ORIGINAL_ARTICLE
Effective Calculation of Multiple Solutions of Mixed Convection in a Porous Medium
This paper considers an important model of boundary value problem with a condition at infinity namely combined free and forced convection over a plane of arbitrary shape embedded in a fluid-saturated porous medium; this model admits dual solutions, and uses a technique, which is to some extent modification of homotopy analysis method (HAM), in order to obtain dual solutions analytically with high accuracy.
http://miscj.aut.ac.ir/article_20_89475039f668eb455baf0b5a70e2b898.pdf
2012-03-01T11:23:20
2017-11-19T11:23:20
1
6
10.22060/miscj.2012.20
Homotopy analysis method
rule of multiplicity of solutions
prescribed parameter
convergence-controller parameter
S.
Abbasbandy
true
1
Corresponding Author, S. Abbasbandy is with the Department of Mathematics, Imam Khomeini International University, Qazvin, Iran (e-mail:
abbasbandy@yahoo.com).
Corresponding Author, S. Abbasbandy is with the Department of Mathematics, Imam Khomeini International University, Qazvin, Iran (e-mail:
abbasbandy@yahoo.com).
Corresponding Author, S. Abbasbandy is with the Department of Mathematics, Imam Khomeini International University, Qazvin, Iran (e-mail:
abbasbandy@yahoo.com).
LEAD_AUTHOR
E.
Shivanian
true
2
E. Shivanian is with the Department of Mathematics, Imam Khomeini International University, Qazvin, Iran (e-mail: shivanian@ikiu.ac.ir).
E. Shivanian is with the Department of Mathematics, Imam Khomeini International University, Qazvin, Iran (e-mail: shivanian@ikiu.ac.ir).
E. Shivanian is with the Department of Mathematics, Imam Khomeini International University, Qazvin, Iran (e-mail: shivanian@ikiu.ac.ir).
AUTHOR
[1] S. J. Liao, Beyond Perturbation: Introduction to the Homotopy Analysis Method, Chapman Hall CRC/Press, Boca Raton, 2003.
1
[2] T. Hayat, N. Ahmed, M. Sajid, S. Asghar, “On the MHD flow of a second grade fluid in a porous channel,” Comput Math Appl,vol. 3, pp. 549-557, Apr. 1988. 2007;54:14-40.
2
[3] S. Abbasbandy, “Soliton solutions for the 5th-order KdV equation with the homotopy analysis method,” Nonlinear Dyn,vol. 51, pp. 83-87, Apr. 2008.
3
[4] S. Abbasbandy, “The application of the homotopy analysis method to solve a generalized Hirota-Satsuma coupled KdV equation,” Phys Lett A, vol. 361, pp. 478-483, Apr. 2007.
4
[5] S. Abbasbandy , “The application of the homotopy analysis method to nonlinear equations arising in heat transfer,” Phys Lett A, vol. 360, pp. 109-113, Apr. 2006.
5
[6] S. P. Zhu, “An exact and explicit solution for the valuation of American put options,” Quant Fin, vol. 6, pp. 229-242, Apr.2006.
6
[7] M. Yamashita, K. Yabushita, K. Tsuboi, “An analytic solution of projectile motion with the quadratic resistance law using the homotopy analysis method,” J Phys A, vol. 40, pp. 8403-8416,Apr. 2007.
7
[8] Y. Bouremel, “Explicit series solution for the Glauert-jet problem by means of the homotopy analysis method,” Commun Nonlinear Sci Numer Simulat, vol. 12(5), pp. 714-724, Apr.2007.
8
[9] L. Tao, H. Song, S. Chakrabarti, “Nonlinear progressive waves in water of finite depth-an analytic approximation,” vol. 54, pp.549825-834, Apr. 2007.
9
[10] H. Song H, L. Tao, “Homotopy analysis of 1D unsteady,nonlinear groundwater flow through porous media,” J Coastal Res, vol. 50, pp. 292-305, Apr. 2007.
10
[11] A. S. Bataineh, M. S. M. Noorani, I. Hashim, “Solutions of timedependent Emden–Fowler type equations by homotopy analysis method,” Phys Lett A, vol. 371, pp. 72-82, Apr. 2007.
11
[12] Z. Wang, L. Zou, H. Zhang, “Applying homotopy analysis method for solving differential-difference equation,” Phys Lett A, vol. 369, pp. 77-84, Apr. 2007.
12
[13] Inc. Mustafa, “On exact solution of Laplace equation with Dirichlet and Neumann boundary conditions by the homotopy analysis method,” Phys Lett A, vol. 365, pp. 412-415, Apr. 2007.
13
[14] S. Abbasbandy, E. Magyari, E. Shivanian, “The homotopy analysis method for multiple solutions of nonlinear boundary value problems,” Commun Nonlinear Sci Numer Simulat, vol.14, pp. 3530-3536, Apr. 2009.
14
[15] S. Abbasbandy, E. Shivanian, “Prediction of multiplicity of solutions of nonlinear boundary value problems: novel application of homotopy analysis method,” Commun Nonlinear Sci Numer Simulat, vol. 15, pp. 3830-3846, Apr. 2010.
15
[16] A. Nakayama, H. Koyama, “A general similarity transformation for combined free and forced-convection flows within a fluidsaturated
16
porous medium,” ASME J. Heat Trans, vol. 109, pp. 1041-1045, Apr. 1987.
17
[17] E. Magyari, I. Pop, B. Keller, “Exact dual solutions occurring in Darcy mixed convection flow,” Int Journal Heat Mass Transf, vol. 44, pp. 4563-4566, Apr. 2001.
18
ORIGINAL_ARTICLE
A Fuzzy Based Approach for Rate Control in Wireless Multimedia Sensor Networks
Wireless Multimedia Sensor Networks (WMSNs) undergo congestion when a link (or a node) becomes overpopulated in terms of incoming packets. In WMSNs this happens especially in upstream nodes where all incoming packets meet and directed to the sink node. Congestion in networks, if not handled properly, might lead to congestion collapse which deteriorates the quality of service (QoS). Therefore, in order to avoid such situations corresponding actions should be taken into account so that to yield lower packet loss and consequently energy loss that is of utmost importance in WSNs. However, the term "packet loss" as implied by today's literature might not be effective in many applications especially in multimedia sensor networks. In this paper a new weighted packet loss metric is proposed which is best suited for multimedia sensor networks that convey packets of different priority classes. The proposed method then tries to minimize the aforementioned criterion by means of fuzzy queue management and a newly introduced adaptive rate control mechanism, in the presence of both abrupt and gradual changes in network dynamics. The employment of these two techniques provides us a synergy to handling short term and long term variations arising through the underlying simulated networks. The simulation results approve the superiority of the proposed approach over the selected competitive method when dealing with packets of different priorities.
http://miscj.aut.ac.ir/article_21_e6b10af493697232d9aa7b3948f3a51a.pdf
2012-03-01T11:23:20
2017-11-19T11:23:20
7
20
10.22060/miscj.2012.21
Adaptive rate control
Multimedia sensor networks
Fuzzy queue management
Mohammad Hossein
Yaghmaee Moghaddam
yaghmaee@ieee.org
true
1
Corresponding Author, M.H. Yaghmaee Moghaddam is with the Department of Computer Engineering and Center of Excellence on Soft
Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran (e-mail: yaghmaee@ieee.org).
Corresponding Author, M.H. Yaghmaee Moghaddam is with the Department of Computer Engineering and Center of Excellence on Soft
Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran (e-mail: yaghmaee@ieee.org).
Corresponding Author, M.H. Yaghmaee Moghaddam is with the Department of Computer Engineering and Center of Excellence on Soft
Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran (e-mail: yaghmaee@ieee.org).
LEAD_AUTHOR
Hamid Reza
Hassanzadeh
true
2
Hamid Reza Hassanzadeh is a graduate student in Department of Computer Engineering, Ferdowsi University of Mashhad (FUM), Mashhad,
Iran (e-mail:ha.hassanzadeh@ieee.org)
Hamid Reza Hassanzadeh is a graduate student in Department of Computer Engineering, Ferdowsi University of Mashhad (FUM), Mashhad,
Iran (e-mail:ha.hassanzadeh@ieee.org)
Hamid Reza Hassanzadeh is a graduate student in Department of Computer Engineering, Ferdowsi University of Mashhad (FUM), Mashhad,
Iran (e-mail:ha.hassanzadeh@ieee.org)
AUTHOR
[1] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey, Computer Networks 38 (4) (2002) 393– 422.
1
[2] I.F. Akyildiz, T. Melodia, T.R. Chowdhury, A survey on wireless multimedia sensor networks, Computer Networks 51 (2007) 921–960.
2
[3] V. Jacobson, Congestion Avoidance and Control, Symposium proceeding on communications architecture and protocols, (1988) 314-329.
3
[4] Yassine Hadjadj Aoul, Ahmaed Mehaoua, Charalabos Skianis, A Fuzzy Logic-Based AQM for Real-Time Traffic Over Internet, Computer Networks 51 (2007) 4617-4633.
4
[5] S. Floyd, K. Fall, Random early detection gateways for congestion avoidance, IEEE/ACM Transactions on Networking (August) (1993).
5
[6] Zadeh, L.: Fuzzy Sets, Information and Control, 8:338 – 353, (1965).
6
[7] Zargar, S.T., Yaghmaee, M.H.; Fard, A.M , Fuzzy Proactive Queue Management Technique, Annual India Conference, (2006).
7
[8] Tapio Frantti, Fuzzy Congestion Control In Packet Networks, Springer Berlin / Heidelberg, Volume 2/2005.
8
[9] B. Safaiezadeh, A.M. Rahmani, E. Mahdipour, A New Fuzzy Congestion Control in Computer Networks, International Conference on Future Computer and Communication, (2009) 314-318 .
9
[10] C.N. Nyirenda, D.S. Dawoud, “Self-Organization in a Particle Swarm Optimized Fuzzy Logic Con gestion Detection Mechanism for IP Networks”, Submitted to Scientia Iranica, International Journal of Science and Technology.
10
[11] C. Wang, Member, K. Sohraby, M. Daneshmand, Y. Hu, Upstream congestion control in wireless sensor networks through cross-layer optimization, IEEE Journal on Selected Areas in Communications 25 (4) (2007) 786–795.
11
[12] C.-T. Ee, R. Bajcsy, Congestion control and fairness for many-to one routing in sensor networks, in: Proceedings of ACM Sensys, November 2004.
12
[13] C.-Y. Wan, S.B. Eisenman, A.T. Campbell, CODA: congestion detection and avoidance in sensor networks, in: Proceedings of ACM Sensys’03, Los Angeles, CA, November 5–7, 2003.
13
[14] H. Zhang et al., Reliable bursty convergecast in wireless sensor networks, in: Proceedings of ACM Mobihoc’05, Urbana-Champain, IL, May 25–28, 2005.
14
[15] Mohammad Hossein Yaghmaee a,*, Donald A. Adjeroh, Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks, Computer Networks 53 (2009) 1798–1811.
15
ORIGINAL_ARTICLE
Large Deformation Characterization of Mouse Oocyte Cell Under Needle Injection Experiment
In order to better understand the mechanical properties of biological cells, characterization and investigation of their material behavior is necessary. In this paper hyperelastic Neo-Hookean material is used to characterize the mechanical properties of mouse oocyte cell. It has been assumed that the cell behaves as continuous, isotropic, nonlinear and homogenous material for modeling. Then, by matching the experimental data with finite element (FE) simulation result and using the Levenberg–Marquardt optimization algorithm, the nonlinear hyperelastic model parameters have been extracted. Experimental data of mouse oocyte captured from literatures. Advantage of the developed model is that it can be used to calculate accurate reaction force on surgical instrument or it can be used to compute deformation or force in virtual reality based medical simulations.
http://miscj.aut.ac.ir/article_22_a9d39c83e5424cb747323f7c1d1c8ea4.pdf
2012-03-01T11:23:20
2017-11-19T11:23:20
21
25
10.22060/miscj.2012.22
Biological cells
Levenberg–Marquardt optimization algorithm
Inverse finite element
Hyperelastic material
Ali A.
Abbasi
true
1
Corresponding Author, School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran, Email: Ali.eng.edu@gmail.com.
Corresponding Author, School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran, Email: Ali.eng.edu@gmail.com.
Corresponding Author, School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran, Email: Ali.eng.edu@gmail.com.
LEAD_AUTHOR
M.T.
Ahmadian
true
2
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology,
Tehran, Iran.
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology,
Tehran, Iran.
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology,
Tehran, Iran.
AUTHOR
[1] C.T. Lim, E.H. Zhou, and S.T. Quek, "Mechanical models for living cells—a review,” Journal of Biomechanics, vol. 39, pp.195–216. 2006.
1
[2] Y. Tan, D. Sun, W. Huang, and S. Han Cheng, "Characterizing Mechanical Properties of Biological Cells by Microinjection,” IEEE Transactions on Nanobioscience, Vol. 9, No. 3, September 2010.
2
[3] F.P.T. Baaijens, W.R. Trickey, T.A. Laursen, and F. Guilak, "Large deformation ﬁnite element analysis of micropipette aspiration to determine the mechanical properties of the chondrocyte". Annals of Biomedical Engineering, vol.33, No.4, pp. 494–501. 2005.
3
[4] Y. Tan, D. Sun, and W. Huang, “Mechanical modeling of red blood cells during optical stretching,” J. Biomech. Eng.-Trans. ASME, vol. 132, pp. 044504, 2010.
4
[5] Y. Kim, J. H. Shin, and J. Kim, “Atomic Force Microscopy Probing for Biomechanical Characterization of Living Cells,” Proceedings of the 2nd Biennial IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics Scottsdale, AZ, USA, October 19-22, 2008.
5
[6] M.T. Ahmadian, G.R. Vossoughi, A.A. Abbasi, P. Raeissi,“Modeling Of Cell Deformation Under External Force Using Artificial Neural Network” , Proceedings of the ASME 2010 International Mechanical Engineering Congress & Exposition, November 12-18, 2010, Vancouver, British Columbia, Canada.
6
[7] M.T. Ahmadian, G.R. Vossoughi, A.A. Abbasi, P. Raeissi, “Cell Deformation Modeling Under External Force Using Artificial Neural Network” Journal of Solid Mechanics Vol. 2, No. 2, pp 190-198. 2010.
7
[8] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Deformation Prediction Of Mouse Embryos In Cell Injection Experiment By A Feed forward Artificial Neural Network” Proceedings of the ASME International Design Engineering Technical Conferences &Computers and Information in Engineering Conference, August 29-31, 2011, Washington, DC, USA.
8
[9] A. A. Abbasi, H. Sayyaadi, G.R. Vossoughi, “Sensitivity Analysis Of Mouse Embryos In Needle Injection Experiment Using Artificial Neural Network”, 2nd International Conference on Future Information Technology (ICFIT 2011), 16-18 September 2011, Singapore.
9
[10] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Deformation Prediction By A Feed forward Artificial Neural Network during mouse embryo micromanipulation” Animal cells and systems, Vol. 16, No. 2, pp.121-126,2012.
10
[11] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Application Of Adaptive Neural Fuzzy Inference Technique For Biological Cell Modeling –Part A:Deformation Prediction” 2nd International Conference on Future Information Technology (ICFIT 2011), 16-18 September 2011, Singapore.
11
[12] A. A. Abbasi, G.R. Vossoughi, M.T. Ahmadian “Application of Adaptive Neural Fuzzy Inference Technique for Biological Cell Modeling –Part B: Prediction of External Applied Force”, 2nd International Conference on Future Information Technology (ICFIT 2011), 16-18 September 2011, Singapore.
12
[13] L.G. Alexopoulos, M.A. Haider, T.P. Vail, and F. Guilak, “Alterations in the mechanical properties of the human chondrocyte pericellular matrix with osteoarthritis”. Journal of Biomechanical Engineering 125 (3), 323–333, 2003.
13
[14] E.H. Zhou, C.T. Lim, and S.T. Quek, “Finite element simulation of the micropipette aspiration of a living cell undergoing large viscoelastic deformation” Mechanics of Advanced Materials and Structures, vol. 12, No. 6, pp. 501–512, 2005.
14
[15] T. Boudou, J. Ohayon, Y. Arntz, G. Finet, C. Picart, P. Tracqui,. An extended modeling of the micropipette aspiration experiment for the characterization of the Young’s modulus and Poisson’s ratio of adherent thin biological samples: numerical and experimental studies. Journal of Biomechanics, vol. 39 No. 9, pp.1677–1685, 2006.
15
[16] M. Flückiger, “Cell Membrane Mechanical Modeling for Microrobotic Cell Manipulation”, Diploma Thesis, ETHZ Swiss Federal Institute of Technology, Zurich, WS03/04, 2004.
16
[17] Y. Sun, K.T. Wan, K.P. Roberts, J.C. Bischof, and B.J. Nelson, “Mechanical Property Characterization of Mouse Zona Pellucida” IEEE Transactions on Nanobioscience, vol. 2, pp.279-286, 2003.
17
[18] A. Bummo and J. Kim, “an Efficient Soft Tissue Characterization Method for Haptic Rendering of Soft Tissue Deformation in Medical Simulation”, Frontiers in the Convergence of Bioscience and Information Technologies 2007.IEEE.
18
[19] Abaqus/CAE user’s manual, Version 6.9, Inc., Providence, RI, USA, 2009.
19
[20] W.H. Press, S.A. Teukolsky, W.T. Vetterling and B.P. Flannery, Numerical recipes in C++. The art of scientiﬁc computing, second ed. Cambridge University Press, 1992.
20
[21] A. A. Abbasi, “Modeling of biological cells with applications to the design of a nano-micro gripper used in cell manipulation”, M.S. thesis, Sharif University of technology, Tehran, Iran, 2011.
21
[22] E. Samur, M. Sedef, C. Basdogan, L. Avtan and O. Duzgun, “A robotic indenter for minimally invasive measurement and characterization of soft tissue response”, Medical Image Analysis vol. 11, pp. 361–373, 2007.
22
ORIGINAL_ARTICLE
Cross-layer Packet-dependant OFDM Scheduling Based on Proportional Fairness
This paper assumes each user has more than one queue, derives a new packet-dependant proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new cross-layer packet-dependant OFDM scheduling schemes based on proportional fairness for heterogeneous classes of traffic. Scenario 1, scenario 2 and scenario 3 lead respectively artificial fish swarm algorithm, self-adaptive particle swarm optimization algorithm and cloud adaptive particle swarm optimization algorithm into sub-carrier allocation in packet-dependant proportional fairness scheduling, and use respectively new power allocation pattern, self-adaptive particle swarm optimization algorithm and population migration algorithm to allocate power. Scenario 4 uses greedy algorithm concerning fairness to allocate sub-carriers, and uses new power allocation pattern to allocate power. Simulation indicates scenario 1,scenario 2 and scenario 3 raise the system’s total rate on the basis of undertaking the fairness among users’ rates and average packet delay; scenario 4 not only meets users’ rates and average packet delay demands, but also improve the fairness among users’ rates.
http://miscj.aut.ac.ir/article_23_39b25d9619b2d099ae23d55916fc0eab.pdf
2012-03-01T11:23:20
2017-11-19T11:23:20
27
39
10.22060/miscj.2012.23
Multi-user OFDM
Scheduling
Proportional fairness
Swarm Intelligence Algorithm
Cross-layer
Resource allocation
Particle Swarm algorithm
Population migration algorithm
Artificial fish swarm algorithm
Packet-dependant
Hua
Hou
true
1
Corresponding Author Hua Hou is with school of Information Science and Electrical Engineering, Hebei University of Engineering, Handan ,
P.R.China ( Email: hh110040@gmail.com).
Corresponding Author Hua Hou is with school of Information Science and Electrical Engineering, Hebei University of Engineering, Handan ,
P.R.China ( Email: hh110040@gmail.com).
Corresponding Author Hua Hou is with school of Information Science and Electrical Engineering, Hebei University of Engineering, Handan ,
P.R.China ( Email: hh110040@gmail.com).
LEAD_AUTHOR
Gen-
xuan
true
2
Gen-xuan Li is with School of Information Science and Electrical Engineering, Hebei University of Engineering, Handan , P.R.China ( Email:
hh110040@gmail.com ).
Gen-xuan Li is with School of Information Science and Electrical Engineering, Hebei University of Engineering, Handan , P.R.China ( Email:
hh110040@gmail.com ).
Gen-xuan Li is with School of Information Science and Electrical Engineering, Hebei University of Engineering, Handan , P.R.China ( Email:
hh110040@gmail.com ).
AUTHOR
[1] Y.L. Liu, M.Y. Jiang.Adaptive resource allocation in multiuser OFDM system based on hopfield neural networks. JOURNAL OF CIRCUITS AND SYSTEMS,2010,15(2):47-51.
1
[2] D.X. Yu, Y.M. Cai,D. Wu,W. Zhong.Subcarrier and Power Allocation Based on Game Theory in Uplink OFDMA Systems. Journal of Electronics and Information Technology,2010,32(4):775-779.
2
[3] L. Peng, M.Y. Jiang. Adaptive cross-layer resource allocation scheme resisting delay sensibility. Application Research of Computers, 2010,27(3):1122-1125.
3
[4] N.Zhou, X.zhu, Y.Huang, H.Lin. Low Complexity Cross-Layer Design with Packet Dependent Scheduling for Heterogeneous Traffic in Multiuser OFDM Systems. Wireless Com.,IEEE,Jun.2010,9(6):1912– 1923.
4
[5] Z.K.Shen, J.G. Andrews, B.L. Evans. Adaptive Resource Allocation in Multiuser OFDM Systems With Proportional Rate Constraints. IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, NOVEMBER 2005,4(6): 2726-2737.
5
[6] X. Ma,Q. Liu. Artificial fish swarm algorithm for multiple knapsack problem. Journal of Computer Applications, 2010,30(2):469-471.
6
[7] Y.M. Cheng, M.Y. Jiang. Adaptive resource allocation in multiuser OFDM system based on improved artificial fish swarm algorithm. Application Research of Computers, 2009,26(6):2092-2094.
7
[8] X.J. Bi, W.W. Cao. Adaptive sub-carrier allocation for an orthogonal frequency division multiple access system based on a particle swarm optimization algorithm. Journal of Harbin Engineering University,2010,32(4):775-779.
8
[9] K. Niu, W.W. Sun, W.J. Xu, Z.Q. He.The Distributed Power Allocation used in OFDMA systems Based on Particle Swarm Optimization Algorithm. China,201010033918.8,2010.
9
[10] J. Li, Ch. Wang. A modified self-adaptive particle swarm optimization.Journal of Huazhong University of Science and Technology(Natural Science Edition),2008,36(3):118-121.
10
[11] X.Q. Wei,Y.Q. Zhou,H.J. Huang,D.X. Luo. Adaptive particle swarm optimization algorithm based on cloud theory.Computer Engineering and Application, 2009,45(1):48-50.
11
[12] A.J.OuYang, W.W. Zhang, Y.Q. Zhou. Hybrid global optimization algorithm based on simplex and population migration.Computer Engineering and Applications, 2010,46(4):29-31.
12
ORIGINAL_ARTICLE
Investigating Effective Parameters in Tactile Determination of Artery included in Soft Tissue by FEM
One of the newest ways of surgery is known as Minimally Invasive Surgery (MIS), which in spite of its benefits, because of surgeon's tactile sensing omission, causes some problems with detection of arteries and their exact positions in tissue during a surgery. In this study, tactile detection of an artery in tissue has been modeled by finite element method. In this modeling, three 2D models of tissue have been created: tissue, tissue including a tumor, and tissue including an artery. After solving the three models with similar boundary conditions and loadings, the 2D tactile mappings and stress graphs for upper nodes of models, which have the role of transferring tactile data, have been explored. Comparing these results showed that stress graphs of upper nodes of tissue including an artery is time-dependent. However, for two other models it is constant. Then, the effect of variation of different parameters of the model on artery detection such as tissue thickness, artery diameter, and elastic module of artery wall has been studied.
http://miscj.aut.ac.ir/article_24_59ce0e8b12caca0b813954ad0b0151e8.pdf
2012-04-01T11:23:20
2017-11-19T11:23:20
41
46
10.22060/miscj.2012.24
Soft tissue
artery
tactile detection
physical properties
Finite Element Method (FEM)
Ali
Abouei Mehrizi
true
1
A. Abouei Mehrizi is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
abouei.ali@gmail.com).
A. Abouei Mehrizi is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
abouei.ali@gmail.com).
A. Abouei Mehrizi is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
abouei.ali@gmail.com).
AUTHOR
Siamak
Najarian
najarian@aut.ac.ir
true
2
Corresponding Author, S. Najarian is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
najarian@aut.ac.ir).
Corresponding Author, S. Najarian is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
najarian@aut.ac.ir).
Corresponding Author, S. Najarian is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email:
najarian@aut.ac.ir).
LEAD_AUTHOR
Majid
Moini
true
3
M. Moini is with Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran (email:
moinim@hotmail.com).
M. Moini is with Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran (email:
moinim@hotmail.com).
M. Moini is with Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran (email:
moinim@hotmail.com).
AUTHOR
Pedram
Pahlavan
true
4
P. Pahlavan is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email: pe_pedram@yahoo.com).
P. Pahlavan is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email: pe_pedram@yahoo.com).
P. Pahlavan is with the Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran (email: pe_pedram@yahoo.com).
AUTHOR
Javad
Dargahi
true
5
Professor J. Dargahi, Mechanical &Industrial Engineering Dept., Concordia University, Montreal, Canada.
Professor J. Dargahi, Mechanical &Industrial Engineering Dept., Concordia University, Montreal, Canada.
Professor J. Dargahi, Mechanical &Industrial Engineering Dept., Concordia University, Montreal, Canada.
AUTHOR
[1] A. Abouei Mehrizi, S. Najarian and M. Moini, "Modeling of tactile detection of an artery in a soft tissue by finite element analysis," Amirkabir Journal of Science and technology, to be published.
1
[2] W. J. Peine, "Remote palpation instruments for minimally invasive surgery," Ph.D. dissertation, Div. of Eng. and Appl. Sci., HarvardUniversity, 1998.
2
[3] J. Dargahi and S. Najarian, "Human tactile perception as a standard for artificial tactile sensing- a review”, Inter. J. of Med. Rob. Comp. Ass. Surg., vol. 1, pp. 23-35, 2004.
3
[4] M. E. H. Eltaib and J. R. Hewit, "Tactile sensing technology for minimal access surgery-a review", Mechatronics, vol. 13, p.p. 1163-1177, 2003.
4
[5] J. Dargahi and S. Najarian, "A Supported membrane type sensor for medical tactile mapping", Sensor Review, vol. 24, pp. 284-297, 2004.
5
[6] S. M. Hosseini, S. Najarian, S. Motaghinasab, and J. Dargahi, "Detection of tumors using computational tactile sensing approach", Inter. J. of Med. Rob. Comp. Ass. Surg., vol. 2, no. 4, p.p. 333-340, 2006.
6
[7] S. M. Hosseini, S. Najarian, S. Motaghinasab, "Analysis of effects of tumors in tissue using of artificial tactile modeling", Amirkabir Journal, to be published.
7
[8] S. M. Hosseini, S. Najarian, S. Motaghinasab, and S. Torabi, "Experimental and numerical verification of artificial tactile sensing approach for predicting tumor existence in virtual soft tissue", Proc. of the 15th Annual-International Conf. of Mechanical Engineering, 2007.
8
[9] P. Dario, M. Bergamasco, "An advanced robot system for automated diagnostic tasks through palpation" IEEE Trans. on Biomed. Eng., vol. 35, no. 2, p.p. 118-26, 1988.
9
[10] W. J. Peine, S. Son, and R. D. Howe, "A palpation system for artery localization in laparoscopic surgery", First Inter. Symp. on Medical Robotics and Computer-Assisted Surgery, Pittsburgh, 1994.
10
[11] R. A. Beasley and R. D. Howe, "Tactile tracking of arteries in robotic surgery", Proc. of IEEE, International Conf. on Robotics&Automation, Washington, DC, 2002.
11
[12] M. H. Lee and H. R. Nicholls, "Review article tactile sensing for mechatronics-a state of the art survey", Mechatronics, vol. 9, pp. 1-31, 1999.
12
[13] D. J. Mozersky, D. Sumnfer, D.E. Hokanson, and D.E. Strandness, "Transcutaneous measurement of the elastic properties of the human femoral artery", Circulation AHA Journal, v. XLVI, 1972.
13
[14] A. E. Kerdoke, S. M. Cotin, M. P. Ottensmeyer, A. M. Galea, R. D. Howe, and S. L. Dawson, "Truth cube: establishing physical standard for soft tissue simulation", Med. Imag. Anal., vol. 7, pp. 283-291, 2003.
14
ORIGINAL_ARTICLE
A Multi-Period 1-Center Location Problem in the Presence of a Probabilistic Line Barrier
This paper investigates a multi-period rectilinear distance 1-center location problem considering a line-shaped barrier, in which the starting point of the barrier follows the uniform distribution function. In addition, the existing points are sensitive to demands and locations. The purpose of the presented model is to minimize the maximum barrier distance from the new facility to the existing facilities during the finite planning horizon. Additionally, a lower bound problem is generated. The presented model is mixed-integer nonlinear programming (MINLP); however, an optimum solution is reached.
http://miscj.aut.ac.ir/article_25_c26e80baa39e9d5b08064f8580171215.pdf
2012-04-01T11:23:20
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47
55
10.22060/miscj.2012.25
Multi-period Center location problem
Probabilistic line barrier
Rectilinear distance
M.
Amiri-Aref
true
1
AUTHOR
N.
Javadian
true
2
AUTHOR
R.
Tavakkoli-Moghaddam
true
3
AUTHOR
M. B.
Aryanezhad
true
4
AUTHOR
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1
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[9] C. Canel, B. M. Khumawala, J. Law and A. Loh, “An algorithm for the capacitated, multi-commodity multi-period facility location problem,” Computers and Operations Research, vol. 28, pp. 411–427, 2001.
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[21] R. Z. Farahani, Z. Drezner, and N. Asgari, “Single facility location and relocation problem with time dependent weights and discrete planning horizon,” Annals of Operations Research, vol. 167, pp. 353–368, 2009.
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[23] L. Frieß, K. Klamroth and M. Sprau, “A wavefront approach to center location problems with barriers,” Annals of Operations Research, vol. 136, pp. 35–48, 2005.
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[26] H. W. Hamacher, and K. Klamroth, “Planar Weber location problems with barriers and block norms,” Annals of Operations Research, vol. 96, pp. 191–208, 2000.
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[30] Y. Hinojosa, J. Puerto, and F. R. Fernández, “A multiperiod two-echelon multicommodity capacitated plant location problem,” European Journal of Operational Research, vol. 123, pp. 271–291, 2000.
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[33] H. Kelachankuttu, R. Batta, and R. Nagi, “Contour line construction for a new rectangular facility in an existing layout with rectangular departments,” European Journal of Operational Research, vol. 180, pp. 149–162, 2007.
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[35] Klamroth, K. “A reduction result for location problems with polyhedral barriers,” European Journal of Operational Research, vol. 130, pp. 486–497, 2001.
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[43] P. Nandikonda, R. Batta and R. Nagi, “Locating a 1-center on a Manhattan plane with ‘arbitrarily’ shaped barriers,” Annals of Operations Research, vol. 123, pp. 157–172, 2003.
43
[44] S. Nickel, “Restricted center problems under polyhedral gauges,” European Journal of Operational Research, vol. 104, pp. 343–357, 1998.
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47
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[51] T. Van Roy, D. Erlenkotter, “A dual-based procedure for dynamic facility location,” Management Science, vol. 28, pp. 1091–1105, 1982.
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[54] R. Z. Farahani and M. Hekmatfar, Facility location: Concepts, models, algorithms and case studies, Berlin: Physica-Verlag, 2009, p. 347.
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55
Papers from Conference Proceedings (Published):
56
[56] S. Shiripour, I .Mahdavi, M. Amiri-Aref, M. Mohammadnia-Otaghsara, “A Nonlinear Programming Model for a Multi-Facility Location Problem with a Probabilistic Line Barrier” in Proc. International Conference on Industrial Engineering and Engineering Management (IEEM) 2010 IEEE, pp. 630-634.
57
ORIGINAL_ARTICLE
Numerical Computation Of Multi-Component Two-Phase Flow in Cathode Of PEM Fuel Cells
A two-dimensional, unsteady, isothermal and two-phase flow of reactant-product mixture in the air-side electrode of proton exchange membrane fuel cells (PEMFC) is studied numerically in the present study. The mixture is composed of oxygen, nitrogen, liquid water and water vapor. The governing equations are two species conservation, a single momentum equation for mobile mixture, liquid mass conservation, and the whole mixture mass conservation. In this study, liquid mass conservation is used to calculate the saturation, so, the effect of liquid phase velocity and also saturation at previous time step are accounted in calculating the next time step saturation. The capillary pressure was used to express the slip velocity between the phases. The strongly coupled equations are solved using the finite volume SIMPLER scheme of Patankar (1984). The computational domain consists of an open area (gas delivery channel), and a porous Gas Diffusion Layer (GDL). A single set of governing equations are solved for both sub domains with respect to each sub domain property. The comparison between the numerical current density and that of experimental (Ticianelli et al.(1988)) shows a good agreement.
http://miscj.aut.ac.ir/article_26_883c61d4b0c6a8f0efcb5eab77b35183.pdf
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57
65
10.22060/miscj.2012.26
CFD
PEM Fuel Cells
Two-Phase
Two Component
M.
Khakbaz Baboli
true
1
Graduate Student, member of Energy Conversion Research Laboratory, Department of Mechanical Engineering Amirkabir University of
Technology (Tehran Polytechnic) Tehran, Iran, 15875—4413, mobinkhakbaz@gmail.com.
Graduate Student, member of Energy Conversion Research Laboratory, Department of Mechanical Engineering Amirkabir University of
Technology (Tehran Polytechnic) Tehran, Iran, 15875—4413, mobinkhakbaz@gmail.com.
Graduate Student, member of Energy Conversion Research Laboratory, Department of Mechanical Engineering Amirkabir University of
Technology (Tehran Polytechnic) Tehran, Iran, 15875—4413, mobinkhakbaz@gmail.com.
AUTHOR
M. J.
Kermani
true
2
AUTHOR
[1] Bird, R.B., Steward, W. and Lightfoot, E.N., 2002, ``Transport Phenomena'', Wiley, New York.
1
[2] Ticianelli, E. A., Derouin, C. R., Redondo, A. and Srinivasan S.,1988,``Methods to Advance Technology of Proton Exchange Membrane Fuel Cells'' J. of The Electrochem. Soc., 135, 2209.
2
[3] Bernardi, D.M., Verbrugge M.W., 1991, ``Mathematical model of a gas diffusion electrode bonded to a polymer electrolyte'', AIChE J., 37 1151–-1163.
3
[4] Bernardi, D.M., Verbrugge M.W., 1992, ``A mathematical model for the solid-polymer-electrode fuel cell'', J. of The Electrochem. Soc.,139 2477–-2491.
4
[5] Springer, F.E., Zawodzinski, T.A., Gottesfeld S., 1991,``Polymer electrolyte fuel cell model'', J. Electrochem. Soc., 138 2334–-2342.
5
[6] Nguyen, T.V., White, R.E.,1993 , ``A water and thermal management model for proton-exchange-membrane fuel cells'', J. Electrochem. Soc., 140 2178–-2186.
6
[7] Gurau, V., Liu, H.T., Kakac, S.,1998 , ``Two-dimensional model for proton exchange membrane fuel cells'', AIChE J., 44 2410-–2422.
7
[8] Wang, Z.H., Wang, C.Y., Chen, K.S., 2001, ``Two-phase flow and transport in the air cathode of PEM fuel cells'', J. Power Source, 94 40–-50.
8
[9] Natarajan, D. and Nguyen, T. V., 2001, ``A Two-Dimensional, Two-phase, Multicomponent, Transient Model for the Cathode of a Proton Exchange Fuel Cell Using Conventional Gas Distributors'', J. of The Electrochem. Soc., 148 (12) A1324--A1335
9
[10] You, L. and Liu, H., 2002, ``A two-phase flow and transport model for the cathode of PEM fuel cells'', Int. J. of Heat and Mass Transfer, 45 2277–-2287
10
[11] Parthasarathy, A., Srinivasan, S., Appleby, J. A. and Martin, C. R., 1992,``Temperature Dependence of the Electrode Kinetics of Oxygen Reduction at the Platinum/Na on Interface – A Microelectrode Investigation'', J. of The Electrochem. Soc., 139(9):2530–-2537.
11
[12] Nguyen, P. T. B.E.Sc., 2003, ``A Three-Dimensional Computational Model of PEM Fuel Cell with Serpentine Gas Channels'', University of Western Ontario.
12
[13] Nam, J. H.; Kaviany, M., 2003, ``Effective Diffusivity and Water-Saturation Distribution in Single- and Two-Layer PEMFC Diffusion Medium'', Int. J. Heat and Mass Transfer, 46, 4595--4611.
13
[14] Khakbaz Baboli, M., 2007, ``A Two-Dimensional Computational model of cathode electrode of PEM fuel cells'', M.Sc. Thesis, Department of Mechanical Engineering, Amirkabir University of Technology (Tehran polytechnic), Tehran, Iran.
14