Fast Ray Tetrahedron Intersection using Plücker Coordinates

Size: px
Start display at page:

Download "Fast Ray Tetrahedron Intersection using Plücker Coordinates"

Transcription

1 Fast Ray Tetrahedron Intersection sing Plücker Coordinates Nikos Platis and Theoharis Theoharis Department of Informatics & Telecommnications University of Athens Panepistemiopolis, GR Ilissia, Greece {nplatis Abstract We present an algorithm for ray tetrahedron intersection. The algorithm ses Plücker coordinates to represent the ray and the edges of the tetrahedron and employs a robst and efficient test to determine the intersection. The algorithm is highly optimized and provides a significant performance increase over related algorithms. 1 Introdction Tests for intersection of directed lines with graphics primitives are at the heart of many rendering and processing algorithms. The crrent litteratre does not treat explicitly the ray tetrahedron intersection problem, even thogh tetrahedral meshes are sed increasingly for the representation of volmetric models [GCMS01]. In this paper we investigate efficient soltions to this problem. Notation and Conventions In the ray tetrahedron algorithms that follow, the ray will be assmed an infinite directed line, determined by a point P and a direction L. The vertices of the tetrahedron will be marked V 0, V 1, V 2, V, and its faces by the index of the opposite vertex: F (V 0 V 1 V 2 ), F 2 (V 1 V 0 V ), F 1 (V 2 V V 0 ), F 0 (V V 2 V 1 ). We will se the notation V0 i, V1 i, V2 i to refer to the vertices of face F i ; for example, the vertices of face F 2 above are V0 2 = V 1, V1 2 = V 0 and V2 2 = V. Similarly, the edges of face F i will be sbscripted by the index of the opposite vertex: e i 0(V1 i V2 i ), e i 1(V2 i V0 i ), e i 2(V0 i V1 i ). We will assme that the tetrahedron is oriented so that the otward-pointing normal of face F i is directed away from vertex V i. If the ray intersects the tetrahedron, in general there will be two intersection points, and. Special cases with one or infinite intersection points arise if the ray intersects one or more edges; these cases can be handled niformly by the general case as shown in Figre 1, bt in some applications it may be beneficial to mark them explicitly. For the two intersection points, we reqire that the algorithms compte: 1

2 V V 0 V 1 V 2 (a) (b) (c) Figre 1: Ray tetrahedron intersection: (a) two, (b) one, (c) infinite intersection points. Their Cartesian coordinates and. Their barycentric coordinates enter 1, enter 2 and leave 1, leave 2 with respect to the faces that they intersect, F enter and F leave, sch that P k = (1 k 1 k 2)V k 0 + k 1V k 1 + k 2V k 2 for k = enter, leave. Their parametric distance t enter and t leave from the ray origin, sch that P k = P + t k L for k = enter, leave. 2 Related Work 2.1 Approaches for ray tetrahedron intersection A ray tetrahedron intersection test can be solved by a general ray convex polyhedron intersection algorithm. Haines [Hai91] handles this general case with an algorithm that works similarly to the familiar Liang-Barsky [FvDFH96] line clipping algorithm. This algorithm is fairly efficient also for tetrahedra and is sed as a base for or comparisons. It works with the parametric eqation of the ray and comptes the intersection points sing their parametric distance from the ray origin; ths it has the advantage that restrictions concerning this distance (for example, a bond on the maximm valid distance along the ray, sefl in ray tracing) can be applied early. On the other hand, it does not se barycentric coordinates, which conceqently mst be compted as a post-processing for the intersection points; moreover, it can recognize the special cases of intersection mentioned above only throgh these barycentric coordinates. Alternatively, the ray tetrahedron intersection problem can be solved by testing each face of the tetrahedron for intersection with the ray and combining the reslts; several efficient ray triangle intersection algorithms exist, and it is important to se one that can better adapt to this specific problem. For instance, Möller and Trmbore [MT97] provide a very efficient sch algorithm, which also ses the parametric eqation of the ray and at the same time optimizes the comptation of barycentric coordinates; however, the ray tetrahedron intersection algorithm that we constrcted sing this algorithm did not perform well. In the next section we present the ray triangle intersection algorithm that forms the basis of or ray tetrahedron intersection algorithm. 2

3 (a) s (b) s (c) r r r s Figre 2: Relative orientation of two lines: Looking towards the direction of r, (a) s goes conterclockwise arond r, (b) s goes clockwise arond r; (c) s intersects r. 2.2 Ray Triangle Intersection sing Plücker Coordinates Plücker coordinates [Eri97, Sho98, Sto91, TH99] are a way of specifying directed lines in three-dimensional space sing six-dimensional vectors. Given a ray r determined by point P and direction L, its Plücker coordinates are given by the six-vector π r = {L : L P } = {U r : V r } (1) In or context, their important property is that, given two rays r and s, the permted inner prodct indicates their relative orientation (Figre 2): π r π s = U r V s + U s V r (2) π r π s > 0 s goes conterclockwise arond r π r π s < 0 s goes clockwise arond r π r π s = 0 s intersects or is parallel to r This property is the basis of a ray triangle intersection test. Sppose we are given a ray r and a triangle (V 0, V 1, V 2 ) with edges e 0 (V 1 V 2 ), e 1 (V 2 V 0 ), e 2 (V 0 V 1 ). Then r intersects iff it has the same orientation (cw or ccw) relative to all its edges or it intersects at most two of its edges (Figre ). Ths the following hold: r intersects (enters) π r π ei 0 i and j : π r π ej 0 r intersects (leaves) π r π ei 0 i and j : π r π ej 0 r is coplanar with π r π ei = 0 i () This test is sed sccessflly in [AC97] (and in [SF01] as the eqivalent 4 4 determinant method) to speed p ray tracing of trianglar meshes. It is robst and efficient since it reqires few floating point operations, no division, and relies only on sign comparisons; moreover, calclations for an edge can be shared among neighboring triangles. Additionally, it is important that if the ray and the triangle are not coplanar, the permted inner prodcts π r π ei provide directly the (nscaled) barycentric coordinates of the intersection point P k with respect to the vertices V i [Jon00]. Ths setting w k i = π r π ei and k i = w k i / wi k, (4) i=0

4 (a) (b) (c) Figre : (a) The ray enters the triangle; (b) The ray leaves the triangle; (c) The ray and the triangle do not intersect. the Cartesian coordinates of the intersection points can be compted as P k = k 0V 0 + k 1V 1 + k 2V 2. Sbseqently, their parametric distance from the ray origin can be trivially compted by solving for t k a coordinate of the eqation P k = P + t k L for which L is non-zero. Ray Tetrahedron Intersection sing Plücker Coordinates.1 Basic Algorithm The above ray triangle intersection test leads to a simple ray tetrahedron intersection algorithm. In the following, referring to face F i of the tetrahedron, we will denote by πj i the Plücker coordinates of edge ei j and by σi j the sign of the permted inner prodct π r πj i for the given ray r: 1, if π r π σj i = sign(π r πj) i j i > 0 = 0, if π r πj i = 0 1, if π r πj i < 0 The algorithm tests each face of the tetrahedron in trn and determines if it is F enter or F leave according to eqation (); if either of them has been fond, the relevant sign tests need not be performed for the remaining faces. F enter = nil F leave = nil for i =, 2, 1, 0 do Compte σ i 0, σ i 1 and σ i 2 if ((σ i 0 0) or (σ i 1 0) or (σ i 2 0)) if ((F enter == nil) and (σ i 0 0) and (σ i 1 0) and (σ i 2 0)) F enter = F i else if ((F leave == nil) and (σ i 0 0) and (σ i 1 0) and (σ i 2 0)) F leave = F i end for This algorithm has the advantage that it can compte the barycentric coordinates of the intersection points with little additional work, sing eqation (4). 4

5 It can also readily discern, if reqired, the special cases of bondary intersections (Figre 1(b,c)), which correspond to some of the σj i being zero. Compared to Haines algorithm, it has the drawback that it can accomodate restrictions concerning the parametric distance along the ray only as a post-processing step. As we will show, this basic algorithm can be greatly optimized and adapted to the problem being solved. Some simple enhancements are possible by nrolling the for loop and changing the sccessive tests as follows: As soon as F enter and F leave are determined, the algorithm may terminate. The inner test needs to be performed for at most three of the for faces of the tetrahedron. If none of the three faces is intersected, the forth will not be intersected either; otherwise it will be F enter or F leave depending on which face is not already fond. Comptations of the permted inner prodcts can be resed for the faces that share each edge. Care shold be taken to adjst the sign of the prodct according to the edge orientation within each face; for example, edge V 0 V 1 is sed for face F (V 0 V 1 V 2 ) whereas V 1 V 0 is sed for F 2 (V 1 V 0 V ), and π r π V0 V 1 = (π r π V1 V 0 ), see eqations (1),(2). This is important when the permted inner prodcts are not calclated in advance, since only one mst be compted for each pair of opposite directed edges; it is even more important when ray-tracing tetrahedral meshes, where each edge is shared by mltiple tetrahedra..2 Optimizations While the enhancements mentioned in the previos paragraph reqire few modifications of the basic algorithm, frther optimizations are possible at the expense of increased code complexity. Or aim is to se as little information as possible in order to decide whether a face is intersected by the ray. We notice that the inner test examines all σj i at once; however, if two of them do not agree, the third one need not be examined at all and the comptation of the relevant Plücker coordinates and permted inner prodct can be avoided. Care mst be taken since any two (bt not all three) σj i may be zero. Ths the inner test for face F i becomes: Compte σ i 0 and σ i 1 {Check if σ i 0 and σ i 1 agree, or they are zero} if ((σ i 0 == σ i 1) or (σ i 0 == 0) or (σ i 1 == 0)) Compte σ i 2 {Find the sign (orientation) σ i of the face} σ i = σ i 0 if (σ i == 0) σ i = σ i 1 if (σ i == 0) σ i = σ i 2 {At this point, σ i will be eqal to σ i 0 or σ i 1, whichever is non-zero;} {in that case it mst agree with σ i 2, or σ i 2 can be zero.} 5

6 {If both σ i 0 and σ i 1 are zero, σ i will be eqal to σ i 2} {and it mst be non-zero.} if ((σ i 0) and ((σ i 2 == σ i ) or (σ i 2 == 0))) if (σ i > 0) F enter = F i else F leave = F i When one face intersected by the ray has been fond, the above test can be simplified for the remaining faces: edges shared with the intersected face will have conforming sign and need not be tested again; frthermore, the σ i j for the remaining edges shold satisfy σi j 0 if F leave is not fond or σ i j 0 if F enter is not fond. When one face intersected by the ray has been fond and only two faces remain ntested, it is possible to determine the other one by performing only a sbset of the sign tests normally reqired. The choice depends on the sign of their common edge: sppose that F leave mst be determined between F 1 (V 2 V V 0 ) and F 0 (V V 2 V 1 ); if π r π V2V < 0, then F leave = F 1, otherwise F leave = F 0 (nless all three σj 0 are zero, in which case also F leave = F 1 ). The last two optimizations will be especially sefl when ray-tracing tetrahedral meshes. In this setting, having fond a tetrahedron intersected by the ray, connectivity information of the mesh provides the tetrahedron intersected next and F enter is already known for it (this holds nless the ray leaves the last tetrahedron throgh an edge, in which case the next tetrahedron cannot be determined directly).. Revisiting Geometry The ray tetrahedron intersection problem presents a geometric property which appears as a potentially sefl mechanism to gide the intersection algorithm. Unfortnately, in practice it does not accelerate the flly optimized algorithm of the previos section. We describe this property here for completeness and for its geometric interest. Sppose that the first face examined is F (V 0 V 1 V 2 ). If it is intersected by the ray, the algorithm contines as described in the previos section. If not, the ray hits its spporting plane inside one of the six regions formed by the lines along the edges of F (Figre 4); these regions correspond to different ranges of barycentric coordinates on this plane with respect to V 0, V 1 and V 2. Depending on the region and the ray direction, the ray may enter or leave the tetrahedron only throgh a specific face; if it does not, there is no intersection at all. For example, if it enters the plane in region (E), it may enter the tetrahedron only throgh F 1 (V 2 V V 0 ); if it enters the plane in region (A), it may leave the tetrahedron only throgh F 0 (V V 2 V 1 ). We note that the ray enters the plane if 2 j=0 (π r πj ) > 0 (it is easy to show that this is eqivalent to the test L N < 0, where N is the face normal). 6

7 V (E) (A) (F) V0 V1 (C) V 2 1 < 0 0 > 0 (D) 1 > 0 0 < 0 (B) 2 < 0 2 > 0 Figre 4: If a ray does not intersect F (V 0 V 1 V 2 ), it intersects its spporting plane in one of the six regions shown (A F). Using this test is slower than testing the remaining faces as per section.2, for two reasons: first, all three prodcts π r πj, j = 0, 1, 2, mst be compted in order to apply this property, whereas one of them cold potentially be avoided as mentioned earlier; second, a rather involved examination of the barycentric coordinates is reqired in order to determine the region of intersection on the plane. 4 Reslts We tested or algorithms on random pairs of rays and tetrahedra. Mltiple sets of 10,000 random ray tetrahedron pairs were generated, with increasing percentage of intersecting pairs from 0% to 100%; in this way the efficiency of each algorithm when different proportions of the tests scceed was assessed. Five algorithms were compared: the three variations of or algorithm corresponding to Sections.1,.2 and., Haines algorithm adapted for tetrahedra, and an algorithm similar to the one of Section.2 bt sing the Möller/Trmbore ray triangle test. All algorithms prodce, when the test is sccessfl, the two intersection points and, the intersected faces F enter and F leave, the corresponding barycentric coordinates enter 1, enter 2 and leave 1, leave 2, and the parametric distances t enter and t leave. Barycentric coordinates for Haines algorithm were compted as described in [BA88]. Tests were performed on an Intel Celeron PC at 900MHz rnning Linx. Figre 5 attests that or algorithms sing Plücker coordinates otperform the other algorithms in all cases. The optimizations of Section.2 provide an important performance gain, whereas the modifications of Section. have negative impact, as already noted. It is also interesting that Haines algorithm performs comparatively better when few pairs intersect; this is de to the fact that, in some cases, it is able to decide that there is no intersection withot examining all for faces of the tetrahedron, bt it mst process them all to find the intersection points. 7

8 Time per intersection test (µs) Plücker 1 Plücker Plücker Haines Möller/Trmbore Percentage of intersected tetrahedra Figre 5: Reslts for ray tetrahedron intersection tests Time per intersection test (µs) Plücker Plücker 2 Plücker Haines Percentage of intersected tetrahedra Figre 6: Reslts for intersection tests with precompted qantities. In a practical sitation, a spatial data strctre can be sed to identify the tetrahedra along the path of the ray; for these tetrahedra several comptations can be performed once for each ray. We modified the algorithms so as not to inclde sch comptations in the timings (π r πj i and σi j for all i, j in the case of or algorithms, similar relevant qantities for Haines algorithm; the algorithm sing the Möller/Trmbore test was not inclded in this test since it wold reqire storing a large nmber of precompted qantities). The reslts, shown in Figre 6, are remarkably consistent with the previos ones and affirm the potential of or algorithms. In any case, or flly optimized algorithm is the fastest. 8

9 References [AC97] John Amanatides and Kin Choi. Ray Tracing Trianglar Meshes. In Proceedings of the Eighth Western Compter Graphics Symposim, pages 4 52, April [BA88] Rod Bogart and Jeff Arenberg. Ray/Triangle Intersection with Barycentric Coordinates. Ray Tracing News, 1(11), November rtnews5b.html#art. [Eri97] Jeff Erickson. Plücker Coordinates. Ray Tracing News, 10(), December html/rtnv10n.html#art11. [FvDFH96] James D. Foley, Andries van Dam, Steven K. Feiner, and John F. Hghes. Compter Graphics, Principles and Practice. Addison- Wesley, second edition, [GCMS01] [Hai91] Fabio Ganovelli, Paolo Cignoni, Cladio Montani, and Roberto Scopigno. Enabling cts on mltiresoltion representation. The Visal Compter, 17: , Eric Haines. Fast Ray Convex Polyhedron Intersection. In James Arvo, editor, Graphics Gems II, pages Academic Press, [Jon00] Ray Jones. Plücker Coordinate Ttorial. Ray Tracing News, 1(1), Jly rtnv1n1.html#art8. [MT97] Tomas Möller and Ben Trmbore. Fast, Minimm Storage Ray/Triangle Intersection. jornal of graphics tools, 2(1):21 28, [SF01] Rafael J. Segra and Francisco R. Feito. Algorithms to Test Ray- Triangle Intersection. Comparative Stdy. In Vaclav Skala, editor, WSCG 2001 Conference Proceedings, Febrary [Sho98] Ken Shoemake. Plücker Coordinate Ttorial. Ray Tracing News, 11(1), Jly html/rtnv11n1.html#art. [Sto91] Jorge Stolfi. Oriented Projective Geometry. Academic Press, [TH99] Seth Teller and Michael Hohmeyer. Determining the Lines Throgh For Lines. jornal of graphics tools, 4():11 22, Web Information Sample C++ code implementing the ray tetrahedron intersection algorithm of section.2 is availabe online at 9

A sufficient condition for spiral cone beam long object imaging via backprojection

A sufficient condition for spiral cone beam long object imaging via backprojection A sfficient condition for spiral cone beam long object imaging via backprojection K. C. Tam Siemens Corporate Research, Inc., Princeton, NJ, USA Abstract The response of a point object in cone beam spiral

More information

COMPOSITION OF STABLE SET POLYHEDRA

COMPOSITION OF STABLE SET POLYHEDRA COMPOSITION OF STABLE SET POLYHEDRA Benjamin McClosky and Illya V. Hicks Department of Comptational and Applied Mathematics Rice University November 30, 2007 Abstract Barahona and Mahjob fond a defining

More information

The Disciplined Flood Protocol in Sensor Networks

The Disciplined Flood Protocol in Sensor Networks The Disciplined Flood Protocol in Sensor Networks Yong-ri Choi and Mohamed G. Goda Department of Compter Sciences The University of Texas at Astin, U.S.A. fyrchoi, godag@cs.texas.ed Hssein M. Abdel-Wahab

More information

Multiple-Choice Test Chapter Golden Section Search Method Optimization COMPLETE SOLUTION SET

Multiple-Choice Test Chapter Golden Section Search Method Optimization COMPLETE SOLUTION SET Mltiple-Choice Test Chapter 09.0 Golden Section Search Method Optimization COMPLETE SOLUTION SET. Which o the ollowing statements is incorrect regarding the Eqal Interval Search and Golden Section Search

More information

Introduction to Computational Manifolds and Applications

Introduction to Computational Manifolds and Applications IMPA - Institto de Matemática Pra e Aplicada, Rio de Janeiro, RJ, Brazil Introdction to Comptational Manifolds and Applications Part 1 - Constrctions Prof. Marcelo Ferreira Siqeira mfsiqeira@dimap.frn.br

More information

Augmenting the edge connectivity of planar straight line graphs to three

Augmenting the edge connectivity of planar straight line graphs to three Agmenting the edge connectivity of planar straight line graphs to three Marwan Al-Jbeh Mashhood Ishaqe Kristóf Rédei Diane L. Sovaine Csaba D. Tóth Pavel Valtr Abstract We characterize the planar straight

More information

h-vectors of PS ear-decomposable graphs

h-vectors of PS ear-decomposable graphs h-vectors of PS ear-decomposable graphs Nima Imani 2, Lee Johnson 1, Mckenzie Keeling-Garcia 1, Steven Klee 1 and Casey Pinckney 1 1 Seattle University Department of Mathematics, 901 12th Avene, Seattle,

More information

POWER-OF-2 BOUNDARIES

POWER-OF-2 BOUNDARIES Warren.3.fm Page 5 Monday, Jne 17, 5:6 PM CHAPTER 3 POWER-OF- BOUNDARIES 3 1 Ronding Up/Down to a Mltiple of a Known Power of Ronding an nsigned integer down to, for eample, the net smaller mltiple of

More information

Fault Tolerance in Hypercubes

Fault Tolerance in Hypercubes Falt Tolerance in Hypercbes Shobana Balakrishnan, Füsn Özgüner, and Baback A. Izadi Department of Electrical Engineering, The Ohio State University, Colmbs, OH 40, USA Abstract: This paper describes different

More information

Evaluating Influence Diagrams

Evaluating Influence Diagrams Evalating Inflence Diagrams Where we ve been and where we re going Mark Crowley Department of Compter Science University of British Colmbia crowley@cs.bc.ca Agst 31, 2004 Abstract In this paper we will

More information

On the Computational Complexity and Effectiveness of N-hub Shortest-Path Routing

On the Computational Complexity and Effectiveness of N-hub Shortest-Path Routing 1 On the Comptational Complexity and Effectiveness of N-hb Shortest-Path Roting Reven Cohen Gabi Nakibli Dept. of Compter Sciences Technion Israel Abstract In this paper we stdy the comptational complexity

More information

Constrained Routing Between Non-Visible Vertices

Constrained Routing Between Non-Visible Vertices Constrained Roting Between Non-Visible Vertices Prosenjit Bose 1, Matias Korman 2, André van Renssen 3,4, and Sander Verdonschot 1 1 School of Compter Science, Carleton University, Ottawa, Canada. jit@scs.carleton.ca,

More information

OPTI-502 Optical Design and Instrumentation I John E. Greivenkamp Homework Set 9 Fall, 2018

OPTI-502 Optical Design and Instrumentation I John E. Greivenkamp Homework Set 9 Fall, 2018 OPTI-502 Optical Design and Instrmentation I John E. Greivenkamp Assigned: 10/31/18 Lectre 21 De: 11/7/18 Lectre 23 Note that in man 502 homework and exam problems (as in the real world!!), onl the magnitde

More information

CS 450: COMPUTER GRAPHICS REVIEW: CLIPPING SPRING 2015 DR. MICHAEL J. REALE

CS 450: COMPUTER GRAPHICS REVIEW: CLIPPING SPRING 2015 DR. MICHAEL J. REALE CS 45: COMPUTER GRAPHICS REVIEW: CLIPPING SPRING 215 DR. MICHAEL J. REALE CLIPPING Clipping = removing part or all of the primitives otside of the clipping volme/window Clipping volme in OpenGL nit cbe

More information

Blended Deformable Models

Blended Deformable Models Blended Deformable Models (In IEEE Trans. Pattern Analysis and Machine Intelligence, April 996, 8:4, pp. 443-448) Doglas DeCarlo and Dimitri Metaxas Department of Compter & Information Science University

More information

arxiv: v1 [cs.cg] 26 Sep 2018

arxiv: v1 [cs.cg] 26 Sep 2018 Convex partial transversals of planar regions arxiv:1809.10078v1 [cs.cg] 26 Sep 2018 Vahideh Keikha Department of Mathematics and Compter Science, University of Sistan and Balchestan, Zahedan, Iran va.keikha@gmail.com

More information

Dynamic Maintenance of Majority Information in Constant Time per Update? Gudmund S. Frandsen and Sven Skyum BRICS 1 Department of Computer Science, Un

Dynamic Maintenance of Majority Information in Constant Time per Update? Gudmund S. Frandsen and Sven Skyum BRICS 1 Department of Computer Science, Un Dynamic Maintenance of Majority Information in Constant Time per Update? Gdmnd S. Frandsen and Sven Skym BRICS 1 Department of Compter Science, University of arhs, Ny Mnkegade, DK-8000 arhs C, Denmark

More information

Hardware-Accelerated Free-Form Deformation

Hardware-Accelerated Free-Form Deformation Hardware-Accelerated Free-Form Deformation Clint Cha and Ulrich Nemann Compter Science Department Integrated Media Systems Center University of Sothern California Abstract Hardware-acceleration for geometric

More information

Ma Lesson 18 Section 1.7

Ma Lesson 18 Section 1.7 Ma 15200 Lesson 18 Section 1.7 I Representing an Ineqality There are 3 ways to represent an ineqality. (1) Using the ineqality symbol (sometime within set-bilder notation), (2) sing interval notation,

More information

Planarity-Preserving Clustering and Embedding for Large Planar Graphs

Planarity-Preserving Clustering and Embedding for Large Planar Graphs Planarity-Presering Clstering and Embedding for Large Planar Graphs Christian A. Dncan, Michael T. Goodrich, and Stephen G. Koboro Center for Geometric Compting The Johns Hopkins Uniersity Baltimore, MD

More information

Multiresolution Techniques for the Simplification of Triangular and Tetrahedral Meshes

Multiresolution Techniques for the Simplification of Triangular and Tetrahedral Meshes Multiresolution Techniques for the Simplification of Triangular and Tetrahedral Meshes Nikos Platis Department of Informatics and Telecommunications University of Athens, Greece nplatis@di.uoa.gr Abstract.

More information

Minimal Edge Addition for Network Controllability

Minimal Edge Addition for Network Controllability This article has been accepted for pblication in a ftre isse of this jornal, bt has not been flly edited. Content may change prior to final pblication. Citation information: DOI 10.1109/TCNS.2018.2814841,

More information

Picking and Curves Week 6

Picking and Curves Week 6 CS 48/68 INTERACTIVE COMPUTER GRAPHICS Picking and Crves Week 6 David Breen Department of Compter Science Drexel University Based on material from Ed Angel, University of New Mexico Objectives Picking

More information

EECS 487: Interactive Computer Graphics f

EECS 487: Interactive Computer Graphics f Interpolating Key Vales EECS 487: Interactive Compter Graphics f Keys Lectre 33: Keyframe interpolation and splines Cbic splines The key vales of each variable may occr at different frames The interpolation

More information

arxiv: v1 [cs.cg] 1 Feb 2016

arxiv: v1 [cs.cg] 1 Feb 2016 The Price of Order Prosenjit Bose Pat Morin André van Renssen, arxiv:160.00399v1 [cs.cg] 1 Feb 016 Abstract We present tight bonds on the spanning ratio of a large family of ordered θ-graphs. A θ-graph

More information

CS 4204 Computer Graphics

CS 4204 Computer Graphics CS 424 Compter Graphics Crves and Srfaces Yong Cao Virginia Tech Reference: Ed Angle, Interactive Compter Graphics, University of New Mexico, class notes Crve and Srface Modeling Objectives Introdce types

More information

Optimal Sampling in Compressed Sensing

Optimal Sampling in Compressed Sensing Optimal Sampling in Compressed Sensing Joyita Dtta Introdction Compressed sensing allows s to recover objects reasonably well from highly ndersampled data, in spite of violating the Nyqist criterion. In

More information

On Plane Constrained Bounded-Degree Spanners

On Plane Constrained Bounded-Degree Spanners On Plane Constrained Bonded-Degree Spanners Prosenjit Bose 1, Rolf Fagerberg 2, André an Renssen 1, Sander Verdonschot 1 1 School of Compter Science, Carleton Uniersity, Ottaa, Canada. Email: jit@scs.carleton.ca,

More information

Alliances and Bisection Width for Planar Graphs

Alliances and Bisection Width for Planar Graphs Alliances and Bisection Width for Planar Graphs Martin Olsen 1 and Morten Revsbæk 1 AU Herning Aarhs University, Denmark. martino@hih.a.dk MADAGO, Department of Compter Science Aarhs University, Denmark.

More information

This chapter is based on the following sources, which are all recommended reading:

This chapter is based on the following sources, which are all recommended reading: Bioinformatics I, WS 09-10, D. Hson, December 7, 2009 105 6 Fast String Matching This chapter is based on the following sorces, which are all recommended reading: 1. An earlier version of this chapter

More information

Tutte Embeddings of Planar Graphs

Tutte Embeddings of Planar Graphs Spectral Graph Theory and its Applications Lectre 21 Ttte Embeddings o Planar Graphs Lectrer: Daniel A. Spielman November 30, 2004 21.1 Ttte s Theorem We sally think o graphs as being speciied by vertices

More information

REPLICATION IN BANDWIDTH-SYMMETRIC BITTORRENT NETWORKS. M. Meulpolder, D.H.J. Epema, H.J. Sips

REPLICATION IN BANDWIDTH-SYMMETRIC BITTORRENT NETWORKS. M. Meulpolder, D.H.J. Epema, H.J. Sips REPLICATION IN BANDWIDTH-SYMMETRIC BITTORRENT NETWORKS M. Melpolder, D.H.J. Epema, H.J. Sips Parallel and Distribted Systems Grop Department of Compter Science, Delft University of Technology, the Netherlands

More information

Maximum Weight Independent Sets in an Infinite Plane

Maximum Weight Independent Sets in an Infinite Plane Maximm Weight Independent Sets in an Infinite Plane Jarno Nosiainen, Jorma Virtamo, Pasi Lassila jarno.nosiainen@tkk.fi, jorma.virtamo@tkk.fi, pasi.lassila@tkk.fi Department of Commnications and Networking

More information

(2, 4) Tree Example (2, 4) Tree: Insertion

(2, 4) Tree Example (2, 4) Tree: Insertion Presentation for se with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015 B-Trees and External Memory (2, 4) Trees Each internal node has 2 to 4 children:

More information

FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES

FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES FINITE ELEMENT APPROXIMATION OF CONVECTION DIFFUSION PROBLEMS USING GRADED MESHES RICARDO G. DURÁN AND ARIEL L. LOMBARDI Abstract. We consider the nmerical approximation of a model convection-diffsion

More information

Vertex Guarding in Weak Visibility Polygons

Vertex Guarding in Weak Visibility Polygons Vertex Garding in Weak Visibility Polygons Pritam Bhattacharya, Sbir Kmar Ghosh*, Bodhayan Roy School of Technology and Compter Science Tata Institte of Fndamental Research Mmbai 400005, India arxi:1409.46212

More information

Constructing Multiple Light Multicast Trees in WDM Optical Networks

Constructing Multiple Light Multicast Trees in WDM Optical Networks Constrcting Mltiple Light Mlticast Trees in WDM Optical Networks Weifa Liang Department of Compter Science Astralian National University Canberra ACT 0200 Astralia wliang@csaneda Abstract Mlticast roting

More information

An Adaptive Strategy for Maximizing Throughput in MAC layer Wireless Multicast

An Adaptive Strategy for Maximizing Throughput in MAC layer Wireless Multicast University of Pennsylvania ScholarlyCommons Departmental Papers (ESE) Department of Electrical & Systems Engineering May 24 An Adaptive Strategy for Maximizing Throghpt in MAC layer Wireless Mlticast Prasanna

More information

Tu P7 15 First-arrival Traveltime Tomography with Modified Total Variation Regularization

Tu P7 15 First-arrival Traveltime Tomography with Modified Total Variation Regularization T P7 15 First-arrival Traveltime Tomography with Modified Total Variation Reglarization W. Jiang* (University of Science and Technology of China) & J. Zhang (University of Science and Technology of China)

More information

Curves and Surfaces. CS 537 Interactive Computer Graphics Prof. David E. Breen Department of Computer Science

Curves and Surfaces. CS 537 Interactive Computer Graphics Prof. David E. Breen Department of Computer Science Crves and Srfaces CS 57 Interactive Compter Graphics Prof. David E. Breen Department of Compter Science E. Angel and D. Shreiner: Interactive Compter Graphics 6E Addison-Wesley 22 Objectives Introdce types

More information

Neighbourhood Searches for the Bounded Diameter Minimum Spanning Tree Problem Embedded in a VNS, EA, and ACO

Neighbourhood Searches for the Bounded Diameter Minimum Spanning Tree Problem Embedded in a VNS, EA, and ACO Neighborhood Searches for the Bonded Diameter Minimm Spanning Tree Problem Embedded in a VNS, EA, and ACO Martin Grber Institte for Compter Graphics and Algorithms, Vienna University of Technology, Favoritenstraße

More information

The Impact of Avatar Mobility on Distributed Server Assignment for Delivering Mobile Immersive Communication Environment

The Impact of Avatar Mobility on Distributed Server Assignment for Delivering Mobile Immersive Communication Environment This fll text paper was peer reviewed at the direction of IEEE Commnications Society sbject matter experts for pblication in the ICC 27 proceedings. The Impact of Avatar Mobility on Distribted Server Assignment

More information

Uncertainty Determination for Dimensional Measurements with Computed Tomography

Uncertainty Determination for Dimensional Measurements with Computed Tomography Uncertainty Determination for Dimensional Measrements with Compted Tomography Kim Kiekens 1,, Tan Ye 1,, Frank Welkenhyzen, Jean-Pierre Krth, Wim Dewlf 1, 1 Grop T even University College, KU even Association

More information

Real-time mean-shift based tracker for thermal vision systems

Real-time mean-shift based tracker for thermal vision systems 9 th International Conference on Qantitative InfraRed Thermography Jly -5, 008, Krakow - Poland Real-time mean-shift based tracker for thermal vision systems G. Bieszczad* T. Sosnowski** * Military University

More information

Computer-Aided Mechanical Design Using Configuration Spaces

Computer-Aided Mechanical Design Using Configuration Spaces Compter-Aided Mechanical Design Using Configration Spaces Leo Joskowicz Institte of Compter Science The Hebrew University Jersalem 91904, Israel E-mail: josko@cs.hji.ac.il Elisha Sacks (corresponding athor)

More information

Discrete Cost Multicommodity Network Optimization Problems and Exact Solution Methods

Discrete Cost Multicommodity Network Optimization Problems and Exact Solution Methods Annals of Operations Research 106, 19 46, 2001 2002 Klwer Academic Pblishers. Manfactred in The Netherlands. Discrete Cost Mlticommodity Network Optimization Problems and Exact Soltion Methods MICHEL MINOUX

More information

Bias of Higher Order Predictive Interpolation for Sub-pixel Registration

Bias of Higher Order Predictive Interpolation for Sub-pixel Registration Bias of Higher Order Predictive Interpolation for Sb-pixel Registration Donald G Bailey Institte of Information Sciences and Technology Massey University Palmerston North, New Zealand D.G.Bailey@massey.ac.nz

More information

Continuity Smooth Path Planning Using Cubic Polynomial Interpolation with Membership Function

Continuity Smooth Path Planning Using Cubic Polynomial Interpolation with Membership Function J Electr Eng Technol Vol., No.?: 74-?, 5 http://dx.doi.org/.537/jeet.5..?.74 ISSN(Print) 975- ISSN(Online) 93-743 Continity Smooth Path Planning Using Cbic Polomial Interpolation with Membership Fnction

More information

p-norm MINIMIZATION OVER INTERSECTIONS OF CONVEX SETS İlker Bayram

p-norm MINIMIZATION OVER INTERSECTIONS OF CONVEX SETS İlker Bayram p-norm MINIMIZATION OVER INTERSECTIONS OF CONVEX SETS İlker Bayram Istanbl Technical University, Department of Electronics and Telecommnications Engineering, Istanbl, Trkey ABSTRACT We consider the imization

More information

Networks An introduction to microcomputer networking concepts

Networks An introduction to microcomputer networking concepts Behavior Research Methods& Instrmentation 1978, Vol 10 (4),522-526 Networks An introdction to microcompter networking concepts RALPH WALLACE and RICHARD N. JOHNSON GA TX, Chicago, Illinois60648 and JAMES

More information

Fast Obstacle Detection using Flow/Depth Constraint

Fast Obstacle Detection using Flow/Depth Constraint Fast Obstacle etection sing Flow/epth Constraint S. Heinrich aimlerchrylser AG P.O.Box 2360, -89013 Ulm, Germany Stefan.Heinrich@aimlerChrysler.com Abstract The early recognition of potentially harmfl

More information

Maximal Cliques in Unit Disk Graphs: Polynomial Approximation

Maximal Cliques in Unit Disk Graphs: Polynomial Approximation Maximal Cliqes in Unit Disk Graphs: Polynomial Approximation Rajarshi Gpta, Jean Walrand, Oliier Goldschmidt 2 Department of Electrical Engineering and Compter Science Uniersity of California, Berkeley,

More information

ABSOLUTE DEFORMATION PROFILE MEASUREMENT IN TUNNELS USING RELATIVE CONVERGENCE MEASUREMENTS

ABSOLUTE DEFORMATION PROFILE MEASUREMENT IN TUNNELS USING RELATIVE CONVERGENCE MEASUREMENTS Proceedings th FIG Symposim on Deformation Measrements Santorini Greece 00. ABSOUTE DEFORMATION PROFIE MEASUREMENT IN TUNNES USING REATIVE CONVERGENCE MEASUREMENTS Mahdi Moosai and Saeid Khazaei Mining

More information

arxiv: v1 [cs.cg] 27 Nov 2015

arxiv: v1 [cs.cg] 27 Nov 2015 On Visibility Representations of Non-planar Graphs Therese Biedl 1, Giseppe Liotta 2, Fabrizio Montecchiani 2 David R. Cheriton School of Compter Science, University of Waterloo, Canada biedl@waterloo.ca

More information

Tri-Edge-Connectivity Augmentation for Planar Straight Line Graphs

Tri-Edge-Connectivity Augmentation for Planar Straight Line Graphs Tri-Edge-Connectivity Agmentation for Planar Straight Line Graphs Marwan Al-Jbeh 1, Mashhood Ishaqe 1, Kristóf Rédei 1, Diane L. Sovaine 1, and Csaba D. Tóth 1,2 1 Department of Compter Science, Tfts University,

More information

Stereo Matching and 3D Visualization for Gamma-Ray Cargo Inspection

Stereo Matching and 3D Visualization for Gamma-Ray Cargo Inspection Stereo Matching and 3D Visalization for Gamma-Ray Cargo Inspection Zhigang Zh *ab, Y-Chi H bc a Department of Compter Science, The City College of New York, New York, NY 3 b Department of Compter Science,

More information

Master for Co-Simulation Using FMI

Master for Co-Simulation Using FMI Master for Co-Simlation Using FMI Jens Bastian Christoph Claß Ssann Wolf Peter Schneider Franhofer Institte for Integrated Circits IIS / Design Atomation Division EAS Zenerstraße 38, 69 Dresden, Germany

More information

Resolving Linkage Anomalies in Extracted Software System Models

Resolving Linkage Anomalies in Extracted Software System Models Resolving Linkage Anomalies in Extracted Software System Models Jingwei W and Richard C. Holt School of Compter Science University of Waterloo Waterloo, Canada j25w, holt @plg.waterloo.ca Abstract Program

More information

Topic Continuity for Web Document Categorization and Ranking

Topic Continuity for Web Document Categorization and Ranking Topic Continity for Web ocment Categorization and Ranking B. L. Narayan, C. A. Mrthy and Sankar. Pal Machine Intelligence Unit, Indian Statistical Institte, 03, B. T. Road, olkata - 70008, India. E-mail:

More information

Triangle-Free Planar Graphs as Segments Intersection Graphs

Triangle-Free Planar Graphs as Segments Intersection Graphs Triangle-ree Planar Graphs as Segments Intersection Graphs N. de Castro 1,.J.Cobos 1, J.C. Dana 1,A.Márqez 1, and M. Noy 2 1 Departamento de Matemática Aplicada I Universidad de Sevilla, Spain {natalia,cobos,dana,almar}@cica.es

More information

Prof. Kozyrakis. 1. (10 points) Consider the following fragment of Java code:

Prof. Kozyrakis. 1. (10 points) Consider the following fragment of Java code: EE8 Winter 25 Homework #2 Soltions De Thrsday, Feb 2, 5 P. ( points) Consider the following fragment of Java code: for (i=; i

More information

Fast Ray-Axis Aligned Bounding Box Overlap Tests with Plücker Coordinates

Fast Ray-Axis Aligned Bounding Box Overlap Tests with Plücker Coordinates Vol.9,No.1:35 46 Fast ay-axis Aligned Bounding Box Overlap Tests with Plücker Coordinates Jeffrey Mahovsky and Brian Wyvill University of Calgary Abstract. Fast ray-axis aligned bounding box overlap tests

More information

Review Multicycle: What is Happening. Controlling The Multicycle Design

Review Multicycle: What is Happening. Controlling The Multicycle Design Review lticycle: What is Happening Reslt Zero Op SrcA SrcB Registers Reg Address emory em Data Sign etend Shift left Sorce A B Ot [-6] [5-] [-6] [5-] [5-] Instrction emory IR RegDst emtoreg IorD em em

More information

Today. B-splines. B-splines. B-splines. Computergrafik. Curves NURBS Surfaces. Bilinear patch Bicubic Bézier patch Advanced surface modeling

Today. B-splines. B-splines. B-splines. Computergrafik. Curves NURBS Surfaces. Bilinear patch Bicubic Bézier patch Advanced surface modeling Comptergrafik Matthias Zwicker Uniersität Bern Herbst 29 Cres Srfaces Parametric srfaces Bicbic Bézier patch Adanced srface modeling Piecewise Bézier cres Each segment spans for control points Each segment

More information

On Plane Constrained Bounded-Degree Spanners

On Plane Constrained Bounded-Degree Spanners Algorithmica manscript No. (ill be inserted by the editor) 1 On Plane Constrained Bonded-Degree Spanners 2 3 Prosenjit Bose Rolf Fagerberg André an Renssen Sander Verdonschot 4 5 Receied: date / Accepted:

More information

Chapter 7 TOPOLOGY CONTROL

Chapter 7 TOPOLOGY CONTROL Chapter TOPOLOGY CONTROL Oeriew Topology Control Gabriel Graph et al. XTC Interference SINR & Schedling Complexity Distribted Compting Grop Mobile Compting Winter 00 / 00 Distribted Compting Grop MOBILE

More information

Efficient and Accurate Delaunay Triangulation Protocols under Churn

Efficient and Accurate Delaunay Triangulation Protocols under Churn Efficient and Accrate Delanay Trianglation Protocols nder Chrn Dong-Yong Lee and Simon S. Lam Department of Compter Sciences The University of Texas at Astin {dylee, lam}@cs.texas.ed November 9, 2007 Technical

More information

Multiple Source Shortest Paths in a Genus g Graph

Multiple Source Shortest Paths in a Genus g Graph Mltiple Sorce Shortest Paths in a Gens g Graph Sergio Cabello Erin W. Chambers Abstract We gie an O(g n log n) algorithm to represent the shortest path tree from all the ertices on a single specified face

More information

Towards Tight Bounds on Theta-Graphs

Towards Tight Bounds on Theta-Graphs Toards Tight Bonds on Theta-Graphs arxiv:10.633v1 [cs.cg] Apr 01 Prosenjit Bose Jean-Lo De Carfel Pat Morin André van Renssen Sander Verdonschot Abstract We present improved pper and loer bonds on the

More information

SZ-1.4: Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error- Controlled Quantization

SZ-1.4: Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error- Controlled Quantization SZ-1.4: Significantly Improving Lossy Compression for Scientific Data Sets Based on Mltidimensional Prediction and Error- Controlled Qantization Dingwen Tao (University of California, Riverside) Sheng

More information

Representing a Cubic Graph as the Intersection Graph of Axis-parallel Boxes in Three Dimensions

Representing a Cubic Graph as the Intersection Graph of Axis-parallel Boxes in Three Dimensions Representing a Cbic Graph as the Intersection Graph of Axis-parallel Boxes in Three Dimensions ABSTRACT Abhijin Adiga Network Dynamics and Simlation Science Laboratory Virginia Bioinformatics Institte,

More information

v e v 1 C 2 b) Completely assigned T v a) Partially assigned Tv e T v 2 p k

v e v 1 C 2 b) Completely assigned T v a) Partially assigned Tv e T v 2 p k Approximation Algorithms for a Capacitated Network Design Problem R. Hassin 1? and R. Rai 2?? and F. S. Salman 3??? 1 Department of Statistics and Operations Research, Tel-Ai Uniersity, Tel Ai 69978, Israel.

More information

The extra single-cycle adders

The extra single-cycle adders lticycle Datapath As an added bons, we can eliminate some of the etra hardware from the single-cycle path. We will restrict orselves to sing each fnctional nit once per cycle, jst like before. Bt since

More information

[1] Hopcroft, J., D. Joseph and S. Whitesides, Movement problems for twodimensional

[1] Hopcroft, J., D. Joseph and S. Whitesides, Movement problems for twodimensional Acknoledgement. The athors thank Bill Lenhart for interesting discssions on the recongration of rlers. References [1] Hopcroft, J., D. Joseph and S. Whitesides, Moement problems for todimensional linkages,

More information

The single-cycle design from last time

The single-cycle design from last time lticycle path Last time we saw a single-cycle path and control nit for or simple IPS-based instrction set. A mlticycle processor fies some shortcomings in the single-cycle CPU. Faster instrctions are not

More information

Multi-lingual Multi-media Information Retrieval System

Multi-lingual Multi-media Information Retrieval System Mlti-lingal Mlti-media Information Retrieval System Shoji Mizobchi, Sankon Lee, Fmihiko Kawano, Tsyoshi Kobayashi, Takahiro Komats Gradate School of Engineering, University of Tokshima 2-1 Minamijosanjima,

More information

Cutting Cycles of Rods in Space: Hardness and Approximation

Cutting Cycles of Rods in Space: Hardness and Approximation Ctting Cycles of Rods in Space: Hardness and pproximation oris rono ark de erg Chris Gray Elena mford bstract We stdy the problem of ctting a set of rods (line segments in R 3 ) into fragments, sing a

More information

The Intersection of Two Ringed Surfaces and Some Related Problems

The Intersection of Two Ringed Surfaces and Some Related Problems Graphical Models 63, 8 44 001) doi:10.1006/gmod.001.0553, available online at http://www.idealibrary.com on The Intersection of Two Ringed Srfaces and Some Related Problems Hee-Seok Heo and Sng Je Hong

More information

A GENERIC MODEL OF A BASE-ISOLATED BUILDING

A GENERIC MODEL OF A BASE-ISOLATED BUILDING Chapter 5 A GENERIC MODEL OF A BASE-ISOLATED BUILDING This chapter draws together the work o Chapters 3 and 4 and describes the assembly o a generic model o a base-isolated bilding. The irst section describes

More information

METAPOST and the FIIT Logo

METAPOST and the FIIT Logo METAPOST and the FIIT Logo Matej KOŠÍK Slovak University of Technology Faclty of Informatics and Information Technologies Ilkovičova 3, 842 16 Bratislava, Slovakia kosik@fiit.stba.sk 1 The Tools Abstract.

More information

arxiv: v3 [math.co] 7 Sep 2018

arxiv: v3 [math.co] 7 Sep 2018 Cts in matchings of 3-connected cbic graphs Kolja Knaer Petr Valicov arxiv:1712.06143v3 [math.co] 7 Sep 2018 September 10, 2018 Abstract We discss conjectres on Hamiltonicity in cbic graphs (Tait, Barnette,

More information

10.2 Solving Quadratic Equations by Completing the Square

10.2 Solving Quadratic Equations by Completing the Square . Solving Qadratic Eqations b Completing the Sqare Consider the eqation We can see clearl that the soltions are However, What if the eqation was given to s in standard form, that is 6 How wold we go abot

More information

Cost Based Local Forwarding Transmission Schemes for Two-hop Cellular Networks

Cost Based Local Forwarding Transmission Schemes for Two-hop Cellular Networks Cost Based Local Forwarding Transmission Schemes for Two-hop Celllar Networks Zhenggang Zhao, Xming Fang, Yan Long, Xiaopeng H, Ye Zhao Key Lab of Information Coding & Transmission Sothwest Jiaotong University,

More information

Reconstructing Generalized Staircase Polygons with Uniform Step Length

Reconstructing Generalized Staircase Polygons with Uniform Step Length Jornal of Graph Algorithms and Applications http://jgaa.info/ ol. 22, no. 3, pp. 431 459 (2018) DOI: 10.7155/jgaa.00466 Reconstrcting Generalized Staircase Polygons with Uniform Step Length Nodari Sitchinaa

More information

Identification of the Symmetries of Linear Systems with Polytopic Constraints

Identification of the Symmetries of Linear Systems with Polytopic Constraints 2014 American Control Conference (ACC) Jne 4-6, 2014. Portland, Oregon, USA Identification of the Symmetries of Linear Systems with Polytopic Constraints Clas Danielson and Francesco Borrelli Abstract

More information

Compound Catadioptric Stereo Sensor for Omnidirectional Object Detection

Compound Catadioptric Stereo Sensor for Omnidirectional Object Detection Compond Catadioptric Stereo Sensor for mnidirectional bject Detection Ryske Sagawa Naoki Krita Tomio Echigo Yasshi Yagi The Institte of Scientific and Indstrial Research, saka University 8-1 Mihogaoka,

More information

Requirements Engineering. Objectives. System requirements. Types of requirements. FAQS about requirements. Requirements problems

Requirements Engineering. Objectives. System requirements. Types of requirements. FAQS about requirements. Requirements problems Reqirements Engineering Objectives An introdction to reqirements Gerald Kotonya and Ian Sommerville To introdce the notion of system reqirements and the reqirements process. To explain how reqirements

More information

METAMODEL FOR SOFTWARE SOLUTIONS IN COMPUTED TOMOGRAPHY

METAMODEL FOR SOFTWARE SOLUTIONS IN COMPUTED TOMOGRAPHY VOL. 10, NO 22, DECEBER, 2015 ISSN 1819-6608 ETAODEL FOR SOFTWARE SOLUTIONS IN COPUTED TOOGRAPHY Vitaliy ezhyev Faclty of Compter Systems and Software Engineering, Universiti alaysia Pahang, Gambang, alaysia

More information

EMC VNX Series. Problem Resolution Roadmap for VNX with ESRS for VNX and Connect Home. Version VNX1, VNX2 P/N REV. 03

EMC VNX Series. Problem Resolution Roadmap for VNX with ESRS for VNX and Connect Home. Version VNX1, VNX2 P/N REV. 03 EMC VNX Series Version VNX1, VNX2 Problem Resoltion Roadmap for VNX with ESRS for VNX and Connect Home P/N 300-014-335 REV. 03 Copyright 2012-2014 EMC Corporation. All rights reserved. Pblished in USA.

More information

Nash Convergence of Gradient Dynamics in General-Sum Games. Michael Kearns.

Nash Convergence of Gradient Dynamics in General-Sum Games. Michael Kearns. Convergence of Gradient Dynamics in General-Sm Games Satinder Singh AT&T Labs Florham Park, NJ 7932 bavejaresearch.att.com Michael Kearns AT&T Labs Florham Park, NJ 7932 mkearnsresearch.att.com Yishay

More information

arxiv: v2 [cs.cg] 5 Aug 2014

arxiv: v2 [cs.cg] 5 Aug 2014 The θ 5 -graph is a spanner Prosenjit Bose Pat Morin André van Renssen Sander Verdonschot November 5, 2018 arxiv:12120570v2 [cscg] 5 Ag 2014 Abstract Given a set of points in the plane, e sho that the

More information

Factors Influencing Performance of Firefly and Particle Swarm Optimization Algorithms

Factors Influencing Performance of Firefly and Particle Swarm Optimization Algorithms Factors Inflencing Performance of Firefly and Particle Swarm Optimization Algorithms Damanjeet Kar, UIET, Panjab University, Chandigarh Abstract In this paper, two natre inspired meta heristic approaches

More information

Subgraph Matching with Set Similarity in a Large Graph Database

Subgraph Matching with Set Similarity in a Large Graph Database 1 Sbgraph Matching with Set Similarity in a Large Graph Database Liang Hong, Lei Zo, Xiang Lian, Philip S. Y Abstract In real-world graphs sch as social networks, Semantic Web and biological networks,

More information

EMC ViPR. User Guide. Version

EMC ViPR. User Guide. Version EMC ViPR Version 1.1.0 User Gide 302-000-481 01 Copyright 2013-2014 EMC Corporation. All rights reserved. Pblished in USA. Pblished Febrary, 2014 EMC believes the information in this pblication is accrate

More information

arxiv: v1 [cs.si] 12 Dec 2016

arxiv: v1 [cs.si] 12 Dec 2016 Connection Discovery sing Shared Images by Gassian Relational Topic Model Xiaopeng Li, Ming Cheng, James She HKUST-NIE Social Media Lab, Hong Kong University of Science & Technology, Hong Kong xlibo@connect.st.hk,

More information

Chapter 6: Pipelining

Chapter 6: Pipelining CSE 322 COPUTER ARCHITECTURE II Chapter 6: Pipelining Chapter 6: Pipelining Febrary 10, 2000 1 Clothes Washing CSE 322 COPUTER ARCHITECTURE II The Assembly Line Accmlate dirty clothes in hamper Place in

More information

Functions of Combinational Logic

Functions of Combinational Logic CHPTER 6 Fnctions of Combinational Logic CHPTER OUTLINE 6 6 6 6 6 5 6 6 6 7 6 8 6 9 6 6 Half and Fll dders Parallel inary dders Ripple Carry and Look-head Carry dders Comparators Decoders Encoders Code

More information

OPTI-502 Optical Design and Instrumentation I John E. Greivenkamp Homework Set 7 Fall, 2018

OPTI-502 Optical Design and Instrumentation I John E. Greivenkamp Homework Set 7 Fall, 2018 Assigned: 10/10/18 Lectre 15 De: 10/17/18 Lectre 17 Midterm Exam: Wednesda October 24 (Lectre 19) The eqation sheet for the exam has been posted on the corse website. This eqation sheet will be inclded

More information

Local Run Manager. Software Reference Guide for MiSeqDx

Local Run Manager. Software Reference Guide for MiSeqDx Local Rn Manager Software Reference Gide for MiSeqDx Local Rn Manager Overview 3 Dashboard Overview 4 Administrative Settings and Tasks 7 Workflow Overview 12 Technical Assistance 17 Docment # 1000000011880

More information

An Introduction to GPU Computing. Aaron Coutino MFCF

An Introduction to GPU Computing. Aaron Coutino MFCF An Introdction to GPU Compting Aaron Cotino acotino@waterloo.ca MFCF What is a GPU? A GPU (Graphical Processing Unit) is a special type of processor that was designed to render and maniplate textres. They

More information