Probablty of an Acute Trangle n the Two-dmensonal Spaces of Constant Curvature Abstract The nterest n the statstcal theory of shape has arsen snce Ken

Size: px
Start display at page:

Download "Probablty of an Acute Trangle n the Two-dmensonal Spaces of Constant Curvature Abstract The nterest n the statstcal theory of shape has arsen snce Ken"

Transcription

1 Probablty of an Acute Trangle n the Two-dmensonal Spaces of Constant Curvature Afflated Hgh School of SCNU, Canton, Chna Student: Lv Zyuan, Guo Yuyu Advsor: We Jzhu

2 Probablty of an Acute Trangle n the Two-dmensonal Spaces of Constant Curvature Abstract The nterest n the statstcal theory of shape has arsen snce Kendall found that the metrc geometry of spaces s precsely the requred tool for the systematc comparson and classfcaton of varous shapes n 980s. The statstcal theory of shape s wdely used n the felds such as quantum physcs, bology, and medcal scence. Ths paper concerns the probablty of acute trangles on the spaces of constant curvature. We prove the followng results:. On the unt sphere S, the probablty for a trangle formed by choosng three ponts at random to be an acute one s. 6. On Poncaré dsc D, the probablty for a trangle formed by choosng three 5 ponts at random to be an acute one s. 8 The paper nvolves many dscplnes, ncludng probablty, geometry. The hghlght s the dea of reducng the gven probablty problem to a queston of sold geometry. Key words: Random trangle, Geometrc probablty, Non-Eucldean geometry, Spaces of constant curvature, Rgdty theorem

3 Probablty of an Acute Trangle n the Two-dmensonal Spaces of Constant Curvature Introducton The nterest n the statstcal theory of shape has arsen snce Kendall found that the metrc geometry of spaces s precsely the requred tool for the systematc comparson and classfcaton of varous shapes n 980s. The statstcal theory of shape s wdely used n the felds such as quantum physcs, bology and medcal scence. ( [],[],[],[4],[6]). The statstcal theory of shape can be traced back from 89 when Charles Dodgson (Lews Carroll) proposed the followng queston. Queston: Fnd the probablty that a trangle formed by choosng three ponts at random on an nfnte plane would have an obtuse trangle. In [5], by ntroducng the Cartesan coordnates of the three ponts, S. Portnoy argued that the set of trangles can be dentfed wth the sx-dmensonal Eucldean space R 6. And the set T O of obtuse trangles s a double cone. Also, he clamed that the requrement of takng three ponts at random n the plane can be understood as the nduced probablty dstrbuton n R 6 beng sphercally symmetrc. Hence, the condtonal dstrbuton gven the dstance from the orgn s unform on the approprate sphere. S. Portnoy proved the probablty of formng obtuse trangle s 4. Ths paper concerns the probablty of an acute trangles n the two dmensonal spaces of constant curvature. By choosng the values of nteror angles as coordnates, the set of trangles can be dentfed wth a regon S n the three-dmensonal Eucldean space R. Also, the requrement of takng three ponts at random n the two-dmensonal spaces of constant curvature s understood as the pont n the set S unformly dstrbuted. In ths way, we can compute the probablty of an acute trangle n the two- dmensonal spaces of constant curvature. In partcular, n the Eucldean case, we obtan the same result as S. Portnoy

4 Prelmnary and Man results It s well known that Eucldean geometry s based on fve postulates. The Eucld s ffth postulate, called the parallel postulate, can be expressed as follow: The parallel postulate: There s at least one lne L and at least one pont P not on L, such that one lne can be drawn through P coplanar wth but not meetng L. Durng a long perod of tme, people attempted to prove that the parallel postulate could be deduced from the other four postulates and found that the parallel postulate s equvalent to the fact that the sum of nteror angles of a trangle equals π (represented by radan). In nneteenth century, Gauss, Bolya, Lobachevsky found that the parallel postulate was ndependent of the other four postulates. By replacng the ffth postulate wth one of the followng two postulates whle keepng the other four postulates unchanged, the sphercal geometry and hyperbolc geometry may be establshed respectvely. The parallel postulate n sphercal geometry: Gven a lne L and a pont P not on t, there s no lne can be drawn through the pont P whch s parallel to the gven lne L (that s, all lnes through the pont P ntersect wth the gven lne L). The parallel postulate n hyperbolc geometry: There s at least one lne L and at least one pont P, not on L, such that two lnes can be drawn through P coplanar wth but not meetng L. The unt sphere n three-dmensonal Eucldean space S {( x, y, z) R x y z } can be regarded as a model of sphercal geometry, where lnes are defned as great crcles (As the shortest dstance between two ponts n a sphere s the nferor great crcular arc whch s analogue to the fact n Eucldean geometry that the shortest dstance between two ponts s a lne segment.) Defnton : Let A, B, C be three ponts n the sphere whch are not on the same great crcle. The sde AB of the sphercal trangle ABC s defned to be the nferor great crcular arc jonng A and B. The angle A wth vertce A s defned to be the angle formed by the tangent vectors AX and AY of the sdes AB and AC respectvely. See

5 Fgure. Fgure Defnton : The sphercal trangle ABC s called an acute trangle f A B C are all acute angles. From the defnton of dhedral angle, t s easy to see that XAY s the plane angle <B-OA-C> of the dhedral angle B-OA-C,.e. A=<B-OA-C>. Smlarly, B=<C-OB-A>, C=<A-OC-B>. Let ABC be a sphercal trangle n S²and let A, B, C (0,, ). Set ', ', '..e. α,β,γ are the exteror angle of ABC. Then by the specal case of Gauss-Bonnet Theorem (Theorem.0 n [7],) we have ' ' ' S ' ' ' S ABC ABC () where S ABC s the area of the trangle ABC. Gauss-Bonnet theorem suggests that the sphercal trangle s, up to an sometry of the sphere, unquely determned by ts angles. Actually we have the followng rgdty theorem: Rgdty theorem: f α,β,γ satsfy the nequaltes ( ' ' ' ) () ( ' ' ') () ( ' ' ') (4) ( ' ' ') (5)

6 Then up to an sometry of the sphere, there exsts a unque trangle ABC wth α,β, γ as ts nteror angles. The above Theorem s stated on page 6, [7], and a proof s ndcated on page 66. For hyperbolc geometry, the unt dsc n complex-plane C D z C z x y R x y { } {(, ) } can be regarded as ts model, where lnes are the dameters of D and arcs of crcles n D that are orthogonal to the unt crcle D { z D z }. The model s called Poncaré dsc. Defnton : Gven three ponts A,B,C n the Poncarédsc whch are not on the same lne, the sde AB of the hyperbolc trangle ABC s defned to be the arc of crcle n D jonng A and B and orthogonal to the unt crcle D { z D z }. The angle A wth vertce A s defned to be the angle formed by the tangent vector AX and AY of the sdes AB and AC respectvely. See Fgure. Fgure Defnton 4: The hyperbolc trangle ABC s called an acute trangle f A B C are all acute angles. From the specal case of Gauss-Bonnet theorem (Theorem.0, [7]), we know that, Hence ( ) ( ) ( ) S ABC S ABC (6) Gauss-Bonnet theorem suggests that the hyperbolc trangle s, up to an sometry of the Poncarédsc, unquely determned by ts angles. Actually we have the followng

7 rgdty theorem: Rgdty theorem: If α,β,γ satsfy the nequaltes, 0,, Then up to an sometry of the Poncare dsc, there exsts a unque trangle (7) ABC wth α, β,γ as ts nteror angles. Fgure Note: The above Theorem s a specal case of Theorem.8 n [7], where the exstence s proved and the proof of unqueness s ndcated on page 66. For reader s convenence, we gve a detaled proof here. Proof : For exstence, t s suffcent to look for the desred trangle n the class of trangles admttng an nscrbed crcle. For postve number r 0, 0,,,, consder the quadrlateral Q,,, as n fgure : We need only to prove that there exsts r 0 such that (8) In fact, f such an r>0 can be found, then the problem s solved: one can smply lay the quadrlaterals Q, Q, Qone besde the other, successvely jonng them along the sdes equal to r, then the resultng trangle s the desred one. Note that when r s small enough, Q, =,, can be approxmately regarded as the fgure n the Eucldean plane. Therefore as r 0+, ( ) 0,whch mples that ( ) ( )

8 On the other hand, as r, 0. Snce s a contnuous functon of r, accordng to the ntermedate value theorem of contnuous functon, there exsts r satsfyng. We have Ths fnshes the proof of exstence. The unqueness n rgdty theorem can be proved as follow: By the dual cosne theorem of hyperbolc geometry, Here a s the length of sde BC n Thus cosha cos cos cos sn sn cosh a, cos cos cos cosh a. sn sn ABC s determned by α,β,γ. a a e e, also cosh a. x x x x e e e e Now consder the functon f( x), we have f '( x). When x 0, f '( x) 0,hence f(x) s monotonc ncreasng n (0, ). As a consequence, a s unquely determned bycosha. Smlarly, b,c s unquely determned. Therefore sdes a,b,c of hyperbolc trangle can be unquely determned by α,β,γ. Next we prove the trangle s unquely determned up to sometry. By Cosne Law n hyperbolc geometry: We have, for fxed b, c>0, cosh a cosh b cosh c snh b snh c cos (9) cosha s monotoncally ncreasng. Hence for fxed a, b, c>0, there exsts a unque angle α satsfyng (9). As a consequence, determned up to sometry. The unqueness s proved. 7 ABC s unquely - 6 -

9 From the vewpont of dfferental geometry, Eucldean plane E, unt sphere S n three-dmensonal Eucldean space and the Poncarédsc (endowed wth sutable metrc) have Gaussan curvature 0, +, - respectvely. So they are generally called two-dmensonal spaces of constant curvature. The followng specal case of Toponogov s trangle comparson theorem n Remannan geometry s ntutvely clear. Toponogov s trangle comparson theorem (Specal Case) Gven a,b,c>0, Let T, T, T be the trangles wth sde lengths a,b,c n S, E and D respectvely, and let A, B, C, A, B, C, A, B, C. be the correspondng angles, then we have A >A >A B >B >B C >C >C Fgure 4 By the above theorem, t s reasonable to clam the followng. The probablty of acute trangles n the Eucldean plane E s greater than that of acute trangles n unt Sphere S, whle less than that of acute trangles n Poncarédsc. We verfy the above clam and calculate the correspondng probablty of an acute trangle. More precsely, we have the followng: Man Results. On the unt sphere S, the probablty for a trangle formed by choosng three ponts at random to be an acute one s. 6. On Poncaré dsc D, the probablty for a trangle formed by choosng three 8-6 -

10 5 ponts at random to be an acute one s. 8 Proof of the Man Results. Consder frst the Eucldean plane E², n ths case the Gaussan curvature K=0. Assumng <),then ABC s a random trangle n E², and A=, B=, C= (0<,, 0,, (0) Fgure 5 Takng α,β,γ as Cartesan coordnates, as shown n fgure 5. Snce ABC s randomly chosen on E², we may assume the ponts wth coordnates (α,β,γ) s unformly dstrbuted n the regon determned by (0), whch corresponds to the set of Eucldean trangles. The necessary and suffcent condton for 0,, ABC to be an acute trangle s: () corresponds to G H I n fgure 5, whch s obtaned by cuttng the cube OD G E -F H J I by the trangle A B C. Snce α,β,γ obeys unform dstrbuton n () A B C, therefore, SG P( ABC s an acute trangle)= H I S A B C

11 . Next, we consder the unt Sphere S², n ths case the Gaussan curvature K=. As n Secton, let ', ', ' be the exteror angles of the trangle ABC. Snce 0<,, <,we have 0<,, <. Takng,, as Cartesan coordnates, as n fgure 6: Fgure 6 where D,E,F are mdponts of G H,G I,H I respectvely. Snce ABC s randomly chosen on S², we may assume the ponts wth coordnates (α,β,γ) s unformly dstrbuted n the regon determned by ()-(5), whch corresponds to the set of sphercal trangles. The regon determned by ()~(5) s the nteror of the tetrahedron O-I G H, whch can be obtaned from the cube OA G B -C H J I by elmnatng the tetrahedra C -OI H,A -OG H,B -OG I,J -I G H, as shown n Fgure 6. Hence the volume of the tetrahedron O-I G H can be computed as V V ( V V V V ) OI G H OA G B C H J I A OG H B OG I C OI H J I G H 4 Note that the trangle ABC s an acute one f and only f ', ', '. The regon determned by ()-(5) and the condton ', ', ' s the ntersecton of

12 the cube N D K E -F L J M and the tetrahedron O-I G H, whch s also a tetrahedron N -D E F. The volume of the tetrahedron N -D E F s ( ) V N D E F 48 and VN P( ABC s an acute trangle)= D E F. VO I 6 GH. Fnally, we consder the Poncarédsc D, n ths case the Gaussan curvature K= - Let ABC be a random trangle on П², and let A=, B=, C= (0<,, <). Takng,, as Cartesan coordnates, as shown n fgure 7: Fgure 7 In fgure 7, the regon determned by (7) s the nteror of tetrahedron O-A B C Note that the trangle ABC s an acute one f and only f 0,,. The regon determned by (7) and the condton T of the cube OG D H -I E J F and the tetrahedron O-A B C. Note that T can be obtaned from the cube OG D H -I E J F by elmnatng the tetrahedron J -E D F. The volumes of the tetrahedron O-A B C and T can be computed as: 0,, s the ntersecton V O - ABC π π π 6,

13 V T π π - π 5π 48 and VT 5 P( ABC s an acute trangle)=. V 8 O A B C Thus the theorem s proved. 4 Research Prospectve In ths paper, we only nvestgate the probablty of an acute trangle n the two-dmensonal spaces of constant curvature. It s natural to contnue our research on surfaces of varable curvature. For nstance, we may study the probablty of an acute trangle on the parabolod of revoluton z=x +y. Reference [] Aste T, BooséD and Rver N, From one cell to the whole froth:a dynamcal map, Phys. Rev. E , 996 [] Atyah M and Sutclffe P, The geometry of pont partcles Proc. R. Soc. London A , 00 [] Battye R A,Gbbon G W and Sutclffe P M, Central confguraton n three Dmensons,Proc. R. Soc London A , 00 [4] Brody D C,Shapes of Quantum States,J. Phys. A:Math, Gen , 004 [5] Portnoy S,A Lews Carroll Pllow Problem: Probablty of an Obtuse Trangle, Statstcal Scence vol.9, no , 994 [6] Small C G,The Statstcal Theory of Shape, Sprnger-Verlag New York, Inc., 996 [7] Vnberg E.B. (ed.), Geometry II Spaces of Constant Curvature, Sprnger-Verlag Berln Hedelberg,

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

8.5 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 information

v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

v 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 information

1 Example 1: Axis-aligned rectangles

1 Example 1: Axis-aligned 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 information

Rotation Kinematics, Moment of Inertia, and Torque

Rotation Kinematics, Moment of Inertia, and Torque Rotaton Knematcs, Moment of Inerta, and Torque Mathematcally, rotaton of a rgd body about a fxed axs s analogous to a lnear moton n one dmenson. Although the physcal quanttes nvolved n rotaton are qute

More information

Ring structure of splines on triangulations

Ring structure of splines on triangulations www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAM-Report 2014-48 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon

More information

Recurrence. 1 Definitions and main statements

Recurrence. 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 information

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

Luby 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 information

Conversion between the vector and raster data structures using Fuzzy Geographical Entities

Conversion 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 information

Support Vector Machines

Support 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 information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) 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 information

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

SPEE 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 information

We are now ready to answer the question: What are the possible cardinalities for finite fields?

We are now ready to answer the question: What are the possible cardinalities for finite fields? Chapter 3 Fnte felds We have seen, n the prevous chapters, some examples of fnte felds. For example, the resdue class rng Z/pZ (when p s a prme) forms a feld wth p elements whch may be dentfed wth the

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit 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 information

Inter-Ing 2007. INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 15-16 November 2007.

Inter-Ing 2007. INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 15-16 November 2007. Inter-Ing 2007 INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 15-16 November 2007. UNCERTAINTY REGION SIMULATION FOR A SERIAL ROBOT STRUCTURE MARIUS SEBASTIAN

More information

A machine vision approach for detecting and inspecting circular parts

A machine vision approach for detecting and inspecting circular parts A machne vson approach for detectng and nspectng crcular parts Du-Mng Tsa Machne Vson Lab. Department of Industral Engneerng and Management Yuan-Ze Unversty, Chung-L, Tawan, R.O.C. E-mal: edmtsa@saturn.yzu.edu.tw

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne 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 information

Lecture 3: Force of Interest, Real Interest Rate, Annuity

Lecture 3: Force of Interest, Real Interest Rate, Annuity Lecture 3: Force of Interest, Real Interest Rate, Annuty Goals: Study contnuous compoundng and force of nterest Dscuss real nterest rate Learn annuty-mmedate, and ts present value Study annuty-due, and

More information

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM BARRIOT Jean-Perre, SARRAILH Mchel BGI/CNES 18.av.E.Beln 31401 TOULOUSE Cedex 4 (France) Emal: jean-perre.barrot@cnes.fr 1/Introducton The

More information

Calculation of Sampling Weights

Calculation 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 two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

On Lockett pairs and Lockett conjecture for π-soluble Fitting classes

On Lockett pairs and Lockett conjecture for π-soluble Fitting classes On Lockett pars and Lockett conjecture for π-soluble Fttng classes Lujn Zhu Department of Mathematcs, Yangzhou Unversty, Yangzhou 225002, P.R. Chna E-mal: ljzhu@yzu.edu.cn Nanyng Yang School of Mathematcs

More information

How Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence

How 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 information

) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance

) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance Calbraton Method Instances of the Cell class (one nstance for each FMS cell) contan ADC raw data and methods assocated wth each partcular FMS cell. The calbraton method ncludes event selecton (Class Cell

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fttng of Data Davd Eberly Geoetrc Tools, LLC http://www.geoetrctools.co/ Copyrght c 1998-2016. All Rghts Reserved. Created: July 15, 1999 Last Modfed: January 5, 2015 Contents 1 Lnear Fttng

More information

where the coordinates are related to those in the old frame as follows.

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 non-coplanar vectors Scalar product

More information

The OC Curve of Attribute Acceptance Plans

The 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

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo

More information

n + d + q = 24 and.05n +.1d +.25q = 2 { n + d + q = 24 (3) n + 2d + 5q = 40 (2)

n + d + q = 24 and.05n +.1d +.25q = 2 { n + d + q = 24 (3) n + 2d + 5q = 40 (2) MATH 16T Exam 1 : Part I (In-Class) Solutons 1. (0 pts) A pggy bank contans 4 cons, all of whch are nckels (5 ), dmes (10 ) or quarters (5 ). The pggy bank also contans a con of each denomnaton. The total

More information

AN EFFECTIVE MATRIX GEOMETRIC MEAN SATISFYING THE ANDO LI MATHIAS PROPERTIES

AN EFFECTIVE MATRIX GEOMETRIC MEAN SATISFYING THE ANDO LI MATHIAS PROPERTIES MATHEMATICS OF COMPUTATION Volume, Number, Pages S 5-578(XX)- AN EFFECTIVE MATRIX GEOMETRIC MEAN SATISFYING THE ANDO LI MATHIAS PROPERTIES DARIO A. BINI, BEATRICE MEINI AND FEDERICO POLONI Abstract. We

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 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 information

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits

Linear 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 information

What is Candidate Sampling

What 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 information

Upper Bounds on the Cross-Sectional Volumes of Cubes and Other Problems

Upper Bounds on the Cross-Sectional Volumes of Cubes and Other Problems Upper Bounds on the Cross-Sectonal Volumes of Cubes and Other Problems Ben Pooley March 01 1 Contents 1 Prelmnares 1 11 Introducton 1 1 Basc Concepts and Notaton Cross-Sectonal Volumes of Cubes (Hyperplane

More information

An Alternative Way to Measure Private Equity Performance

An 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 information

Rate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process

Rate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based 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? Real-Tme Systems Laboratory Department of Computer

More information

The descriptive complexity of the family of Banach spaces with the π-property

The descriptive complexity of the family of Banach spaces with the π-property Arab. J. Math. (2015) 4:35 39 DOI 10.1007/s40065-014-0116-3 Araban Journal of Mathematcs Ghadeer Ghawadrah The descrptve complexty of the famly of Banach spaces wth the π-property Receved: 25 March 2014

More information

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are:

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are: polar Juncton Transstor rcuts Voltage and Power Amplfer rcuts ommon mtter Amplfer The crcut shown on Fgure 1 s called the common emtter amplfer crcut. The mportant subsystems of ths crcut are: 1. The basng

More information

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure

More information

NMT 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 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 information

Section 5.4 Annuities, Present Value, and Amortization

Section 5.4 Annuities, Present Value, and Amortization Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today

More information

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008 Rsk-based Fatgue Estmate of Deep Water Rsers -- Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn

More information

Extending Probabilistic Dynamic Epistemic Logic

Extending 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 σ-algebra: a set

More information

REGULAR MULTILINEAR OPERATORS ON C(K) SPACES

REGULAR MULTILINEAR OPERATORS ON C(K) SPACES REGULAR MULTILINEAR OPERATORS ON C(K) SPACES FERNANDO BOMBAL AND IGNACIO VILLANUEVA Abstract. The purpose of ths paper s to characterze the class of regular contnuous multlnear operators on a product of

More information

DEFINING %COMPLETE IN MICROSOFT PROJECT

DEFINING %COMPLETE IN MICROSOFT PROJECT CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,

More information

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem. Producer Theory Producton ASSUMPTION 2.1 Propertes of the Producton Set The producton set Y satsfes the followng propertes 1. Y s non-empty If Y s empty, we have nothng to talk about 2. Y s closed A set

More information

A Probabilistic Theory of Coherence

A Probabilistic Theory of Coherence A Probablstc Theory of Coherence BRANDEN FITELSON. The Coherence Measure C Let E be a set of n propostons E,..., E n. We seek a probablstc measure C(E) of the degree of coherence of E. Intutvely, we want

More information

21 Vectors: The Cross Product & Torque

21 Vectors: The Cross Product & Torque 21 Vectors: The Cross Product & Torque Do not use our left hand when applng ether the rght-hand rule for the cross product of two vectors dscussed n ths chapter or the rght-hand rule for somethng curl

More information

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy 4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

More information

RELIABILITY, RISK AND AVAILABILITY ANLYSIS OF A CONTAINER GANTRY CRANE ABSTRACT

RELIABILITY, 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 information

Existence of an infinite particle limit of stochastic ranking process

Existence of an infinite particle limit of stochastic ranking process Exstence of an nfnte partcle lmt of stochastc rankng process Kumko Hattor Tetsuya Hattor February 8, 23 arxv:84.32v2 [math.pr] 25 Feb 29 ABSTRAT We study a stochastc partcle system whch models the tme

More information

PERRON FROBENIUS THEOREM

PERRON FROBENIUS THEOREM PERRON FROBENIUS THEOREM R. CLARK ROBINSON Defnton. A n n matrx M wth real entres m, s called a stochastc matrx provded () all the entres m satsfy 0 m, () each of the columns sum to one, m = for all, ()

More information

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node Fnal Report of EE359 Class Proect Throughput and Delay n Wreless Ad Hoc Networs Changhua He changhua@stanford.edu Abstract: Networ throughput and pacet delay are the two most mportant parameters to evaluate

More information

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

More information

1 What is a conservation law?

1 What is a conservation law? MATHEMATICS 7302 (Analytcal Dynamcs) YEAR 2015 2016, TERM 2 HANDOUT #6: MOMENTUM, ANGULAR MOMENTUM, AND ENERGY; CONSERVATION LAWS In ths handout we wll develop the concepts of momentum, angular momentum,

More information

Goals Rotational quantities as vectors. Math: Cross Product. Angular momentum

Goals 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 information

INTERPRETING TRUE ARITHMETIC IN THE LOCAL STRUCTURE OF THE ENUMERATION DEGREES.

INTERPRETING TRUE ARITHMETIC IN THE LOCAL STRUCTURE OF THE ENUMERATION DEGREES. INTERPRETING TRUE ARITHMETIC IN THE LOCAL STRUCTURE OF THE ENUMERATION DEGREES. HRISTO GANCHEV AND MARIYA SOSKOVA 1. Introducton Degree theory studes mathematcal structures, whch arse from a formal noton

More information

FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES

FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES Zuzanna BRO EK-MUCHA, Grzegorz ZADORA, 2 Insttute of Forensc Research, Cracow, Poland 2 Faculty of Chemstry, Jagellonan

More information

Natural hp-bem for the electric field integral equation with singular solutions

Natural hp-bem for the electric field integral equation with singular solutions Natural hp-bem for the electrc feld ntegral equaton wth sngular solutons Alexe Bespalov Norbert Heuer Abstract We apply the hp-verson of the boundary element method (BEM) for the numercal soluton of the

More information

How To Assemble The Tangent Spaces Of A Manfold Nto A Coherent Whole

How To Assemble The Tangent Spaces Of A Manfold Nto A Coherent Whole CHAPTER 7 VECTOR BUNDLES We next begn addressng the queston: how do we assemble the tangent spaces at varous ponts of a manfold nto a coherent whole? In order to gude the decson, consder the case of U

More information

Product-Form Stationary Distributions for Deficiency Zero Chemical Reaction Networks

Product-Form Stationary Distributions for Deficiency Zero Chemical Reaction Networks Bulletn of Mathematcal Bology (21 DOI 1.17/s11538-1-9517-4 ORIGINAL ARTICLE Product-Form Statonary Dstrbutons for Defcency Zero Chemcal Reacton Networks Davd F. Anderson, Gheorghe Cracun, Thomas G. Kurtz

More information

Section 2 Introduction to Statistical Mechanics

Section 2 Introduction to Statistical Mechanics Secton 2 Introducton to Statstcal Mechancs 2.1 Introducng entropy 2.1.1 Boltzmann s formula A very mportant thermodynamc concept s that of entropy S. Entropy s a functon of state, lke the nternal energy.

More information

A DATA MINING APPLICATION IN A STUDENT DATABASE

A DATA MINING APPLICATION IN A STUDENT DATABASE JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES JULY 005 VOLUME NUMBER (53-57) A DATA MINING APPLICATION IN A STUDENT DATABASE Şenol Zafer ERDOĞAN Maltepe Ünversty Faculty of Engneerng Büyükbakkalköy-Istanbul

More information

Solution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt.

Solution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt. Chapter 9 Revew problems 9.1 Interest rate measurement Example 9.1. Fund A accumulates at a smple nterest rate of 10%. Fund B accumulates at a smple dscount rate of 5%. Fnd the pont n tme at whch the forces

More information

Embedding lattices in the Kleene degrees

Embedding lattices in the Kleene degrees F U N D A M E N T A MATHEMATICAE 62 (999) Embeddng lattces n the Kleene degrees by Hsato M u r a k (Nagoya) Abstract. Under ZFC+CH, we prove that some lattces whose cardnaltes do not exceed ℵ can be embedded

More information

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently. Corporate Polces & Procedures Human Resources - Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:

More information

Faraday's Law of Induction

Faraday'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 information

Complete Fairness in Secure Two-Party Computation

Complete Fairness in Secure Two-Party Computation Complete Farness n Secure Two-Party Computaton S. Dov Gordon Carmt Hazay Jonathan Katz Yehuda Lndell Abstract In the settng of secure two-party computaton, two mutually dstrustng partes wsh to compute

More information

Fisher Markets and Convex Programs

Fisher Markets and Convex Programs Fsher Markets and Convex Programs Nkhl R. Devanur 1 Introducton Convex programmng dualty s usually stated n ts most general form, wth convex objectve functons and convex constrants. (The book by Boyd and

More information

Damage detection in composite laminates using coin-tap method

Damage detection in composite laminates using coin-tap method Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

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, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo. ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract

More information

A Lyapunov Optimization Approach to Repeated Stochastic Games

A Lyapunov Optimization Approach to Repeated Stochastic Games PROC. ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, OCT. 2013 1 A Lyapunov Optmzaton Approach to Repeated Stochastc Games Mchael J. Neely Unversty of Southern Calforna http://www-bcf.usc.edu/

More information

An Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch

An 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 information

Forecasting the Direction and Strength of Stock Market Movement

Forecasting 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 information

Brigid Mullany, Ph.D University of North Carolina, Charlotte

Brigid 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 information

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

I. INTRODUCTION. 1 IRCCyN: UMR CNRS 6596, Ecole Centrale de Nantes, Université de Nantes, Ecole des Mines de Nantes he Knematc Analyss of a Symmetrcal hree-degree-of-freedom lanar arallel Manpulator Damen Chablat and hlppe Wenger Insttut de Recherche en Communcatons et Cybernétque de Nantes, rue de la Noë, 442 Nantes,

More information

Lecture 2: Single Layer Perceptrons Kevin Swingler

Lecture 2: Single Layer Perceptrons Kevin Swingler Lecture 2: Sngle Layer Perceptrons Kevn Sngler kms@cs.str.ac.uk Recap: McCulloch-Ptts 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 information

FINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals

FINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals FINANCIAL MATHEMATICS A Practcal Gude for Actuares and other Busness Professonals Second Edton CHRIS RUCKMAN, FSA, MAAA JOE FRANCIS, FSA, MAAA, CFA Study Notes Prepared by Kevn Shand, FSA, FCIA Assstant

More information

Using Series to Analyze Financial Situations: Present Value

Using Series to Analyze Financial Situations: Present Value 2.8 Usng Seres to Analyze Fnancal Stuatons: Present Value In the prevous secton, you learned how to calculate the amount, or future value, of an ordnary smple annuty. The amount s the sum of the accumulated

More information

Actuator forces in CFD: RANS and LES modeling in OpenFOAM

Actuator forces in CFD: RANS and LES modeling in OpenFOAM Home Search Collectons Journals About Contact us My IOPscence Actuator forces n CFD: RANS and LES modelng n OpenFOAM Ths content has been downloaded from IOPscence. Please scroll down to see the full text.

More information

An Interest-Oriented Network Evolution Mechanism for Online Communities

An Interest-Oriented Network Evolution Mechanism for Online Communities An Interest-Orented 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 information

New Approaches to Support Vector Ordinal Regression

New Approaches to Support Vector Ordinal Regression New Approaches to Support Vector Ordnal Regresson We Chu chuwe@gatsby.ucl.ac.uk Gatsby Computatonal Neuroscence Unt, Unversty College London, London, WCN 3AR, UK S. Sathya Keerth selvarak@yahoo-nc.com

More information

Nonbinary Quantum Error-Correcting Codes from Algebraic Curves

Nonbinary Quantum Error-Correcting Codes from Algebraic Curves Nonbnary Quantum Error-Correctng Codes from Algebrac Curves Jon-Lark Km and Judy Walker Department of Mathematcs Unversty of Nebraska-Lncoln, Lncoln, NE 68588-0130 USA e-mal: {jlkm, jwalker}@math.unl.edu

More information

Can Auto Liability Insurance Purchases Signal Risk Attitude?

Can Auto Liability Insurance Purchases Signal Risk Attitude? Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang

More information

Chapter 7: Answers to Questions and Problems

Chapter 7: Answers to Questions and Problems 19. Based on the nformaton contaned n Table 7-3 of the text, the food and apparel ndustres are most compettve and therefore probably represent the best match for the expertse of these managers. Chapter

More information

On Secrecy Capacity Scaling in Wireless Networks

On Secrecy Capacity Scaling in Wireless Networks On Secrecy Capacty Scalng n Wreless Networks O. Ozan Koyluoglu, Student Member, IEEE, C. Emre Koksal, Member, IEEE, and esham El Gamal, Fellow, IEEE arxv:0908.0898v [cs.it] 0 Apr 00 Abstract Ths work studes

More information

How To Understand The Results Of The German Meris Cloud And Water Vapour Product

How To Understand The Results Of The German Meris Cloud And Water Vapour Product Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller

More information

Inertial Field Energy

Inertial Field Energy Adv. Studes Theor. Phys., Vol. 3, 009, no. 3, 131-140 Inertal Feld Energy C. Johan Masrelez 309 W Lk Sammamsh Pkwy NE Redmond, WA 9805, USA jmasrelez@estfound.org Abstract The phenomenon of Inerta may

More information

Politecnico di Torino. Porto Institutional Repository

Politecnico di Torino. Porto Institutional Repository Poltecnco d orno Porto Insttutonal Repostory [Artcle] Study and development of morphologcal analyss gudelnes for pont cloud management: he "decsonal cube" Orgnal Ctaton: Vezzett E. (2011). Study and development

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

HÜCKEL MOLECULAR ORBITAL THEORY

HÜCKEL MOLECULAR ORBITAL THEORY 1 HÜCKEL MOLECULAR ORBITAL THEORY In general, the vast maorty polyatomc molecules can be thought of as consstng of a collecton of two electron bonds between pars of atoms. So the qualtatve pcture of σ

More information

POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and

POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and POLYSA: A Polynomal Algorthm for Non-bnary 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 information

Pricing Overage and Underage Penalties for Inventory with Continuous Replenishment and Compound Renewal Demand via Martingale Methods

Pricing Overage and Underage Penalties for Inventory with Continuous Replenishment and Compound Renewal Demand via Martingale Methods Prcng Overage and Underage Penaltes for Inventory wth Contnuous Replenshment and Compound Renewal emand va Martngale Methods RAF -Jun-3 - comments welcome, do not cte or dstrbute wthout permsson Junmn

More information

Kinetic Energy-Based Temperature Computation in Non-Equilibrium Molecular. Dynamics Simulation. China. Avenue, Kowloon, Hong Kong, China

Kinetic Energy-Based Temperature Computation in Non-Equilibrium Molecular. Dynamics Simulation. China. Avenue, Kowloon, Hong Kong, China Knetc Energy-Based Temperature omputaton n on-equlbrum Molecular Dynamcs Smulaton Bn Lu, * Ran Xu, and Xaoqao He AML, Department of Engneerng Mechancs, Tsnghua Unversty, Bejng 00084, hna Department of

More information

Period and Deadline Selection for Schedulability in Real-Time Systems

Period and Deadline Selection for Schedulability in Real-Time Systems Perod and Deadlne Selecton for Schedulablty n Real-Tme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng

More information

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance Applcaton of Quas Monte Carlo methods and Global Senstvty Analyss n fnance Serge Kucherenko, Nlay Shah Imperal College London, UK skucherenko@mperalacuk Daro Czraky Barclays Captal DaroCzraky@barclayscaptalcom

More information

How To Calculate The Accountng Perod Of Nequalty

How To Calculate The Accountng Perod Of Nequalty Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.

More information

An Analysis of Dynamic Severity and Population Size

An Analysis of Dynamic Severity and Population Size An Analyss of Dynamc Severty and Populaton Sze Karsten Wecker Unversty of Stuttgart, Insttute of Computer Scence, Bretwesenstr. 2 22, 7565 Stuttgart, Germany, emal: Karsten.Wecker@nformatk.un-stuttgart.de

More information

Introduction to Statistical Physics (2SP)

Introduction to Statistical Physics (2SP) Introducton to Statstcal Physcs (2SP) Rchard Sear March 5, 20 Contents What s the entropy (aka the uncertanty)? 2. One macroscopc state s the result of many many mcroscopc states.......... 2.2 States wth

More information

SUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW.

SUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW. SUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW. Lucía Isabel García Cebrán Departamento de Economía y Dreccón de Empresas Unversdad de Zaragoza Gran Vía, 2 50.005 Zaragoza (Span) Phone: 976-76-10-00

More information