ORIGINAL_ARTICLE
Technical possibility assessment of creating wind power station at Soltanieh zone of Zanjan province
Due to increasing expansion of energy consumption and also the decrease and tendency towardsending fossil energy reserves, the current energy cycle needs to use alternative energy speciallywind energy, because it’s considerably cheaper than other recycling sources. The presentresearch investigates suitable possibility of exploiting wind energy to create wind power stationin Soltanieh zone of Zanajn province by considering technical cases. Some researches have beencarried out on possibility assessment, measurement and comparison of power density. Intechnical possibility investigation, several turbines were investigated to calculate obtainableannual energy capacity coefficient of each turbine. Then these were compared to select the besttype of turbine. According to the results, wind turbine owned by Vestas Company, model V100,rated power of 1800 kW and capacity coefficient of 33.1% was selected as the best turbine.
http://jaiee.iau-ahar.ac.ir/article_516358_f42844019a80e8c5c277ab66da6f6854.pdf
2015-03-01T11:23:20
2017-09-26T11:23:20
1
7
Weibull distribution function
Wind turbine
Soltanieh
wind power density
technical possibility investigation
Davoud
Karimzadeh
davoudkarimzadeh@gmail.com
true
1
AUTHOR
REFERENCES
1
[1] Jain, Amit, Pramod Kumar Singh, and Kumar
2
Anurag Singh (2011). "Short term load
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Appl 32.1 (2011): 0975-8887.
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[6] Kaldellis, John K., and D. Zafirakis (2011).
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[7] Kostakis, Vasilis, Michail Fountouklis, and
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ORIGINAL_ARTICLE
An Evolutionary Method for Improving the Reliability of Safetycritical Robots against Soft Errors
Nowadays, Robots account for most part of our lives in such a way that it is impossible for usto do many of affairs without them. Increasingly, the application of robots is developing fastand their functions become more sensitive and complex. One of the important requirements ofRobot use is a reliable software operation. For enhancement of reliability, it is a necessity todesign the fault tolerance system. In this paper, we will present a genetic algorithm andlearning automata with high reliability to evaluate the software designed into the robotagainst soft-error with minimum performance over-head. This method relies on experiment;hence, we use the program sets as criteria in evaluation stages. Indeed, we have used the errorinjection method in the execution of experimental processes. Relevant data, regardingprogram execution behavior were collected and then analyzed. To evaluate the behavior ofprogram, errors entered using the simple scalar simulation software.
http://jaiee.iau-ahar.ac.ir/article_516359_77264f3b1658d9a4c16e8171e37cb5f8.pdf
2015-03-01T11:23:20
2017-09-26T11:23:20
8
17
Soft-Error
fault tolerance
Retrieval Blocks Technique
Evolutionary
Algorithms
Mahnaz
Mohammadzadeh
mmohammadzadeh1989@gmail.com
true
1
AUTHOR
Bahman
Arasteh
b_arasteh@iaut.ac.ir
true
2
AUTHOR
1] Rajabzadeh, G. Miremadi and M.
1
Mohandespour (1999). Error detection
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enhancement in COTS superscalar processors
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with performance monitoring features,Journal
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of Electronic Testing: Theory
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Application(JETTA), 20(5), pp. 553–67, 2004
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[2] Profeta, N. Andrianos, Yu. Bing, B. Johnson,
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T.DeLong and D.Guaspart, (1996). Safetycritical
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systems built with COTS, Computer,
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29(11), pp.54–60.
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[3] P. Tso and P. Galaviz, (1999). Improved
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aircraft readiness through COTS, In IEEE
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systems readiness technology conference
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(AUTOTESTCON_99), pp. 451–6.
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[4] M.Jafari-Nodoushan, G.Miremadi and A.Ejlali
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(2008). Control-Flow Checking Using Branc
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Instructions, In Proceeding of the 8th
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International Conference on Embedded and
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Ubiquitous Computing, 2008.
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[5] Yenier, U. (2003). Fault Tolerant Computing
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Techniques, Technical Report, Department of
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Computer Engineering, Bosphorus University,
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[6] A. Benso, S. Di Carlo, G. Di Natale, P.
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Prinetto, L.Tagliaferri, (2003). “Data
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Criticality Estimation in SoftwareAppliction”
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,INTERNATIONAL TEST CONFERENCE
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[7] D. Borodin and B.H.H. Juurlink, (2010). ”
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Protective Redundancy Overhead Reduction
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Using Instruction Vulnerability Factor”, ACM
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,CF’10, Italy
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[8] Shuguang Feng, Shantanu Gupta, Amin Ansari
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and Scott Mahlke (2010). “Shoestring:
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Probabilistic Soft-error Resilience on the
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Cheap,” in ASPLOS.
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[9] D. Thaker, D. Franklin, J. Oliver, S. Biswas,
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D. Lockhart, T. Metodi, and F. T. Chong
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(2006). “Characterization ofError-Tolerant
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Applications when Protecting Control Data,”In
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Proc. of the IEEE Int’l Symp. on Workload
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Characterization.
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[10] K. pattabiraman, Z. Kalbarczyk, R. Iyer
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(2011). “Automated Derivation of Application
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Aware Error Detectors Using Static Analysis:
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Trusted Approach”, IEEE Transaction on
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Dependable and Secure Computing, Volume 8
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, Issue 5.
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[11] T. Vijaykumar, I. Pomeranz and K. Chen,
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(2002). “ Transient Fault Recovery using
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Simultance Multithreading” , in 29th
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(2000). “C/C++ Source-to-Source Compiler
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for Dependable Applications”, in IEEE
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Mahnaz Mohammadzadeh, Bahman Arasteh: An Evolutionary Method for Improving…
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[13] A. Benso, S. Di Carlo, G. Di Natale, P.
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Prinetto, L. Tagliaferri, (2003). “Data
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Criticality Estimation in Software
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Application”, in International Test Conference,
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pp. 802-810.
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[14] B.Arasteh., A.Rahmani., A.Mansoor,
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GH.Miremadi (2012). ” Using Genetic
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Algorithm to Identify Soft-Error Derating
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Blocks of an Application
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Program”,EuromicroConference on Digital
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System Design,
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[15] D. E. Goldberg, (1989). “Genetic Algorithms
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in Search,Optimization and Machine
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Learning”, Reading, MA,Addition-Wesley.
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[16] P. Mars, K. S. Narendra, and M. Chrystall
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(1983). “Learning Automata Control of
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ComputerCommunication
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(1989). “Learning Automata: An
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[18] M. R. Meybodi, and S. Lakshmivarhan,
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(1983). “A Learning Approach to Priority
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University, 106-109
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(1989). “Learning Automata: An
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Distributed Learning Automata to Solve
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99
Report, Soft Computing Laboratory, Computer
100
Engineering Department, Amirkabir
101
University of Technology.
102
ORIGINAL_ARTICLE
Geoid Determination Based on Log Sigmoid Function of Artificial Neural Networks: (A case Study: Iran)
A Back Propagation Artificial Neural Network (BPANN) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. In this study, 261 GPS/Leveling and 8869 gravity intensityvalues of Iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“BPANN”, and “collocation” were evaluated. Finally obtained results were compared and bestthe method was introduced. In Iran, the consequences showed that “BPANN” has been superiorthan other methods. Root Mean Square Error of this algorithm was less than ±0.292 m.Therefore, we concluded that BPANN can be used for geoid determination as an excellentalternative to the classic methods.
http://jaiee.iau-ahar.ac.ir/article_516360_ddfc1e27d5bfbf3d7bb1a15750321c13.pdf
2015-03-01T11:23:20
2017-09-26T11:23:20
18
24
Geoid
Collocation
Ellipsoidal stokes integral
Artificial Neural Networks
Omid
Memarian Sorkhabi
omidmemaryan@gmail.com
true
1
AUTHOR
ORIGINAL_ARTICLE
Economic (Cost-Benefit) Analysis of Power Generation from Commercial Reinforced Concrete Solar Chimney Power Plant Built in the Desert Regions of Iran
This paper expands a model different from existing models to analyze the cost and benefit of areinforced concrete solar chimney power plant (RCSCPP) built in the desert regions of Iran.Based on the model and some assumptions for values of parameters, this paper calculates totalnet present value (TNPV) and the minimum electricity price in each phase by dividing the wholeservice period into four phases. The results showed that the minimum electricity price in the firstphase is higher than the current market price of electricity, but the minimum prices in the otherphases are far less than the current market price. The analysis indicated that huge advantages ofthe RCSCPP over coal-fired power plants could be embodied in phases 2–4. In addition, thesensitivity analysis performed in this paper discovered that TNPV is very sensitive to changes inthe solar electricity price and inflation rate, but responds only slightly to changes in carboncredits price, income tax rate and interest rate of loans. Our analysis predicts that RCSCPPshave very good application prospect.
http://jaiee.iau-ahar.ac.ir/article_516361_d56f85d29d31bbd4fe9bb7bdd08329fb.pdf
2015-03-01T11:23:20
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25
43
Cost-benefit analysis
Power generation
Reinforced concrete solar chimney
sensitivity analysis
Farhad
Saleki Baghban
f_saleki_b@yahoo.com
true
1
AUTHOR
Hosein
Nasir Aghdam
h_nasir59@yahoo.com
true
2
AUTHOR
[1] Xinping Zhou, Fang Wang, Reccab M. Ochieng. A
1
review of solar chimney power technology.
2
Renewable and Sustainable Energy Reviews,
3
Volume 14, Issue 8, October 2010, Pages 2315-
4
[2] Weibing Li, Ping Wei, Xinping Zhou. A costbenefit
5
analysis of power generation from
6
commercial reinforced concrete solar chimney
7
power plant. Energy Conversion and
8
Management, Volume 79, March 2014, Pages
9
[3] Zhou XP, Yang JK, Wang F, Xiao B. Economic
10
analysis of power generation from floating solar
11
chimney power plant. Renew Sustain Energy Rev
12
2009;13:736–49.
13
[4] http://www.suna.org.ir
14
[5] http://www.tax.gov.ir
15
ORIGINAL_ARTICLE
The reduction coefficient of PID controller by using PSO algorithm method for Flexible single-arm robot system
This study on the design of PID controllers for flexible single-arm robot system optimizationPSO method is focused so that the coefficients of the PID controller are reduced. In this study,PID controller and PSO algorithm have been described and then by using MATLAB, PIDcontrol was simulated. Then by PSO algorithm, attempts to reduce the PID coefficients are givenby simulation. Finally PID coefficients' values were compared with and without the PSOalgorithm. The results showed that by using the number of birds and birds number steps, bothequal to 30 (the sixth), the lowest values of the coefficients p K , d K , i K are 0.741, 0.1491and0, respectively.
http://jaiee.iau-ahar.ac.ir/article_516362_e6c6dcaae355ddb80f806ec8abcfe0ca.pdf
2015-03-01T11:23:20
2017-09-26T11:23:20
44
54
PID
PSO
single-arm robot
reduction of coefficients
Mohammad Mehdi
Moradi
mehdimoradi8797@gmail.com
true
1
AUTHOR
[1] Betin F., Pinchon D., and Capolino G. (2000).
1
“Fuzzy logic applied to speed control of a
2
stepping motor drive,” IEEE Transactions on
3
Industrial Electronics, vol. 47, pp.610-622.
4
[2] Qingding G. and Yanna S. (2000). “H control
5
based on internal model theory for linear
6
permanent magnet synchronous servo motor
7
(LPSM),” Control Theory & Applications,
8
vol.17, pp. 509-512.3
9
[3] Satyobroto Talukder (2011). Mathematical
10
Modelling and Applications of Particle Swarm
11
Optimization, Submitted to the School of
12
Engineering at Blekinge Institute of Technology
13
In partial fulfillment of the requirements ,
14
Department of Mathematics and Science.
15
[4] Betin F., Pinchon D., and Capolino G.
16
(2000). “Fuzzy logic applied to speed
17
control of a stepping motor drive,” IEEE
18
Transactions on Industrial Electronics, vol.47,
19
pp.610-622.
20
[5] Systematic Design Approach for a New Series
21
of Ultra‐NEMA Premium Copper Rotor Motors,
22
by Fuchsloch, J. and E.F. Brush (2007), in
23
EEMODS 2007 Conference Proceedings, 10‐15
24
June,Beijing.
25
[6] Kalman, R.E. (1960). “A New Approach to
26
Linear Filtering and PredictionProblems,”
27
Transactions of the ASME--Journal of Basic
28
Engineering, vol.82,pp. 35-45.
29
[7] Stengel R., “Optimal Control and Estimation:
30
First Edition,” Dover Publication, Inc., New
31
[8] Behal A., Feemster M., Dawson D., and Mangal
32
A. (2000). “Sensorless Rotor Velocity Tracking
33
Control of the Permanent Magnet Stepper
34
Motor,” Proceedings of the IEEE International
35
conference on Control Applications, pp. 150-
36
154, Alaska, September.
37
[9] Simon D. (2000). “Design and rule base
38
reduction of a fuzzy filter for the estimation of
39
motor currents,” International Journal of
40
Approximate Reasoning, pp. 145-167.
41
[10] Crnosija P., Kuzmanvoic B., and Ajdukovic S.
42
(2000). “Microcomputer implementation of
43
optimal algorithms for closed-loop control of
44
hybrid stepper motor drives,” IEEE Transactions
45
on Industrial Electronics, vol. 47, pp. 1319-
46
[11] A.Nabae, S. Ogasawara, and H. Akagi, (1986)
47
“A Novel Control Scheme for Current-
48
Controlled PWM Inverters,” IEEE
49
Transactions on Industry Applications, vol. IA-
50
22, pp. 697-701, July/Aug.
51
[12] Araki M., Control Systems, Robotics, and
52
Automation – Vol. II - PID Control -,Kyoto
53
University, Japan.
54
[13] Gaing Z. L., (2004). A particle swarm
55
optimization approach for optimum design of
56
PID controller in AVR system, IEEE Trans.
57
Energy Conversion, vol. 19, p. 384 –391.
58
[14] Kim T. H., Maruta I., Sugie T. (2008). Robust
59
PID controller tuning based on the constrained
60
particle swarm optimization, Automatica, Vol.
61
44, Issue 4, p. 1104 – 1110.
62
[15] Akbari, M., et al. "Nonlinear H∞ controller for
63
flexible joint robots with using feedback
64
linearization." International Journal on
65
Computer Science and Engineering (IJCSE),
66
ISSN (2011): 0975-3397.
67
[16] Pourmahmood, Mohammad, Mohammd Esmaeel
68
Akbari, and Amin Mohammadpour. "An
69
efficient modified shuffled frog leaping
70
optimization algorithm." Int. J. Comput.
71
Appl 32.1 (2011): 0975-8887.
72
[17] Akbari, M. E., M. A. Badamchizadeh, and M. A.
73
Poor. "Implementation of a fuzzy TSK
74
controller for a flexible joint robot." Discrete
75
Dynamics in Nature and Society 2012 (2012).
76
ORIGINAL_ARTICLE
The effect of cells' radius on optical filter output spectrum based on photonic crystals
In this article, the effect of cells' radius on the behavior of wavelength switching optical filter andthe effect of the radius of the optical filters' key characteristics such as wavelength resonance onan optical filter based on photonic crystals, have been investigated. Currently, the most commonapplied mechanism for designing optical filter based on photonic crystals is using twomechanisms such as (a) The resonant cavities and (b) Ring resonators. The applied mechanism inoptical filter used in this article is the resonant cavities. In this filter, filtering act is operated byusing cavity located between output Waveguide and input waveguide and it has been used todesign filter at the first extracted band structure and we have applied forbidden band photonicbased-crystal by using PWE method. Then, the calculations related to filter output spectrum werecarried out by using an FDTD method. Thus, the effect of cells' radius on the behavior ofwavelength switching optical filter has been investigated in this study.
http://jaiee.iau-ahar.ac.ir/article_516365_d2c2a143d0832a10c06f17b314287a34.pdf
2015-03-01T11:23:20
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55
61
Photonic crystals
forbidden photonic band
the cavity resonance
optical filters
Jabraeil
Farajzadeh
farajzadeh.j@gmail.com
true
1
AUTHOR
Mir Mansur
Ziabari
ziabary@ guilan.ac.ir
true
2
AUTHOR
[1] E.Yablonovitch (1987). ” Inhibited
1
Spontaneous Emission in Solid-State Physics
2
and Electronics” Physical Review Letters
3
58(20), 2059-2062.
4
[2] K.Sakoda (2001). “Optical Properties of
5
Photonic Crystals” Springer-Verlag, Berlin,
6
[3] A. Rostami, A. Haddadpour.F. Nazari and H.
7
Alipour- Banaei (2010). “Proposal for an
8
ultracompact tunable wavelength-divisionmultiplexing
9
optical filter based on quasi-2D
10
photonic crystals,” Iop- J. Opt. 12 015405.
11
[4] H.Alipour-Banaei, F. Mehdizadeh (2012).
12
“Significant role of photonic crystal resonant
13
cavities in WDM and DWDM
14
communication tunable filters”, Optik
15
[5] F. Mehdizadeh, H. Alipour-Banaei, and Z.
16
Daie-Kuzekanani (2012). “All optical multi
17
reflection structure based on one dimensional
18
photonic crystals for WDM communication
19
systems”, Optoelectronics and Advanced
20
Materials-Rapid Communications 6 527-531.
21
[6] H. P. Bazargani (2012). “Proposal for a 4-
22
channel all optical demultiplexer using 12-
23
fold photonic crystal quasicrystal” Optics
24
Communication, Vol. 285, No. 7, pp. 1848-
25
[7] H. Alipour-Banaei, F. Mehdizadeh (2012). “A
26
proposal for anti-uvb filter based on onedimensional
27
photonic crystal structure”,
28
Digest Journal of Nanomaterials and
29
Biostructures 7 361-367.
30
[8] F.Mehdizadeh, H. Alipour-Banaei, S.
31
Serajmohammadi (2013). “ Channel-Drop
32
filter based on a photonic crystal ring
33
resonator”, J. Opt ,
34
[9] A. Rostami, A. Haddadpour.F. Nazari and H.
35
Alipour-Banaei (2010). “Proposal for an
36
ultracompact tunable wavelength-divisionmultiplexing
37
optical filter based on quasi-2D
38
photonic crystals,” Iop- J. Opt. 12 015405
39