Measuring Magneto Energy Output and Inductance Revision 1

Size: px
Start display at page:

Download "Measuring Magneto Energy Output and Inductance Revision 1"

Transcription

1 Measurig Mageto Eergy Output ad Iductace evisio Itroductio A mageto is fudametally a iductor that is mechaically charged with a iitial curret value. That iitial curret is produced by movemet of the rotor while the primary coil is shorted by mechaical (or electroic) igitio poits. Iductors ted to maitai curret flow whe the poits ope, the stored iductive eergy discharges ito a spark gap, igitig a combustible fuel mixture. Iductor curret steadily decreases as eergy is delivered to the spark from its magetic field. Durig the spark the output voltage is determied by the ature of the spark; it does ot deped upo the mageto itself. Spark discharge voltage is wildly variable, difficult to measure or to characterize. The istataeous output voltage does determie the rate of chage of output curret. Neither curret or voltage are well eough behaved to easily measure the output eergy directly. Oe method for measurig output eergy is to coect a appropriate resistor load across the spark gap to suppress the spark ad absorb the output eergy. The discharge will the occur i a predictable ad easily measured maer. This works well uder may coditios, but there are complicatios that will be discussed below. Measuremet Method for ow Tesio Mageto Ideally, output eergy of a low-tesio mageto would be measured by the followig method. Coect the mageto coil to quick-opeig iterrupter poits that are sychroized with the rotor. Time the poits to ope at the istat of maximum short circuit curret while the rotor turs at the desired operatig rotor speed. Coect a appropriate resistor to divert the coil curret so that there is o spark discharge at the cotact poits. ecord a table of samples of the discharge pulse with a recordig oscilloscope. Output power ad total eergy are calculated: N v v P = ad W = P, or W t The summatio form is used to calculate the itegral umerically from the table of sampled data. This method has two practical problems that must be dealt with. First is that the output voltage trasiet will be sufficiet to iduce a spark ayway if the rotor speed is high or if the resistor is large. The method is thus limited to low speed testig with relatively small resistace loads. Secod, the turig rotor geerates some voltage durig the discharge period, ad that voltage becomes the domiat part of the output voltage ear the ed of the trasiet decay. The method must therefore be refied to separate the rotor-geerated voltage from that produced by the iductorstored eergy. The schematic diagram below shows the discharge circuit after the poits ope with rotor-geerated voltage, vg, icluded. ow Tesio Mageto with resistor load copyright Doald K Grimm page of 5 May 7, 5

2 P = ( v vg ) i = ( v vg ) v N W = P, or W v ( v vg ) t The variable tables cotaiig v ad vg samples are recorded i two separate data rus with a digital samplig scope. v is measured with the switch operatig. vgis the ope circuit mageto-geerated voltage measured o the same time scale, usig the igitio poits to trigger the measuremet so the measuremet periods are coicidet. The two data files are liked directly to software i a Access program that calculates the eergy usig the uatios above. See the author for details about the Access program implemetatio. This residual geerated voltage, vg udoubtedly cotributes some eergy to the spark output above ad beyod the stored iductor eergy. That icremetal output eergy is ot calculated here. Uless oe ca characterize the time-voltage behavior of the spark, it is ot possible to calculate the magitude of the cotributio. For most situatios it appears to costitute a small bous eergy of relatively isigificat value, although exceptioal cases have bee see, especially with high-tesio magetos havig large coil turs ratios that greatly step up the rotor-geerated voltage. Calculatig ow Tesio Mageto Iductace ad Iductace-stored Eergy Aalysis of the iitial part of the discharge pulse ca provide additioal iformatio, icludig a measuremet of the mageto iductace ad a idepedet calculatio of stored iductor eergy. di v di v vg =, i =, ad = v vg = vg v = at t = T = at = W v i = = ( vg v ) v W t T Voltages v, vg, ad the slope of the discharge curve, the data sample tables recorded by the oscilloscope as above. ( vg v ) ad, ca all be obtaied from the early part of will both be egative the results will be positive. Be aware that oise o the sampled data will give ureliable results to these quatities uless the samples are appropriately smoothed over time. Eyeball estimates of these quatities from oscilloscope pictures ca give useful results. From oe or two examples so far, appears to be fairly costat for values of tthroughout the discharge iterval. vg i v copyright Doald K Grimm page of 5 May 7, 5

3 High Tesio Mageto Measuremets Voltage delivered to the spark plug by a high-tesio mageto geerally exceeds the breakdow voltage of stadard oscilloscope probes. Usig a high voltage probe with sufficiet rage, the measuremet methods developed above ca still be applied. However, as a practical matter, stadard istrumets ad probes may be used with a resistive voltage divider coected as show i the diagram. A atteuatio ratio i the order of : combied with typical hardware voltage limits of 3 volts will accommodate trasiets up to 3kv. As with the low-tesio mageto measuremets, two data files are recorded. The symbol vm i the uatios at right represets the operatig mageto output, ad vb represets the ope circuit voltage with the coil ope. Both files are sychroized by the mageto igitio poits so they have the same time base. The uatios show assume the atteuator cosistig of ad is i place for both measuremets. Software developed for data reductio described above may be used directly by calculatig the value of a "uivalet load resistor," as show at right. Actual measured voltage readigs are processed i the program. No further scalig is ruired. Atteuator output measuremets of the begiig of the output pulse from a high-tesio mageto ca also be used to calculate iductace ad stored eergy. The uatios are derived at right, ad are similar i form to those derived for low-tesio magetos i the previous sectio. As oted before, oise o the sample data files for vm ad vb must be appropriately smoothed to get accurate results. Mageto poits operatig: + + vm = vh vh = vm Mageto poits ope: + + vb = vg vg = vb + P = ( vh vg ) i = ( vm vb) vm + P = ( vm vb) vb + =, or = + P = ( vm vb) vb N W = P, or W vm ( vm vb ) t vg i vh vm, vb vm i = ( ) di d vm, = vh vg = ( + )( vb vm ) di, or + ( vm vb) = at t = T = d( vm) d( vm ) ( vb vm ) vm W t T = at = d vm + vb vm vm W = i = copyright Doald K Grimm page 3 of 5 May 7, 5

4 Example esults from ecet Tests ed Wig ow Tesio Mageto The waveform show o page is from a test of the low-tesio Grimm ed Wig mageto described i Model Egie Builder magazie, Issue 5. The body of this mageto is.75" thick ad.9" wide. The coil core is of octagoal cross sectio made from lamiated trasformer iro, with a area of.67 i. 5 Mageto Output Eergy ed Wig ow Tesio mjoule rpm W rpm mjoule Vietti Cast Frame High Tesio Mageto Data from a recet high-tesio mageto desiged ad built by Joh Vietti is show here. The body of the mageto is.3" wide ad.975 thick, with a coil core cross sectio of.49 i. Body stator thickess is.375". The waveform photo at right shows some evidece of spark plug or igitio poit flashover durig the leadig edge of the pulse, reducig measured output eergy ito the load resistor. Mageto Output Eergy Vietti Molded Body High Tesio mjoule rpm W rpm mjoule copyright Doald K Grimm page 4 of 5 May 7, 5

5 Selectig oad esistor Values Determiig the best resistor value for testig is more art tha sciece. The legth of the discharge pulse is cotrolled by the resistace of the load. High resistace icreases the discharge voltage ad shortes the pulse. Short pulse effects iclude susceptibility to flashover breakdow of the iterrupter poits or the spark plug* (high-tesio mageto). Eergy shuted ito a spark discharge will deduct from the eergy measuremet. Short discharge pulses will also iduce higher eddy curret losses i the mageto iro flux path. owerig the load resistor decreases the pulse voltage ad icreases its duratio. This allows measuremets at higher rpm without sparkig. The prologed curret flow does icrease the copper loss i the mageto widig(s). owerig the pulse voltage also makes the ope circuit geerator voltage of the mageto a more sigificat fractio of the total voltage compesatio for this effect becomes more importat. The practical optio, the, is to choose a resistace value that just suppresses sparkig at the maximum rpm to be tested. It is ot ecessary to suppress all sparkig. The sigle trace optio of the oscilloscope ca be used to select oe good pulse out of umerous bad oes, give some patiece ad persistece. It seems best, however, to avoid reducig the resistace to the poit where the output pulse becomes sigificatly loger tha ms. Most igitio sparks are shorter tha that, ad it is usually aisable to test the mageto with operatig coditios as close to ormal as possible. Most of my T tests were made with a 55 ohm load, ad HT tests were coducted with a value of about 7 kohm. Coclusios Theoretical bases for two methods for measurig mageto output eergy have bee described, alog with oe method of measurig iductace. Detailed implemetatio istructios are ot provided here, but ca be obtaied from the author. Other methods exist. See for a example. This tester discharges the output pulse ito a Zeer diode array that clamps the output voltage to a value ear kv. Power is calculated by multiplyig the pulse curret times the clamped voltage, ad the itegratig over time to compute eergy. It should give accurate results, but is ot easily adapted to testig low-tesio magetos. A commoly used aalysis tool is the calibrated spark gap. Oe form is described i my workig paper, o page 6. This will give approximate values of output eergy whe properly applied. Please cotact the author with suggestios for improvemets or iformatio regardig other methods that may exist. *Best practice is to keep the spark plug i place whe testig a high-tesio mageto to protect the coil from iteral flashover if excessively high voltage spikes should happe to occur. copyright Doald K Grimm page 5 of 5 May 7, 5

CHAPTER 3 DIGITAL CODING OF SIGNALS

CHAPTER 3 DIGITAL CODING OF SIGNALS CHAPTER 3 DIGITAL CODING OF SIGNALS Computers are ofte used to automate the recordig of measuremets. The trasducers ad sigal coditioig circuits produce a voltage sigal that is proportioal to a quatity

More information

Semiconductor Devices

Semiconductor Devices emicoductor evices Prof. Zbigiew Lisik epartmet of emicoductor ad Optoelectroics evices room: 116 e-mail: zbigiew.lisik@p.lodz.pl Uipolar devices IFE T&C JFET Trasistor Uipolar evices - Trasistors asic

More information

*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature.

*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature. Itegrated Productio ad Ivetory Cotrol System MRP ad MRP II Framework of Maufacturig System Ivetory cotrol, productio schedulig, capacity plaig ad fiacial ad busiess decisios i a productio system are iterrelated.

More information

WindWise Education. 2 nd. T ransforming the Energy of Wind into Powerful Minds. editi. A Curriculum for Grades 6 12

WindWise Education. 2 nd. T ransforming the Energy of Wind into Powerful Minds. editi. A Curriculum for Grades 6 12 WidWise Educatio T rasformig the Eergy of Wid ito Powerful Mids A Curriculum for Grades 6 12 Notice Except for educatioal use by a idividual teacher i a classroom settig this work may ot be reproduced

More information

Confidence Intervals for One Mean

Confidence Intervals for One Mean Chapter 420 Cofidece Itervals for Oe Mea Itroductio This routie calculates the sample size ecessary to achieve a specified distace from the mea to the cofidece limit(s) at a stated cofidece level for a

More information

INVESTMENT PERFORMANCE COUNCIL (IPC)

INVESTMENT PERFORMANCE COUNCIL (IPC) INVESTMENT PEFOMANCE COUNCIL (IPC) INVITATION TO COMMENT: Global Ivestmet Performace Stadards (GIPS ) Guidace Statemet o Calculatio Methodology The Associatio for Ivestmet Maagemet ad esearch (AIM) seeks

More information

Analyzing Longitudinal Data from Complex Surveys Using SUDAAN

Analyzing Longitudinal Data from Complex Surveys Using SUDAAN Aalyzig Logitudial Data from Complex Surveys Usig SUDAAN Darryl Creel Statistics ad Epidemiology, RTI Iteratioal, 312 Trotter Farm Drive, Rockville, MD, 20850 Abstract SUDAAN: Software for the Statistical

More information

How to read A Mutual Fund shareholder report

How to read A Mutual Fund shareholder report Ivestor BulletI How to read A Mutual Fud shareholder report The SEC s Office of Ivestor Educatio ad Advocacy is issuig this Ivestor Bulleti to educate idividual ivestors about mutual fud shareholder reports.

More information

GENERAL INFORMATION FOR PROXIMITY SWITCHES

GENERAL INFORMATION FOR PROXIMITY SWITCHES 78 C wire proximity switch The devices operate exactly like mechaical switches, with the coected load beig switched i series. They ca be used ito PLC iputs like relays. Notice should be take o the ifluece

More information

HCL Dynamic Spiking Protocol

HCL Dynamic Spiking Protocol ELI LILLY AND COMPANY TIPPECANOE LABORATORIES LAFAYETTE, IN Revisio 2.0 TABLE OF CONTENTS REVISION HISTORY... 2. REVISION.0... 2.2 REVISION 2.0... 2 2 OVERVIEW... 3 3 DEFINITIONS... 5 4 EQUIPMENT... 7

More information

3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2

3 Energy. 3.3. Non-Flow Energy Equation (NFEE) Internal Energy. MECH 225 Engineering Science 2 MECH 5 Egieerig Sciece 3 Eergy 3.3. No-Flow Eergy Equatio (NFEE) You may have oticed that the term system kees croig u. It is ecessary, therefore, that before we start ay aalysis we defie the system that

More information

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig

More information

COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S 2 CONTROL CHART FOR THE CHANGES IN A PROCESS

COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S 2 CONTROL CHART FOR THE CHANGES IN A PROCESS COMPARISON OF THE EFFICIENCY OF S-CONTROL CHART AND EWMA-S CONTROL CHART FOR THE CHANGES IN A PROCESS Supraee Lisawadi Departmet of Mathematics ad Statistics, Faculty of Sciece ad Techoology, Thammasat

More information

Z-TEST / Z-STATISTIC: used to test hypotheses about. µ when the population standard deviation is unknown

Z-TEST / Z-STATISTIC: used to test hypotheses about. µ when the population standard deviation is unknown Z-TEST / Z-STATISTIC: used to test hypotheses about µ whe the populatio stadard deviatio is kow ad populatio distributio is ormal or sample size is large T-TEST / T-STATISTIC: used to test hypotheses about

More information

INVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology

INVESTMENT PERFORMANCE COUNCIL (IPC) Guidance Statement on Calculation Methodology Adoptio Date: 4 March 2004 Effective Date: 1 Jue 2004 Retroactive Applicatio: No Public Commet Period: Aug Nov 2002 INVESTMENT PERFORMANCE COUNCIL (IPC) Preface Guidace Statemet o Calculatio Methodology

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

Forecasting techniques

Forecasting techniques 2 Forecastig techiques this chapter covers... I this chapter we will examie some useful forecastig techiques that ca be applied whe budgetig. We start by lookig at the way that samplig ca be used to collect

More information

Information about Bankruptcy

Information about Bankruptcy Iformatio about Bakruptcy Isolvecy Service of Irelad Seirbhís Dócmhaieachta a héirea Isolvecy Service of Irelad Seirbhís Dócmhaieachta a héirea What is the? The Isolvecy Service of Irelad () is a idepedet

More information

Chapter 7 Methods of Finding Estimators

Chapter 7 Methods of Finding Estimators Chapter 7 for BST 695: Special Topics i Statistical Theory. Kui Zhag, 011 Chapter 7 Methods of Fidig Estimators Sectio 7.1 Itroductio Defiitio 7.1.1 A poit estimator is ay fuctio W( X) W( X1, X,, X ) of

More information

Incremental calculation of weighted mean and variance

Incremental calculation of weighted mean and variance Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically

More information

Tradigms of Astundithi and Toyota

Tradigms of Astundithi and Toyota Tradig the radomess - Desigig a optimal tradig strategy uder a drifted radom walk price model Yuao Wu Math 20 Project Paper Professor Zachary Hamaker Abstract: I this paper the author iteds to explore

More information

The Forgotten Middle. research readiness results. Executive Summary

The Forgotten Middle. research readiness results. Executive Summary The Forgotte Middle Esurig that All Studets Are o Target for College ad Career Readiess before High School Executive Summary Today, college readiess also meas career readiess. While ot every high school

More information

I. Chi-squared Distributions

I. Chi-squared Distributions 1 M 358K Supplemet to Chapter 23: CHI-SQUARED DISTRIBUTIONS, T-DISTRIBUTIONS, AND DEGREES OF FREEDOM To uderstad t-distributios, we first eed to look at aother family of distributios, the chi-squared distributios.

More information

Using Four Types Of Notches For Comparison Between Chezy s Constant(C) And Manning s Constant (N)

Using Four Types Of Notches For Comparison Between Chezy s Constant(C) And Manning s Constant (N) INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH OLUME, ISSUE, OCTOBER ISSN - Usig Four Types Of Notches For Compariso Betwee Chezy s Costat(C) Ad Maig s Costat (N) Joyce Edwi Bategeleza, Deepak

More information

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the.

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the. Cofidece Itervals A cofidece iterval is a iterval whose purpose is to estimate a parameter (a umber that could, i theory, be calculated from the populatio, if measuremets were available for the whole populatio).

More information

CHAPTER 3 The Simple Surface Area Measurement Module

CHAPTER 3 The Simple Surface Area Measurement Module CHAPTER 3 The Simple Surface Area Measuremet Module I chapter 2, the quality of charcoal i each batch might chage due to traditioal operatio. The quality test shall be performed before usig it as a adsorbet.

More information

CS100: Introduction to Computer Science

CS100: Introduction to Computer Science I-class Exercise: CS100: Itroductio to Computer Sciece What is a flip-flop? What are the properties of flip-flops? Draw a simple flip-flop circuit? Lecture 3: Data Storage -- Mass storage & represetig

More information

Savings and Retirement Benefits

Savings and Retirement Benefits 60 Baltimore Couty Public Schools offers you several ways to begi savig moey through payroll deductios. Defied Beefit Pesio Pla Tax Sheltered Auities ad Custodial Accouts Defied Beefit Pesio Pla Did you

More information

A Combined Continuous/Binary Genetic Algorithm for Microstrip Antenna Design

A Combined Continuous/Binary Genetic Algorithm for Microstrip Antenna Design A Combied Cotiuous/Biary Geetic Algorithm for Microstrip Atea Desig Rady L. Haupt The Pesylvaia State Uiversity Applied Research Laboratory P. O. Box 30 State College, PA 16804-0030 haupt@ieee.org Abstract:

More information

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return EVALUATING ALTERNATIVE CAPITAL INVESTMENT PROGRAMS By Ke D. Duft, Extesio Ecoomist I the March 98 issue of this publicatio we reviewed the procedure by which a capital ivestmet project was assessed. The

More information

Chair for Network Architectures and Services Institute of Informatics TU München Prof. Carle. Network Security. Chapter 2 Basics

Chair for Network Architectures and Services Institute of Informatics TU München Prof. Carle. Network Security. Chapter 2 Basics Chair for Network Architectures ad Services Istitute of Iformatics TU Müche Prof. Carle Network Security Chapter 2 Basics 2.4 Radom Number Geeratio for Cryptographic Protocols Motivatio It is crucial to

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling Taig DCOP to the Real World: Efficiet Complete Solutios for Distributed Multi-Evet Schedulig Rajiv T. Maheswara, Milid Tambe, Emma Bowrig, Joatha P. Pearce, ad Pradeep araatham Uiversity of Souther Califoria

More information

summary of cover CONTRACT WORKS INSURANCE

summary of cover CONTRACT WORKS INSURANCE 1 SUMMARY OF COVER CONTRACT WORKS summary of cover CONTRACT WORKS INSURANCE This documet details the cover we ca provide for our commercial or church policyholders whe udertakig buildig or reovatio works.

More information

Domain 1: Designing a SQL Server Instance and a Database Solution

Domain 1: Designing a SQL Server Instance and a Database Solution Maual SQL Server 2008 Desig, Optimize ad Maitai (70-450) 1-800-418-6789 Domai 1: Desigig a SQL Server Istace ad a Database Solutio Desigig for CPU, Memory ad Storage Capacity Requiremets Whe desigig a

More information

A Guide to the Pricing Conventions of SFE Interest Rate Products

A Guide to the Pricing Conventions of SFE Interest Rate Products A Guide to the Pricig Covetios of SFE Iterest Rate Products SFE 30 Day Iterbak Cash Rate Futures Physical 90 Day Bak Bills SFE 90 Day Bak Bill Futures SFE 90 Day Bak Bill Futures Tick Value Calculatios

More information

Conversion Instructions:

Conversion Instructions: Coversio Istructios: QMS magicolor 2 DeskLaser to QMS magicolor 2 CX 1800502-001A Trademarks QMS, the QMS logo, ad magicolor are registered trademarks of QMS, Ic., registered i the Uited States Patet ad

More information

Amendments to employer debt Regulations

Amendments to employer debt Regulations March 2008 Pesios Legal Alert Amedmets to employer debt Regulatios The Govermet has at last issued Regulatios which will amed the law as to employer debts uder s75 Pesios Act 1995. The amedig Regulatios

More information

Domain 1 - Describe Cisco VoIP Implementations

Domain 1 - Describe Cisco VoIP Implementations Maual ONT (642-8) 1-800-418-6789 Domai 1 - Describe Cisco VoIP Implemetatios Advatages of VoIP Over Traditioal Switches Voice over IP etworks have may advatages over traditioal circuit switched voice etworks.

More information

FIRE PROTECTION SYSTEM INSPECTION, TESTING AND MAINTENANCE PROGRAMS

FIRE PROTECTION SYSTEM INSPECTION, TESTING AND MAINTENANCE PROGRAMS STRATEGIC OUTCOMES PRACTICE TECHNICAL ADVISORY BULLETIN February 2011 FIRE PROTECTION SYSTEM INSPECTION, TESTING AND MAINTENANCE PROGRAMS www.willis.com Natioal Fire Protectio Associatio (NFPA) #25 a mai

More information

BENEFIT-COST ANALYSIS Financial and Economic Appraisal using Spreadsheets

BENEFIT-COST ANALYSIS Financial and Economic Appraisal using Spreadsheets BENEIT-CST ANALYSIS iacial ad Ecoomic Appraisal usig Spreadsheets Ch. 2: Ivestmet Appraisal - Priciples Harry Campbell & Richard Brow School of Ecoomics The Uiversity of Queeslad Review of basic cocepts

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

1 Computing the Standard Deviation of Sample Means

1 Computing the Standard Deviation of Sample Means Computig the Stadard Deviatio of Sample Meas Quality cotrol charts are based o sample meas ot o idividual values withi a sample. A sample is a group of items, which are cosidered all together for our aalysis.

More information

Statement of cash flows

Statement of cash flows 6 Statemet of cash flows this chapter covers... I this chapter we study the statemet of cash flows, which liks profit from the statemet of profit or loss ad other comprehesive icome with chages i assets

More information

5: Introduction to Estimation

5: Introduction to Estimation 5: Itroductio to Estimatio Cotets Acroyms ad symbols... 1 Statistical iferece... Estimatig µ with cofidece... 3 Samplig distributio of the mea... 3 Cofidece Iterval for μ whe σ is kow before had... 4 Sample

More information

Detecting Voice Mail Fraud. Detecting Voice Mail Fraud - 1

Detecting Voice Mail Fraud. Detecting Voice Mail Fraud - 1 Detectig Voice Mail Fraud Detectig Voice Mail Fraud - 1 Issue 2 Detectig Voice Mail Fraud Detectig Voice Mail Fraud Several reportig mechaisms ca assist you i determiig voice mail fraud. Call Detail Recordig

More information

Present Value Tax Expenditure Estimate of Tax Assistance for Retirement Saving

Present Value Tax Expenditure Estimate of Tax Assistance for Retirement Saving Preset Value Tax Expediture Estimate of Tax Assistace for Retiremet Savig Tax Policy Brach Departmet of Fiace Jue 30, 1998 2 Preset Value Tax Expediture Estimate of Tax Assistace for Retiremet Savig This

More information

Research Method (I) --Knowledge on Sampling (Simple Random Sampling)

Research Method (I) --Knowledge on Sampling (Simple Random Sampling) Research Method (I) --Kowledge o Samplig (Simple Radom Samplig) 1. Itroductio to samplig 1.1 Defiitio of samplig Samplig ca be defied as selectig part of the elemets i a populatio. It results i the fact

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

This document contains a collection of formulas and constants useful for SPC chart construction. It assumes you are already familiar with SPC.

This document contains a collection of formulas and constants useful for SPC chart construction. It assumes you are already familiar with SPC. SPC Formulas ad Tables 1 This documet cotais a collectio of formulas ad costats useful for SPC chart costructio. It assumes you are already familiar with SPC. Termiology Geerally, a bar draw over a symbol

More information

4.1.4 Electrical Characterisation of MOVPE Grown n- and pn-gaas Nanowires

4.1.4 Electrical Characterisation of MOVPE Grown n- and pn-gaas Nanowires 3 Bi-Aual Reort 28/29 - Solid-State Electroics Deartmet 4.1.4 Electrical Characterisatio of MOVPE Grow - ad -GaAs Naowires Scietist: C. Gutsche, I. Regoli, A. Lysov Itroductio Recetly, we reseted a cotrolled

More information

Output Analysis (2, Chapters 10 &11 Law)

Output Analysis (2, Chapters 10 &11 Law) B. Maddah ENMG 6 Simulatio 05/0/07 Output Aalysis (, Chapters 10 &11 Law) Comparig alterative system cofiguratio Sice the output of a simulatio is radom, the comparig differet systems via simulatio should

More information

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,

More information

Present Values, Investment Returns and Discount Rates

Present Values, Investment Returns and Discount Rates Preset Values, Ivestmet Returs ad Discout Rates Dimitry Midli, ASA, MAAA, PhD Presidet CDI Advisors LLC dmidli@cdiadvisors.com May 2, 203 Copyright 20, CDI Advisors LLC The cocept of preset value lies

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n We will cosider the liear regressio model i matrix form. For simple liear regressio, meaig oe predictor, the model is i = + x i + ε i for i =,,,, This model icludes the assumptio that the ε i s are a sample

More information

Electrostatic solutions for better efficiency

Electrostatic solutions for better efficiency Electrostatic solutios for better efficiecy idustry for egieers, professioals ad techicias i developmet, productio ad istallatio. www.kerste.de/e Electrostatic solutios kerste has bee the leadig supplier

More information

MARTINGALES AND A BASIC APPLICATION

MARTINGALES AND A BASIC APPLICATION MARTINGALES AND A BASIC APPLICATION TURNER SMITH Abstract. This paper will develop the measure-theoretic approach to probability i order to preset the defiitio of martigales. From there we will apply this

More information

PSYCHOLOGICAL STATISTICS

PSYCHOLOGICAL STATISTICS UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION B Sc. Cousellig Psychology (0 Adm.) IV SEMESTER COMPLEMENTARY COURSE PSYCHOLOGICAL STATISTICS QUESTION BANK. Iferetial statistics is the brach of statistics

More information

Study on the application of the software phase-locked loop in tracking and filtering of pulse signal

Study on the application of the software phase-locked loop in tracking and filtering of pulse signal Advaced Sciece ad Techology Letters, pp.31-35 http://dx.doi.org/10.14257/astl.2014.78.06 Study o the applicatio of the software phase-locked loop i trackig ad filterig of pulse sigal Sog Wei Xia 1 (College

More information

Hypothesis testing. Null and alternative hypotheses

Hypothesis testing. Null and alternative hypotheses Hypothesis testig Aother importat use of samplig distributios is to test hypotheses about populatio parameters, e.g. mea, proportio, regressio coefficiets, etc. For example, it is possible to stipulate

More information

Basic Measurement Issues. Sampling Theory and Analog-to-Digital Conversion

Basic Measurement Issues. Sampling Theory and Analog-to-Digital Conversion Theory ad Aalog-to-Digital Coversio Itroductio/Defiitios Aalog-to-digital coversio Rate Frequecy Aalysis Basic Measuremet Issues Reliability the extet to which a measuremet procedure yields the same results

More information

Modified Line Search Method for Global Optimization

Modified Line Search Method for Global Optimization Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o

More information

Estimating Probability Distributions by Observing Betting Practices

Estimating Probability Distributions by Observing Betting Practices 5th Iteratioal Symposium o Imprecise Probability: Theories ad Applicatios, Prague, Czech Republic, 007 Estimatig Probability Distributios by Observig Bettig Practices Dr C Lych Natioal Uiversity of Irelad,

More information

PENSION ANNUITY. Policy Conditions Document reference: PPAS1(7) This is an important document. Please keep it in a safe place.

PENSION ANNUITY. Policy Conditions Document reference: PPAS1(7) This is an important document. Please keep it in a safe place. PENSION ANNUITY Policy Coditios Documet referece: PPAS1(7) This is a importat documet. Please keep it i a safe place. Pesio Auity Policy Coditios Welcome to LV=, ad thak you for choosig our Pesio Auity.

More information

UM USER SATISFACTION SURVEY 2011. Final Report. September 2, 2011. Prepared by. ers e-research & Solutions (Macau)

UM USER SATISFACTION SURVEY 2011. Final Report. September 2, 2011. Prepared by. ers e-research & Solutions (Macau) UM USER SATISFACTION SURVEY 2011 Fial Report September 2, 2011 Prepared by ers e-research & Solutios (Macau) 1 UM User Satisfactio Survey 2011 A Collaboratio Work by Project Cosultat Dr. Agus Cheog ers

More information

Inference on Proportion. Chapter 8 Tests of Statistical Hypotheses. Sampling Distribution of Sample Proportion. Confidence Interval

Inference on Proportion. Chapter 8 Tests of Statistical Hypotheses. Sampling Distribution of Sample Proportion. Confidence Interval Chapter 8 Tests of Statistical Hypotheses 8. Tests about Proportios HT - Iferece o Proportio Parameter: Populatio Proportio p (or π) (Percetage of people has o health isurace) x Statistic: Sample Proportio

More information

Modeling of Ship Propulsion Performance

Modeling of Ship Propulsion Performance odelig of Ship Propulsio Performace Bejami Pjedsted Pederse (FORCE Techology, Techical Uiversity of Demark) Ja Larse (Departmet of Iformatics ad athematical odelig, Techical Uiversity of Demark) Full scale

More information

Partial Di erential Equations

Partial Di erential Equations Partial Di eretial Equatios Partial Di eretial Equatios Much of moder sciece, egieerig, ad mathematics is based o the study of partial di eretial equatios, where a partial di eretial equatio is a equatio

More information

ODBC. Getting Started With Sage Timberline Office ODBC

ODBC. Getting Started With Sage Timberline Office ODBC ODBC Gettig Started With Sage Timberlie Office ODBC NOTICE This documet ad the Sage Timberlie Office software may be used oly i accordace with the accompayig Sage Timberlie Office Ed User Licese Agreemet.

More information

IntelliSOURCE Comverge s enterprise software platform provides the foundation for deploying integrated demand management programs.

IntelliSOURCE Comverge s enterprise software platform provides the foundation for deploying integrated demand management programs. ItelliSOURCE Comverge s eterprise software platform provides the foudatio for deployig itegrated demad maagemet programs. ItelliSOURCE Demad maagemet programs such as demad respose, eergy efficiecy, ad

More information

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals Overview Estimatig the Value of a Parameter Usig Cofidece Itervals We apply the results about the sample mea the problem of estimatio Estimatio is the process of usig sample data estimate the value of

More information

Processor Card Specifications PN A6560, A6560-T

Processor Card Specifications PN A6560, A6560-T Specificatios Sheet CSI 6500 Machiery Health Moitor Processor Card Specificatios PN A6560, A6560-T The machiery health processor is the heart of the CSI 6500 Machiery Health Moitor providig field-based,

More information

Mathematical goals. Starting points. Materials required. Time needed

Mathematical goals. Starting points. Materials required. Time needed Level A1 of challege: C A1 Mathematical goals Startig poits Materials required Time eeded Iterpretig algebraic expressios To help learers to: traslate betwee words, symbols, tables, ad area represetatios

More information

Now here is the important step

Now here is the important step LINEST i Excel The Excel spreadsheet fuctio "liest" is a complete liear least squares curve fittig routie that produces ucertaity estimates for the fit values. There are two ways to access the "liest"

More information

How to use what you OWN to reduce what you OWE

How to use what you OWN to reduce what you OWE How to use what you OWN to reduce what you OWE Maulife Oe A Overview Most Caadias maage their fiaces by doig two thigs: 1. Depositig their icome ad other short-term assets ito chequig ad savigs accouts.

More information

iprox sensors iprox inductive sensors iprox programming tools ProxView programming software iprox the world s most versatile proximity sensor

iprox sensors iprox inductive sensors iprox programming tools ProxView programming software iprox the world s most versatile proximity sensor iprox sesors iprox iductive sesors iprox programmig tools ProxView programmig software iprox the world s most versatile proximity sesor The world s most versatile proximity sesor Eato s iproxe is syoymous

More information

Domain 1: Identifying Cause of and Resolving Desktop Application Issues Identifying and Resolving New Software Installation Issues

Domain 1: Identifying Cause of and Resolving Desktop Application Issues Identifying and Resolving New Software Installation Issues Maual Widows 7 Eterprise Desktop Support Techicia (70-685) 1-800-418-6789 Domai 1: Idetifyig Cause of ad Resolvig Desktop Applicatio Issues Idetifyig ad Resolvig New Software Istallatio Issues This sectio

More information

Statistical inference: example 1. Inferential Statistics

Statistical inference: example 1. Inferential Statistics Statistical iferece: example 1 Iferetial Statistics POPULATION SAMPLE A clothig store chai regularly buys from a supplier large quatities of a certai piece of clothig. Each item ca be classified either

More information

Determining the sample size

Determining the sample size Determiig the sample size Oe of the most commo questios ay statisticia gets asked is How large a sample size do I eed? Researchers are ofte surprised to fid out that the aswer depeds o a umber of factors

More information

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have Comple Numbers I spite of Calvi s discomfiture, imagiar umbers (a subset of the set of comple umbers) eist ad are ivaluable i mathematics, egieerig, ad sciece. I fact, i certai fields, such as electrical

More information

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized?

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized? 5.4 Amortizatio Questio 1: How do you fid the preset value of a auity? Questio 2: How is a loa amortized? Questio 3: How do you make a amortizatio table? Oe of the most commo fiacial istrumets a perso

More information

(VCP-310) 1-800-418-6789

(VCP-310) 1-800-418-6789 Maual VMware Lesso 1: Uderstadig the VMware Product Lie I this lesso, you will first lear what virtualizatio is. Next, you ll explore the products offered by VMware that provide virtualizatio services.

More information

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT Keywords: project maagemet, resource allocatio, etwork plaig Vladimir N Burkov, Dmitri A Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT The paper deals with the problems of resource allocatio betwee

More information

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method Chapter 6: Variace, the law of large umbers ad the Mote-Carlo method Expected value, variace, ad Chebyshev iequality. If X is a radom variable recall that the expected value of X, E[X] is the average value

More information

Create Income for Your Retirement. What You Can Expect. What to Consider. Page 1 of 7

Create Income for Your Retirement. What You Can Expect. What to Consider. Page 1 of 7 Page 1 of 7 RBC Retiremet Icome Plaig Process Create Icome for Your Retiremet At RBC Wealth Maagemet, we believe maagig your wealth to produce a icome durig retiremet is fudametally differet from maagig

More information

Cantilever Beam Experiment

Cantilever Beam Experiment Mechaical Egieerig Departmet Uiversity of Massachusetts Lowell Catilever Beam Experimet Backgroud A disk drive maufacturer is redesigig several disk drive armature mechaisms. This is the result of evaluatio

More information

Systems Design Project: Indoor Location of Wireless Devices

Systems Design Project: Indoor Location of Wireless Devices Systems Desig Project: Idoor Locatio of Wireless Devices Prepared By: Bria Murphy Seior Systems Sciece ad Egieerig Washigto Uiversity i St. Louis Phoe: (805) 698-5295 Email: bcm1@cec.wustl.edu Supervised

More information

Research Article Sign Data Derivative Recovery

Research Article Sign Data Derivative Recovery Iteratioal Scholarly Research Network ISRN Applied Mathematics Volume 0, Article ID 63070, 7 pages doi:0.540/0/63070 Research Article Sig Data Derivative Recovery L. M. Housto, G. A. Glass, ad A. D. Dymikov

More information

Message Exchange in the Utility Market Using SAP for Utilities. Point of View by Marc Metz and Maarten Vriesema

Message Exchange in the Utility Market Using SAP for Utilities. Point of View by Marc Metz and Maarten Vriesema Eergy, Utilities ad Chemicals the way we see it Message Exchage i the Utility Market Usig SAP for Utilities Poit of View by Marc Metz ad Maarte Vriesema Itroductio Liberalisatio of utility markets has

More information

FOUNDATIONS OF MATHEMATICS AND PRE-CALCULUS GRADE 10

FOUNDATIONS OF MATHEMATICS AND PRE-CALCULUS GRADE 10 FOUNDATIONS OF MATHEMATICS AND PRE-CALCULUS GRADE 10 [C] Commuicatio Measuremet A1. Solve problems that ivolve liear measuremet, usig: SI ad imperial uits of measure estimatio strategies measuremet strategies.

More information

Center, Spread, and Shape in Inference: Claims, Caveats, and Insights

Center, Spread, and Shape in Inference: Claims, Caveats, and Insights Ceter, Spread, ad Shape i Iferece: Claims, Caveats, ad Isights Dr. Nacy Pfeig (Uiversity of Pittsburgh) AMATYC November 2008 Prelimiary Activities 1. I would like to produce a iterval estimate for the

More information

Domain 1: Configuring Domain Name System (DNS) for Active Directory

Domain 1: Configuring Domain Name System (DNS) for Active Directory Maual Widows Domai 1: Cofigurig Domai Name System (DNS) for Active Directory Cofigure zoes I Domai Name System (DNS), a DNS amespace ca be divided ito zoes. The zoes store ame iformatio about oe or more

More information

Example: Probability ($1 million in S&P 500 Index will decline by more than 20% within a

Example: Probability ($1 million in S&P 500 Index will decline by more than 20% within a Value at Risk For a give portfolio, Value-at-Risk (VAR) is defied as the umber VAR such that: Pr( Portfolio loses more tha VAR withi time period t)

More information

II. Goals of the Sentinel Event Policy

II. Goals of the Sentinel Event Policy Setiel Evets (SE) I. Setiel Evets I support of its missio to cotiuously improve the safety ad quality of health care provided to the public, The Joit Commissio i its accreditatio process reviews hospitals

More information

Normal Distribution.

Normal Distribution. Normal Distributio www.icrf.l Normal distributio I probability theory, the ormal or Gaussia distributio, is a cotiuous probability distributio that is ofte used as a first approimatio to describe realvalued

More information

Agenda. Outsourcing and Globalization in Software Development. Outsourcing. Outsourcing here to stay. Outsourcing Alternatives

Agenda. Outsourcing and Globalization in Software Development. Outsourcing. Outsourcing here to stay. Outsourcing Alternatives Outsourcig ad Globalizatio i Software Developmet Jacques Crocker UW CSE Alumi 2003 jc@cs.washigto.edu Ageda Itroductio The Outsourcig Pheomeo Leadig Offshore Projects Maagig Customers Offshore Developmet

More information

Agency Relationship Optimizer

Agency Relationship Optimizer Decideware Developmet Agecy Relatioship Optimizer The Leadig Software Solutio for Cliet-Agecy Relatioship Maagemet supplier performace experts scorecards.deploymet.service decide ware Sa Fracisco Sydey

More information

PUBLIC RELATIONS PROJECT 2016

PUBLIC RELATIONS PROJECT 2016 PUBLIC RELATIONS PROJECT 2016 The purpose of the Public Relatios Project is to provide a opportuity for the chapter members to demostrate the kowledge ad skills eeded i plaig, orgaizig, implemetig ad evaluatig

More information

T R A N S F O R M E R A C C E S S O R I E S SAM REMOTE CONTROL SYSTEM

T R A N S F O R M E R A C C E S S O R I E S SAM REMOTE CONTROL SYSTEM REMOTE CONTROL SYSTEM REMOTE CONTROL SYSTEM TYPE MRCS T R A N S F O R M E R A C C E S S O R I E S PLN.03.08 CODE NO: 720 (20A.) CODE NO: 72400 / 800 (400/800A.) CODE NO: 73000 (000A.). GENERAL This system

More information