PPT-Semantic Heuristic Localization

TerraSwarm Localization Workshop Ann Arbor MI May 16 2014 University of Michigan Branden Ghena Background Whos in Lab TerraSwarm Research Center 2 Background What People Carry Phones. - . or. -. How to Spoof Your Location with a Tin Can. Kevin Bauer. , Damon McCoy, Eric Anderson, Markus Breitenbach, . Greg Grudic, Dirk Grunwald, and Douglas Sicker. University of Colorado. . IEEE GLOBECOM 2009 December 3, 2009 . Polly Huang. Electrical Engineering. National Taiwan University. http://nslab.ee.ntu.edu.tw/. 1. Road Map. Sensor network?. Indoor localization?. The system & . testbed. Technical challenges. Causality Study. WELCOME. to the inaugural. Game Localization Summit @ GDC. Co-Advisors of the Game Localization Summit and chairs of the . IGDA Localization SIG:. Miguel Á. Bernal-Merino . (Roehampton University), SIG Vice-Chair. NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. Learning Objectives. Understand why WSNs need localization protocols. Understand localization protocols in WSNs. Understand secure localization protocols. Prerequisites. Module 7. Basic concepts of network security. NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. David Johnson. cs6370. Basic Problem. Go from this to this. [Thrun, Burgard & Fox (2005)]. . Kalman . Filter. [Thrun, Burgard & Fox (2005)]. . Kalman Limitations. Need initial state and confidence. Gabriel Robins and . Kirti Chawla. Department of Computer Science. robins@cs.virginia.edu kirti@cs.virginia.edu. Outline. Problem: Object Localization. Prior Art. RFID Technology Primer. Our Localization Approach. CPSC 481: HCI I. Fall 2014. 1. Anthony Tang with acknowledgements to Saul Greenberg and Ehud . Sharlin. Learning Objectives. By the end of this class, you should be able to:. » understand and describe . unknown environment. Athanasios Ch. Kapoutsis. , Christina M. . Malliou. , Savvas A. Chatzichristofis and Elias B. . Kosmatopoulos. School of Electrical and Computer Engineering,. Democritus University of Thrace, Xanthi, Greece. SING a LOCAL SONG that is POPULAR in your PLACE. ACTIVITY. Localization and Contextualization. Legal Basis. RA 10533. Enhanced Basic . E. ducation . A. ct of 2013. Localization and Contextualization. Continued. Before we continue. Breadth-First. Depth-First. Uniform Cost. Iterative-Deepening. Before we continue. Breadth-First. S,A,B,D,C,G. Depth-First. S,A,C,D,B,G. Uniform Cost. S,A,B,D,C,G. Iterative-Deepening. Introduction. Semantic Role Labeling. Agent. Theme. Predicate. Location. Can we figure out that these have the same meaning?. XYZ . corporation . bought. the . stock.. They . sold. the stock to XYZ . often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. heuristic search methods are known as “weak methods” because of their generality and because they do not apply a great deal of knowledge .