8. Supplementary Material

Size: px
Start display at page:

Download "8. Supplementary Material"

Transcription

1 8. Supplementary Material 8.1. Proofs Proof of Proposition 1 Proof. (R2) = (R3): As for both (R2) and (R3) we have µ L and µ ( s) = µ s (u), s X u, we only need to prove that µ s conv(x s ), s L is equivalent to µ M. By inspecting the definition (6) of M we see that it is the intersection of (i) µ u X u, u V and (ii) µ s X s, s L. However, by the equality constraints µ u (s) = µ s (u) constraints (i) are already enforced, in (R2), hence equality follows. (R4) = (R5): Analoguously to (R2) = (R3). Relaxation (R1) is weaker than (R2) and (R3): Relaxations (R2) and (R3) include additional constraints Optimization Subproblems of Procedure 1 In Procedure 1 the two problem in lines 1 and 3 must be solved. Solution of the optimization problem in line 1 was discussed in the main part of the paper. Therefore, it only remains to show how to carry optimization of the problem in line 3 efficiently for all cases that can occur. This is shown in Table 3. Checking validity of the operations in Table 3 for i = u V and i = uv E is straightforward. For i = M and J = V, we prove correctness below. Correctness for i = M and J = L is analoguous. Lemma 2. The reparametrization adjustment problem (9) for i = M and J = V is given by (14). Moreover it is the dual of a minimum cost network flow problem. Proof. Recall from network flow theory [7], that x u X u is optimal for cost θ, iff π R V, ψ R L such that { 0, x θ u (x u ) π(u) + ψ(x u ) u(x u ) = 1 0, x u(x u ) = 0 u V, x u X u. Consider the primal/dual pair min (µu) u V u V θ u, µ u max,π,ψ u V u, δ u u V, x u X u µ u (x u ) = 0 π(u) R l L, { u:l X u µ u (l) = 0 { ψ(l) R δ u (x u ), x u x u 0, x u = x u µ u (x u ) δ u (x u ), x u = x u (x u ) u 0, x u x u µ u (x u ) R θu (x u ) + u (x u ) + π(u) ψ(x u ) = 0 (12) On the right side, the adjustment problem (3) is written down explicitly. The left hand side is a minimum cost flow problem, hence the second part of the claim is proven. The last equality above on the right hand side ensures that u (x u ) = θ u (x u ) π(u) + ψ(x u ). Substituting this everywhere on the right hand side of (12) gives max π,ψ u V π(u) ( x u X u δ u (x u ) ) + l L ψ(l) ( u V:l X u δ u (l) ) s.t. π(u) R ψ(l) R This form matches the format given in (14) Time complexity θ u (x u ) + π(u) ψ(x u ) { 0, 0, x u = x u x u x u The time complexity of running one iteration of message passing is essentially the time to run all required invocations of Algorithm 1 via the routines described in Table 3. Total runtime per iteration for the various algorithms we have proposed can (13)

2 be found in Table 4. We assume that X u = L u V. In sparse assignment problems, where this is not the case, run-time decreases according to sparsity. If we hold the unary potentials θ u, u V in a heap, we can support operation min s J X u θ u (s ) which is required in the third line in Table 3 in time log( L ), since either J X u = X u (sending) or J X u = 1 (receiving). Hence, all our algorithms scale to realistic problem sizes Detailed Experimental Evaluation Plots showing lower bound and primal solution energy per over time can be seen in Figure 2. In Table 5 dataset statistics are given together with final upper and lower bound as well as runtime averaged over all instances in specific datasets are given. A per-instance evaluation of all considered algorithms can be found in Table 6.

3 Algorithm 1 input i V J N G (i) Solution (i,j) j J of (9) i = u V J E {M} L (u,uv) = (θu min xu Xu θu(xu)) / J uv E J (u,m) = (θu min xu Xu θu(xu)) / J (u,s) = (θu(s) min s / J Xu θu(s ))/ J s X u J i = uv E J = {u}, u V (uv,u) (x u) = min {θ uv (x u, x v )} min xuv X uv {θ uv (x uv )} x v X v i = M J = V u (x u ) = θ u (x u ) π (u) + ψ (x u ) (π, ψ u V ) argmax π(u) ( x u X u δ u (x u ) ) π,ψ + l L ψ(l) ( u V:l X u δ u (l) ) { 0, x u = x u s.t. θu (x u ) + π(u) ψ(x u ) 0, x u x u (14) i = M J = L s (u) = θ u (s) π (u) + ψ (s) (π, ψ u V ) argmax π(u) ( x u X u δ xu (u) ) π,ψ + l L ψ(l) ( u V:l X u δ l (u) ) { 0, x u = x u s.t. θu (x u ) + π(u) ψ(x u ) 0, x u x u (15) Table 3. Message computation problems (9) Algorithm Time complexity GM O( L V + L 2 Ê ) AMP O( L V + L 2 E + L 3 ) AMP O( L V + L 2 E + L 2 log L ) AMCF O( L V + L 2 E + MCF ( V, V 2 ) Table 4. Time complexity per iteration for the three proposed algorithms. MCF (n, m) is the time to solve a min-cost-flow problem on a graph with n nodes and m edges: Orlin s algorithm has time complexity O(m 2 log n + m log 2 n) [7]. AMP stores reparametrized unary costs in a heap to accelerate computation of the messages between label factors and unaries.

4 energy 3,000 3,500 AMP AMCF GM HBP DD energy 4,240 4,260 4,280 AMP AMCF GM HBP DD energy AMP AMCF GM HBP DD 4, energy 4, runtime(s) house AMP AMCF GM HBP DD energy 1,500 2,000 2, runtime(s) hotel AMP AMCF GM HBP DD energy runtime(s) car AMP AMCF GM HBP DD 80 3, runtime(s) motor runtime(s) Hassan runtime(s) worms Figure 2. Runtime plots for house, hotel, car, motor, graph flow and worms datasets. Continuous lines denote dual lower bounds and dashed ones primal energies. Values are averaged over all instances of the dataset. The x-axis is logarithmic. hotel house graph flow car motor worms Dataset/Algorithm AMP AMCF GM HBP DD #I 105 LB #V 30 UB #L 30 time(s) #I 105 LB #V 30 UB #L 30 time(s) #I 6 LB #V 126 UB #L 126 time(s) #I 30 LB #V 49 UB #L 49 time(s) #I 20 LB #V 52 UB #L 52 time(s) #I 30 LB #V 605 UB #L 1500 time(s) Table 5. Description of datasets together with averaged algorithm results over all instances. #I means number of instances in dataset, #V the number of nodes per instance, #L the number of labels per instance, LB means lower bound, UB upper bound. Bold numbers indicate highest lower bound, lowest primal energy and smallest runtime.

5 hotel UB energy hotel frame15frame22 LB runtime(s) UB energy hotel frame15frame29 LB runtime(s) UB energy hotel frame15frame36 LB runtime(s) UB energy hotel frame15frame43 LB runtime(s) UB energy hotel frame15frame50 LB runtime(s) UB energy hotel frame15frame57 LB runtime(s) UB energy hotel frame15frame64 LB runtime(s) UB energy hotel frame15frame71 LB runtime(s) UB energy hotel frame15frame78 LB runtime(s) UB energy hotel frame15frame85 LB runtime(s) UB energy hotel frame15frame92 LB runtime(s) UB energy hotel frame15frame99 LB runtime(s) UB energy hotel frame1frame15 LB runtime(s) UB energy hotel frame1frame22 LB runtime(s) UB energy hotel frame1frame29 LB runtime(s) UB energy hotel frame1frame36 LB runtime(s) UB energy hotel frame1frame43 LB runtime(s) UB energy hotel frame1frame50 LB runtime(s) UB energy hotel frame1frame57 LB runtime(s) UB energy hotel frame1frame64 LB runtime(s)

6 UB energy hotel frame1frame71 LB runtime(s) UB energy hotel frame1frame78 LB runtime(s) UB energy hotel frame1frame8 LB runtime(s) UB energy hotel frame1frame85 LB runtime(s) UB energy hotel frame1frame92 LB runtime(s) UB energy hotel frame1frame99 LB runtime(s) UB energy hotel frame22frame29 LB runtime(s) UB energy hotel frame22frame36 LB runtime(s) UB energy hotel frame22frame43 LB runtime(s) UB energy hotel frame22frame50 LB runtime(s) UB energy hotel frame22frame57 LB runtime(s) UB energy hotel frame22frame64 LB runtime(s) UB energy hotel frame22frame71 LB runtime(s) UB energy hotel frame22frame78 LB runtime(s) UB energy hotel frame22frame85 LB runtime(s) UB energy hotel frame22frame92 LB runtime(s) UB energy hotel frame22frame99 LB runtime(s) UB energy hotel frame29frame36 LB runtime(s) UB energy hotel frame29frame43 LB runtime(s) UB energy hotel frame29frame50 LB runtime(s)

7 UB energy hotel frame29frame57 LB runtime(s) UB energy hotel frame29frame64 LB runtime(s) UB energy hotel frame29frame71 LB runtime(s) UB energy hotel frame29frame78 LB runtime(s) UB energy hotel frame29frame85 LB runtime(s) UB energy hotel frame29frame92 LB runtime(s) UB energy hotel frame29frame99 LB runtime(s) UB energy hotel frame36frame43 LB runtime(s) UB energy hotel frame36frame50 LB runtime(s) UB energy hotel frame36frame57 LB runtime(s) UB energy hotel frame36frame64 LB runtime(s) UB energy hotel frame36frame71 LB runtime(s) UB energy hotel frame36frame78 LB runtime(s) UB energy hotel frame36frame85 LB runtime(s) UB energy hotel frame36frame92 LB runtime(s) UB energy hotel frame36frame99 LB runtime(s) UB energy hotel frame43frame50 LB runtime(s) UB energy hotel frame43frame57 LB runtime(s) UB energy hotel frame43frame64 LB runtime(s) UB energy hotel frame43frame71 LB runtime(s)

8 UB energy hotel frame43frame78 LB runtime(s) UB energy hotel frame43frame85 LB runtime(s) UB energy hotel frame43frame92 LB runtime(s) UB energy hotel frame43frame99 LB runtime(s) UB energy hotel frame50frame57 LB runtime(s) UB energy hotel frame50frame64 LB runtime(s) UB energy hotel frame50frame71 LB runtime(s) UB energy hotel frame50frame78 LB runtime(s) UB energy hotel frame50frame85 LB runtime(s) UB energy hotel frame50frame92 LB runtime(s) UB energy hotel frame50frame99 LB runtime(s) UB energy hotel frame57frame64 LB runtime(s) UB energy hotel frame57frame71 LB runtime(s) UB energy hotel frame57frame78 LB runtime(s) UB energy hotel frame57frame85 LB runtime(s) UB energy hotel frame57frame92 LB runtime(s) UB energy hotel frame57frame99 LB runtime(s) UB energy hotel frame64frame71 LB runtime(s) UB energy hotel frame64frame78 LB runtime(s) UB energy hotel frame64frame85 LB runtime(s)

9 UB energy hotel frame64frame92 LB runtime(s) UB energy hotel frame64frame99 LB runtime(s) UB energy hotel frame71frame78 LB runtime(s) UB energy hotel frame71frame85 LB runtime(s) UB energy hotel frame71frame92 LB runtime(s) UB energy hotel frame71frame99 LB runtime(s) UB energy hotel frame78frame85 LB runtime(s) UB energy hotel frame78frame92 LB runtime(s) UB energy hotel frame78frame99 LB runtime(s) UB energy hotel frame85frame92 LB runtime(s) UB energy hotel frame85frame99 LB runtime(s) UB energy hotel frame8frame15 LB runtime(s) UB energy hotel frame8frame22 LB runtime(s) UB energy hotel frame8frame29 LB runtime(s) UB energy hotel frame8frame36 LB runtime(s) UB energy hotel frame8frame43 LB runtime(s) UB energy hotel frame8frame50 LB runtime(s) UB energy hotel frame8frame57 LB runtime(s) UB energy hotel frame8frame64 LB runtime(s) UB energy hotel frame8frame71 LB runtime(s)

10 UB energy hotel frame8frame78 LB runtime(s) UB energy hotel frame8frame85 LB runtime(s) UB energy hotel frame8frame92 LB runtime(s) UB energy hotel frame8frame99 LB runtime(s) UB energy hotel frame92frame99 LB runtime(s) house UB energy house frame10frame100 LB runtime(s) UB energy house frame10frame95 LB runtime(s) UB energy house frame10frame96 LB runtime(s) UB energy house frame10frame97 LB runtime(s) UB energy house frame10frame98 LB runtime(s) UB energy house frame10frame99 LB runtime(s) UB energy house frame11frame100 LB runtime(s) UB energy house frame11frame101 LB runtime(s) UB energy house frame11frame96 LB runtime(s) UB energy house frame11frame97 LB runtime(s) UB energy house frame11frame98 LB runtime(s) UB energy house frame11frame99 LB runtime(s) UB energy house frame12frame100 LB runtime(s) UB energy house frame12frame101 LB runtime(s) UB energy house frame12frame102 LB runtime(s)

11 UB energy house frame12frame97 LB runtime(s) UB energy house frame12frame98 LB runtime(s) UB energy house frame12frame99 LB runtime(s) UB energy house frame13frame100 LB runtime(s) UB energy house frame13frame101 LB runtime(s) UB energy house frame13frame102 LB runtime(s) UB energy house frame13frame103 LB runtime(s) UB energy house frame13frame98 LB runtime(s) UB energy house frame13frame99 LB runtime(s) UB energy house frame14frame100 LB runtime(s) UB energy house frame14frame101 LB runtime(s) UB energy house frame14frame102 LB runtime(s) UB energy house frame14frame103 LB runtime(s) UB energy house frame14frame104 LB runtime(s) UB energy house frame14frame99 LB runtime(s) UB energy house frame15frame100 LB runtime(s) UB energy house frame15frame101 LB runtime(s) UB energy house frame15frame102 LB runtime(s) UB energy house frame15frame103 LB runtime(s) UB energy house frame15frame104 LB runtime(s)

12 UB energy house frame15frame105 LB runtime(s) UB energy house frame16frame101 LB runtime(s) UB energy house frame16frame102 LB runtime(s) UB energy house frame16frame103 LB runtime(s) UB energy house frame16frame104 LB runtime(s) UB energy house frame16frame105 LB runtime(s) UB energy house frame17frame102 LB runtime(s) UB energy house frame17frame103 LB runtime(s) UB energy house frame17frame104 LB runtime(s) UB energy house frame17frame105 LB runtime(s) UB energy house frame18frame103 LB runtime(s) UB energy house frame18frame104 LB runtime(s) UB energy house frame18frame105 LB runtime(s) UB energy house frame19frame104 LB runtime(s) UB energy house frame19frame105 LB runtime(s) UB energy house frame1frame86 LB runtime(s) UB energy house frame1frame87 LB runtime(s) UB energy house frame1frame88 LB runtime(s) UB energy house frame1frame89 LB runtime(s) UB energy house frame1frame90 LB runtime(s)

13 UB energy house frame1frame91 LB runtime(s) UB energy house frame20frame105 LB runtime(s) UB energy house frame2frame87 LB runtime(s) UB energy house frame2frame88 LB runtime(s) UB energy house frame2frame89 LB runtime(s) UB energy house frame2frame90 LB runtime(s) UB energy house frame2frame91 LB runtime(s) UB energy house frame2frame92 LB runtime(s) UB energy house frame3frame88 LB runtime(s) UB energy house frame3frame89 LB runtime(s) UB energy house frame3frame90 LB runtime(s) UB energy house frame3frame91 LB runtime(s) UB energy house frame3frame92 LB runtime(s) UB energy house frame3frame93 LB runtime(s) UB energy house frame4frame89 LB runtime(s) UB energy house frame4frame90 LB runtime(s) UB energy house frame4frame91 LB runtime(s) UB energy house frame4frame92 LB runtime(s) UB energy house frame4frame93 LB runtime(s) UB energy house frame4frame94 LB runtime(s)

14 UB energy house frame5frame90 LB runtime(s) UB energy house frame5frame91 LB runtime(s) UB energy house frame5frame92 LB runtime(s) UB energy house frame5frame93 LB runtime(s) UB energy house frame5frame94 LB runtime(s) UB energy house frame5frame95 LB runtime(s) UB energy house frame6frame91 LB runtime(s) UB energy house frame6frame92 LB runtime(s) UB energy house frame6frame93 LB runtime(s) UB energy house frame6frame94 LB runtime(s) UB energy house frame6frame95 LB runtime(s) UB energy house frame6frame96 LB runtime(s) UB energy house frame7frame92 LB runtime(s) UB energy house frame7frame93 LB runtime(s) UB energy house frame7frame94 LB runtime(s) UB energy house frame7frame95 LB runtime(s) UB energy house frame7frame96 LB runtime(s) UB energy house frame7frame97 LB runtime(s) UB energy house frame8frame93 LB runtime(s) UB energy house frame8frame94 LB runtime(s)

15 UB energy house frame8frame95 LB runtime(s) UB energy house frame8frame96 LB runtime(s) UB energy house frame8frame97 LB runtime(s) UB energy house frame8frame98 LB runtime(s) UB energy house frame9frame94 LB runtime(s) UB energy house frame9frame95 LB runtime(s) UB energy house frame9frame96 LB runtime(s) UB energy house frame9frame97 LB runtime(s) UB energy house frame9frame98 LB runtime(s) UB energy house frame9frame99 LB runtime(s) Hassan UB board torresani LB runtime(s) UB books torresani LB runtime(s) UB hammer torresani LB runtime(s) UB party torresani LB runtime(s) UB table torresani LB runtime(s) UB walking torresani LB runtime(s) car UB car1 LB runtime(s) UB car10 LB runtime(s) UB car11 LB runtime(s)

16 UB car12 LB runtime(s) UB car13 LB runtime(s) UB car14 LB runtime(s) UB car15 LB runtime(s) UB car16 LB runtime(s) UB car17 LB runtime(s) UB car18 LB runtime(s) UB car19 LB runtime(s) UB car2 LB runtime(s) UB car20 LB runtime(s) UB car21 LB runtime(s) UB car22 LB runtime(s) UB car23 LB runtime(s) UB car24 LB runtime(s) UB car25 LB runtime(s) UB car26 LB runtime(s) UB car27 LB runtime(s) UB car28 LB runtime(s) UB car29 LB runtime(s) UB car3 LB runtime(s)

17 UB car30 LB runtime(s) UB car4 LB runtime(s) UB car5 LB runtime(s) UB car6 LB runtime(s) UB car7 LB runtime(s) UB car8 LB runtime(s) UB car9 LB runtime(s) motor UB motor1 LB runtime(s) UB motor10 LB runtime(s) UB motor11 LB runtime(s) UB motor12 LB runtime(s) UB motor13 LB runtime(s) UB motor14 LB runtime(s) UB motor15 LB runtime(s) UB motor16 LB runtime(s) UB motor17 LB runtime(s) UB motor18 LB runtime(s) UB motor19 LB runtime(s) UB motor2 LB runtime(s) UB motor20 LB runtime(s)

18 UB motor3 LB runtime(s) UB motor4 LB runtime(s) UB motor5 LB runtime(s) UB motor6 LB runtime(s) UB motor7 LB runtime(s) UB motor8 LB runtime(s) UB motor9 LB runtime(s) worms UB inf C18G1 2L1 1-lowThresh-more-hyp.surf LB runtime(s) UB inf cnd1threel lowThresh-more-hyp.surf LB runtime(s) UB inf cnd1threel lowThresh-more-hyp.surf LB runtime(s) UB inf cnd1threel lowThresh-more-hyp.surf LB runtime(s) UB inf cnd1threel lowThresh-more-hyp.surf LB runtime(s) UB inf cnd1threel lowThresh-more-hyp.surf LB runtime(s) UB inf eft3rw10035l lowThresh-more-hyp.surf LB runtime(s) UB inf eft3rw10035l lowThresh-more-hyp.surf LB runtime(s) UB inf eft3rw10035l lowThresh-more-hyp.surf LB runtime(s) UB inf egl5l lowThresh-more-hyp.surf LB runtime(s) UB inf elt3l lowThresh-more-hyp.surf LB runtime(s) UB inf elt3l lowThresh-more-hyp.surf LB runtime(s) UB inf elt3l lowThresh-more-hyp.surf LB runtime(s)

19 UB inf hlh1fourl lowThresh-more-hyp.surf LB runtime(s) UB inf hlh1fourl lowThresh-more-hyp.surf LB runtime(s) UB inf hlh1fourl lowThresh-more-hyp.surf LB runtime(s) UB inf hlh1fourl lowThresh-more-hyp.surf LB runtime(s) UB inf hlh1fourl lowThresh-more-hyp.surf LB runtime(s) UB inf mir61l lowThresh-more-hyp.surf LB runtime(s) UB inf mir61l lowThresh-more-hyp.surf LB runtime(s) UB inf mir61l lowThresh-more-hyp.surf LB runtime(s) UB inf pha4a7l lowThresh-more-hyp.surf LB runtime(s) UB inf pha4a7l lowThresh-more-hyp.surf LB runtime(s) UB inf pha4a7l lowThresh-more-hyp.surf LB runtime(s) UB inf pha4b2l lowThresh-more-hyp.surf LB runtime(s) UB inf pha4i2l lowThresh-more-hyp.surf LB runtime(s) UB pha4i2l lowThresh-more-hyp.surf LB runtime(s) UB pha4i2l lowThresh-more-hyp.surf LB runtime(s) UB inf unc54l lowThresh-more-hyp.surf LB runtime(s) UB inf unc54l lowThresh-more-hyp.surf LB runtime(s)

Supplementary file related to the paper titled On the Design and Deployment of RFID Assisted Navigation Systems for VANET

Supplementary file related to the paper titled On the Design and Deployment of RFID Assisted Navigation Systems for VANET Supplementary file related to the paper titled On the Design and Deployment of RFID Assisted Navigation Systems for VANET SUPPLEMENTARY FILE RELATED TO SECTION 3: RFID ASSISTED NAVIGATION SYS- TEM MODEL

More information

Automatic Optimization of Wayfinding Design Supplementary Material

Automatic Optimization of Wayfinding Design Supplementary Material TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL.??, NO.??,???? 1 Automatic Optimization of Wayfinding Design Supplementary Material 1 ADDITIONAL EXAMPLES We use our approach to generate wayfinding

More information

Sharjah Indian School Sharjah Boys Wing

Sharjah Indian School Sharjah Boys Wing Read the instructions given below carefully before writing the fair record book. The following details are to be written on the LEFT HAND SIDE of the book. CIRCUIT DIAGRAM CALCULATIONS The remaining details

More information

arxiv: v3 [cs.sy] 14 Sep 2016

arxiv: v3 [cs.sy] 14 Sep 2016 1 Optimal Pricing to Manage Electric Vehicles in Coupled Power and Transportation Networks Mahnoosh Alizadeh, Hoi-To Wai, Mainak Chowdhury, Andrea Goldsmith, Anna Scaglione, and Tara Javidi arxiv:1511.03611v3

More information

2010 Journal of Industrial Ecology

2010 Journal of Industrial Ecology 21 Journal of Industrial Ecology www.wiley.com/go/jie Subramanian, R., B. Talbot, and S. Gupta. 21. An approach to integrating environmental considerations within managerial decisionmaking. Journal of

More information

A Stochastic Flow-Capturing Model to Optimize the Location of Fast-Charging Stations with Uncertain Electric Vehicle Flows

A Stochastic Flow-Capturing Model to Optimize the Location of Fast-Charging Stations with Uncertain Electric Vehicle Flows A Stochastic Flow-Capturing Model to Optimize the Location of Fast-Charging Stations with Uncertain Electric Vehicle Flows Fei Wu, Ramteen Sioshansi Integrated Systems Engineering Department, The Ohio

More information

IMA Preprint Series # 2035

IMA Preprint Series # 2035 PARTITIONS FOR SPECTRAL (FINITE) VOLUME RECONSTRUCTION IN THE TETRAHEDRON By Qian-Yong Chen IMA Preprint Series # 2035 ( April 2005 ) INSTITUTE FOR MATHEMATICS AND ITS APPLICATIONS UNIVERSITY OF MINNESOTA

More information

1 Configuration Space Path Planning

1 Configuration Space Path Planning CS 4733, Class Notes 1 Configuration Space Path Planning Reference: 1) A Simple Motion Planning Algorithm for General Purpose Manipulators by T. Lozano-Perez, 2) Siegwart, section 6.2.1 Fast, simple to

More information

Cyber-Physical Systems for Smart Grid

Cyber-Physical Systems for Smart Grid Shanghai Jiao Tong University University of Michigan - Shanghai Jiao Tong University Joint Institute Cyber-Physical Systems for Smart Grid by Yibo Pi A thesis submitted in partial satisfaction of the requirements

More information

CDI15 6. Haar wavelets (1D) 1027, 1104, , 416, 428 SXD

CDI15 6. Haar wavelets (1D) 1027, 1104, , 416, 428 SXD CDI15 6. Haar wavelets (1D) 1027, 1104, 1110 414, 416, 428 SXD Notations 6.1. The Haar transforms 6.2. Haar wavelets 6.3. Multiresolution analysis 6.4. Compression/decompression James S. Walker A primer

More information

Anytime Pareto Local Search

Anytime Pareto Local Search Anytime Pareto Local Search Jérémie Dubois Lacoste, Manuel López Ibáñez, Thomas Stützle IRIDIA, CoDE, Université Libre de Bruxelles, 50 Av. F. Roosevelt, 1050 Brussels, Belgium Abstract Pareto Local Search

More information

Designing and Optimizing an Integrated Car-and-ride Sharing System for Mobilizing Underserved Populations

Designing and Optimizing an Integrated Car-and-ride Sharing System for Mobilizing Underserved Populations Designing and Optimizing an Integrated Car-and-ride Sharing System for Mobilizing Underserved Populations Miao Yu Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor,

More information

Optimization Methodology for CVT Ratio Scheduling with Consideration of Both Engine and CVT Efficiency

Optimization Methodology for CVT Ratio Scheduling with Consideration of Both Engine and CVT Efficiency Western Michigan University ScholarWorks at WMU Master's Theses Graduate College 12-2016 Optimization Methodology for CVT Ratio Scheduling with Consideration of Both Engine and CVT Efficiency Steven Beuerle

More information

Bayesian Trajectory Optimization for Magnetic Resonance Imaging Sequences

Bayesian Trajectory Optimization for Magnetic Resonance Imaging Sequences Bayesian Trajectory Optimization for Magnetic Resonance Imaging Sequences Matthias Seeger Saarland University and MPI for Informatics, Saarbrücken Joint work with Hannes Nickisch, Rolf Pohmann, Bernhard

More information

Restricted dynamic programming for the VRP

Restricted dynamic programming for the VRP Restricted dynamic programming for the VRP A flexible framework for solving realistic VRPS Leendert Kok, Marco Schutten (UT, OMPL) Jelke van Hoorn, Joaquim Gromicho (ORTEC) 1 Overview Introduction DP for

More information

Torsional analysis of the chassis and its validation through Finite. Element Analysis

Torsional analysis of the chassis and its validation through Finite. Element Analysis Torsional analysis of the chassis and its validation through Finite Ayush Anand Student(Production) BIT Mesra,Ranchi, Jharkhand-835215,India ayush.aand@gmail.com Element Analysis Keywords: Roll cage, Torsional

More information

Cost-Efficiency by Arash Method in DEA

Cost-Efficiency by Arash Method in DEA Applied Mathematical Sciences, Vol. 6, 2012, no. 104, 5179-5184 Cost-Efficiency by Arash Method in DEA Dariush Khezrimotlagh*, Zahra Mohsenpour and Shaharuddin Salleh Department of Mathematics, Faculty

More information

Adaptive Routing and Recharging Policies for Electric Vehicles

Adaptive Routing and Recharging Policies for Electric Vehicles Adaptive Routing and Recharging Policies for Electric Vehicles Timothy M. Sweda, Irina S. Dolinskaya, Diego Klabjan Department of Industrial Engineering and Management Sciences Northwestern University

More information

M:2:I Milestone 2 Final Installation and Ground Test

M:2:I Milestone 2 Final Installation and Ground Test Iowa State University AerE 294X/AerE 494X Make to Innovate M:2:I Milestone 2 Final Installation and Ground Test Author(s): Angie Burke Christopher McGrory Mitchell Skatter Kathryn Spierings Ryan Story

More information

Vehicle Rotation Planning for Intercity Railways

Vehicle Rotation Planning for Intercity Railways Vehicle Rotation Planning for Intercity Railways Markus Reuther ** Joint work with Ralf Borndörfer, Thomas Schlechte and Steffen Weider Zuse Institute Berlin May 24, 2011 Markus Reuther (Zuse Institute

More information

ATTEND Analytical Tools To Evaluate Negotiation Difficulty

ATTEND Analytical Tools To Evaluate Negotiation Difficulty ATTEND Analytical Tools To Evaluate Negotiation Difficulty Computational Complexity Fest USC ISI - September 6, 2000 Key Ideas: Difficulty Warnings that Allow Negotiation Systems to Adapt Partition task

More information

1 Configuration Space Path Planning

1 Configuration Space Path Planning CS 4733, Class Notes 1 Configuration Space Path Planning Reference: 1) A Simple Motion Planning Algorithm for General Purpose Manipulators by T. Lozano-Perez, 2) Siegwart, section 6.2.1 Fast, simple to

More information

Physics 2048 Test 2 Dr. Jeff Saul Fall 2001

Physics 2048 Test 2 Dr. Jeff Saul Fall 2001 Physics 2048 Test 2 Dr. Jeff Saul Fall 2001 Name: Group: Date: READ THESE INSTRUCTIONS BEFORE YOU BEGIN Before you start the test, WRITE YOUR NAME ON EVERY PAGE OF THE EXAM. Calculators are permitted,

More information

INTERNATIONAL JOURNAL OF DESIGN AND MANUFACTURING TECHNOLOGY (IJDMT) CONSTANT SPEED ENGINE CONROD SOFT VALIDATION & OPTIMIZATION

INTERNATIONAL JOURNAL OF DESIGN AND MANUFACTURING TECHNOLOGY (IJDMT) CONSTANT SPEED ENGINE CONROD SOFT VALIDATION & OPTIMIZATION INTERNATIONAL JOURNAL OF DESIGN AND MANUFACTURING TECHNOLOGY (IJDMT) International Journal of Design and Manufacturing Technology (IJDMT), ISSN 0976 6995(Print), ISSN 0976 6995 (Print) ISSN 0976 7002 (Online)

More information

Monadic Design for Universal Systems

Monadic Design for Universal Systems Monadic Design for Universal Systems Nick Rossiter Visiting Fellow Computing Science and Digital Technologies Northumbria University ANPA 37 (August 2016, modified March 2017) Outline of Presentation Basic

More information

Proposed Solution to Mitigate Concerns Regarding AC Power Flow under Convergence Bidding. September 25, 2009

Proposed Solution to Mitigate Concerns Regarding AC Power Flow under Convergence Bidding. September 25, 2009 Proposed Solution to Mitigate Concerns Regarding AC Power Flow under Convergence Bidding September 25, 2009 Proposed Solution to Mitigate Concerns Regarding AC Power Flow under Convergence Bidding Background

More information

Postprint.

Postprint. http://www.diva-portal.org Postprint This is the accepted version of a paper presented at 7th International Conference on Railway Operations Modelling and Analysis (RailLille2017), Lille, France, April

More information

Optimal Power Flow Formulation in Market of Retail Wheeling

Optimal Power Flow Formulation in Market of Retail Wheeling Optimal Power Flow Formulation in Market of Retail Wheeling Taiyou Yong, Student Member, IEEE Robert Lasseter, Fellow, IEEE Department of Electrical and Computer Engineering, University of Wisconsin at

More information

Locomotive Allocation for Toll NZ

Locomotive Allocation for Toll NZ Locomotive Allocation for Toll NZ Sanjay Patel Department of Engineering Science University of Auckland, New Zealand spat075@ec.auckland.ac.nz Abstract A Locomotive is defined as a self-propelled vehicle

More information

Routing and Planning for the Last Mile Mobility System

Routing and Planning for the Last Mile Mobility System Routing and Planning for the Last Mile Mobility System Nguyen Viet Anh 30 October 2012 Nguyen Viet Anh () Routing and Planningfor the Last Mile Mobility System 30 October 2012 1 / 33 Outline 1 Introduction

More information

A routing model and solution approach for alternative fuel vehicles with consideration of the fixed fueling time

A routing model and solution approach for alternative fuel vehicles with consideration of the fixed fueling time A routing model and solution approach for alternative fuel vehicles with consideration of the fixed fueling time Yihuan Shao (yihuansh@usc.edu), Maged Dessouky (maged@usc.edu) Department of Industrial

More information

Suburban bus route design

Suburban bus route design University of Wollongong Research Online Faculty of Engineering and Information Sciences - Papers: Part A Faculty of Engineering and Information Sciences 2013 Suburban bus route design Shuaian Wang University

More information

Engine Performance Analysis

Engine Performance Analysis Engine Performance Analysis Introduction The basics of engine performance analysis The parameters and tools used in engine performance analysis Introduction Parametric cycle analysis: Independently selected

More information

Topic 5 Lecture 3 Estimating Policy Effects via the Simple Linear. Regression Model (SLRM) and the Ordinary Least Squares (OLS) Method

Topic 5 Lecture 3 Estimating Policy Effects via the Simple Linear. Regression Model (SLRM) and the Ordinary Least Squares (OLS) Method Econometrics for Health Policy, Health Economics, and Outcomes Research Topic 5 Lecture 3 Estimating Policy Effects via the Simple Linear Regression Model (SLRM) and the Ordinary Least Squares (OLS) Method

More information

A Study on Noncircular Gears with Non-Uniform Teeth

A Study on Noncircular Gears with Non-Uniform Teeth A Study on Noncircular Gears with Non-Uniform Teeth Kazushi Kumagai* 1 and Tetsuya Oizumi* *1 Department of Infomation System, Sendai National College of Technology 4-16-1 Ayashi-Chuo, Aoba-ku, Sendai

More information

1 Benefits of the Minivan

1 Benefits of the Minivan 1 Benefits of the Minivan 1. Motivation. 2. Demand Model. 3. Data/Estimation. 4. Results 2 Motivation In this paper, Petrin attempts to measure the benefits from a new good- the minivan. Theory has ambiguous

More information

Damper Analysis using Energy Method

Damper Analysis using Energy Method SAE TECHNICAL 2002-01-3536 PAPER SERIES E Damper Analysis using Energy Method Angelo Cesar Nuti General Motors do Brasil Ramon Orives General Motors do Brasil Flavio Garzeri General Motors do Brasil 11

More information

MOTORCYCLE BRAKING DYNAMICS

MOTORCYCLE BRAKING DYNAMICS MOTORCYCLE BRAKING DYNAMICS By Rudy Limpert, Ph.D. PC-BRAKE, Inc. 2008 www.pcbrakeinc.com 1 1.0 INTRODUCTION In recent issues of Accident Investigation Quarterly motorcycle braking systems as well as braking

More information

Capacity-Achieving Accumulate-Repeat-Accumulate Codes for the BEC with Bounded Complexity

Capacity-Achieving Accumulate-Repeat-Accumulate Codes for the BEC with Bounded Complexity Capacity-Achieving Accumulate-Repeat-Accumulate Codes for the BEC with Bounded Complexity Igal Sason 1 and Henry D. Pfister 2 Department of Electrical Engineering 1 Techion Institute, Haifa, Israel Department

More information

IN recent years, aiming at profit increase, great attention has

IN recent years, aiming at profit increase, great attention has 1042 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS PART C: APPLICATIONS AND REVIEWS, VOL. 42, NO. 6, NOVEMBER 2012 A Novel Approach to Optimization of Refining Schedules for Crude Oil Operations in

More information

Chapter 5 ESTIMATION OF MAINTENANCE COST PER HOUR USING AGE REPLACEMENT COST MODEL

Chapter 5 ESTIMATION OF MAINTENANCE COST PER HOUR USING AGE REPLACEMENT COST MODEL Chapter 5 ESTIMATION OF MAINTENANCE COST PER HOUR USING AGE REPLACEMENT COST MODEL 87 ESTIMATION OF MAINTENANCE COST PER HOUR USING AGE REPLACEMENT COST MODEL 5.1 INTRODUCTION Maintenance is usually carried

More information

Optimal Power Flow (DC-OPF and AC-OPF)

Optimal Power Flow (DC-OPF and AC-OPF) Optimal Power Flow (DC-OPF and AC-OPF) DTU Summer School 2018 Spyros Chatzivasileiadis What is optimal power flow? 2 DTU Electrical Engineering Optimal Power Flow (DC-OPF and AC-OPF) Jun 25, 2018 Optimal

More information

w o r k o G E x - p e S i n c e r t Elegance and Strength BBR HiAm CONA Strand Stay Cable Damping Systems

w o r k o G E x - p e S i n c e r t Elegance and Strength BBR HiAm CONA Strand Stay Cable Damping Systems o b a l N e t w o r k l o G f A E x - p e S i n c e 1 9 4 4 - s r t Elegance and Strength BBR HiAm CONA Strand Stay Cable Damping Systems 1 Cable vibration and damping Despite the wide use of cable-stayed

More information

The Mechanics of Tractor Implement Performance

The Mechanics of Tractor Implement Performance The Mechanics of Tractor Implement Performance Theory and Worked Examples R.H. Macmillan CHAPTER 2 TRACTOR MECHANICS Printed from: http://www.eprints.unimelb.edu.au CONTENTS 2.1 INTRODUCTION 2.1 2.2 IDEAL

More information

Evaluation copy. The Magnetic Field in a Slinky. computer OBJECTIVES MATERIALS INITIAL SETUP

Evaluation copy. The Magnetic Field in a Slinky. computer OBJECTIVES MATERIALS INITIAL SETUP The Magnetic Field in a Slinky Computer 26 A solenoid is made by taking a tube and wrapping it with many turns of wire. A metal Slinky is the same shape and will serve as our solenoid. When a current passes

More information

Electric Motors and Drives

Electric Motors and Drives EML 2322L MAE Design and Manufacturing Laboratory Electric Motors and Drives To calculate the peak power and torque produced by an electric motor, you will need to know the following: Motor supply voltage:

More information

TEL AVIV UNIVERSITY. The Iby and Aladar Fleischman Faculty of Engineering The Zandman-Slaner School of Graduate Studies. The Mixed Transit Fleet

TEL AVIV UNIVERSITY. The Iby and Aladar Fleischman Faculty of Engineering The Zandman-Slaner School of Graduate Studies. The Mixed Transit Fleet TEL AVIV UNIVERSITY The Iby and Aladar Fleischman Faculty of Engineering The Zandman-Slaner School of Graduate Studies The Mixed Transit Fleet Bus Scheduling Problem A thesis submitted toward the degree

More information

Computation of Sensitive Node for IEEE- 14 Bus system Subjected to Load Variation

Computation of Sensitive Node for IEEE- 14 Bus system Subjected to Load Variation Computation of Sensitive Node for IEEE- 4 Bus system Subjected to Load Variation P.R. Sharma, Rajesh Kr.Ahuja 2, Shakti Vashisth 3, Vaibhav Hudda 4, 2, 3 Department of Electrical Engineering, YMCAUST,

More information

Pre-Calculus Polar & Complex Numbers

Pre-Calculus Polar & Complex Numbers Slide 1 / 106 Slide 2 / 106 Pre-Calculus Polar & Complex Numbers 2015-03-23 www.njctl.org Slide 3 / 106 Table of Contents click on the topic to go to that section Complex Numbers Polar Number Properties

More information

REC: Predictable Charging Scheduling for Electric Taxi Fleets

REC: Predictable Charging Scheduling for Electric Taxi Fleets REC: Predictable Charging Scheduling for Electric Taxi Fleets Zheng Dong, Cong Liu, Yanhua Li, Jie Bao, Yu Gu, Tian He The University of Texas at Dallas, Worcester Polytechnic Institute Microsft Reseach

More information

DHANALAKSHMI COLLEGE OF ENGINEERING

DHANALAKSHMI COLLEGE OF ENGINEERING DHANALAKSHMI COLLEGE OF ENGINEERING (Dr.VPR Nagar, Manimangalam, Tambaram) Chennai - 601 301 DEPARTMENT OF MECHANICAL ENGINEERING III YEAR MECHANICAL - VI SEMESTER ME 6601 DESIGN OF TRANSMISSION SYSTEMS

More information

Capacity-Achieving Accumulate-Repeat-Accumulate Codes for the BEC with Bounded Complexity

Capacity-Achieving Accumulate-Repeat-Accumulate Codes for the BEC with Bounded Complexity Capacity-Achieving Accumulate-Repeat-Accumulate Codes for the BEC with Bounded Complexity Igal Sason 1 and Henry D. Pfister 2 Department of Electrical Engineering 1 Techion Institute, Haifa, Israel School

More information

Full Vehicle Simulation Model

Full Vehicle Simulation Model Chapter 3 Full Vehicle Simulation Model Two different versions of the full vehicle simulation model of the test vehicle will now be described. The models are validated against experimental results. A unique

More information

Some new distance-4 constant weight codes

Some new distance-4 constant weight codes Some new distance-4 constant weight codes A. E. Brouwer & T. Etzion 2010-02-15 Abstract Improved binary constant weight codes with minimum distance 4 and length at most 28 are constructed. A table with

More information

MAGNETIC EFFECTS ON AND DUE TO CURRENT-CARRYING WIRES

MAGNETIC EFFECTS ON AND DUE TO CURRENT-CARRYING WIRES 22 January 2013 1 2013_phys230_expt3.doc MAGNETIC EFFECTS ON AND DUE TO CURRENT-CARRYING WIRES OBJECTS To study the force exerted on a current-carrying wire in a magnetic field; To measure the magnetic

More information

The Degrees of Freedom of Partial Least Squares Regression

The Degrees of Freedom of Partial Least Squares Regression The Degrees of Freedom of Partial Least Squares Regression Dr. Nicole Krämer TU München 5th ESSEC-SUPELEC Research Workshop May 20, 2011 My talk is about...... the statistical analysis of Partial Least

More information

The University of Melbourne Engineering Mechanics

The University of Melbourne Engineering Mechanics The University of Melbourne 436-291 Engineering Mechanics Tutorial Twelve General Plane Motion, Work and Energy Part A (Introductory) 1. (Problem 6/78 from Meriam and Kraige - Dynamics) Above the earth

More information

Distributed Rate Control for Smart Solar Arrays

Distributed Rate Control for Smart Solar Arrays Distributed Rate Control for Smart Solar Arrays College of Information and Computer Sciences University of Massachusetts Amherst ABSTRACT Continued advances in technology have led to falling costs and

More information

06IP/IM74 OPERATIONS RESEARCH. UNIT - 3: Transportation Problem

06IP/IM74 OPERATIONS RESEARCH. UNIT - 3: Transportation Problem 06IP/IM74 OPERATIONS RESEARCH UNIT - 3: Transportation Problem Introduction: The objective of the transportation problem is to transport various quantities of a single homogenous commodity, which are initially

More information

TSFS02 Vehicle Dynamics and Control. Computer Exercise 2: Lateral Dynamics

TSFS02 Vehicle Dynamics and Control. Computer Exercise 2: Lateral Dynamics TSFS02 Vehicle Dynamics and Control Computer Exercise 2: Lateral Dynamics Division of Vehicular Systems Department of Electrical Engineering Linköping University SE-581 33 Linköping, Sweden 1 Contents

More information

Chapter 20: Cost Minimization Problem

Chapter 20: Cost Minimization Problem Econ 323 Microeconomic Analysis Chapter : Cost Minimization Problem Instructor: Hiroki Watanabe Spring 13 Watanabe Econ 323 CMP 1 / 91 1 Introduction Overview Cost Minimization Problem (CMP) 2 Cost Minimization

More information

Session 5 Wind Turbine Scaling and Control W. E. Leithead

Session 5 Wind Turbine Scaling and Control W. E. Leithead SUPERGEN Wind Wind Energy Technology Session 5 Wind Turbine Scaling and Control W. E. Leithead Supergen 2 nd Training Seminar 24 th /25 th March 2011 Wind Turbine Scaling and Control Outline Introduction

More information

Adaptive Resource and Job Management for limited power consumption

Adaptive Resource and Job Management for limited power consumption Adaptive Resource and Job Management for limited power consumption 02/07/14 Bull, 2012 Yiannis Georgiou David Glesser Matthieu Hautreux Denis Trystram 1 Introduction High Performance Computing Target:

More information

OStrich: Fair Scheduler for Burst Submissions of Parallel Jobs. Krzysztof Rzadca Institute of Informatics, University of Warsaw, Poland

OStrich: Fair Scheduler for Burst Submissions of Parallel Jobs. Krzysztof Rzadca Institute of Informatics, University of Warsaw, Poland Krzysztof Rzadca Institute of Informatics, University of Warsaw, Poland! joint work with: Filip Skalski (U Warsaw / Google)! based on work with: Vinicius Pinheiro (Grenoble) Denis Trystram (Grenoble) http://www.flickr.com/photos/bobjagendorf/345683620/

More information

Real-Time Distributed Control for Smart Electric Vehicle Chargers: From a Static to a Dynamic Study

Real-Time Distributed Control for Smart Electric Vehicle Chargers: From a Static to a Dynamic Study IEEE TRANSACTIONS ON SMART GRID, VOL. 5, NO. 5, SEPTEMBER 2014 2295 Real-Time Distributed Control for Smart Electric Vehicle Chargers: From a Static to a Dynamic Study Omid Ardakanian, Student Member,

More information

Selective Coordination

Selective Coordination Circuit Breaker Curves The following curve illustrates a typical thermal magnetic molded case circuit breaker curve with an overload region and an instantaneous trip region (two instantaneous trip settings

More information

Chapter 22: Firm Supply

Chapter 22: Firm Supply Econ 33 Microeconomic Analysis Chapter : Firm Supply Instructor: Hiroki Watanabe Fall Watanabe Econ 33 Firm Supply / 8 Warning. (An Awkward Representation) In supply/demand analysis, an explanatory variable

More information

Throughput Maximization for Laser-Powered UAV Wireless Communication Systems

Throughput Maximization for Laser-Powered UAV Wireless Communication Systems Throughput Maximization for Laser-Powered UAV Wireless Communication Systems Jie Ouyang, Yueling Che, Jie Xu, and Kaishun Wu School of Computer Science and Software Engineering, Shenzhen University School

More information

The Charging-Scheduling Problem for Electric Vehicle Networks

The Charging-Scheduling Problem for Electric Vehicle Networks The Charging-Scheduling Problem for Electric Vehicle Networks Ming Zhu, Xiao-Yang Liu, Linghe Kong, Ruimin Shen, Wei Shu, Min-You Wu Shanghai Jiao Tong University, China Singapore University of Technology

More information

Some new distance-4 constant weight codes

Some new distance-4 constant weight codes Some new distance-4 constant weight codes A. E. Brouwer & T. Etzion 2010-02-18 Abstract Improved binary constant weight codes with minimum distance 4 and length at most 28 are constructed. A table with

More information

A Viewpoint on the Decoding of the Quadratic Residue Code of Length 89

A Viewpoint on the Decoding of the Quadratic Residue Code of Length 89 International Journal of Networks and Communications 2012, 2(1): 11-16 DOI: 10.5923/j.ijnc.20120201.02 A Viewpoint on the Decoding of the Quadratic Residue Code of Length 89 Hung-Peng Lee Department of

More information

Maximum A Posteriori Inference in Sum-Product Networks (Supplementary Material)

Maximum A Posteriori Inference in Sum-Product Networks (Supplementary Material) Maximum A Posteriori Inference in Sum-Product Networks (Supplementary Material) Jun Mei, Yong Jiang, Kewei Tu ShanghaiTech University {meijun,jiangyong,tukw}@shanghaitech.edu.cn Proof of Lemma 1 Lemma

More information

White Paper. Stator Coupling Model Analysis By Johan Ihsan Mahmood Motion Control Products Division, Avago Technologies. Abstract. 1.

White Paper. Stator Coupling Model Analysis By Johan Ihsan Mahmood Motion Control Products Division, Avago Technologies. Abstract. 1. Stator Coupling Model Analysis By Johan Ihsan Mahmood Motion Control Products Division, Avago Technologies White Paper Abstract In this study, finite element analysis was used to optimize the design of

More information

DESIGN AND EXPERIMENTATION OF TEST RIG TO CHARACTERIZE HYDROSTATIC DRIVEFOR LINEAR ACTUATOR

DESIGN AND EXPERIMENTATION OF TEST RIG TO CHARACTERIZE HYDROSTATIC DRIVEFOR LINEAR ACTUATOR DESIGN AND EXPERIMENTATION OF TEST RIG TO CHARACTERIZE HYDROSTATIC DRIVEFOR LINEAR ACTUATOR Sherif Elbaz 1, Moatasem 2, Ibrahim 3, Nabila 4, Mohamed 5 1 Automotive Engineering Department, Ain-Shames University,

More information

FLUID FLOW Introduction General Description

FLUID FLOW Introduction General Description FLUID FLOW Introduction Fluid flow is an important part of many processes, including transporting materials from one point to another, mixing of materials, and chemical reactions. In this experiment, you

More information

H. Hadera 1,2, I. Harjunkoski 1, G. Sand 1, I. E. Grossmann 3, S. Engell 2 1

H. Hadera 1,2, I. Harjunkoski 1, G. Sand 1, I. E. Grossmann 3, S. Engell 2 1 H. Hadera 1,2, I. Harjunkoski 1, G. Sand 1, I. E. Grossmann 3, S. Engell 2 1 ABB Corporate Research Germany, 2 Technical University of Dortmund Germany, 3 Carnegie Mellon University US Bi-level Heuristic

More information

Transmission Error in Screw Compressor Rotors

Transmission Error in Screw Compressor Rotors Purdue University Purdue e-pubs International Compressor Engineering Conference School of Mechanical Engineering 2008 Transmission Error in Screw Compressor Rotors Jack Sauls Trane Follow this and additional

More information

Scheduling Electric Vehicles

Scheduling Electric Vehicles Scheduling Electric Vehicles M.E. van Kooten Niekerk J.M. van den Akker J.A. Hoogeveen Technical Report UU-CS-2015-013 October 2015 Department of Information and Computing Sciences Utrecht University,

More information

This white paper details how these critical engineering factors should be addressed when designing and sizing a screw jack system.

This white paper details how these critical engineering factors should be addressed when designing and sizing a screw jack system. Critical Factors in Sizing and Designing a Screw jack System Abstract At Motion Technologies we re not afraid to redesign customer concepts in order to increase system performance and save our customers

More information

POST-WELD TREATMENT OF A WELDED BRIDGE GIRDER BY ULTRASONIC IMPACT TREATMENT

POST-WELD TREATMENT OF A WELDED BRIDGE GIRDER BY ULTRASONIC IMPACT TREATMENT POST-WELD TREATMENT OF A WELDED BRIDGE GIRDER BY ULTRASONIC IMPACT TREATMENT BY William Wright, PE Research Structural Engineer Federal Highway Administration Turner-Fairbank Highway Research Center 6300

More information

Effect of Geometry Factor I & J Factor Multipliers in the performance of Helical Gears

Effect of Geometry Factor I & J Factor Multipliers in the performance of Helical Gears Effect of Geometry Factor I & J Factor Multipliers in the performance of Helical Gears 1 Amit D. Modi, 2 Manan B. Raval, 1 Lecturer, 2 Lecturer, 1 Department of Mechanical Engineering, 2 Department of

More information

INDUCTION motors are widely used in various industries

INDUCTION motors are widely used in various industries IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 44, NO. 6, DECEMBER 1997 809 Minimum-Time Minimum-Loss Speed Control of Induction Motors Under Field-Oriented Control Jae Ho Chang and Byung Kook Kim,

More information

Menu-Based Pricing for Charging of Electric. Vehicles with Vehicle-to-Grid Service

Menu-Based Pricing for Charging of Electric. Vehicles with Vehicle-to-Grid Service Menu-Based Pricing for Charging of Electric 1 Vehicles with Vehicle-to-Grid Service Arnob Ghosh and Vaneet Aggarwal arxiv:1612.00106v1 [math.oc] 1 Dec 2016 Abstract The paper considers a bidirectional

More information

Technical Report Con Rod Length, Stroke, Piston Pin Offset, Piston Motion and Dwell in the Lotus-Ford Twin Cam Engine. T. L. Duell.

Technical Report Con Rod Length, Stroke, Piston Pin Offset, Piston Motion and Dwell in the Lotus-Ford Twin Cam Engine. T. L. Duell. Technical Report - 1 Con Rod Length, Stroke, Piston Pin Offset, Piston Motion and Dwell in the Lotus-Ford Twin Cam Engine by T. L. Duell May 24 Terry Duell consulting 19 Rylandes Drive, Gladstone Park

More information

LIFE CYCLE COSTING FOR BATTERIES IN STANDBY APPLICATIONS

LIFE CYCLE COSTING FOR BATTERIES IN STANDBY APPLICATIONS LIFE CYCLE COSTING FOR BATTERIES IN STANDBY APPLICATIONS Anthony GREEN Saft Advanced and Industrial Battery Group 93230 Romainville, France e-mail: anthony.green@saft.alcatel.fr Abstract - The economics

More information

KINEMATICAL SUSPENSION OPTIMIZATION USING DESIGN OF EXPERIMENT METHOD

KINEMATICAL SUSPENSION OPTIMIZATION USING DESIGN OF EXPERIMENT METHOD Jurnal Mekanikal June 2014, No 37, 16-25 KINEMATICAL SUSPENSION OPTIMIZATION USING DESIGN OF EXPERIMENT METHOD Mohd Awaluddin A Rahman and Afandi Dzakaria Faculty of Mechanical Engineering, Universiti

More information

Human interaction in solving hard practical optimization problems

Human interaction in solving hard practical optimization problems Human interaction in solving hard practical optimization problems Richard Eglese Professor of Operational Research Department of Management Science Lancaster University Management School Lancaster, U.K.

More information

FAN ENGINEERING. Application Guide for Selecting AC Motors Capable of Overcoming Fan Inertia ( ) 2

FAN ENGINEERING. Application Guide for Selecting AC Motors Capable of Overcoming Fan Inertia ( ) 2 FAN ENGINEERING Information and Recommendations for the Engineer Twin City Fan FE-1800 Application Guide for Selecting AC Motors Capable of Overcoming Fan Inertia Introduction Bringing a fan up to speed

More information

Investigation of Relationship between Fuel Economy and Owner Satisfaction

Investigation of Relationship between Fuel Economy and Owner Satisfaction Investigation of Relationship between Fuel Economy and Owner Satisfaction June 2016 Malcolm Hazel, Consultant Michael S. Saccucci, Keith Newsom-Stewart, Martin Romm, Consumer Reports Introduction This

More information

ISO 7401 INTERNATIONAL STANDARD. Road vehicles Lateral transient response test methods Open-loop test methods

ISO 7401 INTERNATIONAL STANDARD. Road vehicles Lateral transient response test methods Open-loop test methods INTERNATIONAL STANDARD ISO 7401 Third edition 2011-04-15 Road vehicles Lateral transient response test methods Open-loop test methods Véhicules routiers Méthodes d'essai de réponse transitoire latérale

More information

Degradation-aware Valuation and Sizing of Behind-the-Meter Battery Energy Storage Systems for Commercial Customers

Degradation-aware Valuation and Sizing of Behind-the-Meter Battery Energy Storage Systems for Commercial Customers Degradation-aware Valuation and Sizing of Behind-the-Meter Battery Energy Storage Systems for Commercial Customers Zhenhai Zhang, Jie Shi, Yuanqi Gao, and Nanpeng Yu Department of Electrical and Computer

More information

Data envelopment analysis with missing values: an approach using neural network

Data envelopment analysis with missing values: an approach using neural network IJCSNS International Journal of Computer Science and Network Security, VOL.17 No.2, February 2017 29 Data envelopment analysis with missing values: an approach using neural network B. Dalvand, F. Hosseinzadeh

More information

Maximum Weight Relaxed Cliques and Russian Doll Search Revisited

Maximum Weight Relaxed Cliques and Russian Doll Search Revisited Maximum Weight Relaxed Cliques and Russian Doll Search Revisited Timo Gschwind a, Stefan Irnich a, Isabel Podlinski b a Chair of Logistics Management, Gutenberg School of Management and Economics, Johannes

More information

APPLICATION OF VARIABLE FREQUENCY TRANSFORMER (VFT) FOR INTEGRATION OF WIND ENERGY SYSTEM

APPLICATION OF VARIABLE FREQUENCY TRANSFORMER (VFT) FOR INTEGRATION OF WIND ENERGY SYSTEM APPLICATION OF VARIABLE FREQUENCY TRANSFORMER (VFT) FOR INTEGRATION OF WIND ENERGY SYSTEM A THESIS Submitted in partial fulfilment of the requirements for the award of the degree of DOCTOR OF PHILOSOPHY

More information

A Dynamic Programming Heuristic for the Vehicle Routing Problem with Time Windows and the European Community Social Legislation

A Dynamic Programming Heuristic for the Vehicle Routing Problem with Time Windows and the European Community Social Legislation A Dynamic Programming Heuristic for the Vehicle Routing Problem with Time Windows and the European Community Social Legislation A. Leendert Kok Operational Methods for Production and Logistics, University

More information

Application of Airborne Electro-Optical Platform with Shock Absorbers. Hui YAN, Dong-sheng YANG, Tao YUAN, Xiang BI, and Hong-yuan JIANG*

Application of Airborne Electro-Optical Platform with Shock Absorbers. Hui YAN, Dong-sheng YANG, Tao YUAN, Xiang BI, and Hong-yuan JIANG* 2016 International Conference on Applied Mechanics, Mechanical and Materials Engineering (AMMME 2016) ISBN: 978-1-60595-409-7 Application of Airborne Electro-Optical Platform with Shock Absorbers Hui YAN,

More information

Pareto Local Search Algorithms for Anytime Bi-Objective Optimization

Pareto Local Search Algorithms for Anytime Bi-Objective Optimization Université Libre de Bruxelles Institut de Recherches Interdisciplinaires et de Développements en Intelligence Artificielle Pareto Local Search Algorithms for Anytime Bi-Objective Optimization Jérémie Dubois-Lacoste,

More information

EXPERIMENT 8 CURRENT AND VOLTAGE MEASUREMENTS

EXPERIMENT 8 CURRENT AND VOLTAGE MEASUREMENTS EXPERMENT 8 CURRENT AND VOLTAGE MEASUREMENTS Structure 8.1 ntroduction 8.2 Aim 8.3 Getting to Know Ammeters and Voltmeters 8.4 Ammeters and Voltmeters in DC Circuits V Characteristics of a Resistor V Characteristics

More information

Evaluating Selective Coordination Between Current-Limiting Fuses And Non Current-Limiting Circuit Breakers

Evaluating Selective Coordination Between Current-Limiting Fuses And Non Current-Limiting Circuit Breakers Evaluating Selective Coordination Between And Non Current-Limiting Circuit Breakers Tech Topics: Selective Coordination Note 1, Issue 1 Steve Hansen Sr. Field Engineer Robert Lyons Jr. Product Manager

More information

Circuit Analysis Questions A level standard

Circuit Analysis Questions A level standard 1. (a) set of decorative lights consists of a string of lamps. Each lamp is rated at 5.0 V, 0.40 W and is connected in series to a 230 V supply. Calculate the number of lamps in the set, so that each lamp

More information