Three-Dimensional Experimental Kinematics
|
|
- Άνεμονη Τρικούπης
- 5 χρόνια πριν
- Προβολές:
Transcript
1 Notes_5_3 o 8 Three-Dmesoal Epermetal Kematcs Dgte locatos o ladmarks { r } o bod or pots to at gve tme t All pots must be o same bod Use ladmark weghtg actor = pot k s avalable at tme t. Use = pot k ot avalable at gve tme t. r r r at gve tme t. Determe { } { } { } Mea values mea { r } = { r } / = = = = = / / / / k mea { r } { r } mea { r } { r } mea { r } { r } mea { r } { r } = mea [ X ] ({ r } { r } ){ r } { r } [ M] = ([ I3 ] trace( [ X] )) [ X] mea T ( ) / Veloct [ V] = mea T ( ) / { r } { r } { r } 32 { ω } = [ M] V V = ω ω = orm{ ω } V V 3 2 V V ω ω
2 ω [ ω ] = ω ω { û} = { ω} ω / ω ω ω Notes_5_3 2 o 8 ot ISA s o the stataeous screw as or bod at the root o the perpedcular rom the cetrod o the ladmarks. Note that the ISA s ot attached to the bod. A pot o the bod cocdet wth the ISA has traslatoal veloct s alog the ISA. ISA ( ) or a pot attached to bod { r } = s { û} + [ ω ]{ r } { r} ISA mea mea 2 { r} = { r } + [ ω]{ r } / ω s = { û} T { r } mea Accelerato [ A] = mea T ( ) / { r } { r } { r } [ B] = [ A] [ ω ][ ω ][ X] 32 { ω } = [ M] B B = ω ω = orm{ ω } B B 3 2 B B ω ω [ ω ] = ω ω [ β ] = [ ω ] ω ω ω ω ot IA s the stataeous accelerato pole or bod. Note that the IA s ot attached to the bod. ot o the bod cocdet wth IA has ero accelerato. IA ( ) { r } = [ β ]{ r } { r} or a pot attached to bod IA mea mea _ IA { r} = { r } [ β ] { r } or { r } _ at =
3 Notes_5_3 3 o 8 Jerk [ J] = mea T ( ) / { r } { r } { r } ( )[ X] [ H] = [ J] 2[ ω ] 32 { ω } = [ M] H H = ω ω = orm{ ω } H H 3 2 H H ω ω [ ω ] = ω ω [ η ] = [ ω ] + 2[ ω ] ω ω ω ω ot IJ s the stataeous jerk pole or bod. Note that the IJ s ot attached to the bod. ot o the bod cocdet wth IJ has ero jerk. IJ ( ) { r } = [ η ]{ r } { r} or a pot attached to bod IJ mea mea _ IJ { r} = { r } [ η ] { r } or { r} _ at = Secod Order Screw As Ω Ω 2 { Ω } = Ω = [ ω]{ ω }/ ω Ω = orm{ Ω} { tˆ } = { Ω} / Ω d = T IA IHA T ({ tˆ } [ β]{ ( r} { r} )/ { tˆ } [ β]{ û} { c} = { r} IHA + d{ û} ( ) T ({ } [ ω IA 2 tˆ ][ β]{ ( c} { r} )/ ω ) s Ω ω S = /
4 Notes_5_3 4 o 8 t_lm2k3d.m - test 3D kematcs rom ladmark moto HJSIII, 4..4 clear eample data - CRS = [ ]; r = [ ; ; ]; rd = [ ; ; ]; rdd = [ ; ; ]; rddd = [ ; ; ]; vel_test = [ ; ; ]; accel_test = [ ; ; ]; jerk_test = [.5. ; ; ]; aode_test = [ ; ; ]; eample data - RSUR = [ ]; r = [ ; ; ]; rd = [ ; ; ]; rdd = [ ; ; ]; rddd = [ ; ; ]; vel_test = [ ; ; ]; accel_test = [ ; ; ]; jerk_test = [ ; ;
5 Notes_5_3 5 o ]; aode_test = [ ; ; ]; test ucto [ vel, accel, jerk, aode ] = lm2k3d(, r, rd, rdd, rddd ) bottom o t_lm2k3d
6 Notes_5_3 6 o 8 ucto [ vel, accel, jerk, aode ] = lm2k3d(, r, rd, rdd, rddd ) 3D kematcs o a rgd bod rom ladmark moto HJSIII, 4..4 USAGE [ vel, accel, jerk, aode ] = lm2k3d(, r, rd, rdd, rddd ) INUTS - vector o weghts - (j)= meas data vald, (j)= meas data ot avalable r - 3 matr o,, ladmark locato rd - 3 matr o,, ladmark veloct rdd - 3 matr o,, ladmark accelerato rddd - 3 matr o,, ladmark jerk OUTUTS vel = [ w_vec risa sisa ] w_vec = 3 agular veloct vector risa = 3 locato o ISA at root o perpedcular rom cetrod o ladmarks sisa = sldg veloct vector alog ISA accel = [ wd_vec ria rdd_at_ia ] wd_vec = 3 agular accelerato vector ria = 3 locato o accelerato pole rdd_at_ia = 3 accelerato o pot o bod at IA jerk = [ wdd_vec rij rddd_at_ij ] wdd_vec = 3 agular jerk vector rij = 3 locato o jerk pole rddd_at_ij = 3 jerk o pot o bod at IJ aode = [ OMEGA_vec c Sd ] OMEGA_vec = 3 rotato o secod order screw c = 3 cetral pot o geerator Sd = 3 sldg veloct vector alog secod order screw costats eps = e-4; umber o coordates ad ladmarks [ coord, ] = se( r ); mea values mat = dag(); s = trace( mat ); rm = sum( mat*r' )' /s; rdm = sum( mat*rd' )' /s; rddm = sum( mat*rdd' )' /s; rdddm = sum( mat*rddd' )' /s; cetered locato rc = r - rm*oes(,); X = rc * mat * rc' /s; M = trace(x) * ee(coord) - X; Mv = v( M ); veloct V = rd * mat * rc' /s; w_vec = Mv * [ V(3,2)-V(2,3) ; V(,3)-V(3,) ; V(2,)-V(,2) ]; w = orm( w_vec ); w_mat = skew_sm( w_vec ); geeral veloct soluto w > eps, u = w_vec / w; sd = u' * rdm; risa = rm + w_mat * rdm / w^2; sisa = sd * u; specal case - w=, pure traslato risa s at cetrod o ladmarks, sisa s traslato veloct sd = orm( rdm ); u = rdm / sd;
7 Notes_5_3 7 o 8 risa = rm; sisa = rdm; ed accelerato A = rdd * mat * rc' / s; B = A - w_mat*w_mat * X; wd_vec = Mv * [ B(3,2)-B(2,3) ; B(,3)-B(3,) ; B(2,)-B(,2) ]; wd = orm( wd_vec ); wd_mat = skew_sm( wd_vec ); beta_mat = wd_mat + w_mat*w_mat; geeral accelerato soluto abs(det(beta_mat)) > eps; ria = rm - v(beta_mat) * rddm; rdd_at_ia = eros(coord,); specal case - w=, wd=, pure traslato ria s at cetrod o ladmarks, rdd_at_ia s traslato accelerato w < eps, wd < eps, sdd = orm( rddm ); e = rddm / sdd; ria = rm; rdd_at_ia = rddm; specal case 2 - w=, wd>, pure agular accelerato smlar to geeral agular veloct soluto ria s at root o perpedcular to agular accelerato vector rom cetrod o ladmarks rdd_at_ia s traslato accelerato e = wd_vec / wd; sdd = e' * rddm; ria = rm + wd_mat * rddm / wd^2; rdd_at_ia = sdd * e; ed specal case 3 - w>, wd=, pure agular veloct smlar to ero agular veloct soluto wd < eps, e = u; sdd = e' * rddm; rdd_at_ia = sdd * e; ria = rm + (rddm-rdd_at_ia) / w*w; specal case 4 - w>, wd>, w_vec parallel to wd_vec e = wd_vec / wd; sdd = e' * rddm; rdd_at_ia = sd * e; ed ed ed w2a = w*w*ee(3) - wd_mat; ria = rm + v(w2a) * (rddm-rdd_at_ia); jerk J = rddd * mat * rc' / s; eta_mat_mwdd = 2*wd_mat*w_mat + w_mat*wd_mat + w_mat*w_mat*w_mat; H = J - eta_mat_mwdd * X; wdd_vec = Mv * [ H(3,2)-H(2,3) ; H(,3)-H(3,) ; H(2,)-H(,2) ]; wdd = orm( wdd_vec ); h = wdd_vec / wdd; wdd_mat = skew_sm( wdd_vec ); eta_mat = eta_mat_mwdd + wdd_mat; rij = rm - v(eta_mat) * rdddm; rddd_at_ij = eros(coord,); secod order screw
8 Notes_5_3 8 o 8 OMEGA_vec = w_mat * wd_vec /w/w; OMEGA = orm( OMEGA_vec ); t = OMEGA_vec / OMEGA; d = t' * beta_mat * (ria-risa) / (t' * beta_mat * u ); c = risa + d * u; Sd = ( t' * w_mat * beta_mat * (c-ria) /w/w ) - sd * OMEGA /w; Sd_vec = Sd * t; retur argumets vel = [ w_vec risa sisa ]; accel = [ wd_vec ria rdd_at_ia ]; jerk = [ wdd_vec rij rddd_at_ij ]; aode = [ OMEGA_vec c Sd_vec ]; bottom o lm2k3d
CS 1675 Introduction to Machine Learning Lecture 7. Density estimation. Milos Hauskrecht 5329 Sennott Square
CS 675 Itroducto to Mache Learg Lecture 7 esty estmato Mlos Hausrecht mlos@cs.tt.edu 539 Seott Square ata: esty estmato {.. } a vector of attrbute values Objectve: estmate the model of the uderlyg robablty
Διαβάστε περισσότεραK r i t i k i P u b l i s h i n g - d r a f t
T ij = A Y i Y j /D ij A T ij i j Y i i Y j j D ij T ij = A Y α Y b i j /D c ij b c b c a LW a LC L P F Q W Q C a LW Q W a LC Q C L a LC Q C + a LW Q W L P F L/a LC L/a LW 1.000/2 = 500
Διαβάστε περισσότερα1. For each of the following power series, find the interval of convergence and the radius of convergence:
Math 6 Practice Problems Solutios Power Series ad Taylor Series 1. For each of the followig power series, fid the iterval of covergece ad the radius of covergece: (a ( 1 x Notice that = ( 1 +1 ( x +1.
Διαβάστε περισσότεραEstimators when the Correlation Coefficient. is Negative
It J Cotemp Math Sceces, Vol 5, 00, o 3, 45-50 Estmators whe the Correlato Coeffcet s Negatve Sad Al Al-Hadhram College of Appled Sceces, Nzwa, Oma abur97@ahoocouk Abstract Rato estmators for the mea of
Διαβάστε περισσότεραDESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.
DESIGN OF MACHINERY SOLUTION MANUAL -7-1! PROBLEM -7 Statement: Design a double-dwell cam to move a follower from to 25 6, dwell for 12, fall 25 and dwell for the remader The total cycle must take 4 sec
Διαβάστε περισσότεραn r f ( n-r ) () x g () r () x (1.1) = Σ g() x = Σ n f < -n+ r> g () r -n + r dx r dx n + ( -n,m) dx -n n+1 1 -n -1 + ( -n,n+1)
8 Higher Derivative of the Product of Two Fuctios 8. Leibiz Rule about the Higher Order Differetiatio Theorem 8.. (Leibiz) Whe fuctios f ad g f g are times differetiable, the followig epressio holds. r
Διαβάστε περισσότεραSolve the difference equation
Solve the differece equatio Solutio: y + 3 3y + + y 0 give tat y 0 4, y 0 ad y 8. Let Z{y()} F() Taig Z-trasform o both sides i (), we get y + 3 3y + + y 0 () Z y + 3 3y + + y Z 0 Z y + 3 3Z y + + Z y
Διαβάστε περισσότεραp n r.01.05.10.15.20.25.30.35.40.45.50.55.60.65.70.75.80.85.90.95
r r Table 4 Biomial Probability Distributio C, r p q This table shows the probability of r successes i idepedet trials, each with probability of success p. p r.01.05.10.15.0.5.30.35.40.45.50.55.60.65.70.75.80.85.90.95
Διαβάστε περισσότεραBoundary-Fitted Coordinates!
Computatoal Flud Damcs I Computatoal Flud Damcs I http://users.wp.edu/~gretar/me.html! Computatoal Methods or Domas wth! Comple Boudares-I! Grétar Trggvaso! Sprg 00! For most egeerg problems t s ecessar
Διαβάστε περισσότεραDiscrete Fourier Transform { } ( ) sin( ) Discrete Sine Transformation. n, n= 0,1,2,, when the function is odd, f (x) = f ( x) L L L N N.
Dscrete Fourer Trasform Refereces:. umercal Aalyss of Spectral Methods: Theory ad Applcatos, Davd Gottleb ad S.A. Orszag, Soc. for Idust. App. Math. 977.. umercal smulato of compressble flows wth smple
Διαβάστε περισσότεραSecond Order RLC Filters
ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor
Διαβάστε περισσότεραSrednicki Chapter 55
Srednicki Chapter 55 QFT Problems & Solutions A. George August 3, 03 Srednicki 55.. Use equations 55.3-55.0 and A i, A j ] = Π i, Π j ] = 0 (at equal times) to verify equations 55.-55.3. This is our third
Διαβάστε περισσότεραΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 24/3/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Όλοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα μικρότεροι του 10000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Αν κάπου κάνετε κάποιες υποθέσεις
Διαβάστε περισσότεραSimilarly, we may define hyperbolic functions cosh α and sinh α from the unit hyperbola
Universit of Hperbolic Functions The trigonometric functions cos α an cos α are efine using the unit circle + b measuring the istance α in the counter-clockwise irection along the circumference of the
Διαβάστε περισσότεραExam Statistics 6 th September 2017 Solution
Exam Statstcs 6 th September 17 Soluto Maura Mezzett Exercse 1 Let (X 1,..., X be a raom sample of... raom varables. Let f θ (x be the esty fucto. Let ˆθ be the MLE of θ, θ be the true parameter, L(θ be
Διαβάστε περισσότεραSUPERPOSITION, MEASUREMENT, NORMALIZATION, EXPECTATION VALUES. Reading: QM course packet Ch 5 up to 5.6
SUPERPOSITION, MEASUREMENT, NORMALIZATION, EXPECTATION VALUES Readig: QM course packet Ch 5 up to 5. 1 ϕ (x) = E = π m( a) =1,,3,4,5 for xa (x) = πx si L L * = πx L si L.5 ϕ' -.5 z 1 (x) = L si
Διαβάστε περισσότεραHomework 8 Model Solution Section
MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx
Διαβάστε περισσότεραEE512: Error Control Coding
EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3
Διαβάστε περισσότεραΝΕΑ ΑΠΟΤΕΛΕΣΜΑΤΑ ΣΧΕΤΙΚΑ ΜΕ ΤΗΝ ΥΠΑΡΞΗ ΕΚΤΙΜΗΤΩΝ ΜΕΓΙΣΤΗΣ ΠΙΘΑΝΟΦΑΝΕΙΑΣ ΓΙΑ ΤΗΝ 3-ΠΑΡΑΜΕΤΡΙΚΗ ΓΑΜΜΑ ΚΑΤΑΝΟΜΗ
Ελληνικό Στατιστικό Ινστιτούτο Πρακτικά ου Πανελληνίου Συνεδρίου Στατιστικής 008, σελ 9-98 ΝΕΑ ΑΠΟΤΕΛΕΣΜΑΤΑ ΣΧΕΤΙΚΑ ΜΕ ΤΗΝ ΥΠΑΡΞΗ ΕΚΤΙΜΗΤΩΝ ΜΕΓΙΣΤΗΣ ΠΙΘΑΝΟΦΑΝΕΙΑΣ ΓΙΑ ΤΗΝ 3-ΠΑΡΑΜΕΤΡΙΚΗ ΓΑΜΜΑ ΚΑΤΑΝΟΜΗ Γεώργιος
Διαβάστε περισσότεραExamples of Cost and Production Functions
Dvso of the Humates ad Socal Sceces Examples of Cost ad Producto Fuctos KC Border October 200 v 20605::004 These otes sho ho you ca use the frst order codtos for cost mmzato to actually solve for cost
Διαβάστε περισσότεραOperating Temperature Range ( C) ±1% (F) ± ~ 1M E-24 NRC /20 (0.05) W 25V 50V ±5% (J) Resistance Tolerance (Code)
FEATURES EIA STANDARD SIZING 0201(1/20), 0402(1/16), 0603(1/10), 0805(1/8), 1206(1/4), 1210(1/3), 2010(3/4) AND 2512(1) METAL GLAZED THICK FILM ON HIGH PURITY ALUMINA SUBSTRATE..(CERMET) PROVIDES UNIFORM
Διαβάστε περισσότερα8.1 The Nature of Heteroskedasticity 8.2 Using the Least Squares Estimator 8.3 The Generalized Least Squares Estimator 8.
8.1 The Nature of Heteroskedastcty 8. Usng the Least Squares Estmator 8.3 The Generalzed Least Squares Estmator 8.4 Detectng Heteroskedastcty E( y) = β+β 1 x e = y E( y ) = y β β x 1 y = β+β x + e 1 Fgure
Διαβάστε περισσότεραΨηφιακή Επεξεργασία Εικόνας
ΠΑΝΕΠΙΣΤΗΜΙΟ ΙΩΑΝΝΙΝΩΝ ΑΝΟΙΚΤΑ ΑΚΑΔΗΜΑΪΚΑ ΜΑΘΗΜΑΤΑ Ψηφιακή Επεξεργασία Εικόνας Φιλτράρισμα στο πεδίο των συχνοτήτων Διδάσκων : Αναπληρωτής Καθηγητής Νίκου Χριστόφορος Άδειες Χρήσης Το παρόν εκπαιδευτικό
Διαβάστε περισσότεραCHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS
CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =
Διαβάστε περισσότεραΠανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών. ΗΥ-570: Στατιστική Επεξεργασία Σήµατος. ιδάσκων : Α. Μουχτάρης. εύτερη Σειρά Ασκήσεων.
Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 2015 ιδάσκων : Α. Μουχτάρης εύτερη Σειρά Ασκήσεων Λύσεις Ασκηση 1. 1. Consder the gven expresson for R 1/2 : R 1/2
Διαβάστε περισσότεραPresentation of complex number in Cartesian and polar coordinate system
1 a + bi, aεr, bεr i = 1 z = a + bi a = Re(z), b = Im(z) give z = a + bi & w = c + di, a + bi = c + di a = c & b = d The complex cojugate of z = a + bi is z = a bi The sum of complex cojugates is real:
Διαβάστε περισσότερα( y) Partial Differential Equations
Partial Dierential Equations Linear P.D.Es. contains no owers roducts o the deendent variables / an o its derivatives can occasionall be solved. Consider eamle ( ) a (sometimes written as a ) we can integrate
Διαβάστε περισσότερα(6,5 μονάδες) Θέμα 1 ο. Τμήμα Πολιτικών Μηχανικών Σχολή Τεχνολογικών Εφαρμογών Διεθνές Πανεπιστήμιο Ελλάδος ΟΝΟΜΑΤΕΠΩΝΥΜΟ
Τμήμα Πολιτικών Μηχανικών Σχολή Τεχνολογικών Εφαρμογών Διεθνές Πανεπιστήμιο Ελλάδος ΤΕΛΙΚΗ ΕΞΕΤΑΣΗ ΕΡΓΑΣΤΗΡΙΟΥ ΑΡΙΘΜΗΤΙΚΗΣ ΑΝΑΛΥΣΗΣ ΕΑΡΙΝΟ ΕΞΑΜΗΝΟ ΑΚΑΔ. ΕΤΟΣ 08-09 ΔΙΔΑΣΚΩΝ : Χ. Βοζίκης ΟΝΟΜΑΤΕΠΩΝΥΜΟ Αριθμός
Διαβάστε περισσότεραAnswers - Worksheet A ALGEBRA PMT. 1 a = 7 b = 11 c = 1 3. e = 0.1 f = 0.3 g = 2 h = 10 i = 3 j = d = k = 3 1. = 1 or 0.5 l =
C ALGEBRA Answers - Worksheet A a 7 b c d e 0. f 0. g h 0 i j k 6 8 or 0. l or 8 a 7 b 0 c 7 d 6 e f g 6 h 8 8 i 6 j k 6 l a 9 b c d 9 7 e 00 0 f 8 9 a b 7 7 c 6 d 9 e 6 6 f 6 8 g 9 h 0 0 i j 6 7 7 k 9
Διαβάστε περισσότερα6.1. Dirac Equation. Hamiltonian. Dirac Eq.
6.1. Dirac Equation Ref: M.Kaku, Quantum Field Theory, Oxford Univ Press (1993) η μν = η μν = diag(1, -1, -1, -1) p 0 = p 0 p = p i = -p i p μ p μ = p 0 p 0 + p i p i = E c 2 - p 2 = (m c) 2 H = c p 2
Διαβάστε περισσότεραInertial Navigation Mechanization and Error Equations
Iertial Navigatio Mechaizatio ad Error Equatios 1 Navigatio i Earth-cetered coordiates Coordiate systems: i iertial coordiate system; ECI. e earth fixed coordiate system; ECEF. avigatio coordiate system;
Διαβάστε περισσότερα(6,5 μονάδες) Θέμα 1 ο. Τμήμα Πολιτικών Μηχανικών Σχολή Τεχνολογικών Εφαρμογών Διεθνές Πανεπιστήμιο Ελλάδος ΟΝΟΜΑΤΕΠΩΝΥΜΟ
Τμήμα Πολιτικών Μηχανικών Σχολή Τεχνολογικών Εφαρμογών Διεθνές Πανεπιστήμιο Ελλάδος ΤΕΛΙΚΗ ΕΞΕΤΑΣΗ ΕΡΓΑΣΤΗΡΙΟΥ ΑΡΙΘΜΗΤΙΚΗΣ ΑΝΑΛΥΣΗΣ ΕΑΡΙΝΟ ΕΞΑΜΗΝΟ ΑΚΑΔ. ΕΤΟΣ 8-9 ΔΙΔΑΣΚΩΝ : Χ. Βοζίκης ΟΝΟΜΑΤΕΠΩΝΥΜΟ Αριθμός
Διαβάστε περισσότεραL.K.Gupta (Mathematic Classes) www.pioeermathematics.com MOBILE: 985577, 4677 + {JEE Mai 04} Sept 0 Name: Batch (Day) Phoe No. IT IS NOT ENOUGH TO HAVE A GOOD MIND, THE MAIN THING IS TO USE IT WELL Marks:
Διαβάστε περισσότεραOne and two particle density matrices for single determinant HF wavefunctions. (1) = φ 2. )β(1) ( ) ) + β(1)β * β. (1)ρ RHF
One and two partcle densty matrces for sngle determnant HF wavefunctons One partcle densty matrx Gven the Hartree-Fock wavefuncton ψ (,,3,!, = Âϕ (ϕ (ϕ (3!ϕ ( 3 The electronc energy s ψ H ψ = ϕ ( f ( ϕ
Διαβάστε περισσότεραCYLINDRICAL & SPHERICAL COORDINATES
CYLINDRICAL & SPHERICAL COORDINATES Here we eamine two of the more popular alternative -dimensional coordinate sstems to the rectangular coordinate sstem. First recall the basis of the Rectangular Coordinate
Διαβάστε περισσότερα( )( ) ( ) ( )( ) ( )( ) β = Chapter 5 Exercise Problems EX α So 49 β 199 EX EX EX5.4 EX5.5. (a)
hapter 5 xercise Problems X5. α β α 0.980 For α 0.980, β 49 0.980 0.995 For α 0.995, β 99 0.995 So 49 β 99 X5. O 00 O or n 3 O 40.5 β 0 X5.3 6.5 μ A 00 β ( 0)( 6.5 μa) 8 ma 5 ( 8)( 4 ) or.88 P on + 0.0065
Διαβάστε περισσότεραHomework 3 Solutions
Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For
Διαβάστε περισσότεραF19MC2 Solutions 9 Complex Analysis
F9MC Solutions 9 Complex Analysis. (i) Let f(z) = eaz +z. Then f is ifferentiable except at z = ±i an so by Cauchy s Resiue Theorem e az z = πi[res(f,i)+res(f, i)]. +z C(,) Since + has zeros of orer at
Διαβάστε περισσότεραMatrices and Determinants
Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z
Διαβάστε περισσότεραChapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
Διαβάστε περισσότεραLifting Entry (continued)
ifting Entry (continued) Basic planar dynamics of motion, again Yet another equilibrium glide Hypersonic phugoid motion Planar state equations MARYAN 1 01 avid. Akin - All rights reserved http://spacecraft.ssl.umd.edu
Διαβάστε περισσότεραMacromechanics of a Laminate. Textbook: Mechanics of Composite Materials Author: Autar Kaw
Macromechanics of a Laminate Tetboo: Mechanics of Composite Materials Author: Autar Kaw Figure 4.1 Fiber Direction θ z CHAPTER OJECTIVES Understand the code for laminate stacing sequence Develop relationships
Διαβάστε περισσότεραMulti-Body Kinematics and Dynamics in Terms of Quaternions: Langrange Formulation in Covariant Form Rodriguez Approach
Nemaa D. Zorc Research Assstat Uversty of Belgrade Faculty of Mechacal Egeerg Mhalo P. Lazarevc Full Professor Uversty of Belgrade Faculty of Mechacal Egeerg Alesadar M. Smoovc Assstat Professor Uversty
Διαβάστε περισσότεραMulti-dimensional Central Limit Theorem
Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t tme
Διαβάστε περισσότεραHomework for 1/27 Due 2/5
Name: ID: Homework for /7 Due /5. [ 8-3] I Example D of Sectio 8.4, the pdf of the populatio distributio is + αx x f(x α) =, α, otherwise ad the method of momets estimate was foud to be ˆα = 3X (where
Διαβάστε περισσότεραOutline. Detection Theory. Background. Background (Cont.)
Outlie etectio heory Chapter7. etermiistic Sigals with Ukow Parameters afiseh S. Mazloum ov. 3th Backgroud Importace of sigal iformatio Ukow amplitude Ukow arrival time Siusoidal detectio Classical liear
Διαβάστε περισσότεραΣτο εστιατόριο «ToDokimasesPrinToBgaleisStonKosmo?» έξω από τους δακτυλίους του Κρόνου, οι παραγγελίες γίνονται ηλεκτρονικά.
Διαστημικό εστιατόριο του (Μ)ΑστροΈκτορα Στο εστιατόριο «ToDokimasesPrinToBgaleisStonKosmo?» έξω από τους δακτυλίους του Κρόνου, οι παραγγελίες γίνονται ηλεκτρονικά. Μόλις μια παρέα πελατών κάτσει σε ένα
Διαβάστε περισσότεραAppendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee
Appendi to On the stability of a compressible aisymmetric rotating flow in a pipe By Z. Rusak & J. H. Lee Journal of Fluid Mechanics, vol. 5 4, pp. 5 4 This material has not been copy-edited or typeset
Διαβάστε περισσότεραα β
6. Eerg, Mometum coefficiets for differet velocit distributios Rehbock obtaied ) For Liear Velocit Distributio α + ε Vmax { } Vmax ε β +, i which ε v V o Give: α + ε > ε ( α ) Liear velocit distributio
Διαβάστε περισσότεραEcon 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1
Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test
Διαβάστε περισσότεραΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα,
ΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα Βασίλειος Σύρης Τμήμα Επιστήμης Υπολογιστών Πανεπιστήμιο Κρήτης Εαρινό εξάμηνο 2008 Economcs Contents The contet The basc model user utlty, rces and
Διαβάστε περισσότεραVariance of Trait in an Inbred Population. Variance of Trait in an Inbred Population
Varance of Trat n an Inbred Populaton Varance of Trat n an Inbred Populaton Varance of Trat n an Inbred Populaton Revew of Mean Trat Value n Inbred Populatons We showed n the last lecture that for a populaton
Διαβάστε περισσότεραPractice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1
Conceptual Questions. State a Basic identity and then verify it. a) Identity: Solution: One identity is cscθ) = sinθ) Practice Exam b) Verification: Solution: Given the point of intersection x, y) of the
Διαβάστε περισσότεραReview: Molecules = + + = + + Start with the full Hamiltonian. Use the Born-Oppenheimer approximation
Review: Molecules Start with the full amiltonian Ze e = + + ZZe A A B i A i me A ma ia, 4πε 0riA i< j4πε 0rij A< B4πε 0rAB Use the Born-Oppenheimer approximation elec Ze e = + + A A B i i me ia, 4πε 0riA
Διαβάστε περισσότεραFEATURES APPLICATION PRODUCT T IDENTIFICATION PRODUCT T DIMENSION MAG.LAYERS
FEATURES RoHS compliant. Super low resistance, ultra high current rating. High performance (I sat) realized by metal dust core. Frequency Range: up to 1MHz. APPLICATION PDA, notebook, desktop, and server
Διαβάστε περισσότεραaluset sliding system for doors and windows
aluset sliding system for doors and windows ÐÉÓÔÏÐÏÉÇÔÉÊÁ - CERTIFICATES 4 aluset ÔÅ ÍÉÊÁ ÁÑÁÊÔÇÑÉÓÔÉÊÁ ÓÕÓÔÇÌÁÔÏÓ - SYSTEM TECHNICAL FEATURES aluset 5 ÔÅ ÍÉÊH ÐÅÑÉÃÑÁÖÇ - TECHNICAL DESCRIPTION TEXNIKH
Διαβάστε περισσότεραBoundary-Layer Flow over a Flat Plate Approximate Method
Bounar-aer lo oer a lat Plate Approimate Metho Transition Turbulent aminar The momentum balance on a control olume o the bounar laer leas to the olloing equation: + () The approimate metho o bounar laer
Διαβάστε περισσότεραStresses in a Plane. Mohr s Circle. Cross Section thru Body. MET 210W Mohr s Circle 1. Some parts experience normal stresses in
ME 10W E. Evans Stresses in a Plane Some parts eperience normal stresses in two directions. hese tpes of problems are called Plane Stress or Biaial Stress Cross Section thru Bod z angent and normal to
Διαβάστε περισσότεραQueensland University of Technology Transport Data Analysis and Modeling Methodologies
Queensland University of Technology Transport Data Analysis and Modeling Methodologies Lab Session #7 Example 5.2 (with 3SLS Extensions) Seemingly Unrelated Regression Estimation and 3SLS A survey of 206
Διαβάστε περισσότεραΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΤΜΗΜΑ ΟΔΟΝΤΙΑΤΡΙΚΗΣ ΕΡΓΑΣΤΗΡΙΟ ΟΔΟΝΤΙΚΗΣ ΚΑΙ ΑΝΩΤΕΡΑΣ ΠΡΟΣΘΕΤΙΚΗΣ
ΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΤΜΗΜΑ ΟΔΟΝΤΙΑΤΡΙΚΗΣ ΕΡΓΑΣΤΗΡΙΟ ΟΔΟΝΤΙΚΗΣ ΚΑΙ ΑΝΩΤΕΡΑΣ ΠΡΟΣΘΕΤΙΚΗΣ ΣΥΓΚΡΙΤΙΚΗ ΜΕΛΕΤΗ ΤΗΣ ΣΥΓΚΡΑΤΗΤΙΚΗΣ ΙΚΑΝΟΤΗΤΑΣ ΟΡΙΣΜΕΝΩΝ ΠΡΟΚΑΤΑΣΚΕΥΑΣΜΕΝΩΝ ΣΥΝΔΕΣΜΩΝ ΑΚΡΙΒΕΙΑΣ
Διαβάστε περισσότεραLecture 26: Circular domains
Introductory lecture notes on Partial Differential Equations - c Anthony Peirce. Not to be copied, used, or revised without eplicit written permission from the copyright owner. 1 Lecture 6: Circular domains
Διαβάστε περισσότεραLecture 13 - Root Space Decomposition II
Lecture 13 - Root Space Decomposition II October 18, 2012 1 Review First let us recall the situation. Let g be a simple algebra, with maximal toral subalgebra h (which we are calling a CSA, or Cartan Subalgebra).
Διαβάστε περισσότεραMath221: HW# 1 solutions
Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin
Διαβάστε περισσότεραFinite Field Problems: Solutions
Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The
Διαβάστε περισσότεραΚεφάλαιο 3. Εξίσωση Καθαρής Συναγωγής Εξίσωση Καθαρής Συναγωγής Ρύπου
Κεφάλαιο 3 Εξίσωση Καθαρής Συναγωγής Σύνοψη Παρουσιάζεται η εξίσωση συναγωγής και η αριθμητική λύση της με το αριθμητικό σχήμα FTBS. Αναλύονται οι έννοιες της συνέπειας, της ευστάθειας και της σύγκλισης
Διαβάστε περισσότεραMulti-dimensional Central Limit Theorem
Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t ();
Διαβάστε περισσότεραΜηχανική Μάθηση Hypothesis Testing
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Μηχανική Μάθηση Hypothesis Testing Γιώργος Μπορμπουδάκης Τμήμα Επιστήμης Υπολογιστών Procedure 1. Form the null (H 0 ) and alternative (H 1 ) hypothesis 2. Consider
Διαβάστε περισσότεραΚΖ ΙΩΝΙΔΕΙΑ 2014 8-9 ΕΤΩΝ ΝΙΚΑΙΑ 01-02 Φεβ 2014
ΚΖ ΙΩΝΙΔΕΙΑ 2014 8-9 ΕΤΩΝ ΝΙΚΑΙΑ 01-02 Φεβ 2014 1/2/2014 Πρωί 50m EΛΕΥΘΕΡΟ - ΑΓΟΡΙΑ 8 ΕΤΩΝ (50) 1 158554 ΓΙΑΝΝΟΠΟΥΛΟΣ ΜΗΝΑΣ 2006 ΠΕΡΑ ΑΓ8 00:41.64 2 163655 ΣΑΒΒΙΤΣ ΓΕΩΡΓΙΟΣ 2006 Α.Ο. Ω. ΑΓ8 00:45.07 3
Διαβάστε περισσότερα[1] P Q. Fig. 3.1
1 (a) Define resistance....... [1] (b) The smallest conductor within a computer processing chip can be represented as a rectangular block that is one atom high, four atoms wide and twenty atoms long. One
Διαβάστε περισσότεραPARTIAL NOTES for 6.1 Trigonometric Identities
PARTIAL NOTES for 6.1 Trigonometric Identities tanθ = sinθ cosθ cotθ = cosθ sinθ BASIC IDENTITIES cscθ = 1 sinθ secθ = 1 cosθ cotθ = 1 tanθ PYTHAGOREAN IDENTITIES sin θ + cos θ =1 tan θ +1= sec θ 1 + cot
Διαβάστε περισσότεραPolitical Science 552. Qualitative Variables. Dichotomous Predictor. Dummy Variables-Gender. Qualitative Variables March 3, 2004
Qualtatve Varables Marh, Poltal See 55 Qualtatve Varables Dhotomous Predtor Y PID Geder ( male, female) Y ( ) Y Y Y Y Dummy Varables-Geder. FT-BUSH PID GENDER. ge geder(v9). regress v6 v5 geder v6 Coef.
Διαβάστε περισσότεραCHAPTER 101 FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD
CHAPTER FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD EXERCISE 36 Page 66. Determine the Fourier series for the periodic function: f(x), when x +, when x which is periodic outside this rge of period.
Διαβάστε περισσότεραSymplecticity of the Störmer-Verlet algorithm for coupling between the shallow water equations and horizontal vehicle motion
Symplectcty of the Störmer-Verlet algorthm for couplng between the shallow water equatons and horzontal vehcle moton by H. Alem Ardakan & T. J. Brdges Department of Mathematcs, Unversty of Surrey, Guldford
Διαβάστε περισσότεραECE 308 SIGNALS AND SYSTEMS FALL 2017 Answers to selected problems on prior years examinations
ECE 308 SIGNALS AND SYSTEMS FALL 07 Answers to selected problems on prior years examinations Answers to problems on Midterm Examination #, Spring 009. x(t) = r(t + ) r(t ) u(t ) r(t ) + r(t 3) + u(t +
Διαβάστε περισσότεραLatent variable models Variational approximations.
CS 3750 Mache Learg Lectre 9 Latet varable moel Varatoal appromato. Mlo arecht mlo@c.ptt.e 539 Seott Sqare CS 750 Mache Learg Cooperatve vector qatzer Latet varable : meoalty bary var Oberve varable :
Διαβάστε περισσότεραLatent variable models Variational approximations.
CS 3750 Mache Learg Lectre 9 Latet varable moel Varatoal appromato. Mlo arecht mlo@c.ptt.e 539 Seott Sqare CS 750 Mache Learg Cooperatve vector qatzer Latet varable : meoalty bary var Oberve varable :
Διαβάστε περισσότεραNumerical Analysis FMN011
Numerical Analysis FMN011 Carmen Arévalo Lund University carmen@maths.lth.se Lecture 12 Periodic data A function g has period P if g(x + P ) = g(x) Model: Trigonometric polynomial of order M T M (x) =
Διαβάστε περισσότερα14 Lesson 2: The Omega Verb - Present Tense
Lesson 2: The Omega Verb - Present Tense Day one I. Word Study and Grammar 1. Most Greek verbs end in in the first person singular. 2. The present tense is formed by adding endings to the present stem.
Διαβάστε περισσότεραEE 570: Location and Navigation
EE 570: Locatio ad Navigatio INS Iitializatio Aly El-Osery Electrical Egieerig Departmet, New Mexico Tech Socorro, New Mexico, USA April 25, 2013 Aly El-Osery (NMT) EE 570: Locatio ad Navigatio April 25,
Διαβάστε περισσότεραThe Heisenberg Uncertainty Principle
Chemistry 460 Sprig 015 Dr. Jea M. Stadard March, 015 The Heiseberg Ucertaity Priciple A policema pulls Werer Heiseberg over o the Autobah for speedig. Policema: Sir, do you kow how fast you were goig?
Διαβάστε περισσότεραMarkov Processes and Applications
Markov rocesses ad Applcatos Dscrete-Tme Markov Chas Cotuous-Tme Markov Chas Applcatos Queug theory erformace aalyss ΠΜΣ524: Μοντελοποίηση και Ανάλυση Απόδοσης Δικτύων (Ι. Σταυρακάκης - ΕΚΠΑ) Dscrete-Tme
Διαβάστε περισσότεραΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ. ΕΠΛ 035: οµές εδοµένων και Αλγόριθµοι για Ηλεκτρολόγους Μηχανικούς και Μηχανικούς Υπολογιστών
ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ ΕΠΛ 035: οµές εδοµένων και Αλγόριθµοι για Ηλεκτρολόγους Μηχανικούς και Μηχανικούς Υπολογιστών Ακαδηµαϊκό έτος 2010 2011, Χειµερινό εξάµηνο Λύσεις Ασκήσεων Επανάληψης
Διαβάστε περισσότεραThin Film Chip Resistors
FETURES PRECISE TOLERNCE ND TEMPERTURE COEFFICIENT EI STNDRD CSE SIZES (0201 ~ 2512) LOW NOISE, THIN FILM (NiCr) CONSTRUCTION REFLOW SOLDERLE (Pb FREE TERMINTION FINISH) Type EI Size Power Rating at 70
Διαβάστε περισσότεραPartial Trace and Partial Transpose
Partial Trace and Partial Transpose by José Luis Gómez-Muñoz http://homepage.cem.itesm.mx/lgomez/quantum/ jose.luis.gomez@itesm.mx This document is based on suggestions by Anirban Das Introduction This
Διαβάστε περισσότεραThin Film Chip Resistors
FETURES PRECISE TOLERNCE ND TEMPERTURE COEFFICIENT EI STNDRD CSE SIZES (0201 ~ 2512) LOW NOISE, THIN FILM (NiCr) CONSTRUCTION REFLOW SOLDERLE (Pb FREE TERMINTION FINISH) RoHS Compliant includes all homogeneous
Διαβάστε περισσότεραGeneralized Fibonacci-Like Polynomial and its. Determinantal Identities
Int. J. Contemp. Math. Scences, Vol. 7, 01, no. 9, 1415-140 Generalzed Fbonacc-Le Polynomal and ts Determnantal Identtes V. K. Gupta 1, Yashwant K. Panwar and Ompraash Shwal 3 1 Department of Mathematcs,
Διαβάστε περισσότερα( )( ) ( )( ) 2. Chapter 3 Exercise Solutions EX3.1. Transistor biased in the saturation region
Chapter 3 Exercise Solutios EX3. TN, 3, S 4.5 S 4.5 > S ( sat TN 3 Trasistor biased i the saturatio regio TN 0.8 3 0. / K K K ma (a, S 4.5 Saturatio regio: 0. 0. ma (b 3, S Nosaturatio regio: ( 0. ( 3
Διαβάστε περισσότεραOutline. M/M/1 Queue (infinite buffer) M/M/1/N (finite buffer) Networks of M/M/1 Queues M/G/1 Priority Queue
Queueig Aalysis Outlie M/M/ Queue (ifiite buffer M/M//N (fiite buffer M/M// (Erlag s B forula M/M/ (Erlag s C forula Networks of M/M/ Queues M/G/ Priority Queue M/M/ M: Markovia/Meoryless Arrival process
Διαβάστε περισσότεραHistogram list, 11 RANDOM NUMBERS & HISTOGRAMS. r : RandomReal. ri : RandomInteger. rd : RandomInteger 1, 6
In[1]:= In[2]:= RANDOM NUMBERS & HISTOGRAMS r : RandomReal In[3]:= In[4]:= In[5]:= ri : RandomInteger In[6]:= rd : RandomInteger 1, 6 In[7]:= list Table rd rd, 100 2 dice Out[7]= 7, 11, 7, 10, 7, 8, 3,
Διαβάστε περισσότεραTridiagonal matrices. Gérard MEURANT. October, 2008
Tridiagonal matrices Gérard MEURANT October, 2008 1 Similarity 2 Cholesy factorizations 3 Eigenvalues 4 Inverse Similarity Let α 1 ω 1 β 1 α 2 ω 2 T =......... β 2 α 1 ω 1 β 1 α and β i ω i, i = 1,...,
Διαβάστε περισσότερα3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β
3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle
Διαβάστε περισσότεραCapacitors - Capacitance, Charge and Potential Difference
Capacitors - Capacitance, Charge and Potential Difference Capacitors store electric charge. This ability to store electric charge is known as capacitance. A simple capacitor consists of 2 parallel metal
Διαβάστε περισσότεραSOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM
SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr (T t N n) Pr (max (X 1,..., X N ) t N n) Pr (max
Διαβάστε περισσότεραEd Stanek. c08ed01v6.doc A version of the grant proposal to be submitted for review in 2008.
Relatnhp between tatn ued b ew Grant Applcatn, and Regren Predctr Develpment f Gnzala wth Suggeted Change t Cmmn tatn Baed n Gnzala and Stanek ntrductn Ed Stanek We lt ntatn ued n tw prncpal dcument, wth
Διαβάστε περισσότεραΠΑΛΙΟΓΙΑΝΝΗΣ ΓΡΗΓΟΡΙΟΣ ΜΠL/1033
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ ΣΧΟΛΗ ΧΗΜΙΚΩΝ ΜΗΧΑΝΙΚΩΝ ΠΑΝΕΠΙΣΤΗΜΙΟ ΠΕΙΡΑΙΩΣ ΤΜΗΜΑ ΒΙΟΜΗΧΑΝΙΚΗΣ ΔΙΟΙΚΗΣΗΣ & ΤΕΧΝΟΛΟΓΙΑΣ ΠΡΟΓΡΑΜΜΑ ΜΕΤΑΠΤΥΧΙΑΚΩΝ ΣΠΟΥΔΩΝ ΟΡΓΑΝΩΣΗ ΚΑΙ ΔΙΟΙΚΗΣΗ ΒΙΟΜΗΧΑΝΙΚΩΝ ΣΥΣΤΗΜΑΤΩΝ ΕΙΔΙΚΕΥΣΗ:
Διαβάστε περισσότεραCorrection Table for an Alcoholometer Calibrated at 20 o C
An alcoholometer is a device that measures the concentration of ethanol in a water-ethanol mixture (often in units of %abv percent alcohol by volume). The depth to which an alcoholometer sinks in a water-ethanol
Διαβάστε περισσότεραOther Test Constructions: Likelihood Ratio & Bayes Tests
Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :
Διαβάστε περισσότεραREAL-TIME CLOCKS MIXED-SIGNAL DESIGN GUIDE. Data Sheets Applications Notes Free Samples. DS32kHz
REAL-TIME CLOCKS MIXED-SIGNAL DESIGN GUIDE Data Sheets Applications Notes Free Samples DS32kHz TCXO 32.768kHz Dallas Semiconductor RTC RTC IC X1 DS32kHz 32kHz 4 1 DS32kHz 1998 RTC (V) SRAM 32kHz DS1500
Διαβάστε περισσότεραCongruence Classes of Invertible Matrices of Order 3 over F 2
International Journal of Algebra, Vol. 8, 24, no. 5, 239-246 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.2988/ija.24.422 Congruence Classes of Invertible Matrices of Order 3 over F 2 Ligong An and
Διαβάστε περισσότεραSecond Order Partial Differential Equations
Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y
Διαβάστε περισσότερα