'Tunable parameters' presentation slideshows

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The coupled stratosphere-troposphere response to impulsive forcing from the troposphere

The coupled stratosphere-troposphere response to impulsive forcing from the troposphere

The coupled stratosphere-troposphere response to impulsive forcing from the troposphere. Thomas J. Reichler Geophysical Fluid Dynamics Laboratory / Princeton University, Princeton NJ Paul J. Kushner Department of Physics / University of Toronto, Toronto Lorenzo M. Polvani

By jebediah
(171 views)

IETF-87 AQM BoF

IETF-87 AQM BoF

IETF-87 AQM BoF. http:// www.ietf.org/mail-archive/web/aqm/current/maillist.html. Wesley Eddy < wes@mti-systems.com > Richard Scheffenegger < rs@netapp.com > Tue., 30. July 2013 17:00, Potsdam 1 Room . Introduction.

By mura
(89 views)

Starcraft Behavior Tree AI

Starcraft Behavior Tree AI

Starcraft Behavior Tree AI. Hashem Aayed Sean Boocock Michael Hsu Aadarsh Patel. Overview. Recapping our original goal Behavior tree implementation Other design considerations Replays! Future work Q/A. Original Goal.

By poppy
(110 views)

UEISIM Desktop

UEISIM Desktop

UEISIM Desktop. Overview. The UEISIM is a Linux based system that runs S imulink models. UEISIM Desktop allows remote monitoring and parameter tuning while a model is running . R emote monitoring/Parameter tuning. External mode :

By sailor
(158 views)

Track Output Interpretation

Track Output Interpretation

Track Output Interpretation. Thomas Herring. Track Output Files. Track outputs progress directly to the screen and this output can be re-directed with > to a file. (Generally track_xxx.out) Summary file (track.sum by default) Position files (NEU or GEOD) Phase residual files (optional)

By mea
(117 views)

Dynamic Phase-based Tuning for Embedded Systems Using Phase Distance Mapping

Dynamic Phase-based Tuning for Embedded Systems Using Phase Distance Mapping

Dynamic Phase-based Tuning for Embedded Systems Using Phase Distance Mapping. Tosiron Adegbija 1 , Ann Gordon-Ross 1+ , and Arslan Munir 2 1 Department of Electrical and Computer Engineering University of Florida, Gainesville, Florida, USA

By bran
(171 views)

Bob Lucas University of Southern California Sept. 23, 2011

Bob Lucas University of Southern California Sept. 23, 2011

Science Pipeline Allen D. Malony University of Oregon May 6, 2014. Bob Lucas University of Southern California Sept. 23, 2011.

By eve
(111 views)

Efficient Diverse Search

Efficient Diverse Search

Efficient Diverse Search. HY-562: Advanced Topics in Databases Orfanoudakis Nikolaos 2059 Spring 2014. Introduction Efficient Computation of Diverse Query Results Diversity Definition and Impossibility Results One-pass Algorithms Probing Algorithms Experiments

By satin
(110 views)

Simple and Near-Optimal Auctions

Simple and Near-Optimal Auctions

Simple and Near-Optimal Auctions. Tim Roughgarden (Stanford). Motivation. Optimal auction design: what's the point? One primary reason: suggests auction formats likely be useful in practice. Exhibit A: single-item Vickrey auction. maximizes welfare (ex post) [ Vickrey 61]

By ova
(121 views)

Martin Theobald Max Planck Institute for Computer Science Stanford University Joint work with

Martin Theobald Max Planck Institute for Computer Science Stanford University Joint work with

TopX Efficient & Versatile Top-k Query Processing for Semistructured Data. Martin Theobald Max Planck Institute for Computer Science Stanford University Joint work with Ralf Schenkel , Gerhard Weikum. article. article. title. title. “ Current Approaches

By carr
(141 views)

Texture

Texture

Texture. Texture. Texture is an innate property of all surfaces (clouds, trees, bricks, hair etc…). It refers to visual patterns of homogeneity and does not result from the presence of a single color.

By austin
(185 views)

Uncovering the Temporal Dynamics of Diffusion Networks

Uncovering the Temporal Dynamics of Diffusion Networks

1 MPI for Intelligent Systems 2 Stanford University. Manuel Gomez Rodriguez 1,2 David Balduzzi 1 Bernhard Schölkopf 1. Uncovering the Temporal Dynamics of Diffusion Networks. Diffusion and propagation. Diffusion and propagation processes occur in many domains :. Reconstructing cascades.

By shelley
(216 views)

Queuing and Queue Management

Queuing and Queue Management

Queuing and Queue Management. COS 561: Advanced Networking Spring 2012 Mike Freedman http://www.cs.princeton.edu/courses/archive/fall12/cos561/. Outline of Today’s Lecture. Router Queuing Models Limitations of FIFO and Drop Tail Scheduling Policies Fair Queuing Drop policies

By dom
(172 views)

IndIGO

IndIGO

IndIGO.  Preparing India for Gravitational wave Astronomy. Ind i an I nititative in G ravitational-wave O bservations. Tarun Souradeep. IUCAA Retreat 2011 April 21, 2011. GEO: 0.6km. VIRGO: 3km. LIGO-LHO: 2km, 4km. TAMA: 0.3km. LIGO-LLO: 4km. LIGO-Australia?.

By nau
(230 views)

Changes in TPC tracking code and seeding optimisation

Changes in TPC tracking code and seeding optimisation

Sylwester Radomski off-line week CERN, June 12, 2002. Changes in TPC tracking code and seeding optimisation. Sylwester Radomski GSI, Darmstadt S.Radomski@gsi.de Sylwester.Radomski@cern.ch. Sylwester Radomski off-line week CERN, June 12, 2002. Content. Introduction

By regis
(104 views)

Passive Fractionation of Colloids and Cells Using Optofluidics

Passive Fractionation of Colloids and Cells Using Optofluidics

Passive Fractionation of Colloids and Cells Using Optofluidics. Praveen C. Ashok and Kishan Dholakia. Optical Manipulation Group, University of St Andrews, Scotland. Cell or colloidal fractionation - rationale. Possible tools that can be used. Optical fractionation.

By mabyn
(120 views)

Wireless Sensor Networks COE 499 Sleep-based Topology Control I

Wireless Sensor Networks COE 499 Sleep-based Topology Control I

Wireless Sensor Networks COE 499 Sleep-based Topology Control I. Tarek Sheltami KFUPM CCSE COE http://faculty.kfupm.edu.sa/coe/tarek/coe499.htm. Outline. Overview Constructing topologies for connectivity BEAC/AFECA GAF, CEC ASCENT SPAN. Overview.

By zytka
(149 views)


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