80 Pages

p1

Course: ACM 05, Fall 2009
School: Carnegie Mellon
Rating:
 
 
 
 
 

Word Count: 1331

Document Preview

East 2004 Central Regional Contest 5 Problem D: I Conduit! Irv Kenneth Diggit works for a company that excavates trenches, digs holes and generally tears up people's yards. Irv's job is to make sure that no underground pipe or cable is underneath where excavation is planned. He has several different maps, one for each utility company, showing where their conduits lie, and he needs to draw one large,...

Register Now

Unformatted Document Excerpt

Coursehero >> Pennsylvania >> Carnegie Mellon >> ACM 05

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.

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.
East 2004 Central Regional Contest 5 Problem D: I Conduit! Irv Kenneth Diggit works for a company that excavates trenches, digs holes and generally tears up people's yards. Irv's job is to make sure that no underground pipe or cable is underneath where excavation is planned. He has several different maps, one for each utility company, showing where their conduits lie, and he needs to draw one large, consolidated map combining them all. One approach would be to simply draw each of the smaller maps one at a time onto the large map. However, this often wastes time, not to mention ink for the pen-plotter in the office, since in many cases portions of the conduits overlap with each other (albeit at different depths underground). What Irv wants is a way to determine the minimum number of line segments to draw given all the line segments from the separate maps. Input Input will consist of multiple input sets. Each set will start with a single line containing a positive integer n indicating the total number of line segments from all the smaller maps. Each of the next n lines will contain a description of one segment in the format x1 y1 x2 y2 where (x1 , y1 ) are the coordinates of one endpoint and (x2 , y2 ) are the coordinates of the other. Coordinate values are floating point values in the range 0 . . . 1000 specified to at most two decimal places. The maximum number of line segments will be 10000 and all segments will have non-zero length. Following the last input set there will be a line containing a 0 indicating end of input; it should not be processed. Output For each input set, output on a single line the minimum number of line segments that need to be drawn on the larger, consolidated map. Sample Input 3 1.0 10.0 3.0 14.0 0.0 0.0 20.0 20.0 10.0 28.0 2.0 12.0 2 0.0 0.0 1.0 1.0 1.0 1.0 2.15 2.15 2 0.0 0.0 1.0 1.0 1.0 1.0 2.15 2.16 0 Sample Output 2 1 2 2004 East Central Regional Contest 6 Problem E: Roll Playing Games Phil Kropotnik is a game maker, and one common problem he runs into is determining the set of dice to use in a game. In many current games, non-traditional dice are often required, that is, dice with more or fewer sides than the traditional 6-sided cube. Typically, Phil will pick random values for all but the last die, then try to determine specific values to put on the last die so that certain sums can be rolled with certain probabilities (actually, instead of dealing with probabilities, Phil just deals with the total number of different ways a given sum can be obtained by rolling all the dice). Currently he makes this determination by hand, but needless to say he would love to see this process automated. That is your task. For example, suppose Phil starts with a 4-sided die with face values 1, 10, 15, and 20 and he wishes to determine how to label a 5-sided die so that there are a) 3 ways to obtain a sum of 2, b) 1 way to obtain a sum of 3, c) 3 ways to obtain 11, d) 4 ways to obtain 16, and e)1 way to obtain 26. To get these results he should label the faces of his 5-sided die with the values 1, 1, 1, 2, and 6. (For instance, the sum 16 may be obtained as 10 + 6 or as 15 + 1, with three different "1" faces to choose from on the second die, for a total of 4 different ways.) Input Input will consist of multiple input sets. Each input set will start with a single line containing an integer n indicating the number of dice that are already specified. Each of the next n lines describes one of these dice. Each of these lines will start with an integer f (indicating the number of faces on the die) followed by f integers indicating the value of each face. The last line of each problem instance will have the form r m v1 c1 v2 c2 v3 c3 vm cm where r is the number of faces required on the unspecified die, m is the number of sums of interest, v1 , . . . , vm are these sums, and c1 , . . . , cm are the counts of the desired number of different ways in which to achieve each of the respective sums. Input values will satisfy the following constraints: 1 20, n 3 f 20, 1 m 10, and 4 r 6. Values on the faces of all dice, both the specified ones and the unknown die, will be integers in the range 1 . . . 50, and values for the vi 's and ci 's are all non-negative and are strictly less than the maximum value of a 32-bit signed integer. The last input set is followed by a line containing a single 0; it should not be processed. Output For each input set, output a single line containing either the phrase "Final die face values are" followed by the r face values in non-descending order, or the phrase "Impossible" if no die can be found meeting the specifications of the problem. If there are multiple dice which will solve the problem, choose the one whose lowest face value is the smallest; if there is still a tie, choose the one whose second-lowest face value is smallest, etc. 2004 East Central Regional Contest 7 Sample Input 1 4 5 1 6 6 4 6 4 3 8 4 0 1 10 15 20 5 2 3 3 1 11 3 16 4 26 1 1 2 3 4 5 6 3 7 6 2 1 13 1 1 1 3 1 4 2 3 4 5 6 2 2 3 7 9 4 5 9 23 24 30 38 48 57 51 37 56 31 63 11 Sample Output Final die face values are 1 1 1 2 6 Impossible Final die face values are 3 7 9 9 2004 East Central Regional Contest 10 Problem H: Translations Bob Roberts is in charge of performing translations of documents between various languages. To aid him in this endeavor his bosses have provided him with translation files. These files come in twos -- one containing sample phrases in one of the languages and the other containing their translations into the other language. However, some over-zealous underling, attempting to curry favor with the higher-ups with his initiative, decided to alphabetically sort the contents of all of the files, losing the connections between the phrases and their translations. Fortunately, the lists are comprehensive enough that the original translations can be reconstructed from these sorted lists. Bob has found this is most usually the case when the phrases all consist of two words. For example, given the following two lists: Language 1 Phrases arlo zym flub pleve pleve dourm pleve zym Language 2 Phrases bus seat bus stop hot seat school bus Bob is able to determine that arlo means hot, zym means seat, flub means school, pleve means bus, and dourm means stop. After doing several of these reconstructions by hand, Bob has decided to automate the process. And if Bob can do it, then so can you. Input I...

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:

Carnegie Mellon - ACM - 08
ASU Annual Programming Competition 2006 Problem SetDirections Please read these directions carefully! The following pages contain the problem set for the 2006 Arizona State University programming competition. There are ten (10) problems. You have fo
Carnegie Mellon - ACM - 02
The "Simple" Probleminput file: simple.in output file: simple.outIntroductionA (planar) polygon can be described by the closed sequence of vertices around the polygon. The vertices themselves are described by their x- and y-coordinates. Algorithm
Carnegie Mellon - ACM - 06
Problem F: Leaping LizardsOverview Your platoon of wandering lizards has entered a strange room in the labyrinth you are exploring. As you are looking around for hidden treasures, one of the rookies steps on an innocent-looking stone and the room's
Carnegie Mellon - ACM - 06
Problem B: Hilbert Curve IntersectionsPage 1 of 2Problem B: Hilbert Curve IntersectionsSource file: hilbert.{c, cpp, java, pas} Input file: hilbert.in Output file: hilbert.out Transformation 1 Transformation 2 Transformation 3Starting curveT
Carnegie Mellon - ACM - 06
Bright BraceletPage 1 of 2Problem C: Bright BraceletSource file: bracelet.{c, cpp, java, pas} Input file: bracelet.in Output file: bracelet.outBracelet 1Bracelet 2 Bracelets can be made from a collection of octagonal pieces, with two opposit
Carnegie Mellon - DRAFT - 2
Ajay Surie Naju Mancheril 15-398 Attributes How do we categorize nanotechnology? Once we determine that something can be classified as nanotechnology, the following attributes can help determine it sits in the design space. Size: For something to be
Carnegie Mellon - DRAFT - 3
Ajay Surie Naju G. Mancheril18-398: Introduction to NanotechnologyNovember 13, 2004 GoldsteinAttributes of NanotechnologySCU: A significant, controllable unit of any system, material or device. A process can be called nanotechnology if and onl
Carnegie Mellon - DRAFT - 2
Matt Osius and Shiva Nanotechnology Final Draft SCU The smallest complete, controllable and significant unit which contributes to the functionality of the process at the nanoscale. Listed from most important to least important Size Scale The average
Carnegie Mellon - DRAFT - 1
Nanotechnology Design SpaceWilliam Knop, Dmitry Saltykov November 1st, 20041DefinitionsAssembly Method The degree, on a scale from 0 to 1, to which the assembly is top-down, as opposed to bottom-up. [0.1] Assembly Precision The degree, on a sc
Carnegie Mellon - DRAFT - 1
Ajay Surie 15-398 Design Space What is nanotechnology? How "nanotechy" is it? What are the hazards of a particular nanotechnological process?Assembly Method: The most important attribute has to do with how the tool / device is assembled. When one
Carnegie Mellon - DRAFT - 3
Nanotechnology Design AxesWilliam Knop, Dmitry Saltykov November 14th, 20041General DefinitionsProcess : Description: A method manipulating materials to result in a product. Explanation: A process qualifies as nanotechnology if and only if its
Carnegie Mellon - DRAFT - 3
Nanotechnology Design SpaceMatt Osius, Shiva Ramaswamy November 10th, 20041DefinitionsSCU The smallest complete, controllable and significant unit which contributes to the functionality of the process at the nanoscale. Size Scale The average s
Carnegie Mellon - DRAFT - 2
Nanotechnology Design SpaceWilliam Knop, Dmitry Saltykov November 3rd, 200411.1AttributesNumerical AttributesAssembly Method : Description: The degree, on a scale from 0 to 1, to which the assembly is top-down, as opposed to bottom-up. Scale
Carnegie Mellon - PUB - 2
Real-time 3-D Pose Estimation Using a High-Speed Range SensorDavid A. Simon, Martial Hebert and Takeo Kanade The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213-3891AbstractThis paper describes a system which can perform full 3-
Carnegie Mellon - PUB - 2
Carnegie Mellon - PUB - 4
Toward Generating Labeled Maps from Color and Range Data for Robot NavigationCaroline Pantofaru, Ranjith Unnikrishnan, Martial Hebert The Robotics Institute Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA 15213, USA {crp,ranjith,hebert}@
Carnegie Mellon - PUB - 1
EFFECT OF CUP ORIENTATION AND NECK LENGTH IN RANGE OF MOTION SIMULATION, Jaramaz B.1,2, Nikou C.2, DiGioia A.M.1,2, 1Center for Orthopaedic Research, Shadyside Hospital, and 2Center for MRCAS, Robotics Institute, Carnegie Mellon Univesity, Pittsburgh
Carnegie Mellon - PUB - 4
Carnegie Mellon - PUB - 3
SPIE Proceedings on Iiitelligent Trunsportution Systems, I99High-performance laser range scannerJohn Hancock", Eric Hoffman', Ryan Sullivan b, Darin Ingirnarson', Dirk Langer", Martial Hebert""The Robotics Institute, Carnegie Mellon Univ., Pitts
Carnegie Mellon - PUB - 4
Real-Time Computational Needs of a Multisensor Feature-Based Range-Estimation MethodRaymond E. Suorsa, Banavar Sridhar and Terrence W. Fong NASA Ames Research Center Mo ett Field, CA 94035 suorsa@windchime.arc.nasa.govAbstractThe computer vision
Carnegie Mellon - PUB - 4
2D localization of outdoor mobile robots using 3D laser range dataTakeshi Takahashi CMU-RI-TR-07-11May 2007Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania 15213c Carnegie Mellon UniversitySubmitted in partial fulfillme
Carnegie Mellon - PUB - 2
Carnegie Mellon - PUB - 3
Preliminary Results in RangeOnly Localization and MappingGeorge Kantor Sanjiv SinghThe Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15217, e-mail {kantor,ssingh}@ri.cmu.eduAbstractThis paper presents methods of localization usin
Carnegie Mellon - PUB - 1
Proc. CVPR'98, Santa Barbara, CA, June 23-25, pp. 496-501, 19981Qualitative and Quantitative Car Tracking from a Range Image SequenceLiang Zhao and Chuck Thorpe Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213 E-mail: flzhao,
Carnegie Mellon - PUB - 4
Preliminary Results in Tracking Mobile Targets Using Range Sensors from Multiple RobotsElizabeth Liao, Geoffrey Hollinger, Joseph Djugash, and Sanjiv SinghCarnegie Mellon University {eliao@andrew.cmu.edu, gholling@andrew.cmu.edu, robojoe@cmu.edu, s
Wisconsin - FC - 2002
Farmer Cooperatives ConferenceNovember 1315, 2002"Role of Education & Research for the Future of Cooperatives"Dennis Bolling United Producers, Inc. Two Perspectives NCFC Education Committee Cooperative ManagementNCFC Mission Statement To
Wisconsin - FARMERCOOP - 04
Welcome!Cooperative Innovation7th Annual Farmer Cooperatives ConferenceConference Objectives Provide timely and relevant informationon agricultural co-op issues. Presentationsthat are valuable to participants and encourage critical thinking
Carnegie Mellon - FONG - 2
Strong Reciprocity and the Welfare State Christina M. Fong, Samuel Bowles and Herbert Gintis July 3, 2004A man ought to be a friend to his friend and repay gift with gift. People should meet smiles with smiles and lies with treachery.The Edda, a 1
Carnegie Mellon - JAMESS - 3
Tribology International 38 (2005) 528532 www.elsevier.com/locate/tribointMeasurement of disjoining pressure of Z-type peruoropolyether lubricants on Si and SiNx surfacesPaul M. Jonesa,*, Min Luob, Lee R. Whiteb, James Schneiderb, Mei-Ling Wua, Chr
Carnegie Mellon - STRESSGROU - 13
StressAnalysisDesignProjectSpring2007 Group13MalloryStewart JustinMoidel NedFoxIntroductionRationalization Results OpportunitiesforImprovementRationalization Largerhole Buildtrussstructuretotopofhole 6by6base Liftingmechani
Carnegie Mellon - STRESSGROU - 13
Stress Analysis Design ProjectSpring 2007 Group 13Mallory Stewart Justin Moidel Ned Fox IntroductionRationalization Results Opportunities for Improvement RationalizationAdd Counterweight Location of Lever Arm in Relation to
Carnegie Mellon - AT - 33
X-Andrew-WideReply: netnews.alt.drwho.creativeX-Andrew-Authenticated-as: 0;andrew.cmu.edu;Network-MailReceived: via nntpserv with nntp; Thu, 15 Aug 1996 04:31:01 -0400 (EDT)Message-ID: <080343Z15081996@anon.penet.fi>Path: andrew.cmu.edu!bb3.andre
Carnegie Mellon - AT - 33
X-Andrew-WideReply: netnews.alt.drwho.creativeX-Andrew-Authenticated-as: 0;andrew.cmu.edu;Network-MailReceived: via nntpserv with nntp; Wed, 14 Aug 1996 16:18:32 -0400 (EDT)Path: andrew.cmu.edu!bb3.andrew.cmu.edu!newsfeed.pitt.edu!newsflash.concor
Carnegie Mellon - AT - 33
<body bgcolor = "#FFFFFF">THE CATALYST By Jenifer Jennings Hancock It was 11:30 in the evening and a large blue Chevy was illegallyparked on the side of the road. There were four policemen in the car,all very unimpressed at being where t
Carnegie Mellon - AT - 33
X-Andrew-WideReply: netnews.alt.drwho.creativeX-Andrew-Authenticated-as: 0;andrew.cmu.edu;Network-MailReceived: via nntpserv with nntp; Wed, 7 Aug 1996 20:59:50 -0400 (EDT)Path: andrew.cmu.edu!bb3.andrew.cmu.edu!nntp.sei.cmu.edu!news.psc.edu!scra
Carnegie Mellon - AT - 33
X-Andrew-WideReply: netnews.alt.drwho.creativeX-Andrew-Authenticated-as: 0;andrew.cmu.edu;Network-MailReceived: via nntpserv with nntp; Wed, 14 Aug 1996 21:59:19 -0400 (EDT)Path: andrew.cmu.edu!bb3.andrew.cmu.edu!nntp.sei.cmu.edu!news.cis.ohio-sta
Carnegie Mellon - AT - 33
X-Andrew-WideReply: netnews.alt.drwho.creativeX-Andrew-Authenticated-as: 0;andrew.cmu.edu;Network-MailReceived: via nntpserv with nntp; Tue, 16 Jul 1996 08:17:25 -0400 (EDT)Path: andrew.cmu.edu!bb3.andrew.cmu.edu!newsfeed.pitt.edu!godot.cc.duq.edu
Carnegie Mellon - AT - 33
X-Andrew-WideReply: netnews.alt.drwho.creativeX-Andrew-Authenticated-as: 0;andrew.cmu.edu;Network-MailReceived: via nntpserv with nntp; Wed, 14 Aug 1996 21:59:20 -0400 (EDT)Path: andrew.cmu.edu!bb3.andrew.cmu.edu!nntp.sei.cmu.edu!news.cis.ohio-sta
Wisconsin - ECON - 102
Economics 102 Ms. Elizabeth Kelly Midterm #1 October 8, 1996 Version 3Name _ ID Number _ Section Number _ TA Name _ DO NOT BEGIN WORKING UNTIL THE INSTRUCTOR TELLS YOU TO DO SO. READ THESE INSTRUCTIONS FIRSTYou have 75 minutes to complete the exa
Wisconsin - BOTANY - 400
*Convolvulaceae- morning gloryDiversity and Evolution of Asterids. . . morning glories, mints, and snapdragons . . .Largely tropical family of 57 genera and 1600 spp. Twining herbs or woody with alternate leaves.Calystegia sepium Hedge bindweed
Wisconsin - BOTANY - 400
CaryophyllidsDiversity and Evolution of Caryophyllids. . . carnations, cacti, chenopods . . .What are caryophyllids? caryophyllids? First of the core eudicots we will examine = order Caryophyllales (sometimes Polygonales is also recognized)co
Wisconsin - BOTANY - 401
Pinophyta - GymnospermsPinophyta - GymnospermsSeed bearing plants without flowers and pistils - "naked seeds" 4 major groups recognized; sometimes as separate phyla 3 families of conifers only in Great Lakes region with 8 genera and 13 species Cup
Wisconsin - PHYS - 107
New HW assignment Chapter 4 Calculate acceleration from falling body on web page Conceptual Exercises 2, 30, 36, 40 Problems 4, 6, 16Sep. 15, 2004Phy 107, Lecture 5From Last Time. Principle of inertia: object continues in its state of
Wisconsin - PHYS - 107
Physics 107: Ideas of Modern PhysicsExam 2 March 8, 2006Name_ ID #_ Section #_On the Scantron sheet, 1) Fill in your name 2) Fill in your student ID # (not your social security #) 3) Fill in your section # (under ABC of special codes)Useful co
Wisconsin - PHYS - 107
Physics 107: Ideas of Modern PhysicsExam 2 March 8, 2006Name_ ID #_ Section #_On the Scantron sheet, 1) Fill in your name 2) Fill in your student ID # (not your social security #) 3) Fill in your section # (under ABC of special codes)Useful co
Wisconsin - PHYS - 107
Physics 107: Ideas of Modern PhysicsExam 2 March 8, 2006Name_ ID #_ Section #_On the Scantron sheet, 1) Fill in your name 2) Fill in your student ID # (not your social security #) 3) Fill in your section # (under ABC of special codes)Useful co
Wisconsin - EXAMSSPR - 208
Name: _ Student ID: _ Section #: _Physics 208 Exam 3Apr. 23, 2008Print your name and section above. If you do not know your section number, write your TAs name. Your final answer must be placed in the box provided. You must show all your work t
Carnegie Mellon - DIPES - 00
A Product Family Approach to Graceful DegradationBill Nace Philip KoopmanCarnegie Mellon University Pittsburgh, PA USAAgendaM RoSES = Robust Self-configuring Embedded SystemsnExamines automatic graceful degradationM Graceful Degradationn
Carnegie Mellon - DSN - 2000
Robustness Testing of the Microsoft Win32 APICharles P. Shelton ECE Department & ICES Carnegie Mellon University Pittsburgh, PA, USA cshelton@cmu.edu AbstractAlthough Microsoft Windows is being deployed in mission-critical applications, little quan
Carnegie Mellon - GG - 2
Garth R. GoodsonCarnegie Mellon University, ECE Dept., Hamerschlag Hall, Pittsburgh, PA 15217 6533 Northumberland St, Apt 2, Pittsburgh, PA 15217 Research Interests Educationgg2k@ece.cmu.edu412.268.4262 412.422.2781My research interests include
Carnegie Mellon - SCHEN - 1
Carnegie Mellon University, Hamerschlag Hall Dept. of ECE 5000 Forbes Ave., Pittsburgh, PA 15213 (412) 687-1861 shelleychen@cmu.edu http:/www.ece.cmu.edu/~schen1Shelley ChenOBJECTIVEFull time research and development position in Microarchitec
Carnegie Mellon - STAT - 36
Journal of Statistical Physics, Vol. 101, Nos. 34, 2000Models of the Small WorldM. E. J. Newman 1Received March 21, 2000; final June 26, 2000 It is believed that almost any pair of people in the world can be connected to one another by a short ch
Carnegie Mellon - TR - 803
A Fast Clustering Algorithm with Application to Cosmology Woncheol JangMay 5, 2004Abstract We present a fast clustering algorithm for density contour clusters (Hartigan , 1975) that is a modied version of the Cuevas, Febrero and Fraiman (2000) alg
Carnegie Mellon - HW - 724
deviance1250lambda251500p[1,1]501750p[1,2]7511000p[2,1]10011250p[2,2]12511500p[3,1]15011750p[3,2]17512000
Carnegie Mellon - HW - 724
36-724: Applied Bayesian and Computational Statistics Homework 6: Due Friday April 21, 2006Announcements: Class is cancelled for April 10, 12, and 15. We have one more makeup class on April 18, 4:305:30, PH 226A. The material on model selection an
Carnegie Mellon - WEEK - 720
36-720: Graphical ModelsBrian Junker September 17, 2007 Undirected Graphs and Conditional Independence Generators and Graphs Graphical Models Log-Linear Graphical Models Example Decomposabe Models136-720 September 17, 2007References: Ch
Carnegie Mellon - WEEK - 201
INTRODUCTION TO STATISTICAL REASONING36-201 Lab #3 -Partial Solutions Question #1-2 The stem-and-leaf plot is given below. The distribution is unimodal and looks pretty symmetric. The center of the distribution is in the 70's. There is a gap in the
Carnegie Mellon - WEEK - 201
Random Variables We've been working with random variables all semester, we just haven't called them that. A Random variables is just a numerical variable in statistics, i.e. a random outcome that is quantitative (numerical).Example: Sally, B
Carnegie Mellon - NCME - 07
Investigating the utility of a conjunctive model in Q-matrix assessment using monthly student records in an online tutoring systemNathaniel O. Anozie and Brian W. Junker Department of Statistics Carnegie Mellon University Paper Prepared for the Annu
Carnegie Mellon - AAAI - 2006
Do skills combine additively to predict task difficulty in eighth-grade mathematics?Elizabeth Ayers, Brian Junker Department of Statistics, Carnegie Mellon University Pittsburgh, PA, USA {eayers, brian} @ stat.cmu.eduAbstract During the 20042005 sc
Carnegie Mellon - CMU - 315
36-315 Homework 5 Solutions[Note: On this assignment, you get 2 points for turning it in (14 7 is 98)] [Note: For each question, the point breakdown is: 7 points for the graph, 4 for answering the question, and 3 for justifying your choice of graph