beln 31401 TOULOUSE Cedex 4 (France) Emal: jeanperre.barrot@cnes.fr 1/Introducton The
More informationSoftware project management with GAs
Informaton Scences 177 (27) 238 241 www.elsever.com/locate/ns Software project management wth GAs Enrque Alba *, J. Francsco Chcano Unversty of Málaga, Grupo GISUM, Departamento de Lenguajes y Cencas de
More informationActivity Scheduling for CostTime Investment Optimization in Project Management
PROJECT MANAGEMENT 4 th Internatonal Conference on Industral Engneerng and Industral Management XIV Congreso de Ingenería de Organzacón Donosta San Sebastán, September 8 th 10 th 010 Actvty Schedulng
More informationAn Overview of Financial Mathematics
An Overvew of Fnancal Mathematcs Wllam Benedct McCartney July 2012 Abstract Ths document s meant to be a quck ntroducton to nterest theory. It s wrtten specfcally for actuaral students preparng to take
More informationExtending Probabilistic Dynamic Epistemic Logic
Extendng Probablstc Dynamc Epstemc Logc Joshua Sack May 29, 2008 Probablty Space Defnton A probablty space s a tuple (S, A, µ), where 1 S s a set called the sample space. 2 A P(S) s a σalgebra: a set
More informationCalculation of Sampling Weights
Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a twostage stratfed cluster desgn. 1 The frst stage conssted of a sample
More informationSPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:
SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and
More informationSingle and multiple stage classifiers implementing logistic discrimination
Sngle and multple stage classfers mplementng logstc dscrmnaton Hélo Radke Bttencourt 1 Dens Alter de Olvera Moraes 2 Vctor Haertel 2 1 Pontfíca Unversdade Católca do Ro Grande do Sul  PUCRS Av. Ipranga,
More informationGender Classification for RealTime Audience Analysis System
Gender Classfcaton for RealTme Audence Analyss System Vladmr Khryashchev, Lev Shmaglt, Andrey Shemyakov, Anton Lebedev Yaroslavl State Unversty Yaroslavl, Russa vhr@yandex.ru, shmaglt_lev@yahoo.com, andrey.shemakov@gmal.com,
More informationEE201 Circuit Theory I 2015 Spring. Dr. Yılmaz KALKAN
EE201 Crcut Theory I 2015 Sprng Dr. Yılmaz KALKAN 1. Basc Concepts (Chapter 1 of Nlsson  3 Hrs.) Introducton, Current and Voltage, Power and Energy 2. Basc Laws (Chapter 2&3 of Nlsson  6 Hrs.) Voltage
More informationAutomated information technology for ionosphere monitoring of loworbit navigation satellite signals
Automated nformaton technology for onosphere montorng of loworbt navgaton satellte sgnals Alexander Romanov, Sergey Trusov and Alexey Romanov Federal State Untary Enterprse Russan Insttute of Space Devce
More information8 Algorithm for Binary Searching in Trees
8 Algorthm for Bnary Searchng n Trees In ths secton we present our algorthm for bnary searchng n trees. A crucal observaton employed by the algorthm s that ths problem can be effcently solved when the
More informationRate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Prioritybased scheduling. States of a process
Dsadvantages of cyclc TDDB47 Real Tme Systems Manual scheduler constructon Cannot deal wth any runtme changes What happens f we add a task to the set? RealTme Systems Laboratory Department of Computer
More informationOn Robust Network Planning
On Robust Network Plannng Al Tzghadam School of Electrcal and Computer Engneerng Unversty of Toronto, Toronto, Canada Emal: al.tzghadam@utoronto.ca Alberto LeonGarca School of Electrcal and Computer Engneerng
More informationDetailed Analysis of SCARAType Serial Manipulator on a Moving Base with LabView
Internatonal Journal of Advanced Robotc Systems ARTICLE Detaled Analyss of SCARAType Seral Manpulator on a Movng Base wth LabVew Regular Paper Alrıa Kalel 1,*, Ahmet Dumlu 1, M. Fath Çorapsı 1 and Köksal
More informationA Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy Scurve Regression
Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy Scurve Regresson ChengWu Chen, Morrs H. L. Wang and TngYa Hseh Department of Cvl Engneerng, Natonal Central Unversty,
More informationRealistic Image Synthesis
Realstc Image Synthess  Combned Samplng and Path Tracng  Phlpp Slusallek Karol Myszkowsk Vncent Pegoraro Overvew: Today Combned Samplng (Multple Importance Samplng) Renderng and Measurng Equaton Random
More informationRELIABILITY, RISK AND AVAILABILITY ANLYSIS OF A CONTAINER GANTRY CRANE ABSTRACT
Kolowrock Krzysztof Joanna oszynska MODELLING ENVIRONMENT AND INFRATRUCTURE INFLUENCE ON RELIABILITY AND OPERATION RT&A # () (Vol.) March RELIABILITY RIK AND AVAILABILITY ANLYI OF A CONTAINER GANTRY CRANE
More informationCALL ADMISSION CONTROL IN WIRELESS MULTIMEDIA NETWORKS
CALL ADMISSION CONTROL IN WIRELESS MULTIMEDIA NETWORKS Novella Bartoln 1, Imrch Chlamtac 2 1 Dpartmento d Informatca, Unverstà d Roma La Sapenza, Roma, Italy novella@ds.unroma1.t 2 Center for Advanced
More informationWhat is Candidate Sampling
What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble
More informationThe OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
More information