Clipping Algorithms; 8-5 (contd.) Computer Graphics. Spring CS4815

Size: px
Start display at page:

Download "Clipping Algorithms; 8-5 (contd.) Computer Graphics. Spring CS4815"

Transcription

1 Computer Graphics Spring

2 Outline Clipping Algorithms; 8-5 (contd.) 1 Clipping Algorithms; 8-5 (contd.)

3 Announcements Clipping Algorithms; 8-5 (contd.) Mid-term: Tues, 12.00, Week07 (???)

4 Liang-Barsky Line Clipper Liang-Barsky algorithm is a better approach by avoiding repeated shortening of segment s e; like C-S also works for 3-D clipping regions Idea is to return to parametric form of line (see prev. lecture) where x = x s + u x y = y s + u y, 0 u 1 x = x e x s, y = y e y s

5 Liang-Barsky Line Clipper Liang-Barsky algorithm is a better approach by avoiding repeated shortening of segment s e; like C-S also works for 3-D clipping regions Idea is to return to parametric form of line (see prev. lecture) where x = x s + u x y = y s + u y, 0 u 1 x = x e x s, y = y e y s

6 Liang-Barsky Line Clipper Applying window test x bl x s + u x x ur y bl y s + u y y ur We break this in to four inequalities of the form u k p k q k p 1 = x, p 2 = x, p 3 = y, p 4 = y, q 1 = x s x bl (left border) q 2 = x ur x s (right border) q 3 = y s y bl (bot border) q 4 = y ur y s (top border) We can now evaluate the four u k s with u k = q k /p k Liang-Barsky: it s all about finding the 4 u k s

7 Liang-Barsky Line Clipper We want to find the points where line segment crosses borders Extension of line segment will cross all four borders somewhere! We do this by working with the u k s

8 Liang-Barsky Line Clipper We want to find the points where line segment crosses borders Extension of line segment will cross all four borders somewhere! We do this by working with the u k s

9 Liang-Barsky Line Clipper We want to find the points where line segment crosses borders Extension of line segment will cross all four borders somewhere! We do this by working with the u k s

10 If line is parallel to window border then x = 0 or y = 0; so, two of p i s will be 0, also (either p 1, p 2 or p 3, p 4 ) For each p i that is 0, if q i < 0 then line is entirely outside that clipping boundary; o/w, q i 0 and line is inside Proceeding from u = to u = + the infinite extension of every non-parallel (to borders) line will cut 2 borders from outside to inside and 2 borders from inside to out If p k < 0, with respect to that border, the infinite extension of the line moves from outside to inside; p k > 0 means the line proceeds from inside to outside So two p i s will be positive and two negative The value of u k = q k /p k tells us critical information about the line

11 Instead of maintaining four u i s, we only maintain 2: t 1 for the outside to inside cases (p k < 0) t 2 for the inside to outside cases (p k > 0) t 1 is initialised to 0 (corresponds to s) and is taken to be the larger of the two cases where p k < 0 t 2 is initialised to 1 (corresponds to e) and is taken to be the smaller of the two cases where p k > 0 u i : out-in u j : in-out u 2 e e t 2 =1 u 4 t 1 u 3 s u 1

12 Instead of maintaining four u i s, we only maintain 2: t 1 for the outside to inside cases (p k < 0) t 2 for the inside to outside cases (p k > 0) t 1 is initialised to 0 (corresponds to s) and is taken to be the larger of the two cases where p k < 0 t 2 is initialised to 1 (corresponds to e) and is taken to be the smaller of the two cases where p k > 0 u i : out-in u j : in-out u 2 e e t 2 =1 u 4 t 1 u 3 s u 1

13 Instead of maintaining four u i s, we only maintain 2: t 1 for the outside to inside cases (p k < 0) t 2 for the inside to outside cases (p k > 0) t 1 is initialised to 0 (corresponds to s) and is taken to be the larger of the two cases where p k < 0 t 2 is initialised to 1 (corresponds to e) and is taken to be the smaller of the two cases where p k > 0 u i : out-in u j : in-out u 2 e e t 2 =1 u 4 t 1 u 3 s u 1

14 Instead of maintaining four u i s, we only maintain 2: t 1 for the outside to inside cases (p k < 0) t 2 for the inside to outside cases (p k > 0) t 1 is initialised to 0 (corresponds to s) and is taken to be the larger of the two cases where p k < 0 t 2 is initialised to 1 (corresponds to e) and is taken to be the smaller of the two cases where p k > 0 u i : out-in u j : in-out u 2 e e t 2 =1 u 4 t 1 u 3 s u 1

15 Instead of maintaining four u i s, we only maintain 2: t 1 for the outside to inside cases (p k < 0) t 2 for the inside to outside cases (p k > 0) t 1 is initialised to 0 (corresponds to s) and is taken to be the larger of the two cases where p k < 0 t 2 is initialised to 1 (corresponds to e) and is taken to be the smaller of the two cases where p k > 0 u i : out-in u j : in-out u 2 e e t 2 =1 u 4 t 1 u 3 s u 1

16 u 1 s t 2 =1 e u 2 t 1 >1 u 4 u i : out-in u j : in-out if t 1 > t 2 line is completely outside the clipping region and it can be discarded Over Cohen-Sutherland, Liang-Barsky has been found to run 36% faster for 2-D lines and 40% faster for 3-D lines Note: alg doesn t depend on any ordering of start and end points of line See tutorial here

17 u 1 s t 2 =1 e u 2 t 1 >1 u 4 u i : out-in u j : in-out if t 1 > t 2 line is completely outside the clipping region and it can be discarded Over Cohen-Sutherland, Liang-Barsky has been found to run 36% faster for 2-D lines and 40% faster for 3-D lines Note: alg doesn t depend on any ordering of start and end points of line See tutorial here

18 u 1 s t 2 =1 e u 2 t 1 >1 u 4 u i : out-in u j : in-out if t 1 > t 2 line is completely outside the clipping region and it can be discarded Over Cohen-Sutherland, Liang-Barsky has been found to run 36% faster for 2-D lines and 40% faster for 3-D lines Note: alg doesn t depend on any ordering of start and end points of line See tutorial here

19 u 1 s t 2 =1 e u 2 t 1 >1 u 4 u i : out-in u j : in-out if t 1 > t 2 line is completely outside the clipping region and it can be discarded Over Cohen-Sutherland, Liang-Barsky has been found to run 36% faster for 2-D lines and 40% faster for 3-D lines Note: alg doesn t depend on any ordering of start and end points of line See tutorial here

Data Structures and Algorithms

Data Structures and Algorithms Data Structures and Algorithms Spring 2017-2018 Outline Announcements 1 Announcements 2 3 Recap Mergesort Of Note Labs start in Week02 in CS305b Do you have linux account? Lab times: Fri. 15.00, 16.00

More information

CSC 470 Introduction to Computer Graphics. Mathematical Foundations Part 2

CSC 470 Introduction to Computer Graphics. Mathematical Foundations Part 2 CSC 47 Introduction to Computer Graphics Mathematical Foundations Part 2 Vector Magnitude and Unit Vectors The magnitude (length, size) of n-vector w is written w 2 2 2 w = w + w2 + + w n Example: the

More information

Hypothesis Testing and Confidence Intervals (Part 2): Cohen s d, Logic of Testing, and Confidence Intervals

Hypothesis Testing and Confidence Intervals (Part 2): Cohen s d, Logic of Testing, and Confidence Intervals Hypothesis Testing and Confidence Intervals (Part 2): Cohen s d, Logic of Testing, and Confidence Intervals Lecture 9 Justin Kern April 9, 2018 Measuring Effect Size: Cohen s d Simply finding whether a

More information

AP Calculus AB Syllabus

AP Calculus AB Syllabus Introduction AP Calculus AB Syllabus Our study of calculus, the mathematics of motion and change, is divided into two major branches differential and integral calculus. Differential calculus allows us

More information

Preliminary check: are the terms that we are adding up go to zero or not? If not, proceed! If the terms a n are going to zero, pick another test.

Preliminary check: are the terms that we are adding up go to zero or not? If not, proceed! If the terms a n are going to zero, pick another test. Throughout these templates, let series. be a series. We hope to determine the convergence of this Divergence Test: If lim is not zero or does not exist, then the series diverges. Preliminary check: are

More information

Welcome to MAT 137! Course website:

Welcome to MAT 137! Course website: Welcome to MAT 137! Course website: http://uoft.me/ Read the course outline Office hours to be posted here Online forum: Piazza Precalculus review: http://uoft.me/precalc If you haven t gotten an email

More information

The Integral Test. P. Sam Johnson. September 29, P. Sam Johnson (NIT Karnataka) The Integral Test September 29, / 39

The Integral Test. P. Sam Johnson. September 29, P. Sam Johnson (NIT Karnataka) The Integral Test September 29, / 39 The Integral Test P. Sam Johnson September 29, 207 P. Sam Johnson (NIT Karnataka) The Integral Test September 29, 207 / 39 Overview Given a series a n, we have two questions:. Does the series converge?

More information

Analysis of Functions

Analysis of Functions Lecture for Week 11 (Secs. 5.1 3) Analysis of Functions (We used to call this topic curve sketching, before students could sketch curves by typing formulas into their calculators. It is still important

More information

Lecture 27. DATA 8 Spring Sample Averages. Slides created by John DeNero and Ani Adhikari

Lecture 27. DATA 8 Spring Sample Averages. Slides created by John DeNero and Ani Adhikari DATA 8 Spring 2018 Lecture 27 Sample Averages Slides created by John DeNero (denero@berkeley.edu) and Ani Adhikari (adhikari@berkeley.edu) Announcements Questions for This Week How can we quantify natural

More information

MA 1128: Lecture 08 03/02/2018. Linear Equations from Graphs And Linear Inequalities

MA 1128: Lecture 08 03/02/2018. Linear Equations from Graphs And Linear Inequalities MA 1128: Lecture 08 03/02/2018 Linear Equations from Graphs And Linear Inequalities Linear Equations from Graphs Given a line, we would like to be able to come up with an equation for it. I ll go over

More information

Optimisation and Operations Research

Optimisation and Operations Research Optimisation and Operations Research Lecture 22: Linear Programming Revisited Matthew Roughan http://www.maths.adelaide.edu.au/matthew.roughan/ Lecture_notes/OORII/ School

More information

Example. 171S Introduction to Graphing. January 06, Introduction to Graphing. Cartesian Coordinate System

Example. 171S Introduction to Graphing. January 06, Introduction to Graphing. Cartesian Coordinate System MAT 171 Dr. Claude Moore, CFCC CHAPTER 1: Graphs, Functions, and Models 1.1 Introduction to Graphing 1.2 Functions and Graphs 1.3 Linear Functions, Slope, and Applications 1.4 Equations of Lines and Modeling

More information

User Equilibrium CE 392C. September 1, User Equilibrium

User Equilibrium CE 392C. September 1, User Equilibrium CE 392C September 1, 2016 REVIEW 1 Network definitions 2 How to calculate path travel times from path flows? 3 Principle of user equilibrium 4 Pigou-Knight Downs paradox 5 Smith paradox Review OUTLINE

More information

The Simplex Method of Linear Programming

The Simplex Method of Linear Programming The Simplex Method of Linear Programming Online Tutorial 3 Tutorial Outline CONVERTING THE CONSTRAINTS TO EQUATIONS SETTING UP THE FIRST SIMPLEX TABLEAU SIMPLEX SOLUTION PROCEDURES SUMMARY OF SIMPLEX STEPS

More information

Name Date College Prep Mid-Term Review

Name Date College Prep Mid-Term Review Name Date Chapter 4 College Prep Mid-Term Review Define the following terms, and provide an example: Domain: Range: Slope Intercept form: Point Slope Form: Standard Form of a linear equation: Function:

More information

Response Surface Methods

Response Surface Methods Response Surface Methods 3.12.2014 Goals of Today s Lecture See how a sequence of experiments can be performed to optimize a response variable. Understand the difference between first-order and second-order

More information

171S1.1 Graphs, Functions, Models August 23, 2012

171S1.1 Graphs, Functions, Models August 23, 2012 MAT 171 D10 8:00 9:15 MAT 171 D11 9:30 10:45 Aug 21 7:11 AM Aug 21 7:14 AM MAT 171 D14 2:00 3:15 MAT 171 D15 3:30 4:45 Aug 21 7:14 AM Aug 21 7:14 AM 1 MAT 171 Dr. Claude Moore, CFCC CHAPTER 1: Graphs,

More information

Physics 1110: Mechanics

Physics 1110: Mechanics Physics 1110: Mechanics Announcements: Tutorials Thursday and Friday in G2B60, G2B75, & G2B77 Students on wait list should attend lectures and tutorials. CAPA assignments are in bins in G2B hallway. No

More information

G.4 Linear Inequalities in Two Variables Including Systems of Inequalities

G.4 Linear Inequalities in Two Variables Including Systems of Inequalities G.4 Linear Inequalities in Two Variables Including Systems of Inequalities Linear Inequalities in Two Variables In many real-life situations, we are interested in a range of values satisfying certain conditions

More information

{ } Notation, Functions, Domain & Range

{ } Notation, Functions, Domain & Range Lesson 02, page 1 of 9 Déjà Vu, It's Algebra 2! Lesson 02 Notation, Functions, Domain & Range Since Algebra grew out of arithmetic, which is operations on number sets, it is important early on to understand

More information

Intermediate Math Circles Winter 2018 Even More Fun With Inequalities

Intermediate Math Circles Winter 2018 Even More Fun With Inequalities Intermediate Math Circles Winter 2018 Even More Fun With Inequalities Michael Miniou The Centre for Education in Mathematics and Computing Faculty of Mathematics University of Waterloo April 4, 2018 Michael

More information

Pre-Calculus with Limits

Pre-Calculus with Limits Pre-Calculus with Limits John Gomm jgomm@sanroque.net Pre-Calculus mathematics extends algebra and geometry into advanced trigonometry, matrix math, series, alternative graphing coordinate systems, limits,

More information

15-388/688 - Practical Data Science: Basic probability. J. Zico Kolter Carnegie Mellon University Spring 2018

15-388/688 - Practical Data Science: Basic probability. J. Zico Kolter Carnegie Mellon University Spring 2018 15-388/688 - Practical Data Science: Basic probability J. Zico Kolter Carnegie Mellon University Spring 2018 1 Announcements Logistics of next few lectures Final project released, proposals/groups due

More information

Solutions to Problem Sheet for Week 6

Solutions to Problem Sheet for Week 6 THE UNIVERSITY OF SYDNEY SCHOOL OF MATHEMATICS AND STATISTICS Solutions to Problem Sheet for Week 6 MATH90: Differential Calculus (Advanced) Semester, 07 Web Page: sydney.edu.au/science/maths/u/ug/jm/math90/

More information

Brief Review of Exam Topics

Brief Review of Exam Topics Math 32A Discussion Session Week 3 Notes October 17 and 19, 2017 We ll use this week s discussion session to prepare for the first midterm. We ll start with a quick rundown of the relevant topics, and

More information

Graphical Solutions of Linear Systems

Graphical Solutions of Linear Systems Graphical Solutions of Linear Systems Consistent System (At least one solution) Inconsistent System (No Solution) Independent (One solution) Dependent (Infinite many solutions) Parallel Lines Equations

More information

Lecture 2.1 :! Electric Field

Lecture 2.1 :! Electric Field Lecture 2.1 :! Electric Field Lecture Outline:! Electric Field! Electric Field of Point Charges! Electric Field of Continuous Distribution of Charge! Textbook Reading:! Ch. 26.1-26.3 Jan. 20, 2015 1 Announcements

More information

A. Incorrect! Replacing is not a method for solving systems of equations.

A. Incorrect! Replacing is not a method for solving systems of equations. ACT Math and Science - Problem Drill 20: Systems of Equations No. 1 of 10 1. What methods were presented to solve systems of equations? (A) Graphing, replacing, and substitution. (B) Solving, replacing,

More information

Sufficient Conditions for Finite-variable Constrained Minimization

Sufficient Conditions for Finite-variable Constrained Minimization Lecture 4 It is a small de tour but it is important to understand this before we move to calculus of variations. Sufficient Conditions for Finite-variable Constrained Minimization ME 256, Indian Institute

More information

Algebra II Notes Quadratic Functions Unit Complex Numbers. Math Background

Algebra II Notes Quadratic Functions Unit Complex Numbers. Math Background Complex Numbers Math Background Previously, you Studied the real number system and its sets of numbers Applied the commutative, associative and distributive properties to real numbers Used the order of

More information

Linear Programming II NOT EXAMINED

Linear Programming II NOT EXAMINED Chapter 9 Linear Programming II NOT EXAMINED 9.1 Graphical solutions for two variable problems In last week s lecture we discussed how to formulate a linear programming problem; this week, we consider

More information

Designing Information Devices and Systems I Spring 2018 Lecture Notes Note 3

Designing Information Devices and Systems I Spring 2018 Lecture Notes Note 3 EECS 16A Designing Information Devices and Systems I Spring 2018 Lecture Notes Note 3 3.1 Linear Dependence Recall the simple tomography example from Note 1, in which we tried to determine the composition

More information

Applied Mathematics B Study Guide

Applied Mathematics B Study Guide Science, Engineering and Technology Portfolio School of Life and Physical Sciences Foundation Studies (Applied Science/Engineering) Applied Mathematics B Study Guide Topics Kinematics Dynamics Work, Energy

More information

The Awesome Averaging Power of Heat. Heat in Geometry

The Awesome Averaging Power of Heat. Heat in Geometry The Awesome Averaging Power of Heat in Geometry exemplified by the curve shortening flow PUMS lecture 17 October 2012 1 The Heat Equation 2 The Curve Shortening Flow 3 Proof of Grayson s Theorem 4 Postscript

More information

Mon Jan Matrix and linear transformations. Announcements: Warm-up Exercise:

Mon Jan Matrix and linear transformations. Announcements: Warm-up Exercise: Math 2270-004 Week 4 notes We will not necessarily finish the material from a given day's notes on that day. We may also add or subtract some material as the week progresses, but these notes represent

More information

Announcements. The Schrodinger Equation for Interacting Particles. Lecture 16 Chapter. 5 Bound States: Simple Case

Announcements. The Schrodinger Equation for Interacting Particles. Lecture 16 Chapter. 5 Bound States: Simple Case Announcements! HW5: 4-36, 41, 48, 53, 63, 66! Mid-term Exam: 10/16 Ch 1,2,3,4,5(part) *** Course Web Page ** http://highenergy.phys.ttu.edu/~slee/2402/ Lecture Notes, HW Assignments, Schedule for thephysics

More information

[ ] ( ) L = L = r p. We can deal with this more conveniently by writing: so that L becomes: α α α. α α N N N N

[ ] ( ) L = L = r p. We can deal with this more conveniently by writing: so that L becomes: α α α. α α N N N N Lecture 5: Angular Momentum and Energy of a System The total angular momentum is given by the sum of the angular momenta of all particles in the system: We can deal with this more conveniently by writing:

More information

CS 188: Artificial Intelligence Spring Announcements

CS 188: Artificial Intelligence Spring Announcements CS 188: Artificial Intelligence Spring 2010 Lecture 22: Nearest Neighbors, Kernels 4/18/2011 Pieter Abbeel UC Berkeley Slides adapted from Dan Klein Announcements On-going: contest (optional and FUN!)

More information

Worksheet 9. Topics: Taylor series; using Taylor polynomials for approximate computations. Polar coordinates.

Worksheet 9. Topics: Taylor series; using Taylor polynomials for approximate computations. Polar coordinates. ATH 57H Spring 0 Worksheet 9 Topics: Taylor series; using Taylor polynomials for approximate computations. Polar coordinates.. Let f(x) = +x. Find f (00) (0) - the 00th derivative of f at point x = 0.

More information

Farkas Lemma, Dual Simplex and Sensitivity Analysis

Farkas Lemma, Dual Simplex and Sensitivity Analysis Summer 2011 Optimization I Lecture 10 Farkas Lemma, Dual Simplex and Sensitivity Analysis 1 Farkas Lemma Theorem 1. Let A R m n, b R m. Then exactly one of the following two alternatives is true: (i) x

More information

Lecture 8: Ch Sept 2018

Lecture 8: Ch Sept 2018 University of Alabama Department of Physics and Astronomy PH 301 / LeClair Fall 2018 Lecture 8: Ch. 4.5-7 12 Sept 2018 1 Time-dependent potential energy Sometimes we need to consider time-dependent forces,

More information

Finite Math - J-term Section Systems of Linear Equations in Two Variables Example 1. Solve the system

Finite Math - J-term Section Systems of Linear Equations in Two Variables Example 1. Solve the system Finite Math - J-term 07 Lecture Notes - //07 Homework Section 4. - 9, 0, 5, 6, 9, 0,, 4, 6, 0, 50, 5, 54, 55, 56, 6, 65 Section 4. - Systems of Linear Equations in Two Variables Example. Solve the system

More information

Solving and Graphing a Linear Inequality of a Single Variable

Solving and Graphing a Linear Inequality of a Single Variable Chapter 3 Graphing Fundamentals Section 3.1 Solving and Graphing a Linear Inequality of a Single Variable TERMINOLOGY 3.1 Previously Used: Isolate a Variable Simplifying Expressions Prerequisite Terms:

More information

Solutions to Problem Sheet for Week 11

Solutions to Problem Sheet for Week 11 THE UNIVERSITY OF SYDNEY SCHOOL OF MATHEMATICS AND STATISTICS Solutions to Problem Sheet for Week MATH9: Differential Calculus (Advanced) Semester, 7 Web Page: sydney.edu.au/science/maths/u/ug/jm/math9/

More information

3.6 Interpreting Functions

3.6 Interpreting Functions 27 FEATURES OF FUNCTIONS Interpreting Functions A Practice Understanding Task CCBY Jan Kalab https://flic.kr/p/ekgaa Given the graph of f(x), answer the following questions. Unless otherwise specified,

More information

In case (1) 1 = 0. Then using and from the previous lecture,

In case (1) 1 = 0. Then using and from the previous lecture, Math 316, Intro to Analysis The order of the real numbers. The field axioms are not enough to give R, as an extra credit problem will show. Definition 1. An ordered field F is a field together with a nonempty

More information

4.3 Rational Inequalities and Applications

4.3 Rational Inequalities and Applications 342 Rational Functions 4.3 Rational Inequalities and Applications In this section, we solve equations and inequalities involving rational functions and eplore associated application problems. Our first

More information

Astronomy 104: Stellar Astronomy

Astronomy 104: Stellar Astronomy Astronomy 104: Stellar Astronomy Lecture 5: Observing is the key... Brahe and Kepler Spring Semester 2013 Dr. Matt Craig 1 For next time: Read Slater and Freedman 3-5 and 3-6 if you haven't already. Focus

More information

SUMMER PACKET. Accelerated Algebra Name Date. Teacher Semester

SUMMER PACKET. Accelerated Algebra Name Date. Teacher Semester Name Date Teacher Semester SUMMER PACKET Accelerated Algebra 017-018 Teacher Mrs. Robison Mrs. Miller Email krobison@gettysburg.k1.pa.us emiller@gettysburg.k1.pa.us 1 Welcome to Accelerated Algebra! I.

More information

Unit 6. Systems of Linear Equations. 3 weeks

Unit 6. Systems of Linear Equations. 3 weeks Unit 6 Systems of Linear Equations 3 weeks Unit Content Investigation 1: Solving Systems of Linear Equations (3 days) Investigation 2: Solving Systems of Linear Equations by Substitution (4 days) Investigation

More information

Linear Methods (Math 211) - Lecture 2

Linear Methods (Math 211) - Lecture 2 Linear Methods (Math 211) - Lecture 2 David Roe September 11, 2013 Recall Last time: Linear Systems Matrices Geometric Perspective Parametric Form Today 1 Row Echelon Form 2 Rank 3 Gaussian Elimination

More information

Week #4: Midterm 1 Review

Week #4: Midterm 1 Review Week #4: Midterm Review April 5, NAMES: TARDIS : http://math.ucsb.edu/ kgracekennedy/spring 4A.html Week : Introduction to Systems of Linear Equations Problem.. What row operations are allowed and why?...

More information

Discrete Mathematics for CS Spring 2007 Luca Trevisan Lecture 20

Discrete Mathematics for CS Spring 2007 Luca Trevisan Lecture 20 CS 70 Discrete Mathematics for CS Spring 2007 Luca Trevisan Lecture 20 Today we shall discuss a measure of how close a random variable tends to be to its expectation. But first we need to see how to compute

More information

We saw in the previous lectures that continuity and differentiability help to understand some aspects of a

We saw in the previous lectures that continuity and differentiability help to understand some aspects of a Module 3 : Differentiation and Mean Value Theorems Lecture 9 : Roll's theorem and Mean Value Theorem Objectives In this section you will learn the following : Roll's theorem Mean Value Theorem Applications

More information

Announcements. CS 188: Artificial Intelligence Spring Classification. Today. Classification overview. Case-Based Reasoning

Announcements. CS 188: Artificial Intelligence Spring Classification. Today. Classification overview. Case-Based Reasoning CS 188: Artificial Intelligence Spring 21 Lecture 22: Nearest Neighbors, Kernels 4/18/211 Pieter Abbeel UC Berkeley Slides adapted from Dan Klein Announcements On-going: contest (optional and FUN!) Remaining

More information

Lecture 3.1 :! Electric Flux

Lecture 3.1 :! Electric Flux Lecture 3.1 :! Electric Flux Lecture Outline:! Motion in a Uniform Electric Field! Symmetry and Electric Fields! Electric Flux! Gauss s Law!! Textbook Reading:! Ch. 26.6-27.3 Jan. 27, 2015 1 Announcements

More information

Roberto s Notes on Differential Calculus Chapter 1: Limits and continuity Section 7. Discontinuities. is the tool to use,

Roberto s Notes on Differential Calculus Chapter 1: Limits and continuity Section 7. Discontinuities. is the tool to use, Roberto s Notes on Differential Calculus Chapter 1: Limits and continuity Section 7 Discontinuities What you need to know already: The concept and definition of continuity. What you can learn here: The

More information

Chapter 7. Kinetic Energy and Work

Chapter 7. Kinetic Energy and Work Chapter 7 Kinetic Energy and Work 7.3 Kinetic Energy Kinetic energy K is energy associated with the state of motion of an object. The faster the object moves, the greater is its kinetic energy. For an

More information

Evaluating Corridors. Jeff Jenness Dan Majka Paul Beier. CorridorDesigner Workshop Fall 2007

Evaluating Corridors. Jeff Jenness Dan Majka Paul Beier. CorridorDesigner Workshop Fall 2007 Evaluating Corridors Jeff Jenness Dan Majka Paul Beier CorridorDesigner Workshop Fall 2007 1 1 Evaluating Corridors Test Alternative Corridors Least cost methods always provide a best solution, even when

More information

CLEP Precalculus - Problem Drill 15: Systems of Equations and Inequalities

CLEP Precalculus - Problem Drill 15: Systems of Equations and Inequalities CLEP Precalculus - Problem Drill 15: Systems of Equations and Inequalities No. 1 of 10 1. What are the methods to solve a system of equations? (A) Graphing, replacing, substitution and matrix techniques.

More information

Queueing Systems: Lecture 3. Amedeo R. Odoni October 18, Announcements

Queueing Systems: Lecture 3. Amedeo R. Odoni October 18, Announcements Queueing Systems: Lecture 3 Amedeo R. Odoni October 18, 006 Announcements PS #3 due tomorrow by 3 PM Office hours Odoni: Wed, 10/18, :30-4:30; next week: Tue, 10/4 Quiz #1: October 5, open book, in class;

More information

Definition: A "system" of equations is a set or collection of equations that you deal with all together at once.

Definition: A system of equations is a set or collection of equations that you deal with all together at once. System of Equations Definition: A "system" of equations is a set or collection of equations that you deal with all together at once. There is both an x and y value that needs to be solved for Systems

More information

p(t)dt a p(τ)dτ , c R.

p(t)dt a p(τ)dτ , c R. 11 3. Solutions of first order linear ODEs 3.1. Homogeneous and inhomogeneous; superposition. A first order linear equation is homogeneous if the right hand side is zero: (1) ẋ + p(t)x = 0. Homogeneous

More information

CSC236 Week 4. Larry Zhang

CSC236 Week 4. Larry Zhang CSC236 Week 4 Larry Zhang 1 Announcements PS2 due on Friday This week s tutorial: Exercises with big-oh PS1 feedback People generally did well Writing style need to be improved. This time the TAs are lenient,

More information

Intermediate Algebra

Intermediate Algebra Intermediate Algebra COURSE OUTLINE FOR MATH 0312 (REVISED JULY 29, 2015) Catalog Description: Topics include factoring techniques, radicals, algebraic fractions, absolute values, complex numbers, graphing

More information

Curvaceous Circles BUT IT DOES WORK! Yep we can still relate the formula for the area of a circle to the formula for the area of a rectangle

Curvaceous Circles BUT IT DOES WORK! Yep we can still relate the formula for the area of a circle to the formula for the area of a rectangle Curvaceous Circles So our running theme on our worksheets has been that all the formulas for calculating the area of various shapes comes back to relating that shape to a rectangle. But how can that possibly

More information

CSC236 Week 11. Larry Zhang

CSC236 Week 11. Larry Zhang CSC236 Week 11 Larry Zhang 1 Announcements Next week s lecture: Final exam review This week s tutorial: Exercises with DFAs PS9 will be out later this week s. 2 Recap Last week we learned about Deterministic

More information

Discrete Mathematics. Spring 2017

Discrete Mathematics. Spring 2017 Discrete Mathematics Spring 2017 Previous Lecture Principle of Mathematical Induction Mathematical Induction: rule of inference Mathematical Induction: Conjecturing and Proving Climbing an Infinite Ladder

More information

Assignment 1b: due Tues Nov 3rd at 11:59pm

Assignment 1b: due Tues Nov 3rd at 11:59pm n Today s Lecture: n n Vectorized computation Introduction to graphics n Announcements:. n Assignment 1b: due Tues Nov 3rd at 11:59pm 1 Monte Carlo Approximation of π Throw N darts L L/2 Sq. area = N =

More information

Physics 280 Quantum Mechanics Lecture III

Physics 280 Quantum Mechanics Lecture III Summer 2016 1 1 Department of Physics Drexel University August 17, 2016 Announcements Homework: practice final online by Friday morning Announcements Homework: practice final online by Friday morning Two

More information

Chapter 7. Kinetic energy and work. Energy is a scalar quantity associated with the state (or condition) of one or more objects.

Chapter 7. Kinetic energy and work. Energy is a scalar quantity associated with the state (or condition) of one or more objects. Chapter 7 Kinetic energy and work 7.2 What is energy? One definition: Energy is a scalar quantity associated with the state (or condition) of one or more objects. Some characteristics: 1.Energy can be

More information

Physics 121. Quiz lecture 14. Linear momentum (a quick review). Linear momentum (a quick review). Systems with variable mass. ( ) = M d!

Physics 121. Quiz lecture 14. Linear momentum (a quick review). Linear momentum (a quick review). Systems with variable mass. ( ) = M d! Physics 121. Thursday, March 6, 2008. Physics 121. Thursday, March 6, 2008. Course Information Quiz Topics to be discussed today: Conservation of linear momentum and one-dimensional collisions (a brief

More information

Section 2.4: The Precise Definition of a Limit

Section 2.4: The Precise Definition of a Limit Section 2.4: The Precise Definition of a Limit In the previous sections, we examined the idea of a it. However, the definitions we gave were me intuitive as opposed to precise. In mathematics, in der to

More information

27 : Distributed Monte Carlo Markov Chain. 1 Recap of MCMC and Naive Parallel Gibbs Sampling

27 : Distributed Monte Carlo Markov Chain. 1 Recap of MCMC and Naive Parallel Gibbs Sampling 10-708: Probabilistic Graphical Models 10-708, Spring 2014 27 : Distributed Monte Carlo Markov Chain Lecturer: Eric P. Xing Scribes: Pengtao Xie, Khoa Luu In this scribe, we are going to review the Parallel

More information

4 Elementary matrices, continued

4 Elementary matrices, continued 4 Elementary matrices, continued We have identified 3 types of row operations and their corresponding elementary matrices. If you check the previous examples, you ll find that these matrices are constructed

More information

mith College Computer Science CSC270 Spring 16 Circuits and Systems Lecture Notes Week 3 Dominique Thiébaut

mith College Computer Science CSC270 Spring 16 Circuits and Systems Lecture Notes Week 3 Dominique Thiébaut mith College Computer Science CSC270 Spring 16 Circuits and Systems Lecture Notes Week 3 Dominique Thiébaut dthiebaut@smith.edu Crash Course in Electricity and Electronics Zero Physics background expected!

More information

Chapter 22: Gauss s Law

Chapter 22: Gauss s Law Chapter 22: Gauss s Law How you can determine the amount of charge within a closed surface by examining the electric field on the surface. What is meant by electric flux, and how to calculate it. How Gauss

More information

LECTURE 19: SEPARATION OF VARIABLES, HEAT CONDUCTION IN A ROD

LECTURE 19: SEPARATION OF VARIABLES, HEAT CONDUCTION IN A ROD ECTURE 19: SEPARATION OF VARIABES, HEAT CONDUCTION IN A ROD The idea of separation of variables is simple: in order to solve a partial differential equation in u(x, t), we ask, is it possible to find a

More information

Physics 121. Thursday, March 6, Department of Physics and Astronomy, University of Rochester

Physics 121. Thursday, March 6, Department of Physics and Astronomy, University of Rochester Physics 121. Thursday, March 6, 2008. Physics 121. Thursday, March 6, 2008. Course Information Quiz Topics to be discussed today: Conservation of linear momentum and one-dimensional collisions (a brief

More information

Mat104 Fall 2002, Improper Integrals From Old Exams

Mat104 Fall 2002, Improper Integrals From Old Exams Mat4 Fall 22, Improper Integrals From Old Eams For the following integrals, state whether they are convergent or divergent, and give your reasons. () (2) (3) (4) (5) converges. Break it up as 3 + 2 3 +

More information

Simon Fraser University School of Engineering Science ENSC Linear Systems Spring Instructor Jim Cavers ASB

Simon Fraser University School of Engineering Science ENSC Linear Systems Spring Instructor Jim Cavers ASB Simon Fraser University School of Engineering Science ENSC 380-3 Linear Systems Spring 2000 This course covers the modeling and analysis of continuous and discrete signals and systems using linear techniques.

More information

Math Lab 10: Differential Equations and Direction Fields Complete before class Wed. Feb. 28; Due noon Thu. Mar. 1 in class

Math Lab 10: Differential Equations and Direction Fields Complete before class Wed. Feb. 28; Due noon Thu. Mar. 1 in class Matter & Motion Winter 2017 18 Name: Math Lab 10: Differential Equations and Direction Fields Complete before class Wed. Feb. 28; Due noon Thu. Mar. 1 in class Goals: 1. Gain exposure to terminology and

More information

Lecture: Testing Stationarity: Structural Change Problem

Lecture: Testing Stationarity: Structural Change Problem Lecture: Testing Stationarity: Structural Change Problem Applied Econometrics Jozef Barunik IES, FSV, UK Summer Semester 2009/2010 Lecture: Testing Stationarity: Structural Change Summer ProblemSemester

More information

Ca Foscari University of Venice - Department of Management - A.A Luciano Battaia. December 14, 2017

Ca Foscari University of Venice - Department of Management - A.A Luciano Battaia. December 14, 2017 Ca Foscari University of Venice - Department of Management - A.A.27-28 Mathematics Luciano Battaia December 4, 27 Brief summary for second partial - Sample Exercises Two variables functions Here and in

More information

MICROECONOMIC THEORY I PROBLEM SET 1

MICROECONOMIC THEORY I PROBLEM SET 1 MICROECONOMIC THEORY I PROBLEM SET 1 MARCIN PĘSKI Properties of rational preferences. MWG 1.B1 and 1.B.2. Solutions: Tutorial Utility and preferences. MWG 1.B.4. Solutions: Tutorial Choice structure. MWG

More information

Remember next exam is 1 week from Friday. This week will be last quiz before exam.

Remember next exam is 1 week from Friday. This week will be last quiz before exam. Lecture Chapter 3 Extent of reaction and equilibrium Remember next exam is week from Friday. his week will be last quiz before exam. Outline: Extent of reaction Reaction equilibrium rxn G at non-standard

More information

Water Resources Systems: Modeling Techniques and Analysis

Water Resources Systems: Modeling Techniques and Analysis INDIAN INSTITUTE OF SCIENCE Water Resources Systems: Modeling Techniques and Analysis Lecture - 9 Course Instructor : Prof. P. P. MUJUMDAR Department of Civil Engg., IISc. Summary of the previous lecture

More information

Alg 1 Systems. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

Alg 1 Systems. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question. Class: Date: Alg 1 Systems Multiple Choice Identify the choice that best completes the statement or answers the question. What is the solution of the system? Use a graph. 1. y = x + 2 y = 3x 1 a. c. b.

More information

Lecture #19 MINEQL: Intro & Tutorial Benjamin; Chapter 6

Lecture #19 MINEQL: Intro & Tutorial Benjamin; Chapter 6 Updated: 6 October 2013 Print version Lecture #19 MINEQL: Intro & Tutorial Benjamin; Chapter 6 David Reckhow CEE 680 #19 1 MINEQL today MINEQL is available from Environmental Research Software: http://www.mineql.com/

More information

2.004 Dynamics and Control II Spring 2008

2.004 Dynamics and Control II Spring 2008 MT OpenCourseWare http://ocw.mit.edu.004 Dynamics and Control Spring 008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Massachusetts nstitute of Technology

More information

Math 111: Final Review

Math 111: Final Review Math 111: Final Review Suggested Directions: Start by reviewing the new material with the first portion of the review sheet. Then take every quiz again as if it were a test. No book. No notes. Limit yourself

More information

4 Elementary matrices, continued

4 Elementary matrices, continued 4 Elementary matrices, continued We have identified 3 types of row operations and their corresponding elementary matrices. To repeat the recipe: These matrices are constructed by performing the given row

More information

Queens College, CUNY, Department of Computer Science Numerical Methods CSCI 361 / 761 Spring 2018 Instructor: Dr. Sateesh Mane.

Queens College, CUNY, Department of Computer Science Numerical Methods CSCI 361 / 761 Spring 2018 Instructor: Dr. Sateesh Mane. Queens College, CUNY, Department of Computer Science Numerical Methods CSCI 361 / 761 Spring 2018 Instructor: Dr. Sateesh Mane c Sateesh R. Mane 2018 3 Lecture 3 3.1 General remarks March 4, 2018 This

More information

Lecture 3: Analysis of Variance II

Lecture 3: Analysis of Variance II Lecture 3: Analysis of Variance II http://www.stats.ox.ac.uk/ winkel/phs.html Dr Matthias Winkel 1 Outline I. A second introduction to two-way ANOVA II. Repeated measures design III. Independent versus

More information

Randomized Algorithms

Randomized Algorithms Randomized Algorithms Prof. Tapio Elomaa tapio.elomaa@tut.fi Course Basics A new 4 credit unit course Part of Theoretical Computer Science courses at the Department of Mathematics There will be 4 hours

More information

MAT01A1. Numbers, Inequalities and Absolute Values. (Appendix A)

MAT01A1. Numbers, Inequalities and Absolute Values. (Appendix A) MAT01A1 Numbers, Inequalities and Absolute Values (Appendix A) Dr Craig 8 February 2017 Leftovers from yesterday: lim n i=1 3 = lim n n 3 = lim n n n 3 i ) 2 ] + 1 n[( n ( n i 2 n n + 2 i=1 i=1 3 = lim

More information

Key Intuition: invertibility

Key Intuition: invertibility Introduction to Fourier Analysis CS 510 Lecture #6 January 30, 2017 In the extreme, a square wave Graphic from http://www.mechatronics.colostate.edu/figures/4-4.jpg 2 Fourier Transform Formally, the Fourier

More information

Definition: Absolute Value The absolute value of a number is the distance that the number is from zero. The absolute value of x is written x.

Definition: Absolute Value The absolute value of a number is the distance that the number is from zero. The absolute value of x is written x. R. Absolute Values We begin this section by recalling the following definition. Definition: Absolute Value The absolute value of a number is the distance that the number is from zero. The absolute value

More information

Class Note #14. In this class, we studied an algorithm for integer multiplication, which. 2 ) to θ(n

Class Note #14. In this class, we studied an algorithm for integer multiplication, which. 2 ) to θ(n Class Note #14 Date: 03/01/2006 [Overall Information] In this class, we studied an algorithm for integer multiplication, which improved the running time from θ(n 2 ) to θ(n 1.59 ). We then used some of

More information