Mechanical Design Technology (Free-form Surface) April 28, /12
|
|
|
- Patricia Maxwell
- 5 years ago
- Views:
Transcription
1 Mechacal Desg echolog Free-form Srface Prof. amos Mrakam Assgme #: Free-form Srface Geerao Make a program ha geeraes a bcbc eer srface from 4 4 defg polgo e pos ad dsplas he srface graphcall a a ha allos he hree-dmesoal feares of he srface o appear comprehesvel Yo ll eed approprae hreedmesoal rasformao ad proeco Sppose he 4 4 defg polgo e pos are specfed as ] 4; Accordg o he defo of a eer srface a po o he srface P ] for he parameers s calclaed dvdg he parameer rage ] o 6 ervals 7 7 pos ] /6 /6 5/6 ad o he srface are calclaed; coecg he calclaed pos h les ad makg a lace a mesh o appromae he eer srface s obaed he program o re ll eed o be able o ed he shape of he srface b chagg he 4 4 defg polgo e pos ecase of he coordae ssem of a NC mllg mache ad he ork se sbseqel sed hs corse se he rgh-had coordae ssem ad he oreao ad vale rage for he parameers ad shold be as follos ad o corol he horoal rage of he srface: ; : 75 o corol he cove/cocave shape of he srface: Mechacal Desg echolog Free-form Srface Aprl 8 4 /
2 Sbmsso Wha s Epeced Oe pred cop of he graphcs scree dsplag he eer srface ad defg polgo e Do o sbm he sorce code of or program a hs me he program s sed for Assgme # so do o delee afer o fsh Assgme # Deadle e 4 a he ed of he lecre Room 8- eer Crve Defo Defg polgo pos: ] Crve parameer: eer/erse bass fco bledg fco: A po o he eer crve: P ] P ] ]!!! Mechacal Desg echolog Free-form Srface Aprl 8 4 /
3 Aprl 8 4 Mechacal Desg echolog Free-form Srface / Eample: Cbc eer crve P s defed as a eghed sm of here a egh for s Some properes of he eer crve he crve geerall follos he shape of he defg polgo Ol he frs ad las pos of he defg polgo ad he crve are cocde he degree of he polomal defg he crve s oe less ha he mber of defg polgo pos he crve s vara der a affe rasformao ] P
4 Rogers ad Adams 99] Mechacal Desg echolog Free-form Srface Aprl 8 4 4/
5 Rogers ad Adams 99] Mechacal Desg echolog Free-form Srface Aprl 8 4 5/
6 Aprl 8 4 Mechacal Desg echolog Free-form Srface 6/ eer srface Eeso of a eer crve o he srface Defo Defg polgo e pos: ] Srface parameers: eer/erse bass fcos bledg fcos: K m A po o he eer srface: P ] Eample: cbc eer srface m ] m m m m m K K P ] K K K K P
7 ] ] Some properes of he eer srface he srface geerall follos he shape of he defg polgo e Ol he corer pos of he defg polgo e ad he srface are cocde he degree of he srface each paramerc dreco s oe less ha he mber of defg polgo e pos ha dreco he srface s vara der a affe rasformao Mechacal Desg echolog Free-form Srface Aprl 8 4 7/
8 Rogers ad Adams 99] Mechacal Desg echolog Free-form Srface Aprl 8 4 8/
9 Rogers ad Adams 99] Mechacal Desg echolog Free-form Srface Aprl 8 4 9/
10 Rogers ad Adams 99] Mechacal Desg echolog Free-form Srface Aprl 8 4 /
11 Aprl 8 4 Mechacal Desg echolog Free-form Srface / hree dmesoal rasformao Ordar coordaes: ] Homogeeos coordaes: ] 4 4 rasformao mar: ] Composo of rasformaos Mar mlplcao Scalg Roao abo as Roao abo as Roao abo as raslao Referece Rogers D.F. ad Adams.A. Mahemacal Elemes for Comper Graphcs d ed. McGra-Hll 99. ] ] ] ' ' ' cos s s cos ] ] S S S ] cos s s cos ] cos s s cos ] ] ] ] Λ ] ] ' ' '
12 Implemeao H pblc class bcbc_beer_srface { prvae doble bass_fco doble { } } prvae vecord srface_popo_lace polgo_e doble doble { /* Loop for ad */ polgo_e.ge_po ; bass_fco ; bass_fco ; } pblc vod dragraphcsd g po_lace polgo_e doble]] mar { /* Loop for ad */ srface_popolgo_e.rasformmar; } Mechacal Desg echolog Free-form Srface Aprl 8 4 /
Geometric Modeling
Geomerc Modelg 9.58. Crves coed Cc Bezer ad B-Sle Crves Far Chaers 4-5 8 Moreso Chaers 4 5 4 Tycal Tyes of Paramerc Crves Corol os flece crve shae. Ierolag Crve asses hrogh all corol os. Herme Defed y
B-spline curves. 1. Properties of the B-spline curve. control of the curve shape as opposed to global control by using a special set of blending
B-sple crve Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last pdated: Yeh-Lag Hs (--9). ote: Ths s the corse materal for ME Geometrc modelg ad compter graphcs, Ya Ze Uversty. art of ths materal
Least squares and motion. Nuno Vasconcelos ECE Department, UCSD
Leas squares ad moo uo Vascocelos ECE Deparme UCSD Pla for oda oda we wll dscuss moo esmao hs s eresg wo was moo s ver useful as a cue for recogo segmeao compresso ec. s a grea eample of leas squares problem
Analytical modelling of extruded plates
paper ID: 56 /p. Aalcal modellg of erded plaes C. Pézera, J.-L. Gader Laboraore Vbraos Acosqe, INSA de Lo,5 bs a.j. Cappelle 696 VILLEURBANNE Cede Erded plaes are ofe sed o bld lgh srcres h hgh sffess.
Final Exam Applied Econometrics
Fal Eam Appled Ecoomercs. 0 Sppose we have he followg regresso resl: Depede Varable: SAT Sample: 437 Iclded observaos: 437 Whe heeroskedasc-cosse sadard errors & covarace Varable Coeffce Sd. Error -Sasc
The Linear Regression Of Weighted Segments
The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed
HYPOTHESIS TESTING. four steps
Irodcio o Saisics i Psychology PSY 20 Professor Greg Fracis Lecre 24 Correlaios ad proporios Ca yo read my mid? Par II HYPOTHESIS TESTING for seps. Sae he hypohesis. 2. Se he crierio for rejecig H 0. 3.
Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF
EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae
AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending
CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral
Introduction to Mathematical Modeling and Computation
Ole Lecre Noe Irodco o Mahemacal Modelg ad Compao Verso.0 Aprl 08 Saor Yamamoo Professor Dr. Eg. Laboraory of Mahemacal Modelg ad Compao Dep. of Comper ad Mahemacal Sceces oho Uversy Seda 980-8579 Japa
Interactive Shape Preserving Interpolation by T-conic Spiral Spline
hp://www.spubs.org/cgacc/ Compuer Graphcs ad CAD/CAM (8 5 4 A Ieraoal Joural Ieracve Shape Preservg Ierpolao b T-coc Spral Sple Zulfqar Habb * Deparme of Compuer Scece Naoal Uvers of Compuer & Emergg Sceces
Linear Regression Linear Regression with Shrinkage
Lear Regresso Lear Regresso h Shrkage Iroduco Regresso meas predcg a couous (usuall scalar oupu from a vecor of couous pus (feaures x. Example: Predcg vehcle fuel effcec (mpg from 8 arbues: Lear Regresso
NUMERICAL EVALUATION of DYNAMIC RESPONSE
NUMERICAL EVALUATION of YNAMIC RESPONSE Aalycal solo of he eqao of oo for a sgle degree of freedo syse s sally o ossble f he excao aled force or grod accelerao ü g -vares arbrarly h e or f he syse s olear.
( ) ( ) Weibull Distribution: k ti. u u. Suppose t 1, t 2, t n are times to failure of a group of n mechanisms. The likelihood function is
Webll Dsbo: Des Bce Dep of Mechacal & Idsal Egeeg The Uvesy of Iowa pdf: f () exp Sppose, 2, ae mes o fale of a gop of mechasms. The lelhood fco s L ( ;, ) exp exp MLE: Webll 3//2002 page MLE: Webll 3//2002
1.225J J (ESD 205) Transportation Flow Systems
.5J J ESD 5 Trasporaio Flow Sysems Lecre 3 Modelig Road Traffic Flow o a Li Prof. Ismail Chabii ad Prof. Amedeo Odoi Lecre 3 Olie Time-Space Diagrams ad Traffic Flow Variables Irodcio o Li Performace Models
FORCED VIBRATION of MDOF SYSTEMS
FORCED VIBRAION of DOF SSES he respose of a N DOF sysem s govered by he marx equao of moo: ] u C] u K] u 1 h al codos u u0 ad u u 0. hs marx equao of moo represes a sysem of N smulaeous equaos u ad s me
Solution set Stat 471/Spring 06. Homework 2
oluo se a 47/prg 06 Homework a Whe he upper ragular elemes are suppressed due o smmer b Le Y Y Y Y A weep o he frs colum o oba: A ˆ b chagg he oao eg ad ec YY weep o he secod colum o oba: Aˆ YY weep o
Geometric Modeling
Geometrc Modelg 9.580.0 Crves Morteso Chater -5 ad Agel Chater 9 Crve Bascs Crve: Locs of a ot movg wth degree of freedom. Some tyes of eqatos to descrbe crves: Itrsc o relace o exteral frame of referece
Fundamentals of Regression Analysis
Fdametals of Regresso Aalyss Regresso aalyss s cocered wth the stdy of the depedece of oe varable, the depedet varable, o oe or more other varables, the explaatory varables, wth a vew of estmatg ad/or
Unit 10. The Lie Algebra of Vector Fields
U 10. The Le Algebra of Vecor Felds ================================================================================================================================================================ -----------------------------------
Competitive Facility Location Problem with Demands Depending on the Facilities
Aa Pacc Maageme Revew 4) 009) 5-5 Compeve Facl Locao Problem wh Demad Depedg o he Facle Shogo Shode a* Kuag-Yh Yeh b Hao-Chg Ha c a Facul of Bue Admrao Kobe Gau Uver Japa bc Urba Plag Deparme Naoal Cheg
Continuous Time Markov Chains
Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,
NUMERICAL SOLUTIONS TO ORDINARY DIFFERENTIAL EQUATIONS
NUMERICAL SOLUTIONS TO ORDINARY DIFFERENTIAL EQUATIONS If e eqao coas dervaves of a - order s sad o be a - order dffereal eqao. For eample a secod-order eqao descrbg e oscllao of a weg aced po b a sprg
14. Poisson Processes
4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur
DISTURBANCE TERMS. is a scalar and x i
DISTURBANCE TERMS I a feld of research desg, we ofte have the qesto abot whether there s a relatoshp betwee a observed varable (sa, ) ad the other observed varables (sa, x ). To aswer the qesto, we ma
Support vector machines II
CS 75 Mache Learg Lecture Support vector maches II Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Learl separable classes Learl separable classes: here s a hperplae that separates trag staces th o error
Theory and application of the generalized integral representation method (GIRM) in advection diffusion problem
Appled ad ompaoal Mahemacs 4; 4: 7-49 blshed ole Ags 4 hp://www.scecepblshggrop.com//acm do:.648/.acm.44.5 IN: 8-565 r; IN: 8-56 Ole Theory ad applcao of he geeralzed egral represeao mehod IRM adveco dffso
Binary classification: Support Vector Machines
CS 57 Itroducto to AI Lecture 6 Bar classfcato: Support Vector Maches Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square CS 57 Itro to AI Supervsed learg Data: D { D, D,.., D} a set of eamples D, (,,,,,
CS 1675 Introduction to Machine Learning Lecture 12 Support vector machines
CS 675 Itroducto to Mache Learg Lecture Support vector maches Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Mdterm eam October 9, 7 I-class eam Closed book Stud materal: Lecture otes Correspodg chapters
Solving fuzzy linear programming problems with piecewise linear membership functions by the determination of a crisp maximizing decision
Frs Jo Cogress o Fuzzy ad Iellge Sysems Ferdows Uversy of Mashhad Ira 9-3 Aug 7 Iellge Sysems Scefc Socey of Ira Solvg fuzzy lear programmg problems wh pecewse lear membershp fucos by he deermao of a crsp
Mechanics of Materials CIVL 3322 / MECH 3322
Mechacs of Materals CVL / MECH Cetrods ad Momet of erta Calculatos Cetrods = A = = = A = = Cetrod ad Momet of erta Calculatos z= z A = = Parallel As Theorem f ou kow the momet of erta about a cetrodal
General Complex Fuzzy Transformation Semigroups in Automata
Joural of Advaces Compuer Research Quarerly pissn: 345-606x eissn: 345-6078 Sar Brach Islamc Azad Uversy Sar IRIra Vol 7 No May 06 Pages: 7-37 wwwacrausaracr Geeral Complex uzzy Trasformao Semgroups Auomaa
Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem
Mahmacal ascs 8 Chapr VIII amplg Dsrbos ad h Cral Lm Thorm Fcos of radom arabls ar sall of rs sascal applcao Cosdr a s of obsrabl radom arabls L For ampl sppos h arabls ar a radom sampl of s from a poplao
Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model
. Projec Iroduco Fudameals of Speech Recogo Suggesed Projec The Hdde Markov Model For hs projec, s proposed ha you desg ad mpleme a hdde Markov model (HMM) ha opmally maches he behavor of a se of rag sequeces
Chapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I
CEE49b Chaper - Free Vbrao of M-Degree-of-Freedo Syses - I Free Udaped Vbrao The basc ype of respose of -degree-of-freedo syses s free daped vbrao Aaogos o sge degree of freedo syses he aayss of free vbrao
For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body.
The kecs of rgd bodes reas he relaoshps bewee he exeral forces acg o a body ad he correspodg raslaoal ad roaoal moos of he body. he kecs of he parcle, we foud ha wo force equaos of moo were requred o defe
The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3.
C. Trael me cures for mulple reflecors The ray pahs ad rael mes for mulple layers ca be compued usg ray-racg, as demosraed Lab. MATLAB scrp reflec_layers_.m performs smple ray racg. (m) ref(ms) ref(ms)
An Extended Single-valued Neutrosophic Normalized Weighted Bonferroni Mean Einstein Aggregation Operator
Eeded Sgle-valed Nerosohc Normalzed Weghed Boferro Mea Ese ggregao Oeraor Lha Yag Baol L bsrac I order o deal wh he deermae formao ad cosse formao esg commo real decso makg roblems a eeded Sgle-valed Nerosohc
Equivalent Finite Element Formulations for the Calculation of Eigenvalues Using Higher-Order Polynomials
Appled Mahemacs: ; (: 3-3 DOI:. 593/.am.. Equvale Fe Eleme Formulaos for he Calculao of Egevalues Usg Hgher-Order Polyomals C. G. Provads Deparme of Mechacal Egeerg, Naoal echcal Uversy of Ahes, Ahes,
Chapter 2. Review of Hydrodynamics and Vector Analysis
her. Ree o Hdrodmcs d Vecor Alss. Tlor seres L L L L ' ' L L " " " M L L! " ' L " ' I s o he c e romed he Tlor seres. O he oher hd ' " L . osero o mss -dreco: L L IN ] OUT [mss l [mss l] mss ccmled h me
Cyclone. Anti-cyclone
Adveco Cycloe A-cycloe Lorez (963) Low dmesoal aracors. Uclear f hey are a good aalogy o he rue clmae sysem, bu hey have some appealg characerscs. Dscusso Is he al codo balaced? Is here a al adjusme
Introduction. Question: Why do we need new forms of parametric curves? Answer: Those parametric curves discussed are not very geometric.
Itrodctio Qestio: Why do we eed ew forms of parametric crves? Aswer: Those parametric crves discssed are ot very geometric. Itrodctio Give sch a parametric form, it is difficlt to kow the derlyig geometry
DESIGN OF OBSERVERS FOR A CLASS OF NONLINEAR SYSTEMS IN ASSOCIATIVE OBSERVER FORM
MODELLING SIMULATION AND IDENTIFICATION OF PROCESSES DESIGN OF OBSERVERS FOR A CLASS OF NONLINEAR SYSTEMS IN ASSOCIATIVE OBSERVER FORM Ü Koa T Mllar R Pearso Absrac Coos or he esece o a observer orm or
Suppose we have observed values t 1, t 2, t n of a random variable T.
Sppose we have obseved vales, 2, of a adom vaable T. The dsbo of T s ow o belog o a cea ype (e.g., expoeal, omal, ec.) b he veco θ ( θ, θ2, θp ) of ow paamees assocaed wh s ow (whee p s he mbe of ow paamees).
An Exact Solution for the Differential Equation. Governing the Lateral Motion of Thin Plates. Subjected to Lateral and In-Plane Loadings
Appled Mahemacal Sceces, Vol., 8, o. 34, 665-678 A Eac Soluo for he Dffereal Equao Goverg he Laeral Moo of Th Plaes Subjeced o Laeral ad I-Plae Loadgs A. Karmpour ad D.D. Gaj Mazadara Uvers Deparme of
QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA
QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.
The Poisson Process Properties of the Poisson Process
Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad
Probability Bracket Notation and Probability Modeling. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA 94087, USA. Abstract
Probably Bracke Noao ad Probably Modelg Xg M. Wag Sherma Vsual Lab, Suyvale, CA 94087, USA Absrac Ispred by he Drac oao, a ew se of symbols, he Probably Bracke Noao (PBN) s proposed for probably modelg.
4. THE DENSITY MATRIX
4. THE DENSTY MATRX The desy marx or desy operaor s a alerae represeao of he sae of a quaum sysem for whch we have prevously used he wavefuco. Alhough descrbg a quaum sysem wh he desy marx s equvale o
EE 6885 Statistical Pattern Recognition
EE 6885 Sascal Paer Recogo Fall 005 Prof. Shh-Fu Chag hp://www.ee.columba.edu/~sfchag Lecure 5 (9//05 4- Readg Model Parameer Esmao ML Esmao, Chap. 3. Mure of Gaussa ad EM Referece Boo, HTF Chap. 8.5 Teboo,
(1) Cov(, ) E[( E( ))( E( ))]
![(1) Cov(, ) E[( E( ))( E( ))]](/thumbs/86/94405490.jpg "(1) Cov(, ) E[( E( ))( E( ))]")
Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )
Hydraulic Model of Dam Break Using Navier Stokes Equation with Arbitrary Lagrangian-Eulerian Approach
IACIT Ieraoal Joral of Egeerg ad Tecolog ol. 8 No. 4 Ags 6 dralc odel of Dam Break Usg Naer okes Eqao Arbrar Lagraga-Elera Aroac Alreza Lorasb oarram Dolasa Prooz ad Alreza Laae Absrac Te lqd flo ad e
Numerical Method for Ordinary Differential Equation
Numerical ehod for Ordiar Differeial Equaio. J. aro ad R. J. Lopez, Numerical Aalsis: A Pracical Approach, 3rd Ed., Wadsworh Publishig Co., Belmo, CA (99): Chap. 8.. Iiial Value Problem (IVP) d (IVP):
Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination
Lecure 3 Topc : Drbuo, hypohe eg, ad ample ze deermao The Sude - drbuo Coder a repeaed drawg of ample of ze from a ormal drbuo of mea. For each ample, compue,,, ad aoher ac,, where: The ac he devao of
Computational Functional Anatomy
Compuaoal Fucoal Aaomy Aq Qu Dvso of Boegeerg Compuaoal Fucoal Aaomy CFA s he mahemacal sudy of aaomcal cofguraos ad sgals assocaed wh aaomy ad fucos aaomcal coordaes. ulmodal Images MRI DTI fmri 5 Sascal
-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for
Assgme Sepha Brumme Ocober 8h, 003 9 h semeser, 70544 PREFACE I 004, I ed o sped wo semesers o a sudy abroad as a posgraduae exchage sude a he Uversy of Techology Sydey, Ausrala. Each opporuy o ehace my
Moving Least Squares Coordinates. Josiah Manson and Scott Schaefer Texas A&M University
Movg Leas Squares Coordaes Josah Maso ad Sco Schaefer Teas A&M Uversy Barycerc Coordaes olygo Doma p 4 p 3 p 2 p 0 p Barycerc Coordaes olygo Doma 4 3 2 0 Barycerc Coordaes olygo Doma f 4 f 3 f 2 f 0 f
Supervised learning: Linear regression Logistic regression
CS 57 Itroducto to AI Lecture 4 Supervsed learg: Lear regresso Logstc regresso Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square CS 57 Itro to AI Data: D { D D.. D D Supervsed learg d a set of eamples s
An Introduction to. Support Vector Machine
A Itroducto to Support Vector Mache Support Vector Mache (SVM) A classfer derved from statstcal learg theory by Vapk, et al. 99 SVM became famous whe, usg mages as put, t gave accuracy comparable to eural-etwork
Cosmic Microwave Background Radiation. Carl W. Akerlof April 7, 2013
Cosmic Microwave Backgrond Radiation Carl W. Akerlof April 7, 013 Notes: Dry ice sblimation temperatre: Isopropyl alcohol freezing point: LNA operating voltage: 194.65 K 184.65 K 18.0 v he terrestrial
Multiphase Flow Simulation Based on Unstructured Grid
200 Tuoral School o Flud Dyamcs: Topcs Turbulece Uversy of Marylad, May 24-28, 200 Oule Bacgroud Mulphase Flow Smulao Based o Usrucured Grd Bubble Pacg Mehod mehod Based o he Usrucured Grd Remar B CHEN,
Synchronization of Complex Network System with Time-Varying Delay Via Periodically Intermittent Control
Sychrozao of Complex ework Sysem wh me-varyg Delay Va Perodcally Ierme Corol JIAG Ya Deparme of Elecrcal ad Iformao Egeerg Hua Elecrcal College of echology Xaga 4, Cha Absrac he sychrozao corol problem
Existence and Uniqueness of the Optimal Control in Hilbert Spaces for a Class of Linear Systems
Iellge Iformao aageme 34-4 do:436/m6 Pblshed Ole Febrar (hp://wwwscrporg/joral/m Esece ad eess of he Opmal Corol lber Spaces for a Class of Lear Ssems Absrac ha Popesc Ise of ahemacal Sascs ad Appled ahemacs
Centroids Method of Composite Areas
Cetrods Method of Composte reas small boy swallowed some cos ad was take to a hosptal. Whe hs gradmother telephoed to ask how he was a urse sad 'No chage yet'. Cetrods Prevously, we developed a geeral
A note on Turán number Tk ( 1, kn, )
A oe o Turá umber T (,, ) L A-Pg Beg 00085, P.R. Cha apl000@sa.com Absrac: Turá umber s oe of prmary opcs he combaorcs of fe ses, hs paper, we wll prese a ew upper boud for Turá umber T (,, ). . Iroduco
FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below.
Jorge A. Ramírez HOMEWORK NO. 6 - SOLUTION Problem 1.: Use he Sorage-Idcao Mehod o roue he Ipu hydrograph abulaed below. Tme (h) Ipu Hydrograph (m 3 /s) Tme (h) Ipu Hydrograph (m 3 /s) 0 0 90 450 6 50
and the sum of its first n terms be denoted by. Convergence: An infinite series is said to be convergent if, a definite unique number., finite.
INFINITE SERIES Seqece: If a set of real mbers a seqece deoted by * + * Or * + * occr accordig to some defiite rle, the it is called + if is fiite + if is ifiite Series: is called a series ad is deoted
Construction of resilient S-boxes with higherdimensional vectorial outputs and strictly almost optimal non-linearity
IET Iformao Secry Research Arcle Cosrco of resle S-boxes wh hgherdmesoal vecoral ops ad srcly almos opmal o-leary ISSN 1751-8709 Receved o 1s Aprl 2016 Acceped o 21s Je 2016 E-Frs o 12h Sepember 2016 do:
A Constitutive Model for Multi-Line Simulation of Granular Material Behavior Using Multi-Plane Pattern
Joural of Compuer Scece 5 (): 8-80, 009 ISSN 549-009 Scece Publcaos A Cosuve Model for Mul-Le Smulao of Graular Maeral Behavor Usg Mul-Plae Paer S.A. Sadread, A. Saed Darya ad M. Zae KN Toos Uversy of
Course Outline. Course Outline. Computer Graphics (Fall 2008) Motivation. Outline of Unit. Bezier Curve (with HW2 demo)
Compter Graphics (Fall 2008) COMS 4160, Lectre 6: Crves 1 http://www.cs.colmbia.ed/~cs4160 3D Graphics Pipelie Modelig (Creatig 3D Geometry) Corse Otlie Rederig (Creatig, shadig images from geometry, lightig,
IV. Engineering Plasticity 4.1 Engineering plasticity 4.2 Elastoplaticity
IV. Eeer lasc 4. Eeer lasc 4. Elasolac Refereces. For smulao (M. S. Jou,, Jseam Meda). Advaced sold mechacs ad fe eleme mehod (M. S. Jou, 9, Jseam Meda) 4. Eeer lasc Tesor quaes ad her dcal oao Coordae
Course Outline. Curves for Modeling. Graphics Pipeline. Outline of Unit. Motivation. Foundations of Computer Graphics (Spring 2012)
Fodatios of Compter Graphics (Sprig 0) CS 84, Lectre : Crves http://ist.eecs.bereley.ed/~cs84 3D Graphics Pipelie Corse Otlie Modelig Aimatio Rederig Graphics Pipelie Crves for Modelig I HW, HW, draw,
Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables
Joural of Sceces Islamc epublc of Ira 6(: 63-67 (005 Uvers of ehra ISSN 06-04 hp://scecesuacr Some Probabl Iequales for Quadrac Forms of Negavel Depede Subgaussa adom Varables M Am A ozorga ad H Zare 3
Eigen analysis The correlation matrix plays a large role in statistical characterization and processing. It was previously shown that R is Hermetian
ge aalss he orrelato matr plas a large role statstal haraterzato ad proessg It as preosl sho that s ermeta We ll o frther aalze the orrelato matr throgh ege aalss - egeales ad etors - matr dagoalzato -
Mat 267 Engineering Calculus III Updated on 04/30/ x 4y 4z 8x 16y / 4 0. x y z x y. 4x 4y 4z 24x 16y 8z.
Ma 67 Engineering Calcls III Updaed on 04/0/0 r. Firoz Tes solion:. a) Find he cener and radis of he sphere 4 4 4z 8 6 0 z ( ) ( ) z / 4 The cener is a (, -, 0), and radis b) Find he cener and radis of
SYRIAN SEISMIC CODE :
SYRIAN SEISMIC CODE 2004 : Two sac mehods have bee ssued Syra buldg code 2004 o calculae he laeral sesmc forces he buldg. The Frs Sac Mehod: I s he same mehod he prevous code (995) wh few modfcaos. I s
UNIT 1: ANALYTICAL METHODS FOR ENGINEERS
UNIT : ANALYTICAL METHODS FOR ENGINEERS Ui code: A// QCF Level: Credi vale: OUTCOME TUTORIAL SERIES Ui coe Be able o aalyse ad model egieerig siaios ad solve problems sig algebraic mehods Algebraic mehods:
Least squares and motion. Nuno Vasconcelos ECE Department, UCSD
Las squars ad moo uo Vascoclos ECE Dparm UCSD Pla for oda oda w wll dscuss moo smao hs s rsg wo was moo s vr usful as a cu for rcogo sgmao comprsso c. s a gra ampl of las squars problm w wll also wrap
Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations
Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare
Lab Manual for Engrd 202, Virtual Torsion Experiment. Aluminum module
Lab Manal for Engrd 202, Virtal Torsion Experiment Alminm modle Introdction In this modle, o will perform data redction and analsis for circlar cross section alminm samples. B plotting the torqe vs. twist
Time-Domain Finite Element Method in Electromagnetics A Brief Review
Tme-Doma Fe leme ehod lecromagecs A ref Revew y D. Xe Ph.D. Tme doma compao of awell eqaos s reqred elecromagec radao scaerg ad propagao problems. I addo s ofe more ecoomcal o ge freqecy doma resls va
Earthquake, Volcano and Tsunami
A. Merapi Volcano Erpion Earhqake, Volcano and Tsnami Qesion Answer Marks A. Using Black s Principle he eqilibrim emperare can be obained Ths,.5 A. For ideal gas, pv e e RTe, hs.3 A.3 The relaive velociy
Computational Fluid Dynamics CFD. Solving system of equations, Grid generation
Compaoal ld Dyamcs CD Solvg sysem of eqaos, Grd geerao Basc seps of CD Problem Dscrezao Resl Gov. Eq. BC I. Cod. Solo OK??,,... Solvg sysem of eqaos he ype of eqaos decdes solo sraegy Marchg problems Eqlbrm
RADIOSS THEORY MANUAL
RADOSS THEORY MANUAL. verso Jauar 9 Large Dsplaceme Fe Eleme Aalss PART Alar Egeerg c. World Headquarers: 8 E. Bg Beaver Rd. Tro M 488- USA Phoe:.48.64.4 Fa:.48.64.4 www.alar.com fo@alar.com RADOSS THEORY
ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT
V M Chacko E CONVE AND INCREASIN CONVE OAL IME ON ES RANSORM ORDER R&A # 4 9 Vol. Decembe ON OAL IME ON ES RANSORM ORDER V. M. Chacko Depame of Sascs S. homas Collee hss eala-68 Emal: chackovm@mal.com
PH2130 Mathematical Methods Lab 3. z x
PH130 Mahemaical Mehods Lab 3 This scrip shold keep yo bsy for he ne wo weeks. Yo shold aim o creae a idy and well-srcred Mahemaica Noebook. Do inclde plenifl annoaions o show ha yo know wha yo are doing,
Part II Image recognition
Image ad speech recogo Lecure oes Włodzmerz Kasprza Proec s co-faced by Europea Uo wh Europea Socal Fud. Paer recogo. Paer rasformao 3. Paer classfcao 4. Image pre-processg CONTENT Par I Paer recogo Par
Reliability Equivalence of a Parallel System with Non-Identical Components
Ieraoa Mahemaca Forum 3 8 o. 34 693-7 Reaby Equvaece of a Parae Syem wh No-Ideca ompoe M. Moaer ad mmar M. Sarha Deparme of Sac & O.R. oege of Scece Kg Saud Uvery P.O.ox 455 Ryadh 45 Saud raba aarha@yahoo.com
Lecture 2: The Simple Regression Model
Lectre Notes o Advaced coometrcs Lectre : The Smple Regresso Model Takash Yamao Fall Semester 5 I ths lectre we revew the smple bvarate lear regresso model. We focs o statstcal assmptos to obta based estmators.
Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes,
Trasport Eqato For ostat ε, the fore per t fld volme de to eletr feld beomes, - ρ f E N/m 3 or ρ f ψ Mometm Eq. (trodg the eletr fore term as body fore term) ρ + ρ = p + µ d t Steady state, reep flow d
This Topic follows on from Calculus Topics C1 - C3 to give further rules and applications of differentiation.
CALCULUS C Topic Overview C FURTHER DIFFERENTIATION This Topic follows on from Calcls Topics C - C to give frther rles applications of differentiation. Yo shold be familiar with Logarithms (Algebra Topic
Curves - Foundation of Free-form Surfaces
//9 Cres - Fodato of Free-form Srfaces Why Stdy Cres? Cres are the bascs for srfaces Whe asked to modfy a partclar etty o a CAD system, kowledge of the ettes ca crease yor prodctty Uderstad how the math
15-381: Artificial Intelligence. Regression and neural networks (NN)
5-38: Artfcal Itellece Reresso ad eural etorks NN) Mmck the bra I the earl das of AI there as a lot of terest develop models that ca mmc huma thk. Whle o oe ke eactl ho the bra orks ad, eve thouh there
Algorithmic verification of feasibility for generalized median voter schemes on compact ranges Korgin N.*
Preprs of he 8h IFAC orld Cogress Mlao (Ialy) Augus 8 - Sepeber 0 Algorhc verfcao of feasbly for geeralzed eda voer schees o copac rages Korg N* *Isue of Corol Sceces of Russa Acadey of Sceces Mosco Russa
Surfaces II Lecture Series. Prof. G. Wang Department of Mechanical and Manufacturing Engineering University of Manitoba
Srfces II 5.5 Lectre Seres rof. G. Wg Dertmet of Mechcl d Mfctrg Egeerg Uversty of Mtob Tye of Srfces lr Srfce Bler Srfce Rled (lofted Srfce B-cbc srfce Bezer Srfce B-Sle Srfce B-Cbc Srfce tch B-Cbc Srfce
Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction
refeed Soluos for R&D o Desg Deermao of oe Equao arameers Soluos for R&D o Desg December 4, 0 refeed orporao Yosho Kumagae refeed Iroduco hyscal propery daa s exremely mpora for performg process desg ad
θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions:
Paramerc coug process models Cosder coug processes: N,,..., ha cou he occurreces of a eve of eres for dvduals Iesy processes: Lelhood λ ( ;,,..., N { } λ < Log-lelhood: l( log L( Score fucos: U ( l( log
Lecture VI Regression
Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M
Scalar Conservation Laws
MATH-459 Nmerical Mehods for Conservaion Laws by Prof. Jan S. Heshaven Solion se : Scalar Conservaion Laws Eercise. The inegral form of he scalar conservaion law + f ) = is given in Eq. below. ˆ 2, 2 )
Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters
Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo