J-DSP-CONTROL: A CONTROL SYSTEMS SIMULATION ENVIRONMENT +

Size: px
Start display at page:

Download "J-DSP-CONTROL: A CONTROL SYSTEMS SIMULATION ENVIRONMENT +"

Transcription

1 J-DSP-CONTROL: A CONTROL SYSTEMS SIMULATION ENVIRONMENT + T. Thrasyvoulou, K. Tsakals and A. Spanas MIDL Department of Electrcal Engneerng Arzona State Unversty, Tempe, AZ thrassos@asu.edu, tsakals@asu.edu, spanas@asu.edu ABSTRACT J-DSP-C s a java-based object-orented programmng envronment that was developed at Arzona State Unversty for use n control systems educaton. Ths envronment enables the smulaton of dynamcal systems on-lne from any computer system equpped wth an Internet browser. The J-DSP-C features are prmarly amed to provde an on-lne laboratory experence to dstance learnng students. Combned wth a report submsson and scorng faclty, J-DSP-C ntegrates nteractve examples nto web content for educaton and demonstraton purposes. KEYWORDS Smulaton, Educaton, Control Systems. control systems extenson J-DSP-C wll soon be tested for use n undergraduate control classes. Smlar to ts precursor, J-DSP-C s an objectorented smulaton envronment that enables students to establsh and execute control systems smulatons from any computer equpped wth an Internet browser. All functons n J-DSP-C appear as graphcal blocks that are accessed through pull-down menus and are grouped accordng to ther functonalty. The J-DSP-C edtor allows the user to graphcally setup and smulate systems wth arbtrary nterconnecton topology. An example of the J-DSP-C graphcal user nterface (GUI) s llustrated n Fgure 1. The followng sectons provde an overvew of the J-DSP prototype, the J-DSP-C enhancements and lmtatons, ts current functonalty, and examples of use. 1. INTRODUCTION Ths paper presents a prototype laboratory software tool, called Java-Dgtal Sgnal Processng - Control (J-DSP-C). J-DSP-C can be used to smulate control systems on-lne, takng advantage of recent developments n Internet technology. The man motvaton behnd ts development stems from the recent ncrease of the percentage of dstance-learnng students at Arzona State Unversty (ASU) and other major metropoltan unverstes. Dstance learnng s a trend n today s educaton, and J-DSP-C flls a gap by provdng a smple yet powerful tool for on-lne control systems smulatons. The software s freely dstrbuted and s desgned to enhance dstance-learnng and contnung educaton wth an on-lne laboratory experence. Its precursor s J-DSP that was developed n the ASU Multdscplnary Intatve on Dstance Learnng (MIDL) laboratory. J-DSP was successfully tested n ASU s undergraduate dgtal sgnal processng class. Based on ths experence, further enhancements of ths tool are currently under development n MIDL, for use n controls, communcatons, and mage processng educaton. The Buttons to select blocks Blocks Fgure 1: J-DSP-C user nterface Work space Detals on J-DSP and J-DSP-C are gven n [1] and n the on-lne documentaton at [3]. Fundng for the development of J-DSP and J-DSP-C was provded by the NSF CCLI program and ncludes + Supported n part by NSF CCLI grant DUE J-DSP concept by A. Spanas. For more nformaton on J-DSP and ts dssemnaton please contact spanas@asu.edu..

2 software development and dssemnaton along wth a seres of on-lne laboratory exercses. 2. J-DSP OVERVIEW The J-DSP edtor s the bass on whch J-DSP-C was developed. J-DSP was orgnally developed as a platform to smulate the typcal systems and operatons encountered n dgtal sgnal processng. Its underlyng phlosophy was dctated by ts sutablty for operaton over the Internet. Usng object-orented programmng prncples, J-DSP proved to be a successful tool to address the typcal computatonal and vsualzaton needs of DSP courses. The exstng functonalty ncludes basc flter desgn, fast Fourer transforms (FFT), upsamplng, downsamplng, sgnal generaton and plottng. More advanced functons nclude autocorrelaton, varous types of perodograms and correlograms and AR tme-seres. (See [1,3] for detals.) To address the needs of other DSP-related problems, the J-DSP edtor s currently beng expanded to offer new specalzed functonalty. Several new functons are beng developed wthn ths framework to support experments on speech analyss-synthess, tme frequency representatons, mage processng, and communcatons systems [2]. On the other hand, enablng the support of experments n feedback systems requred more substantal modfcatons. A key characterstc of J-DSP was ts sequental processng of nformaton. Once a block s ntroduced n the edtor, ts output s mmedately computed based on the nput t receves. Although ths s an attractve feature, especally for educatonal examples, t cannot accommodate general nterconnecton topologes, such as feedback systems. Addressng ths ssue, J-DSP-C represents a sgnfcant enhancement of the basc J-DSP engne, whle t preserves the same fundamental object-orented structure and most of the already developed nfrastructure. 3. THE J-DSP-C ENVIRONMENT The handlng of feedback and, n general, arbtrary nterconnectons of blocks requred some major changes n the J-DSP edtor nfrastructure. Our objectve durng ths development was to preserve the orgnal structure as much as possble together wth ts underlyng concept. That s, the J-DSP-C development adheres to the same smplcty, compactness, and object-orented phlosophy of ts precursor. Ths resulted n some compromses n terms of generalty and computatonal effcency. However, n ts prmary msson as an educatonal tool, the J-DSP-C lmtatons are not too severe and can usually be crcumvented by a careful plannng of the smulaton experments. The modfcatons of the basc edtor can be dvded nto two categores. One s the enhancement of the GUI nterface, together wth the assocated changes n the object classes. The other s the modfcaton of the executon procedure to enable the smulaton of feedback loops. In the orgnal J-DSP, blocks were rectangular and had two ports, the left one desgnated as an nput port and the rght one as output. Two addtonal ports top/bottom were avalable for exchange of parameters. Ths confguraton was adequate to represent the usual DSP operatons but too nflexble for feedback systems. In order to acheve consstency wth the standard notaton and appearance of feedback control systems, the J-DSP-C GUI and the edtor can now handle blocks wth multple nput/output ports that are not lmted to rectangular shapes. For example, a summaton node can now appear as a crcle wth several nput ports, whle a gan block s shown as a trangle. The new envronment also allows blocks to be rotated and flpped and the connectons to be edted or modfed. Ths capablty s qute essental n mantanng a clean vsual appearance of more complcated system nterconnectons. The dfferences between the GUI capabltes of the J-DSP and J-DSP-C edtors are llustrated n Fgures 2 and 3. Fgure 2: J-DSP user nterface Fgure 3: J-DSP-C user nterface

3 A more extensve modfcaton of the orgnal J- DSP engne was necessary to enable the smulaton of feedback systems. The class of control blocks was expanded to nclude state-space descrptons of dynamcal systems. All blocks now have a state attrbute (trval for memoryless blocks) to enable the recursve computaton of the system response. For smplcty, dscrete-tme approxmatons are used nternally to compute the response of contnuous-tme systems. Ths converson s transparent to the user, but care should be exercsed n the selecton of the samplng tme so that the dscretzaton s reasonably accurate. (A warnng s ssued when the samplng tme seems too large.) In ths settng, the computaton of the response of the system nterconnecton s computed recursvely n tme and teratvely wth respect to the varous blocks. The recursve porton of the soluton s made possble by usng state-space descrptons. At each tme nstant, the soluton can be advanced by one tme step and only the state vector needs to be stored n memory. The teratve porton of the soluton s requred to ensure that the correct nputs are computed for all blocks. That s, at each tme nstant, the nput/output computatons are terated untl they converge, before updatng the states. Ths smplfed approach s compatble wth the objectorented defnton of the varous blocks. However, a subtle pont and a key lmtaton s that convergence s not necessarly guaranteed for any system nterconnecton. It can be shown that: When a feedback loop has no algebrac part (at least one of the systems has no drect throughput) then the teraton convergence n fnte steps, proportonal to the number of blocks n the loop. When a feedback loop has an algebrac part then the teraton converges exponentally as (1-ρ) k, where ρ s the loop drect throughput, provded that ρ < 1. Otherwse, the teraton dverges. In practce, ths lmtaton s not very restrctve but t should be obeyed when defnng the feedback nterconnectons. (Agan, a warnng s ssued when the local teraton fals to converge n a prescrbed number of steps.) Fnally, to avod repeated unnecessary computatons whle edtng the system nterconnectons, a smulaton button has been ntroduced to dsable J-DSP s automatc block executon. Instead the smulaton computatons are performed on-demand by pressng ths button. 4. J-DSP-C FUNCTIONALITY A fundamental set of functons has been developed n order to accommodate the need for control systems smulatons. The currently avalable blocks are brefly descrbed below, grouped n terms of ther fundamental propertes Sgnal generators Sgnal generators are an essental part of every smulaton. The J-DSP edtor has been ftted wth two sgnal generators, provdng a varety of sgnals. The frst sgnal generator supples a smple step sgnal that s encountered most frequently n control systems smulatons. It s smple to use and wthn easy reach. The second sgnal generator has been desgned to offer a more elaborate selecton of sgnals. Among others, ths block provdes dscrete mpulses, snusods, snc functons, random sgnals wth ether unform, Gaussan, or Raylegh dstrbutons and exponental sgnals. Where applcable, sgnals can be chosen to repeat perodcally Memoryless Systems and Arthmetc operatons These nclude summaton nodes, gans and varous other blocks performng arthmetc operatons. For example, the user can multply two sgnals, compute ther exponental or ther natural logarthm Dynamcal Systems Currently ths class contans lnear dynamcal systems that can be specfed n terms of ther transfer functon or ther state-space descrpton. The transfer functon block s used to enter a ratonal transfer functon descrbng a system. More precsely, ths block smulates a system gven a transfer functon n the form H ( s) = n = 0 n = 0 b s a s The numerator and denomnator coeffcents b and a are entered n the block s dalog box, shown n Fgure 4. An alternatve and more general way to specfy a lnear system s wth ts state-space descrpton. Ths block mplements the equaton x& = Ax + Bu y = Cx+ Du where, A R, B R, C R, D R nxn nxm pxn pxm, and x R n, u R m, y R p. x s the state vector, u s the system nput and y s the system s output response. Currently, the maxmum number of states s lmted to 10. The dalog wndow for ths block s shown n Fgure 5, along wth a wndow for enterng a matrx. Notce that the user can select to enter matrces n canoncal or other

4 common forms, where many of the entres have fxed values that are automatcally ntalzed Blocks Under Development Future enhancements of the J-DSP-C edtor wll nclude addtonal components to facltate the modelng and smulaton of nonlnear systems (e.g., nverted pendulum and other mechancal systems). Addtonal blocks wll perform matrx manpulatons and leastsquares approxmaton, enablng the mplementaton of adaptve systems. Other enhancements nclude the support of systems wth multple nputs and outputs, and the ablty to group several blocks nto a composte one. Notce that the ablty to change the block shape and number of nput/output ports has been ntroduced wth ths goal n mnd. Fgure 4: Ratonal transfer functon dalog wndow Fgure 6: Bode plot 5. EXAMPLES In ths secton, two llustratve examples of J- DSP-C smulatons are presented. The frst example smulates a smple unty feedback system wth Fgure 5: State Space system s dalog wndow 4.4. Plottng and Vsualzaton Blocks The results of a smulaton can be examned usng the graphcal output capabltes of the Plot block. Ths block smply plots ts nput n a lnear or logarthmc scale. It has zoomng capabltes and can provde statstcal propertes of the dsplayed sgnal. In the same famly, the Bode and Nyqust plot blocks can be used to vsualze system propertes and ad the desgn of control systems. The Bode plot dsplays the magntude and phase of the system transfer functon (see Fgure 6), whle the Nyqust block plots real versus magnary parts. H() 2 s + 4s s s s The block dagram and the plot of the smulaton result for a step reference nput are shown n Fgure 7. In the second example, the feedback system contans two transfer functons, one n the forward path and the other n the feedback path. Here, s + 2 H1() s + 3s + 13s +2 2 s + 4s+ 5 H2() s + 6s + 3s + 10 For ths case, the block dagram and the plot of the smulaton result for a step reference nput are shown n Fgure 8.

5 feedback system s defned through a GUI edtor by connectng blocks together, mantanng a classcal textbook appearance. Although t lacks the power, effcency, and generalty of manstream commercal software lke MATLAB/Smulnk, J-DSP-C s easy to use and can provde a platform wth suffcent flexblty to smulate the typcal exercses found n control systems educaton. Its prmary use s envsoned as a dstance learnng tool because of ts ablty to run over the Internet through a smple web browser. Furthermore, wth ts open archtecture, J-DSP-C s contnuously mproved wth respect to the collecton of blocks avalable for use n smulatons. Combned wth a report submsson and scorng faclty, J-DSP-C ntegrates nteractve examples nto web content to mprove the qualty and effectveness of control systems educaton. Fgure 7: Block dagram and smulaton results for example REFERENCES [1] A. Spanas et al, Development and Evaluaton of a Web- Based Sgnal and Speech Processng Laboratory for Dstance Learnng, Proc. IEEE ICASSP-2000, Istanbul, Vol. 6, pp , June [2] A. Spanas et al, On-lne laboratores for speech and mage processng and for communcaton systems usng J-DSP, to appear at 2 nd DSP-Educaton workshop, Pne Mountan GA, Oct 13-16, [3] J-DSP on-lne help, Fgure 8: Block dagram and smulaton results for example CONCLUSIONS Ths paper presented the varous enhancements and modfcatons of the J-DSP software tool for use n control systems educaton. Ths new verson, J-DSP-C, s an object-orented programmng envronment, that enables the smulaton of feedback systems n a straghtforward and easy to comprehend manner. The

A Binarization Algorithm specialized on Document Images and Photos

A Binarization Algorithm specialized on Document Images and Photos A Bnarzaton Algorthm specalzed on Document mages and Photos Ergna Kavalleratou Dept. of nformaton and Communcaton Systems Engneerng Unversty of the Aegean kavalleratou@aegean.gr Abstract n ths paper, a

More information

Assignment # 2. Farrukh Jabeen Algorithms 510 Assignment #2 Due Date: June 15, 2009.

Assignment # 2. Farrukh Jabeen Algorithms 510 Assignment #2 Due Date: June 15, 2009. Farrukh Jabeen Algorthms 51 Assgnment #2 Due Date: June 15, 29. Assgnment # 2 Chapter 3 Dscrete Fourer Transforms Implement the FFT for the DFT. Descrbed n sectons 3.1 and 3.2. Delverables: 1. Concse descrpton

More information

Lecture 5: Multilayer Perceptrons

Lecture 5: Multilayer Perceptrons Lecture 5: Multlayer Perceptrons Roger Grosse 1 Introducton So far, we ve only talked about lnear models: lnear regresson and lnear bnary classfers. We noted that there are functons that can t be represented

More information

Review of approximation techniques

Review of approximation techniques CHAPTER 2 Revew of appromaton technques 2. Introducton Optmzaton problems n engneerng desgn are characterzed by the followng assocated features: the objectve functon and constrants are mplct functons evaluated

More information

Simulation Based Analysis of FAST TCP using OMNET++

Simulation Based Analysis of FAST TCP using OMNET++ Smulaton Based Analyss of FAST TCP usng OMNET++ Umar ul Hassan 04030038@lums.edu.pk Md Term Report CS678 Topcs n Internet Research Sprng, 2006 Introducton Internet traffc s doublng roughly every 3 months

More information

Mathematics 256 a course in differential equations for engineering students

Mathematics 256 a course in differential equations for engineering students Mathematcs 56 a course n dfferental equatons for engneerng students Chapter 5. More effcent methods of numercal soluton Euler s method s qute neffcent. Because the error s essentally proportonal to the

More information

Image Representation & Visualization Basic Imaging Algorithms Shape Representation and Analysis. outline

Image Representation & Visualization Basic Imaging Algorithms Shape Representation and Analysis. outline mage Vsualzaton mage Vsualzaton mage Representaton & Vsualzaton Basc magng Algorthms Shape Representaton and Analyss outlne mage Representaton & Vsualzaton Basc magng Algorthms Shape Representaton and

More information

AADL : about scheduling analysis

AADL : about scheduling analysis AADL : about schedulng analyss Schedulng analyss, what s t? Embedded real-tme crtcal systems have temporal constrants to meet (e.g. deadlne). Many systems are bult wth operatng systems provdng multtaskng

More information

Learning the Kernel Parameters in Kernel Minimum Distance Classifier

Learning the Kernel Parameters in Kernel Minimum Distance Classifier Learnng the Kernel Parameters n Kernel Mnmum Dstance Classfer Daoqang Zhang 1,, Songcan Chen and Zh-Hua Zhou 1* 1 Natonal Laboratory for Novel Software Technology Nanjng Unversty, Nanjng 193, Chna Department

More information

Cluster Analysis of Electrical Behavior

Cluster Analysis of Electrical Behavior Journal of Computer and Communcatons, 205, 3, 88-93 Publshed Onlne May 205 n ScRes. http://www.scrp.org/ournal/cc http://dx.do.org/0.4236/cc.205.350 Cluster Analyss of Electrcal Behavor Ln Lu Ln Lu, School

More information

TN348: Openlab Module - Colocalization

TN348: Openlab Module - Colocalization TN348: Openlab Module - Colocalzaton Topc The Colocalzaton module provdes the faclty to vsualze and quantfy colocalzaton between pars of mages. The Colocalzaton wndow contans a prevew of the two mages

More information

Helsinki University Of Technology, Systems Analysis Laboratory Mat Independent research projects in applied mathematics (3 cr)

Helsinki University Of Technology, Systems Analysis Laboratory Mat Independent research projects in applied mathematics (3 cr) Helsnk Unversty Of Technology, Systems Analyss Laboratory Mat-2.08 Independent research projects n appled mathematcs (3 cr) "! #$&% Antt Laukkanen 506 R ajlaukka@cc.hut.f 2 Introducton...3 2 Multattrbute

More information

Module Management Tool in Software Development Organizations

Module Management Tool in Software Development Organizations Journal of Computer Scence (5): 8-, 7 ISSN 59-66 7 Scence Publcatons Management Tool n Software Development Organzatons Ahmad A. Al-Rababah and Mohammad A. Al-Rababah Faculty of IT, Al-Ahlyyah Amman Unversty,

More information

A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS

A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Proceedngs of the Wnter Smulaton Conference M E Kuhl, N M Steger, F B Armstrong, and J A Jones, eds A MOVING MESH APPROACH FOR SIMULATION BUDGET ALLOCATION ON CONTINUOUS DOMAINS Mark W Brantley Chun-Hung

More information

An Entropy-Based Approach to Integrated Information Needs Assessment

An Entropy-Based Approach to Integrated Information Needs Assessment Dstrbuton Statement A: Approved for publc release; dstrbuton s unlmted. An Entropy-Based Approach to ntegrated nformaton Needs Assessment June 8, 2004 Wllam J. Farrell Lockheed Martn Advanced Technology

More information

Wavefront Reconstructor

Wavefront Reconstructor A Dstrbuted Smplex B-Splne Based Wavefront Reconstructor Coen de Vsser and Mchel Verhaegen 14-12-201212 2012 Delft Unversty of Technology Contents Introducton Wavefront reconstructon usng Smplex B-Splnes

More information

Problem Definitions and Evaluation Criteria for Computational Expensive Optimization

Problem Definitions and Evaluation Criteria for Computational Expensive Optimization Problem efntons and Evaluaton Crtera for Computatonal Expensve Optmzaton B. Lu 1, Q. Chen and Q. Zhang 3, J. J. Lang 4, P. N. Suganthan, B. Y. Qu 6 1 epartment of Computng, Glyndwr Unversty, UK Faclty

More information

AC : TEACHING SPREADSHEET-BASED NUMERICAL ANAL- YSIS WITH VISUAL BASIC FOR APPLICATIONS AND VIRTUAL IN- STRUMENTS

AC : TEACHING SPREADSHEET-BASED NUMERICAL ANAL- YSIS WITH VISUAL BASIC FOR APPLICATIONS AND VIRTUAL IN- STRUMENTS AC 2011-1615: TEACHING SPREADSHEET-BASED NUMERICAL ANAL- YSIS WITH VISUAL BASIC FOR APPLICATIONS AND VIRTUAL IN- STRUMENTS Nkunja Swan, South Carolna State Unversty Dr. Swan s currently a Professor at

More information

A Fast Visual Tracking Algorithm Based on Circle Pixels Matching

A Fast Visual Tracking Algorithm Based on Circle Pixels Matching A Fast Vsual Trackng Algorthm Based on Crcle Pxels Matchng Zhqang Hou hou_zhq@sohu.com Chongzhao Han czhan@mal.xjtu.edu.cn Ln Zheng Abstract: A fast vsual trackng algorthm based on crcle pxels matchng

More information

Wishing you all a Total Quality New Year!

Wishing you all a Total Quality New Year! Total Qualty Management and Sx Sgma Post Graduate Program 214-15 Sesson 4 Vnay Kumar Kalakband Assstant Professor Operatons & Systems Area 1 Wshng you all a Total Qualty New Year! Hope you acheve Sx sgma

More information

Load Balancing for Hex-Cell Interconnection Network

Load Balancing for Hex-Cell Interconnection Network Int. J. Communcatons, Network and System Scences,,, - Publshed Onlne Aprl n ScRes. http://www.scrp.org/journal/jcns http://dx.do.org/./jcns.. Load Balancng for Hex-Cell Interconnecton Network Saher Manaseer,

More information

Support Vector Machines

Support Vector Machines /9/207 MIST.6060 Busness Intellgence and Data Mnng What are Support Vector Machnes? Support Vector Machnes Support Vector Machnes (SVMs) are supervsed learnng technques that analyze data and recognze patterns.

More information

An Iterative Solution Approach to Process Plant Layout using Mixed Integer Optimisation

An Iterative Solution Approach to Process Plant Layout using Mixed Integer Optimisation 17 th European Symposum on Computer Aded Process Engneerng ESCAPE17 V. Plesu and P.S. Agach (Edtors) 2007 Elsever B.V. All rghts reserved. 1 An Iteratve Soluton Approach to Process Plant Layout usng Mxed

More information

Modeling, Manipulating, and Visualizing Continuous Volumetric Data: A Novel Spline-based Approach

Modeling, Manipulating, and Visualizing Continuous Volumetric Data: A Novel Spline-based Approach Modelng, Manpulatng, and Vsualzng Contnuous Volumetrc Data: A Novel Splne-based Approach Jng Hua Center for Vsual Computng, Department of Computer Scence SUNY at Stony Brook Talk Outlne Introducton and

More information

S1 Note. Basis functions.

S1 Note. Basis functions. S1 Note. Bass functons. Contents Types of bass functons...1 The Fourer bass...2 B-splne bass...3 Power and type I error rates wth dfferent numbers of bass functons...4 Table S1. Smulaton results of type

More information

A Fast Content-Based Multimedia Retrieval Technique Using Compressed Data

A Fast Content-Based Multimedia Retrieval Technique Using Compressed Data A Fast Content-Based Multmeda Retreval Technque Usng Compressed Data Borko Furht and Pornvt Saksobhavvat NSF Multmeda Laboratory Florda Atlantc Unversty, Boca Raton, Florda 3343 ABSTRACT In ths paper,

More information

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) , Fax: (370-5) ,

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) , Fax: (370-5) , VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual

More information

Analysis on the Workspace of Six-degrees-of-freedom Industrial Robot Based on AutoCAD

Analysis on the Workspace of Six-degrees-of-freedom Industrial Robot Based on AutoCAD Analyss on the Workspace of Sx-degrees-of-freedom Industral Robot Based on AutoCAD Jn-quan L 1, Ru Zhang 1,a, Fang Cu 1, Q Guan 1 and Yang Zhang 1 1 School of Automaton, Bejng Unversty of Posts and Telecommuncatons,

More information

Chapter 6 Programmng the fnte element method Inow turn to the man subject of ths book: The mplementaton of the fnte element algorthm n computer programs. In order to make my dscusson as straghtforward

More information

Petri Net Based Software Dependability Engineering

Petri Net Based Software Dependability Engineering Proc. RELECTRONIC 95, Budapest, pp. 181-186; October 1995 Petr Net Based Software Dependablty Engneerng Monka Hener Brandenburg Unversty of Technology Cottbus Computer Scence Insttute Postbox 101344 D-03013

More information

Multigranular Simulation of Heterogeneous Embedded Systems

Multigranular Simulation of Heterogeneous Embedded Systems Multgranular Smulaton of Heterogeneous Embedded Systems Adtya Agrawal Insttute for Software Integrated Systems Vanderblt Unversty Nashvlle, TN - 37235 1 615 343 7567 adtya.agrawal@vanderblt.edu Akos Ledecz

More information

Exercises (Part 4) Introduction to R UCLA/CCPR. John Fox, February 2005

Exercises (Part 4) Introduction to R UCLA/CCPR. John Fox, February 2005 Exercses (Part 4) Introducton to R UCLA/CCPR John Fox, February 2005 1. A challengng problem: Iterated weghted least squares (IWLS) s a standard method of fttng generalzed lnear models to data. As descrbed

More information

A mathematical programming approach to the analysis, design and scheduling of offshore oilfields

A mathematical programming approach to the analysis, design and scheduling of offshore oilfields 17 th European Symposum on Computer Aded Process Engneerng ESCAPE17 V. Plesu and P.S. Agach (Edtors) 2007 Elsever B.V. All rghts reserved. 1 A mathematcal programmng approach to the analyss, desgn and

More information

APPLICATION OF MULTIVARIATE LOSS FUNCTION FOR ASSESSMENT OF THE QUALITY OF TECHNOLOGICAL PROCESS MANAGEMENT

APPLICATION OF MULTIVARIATE LOSS FUNCTION FOR ASSESSMENT OF THE QUALITY OF TECHNOLOGICAL PROCESS MANAGEMENT 3. - 5. 5., Brno, Czech Republc, EU APPLICATION OF MULTIVARIATE LOSS FUNCTION FOR ASSESSMENT OF THE QUALITY OF TECHNOLOGICAL PROCESS MANAGEMENT Abstract Josef TOŠENOVSKÝ ) Lenka MONSPORTOVÁ ) Flp TOŠENOVSKÝ

More information

FEATURE EXTRACTION. Dr. K.Vijayarekha. Associate Dean School of Electrical and Electronics Engineering SASTRA University, Thanjavur

FEATURE EXTRACTION. Dr. K.Vijayarekha. Associate Dean School of Electrical and Electronics Engineering SASTRA University, Thanjavur FEATURE EXTRACTION Dr. K.Vjayarekha Assocate Dean School of Electrcal and Electroncs Engneerng SASTRA Unversty, Thanjavur613 41 Jont Intatve of IITs and IISc Funded by MHRD Page 1 of 8 Table of Contents

More information

TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS. Muradaliyev A.Z.

TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS. Muradaliyev A.Z. TECHNIQUE OF FORMATION HOMOGENEOUS SAMPLE SAME OBJECTS Muradalyev AZ Azerbajan Scentfc-Research and Desgn-Prospectng Insttute of Energetc AZ1012, Ave HZardab-94 E-mal:aydn_murad@yahoocom Importance of

More information

IP Camera Configuration Software Instruction Manual

IP Camera Configuration Software Instruction Manual IP Camera 9483 - Confguraton Software Instructon Manual VBD 612-4 (10.14) Dear Customer, Wth your purchase of ths IP Camera, you have chosen a qualty product manufactured by RADEMACHER. Thank you for the

More information

Steps for Computing the Dissimilarity, Entropy, Herfindahl-Hirschman and. Accessibility (Gravity with Competition) Indices

Steps for Computing the Dissimilarity, Entropy, Herfindahl-Hirschman and. Accessibility (Gravity with Competition) Indices Steps for Computng the Dssmlarty, Entropy, Herfndahl-Hrschman and Accessblty (Gravty wth Competton) Indces I. Dssmlarty Index Measurement: The followng formula can be used to measure the evenness between

More information

Compiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz

Compiler Design. Spring Register Allocation. Sample Exercises and Solutions. Prof. Pedro C. Diniz Compler Desgn Sprng 2014 Regster Allocaton Sample Exercses and Solutons Prof. Pedro C. Dnz USC / Informaton Scences Insttute 4676 Admralty Way, Sute 1001 Marna del Rey, Calforna 90292 pedro@s.edu Regster

More information

3D vector computer graphics

3D vector computer graphics 3D vector computer graphcs Paolo Varagnolo: freelance engneer Padova Aprl 2016 Prvate Practce ----------------------------------- 1. Introducton Vector 3D model representaton n computer graphcs requres

More information

CMPS 10 Introduction to Computer Science Lecture Notes

CMPS 10 Introduction to Computer Science Lecture Notes CPS 0 Introducton to Computer Scence Lecture Notes Chapter : Algorthm Desgn How should we present algorthms? Natural languages lke Englsh, Spansh, or French whch are rch n nterpretaton and meanng are not

More information

UNIVERSITY OF CALIFORNIA. Los Angeles. Development of. Statistical Online Computational Resources. and Teaching Tools

UNIVERSITY OF CALIFORNIA. Los Angeles. Development of. Statistical Online Computational Resources. and Teaching Tools UNIVERSITY OF CALIFORNIA Los Angeles Development of Statstcal Onlne Computatonal Resources and Teachng Tools A thess submtted n partal satsfacton of the requrements for the degree Master of Scence n Statstcs

More information

Agenda & Reading. Simple If. Decision-Making Statements. COMPSCI 280 S1C Applications Programming. Programming Fundamentals

Agenda & Reading. Simple If. Decision-Making Statements. COMPSCI 280 S1C Applications Programming. Programming Fundamentals Agenda & Readng COMPSCI 8 SC Applcatons Programmng Programmng Fundamentals Control Flow Agenda: Decsonmakng statements: Smple If, Ifelse, nested felse, Select Case s Whle, DoWhle/Untl, For, For Each, Nested

More information

Overview. Basic Setup [9] Motivation and Tasks. Modularization 2008/2/20 IMPROVED COVERAGE CONTROL USING ONLY LOCAL INFORMATION

Overview. Basic Setup [9] Motivation and Tasks. Modularization 2008/2/20 IMPROVED COVERAGE CONTROL USING ONLY LOCAL INFORMATION Overvew 2 IMPROVED COVERAGE CONTROL USING ONLY LOCAL INFORMATION Introducton Mult- Smulator MASIM Theoretcal Work and Smulaton Results Concluson Jay Wagenpfel, Adran Trachte Motvaton and Tasks Basc Setup

More information

SLAM Summer School 2006 Practical 2: SLAM using Monocular Vision

SLAM Summer School 2006 Practical 2: SLAM using Monocular Vision SLAM Summer School 2006 Practcal 2: SLAM usng Monocular Vson Javer Cvera, Unversty of Zaragoza Andrew J. Davson, Imperal College London J.M.M Montel, Unversty of Zaragoza. josemar@unzar.es, jcvera@unzar.es,

More information

Content Based Image Retrieval Using 2-D Discrete Wavelet with Texture Feature with Different Classifiers

Content Based Image Retrieval Using 2-D Discrete Wavelet with Texture Feature with Different Classifiers IOSR Journal of Electroncs and Communcaton Engneerng (IOSR-JECE) e-issn: 78-834,p- ISSN: 78-8735.Volume 9, Issue, Ver. IV (Mar - Apr. 04), PP 0-07 Content Based Image Retreval Usng -D Dscrete Wavelet wth

More information

Lobachevsky State University of Nizhni Novgorod. Polyhedron. Quick Start Guide

Lobachevsky State University of Nizhni Novgorod. Polyhedron. Quick Start Guide Lobachevsky State Unversty of Nzhn Novgorod Polyhedron Quck Start Gude Nzhn Novgorod 2016 Contents Specfcaton of Polyhedron software... 3 Theoretcal background... 4 1. Interface of Polyhedron... 6 1.1.

More information

Very simple computational domains can be discretized using boundary-fitted structured meshes (also called grids)

Very simple computational domains can be discretized using boundary-fitted structured meshes (also called grids) Structured meshes Very smple computatonal domans can be dscretzed usng boundary-ftted structured meshes (also called grds) The grd lnes of a Cartesan mesh are parallel to one another Structured meshes

More information

Hermite Splines in Lie Groups as Products of Geodesics

Hermite Splines in Lie Groups as Products of Geodesics Hermte Splnes n Le Groups as Products of Geodescs Ethan Eade Updated May 28, 2017 1 Introducton 1.1 Goal Ths document defnes a curve n the Le group G parametrzed by tme and by structural parameters n the

More information

Optimal Workload-based Weighted Wavelet Synopses

Optimal Workload-based Weighted Wavelet Synopses Optmal Workload-based Weghted Wavelet Synopses Yoss Matas School of Computer Scence Tel Avv Unversty Tel Avv 69978, Israel matas@tau.ac.l Danel Urel School of Computer Scence Tel Avv Unversty Tel Avv 69978,

More information

High-Boost Mesh Filtering for 3-D Shape Enhancement

High-Boost Mesh Filtering for 3-D Shape Enhancement Hgh-Boost Mesh Flterng for 3-D Shape Enhancement Hrokazu Yagou Λ Alexander Belyaev y Damng We z Λ y z ; ; Shape Modelng Laboratory, Unversty of Azu, Azu-Wakamatsu 965-8580 Japan y Computer Graphcs Group,

More information

FIBARO WALL PLUG OPERATING MANUAL FGBWHWPE-102/FGBWHWPF-102 CONTENTS

FIBARO WALL PLUG OPERATING MANUAL FGBWHWPE-102/FGBWHWPF-102 CONTENTS OPERATING MANUAL EN FIBARO WALL PLUG FGBWHWPE-102/FGBWHWPF-102 CONTENTS #1: Descrpton and features 3 #2: Parng the accessory 4 #3: Reset 5 #4: Functonalty 6 v1.0 #5: W-F 8 #6: Confgurable parameters 9

More information

X- Chart Using ANOM Approach

X- Chart Using ANOM Approach ISSN 1684-8403 Journal of Statstcs Volume 17, 010, pp. 3-3 Abstract X- Chart Usng ANOM Approach Gullapall Chakravarth 1 and Chaluvad Venkateswara Rao Control lmts for ndvdual measurements (X) chart are

More information

Course Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms

Course Introduction. Algorithm 8/31/2017. COSC 320 Advanced Data Structures and Algorithms. COSC 320 Advanced Data Structures and Algorithms Course Introducton Course Topcs Exams, abs, Proects A quc loo at a few algorthms 1 Advanced Data Structures and Algorthms Descrpton: We are gong to dscuss algorthm complexty analyss, algorthm desgn technques

More information

Virtual Memory. Background. No. 10. Virtual Memory: concept. Logical Memory Space (review) Demand Paging(1) Virtual Memory

Virtual Memory. Background. No. 10. Virtual Memory: concept. Logical Memory Space (review) Demand Paging(1) Virtual Memory Background EECS. Operatng System Fundamentals No. Vrtual Memory Prof. Hu Jang Department of Electrcal Engneerng and Computer Scence, York Unversty Memory-management methods normally requres the entre process

More information

ANSYS FLUENT 12.1 in Workbench User s Guide

ANSYS FLUENT 12.1 in Workbench User s Guide ANSYS FLUENT 12.1 n Workbench User s Gude October 2009 Copyrght c 2009 by ANSYS, Inc. All Rghts Reserved. No part of ths document may be reproduced or otherwse used n any form wthout express wrtten permsson

More information

The Codesign Challenge

The Codesign Challenge ECE 4530 Codesgn Challenge Fall 2007 Hardware/Software Codesgn The Codesgn Challenge Objectves In the codesgn challenge, your task s to accelerate a gven software reference mplementaton as fast as possble.

More information

Conditional Speculative Decimal Addition*

Conditional Speculative Decimal Addition* Condtonal Speculatve Decmal Addton Alvaro Vazquez and Elsardo Antelo Dep. of Electronc and Computer Engneerng Unv. of Santago de Compostela, Span Ths work was supported n part by Xunta de Galca under grant

More information

R s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes

R s s f. m y s. SPH3UW Unit 7.3 Spherical Concave Mirrors Page 1 of 12. Notes SPH3UW Unt 7.3 Sphercal Concave Mrrors Page 1 of 1 Notes Physcs Tool box Concave Mrror If the reflectng surface takes place on the nner surface of the sphercal shape so that the centre of the mrror bulges

More information

An Optimal Algorithm for Prufer Codes *

An Optimal Algorithm for Prufer Codes * J. Software Engneerng & Applcatons, 2009, 2: 111-115 do:10.4236/jsea.2009.22016 Publshed Onlne July 2009 (www.scrp.org/journal/jsea) An Optmal Algorthm for Prufer Codes * Xaodong Wang 1, 2, Le Wang 3,

More information

Explicit Formulas and Efficient Algorithm for Moment Computation of Coupled RC Trees with Lumped and Distributed Elements

Explicit Formulas and Efficient Algorithm for Moment Computation of Coupled RC Trees with Lumped and Distributed Elements Explct Formulas and Effcent Algorthm for Moment Computaton of Coupled RC Trees wth Lumped and Dstrbuted Elements Qngan Yu and Ernest S.Kuh Electroncs Research Lab. Unv. of Calforna at Berkeley Berkeley

More information

Programming in Fortran 90 : 2017/2018

Programming in Fortran 90 : 2017/2018 Programmng n Fortran 90 : 2017/2018 Programmng n Fortran 90 : 2017/2018 Exercse 1 : Evaluaton of functon dependng on nput Wrte a program who evaluate the functon f (x,y) for any two user specfed values

More information

Problem Set 3 Solutions

Problem Set 3 Solutions Introducton to Algorthms October 4, 2002 Massachusetts Insttute of Technology 6046J/18410J Professors Erk Demane and Shaf Goldwasser Handout 14 Problem Set 3 Solutons (Exercses were not to be turned n,

More information

Learning-Based Top-N Selection Query Evaluation over Relational Databases

Learning-Based Top-N Selection Query Evaluation over Relational Databases Learnng-Based Top-N Selecton Query Evaluaton over Relatonal Databases Lang Zhu *, Wey Meng ** * School of Mathematcs and Computer Scence, Hebe Unversty, Baodng, Hebe 071002, Chna, zhu@mal.hbu.edu.cn **

More information

Active Contours/Snakes

Active Contours/Snakes Actve Contours/Snakes Erkut Erdem Acknowledgement: The sldes are adapted from the sldes prepared by K. Grauman of Unversty of Texas at Austn Fttng: Edges vs. boundares Edges useful sgnal to ndcate occludng

More information

NAG Fortran Library Chapter Introduction. G10 Smoothing in Statistics

NAG Fortran Library Chapter Introduction. G10 Smoothing in Statistics Introducton G10 NAG Fortran Lbrary Chapter Introducton G10 Smoothng n Statstcs Contents 1 Scope of the Chapter... 2 2 Background to the Problems... 2 2.1 Smoothng Methods... 2 2.2 Smoothng Splnes and Regresson

More information

Complex Numbers. Now we also saw that if a and b were both positive then ab = a b. For a second let s forget that restriction and do the following.

Complex Numbers. Now we also saw that if a and b were both positive then ab = a b. For a second let s forget that restriction and do the following. Complex Numbers The last topc n ths secton s not really related to most of what we ve done n ths chapter, although t s somewhat related to the radcals secton as we wll see. We also won t need the materal

More information

Range images. Range image registration. Examples of sampling patterns. Range images and range surfaces

Range images. Range image registration. Examples of sampling patterns. Range images and range surfaces Range mages For many structured lght scanners, the range data forms a hghly regular pattern known as a range mage. he samplng pattern s determned by the specfc scanner. Range mage regstraton 1 Examples

More information

Fitting & Matching. Lecture 4 Prof. Bregler. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros.

Fitting & Matching. Lecture 4 Prof. Bregler. Slides from: S. Lazebnik, S. Seitz, M. Pollefeys, A. Effros. Fttng & Matchng Lecture 4 Prof. Bregler Sldes from: S. Lazebnk, S. Setz, M. Pollefeys, A. Effros. How do we buld panorama? We need to match (algn) mages Matchng wth Features Detect feature ponts n both

More information

Fitting: Deformable contours April 26 th, 2018

Fitting: Deformable contours April 26 th, 2018 4/6/08 Fttng: Deformable contours Aprl 6 th, 08 Yong Jae Lee UC Davs Recap so far: Groupng and Fttng Goal: move from array of pxel values (or flter outputs) to a collecton of regons, objects, and shapes.

More information

User Authentication Based On Behavioral Mouse Dynamics Biometrics

User Authentication Based On Behavioral Mouse Dynamics Biometrics User Authentcaton Based On Behavoral Mouse Dynamcs Bometrcs Chee-Hyung Yoon Danel Donghyun Km Department of Computer Scence Department of Computer Scence Stanford Unversty Stanford Unversty Stanford, CA

More information

NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS

NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS ARPN Journal of Engneerng and Appled Scences 006-017 Asan Research Publshng Network (ARPN). All rghts reserved. NUMERICAL SOLVING OPTIMAL CONTROL PROBLEMS BY THE METHOD OF VARIATIONS Igor Grgoryev, Svetlana

More information

2x x l. Module 3: Element Properties Lecture 4: Lagrange and Serendipity Elements

2x x l. Module 3: Element Properties Lecture 4: Lagrange and Serendipity Elements Module 3: Element Propertes Lecture : Lagrange and Serendpty Elements 5 In last lecture note, the nterpolaton functons are derved on the bass of assumed polynomal from Pascal s trangle for the fled varable.

More information

EXTENDED BIC CRITERION FOR MODEL SELECTION

EXTENDED BIC CRITERION FOR MODEL SELECTION IDIAP RESEARCH REPORT EXTEDED BIC CRITERIO FOR ODEL SELECTIO Itshak Lapdot Andrew orrs IDIAP-RR-0-4 Dalle olle Insttute for Perceptual Artfcal Intellgence P.O.Box 59 artgny Valas Swtzerland phone +4 7

More information

Virtual Environment of Design: A Hybrid CAD Tool

Virtual Environment of Design: A Hybrid CAD Tool Vrtual Envronment of Desgn: A Hybrd CAD Tool Chensheng Wang, Jors. S. M. Vergeest Faculty of Desgn, Engneerng and Producton Delft Unversty of Technology Landbergstraat 15, NL-2628 CE Delft, The Netherlands

More information

Classifying Acoustic Transient Signals Using Artificial Intelligence

Classifying Acoustic Transient Signals Using Artificial Intelligence Classfyng Acoustc Transent Sgnals Usng Artfcal Intellgence Steve Sutton, Unversty of North Carolna At Wlmngton (suttons@charter.net) Greg Huff, Unversty of North Carolna At Wlmngton (jgh7476@uncwl.edu)

More information

PRÉSENTATIONS DE PROJETS

PRÉSENTATIONS DE PROJETS PRÉSENTATIONS DE PROJETS Rex Onlne (V. Atanasu) What s Rex? Rex s an onlne browser for collectons of wrtten documents [1]. Asde ths core functon t has however many other applcatons that make t nterestng

More information

VISUAL SELECTION OF SURFACE FEATURES DURING THEIR GEOMETRIC SIMULATION WITH THE HELP OF COMPUTER TECHNOLOGIES

VISUAL SELECTION OF SURFACE FEATURES DURING THEIR GEOMETRIC SIMULATION WITH THE HELP OF COMPUTER TECHNOLOGIES UbCC 2011, Volume 6, 5002981-x manuscrpts OPEN ACCES UbCC Journal ISSN 1992-8424 www.ubcc.org VISUAL SELECTION OF SURFACE FEATURES DURING THEIR GEOMETRIC SIMULATION WITH THE HELP OF COMPUTER TECHNOLOGIES

More information

Efficient Distributed File System (EDFS)

Efficient Distributed File System (EDFS) Effcent Dstrbuted Fle System (EDFS) (Sem-Centralzed) Debessay(Debsh) Fesehaye, Rahul Malk & Klara Naherstedt Unversty of Illnos-Urbana Champagn Contents Problem Statement, Related Work, EDFS Desgn Rate

More information

Lecture #15 Lecture Notes

Lecture #15 Lecture Notes Lecture #15 Lecture Notes The ocean water column s very much a 3-D spatal entt and we need to represent that structure n an economcal way to deal wth t n calculatons. We wll dscuss one way to do so, emprcal

More information

6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour

6.854 Advanced Algorithms Petar Maymounkov Problem Set 11 (November 23, 2005) With: Benjamin Rossman, Oren Weimann, and Pouya Kheradpour 6.854 Advanced Algorthms Petar Maymounkov Problem Set 11 (November 23, 2005) Wth: Benjamn Rossman, Oren Wemann, and Pouya Kheradpour Problem 1. We reduce vertex cover to MAX-SAT wth weghts, such that the

More information

Graphical Program Development with PECAN Program Development Systemst

Graphical Program Development with PECAN Program Development Systemst Graphcal Program Development wth PECAN Program Development Systemst Steven P. Ress Department of Computer Scence Brown Unversty Provdence, RI 02912 ABSTRACT Ths paper descrbes the user's vew of the PECAN

More information

Installation Instructions. METRAwin Version 8/ Calibration Software

Installation Instructions. METRAwin Version 8/ Calibration Software Installaton Instructons METRAwn 90 Calbraton Software 3-349-717-15 Verson 8/05.13 Copyrght Copyrght 2003-2013 GMC-I Messtechnk GmbH. All rghts reserved. These nstallaton nstructons, as well as the software

More information

A plan-driven dynamic reconfiguration mechanism for C2 Communities of Interest

A plan-driven dynamic reconfiguration mechanism for C2 Communities of Interest 15 th ICCRTS The Evoluton of C2 Ttle of Paper: A plan-drven dynamc reconfguraton mechansm for C2 Communtes of Interest Topcs Topc 6: Modelng and Smulaton Paper ID ID# 080 Authors JngJng Yan ZhuYun Duanmu

More information

Resource and Virtual Function Status Monitoring in Network Function Virtualization Environment

Resource and Virtual Function Status Monitoring in Network Function Virtualization Environment Journal of Physcs: Conference Seres PAPER OPEN ACCESS Resource and Vrtual Functon Status Montorng n Network Functon Vrtualzaton Envronment To cte ths artcle: MS Ha et al 2018 J. Phys.: Conf. Ser. 1087

More information

Meta-heuristics for Multidimensional Knapsack Problems

Meta-heuristics for Multidimensional Knapsack Problems 2012 4th Internatonal Conference on Computer Research and Development IPCSIT vol.39 (2012) (2012) IACSIT Press, Sngapore Meta-heurstcs for Multdmensonal Knapsack Problems Zhbao Man + Computer Scence Department,

More information

Feature Reduction and Selection

Feature Reduction and Selection Feature Reducton and Selecton Dr. Shuang LIANG School of Software Engneerng TongJ Unversty Fall, 2012 Today s Topcs Introducton Problems of Dmensonalty Feature Reducton Statstc methods Prncpal Components

More information

Evaluation of an Enhanced Scheme for High-level Nested Network Mobility

Evaluation of an Enhanced Scheme for High-level Nested Network Mobility IJCSNS Internatonal Journal of Computer Scence and Network Securty, VOL.15 No.10, October 2015 1 Evaluaton of an Enhanced Scheme for Hgh-level Nested Network Moblty Mohammed Babker Al Mohammed, Asha Hassan.

More information

Multiblock method for database generation in finite element programs

Multiblock method for database generation in finite element programs Proc. of the 9th WSEAS Int. Conf. on Mathematcal Methods and Computatonal Technques n Electrcal Engneerng, Arcachon, October 13-15, 2007 53 Multblock method for database generaton n fnte element programs

More information

[33]. As we have seen there are different algorithms for compressing the speech. The

[33]. As we have seen there are different algorithms for compressing the speech. The 49 5. LD-CELP SPEECH CODER 5.1 INTRODUCTION Speech compresson s one of the mportant doman n dgtal communcaton [33]. As we have seen there are dfferent algorthms for compressng the speech. The mportant

More information

Oracle Database: SQL and PL/SQL Fundamentals Certification Course

Oracle Database: SQL and PL/SQL Fundamentals Certification Course Oracle Database: SQL and PL/SQL Fundamentals Certfcaton Course 1 Duraton: 5 Days (30 hours) What you wll learn: Ths Oracle Database: SQL and PL/SQL Fundamentals tranng delvers the fundamentals of SQL and

More information

APPLICATION OF PREDICTION-BASED PARTICLE FILTERS FOR TELEOPERATIONS OVER THE INTERNET

APPLICATION OF PREDICTION-BASED PARTICLE FILTERS FOR TELEOPERATIONS OVER THE INTERNET APPLICATION OF PREDICTION-BASED PARTICLE FILTERS FOR TELEOPERATIONS OVER THE INTERNET Jae-young Lee, Shahram Payandeh, and Ljljana Trajovć School of Engneerng Scence Smon Fraser Unversty 8888 Unversty

More information

An Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices

An Application of the Dulmage-Mendelsohn Decomposition to Sparse Null Space Bases of Full Row Rank Matrices Internatonal Mathematcal Forum, Vol 7, 2012, no 52, 2549-2554 An Applcaton of the Dulmage-Mendelsohn Decomposton to Sparse Null Space Bases of Full Row Rank Matrces Mostafa Khorramzadeh Department of Mathematcal

More information

MODULE DESIGN BASED ON INTERFACE INTEGRATION TO MAXIMIZE PRODUCT VARIETY AND MINIMIZE FAMILY COST

MODULE DESIGN BASED ON INTERFACE INTEGRATION TO MAXIMIZE PRODUCT VARIETY AND MINIMIZE FAMILY COST INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED 07 28-31 AUGUST 2007, CITE DES SCIENCES ET DE L'INDUSTRIE, PARIS, FRANCE MODULE DESIGN BASED ON INTERFACE INTEGRATION TO MAIMIZE PRODUCT VARIETY AND

More information

Improvement of Spatial Resolution Using BlockMatching Based Motion Estimation and Frame. Integration

Improvement of Spatial Resolution Using BlockMatching Based Motion Estimation and Frame. Integration Improvement of Spatal Resoluton Usng BlockMatchng Based Moton Estmaton and Frame Integraton Danya Suga and Takayuk Hamamoto Graduate School of Engneerng, Tokyo Unversty of Scence, 6-3-1, Nuku, Katsuska-ku,

More information

Model Integrated Computing: A Framework for Creating Domain Specific Design Environments

Model Integrated Computing: A Framework for Creating Domain Specific Design Environments Model Integrated Computng: A Framework for Creatng Doman Specfc Desgn Envronments James R. DAVIS Vanderblt Unversty, Insttute for Software Integrated Systems Nashvlle, TN 37203, USA ABSTRACT Model Integrated

More information

A Robust Method for Estimating the Fundamental Matrix

A Robust Method for Estimating the Fundamental Matrix Proc. VIIth Dgtal Image Computng: Technques and Applcatons, Sun C., Talbot H., Ourseln S. and Adraansen T. (Eds.), 0- Dec. 003, Sydney A Robust Method for Estmatng the Fundamental Matrx C.L. Feng and Y.S.

More information

FAHP and Modified GRA Based Network Selection in Heterogeneous Wireless Networks

FAHP and Modified GRA Based Network Selection in Heterogeneous Wireless Networks 2017 2nd Internatonal Semnar on Appled Physcs, Optoelectroncs and Photoncs (APOP 2017) ISBN: 978-1-60595-522-3 FAHP and Modfed GRA Based Network Selecton n Heterogeneous Wreless Networks Xaohan DU, Zhqng

More information

NGPM -- A NSGA-II Program in Matlab

NGPM -- A NSGA-II Program in Matlab Verson 1.4 LIN Song Aerospace Structural Dynamcs Research Laboratory College of Astronautcs, Northwestern Polytechncal Unversty, Chna Emal: lsssswc@163.com 2011-07-26 Contents Contents... 1. Introducton...

More information

APPLICATION OF PREDICTION-BASED PARTICLE FILTERS FOR TELEOPERATIONS OVER THE INTERNET

APPLICATION OF PREDICTION-BASED PARTICLE FILTERS FOR TELEOPERATIONS OVER THE INTERNET APPLICATION OF PREDICTION-BASED PARTICLE FILTERS FOR TELEOPERATIONS OVER THE INTERNET Jae-young Lee, Shahram Payandeh, and Ljljana Trajovć School of Engneerng Scence Smon Fraser Unversty 8888 Unversty

More information