On the Boyd- Kuramoto Model : Emergence in a Mathematical Model for Adversarial C2 Systems
|
|
- Harriet Lewis
- 5 years ago
- Views:
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
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 informationDynamic 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 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 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 informationMulti-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 informationBayes 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 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 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 informationResearch 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 informationDensity 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 informationLinear 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 informationBorn 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 informationLecture 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 informationCS286.2 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 informationExistence 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 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 informationDual 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 information2.1 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 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 informationOn 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 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 informationOnline 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 informationLet 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 informationV.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 informationIn 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 informationForecasting 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 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 informationOptimal 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 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 informationExact 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 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 informationNormal 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 informationWe 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 informationThe 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 informationReal-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 informationHow 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 informationRobustness 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 informationDepartment 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 informationPerformance 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 informationSingle-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 informationModeling 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
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 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 informationSolving 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 informationTSS = 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 informationRobust 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 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 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 informationClustering (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 informationComputing 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 informationThis 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 informationImplementation 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 informationOptimal 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 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 informationSupporting 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 informationThe 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 information2/20/2013. 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 informationLi 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 informationMotivations. 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 informationMulti-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 informationVEHICLE 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 informationSolving 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 informationLecture 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 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 informationDeepanshu 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 informationAttribute 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 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 informationReactive 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 informationMulti-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 informationPHYS 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 informationA 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 informationRELATIONSHIP 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 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 informationAppendix 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 informationA 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 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 informationWay 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 informationTolerance 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 informationThe 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 informationModel 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 informationAdvanced 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 informationApproximate 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 informatione-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 informationChapter 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 informationPlaying 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 informationSymbolic 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 informationFall 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 informationChapter 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 informationWiH 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 informationMeta-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 informationLecture 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 informationWITH 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 informationDetection 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 informationUNIVERSITAT 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 informationOn 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 informationOP = 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 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 informationCHAPTER 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 informationSingle-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 informationShannon 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