'Unit disk' presentation slideshows

VECTOR CALCULUS

17. VECTOR CALCULUS. VECTOR CALCULUS. 17.7 Surface Integrals. In this section, we will learn about: Integration of different types of surfaces. SURFACE INTEGRALS.

1.56k views • 103 slides

VECTOR CALCULUS

16. VECTOR CALCULUS. VECTOR CALCULUS. 16.7 Surface Integrals. In this section, we will learn about: Integration of different types of surfaces. SURFACE INTEGRALS.

1.44k views • 103 slides

University of Denver Department of Mathematics Department of Computer Science

University of Denver Department of Mathematics Department of Computer Science. Geometric graphs Planar graph Unit disk graph Applications Ad hoc wireless networks Robot route planning moving in a terrain of varied types (e.g. grassland, brush land, forest, water etc.

1.12k views • 90 slides

University of Denver Department of Mathematics Department of Computer Science

University of Denver Department of Mathematics Department of Computer Science. Applications Ad hoc Wireless networks Robot Route Planning in a terrain of varied types (ex: grassland, brush land, forest, water etc.) Geometric graphs Planar graph Unit disk graph. Geometric Routing.

770 views • 62 slides

Tiny Networking

Tiny Networking. David Culler University of California, Berkeley Intel Research Berkeley. http://webs.cs.berkeley.edu. Vast Networks of Tiny Devices. Past 25 years of internet technology built up around powerful dedicated devices that are carefully configured and very stable

676 views • 53 slides

Packing Necklaces into a Box

Packing Necklaces into a Box. Valentin Polishchuk Helsinki Institute for Information Technology, University of Helsinki and Helsinki University of Technology. Joint work with. Estie Arkin , Joe Mitchell Applied Math and Statistics, Stony Brook University

636 views • 47 slides

Chapter 6 Relaxation (1) CDS in unit disk graph

Chapter 6 Relaxation (1) CDS in unit disk graph. Ding-Zhu Du. Sensor network. Internet / Satellite. User1. User2. Sink. phenomenon. Sensing Area. Sensor Networks.

570 views • 43 slides

Tensor and Emission Tomography Problems on the Plane

Tensor and Emission Tomography Problems on the Plane. A. L. Bukhgeim S. G. Kazantsev A. A. Bukhgeim Sobolev Institute of Mathematics Novosibirsk, RUSSIA. Overview. 1) Transmission tomography inversion formula on the basis of SVD of the Radon transform scalar, vector and tensor cases.

564 views • 43 slides

On agent-friendly aggregation in networks

On agent-friendly aggregation in networks. ATSN 2008 (at AAMAS 2008) Christian Sommer and Shinichi Honiden National Institute of Informatics, The University of Tokyo Tokyo, Japan. Agenda. Sensor networks Aggregation Agent aggregation specifics Problem model: aggregation graph

512 views • 38 slides

Efficient Hop ID based Routing for Sparse Ad Hoc Networks

Efficient Hop ID based Routing for Sparse Ad Hoc Networks. Yao Zhao 1 , Bo Li 2 , Qian Zhang 2 , Yan Chen 1 , Wenwu Zhu 3. 1 Lab for Internet & Security Technology, Northwestern University 2 Hong Kong University of Science and Technology 3 Microsoft Research Asia. Outline. Motivation

473 views • 36 slides

Fast Geometric Routing with Concurrent Face Traversal

Fast Geometric Routing with Concurrent Face Traversal. Tom Clouser Mark Miyashita Mikhail Nesterenko Kent State University OPODIS December 17, 2008. ?. Geometric Routing: Routing without Overhead. static nodes, each node knows its global coordinates, source knows coords of destination

448 views • 36 slides

Parameterizing N-holed Tori

444 views • 29 slides

Composition Operators Associated with Linear Fractional Transformations in Complex Spaces

Composition Operators Associated with Linear Fractional Transformations in Complex Spaces. Fiana Jacobzon, Simeon Reich and David Shoikhet ORT BRAUDE COLLEGE & TECHNION. The Galton-Watson model Historical background.

390 views • 25 slides

K-clustering in Wireless Ad Hoc Networks

K-clustering in Wireless Ad Hoc Networks . Fernandess and Malkhi Hebrew University of Jerusalem Presented by: Ashish Deopura. Outline of the presentation. Motivation for clustering in Mobile Ad hoc networks Problem Statement Algorithm Description Conclusions / Summary.

367 views • 24 slides

Binary Shape Clustering via Zernike Moments

Binary Shape Clustering via Zernike Moments. By: Stephen Yoo Michael Vorobyov. Moments. In general, moments describe numeric quantities at some distance from a reference point or axis. . Regular (Cartesian) Moments.

493 views • 21 slides

Outline

Generic Fourier Descriptor for Shape-based Image Retrieval Dengsheng Zhang, Guojun Lu Gippsland School of Comp. & Info Tech Monash University Churchill, VIC 3842 Australia dengsheng.zhang@infotech.monash.edu.au http://www.gscit.monash.edu.au/~dengs/. Outline. Motivations Problems

352 views • 20 slides

Linear Discriminators

250 views • 13 slides

Leveraging Linial's Locality Limit

Leveraging Linial's Locality Limit. Christoph Lenzen, Roger Wattenhofer. D istributed C omputing G roup. The problem. we have a sensor network, where nodes communicate by radio all radios have the same (normalized) range we want to minimize energy consumption for communication

265 views • 13 slides

Void Traversal for Guaranteed Delivery in Geometric Routing

d 2. s. V 1. V 3. d 1. V 2. Void Traversal for Guaranteed Delivery in Geometric Routing. Mikhail Nesterenko Adnan Vora Kent State University MASS November 09, 2005. d 2. ?. Geometric Routing: Routing without Overhead. no tables : each node knows only neighbors

247 views • 13 slides

Reserved Names

Reserved Names. //TPEIN DD UNIT=TAPE,DSN=PR.FLE, // DISP=(OLD,KEEP,KEEP)

188 views • 11 slides