'Initial states' presentation slideshows

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window

window. power. power. [10 ,14:30]. X. X. X. X. Visual servo (.2, -.15). Dig(5). Drive (-1). NIR. data. Workspace pan. Lo res. Rock finder. Hi res. Carbonate. [10 ,14:30].

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Sequential System Synthesis -- Finite State Machine

Sequential System Synthesis -- Finite State Machine. Outline: Finite State Machine. Definitions FSM Representations State Transition Graph (STG) Flow Table Cube Table State Minimization Completely Specified FSM Incompletely Specified Machine (ISM) State Encoding.

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ATLAS physics studies

ATLAS physics studies. Lian-You SHAN On behalf of AtlasClusterChina TeV 4 @ Tango Aug 25, 2009 . Outline. Introduction Published studies Studies on going Possible Studies later Summary. Introduction. A brief report of past works For your review

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Muon Collider/Neutrino Factory Collaboration Meeting Riverside, California, January 27-31, 2004

Muon Collider/Neutrino Factory Collaboration Meeting Riverside, California, January 27-31, 2004. Modeling and Simulations of Cavitating and Bubbly Flows Roman Samulyak Tianshi Lu, Yarema Prykarpatskyy Center for Data Intensive Computing Brookhaven National Laboratory

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Logic Synthesis

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Statistical NLP: Hidden Markov Models

Statistical NLP: Hidden Markov Models. Updated 8/12/2005. Markov Models. Markov models are statistical tools that are useful for NLP because they can be used for part-of-speech-tagging applications Their first use was in modeling the letter sequences in works of Russian literature

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An Approach to Preserve Protocol Consistency and Executability Across Updates

An Approach to Preserve Protocol Consistency and Executability Across Updates. M. Subramaniam University of Nebraska at Omaha Joint Work with P. Chundi. Outline. Motivation and goal Specifying protocols and updates Consistent single rule updates Add-updates Replace-updates

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Linear Time vs. Branching Time

CS 267: Automated Verification Lecture 2: Linear vs. Branching time. Temporal Logics: CTL, CTL*. CTL model checking algorithm. Counter-example generation. Instructor: Tevfik Bultan. Linear Time vs. Branching Time. In linear time logics we look at the execution paths individually

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Ab Initio Direct (Chemical) Dynamics Nonadiabatic Reactions X Statistical Methods X

Ab Initio Direct (Chemical) Dynamics Nonadiabatic Reactions X Statistical Methods X Adiabatic Reactions . What do we want to know?. Products Rate coefficients, reaction cross sections, initial state dependence, final state distribution, state to state cross sections, Mechanism.

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P. Zanardi USC

Ground State and out of equilibrium fidelities: from quantum phase transitions to equilibration dynamics. P. Zanardi USC. KITPC April 2011. (Quantum) Phase Transition : dramatic change of the

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Game-Based Verification of Fair Exchange Protocols

CS 259. Game-Based Verification of Fair Exchange Protocols. Vitaly Shmatikov. Overview. Fair exchange protocols Protocols as games Security as presence or absence of certain strategies Alternating transition systems Formal model for adversarial protocols Alternating-time temporal logic

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Simultaneous Transducers for Data-Parallel XML Parsing

Simultaneous Transducers for Data-Parallel XML Parsing. Yinfei Pan, Ying Zhang, and Kenneth Chiu. Computer Science SUNY Binghamton. Problem. It is well-known that XML parsing is slow (DOM style) What we want to address? Build faster XML DOM parser How?

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Towards Automating the Redesign of the Synchronization Skeletons of UPC Programs

Towards Automating the Redesign of the Synchronization Skeletons of UPC Programs. Presenter: Amin Alipour Adviser: Ali Ebnenasir. Motivations. Help developers in automated behavioral debugging, and

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Observation of the Spin Hall Effect of Light via Weak Measurements

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Streamflow assimilation for improving ensemble streamflow forecasts

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Converting LTL to Buchi

Converting LTL to Buchi. Wishnu Prasetya wishnu@cs.uu.nl www.cs.uu.nl/docs/vakken/pv. Converting LTL to Buchi. Given an LTL formula ?, construct a Buchi automaton M that accepts the same sentences as ?.

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Serial and Serializable Schedules (Section 18.1)

Serial and Serializable Schedules (Section 18.1). Sean Gilpin ID: 109. Overview. Topics Covered: Schedules Serial Schedules Serializable Schedules Effect of Transaction Semantics Notation for Transactions and Schedules. Introduction.

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Learning, Uncertainty, and Information: Learning Parameters

Learning, Uncertainty, and Information: Learning Parameters. Big Ideas November 10, 2004. Roadmap. Noisy-channel model: Redux Hidden Markov Models The Model Decoding the best sequence Training the model (EM) N-gram models: Modeling sequences Shannon, Information Theory, and Perplexity

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