Finite Automata. a) Reading a symbol, b) Transferring to a new instruction, and c) Advancing the tape head one square to the right.

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Finite Automata. a) Reading a symbol, b) Transferring to a new instruction, and c) Advancing the tape head one square to the right."

Transcription

1 Finite Automata Let u begin by removing almot all of the Turing machine' power! Maybe then we hall have olvable deciion problem and till be able to accomplih ome computational tak. Alo, we might be able to gain inight into the nature of computation by examining what computational loe we incur with thi lo of power. If we do t allow writing or two-way operation of the tape head, we have what ha been traditionally called a finite automaton. Thi machine i only allowed to read it input tape and then, on the bai of what it ha read and proceed, accept or reject the input. Thi retricted machine operate by: a) Reading a ymbol, b) Tranferring to a new intruction, and c) Advancing the tape head one quare to the right. When it arrive at the end of it input it then accept or reject depending upon what intruction i being executed. Thi ound very imple. It i merely a one-way, emi-literate Turing machine that jut decide memberhip problem for a living! Let u examine one. In order to depict one, all we need to do i jot down Turing machine intruction in one large table, leave out the write part (that wa t a pun!), and add a te which indicate whether the machine hould accept. Here i an example: Intruction Read Goto Accept? ame next ame next ye ame ame Look cloely at thi machine. It tay on intruction one until it read a one. Then it goe to intruction two and accept any input unle ather one arrive (the ymbol - t ather input). If two or more one appear in the input, then it end up executing intruction three and doe t accept when the input i over. And if one appear in the input the machine remain on intruction one and doe t accept. So, thi machine accept only input that contain exactly one.

2 Finite Automata (N.B. Endmarker are t needed ince the machine jut move to the right. Accepting happen when the machine finihe the input while executing an intruction that call for acceptance. Try thi machine out on the input,,, etc.) Traditionally thee machine have t had intruction but tate. (Recall A. M. Turing' tate of mind.) Ather way to repreent thi ame machine i to put the next intruction or next tate or goto portion under the input in a table like that in figure. There i ather traditional method to decribe finite automata which i extremely intuitive. It i a picture called a tate graph. The tate of the finite automaton appear a vertice of the graph while the tranition from tate to tate under input are the graph edge. The tate graph for the ame machine alo appear in figure. State Input, Accept? ye Figure - Finite Automaton Repreentation (Note that the two circle that urround tate two mean acceptance.) Before continuing let' examine the computation of a finite automaton. Our firt example begin in tate one and read the input ymbol in turn changing tate a neceary. Thu a computation can be characterized by a equence of tate. (Recall that Turing machine configuration needed the tate plu the tape content. Since a finite automaton never write, we alway kw what i on the tape and need only look at a tate a a configuration.) Here i the equence for the input. Input Read: State:

3 Finite Automata Our next example i an elevator controller. Let' imagine an elevator that erve two floor. Input are call to a floor either from inide the elevator or from the floor itelf. Thi make three ditinct input poible, namely: - call - call to floor one - call to floor two The elevator itelf can be going up, going down, or halted at a floor. If it i on a floor it could be waiting for a call or about to go to the other floor. Thi provide u with the ix tate hown in figure along with the tate graph for the elevator controller., W D W Waiting on firt floor,, U About to go up Going up Going down,, W Waiting - econd floor D About to go down W D, Figure - Elevator Control A tate table for the elevator i provided below a table. State W (wait on ) U (tart up) W (wait on ) D (tart down) Input ne call to call to W W W W W U D W W U W D Table - Elevator Control Accepting and rejecting tate are t included in the elevator deign becaue acceptance i t an iue. If we were to deign a more ophiticated elevator, it might have tate that indicated:

4 Finite Automata 4 a) power failure, b) overloading, or c) breakdown In thi cae acceptance and rejection might make ene. Let u make a few mall te about the deign. If the elevator i about to move (i.e. in tate U or D) and it i called to the floor it i preently on it will tay. (Thi may be good - try it next time you are in an elevator.) And if it i moving (up or down) and get called back the other way, it remember the call by going to the U or D tate upon arrival on the next floor. Of coure the elevator doe t do thing like open and cloe door (thee could be tate too) ince that would have added complexity to the deign. Speaking of complexity, imagine having floor. That i our levity for thi ection. Now that we kw what a finite automaton i, we mut (a uual) define it preciely. Definition. A finite automaton M i a quintuple M = (S,I,δ,,F) where: S i a finite et (of tate) I i a finite alphabet (of input ymbol) δ: S I S (next tate function) S (the tarting tate) F S (the accepting tate). We alo need ome additional tation. The next tate function i called the tranition function and the accepting tate are often called final tate. The entire machine i uually defined by preenting a tate table or a tate graph. In thi way, the tate, alphabet, tranition function, and final tate are contructively defined. The tarting tate i uually the lowet numbered tate. Our firt example of a finite automaton i: M = ({,, }, {,}, δ,, { }) where the tranition function δ, i defined explicitly by either a tate table or a tate graph. At thi point we mut make a light detour and examine a very important yet eemingly inignificant input tring called the empty tring. It i a tring without any ymbol in it and i deted a ε. It i t a tring of blank. An example might make thi clear. Look between the bracket in the picture below.

5 Finite Automata 5 A Blank Empty String [ ] [] Let' look again at a computation by our firt finite automaton. For the input, our machine begin in, read a and goe to δ(,) =, then read a and goe to δ(,) =, and end up in δ(,) = after reading the final. All of that can be put together a: δ(δ(δ(,),),) = We call thi tranition on tring δ * and define it a follow. Definition. Let M = (S,I,δ,,F). For any input tring x, input ymbol a, and tate i, the tranition function on tring δ* take the value: δ* (i,(*e) = i δ* (i,a) = δ( i,a) δ* (i,xa) = δ(δ* (i,x),a). That certainly wa tere. But, δ * i really jut what one expect it to be. It merely applie the tranition function to the ymbol in the tring. Let' look at thi for the example in figure. b a a b a,b a,b Thi machine ha a et of tate = {,,, } and operate over the input alphabet {a, b}. It tarting tate i and it et of final or accepting tate, F = { }. The tranition function i fully decribed twice in figure ; once in figure a a a tate table and once in figure b a a tate graph.

6 Finite Automata 6 State Input a b Accept? ye Figure - Finite Automaton If the machine receive the input bbaa it goe through the equence of tate:,,,, while when it get an input uch a abab it goe through the tate tranition:,,,, Now we hall become a bit more abtract. When a finite automaton receive an input tring uch a: x = x x... x n where the x i are ymbol from it input alphabet, it progree through the equence: k, k,..., k n+ where the tate in the equence are defined a: k k k kn+ = = δ( = δ( k k = δ(,x ) = δ(,x ),x ) = δ (! kn,x ) = δ ( n Getting back to a more intuitive reality, the following table provide an aignment of value to the ymbol ued above for an input of bbaba to the finite automaton of figure.,x x,x x )...x n ) i x i b b a b a k i

7 Finite Automata 7 We have mentioned acceptance and rejection but have t talked too much about it. Thi can be made precie alo. Definition. The et (of tring) accepted by the finite automaton M = (S,I,δ,,F) i: T(M) = { x δ* (,x) F } Thi et of accepted tring (named T(M) to mean Tape of M) i merely all of the tring for which M ended up in a final or accepting tate after proceing the tring. For our firt example (figure ) thi wa all tring of ' and ' that contain exactly one. Our lat example (figure..) accepted the et of tring over the alphabet {a, b} which began with exactly two b'.

State-space analysis of control systems: Part I

State-space analysis of control systems: Part I Why a different approach? State-pace analyi of control ytem: Part I Uing a tate-variable approach give u a traightforward way to analyze MIM multiple-input, multiple output ytem. A tate variable model

More information

Unit 11 Using Linear Regression to Describe Relationships

Unit 11 Using Linear Regression to Describe Relationships Unit 11 Uing Linear Regreion to Decribe Relationhip Objective: To obtain and interpret the lope and intercept of the leat quare line for predicting a quantitative repone variable from a quantitative explanatory

More information

6. Friction, Experiment and Theory

6. Friction, Experiment and Theory 6. Friction, Experiment and Theory The lab thi wee invetigate the rictional orce and the phyical interpretation o the coeicient o riction. We will mae ue o the concept o the orce o gravity, the normal

More information

Newton s Laws. A force is simply a push or a pull. Forces are vectors; they have both size and direction.

Newton s Laws. A force is simply a push or a pull. Forces are vectors; they have both size and direction. Newton Law Newton firt law: An object will tay at ret or in a tate of uniform motion with contant velocity, in a traight line, unle acted upon by an external force. In other word, the bodie reit any change

More information

2. METHOD DATA COLLECTION

2. METHOD DATA COLLECTION Key to learning in pecific ubject area of engineering education an example from electrical engineering Anna-Karin Cartenen,, and Jonte Bernhard, School of Engineering, Jönköping Univerity, S- Jönköping,

More information

Quadrilaterals. Learning Objectives. Pre-Activity

Quadrilaterals. Learning Objectives. Pre-Activity Section 3.4 Pre-Activity Preparation Quadrilateral Intereting geometric hape and pattern are all around u when we tart looking for them. Examine a row of fencing or the tiling deign at the wimming pool.

More information

Chapter and. FIGURE 9 36 The deviation of an actual gas-turbine cycle from the ideal Brayton cycle as a result of irreversibilities.

Chapter and. FIGURE 9 36 The deviation of an actual gas-turbine cycle from the ideal Brayton cycle as a result of irreversibilities. Chapter 9 The thermal efficiency could alo be determined from where h th q out q out h h 789.7 00.9 89. kj>kg Dicuion Under the cold-air-tard aumption (contant pecific heat value at room temperature),

More information

Candy Phylogeny Lab. Procedure:

Candy Phylogeny Lab. Procedure: Candy Phylogeny Lab Material Candy Bar (2 each) o Baby Ruth o Reee Piece o rhey Cookie and Cream o Snicker Cruncher o Snicker o MM Peanut o MM Plain o rhey o rhey Almond o Skittle Picture of Candy Bar

More information

MA 408 Homework m. f(p ) = f ((x p, mx p + b)) = s, and. f(q) = f (x q, mx q + b) = x q 1 + m2. By our assumption that f(p ) = f(q), we have

MA 408 Homework m. f(p ) = f ((x p, mx p + b)) = s, and. f(q) = f (x q, mx q + b) = x q 1 + m2. By our assumption that f(p ) = f(q), we have MA 408 Homework 4 Remark 0.1. When dealing with coordinate function, I continually ue the expreion ditance preerving throughout. Thi mean that you can calculate the ditance in the geometry P Q or you can

More information

Name: SID: Instructions

Name: SID: Instructions CS168 Fall 2014 Homework 1 Aigned: Wedneday, 10 September 2014 Due: Monday, 22 September 2014 Name: SID: Dicuion Section (Day/Time): Intruction - Submit thi homework uing Pandagrader/GradeScope(http://www.gradecope.com/

More information

ECE 320 Energy Conversion and Power Electronics Dr. Tim Hogan. Chapter 7: Synchronous Machines and Drives (Textbook Chapter 5)

ECE 320 Energy Conversion and Power Electronics Dr. Tim Hogan. Chapter 7: Synchronous Machines and Drives (Textbook Chapter 5) ECE 30 Energy Converion and Power Electronic Dr. Tim Hogan Chapter 7: ynchronou Machine and Drive (Textbook Chapter 5) Chapter Objective For induction machine, a the rotor approache ynchronou peed, the

More information

Partial optimal labeling search for a NP-hard subclass of (max,+) problems

Partial optimal labeling search for a NP-hard subclass of (max,+) problems Partial optimal labeling earch for a NP-hard ubcla of (max,+) problem Ivan Kovtun International Reearch and Training Center of Information Technologie and Sytem, Kiev, Uraine, ovtun@image.iev.ua Dreden

More information

A note on profit maximization and monotonicity for inbound call centers

A note on profit maximization and monotonicity for inbound call centers A note on profit maximization and monotonicity for inbound call center Ger Koole & Aue Pot Department of Mathematic, Vrije Univeriteit Amterdam, The Netherland 23rd December 2005 Abtract We conider an

More information

Project Management Basics

Project Management Basics Project Management Baic A Guide to undertanding the baic component of effective project management and the key to ucce 1 Content 1.0 Who hould read thi Guide... 3 1.1 Overview... 3 1.2 Project Management

More information

FEDERATION OF ARAB SCIENTIFIC RESEARCH COUNCILS

FEDERATION OF ARAB SCIENTIFIC RESEARCH COUNCILS Aignment Report RP/98-983/5/0./03 Etablihment of cientific and technological information ervice for economic and ocial development FOR INTERNAL UE NOT FOR GENERAL DITRIBUTION FEDERATION OF ARAB CIENTIFIC

More information

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science

Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science aachuett Intitute of Technology Department of Electrical Engineering and Computer Science 6.685 Electric achinery Cla Note 10: Induction achine Control and Simulation c 2003 Jame L. Kirtley Jr. 1 Introduction

More information

A PROPERTY OF MULTINOMIAL COEFFICIENTS

A PROPERTY OF MULTINOMIAL COEFFICIENTS A PROPERTY OF MULTINOMIAL COEFFICIENTS V.E. HOGGATT, JR. San Joe State College, San Joe, California and G. L ALEXANDERSON Univerity of Santa Clara, Santa Clara, California ABSTRACT The ultinoial coefficient

More information

CASE STUDY ALLOCATE SOFTWARE

CASE STUDY ALLOCATE SOFTWARE CASE STUDY ALLOCATE SOFTWARE allocate caetud y TABLE OF CONTENTS #1 ABOUT THE CLIENT #2 OUR ROLE #3 EFFECTS OF OUR COOPERATION #4 BUSINESS PROBLEM THAT WE SOLVED #5 CHALLENGES #6 WORKING IN SCRUM #7 WHAT

More information

MSc Financial Economics: International Finance. Bubbles in the Foreign Exchange Market. Anne Sibert. Revised Spring 2013. Contents

MSc Financial Economics: International Finance. Bubbles in the Foreign Exchange Market. Anne Sibert. Revised Spring 2013. Contents MSc Financial Economic: International Finance Bubble in the Foreign Exchange Market Anne Sibert Revied Spring 203 Content Introduction................................................. 2 The Mone Market.............................................

More information

Report 4668-1b 30.10.2010. Measurement report. Sylomer - field test

Report 4668-1b 30.10.2010. Measurement report. Sylomer - field test Report 4668-1b Meaurement report Sylomer - field tet Report 4668-1b 2(16) Contet 1 Introduction... 3 1.1 Cutomer... 3 1.2 The ite and purpoe of the meaurement... 3 2 Meaurement... 6 2.1 Attenuation of

More information

Abstract parsing: static analysis of dynamically generated string output using LR-parsing technology

Abstract parsing: static analysis of dynamically generated string output using LR-parsing technology Abtract paring: tatic analyi of dynamically generated tring output uing LR-paring technology Kyung-Goo Doh 1, Hyunha Kim 1, David A. Schmidt 2 1 Hanyang Univerity, Anan, South Korea 2 Kana State Univerity,

More information

Recall the commutative and associative properties of multiplication. The Commutative Property of Multiplication. If a and b are any integers,

Recall the commutative and associative properties of multiplication. The Commutative Property of Multiplication. If a and b are any integers, 6 MODULE 2. FUNDAMENTALS OF ALGEBRA 2b Order of Operation Simplifying Algebraic Expreion Recall the commutative and aociative propertie of multiplication. The Commutative Property of Multiplication. If

More information

12.4 Problems. Excerpt from "Introduction to Geometry" 2014 AoPS Inc. Copyrighted Material CHAPTER 12. CIRCLES AND ANGLES

12.4 Problems. Excerpt from Introduction to Geometry 2014 AoPS Inc.  Copyrighted Material CHAPTER 12. CIRCLES AND ANGLES HTER 1. IRLES N NGLES Excerpt from "Introduction to Geometry" 014 os Inc. onider the circle with diameter O. all thi circle. Why mut hit O in at leat two di erent point? (b) Why i it impoible for to hit

More information

of absorption transitions (1, 2) and the mean rate of visits to state or are, respectively, J.=

of absorption transitions (1, 2) and the mean rate of visits to state or are, respectively, J.= Proc. Natl. Acad. Sci. USA Vol. 85, pp. 4577-4581, July 1988 Applied Mathematical Science Number of viit to a tate in a random walk, before aborption, and related topic (kinetic dim/multitate directional

More information

A technical guide to 2014 key stage 2 to key stage 4 value added measures

A technical guide to 2014 key stage 2 to key stage 4 value added measures A technical guide to 2014 key tage 2 to key tage 4 value added meaure CONTENTS Introduction: PAGE NO. What i value added? 2 Change to value added methodology in 2014 4 Interpretation: Interpreting chool

More information

Chapter 4: Mean-Variance Analysis

Chapter 4: Mean-Variance Analysis Chapter 4: Mean-Variance Analyi Modern portfolio theory identifie two apect of the invetment problem. Firt, an invetor will want to maximize the expected rate of return on the portfolio. Second, an invetor

More information

CHARACTERISTICS OF WAITING LINE MODELS THE INDICATORS OF THE CUSTOMER FLOW MANAGEMENT SYSTEMS EFFICIENCY

CHARACTERISTICS OF WAITING LINE MODELS THE INDICATORS OF THE CUSTOMER FLOW MANAGEMENT SYSTEMS EFFICIENCY Annale Univeritati Apuleni Serie Oeconomica, 2(2), 200 CHARACTERISTICS OF WAITING LINE MODELS THE INDICATORS OF THE CUSTOMER FLOW MANAGEMENT SYSTEMS EFFICIENCY Sidonia Otilia Cernea Mihaela Jaradat 2 Mohammad

More information

FORMAL LANGUAGES, AUTOMATA AND COMPUTATION

FORMAL LANGUAGES, AUTOMATA AND COMPUTATION FORMAL LANGUAGES, AUTOMATA AND COMPUTATION REDUCIBILITY ( LECTURE 16) SLIDES FOR 15-453 SPRING 2011 1 / 20 THE LANDSCAPE OF THE CHOMSKY HIERARCHY ( LECTURE 16) SLIDES FOR 15-453 SPRING 2011 2 / 20 REDUCIBILITY

More information

322 CHAPTER 11 Motion and Momentum Telegraph Colour Library/FPG/Getty Images

322 CHAPTER 11 Motion and Momentum Telegraph Colour Library/FPG/Getty Images Standard 7.7.4: Ue ymbolic equation to how how the quantity of omething change over time or in repone to change in other quantitie. Alo cover: 7.2.6, 7.2.7 (Detailed tandard begin on page IN8.) What i

More information

Ch. 22 Electromagnetic Induction

Ch. 22 Electromagnetic Induction Ch. 22 Electromagnetic Induction 22.1 Induced emf So electric current (moving charge) create agnetic Field. I the revere true? Can magnetic field create current??? D Ye!!! ut it take a changing magnetic

More information

Optimization Model of Higher Education Resources Allocation Based on Genetic Algorithm

Optimization Model of Higher Education Resources Allocation Based on Genetic Algorithm Management cience and ngineering Vol. 7, No. 3, 203, pp. 76-80 DOI:0.3968/j.me.93035X2030703.2622 IN 93-034 [Print] IN 93-035X [Online] www.ccanada.net www.ccanada.org Optimization Model of Higher ducation

More information

Queueing systems with scheduled arrivals, i.e., appointment systems, are typical for frontal service systems,

Queueing systems with scheduled arrivals, i.e., appointment systems, are typical for frontal service systems, MANAGEMENT SCIENCE Vol. 54, No. 3, March 28, pp. 565 572 in 25-199 ein 1526-551 8 543 565 inform doi 1.1287/mnc.17.82 28 INFORMS Scheduling Arrival to Queue: A Single-Server Model with No-Show INFORMS

More information

Mixed Method of Model Reduction for Uncertain Systems

Mixed Method of Model Reduction for Uncertain Systems SERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol 4 No June Mixed Method of Model Reduction for Uncertain Sytem N Selvaganean Abtract: A mixed method for reducing a higher order uncertain ytem to a table reduced

More information

The quartz crystal model and its frequencies 4,000 3,000 2,000. Reactance X [ohms] 1,000 -1,000 -2,000

The quartz crystal model and its frequencies 4,000 3,000 2,000. Reactance X [ohms] 1,000 -1,000 -2,000 TEHNIA NOTE 3 The quartz crytal model and it frequencie. Introduction The region between and i a region of poitive In thi note, we preent ome of the baic electrical propertie of quartz crytal. In particular,

More information

Simulation on Stern-Rudder Independent Control for Submarine Motion in a Vertical Plane

Simulation on Stern-Rudder Independent Control for Submarine Motion in a Vertical Plane BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 15, No 6 Special Iue on Logitic, Informatic and Service Science Sofia 2015 Print ISSN: 1311-9702; Online ISSN: 1314-4081 DOI:

More information

DISTRIBUTED DATA PARALLEL TECHNIQUES FOR CONTENT-MATCHING INTRUSION DETECTION SYSTEMS. G. Chapman J. Cleese E. Idle

DISTRIBUTED DATA PARALLEL TECHNIQUES FOR CONTENT-MATCHING INTRUSION DETECTION SYSTEMS. G. Chapman J. Cleese E. Idle DISTRIBUTED DATA PARALLEL TECHNIQUES FOR CONTENT-MATCHING INTRUSION DETECTION SYSTEMS G. Chapman J. Cleee E. Idle ABSTRACT Content matching i a neceary component of any ignature-baed network Intruion Detection

More information

Processor Cooling. Report for the practical course Chemieingenieurwesen I WS06/07. Zürich, January 16,

Processor Cooling. Report for the practical course Chemieingenieurwesen I WS06/07. Zürich, January 16, Proceor Cooling Report for the practical coure Chemieingenieurween I WS06/07 Zürich, January 16, 2007 Student: Francico Joé Guerra Millán fguerram@tudent.ethz.ch Andrea Michel michela@tudent.ethz.ch Aitant:

More information

Solution of the Heat Equation for transient conduction by LaPlace Transform

Solution of the Heat Equation for transient conduction by LaPlace Transform Solution of the Heat Equation for tranient conduction by LaPlace Tranform Thi notebook ha been written in Mathematica by Mark J. McCready Profeor and Chair of Chemical Engineering Univerity of Notre Dame

More information

DISTRIBUTED DATA PARALLEL TECHNIQUES FOR CONTENT-MATCHING INTRUSION DETECTION SYSTEMS

DISTRIBUTED DATA PARALLEL TECHNIQUES FOR CONTENT-MATCHING INTRUSION DETECTION SYSTEMS DISTRIBUTED DATA PARALLEL TECHNIQUES FOR CONTENT-MATCHING INTRUSION DETECTION SYSTEMS Chritopher V. Kopek Department of Computer Science Wake Foret Univerity Winton-Salem, NC, 2709 Email: kopekcv@gmail.com

More information

Chapter 10 Stocks and Their Valuation ANSWERS TO END-OF-CHAPTER QUESTIONS

Chapter 10 Stocks and Their Valuation ANSWERS TO END-OF-CHAPTER QUESTIONS Chapter Stoc and Their Valuation ANSWERS TO EN-OF-CHAPTER QUESTIONS - a. A proxy i a document giving one peron the authority to act for another, typically the power to vote hare of common toc. If earning

More information

Pekka Helkiö, 58490K Antti Seppälä, 63212W Ossi Syd, 63513T

Pekka Helkiö, 58490K Antti Seppälä, 63212W Ossi Syd, 63513T Pekka Helkiö, 58490K Antti Seppälä, 63212W Oi Syd, 63513T Table of Content 1. Abtract...1 2. Introduction...2 2.1 Background... 2 2.2 Objective and Reearch Problem... 2 2.3 Methodology... 2 2.4 Scoping

More information

TIME SERIES ANALYSIS AND TRENDS BY USING SPSS PROGRAMME

TIME SERIES ANALYSIS AND TRENDS BY USING SPSS PROGRAMME TIME SERIES ANALYSIS AND TRENDS BY USING SPSS PROGRAMME RADMILA KOCURKOVÁ Sileian Univerity in Opava School of Buine Adminitration in Karviná Department of Mathematical Method in Economic Czech Republic

More information

Culture, Identity and Sociability (Design of a Flemish cultural centre) De Brakke Grond

Culture, Identity and Sociability (Design of a Flemish cultural centre) De Brakke Grond Overview of the courtyard Square Overview from Ne De Brakke Grond a a Culture Center B De Brakke Grond a a Flemih Culture Center in Amterdam, a my undertanding, i for contemporary art and performance,

More information

Experiment 3. Filters II Filter Design with MATLAB

Experiment 3. Filters II Filter Design with MATLAB Experiment 3 Filter II Filter Deign with MATLAB The objective o thi experiment i to gain ome experience in deigning ilter with deired peciication. You will work with a number o tool helping you in deigning

More information

Harmonic Oscillations / Complex Numbers

Harmonic Oscillations / Complex Numbers Harmonic Ocillation / Complex Number Overview and Motivation: Probably the ingle mot important problem in all of phyic i the imple harmonic ocillator. It can be tudied claically or uantum mechanically,

More information

Laboratory 3 Diode Characteristics

Laboratory 3 Diode Characteristics Laboratory 3 Diode Characteritic BACKGROUND A diode i a non-linear, two terminal emiconductor device. he two terminal are the anode and the cathode. he circuit ymbol of a diode i depicted in Fig. 3-1.

More information

Three Phase Theory - Professor J R Lucas

Three Phase Theory - Professor J R Lucas Three Phae Theory - Profeor J Luca A you are aware, to tranit power with ingle phae alternating current, we need two wire live wire and neutral. However you would have een that ditribution line uually

More information

Heat transfer to or from a fluid flowing through a tube

Heat transfer to or from a fluid flowing through a tube Heat tranfer to or from a fluid flowing through a tube R. Shankar Subramanian A common ituation encountered by the chemical engineer i heat tranfer to fluid flowing through a tube. Thi can occur in heat

More information

Scheduling of Jobs and Maintenance Activities on Parallel Machines

Scheduling of Jobs and Maintenance Activities on Parallel Machines Scheduling of Job and Maintenance Activitie on Parallel Machine Chung-Yee Lee* Department of Indutrial Engineering Texa A&M Univerity College Station, TX 77843-3131 cylee@ac.tamu.edu Zhi-Long Chen** Department

More information

STUDY ON THE EFFECT OF COOLING WATER TEMPERATURE RISE ON LOSS FACTOR AND EFFICIENCY OF A CONDENSER FOR A 210 MW THERMAL POWER UNIT

STUDY ON THE EFFECT OF COOLING WATER TEMPERATURE RISE ON LOSS FACTOR AND EFFICIENCY OF A CONDENSER FOR A 210 MW THERMAL POWER UNIT International Journal of Emerging Technology and Advanced Engineering Volume 3, Special Iue 3: ICERTSD 2013, Feb 2013, page 485-489 An ISO 9001:2008 certified Int. Journal, ISSN 2250-2459, available online

More information

Announcing the ADVANCED ENCRYPTION STANDARD (AES)

Announcing the ADVANCED ENCRYPTION STANDARD (AES) Federal Information Proceing Standard Publication 197 November 26, 2001 Announcing the ADVANCED ENCRYPTION STANDARD (AES) Federal Information Proceing Standard Publication (FIPS PUBS) are iued by the National

More information

A Note on Profit Maximization and Monotonicity for Inbound Call Centers

A Note on Profit Maximization and Monotonicity for Inbound Call Centers OPERATIONS RESEARCH Vol. 59, No. 5, September October 2011, pp. 1304 1308 in 0030-364X ein 1526-5463 11 5905 1304 http://dx.doi.org/10.1287/opre.1110.0990 2011 INFORMS TECHNICAL NOTE INFORMS hold copyright

More information

DIHEDRAL GROUPS KEITH CONRAD

DIHEDRAL GROUPS KEITH CONRAD DIHEDRAL GROUPS KEITH CONRAD 1. Introduction For n 3, the dihedral group D n i defined a the rigid motion 1 of the plane preerving a regular n-gon, with the operation being compoition. Thee polygon for

More information

No. 73,122 MODEL FORM OF VERDICT ITEMIZING PERSONAL INJURY DAMAGES (TORT REFORM ACT OF 1986, S 768.77 F.S. 1987)

No. 73,122 MODEL FORM OF VERDICT ITEMIZING PERSONAL INJURY DAMAGES (TORT REFORM ACT OF 1986, S 768.77 F.S. 1987) CORRECTED OPINION No. 73,122 IN RE: STANDARD JURY INSTRUCTIONS (CIVIL CASES 88-2) [March 2, 19891 PER CURIAM. The Florida Supreme Court Committee on Standard Jury Intruction (Civil) ha recommended to thi

More information

Lab 4: Motor Control

Lab 4: Motor Control 2.017 Deign of Electromechanical Robotic Sytem, Fall 2009 Lab 4: Motor Control Aigned: 10/5/09 1 Overview So far we have learnt how to ue the Arduino to acquire variou type of ignal from enor uch a the

More information

CASE STUDY BRIDGE. www.future-processing.com

CASE STUDY BRIDGE. www.future-processing.com CASE STUDY BRIDGE TABLE OF CONTENTS #1 ABOUT THE CLIENT 3 #2 ABOUT THE PROJECT 4 #3 OUR ROLE 5 #4 RESULT OF OUR COLLABORATION 6-7 #5 THE BUSINESS PROBLEM THAT WE SOLVED 8 #6 CHALLENGES 9 #7 VISUAL IDENTIFICATION

More information

Factoring Finite State Machines

Factoring Finite State Machines Chapter 17 Factoring Finite State Machine Factoring a tate machine i the proce of plitting the machine into two or more impler machine. Factoring can greatly implify the deign of a tate machine by eparating

More information

CHAPTER 5 BROADBAND CLASS-E AMPLIFIER

CHAPTER 5 BROADBAND CLASS-E AMPLIFIER CHAPTER 5 BROADBAND CLASS-E AMPLIFIER 5.0 Introduction Cla-E amplifier wa firt preented by Sokal in 1975. The application of cla- E amplifier were limited to the VHF band. At thi range of frequency, cla-e

More information

Chapter 32. OPTICAL IMAGES 32.1 Mirrors

Chapter 32. OPTICAL IMAGES 32.1 Mirrors Chapter 32 OPTICAL IMAGES 32.1 Mirror The point P i called the image or the virtual image of P (light doe not emanate from it) The left-right reveral in the mirror i alo called the depth inverion (the

More information

Mobile Network Configuration for Large-scale Multimedia Delivery on a Single WLAN

Mobile Network Configuration for Large-scale Multimedia Delivery on a Single WLAN Mobile Network Configuration for Large-cale Multimedia Delivery on a Single WLAN Huigwang Je, Dongwoo Kwon, Hyeonwoo Kim, and Hongtaek Ju Dept. of Computer Engineering Keimyung Univerity Daegu, Republic

More information

No. 51. R.E. Woodrow. In the November 2000 number of the Corner we gave the problems of. Junior High School Mathematics Contest

No. 51. R.E. Woodrow. In the November 2000 number of the Corner we gave the problems of. Junior High School Mathematics Contest 7 THE SKOLIAD CORNER No. 51 R.E. Woodrow In the November 000 number of the Corner we gave the problem of the Final Round of the Britih Columbia College Junior High School Mathematic Contet, May 5, 000.

More information

BUILT-IN DUAL FREQUENCY ANTENNA WITH AN EMBEDDED CAMERA AND A VERTICAL GROUND PLANE

BUILT-IN DUAL FREQUENCY ANTENNA WITH AN EMBEDDED CAMERA AND A VERTICAL GROUND PLANE Progre In Electromagnetic Reearch Letter, Vol. 3, 51, 08 BUILT-IN DUAL FREQUENCY ANTENNA WITH AN EMBEDDED CAMERA AND A VERTICAL GROUND PLANE S. H. Zainud-Deen Faculty of Electronic Engineering Menoufia

More information

RISK MANAGEMENT POLICY

RISK MANAGEMENT POLICY RISK MANAGEMENT POLICY The practice of foreign exchange (FX) rik management i an area thrut into the potlight due to the market volatility that ha prevailed for ome time. A a conequence, many corporation

More information

Lean Warehouse: Low-Hanging Fruit

Lean Warehouse: Low-Hanging Fruit Chapter 8 Lean Warehoue: Low-Hanging Fruit Lean i till in it early tage in upply chain and logitic, o it i ometime difficult finding a place to tart it. A place that many companie have found a a good place

More information

Adult/Gerontology Primary Care Nurse Practitioner Program at UCLA School of Nursing

Adult/Gerontology Primary Care Nurse Practitioner Program at UCLA School of Nursing Adult/Gerontology Primary Care Nure Practitioner Program at UCLA School of Nuring Overview: The Adult/Gerontology Primary Care Nure Practitioner (AGNP) i a Regitered Nure educated at the Mater level a

More information

Physical Properties of Soils and Compaction

Physical Properties of Soils and Compaction Soil Mechanic Phyical Propertie of Soil and Compaction page 1 Content of thi chapter : CHAPITRE 2. PHYSICAL PROPERTIES OF SOILS AND COMPACTION...1 2.1 UNITS...1 2.2 BASIC DEFINITIONS AND TERMINOLOGY...2

More information

Sharps and Flats Any note sharp or flat may have 2 names.if you move up 1 fret from F, the note is raised in pitch.this makes the note sharp.

Sharps and Flats Any note sharp or flat may have 2 names.if you move up 1 fret from F, the note is raised in pitch.this makes the note sharp. YOU CAN PLAY GUITAR - BASS GUITAR BOOK BY SCOTT MORRIS INTRODUCTION... Below i an eay to follow diagram, that will teach you the name of the note played on the ba guitar. The number hown on top, indicate

More information

Bi-Objective Optimization for the Clinical Trial Supply Chain Management

Bi-Objective Optimization for the Clinical Trial Supply Chain Management Ian David Lockhart Bogle and Michael Fairweather (Editor), Proceeding of the 22nd European Sympoium on Computer Aided Proce Engineering, 17-20 June 2012, London. 2012 Elevier B.V. All right reerved. Bi-Objective

More information

SCM- integration: organiational, managerial and technological iue M. Caridi 1 and A. Sianei 2 Dipartimento di Economia e Produzione, Politecnico di Milano, Italy E-mail: maria.caridi@polimi.it Itituto

More information

Introduction to Finite Automata

Introduction to Finite Automata Introduction to Finite Automata Our First Machine Model Captain Pedro Ortiz Department of Computer Science United States Naval Academy SI-340 Theory of Computing Fall 2012 Captain Pedro Ortiz (US Naval

More information

MECH 2110 - Statics & Dynamics

MECH 2110 - Statics & Dynamics Chapter D Problem 3 Solution 1/7/8 1:8 PM MECH 11 - Static & Dynamic Chapter D Problem 3 Solution Page 7, Engineering Mechanic - Dynamic, 4th Edition, Meriam and Kraige Given: Particle moving along a traight

More information

4.1 Radian and Degree Measure

4.1 Radian and Degree Measure 4. Radian and Degree Meaure An angle AOB (notation: AOB ) conit of two ray R and R with a common vertex O (ee Figure below). We often interpret an angle a a rotation of the ray R onto R. In thi cae, R

More information

Assessing the Discriminatory Power of Credit Scores

Assessing the Discriminatory Power of Credit Scores Aeing the Dicriminatory Power of Credit Score Holger Kraft 1, Gerald Kroiandt 1, Marlene Müller 1,2 1 Fraunhofer Intitut für Techno- und Wirtchaftmathematik (ITWM) Gottlieb-Daimler-Str. 49, 67663 Kaierlautern,

More information

Basic Quantum Mechanics in Coordinate, Momentum and Phase Space

Basic Quantum Mechanics in Coordinate, Momentum and Phase Space Baic Quantum Mechanic in Coorinate, Momentum an Phae Space Frank Rioux Department of Chemitry College of St. Beneict St. Johnʹ Univerity The purpoe of thi paper i to ue calculation on the harmonic ocillator

More information

Achieving Quality Through Problem Solving and Process Improvement

Achieving Quality Through Problem Solving and Process Improvement Quality Aurance Methodology Refinement Serie Achieving Quality Through Problem Solving and Proce Improvement Second Edition By Lynne Miller Franco Jeanne Newman Gaël Murphy Elizabeth Mariani Quality Aurance

More information

1 Safe Drivers versus Reckless Drunk Drivers

1 Safe Drivers versus Reckless Drunk Drivers ECON 301: General Equilibrium IV (Externalitie) 1 Intermediate Microeconomic II, ECON 301 General Equilibrium IV: Externalitie In our dicuion thu far, we have implicitly aumed that all good can be traded

More information

Chapter 5: Design of IIR Filters

Chapter 5: Design of IIR Filters EEE35, EEE8 Part A : Digital Signal Proceing Chapter 5 Deign of IIR Filter 5. Introduction IIR filter deign primarily concentrate on the magnitude repone of the filter and regard the phae repone a econdary.

More information

Progress 8 measure in 2016, 2017, and 2018. Guide for maintained secondary schools, academies and free schools

Progress 8 measure in 2016, 2017, and 2018. Guide for maintained secondary schools, academies and free schools Progre 8 meaure in 2016, 2017, and 2018 Guide for maintained econdary chool, academie and free chool July 2016 Content Table of figure 4 Summary 5 A ummary of Attainment 8 and Progre 8 5 Expiry or review

More information

Stochasticity in Transcriptional Regulation: Origins, Consequences, and Mathematical Representations

Stochasticity in Transcriptional Regulation: Origins, Consequences, and Mathematical Representations 36 Biophyical Journal Volume 8 December 200 36 336 Stochaticity in Trancriptional Regulation: Origin, Conequence, and Mathematical Repreentation Thoma B. Kepler* and Timothy C. Elton *Santa Fe Intitute,

More information

Ohm s Law. Ohmic relationship V=IR. Electric Power. Non Ohmic devises. Schematic representation. Electric Power

Ohm s Law. Ohmic relationship V=IR. Electric Power. Non Ohmic devises. Schematic representation. Electric Power Ohm Law Ohmic relationhip V=IR Ohm law tate that current through the conductor i directly proportional to the voltage acro it if temperature and other phyical condition do not change. In many material,

More information

IMPORTANT: Read page 2 ASAP. *Please feel free to email (longo.physics@gmail.com) me at any time if you have questions or concerns.

IMPORTANT: Read page 2 ASAP. *Please feel free to email (longo.physics@gmail.com) me at any time if you have questions or concerns. rev. 05/4/16 AP Phyic C: Mechanic Summer Aignment 016-017 Mr. Longo Foret Park HS longo.phyic@gmail.com longodb@pwc.edu Welcome to AP Phyic C: Mechanic. The purpoe of thi ummer aignment i to give you a

More information

REDUCTION OF TOTAL SUPPLY CHAIN CYCLE TIME IN INTERNAL BUSINESS PROCESS OF REAMER USING DOE AND TAGUCHI METHODOLOGY. Abstract. 1.

REDUCTION OF TOTAL SUPPLY CHAIN CYCLE TIME IN INTERNAL BUSINESS PROCESS OF REAMER USING DOE AND TAGUCHI METHODOLOGY. Abstract. 1. International Journal of Advanced Technology & Engineering Reearch (IJATER) REDUCTION OF TOTAL SUPPLY CHAIN CYCLE TIME IN INTERNAL BUSINESS PROCESS OF REAMER USING DOE AND Abtract TAGUCHI METHODOLOGY Mr.

More information

published in Statistics and Probability Letters, 78, , 2008 Michael Lechner * SIAW

published in Statistics and Probability Letters, 78, , 2008 Michael Lechner * SIAW publihed in Statitic and Probability Letter, 78, 9-95, 28 A NOTE ON ENDOGENOUS CONTROL VARIABLES IN CAUSAL STUDIES Michael Lechner * SIAW Thi verion: March, 27 Date thi verion ha been printed: 8 May 27

More information

Tracking Control and Adaptive Local Navigation for Nonholonomic Mobile Robots

Tracking Control and Adaptive Local Navigation for Nonholonomic Mobile Robots Tracking Control and Adaptive Local Navigation for Nonholonomic Mobile Robot Alexander Mojaev Andrea Zell Univerity of Tuebingen, Computer Science Dept., Computer Architecture, Sand, D - 776 Tuebingen,

More information

Formal Languages and Automata Theory - Regular Expressions and Finite Automata -

Formal Languages and Automata Theory - Regular Expressions and Finite Automata - Formal Languages and Automata Theory - Regular Expressions and Finite Automata - Samarjit Chakraborty Computer Engineering and Networks Laboratory Swiss Federal Institute of Technology (ETH) Zürich March

More information

Algorithms for Advance Bandwidth Reservation in Media Production Networks

Algorithms for Advance Bandwidth Reservation in Media Production Networks Algorithm for Advance Bandwidth Reervation in Media Production Network Maryam Barhan 1, Hendrik Moen 1, Jeroen Famaey 2, Filip De Turck 1 1 Department of Information Technology, Ghent Univerity imind Gaton

More information

Performance of a Browser-Based JavaScript Bandwidth Test

Performance of a Browser-Based JavaScript Bandwidth Test Performance of a Brower-Baed JavaScript Bandwidth Tet David A. Cohen II May 7, 2013 CP SC 491/H495 Abtract An exiting brower-baed bandwidth tet written in JavaScript wa modified for the purpoe of further

More information

The Import-Export Paradigm for High-Quality College Courses

The Import-Export Paradigm for High-Quality College Courses Public Policy Editor: Stephen Ruth ruth@gmu.edu The Import-Export Paradigm for High-Quality College Coure An Anwer to Tuition Through-the- Roof Cot Spiral? Stephen Ruth George Maon Univerity Three new

More information

Critical issues in wind turbine design (Uncertainties) IEA-meeting Trondheim, Norway June 14-15 2005

Critical issues in wind turbine design (Uncertainties) IEA-meeting Trondheim, Norway June 14-15 2005 Critical iue in wind turbine deign (Uncertaintie) IEA-meeting Trondheim, Norway June 4-5 005 Proect idea: To ignificantly improve deign bai for offhore wind turbine by: Analying all deign proce component

More information

Block Diagrams, State-Variable Models, and Simulation Methods

Block Diagrams, State-Variable Models, and Simulation Methods 5 C H A P T E R Block Diagram, State-Variable Model, and Simulation Method CHAPTER OUTLINE CHAPTER OBJECTIVES Part I. Model Form 25 5. Tranfer Function and Block Diagram Model 25 5.2 State-Variable Model

More information

naifa Members: SERVING AMERICA S NEIGHBORHOODS FOR 120 YEARS

naifa Members: SERVING AMERICA S NEIGHBORHOODS FOR 120 YEARS naifa Member: SERVING AMERICA S NEIGHBORHOODS FOR 120 YEARS National Aociation of Inurance and Financial Advior Serving America Neigborhood for Over 120 Year Since 1890, NAIFA ha worked to afeguard the

More information

T-test for dependent Samples. Difference Scores. The t Test for Dependent Samples. The t Test for Dependent Samples. s D

T-test for dependent Samples. Difference Scores. The t Test for Dependent Samples. The t Test for Dependent Samples. s D The t Tet for ependent Sample T-tet for dependent Sample (ak.a., Paired ample t-tet, Correlated Group eign, Within- Subject eign, Repeated Meaure,.. Repeated-Meaure eign When you have two et of core from

More information

Turing Machines: An Introduction

Turing Machines: An Introduction CIT 596 Theory of Computation 1 We have seen several abstract models of computing devices: Deterministic Finite Automata, Nondeterministic Finite Automata, Nondeterministic Finite Automata with ɛ-transitions,

More information

Automata and Languages

Automata and Languages Automata and Languages Computational Models: An idealized mathematical model of a computer. A computational model may be accurate in some ways but not in others. We shall be defining increasingly powerful

More information

Progress 8 and Attainment 8 measure in 2016, 2017, and Guide for maintained secondary schools, academies and free schools

Progress 8 and Attainment 8 measure in 2016, 2017, and Guide for maintained secondary schools, academies and free schools Progre 8 and Attainment 8 meaure in 2016, 2017, and 2018 Guide for maintained econdary chool, academie and free chool October 2016 Content Table of figure 4 Summary 5 A ummary of Attainment 8 and Progre

More information

Periodic Symmetric Functions and Addition Related Arithmetic Operations in Single Electron Tunneling Technology

Periodic Symmetric Functions and Addition Related Arithmetic Operations in Single Electron Tunneling Technology Periodic Symmetric Function and Addition Related Arithmetic Operation in Single Electron Tunneling Technology or Meenderinck Sorin otofana omputer Engineering Lab, Delft Univerity of Technology, Delft,

More information

A Spam Message Filtering Method: focus on run time

A Spam Message Filtering Method: focus on run time , pp.29-33 http://dx.doi.org/10.14257/atl.2014.76.08 A Spam Meage Filtering Method: focu on run time Sin-Eon Kim 1, Jung-Tae Jo 2, Sang-Hyun Choi 3 1 Department of Information Security Management 2 Department

More information

Progress 8 and Attainment 8 measure in 2016, 2017, and 2018. Guide for maintained secondary schools, academies and free schools

Progress 8 and Attainment 8 measure in 2016, 2017, and 2018. Guide for maintained secondary schools, academies and free schools Progre 8 and Attainment 8 meaure in 2016, 2017, and 2018 Guide for maintained econdary chool, academie and free chool September 2016 Content Table of figure 4 Summary 5 A ummary of Attainment 8 and Progre

More information

Queueing Models for Multiclass Call Centers with Real-Time Anticipated Delays

Queueing Models for Multiclass Call Centers with Real-Time Anticipated Delays Queueing Model for Multicla Call Center with Real-Time Anticipated Delay Oualid Jouini Yve Dallery Zeynep Akşin Ecole Centrale Pari Koç Univerity Laboratoire Génie Indutriel College of Adminitrative Science

More information

Laboratory Exercise 1

Laboratory Exercise 1 Laboratory Exercie Switche, Light, and Multiplexer The purpoe of thi exercie i to learn how to connect iple input and output device to an FPGA chip and ipleent a circuit that ue thee device. We will ue

More information