PPT-Modeling Space/Time Variability with BMEGUI

Prahlad Jat 1 and Marc Serre 1 1 University of North Carolina at Chapel Hill Agenda Introduction Mean Trend Analysis SpaceTime Covariance Analysis Introduction Temporal GIS analysis process. Phil Uttley. T. Wilkinson, P. Cassatella (Southampton). J. Wilms, M. Hanke, M. Böck (FAU) . K. Pottschmidt (NASA-GSFC). Introduction. . BHXRB hard state spectra show clear evidence for both disc and hot coronal components, as well as interaction between them (reflection).. Time Series in High Energy Astrophysics. Brandon C. Kelly. Harvard-Smithsonian Center for Astrophysics. Lightcurve. shape determined by time and parameters. Examples: . SNe. , . γ. -ray bursts. Can use . Waiting Lines. Now Let’s Look at the Rest of the System; . The Little’s Law Applies Everywhere . Flow time . T = Ti. . + . Tp. Inventory I = . . Matthew Lave and Jan Kleissl. Solar 2011. Variability Reduction through Aggregation. Relative Output. Large ramps are detectable real-time by satellite and ground stations. Variability models primarily needed for large central power plants / . Week 7 – Variability and Noise:. The question of . . the neural code. Wulfram. Gerstner. EPFL, Lausanne, Switzerland. 7. .1. . Variability. of . spike. trains. - . experiments. 7. .2 Sources of . Kepler. . AutoRegressive. Planet Search. Eric . Feigelson & . Gabriel Caceres. Penn State Astronomy & Astrophysics. with . statisticians G. . . J. . Babu. , N. . Bahamonde. , . K. . . Bertin. a tale of 1965. Leonid Gurvits Ken . Kellermann. JIVE and TU Delft NRAO. The Netherlands USA. w. ith contributions . by Mikhail . Larionov. and . . Alexander Midler. Global offset and residual covariance. ENVR 468. Prahlad. . Jat. and Marc . Serre. Agenda. Why use a global offset?. How is the global offset calculated ?. Remove the global offset from data. Effect of global offset on covariance. Andrew Pendergast. Dynamical Systems modeling. Dynamical Systems: Mathematical object to describe behavior that changes over time. Modeling a functional relationship such that time is a primary variable wherein a value or vector function is produced . Kyung Koh. Background. Motor variability . A . commonly seen features in human movements. Bernstein “repetition without repetition”. In the past, motor variability is thought to be the result of error.. – . A . Scenario using CMMN. Nico Herzberg. , Kathrin Kirchner, and . Mathia. s Weske. September 8, 2014. ProHealth. 2012. Nico Herzberg. 2. Modeling and Monitoring Variability in Hospital Treatments - A Scenario using CMMN. Swift. -BAT blazars with . NICER. Sergio Mundo, Richard . Mushotzky. University of Maryland, College Park. MARLAM 9, JHU, Baltimore, MD. Blazar characteristics. Radio-loud AGN with jet aligned close to line of sight. Marc . Pollefeys. , . Daniel Barath. Spring 202. 2. http://www.cvg.ethz.ch/teaching/3dvision/. Feb . 2. 1. Introduction. Feb. . 28. Geometry, Camera Model, Calibration . Mar. . 7. Features, Tracking / Matching. an introduction. Pierre-Louis Toutain. Royal veterinary College London & project officer at the ENV of . Toulouse . Wuhan University October . 2017. To . explain the main concepts related to .