COMPARISON OF TWO MODELS FOR HUMAN EVACUATING SIMULATION IN LARGE BUILDING SPACES. University, Beijing , China

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "COMPARISON OF TWO MODELS FOR HUMAN EVACUATING SIMULATION IN LARGE BUILDING SPACES. University, Beijing , China"

Transcription

1 COMPARISON OF TWO MODELS FOR HUMAN EVACUATING SIMULATION IN LARGE BUILDING SPACES Bn Zhao 1, 2, He Xao 1, Yue Wang 1, Yuebao Wang 1 1 Department of Buldng Scence and Technology, Tsnghua Unversty, Bejng , Chna 2 Tsnghua-U Penn. Smulaton Center (T C Chan center) ABSTRACT Ths paper presents the smulated results of human evacuaton n a large space buldng. Two dfferent models, Cellular Automata (CA) model and socal force (SF) model are adopted. The smulated evacuaton tme and man characterstcs of human evacuaton are smulated and these results by the two models are compared. To check the practcablty of the models for actual complcated cases, the smulatng tme s also compared. The results denote that both the two models can smulate the arch and faster-s-slower effect for human evacuaton. It also could be found that the CA model s easly analyzed and possess fewer CPU tme, whle the SF model s much easer to be expanded to consder more complcated human behavor models. KEYWORDS Human behavor, Smulaton, Cellular Automata (CA) model, Socal force model ntroducton INTRODUCTION Durng the last decade, the nvestgaton of vehcle streams by means of experments and models has captured the nterest of many scholars. The statstcal physcs or flud-dynamcs method was used to reproduce the mechansms behnd many observed phenomena such as dfferent forms of congeston and jammng. Those dverse phenomena between fluds, granular meda, vehcles and pedestrans were owng to dstnct laws and drvng terms. In classcal drven many-partcle system, there are mcroscopc, molecular dynamc models, lattce gas automata or cellular automata model, gas models and fluddynamc models (Helbng 2001). Whle n selfdrven many-partcle system, the drvng force s not of external, but s assocated wth each sngle partcle, an nternal force, whch can represent the moton and mentalty characterstcs of human bengs. Approxmately, the human behavor n conflct stuatons s guded by socal felds or socal forces (Lewn 1951), an dea that has been put nto mathematcal terms by Helbng (1995). researchers study the pedestran flow wth the smlar methods n traffc flow feld. Very recently, Song et al. (2006) have studed dynamcal features of fre escape panc by applyng the mproved cellular automata model. They have shown the characterstc features of escape pancs: Archng and faster s slower of people occur at ext. In most of the tme, human behavor s relaxed and normal, dfferent from the escape pancs. So t s essental to research those features n large buldng space n order to nstruct the archtects to desgn buldngs more optmzed and reasonable, and avod casualty n emergency cases. In ths paper, we learn to study the human evacuaton features n a large-space buldng. We apply the pedestran mproved cellular automata model (CA) and socal force model (SF) to smulate the crowd flow n a large-space buldng. We calculate the evacuaton tme and compare the two models result. We also smulate the man characterstcs of human evacuaton, such as arch and faster s slower effect, and draw the compared conclusons of two pedestran models. MODELS Cellular automata (CA) model Cellular automata (CA) model s a specal manypartcle model n whch the topologcal structure s fxed. It s wdely appled n both natural scence and socal scence. In ths paper, a large-scale buldng based on genetc cellular automata s establshed. Cells are used to represent people n the buldng, who has the capablty of self-learnng and are affected by the neghborng ones. The topologcal structure of CA n ths paper s a two-dmensonal square lattce, whch the neghborng relatonshp can be consdered as the Von Neunann style (Fg. 1.). Whle the pedestran flow dynamcs s also closely connected wth the traffc stream. So many

2 Fg.1. (Zhou et al. 1999) (a-c) shows the three styles of the neghborng relatonshp. The dark black lattce s the center cell and the gray ones are neghbors. The center cell can only have the nteracton wth ther neghbors. confguraton (3-b): θ = 0.1,V = v, for confguraton (3-c): θ = 0.5,V = v. The two-dmensonal smulated room s represented by the square of L L stes where L s the length of the room. The room was dvded nto average cells 2 wth the square of m whch represents an adult. The room has a sngle ext wth wdth W. We assume that people are randomly dstrbuted, ntallyt = 0, over the square space of the room. At the next tme t > 0, all people n the room move toward the ext. We defne the evacuated speed v as the desred velocty, whle the Δ t = 0. 5 v as the tme-step. Update the dstrbutng at every tme step and export the map. People decson ncludes two steps: frst, each person makes a preparatory choce of the neghborng cells by the dstance force law (Song et al.2006.), they chose the lattce among the neghbors and go nto t whch has the smallest dstance to the ext. Second, each person judges and modfes ther prmary decson. If there are no other people chose the same lattce, ths person can walk nto the cell n the next tme step. But f there are more than one person make the same choce, we should calculate ther frcton and repulson probablty, then chose the rght person enter the target based on our random functon. Fg.2. ndcates all possble confguratons of repulson. The black dots and shadows ndcate walker and wall. The repulson probablty of the walker correspondng to each confguraton s gven by the followng equaton (Song et al.2006.): 1 e r = 1 + e αv αv (1) Where α s the rgdty coeffcent whch generally reflects the possble njury between people and people or people and wall. For confguraton (2- a): α = 1, for confguraton (2-b): α = 2. Fg.3. ndcates all possble confguratons of frcton. The frcton probablty of the walker correspondng to each confguraton s gven by the followng equaton (Song et al.2006.): f = θ V (2) Where θ s the frcton coeffcent whch reflects frcton degree between people and people or people and wall. In addton, V s the relatve velocty. For confguraton (3-a): θ = 0.1,V = 2v, for Fg.2. (Song et al.2006.) ndcates two possble confguratons of repulson. Fg.(2-a) llustrates the nteracton between several people. Fg.(2-b) llustrates the nteracton between people and wall. Fg.3. (Song et al.2006.) ndcates three possble confguratons of frcton. Fg. (3-a) llustrates movng vs-à-vs. Fg. (3-b) llustrates the quescence and movement. Fg. (3-c) llustrates the people and wall. Socal force (SF) model CA model focus on the partcle character of people, but for relable smulatons of pedestran crowds we do not need to know the moton character of a certan person, we pay more attenton on the whole crowd, the flud character nstead. On the other sde, human behavor often seems to be chaotc, rregular, and unpredctable, one s own mentalty and the nteracton between partcle bodes make more effect than external envronment, so those can not be well smulated by CA model. Lewn(1951) suggests an approach for modelng human behavoral changes. Accordng to hs dea behavoral changes are guded by so-called socal feld or socal forces. In ths study, we use the SF model establshed by Helbng (2000). Accordng to hs dea, a mxture of soco-psychologcal and physcal forces nfluences the behavor n a crowd: The mass of pedestran s m, movng wth a certan desred velocty v 0, whch has a certan drecton and a certan characterstc tme τ. 0 e,

3 The nteracton force f j and f W whch represent the velocty-dependent dstance to other pedestran j and walls W. So n mathematcal terms, the change of velocty n tme t s then gven by the equaton: dv m dt = m 0 0 v e ( t) v ( t) τ + fj + j Then Helbng brngs the concept psychologcal tendency, and puts f j, fw nto mathematcal terms based on the defnton of body force and sldng frcton force. The change of poston r (t) s gven by the equaton v ( t) = dr dt. So we can calculate the poston r (t) by the twce-defnte ntegral of acceleraton. RESULTS COMPARISON Both two models smulate the same evacuaton process n a sngle-ext, 15 m by 15 m room. The wdth of the door s1 m. There are 196 pedestrans n 2 the room. The cell of the room s m. W f W (3) Although the evacuaton tme of two models s dfferent, the typcal stages of the process are smlar. Fg.4. and Fg.5.denotes the patterns formed by walkers gong to the ext at four dfferent stages. The desred velocty s1 m / s.at (a) the begnnng stage ( t = 0 ), all walkers are dstrbuted and get the basc nformaton of the room, lke the locaton of obstacles and door. At (b) the archng stage ( 0 < t < 25 ), archng of walkers occurs snce only a few walkers go, throughout the ext, outsde the hall and most walkers cannot go out from the ext. At (c) the mddle stage ( 25 < t < 100 ), the archng decays and most of pedestrans go out of the ext. At (d) the end stage ( t > 100 ), the remanng walkers go out of the ext wthout chokng. Evacuaton tme Table 1.denotes the evacuaton tme based on the dfferent desred velocty of two models. Both of models consder that the pedestran can evacuate smoothly wthn two and a half mnute n our case, but the evacuaton tme calculated by SF s obvously faster than CA. Especally the desred velocty s hgher. The result depends on the dfferent features of two models. In the CA model, we consder more about the nteracton between cells, whle n the SF model, we pay more attenton to the flud dynamc characterstc of the pedestran. Table 1. The evacuaton tme of two models based on dfferent desred velocty Desred Evacuaton Tme( s ) Velocty( m / s ) CA model SF model Fg.4. ndcates the four typcal stages of CA model: the begnnng stage, the archng stage, the mddle stage and the endng stage

4 flow, and reduces the effcency of leavng. But the speed threshold of two models s dfferent. The turnng pont of CA model s 1 m / s n round numbers, half of SF s. Fg.7. compares the evacuaton tme of two models and llustrates faster-s-slower effect. The upper lne s CA model and the nether one s SF model. Fg.5.ndcates the four typcal stages of SF model: the begnnng stage, the archng stage, the mddle stage and the endng stage. Arch effect The result denotes that both the two models could predct the arch effect reproduced at the ext, as shown n Fg.6. Because all pedestrans move towards the ext, t becomes a bottleneck of pedestran flow. The archng phenomenon of both the models s evdent. Fg.6. ndcates the archng phenomenon of the two models. Faster s slower effect If the desred velocty s small, along wth ts ncrease, the evacuaton tme wll decrease. However, both two models gve a same smulaton result that tryng to move faster above a speed threshold leads to longer evacuaton tme. Fg.7 llustrates the fasters-slower phenomenon reproduced by CA and SF as a comparson. The evacuaton tme of two models shown here does not decrease monotonously wth the ncrease of desred velocty, but behave a parabola shape nstead. Hgher desred velocty ncreases the nteracton between people, blocks the pedestran Predctng tme We use a same personal computer to calculate all the cases, the CA model needs 5 seconds to fnsh the calculaton approxmately, compares 85 seconds of SF model. So the CA model consumes less CPUtme than SF. The man reason s that regulaton of SF model s more complex, t should calculate whole people n the room durng a tme-step, whle the CA model just consders the neghborng ones. RESULTS COMPARISON Dscusson The current CA and SF models can evaluate the major nteractons between pedestrans, such as frcton, repulson and the dstance force. They use the randomzaton of probablty or the flud dynamc features of pedestran to smulate evacuaton case n realty. However both the models have obvous defcences. One hand, the parameters of the model should be researched over agan. We should desgn a seres of experment to test the human evacuaton behavor so as to confrm the certan parameters. On the other hand, we are now mprovng the arthmetc and rules and callng for complementary data and addtonal vdeo materal on evacuaton to test our model, consder mult-ext, obstacles and threedmenson cases, and mplement more complex strateges and nteractons. Concluson In ths paper, we use the mproved CA model to smulate an evacuaton case n a large-space twodmensonal room and compare ts performance wth the SF model. Despte the dfferent types of rules, both of the models can smulate the arch and faster-s-slower effect. Consderng the smple rules, the CA model s easly analyzed and possessed

5 fewer CPU tmes, whle the SF model s much easer to be expanded to consder more complcated human behavor models. ACKNOWLEDGEMENT Ths work s supported by the Student Research Tranng (SRT) project of Tsnghua Unversty (071S0030). REFERENCE Drk Helbng Socal force model for pedestran dynamcs, PHYSICAL REVIEW E, Vol 51, pp Drk Helbng Smulatng Dynamcal Features of Escape Panc, arxv: cond-mat/ v1 Drk Helbng Traffc and related self-drven many-partcle systems, REVIEWS OF MODERN PHYSICS, Vol 73, pp Lewn K Feld Theory n Socal Scence (Harper, New York) Song WG. Yu YF. Wang BH. Fan WC Evacuaton behavors at ext n CA model wth force essentals: A comparson wth socal force model, PHYSICA A, Vol 37, pp Zhou CH. Sun ZL. Xe YC Research of Cellular Automata n Geography. Chna: Chnese ScentfcPress

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

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

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

Physics 132 4/24/17. April 24, 2017 Physics 132 Prof. E. F. Redish. Outline

Physics 132 4/24/17. April 24, 2017 Physics 132 Prof. E. F. Redish. Outline Aprl 24, 2017 Physcs 132 Prof. E. F. Redsh Theme Musc: Justn Tmberlake Mrrors Cartoon: Gary Larson The Far Sde 1 Outlne Images produced by a curved mrror Image equatons for a curved mrror Lght n dense

More information

Smoothing Spline ANOVA for variable screening

Smoothing Spline ANOVA for variable screening Smoothng Splne ANOVA for varable screenng a useful tool for metamodels tranng and mult-objectve optmzaton L. Rcco, E. Rgon, A. Turco Outlne RSM Introducton Possble couplng Test case MOO MOO wth Game Theory

More information

BioTechnology. An Indian Journal FULL PAPER. Trade Science Inc.

BioTechnology. An Indian Journal FULL PAPER. Trade Science Inc. [Type text] [Type text] [Type text] ISSN : 0974-74 Volume 0 Issue BoTechnology 04 An Indan Journal FULL PAPER BTAIJ 0() 04 [684-689] Revew on Chna s sports ndustry fnancng market based on market -orented

More information

Structure Formation of Social Network

Structure Formation of Social Network Structure Formaton of Socal Network DU Nan 1, FENG Hu 2, HUANG Zgang 3, Sally MAKI 4, WANG Ru(Ruby) 5, and ZHAO Hongxa (Melssa) 6 1 Bejng Unversty of Posts and Telecommuncatons, Chna 2 Fudan Unversty,

More information

Computer models of motion: Iterative calculations

Computer models of motion: Iterative calculations Computer models o moton: Iteratve calculatons OBJECTIVES In ths actvty you wll learn how to: Create 3D box objects Update the poston o an object teratvely (repeatedly) to anmate ts moton Update the momentum

More information

Dynamic wetting property investigation of AFM tips in micro/nanoscale

Dynamic wetting property investigation of AFM tips in micro/nanoscale Dynamc wettng property nvestgaton of AFM tps n mcro/nanoscale The wettng propertes of AFM probe tps are of concern n AFM tp related force measurement, fabrcaton, and manpulaton technques, such as dp-pen

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

Finite Element Analysis of Rubber Sealing Ring Resilience Behavior Qu Jia 1,a, Chen Geng 1,b and Yang Yuwei 2,c

Finite Element Analysis of Rubber Sealing Ring Resilience Behavior Qu Jia 1,a, Chen Geng 1,b and Yang Yuwei 2,c Advanced Materals Research Onlne: 03-06-3 ISSN: 66-8985, Vol. 705, pp 40-44 do:0.408/www.scentfc.net/amr.705.40 03 Trans Tech Publcatons, Swtzerland Fnte Element Analyss of Rubber Sealng Rng Reslence Behavor

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

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

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

VFH*: Local Obstacle Avoidance with Look-Ahead Verification

VFH*: Local Obstacle Avoidance with Look-Ahead Verification 2000 IEEE Internatonal Conference on Robotcs and Automaton, San Francsco, CA, Aprl 24-28, 2000, pp. 2505-25 VFH*: Local Obstacle Avodance wth Look-Ahead Verfcaton Iwan Ulrch and Johann Borensten The Unversty

More information

For instance, ; the five basic number-sets are increasingly more n A B & B A A = B (1)

For instance, ; the five basic number-sets are increasingly more n A B & B A A = B (1) Secton 1.2 Subsets and the Boolean operatons on sets If every element of the set A s an element of the set B, we say that A s a subset of B, or that A s contaned n B, or that B contans A, and we wrte A

More information

Fast Computation of Shortest Path for Visiting Segments in the Plane

Fast Computation of Shortest Path for Visiting Segments in the Plane Send Orders for Reprnts to reprnts@benthamscence.ae 4 The Open Cybernetcs & Systemcs Journal, 04, 8, 4-9 Open Access Fast Computaton of Shortest Path for Vstng Segments n the Plane Ljuan Wang,, Bo Jang

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

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

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

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

Pose, Posture, Formation and Contortion in Kinematic Systems

Pose, Posture, Formation and Contortion in Kinematic Systems Pose, Posture, Formaton and Contorton n Knematc Systems J. Rooney and T. K. Tanev Department of Desgn and Innovaton, Faculty of Technology, The Open Unversty, Unted Kngdom Abstract. The concepts of pose,

More information

Boundary Condition Simulation for Structural Local Refined Modeling Using Genetic Algorithm

Boundary Condition Simulation for Structural Local Refined Modeling Using Genetic Algorithm 2016 Internatonal Conference on Artfcal Intellgence: Technques and Applcatons (AITA 2016) ISBN: 978-1-60595-389-2 Boundary Condton Smulaton for Structural Local Refned Modelng Usng Genetc Algorthm Zhong

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

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

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

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

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

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

Simulation: Solving Dynamic Models ABE 5646 Week 11 Chapter 2, Spring 2010

Simulation: Solving Dynamic Models ABE 5646 Week 11 Chapter 2, Spring 2010 Smulaton: Solvng Dynamc Models ABE 5646 Week Chapter 2, Sprng 200 Week Descrpton Readng Materal Mar 5- Mar 9 Evaluatng [Crop] Models Comparng a model wth data - Graphcal, errors - Measures of agreement

More information

Outline. Self-Organizing Maps (SOM) US Hebbian Learning, Cntd. The learning rule is Hebbian like:

Outline. Self-Organizing Maps (SOM) US Hebbian Learning, Cntd. The learning rule is Hebbian like: Self-Organzng Maps (SOM) Turgay İBRİKÇİ, PhD. Outlne Introducton Structures of SOM SOM Archtecture Neghborhoods SOM Algorthm Examples Summary 1 2 Unsupervsed Hebban Learnng US Hebban Learnng, Cntd 3 A

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

S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION?

S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION? S.P.H. : A SOLUTION TO AVOID USING EROSION CRITERION? Célne GALLET ENSICA 1 place Emle Bloun 31056 TOULOUSE CEDEX e-mal :cgallet@ensca.fr Jean Luc LACOME DYNALIS Immeuble AEROPOLE - Bat 1 5, Avenue Albert

More information

Some Advanced SPC Tools 1. Cumulative Sum Control (Cusum) Chart For the data shown in Table 9-1, the x chart can be generated.

Some Advanced SPC Tools 1. Cumulative Sum Control (Cusum) Chart For the data shown in Table 9-1, the x chart can be generated. Some Advanced SP Tools 1. umulatve Sum ontrol (usum) hart For the data shown n Table 9-1, the x chart can be generated. However, the shft taken place at sample #21 s not apparent. 92 For ths set samples,

More information

Brave New World Pseudocode Reference

Brave New World Pseudocode Reference Brave New World Pseudocode Reference Pseudocode s a way to descrbe how to accomplsh tasks usng basc steps lke those a computer mght perform. In ths week s lab, you'll see how a form of pseudocode can be

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

A Topology-aware Random Walk

A Topology-aware Random Walk A Topology-aware Random Walk Inkwan Yu, Rchard Newman Dept. of CISE, Unversty of Florda, Ganesvlle, Florda, USA Abstract When a graph can be decomposed nto clusters of well connected subgraphs, t s possble

More information

Solving two-person zero-sum game by Matlab

Solving two-person zero-sum game by Matlab Appled Mechancs and Materals Onlne: 2011-02-02 ISSN: 1662-7482, Vols. 50-51, pp 262-265 do:10.4028/www.scentfc.net/amm.50-51.262 2011 Trans Tech Publcatons, Swtzerland Solvng two-person zero-sum game by

More information

REFRACTION. a. To study the refraction of light from plane surfaces. b. To determine the index of refraction for Acrylic and Water.

REFRACTION. a. To study the refraction of light from plane surfaces. b. To determine the index of refraction for Acrylic and Water. Purpose Theory REFRACTION a. To study the refracton of lght from plane surfaces. b. To determne the ndex of refracton for Acrylc and Water. When a ray of lght passes from one medum nto another one of dfferent

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

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

Parallel matrix-vector multiplication

Parallel matrix-vector multiplication Appendx A Parallel matrx-vector multplcaton The reduced transton matrx of the three-dmensonal cage model for gel electrophoress, descrbed n secton 3.2, becomes excessvely large for polymer lengths more

More information

Study on Properties of Traffic Flow on Bus Transport Networks

Study on Properties of Traffic Flow on Bus Transport Networks Study on Propertes of Traffc Flow on Bus Transport Networks XU-HUA YANG, JIU-QIANG ZHAO, GUANG CHEN, AND YOU-YU DONG College of Computer Scence and Technology Zhejang Unversty of Technology Hangzhou, 310023,

More information

The Comparison of Calibration Method of Binocular Stereo Vision System Ke Zhang a *, Zhao Gao b

The Comparison of Calibration Method of Binocular Stereo Vision System Ke Zhang a *, Zhao Gao b 3rd Internatonal Conference on Materal, Mechancal and Manufacturng Engneerng (IC3ME 2015) The Comparson of Calbraton Method of Bnocular Stereo Vson System Ke Zhang a *, Zhao Gao b College of Engneerng,

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

Proper Choice of Data Used for the Estimation of Datum Transformation Parameters

Proper Choice of Data Used for the Estimation of Datum Transformation Parameters Proper Choce of Data Used for the Estmaton of Datum Transformaton Parameters Hakan S. KUTOGLU, Turkey Key words: Coordnate systems; transformaton; estmaton, relablty. SUMMARY Advances n technologes and

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

Inverse kinematic Modeling of 3RRR Parallel Robot

Inverse kinematic Modeling of 3RRR Parallel Robot ème Congrès Franças de Mécanque Lyon, 4 au 8 Août 5 Inverse knematc Modelng of RRR Parallel Robot Ouafae HAMDOUN, Fatma Zahra BAGHLI, Larb EL BAKKALI Modelng and Smulaton of Mechancal Systems Laboratory,

More information

Multi-objective optimization method for the ATO system using Cellular Automata

Multi-objective optimization method for the ATO system using Cellular Automata Computers n Ralways XI 173 Mult-objectve optmzaton method for the ATO system usng Cellular Automata J. Xun, B. Nng & K. P. L The Key State Laboratory of Ral Traffc Control and Safety, Bejng Jaotong Unversty,

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

The Shortest Path of Touring Lines given in the Plane

The Shortest Path of Touring Lines given in the Plane Send Orders for Reprnts to reprnts@benthamscence.ae 262 The Open Cybernetcs & Systemcs Journal, 2015, 9, 262-267 The Shortest Path of Tourng Lnes gven n the Plane Open Access Ljuan Wang 1,2, Dandan He

More information

F Geometric Mean Graphs

F Geometric Mean Graphs Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 2 (December 2015), pp. 937-952 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) F Geometrc Mean Graphs A.

More information

K-means and Hierarchical Clustering

K-means and Hierarchical Clustering Note to other teachers and users of these sldes. Andrew would be delghted f you found ths source materal useful n gvng your own lectures. Feel free to use these sldes verbatm, or to modfy them to ft your

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

Classifier Selection Based on Data Complexity Measures *

Classifier Selection Based on Data Complexity Measures * Classfer Selecton Based on Data Complexty Measures * Edth Hernández-Reyes, J.A. Carrasco-Ochoa, and J.Fco. Martínez-Trndad Natonal Insttute for Astrophyscs, Optcs and Electroncs, Lus Enrque Erro No.1 Sta.

More information

Simulation of a Ship with Partially Filled Tanks Rolling in Waves by Applying Moving Particle Semi-Implicit Method

Simulation of a Ship with Partially Filled Tanks Rolling in Waves by Applying Moving Particle Semi-Implicit Method Smulaton of a Shp wth Partally Flled Tanks Rollng n Waves by Applyng Movng Partcle Sem-Implct Method Jen-Shang Kouh Department of Engneerng Scence and Ocean Engneerng, Natonal Tawan Unversty, Tape, Tawan,

More information

Edge Detection in Noisy Images Using the Support Vector Machines

Edge Detection in Noisy Images Using the Support Vector Machines Edge Detecton n Nosy Images Usng the Support Vector Machnes Hlaro Gómez-Moreno, Saturnno Maldonado-Bascón, Francsco López-Ferreras Sgnal Theory and Communcatons Department. Unversty of Alcalá Crta. Madrd-Barcelona

More information

A NOTE ON FUZZY CLOSURE OF A FUZZY SET

A NOTE ON FUZZY CLOSURE OF A FUZZY SET (JPMNT) Journal of Process Management New Technologes, Internatonal A NOTE ON FUZZY CLOSURE OF A FUZZY SET Bhmraj Basumatary Department of Mathematcal Scences, Bodoland Unversty, Kokrajhar, Assam, Inda,

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

Virtual Machine Migration based on Trust Measurement of Computer Node

Virtual Machine Migration based on Trust Measurement of Computer Node Appled Mechancs and Materals Onlne: 2014-04-04 ISSN: 1662-7482, Vols. 536-537, pp 678-682 do:10.4028/www.scentfc.net/amm.536-537.678 2014 Trans Tech Publcatons, Swtzerland Vrtual Machne Mgraton based on

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

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

Electrical analysis of light-weight, triangular weave reflector antennas

Electrical analysis of light-weight, triangular weave reflector antennas Electrcal analyss of lght-weght, trangular weave reflector antennas Knud Pontoppdan TICRA Laederstraede 34 DK-121 Copenhagen K Denmark Emal: kp@tcra.com INTRODUCTION The new lght-weght reflector antenna

More information

USING GRAPHING SKILLS

USING GRAPHING SKILLS Name: BOLOGY: Date: _ Class: USNG GRAPHNG SKLLS NTRODUCTON: Recorded data can be plotted on a graph. A graph s a pctoral representaton of nformaton recorded n a data table. t s used to show a relatonshp

More information

Design of Structure Optimization with APDL

Design of Structure Optimization with APDL Desgn of Structure Optmzaton wth APDL Yanyun School of Cvl Engneerng and Archtecture, East Chna Jaotong Unversty Nanchang 330013 Chna Abstract In ths paper, the desgn process of structure optmzaton wth

More information

DESIGN OF A HAPTIC DEVICE FOR EXCAVATOR EQUIPPED WITH CRUSHER

DESIGN OF A HAPTIC DEVICE FOR EXCAVATOR EQUIPPED WITH CRUSHER DESIGN OF A HAPTIC DEVICE FOR EXCAVATOR EQUIPPED WITH CRUSHER Kyeong Won Oh, Dongnam Km Korea Unversty, Graduate School 5Ga-1, Anam-Dong, Sungbuk-Gu, Seoul, Korea {locosk, smleast}@korea.ac.kr Jong-Hyup

More information

HEAD LEADING ALGORITHM FOR URBAN TRAFFIC MODELING

HEAD LEADING ALGORITHM FOR URBAN TRAFFIC MODELING HEAD LEADING ALGOITHM FO UBAN TAFFIC MODELING Davd Hartman Department of Computer Scence and Engneerng Unversty of West Bohema Unverztní 22, Plzeň, 360 14, Czech epublc Emal: tazman@kv.zcu.cz KEYWODS Smulaton,

More information

Load-Balanced Anycast Routing

Load-Balanced Anycast Routing Load-Balanced Anycast Routng Chng-Yu Ln, Jung-Hua Lo, and Sy-Yen Kuo Department of Electrcal Engneerng atonal Tawan Unversty, Tape, Tawan sykuo@cc.ee.ntu.edu.tw Abstract For fault-tolerance and load-balance

More information

FPGA-based implementation of circular interpolation

FPGA-based implementation of circular interpolation Avalable onlne www.jocpr.com Journal of Chemcal and Pharmaceutcal Research, 04, 6(7):585-593 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 FPGA-based mplementaton of crcular nterpolaton Mngyu Gao,

More information

3D Geo-Network for Agent-based Building Evacuation Simulation

3D Geo-Network for Agent-based Building Evacuation Simulation Chapter 18 3D Geo-Network for Agent-based Buldng Evacuaton Smulaton Jnmu Cho and Jyeong Lee Abstract. Ths paper dscusses 3D geometrc network extracton for buldng evacuaton smulaton wth an agent-based model.

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

Quality Improvement Algorithm for Tetrahedral Mesh Based on Optimal Delaunay Triangulation

Quality Improvement Algorithm for Tetrahedral Mesh Based on Optimal Delaunay Triangulation Intellgent Informaton Management, 013, 5, 191-195 Publshed Onlne November 013 (http://www.scrp.org/journal/m) http://dx.do.org/10.36/m.013.5601 Qualty Improvement Algorthm for Tetrahedral Mesh Based on

More information

MobileGrid: Capacity-aware Topology Control in Mobile Ad Hoc Networks

MobileGrid: Capacity-aware Topology Control in Mobile Ad Hoc Networks MobleGrd: Capacty-aware Topology Control n Moble Ad Hoc Networks Jle Lu, Baochun L Department of Electrcal and Computer Engneerng Unversty of Toronto {jenne,bl}@eecg.toronto.edu Abstract Snce wreless moble

More information

XV International PhD Workshop OWD 2013, October Machine Learning for the Efficient Control of a Multi-Wheeled Mobile Robot

XV International PhD Workshop OWD 2013, October Machine Learning for the Efficient Control of a Multi-Wheeled Mobile Robot XV Internatonal PhD Workshop OWD 203, 9 22 October 203 Machne Learnng for the Effcent Control of a Mult-Wheeled Moble Robot Uladzmr Dzomn, Brest State Techncal Unversty (prof. Vladmr Golovko, Brest State

More information

Calculation of Sound Ray s Trajectories by the Method of Analogy to Mechanics at Ocean

Calculation of Sound Ray s Trajectories by the Method of Analogy to Mechanics at Ocean Open Journal of Acoustcs, 3, 3, -6 http://dx.do.org/.436/oja.3.3 Publshed Onlne March 3 (http://www.scrp.org/journal/oja) Calculaton of Sound Ray s Trajectores by the Method of Analogy to Mechancs at Ocean

More information

A Clustering Algorithm Solution to the Collaborative Filtering

A Clustering Algorithm Solution to the Collaborative Filtering Internatonal Journal of Scence Vol.4 No.8 017 ISSN: 1813-4890 A Clusterng Algorthm Soluton to the Collaboratve Flterng Yongl Yang 1, a, Fe Xue, b, Yongquan Ca 1, c Zhenhu Nng 1, d,* Hafeng Lu 3, e 1 Faculty

More information

The Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique

The Greedy Method. Outline and Reading. Change Money Problem. Greedy Algorithms. Applications of the Greedy Strategy. The Greedy Method Technique //00 :0 AM Outlne and Readng The Greedy Method The Greedy Method Technque (secton.) Fractonal Knapsack Problem (secton..) Task Schedulng (secton..) Mnmum Spannng Trees (secton.) Change Money Problem Greedy

More information

Reducing Frame Rate for Object Tracking

Reducing Frame Rate for Object Tracking Reducng Frame Rate for Object Trackng Pavel Korshunov 1 and We Tsang Oo 2 1 Natonal Unversty of Sngapore, Sngapore 11977, pavelkor@comp.nus.edu.sg 2 Natonal Unversty of Sngapore, Sngapore 11977, oowt@comp.nus.edu.sg

More information

Empirical Distributions of Parameter Estimates. in Binary Logistic Regression Using Bootstrap

Empirical Distributions of Parameter Estimates. in Binary Logistic Regression Using Bootstrap Int. Journal of Math. Analyss, Vol. 8, 4, no. 5, 7-7 HIKARI Ltd, www.m-hkar.com http://dx.do.org/.988/jma.4.494 Emprcal Dstrbutons of Parameter Estmates n Bnary Logstc Regresson Usng Bootstrap Anwar Ftranto*

More information

Lecture 15: Memory Hierarchy Optimizations. I. Caches: A Quick Review II. Iteration Space & Loop Transformations III.

Lecture 15: Memory Hierarchy Optimizations. I. Caches: A Quick Review II. Iteration Space & Loop Transformations III. Lecture 15: Memory Herarchy Optmzatons I. Caches: A Quck Revew II. Iteraton Space & Loop Transformatons III. Types of Reuse ALSU 7.4.2-7.4.3, 11.2-11.5.1 15-745: Memory Herarchy Optmzatons Phllp B. Gbbons

More information

Air Transport Demand. Ta-Hui Yang Associate Professor Department of Logistics Management National Kaohsiung First Univ. of Sci. & Tech.

Air Transport Demand. Ta-Hui Yang Associate Professor Department of Logistics Management National Kaohsiung First Univ. of Sci. & Tech. Ar Transport Demand Ta-Hu Yang Assocate Professor Department of Logstcs Management Natonal Kaohsung Frst Unv. of Sc. & Tech. 1 Ar Transport Demand Demand for ar transport between two ctes or two regons

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

Machine Learning 9. week

Machine Learning 9. week Machne Learnng 9. week Mappng Concept Radal Bass Functons (RBF) RBF Networks 1 Mappng It s probably the best scenaro for the classfcaton of two dataset s to separate them lnearly. As you see n the below

More information

Intro. Iterators. 1. Access

Intro. Iterators. 1. Access Intro Ths mornng I d lke to talk a lttle bt about s and s. We wll start out wth smlartes and dfferences, then we wll see how to draw them n envronment dagrams, and we wll fnsh wth some examples. Happy

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

Parallelism for Nested Loops with Non-uniform and Flow Dependences

Parallelism for Nested Loops with Non-uniform and Flow Dependences Parallelsm for Nested Loops wth Non-unform and Flow Dependences Sam-Jn Jeong Dept. of Informaton & Communcaton Engneerng, Cheonan Unversty, 5, Anseo-dong, Cheonan, Chungnam, 330-80, Korea. seong@cheonan.ac.kr

More information

Determining the Optimal Bandwidth Based on Multi-criterion Fusion

Determining the Optimal Bandwidth Based on Multi-criterion Fusion Proceedngs of 01 4th Internatonal Conference on Machne Learnng and Computng IPCSIT vol. 5 (01) (01) IACSIT Press, Sngapore Determnng the Optmal Bandwdth Based on Mult-crteron Fuson Ha-L Lang 1+, Xan-Mn

More information

Parallel manipulator robots design and simulation

Parallel manipulator robots design and simulation Proceedngs of the 5th WSEAS Int. Conf. on System Scence and Smulaton n Engneerng, Tenerfe, Canary Islands, Span, December 16-18, 26 358 Parallel manpulator robots desgn and smulaton SAMIR LAHOUAR SAID

More information

Related-Mode Attacks on CTR Encryption Mode

Related-Mode Attacks on CTR Encryption Mode Internatonal Journal of Network Securty, Vol.4, No.3, PP.282 287, May 2007 282 Related-Mode Attacks on CTR Encrypton Mode Dayn Wang, Dongda Ln, and Wenlng Wu (Correspondng author: Dayn Wang) Key Laboratory

More information

A New Approach For the Ranking of Fuzzy Sets With Different Heights

A New Approach For the Ranking of Fuzzy Sets With Different Heights New pproach For the ankng of Fuzzy Sets Wth Dfferent Heghts Pushpnder Sngh School of Mathematcs Computer pplcatons Thapar Unversty, Patala-7 00 Inda pushpndersnl@gmalcom STCT ankng of fuzzy sets plays

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

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

The Research of Ellipse Parameter Fitting Algorithm of Ultrasonic Imaging Logging in the Casing Hole

The Research of Ellipse Parameter Fitting Algorithm of Ultrasonic Imaging Logging in the Casing Hole Appled Mathematcs, 04, 5, 37-3 Publshed Onlne May 04 n ScRes. http://www.scrp.org/journal/am http://dx.do.org/0.436/am.04.584 The Research of Ellpse Parameter Fttng Algorthm of Ultrasonc Imagng Loggng

More information

Analysis of 3D Cracks in an Arbitrary Geometry with Weld Residual Stress

Analysis of 3D Cracks in an Arbitrary Geometry with Weld Residual Stress Analyss of 3D Cracks n an Arbtrary Geometry wth Weld Resdual Stress Greg Thorwald, Ph.D. Ted L. Anderson, Ph.D. Structural Relablty Technology, Boulder, CO Abstract Materals contanng flaws lke nclusons

More information

Sequential search. Building Java Programs Chapter 13. Sequential search. Sequential search

Sequential search. Building Java Programs Chapter 13. Sequential search. Sequential search Sequental search Buldng Java Programs Chapter 13 Searchng and Sortng sequental search: Locates a target value n an array/lst by examnng each element from start to fnsh. How many elements wll t need to

More information

Modeling Concave Globoidal Cam with Swinging Roller Follower: A Case Study

Modeling Concave Globoidal Cam with Swinging Roller Follower: A Case Study Modelng Concave Globodal Cam wth Swngng Roller Follower: A Case Study Nguyen Van Tuong, and Premysl Pokorny Abstract Ths paper descrbes a computer-aded desgn for desgn of the concave globodal cam wth cylndrcal

More information

Type-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data

Type-2 Fuzzy Non-uniform Rational B-spline Model with Type-2 Fuzzy Data Malaysan Journal of Mathematcal Scences 11(S) Aprl : 35 46 (2017) Specal Issue: The 2nd Internatonal Conference and Workshop on Mathematcal Analyss (ICWOMA 2016) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES

More information

Scheduling Remote Access to Scientific Instruments in Cyberinfrastructure for Education and Research

Scheduling Remote Access to Scientific Instruments in Cyberinfrastructure for Education and Research Schedulng Remote Access to Scentfc Instruments n Cybernfrastructure for Educaton and Research Je Yn 1, Junwe Cao 2,3,*, Yuexuan Wang 4, Lanchen Lu 1,3 and Cheng Wu 1,3 1 Natonal CIMS Engneerng and Research

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

An Obstacle Based Realistic Ad-Hoc Mobility Model for Social Networks

An Obstacle Based Realistic Ad-Hoc Mobility Model for Social Networks JOURNAL OF NETWORKS, VOL. 1, NO. 2, JUNE 2006 37 An Obstacle Based Realstc Ad-Hoc Moblty Model for Socal Networks P. Venkateswaran Dept. of Electroncs & Tele-Communcaton Engneerng Jadavpur Unversty, Kolkata

More information