'Poisson process' diaporamas de présentation

Chapter 3

Chapter 3. Inferences About Process Quality. 3-1. Statistics and Sampling Distributions. Statistical methods are used to make decisions about a process Is the process out of control? Is the process average you were given the true value? What is the true process variability?.

1.6k views • 83 slides

Performance Engineering

1.12k views • 65 slides

Presentation of M.Sc. Thesis Work

Presentation of M.Sc. Thesis Work. Presented by: S. M. Farhad [040405056P] Department of Computer Science and Engineering, BUET Supervised by: Dr. Md. Mostofa Akbar Associate Professor Department of Computer Science and Engineering, BUET. Thesis Title.

774 views • 55 slides

Chapter 13

Chapter 13. Improving Predictions, Products Processes, and Resources Shari L. Pfleeger Joann M. Atlee 4 th Edition. Contents. 13.1 Improving Prediction 13.2 Improving Products 13.3 Improving Processes 13.4 Improving Resources 13.5 General Improvement Guidelines

715 views • 54 slides

Change of Time Method in Mathematical Finance

Change of Time Method in Mathematical Finance. Anatoliy Swishchuk Mathematical & Computational Finance Lab Department of Mathematics & Statistics University of Calgary, Calgary, Alberta, Canada CMS 2006 Summer Meeting Mathematical Finance Session Calgary, AB, Canada June 3-5, 2006.

593 views • 46 slides

625 views • 40 slides

Ph.D. Methods Seminar

Ph.D. Methods Seminar. Aaron K. Chatterji March 16th, 2009. Agenda. I. Patents 101 2. Analyzing Count Data (Poisson/NB) 3. Review Assigned Papers 4. Assignment for next week.

699 views • 39 slides

Stochastic Differential Equation Modeling and Analysis of TCP - Windowsize Behavior

Stochastic Differential Equation Modeling and Analysis of TCP - Windowsize Behavior . Presented by Sri Hari Krishna Narayanan (Some slides taken from or based on presentations by Vishal Mishra). Outline. Introduction TCP window Algorithms

537 views • 35 slides

Chapter 4 Single Stage Produce-to-Stock

Chapter 4 Single Stage Produce-to-Stock. Better customer service Lower manufacturing costs (setups) More uniform utilization. Target-Level Production Authorization (PA) Mechanism with Backlogs. I ( t ) B ( t ) = 0. B ( t ). Store I ( t ). C ( t ). I ( t ) = 0. m/c. I ( t ) > 0.

437 views • 33 slides

Queuing Theory and Traffic Analysis

Queuing Theory and Traffic Analysis. Based on Slides by Richard Martin. Queuing theory . View network as collections of queues FIFO data-structures Queuing theory provides probabilistic analysis of these queues Examples: Average length Probability queue is at a certain length

1.4k views • 29 slides

Chapter 5 Flow Lines

Chapter 5 Flow Lines. Types Issues in Design and Operation Models of Asynchronous Lines Infinite or Finite Buffers Models of Synchronous (Indexing) Lines Closed-Loop Material Handling Focus on the impact of variability on design, operation, and performance. Types of Flow Lines.

449 views • 29 slides

GloVE: A Distributed Environment for Low Cost Scalable VoD Systems

SBAC-PAD 2002. GloVE: A Distributed Environment for Low Cost Scalable VoD Systems. Leonardo Bidese de Pinho Edison Ishikawa * Claudio Luis de Amorim COPPE Systems Engineering Program Federal University of Rio de Janeiro, RJ, Brazil * Systems Engineering Department

471 views • 25 slides

Scaling in the Geography of US Computer Science Rui Carvalho and Michael Batty University College London rui.carvalho@u

Scaling in the Geography of US Computer Science Rui Carvalho and Michael Batty University College London rui.carvalho@ucl.ac.uk m.batty@ucl.ac.uk http://www.casa.ucl.ac.uk/ Thanks: Michael Gastner (SFI), Isaac Councill (PSU), Chris Brunsdon (Leicester), Ben Gimpert (UCL). Motivation.

395 views • 23 slides

Extremes

379 views • 23 slides

AN INTRODUCTION TO RECOMBINATION AND LINKAGE ANALYSIS

634 views • 19 slides

Queuing Models

Queuing Models. M/M/k Systems. CLASSIFICATION OF QUEUING SYSTEMS. Recall that queues are classified by (Arrival Dist.)/(Service Dist.)/(# servers) Designations for Arrival/Service distributions include: M = Markovian (Poisson process) D = Deterministic (Constant) G = General

386 views • 19 slides

167 views • 16 slides

Determination of Upperbound Failure Rate by Graphic Confidence Interval Estimate

LAUR-01-1671. Determination of Upperbound Failure Rate by Graphic Confidence Interval Estimate. K. S. Kim (Kyo) Los Alamos National Laboratory Los Alamos, NM 87545 E-mail: kyokim@lanl.gov. Kim-1.

501 views • 14 slides

RED PERFORMANCE EVALUATION USING STOCHASTIC MODELLING AND FLUID-BASED ANALYSIS APPROACHES

RED PERFORMANCE EVALUATION USING STOCHASTIC MODELLING AND FLUID-BASED ANALYSIS APPROACHES. Hussein Al-Zubaidy Tariq Omari System and Computer Engineering Carleton University . {hussein, tomari} @sce.carleton.ca May 10, 2006 CCECE06. Random Early Detection (RED) Queue Management Scheme .

242 views • 14 slides

4th IMPRS Astronomy Summer School Drawing Astrophysical Inferences from Data Sets

4th IMPRS Astronomy Summer School Drawing Astrophysical Inferences from Data Sets. William H. Press The University of Texas at Austin Lecture 5. We want to go beyond simply maximizing and get the whole Bayesian posterior distribution of .

185 views • 10 slides