Computer models of motion: Iterative calculations
|
|
- Homer Owen
- 6 years ago
- Views:
Transcription
1 Computer models o moton: Iteratve calculatons OBJECTIVES In ths actvty you wll learn how to: Create 3D box objects Update the poston o an object teratvely (repeatedly) to anmate ts moton Update the momentum and poston o an object teratvely (repeatedly) to predct ts moton TIME You should plan to nsh ths actvty n 50 mnutes or less. COMPUTER PROGRAM ORGANIZATION A computer program conssts o a sequence o nstructons. The computer carres out the nstructons one by one, n the order n whch they appear, and stops when t reaches the end. Each nstructon must be entered exactly correctly (as t were an nstructon to your calculator). I the computer encounters an error n an nstructon (such as a typng error), t wll stop runnng and prnt a red error message. A typcal program has our sectons: 1. Setup statements 2. Dentons o constants ( needed) 3. Creaton o objects and speccaton o ntal condtons 4. Calculatons to predct moton or move objects (done repettvely n a loop ) I. Setup statements Usng IDLE or VPython, create a new le and save t to your own student drve. Make sure to add ".py" to the le name. Enter the ollowng two statements n the IDLE edtor wndow: rom uture mport dvson rom vsual mport * Remember that every VPython program begns wth these setup statements. The rst statement (rom space underscore underscore uture underscore underscore space mport space *) tells the Python language to treat 1/2 as 0.5. Wthout the rst statement, the Python programmng language does nteger dvson wth truncaton and 1/2 s zero! The second statement tells the program to use the 3D module (called vsual ). 2. Constants Followng the setup secton o the program you would dene physcs constants. We ll talk about ths n later projects. 3a. Creatng objects Create a box object to represent the track: 1
2 track = box(pos=vector(0,-.05, 0), sze=(2.0, 0.05,.10), color=color.whte) Run the program by pressng F5. Arrange your wndows so the Python Shell wndow s always vsble. Kll the program by closng the graphc dsplay wndow. Now create a second box object, named "cart", wth some color other than whte. Gve ths object a poston (pos) o (0,0,0) and a sze o (0.1, 0.04, 0.06). Run the program by pressng F5. Zoom (both mouse buttons down) and rotate (rght mouse button down) to examne the scene. The cart should be loatng just above the track. Is t? Reposton the cart so ts let end s algned wth the let end o the track. To do ths you wll have to answer the ollowng questons: Where s the "pos" o a box object? The let end? The rght end? The center? Do the numbers n the "sze" o a box reer to the total length, or the dstance rom the center to one edge? You can answer these by expermentaton, or by lookng n the onlne reerence manual (Help menu, choose Vsual, clck on Reerence Manual.) 3b. Intal condtons Any object that moves needs two vector quanttes declared beore the loop begns: 1. ntal poston; and 2. ntal momentum. You ve already gven the cart an ntal poston at the let end o the track. Now you need to gve t an ntal momentum. I you push the cart wth your hand, the ntal momentum s the momentum o the cart just ater t leaves your hand. Snce the denton o momentum at speeds much less than the speed o lght s p mv, we need to tell the computer the cart s mass and the cart s ntal velocty. Below the exstng lnes o code, type the ollowng new lnes: mcart = 0.80 pcart = mcart*vector(0.5, 0, 0) prnt ('cart momentum =', pcart) We have made up a new varable named mcart The symbol mcart now stands or the value 0.80 (a scalar), whch represents the mass o the cart n klograms. We have also created a new vector varable pcart, whch s the momentum o the cart. We assgned t the ntal value o ( 0.80 kg) 0.5, 0, 0 m/s. Run the program. Look at the Python Shell wndow. Is the correct value o the vector pcart prnted there? From what s prnted, how can you tell t s a vector? Note: There are no bult n physcs attrbutes p or m or objects lke there are bult-n geometrcal attrbutes pos or radus. However, Python allows us to create new attrbutes or objects. We could have called the momentum cart.p, or the mass cart.m, nstead o pcart or mcart. It can be helpul to create attrbutes lke mass or momentum assocated wth objects so we can easly tell apart the masses and momenta o derent objects n a complex program. 2
3 3b. Tme step and total elapsed tme To make the cart move we wll use the poston update equaton r r vt repeatedly n a loop. We need to dene a varable deltat to stand or the tme step t, and a varable t to stand or the total tme elapsed snce the moton started. Here we wll use the value t = 0.01 s. Type the ollowng new lnes at the end o your program: deltat = 0.01 t = 0 Ths completes the rst part o the program, whch tells the computer to: a. Create numercal values or constants we mght need (none were needed ths tme) b. Create 3D objects c. Gve them ntal postons and momenta 4. Repeated calculatons: Loops In a computer program a sequence o nstructons that are to be repeated s called a loop. The knd o loop we wll use n VPython starts wth a "whle" statement. Instructons nsde the loop are ndented. IDLE wll ndent automatcally ater you type a colon. To wrte a smple loop, type the ollowng new lnes at the end o your program. Be sure to type a colon (:) at the end o the whle statement. Make sure the ndentng s correct, as shown below, then run: whle t < 0.2: prnt 'the tme s now', t t = t + deltat prnt 'ater the loop' The statement: t = t + deltat may look lke a mathematcal error. However, n a program, the "=" sgn has a derent meanng than n a mathematcal equaton. The rght hand sde o the statement tells Python to read up the old value o t, and add the value o deltat to t. The let hand sde o the statement tells Python to store ths new value nto the varable t. Run the program. Look at the Python Shell wndow. Look at the prnted output n the Shell wndow. Answer the ollowng questons: What makes the loop stop? Why s the rst prnted tme 0? Why s the last tme 0.19 and not 0.2? How can you get the program to prnt values rom 0 through 0.3? (Try t.) 4a. Constant momentum moton Consder a cart movng wth constant momentum. Somebody or somethng gave the cart some ntal momentum. We re not concerned here wth how t got that ntal momentum. We ll predct how the cart wll move n the uture, ater t acqured ts ntal momentum. 3
4 You wll use your teratve calculatonal loop. Each tme the program runs through ths loop, t wll do two thngs: 1. Use the cart s current momentum to calculate the cart s new poston 2. Increment the cumulatve tme t by deltat You know that the new poston o an object ater a tme nterval r r v t avg t s gven by where r s the nal poston o the object, and r s ts ntal poston. I the tme nterval t.s very short, so the velocty doesn t change very much, we can use the ntal or nal velocty to approxmate the average velocty. Snce at low speed p mv, or v p / m, we can wrte r r ( p / m) t We wll use ths equaton to ncrement the poston o the cart n the program. Frst, we must translate t so VPython can understand t. Delete or comment out the lne nsde your loop that prnts the value o t. On the ndented lne ater the whle statement, and beore the statement updatng t, type the ollowng: cart.pos = cart.pos + (pcart/mcart)*deltat Notce how ths statement corresponds to the algebrac equaton: r r ( p / m) t cart.pos = cart.pos + (pcart/mcart)*deltat Fnal poston Intal poston Velocty Tme step Thnk about the stuaton and answer the ollowng queston: What wll the elapsed tme t be ater movng two meters? Change the whle statement so the program runs just long enough or the cart to travel 2 meters. Now, run the program. What do you see? Slowng down the anmaton When you run the program, you should see the cart at ts nal pont. The program s executed so rapdly that the entre moton occurs aster than we can see, because a "vrtual tme" n the program elapses much aster than real tme does. We can slow down the anmaton rate by addng a rate statement. Add the ollowng lne nsde your loop (ndented): 4
5 rate(100) Every tme the computer executes the loop, when t reads rate(100), t pauses long enough to ensure the loop wll take 1/100 th o a second. Thereore, the computer wll only execute the loop 100 tmes per second. Now, run the program. You should see the cart travel to the rght at a constant velocty, endng up 2 meters rom ts startng locaton. Note: The cart gong beyond the edge o the track sn t a good smulaton o what really happens, but t s what we told the computer to do. There are no bult-n physcal behavors, lke gravtatonal orce, n VPython. Rght now, all we ve done s tell the program to make the cart move n a straght lne. I we wanted the cart to all o the edge, we would have to enter statements nto the program to tell the computer how to do ths. Answer the ollowng questons: 1. Whch statement n your program represents the poston update ormula? 2. What would you have to change n your program to make the cart start at the rght end o the track and move to the let? Do ths. When you have succeeded, compare your program to that o another group. 4b. 2D moton In a computer program you can model behavor that would be dcult to observe n the real world. Do the ollowng: Change the ntal momentum o the ancart so that t ncludes a +y component smlar n magntude to the x component o the momentum. What happens? Explan ths, then compare your explanaton to that o a neghborng group. Usng VPython on your own VPython s ree. You can download VPython rom and nstall t on your own computer. VPython s also avalable n the campus publc clusters n the Math, Statstcs, and Physcs secton o the Novell Applcaton Launcher; doubleclck "IDLE or VPython". In the text edtor (IDLE), on the Help menu you can choose Vsual, then Reerence manual, or choose Python Docs to obtan detaled normaton on the Python programmng language upon whch VPython s based. We wll use only a small subset o Python s extensve capabltes. 5
News. Recap: While Loop Example. Reading. Recap: Do Loop Example. Recap: For Loop Example
Unversty of Brtsh Columba CPSC, Intro to Computaton Jan-Apr Tamara Munzner News Assgnment correctons to ASCIIArtste.java posted defntely read WebCT bboards Arrays Lecture, Tue Feb based on sldes by Kurt
More informationBrave New World Pseudocode Reference
Brave New World Pseudocode Reference Pseudocode s a way to descrbe how to accomplsh tasks usng basc steps lke those a computer mght perform. In ths week s lab, you'll see how a form of pseudocode can be
More informationComplex Numbers. Now we also saw that if a and b were both positive then ab = a b. For a second let s forget that restriction and do the following.
Complex Numbers The last topc n ths secton s not really related to most of what we ve done n ths chapter, although t s somewhat related to the radcals secton as we wll see. We also won t need the materal
More informationR s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes
SPH3UW Unt 7.3 Sphercal Concave Mrrors Page 1 of 1 Notes Physcs Tool box Concave Mrror If the reflectng surface takes place on the nner surface of the sphercal shape so that the centre of the mrror bulges
More informationCMPS 10 Introduction to Computer Science Lecture Notes
CPS 0 Introducton to Computer Scence Lecture Notes Chapter : Algorthm Desgn How should we present algorthms? Natural languages lke Englsh, Spansh, or French whch are rch n nterpretaton and meanng are not
More informationMathematics 256 a course in differential equations for engineering students
Mathematcs 56 a course n dfferental equatons for engneerng students Chapter 5. More effcent methods of numercal soluton Euler s method s qute neffcent. Because the error s essentally proportonal to the
More information9. BASIC programming: Control and Repetition
Am: In ths lesson, you wll learn: H. 9. BASIC programmng: Control and Repetton Scenaro: Moz s showng how some nterestng patterns can be generated usng math. Jyot [after seeng the nterestng graphcs]: Usng
More informationAssembler. Building a Modern Computer From First Principles.
Assembler Buldng a Modern Computer From Frst Prncples www.nand2tetrs.org Elements of Computng Systems, Nsan & Schocken, MIT Press, www.nand2tetrs.org, Chapter 6: Assembler slde Where we are at: Human Thought
More informationHarvard University CS 101 Fall 2005, Shimon Schocken. Assembler. Elements of Computing Systems 1 Assembler (Ch. 6)
Harvard Unversty CS 101 Fall 2005, Shmon Schocken Assembler Elements of Computng Systems 1 Assembler (Ch. 6) Why care about assemblers? Because Assemblers employ some nfty trcks Assemblers are the frst
More informationAssembler. Shimon Schocken. Spring Elements of Computing Systems 1 Assembler (Ch. 6) Compiler. abstract interface.
IDC Herzlya Shmon Schocken Assembler Shmon Schocken Sprng 2005 Elements of Computng Systems 1 Assembler (Ch. 6) Where we are at: Human Thought Abstract desgn Chapters 9, 12 abstract nterface H.L. Language
More informationAP PHYSICS B 2008 SCORING GUIDELINES
AP PHYSICS B 2008 SCORING GUIDELINES General Notes About 2008 AP Physcs Scorng Gudelnes 1. The solutons contan the most common method of solvng the free-response questons and the allocaton of ponts for
More informationUSING GRAPHING SKILLS
Name: BOLOGY: Date: _ Class: USNG GRAPHNG SKLLS NTRODUCTON: Recorded data can be plotted on a graph. A graph s a pctoral representaton of nformaton recorded n a data table. t s used to show a relatonshp
More informationIntro. Iterators. 1. Access
Intro Ths mornng I d lke to talk a lttle bt about s and s. We wll start out wth smlartes and dfferences, then we wll see how to draw them n envronment dagrams, and we wll fnsh wth some examples. Happy
More informationAssignment # 2. Farrukh Jabeen Algorithms 510 Assignment #2 Due Date: June 15, 2009.
Farrukh Jabeen Algorthms 51 Assgnment #2 Due Date: June 15, 29. Assgnment # 2 Chapter 3 Dscrete Fourer Transforms Implement the FFT for the DFT. Descrbed n sectons 3.1 and 3.2. Delverables: 1. Concse descrpton
More informationWightman. Mobility. Quick Reference Guide THIS SPACE INTENTIONALLY LEFT BLANK
Wghtman Moblty Quck Reference Gude THIS SPACE INTENTIONALLY LEFT BLANK WIGHTMAN MOBILITY BASICS How to Set Up Your Vocemal 1. On your phone s dal screen, press and hold 1 to access your vocemal. If your
More informationELEC 377 Operating Systems. Week 6 Class 3
ELEC 377 Operatng Systems Week 6 Class 3 Last Class Memory Management Memory Pagng Pagng Structure ELEC 377 Operatng Systems Today Pagng Szes Vrtual Memory Concept Demand Pagng ELEC 377 Operatng Systems
More informationFor instance, ; the five basic number-sets are increasingly more n A B & B A A = B (1)
Secton 1.2 Subsets and the Boolean operatons on sets If every element of the set A s an element of the set B, we say that A s a subset of B, or that A s contaned n B, or that B contans A, and we wrte A
More informationA Binarization Algorithm specialized on Document Images and Photos
A Bnarzaton Algorthm specalzed on Document mages and Photos Ergna Kavalleratou Dept. of nformaton and Communcaton Systems Engneerng Unversty of the Aegean kavalleratou@aegean.gr Abstract n ths paper, a
More information3D vector computer graphics
3D vector computer graphcs Paolo Varagnolo: freelance engneer Padova Aprl 2016 Prvate Practce ----------------------------------- 1. Introducton Vector 3D model representaton n computer graphcs requres
More informationSetup and Use. Version 3.7 2/1/2014
Verson 3.7 2/1/2014 Setup and Use MaestroSoft, Inc. 1750 112th Avenue NE, Sute A200, Bellevue, WA 98004 425.688.0809 / 800.438.6498 Fax: 425.688.0999 www.maestrosoft.com Contents Text2Bd checklst 3 Preparng
More informationPhysics 132 4/24/17. April 24, 2017 Physics 132 Prof. E. F. Redish. Outline
Aprl 24, 2017 Physcs 132 Prof. E. F. Redsh Theme Musc: Justn Tmberlake Mrrors Cartoon: Gary Larson The Far Sde 1 Outlne Images produced by a curved mrror Image equatons for a curved mrror Lght n dense
More informationSetup and Use. For events not using AuctionMaestro Pro. Version /7/2013
Verson 3.1.2 2/7/2013 Setup and Use For events not usng AuctonMaestro Pro MaestroSoft, Inc. 1750 112th Avenue NE, Sute A200, Bellevue, WA 98004 425.688.0809 / 800.438.6498 Fax: 425.688.0999 www.maestrosoft.com
More informationSequential search. Building Java Programs Chapter 13. Sequential search. Sequential search
Sequental search Buldng Java Programs Chapter 13 Searchng and Sortng sequental search: Locates a target value n an array/lst by examnng each element from start to fnsh. How many elements wll t need to
More informationSlide 1 SPH3UW: OPTICS I. Slide 2. Slide 3. Introduction to Mirrors. Light incident on an object
Slde 1 SPH3UW: OPTICS I Introducton to Mrrors Slde 2 Lght ncdent on an object Absorpton Relecton (bounces)** See t Mrrors Reracton (bends) Lenses Oten some o each Everythng true or wavelengths
More informationProgramming in Fortran 90 : 2017/2018
Programmng n Fortran 90 : 2017/2018 Programmng n Fortran 90 : 2017/2018 Exercse 1 : Evaluaton of functon dependng on nput Wrte a program who evaluate the functon f (x,y) for any two user specfed values
More informationReading. 14. Subdivision curves. Recommended:
eadng ecommended: Stollntz, Deose, and Salesn. Wavelets for Computer Graphcs: heory and Applcatons, 996, secton 6.-6., A.5. 4. Subdvson curves Note: there s an error n Stollntz, et al., secton A.5. Equaton
More informationVirtual Memory. Background. No. 10. Virtual Memory: concept. Logical Memory Space (review) Demand Paging(1) Virtual Memory
Background EECS. Operatng System Fundamentals No. Vrtual Memory Prof. Hu Jang Department of Electrcal Engneerng and Computer Scence, York Unversty Memory-management methods normally requres the entre process
More informationWelcome to the Three Ring %CIRCOS: An Example of Creating a Circular Graph without a Polar Axis
PharmaSUG 2018 - Paper DV14 Welcome to the Three Rng %CIRCOS: An Example of Creatng a Crcular Graph wthout a Polar Axs Jeffrey Meyers, Mayo Clnc ABSTRACT An nternal graphcs challenge between SAS and R
More informationExercises (Part 4) Introduction to R UCLA/CCPR. John Fox, February 2005
Exercses (Part 4) Introducton to R UCLA/CCPR John Fox, February 2005 1. A challengng problem: Iterated weghted least squares (IWLS) s a standard method of fttng generalzed lnear models to data. As descrbed
More informationTN348: Openlab Module - Colocalization
TN348: Openlab Module - Colocalzaton Topc The Colocalzaton module provdes the faclty to vsualze and quantfy colocalzaton between pars of mages. The Colocalzaton wndow contans a prevew of the two mages
More informationSLAM Summer School 2006 Practical 2: SLAM using Monocular Vision
SLAM Summer School 2006 Practcal 2: SLAM usng Monocular Vson Javer Cvera, Unversty of Zaragoza Andrew J. Davson, Imperal College London J.M.M Montel, Unversty of Zaragoza. josemar@unzar.es, jcvera@unzar.es,
More informationConfigure Address Book. Configure Show Send To. Options Supervision Message. Options Flood Preventer
FlashPont Sotware Inc. eomega Pagng Sotware Qualty Sotware For The Fre Alarm Industry Descrpton eomega pagng sotware provdes a means o convertng prnter output rom a Smplex re alarm panel nto short messages.
More informationEsc101 Lecture 1 st April, 2008 Generating Permutation
Esc101 Lecture 1 Aprl, 2008 Generatng Permutaton In ths class we wll look at a problem to wrte a program that takes as nput 1,2,...,N and prnts out all possble permutatons of the numbers 1,2,...,N. For
More informationNotes on Organizing Java Code: Packages, Visibility, and Scope
Notes on Organzng Java Code: Packages, Vsblty, and Scope CS 112 Wayne Snyder Java programmng n large measure s a process of defnng enttes (.e., packages, classes, methods, or felds) by name and then usng
More informationPaper style and format for the Sixth International Symposium on Turbulence, Heat and Mass Transfer
K. Hanjalć, Y. Nagano and S. Jakrlć (Edtors) 2009 Begell House, Inc. Paper style and format for the Sxth Internatonal Symposum on Turbulence, Heat and Mass Transfer K. Hanjalć 1, Y. Nagano 2 and S. Jakrlć
More informationSome Advanced SPC Tools 1. Cumulative Sum Control (Cusum) Chart For the data shown in Table 9-1, the x chart can be generated.
Some Advanced SP Tools 1. umulatve Sum ontrol (usum) hart For the data shown n Table 9-1, the x chart can be generated. However, the shft taken place at sample #21 s not apparent. 92 For ths set samples,
More informationwith Optic65 and Optic25 Cameras FOR OUTDOOR TRACKING ONLY unless used in conjunction with the Indoor Tracking Accessory.
wth Optc6 and Optc Cameras Quck Start Gude FOR OUTDOOR TRACKING ONLY unless used n conjuncton wth the Indoor Trackng Accessory. CONGRATULATIONS ON SCORING YOUR SOLOSHOT Our category-creatng lne of personal
More informationReal-time Motion Capture System Using One Video Camera Based on Color and Edge Distribution
Real-tme Moton Capture System Usng One Vdeo Camera Based on Color and Edge Dstrbuton YOSHIAKI AKAZAWA, YOSHIHIRO OKADA, AND KOICHI NIIJIMA Graduate School of Informaton Scence and Electrcal Engneerng,
More information3-Wheel Swerve Drive - The Trouble with Tribots
3-Wheel Swerve Drve - The Trouble wth Trbots Clem McKown - FRC Team 1640 17-August-2014 Executve Summary FRC's 2013 change n robot permeter rules (to 112 nch maxmum overall permeter from the earler maxmum
More informationWishing you all a Total Quality New Year!
Total Qualty Management and Sx Sgma Post Graduate Program 214-15 Sesson 4 Vnay Kumar Kalakband Assstant Professor Operatons & Systems Area 1 Wshng you all a Total Qualty New Year! Hope you acheve Sx sgma
More informationA Fast Visual Tracking Algorithm Based on Circle Pixels Matching
A Fast Vsual Trackng Algorthm Based on Crcle Pxels Matchng Zhqang Hou hou_zhq@sohu.com Chongzhao Han czhan@mal.xjtu.edu.cn Ln Zheng Abstract: A fast vsual trackng algorthm based on crcle pxels matchng
More informationON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE
Yordzhev K., Kostadnova H. Інформаційні технології в освіті ON SOME ENTERTAINING APPLICATIONS OF THE CONCEPT OF SET IN COMPUTER SCIENCE COURSE Yordzhev K., Kostadnova H. Some aspects of programmng educaton
More informationANSYS FLUENT 12.1 in Workbench User s Guide
ANSYS FLUENT 12.1 n Workbench User s Gude October 2009 Copyrght c 2009 by ANSYS, Inc. All Rghts Reserved. No part of ths document may be reproduced or otherwse used n any form wthout express wrtten permsson
More informationReproducing Works of Calder
Reproducng Works of Calder Dongkyoo Lee*, Hee-Jung Bae*, Chang Tae Km*, Dong-Chun Lee*, Dae-Hyun Jung*, Nam-Kyung Lee*, Kyoo-Ho Lee*, Nakhoon Baek**, J. Won Lee***, Kwan Woo Ryu* and James K. Hahn*** *
More informationAnalysis of Continuous Beams in General
Analyss of Contnuous Beams n General Contnuous beams consdered here are prsmatc, rgdly connected to each beam segment and supported at varous ponts along the beam. onts are selected at ponts of support,
More informationIntroduction to 3D computer modeling
OBJECTIVES In this course you will construct computer models to: Introduction to 3D computer modeling Visualize motion in 3D Visualize vector quantities like position, momentum, and force in 3D Do calculations
More informationLife Tables (Times) Summary. Sample StatFolio: lifetable times.sgp
Lfe Tables (Tmes) Summary... 1 Data Input... 2 Analyss Summary... 3 Survval Functon... 5 Log Survval Functon... 6 Cumulatve Hazard Functon... 7 Percentles... 7 Group Comparsons... 8 Summary The Lfe Tables
More informationAmnon Shashua Shai Avidan Michael Werman. The Hebrew University, objects.
Trajectory Trangulaton over Conc Sectons Amnon Shashua Sha Avdan Mchael Werman Insttute of Computer Scence, The Hebrew Unversty, Jerusalem 91904, Israel e-mal: fshashua,avdan,wermang@cs.huj.ac.l Abstract
More informationAMath 483/583 Lecture 21 May 13, Notes: Notes: Jacobi iteration. Notes: Jacobi with OpenMP coarse grain
AMath 483/583 Lecture 21 May 13, 2011 Today: OpenMP and MPI versons of Jacob teraton Gauss-Sedel and SOR teratve methods Next week: More MPI Debuggng and totalvew GPU computng Read: Class notes and references
More informationPass by Reference vs. Pass by Value
Pass by Reference vs. Pass by Value Most methods are passed arguments when they are called. An argument may be a constant or a varable. For example, n the expresson Math.sqrt(33) the constant 33 s passed
More informationSENSITIVITY ANALYSIS IN LINEAR PROGRAMMING USING A CALCULATOR
SENSITIVITY ANALYSIS IN LINEAR PROGRAMMING USING A CALCULATOR Judth Aronow Rchard Jarvnen Independent Consultant Dept of Math/Stat 559 Frost Wnona State Unversty Beaumont, TX 7776 Wnona, MN 55987 aronowju@hal.lamar.edu
More informationHigh level vs Low Level. What is a Computer Program? What does gcc do for you? Program = Instructions + Data. Basic Computer Organization
What s a Computer Program? Descrpton of algorthms and data structures to acheve a specfc ojectve Could e done n any language, even a natural language lke Englsh Programmng language: A Standard notaton
More informationF-5000 View Software Installation and Operation Guide Belcher Road South, Largo, FL USA Tel +1 (727) Fax +1 (727)
ONICON Flow and Energy Measurement F-5000 Vew Software Installaton and Operaton Gude 11451 Belcher Road South, Largo, FL 33773 USA Tel +1 (727) 447-6140 Fax +1 (727)442-5699 2032-1 / 107050 Rev B www.oncon.com
More informationGSA Training Notes Raft and Piled-raft Analysis
GSA Tranng Notes Rat and Pled-rat Analyss 1 Introdcton Rat analyss n GSA provdes a means o lnkng GSA statc analyss and sol settlement analyss, so the sol-strctre nteractons can be consdered n the analyss.
More informationIP Camera Configuration Software Instruction Manual
IP Camera 9483 - Confguraton Software Instructon Manual VBD 612-4 (10.14) Dear Customer, Wth your purchase of ths IP Camera, you have chosen a qualty product manufactured by RADEMACHER. Thank you for the
More informationOn Some Entertaining Applications of the Concept of Set in Computer Science Course
On Some Entertanng Applcatons of the Concept of Set n Computer Scence Course Krasmr Yordzhev *, Hrstna Kostadnova ** * Assocate Professor Krasmr Yordzhev, Ph.D., Faculty of Mathematcs and Natural Scences,
More informationCompiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz
Compler Desgn Sprng 2014 Regster Allocaton Sample Exercses and Solutons Prof. Pedro C. Dnz USC / Informaton Scences Insttute 4676 Admralty Way, Sute 1001 Marna del Rey, Calforna 90292 pedro@s.edu Regster
More informationWireless Temperature Monitoring Overview
Wreless Temperature Montorng Overvew Wreless Temperature Montorng and Alerts. Your Dashboard gves you advanced montorng, alerts (SMS or Emals), graphng and PDF reports from anywhere n the world. Product
More informationAngle-Independent 3D Reconstruction. Ji Zhang Mireille Boutin Daniel Aliaga
Angle-Independent 3D Reconstructon J Zhang Mrelle Boutn Danel Alaga Goal: Structure from Moton To reconstruct the 3D geometry of a scene from a set of pctures (e.g. a move of the scene pont reconstructon
More informationAgenda & Reading. Simple If. Decision-Making Statements. COMPSCI 280 S1C Applications Programming. Programming Fundamentals
Agenda & Readng COMPSCI 8 SC Applcatons Programmng Programmng Fundamentals Control Flow Agenda: Decsonmakng statements: Smple If, Ifelse, nested felse, Select Case s Whle, DoWhle/Untl, For, For Each, Nested
More informationSolutions to Programming Assignment Five Interpolation and Numerical Differentiation
College of Engneerng and Coputer Scence Mechancal Engneerng Departent Mechancal Engneerng 309 Nuercal Analyss of Engneerng Systes Sprng 04 Nuber: 537 Instructor: Larry Caretto Solutons to Prograng Assgnent
More informationThis chapter discusses aspects of heat conduction. The equilibrium heat conduction on a rod. In this chapter, Arrays will be discussed.
1 Heat Flow n a Rod Ths chapter dscusses aspects of heat conducton. The equlbrum heat conducton on a rod. In ths chapter, Arrays wll be dscussed. Arrays provde a mechansm for declarng and accessng several
More informationEfficient Distributed File System (EDFS)
Effcent Dstrbuted Fle System (EDFS) (Sem-Centralzed) Debessay(Debsh) Fesehaye, Rahul Malk & Klara Naherstedt Unversty of Illnos-Urbana Champagn Contents Problem Statement, Related Work, EDFS Desgn Rate
More informationMidterms Save the Dates!
Unversty of Brtsh Columba CPSC, Intro to Computaton Alan J. Hu Readngs Ths Week: Ch 6 (Ch 7 n old 2 nd ed). (Remnder: Readngs are absolutely vtal for learnng ths stuff!) Thnkng About Loops Lecture 9 Some
More informationReport on On-line Graph Coloring
2003 Fall Semester Comp 670K Onlne Algorthm Report on LO Yuet Me (00086365) cndylo@ust.hk Abstract Onlne algorthm deals wth data that has no future nformaton. Lots of examples demonstrate that onlne algorthm
More informationSupport Vector Machines
/9/207 MIST.6060 Busness Intellgence and Data Mnng What are Support Vector Machnes? Support Vector Machnes Support Vector Machnes (SVMs) are supervsed learnng technques that analyze data and recognze patterns.
More information3D Virtual Eyeglass Frames Modeling from Multiple Camera Image Data Based on the GFFD Deformation Method
NICOGRAPH Internatonal 2012, pp. 114-119 3D Vrtual Eyeglass Frames Modelng from Multple Camera Image Data Based on the GFFD Deformaton Method Norak Tamura, Somsangouane Sngthemphone and Katsuhro Ktama
More informationMRKOMNO. kéï=~ë=çñw= pfabufp=ud. aáöáí~ä=o~çáçöê~éüó. nìáåâ=êéñéêéååé=öìáçé==== båöäáëü
kéï=~ë=çñw= MRKOMNO pfabufp=ud aáöáí~ä=o~çáçöê~éüó nìáåâ=êéñéêéååé=öìáçé==== båöäáëü 0123 Ths product bears the CE markng n accordance wth the provsons of the Councl Drectve 93/42/EEC of June 14, 1993
More informationHermite Splines in Lie Groups as Products of Geodesics
Hermte Splnes n Le Groups as Products of Geodescs Ethan Eade Updated May 28, 2017 1 Introducton 1.1 Goal Ths document defnes a curve n the Le group G parametrzed by tme and by structural parameters n the
More informationSteps for Computing the Dissimilarity, Entropy, Herfindahl-Hirschman and. Accessibility (Gravity with Competition) Indices
Steps for Computng the Dssmlarty, Entropy, Herfndahl-Hrschman and Accessblty (Gravty wth Competton) Indces I. Dssmlarty Index Measurement: The followng formula can be used to measure the evenness between
More informationCS1100 Introduction to Programming
Factoral (n) Recursve Program fact(n) = n*fact(n-) CS00 Introducton to Programmng Recurson and Sortng Madhu Mutyam Department of Computer Scence and Engneerng Indan Insttute of Technology Madras nt fact
More informationPerformance Evaluation of Information Retrieval Systems
Why System Evaluaton? Performance Evaluaton of Informaton Retreval Systems Many sldes n ths secton are adapted from Prof. Joydeep Ghosh (UT ECE) who n turn adapted them from Prof. Dk Lee (Unv. of Scence
More informationNachos Project 3. Speaker: Sheng-Wei Cheng 2010/12/16
Nachos Project Speaker: Sheng-We Cheng //6 Agenda Motvaton User Programs n Nachos Related Nachos Code for User Programs Project Assgnment Bonus Submsson Agenda Motvaton User Programs n Nachos Related Nachos
More informationLobachevsky State University of Nizhni Novgorod. Polyhedron. Quick Start Guide
Lobachevsky State Unversty of Nzhn Novgorod Polyhedron Quck Start Gude Nzhn Novgorod 2016 Contents Specfcaton of Polyhedron software... 3 Theoretcal background... 4 1. Interface of Polyhedron... 6 1.1.
More informationInstallation and User Guide. Digidim Remote Control (303) Product description. Switching Lights On/Off using Digidim 303 Remote
Installaton and User Gude Dgdm Remote Control (0) Product descrpton The Dgdm Remote (0) can be used n conjuncton wth the Dm Sense to modfy the preset lght levels and recall/ store scenes, as well as actvatng
More informationS.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION?
S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION? Célne GALLET ENSICA 1 place Emle Bloun 31056 TOULOUSE CEDEX e-mal :cgallet@ensca.fr Jean Luc LACOME DYNALIS Immeuble AEROPOLE - Bat 1 5, Avenue Albert
More information6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour
6.854 Advanced Algorthms Petar Maymounkov Problem Set 11 (November 23, 2005) Wth: Benjamn Rossman, Oren Wemann, and Pouya Kheradpour Problem 1. We reduce vertex cover to MAX-SAT wth weghts, such that the
More informationDESIGN OF A HAPTIC DEVICE FOR EXCAVATOR EQUIPPED WITH CRUSHER
DESIGN OF A HAPTIC DEVICE FOR EXCAVATOR EQUIPPED WITH CRUSHER Kyeong Won Oh, Dongnam Km Korea Unversty, Graduate School 5Ga-1, Anam-Dong, Sungbuk-Gu, Seoul, Korea {locosk, smleast}@korea.ac.kr Jong-Hyup
More informationUser Authentication Based On Behavioral Mouse Dynamics Biometrics
User Authentcaton Based On Behavoral Mouse Dynamcs Bometrcs Chee-Hyung Yoon Danel Donghyun Km Department of Computer Scence Department of Computer Scence Stanford Unversty Stanford Unversty Stanford, CA
More informationCSE 326: Data Structures Quicksort Comparison Sorting Bound
CSE 326: Data Structures Qucksort Comparson Sortng Bound Steve Setz Wnter 2009 Qucksort Qucksort uses a dvde and conquer strategy, but does not requre the O(N) extra space that MergeSort does. Here s the
More informationCHARUTAR VIDYA MANDAL S SEMCOM Vallabh Vidyanagar
CHARUTAR VIDYA MANDAL S SEMCOM Vallabh Vdyanagar Faculty Name: Am D. Trved Class: SYBCA Subject: US03CBCA03 (Advanced Data & Fle Structure) *UNIT 1 (ARRAYS AND TREES) **INTRODUCTION TO ARRAYS If we want
More information124 Chapter 8. Case Study: A Memory Component ndcatng some error condton. An exceptonal return of a value e s called rasng excepton e. A return s ssue
Chapter 8 Case Study: A Memory Component In chapter 6 we gave the outlne of a case study on the renement of a safe regster. In ths chapter wepresent the outne of another case study on persstent communcaton;
More informationO n processors in CRCW PRAM
PARALLEL COMPLEXITY OF SINGLE SOURCE SHORTEST PATH ALGORITHMS Mshra, P. K. Department o Appled Mathematcs Brla Insttute o Technology, Mesra Ranch-8355 (Inda) & Dept. o Electroncs & Electrcal Communcaton
More informationLine geometry, according to the principles of Grassmann s theory of extensions. By E. Müller in Vienna.
De Lnengeometre nach den Prnzpen der Grassmanschen Ausdehnungslehre, Monastshefte f. Mathematk u. Physk, II (89), 67-90. Lne geometry, accordng to the prncples of Grassmann s theory of extensons. By E.
More informationParallel matrix-vector multiplication
Appendx A Parallel matrx-vector multplcaton The reduced transton matrx of the three-dmensonal cage model for gel electrophoress, descrbed n secton 3.2, becomes excessvely large for polymer lengths more
More informationPHYSICS-ENHANCED L-SYSTEMS
PHYSICS-ENHANCED L-SYSTEMS Hansrud Noser 1, Stephan Rudolph 2, Peter Stuck 1 1 Department of Informatcs Unversty of Zurch, Wnterthurerstr. 190 CH-8057 Zurch Swtzerland noser(stuck)@f.unzh.ch, http://www.f.unzh.ch/~noser(~stuck)
More informationX- Chart Using ANOM Approach
ISSN 1684-8403 Journal of Statstcs Volume 17, 010, pp. 3-3 Abstract X- Chart Usng ANOM Approach Gullapall Chakravarth 1 and Chaluvad Venkateswara Rao Control lmts for ndvdual measurements (X) chart are
More informationREFRACTION. a. To study the refraction of light from plane surfaces. b. To determine the index of refraction for Acrylic and Water.
Purpose Theory REFRACTION a. To study the refracton of lght from plane surfaces. b. To determne the ndex of refracton for Acrylc and Water. When a ray of lght passes from one medum nto another one of dfferent
More informationFIBARO WALL PLUG OPERATING MANUAL FGBWHWPE-102/FGBWHWPF-102 CONTENTS
OPERATING MANUAL EN FIBARO WALL PLUG FGBWHWPE-102/FGBWHWPF-102 CONTENTS #1: Descrpton and features 3 #2: Parng the accessory 4 #3: Reset 5 #4: Functonalty 6 v1.0 #5: W-F 8 #6: Confgurable parameters 9
More informationThe example below contains two doors and no floor level obstacles. Your panel calculator should now look something like this: 2,400
Step 1: A r c h t e c t u r a l H e a t n g o begn wth you must prepare a smple drawng for each room n whch you wsh to nstall our Heat Profle Skrtng Heatng System. You certanly don't need to be Pcasso,
More informationHelp for Time-Resolved Analysis TRI2 version 2.4 P Barber,
Help for Tme-Resolved Analyss TRI2 verson 2.4 P Barber, 22.01.10 Introducton Tme-resolved Analyss (TRA) becomes avalable under the processng menu once you have loaded and selected an mage that contans
More informationDynamic wetting property investigation of AFM tips in micro/nanoscale
Dynamc wettng property nvestgaton of AFM tps n mcro/nanoscale The wettng propertes of AFM probe tps are of concern n AFM tp related force measurement, fabrcaton, and manpulaton technques, such as dp-pen
More informationBITPLANE AG IMARISCOLOC. Operating Instructions. Manual Version 1.0 January the image revolution starts here.
BITPLANE AG IMARISCOLOC Operatng Instructons Manual Verson 1.0 January 2003 the mage revoluton starts here. Operatng Instructons BITPLANE AG Copyrght Ths document contans propretary nformaton protected
More informationModeling Concave Globoidal Cam with Swinging Roller Follower: A Case Study
Modelng Concave Globodal Cam wth Swngng Roller Follower: A Case Study Nguyen Van Tuong, and Premysl Pokorny Abstract Ths paper descrbes a computer-aded desgn for desgn of the concave globodal cam wth cylndrcal
More informationAnalysis of 3D Cracks in an Arbitrary Geometry with Weld Residual Stress
Analyss of 3D Cracks n an Arbtrary Geometry wth Weld Resdual Stress Greg Thorwald, Ph.D. Ted L. Anderson, Ph.D. Structural Relablty Technology, Boulder, CO Abstract Materals contanng flaws lke nclusons
More informationA MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS
Proceedngs of the Wnter Smulaton Conference M E Kuhl, N M Steger, F B Armstrong, and J A Jones, eds A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Mark W Brantley Chun-Hung
More informationmquest Quickstart Version 11.0
mquest Quckstart Verson 11.0 cluetec GmbH Emmy-Noether-Straße 17 76131 Karlsruhe Germany www.cluetec.de www.mquest.nfo cluetec GmbH Karlsruhe, 2016 Document verson 5 27.04.2016 16:59 > Propretary notce
More informationIntroduction to Geometrical Optics - a 2D ray tracing Excel model for spherical mirrors - Part 2
Introducton to Geometrcal Optcs - a D ra tracng Ecel model for sphercal mrrors - Part b George ungu - Ths s a tutoral eplanng the creaton of an eact D ra tracng model for both sphercal concave and sphercal
More informationPriority queues and heaps Professors Clark F. Olson and Carol Zander
Prorty queues and eaps Professors Clark F. Olson and Carol Zander Prorty queues A common abstract data type (ADT) n computer scence s te prorty queue. As you mgt expect from te name, eac tem n te prorty
More informationAn Optimal Algorithm for Prufer Codes *
J. Software Engneerng & Applcatons, 2009, 2: 111-115 do:10.4236/jsea.2009.22016 Publshed Onlne July 2009 (www.scrp.org/journal/jsea) An Optmal Algorthm for Prufer Codes * Xaodong Wang 1, 2, Le Wang 3,
More information