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Volume-6 Issue-7, December 2016, ISSN:  2278-3075 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

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Amrik Singh, Yoginder Talwar, Ajay Prasad

Paper Title:

Highly Secure and Fast AES Algorithm Implementation on FPGA with 256 bit key size

Abstract: The Block cipher AES is a symmetric key cryptographic standard used for transferring block of data in secure manner for server based communication networks, SCADA systems for Oil refinery, Oil and Gas Pipe Lines, and Smart Grids based applications. High level security of data transfer needs long key size i.e. 256 bits, analysis of certain ideas of round key expansion mechanisms from given key data are discussed and the same is implemented in FPGA configuration with 128 bits and 256 bits key size to achieve low latency, high throughput with high security.

 Advance Encryption Standard, encryption, decryption, FPGA, VHDL, Virtex-5.


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2.       N ferguson, R. Schroeppel, D. Whiting. A simple algebraic  representation of Rijndael Selected Area in Cryptography, SAC 2001,  LNCS 2259, Springer-Verlag, 2001, pp.103-111.

3.       Courtois, N.T. and J. Pieprzyk: Cryptanalysis of Block Ciphers with over defined Systems of   Equations. Accepted by, Asiecrypt 2002, Dec 2002. (See: http://eprint.iacr.org/2002/044).

4.       Y. Talwar, C.E. Veni Madhavan, N. Rajpal, “On the key expansion Mechanisms of the AES Ciphers: Rijndael, Serpent”. 

5.       P. Chdowiec, K. Gaj, “Very compact FPGA implementation of the AES algorithm”, Cryptographic hardware and embedded systems (CHES 2003), LNCS vol. 2779, pp. 319-333, Springer-Verlog, October 2003.       

6.       G. Rouvroy, F.X. Standaert, J.J. Quisquater, J.D. Legat, , Compact and efficient encryption/decryption module for FPGA implementation of the AES Rijndael very well suited for small embedded applications, Proceedings of the international conference on Information Technology: coding and computing 2004 (ITCC 2004), pp. 583-587, vol.
2, April 2004.

7.       Tim Good and Mohammed Benaissa, “AES on FPGA from the Fastest to the Smallest”, CHES 2005, LNCS 3659, pp.  427-440, 2005.  Springer-Verlog Berlin Heidelberg 2005.

8.       Y. Talwar, C.E. Veni Madhavan, Navin Rajpal, “On Partial Linearization of Byte Substitution Transformation of Rijndael-The AES”.  Journal of Computer Science 2(1): 48-52, 2006, ISSN1549-3636 © 2006 Science Publications.

9.       Swinder Kaur and Prof. Renu Vig, “Efficient Implementation of AES Algorithm in FPGA Devices”. International Conference on Computational intelligence and Multimedia Applications 2007, DOI 10.1109/ICCIMA -2007.250, pages 179-187,0-7695-3050-8/07, IEEE-(2007) Volume2, pp 179-187.

10.    J. Elbirt, W. Yip, B. Chatwynd and C. Paes, “An FPGA Implementation and performance Evaluation of the AES block cipher candidate algorithm analyst”, Presented at Proc.3rd AES Conf. (AES).  Available: http:// csrc.nist.gov/encryption/AES/round2/conf3/aes3paper.html.

11.    Thulasimani L. and Madheswarn, “A Single Chip Design and Implementation of AES-128/192/256 Encryption Algorithms”, International journal of Engineering Science and Technology (IJEST); ISSN: 0975-5462, Vol.2(5), 2010, 1052-1059.

12.    M. McLoone and J. V.  McCanny, “Rijndael  FPGA implementation utilizing look-up tables” , in IEEE Workshop on Signal processing systems, Sept. 2001, pp. 349-360.

13.    Amandeep Kaur, Puneet Bhardwaj and Naveen Kumar, “FPGA Implementation of Efficient Hardware for the Advanced Encryption Standard”, in IJITEE; ISSN: 2278-3075, Volume-2, Issue-3, February 2013.







Paper Title:

Quantifying Physical Parameters of Quaternary Glass with Composition Tellurium- Niobium - Zinc-Lithium Oxide

Abstract:  In the present work the tellurite glass a function of alkali metals as network intermediate with composition 85TeO2/ 5Nb2O5/ 5ZnO/ 5Li2O in mol% were been prepared. These glasses contain Li2O can be promising used in optical devices because it has advantage optical properties compared with other tellurite glasses. The physical parameters of these glass studied with respect to values of density, , molar volume, Vm, linear refractive indices, n0, nonlinear refractive index, n2, electronic polarizability, m, molar refraction, Rm,  metallization criterion, M (n0), and third order non-linear optical susceptibility, (3),. The Sellmeier gap energy, Es, and dispersion energy, Ed, were calculated besides the theoretical third order of nonlinear optical susceptibility, (3), calculated by used Lines model. Measure the thermal stability and the glass transition temperature by differential thermal analysis (Shimadzu DTA 50) which can be determine the glass transition temperature, Tg, onset crystallization temperature, Tc, and melting temperature, Tm. These glass have values as; = 5.231 gmcm-3, Vm= 28.75 cm-3, n0= 2.2228 at 435.84 nm, m= 6.478Å3 and Rm=16.024 mol-1cm3 at 435.84nm. and Es = 6.54 eV, Ed= 20.65 eV.

Oxide glass; linear refractive index; dispersion energy.


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5.       H. Takebe, S. Fujino, K. Morinaga “REFRACTIVE-INDEX DISPERSION OF TELLURITE GLASSES IN THE REGION FROM 0.40 TO 1.71 ΜM,” J. Am. Ceram. Soc., 77[9] (1994) pp. 2455–2457.

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11.    El Sayed Yousef, S. F. Mansour, M. Y. Hassan, A. M. Emara“Synthesis optical properties of novel TeO2 based glasses,” J. of Optik 127 (2016) pp.8933-8939.

12.    H. Burger, W. Vogel, V. Kozhukharov “IR transmission and properties of glasses in the TeO2−RnOm, RnXm, Rn(SO4)m, Rn(PO3)mandB2O3] systems,” Infrared Phys. 25 (1995) pp.395-409.

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Javed Ali

Paper Title:

Superiority of Agile over Software Models

Abstract: The Software Development Life Cycle (SDLC) is a structure imposed on the development of software product and also known as Software Development Processes. It is often considered as a subset of a system development life cycle. There are numerous SDLC models widely used for developing software. The SDLC model gives a theoretical guide line regarding development of the software. The every SDLC has its own benefits and drawbacks according to that we decide which models should be implemented under which conditions. The concept of system lifecycle models came into existence that emphasized on the need to follow some structured approach towards building new or improved system. In this paper, the comparative study made on standard life cycle models namely rapid application development, Agile Development Model, V-shaped model, spiral model, incremental model and waterfall model, prototype.

Software Development, Life Cycle, Model, Agile Development, Extreme Programming, Dynamic, Adaptive.


1.       Agrawal, Ashish, Mohd Aurangzeb Atiq, and L. S. Maurya. "A Current Study on the Limitations of Agile Methods in Industry Using Secure Google Forms."Procedia Computer Science 78 (2016): 291-297.
2.       Raj, Gaurav, Dheerendra Singh, and Ankur Bansal. "Analysis for security implementation in SDLC."

3.       In Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference-, pp. 221-226. IEEE, 2014.

4.       Sharma, Anubha, Manoj Kumar, and Sonali Agarwal. "A Complete Survey on Software Architectural Styles and Patterns." Procedia Computer Science 70 (2015): 16-28.

5.       Langer, Arthur M. "System Development Life Cycle (SDLC)." In Analysis and Design of Information Systems, pp. 10-20. Springer London, 2008.

6.       Montini, Denis Ávila, Danilo Douradinho Fernandes, Francisco Supino Marcondes, Paulo Marcelo Tasinaffo, Italo Santiago Vega, and Luiz Alberto Vieira Dias. "Formal Approach Use to Choose a Software Manufactoring Cell's SDLC." In 2010 Seventh International Conference on Information Technology, pp. 1304-1305. IEEE, 2010.

7.       Tohidi, Hamid. "The Role of Risk Management in IT systems of organizations." Procedia Computer Science 3 (2011): 881-887.

8.       Kumar, Chandan, and Dilip Kumar Yadav. "A Probabilistic Software Risk Assessment and Estimation Model for Software Projects." Procedia Computer Science 54 (2015): 353-361.

9.       Molokken-Ostvold et.al, “A comparison of software project overruns - flexible versus sequential development models”, Volume 31, Issue 9, Page(s): 754 – 766, IEEE CNF, Sept.2005.

10.    Niazi, Mahmood, Muhammad Ali Babar, and June M. Verner. "Software Process Improvement barriers: A cross-cultural comparison." Information and software technology 52, no. 11 (2010): 1204-1216.Dybå,  Tore.  "An  empirical  investigation  of  the  key  factors  for  success  in  software  process improvement." Software Engineering, IEEE Transactions on31, no. 5 (2005): 410-424.

11.    Liao, Li, Yuzhong Qu, and Hareton KN Leung. "A software process ontology and its application."(2003).

12.    Laura C. Rodriguez Martinez, Manuel Mora, Francisco. Alvarez, “A Descriptive/Comparative Study of the Evolution of Process Models of Software Development Life Cycles”, Proceedings of the 2009 Mexican International Conference on Computer Science IEEE Computer Society Washington, DC, USA, 2009.

13.    Sharma, B.; Sharma. N, “Software Process Improvement: A Comparative Analysis of SPI models”, Emerging Trends in Engineering and Technology (ICETET), 2009 2nd International Conference on,16-18, 2009, pp. 1019- 1024.

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15.    Maglyas, A.; Nikula, U.; Smolander, K.,“Comparison of two models of success prediction in software development projects”, Software Engineering Conference (CEE-SECR), 2010 6th Central and Eastern European on 13-15 Oct. 2010, pp. 43-49.

16.    Gaurav Kumar, Pradeep Kumar Bhatia,” Impact of Agile Methodology on Software Development Process”,” ISSN 2249- 6343International Journal of Computer Technology and Electronics Engineering (IJCTEE) Volume 2, Issue 4”,august 2012.

17.    Guy Want, “Drowning in the Waterfall, The Benefits of Agile versus the Predominance of Waterfall “Software Engineering CS 390:", October 29, 2008.






Alyaseh Nagi, Issa Ali, Sedat Nazlibilek

Paper Title:

Decentralized Control Based On Active Disturbance Rejection Controller: An Application Quadruple Tank System

Abstract:  This paper presents Decentralized Control for the Quadruple Tank System (QTS) Based on Active Disturbance Rejection Controller (ADRC). The most remarkable advantages of the proposed approach are that it is not depend on the accuracy of mathematical model of the plant along with its simple structure and the ability of strong disturbance rejection. Often, there are some difficulties in designing of suitable controller for Quadruple Tank System due to the interaction between the inputs and outputs of this system. With the proposed control method, the cross coupling within the system treated as a disturbance, which is estimated using extended state observer (ESO) and then actively rejected. The Quadruple Tank System is represented using set of nonlinear differential equations and the ADRC controller is applied directly on the nonlinear model of the system. The effectiveness of the proposed approach is validated via simulation results obtained under MATLAB environment. The results show that the ADRC gives better results compared to nonlinear optimal control strategy.

Active Disturbance Rejection Controller Decentralized Control, Quadruple Tank System, The Nonlinear Coupling.


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