Cable optimization of a long span cable stayed bridge in La Coruña (Spain)

Size: px
Start display at page:

Download "Cable optimization of a long span cable stayed bridge in La Coruña (Spain)"

Transcription

1 Computer Aded Optmum Desgn n Engneerng XI 107 Cable optmzaton of a long span cable stayed brdge n La Coruña (Span) A. Baldomr & S. Hernández School of Cvl Engneerng, Unversty of Coruña, La Coruña, Span Abstract Ths document descrbes an optmzaton problem of cable cross secton of a cable stayed brdge consderng constrants of cable stress and deck dsplacement. Snce the brdge s stll n study phase, the geometry and the mechancal characterstcs are subjected to changes. In order to avod creatng dfferent structural models, a program was produced to construct a model from geometrcal and mechancal data and resolve optmzaton problem. At the end of the document, two examples are presented to show how ths program works. Keywords: optmzaton, cable stayed brdges, cvl engneerng. 1 Introducton The optmzaton technques are not commonly employed n professonal lfe n cvl engneerng, specfcally n the area of structural calculaton, and the majorty of consultng frms do not apply these technques to ther desgns. Nevertheless, n the desgn of great structures, these technques are ganng more mportance due to ther mpact on reducton n materal cost. The presented work comes from the general study of traffc systems around A Coruña, n partcular, the connecton of the lttoral area of Oleros and Sada to the cty. After analyzng traffc n dfferent roads, ther ntensty, and future projects of hub connectons, t was concluded that t would be necessary to construct a new road to be able to effcently releve heavy traffc. The new connecton requres a constructon of a brdge over the Coruña estuary, whch s the most mportant part of the road. Then a study was conducted on the brdge typology that fts the best to the techncal, envronmental, and aesthetc condtons of the area. After consderng dfferent proposals, the typology of cable stayed brdge was found to be the most adequate. do: /op090101

2 108 Computer Aded Optmum Desgn n Engneerng XI Cable stayed brdges are used more and more to overcome long spans and there already exsts one wth one klometer of span length [1]. The reasons to use such typology are for ts good structural functonalty, vsual lghtness, great aesthetc component, and ts low mpact on the envronment, whch was the key ssue at the locaton of the brdge over the Coruña estuary. The work presented n ths document takes part n the project from ths pont, and optmzaton of the cable cross secton of the cable stayed brdge s developed. 2 Brdge descrpton and structural model After the study the road soluton consders the constructon of a cable stayed brdge of 1198 m of total length whch s dvded nto two lateral spans of 270 m and the man span of 658 m. Fgure 1: Sde vew of the brdge. The man elements that compose the brdge are: Deck: made of steel wth an aerodynamc secton of 3 m of heght and 34 meter of wdth, whch permts a confguraton of 3 lanes n each drecton. The dfference n heght between two end ponts s 15 m. Towers: the brdge has two towers: each fxed n the foundaton wth two twn concrete pers separated by the deck wdth as shown n Fgure 3. From the deck two steel masts come out n the form of λ unted by transversal bracng and ther upper part contnue as a sngle vertcal mast. The cables are anchored to ths part of the tower. Moreover, there are other transversal bracng at the lowest part of the vertcal mast to avod bucklng problem. Cables: the brdge deck s sustaned by 80 par of cables that connect to the towers. The cable confguraton s hybrd of harp and fan. Fgure 2: Cross secton of the deck. The optmzaton process of the cables requres successve structural analyss of the brdge. A fnte element model wth beam elements was generated n ABAQUS code [2]. As wll be seen later, ths model s not fxed, but parameterzed for avodng to remodel due to eventual changes n the brdge desgn.

3 Computer Aded Optmum Desgn n Engneerng XI 109 Bastaguero Tower Oza Tower Fgure 3: Tower detals. Fgure 4: Vsualzaton of the new brdge over the Coruña estuary. Fgure 5: Structural model of the brdge.

4 110 Computer Aded Optmum Desgn n Engneerng XI To model the structure, 3D beam element, B31 s used wth ts rotatons released at the beam ends for the cables. The materal utlzed s steel for the deck and the masts of the towers, and concrete for the lower part of the towers. A lnear elastc model s consdered wth sotropc character for Young s module and Posson s rato. 3 Formulaton of optmzaton problem The objectve of ths work s: to create a program that s able to generate a generc fnte element model of a cable stayed brdge (accordng to the structural scheme proposed n the prevous secton), to be calculated n ABAQUS, and from the data obtaned n ths calculaton, to perform optmzaton process on the cable cross sectonal area. The optmzaton problem s defned by the followng elements [3 4]: Desgn varables The desgn varables are each of the cable cross sectonal areas. The number of desgn varable s reduced to half of the number of cables due to symmetry about the longtudnal plane; however, t s not symmetrcal about the perpendcular plane. For better performance of the optmzaton process, the nverse of the areas are used to lnearze the stress constrants of the cables. x = 1/ A = 1,,n From now on, we call n total number of desgn varables. Desgn constrants Three types of desgn constrants were taken nto account: 1. Stress constrants of the cables k σ ( ) σ = 1,,n k=1,,lc x M where: σ k ( x ) : normal tensle stress n the cable, for the load case, k σ : maxmum allowable normal tensle stress n the cables M LC : total number of load cases 2. Dsplacement constrants of the deck w k ( x ) w = 2,,n-1 k=1,,lc max where: w k ( x ): deck dsplacement at the cable poston for the load case k. w : maxmum allowable dsplacement (postve value) max 3. Dsplacement constrants of towers n the longtudnal drecton

5 Computer Aded Optmum Desgn n Engneerng XI 111 u k Towerj u j = 1,2 k=1,,lc max u : dsplacement n x drecton at the top of the tower j for k Towerj the load case k. u : maxmum dsplacement n x drecton at the top of the tower max (postve value). Objectve functon F(X) The objectve of optmzaton n ths case s to reduce the quantty of steel for the cables. Thus the objectve functon s expressed as: n 1 mn F = 2 L x where: L : cable length As we can see, ths s an optmzaton problem wth n desgn varables, 2n x LC nequalty constrants, and an objectve functon. 4 Program descrpton The resoluton of the problem formulated prevously s carred out by a man program created n MATLAB [5] and the use of software ABAQUS for the structural calculaton. Ths program bascally conssts of three parts: 1. Generaton of fnte element models. 2. Calculaton of ntal stresses n the cables for the self weght. 3. Optmzaton of the cable sectons accordng to the establshed load hypotheses. 4.1 Generaton of structural model In ths part of the program, we assgn dmensons, mechancal characterstcs, and dscretzaton for each of the elements that compose the structural model. Ths part of program conssts of three subroutnes, nputtablero, nputtorres and nputcables whch are n charge of wrtng Abaqus code accordng to the data provded ntally. Intal values of desgn varables are assgned to each cable secton n the program. 4.2 Intal tenson force n the cable The constructon of the brdge s executed by balanced cantlever from each of the towers. The constrant to be satsfed n each phase of the process s the dsplacement of the deck where cables are attached should be null. Therefore, = 1

6 112 Computer Aded Optmum Desgn n Engneerng XI just before placng the last center deck secton, the brdge should have zero dsplacement, and after the last deck secton s placed, statc analyss calculaton should show only slght axal forces n such deck secton. If the calculaton of ntal tenson wth the complete model was carred out, ths last deck secton would have axal forces above the actual ones. Therefore the calculaton of ntal tenson s carred out on the brdge wth ts sectons wthout jonng and enterng the weght of ths last deck secton. Fgure 6: Structural model to obtan the ntal tenson forces. These stresses are calculated as follows: 1. Deck dsplacement s calculated where cables are attached to the deck, whch s produced by self-weght wthout ntal stresses n the cables. 2. A unt force s appled to the frst par of cables and dsplacement s obtaned at each pont of the deck. Ths operaton s repeated for the rest of the cable pars. 3. Intal tenson forces are obtaned by resolvng the followng system of lnear equatons: w pp j n + P w = 0 j = 1,,n j = 1 pp w : deck dsplacement j due to the self-weght load j P : ntal tenson force n the cable par, w : deck dsplacement at poston, j due to the tenson force of the j cable par, 4.3 Optmzaton The optmzaton process s carred out usng an optmzaton module mplemented n MATLAB. The functon to perform ths process s called fmncon that mnmzes functons wth varous varables subject to nequalty constrants. Ths optmzaton subroutne requres certan nput values such as desgn varables, constrants, and an objectve functon. For obtanng better results, t

7 Computer Aded Optmum Desgn n Engneerng XI 113 also provdes gradents of the objectve functon and the desgn constrants. Those gradents are calculated by fnte dfference, the most costly part of the program. Fgure 7: Flow chart of optmzaton process. 5 Applcaton examples The frst example we present s a fcttous case of a brdge wth the same longtudnal profle as the ntal brdge descrbed n secton 2, but wth notceably reduced number of desgn varables (n=8). The second example shows the soluton obtaned for the brdge confguraton descrbed at the begnnng of the document. The number of varables n ths case s much greater than the prevous example (n=80). In both examples the optmzaton of the cable s performed for three smple load cases as: Overload of use, 4 KN/m 2 on the left lateral span Overload of use, 4 KN/m 2 on the man span Overload of use, 4 KN/m 2 on the rght lateral span

8 114 Computer Aded Optmum Desgn n Engneerng XI Obvously those load cases are not determnant for the lmt state defned n the regulaton, however, they serve to verfy the program performance. The ntroducton of new load cases n the program does not present any dffculty snce these cases smply need to be entered n the subroutne, casos_carga. 5.1 Brdge wth 16 cables Fgure 8: Structural model (16 cables). Desgn varables The desgn varables are the nverse of the areas of eght cables n the model. We use 0.1m 2 for the ntal value of the area. 0 x 1 1 = = = 10 = 1,,8 () A cable Desgn constrants The desgn constrants consdered for ths example are summarzed n the followng equatons: k KN σ ( x ) m = 1,,8 k=1,2,3 k L1 k L w ( x ) = 2 k=1,2,3; 2 w ( x ) = 3,, k=1,2,3 k L H 3 k j w ( x ) = 7 k=1,2,3; u Tower j =1, 2 j k=1,2,3 where L1, L2 and L3 are the length of the left span, man span, and rght span respectvely and H1 and H2, the tower heght. The dmensons are all n meter. Objectve functon The objectve functon s the total volume of steel cables that we ntend to mnmze. 8 1 F = 2 L = 1 x The optmzaton process converges after 28 teratons gvng results shown n fgure 10 to 12.

9 Computer Aded Optmum Desgn n Engneerng XI 115 Area (m 2 ) Iteraton Cable 1 Cable2 Cable3 Cable4 Cable5 Cable6 Cable7 Cable8 Fgure 9: Evoluton of the cable areas. Cable Intal Area Optmal area Area (m 2 ) Cable Fgure 10: Dstrbuton of cable area Volume (m 3 ) Iteraton Fgure 11: Evoluton of the objectve functon. The optmzaton results lead to larger area for cables attached to both ends of the deck just as occurs n the desgn of cable stayed brdges. Those cables are the ones that brace the towers. Lkewse, the cables close to the center of the man span have a cross secton larger than the rest, whch can be observed n dmensonng of those brdges due to lmtng the deck deflecton. In regard to the objectve functon, we can observe that the ntal model has nsuffcent volume movng from 400m 3 to a value close to 900 m 3. Obvously these results do not correspond to any real cases snce brdges are never desgned

10 116 Computer Aded Optmum Desgn n Engneerng XI wth such small number of cables. We smply want to see the program performance. After the optmzaton, we checked to see f all the desgn constrants are satsfed. The dsplacement constrant n the man span s actve for the overload case on ths secton as well as the stress n the cables adjacent to those wth the largest secton. None of the constrants are volated. 5.2 Brdge wth 160 cables Ths example corresponds to the structural model descrbed at the begnnng of the document. Fgure 12: Structural model (160 cables). Area (m 2 ) Iteraton Fgure 13: Evoluton of the cross sectons.

11 Computer Aded Optmum Desgn n Engneerng XI 117 Area (m 2 ) Cable Fgure 14: Dstrbuton of areas. Area (m 2 ) Iteraton Fgure 15: Evoluton of the objectve functon. Its geometrcal and mechancal characterstcs are dentcal to that of example 1 and t dffers only for the number of cables and ther locatons. Fgure 13 shows the evoluton of the cable areas durng 69 teratons startng from an ntal area of 0.1 m 2. It s dfferent from the other model n terms that the cables at the extreme ends of the brdge have areas much larger than the rest, and two cables close to the center of the man span have approxmately half of that value. Fgure 14 shows the area of each 80 cables after the optmzaton to gve an dea of area dstrbuton along the brdge. Snce the constrants are not volated n any moment, the desgn requrements are satsfed. The most lmtng constrant s the dsplacement at the center of the man span for the dstrbuted load on that span. Although the stress constrants are not actve, some cables have the value close to the mposed lmt.

12 118 Computer Aded Optmum Desgn n Engneerng XI Obvously we cannot assure that ths optmum soluton s unque, and there can be other local mnmums. Nevertheless, the optmzaton proves to be useful to gve more effcent desgn than that obtaned by heurstc rules. 6 Conclusons In ths work, we have presented the results obtaned from a study on the optmzaton of cable cross secton of a cable stayed brdge. Some conclusons can be drawn from the results: 1. Due to hgh degrees of ndetermnacy of ths type of structure, the optmzaton process s not monotonous presentng dscontnutes n the desgn varables as well as n the objectve functon. A small modfcaton n the desgn varables can affect the fulfllment of constrants far away from the locaton where the changes are produced. 2. We can check the results obtaned n the optmzaton a posteror by a fnte element model. As shown n the examples, we can make sure that the results obtaned satsfy the mposed requrements. 3. The program provdes an dea to a desgn engneer how much cross sectonal area s necessary for each cable under certan stress and dsplacement constrants. Snce these values are not ntutve a pror at all, they serve as a desgn tool. 4. The dstrbuton of optmzed cable cross secton along the brdge agrees wth that of actual cable stayed brdges [6]. 5. After the optmzaton process, t can be observed that the areas of cables attached to the extreme ends of the deck are much larger than the rest of the cables. Those cables serve to mprove the longtudnal bracng of the towers and at the same tme they have an mportant nfluence for vertcal deck dsplacements. 6. The cross secton of the cables located close to the center of the man span have larger area than the rest other than those at the extreme ends, due to fulfllng the deck dsplacement constrants. 7. The optmzaton process provdes a result where the objectve functon has a mnmum (local mnmum), however, t does not guarantee that t s the best soluton among all the possble ones (global maxmum). Nevertheless as long as we acheve to reduce the steel volume n comparson to other conventonal technques, the optmzaton proves to be very useful to reduce materal cost. 8. The developed program permts changes on the fnte element model (geometry, mechancal propertes, boundary condton, etc) n a smple way. Besdes t permts to nclude load hypotheses wthn the optmzaton process whenever one s wllng to pay the much hgher computatonal cost. Ths cost s manly due to obtanng the gradents of desgn constrants. The conclusons drawn here on dmensonng of the cables comply exclusvely wth the terms n whch the optmzaton process s defned. Ths study can be developed amply from many ponts of vew such as:

13 Computer Aded Optmum Desgn n Engneerng XI Includng geometry optmzaton to obtan optmum cable postonng on the deck 2. Includng other structural elements such as the deck, towers, etc as desgn varables. 3. Consderng other types of analyss n optmzaton such as bucklng, vbraton, dynamc analyss, etc. 4. Possblty of employng other types of optmzaton algorthms to acheve faster convergence References [1] N.J. GIMSING. Cable Supported Brdges. J. Wley and Sons, Second Edton [2] ABAQUS 6.8 Documentaton. [3] HERNÁNDEZ, S., Métodos de Dseño Óptmo de Estructuras. [4] JASBIR S. ARORA, Introducton to Optmum Desgn, Second Edton, [5] MATLAB Documentaton. [6] Honshu-Shkoku Brdge Authorty, Japan. The Tatara Brdge. Desgn and Constructon Technology for the World s Longest Cable-Stayed Brdge

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

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

GSLM Operations Research II Fall 13/14

GSLM Operations Research II Fall 13/14 GSLM 58 Operatons Research II Fall /4 6. Separable Programmng Consder a general NLP mn f(x) s.t. g j (x) b j j =. m. Defnton 6.. The NLP s a separable program f ts objectve functon and all constrants are

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

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

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

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

Shape Optimization of Shear-type Hysteretic Steel Damper for Building Frames using FEM-Analysis and Heuristic Approach

Shape Optimization of Shear-type Hysteretic Steel Damper for Building Frames using FEM-Analysis and Heuristic Approach The Seventh Chna-Japan-Korea Jont Symposum on Optmzaton of Structural and Mechancal Systems Huangshan, June, 18-21, 2012, Chna Shape Optmzaton of Shear-type Hysteretc Steel Damper for Buldng Frames usng

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

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

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

Structural Optimization Using OPTIMIZER Program

Structural Optimization Using OPTIMIZER Program SprngerLnk - Book Chapter http://www.sprngerlnk.com/content/m28478j4372qh274/?prnt=true ق.ظ 1 of 2 2009/03/12 11:30 Book Chapter large verson Structural Optmzaton Usng OPTIMIZER Program Book III European

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

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

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

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

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

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

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

BOTTOM STRUCTURE FOR DutchEVO CAR: FORMULATION OF THE PROBLEM AND THE ADJUSTMENT OF THE OPTIMIZATION SYSTEM

BOTTOM STRUCTURE FOR DutchEVO CAR: FORMULATION OF THE PROBLEM AND THE ADJUSTMENT OF THE OPTIMIZATION SYSTEM INTERNATIONAL DESIGN CONFERENCE - DESIGN 2002 Dubrovn, May 14-17, 2002. BOTTOM STRUCTURE FOR DutchEVO CAR: FORMULATION OF THE PROBLEM AND THE ADJUSTMENT OF THE OPTIMIZATION SYSTEM Natala S. Ermolaeva,

More information

CHAPTER 2 PROPOSED IMPROVED PARTICLE SWARM OPTIMIZATION

CHAPTER 2 PROPOSED IMPROVED PARTICLE SWARM OPTIMIZATION 24 CHAPTER 2 PROPOSED IMPROVED PARTICLE SWARM OPTIMIZATION The present chapter proposes an IPSO approach for multprocessor task schedulng problem wth two classfcatons, namely, statc ndependent tasks and

More information

Positive Semi-definite Programming Localization in Wireless Sensor Networks

Positive Semi-definite Programming Localization in Wireless Sensor Networks Postve Sem-defnte Programmng Localzaton n Wreless Sensor etworks Shengdong Xe 1,, Jn Wang, Aqun Hu 1, Yunl Gu, Jang Xu, 1 School of Informaton Scence and Engneerng, Southeast Unversty, 10096, anjng Computer

More information

Kinematics of pantograph masts

Kinematics of pantograph masts Abstract Spacecraft Mechansms Group, ISRO Satellte Centre, Arport Road, Bangalore 560 07, Emal:bpn@sac.ernet.n Flght Dynamcs Dvson, ISRO Satellte Centre, Arport Road, Bangalore 560 07 Emal:pandyan@sac.ernet.n

More information

Analysis of Continuous Beams in General

Analysis of Continuous Beams in General Analyss of Contnuous Beams n General Contnuous beams consdered here are prsmatc, rgdly connected to each beam segment and supported at varous ponts along the beam. onts are selected at ponts of support,

More information

Topology optimization considering the requirements of deep-drawn sheet metals

Topology optimization considering the requirements of deep-drawn sheet metals th World Congress on Structural and Multdscplnary Optmsaton 7 th - th, June 5, Sydney Australa Topology optmzaton consderng the requrements of deep-drawn sheet metals Robert Denemann, Axel Schumacher,

More information

WORKSPACE OPTIMIZATION OF ORIENTATIONAL 3-LEGGED UPS PARALLEL PLATFORMS

WORKSPACE OPTIMIZATION OF ORIENTATIONAL 3-LEGGED UPS PARALLEL PLATFORMS Proceedngs of DETC 02 ASME 2002 Desgn Engneerng Techncal Conferences and Computers and Informaton n Engneerng Conference Montreal, Canada, September 29-October 2, 2002 DETC2002/MECH-34366 WORKSPACE OPTIMIZATION

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

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

陳申岳 S-Y. Chen, 2007, Gradient-Based Structural and CFD Global Shape Optimization with SmartDO and the Response Smoothing Technology, Proceeding of

陳申岳 S-Y. Chen, 2007, Gradient-Based Structural and CFD Global Shape Optimization with SmartDO and the Response Smoothing Technology, Proceeding of 陳申岳 S-Y. Chen, 2007, Gradent-Based Structural and CFD Global Shape Optmzaton wth SmartDO and the Response Smoothng Technology, Proceedng of the 7 th World Congress of Structural and Multdscplnary Optmzaton

More information

CS 534: Computer Vision Model Fitting

CS 534: Computer Vision Model Fitting CS 534: Computer Vson Model Fttng Sprng 004 Ahmed Elgammal Dept of Computer Scence CS 534 Model Fttng - 1 Outlnes Model fttng s mportant Least-squares fttng Maxmum lkelhood estmaton MAP estmaton Robust

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

Unsupervised Learning

Unsupervised Learning Pattern Recognton Lecture 8 Outlne Introducton Unsupervsed Learnng Parametrc VS Non-Parametrc Approach Mxture of Denstes Maxmum-Lkelhood Estmates Clusterng Prof. Danel Yeung School of Computer Scence and

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

Springback Reduction in Stamping of Front Side Member with a Response Surface Method

Springback Reduction in Stamping of Front Side Member with a Response Surface Method Sprngback Reducton n Stampng of Front Sde Member wth a Response Surface Method Jung-Han Song *, Hoon Huh *, Se-Ho Km **, Sung-Ho Park *** * Department of Mechancal Engneerng, Korea Advanced Insttute of

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

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

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

Investigations of Topology and Shape of Multi-material Optimum Design of Structures

Investigations of Topology and Shape of Multi-material Optimum Design of Structures Advanced Scence and Tecnology Letters Vol.141 (GST 2016), pp.241-245 ttp://dx.do.org/10.14257/astl.2016.141.52 Investgatons of Topology and Sape of Mult-materal Optmum Desgn of Structures Quoc Hoan Doan

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

Vibration Characteristic Analysis of Axial Fan Shell Based on ANSYS Workbench

Vibration Characteristic Analysis of Axial Fan Shell Based on ANSYS Workbench Internatonal Conference on Logstcs Engneerng, Management and Computer Scence (LEMCS 2015) Vbraton Characterstc Analyss of Axal Fan Shell Based on ANSYS Workbench Lchun Gu College of Mechancal and Electrcal

More information

ON THE DESIGN OF LARGE SCALE REDUNDANT PARALLEL MANIPULATOR. Wu huapeng, Heikki handroos and Juha kilkki

ON THE DESIGN OF LARGE SCALE REDUNDANT PARALLEL MANIPULATOR. Wu huapeng, Heikki handroos and Juha kilkki ON THE DESIGN OF LARGE SCALE REDUNDANT PARALLEL MANIPULATOR Wu huapeng, Hekk handroos and Juha klkk Machne Automaton Lab, Lappeenranta Unversty of Technology LPR-5385 Fnland huapeng@lut.f, handroos@lut.f,

More information

Biostatistics 615/815

Biostatistics 615/815 The E-M Algorthm Bostatstcs 615/815 Lecture 17 Last Lecture: The Smplex Method General method for optmzaton Makes few assumptons about functon Crawls towards mnmum Some recommendatons Multple startng ponts

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

Outline. Type of Machine Learning. Examples of Application. Unsupervised Learning

Outline. Type of Machine Learning. Examples of Application. Unsupervised Learning Outlne Artfcal Intellgence and ts applcatons Lecture 8 Unsupervsed Learnng Professor Danel Yeung danyeung@eee.org Dr. Patrck Chan patrckchan@eee.org South Chna Unversty of Technology, Chna Introducton

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

TPL-Aware Displacement-driven Detailed Placement Refinement with Coloring Constraints

TPL-Aware Displacement-driven Detailed Placement Refinement with Coloring Constraints TPL-ware Dsplacement-drven Detaled Placement Refnement wth Colorng Constrants Tao Ln Iowa State Unversty tln@astate.edu Chrs Chu Iowa State Unversty cnchu@astate.edu BSTRCT To mnmze the effect of process

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

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

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

Repeater Insertion for Two-Terminal Nets in Three-Dimensional Integrated Circuits

Repeater Insertion for Two-Terminal Nets in Three-Dimensional Integrated Circuits Repeater Inserton for Two-Termnal Nets n Three-Dmensonal Integrated Crcuts Hu Xu, Vasls F. Pavlds, and Govann De Mchel LSI - EPFL, CH-5, Swtzerland, {hu.xu,vasleos.pavlds,govann.demchel}@epfl.ch Abstract.

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

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

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

Subspace clustering. Clustering. Fundamental to all clustering techniques is the choice of distance measure between data points;

Subspace clustering. Clustering. Fundamental to all clustering techniques is the choice of distance measure between data points; Subspace clusterng Clusterng Fundamental to all clusterng technques s the choce of dstance measure between data ponts; D q ( ) ( ) 2 x x = x x, j k = 1 k jk Squared Eucldean dstance Assumpton: All features

More information

A Facet Generation Procedure. for solving 0/1 integer programs

A Facet Generation Procedure. for solving 0/1 integer programs A Facet Generaton Procedure for solvng 0/ nteger programs by Gyana R. Parja IBM Corporaton, Poughkeepse, NY 260 Radu Gaddov Emery Worldwde Arlnes, Vandala, Oho 45377 and Wlbert E. Wlhelm Teas A&M Unversty,

More information

Multiobjective fuzzy optimization method

Multiobjective fuzzy optimization method Buletnul Ştnţfc al nverstăţ "Poltehnca" dn Tmşoara Sera ELECTRONICĂ ş TELECOMNICAŢII TRANSACTIONS on ELECTRONICS and COMMNICATIONS Tom 49(63, Fasccola, 24 Multobjectve fuzzy optmzaton method Gabrel Oltean

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

Module 6: FEM for Plates and Shells Lecture 6: Finite Element Analysis of Shell

Module 6: FEM for Plates and Shells Lecture 6: Finite Element Analysis of Shell Module 6: FEM for Plates and Shells Lecture 6: Fnte Element Analyss of Shell 3 6.6. Introducton A shell s a curved surface, whch by vrtue of ther shape can wthstand both membrane and bendng forces. A shell

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

A New Token Allocation Algorithm for TCP Traffic in Diffserv Network

A New Token Allocation Algorithm for TCP Traffic in Diffserv Network A New Token Allocaton Algorthm for TCP Traffc n Dffserv Network A New Token Allocaton Algorthm for TCP Traffc n Dffserv Network S. Sudha and N. Ammasagounden Natonal Insttute of Technology, Truchrappall,

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

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

UNIT 2 : INEQUALITIES AND CONVEX SETS

UNIT 2 : INEQUALITIES AND CONVEX SETS UNT 2 : NEQUALTES AND CONVEX SETS ' Structure 2. ntroducton Objectves, nequaltes and ther Graphs Convex Sets and ther Geometry Noton of Convex Sets Extreme Ponts of Convex Set Hyper Planes and Half Spaces

More information

LS-TaSC Version 2.1. Willem Roux Livermore Software Technology Corporation, Livermore, CA, USA. Abstract

LS-TaSC Version 2.1. Willem Roux Livermore Software Technology Corporation, Livermore, CA, USA. Abstract 12 th Internatonal LS-DYNA Users Conference Optmzaton(1) LS-TaSC Verson 2.1 Wllem Roux Lvermore Software Technology Corporaton, Lvermore, CA, USA Abstract Ths paper gves an overvew of LS-TaSC verson 2.1,

More information

Machine Learning: Algorithms and Applications

Machine Learning: Algorithms and Applications 14/05/1 Machne Learnng: Algorthms and Applcatons Florano Zn Free Unversty of Bozen-Bolzano Faculty of Computer Scence Academc Year 011-01 Lecture 10: 14 May 01 Unsupervsed Learnng cont Sldes courtesy of

More information

Topology Design using LS-TaSC Version 2 and LS-DYNA

Topology Design using LS-TaSC Version 2 and LS-DYNA Topology Desgn usng LS-TaSC Verson 2 and LS-DYNA Wllem Roux Lvermore Software Technology Corporaton, Lvermore, CA, USA Abstract Ths paper gves an overvew of LS-TaSC verson 2, a topology optmzaton tool

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

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

AP PHYSICS B 2008 SCORING GUIDELINES

AP PHYSICS B 2008 SCORING GUIDELINES AP PHYSICS B 2008 SCORING GUIDELINES General Notes About 2008 AP Physcs Scorng Gudelnes 1. The solutons contan the most common method of solvng the free-response questons and the allocaton of ponts for

More information

OPTIMIZATION OF SKELETAL STRUCTURES USING IMPROVED GENETIC ALGORITHM BASED ON PROPOSED SAMPLING SEARCH SPACE IDEA

OPTIMIZATION OF SKELETAL STRUCTURES USING IMPROVED GENETIC ALGORITHM BASED ON PROPOSED SAMPLING SEARCH SPACE IDEA INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING Int. J. Optm. Cvl Eng., 2018; 8(3): 415-432 OPTIMIZATION OF SKELETAL STRUCTURES USING IMPROVED GENETIC ALGORITHM BASED ON PROPOSED SAMPLING SEARCH

More information

A high precision collaborative vision measurement of gear chamfering profile

A high precision collaborative vision measurement of gear chamfering profile Internatonal Conference on Advances n Mechancal Engneerng and Industral Informatcs (AMEII 05) A hgh precson collaboratve vson measurement of gear chamferng profle Conglng Zhou, a, Zengpu Xu, b, Chunmng

More information

Computational layout design optimization of frame structures

Computational layout design optimization of frame structures Interfaces: archtecture.engneerng.scence 5-8th September, 017, Hamburg, Germany Annette Bögle, Manfred Grohmann (eds.) Computatonal layout desgn optmzaton of frame structures Jun Ye*, Paul Shepherd a,

More information

DESIGNING TRANSMISSION SCHEDULES FOR WIRELESS AD HOC NETWORKS TO MAXIMIZE NETWORK THROUGHPUT

DESIGNING TRANSMISSION SCHEDULES FOR WIRELESS AD HOC NETWORKS TO MAXIMIZE NETWORK THROUGHPUT DESIGNING TRANSMISSION SCHEDULES FOR WIRELESS AD HOC NETWORKS TO MAXIMIZE NETWORK THROUGHPUT Bran J. Wolf, Joseph L. Hammond, and Harlan B. Russell Dept. of Electrcal and Computer Engneerng, Clemson Unversty,

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

MULTISTAGE OPTIMIZATION OF AUTOMOTIVE CONTROL ARM THROUGH TOPOLOGY AND SHAPE OPTIMIZATION. 1 Duane Detwiler, 2 Emily Nutwell*, 2 Deepak Lokesha

MULTISTAGE OPTIMIZATION OF AUTOMOTIVE CONTROL ARM THROUGH TOPOLOGY AND SHAPE OPTIMIZATION. 1 Duane Detwiler, 2 Emily Nutwell*, 2 Deepak Lokesha 6 th BETA CAE Internatonal Conference MULTISTAGE OPTIMIZATION OF AUTOMOTIVE CONTROL ARM THROUGH TOPOLOGY AND SHAPE OPTIMIZATION. 1 Duane Detwler, 2 Emly Nutwell*, 2 Deepak Lokesha 1 Honda R&D Amercas,

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

AMath 483/583 Lecture 21 May 13, Notes: Notes: Jacobi iteration. Notes: Jacobi with OpenMP coarse grain

AMath 483/583 Lecture 21 May 13, Notes: Notes: Jacobi iteration. Notes: Jacobi with OpenMP coarse grain AMath 483/583 Lecture 21 May 13, 2011 Today: OpenMP and MPI versons of Jacob teraton Gauss-Sedel and SOR teratve methods Next week: More MPI Debuggng and totalvew GPU computng Read: Class notes and references

More information

THE design of mechanical systems exploits numerical

THE design of mechanical systems exploits numerical Symbolc Stffness Optmzaton of Planar Tensegrty Structures BRAM DE JAGER, * AND ROBERT E. SKELTON Department of Mechancal Engneerng, Technsche Unverstet Endhoven, P.O. Box 5, 56 MB, Endhoven, The Netherlands

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

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

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

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

Second Asian Symposium on Industrial Automation and Robotics BITEC, Bangkok, Thailand May 17-18, 2001

Second Asian Symposium on Industrial Automation and Robotics BITEC, Bangkok, Thailand May 17-18, 2001 Second Asan Symposum on Industral Automaton and Robotcs BITEC, Bangkok, Thaland May 7-8, 00 DEVELOPMENT OF DISASSEMBLY SUPPORT SYSTEM FOR MECHANICAL PARTS Ej ARAI, Hdefum WAKAMATSU, Akra TSUMAYA, Kech

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

Array transposition in CUDA shared memory

Array transposition in CUDA shared memory Array transposton n CUDA shared memory Mke Gles February 19, 2014 Abstract Ths short note s nspred by some code wrtten by Jeremy Appleyard for the transposton of data through shared memory. I had some

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

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

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

5 The Primal-Dual Method

5 The Primal-Dual Method 5 The Prmal-Dual Method Orgnally desgned as a method for solvng lnear programs, where t reduces weghted optmzaton problems to smpler combnatoral ones, the prmal-dual method (PDM) has receved much attenton

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

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

Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity

Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity Journal of Sgnal and Informaton Processng, 013, 4, 114-119 do:10.436/jsp.013.43b00 Publshed Onlne August 013 (http://www.scrp.org/journal/jsp) Corner-Based Image Algnment usng Pyramd Structure wth Gradent

More information

Step-3 New Harmony vector, improvised based on the following three mechanisms: (1) random selection, (2) memory consideration, and (3)

Step-3 New Harmony vector, improvised based on the following three mechanisms: (1) random selection, (2) memory consideration, and (3) Optmal synthess of a Path Generator Lnkage usng Non Conventonal Approach Mr. Monsh P. Wasnk 1, Prof. M. K. Sonpmple 2, Prof. S. K. Undrwade 3 1 M-Tech MED Pryadarshn College of Engneerng, Nagpur 2,3 Mechancal

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

DESIGN OF VERTICAL ALIGNMET

DESIGN OF VERTICAL ALIGNMET DESIN OF VERTICAL ALINMET Longtudnal gradent : max 0,5% (max see the assgnment paper) Markng of longtudnal gradent n drecton of chanage: + [%].. ascent n the drecton of chanage [%].. descent n the drecton

More information

PHYSICS-ENHANCED L-SYSTEMS

PHYSICS-ENHANCED L-SYSTEMS PHYSICS-ENHANCED L-SYSTEMS Hansrud Noser 1, Stephan Rudolph 2, Peter Stuck 1 1 Department of Informatcs Unversty of Zurch, Wnterthurerstr. 190 CH-8057 Zurch Swtzerland noser(stuck)@f.unzh.ch, http://www.f.unzh.ch/~noser(~stuck)

More information

SENSITIVITY ANALYSIS IN LINEAR PROGRAMMING USING A CALCULATOR

SENSITIVITY ANALYSIS IN LINEAR PROGRAMMING USING A CALCULATOR SENSITIVITY ANALYSIS IN LINEAR PROGRAMMING USING A CALCULATOR Judth Aronow Rchard Jarvnen Independent Consultant Dept of Math/Stat 559 Frost Wnona State Unversty Beaumont, TX 7776 Wnona, MN 55987 aronowju@hal.lamar.edu

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

An Influence of the Noise on the Imaging Algorithm in the Electrical Impedance Tomography *

An Influence of the Noise on the Imaging Algorithm in the Electrical Impedance Tomography * Open Journal of Bophyscs, 3, 3, 7- http://dx.do.org/.436/ojbphy.3.347 Publshed Onlne October 3 (http://www.scrp.org/journal/ojbphy) An Influence of the Nose on the Imagng Algorthm n the Electrcal Impedance

More information

Ecient Computation of the Most Probable Motion from Fuzzy. Moshe Ben-Ezra Shmuel Peleg Michael Werman. The Hebrew University of Jerusalem

Ecient Computation of the Most Probable Motion from Fuzzy. Moshe Ben-Ezra Shmuel Peleg Michael Werman. The Hebrew University of Jerusalem Ecent Computaton of the Most Probable Moton from Fuzzy Correspondences Moshe Ben-Ezra Shmuel Peleg Mchael Werman Insttute of Computer Scence The Hebrew Unversty of Jerusalem 91904 Jerusalem, Israel Emal:

More information