Review of HAARP Experiment and Assessment of Ionospheric Effects

Size: px
Start display at page:

Download "Review of HAARP Experiment and Assessment of Ionospheric Effects"

Transcription

1 Third AL PI ympsium Kna, Hawaii Nvember 9-3, 009 Review f HAARP Experimen and Assessmen f Inspheric Effecs T. L. Ainswrh, Y. Wang, J.-. Lee, and K.-. Chen Naval Research Labrary, Washingn DC, UA CRR, Nainal Cenral Universiy, TN (RC)

2 bjecives Deermine inspheric effecs n PALAR plarimery Develp insphere crrecin mehds Faraday rain cmpensain Assess required cmpensain lerances Based n desired plarimeric capabiliies Emply AR measure insphere prperies High resluin inspheric measuremens

3 TEC Effecs n AR Tal Elecrn Cnen, TEC pah n elecrn ( x) dx aellie Aliude ~700km Insphere F Layer Al. ~300km θ TEC Varies Diurnally and wih lar unsp Cycle Insphere TEC Causes Refracin, θ Faraday Rain Firs-rder Effecs n Pl. AR: Faraday Rain TEC Value Azimuh hifs TEC Gradien 3

4 HAARP Experimen Cncep High-frequency Acive Aurral Research Prgram Generae arificial TEC hle in insphere Use HAARP high pwer HF ransmier Frequency: 3-0 MHz, Max Pwer: ~3.6 Mw ynchrnize wih PALAR quad-pl cllec Image hrugh arificially disurbed insphere Cmpare wih insphere elecrn densiy Grund based measuremens Tmgraphic elecrn densiy infrmain 4

5 bservainal Difficulies Crdinain f experimenal cndiins HAARP HF radar schedule PALAR quad-pl imagery cllecs Naurally ccurring phenmena ufficien TEC levels lar aciviy affecs he insphere Near he minimum f he year slar cycle Primary prblems: Insufficien elecrn densiy Limied bservainal ppruniies 5

6 pprunisic bservains Naurally ccurring inspheric irregulariy erendipiy, r Chse a gd lcain Frequen insphere disurbances ufficien TEC variabiliy Frequen PALAR quad-pl cllecs Cmplemenary, grund based daase E.g. TEC / elecrn densiy mapping 6

7 PALAR Quad-pl Imagery Near Gakna, Alaska (April, 007) Ggle Earh HH-VV, HV+VH, HH+VV Faraday Rain PALAR 7

8 Tmgraphic Imaging Daa High-frequency Acive Aurral Research Prgram 3 March 007; UTC Quie Day April 007; UTC Disurbed Day Gemagneic Laiude N elec [0 e/m 3 ] Gemagneic Laiude N elec [0 e/m 3 ] Insphere measuremens aken a HAARP shw spaial and day--day elecrn densiy variabiliy 8

9 Plarimeric Faraday Effec Mean =.987 Irregulariy Azimuh Prfile f Faraday Rain Faraday Rain 9

10 bservainal ulk Beer ppruniies in he near-erm lar cycle is (shuld be) heading ward a maximum Increased free elecrn densiy increased TEC Increased TEC variabiliy pprunisic insphere bservains Gd sluin a specific es sies Assuming ruine quad-pl image cllecin HAARP cncep is feasible prvided Well crdinaed daa cllecin plan PALAR quad-pl imagery, HAARP HF radar, ec. 0

11 Faraday Cmpensain Hw much des TEC affec AR plarimery? Assess plarimeric effecs n derived prducs Trea Faraday rains as a miscalibrains uncmpensaed Can ne cmpensae dual-pl imagery?

12 Faraday Effecs Faraday rain affecs plarimeric calibrain Generaes nn-reciprcal AR reurns Circular basis: Phase f RL LR* crrelain Nn-unique crss-alk / Faraday separain Crss-alk induces nn-reciprcal reurns Affecs RL LR* crrelains PALAR: crss-alk level n an issue

13 Faraday Rain Esimain hh vh hv vv = hh hv hv vv Esimae Faraday rain,, in he circular basis Well-defined based n secnd-rder saisics Insensiive arge rienain angles Insensiive scaering mechanisms in he scene ( ) π = π 4 Arg * RL LR wih 4 4 RL = [ hv vh + j( hh + LR = [ vh hv + j( hh + vv vv )] )] 3

14 4 Faraday Rain Marix where = an, and is he Faraday rain angle = VV VH HV HH VV VH HV HH VV VH HV HH = vv hv hv hh vv vh hv hh

15 5 + + = VV VH HV HH VV VH HV HH VV VH HV HH VV VH HV HH r r r r VV VH HV HH VV VH HV HH k k z u uz v uv u w wz z vw w v α α α α Full Calibrain Mdel where = an, and is he Faraday rain angle Faraday rains desry diagnal dminance f he [X][G][F] calibrain marix. is n necessarily a small parameer. X-alk, [X] Gain, [G] Faraday, [F] T.L. Ainswrh, L. Ferr-Famil & J.-. Lee, TGR, vl. 44, 006, pp

16 Faraday Rains Faraday Rain Marix Crss-alk Marix [ F( ) ] [ X ] z u uz v uv u w wz z vw w v where = an, and is he Faraday rain angle where u, v, w and z are he crss-alk cefficiens Faraday rain and crss-alk marices are similar Faraday rains affec crss-alk calibrain eing z = -u = -v = w and crss-alk generaes Faraday rain 6

17 Generic Errr Merics Merics shuld be simple imilar merics fr pin and disribued arges Pin arges merics Apply scaering marix frmalism Disribued arge merics Apply cvariance / cherency marices 7

18 Pin Targe Errr Meric Define a pin arge meric assess impacs f Faraday rains and her plarizain errrs eek fr he maximum nrmalized errrs in he arge space: max vec e ( ) = max ( D I ) vec( ) vec( ) D = F ( ) Cannical arges display reciprcal scaering. bservains are n reciprcal due Faraday rains. Faraday crrecin max vec e ( ) = max ( D I ) A4 vec( ) vec( ) A 4 0 = Evaluaed as he induced nrm: ( D I ) A 4 = max ( D I ) A4 vec( ) vec( ) 8

19 Evaluain The defined meric is used evaluae he cmprmised plarimeric accuracy due Faraday rain. Wrs case siuain: quad-pl and several dual-pl mdes ( ) 9

20 Errr Evaluain Crss-pl cupling increases significanly wih Faraday rain and rienain angle rains Induced crss-alk is he similar fr rienain and Faraday rains T mainain a -0 db measuremen accuracy, he Faraday rain shuld be cmpensaed beer han 3 deg, which ranslaes a crss-alk f -5 db. 0

21 Disribued Targe Meric Plarizain synhesis deermines he maximum errr fr all allwed cmbinains f ransmied and received plarizains ynhesis bias is bained frm a general eigen prblem, max v H H H ( A4 DΣ D A4 ) v = max H H H v ( A Σ A ) v v ( A4 Σ A4 ) 4 4 H H ( A DΣ D A )v where A 4 resrics errr maximizain reciprcal scaering v= v H H [ ] linear (H, V) basis C vlume This errr meric represens a wrs case scenari.

22 Plarizain ynhesis Prediced synhesis errrs fr ypical naural arges. Urban Targe j 0. 4e j 7. 09e e 0. 3e j j e 0. 3e j0. 3 j j 0. 36e j. 8e e e j33. 4 j e 0. 8e j64. 6 j j 0. 6e j 0. 64e e e j3. 7 j e 0. 07e j5. 6 j ample cvariance marices drawn frm PALAR imagery

23 Pauli Basis Effecs = 0 Pauli Display: = 0 Duble Bunce HH-VV HV+VH HH+VV HH-VV / (db) urface Pauli Display: = 0 nly he surface scaering cmpnen is affeced. verall, he Pauli decmpsiin shws lile change. HH+VV / (db) 3

24 Pauli Basis Effecs = 0 Pauli Display: = 0 Duble Bunce HH-VV HV+VH HH+VV HH-VV / (db) urface Pauli Display: = 0 nly he surface scaering cmpnen is affeced. verall, he Pauli decmpsiin shws lile change. HH+VV / (db) 4

25 Freeman-Durden Mdel = 0 Freeman-Durden Display: = 0 Even hugh he crss-pl pwer des n change, he Freeman- Durden vlume scaering is reduced keep he mdel psiive semi-definie. verall, Freeman-Durden shws mre yellw, i.e. less blue. Vlume caering (db) Freeman-Durden Display: = 0 Duble Bunce (db) urface caering (db) 5

26 Freeman-Durden Mdel = 0 Freeman-Durden Display: = 0 Even hugh he crss-pl pwer des n change, he Freeman- Durden vlume scaering is reduced keep he mdel psiive semi-definie. verall, Freeman-Durden shws mre yellw, i.e. less blue. Vlume caering (db) Freeman-Durden Display: = 0 Duble Bunce (db) urface caering (db) 6

27 Cnclusins Quad-pl PALAR daa prvides precise Faraday rain esimaes L-band quad-pl imagery can be plarimerically calibraed in he presence f Faraday rains Faraday effecs n PALAR plarimery urface scaering shws greaes effec, i.e. HH+VV Quad-pl imagery Appears lerae up ~0 f uncmpensaed Faraday rain Freeman-Durden classificain cmparisn andard disribued arges analysis Quad-pl easily cmpensaed fr Faraday rains Dual-pl imagery Circular ransmi mdes display smalles Faraday effecs Linear ransmi dual-pl mdes srngly effeced Especially fr surface and duble bunce scaering Linear dual-pl mdes require beer Faraday cmpensain 7

28 Thank yu 8

29 rienain Angle [ ( θ )] = θ θ + θ θ HH VH HV VV θ + θ θ θ [ R( θ) ] = θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ θ Γ Γ Γ Γ Γ Γ Γ Γ Γ Γ Γ Γ where Γ = an θ, and θ is he rienain angle, a rain abu he line f sigh. Γ Γ Γ Rain, Faraday and Crss-alk marices have similar frms Γ Γ Γ Γ [ R ( θ) ] [ F( ) ] Γ Γ Γ Γ Γ [ X ] z u uz Rain Faraday Crss-alk v uv u w wz z vw w v 9

An Introduction to Wavelet Analysis. with Applications to Vegetation Monitoring

An Introduction to Wavelet Analysis. with Applications to Vegetation Monitoring An Inrducin Wavele Analysis wih Applicains Vegeain Mniring Dn Percival Applied Physics Labrary, Universiy f Washingn Seale, Washingn, USA verheads fr alk available a hp://saff.washingn.edu/dbp/alks.hml

More information

An application of nonlinear optimization method to. sensitivity analysis of numerical model *

An application of nonlinear optimization method to. sensitivity analysis of numerical model * An applicain f nnlinear pimizain mehd sensiiviy analysis f numerical mdel XU Hui 1, MU Mu 1 and LUO Dehai 2 (1. LASG, Insiue f Amspheric Physics, Chinese Academy f Sciences, Beijing 129, China; 2. Deparmen

More information

5.1 Angles and Their Measure

5.1 Angles and Their Measure 5. Angles and Their Measure Secin 5. Nes Page This secin will cver hw angles are drawn and als arc lengh and rains. We will use (hea) represen an angle s measuremen. In he figure belw i describes hw yu

More information

Brace-Gatarek-Musiela model

Brace-Gatarek-Musiela model Chaper 34 Brace-Gaarek-Musiela mdel 34. Review f HJM under risk-neural IP where f ( T Frward rae a ime fr brrwing a ime T df ( T ( T ( T d + ( T dw ( ( T The ineres rae is r( f (. The bnd prices saisfy

More information

Storm Time Ring Current - Atmosphere Interactions: Observations and Modeling

Storm Time Ring Current - Atmosphere Interactions: Observations and Modeling Srm Time Ring Curren - Amsphere Ineracins: Observains and Mdeling V. Jrdanva 1, C. Muikis 1, L. Kisler 1, H. Masui 1, P. Puhl-Quinn 1, and Y. Khyainsev 2 (1) Space Science Cener, Universiy f New Hampshire,

More information

Kinematics Review Outline

Kinematics Review Outline Kinemaics Review Ouline 1.1.0 Vecrs and Scalars 1.1 One Dimensinal Kinemaics Vecrs have magniude and direcin lacemen; velciy; accelerain sign indicaes direcin + is nrh; eas; up; he righ - is suh; wes;

More information

The 37th International Physics Olympiad Singapore. Experimental Competition. Wednesday, 12 July, Sample Solution

The 37th International Physics Olympiad Singapore. Experimental Competition. Wednesday, 12 July, Sample Solution The 37h Inernainal Physics Olypiad Singapre Experienal Cpeiin Wednesday, July, 006 Saple Sluin Par a A skech f he experienal seup (n required) Receiver Raing able Gnieer Fixed ar Bea splier Gnieer Mvable

More information

Productivity changes of units: A directional measure of cost Malmquist index

Productivity changes of units: A directional measure of cost Malmquist index Available nline a hp://jnrm.srbiau.ac.ir Vl.1, N.2, Summer 2015 Jurnal f New Researches in Mahemaics Science and Research Branch (IAU Prduciviy changes f unis: A direcinal measure f cs Malmquis index G.

More information

Revelation of Soft-Switching Operation for Isolated DC to Single-phase AC Converter with Power Decoupling

Revelation of Soft-Switching Operation for Isolated DC to Single-phase AC Converter with Power Decoupling Revelain f Sf-Swiching Operain fr Islaed DC Single-phase AC Cnverer wih wer Decupling Nagisa Takaka, Jun-ichi Ih Dep. f Elecrical Engineering Nagaka Universiy f Technlgy Nagaka, Niigaa, Japan nakaka@sn.nagakau.ac.jp,

More information

PRINCE SULTAN UNIVERSITY Department of Mathematical Sciences Final Examination Second Semester (072) STAT 271.

PRINCE SULTAN UNIVERSITY Department of Mathematical Sciences Final Examination Second Semester (072) STAT 271. PRINCE SULTAN UNIVERSITY Deparmen f Mahemaical Sciences Final Examinain Secnd Semeser 007 008 (07) STAT 7 Suden Name Suden Number Secin Number Teacher Name Aendance Number Time allwed is ½ hurs. Wrie dwn

More information

CHAPTER 7 CHRONOPOTENTIOMETRY. In this technique the current flowing in the cell is instantaneously stepped from

CHAPTER 7 CHRONOPOTENTIOMETRY. In this technique the current flowing in the cell is instantaneously stepped from CHAPTE 7 CHONOPOTENTIOMETY In his echnique he curren flwing in he cell is insananeusly sepped frm zer sme finie value. The sluin is n sirred and a large ecess f suppring elecrlye is presen in he sluin;

More information

GAMS Handout 2. Utah State University. Ethan Yang

GAMS Handout 2. Utah State University. Ethan Yang Uah ae Universiy DigialCmmns@UU All ECAIC Maerials ECAIC Repsiry 2017 GAM Handu 2 Ehan Yang yey217@lehigh.edu Fllw his and addiinal wrs a: hps://digialcmmns.usu.edu/ecsaic_all Par f he Civil Engineering

More information

10.7 Temperature-dependent Viscoelastic Materials

10.7 Temperature-dependent Viscoelastic Materials Secin.7.7 Temperaure-dependen Viscelasic Maerials Many maerials, fr example plymeric maerials, have a respnse which is srngly emperaure-dependen. Temperaure effecs can be incrpraed in he hery discussed

More information

The Components of Vector B. The Components of Vector B. Vector Components. Component Method of Vector Addition. Vector Components

The Components of Vector B. The Components of Vector B. Vector Components. Component Method of Vector Addition. Vector Components Upcming eens in PY05 Due ASAP: PY05 prees n WebCT. Submiing i ges yu pin ward yur 5-pin Lecure grade. Please ake i seriusly, bu wha cuns is wheher r n yu submi i, n wheher yu ge hings righ r wrng. Due

More information

Visco-elastic Layers

Visco-elastic Layers Visc-elasic Layers Visc-elasic Sluins Sluins are bained by elasic viscelasic crrespndence principle by applying laplace ransfrm remve he ime variable Tw mehds f characerising viscelasic maerials: Mechanical

More information

Coherent PSK. The functional model of passband data transmission system is. Signal transmission encoder. x Signal. decoder.

Coherent PSK. The functional model of passband data transmission system is. Signal transmission encoder. x Signal. decoder. Cheren PSK he funcinal mdel f passand daa ransmissin sysem is m i Signal ransmissin encder si s i Signal Mdular Channel Deecr ransmissin decder mˆ Carrier signal m i is a sequence f syml emied frm a message

More information

GMM Estimation of the Number of Latent Factors

GMM Estimation of the Number of Latent Factors GMM Esimain f he Number f aen Facrs Seung C. Ahn a, Marcs F. Perez b March 18, 2007 Absrac We prpse a generalized mehd f mmen (GMM) esimar f he number f laen facrs in linear facr mdels. he mehd is apprpriae

More information

DISTANCE PROTECTION OF HVDC TRANSMISSION LINE WITH NOVEL FAULT LOCATION TECHNIQUE

DISTANCE PROTECTION OF HVDC TRANSMISSION LINE WITH NOVEL FAULT LOCATION TECHNIQUE IJRET: Inernainal Jurnal f Research in Engineering and Technlgy eissn: 9-6 pissn: -78 DISTANCE PROTECTION OF HVDC TRANSMISSION LINE WITH NOVEL FAULT LOCATION TECHNIQUE Ruchia Nale, P. Suresh Babu Suden,

More information

THE DETERMINATION OF CRITICAL FLOW FACTORS FOR NATURAL GAS MIXTURES. Part 3: The Calculation of C* for Natural Gas Mixtures

THE DETERMINATION OF CRITICAL FLOW FACTORS FOR NATURAL GAS MIXTURES. Part 3: The Calculation of C* for Natural Gas Mixtures A REPORT ON THE DETERMINATION OF CRITICAL FLOW FACTORS FOR NATURAL GAS MIXTURES Par 3: The Calculain f C* fr Naural Gas Mixures FOR NMSPU Deparmen f Trade and Indusry 151 Buckingham Palace Rad Lndn SW1W

More information

i-clicker Question lim Physics 123 Lecture 2 1 Dimensional Motion x 1 x 2 v is not constant in time v = v(t) acceleration lim Review:

i-clicker Question lim Physics 123 Lecture 2 1 Dimensional Motion x 1 x 2 v is not constant in time v = v(t) acceleration lim Review: Reiew: Physics 13 Lecure 1 Dimensinal Min Displacemen: Dx = x - x 1 (If Dx < 0, he displacemen ecr pins he lef.) Aerage elciy: (N he same as aerage speed) a slpe = a x x 1 1 Dx D x 1 x Crrecin: Calculus

More information

Analysis of Compact Polarimetric SAR Imaging Modes

Analysis of Compact Polarimetric SAR Imaging Modes Analysis of Compact Polarimetric AR Imaging Modes T. L. Ainsworth 1, M. Preiss, N. tacy, M. Nord 1,3 & J.-. Lee 1,4 1 Naval Research Lab., Washington, DC 0375 UA Defence cience and Technology Organisation,

More information

21.9 Magnetic Materials

21.9 Magnetic Materials 21.9 Magneic Maerials The inrinsic spin and rbial min f elecrns gives rise he magneic prperies f maerials è elecrn spin and rbis ac as iny curren lps. In ferrmagneic maerials grups f 10 16-10 19 neighbring

More information

Section 12 Time Series Regression with Non- Stationary Variables

Section 12 Time Series Regression with Non- Stationary Variables Secin Time Series Regressin wih Nn- Sainary Variables The TSMR assumpins include, criically, he assumpin ha he variables in a regressin are sainary. Bu many (ms?) ime-series variables are nnsainary. We

More information

AP Physics 1 MC Practice Kinematics 1D

AP Physics 1 MC Practice Kinematics 1D AP Physics 1 MC Pracice Kinemaics 1D Quesins 1 3 relae w bjecs ha sar a x = 0 a = 0 and mve in ne dimensin independenly f ne anher. Graphs, f he velciy f each bjec versus ime are shwn belw Objec A Objec

More information

Optimization of Four-Button BPM Configuration for Small-Gap Beam Chambers

Optimization of Four-Button BPM Configuration for Small-Gap Beam Chambers Opimizain f Fur-Bun BPM Cnfigurain fr Small-Gap Beam Chamers S. H. Kim Advanced Phn Surce Argnne Nainal Larary 9700 Suh Cass Avenue Argnne, Illinis 60439 USA Asrac. The cnfigurain f fur-un eam psiin mnirs

More information

Small Combustion Chamber. Combustion chamber area ratio

Small Combustion Chamber. Combustion chamber area ratio Lsses & Real Effecs in Nzzles Flw divergence Nnunifrmiy p lss due hea addiin Viscus effecs bundary layers-drag bundary layer-shck ineracins Hea lsses Nzzle ersin (hra) Transiens Muliphase flw Real gas

More information

and Sun (14) and Due and Singlen (19) apply he maximum likelihd mehd while Singh (15), and Lngsa and Schwarz (12) respecively emply he hreesage leas s

and Sun (14) and Due and Singlen (19) apply he maximum likelihd mehd while Singh (15), and Lngsa and Schwarz (12) respecively emply he hreesage leas s A MONTE CARLO FILTERING APPROACH FOR ESTIMATING THE TERM STRUCTURE OF INTEREST RATES Akihik Takahashi 1 and Seish Sa 2 1 The Universiy f Tky, 3-8-1 Kmaba, Megur-ku, Tky 153-8914 Japan 2 The Insiue f Saisical

More information

Theory and Applications for Weather Radars

Theory and Applications for Weather Radars Degree of Polarizaion: Theory and Applicaion for Weaher Radar Michele Gallei DLR-HR Microwave and Radar Iniue David H. O. Bebbingon Madhu Chandra Univeriy of ex TU-Chemniz Thoma Boerner DLR-HR Microwave

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 15 10/30/2013. Ito integral for simple processes

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 15 10/30/2013. Ito integral for simple processes MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.65/15.7J Fall 13 Lecure 15 1/3/13 I inegral fr simple prcesses Cnen. 1. Simple prcesses. I ismery. Firs 3 seps in cnsrucing I inegral fr general prcesses 1 I inegral

More information

Wireless Communication Channel Overview

Wireless Communication Channel Overview EC744 Wireless Communicaion Fall 008 Mohamed Essam Khedr Deparmen of Elecronics and Communicaions Wireless Communicaion Channel Overview Syllabus Tenaively Week 1 Week Week 3 Week 4 Week 5 Week 6 Week

More information

FITTING OF A PARTIALLY REPARAMETERIZED GOMPERTZ MODEL TO BROILER DATA

FITTING OF A PARTIALLY REPARAMETERIZED GOMPERTZ MODEL TO BROILER DATA FITTING OF A PARTIALLY REPARAMETERIZED GOMPERTZ MODEL TO BROILER DATA N. Okendro Singh Associae Professor (Ag. Sa.), College of Agriculure, Cenral Agriculural Universiy, Iroisemba 795 004, Imphal, Manipur

More information

Chem. 6C Midterm 1 Version B October 19, 2007

Chem. 6C Midterm 1 Version B October 19, 2007 hem. 6 Miderm Verin Ocber 9, 007 Name Suden Number ll wr mu be hwn n he exam fr parial credi. Pin will be aen ff fr incrrec r n uni. Nn graphing calcular and ne hand wrien 5 ne card are allwed. Prblem

More information

Uncertainties in TRP Measurements Due to Finite Range Lengths

Uncertainties in TRP Measurements Due to Finite Range Lengths Uncertainties in TRP Measurements Due t Finite Range Lengths James D Huff Carl W Sirles The Hwland Cmpany, Inc 4540 Atwater Curt, Suite 107 Bufrd, Gergia 30518 Abstract Ttal Radiated Pwer (TRP) and Ttal

More information

if N =2 J, obtain analysis (decomposition) of sample variance:

if N =2 J, obtain analysis (decomposition) of sample variance: Wavele Mehds fr Time Series Analysis Eamples: Time Series X Versus Time Inde Par VII: Wavele Variance and Cvariance X (a) (b) eamples f ime series mivae discussin decmpsiin f sample variance using waveles

More information

Microwave Engineering

Microwave Engineering Micrwave Engineering Cheng-Hsing Hsu Deparmen f Elecrical Engineering Nainal Unied Universiy Ouline. Transmissin ine Thery. Transmissin ines and Waveguides eneral Sluins fr TEM, TE, and TM waves ; Parallel

More information

RICSAC-97 A Reevaluation of the Reference Set of Full Scale Crash Tests

RICSAC-97 A Reevaluation of the Reference Set of Full Scale Crash Tests 970961 RICSAC-97 A Reevaluain f he Reference Se f Full Scale Crash Tess Brian G. McHenry and Raymnd R. McHenry McHenry Cnsulans, Inc. Cary, NC ABSTRACT Research perfrmed in he 1970's revealed significan

More information

Determining the Accuracy of Modal Parameter Estimation Methods

Determining the Accuracy of Modal Parameter Estimation Methods Determining the Accuracy f Mdal Parameter Estimatin Methds by Michael Lee Ph.D., P.E. & Mar Richardsn Ph.D. Structural Measurement Systems Milpitas, CA Abstract The mst cmmn type f mdal testing system

More information

The Buck Resonant Converter

The Buck Resonant Converter EE646 Pwer Elecrnics Chaper 6 ecure Dr. Sam Abdel-Rahman The Buck Resnan Cnverer Replacg he swich by he resnan-ype swich, ba a quasi-resnan PWM buck cnverer can be shwn ha here are fur mdes f pera under

More information

Large-scale Distance Metric Learning with Uncertainty

Large-scale Distance Metric Learning with Uncertainty i Large-scale Disance Meric Learning wih Uncerainy Qi Qian Jiasheng Tang Ha Li Shenghu Zhu Rng Jin Alibaba Grup, Bellevue, WA, 98004, USA {qi.qian, jiasheng.js, liha.lh, shenghu.zhu, jinrng.jr}@alibaba-inc.cm

More information

Ensamble methods: Boosting

Ensamble methods: Boosting Lecure 21 Ensamble mehods: Boosing Milos Hauskrech milos@cs.pi.edu 5329 Senno Square Schedule Final exam: April 18: 1:00-2:15pm, in-class Term projecs April 23 & April 25: a 1:00-2:30pm in CS seminar room

More information

Thermal Analysis Validation for Different Design Tubes in a Heat Exchanger

Thermal Analysis Validation for Different Design Tubes in a Heat Exchanger Thermal Analysis Validain fr Differen Design Tubes in a Hea Exchanger Rshan. V. Marde, Ashk. J. Keche Deparmen f Mechanical Engineering, MIT, Aurangabad (M., India Aricle Inf Aricle hisry: Received 2 January

More information

Nelson Primary School Written Calculation Policy

Nelson Primary School Written Calculation Policy Addiin Fundain Y1 Y2 Children will engage in a wide variey f sngs, rhymes, games and aciviies. They will begin relae addiin cmbining w grups f bjecs. They will find ne mre han a given number. Cninue develp

More information

RAPIDLY ADAPTIVE CFAR DETECTION BY MERGING INDIVIDUAL DECISIONS FROM TWO-STAGE ADAPTIVE DETECTORS

RAPIDLY ADAPTIVE CFAR DETECTION BY MERGING INDIVIDUAL DECISIONS FROM TWO-STAGE ADAPTIVE DETECTORS RAPIDLY ADAPIVE CFAR DEECION BY MERGING INDIVIDUAL DECISIONS FROM WO-SAGE ADAPIVE DEECORS Analii A. Knnv, Sung-yun Chi and Jin-a Kim Research Cener, SX Engine Yngin-si, 694 Krea kaa@ieee.rg; dkrein@nesx.cm;

More information

Physics Courseware Physics I Constant Acceleration

Physics Courseware Physics I Constant Acceleration Physics Curseware Physics I Cnsan Accelerain Equains fr cnsan accelerain in dimensin x + a + a + ax + x Prblem.- In he 00-m race an ahlee acceleraes unifrmly frm res his p speed f 0m/s in he firs x5m as

More information

Ensamble methods: Bagging and Boosting

Ensamble methods: Bagging and Boosting Lecure 21 Ensamble mehods: Bagging and Boosing Milos Hauskrech milos@cs.pi.edu 5329 Senno Square Ensemble mehods Mixure of expers Muliple base models (classifiers, regressors), each covers a differen par

More information

independenly fllwing square-r prcesses, he inuiive inerpreain f he sae variables is n clear, and smeimes i seems dicul nd admissible parameers fr whic

independenly fllwing square-r prcesses, he inuiive inerpreain f he sae variables is n clear, and smeimes i seems dicul nd admissible parameers fr whic A MONTE CARLO FILTERING APPROACH FOR ESTIMATING THE TERM STRUCTURE OF INTEREST RATES Akihik Takahashi 1 and Seish Sa 2 1 The Universiy f Tky, 3-8-1 Kmaba, Megur-ku, Tky 153-8914 Japan 2 The Insiue f Saisical

More information

Soccer Player Tracking across Uncalibrated Camera Streams

Soccer Player Tracking across Uncalibrated Camera Streams EEE nernainal rkshp n Visual Surveillance and erfrmance Evaluain f Tracking and Surveillance ETS 3 n cnjuncin wih V Ocber 3 Nice France. Sccer layer Tracking acrss Uncalibraed amera Sreams Jinman Kang

More information

ψ(t) = V x (0)V x (t)

ψ(t) = V x (0)V x (t) .93 Home Work Se No. (Professor Sow-Hsin Chen Spring Term 5. Due March 7, 5. This problem concerns calculaions of analyical expressions for he self-inermediae scaering funcion (ISF of he es paricle in

More information

Comparing Means: t-tests for One Sample & Two Related Samples

Comparing Means: t-tests for One Sample & Two Related Samples Comparing Means: -Tess for One Sample & Two Relaed Samples Using he z-tes: Assumpions -Tess for One Sample & Two Relaed Samples The z-es (of a sample mean agains a populaion mean) is based on he assumpion

More information

Impact Switch Study Modeling & Implications

Impact Switch Study Modeling & Implications L-3 Fuzing & Ordnance Sysems Impac Swich Sudy Mdeling & Implicains Dr. Dave Frankman May 13, 010 NDIA 54 h Annual Fuze Cnference This presenain cnsiss f L-3 Crprain general capabiliies infrmain ha des

More information

ABSTRACT Circular Imaging Block Keywords:

ABSTRACT Circular Imaging Block Keywords: ABSTRACT Phgrammeric 3D measuring prcedure needs careful planning, especially in he clse-range case, in rder fulfill requiremens ih respec accuracy and reliabiliy f measuremens. In he special case f indr

More information

A Note on the Approximation of the Wave Integral. in a Slightly Viscous Ocean of Finite Depth. due to Initial Surface Disturbances

A Note on the Approximation of the Wave Integral. in a Slightly Viscous Ocean of Finite Depth. due to Initial Surface Disturbances Applied Mahemaical Sciences, Vl. 7, 3, n. 36, 777-783 HIKARI Ld, www.m-hikari.cm A Ne n he Apprximain f he Wave Inegral in a Slighly Viscus Ocean f Finie Deph due Iniial Surface Disurbances Arghya Bandypadhyay

More information

Lecture 3: Resistive forces, and Energy

Lecture 3: Resistive forces, and Energy Lecure 3: Resisive frces, and Energy Las ie we fund he velciy f a prjecile ving wih air resisance: g g vx ( ) = vx, e vy ( ) = + v + e One re inegrain gives us he psiin as a funcin f ie: dx dy g g = vx,

More information

Physics 2B Chapter 23 Notes - Faraday s Law & Inductors Spring 2018

Physics 2B Chapter 23 Notes - Faraday s Law & Inductors Spring 2018 Michael Faraday lived in the Lndn area frm 1791 t 1867. He was 29 years ld when Hand Oersted, in 1820, accidentally discvered that electric current creates magnetic field. Thrugh empirical bservatin and

More information

A new Model for Karst Spring Hydrograph Analysis

A new Model for Karst Spring Hydrograph Analysis A new Model for Kars Spring Hydrograph Analysis Ming Ye (mye@fsu.edu) Deparmen of Earh, Ocean, and Amospheric Science, FSU Bin Xu China Universiy of Mining and Technology, Beijing FSU 1 s Kars Symposium

More information

a. (1) Assume T = 20 ºC = 293 K. Apply Equation 2.22 to find the resistivity of the brass in the disk with

a. (1) Assume T = 20 ºC = 293 K. Apply Equation 2.22 to find the resistivity of the brass in the disk with Aignmen #5 EE7 / Fall 0 / Aignmen Sluin.7 hermal cnducin Cnider bra ally wih an X amic fracin f Zn. Since Zn addiin increae he number f cnducin elecrn, we have cale he final ally reiiviy calculaed frm

More information

Variation of Mean Hourly Insolation with Time at Jos

Variation of Mean Hourly Insolation with Time at Jos OR Jurnal f Envirnmenal cience, Txiclgy and Fd Technlgy (OR-JETFT) e-n: 319-40,p- N: 319-399.Vlume 9, ue 7 Ver. (July. 015), PP 01-05 www.irjurnal.rg Variain f Mean urly nlain wih Time a J 1 Ad Mua, Babangida

More information

Generalized Least Squares

Generalized Least Squares Generalized Leas Squares Augus 006 1 Modified Model Original assumpions: 1 Specificaion: y = Xβ + ε (1) Eε =0 3 EX 0 ε =0 4 Eεε 0 = σ I In his secion, we consider relaxing assumpion (4) Insead, assume

More information

Motion Along a Straight Line

Motion Along a Straight Line PH 1-3A Fall 010 Min Alng a Sraigh Line Lecure Chaper (Halliday/Resnick/Walker, Fundamenals f Physics 8 h ediin) Min alng a sraigh line Sudies he min f bdies Deals wih frce as he cause f changes in min

More information

Differentiation Applications 1: Related Rates

Differentiation Applications 1: Related Rates Differentiatin Applicatins 1: Related Rates 151 Differentiatin Applicatins 1: Related Rates Mdel 1: Sliding Ladder 10 ladder y 10 ladder 10 ladder A 10 ft ladder is leaning against a wall when the bttm

More information

Edexcel GCSE Physics

Edexcel GCSE Physics Edexcel GCSE Physics Tpic 10: Electricity and circuits Ntes (Cntent in bld is fr Higher Tier nly) www.pmt.educatin The Structure f the Atm Psitively charged nucleus surrunded by negatively charged electrns

More information

CS 477/677 Analysis of Algorithms Fall 2007 Dr. George Bebis Course Project Due Date: 11/29/2007

CS 477/677 Analysis of Algorithms Fall 2007 Dr. George Bebis Course Project Due Date: 11/29/2007 CS 477/677 Analysis f Algrithms Fall 2007 Dr. Gerge Bebis Curse Prject Due Date: 11/29/2007 Part1: Cmparisn f Srting Algrithms (70% f the prject grade) The bjective f the first part f the assignment is

More information

Machine Learning for Signal Processing Prediction and Estimation, Part II

Machine Learning for Signal Processing Prediction and Estimation, Part II Machine Learning fr Signal Prceing Predicin and Eimain, Par II Bhikha Raj Cla 24. 2 Nv 203 2 Nv 203-755/8797 Adminirivia HW cre u Sme uden wh g really pr mark given chance upgrade Make i all he way he

More information

K The slowest step in a mechanism has this

K The slowest step in a mechanism has this CM 6 Generl Chemisry II Nme SLUTINS Exm, Spring 009 Dr. Seel. (0 pins) Selec he nswer frm he clumn n he righ h bes mches ech descripin frm he clumn n he lef. Ech nswer cn be used, ms, nly nce. E G This

More information

Sliding Mode Control: An Approach To Regulate Nonlinear Chemical Processes

Sliding Mode Control: An Approach To Regulate Nonlinear Chemical Processes Sliding Mde Cnrl: An Apprach T Regulae Nnlinear Chemical rcesses Oscar Camach Deparamen de Circuis y Medidas Universidad de Ls Andes Mérida 5. Venezuela Carls A. Smih Chemical Engineering Deparmen Universiy

More information

ULTRAFAST TIME DOMAIN OPTICS OF SINGLE-CYCLE LASER PULSE INTERACTION WITH MATERIALS

ULTRAFAST TIME DOMAIN OPTICS OF SINGLE-CYCLE LASER PULSE INTERACTION WITH MATERIALS Universiy f Nebraska - Lincln DigialCmmns@Universiy f Nebraska - Lincln Theses, Disserains, and Suden Research frm Elecrical & Cmpuer Engineering Elecrical & Cmpuer Engineering, Deparmen f 1-010 ULTRAFAST

More information

(V 1. (T i. )- FrC p. ))= 0 = FrC p (T 1. (T 1s. )+ UA(T os. (T is

(V 1. (T i. )- FrC p. ))= 0 = FrC p (T 1. (T 1s. )+ UA(T os. (T is . Yu are repnible fr a reacr in which an exhermic liqui-phae reacin ccur. The fee mu be preheae he hrehl acivain emperaure f he caaly, bu he pruc ream mu be cle. T reuce uiliy c, yu are cniering inalling

More information

Ramsey model. Rationale. Basic setup. A g A exogenous as in Solow. n L each period.

Ramsey model. Rationale. Basic setup. A g A exogenous as in Solow. n L each period. Ramsey mdel Rainale Prblem wih he Slw mdel: ad-hc assumpin f cnsan saving rae Will cnclusins f Slw mdel be alered if saving is endgenusly deermined by uiliy maximizain? Yes, bu we will learn a l abu cnsumpin/saving

More information

Physics 111. Exam #1. September 28, 2018

Physics 111. Exam #1. September 28, 2018 Physics xam # Sepember 8, 08 ame Please read and fllw hese insrucins carefully: Read all prblems carefully befre aemping slve hem. Yur wrk mus be legible, and he rganizain clear. Yu mus shw all wrk, including

More information

ENSC Discrete Time Systems. Project Outline. Semester

ENSC Discrete Time Systems. Project Outline. Semester ENSC 49 - iscrete Time Systems Prject Outline Semester 006-1. Objectives The gal f the prject is t design a channel fading simulatr. Upn successful cmpletin f the prject, yu will reinfrce yur understanding

More information

Driver Phase Correlated Fluctuations in the Rotation of a Strongly Driven Quantum Bit

Driver Phase Correlated Fluctuations in the Rotation of a Strongly Driven Quantum Bit [acceped fr PRA Rapid Cmm; quan-ph/] Driver Phase Crrelaed Flucuains in he Rain f a Srngly Driven Quanum Bi M.S. Shahriar,, P. Pradhan,, and J. Mrzinski Dep. f Elecrical and Cmpuer Engineering, Nrhwesern

More information

DUAL EMISSION LASER INDUCED FLUORESCENCE TECHNIQUE (DELIF) FOR OIL FILM THICKNESS AND TEMPERATURE MEASUREMENT

DUAL EMISSION LASER INDUCED FLUORESCENCE TECHNIQUE (DELIF) FOR OIL FILM THICKNESS AND TEMPERATURE MEASUREMENT Prceedings ASME FEDSM ASME Fluids Engineering Divisin Summer Meeing June -5,, Bsn, Massachuses FEDSM-43 DUAL EMSSON LASER NDUCED FLUORESCENCE TECHNQUE DELF FOR OL FLM THCKNESS AND TEMPERATURE MEASUREMENT

More information

Efficient and Fast Simulation of RF Circuits and Systems via Spectral Method

Efficient and Fast Simulation of RF Circuits and Systems via Spectral Method Efficien and Fas Simulain f RF Circuis and Sysems via Specral Mehd 1. Prjec Summary The prpsed research will resul in a new specral algrihm, preliminary simular based n he new algrihm will be subsanially

More information

INFLUENCE OF WIND VELOCITY TO SUPPLY WATER TEMPERATURE IN HOUSE HEATING INSTALLATION AND HOT-WATER DISTRICT HEATING SYSTEM

INFLUENCE OF WIND VELOCITY TO SUPPLY WATER TEMPERATURE IN HOUSE HEATING INSTALLATION AND HOT-WATER DISTRICT HEATING SYSTEM Dr. Branislav Zivkvic, B. Eng. Faculy f Mechanical Engineering, Belgrade Universiy Predrag Zeknja, B. Eng. Belgrade Municipal DH Cmpany Angelina Kacar, B. Eng. Faculy f Agriculure, Belgrade Universiy INFLUENCE

More information

Probabilistic Robotics

Probabilistic Robotics Probabilisic Roboics Bayes Filer Implemenaions Gaussian filers Bayes Filer Reminder Predicion bel p u bel d Correcion bel η p z bel Gaussians : ~ π e p N p - Univariae / / : ~ μ μ μ e p Ν p d π Mulivariae

More information

Building to Transformations on Coordinate Axis Grade 5: Geometry Graph points on the coordinate plane to solve real-world and mathematical problems.

Building to Transformations on Coordinate Axis Grade 5: Geometry Graph points on the coordinate plane to solve real-world and mathematical problems. Building t Transfrmatins n Crdinate Axis Grade 5: Gemetry Graph pints n the crdinate plane t slve real-wrld and mathematical prblems. 5.G.1. Use a pair f perpendicular number lines, called axes, t define

More information

COMP 551 Applied Machine Learning Lecture 9: Support Vector Machines (cont d)

COMP 551 Applied Machine Learning Lecture 9: Support Vector Machines (cont d) COMP 551 Applied Machine Learning Lecture 9: Supprt Vectr Machines (cnt d) Instructr: Herke van Hf (herke.vanhf@mail.mcgill.ca) Slides mstly by: Class web page: www.cs.mcgill.ca/~hvanh2/cmp551 Unless therwise

More information

Misc. ArcMap Stuff Andrew Phay

Misc. ArcMap Stuff Andrew Phay Misc. ArcMap Stuff Andrew Phay aphay@whatcmcd.rg Prjectins Used t shw a spherical surface n a flat surface Distrtin Shape Distance True Directin Area Different Classes Thse that minimize distrtin in shape

More information

References are appeared in the last slide. Last update: (1393/08/19)

References are appeared in the last slide. Last update: (1393/08/19) SYSEM IDEIFICAIO Ali Karimpour Associae Professor Ferdowsi Universi of Mashhad References are appeared in he las slide. Las updae: 0..204 393/08/9 Lecure 5 lecure 5 Parameer Esimaion Mehods opics o be

More information

P4/mmm (D4k). For [(C2Hs)aN]2CoC14, precession data (Mo Kc0 gave a=b= A c A V= A 3.

P4/mmm (D4k). For [(C2Hs)aN]2CoC14, precession data (Mo Kc0 gave a=b= A c A V= A 3. 04 Aca Crys (97) 3 04 The Crysal and Mlecular Srucure f Teraehylammnium Teraehlrnickelae()* B G D STUCKY J B FOLKERS AND T J KSTENMACHER Deparmen f Chemisry and Chemical Engineering and Maerials Research

More information

Unit-I (Feedback amplifiers) Features of feedback amplifiers. Presentation by: S.Karthie, Lecturer/ECE SSN College of Engineering

Unit-I (Feedback amplifiers) Features of feedback amplifiers. Presentation by: S.Karthie, Lecturer/ECE SSN College of Engineering Uni-I Feedback ampliiers Feaures eedback ampliiers Presenain by: S.Karhie, Lecurer/ECE SSN Cllege Engineering OBJECTIVES T make he sudens undersand he eec negaive eedback n he llwing ampliier characerisics:

More information

Introduction. If there are no physical guides, the motion is said to be unconstrained. Example 2. - Airplane, rocket

Introduction. If there are no physical guides, the motion is said to be unconstrained. Example 2. - Airplane, rocket Kinemaic f Paricle Chaper Inrducin Kinemaic: i he branch f dynamic which decribe he min f bdie wihu reference he frce ha eiher caue he min r are generaed a a reul f he min. Kinemaic i fen referred a he

More information

Exponential Weighted Moving Average (EWMA) Chart Under The Assumption of Moderateness And Its 3 Control Limits

Exponential Weighted Moving Average (EWMA) Chart Under The Assumption of Moderateness And Its 3 Control Limits DOI: 0.545/mjis.07.5009 Exponenial Weighed Moving Average (EWMA) Char Under The Assumpion of Moderaeness And Is 3 Conrol Limis KALPESH S TAILOR Assisan Professor, Deparmen of Saisics, M. K. Bhavnagar Universiy,

More information

ABSTRACT. Index terms compact polarimetry, Faraday rotation, bare soil surfaces, soil moisture.

ABSTRACT. Index terms compact polarimetry, Faraday rotation, bare soil surfaces, soil moisture. COPARION BETWEEN THE CONFORITY COEFFICIENT AND PREVIOU CLAIFICATION TECHNIQUE FOR BARE URFACE DICRIINATION AND APPLICATION TO COPACT POLARIETRY ODE y-linh Truong-Loï 13, A. Freeman, P. Dubois-Fernandez

More information

THERMAL TEST LEVELS & DURATIONS

THERMAL TEST LEVELS & DURATIONS PREFERRED RELIABILITY PAGE 1 OF 7 PRACTICES PRACTICE NO. PT-TE-144 Practice: 1 Perfrm thermal dwell test n prtflight hardware ver the temperature range f +75 C/-2 C (applied at the thermal cntrl/munting

More information

Module 4. Analysis of Statically Indeterminate Structures by the Direct Stiffness Method. Version 2 CE IIT, Kharagpur

Module 4. Analysis of Statically Indeterminate Structures by the Direct Stiffness Method. Version 2 CE IIT, Kharagpur Mdle Analysis f Saically Indeerminae Srcres by he Direc Siffness Mehd Versin CE IIT, Kharagr Lessn The Direc Siffness Mehd: Temerare Changes and Fabricain Errrs in Trss Analysis Versin CE IIT, Kharagr

More information

Lecture 4 ( ) Some points of vertical motion: Here we assumed t 0 =0 and the y axis to be vertical.

Lecture 4 ( ) Some points of vertical motion: Here we assumed t 0 =0 and the y axis to be vertical. Sme pins f erical min: Here we assumed and he y axis be erical. ( ) y g g y y y y g dwnwards 9.8 m/s g Lecure 4 Accelerain The aerage accelerain is defined by he change f elciy wih ime: a ; In analgy,

More information

CONTAMINANT TRANSPORT MECHANICAL ASPECTS ADVECTION

CONTAMINANT TRANSPORT MECHANICAL ASPECTS ADVECTION ONTAMINANT TRANSPORT MEHANIAL ASPETS AVETION Kdh φ dl e aerage linear elci ISPERSION/IFFUSION due ariable adecin ha ccurs in he ransiin ne beween w dmains f he fluid wih differen cmpsiins (diffusin is

More information

Polarimetric Calibration of the Ingara Bistatic SAR

Polarimetric Calibration of the Ingara Bistatic SAR Polarimetric Calibration of the Ingara Bistatic SAR Alvin Goh, 1,2 Mark Preiss, 1 Nick Stacy, 1 Doug Gray 2 1. Imaging Radar Systems Group Defence Science and Technology Organisation 2. School of Electrical

More information

Západočeská Univerzita v Plzni, Czech Republic and Groupe ESIEE Paris, France

Západočeská Univerzita v Plzni, Czech Republic and Groupe ESIEE Paris, France ADAPTIVE SIGNAL PROCESSING USING MAXIMUM ENTROPY ON THE MEAN METHOD AND MONTE CARLO ANALYSIS Pavla Holejšovsá, Ing. *), Z. Peroua, Ing. **), J.-F. Bercher, Prof. Assis. ***) Západočesá Univerzia v Plzni,

More information

INSTRUMENTAL VARIABLES

INSTRUMENTAL VARIABLES INSTRUMENTAL VARIABLES Technical Track Sessin IV Sergi Urzua University f Maryland Instrumental Variables and IE Tw main uses f IV in impact evaluatin: 1. Crrect fr difference between assignment f treatment

More information

A Comparison of Methods for Computing the Eigenvalues and Eigenvectors of a Real Symmetric Matrix. By Paul A. White and Robert R.

A Comparison of Methods for Computing the Eigenvalues and Eigenvectors of a Real Symmetric Matrix. By Paul A. White and Robert R. A Cmparisn f Methds fr Cmputing the Eigenvalues and Eigenvectrs f a Real Symmetric Matrix By Paul A. White and Rbert R. Brwn Part I. The Eigenvalues I. Purpse. T cmpare thse methds fr cmputing the eigenvalues

More information

TileThe Bielecrical Penials Auhr(s) SAKAMOTO, Masahir; SUMYA, Tadashi Kazu; Ciain Wd research : bullein f he W Universiy (1984), 7: 42-46 ssue Dae 1984-2-29 URL hp://hdl.handle.ne/2433/53328 Righ Type

More information

Testing for a Single Factor Model in the Multivariate State Space Framework

Testing for a Single Factor Model in the Multivariate State Space Framework esing for a Single Facor Model in he Mulivariae Sae Space Framework Chen C.-Y. M. Chiba and M. Kobayashi Inernaional Graduae School of Social Sciences Yokohama Naional Universiy Japan Faculy of Economics

More information

5 The fitting methods used in the normalization of DSD

5 The fitting methods used in the normalization of DSD The fiing mehods used in he normalizaion of DSD.1 Inroducion Sempere-Torres e al. 1994 presened a general formulaion for he DSD ha was able o reproduce and inerpre all previous sudies of DSD. The mehodology

More information

PSU GISPOPSCI June 2011 Ordinary Least Squares & Spatial Linear Regression in GeoDa

PSU GISPOPSCI June 2011 Ordinary Least Squares & Spatial Linear Regression in GeoDa There are tw parts t this lab. The first is intended t demnstrate hw t request and interpret the spatial diagnstics f a standard OLS regressin mdel using GeDa. The diagnstics prvide infrmatin abut the

More information

The lower limit of interval efficiency in Data Envelopment Analysis

The lower limit of interval efficiency in Data Envelopment Analysis Jurnal f aa nelpmen nalysis and ecisin Science 05 N. (05) 58-66 ailable nline a www.ispacs.cm/dea lume 05, Issue, ear 05 ricle I: dea-00095, 9 Pages di:0.5899/05/dea-00095 Research ricle aa nelpmen nalysis

More information

Deep Learning: Theory, Techniques & Applications - Recurrent Neural Networks -

Deep Learning: Theory, Techniques & Applications - Recurrent Neural Networks - Deep Learning: Theory, Techniques & Applicaions - Recurren Neural Neworks - Prof. Maeo Maeucci maeo.maeucci@polimi.i Deparmen of Elecronics, Informaion and Bioengineering Arificial Inelligence and Roboics

More information

Standard models used for monetary policy analysis typically assume that households and

Standard models used for monetary policy analysis typically assume that households and Cenennial Issue Annuncemens and he Rle f Plicy Guidance Carl E. Walsh By prviding guidance abu fuure ecnmic develpmens, cenral banks can affec privae secr expecains and decisins. This can imprve welfare

More information

G.SRT.A.2-3 PRACTICE WS #1-3 geometrycommoncore.com 1. Name: Date: Similarity Practice

G.SRT.A.2-3 PRACTICE WS #1-3 geometrycommoncore.com 1. Name: Date: Similarity Practice .S..2-3 I WS #1-3 gemetrycmmncre.cm 1 ame: ate: _ Similarity ractice .S..2-3 I WS #1-3 gemetrycmmncre.cm 2 I will knw hw t identify crrespnding angles and sides based n similarity statements. I will knw

More information