Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more.
Course Hero has millions of course specific materials providing students with the best way to expand
their education.
Below is a small sample set of documents:
Mich Tech - CS - 9402
%!PS-Adobe-2.0 %Creator: dvips 5.518 Copyright 1986, 1993 Radical Eye Software %Title: paper.dvi %CreationDate: Thu Mar 10 17:19:11 1994 %Pages: 14 %PageOrder: Ascend %BoundingBox: 0 0 612 792 %EndComments %DVIPSCommandLine: dvips paper.dvi %DVIPSSou
Mich Tech - CS - 9701
3 1 r W) yx5 r !7 I6Rr)I Ga yGWRWi a! yrq )& s y R 8 erRW f !#fW y GIri f WYrR iIr Ga Iq t rW4!2) # ! R4 0 tRraiG rG!WaTR!yraRf6!W6RiyWqIYirfWi5Gr1YW!EriaGI Rrii)(GiWvWri! fraWqti1r!iRyG 6!4)
Mich Tech - CS - 9509
y v y | w v y y { v { x} y | w w } u v | w | { v y w { { } } | v y } ~z0zTF0l03~&eF1Y0FpTFlTRTS"FcpzemT03FF1#~tz0lY v y | x v | { | | ww y y v 01FzcQz"0~l~R17Tj!z| ~ ~ YY30FYT0QFF73~T~l w v |
Mich Tech - CS - 9702
GEOMETRIC COMPUTING IN THE UNDERGRADUATE COMPUTER SCIENCE CURRICULAJohn L. Lowther and Ching-Kuang Shene Department of Computer Science Michigan Technological University Houghton, MI 49931-1295 (john|shene)@mtu.edu AbstractGeometric computing is a
Duke - CPS - 270
CPS 270: Artificial Intelligencehttp:/www.cs.duke.edu/courses/fall08/cps270/Game TheoryInstructor: Vincent Conitzer2/3 of the average game Everyone writes down a number between 0 and 100 Person closest to 2/3 of the average wins Example:
Duke - CPS - 300
8/27/2008Course formatSee website (http:/www.cs.duke.edu/courses/fall08/cps300/) for details Class meetings: every other Wednesday Talks in the department: check dept. event calendar CPS 300: Introduction to Graduate Study I t d ti t G d t St d Ju
Duke - CPS - 270
CPS 270: Artificial Intelligencehttp:/www.cs.duke.edu/courses/fall08/cps270/IntroductionInstructor: Vincent ConitzerBasic information about course TuTh 11:40-12:55, LSRC D243 Text: Artificial Intelligence: A Modern Approach Instructor: Vinc
Duke - CPS - 270
CPS 270: Articial IntelligenceHomework 1: Search (due September 30 before class)Please read the rules for assignments on the course web page. Contact Lirong (lxia@cs.duke.edu) or Vince (conitzer@cs.duke.edu) with any questions. In this assignment,
Duke - CPS - 270
CPS 270: Artificial Intelligencehttp:/www.cs.duke.edu/courses/fall08/cps270/Wrapping upInstructor: Vincent ConitzerWhat are the boundaries of AI?engineering probability & algorithms & statistics complexity economics AI logic psychology & phil
Duke - CPS - 196
Intro to CUDA Programminghttp:/www.oit.duke.edu/scsc scsc@duke.edu hpc-support@duke.eduJohn Pormann, Ph.D. jbp1@duke.eduOverviewIntro to the Operational Model Simple Example x Memory Allocation and Transfer x GPU-Function Launch Grids of Blocks
Duke - CPS - 001
Today's topicsJava Writing Functions/Methods Upcoming Information Retrieval Reading Great Ideas, Chapter 4CPS 00111.1Writing Functions/MethodsFunction is Synonym of Method Funcion is more generic term Method is used in Java Syntax of a functi
Duke - CPS - 001
Todays topicsJava Information Retrieval Upcoming Intellectual Property (Prof Forbes) Reading Great Ideas, Chapter 4Information RetrievalOften want to use program for information storage and retrieval On line phone book is good example Using Paral
Duke - CPS - 100
Towers of HanoiMove disks from from peg to to peg G What is the recurrence relation in terms of numDisks?Gvoid Move(int from, int to, int aux, int numDisks) / pre: numDisks on peg from, / post: numDisks moved to peg to { if (numDisks = 1) { cout
Duke - CPS - 182
The Promise and Perils of a Ubiquitous Wireless InternetSteven Esposito Geoffrey Jacoby October 29, 2003 Peter Whitesteven.esposito@duke.edu geoffrey.jacoby@duke.edu peter.white@duke.edu1Wireless Internet service shows great promise in all
Los Angeles Southwest College - CSCE - 146
1Homework Assignment 6In Lab Assignment 10 you read packet data that arrived in unsorted order for a single message and reassembled packets into correct order. In this assignment, you are to assume that you are receiving packet data for an unspeci
Duke - CPS - 100
What is Computer Science?What is it that distinguishes it from the separate subjects with which it is related? What is the linking thread which gathers these disparate branches into a single discipline? My answer to these questions is simple - it is
Duke - CPS - 100
Why back of the envelope estimates?Often need to make rapid estimates to eliminate candidate solutions establish feasibility sketch out potential trade-offs Most remember key numbers related to their field, not every detail Hence we need to estimate
University of Alabama in Huntsville - MSC - 287
KEY: Computer Quiz 01 MSC 287 Summer 2001Dr. Stafford Quiz AAnswer B C C C C O E D D T Item 1 2 3 4 5 6 7 8 9 10 Explanation A GROYNE is a structure to prevent beach erosion. Answer = B . New Brighton: partly cloudy, hi 65oF, lo 51oF Answer = C . T
University of Alabama in Huntsville - MSC - 287
KEY: Unit Quiz 01MSC 287, Dr. Stafford, Summer 2001Version AQuestion 1 Answer Description O Which scale is most appropriate for measuring the variable: size of bed {twin, regular, queen, king}? ORDINAL scale since bed sizes are larger than previou
Duke - CPS - 196
Semantic WebObstacles 1Usefulness What can syllogisims do for us? Or not do?http:/www.shirky.com/writings/semantic_syllogism.htmlAbility to define logic in a way machines can understandGetting from here to there or not.Flexibility vs. Eff
Duke - CPS - 196
Relational Database Design Part IICPS 196.3 Introduction to Database SystemsAnnouncementReminder of the new schedule: 12:50pm-2:05pm Mondays and Wednesdays Homework #1 will be assigned on Wednesday2Two relational algebra problems have been po
Duke - CPS - 108
Saving and restoring objectsClasses should implement Serializable, this is a tag interface, not necessary to implement a function (see Cloneable) mark non-serializable fields as transient platform specific objects like font sizes, these need to be
Duke - CPS - 140
CPS 140 - Mathematical Foundations of CS Dr. Susan Rodger Section: Properties of Regular Languages (Ch. 4) (handout)Example L = {an ban | n > 0}Closure Properties A set is closed over an operation if L1 , L2 class L1 op L2 = L3 L3 classExamp
Duke - CPS - 108
Java on one slideAll objects allocated on heap, via new, garbage collected Primitive types like int, double, boolean exempt Everything else subclasses ObjectAll variables (non-primitive) are pointers aka references Can we compare pointers for eq
Duke - CPS - 216
Announcements (February 17)Reading assignment for this week2Query ProcessingCPS 216 Advanced Database SystemsVariant indexes (due Wednesday)Homework #1 is being gradedSample solution available outside my officeHomework #2 due February 26
Duke - CPS - 216
A motivating exampleParent (parent, child) Ape Abe Homer Bart Marge Lisa2SQL: Recursionparent Homer Homer Marge Marge Abe Apechild Bart Lisa Bart Lisa Homer AbeExample: find Barts ancestors Ancestor has a recursive definitionX is Ys ances
Duke - CPS - 216
Query Processing: A Systems ViewCPS 216 Advanced Database SystemsAnnouncements (February 24)Reading assignment for this week due Wednesday Homework #2 due this Thursday Midterm and course project proposal in two weeks Recitation session tomorrow
Los Angeles Southwest College - CSCE - 146
1Lab Quiz 2Preparatory InstructionsThe second lab quiz will build primarily on Lab 9 and Lab 10, using the Java Collections Framework. You are free to use your own previous code from your assignments, your notes, and the code available from my sam
Los Angeles Southwest College - CSCE - 146
1Lab Quiz 2Section 2You are to extend some of the work done in Labs 9 and 10. Imagine yourself the Imperial Censor for the Empire of Kukorica. The Emporer wants to ensure that all internet traffic is filtered to remove offending content. You are g
Los Angeles Southwest College - CSCE - 146
1Lab Assignment 10You are to read a simplied version of internet packet data and reassemble the packets into sorted order so that the underlying message can be read. An individual packet will consist of a single line of input data containing a mes
Duke - CPS - 004
What are methods good for?Package a unit of code A well-defined unit of work is named and packaged If well named, aids in higher level design where method name becomes a proxy for the work. Often sections of code are repeated or almost repeated
Duke - CPS - 001
Welcome!Principles of Computer Science CompSci 1 LSRC B101 M, W, F 1:30-2:20 Professor Jeff ForbesTodays topics! ! ! ! !What is this course about? How are we going to learn that? Who is this guy talking to us? Where do we go from here? An overv
Duke - CPS - 140
b 1 c 1 a a b 1ta
Duke - CPS - 237
Date midterm.TreapsReview: Dictionaries for ordered sets Binary tree. Tree balancing by rotations drawbacks in geometry: rebuild on rotation Returning to average case: Assign random arrival orders to keys Build tree as if arrived in that ord
Duke - CPS - 237
Maximal independent settrivial sequential algorithm inherently sequential from node point of view: each thinks can join MIS if others stay out randomization breaks this symmetry Randomized idea each node joins with some probability all neighbor
Duke - CPS - 237
Linear programming. dene assumptions: nonempty, bounded polyhedron minimizing x1 unique minimum, at a vertex exactly d constraints per vertex denitions: hyperplanes H basis B(H) of hyperplanes that dene optimum optimum value O(H) Simplex
Duke - CPS - 237
PollingOutline Set has size u, contains n "special" elements goal: count number of special elements sample with probability p = c(log n)/ 2 n with high probability, (1 )np special elements if observe k elements, deduce n (1 )k. Problem: wha
University of Alabama in Huntsville - CS - 513
CS513 Intro to Computer Architecture Lecture #3 Boolean Algebra Basic Boolean Operators (AND, OR, NOT) S=A+B S=AB S = A S= A Represents A or B Represents A and B Represents the complement of ASpring 2004OR Operation A 0 0 1 1 B 0 1 0 1 A+B 0 1
UMass (Amherst) - Z - 428
Lab 1: Class Data 2007Age Preferences Ad Type yo iy s io oo Male Seeking Female 77 28 41 4 25 Female Seeking Male 15 27 101 32 0 Dependent Variables Ad Type 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Male Seeking Female 860 575 587 167 15 3 0 4 290 38 39 3
UMass (Amherst) - Z - 338
UMass (Amherst) - Z - 736
Problems in Biological Statistics 22.736Winter 2006Workshop 1: Introduction to RChapters 1 & 2 in Quinn and Keough 2002The following workshop is designed to introduce the R statistical language, demonstrate data entry, manipulation, and simple
UMass (Amherst) - Z - 736
Problems in Biological Statistics 22.736Winter 2006Workshop 2: Hypothesis Testing(Quinn and Keough Chapter 3)Hypothesis testing is not only perspective for using statistics in biology, but it is one that is commonly employed. In biology, our h
UMass (Amherst) - Z - 736
Problems in Biological Statistics 22.736Winter 2006Workshop 3: Graphics, Comparisons, and Relationships(Quinn and Keough Ch. 4, Ch. 5 section 5.0 to 5.1, Ch. 14 section 14.0 to 14.2.1)It is always advisable to examine a data set using graphica
UMass (Amherst) - Z - 736
Problems in Biological Statistics 22.736Winter 2006Workshop 4: General Linear Models I - Simple Regression(Quinn and Keough Ch. 5 section 5.2 to end)Whenever we perform an analysis or fit data we are working with statistical models. A basic un
UMass (Amherst) - Z - 736
Problems in Biological Statistics 22.736Winter 2006Workshop 5: General Linear Models II Multiple Regression, Interactions, and Dummy Variables(Quinn and Keough Ch. 6, to the end of section 6.1)The general linear model is essentially a formal d
UMass (Amherst) - Z - 736
Problems in Biological Statistics 22.736Winter 2006Workshop 6: General Linear Models III One-way ANOVA and the R Console(Quinn and Keough Ch. 8)Up until now, we have performed most of our analyses through the R Commander. If you have been foll
University of Alabama in Huntsville - MSP - 430
COMPUTER ENGINEERING DESIGN II TutorialMSP430F149 RS232Prepared by Zexin Pan February 2005This tutorial describes how to utilize MSP430F149 UART to send/receive data to/from a PC. The template has been tested on MSP430-easyWeb2 prototyping board
Duke - CPS - 196
1! 2 3 4 ! "0 1 ( %# )' &$ npU t dUb ef 'd yh eUef qbeUyoh dUih eb d efy' @eon b@Uh y bUhh yme@Ubbt h h5 d h ue ' 7 7 'd 7 ' ' 57d ' ' E 7 d ' 'f '5 j dUb ef yo bU'h bd' bm7h@ h'Uqb7
UMass (Amherst) - Z - 481
YEAR 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986LANDINGS EFFORT (t) (h) 1616 4391 1690 2735 2927 3157 5228 3050 9119 5500 9519 6671 5112 4755 5165 14074 2959 1207
Duke - CPS - 196
t x t w y xqi w p mwxi mwxvyrmyuu r(s mwrxvyxmy pxy ) x 2yvi Vrmu2y xvmRt xy y w x y q q x x w x 64 C(E y xRrRRt i(vy mwR wmR w yt w s t x x w xR2t cy ixxmim2 q p mwxiR! y iwx s w q w x qit x x s w x i s u q yR 2ryq q2mq yH5 ( B
Duke - CPS - 196
4/19/2007&RRUGLQDWHV <RXU &DPHUD DV D 0DWUL[/LQHDU 7UDQVIRUPDWLRQV X ' Y' = Z' X A Y Z 6FDOLQJ X ' m 0 0 X Y ' = 0 m 0 Y Z ' 0 0 m Z 98D884I 7aHI5 VG@A@ED` 2 YHE5 75IEX GAH5FEH FED 6W 987A7ED 8@ VAU 2 TSR
UMass (Amherst) - Z - 481
Data from a B.C. Herring SeineLength of Herring in Seine (to nearest 1/2 cm) Size (cm) Frequency 15 50 15.5 25 16 531 16.5 62 17 318 17.5 230 18 401 18.5 293 19 925 19.5 941 20 292 20.5 421 21 245 21.5 182 22 158 22.5 6 23 21Aged Sample of Haul 1
Duke - CPS - 196
1 y i i2 RU c 2 cyRS T c i y c y B c y yt S s Egh I `Q(g t2Pd q s G h { z s g ii sH st(vtt{v 0t iq v h v q j ( s t q h g qu t(h 7UF(qhvqE |{ (t|q{g i(hq St(i{v i idD ( $ ! 3 BA ! 9 & 2 6 & # $ 3
Duke - CPS - 250
CPS-250, Spring 2007Homework-5Part I : Spatial Discretization. 1. Make change in the provided matlab code so that the sample points on the boundary are randomized 2. [Optional] Provide a function so that the sample density of certain area can be
Duke - CPS - 100
Binary TreesFrom doubly-linked lists to binary treesLinked lists: efficient insertion/deletion, inefficient search ArrayList: search can be efficient, insertion/deletion not Binary trees: efficient insertion, deletion, and search trees used i
Duke - CPS - 100
Big Oh Again AgainRecognizing Common Recurrences Have taken the attitude that mostly you can look things up Now need to be able to do your own derivations Extend our menu of solutions to common recurrences Lets look at previously shown tableB
Duke - CPS - 100
Sets SetsSet is an unordered list of itemsBasic Operations: Items are unique! Only one copy of each item in set!We will use two different implementations of sets TreeSet A TreeSet backed up by a tree structure (future topic) Kee
Duke - CPS - 100
Java String ClassString is a classDo not need new to create String String msg = "hello"; Can join strings (concatenate) with +String mail = "John says " + msg;Most common String methods:int length(); / get number of chars in it String sub
Duke - CPS - 100
Java String ClassString MethodsString is a classDo not need new to create String String msg = hello;More on useful String methodsExamples.What are the values? Can join strings (concatenate) with +String mail = John says + msg;