2015
3
12
12
61
Technical possibility assessment of creating wind power station at Soltanieh zone of Zanjan province
2
2
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.
1

1
7


Davoud
Karimzadeh
Iran
davoudkarimzadeh@gmail.com
Weibull distribution function
Wind Turbine
Soltanieh
wind power density
technical possibility investigation
[REFERENCES##[1] Jain, Amit, Pramod Kumar Singh, and Kumar##Anurag Singh (2011). "Short term load##forecasting using fuzzy inference and ant colony##optimization." Swarm, Evolutionary, and##Memetic Computing. Springer Berlin##Heidelberg, 626636.##[2] Pourmahmood, Mohammad, Mohammd##Esmaeel Akbari, and Amin Mohammadpour.##"An efficient modified shuffled frog leaping##optimization algorithm." Int. J. Comput.##Appl 32.1 (2011): 09758887.##[3] European Wind Energy Association. The##economics of wind energy. EWEA, 2009.##[4] Loue, Sana (1992). "Access to health care and##the undocumented alien." Journal of Legal##Medicine 13.3: 271332.##[5] Hoogwijk, Monique, Bert de Vries, and Wim##Turkenburg (2004). "Assessment of the global##and regional geographical, technical and##economic potential of onshore wind energy."##Energy Economics 26.5: 889919.##[6] Kaldellis, John K., and D. Zafirakis (2011).##"The wind energy (r) evolution: A short review##of a long history." Renewable Energy 36.7:##18871901.##[7] Kostakis, Vasilis, Michail Fountouklis, and##Wolfgang Drechsler (2013). "Peer production##and desktop manufacturing: The case of the##Helix_T wind turbine project." Science,##Technology & Human Values:##0162243913493676.##[8] Satkin, Mohammad, et al. (2014). "Multi##criteria site selection model for windcompressed##air energy storage power plants in##Iran." Renewable and Sustainable Energy##Reviews 32: 579590##]
An Evolutionary Method for Improving the Reliability of Safetycritical Robots against Soft Errors
2
2
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 softerror with minimum performance overhead. 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.
1

8
17


Mahnaz
Mohammadzadeh
Iran
mmohammadzadeh1989@gmail.com


Bahman
Arasteh
Iran
b_arasteh@iaut.ac.ir
SoftError
Fault tolerance
Retrieval Blocks Technique
Evolutionary Algorithms
[1] Rajabzadeh, G. Miremadi and M.##Mohandespour (1999). Error detection##enhancement in COTS superscalar processors##with performance monitoring features,Journal##of Electronic Testing: Theory##Application(JETTA), 20(5), pp. 553–67, 2004##[2] Profeta, N. Andrianos, Yu. Bing, B. Johnson,##T.DeLong and D.Guaspart, (1996). Safetycritical##systems built with COTS, Computer,##29(11), pp.54–60.##[3] P. Tso and P. Galaviz, (1999). Improved##aircraft readiness through COTS, In IEEE##systems readiness technology conference##(AUTOTESTCON_99), pp. 451–6.##[4] M.JafariNodoushan, G.Miremadi and A.Ejlali##(2008). ControlFlow Checking Using Branc##Instructions, In Proceeding of the 8th##International Conference on Embedded and##Ubiquitous Computing, 2008.##[5] Yenier, U. (2003). Fault Tolerant Computing##in Space Environment and Software##Implemented Hardware Fault Tolerance##Techniques, Technical Report, Department of##Computer Engineering, Bosphorus University,##[6] A. Benso, S. Di Carlo, G. Di Natale, P.##Prinetto, L.Tagliaferri, (2003). “Data##Criticality Estimation in SoftwareAppliction”##,INTERNATIONAL TEST CONFERENCE##[7] D. Borodin and B.H.H. Juurlink, (2010). ”##Protective Redundancy Overhead Reduction##Using Instruction Vulnerability Factor”, ACM##,CF’10, Italy##[8] Shuguang Feng, Shantanu Gupta, Amin Ansari##and Scott Mahlke (2010). “Shoestring:##Probabilistic Softerror Resilience on the##Cheap,” in ASPLOS.##[9] D. Thaker, D. Franklin, J. Oliver, S. Biswas,##D. Lockhart, T. Metodi, and F. T. Chong##(2006). “Characterization ofErrorTolerant##Applications when Protecting Control Data,”In##Proc. of the IEEE Int’l Symp. on Workload##Characterization.##[10] K. pattabiraman, Z. Kalbarczyk, R. Iyer##(2011). “Automated Derivation of Application##Aware Error Detectors Using Static Analysis:##Trusted Approach”, IEEE Transaction on##Dependable and Secure Computing, Volume 8##, Issue 5.##[11] T. Vijaykumar, I. Pomeranz and K. Chen,##(2002). “ Transient Fault Recovery using##Simultance Multithreading” , in 29th##Internationa Symosium on Computer##Architecture (ISCA).##[12] Benso, S. Chiusano, P. Prinetto. L. Tagliaferri##(2000). “C/C++ SourcetoSource Compiler##for Dependable Applications”, in IEEE##International Conference on Dependable##systems and Networks (DSN##Mahnaz Mohammadzadeh, Bahman Arasteh: An Evolutionary Method for Improving…##[13] A. Benso, S. Di Carlo, G. Di Natale, P.##Prinetto, L. Tagliaferri, (2003). “Data##Criticality Estimation in Software##Application”, in International Test Conference,##pp. 802810.##[14] B.Arasteh., A.Rahmani., A.Mansoor,##GH.Miremadi (2012). ” Using Genetic##Algorithm to Identify SoftError Derating##Blocks of an Application##Program”,EuromicroConference on Digital##System Design,##[15] D. E. Goldberg, (1989). “Genetic Algorithms##in Search,Optimization and Machine##Learning”, Reading, MA,AdditionWesley.##[16] P. Mars, K. S. Narendra, and M. Chrystall##(1983). “Learning Automata Control of##ComputerCommunication##Networks”,Proceedings of Third Yale##Workshop on Application of Adaptive##Systems Theory, Yale University##[17] K. S. Narendra, and M. A. L. Thathachar##(1989). “Learning Automata: An##Introduction”, Prenticehall, Englewood cliffs.##[18] M. R. Meybodi, and S. Lakshmivarhan,##(1983). “A Learning Approach to Priority##Assignment in a Two Class M/M/1Queuing##System with Unknown Parameters”,##Proceedings of Third Yale Workshop on##Applications of Adaptive System Theory, Yale##University, 106109##[19] B. J. Oommen, and D. C. Y. Ma, (1988).##“Deterministic Learning Automata Solution to##the Keyboard Optimization Problem”,IEEE##Transaction on Computers, Vol. 37, No. 1, 23##[20] Narendra, K.S. and Thathachar, M.A.L.##(1989). “Learning Automata: An##Introduction”, Prentice Hall, Inc##[21] M. R. Meybodi, H. Beigy. (2002). Utilizing##Distributed Learning Automata to Solve##Stochastic Shortest Path Problem. Technical##Report, Soft Computing Laboratory, Computer##Engineering Department, Amirkabir##University of Technology.##]
Geoid Determination Based on Log Sigmoid Function of Artificial Neural Networks: (A case Study: Iran)
2
2
A Back Propagation Artificial Neural Network (BPANN) is a wellknown 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.
1

18
24


Omid
Memarian Sorkhabi
Iran
omidmemaryan@gmail.com
Geoid
Collocation
Ellipsoidal stokes integral
Artificial neural networks
Economic (CostBenefit) Analysis of Power Generation from Commercial Reinforced Concrete Solar Chimney Power Plant Built in the Desert Regions of Iran
2
2
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 coalfired 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.
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25
43


Farhad
Saleki Baghban
Iran
f_saleki_b@yahoo.com


Hosein
Nasir Aghdam
Iran
h_nasir59@yahoo.com
Costbenefit analysis
Power generation
Reinforced concrete solar chimney
Sensitivity Analysis
[[1] Xinping Zhou, Fang Wang, Reccab M. Ochieng. A##review of solar chimney power technology.##Renewable and Sustainable Energy Reviews,##Volume 14, Issue 8, October 2010, Pages 2315##[2] Weibing Li, Ping Wei, Xinping Zhou. A costbenefit##analysis of power generation from##commercial reinforced concrete solar chimney##power plant. Energy Conversion and##Management, Volume 79, March 2014, Pages##[3] Zhou XP, Yang JK, Wang F, Xiao B. Economic##analysis of power generation from floating solar##chimney power plant. Renew Sustain Energy Rev##2009;13:736–49.##[4] http://www.suna.org.ir##[5] http://www.tax.gov.ir##]
The reduction coefficient of PID controller by using PSO algorithm method for Flexible singlearm robot system
2
2
This study on the design of PID controllers for flexible singlearm 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.
1

44
54


Mohammad Mehdi
Moradi
Iran
mehdimoradi8797@gmail.com
PID
PSO
singlearm robot
reduction of coefficients
[[1] Betin F., Pinchon D., and Capolino G. (2000).##“Fuzzy logic applied to speed control of a##stepping motor drive,” IEEE Transactions on##Industrial Electronics, vol. 47, pp.610622.##[2] Qingding G. and Yanna S. (2000). “H control##based on internal model theory for linear##permanent magnet synchronous servo motor##(LPSM),” Control Theory & Applications,##vol.17, pp. 509512.3##[3] Satyobroto Talukder (2011). Mathematical##Modelling and Applications of Particle Swarm##Optimization, Submitted to the School of##Engineering at Blekinge Institute of Technology##In partial fulfillment of the requirements ,##Department of Mathematics and Science.##[4] Betin F., Pinchon D., and Capolino G.##(2000). “Fuzzy logic applied to speed##control of a stepping motor drive,” IEEE##Transactions on Industrial Electronics, vol.47,##pp.610622.##[5] Systematic Design Approach for a New Series##of Ultra‐NEMA Premium Copper Rotor Motors,##by Fuchsloch, J. and E.F. Brush (2007), in##EEMODS 2007 Conference Proceedings, 10‐15##June,Beijing.##[6] Kalman, R.E. (1960). “A New Approach to##Linear Filtering and PredictionProblems,” ##Transactions of the ASMEJournal of Basic##Engineering, vol.82,pp. 3545.##[7] Stengel R., “Optimal Control and Estimation:##First Edition,” Dover Publication, Inc., New##[8] Behal A., Feemster M., Dawson D., and Mangal##A. (2000). “Sensorless Rotor Velocity Tracking##Control of the Permanent Magnet Stepper##Motor,” Proceedings of the IEEE International##conference on Control Applications, pp. 150##154, Alaska, September.##[9] Simon D. (2000). “Design and rule base##reduction of a fuzzy filter for the estimation of##motor currents,” International Journal of##Approximate Reasoning, pp. 145167.##[10] Crnosija P., Kuzmanvoic B., and Ajdukovic S.##(2000). “Microcomputer implementation of##optimal algorithms for closedloop control of##hybrid stepper motor drives,” IEEE Transactions##on Industrial Electronics, vol. 47, pp. 1319##[11] A.Nabae, S. Ogasawara, and H. Akagi, (1986)##“A Novel Control Scheme for Current##Controlled PWM Inverters,” IEEE##Transactions on Industry Applications, vol. IA##22, pp. 697701, July/Aug.##[12] Araki M., Control Systems, Robotics, and##Automation – Vol. II  PID Control ,Kyoto##University, Japan.##[13] Gaing Z. L., (2004). A particle swarm##optimization approach for optimum design of##PID controller in AVR system, IEEE Trans.##Energy Conversion, vol. 19, p. 384 –391.##[14] Kim T. H., Maruta I., Sugie T. (2008). Robust##PID controller tuning based on the constrained##particle swarm optimization, Automatica, Vol.##44, Issue 4, p. 1104 – 1110.##[15] Akbari, M., et al. "Nonlinear H∞ controller for##flexible joint robots with using feedback##linearization." International Journal on##Computer Science and Engineering (IJCSE),##ISSN (2011): 09753397.##[16] Pourmahmood, Mohammad, Mohammd Esmaeel##Akbari, and Amin Mohammadpour. "An##efficient modified shuffled frog leaping##optimization algorithm." Int. J. Comput.##Appl 32.1 (2011): 09758887.##[17] Akbari, M. E., M. A. Badamchizadeh, and M. A.##Poor. "Implementation of a fuzzy TSK##controller for a flexible joint robot." Discrete##Dynamics in Nature and Society 2012 (2012).##]
The effect of cells' radius on optical filter output spectrum based on photonic crystals
2
2
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 photonicbasedcrystal 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.
1

55
61


Jabraeil
Farajzadeh
Iran
farajzadeh.j@gmail.com


Mir Mansur
Ziabari
Iran
ziabary@ guilan.ac.ir
Photonic crystals
forbidden photonic band
the cavity resonance
optical filters
[[1] E.Yablonovitch (1987). ” Inhibited##Spontaneous Emission in SolidState Physics##and Electronics” Physical Review Letters##58(20), 20592062.##[2] K.Sakoda (2001). “Optical Properties of##Photonic Crystals” SpringerVerlag, Berlin,##[3] A. Rostami, A. Haddadpour.F. Nazari and H.##Alipour Banaei (2010). “Proposal for an##ultracompact tunable wavelengthdivisionmultiplexing##optical filter based on quasi2D##photonic crystals,” Iop J. Opt. 12 015405.##[4] H.AlipourBanaei, F. Mehdizadeh (2012).##“Significant role of photonic crystal resonant##cavities in WDM and DWDM##communication tunable filters”, Optik##[5] F. Mehdizadeh, H. AlipourBanaei, and Z.##DaieKuzekanani (2012). “All optical multi##reflection structure based on one dimensional##photonic crystals for WDM communication##systems”, Optoelectronics and Advanced##MaterialsRapid Communications 6 527531.##[6] H. P. Bazargani (2012). “Proposal for a 4##channel all optical demultiplexer using 12##fold photonic crystal quasicrystal” Optics##Communication, Vol. 285, No. 7, pp. 1848##[7] H. AlipourBanaei, F. Mehdizadeh (2012). “A##proposal for antiuvb filter based on onedimensional##photonic crystal structure”,##Digest Journal of Nanomaterials and##Biostructures 7 361367.##[8] F.Mehdizadeh, H. AlipourBanaei, S.##Serajmohammadi (2013). “ ChannelDrop##filter based on a photonic crystal ring##resonator”, J. Opt ,##[9] A. Rostami, A. Haddadpour.F. Nazari and H.##AlipourBanaei (2010). “Proposal for an##ultracompact tunable wavelengthdivisionmultiplexing##optical filter based on quasi2D##photonic crystals,” Iop J. Opt. 12 015405##]