On the Boyd- Kuramoto Model : Emergence in a Mathematical Model for Adversarial C2 Systems

Size: px
Start display at page:

Download "On the Boyd- Kuramoto Model : Emergence in a Mathematical Model for Adversarial C2 Systems"

Transcription

1 On he oyd- Kuramoo Model : Emergence n a Mahemacal Model for Adversaral C2 Sysems Alexander Kallonas DSTO, Jon Operaons Dvson

2 C2 Processes: many are cycles! oyd s Observe-Oren-Decde-Ac Loop: Snowden s Cynefn Framework: Dfferen loops dependng on conex Ineracng OODA: Moon, Kruzns, Calber 2002 Operaonal Plannng Process Execue Sraegc Inen Operaonal Taccal Scope Elaboraons: Lawson s C2 Cycle; DOODA, Msson Analyss COA Dev COA Analyss Decde

3 The Kuramoo* Model Kuramoo Model --dm Oscllaor: K θ = ω + A sn θ θ θ aural Frequency Couplng ework adacency marx Phase Synchronsaon a Hgh K Incoherence a Low K * Kuramoo, Chemcal Oscllaons, Waves and Turbulence, Sprnger, erln, 984; Kallonas, Phys. ev. E 82, , 200 Also conrbuons by. Taylor and T. Dekker

4 Mappng Kuramoo o oyd θ = Pon of progress n decson cycle. K = Couplng = degree of ghness of conrol. ω = aural frequency of each node = nverse me perod for processng approprae nformaon accordng o envronmen n order o advance hrough cycle. A = nra-c2 ework = no us communcaons connecvy, bu also auhory, collaborave, socal, and vsual neworks. Who are my pons of reference for my decson cycle? Wh whom mus I muually adus o progress decsons? Perodcy of sne response funcon: rrelevance of sale nformaon or pas decsons: he curren decson cycle s all ha maers. O D θ O A

5 C2- Tme Perod Specrum p rob d ens y funco n ω accal ω operaonal Model n hs paper: only one such echelon ncluded. ω sraegc Modern mlary operaons nvolve dverse me scales and neworkng of processes days

6 The oyd- Kuramoo equaons cf Lancheser aron and Hughes salvo equaons Phase angles Inrnsc frequences β ω ρ ν Adacency marces M.. Ths s a Carcaure: Informal eworks n Tradonal Mlary Al 20; Herarchy n Insurgen eworks Memon e al 2008 β = ω + ρ = ν + = = sn β β + sn ρ ρ + = = M M F ρ β G β ρ. ω, ν [0,] unform random dsrbuon neracons only whn one echelon

7 Inellgence- Survellance- econnassance & OODA lue has oal IS F ρ β = sn ρ + λ β λ=π/ lue seeks o ge nsde adversary OODA loop G β ρ = sn β ρ exp β 2 / 2s IS srengh s= π.772 phase angle ed synchronses around lue `Acons wh narrow IS

8 Measures of Performance = Ψ e e r θ [ ] = ρ β = e r β = e r ρ Measure of nernal synchronsaon, Measure of exernal synchronsaon

9 asc Exreme ehavours r Dela_ Tme = = 0 0 = Tme lue focused exclusvely on ed; neher nernally coordnaes. r Dela_ Tme Tme.8.5 lue, ed focused exclusvely on nernal coordnaon bu no regard for each oher For hs nsance! ω.56 ν =

10 Emergence: he surprse Laughln: sysem quales or behavours no reducble o he sysem componens bu arse from her neracons. Inermedae Couplng Srong Couplng Eg. andom selecon of frequences makes nodes _ close even hough opologcally `far ; creaes affny for dynamcally formng a sub-cluser Ths canno be desgned for gven agen dfferenaon. Sub-clusers emerge a nermedae neracon srenghs. Each nsance s dfferen!

11 lue v ed a he Edge of Chaos r me r me =.075 = Dela_ Dela_ me me =.075 = lue becomes more synchronsed hrough sronger couplng o ed a cos of oscllaons n sayng nsde ed s OODA DID YOU EXPECT THAT?

12 r r r r me me me lue adaps o red me Anoher example: Only ed a he Edge =.08 =.08 =.08 =.08 = = = 2, a cos of zg-zag n sayng nsde ed s OODA Dela_ Dela_ Dela_ Dela_ me me me me

13 Conclusons There are more varables by whch radonal C2 srucures can acheve Agly; hey are subec o mahemacal modellng. Model enables fndng he balance pon for gven C2 srucures and me scales beween nernal coordnaon and responsveness o adversary. Emergence s nohng myscal: mahemacal models can capure such surprses n represenaons of C2. Applcaons: realsc nework daa, human facors daa, lmed/nerruped IS funcons also for lue. Mul-echelon, mul-me specrum: needs modfcaon of equaons. oyd-kuramoo can nermedae/cross-valdae beween hgh/low fdely models of C2 sysems. Thanks o Tony Dekker, chard Taylor, ran Hanlon, Sharon oswell and Paul Whbread for dscussons and encouragemen over he years.

Gaining advantage from Complexity in Defence: a new DST research initiative

Gaining advantage from Complexity in Defence: a new DST research initiative UNCLASSIFIED Ganng advanage from Complexy n Defence: a new DST research nave Alexander Kallonas, Keeley Hoek [ANU], Mahew Zuparc Jon & Operaons Analyss Dvson 1 UNCLASSIFIED Oulne Complexy Good or ad for

More information

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005 Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc

More information

Chapter 6: AC Circuits

Chapter 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 information

Mechanics Physics 151

Mechanics 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 information

Multi-Objective Control and Clustering Synchronization in Chaotic Connected Complex Networks*

Multi-Objective Control and Clustering Synchronization in Chaotic Connected Complex Networks* Mul-Objecve Conrol and Cluserng Synchronzaon n Chaoc Conneced Complex eworks* JI-QIG FAG, Xn-Bao Lu :Deparmen of uclear Technology Applcaon Insue of Aomc Energy 043, Chna Fjq96@6.com : Deparmen of Auomaon,

More information

Bayes rule for a classification problem INF Discriminant functions for the normal density. Euclidean distance. Mahalanobis distance

Bayes rule for a classification problem INF Discriminant functions for the normal density. Euclidean distance. Mahalanobis distance INF 43 3.. Repeon Anne Solberg (anne@f.uo.no Bayes rule for a classfcaon problem Suppose we have J, =,...J classes. s he class label for a pxel, and x s he observed feaure vecor. We can use Bayes rule

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/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 information

The Finite Element Method for the Analysis of Non-Linear and Dynamic Systems

The 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 information

Research Article Adaptive Synchronization of Complex Dynamical Networks with State Predictor

Research Article Adaptive Synchronization of Complex Dynamical Networks with State Predictor Appled Mahemacs Volume 3, Arcle ID 39437, 8 pages hp://dxdoorg/55/3/39437 Research Arcle Adapve Synchronzaon of Complex Dynamcal eworks wh Sae Predcor Yunao Sh, Bo Lu, and Xao Han Key Laboraory of Beng

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure

More information

Born Oppenheimer Approximation and Beyond

Born Oppenheimer Approximation and Beyond L Born Oppenhemer Approxmaon and Beyond aro Barba A*dex Char Professor maro.barba@unv amu.fr Ax arselle Unversé, nsu de Chme Radcalare LGHT AD Adabac x dabac x nonadabac LGHT AD From Gree dabaos: o be

More information

Lecture 9: Dynamic Properties

Lecture 9: Dynamic Properties Shor Course on Molecular Dynamcs Smulaon Lecure 9: Dynamc Properes Professor A. Marn Purdue Unversy Hgh Level Course Oulne 1. MD Bascs. Poenal Energy Funcons 3. Inegraon Algorhms 4. Temperaure Conrol 5.

More information

CS286.2 Lecture 14: Quantum de Finetti Theorems II

CS286.2 Lecture 14: Quantum de Finetti Theorems II CS286.2 Lecure 14: Quanum de Fne Theorems II Scrbe: Mara Okounkova 1 Saemen of he heorem Recall he las saemen of he quanum de Fne heorem from he prevous lecure. Theorem 1 Quanum de Fne). Le ρ Dens C 2

More information

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE 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

Dual Approximate Dynamic Programming for Large Scale Hydro Valleys

Dual Approximate Dynamic Programming for Large Scale Hydro Valleys Dual Approxmae Dynamc Programmng for Large Scale Hydro Valleys Perre Carpener and Jean-Phlppe Chanceler 1 ENSTA ParsTech and ENPC ParsTech CMM Workshop, January 2016 1 Jon work wh J.-C. Alas, suppored

More information

2.1 Constitutive Theory

2.1 Constitutive Theory Secon.. Consuve Theory.. Consuve Equaons Governng Equaons The equaons governng he behavour of maerals are (n he spaal form) dρ v & ρ + ρdv v = + ρ = Conservaon of Mass (..a) d x σ j dv dvσ + b = ρ v& +

More information

FI 3103 Quantum Physics

FI 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 information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density 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 information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

Let s treat the problem of the response of a system to an applied external force. Again,

Let s treat the problem of the response of a system to an applied external force. Again, Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem

More information

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon

More information

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!) i+1,q - [(! ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal

More information

Forecasting customer behaviour in a multi-service financial organisation: a profitability perspective

Forecasting customer behaviour in a multi-service financial organisation: a profitability perspective Forecasng cusomer behavour n a mul-servce fnancal organsaon: a profably perspecve A. Audzeyeva, Unversy of Leeds & Naonal Ausrala Group Europe, UK B. Summers, Unversy of Leeds, UK K.R. Schenk-Hoppé, Unversy

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT 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 information

Optimal environmental charges under imperfect compliance

Optimal environmental charges under imperfect compliance ISSN 1 746-7233, England, UK World Journal of Modellng and Smulaon Vol. 4 (28) No. 2, pp. 131-139 Opmal envronmenal charges under mperfec complance Dajn Lu 1, Ya Wang 2 Tazhou Insue of Scence and Technology,

More information

Solution in semi infinite diffusion couples (error function analysis)

Solution 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 information

Exact Dynamic Programming for Decentralized POMDPs with Lossless Policy Compression

Exact Dynamic Programming for Decentralized POMDPs with Lossless Policy Compression Proceedngs of he Egheenh Inernaonal Conference on Auomaed Plannng and Schedulng (ICAPS 2008) Exac Dynamc Programmng for Decenralzed POMDPs wh Lossless Polcy Compresson Abdeslam Boularas and Brahm Chab-draa

More information

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

J 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 information

Normal Random Variable and its discriminant functions

Normal Random Variable and its discriminant functions Noral Rando Varable and s dscrnan funcons Oulne Noral Rando Varable Properes Dscrnan funcons Why Noral Rando Varables? Analycally racable Works well when observaon coes for a corruped snle prooype 3 The

More information

We are estimating the density of long distant migrant (LDM) birds in wetlands along Lake Michigan.

We are estimating the density of long distant migrant (LDM) birds in wetlands along Lake Michigan. Ch 17 Random ffecs and Mxed Models 17. Random ffecs Models We are esmang he densy of long dsan mgran (LDM) brds n welands along Lake Mchgan. μ + = LDM per hecaren h weland ~ N(0, ) The varably of expeced

More information

The topology and signature of the regulatory interactions predict the expression pattern of the segment polarity genes in Drosophila m elanogaster

The topology and signature of the regulatory interactions predict the expression pattern of the segment polarity genes in Drosophila m elanogaster The opology and sgnaure of he regulaory neracons predc he expresson paern of he segmen polary genes n Drosophla m elanogaser Hans Ohmer and Réka Alber Deparmen of Mahemacs Unversy of Mnnesoa Complex bologcal

More information

Real-Time Trajectory Generation and Tracking for Cooperative Control Systems

Real-Time Trajectory Generation and Tracking for Cooperative Control Systems Real-Tme Trajecor Generaon and Trackng for Cooperave Conrol Ssems Rchard Mrra Jason Hcke Calforna Inse of Technolog MURI Kckoff Meeng 14 Ma 2001 Olne I. Revew of prevos work n rajecor generaon and rackng

More information

How about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?

How about the more general linear scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )? lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of

More information

Robustness Experiments with Two Variance Components

Robustness Experiments with Two Variance Components Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference

More information

Department of Economics University of Toronto

Department of Economics University of Toronto Deparmen of Economcs Unversy of Torono ECO408F M.A. Economercs Lecure Noes on Heeroskedascy Heeroskedascy o Ths lecure nvolves lookng a modfcaons we need o make o deal wh he regresson model when some of

More information

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen

More information

Single-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method

Single-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method 10 h US Naonal Congress on Compuaonal Mechancs Columbus, Oho 16-19, 2009 Sngle-loop Sysem Relably-Based Desgn & Topology Opmzaon (SRBDO/SRBTO): A Marx-based Sysem Relably (MSR) Mehod Tam Nguyen, Junho

More information

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts nernaonal ournal of Appled Engneerng Research SSN 0973-4562 Volume 13, Number 10 (2018) pp. 8708-8713 Modelng and Solvng of Mul-Produc nvenory Lo-Szng wh Suppler Selecon under Quany Dscouns Naapa anchanaruangrong

More information

( ) [ ] MAP Decision Rule

( ) [ ] MAP Decision Rule Announcemens Bayes Decson Theory wh Normal Dsrbuons HW0 due oday HW o be assgned soon Proec descrpon posed Bomercs CSE 90 Lecure 4 CSE90, Sprng 04 CSE90, Sprng 04 Key Probables 4 ω class label X feaure

More information

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.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 information

Solving Equation [5.61], the helical fiber thickness required to contain the internal pressure is:

Solving Equation [5.61], the helical fiber thickness required to contain the internal pressure is: 5.4.3 eng Analyss of Cylndrcal Pressure Vessels S. T. Peers 001 Ths sofware s provded free for your use wh no guaranee as o s effecveness. I s copyrghed by Process-Research and may no be duplcaed, gven

More information

TSS = SST + SSE An orthogonal partition of the total SS

TSS = SST + SSE An orthogonal partition of the total SS ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally

More information

Robust and Accurate Cancer Classification with Gene Expression Profiling

Robust and Accurate Cancer Classification with Gene Expression Profiling Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem

More information

Notes on the stability of dynamic systems and the use of Eigen Values.

Notes 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 information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () 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 information

Clustering (Bishop ch 9)

Clustering (Bishop ch 9) Cluserng (Bshop ch 9) Reference: Daa Mnng by Margare Dunham (a slde source) 1 Cluserng Cluserng s unsupervsed learnng, here are no class labels Wan o fnd groups of smlar nsances Ofen use a dsance measure

More information

Computing Relevance, Similarity: The Vector Space Model

Computing Relevance, Similarity: The Vector Space Model Compung Relevance, Smlary: The Vecor Space Model Based on Larson and Hears s sldes a UC-Bereley hp://.sms.bereley.edu/courses/s0/f00/ aabase Managemen Sysems, R. Ramarshnan ocumen Vecors v ocumens are

More information

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. Ths documen s downloaded from DR-NTU, Nanyang Technologcal Unversy Lbrary, Sngapore. Tle A smplfed verb machng algorhm for word paron n vsual speech processng( Acceped verson ) Auhor(s) Foo, Say We; Yong,

More information

Implementation of Quantized State Systems in MATLAB/Simulink

Implementation of Quantized State Systems in MATLAB/Simulink SNE T ECHNICAL N OTE Implemenaon of Quanzed Sae Sysems n MATLAB/Smulnk Parck Grabher, Mahas Rößler 2*, Bernhard Henzl 3 Ins. of Analyss and Scenfc Compung, Venna Unversy of Technology, Wedner Haupsraße

More information

Optimal Buyer-Seller Inventory Models in Supply Chain

Optimal Buyer-Seller Inventory Models in Supply Chain Inernaonal Conference on Educaon echnology and Informaon Sysem (ICEIS 03 Opmal Buyer-Seller Invenory Models n Supply Chan Gaobo L Shandong Women s Unversy, Jnan, 50300,Chna emal: lgaobo_979@63.com Keywords:

More information

Motion in Two Dimensions

Motion 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 information

Supporting Information: The integrated Global Temperature change Potential (igtp) and relationships between emission metrics

Supporting Information: The integrated Global Temperature change Potential (igtp) and relationships between emission metrics 2 3 4 5 6 7 8 9 Supporng Informaon: Te negraed Global Temperaure cange Poenal (GTP) and relaonsps beween emsson mercs Glen P. Peers *, Borgar Aamaas, Tere Bernsen,2, Jan S. Fuglesved Cener for Inernaonal

More information

The Impact of Time Delays on Network Synchronization and Coordination in a Noisy Environment

The Impact of Time Delays on Network Synchronization and Coordination in a Noisy Environment Te Impac of Tme Delays on ewor Syncronzaon and Coordnaon n a osy Envronmen G. Kornss Davd Hun B.K. Szymans Suppored by DTRA, ARL S CTA, SF Delay Dfferenal Equaons Macrodynamc eory of busness cycles Kalec,

More information

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

More information

Li An-Ping. Beijing , P.R.China

Li An-Ping. Beijing , P.R.China A New Type of Cpher: DICING_csb L An-Png Bejng 100085, P.R.Chna apl0001@sna.com Absrac: In hs paper, we wll propose a new ype of cpher named DICING_csb, whch s derved from our prevous sream cpher DICING.

More information

Motivations. Opinions, influence networks and centrality. Small deliberative groups. Opinion Dynamics and the Evolution of Influence Networks

Motivations. Opinions, influence networks and centrality. Small deliberative groups. Opinion Dynamics and the Evolution of Influence Networks Movaons Opnon Dynamcs and he Evoluon of drvers Francesco Bullo Deparmen of Mechancal Engneerng Cener for Conrol, Dynamcal Sysems & Compuaon Unversy of Calforna a Sana Barbara bg daa ncreasngle avalable

More information

Multi-priority Online Scheduling with Cancellations

Multi-priority Online Scheduling with Cancellations Submed o Operaons Research manuscrp (Please, provde he manuscrp number!) Auhors are encouraged o subm new papers o INFORMS journals by means of a syle fle emplae, whch ncludes he journal le. However, use

More information

VEHICLE DYNAMIC MODELING & SIMULATION: COMPARING A FINITE- ELEMENT SOLUTION TO A MULTI-BODY DYNAMIC SOLUTION

VEHICLE DYNAMIC MODELING & SIMULATION: COMPARING A FINITE- ELEMENT SOLUTION TO A MULTI-BODY DYNAMIC SOLUTION 21 NDIA GROUND VEHICLE SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM MODELING & SIMULATION, TESTING AND VALIDATION (MSTV) MINI-SYMPOSIUM AUGUST 17-19 DEARBORN, MICHIGAN VEHICLE DYNAMIC MODELING & SIMULATION:

More information

Solving the multi-period fixed cost transportation problem using LINGO solver

Solving the multi-period fixed cost transportation problem using LINGO solver Inernaonal Journal of Pure and Appled Mahemacs Volume 119 No. 12 2018, 2151-2157 ISSN: 1314-3395 (on-lne verson) url: hp://www.pam.eu Specal Issue pam.eu Solvng he mul-perod fxed cos ransporaon problem

More information

Lecture 2 M/G/1 queues. M/G/1-queue

Lecture 2 M/G/1 queues. M/G/1-queue Lecure M/G/ queues M/G/-queue Posson arrval process Arbrary servce me dsrbuon Sngle server To deermne he sae of he sysem a me, we mus now The number of cusomers n he sysems N() Tme ha he cusomer currenly

More information

Mechanics Physics 151

Mechanics 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 information

Deepanshu Vasal. Abstract. We consider a general finite-horizon non zero-sum dynamic game with asymmetric information with N selfish

Deepanshu Vasal. Abstract. We consider a general finite-horizon non zero-sum dynamic game with asymmetric information with N selfish Sequenal decomposon of dynamc games wh 1 asymmerc nformaon and dependen saes Deepanshu Vasal Absrac We consder a general fne-horzon non zero-sum dynamc game wh asymmerc nformaon wh N selfsh players, where

More information

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b Inernaonal Indusral Informacs and Compuer Engneerng Conference (IIICEC 05) Arbue educon Algorhm Based on Dscernbly Marx wh Algebrac Mehod GAO Jng,a, Ma Hu, Han Zhdong,b Informaon School, Capal Unversy

More information

Mechanics Physics 151

Mechanics 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 information

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times Reacve Mehods o Solve he Berh AllocaonProblem wh Sochasc Arrval and Handlng Tmes Nsh Umang* Mchel Berlare* * TRANSP-OR, Ecole Polyechnque Fédérale de Lausanne Frs Workshop on Large Scale Opmzaon November

More information

Multi-Fuel and Mixed-Mode IC Engine Combustion Simulation with a Detailed Chemistry Based Progress Variable Library Approach

Multi-Fuel and Mixed-Mode IC Engine Combustion Simulation with a Detailed Chemistry Based Progress Variable Library Approach Mul-Fuel and Med-Mode IC Engne Combuson Smulaon wh a Dealed Chemsry Based Progress Varable Lbrary Approach Conens Inroducon Approach Resuls Conclusons 2 Inroducon New Combuson Model- PVM-MF New Legslaons

More information

PHYS 705: Classical Mechanics. Canonical Transformation

PHYS 705: Classical Mechanics. Canonical Transformation PHYS 705: Classcal Mechancs Canoncal Transformaon Canoncal Varables and Hamlonan Formalsm As we have seen, n he Hamlonan Formulaon of Mechancs,, are ndeenden varables n hase sace on eual foong The Hamlon

More information

A capacitor consists of two conducting plates, separated by an insulator. Conduction plates: e.g., Aluminum foil Insulator: air, mica, ceramic, etc

A capacitor consists of two conducting plates, separated by an insulator. Conduction plates: e.g., Aluminum foil Insulator: air, mica, ceramic, etc 3//7 haper 6 apacors and Inducors Makng preparaon for dynamc crcus, whch hae far more applcaons han he sac crcus we hae learned so far. 6. apacors Sore energy n elecrc feld nsulaor onducng plaes A capacor

More information

RELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA

RELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA RELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA Mchaela Chocholaá Unversy of Economcs Braslava, Slovaka Inroducon (1) one of he characersc feaures of sock reurns

More information

Motion of Wavepackets in Non-Hermitian. Quantum Mechanics

Motion 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 information

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data Anne Chao Ncholas J Goell C seh lzabeh L ander K Ma Rober K Colwell and Aaron M llson 03 Rarefacon and erapolaon wh ll numbers: a framewor for samplng and esmaon n speces dversy sudes cology Monographs

More information

A HIERARCHICAL KALMAN FILTER

A HIERARCHICAL KALMAN FILTER A HIERARCHICAL KALMAN FILER Greg aylor aylor Fry Consulng Acuares Level 8, 3 Clarence Sree Sydney NSW Ausrala Professoral Assocae, Cenre for Acuaral Sudes Faculy of Economcs and Commerce Unversy of Melbourne

More information

Scattering at an Interface: Oblique Incidence

Scattering 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 information

Way nding under Uncertainty in Continuous Time and Space by Dynamic Programming

Way nding under Uncertainty in Continuous Time and Space by Dynamic Programming Way ndng under Uncerany n Connuous Tme and Space by Dynamc Programmng Dr. Serge P. Hoogendoorn (s.hoogendoorn@c.udelf.nl) Transporaon and Tra c Engneerng Secon Faculy of Cvl Engneerng and Geoscences -

More information

Tolerance Band Controller for a Three-Level Four-Quadrant Converter Including DC Link Balancing

Tolerance Band Controller for a Three-Level Four-Quadrant Converter Including DC Link Balancing 4 35h Annual I Power lecroncs Specalss Conference Aachen, Germany, 4 Tolerance Band Conroller for a ThreeLevel FourQuadran Converer Includng DC Lnk Balancng Joachm Böcker Insue of Power lecroncs and lecrcal

More information

The Dynamic Programming Models for Inventory Control System with Time-varying Demand

The Dynamic Programming Models for Inventory Control System with Time-varying Demand The Dynamc Programmng Models for Invenory Conrol Sysem wh Tme-varyng Demand Truong Hong Trnh (Correspondng auhor) The Unversy of Danang, Unversy of Economcs, Venam Tel: 84-236-352-5459 E-mal: rnh.h@due.edu.vn

More information

Model of Educational Counseling System in Initial and Continuous Training

Model of Educational Counseling System in Initial and Continuous Training Model of Educaonal Counselng Sysem n Inal and Connuous Tranng MIHAELA ŢĂRAU, GEORGE LĂZĂROIU, VIOLETA-ELEA SIMIO, MIHAI COVACI Spru Hare Unversy, ROMÂIA adelaaranu@gmal.com, phd_lazarou@yahoo.com, ushmv_smon.volea@spruhare.ro

More information

Advanced Machine Learning & Perception

Advanced Machine Learning & Perception Advanced Machne Learnng & Percepon Insrucor: Tony Jebara SVM Feaure & Kernel Selecon SVM Eensons Feaure Selecon (Flerng and Wrappng) SVM Feaure Selecon SVM Kernel Selecon SVM Eensons Classfcaon Feaure/Kernel

More information

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae

More information

e-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov

e-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov June 7 e-ournal Relably: Theory& Applcaons No (Vol. CONFIDENCE INTERVALS ASSOCIATED WITH PERFORMANCE ANALYSIS OF SYMMETRIC LARGE CLOSED CLIENT/SERVER COMPUTER NETWORKS Absrac Vyacheslav Abramov School

More information

Chapter 6 DETECTION AND ESTIMATION: Model of digital communication system. Fundamental issues in digital communications are

Chapter 6 DETECTION AND ESTIMATION: Model of digital communication system. Fundamental issues in digital communications are Chaper 6 DEECIO AD EIMAIO: Fundamenal ssues n dgal communcaons are. Deecon and. Esmaon Deecon heory: I deals wh he desgn and evaluaon of decson makng processor ha observes he receved sgnal and guesses

More information

Playing against Hedge

Playing against Hedge In J Communcaons, ework and Sysem Scences, 4, 7, 497-57 Publshed Onlne December 4 n ScRes hp://wwwscrporg/journal/jcns hp://dxdoorg/436/jcns475 Playng agans Hedge Mlades E Anagnosou, Mara A ambrou School

More information

Symbolic Equation of Motion and Linear Algebra Models for High- Speed Ground Vehicle Simulations.

Symbolic Equation of Motion and Linear Algebra Models for High- Speed Ground Vehicle Simulations. Symbolc Equaon of Moon and Lnear Algebra Models for Hgh- Speed Ground Vehcle Smulaons. y: James. D. Turner, Ph.D., ADS and Smulaon Cener, 2401 Oakdale lvd., Iowa Cy, Iowa, 52242. Absrac. Synhec envronmen

More information

Fall 2010 Graduate Course on Dynamic Learning

Fall 2010 Graduate Course on Dynamic Learning Fall 200 Graduae Course on Dynamc Learnng Chaper 4: Parcle Flers Sepember 27, 200 Byoung-Tak Zhang School of Compuer Scence and Engneerng & Cognve Scence and Bran Scence Programs Seoul aonal Unversy hp://b.snu.ac.kr/~bzhang/

More information

Chapter 2 Linear dynamic analysis of a structural system

Chapter 2 Linear dynamic analysis of a structural system Chaper Lnear dynamc analyss of a srucural sysem. Dynamc equlbrum he dynamc equlbrum analyss of a srucure s he mos general case ha can be suded as akes no accoun all he forces acng on. When he exernal loads

More information

WiH Wei He

WiH Wei He Sysem Idenfcaon of onlnear Sae-Space Space Baery odels WH We He wehe@calce.umd.edu Advsor: Dr. Chaochao Chen Deparmen of echancal Engneerng Unversy of aryland, College Par 1 Unversy of aryland Bacground

More information

Meta-Heuristic Optimization techniques in power systems

Meta-Heuristic Optimization techniques in power systems Proceedngs of he 2nd IASME / WSEAS Inernaonal Conference on Energy & Envronmen (EE07), Pororoz, Slovena, May 15-17, 2007 163 Mea-Heursc Opmzaon echnques n power sysems Vlachos Arsds Deparmen of Informacs

More information

Lecture 6: Learning for Control (Generalised Linear Regression)

Lecture 6: Learning for Control (Generalised Linear Regression) Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson

More information

WITH the proliferation of smart wireless devices and mobile

WITH the proliferation of smart wireless devices and mobile Ths arcle has been acceped for publcaon n a fuure ssue of hs journal, bu has no been fully eded Conen may change pror o fnal publcaon Caon nformaon: DOI 1119/TMC18847337, I Transacons on Moble Compung

More information

Detection of Waving Hands from Images Using Time Series of Intensity Values

Detection of Waving Hands from Images Using Time Series of Intensity Values Deecon of Wavng Hands from Images Usng Tme eres of Inensy Values Koa IRIE, Kazunor UMEDA Chuo Unversy, Tokyo, Japan re@sensor.mech.chuo-u.ac.jp, umeda@mech.chuo-u.ac.jp Absrac Ths paper proposes a mehod

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

On computing differential transform of nonlinear non-autonomous functions and its applications

On computing differential transform of nonlinear non-autonomous functions and its applications On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy,

More information

OP = OO' + Ut + Vn + Wb. Material We Will Cover Today. Computer Vision Lecture 3. Multi-view Geometry I. Amnon Shashua

OP = OO' + Ut + Vn + Wb. Material We Will Cover Today. Computer Vision Lecture 3. Multi-view Geometry I. Amnon Shashua Comuer Vson 27 Lecure 3 Mul-vew Geomer I Amnon Shashua Maeral We Wll Cover oa he srucure of 3D->2D rojecon mar omograh Marces A rmer on rojecve geomer of he lane Eolar Geomer an Funamenal Mar ebrew Unvers

More information

Chapters 2 Kinematics. Position, Distance, Displacement

Chapters 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 information

CHAPTER 5: MULTIVARIATE METHODS

CHAPTER 5: MULTIVARIATE METHODS CHAPER 5: MULIVARIAE MEHODS Mulvarae Daa 3 Mulple measuremens (sensors) npus/feaures/arbues: -varae N nsances/observaons/eamples Each row s an eample Each column represens a feaure X a b correspons o he

More information

Single-Allocation Hub Network Design Model with Consolidated Traffic Flows

Single-Allocation Hub Network Design Model with Consolidated Traffic Flows See dscussons, sas, and auhor profles for hs publcaon a: hps://www.researchgae.ne/publcaon/235733752 Sngle-Allocaon Hub Nework Desgn Model wh Consoldaed Traffc Flows ARTICLE n TRANSPORTATION RESEARCH RECORD

More information

Shannon revisited: New separation principles for wireless multimedia

Shannon revisited: New separation principles for wireless multimedia Shannon revsed: New separaon prncples for wreless mulmeda Prof. Mhaela van der Schaar Mulmeda Communcaons and Sysems Lab Elecrcal Engneerng Deparmen, UCLA hp://medanelab.ee.ucla.edu/ UCLA Mulmeda communcaons

More information