PPT-Random Motion

A note on usage The clicker slides in this booklet are meant to be used as stimuli to encourage class discussion They are intended for use in a class that attempts to help students develop a coherent and sophisticated understanding of scientific thinking. Nimantha . Thushan. Baranasuriya. Girisha. . Durrel. De Silva. Rahul . Singhal. Karthik. . Yadati. Ziling. . Zhou. Outline. Random Walks. Markov Chains. Applications. 2SAT. 3SAT. Card Shuffling. Ching. -Chun Hsiao. 1. Outline. Problem description. Why conditional random fields(CRF). Introduction to CRF. CRF model. Inference of CRF. Learning of CRF. Applications. References. 2. Reference. 3. Charles . Network Science: Random Graphs . 2012. Prof. Albert-László Barabási. Dr. Baruch Barzel, Dr. Mauro Martino. RANDOM NETWORK MODEL. Network Science: Random Graphs . 2012. Erdös-Rényi model (1960). Toby Walsh. NICTA and UNSW. Random . Tie Breaking. Haris. Aziz, Serge Gaspers, Nick . Mattei. , Nina . Narodytska. , Toby Walsh. NICTA and UNSW. Ties matter. Manipulators can only change result if election is close!. and Semi-Supervised Learning. Longin Jan Latecki. Based on :. Xiaojin. Zhu. Semi-Supervised Learning with Graphs. PhD thesis. CMU-LTI-05-192, May 2005. Page, Lawrence and . Brin. , Sergey and . Motwani. Andy Wang. CIS 5930-03. Computer Systems. Performance Analysis. Generate Random Values. Two steps. Random-number generation. Get a sequence of random numbers distributed uniformly between 0 and 1. Random-. Expected Value. Airline overbooking. Pooling . blood . samples. Variance and Standard . Deviation . Independent Collections. Optimization. DECS 430-A. Business Analytics . I: Class 2. Random Variables. Fernando . G.S.L. . Brand. ão. 1. . Aram Harrow. 2. Michal Horodecki. 3. Universidade. Federal de Minas . Gerais. , Brazil. University of Washington, USA. 3. . Gdansk University, Poland. IQC, November 2011. Giles Story. Philipp Schwartenbeck. Methods for . dummies 2012/13. With thanks to Guillaume . Flandin. . . Outline. Where are we up to?. Part 1. Hypothesis Testing. Multiple Comparisons . vs. Topological Inference. Haenggi. et al. EE 360 : 19. th. February 2014. . Contents. SNR, SINR and geometry. Poisson Point Processes. Analysing interference and outage. Random Graph models. Continuum percolation and network models. . Motion. Speed & Velocity. Acceleration. Newton’s First Law. Newton’s First Law of Motion. An object at rest will remain at rest and an object in motion will continue moving at a constant velocity unless acted upon by a net force.. the . process of moving . or . changing . places . or position. Anything you do while moving is motion.. Fact: Speed is a major type of Motion. Determining motion. In order to determine motion you must know direction and speed. class is part of the . java.util. package. It provides methods that generate pseudorandom numbers. A . Random. object performs complicated calculations based on a . seed value. to produce a stream of seemingly random values. Describing motion is occasionally difficult to do with words. Graphs can help simplify this description greatly. Position = Distance from a starting point. Velocity = rate of change in position. Acceleration = rate of change in velocity.