N 1. Time points are determined by the
|
|
- Barnard Wright
- 6 years ago
- Views:
Transcription
1 upplemena Mehods Geneaon of scan sgnals In hs secon we descbe n deal how scan sgnals fo 3D scannng wee geneaed. can geneaon was done n hee seps: Fs, he dve sgnal fo he peo-focusng elemen was geneaed o poduce he nended -vbaon of he mcoscope objecve. econd, a ajeco was defned ehe based on an analcal funcon o b poducng a smooh lne passng hough peseleced posons n 3D space (use-defned mode. In he las sep, a new se of fnal scan pons along he pedefned ajeco was defned assung equdsan 3D spacng. Geneaon of -scan sgnal. A snusodal funcon was used fo connuous acceleaon of he mcoscope objecve along he opcal as. The nended vbaon of he objecve was defned as O ( = A sn π F ( wh amplude A, fequenc F and =,..., N. Tme pons ae deemned b he chosen pel dwell me Δ = and he oal numbe of pels pe ccle N s gven b N = /( F. Because of he nea of he peo-focusng elemen plus Δ objecve load he acual -poson of he objecve n geneal does no accuael mach he mposed dve sgnals. Fo a snusodal moon, a fequenc-dependen amplude educon and phase shf esul, whch need o be coeced (upplemena Fg.. We heefoe mposed he followng coeced dve sgnal o he peo-elemen O ( = A sn(π F ϕ (, co co co wh phase shf ϕ co and coeced amplude A co = A /θ, whee θ s he amplude educon faco. Noe ha fo an vbaon fequenc θ and ϕ co mus be newl deemned. We deemned θ and ϕ co fom a smulaneous measuemen of he dve sgnal and he acual poson sgnal. A H, amplude educon was onl aound 5% fo he 4. Coecon was elable up o H. A hghe fequences he amplude educon could no be full coeced fo because of he lmed ange of he conol eleconcs (upplemena Fg. b.
2 Analcal scan paens. A smple mehod o defne a 3D scan paen s o use an analcal mahemacal funcon. We used hs appoach o geneae spal, squaespal o Lssajous scan paens. These paens wee fs compued n a wodmensonal plane o pe-defne he ajeco. The -movemen of he objecve was consdeed lae when calculang he fnal scan pons (see below. Fo spal o squae-spal mode he -componens and of pons,, (whee s a wocomponen veco wee calculaed n one-degee seps as, s π = s sn 8 and, s π = s cos 8 wh =,...,( s and <. pal dens and ccula wee adjused b vang s and. s s he oal numbe of degees fo he spal oaon, hus he basc paen conans s/36 spals. Tpcal values of s wee o 4. Fo =, a ccula spal paen esuls. Loweng leads o a successvel moe squae-spal paen, whch mgh be useful fo lng lage volumes n a space-fllng manne. Tpcal values of wee. o. Fo a Lssajous-pe basc paen he -componens and wee calculaed as π f π f, = sn and, = sn (4 K K wh =,..., ( K. f and f denoe he fequences n and ( f > f and,, (3 f f =. Fo one Lssajous-paen ccle he numbe of peods n - and - decon hus ae gven b K / and K / f, especvel. Tpcal values wee 4 - f fo fequences and - fo K. The basc scan paens wee hen concaenaed o oban a cean numbe of paen eaons pe peod of he objecve's -movemen (pcall o 4 paen eaons. In spal mode, successve spals wee moed o each ohe dung one half ccle of he objecve s oscllaon (n spal-n spal-ou manne so ha a smooh anson fom one spal o he ne was ensued. To mpove volume coveage a 8 -phase jump was appled a he lowe and uppe lms of he - movemen so ha he laeal mama of -scannng fo downwad and upwad movemen of he objecve wee neleaved.
3 3 Use-defned scan paen. Alenavel, we mplemened a use-defned mode, n whch mulple pons (e.g. cell somaa wee pe-seleced fom a pevousl acqued efeence mage sack. Fom hese pe-seleced pons a connuous smooh 3D ajeco was obaned b nseon of addonal pons as descbed n he followng. Fs, all pe-seleced pons I whn each wo-dmensonal mage plane fom he efeence sack wee soed clockwse (upplemena Fg. a. Then, he mamum dsance beween pons n -decon was deemned and pons above half of hs dsance n -decon wee soed fom lef o gh accodng o he - componen, pons n he lowe half fom gh o lef. In ode o educe he lengh of he fnal scan lne, pons wee fuhe eaanged. Fo each pon (sang wh pon he shoes pah o he hd-ne pon was deemned fo he wo possble odes of he nemedae pons, whch wee e-odeed f necessa. Afe defnon of he pon ode, a smooh scan lne was geneaed b eavel nseng new pons and (upplemena Fg. b and c. In he fs ound, wo addonal pons pons I, I and I wh = I, j accodng o e e,, α ; e e α ΔI κ = I I / κ and = / and, j, wee geneaed fo hee consecuve = I e e, α (5 e e α ΔI κ = I I / κ whee κ s a faco = / deemnng he numbe of pons o be nseed beween neghboung I (pcall we used κ =. e = ΔI / ΔI and e = ΔI / ΔI ae he un vecos beween he consdeed pons. In he ne ound (j =,,κ fuhe pons and wee nseed bu now consdeng he angles (, j, j,, j and (, j,, j,, j, especvel (upplemena Fg. c. Usng hs algohm a smooh ajeco whou shap edges was obaned ha ncluded all pe-seleced pons.,, j, j Equdsan 3D pel dsbuon. Afe pe-defnon of he scan ajeco n wo dmensons he -vbaon of he objecve had o be consdeed. can geneaon and fluoescence acquson wee done wh a fed, pe-defned pel dwell me Δ (pcall Δ = μs. To elae fluoescence nens values fom dffeen pels o each ohe adjacen scan pons should be spaced equdsanl n 3D. Because a
4 4 connuous snusodal wavefom was used fo he objecve s moon n -decon he speed of -movemen changes dung he vbaon ccle, necessang a coecon of he -dsances. Effecvel hs foced us o ecalculae he ene 3D ajeco, so ha he newl defned scan pons had equdsan 3D spacng (upplemena Fg. 3. To calculae he equed 3D pel spacng fo a gven scan paen we fs calculaed he oal lengh L of he pe-defned ajeco (conssng of he se of pons fo one vbaon ccle n he -pojecon: L N = =, whee = (,, (,, (6 The mean pel dsance n -dmenson heefoe s d = L / N. Accodng o equaon ( he mean focus change n -decon s gven b equed 3D pel spacng d s compued fom hese wo vaables as d = A N. The / d = d d (7 We ne geneaed a new se of scan pons (hee-componen vecos along he pe-defned ajeco ha wee equdsanl spaced n 3D wh spacng d. To hs end one has o eale ha he dsance beween wo pels n he -plane wll be a funcon of he acual phase of he -oscllaon ccle O ( accodng o d ( = d ΔO ( (8 whee Δ ( = O ( O (. We saed wh he fs new pon, whch was se O equal o :, =,, =, = O, ( The -pojecon s of he dsance o he ne pon was calculaed as s = = ( (,,,, (9 ( and compaed o he equed dsance epeaed fo he ne pons unl s k > d (. If s < ( he calculaon was d ( wh k d =. The ne pel sk k was hen nseed on he lne beween k and a he poson ha elded he
5 5 coec dsance d ( beween he scan pons and (upplemena Fg. 3b. The eac -coodnaes wee calculaed as, = N β M,, = N β M,, = O ( Δ wh wo-componen vecos N k, ( = and M = k k. The faco β s obaned b solvng he quadac equaon ( N M = β ( d eldng β = d ( M ( N M N M N M (3 M Takng no accoun he objecve s dsplacemen n he -decon (ΔO ( he 3D dsance beween and equals d. The above algohm was eavel epeaed usng he followng geneal equaons, = N β M,, = N β M,, = O ( Δ wh N = k,, M = k k and he faco β deemned as gven n equaon (4 (3. Fo he analcal scan paens hs pocedue was epeaed unl he ene ajeco was flled wh he new se of pons, now equdsanl spaced n 3D. In use-defned mode, scan pons wee equall dsbued fo all segmens n mage planes of he efeence sack ha conaned pe-seleced pons (upplemena Fg. 3d. An eo was euned when he me equed o scan one segmen eceeded he me fo he objecve o each he ne plane. The nepolaon neval ΔT beween he las scan pon n one plane (coespondng o he objecve s - poson o he fs scan pon n he ne plane conanng pe-seleced pons (poson s gven b ΔT = O ( O ( (5
6 6 whee O ( s he nvese funcon of (.Thus he numbe of equed O nepolaon pels s N I = ΔT / Δ. Inepolang scan pons wee equall dsbued along he smooh pe-defned ajeco wh he above descbed algohm. Dependng on he nepolaon neval and he phase of he vbaon ccle hs mehod esuled n ehe acceleaed o slowed-down scannng unl he -poson of he ne mage plane was eached and he ne elevan segmen was scanned (upplemena Fg. 3e. Auomac lase nens adjusmen We assumed an eponenal deca of he ecaon lgh nens wh deph. To coec fo hs deca he sgnal appled o he ockel s cell fo lase nens adjusmen was modulaed accodng o O ( λ I( = I e (6 whee I denoes he lase nens a O (. We used -5 μm fo he scaeng lengh λ of nea-nfaed lgh n neococal ssue, and μm fo he bead es sample. Refeences. Klenfeld, D., Ma,.., Helmchen, F. & Denk, W. Flucuaons and smulusnduced changes n blood flow obseved n ndvdual capllaes n laes hough 4 of a neocoe. oc. Nal. Acad. c. UA 95, (998.. Ohem, M., Beauepae, E., Chagneau, E., Me, J. & Chapak,. Twophoon mcoscop n ban ssue: paamees nfluencng he magng deph. J. Neuosc. Meh., 9-37 (.
5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )
5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma
More informationL4:4. motion from the accelerometer. to recover the simple flutter. Later, we will work out how. readings L4:3
elave moon L4:1 To appl Newon's laws we need measuemens made fom a 'fed,' neal efeence fame (unacceleaed, non-oang) n man applcaons, measuemens ae made moe smpl fom movng efeence fames We hen need a wa
More informationChapter 3: Vectors and Two-Dimensional Motion
Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon
More informations = rθ Chapter 10: Rotation 10.1: What is physics?
Chape : oaon Angula poson, velocy, acceleaon Consan angula acceleaon Angula and lnea quanes oaonal knec enegy oaonal nea Toque Newon s nd law o oaon Wok and oaonal knec enegy.: Wha s physcs? In pevous
More informationCHAPTER 10: LINEAR DISCRIMINATION
HAPER : LINEAR DISRIMINAION Dscmnan-based lassfcaon 3 In classfcaon h K classes ( k ) We defned dsmnan funcon g () = K hen gven an es eample e chose (pedced) s class label as f g () as he mamum among g
More informationModern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr.
Moden Enegy Funconal fo Nucle and Nuclea Mae By: lbeo noosa Teas &M Unvesy REU Cycloon 008 Meno: D. Shalom Shlomo Oulne. Inoducon.. The many-body poblem and he aee-fock mehod. 3. Skyme neacon. 4. aee-fock
More informationName of the Student:
Engneeng Mahemacs 05 SUBJEC NAME : Pobably & Random Pocess SUBJEC CODE : MA645 MAERIAL NAME : Fomula Maeal MAERIAL CODE : JM08AM007 REGULAION : R03 UPDAED ON : Febuay 05 (Scan he above QR code fo he dec
More informationLecture 5. Plane Wave Reflection and Transmission
Lecue 5 Plane Wave Reflecon and Tansmsson Incden wave: 1z E ( z) xˆ E (0) e 1 H ( z) yˆ E (0) e 1 Nomal Incdence (Revew) z 1 (,, ) E H S y (,, ) 1 1 1 Refleced wave: 1z E ( z) xˆ E E (0) e S H 1 1z H (
More informationField due to a collection of N discrete point charges: r is in the direction from
Physcs 46 Fomula Shee Exam Coulomb s Law qq Felec = k ˆ (Fo example, f F s he elecc foce ha q exes on q, hen ˆ s a un veco n he decon fom q o q.) Elecc Feld elaed o he elecc foce by: Felec = qe (elecc
More informationCourse Outline. 1. MATLAB tutorial 2. Motion of systems that can be idealized as particles
Couse Oulne. MATLAB uoal. Moon of syses ha can be dealzed as pacles Descpon of oon, coodnae syses; Newon s laws; Calculang foces equed o nduce pescbed oon; Deng and solng equaons of oon 3. Conseaon laws
More informationFast Calibration for Robot Welding System with Laser Vision
Fas Calbaon fo Robo Weldng Ssem h Lase Vson Lu Su Mechancal & Eleccal Engneeng Nanchang Unves Nanchang, Chna Wang Guoong Mechancal Engneeng Souh Chna Unves of echnolog Guanghou, Chna Absac Camea calbaon
More informationESS 265 Spring Quarter 2005 Kinetic Simulations
SS 65 Spng Quae 5 Knec Sulaon Lecue une 9 5 An aple of an lecoagnec Pacle Code A an eaple of a knec ulaon we wll ue a one denonal elecoagnec ulaon code called KMPO deeloped b Yohhau Oua and Hoh Mauoo.
More information2 shear strain / L for small angle
Sac quaons F F M al Sess omal sess foce coss-seconal aea eage Shea Sess shea sess shea foce coss-seconal aea llowable Sess Faco of Safe F. S San falue Shea San falue san change n lengh ognal lengh Hooke
More informationReflection and Refraction
Chape 1 Reflecon and Refacon We ae now neesed n eplong wha happens when a plane wave avelng n one medum encounes an neface (bounday) wh anohe medum. Undesandng hs phenomenon allows us o undesand hngs lke:
More informationCptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1
ps 57 Machne Leann School of EES Washnon Sae Unves ps 57 - Machne Leann Assume nsances of classes ae lneal sepaable Esmae paamees of lnea dscmnan If ( - -) > hen + Else - ps 57 - Machne Leann lassfcaon
More informationAccelerated Sequen.al Probability Ra.o Test (SPRT) for Ongoing Reliability Tes.ng (ORT)
cceleaed Sequen.al Pobably Ra.o Tes (SPRT) fo Ongong Relably Tes.ng (ORT) Mlena Kasch Rayheon, IDS Copygh 25 Rayheon Company. ll ghs eseved. Cusome Success Is Ou Msson s a egseed adema of Rayheon Company
More informationRotations.
oons j.lbb@phscs.o.c.uk To s summ Fmes of efeence Invnce une nsfomons oon of wve funcon: -funcons Eule s ngles Emple: e e - - Angul momenum s oon geneo Genec nslons n Noehe s heoem Fmes of efeence Conse
More informationI-POLYA PROCESS AND APPLICATIONS Leda D. Minkova
The XIII Inenaonal Confeence Appled Sochasc Models and Daa Analyss (ASMDA-009) Jne 30-Jly 3, 009, Vlns, LITHUANIA ISBN 978-9955-8-463-5 L Sakalaskas, C Skadas and E K Zavadskas (Eds): ASMDA-009 Seleced
More informationPhysics 201 Lecture 15
Phscs 0 Lecue 5 l Goals Lecue 5 v Elo consevaon of oenu n D & D v Inouce oenu an Iulse Coens on oenu Consevaon l oe geneal han consevaon of echancal eneg l oenu Consevaon occus n sses wh no ne eenal foces
More informationSolution in semi infinite diffusion couples (error function analysis)
Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of
More informationChapters 2 Kinematics. Position, Distance, Displacement
Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen
More informationGo over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration
Mh Csquee Go oe eco nd eco lgeb Dsplcemen nd poson n -D Aege nd nsnneous eloc n -D Aege nd nsnneous cceleon n -D Poecle moon Unfom ccle moon Rele eloc* The componens e he legs of he gh ngle whose hpoenuse
More informationHandling Fuzzy Constraints in Flow Shop Problem
Handlng Fuzzy Consans n Flow Shop Poblem Xueyan Song and Sanja Peovc School of Compue Scence & IT, Unvesy of Nongham, UK E-mal: {s sp}@cs.no.ac.uk Absac In hs pape, we pesen an appoach o deal wh fuzzy
More information1 Constant Real Rate C 1
Consan Real Rae. Real Rae of Inees Suppose you ae equally happy wh uns of he consumpon good oday o 5 uns of he consumpon good n peod s me. C 5 Tha means you ll be pepaed o gve up uns oday n eun fo 5 uns
More informationPhysics 2A Chapter 11 - Universal Gravitation Fall 2017
Physcs A Chapte - Unvesal Gavtaton Fall 07 hese notes ae ve pages. A quck summay: he text boxes n the notes contan the esults that wll compse the toolbox o Chapte. hee ae thee sectons: the law o gavtaton,
More informationChapter Finite Difference Method for Ordinary Differential Equations
Chape 8.7 Fne Dffeence Mehod fo Odnay Dffeenal Eqaons Afe eadng hs chape, yo shold be able o. Undesand wha he fne dffeence mehod s and how o se o solve poblems. Wha s he fne dffeence mehod? The fne dffeence
More informationCHAPTER 3 DETECTION TECHNIQUES FOR MIMO SYSTEMS
4 CAPTER 3 DETECTION TECNIQUES FOR MIMO SYSTEMS 3. INTRODUCTION The man challenge n he paccal ealzaon of MIMO weless sysems les n he effcen mplemenaon of he deeco whch needs o sepaae he spaally mulplexed
More informationJ i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.
umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal
More informationSuppose 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).
More informationTHE PHYSICS BEHIND THE SODACONSTRUCTOR. by Jeckyll
THE PHYSICS BEHIND THE SODACONSTRUCTOR b Jeckll THE PHYSICS BEHIND THE SODACONSTRUCTOR - b Jeckll /3 CONTENTS. INTRODUCTION 5. UNITS OF MEASUREMENT 7 3. DETERMINATION OF THE PHYSICAL CONSTANTS ADOPTED
More informationSCIENCE CHINA Technological Sciences
SIENE HINA Technologcal Scences Acle Apl 4 Vol.57 No.4: 84 8 do:.7/s43-3-5448- The andom walkng mehod fo he seady lnea convecondffuson equaon wh axsymmec dsc bounday HEN Ka, SONG MengXuan & ZHANG Xng *
More informationLow-complexity Algorithms for MIMO Multiplexing Systems
Low-complexiy Algoihms fo MIMO Muliplexing Sysems Ouline Inoducion QRD-M M algoihm Algoihm I: : o educe he numbe of suviving pahs. Algoihm II: : o educe he numbe of candidaes fo each ansmied signal. :
More informationNotes on the stability of dynamic systems and the use of Eigen Values.
Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon
More informationScienceDirect. Behavior of Integral Curves of the Quasilinear Second Order Differential Equations. Alma Omerspahic *
Avalable onlne a wwwscencedeccom ScenceDec oceda Engneeng 69 4 85 86 4h DAAAM Inenaonal Smposum on Inellgen Manufacung and Auomaon Behavo of Inegal Cuves of he uaslnea Second Ode Dffeenal Equaons Alma
More information( ) () we define the interaction representation by the unitary transformation () = ()
Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger
More informationcalculating electromagnetic
Theoeal mehods fo alulang eleomagne felds fom lghnng dshage ajeev Thoapplll oyal Insue of Tehnology KTH Sweden ajeev.thoapplll@ee.kh.se Oulne Despon of he poblem Thee dffeen mehods fo feld alulaons - Dpole
More information( ) ( ) 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
More informationPHYS 1443 Section 001 Lecture #4
PHYS 1443 Secon 001 Lecure #4 Monda, June 5, 006 Moon n Two Dmensons Moon under consan acceleraon Projecle Moon Mamum ranges and heghs Reerence Frames and relae moon Newon s Laws o Moon Force Newon s Law
More informationToday - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations
Today - Lecue 13 Today s lecue coninue wih oaions, oque, Noe ha chapes 11, 1, 13 all inole oaions slide 1 eiew Roaions Chapes 11 & 1 Viewed fom aboe (+z) Roaional, o angula elociy, gies angenial elociy
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu
More informationChapter Fifiteen. Surfaces Revisited
Chapte Ffteen ufaces Revsted 15.1 Vecto Descpton of ufaces We look now at the vey specal case of functons : D R 3, whee D R s a nce subset of the plane. We suppose s a nce functon. As the pont ( s, t)
More information( ) ( )) ' j, k. These restrictions in turn imply a corresponding set of sample moment conditions:
esng he Random Walk Hypohess If changes n a sees P ae uncoelaed, hen he followng escons hold: va + va ( cov, 0 k 0 whee P P. k hese escons n un mply a coespondng se of sample momen condons: g µ + µ (,,
More informationMotion in Two Dimensions
Phys 1 Chaper 4 Moon n Two Dmensons adzyubenko@csub.edu hp://www.csub.edu/~adzyubenko 005, 014 A. Dzyubenko 004 Brooks/Cole 1 Dsplacemen as a Vecor The poson of an objec s descrbed by s poson ecor, r The
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as
More informationMaximum Likelihood Estimation
Mau Lkelhood aon Beln Chen Depaen of Copue Scence & Infoaon ngneeng aonal Tawan oal Unvey Refeence:. he Alpaydn, Inoducon o Machne Leanng, Chape 4, MIT Pe, 4 Saple Sac and Populaon Paaee A Scheac Depcon
More informationFI 3103 Quantum Physics
/9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon
More informationReal-coded Quantum Evolutionary Algorithm for Global Numerical Optimization with Continuous Variables
Chnese Jounal of Eleconcs Vol.20, No.3, July 2011 Real-coded Quanum Evoluonay Algohm fo Global Numecal Opmzaon wh Connuous Vaables GAO Hu 1 and ZHANG Ru 2 (1.School of Taffc and Tanspoaon, Souhwes Jaoong
More informationCubic Bezier Homotopy Function for Solving Exponential Equations
Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.
More informationHierarchical Production Planning in Make to Order System Based on Work Load Control Method
Unvesal Jounal of Indusal and Busness Managemen 3(): -20, 205 DOI: 0.389/ujbm.205.0300 hp://www.hpub.og Heachcal Poducon Plannng n Make o Ode Sysem Based on Wok Load Conol Mehod Ehsan Faah,*, Maha Khodadad
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ
More informationLecture 17: Kinetics of Phase Growth in a Two-component System:
Lecue 17: Kineics of Phase Gowh in a Two-componen Sysem: descipion of diffusion flux acoss he α/ ineface Today s opics Majo asks of oday s Lecue: how o deive he diffusion flux of aoms. Once an incipien
More informationSimulation of Non-normal Autocorrelated Variables
Jounal of Moden Appled Sascal Mehods Volume 5 Issue Acle 5 --005 Smulaon of Non-nomal Auocoelaed Vaables HT Holgesson Jönöpng Inenaonal Busness School Sweden homasholgesson@bshse Follow hs and addonal
More informationCH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC
CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal
More informationCalculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( )
Clculu 4, econ Lm/Connuy & Devve/Inel noe y Tm Plchow, wh domn o el Wh we hve o : veco-vlued uncon, ( ) ( ) ( ) j ( ) nume nd ne o veco The uncon, nd A w done wh eul uncon ( x) nd connuy e he componen
More informationChapter 6 Plane Motion of Rigid Bodies
Chpe 6 Pne oon of Rd ode 6. Equon of oon fo Rd bod. 6., 6., 6.3 Conde d bod ced upon b ee een foce,, 3,. We cn ume h he bod mde of e numbe n of pce of m Δm (,,, n). Conden f he moon of he m cene of he
More informationBasic molecular dynamics
1.1, 3.1, 1.333,. Inoducon o Modelng and Smulaon Spng 11 Pa I Connuum and pacle mehods Basc molecula dynamcs Lecue Makus J. Buehle Laboaoy fo Aomsc and Molecula Mechancs Depamen of Cvl and Envonmenal Engneeng
More informationajanuary't I11 F or,'.
',f,". ; q - c. ^. L.+T,..LJ.\ ; - ~,.,.,.,,,E k }."...,'s Y l.+ : '. " = /.. :4.,Y., _.,,. "-.. - '// ' 7< s k," ;< - " fn 07 265.-.-,... - ma/ \/ e 3 p~~f v-acecu ean d a e.eng nee ng sn ~yoo y namcs
More informationSilence is the only homogeneous sound field in unbounded space
Cha.5 Soues of Sound Slene s he onl homogeneous sound feld n unbounded sae Sound feld wh no boundaes and no nomng feld 3- d wave equaon whh sasfes he adaon ondon s f / Wh he lose nseon a he on of = he
More informationFIRMS IN THE TWO-PERIOD FRAMEWORK (CONTINUED)
FIRMS IN THE TWO-ERIO FRAMEWORK (CONTINUE) OCTOBER 26, 2 Model Sucue BASICS Tmelne of evens Sa of economc plannng hozon End of economc plannng hozon Noaon : capal used fo poducon n peod (decded upon n
More informationENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes]
ENGI 44 Avance alculus fo Engineeing Faculy of Engineeing an Applie cience Poblem e 9 oluions [Theoems of Gauss an okes]. A fla aea A is boune by he iangle whose veices ae he poins P(,, ), Q(,, ) an R(,,
More informationWORK POWER AND ENERGY Consevaive foce a) A foce is said o be consevaive if he wok done by i is independen of pah followed by he body b) Wok done by a consevaive foce fo a closed pah is zeo c) Wok done
More informationChapter 6: AC Circuits
Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.
More informationScattering at an Interface: Oblique Incidence
Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may
More informationp E p E d ( ) , we have: [ ] [ ] [ ] Using the law of iterated expectations, we have:
Poblem Se #3 Soluons Couse 4.454 Maco IV TA: Todd Gomley, gomley@m.edu sbued: Novembe 23, 2004 Ths poblem se does no need o be uned n Queson #: Sock Pces, vdends and Bubbles Assume you ae n an economy
More informationJohn Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany
Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy
More informationCS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4
CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped
More informationScalars and Vectors Scalar
Scalas and ectos Scala A phscal quantt that s completel chaacteed b a eal numbe (o b ts numecal value) s called a scala. In othe wods a scala possesses onl a magntude. Mass denst volume tempeatue tme eneg
More informationA VISCOPLASTIC MODEL OF ASYMMETRICAL COLD ROLLING
SISOM 4, BUCHAEST, - May A VISCOPLASTIC MODEL OF ASYMMETICAL COLD OLLING odca IOAN Spu Hae Unvesy Buchaes, odcaoan7@homal.com Absac: In hs pape s gven a soluon of asymmecal sp ollng poblem usng a Bngham
More informationThe Feigel Process. The Momentum of Quantum Vacuum. Geert Rikken Vojislav Krstic. CNRS-France. Ariadne call A0/1-4532/03/NL/MV 04/1201
The Fegel Pocess The Momenum of Quanum Vacuum a an Tggelen CNRS -Fance Laboaoe e Physque e Moélsaon es Mleux Complexes Unesé Joseph Foue/CNRS, Genoble, Fance Gee Ren Vosla Ksc CNRS Fance CNRS-Fance Laboaoe
More informationA multi-band approach to arterial traffic signal optimization. Nathan H. Gartner Susan F. Assmann Fernando Lasaga Dennin L. Hou
A mul-an appoach o aeal affc sgnal opmzaon Nahan H. Gane Susan F. Assmann Fenano Lasaga Dennn L. Hou MILP- The asc, symmec, unfom-h anh maxmzaon polem MILP- Exens he asc polem o nclue asymmec anhs n opposng
More informationby Lauren DeDieu Advisor: George Chen
b Laren DeDe Advsor: George Chen Are one of he mos powerfl mehods o nmercall solve me dependen paral dfferenal eqaons PDE wh some knd of snglar shock waves & blow-p problems. Fed nmber of mesh pons Moves
More informationMCTDH Approach to Strong Field Dynamics
MCTDH ppoach o Song Feld Dynamcs Suen Sukasyan Thomas Babec and Msha Ivanov Unvesy o Oawa Canada Impeal College ondon UK KITP Sana Babaa. May 8 009 Movaon Song eld dynamcs Role o elecon coelaon Tunnel
More informationCHAPTER 10: LINEAR DISCRIMINATION
CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g
More informationHEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD
Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,
More informationTHE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS
THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he
More information[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5
TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres
More informationGeneral Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security
1 Geneal Non-Abiage Model I. Paial Diffeenial Equaion fo Picing A. aded Undelying Secuiy 1. Dynamics of he Asse Given by: a. ds = µ (S, )d + σ (S, )dz b. he asse can be eihe a sock, o a cuency, an index,
More informationOutline. GW approximation. Electrons in solids. The Green Function. Total energy---well solved Single particle excitation---under developing
Peenaon fo Theoecal Condened Mae Phyc n TU Beln Geen-Funcon and GW appoxmaon Xnzheng L Theoy Depamen FHI May.8h 2005 Elecon n old Oulne Toal enegy---well olved Sngle pacle excaon---unde developng The Geen
More informationSUBDIFFUSION SUPPORTS JOINING OF CORRECT ENDS DURING REPAIR OF
SUBDIFFUSIO SUPPORTS JOIIG OF CORRECT EDS DURIG REPAIR OF DA DOUBLE-STRAD BREAKS S. Gs *, V. Hable, G.A. Dexle, C. Geubel, C. Sebenwh,. Haum, A.A. Fedl, G. Dollnge Angewande Physk und essechnk LRT, Unvesä
More informationAnswers to Tutorial Questions
Inoducoy Mahs ouse Answes.doc Answes o Tuoal Quesons Enjoy wokng hough he examples. If hee ae any moe quesons, please don hesae o conac me. Bes of luck fo he exam and beyond, I hope you won need. Tuoal
More informationBISTATIC COHERENT MIMO CLUTTER RANK ANALYSIS
3 Euopean Sgnal Pocessng Confeence (EUSIPCO BISAIC COHEEN MIMO CLUE ANK ANALYSIS Ksne Bell, * Joel Johnson, Chsophe Bae, Gaeme Smh, an Mualha angaswam * Meon, Inc, 88 Lba S, Sue 600, eson, Vgna 090, USA
More informationTecnologia e Inovação, Lisboa, Portugal. ABB Corporate Research Center, Wallstadter Str. 59, Ladenburg, Germany,
A New Connuous-Tme Schedulng Fomulaon fo Connuous Plans unde Vaable Eleccy Cos Pedo M. Caso * Io Hajunkosk and Ignaco E. Gossmann Depaameno de Modelação e Smulação de Pocessos Insuo Naconal de Engenhaa
More informationANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2
Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads
More informationResponse of MDOF systems
Response of MDOF syses Degree of freedo DOF: he nu nuber of ndependen coordnaes requred o deerne copleely he posons of all pars of a syse a any nsan of e. wo DOF syses hree DOF syses he noral ode analyss
More informationUNIT10 PLANE OF REGRESSION
UIT0 PLAE OF REGRESSIO Plane of Regesson Stuctue 0. Intoducton Ojectves 0. Yule s otaton 0. Plane of Regesson fo thee Vaales 0.4 Popetes of Resduals 0.5 Vaance of the Resduals 0.6 Summay 0.7 Solutons /
More informationAPPROXIMATIONS FOR AND CONVEXITY OF PROBABILISTICALLY CONSTRAINED PROBLEMS WITH RANDOM RIGHT-HAND SIDES
R U C O R R E S E A R C H R E P O R APPROXIMAIONS FOR AND CONVEXIY OF PROBABILISICALLY CONSRAINED PROBLEMS WIH RANDOM RIGH-HAND SIDES M.A. Lejeune a A. PREKOPA b RRR 7-005, JUNE 005 RUCOR Ruges Cene fo
More informationThe Finite Element Method for the Analysis of Non-Linear and Dynamic Systems
Swss Federal Insue of Page 1 The Fne Elemen Mehod for he Analyss of Non-Lnear and Dynamc Sysems Prof. Dr. Mchael Havbro Faber Dr. Nebojsa Mojslovc Swss Federal Insue of ETH Zurch, Swzerland Mehod of Fne
More informationDensity Matrix Description of NMR BCMB/CHEM 8190
Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae
More informationVariants of Pegasos. December 11, 2009
Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on
More informationGraduate Macroeconomics 2 Problem set 5. - Solutions
Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K
More information(8) Gain Stage and Simple Output Stage
EEEB23 Electoncs Analyss & Desgn (8) Gan Stage and Smple Output Stage Leanng Outcome Able to: Analyze an example of a gan stage and output stage of a multstage amplfe. efeence: Neamen, Chapte 11 8.0) ntoducton
More information( ) ( ) ( ) ( ) ( ) ( ) j ( ) A. b) Theorem
b) Theoe The u of he eco pojecon of eco n ll uull pependcul (n he ene of he cl poduc) decon equl o he eco. ( ) n e e o The pojecon conue he eco coponen of he eco. poof. n e ( ) ( ) ( ) e e e e e e e e
More informationTesting a new idea to solve the P = NP problem with mathematical induction
Tesng a new dea o solve he P = NP problem wh mahemacal nducon Bacground P and NP are wo classes (ses) of languages n Compuer Scence An open problem s wheher P = NP Ths paper ess a new dea o compare he
More informationChapter Lagrangian Interpolation
Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and
More informationMotion of Wavepackets in Non-Hermitian. Quantum Mechanics
Moon of Wavepaces n Non-Herman Quanum Mechancs Nmrod Moseyev Deparmen of Chemsry and Mnerva Cener for Non-lnear Physcs of Complex Sysems, Technon-Israel Insue of Technology www.echnon echnon.ac..ac.l\~nmrod
More informationPhysics 120 Spring 2007 Exam #1 April 20, Name
Phc 0 Spng 007 E # pl 0, 007 Ne P Mulple Choce / 0 Poble # / 0 Poble # / 0 Poble # / 0 ol / 00 In eepng wh he Unon College polc on cdec hone, ued h ou wll nehe ccep no pode unuhozed nce n he copleon o
More informationEN221 - Fall HW # 7 Solutions
EN221 - Fall2008 - HW # 7 Soluions Pof. Vivek Shenoy 1.) Show ha he fomulae φ v ( φ + φ L)v (1) u v ( u + u L)v (2) can be pu ino he alenaive foms φ φ v v + φv na (3) u u v v + u(v n)a (4) (a) Using v
More informationEnergy in Closed Systems
Enegy n Closed Systems Anamta Palt palt.anamta@gmal.com Abstact The wtng ndcates a beakdown of the classcal laws. We consde consevaton of enegy wth a many body system n elaton to the nvese squae law and
More informationAnisotropic Behaviors and Its Application on Sheet Metal Stamping Processes
Ansoropc Behavors and Is Applcaon on Shee Meal Sampng Processes Welong Hu ETA-Engneerng Technology Assocaes, Inc. 33 E. Maple oad, Sue 00 Troy, MI 48083 USA 48-79-300 whu@ea.com Jeanne He ETA-Engneerng
More informationTrack Properities of Normal Chain
In. J. Conemp. Mah. Scences, Vol. 8, 213, no. 4, 163-171 HIKARI Ld, www.m-har.com rac Propes of Normal Chan L Chen School of Mahemacs and Sascs, Zhengzhou Normal Unversy Zhengzhou Cy, Hennan Provnce, 4544,
More information