and this position gives an indication of the tone in which the word is to be pronounced. Tones


 Pearl Gray
 5 years ago
 Views:
Transcription
1 The symbols and sounds of the Ahmao scrpt Ths key to the Ahmao (Pollard) scrpt has been set out usng nontechncal terms, n order that the reader, unfamlar wth the Internatonal Phonetc Scrpt may be able to use the Glossary. The student seekng a detaled apprasal of the scrpt, together wth an account of ts development and an analyss of the tonal system of the language s referred to "A Myth Become Realty. Hstory and Development of the Mao Wrtten Language." Volume 1, by Joakm Enwall. Publshed by the Insttute of Orental Languages, Stockholm Unversty. The Mao language s monosyllabc, each syllable beng made up of an ntal and a fnal. In the scrpt the ntals are wrtten wth large symbols and the fnals wth small symbols. The fnal may be wrtten n any one of four postons relatve to the ntal, thus, Y Y Y Y and ths poston gves an ndcaton of the tone n whch the word s to be pronounced. Tones The seven tones as defned by Wang Mngj have the followng values 1 s 45 2 s 55 3 s 53 4 s 33 5 s 13 6 s 11 7 s 21 The tones are ndcated on a fve level scale, wth 5 as the hghest, and 1 as the lowest level. Thus 55, 44 and 22 are all even tones at the hgh, medum and low levels respectvely, whle 24 begns low and rses, whle 53 begns hgh and falls etc. The seven tones are spread over the four postons of the Ahmao scrpt as follows, Poston 1 ( Y ) Poston 2 ( Y ) Poston 3 ( Y ) Poston 4 ( Y ) Tone 1 Tones 2, 3, and 4 Tone 5 Tone 6 and 7 The eght tone markers n the Pnyn when appled to Ahmao have the followng tone values. Pnyn d b t x k s l f Ahmao tone 45, 55 55,
2 Intals Mao Sound Pnyn P b as n bat b P p as n pen p T d as n do d T t as n ten t X dz as n suds z X ts as n lets c E j as n jug zh or j E ch as n chum ch or q D d(r) Ths sound does not occur n Englsh. It s the letter "d" pronounced wth the tp of the tongue curled toward the roof of the mouth gvng the "d" a fent "r" qualty D t(r) As above but wth the letter "t" tr K g as n go g K k as n kll k A gl as n glass dl A cl as n class tl W Guttural g. Ths sound does not occur n Englsh. It s smlar to the letter "g" but pronounced at the back of the throat. W Guttural k. As the foregong but wth the letter "k" kh M m as n me m M Ths sound does not occur n Englsh. It s an "m", preceded by a short exhalaton of breath through the nose C n as n nght n C Ths sound does not occur n Englsh. It s an "n", wth nasal breathng as explaned above G ng as n sng ngg G Ths sound does not occur n Englsh. It s an "ng", wth a nasal breathng as explaned above L l as n lfe l F Ths sound does not occur n Englsh. It s the Welsh "ll" hl Y Ths symbol has no pronuncaton. It s used as a measure wth words whch are purely vowel sounds,.e. fnals only, so that ther tonal postons can be properly shown H h as n hgh h V v as n vew v dr gh hm hn hngg Not used n Pnyn
3 Mao Sound Pnyn B f as n fun f Z z as n zoo r S s as n sun s Q y as n you. j as n the French word for "I" je Some words are always pronounced one way, some always the other, but there are many where there s some ambvalence between the two J sh as n show sh or x I Ths sound does not occur n Englsh. The voced vowel that follows t s pronounced at the very back of the throat but there s no glottal stop. I Ths sound does not occur n Englsh. It s pronounced as the foregong but s accompaned by the expellng of breath. It s akn to the "ch" n Scottsh pronuncaton of "loch" Ths symbol s occasonally used n Chnese loan words for the sound "w" as n U wang" Note. The frst sxteen of the ntals, P to W, may all be preceded by the letter C, e.g. CP, CP, CT, CT etc. [In Pnyn wrtten nb, np, nd, nt etc.] In all but two cases the pronuncaton of these compound ntals s exactly as would be expected, e.g. CT s "nd" as n land, CX s "nts" as n ants. The exceptons are CP and CP whch are pronounced "mb" as n tmber, and "mp" as n temper respectvely. In the case of the ntals E, E, CE, CE and J, the normal equvalents n Pnyn are zh, c, nzh, nc, and sh. However, when the fnal that follows s or any dphthong begnnng wth ncludng the dphthong, the Pnyn equvalents become j, q, nj, nq, and x, respectvely. y y hx hx w
4 Fnals Mao Sound Pnyn ee as n see as n t a as n father a ou as n ought o ˇ oo as n too u Ths sound does not occur n Englsh. It s the "u" of "une" n French, and s formed by pronouncng "ee" wth the lps pursed e as n the yu e ˆ Ths sound does not occur n Englsh. It s the "e" of "the" but pronounced wth the teeth together and the tp of the tongue close behnd the teeth Ths sound does not occur n Englsh. It s the "e" of "the" but pronounced through the nose, smlar to the "un" n "uncton" Ths sound does not occur n Englsh. It s smlar to the "r" n "shrt", or the "ur" n "church" but wth the "r" pronounced very lghtly Ths sound does not occur n Englsh. It s pronounced n the same way as the foregong but wth the lps pursed w ang yu ye as n yet e ea as n beattude a «yo as n York o ª ew as n hew u eu as n deu n French Ths sound does not occur n Englsh. It s the "e" as n "the" followed by the "u" of the French word "une". It s the sound "ow" n "cow" as t s pronounced n the Devonshre dalect Ths sound does not occur n Englsh. It s the "ee" of "see" followed by the "" e eu eu Ths sound does not occur n Englsh. It s the "ee" of "see " followed by the " " Ths sound does not occur n Englsh. It s the "ee" of "see " followed by the " w ang ay as n say a
5 Mao Sound Pnyn» e as n de a fl ee as n see, followed by e as n de a Ths sound does not occur n Englsh. It s the "o" as n "hot" followed by "oo" as n "too " ao Ths sound does not occur n Englsh. It s the "ee" of "see " followed by "" as descrbed above Ths sound does not occur n Englsh. It s the "u" of " une" n French followed by the "e" as n "let". N.B. many speakers do not dstngush between ths sound and " " Ths symbol s used n Chnese loan words for the sound "un" as n shun º Ths symbol s used n Chnese loan words for the sound "a" as n "father" followed by "ng" as n "hang ". Ths symbol s used n Chnese loan words for the sound "ng" as n "lng " ao e en ang ng Ths symbol s used n Chnese loan words for the sound "ou" as n " ought" followed by "ng" as n "hang " Ths symbol s used n Chnese loan words for the sound "way" as n "away ". ong u ß Ths symbol s used n Chnese loan words for the sound wa as n wag ua _ Ths symbol s used n Chnese loan words for the sound wa as n water uo Ths symbol s used n Chnese loan words for the sound w as n wne ua
o Alphabet Recitation
LetterSound Inventory (Record Sheet #1) 511 o Alphabet Recitation o Alphabet Recitation a b c d e f 9 h a b c d e f 9 h j k m n 0 p q k m n 0 p q r s t u v w x y z r s t u v w x y z 0 Upper Case Letter
More informationP a g e 5 1 of R e p o r t P B 4 / 0 9
P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e
More informationOn the spectral norm of rcirculant matrices with the Pell and PellLucas numbers
Türkmen and Gökbaş Journal of Inequaltes and Applcatons (06) 06:65 DOI 086/s36600609970 R E S E A R C H Open Access On the spectral norm of rcrculant matrces wth the Pell and PellLucas numbers Ramazan
More informationThe Order Relation and Trace Inequalities for. Hermitian Operators
Internatonal Mathematcal Forum, Vol 3, 08, no, 50757 HIKARI Ltd, wwwmhkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence
More informationA quote of the week (or camel of the week): There is no expedience to which a man will not go to avoid the labor of thinking. Thomas A.
A quote of the week (or camel of the week): here s no expedence to whch a man wll not go to avod the labor of thnkng. homas A. Edson Hess law. Algorthm S Select a reacton, possbly contanng specfc compounds
More informationValuated Binary Tree: A New Approach in Study of Integers
Internatonal Journal of Scentfc Innovatve Mathematcal Research (IJSIMR) Volume 4, Issue 3, March 6, PP 6367 ISS 34737X (Prnt) & ISS 34734 (Onlne) wwwarcournalsorg Valuated Bnary Tree: A ew Approach
More information176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s
A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps
More informationThermodynamics Second Law Entropy
Thermodynamcs Second Law Entropy Lana Sherdan De Anza College May 8, 2018 Last tme the Boltzmann dstrbuton (dstrbuton of energes) the MaxwellBoltzmann dstrbuton (dstrbuton of speeds) the Second Law of
More informationExercises H /OOA> f Wo AJoTHS l^»l S. m^ttrt /A/ ?C,0&L6M5 INFERENCE FOR DISTRIBUTIONS OF CATEGORICAL DATA. tts^e&n tains 5 2%cashews^, 27%
/A/ mttrt?c,&l6m5 INFERENCE FOR DISTRIBUTIONS OF CATEGORICAL DATA Exercses, nuts! A cmpany clams that each batch f ttse&n tans 5 2%cashews, 27% almnds, 13% macadama nuts, and 8% brazl nuts. T test ths
More informationRecover plaintext attack to block ciphers
Recover plantext attac to bloc cphers L AnPng Bejng 100085, P.R.Chna apl0001@sna.com Abstract In ths paper, we wll present an estmaton for the upperbound of the amount of 16bytes plantexts for Englsh
More informationSTAT 3008 Applied Regression Analysis
STAT 3008 Appled Regresson Analyss Tutoral : Smple Lnear Regresson LAI Chun He Department of Statstcs, The Chnese Unversty of Hong Kong 1 Model Assumpton To quantfy the relatonshp between two factors,
More informationGravitational Acceleration: A case of constant acceleration (approx. 2 hr.) (6/7/11)
Gravtatonal Acceleraton: A case of constant acceleraton (approx. hr.) (6/7/11) Introducton The gravtatonal force s one of the fundamental forces of nature. Under the nfluence of ths force all objects havng
More informationAP Physics 1 & 2 Summer Assignment
AP Physcs 1 & 2 Summer Assgnment AP Physcs 1 requres an exceptonal profcency n algebra, trgonometry, and geometry. It was desgned by a select group of college professors and hgh school scence teachers
More informationPolynomial Regression Models
LINEAR REGRESSION ANALYSIS MODULE XII Lecture  6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance
More informationDr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur
Analyss of Varance and Desgn of ExermentsI MODULE III LECTURE  2 EXPERIMENTAL DESIGN MODELS Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 2 We consder the models
More informationOutline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property.
Unt Eght Calculatons wth Entropy Mechancal Engneerng 370 Thermodynamcs Larry Caretto October 6, 010 Outlne Quz Seven Solutons Second law revew Goals for unt eght Usng entropy to calculate the maxmum work
More informationI M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o
I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o u l d a l w a y s b e t a k e n, i n c l u d f o l
More informationSupplemental Material: Causal Entropic Forces
Supplemental Materal: Causal Entropc Forces A. D. WssnerGross 1, 2, and C. E. Freer 3 1 Insttute for Appled Computatonal Scence, Harvard Unversty, Cambrdge, Massachusetts 02138, USA 2 The Meda Laboratory,
More informationPopClick Noise Detection Using InterFrame Correlation for Improved Portable Auditory Sensing
Advanced Scence and Technology Letters, pp.164168 http://dx.do.org/10.14257/astl.2013 PopClc Nose Detecton Usng InterFrame Correlaton for Improved Portable Audtory Sensng Dong Yun Lee, Kwang Myung Jeon,
More informationStatistical Evaluation of WATFLOOD
tatstcal Evaluaton of WATFLD By: Angela MacLean, Dept. of Cvl & Envronmental Engneerng, Unversty of Waterloo, n. ctober, 005 The statstcs program assocated wth WATFLD uses spl.csv fle that s produced wth
More informationSolution of Linear System of Equations and Matrix Inversion Gauss Seidel Iteration Method
Soluton of Lnear System of Equatons and Matr Inverson Gauss Sedel Iteraton Method It s another wellknown teratve method for solvng a system of lnear equatons of the form a + a22 + + ann = b a2 + a222
More informationCHAPTER 7 ENERGY BALANCES SYSTEM SYSTEM. * What is energy? * Forms of Energy.  Kinetic energy (KE)  Potential energy (PE) PE = mgz
SYSTM CHAPTR 7 NRGY BALANCS 1 7.17. SYSTM nergy & 1st Law of Thermodynamcs * What s energy? * Forms of nergy  Knetc energy (K) K 1 mv  Potental energy (P) P mgz  Internal energy (U) * Total nergy,
More informationOH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9
OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at
More informationModule 9. Lecture 6. Duality in Assignment Problems
Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept
More informationA L A BA M A L A W R E V IE W
A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N
More informationOn the correction of the hindex for career length
1 On the correcton of the hndex for career length by L. Egghe Unverstet Hasselt (UHasselt), Campus Depenbeek, Agoralaan, B3590 Depenbeek, Belgum 1 and Unverstet Antwerpen (UA), IBW, Stadscampus, Venusstraat
More informationSimulated Power of the Discrete Cramérvon Mises GoodnessofFit Tests
Smulated of the Cramérvon Mses GoodnessofFt Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth
More informationT h e C S E T I P r o j e c t
T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T
More informationAn improved lowerbound on the counterfeit coins problem
An mproved lowerbound on the counterfet cons problem L AnPng Bejng 100085, P.R. Chna apl0001@sna.com Hagen von Etzen hagen@vonetzen.de Abstract In ths paper, we wll gve an mprovement on the lower bound
More informationThe ExpectationMaximization Algorithm
The ExpectatonMaxmaton Algorthm Charles Elan elan@cs.ucsd.edu November 16, 2007 Ths chapter explans the EM algorthm at multple levels of generalty. Secton 1 gves the standard hghlevel verson of the algorthm.
More informationMODELING TRAFFIC LIGHTS IN INTERSECTION USING PETRI NETS
The 3 rd Internatonal Conference on Mathematcs and Statstcs (ICoMS3) Insttut Pertanan Bogor, Indonesa, 56 August 28 MODELING TRAFFIC LIGHTS IN INTERSECTION USING PETRI NETS 1 Deky Adzkya and 2 Subono
More informationArmy Ants Tunneling for Classical Simulations
Electronc Supplementary Materal (ESI) for Chemcal Scence. Ths journal s The Royal Socety of Chemstry 2014 electronc supplementary nformaton (ESI) for Chemcal Scence Army Ants Tunnelng for Classcal Smulatons
More informationLecture 4: Universal Hash Functions/Streaming Cont d
CSE 5: Desgn and Analyss of Algorthms I Sprng 06 Lecture 4: Unversal Hash Functons/Streamng Cont d Lecturer: Shayan Oves Gharan Aprl 6th Scrbe: Jacob Schreber Dsclamer: These notes have not been subjected
More informationBasic Regular Expressions. Introduction. Introduction to Computability. Theory. Motivation. Lecture4: Regular Expressions
Introducton to Computablty Theory Lecture: egular Expressons Prof Amos Israel Motvaton If one wants to descrbe a regular language, La, she can use the a DFA, Dor an NFA N, such L ( D = La that that Ths
More informationExecutive Committee and Officers ( )
Gifted and Talented International V o l u m e 2 4, N u m b e r 2, D e c e m b e r, 2 0 0 9. G i f t e d a n d T a l e n t e d I n t e r n a t i o n a2 l 4 ( 2), D e c e m b e r, 2 0 0 9. 1 T h e W o r
More informationDepartment of Statistics University of Toronto STA305H1S / 1004 HS Design and Analysis of Experiments Term Test  Winter Solution
Department of Statstcs Unversty of Toronto STA35HS / HS Desgn and Analyss of Experments Term Test  Wnter  Soluton February, Last Name: Frst Name: Student Number: Instructons: Tme: hours. Ads: a nonprogrammable
More informationFoundations of Arithmetic
Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an
More informationis the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors
Multple Lnear and Polynomal Regresson wth Statstcal Analyss Gven a set of data of measured (or observed) values of a dependent varable: y versus n ndependent varables x 1, x, x n, multple lnear regresson
More informationSelfcomplementing permutations of kuniform hypergraphs
Dscrete Mathematcs Theoretcal Computer Scence DMTCS vol. 11:1, 2009, 117 124 Selfcomplementng permutatons of kunform hypergraphs Artur Szymańsk A. Paweł Wojda Faculty of Appled Mathematcs, AGH Unversty
More informationOur focus will be on linear systems. A system is linear if it obeys the principle of superposition and homogenity, i.e.
SSTEM MODELLIN In order to solve a control syste proble, the descrptons of the syste and ts coponents ust be put nto a for sutable for analyss and evaluaton. The followng ethods can be used to odel physcal
More informationCHAPTER IV RESEARCH FINDING AND DISCUSSIONS
CHAPTER IV RESEARCH FINDING AND DISCUSSIONS A. Descrpton of Research Fndng. The Implementaton of Learnng Havng ganed the whole needed data, the researcher then dd analyss whch refers to the statstcal data
More informationAmusing Properties of Odd Numbers Derived From Valuated Binary Tree
IOSR Journal of Mathematcs (IOSRJM) eiss: 78578, piss: 19765X. Volume 1, Issue 6 Ver. V (ov.  Dec.016), PP 557 www.osrjournals.org Amusng Propertes of Odd umbers Derved From Valuated Bnary Tree
More informationOn the Interval Zoro Symmetric Singlestep Procedure for Simultaneous Finding of Polynomial Zeros
Appled Mathematcal Scences, Vol. 5, 2011, no. 75, 36933706 On the Interval Zoro Symmetrc Snglestep Procedure for Smultaneous Fndng of Polynomal Zeros S. F. M. Rusl, M. Mons, M. A. Hassan and W. J. Leong
More informationBALLADE TO THE MOON  _ I _
BALLADE TO THE MOON Danel Elde (b 986) Adago Msteoso 66 3 '0# 3 5 S A T B On moonlt nght 7 ' Yg " 2 9 l 0 wan de fee : pp e 9 : n n l j j: 2 a 0 On moonlt nght wan de' fee my mnd to oam on thoughts of
More informationAppendix for Causal Interaction in Factorial Experiments: Application to Conjoint Analysis
A Appendx for Causal Interacton n Factoral Experments: Applcaton to Conjont Analyss Mathematcal Appendx: Proofs of Theorems A. Lemmas Below, we descrbe all the lemmas, whch are used to prove the man theorems
More informationAssignment 4 Solutions
Assgnment 4 Solutons Tmothy Vs February 3, 2006 332 We have n 25, 0.04, P MT 100, and we need to fnd F V. F V P MT (1 + )n 1 100 (1 + 0.04)2 5 1 0.04 4164.59 336 We have F V 8000, n 30, 0.03, and we
More informationWeek3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity
Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1s tme nterval. The velocty of the partcle
More informationComparison of the Population Variance Estimators. of 2Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method
Appled Mathematcal Scences, Vol. 7, 0, no. 47, 070 HIARI Ltd, www.mhkar.com Comparson of the Populaton Varance Estmators of Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method
More informationHomework Notes Week 7
Homework Notes Week 7 Math 4 Sprng 4 #4 (a Complete the proof n example 5 that s an nner product (the Frobenus nner product on M n n (F In the example propertes (a and (d have already been verfed so we
More informationAnnexes. EC.1. Cyclebase move illustration. EC.2. Problem Instances
ec Annexes Ths Annex frst llustrates a cyclebased move n the dynamcblock generaton tabu search. It then dsplays the characterstcs of the nstance sets, followed by detaled results of the parametercalbraton
More informationLeast squares cubic splines without Bsplines S.K. Lucas
Least squares cubc splnes wthout Bsplnes S.K. Lucas School of Mathematcs and Statstcs, Unversty of South Australa, Mawson Lakes SA 595 emal: stephen.lucas@unsa.edu.au Submtted to the Gazette of the Australan
More informationx = , so that calculated
Stat 4, secton Sngle Factor ANOVA notes by Tm Plachowsk n chapter 8 we conducted hypothess tests n whch we compared a sngle sample s mean or proporton to some hypotheszed value Chapter 9 expanded ths to
More informationStatistics MINITAB  Lab 2
Statstcs 20080 MINITAB  Lab 2 1. Smple Lnear Regresson In smple lnear regresson we attempt to model a lnear relatonshp between two varables wth a straght lne and make statstcal nferences concernng that
More informationThe optimal delay of the second test is therefore approximately 210 hours earlier than =2.
THE IEC 61508 FORMULAS 223 The optmal delay of the second test s therefore approxmately 210 hours earler than =2. 8.4 The IEC 61508 Formulas IEC 615086 provdes approxmaton formulas for the PF for smple
More informationLNG CARGO TRANSFER CALCULATION METHODS AND ROUNDINGOFFS
CARGO TRANSFER CALCULATION METHODS AND ROUNDINGOFFS CONTENTS 1. Method for determnng transferred energy durng cargo transfer. Calculatng the transferred energy.1 Calculatng the gross transferred energy.1.1
More information6 Supplementary Materials
6 Supplementar Materals 61 Proof of Theorem 31 Proof Let m Xt z 1:T : l m Xt X,z 1:t Wethenhave mxt z1:t ˆm HX Xt z 1:T mxt z1:t m HX Xt z 1:T + mxt z 1:T HX We consder each of the two terms n equaton
More informationCinChE ProblemSolving Strategy Chapter 4 Development of a Mathematical Model. formulation. procedure
nhe roblemsolvng Strategy hapter 4 Transformaton rocess onceptual Model formulaton procedure Mathematcal Model The mathematcal model s an abstracton that represents the engneerng phenomena occurrng n
More informationPhysics 207: Lecture 20. Today s Agenda Homework for Monday
Physcs 207: Lecture 20 Today s Agenda Homework for Monday Recap: Systems of Partcles Center of mass Velocty and acceleraton of the center of mass Dynamcs of the center of mass Lnear Momentum Example problems
More informationThe Study of Teachinglearningbased Optimization Algorithm
Advanced Scence and Technology Letters Vol. (AST 06), pp.05 http://dx.do.org/0.57/astl.06. The Study of Teachnglearnngbased Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute
More informationGAUTENG DEPARTMENT OF EDUCATION SENIOR SECONDARY INTERVENTION PROGRAMME PHYSICAL SCIENCES GRADE 12 SESSION 1 (LEARNER NOTES)
PHYSICAL SCIENCES GRADE 1 SESSION 1 (LEARNER NOTES) TOPIC 1: MECHANICS PROJECTILE MOTION Learner Note: Always draw a dagram of the stuaton and enter all the numercal alues onto your dagram. Remember to
More informationMOUNT SAINT JOSEPH MILPERRA
Student Name : MOUNT SAINT JOSEPH MILPERRA MOUNT SAINT JOSEPH I YEAR 8 MATHEMATICS 17th November 2006 70 MINUTES (plus 5 mnutes readng tme)... :... INSTRUCTIONS: > WRITE IN BLUE OR BLACK PEN ONLY > ALL
More informationMAE140  Linear Circuits  Winter 16 Midterm, February 5
Instructons ME140  Lnear Crcuts  Wnter 16 Mdterm, February 5 () Ths exam s open book. You may use whatever wrtten materals you choose, ncludng your class notes and textbook. You may use a hand calculator
More informationEconomic and Social Council
Unted Natons Economc and Socal Councl Dstr.: General 26 October 2018 Orgnal: Englsh Economc Commsson for Europe Inland Transport Commttee World Forum for Harmonzaton of ehcle Regulatons Workng Party on
More informationSystem in Weibull Distribution
Internatonal Matheatcal Foru 4 9 no. 9 9495 Relablty Equvalence Factors of a SeresParallel Syste n Webull Dstrbuton M. A. ElDacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co
More informationCOMPLEX NUMBERS AND QUADRATIC EQUATIONS
COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s nonnegatve Hence the equatons x, x, x + 7 0 etc are not
More informationDefinition. Measures of Dispersion. Measures of Dispersion. Definition. The Range. Measures of Dispersion 3/24/2014
Measures of Dsperson Defenton Range Interquartle Range Varance and Standard Devaton Defnton Measures of dsperson are descrptve statstcs that descrbe how smlar a set of scores are to each other The more
More informationStudy on NonLinear Dynamic Characteristic of Vehicle. Suspension Rubber Component
Study on NonLnear Dynamc Characterstc of Vehcle Suspenson Rubber Component Zhan Wenzhang Ln Y Sh GuobaoJln Unversty of TechnologyChangchun, Chna Wang Lgong (MDI, Chna [Abstract] The dynamc characterstc
More informationThe Myerson value in terms of the link agent form: a technical note
The Myerson value n terms of the lnk agent form: a techncal note André Casajus (September 2008, ths verson: October 1, 2008, 18:16) Abstract We represent the Myerson (1977) value n terms of the value ntroduced
More informationSound 2: frequency analysis
COMP 546 Lecture 19 Sound 2: frequency analysis Tues. March 27, 2018 1 Speed of Sound Sound travels at about 340 m/s, or 34 cm/ ms. (This depends on temperature and other factors) 2 Wave equation Pressure
More informationPHYS 705: Classical Mechanics. Newtonian Mechanics
1 PHYS 705: Classcal Mechancs Newtonan Mechancs Quck Revew of Newtonan Mechancs Basc Descrpton: An dealzed pont partcle or a system of pont partcles n an nertal reference frame [Rgd bodes (ch. 5 later)]
More informationDr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur
Analyss of Varance and Desgn of ExpermentI MODULE VII LECTURE  3 ANALYSIS OF COVARIANCE Dr Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Any scentfc experment s performed
More informationELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM
ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look
More informationTHE SCIENTIFIC METHOD
THE SCIENTIFIC METHOD A Hypotheses, sad Medawar n 1964, are magnatve and nspratonal n character ; they are adventures of the mnd. He was argung n favour of the poston taken by Karl Popper n The Logc of
More informationMolecular structure: Diatomic molecules in the rigid rotor and harmonic oscillator approximations Notes on Quantum Mechanics
Molecular structure: Datomc molecules n the rgd rotor and harmonc oscllator approxmatons Notes on Quantum Mechancs http://quantum.bu.edu/notes/quantummechancs/molecularstructuredatomc.pdf Last updated
More informationCOS 511: Theoretical Machine Learning. Lecturer: Rob Schapire Lecture # 15 Scribe: Jieming Mao April 1, 2013
COS 511: heoretcal Machne Learnng Lecturer: Rob Schapre Lecture # 15 Scrbe: Jemng Mao Aprl 1, 013 1 Bref revew 1.1 Learnng wth expert advce Last tme, we started to talk about learnng wth expert advce.
More informationAnalysis of the Magnetomotive Force of a ThreePhase Winding with Concentrated Coils and Different Symmetry Features
Analyss of the Magnetomotve Force of a ThreePhase Wndng wth Concentrated Cols and Dfferent Symmetry Features Deter Gerlng Unversty of Federal Defense Munch, Neubberg, 85579, Germany Emal: Deter.Gerlng@unbw.de
More informationModule 2. Random Processes. Version 2 ECE IIT, Kharagpur
Module Random Processes Lesson 6 Functons of Random Varables After readng ths lesson, ou wll learn about cdf of functon of a random varable. Formula for determnng the pdf of a random varable. Let, X be
More informationVARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES
VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES BÂRZĂ, Slvu Faculty of MathematcsInformatcs Spru Haret Unversty barza_slvu@yahoo.com Abstract Ths paper wants to contnue
More informationCHE450G Final Exam. CP109 December 11, :3012:30 AM
CH450G Fnal xam CP09 December, 2006 0:302:30 AM Last name Frst Name Score [ /5] 00 = % () Construct a physcally realstc molecular orbtal dagram for CS. Draw all SALC s, molecular orbtals, and provde
More informationLecture 7: Gluing prevarieties; products
Lecture 7: Glung prevaretes; products 1 The category of algebrac prevaretes Proposton 1. Let (f,ϕ) : (X,O X ) (Y,O Y ) be a morphsm of algebrac prevaretes. If U X and V Y are affne open subvaretes wth
More informationTHE SUMMATION NOTATION Ʃ
Sngle Subscrpt otaton THE SUMMATIO OTATIO Ʃ Most of the calculatons we perform n statstcs are repettve operatons on lsts of numbers. For example, we compute the sum of a set of numbers, or the sum of the
More informationDEMO #8  GAUSSIAN ELIMINATION USING MATHEMATICA. 1. Matrices in Mathematica
demo8.nb 1 DEMO #8  GAUSSIAN ELIMINATION USING MATHEMATICA Obectves:  defne matrces n Mathematca  format the output of matrces  appl lnear algebra to solve a real problem  Use Mathematca to perform
More informationKinematics in 2Dimensions. Projectile Motion
Knematcs n Dmensons Projectle Moton A medeval trebuchet b Kolderer, c1507 http://members.net.net.au/~rmne/ht/ht0.html#5 Readng Assgnment: Chapter 4, Sectons 6 Introducton: In medeval das, people had
More informationTurbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH
Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant
More informationSound Correspondences in the World's Languages: Online Supplementary Materials
Sound Correspondences in the World's Languages: Online Supplementary Materials Cecil H. Brown, Eric W. Holman, Søren Wichmann Language, Volume 89, Number 1, March 2013, pp. s1s76 (Article) Published by
More informationCOMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD
COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, MskolcEgyetemváros,
More informationOne Dimensional Axial Deformations
One Dmensonal al Deformatons In ths secton, a specfc smple geometr s consdered, that of a long and thn straght component loaded n such a wa that t deforms n the aal drecton onl. The as s taken as the
More informationCOMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 63 ISSN: 97537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
More informationAffine and Riemannian Connections
Affne and Remannan Connectons Semnar Remannan Geometry Summer Term 2015 Prof Dr Anna Wenhard and Dr GyeSeon Lee Jakob Ullmann Notaton: X(M) space of smooth vector felds on M D(M) space of smooth functons
More informationAn Example file... log.txt
# ' ' Start of fie & %$ " 1  : 5? ;., B  ( * * B  ( * * F I / 0. ) +, * ( ) 8 8 7 /. 6 ) +, 5 5 3 2( 7 7 +, 6 6 9( 3 5( ) 70 +, =>  +< ( ) ) +, 7 / +, 5 9 (. 6 ) 0 * D>. C ) +, (A :, C 0 ) +,
More information6.3.7 Example with Runga Kutta 4 th order method
6.3.7 Example wth Runga Kutta 4 th order method Agan, as an example, 3 machne, 9 bus system shown n Fg. 6.4 s agan consdered. Intally, the dampng of the generators are neglected (.e. d = 0 for = 1, 2,
More informationInternational Power, Electronics and Materials Engineering Conference (IPEMEC 2015)
Internatonal Power, Electroncs and Materals Engneerng Conference (IPEMEC 2015) Dynamc Model of Wnd Speed Dstrbuton n Wnd Farm Consderng the Impact of Wnd Drecton and Interference Effects Zhe Dong 1, a,
More informationCollege of Computer & Information Science Fall 2009 Northeastern University 20 October 2009
College of Computer & Informaton Scence Fall 2009 Northeastern Unversty 20 October 2009 CS7880: Algorthmc Power Tools Scrbe: Jan Wen and Laura Poplawsk Lecture Outlne: Prmaldual schema Network Desgn:
More informationThis column is a continuation of our previous column
Comparson of Goodness of Ft Statstcs for Lnear Regresson, Part II The authors contnue ther dscusson of the correlaton coeffcent n developng a calbraton for quanttatve analyss. Jerome Workman Jr. and Howard
More information! " # $! % & '! , ) ( +  (. ) ( ) * + / 0 1 2 3 0 / 4 5 / 6 0 ; 8 7 < = 7 > 8 7 8 9 : Œ Š ž P P h ˆ Š ˆ Œ ˆ Š ˆ Ž Ž Ý Ü Ý Ü Ý Ž Ý ê ç è ± ¹ ¼ ¹ ä ± ¹ w ç ¹ è ¼ è Œ ¹ ± ¹ è ¹ è ä ç w ¹ ã ¼ ¹ ä ¹ ¼ ¹ ±
More informationWINTER 2017 EXAMINATION
(ISO/IEC  70000 Certfed) WINTER 07 EXAMINATION Model wer ject Code: Important Instructons to Eamners: ) The answers should be eamned by key words and not as wordtoword as gven n the model answer scheme.
More informationG4023 MidTerm Exam #1 Solutions
Exam1Solutons.nb 1 G03 MdTerm Exam #1 Solutons 1Oct0, 1:10 p.m to :5 p.m n 1 Pupn Ths exam s openbook, opennotes. You may also use prntouts of the homework solutons and a calculator. 1 (30 ponts,
More informationWeek 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product
The Vector Product Week 11: Chapter 11 Angular Momentum There are nstances where the product of two vectors s another vector Earler we saw where the product of two vectors was a scalar Ths was called the
More informationDr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur
Analyss of Varance and Desgn of ExpermentI MODULE VIII LECTURE  34 ANALYSIS OF VARIANCE IN RANDOMEFFECTS MODEL AND MIXEDEFFECTS EFFECTS MODEL Dr Shalabh Department of Mathematcs and Statstcs Indan
More informationLecture 10: May 6, 2013
TTIC/CMSC 31150 Mathematcal Toolkt Sprng 013 Madhur Tulsan Lecture 10: May 6, 013 Scrbe: Wenje Luo In today s lecture, we manly talked about random walk on graphs and ntroduce the concept of graph expander,
More information