2013
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7
7
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A Machine Learning Approach to NoReference Objective Video Quality Assessment for High Definition Resources
روش یادگیری ماشین برای ارزیابی کیفیت ویدئو بدون مرجع برای منابع با کیفیت بسیار بالا
2
2
The video quality assessment must be adapted to the human visual system, which is why researchers have performed subjective viewing experiments in order to obtain the conditions of encoding of video systems to provide the best quality to the user. The objective of this study is to assess the video quality using image features extraction without using reference video. RMSE values and processing time of SVR for BMP and JPEG formats in quality assessment were 0.78×102, 0.81×102, 6.0s and 4.8s, respectively. In this study, a metric system for noreference assessing the video quality is presented using wavelet transform and generalized Gaussian distribution parameters. Results of ITUBT tests for each video were used to train SVR and its performance for video frames is evaluated
1

1
7
ناصر
فرج زاده
Nacer
Farajzadeh
Iran
nfarajzadeh@azaruniv.edu
ملیحه
مظلومی
Maliheh
Mazloumi
Iran
mmazloumi@iauahar.ac.ir
Video quality assessments
Generalized Gaussian distribution
Wavelet Transform
[1] Juan Pedro López Velasco (2012). Video Quality Assessment, Video Compression, Dr. Amal Punchihewa (Ed.), ISBN: 97895351 04223, InTech. ##[2] M. P. Eckert and A. P. Bradley, "Perceptual quality metrics applied to still image compression," Signal Processing, vol. 70, pp. 177200, Nov. 1998 ##[3] A. M. Eskicioglu and P. S. Fisher, “Image quality measures and their performance,” IEEE Trans Communications, vol. 43, pp. 2959 2965, Dec. 1995. ##[4] ITUR Recommendation BT.50011, “Methodology for the subjective assessment of the quality of television pictures,” Geneva, 2002 (available at www.itu.org). ##[5] Y. K. Lai and C.C. J. Kuo, "A Haar wavelet approach to compressed image quality measurement," Journal of Visual Communication and Image Understanding, vol. 11, pp. 1740, Mar. 2000. ##[6] Z. Wang, A. C. Bovik and L. Lu, “Why is image quality assessment so difficult?” Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Proc., vol. 4, pp. 33133316, May 2002. ##[7] J. Lubin, “A visual discrimination model for image system design and evaluation,” in Visual Models for Target Detection and Recognition, E. Peli, ed., pp. 207220, Singapore: World Scientific Publisher, 1995. ##[8] Zhou Wang, Hamid R. Sheikh and Alan C. Bovik, OBJECTIVE VIDEO QUALITY ASSESSMENT, Chapter 41 in The Handbook of Video Databases: Design and Applications, B. Furht and O. Marqure, ed., CRC Press, pp. 10411078, September 2003. ##[9] Z. Wang, A. C. Bovik and B. L. Evans, “Blind measurement of blocking artifacts in images,” Proc. IEEE Int. Conf. Image Proc., vol. 3, pp. 981984, Sept. 2000. ##[10] P. Gastaldo, S. Rovetta and R. Zunino, “Objective assessment of MPEGvideo quality: a neuralnetwork approach,” in Proc. IJCNN, vol. 2, pp. 14321437, 2001. ##[11] Kawayokeita, Y. ; Horita, Y., NR objective continuous video quality assessment model based on frame quality measure, Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on, Year: 2008, Page(s): 385 – 388. ##[12] N. DameraVenkata, T. D. Kite, W. S. Geisler, B. L. Evans, and A. C. Bovik, "Image quality assessment based on a degradation model," IEEE Trans. Image Processing, vol. 4, pp. 636 650, Apr. 2000. ##[13] Sharifi, K. and LeonGarcia, A. (1995). Estimation of shape parameter for generalized Gaussian distribution in subband decomposition of video. IEEE Trans. onCircuits and Systems for Video Technology, Vol 5, No. 1 Feb. 1995 pp. 5256 ##[14] Choi, S. Cichocki, A. and Amari, S. (2000) Local stability analysis of flexible independent component analysis algorithm. Proceedings of 2000 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP2000, Istanbul, Turkey, June 59, 2000, pp. 34263429. ##[15] Wu, H.C. y Principe, J. (1998). Minimum entropy algorithm for source separation. Proceedings of the 1998 Mindwest symposium on Systems and Circuits. ##[16] J. M. Shapiro, “Embedded image coding using zerotrees of wavelet coefficient,” vol. 41, pp. 34453462, Dec. 1993. ##[17] Drucker, Harris; Burges, Christopher J. C.; Kaufman, Linda; Smola, Alexander J.; and Vapnik, Vladimir N. (1997); "Support Vector Regression Machines", in Advances in Neural Information Processing Systems 9, NIPS 1996, 155–161, MIT Press. ##[18] R. C. Gonzalez and R. E. Woods, Digital Image Processing (2nd Edition). Prentice Hall, 2002.##]
Analysis of MultiRobots Transportation with Multiobjective PSO Algorithm in an Artificial Capital Market
تجزیه و تحلیل حمل و نقل روبات ها با الگوریتم pso چند منظوره در بازار سرمایه مصنوعی
2
2
In this paper, to analyze the transport of autonomous robots, an artificial Capital market is used. Capital market is considered as a pier which loading and unloading of cargo is done. Autonomous robots load and unload from the ship to the warehouse wharf or vice versa. All the robots have the ability of transporting the loads, but depending on loads and the location of unloading (or loading) and position of robots, robots have different role in unloading tasks. The role of robots and their number is decided, planned, and managed by the partial swarm optimization (PSO) algorithm. The main goal of the paper is to optimize a multiobject function (MOF) which is a combination of total work time and fuel cost functions. In this paper, a new method of transporting from ships to warehouses and vice versa was developed and presented considering the cost of fuel and the shortest possible time.
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8
15
داود
آشیانی
Davod
Ashiany
Iran
dashiany@iauahar.ac.ir
سعید
حسین سعادتی
Seied
Hosein Sadati
Iran
sadati@kntu.ac.ir
عبدالرضا
صدیق منش
Abdolreza
Sadighmanesh
Iran
asadighmanesh@iauahar.ac.ir
PSO algorithm
Multiobject function
autonomous robots
artificial capital market
market mechanism
[[1] S. Zhiguo, H. Zhangzheng, L. Xu, Z. Fia; W., Zhiliang, 2010, Collaboration scenario of the mobile robot and household applicances based on IGRS protocol, 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR), Wuhan. ##[2] F. Palacín, F. A. Salse, I. Valgañón, and X. Clua, 2004, Building a mobile robot for a floorcleaning operation in domestic environments, IEEE Trans. Instrum. Meas., vol. 53, no. 5, pp. 1418–1424, Oct. ##[3] H. Wang, M. Zhang, F. Wang, 2010, Design and implementation of an Emergency Search and Rescue System based on mobile robot and WSN, 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR), Wuhan. ##[4] D. Ding and R. A. Cooper, 2005, Electricpowered wheelchairs: A review of current technology and insight into future direction, IEEE Control Syst. Mag., vol. 25, no. 2, pp. 22–34, Apr. ##[5] S. Y. Oh, F. H. Lee, and D. H. Choi, 2000, A new reinforcement learning vehicle control architecture for visionbased road following, IEEE Trans. Veh. Technol., vol. 49, no. 3, pp. 997–1005, May. ##[6] R Zlot, A Stentz, "Marketbased multirobot coordination for complex tasks", The International Fournal of Robotics Research, 2006 ##[7] ] Russell, S. F. and Norvig, P. (2003). Artificial Intelligence: a Modern Approach. Prentice Hall, Englewood Cliffs, NF, 2nd edition ##[8] Sycara, K. (1998). Multiagent systems. AI Magazine, 19(2):79–92. ##[9] Cramton, P., Shoham, Y., and Steinberg, R., editors (2006). Combinatorial Auctions. MIT Press, Cambridge, MA. ##[10] Kitano, H., Tambe, M., Stone, P., Veloso, M., Coradeschi, S., Osawa, E., Matsubara, H., Noda, I., and Asada, M. (1997). The RoboCup synthetic agent challenge 97. In Proc. Int. Foint Conf. on Artificial Intelligence, Nagoya, Fapan ##[11] M. Dorigo and E. Sahin. Special issue: Swarm robotics. Autonomous Robots, 17:111–113, 2004. ##[12] E. Sahin. Swarm robotics: From sources of inspiration to domains of application. In E. Sahin and William Spears, editors, Swarm Robotics Workshop: Stateoftheart Survey, number 3342 in Lecture Notes in Computer Science, pages 10–20, Berlin Heidelberg, 2005. SpringerVerlag. ##[13] G. Caprari and R. Siegwart. Mobile microrobots ready to use: Alice. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3295– 3300, Edmonton, Alberta, Canada, 2005. ##[14] Christopher M. Cianci, Xavier Raemy, Jim Pugh, and Alcherio Martinoli. Communication in a Swarm of Miniature Robots: The ePuck as an Educational Tool for Swarm Robotics. In Simulation of Adaptive Behavior (SAB2006), Swarm Robotics Workshop, Lecture Notes in Computer Science (LNCS), 2006. ##[15] University of Stuttgart. Opensource microrobotic project, 2007. ##[16] F. Mondada, G. C. Pettinaro, A. Guignard, I. Kwee, D. Floreano, J.L. Deneubourg, S. Nolfi, L. M. Gambardella, and M. Dorigo. SWARMBOT: a New Distributed Robotic Concept. Autonomous Robots, special Issue on Swarm Robotics, 17(23):193–221, 2004. September  November 2004 Sponsor: swarmbots, OFES 0100121. ##[17] J. McLurkin and J. Smith. Distributed algorithms for dispersion in indoor environments using a swarm of autonomous mobile robots. In 7th International Symposiumon Distributed Autonomous Robotic Systems, Framce, 2004. ##[18] C. Ortiz, K. Konolige, R. Vincent, B. Morisset, A. Agno, M. Eriksen, D. Fox, B. Limketkai, J. Ko, B. Stewart, and D. Schulz. Centibots: Very large scale distributed robotic teams. In D. L. McGuinness and G. Ferguson, editors, AAAI, pages 1022–1023. AAAI Press / The MIT Press, 2004. ##[19] A. E. Turgut, F. G¨ok¸ce, H. C¸ elikkanat, L. Bayındır, and E S¸ahin. Kobot: A mobile robot designed specifically for swarm robotics research. Technical Report METUCENGTR 200705, Dept. of Computer Engineering, Middle East Technical University, 2007. ##[20] I.J. Cox and N.H. Gehani, Concurrent programming and robotics, Journal of Robotics Research 8 (2) ##[21] T. LozanoPerez, Robot programming, Proc. of the IEEE, Vol. 71, No. 7, (1983). ##[22] C. McGillem and T. Rappaport. "An Infrared Navigation Technique for Mobile Robots," Proc. 1988 IEEE lntnl. Conf on Robotics and Autornation, Philadelphia, PA, Apr. 26, 1988. ##[23] Ray Jarvis, “A Teleautonomous Heavy Duty Robotic Lawn Mower,” Proc. 2001 Australian Conference on Robotics and Automation, Sydney, pp.157161,2001. ##[24] Masanao Koeda, Yoshio Matsumoto, Tsukasa Ogasawara. “Annotationbased Rescue Assistance System for Teleoperated Unmanned Helicopter with Wearable Augmented Reality Environment,” 2005 IEEE International Workshop on Safety, Security and Rescue##]
Application of NonLinear Functions at Distribution of Output SINR Gaussian Interference Channels
استفاده از توابع غیر خطی برای توریع کانال های خروجی گاوسی SINR
2
2
We have examined the convergence behavior of the LSCMA in some simple environments. Algorithms such as Multi¬ Target CMA, Multistage CMA, and Iterative Least Squares with Projection can be used for this purpose. The results presented here can form a basis for analysis of these multisignal extraction techniques. Clearly, the variance and distribution of output SINR obtained with the LSCMA is also an important area for investigation. We finally comment on the hardlimit nonlinearity. For high SIR, the hardlimiter is the optimal nonlinearity when the desired signal has a constant envelope. However, at low SIR other nonlinearities can yield greater SIR gain. Thus, it is possible that nonlinear functions other than the hardlimit can be used to develop blind adaptive algorithms, which converge faster for low initial SINR.
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16
23
توحید
صاذقی
Tohid
Sedghi
Iran
sedghi.tohid@gmail.com
شاهین
شافعی
Shahin
Shafei
Iran
shahin_shafei1987@yahoo.com
[[1] T. E. Biedka, W. H. Tranter, and J. H. Reed, "Convergence analysis of the least squares constant modulus algorithm Application of NonLinear Functions at Distribution … 23 interference cancellation applications", IEEE Trans. on Commun., vol. 48, no. 3, pp. 491501, March 2011. ##[2] A.L. Swindlehurst, S. Daas, and J. Yang, "Analysis of a decision directed beamformer",IEEE Trans. on Signal Processing., vol. 43, no. 12, pp. 2920 2927, December 2005. ##[3] 1. S. Reed, J. D. Mallett, and L. E. Brennan, "Rapid convergence rate in adaptive arrays", IEEE Trans. Aerospace Electron. Syst., vol. AES10, pp. 853863, Nov. 2004. ##[4] B. G. Agee, "Convergent behavior of modulusrestoring adaptive arrays in gaussian interference environments", Proc. of the Asilomar Conf. on Signals, Systems, and Computers, pp. 818822, Dec. 2008. ##[5] J. Lundell and B. Widrow, "Application of the constant modulus adaptive beamformer to constant and nonconstant modulus signals", Proc. of the Asilomar Conf. on Signals, Systems, and Computers, pp. 432 436, Nov. 2007 [6] ] J. R. Treichler and B. G. Agee, "A new approach to multipath correction of constant modulus signals", IEEE Trans. on Acous., Speech, and Signal Process., vol. ASSP31, no. 2, pp. 459471, April 2003. ##[7] R. Gooch and J. Lundell, "The CM array: An adaptive beamformer for constant modulus signals", Proc. of Inter. Conf. on Acous., Speech, and Signal Process., pp. 25232526, April 2006. ##[8] B. G. Agee, "The leastsquares CMA: A new technique for rapid correction of constant modulus signals", Proc. of Inter. Conf. on Acous., Speech, and Signal Process., pp. 953956, April 2006. ##[9] B.G. Agee, "Maximum likelihood approaches to blind adaptive signal extraction using narrowband arrays", Proc. of the Asilomar Conf. on Signals, Systems, and Computers, pp. 716720, Nov. 2011. ##[10] AlleJan van der Veen and A. Paulraj, "An analytical constant modulus algorithm", IEEE Trans. Signal Processing, vol. 44, no. 5, pp. 11361155, May 2006.##]
Using Program Slicing Technique to Reduce the Cost of Software Testing
استفاده ار تکنیک برش برنامه برای کاهش هزینه های تست نرم افزار
2
2
Systems of computers and their application in the lives of modern human beings are vastly expanding. In any kind of computer application, failure in computer systems can lead to a range of financial and mortal losses. Indeed, the major origin of software failure can be located in designing or implementing software. With regard to these statistics, 30% of the software projects have been prosperous and successful. The proposed method is intended to reduce the cost and time of testing and it focuses on enhancing the efficiency of software testing methods. In this paper, we investigated the effect of slicing techniques on the reduction rate of testing cost and time. The results of experiments show that we can cover a large number of program instructions, branches and paths by a small number of test cases in the sliced program
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24
33
اصغر
محمدیان
Asghar
Mohammadian
Iran
asgharmohammadian@gmail.com
بهمن
آراسته
Bahman
Arasteh
Iran
Software Testing
cost
Program slicing
coverage
[[1] M.R. Lyu, “Handbooks of Software Reliability Engineering”, ISBN 0 070394008, IEEECS Press, 1995. ##[2] R.S. Pressman & Associates, “Software Engineering: A Practitioner's Approach, 6/e”, copyright 2005. ##[3] T. Adams, “Total Variance Approach to Software Reliability Estimation”, IEEE Trans.SoftwareEngineering,Vol.22, No.9,1996,pp.687688. ##[4] P. Popic, D. Desovski, W. Abdelmoez, and B. Cukie, “Error Propagation in the Reliability Analysis of Component Based Systems,” Intel Symposium. Software Reliability Eng.,pp.53 62,2005. ##[5] B. Beizer, “Software Testing Techniques”, Second Edition. New York: Van Nostrand Reinhold, 1990. ##[6] A. Bertolino and M. Marre´, “How Many Paths Are Needed for Branch Testing?” The J. Systems and Software, vol. 35, no. 2, pp. 95 106, Nov. 1996. ##[7] P.G. Frankl and E.J. Weyuker, “An Applicable Family of Data Flow Testing Criteria” IEEE Trans. Software Eng., vol. 14, no. 10, pp. 1483 1498, Oct. 1988. ##[8] M. Marre and A. Bertolino, “Reducing and Estimating the Cost of Test Coverage Criteria,” Proc. 18th Int’l Conf. Software Eng. (ICSE 18), pp. 486494, Mar. 1996. ##[9] S. Rapps and E.J. Weyuker, “Selecting Software Test Data Using Data Flow Information,” IEEE Trans. Software Eng., vol. 11, no. 4, pp. 367375, Apr. 1985. ##[10] G. Rothermel, M.J. Harrold, J. Ostrin, and C. Hong, “Empirical Study of the Effects of Minimization on the Fault Detection Capabilities of Test Suites,” Int’l Conf. Software Maintenance, pp. 3443, Nov. 1998. ##[11] W.E. Wong, J.R. Horgan, S. London, and A.P. Mathur, “Effect of Test Set Minimization on Fault Detection Effectiveness,” Proc. 17th Int’l ##[12] C. R. Reeves, “Modern Heuristic Techniques for Combinatorial Problems”, McGrawHill, 1995. ##[13] D. Corne, M. Dorigo, and F. Glover, editors. “New Ideas in Optimization”, McGrawHill, 1999. ##[14] A. Mockus, "Test Coverage and PostVerification Defects: A Multiple Case Study", In the 3rd International Symposium on Empirical Software Engineering and Measurement, ESEM 2009. ##[15] Y. Wei, “Is Coverage a Good Measure of Testing Effectiveness?”, Chair of software engineering ETH Zurich, CH8092 Zurich, Switzerland. ##[16] H. Pham, “System Software Reliability”, Springer Series in Reliability Engineering, ISBN 0 070394008, SpringerVerlag London Limited 2006. ##[17] P. Ammann, J. Offutt, “Introduction to Software Testing”, CAMBRIDGE UNIVERSITY PRESS, ISBN 9780521880381, 2008. ##[18] 18 .G. A. Venkatesh, “The semantic approach to program slicing”, In ACM SIGPLAN Conference on Programming Language Design and Implementation, pages 26, 1991. ##[19] B. Korel, J. Rilling, “Dynamic program slicing methods”, Information and Software Technology special Issue on Program Slicing, volume 40, pages 647, 1998. ##[20] G. Canfora, A. Cimitile, “Conditioned program slicing”, Information and Software Technology special Issue on Program Slicing, volume 40, pages 595, 1998. ##[21] S. Horwitz, T. Reps, D. Binkley, “Interprocedural slicing using dependence graphs”, ACM Transactions on Programming Languages and Systems, 1990.##]
Electronical and Mechanical System Modeling of Robot Dynamics Using a Mass/Pulley Model
مدل سازی سیستم الکتریکی و مکانیکی دینامیک ربات با استفاده از مدل MP
2
2
The wellknown electromechanical analogy that equates current, voltage, resistance, inductance and capacitance to force, velocity, damping, spring constant and mass has a shortcoming in that mass can only be used to simulate a capacitor which has one terminal connected to ground. A new model that was previously proposed by the authors that combines a mass with a pulley (MP) is shown to simulate a capacitor in the general case. This new MP model is used to model the offdiagonal elements of a mass matrix so that devices whose effective mass is coupled between more than one actuator can be represented by a mechanical system diagram that is topographically parallel to its equivalent electric circuit model. Specific examples of this technique are presented to demonstrate how a mechanical model can be derived for both a serial and a parallel robot with both two and three degrees of freedom. The technique, however, is extensible to any number of degrees of freedom
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34
43
عطالله
رجب پور
Ata olah
Rajabpour
Iran
rajabpour_ata@yahoo.com
امیر
زارعی
amir
Zarei
Iran
آرزو
رجب پور
arezoo
Rajabpour
Iran
فاطمه
احمدی
Fatemeh
Ahmadi
Iran
Mass matrix
inertia matrix
MP model
pulley
differential transmission
mechanical system representation
robot dynamics
Impedance
equivalent electric circuit
[[1] Brune, O., 1931. "Synthesis of a finite twoterminal network whose drivingpoint impedance is a prescribed function of frequency". J. Math. Physics. vol. 10, pp. 191 236. ##[2] Craig, J.J., 2005. “Introduction to Robotics Mechanics and Control”. 3rd ed., Pearson Prentice Hall. ##[3] Eppinger, S., Seering, W., 1992. “Three Dynamic Problems in Robot Force Control”. IEEE Trans. Robotics & Auto., V. 8, No. 6, pp. 751758. ##[4] FairlieClarke, A.C., 1999. “Force as a Flow Variable”. Proc. Instn. Mech. Engrs., V. 213, Part I, pp. 7781. Foster, R. M., 1924. "A reactance theorem". Bell System Tech. J., vol. 3, pp. 259267. ##[5] Hamill, D.C., 1993. "Lumped Equivalent Circuits of Magnetic Components: The GyratorCapacitor Approach". IEEE Transactions on Power Electronics, vol. 8, pp. 97. ##[6] Hayward, V., Choksi, J., Lanvin, G., Ramstein, C., 1994. “Design and MultiObjective Optimization of a Linkage for a Haptic Interface”. Proc. of ARK „94, 4th Int. Workshop on Advances in Robot Kinematics (Ljubliana, Slovenia), pp. 352359. ##[7] Paynter, H.M., 1961. Analysis and Design of Engineering Systems. MIT Press. ##[8] Sass, L., McPhee, J., Schmitke, C., Fisette, P., Grenier, D., 2004. "A Comparison of Different Methods for Modelling Electromechanical Multibody Systems". Multibody System Dynamics, vol. 12, pp. 209250 ##[9] ligent Robots & Systems, (Raleigh, NC), pp. 1103,1110. ##[10] Stocco, L., Yedlin, M., Sept. 2006. “Closing the Loop on the ElectroMechanical System Analogy”. Submitted to: IEEE J. Circuits & Systems. ##[11] Tilmans, H.A.C., 1996. "Equivalent circuit representation of electromechanical transducers: I. Lumpedparameter systems". J. Micromech. Microeng, vol. 6, pp. 157176. ##[12] van Amerongen, J., Breedveld, P., 2003. "Modelling of physical systems for the design and control of mechatronic systems". Annual Reviews in Control, vol. 27, pp. 87117. Yamakita, M., Shibasato, H., Furuta, K., 1992. “Tele Virtual Reality of Dynamic Mechanical Model”. Proc. IEEE/RSJ Int. Conf. Int.##]
The New Design and Simulation of an Optical Add Drop Filter Based On Hexagonal Photonic Crystal Single Ring Race Track Resonator
س
2
2
In this paper, using annular resonator we have designed an adding and dropping filter light based ontwodimensional photonic crystals. The shape of ring resonator filter adding and dropping that wehave proposed is Race Track. This filter has a hexagonal lattice structure of silicon bars withrefractive index 3/46 that is located in the context of air with refractive index 1. Transmissionefficiency and quality coefficient of our proposed filter are respectively 94% and 310. Finite differencemethod in twodimensional time domain (2D FDTD) used for normalized transmission spectra ofphotonic crystal ring resonator and to calculate the photonic band, plane wave expansion method(PWE) has been used.
1
س
44
48
ابولفضل
عباسپور
Abolfazl
Abbaspour
Iran
abbaspour.abolfazl@yahoo.com
حامد
علیپور بنایی
Hamed
Alipour Banaei
Iran
h_alipour@tabrizu.ac.ir
علیرضا
عندلیب
Alireza
Andalib
Iran
andalib@iaut.ac.ir
Add drop filter Photonic Crystal
Race Track Ring Resonator
Optical Filter Based On Point Defects in 2D Photonic Crystal Structur
ا
2
2
In this paper, we proposed a novel structure for designing all optical filter based on photonic crystal structure. In designing the proposed filter, we simply employed a point defect localized between input and output waveguides as wavelength selecting part of the filter. The initial form of this filter is capable of selecting optical waves at =1560 nm, the transmission efficiency of the filter is 100%. In designing and studying the optical properties of the filter, we used plane wave expansion and finite difference time domain methods. After designing the filter, we studied the impact of different parameters on the filtering behavior of the structure. The total footprint of the filter is less than 100 100 m2. Simplicity of design and ultracompact dimensions are the most significant characteristics of our filter.
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49
65
آرزو
مالکی
Arezu
Maleki
Iran
arezumaleki@yahoo.com
Photonic Crystal
Optical filter
Defect
FDTD
[[1] F. Qiao, C. Zhang, J. Wan, and J. Zi, “Photonic quantumwell structures: multiple channeled filtering phenomena”, Applied Physics Letters 77 (2000) 3698–3701.##[2] Lin W. H., Wu C. J., Yang T. J., and Chang, S. J., Terahertz multichanneled filter in a superconducting photonic crystal, Optics Express, 18 (2010) pp. 2715527166.##[3] S. John,” Strong localization of photons in certain disordered dielectric superlattices” Physical Review Letters 58(23), 24862489 (1987).##[4] B. Rezaei, and M. Kalafi, Engineering absolute band gap in anisotropic hexagonal photonic##crystals, Optics communications 266 (2006) 159163.##[5] [5] H. AlipourBanaei, F. Mehdizadeh, “ Significant role of photonic crystal resonant cavities in WDM and DWDM communication tunable filters”, Optik (2012) http://dx.doi.org/10.1016/j.ijleo.2012.07.029.##[6] [6] A. Rostami, A. Haddadpour.F. Nazari and H. AlipourBanaei, “Proposal for an ultracompact tunable wavelengthdivisionmultiplexing optical filter based on quasi2D photonic crystals,” Iop J. Opt. 12 015405,##[7] M. Djavid, A. Ghaffari, F. Monifi, M.S. Abrishamian, “Tshaped channeldrop filters using photonic crystal ring resonators”, Physica E, 40 (2008) 31513154.##[8] A. Taalbi, G. Bassou, M. Y. Mahmoud,” New design of channel drop filters based on##photonic crystal ring resonators” Optik (2012), doi:10.1016/j.ijleo.2012.01.045.##[9] [9] S. G. Johnson, J. D. Joannopoulos, Blockiterative frequencydomain methods for##Maxwell’s equations in a plane wave basis, Opt. Express 8 (2001) 173–190.##]
A New Robust Control Design Based on Feedback Compensator for Sssc
A New Robust Control Design
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2
In this paper, the modified linearized PhillipsHeffron model is utilized to theoretically analyze asinglemachine infinitebus (SMIB) installed with SSSC. Then, the results of this analysis are used forassessing the potential of an SSSC supplementary controller to improve the dynamic stability of apower system. This is carried out by measuring the electromechanical controllability through singularvalue decomposition (SVD) analysis. This controller is tuned for simultaneously shifting theundamped electromechanical modes to a prespecifed area in the splane. The issue of designing arobustly SSSC based controller is considered and formulated as an optimization problem accordingto the eigenvaluebased multiobjective function consisting of the damping ratio of the undampedelectromechanical modes and the damping factor. Next, considering its high capability to find themost optimistic results, the Gravitational Search Algorithm (GSA) is used to solve this optimizationproblem. Wide ranges of operating conditions are considered in design process of the proposeddamping controller in order to guarantee its robustness. The effectiveness of the proposed controlleris demonstrated through eigenvalue analysis, controllability measure, nonlinear timedomainsimulation and some performance indices studies. The results show that the tuned GSA based SSSCcontroller which is designed by using the proposed multiobjective function has an outstandingcapability in damping power system low frequency oscillations, also it significantly improves thepower systems dynamic stability.
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54
65
علی
عجمی
Ali
Ajami
Iran
ajami@azaruniv.edu
احد
چهاندیده شندی
Ahad
Jahandideh Shendi
Iran
ajahandideh_msc@yahoo.com
Power system dynamic stability
SSSC
Gravitational Search Algorithm