Journal Vol – 14 No -1, February 2019

Exact wave solutions to the (2+1)-dimensional Klein-Gordon equation with special types of nonlinearity


Sk. Tanzer Ahmed Siddique, Md. Dulal Hossain, M. Ali Akbar



In this article, we investigate the traveling wave solutions to the Klein-Gordon equation in (2+1)-dimension with special types of nonlinearity. The types include quadratic, cubic and polynomial nonlinearity. The Klein-Gordon equation assumes significant role in numerous types of scientific investigation such as in quantum field theory, nonlinear optics, nuclear physics, magnetic field etc. To investigate the aimed traveling wave solutions, we execute the (𝐺′/𝐺)-expansion method. The attained solutions are in the form of hyperbolic, trigonometric and rational functions. The results acknowledged that the applied method is very efficient and suitable for discovering differential equations with various types of nonlinearity considered in optics and quantum field theory. The solutions of the Klein-Gordon equation with quadratic, cubic, and polynomials nonlinearity play a significant role in many scientific measures notably optics and quantum field theory.


Klein-Gordon equation,nonlinearity,travelingwave solutions,


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Correlation between Compressive Strength and Split Tensile Strength of GGBS and MK Based Geopolymer Concrete using Regression Analysis


B. Sarath Chandra Kumar, Sadasivan Karuppusamy, K. Ramesh



In this study, the compressive strength and split tensile strength were performed on totally 264 laboratory made Geopolymer Concrete cubes and 264 laboratory made Geopolymer Concrete cylinders. Regression analysis using R software was carried out. A simple relationship was determined and correlated between compressive strength and split tensile strength. The concrete cubes were prepared with various mix proportions that yield cube crushing strength within the range of 20 to 60 Mpa.


Compressive Strength,Split Tensile Strength,GGBS,Metakaoline,Regression Analysis,


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Muhammad Aadil, Sheeraz Ahmed, Muhammad Zubair, M.Saeed Hussain kakar, Muhammad Junaid, Ata-ur-Rehman



Wireless Body Area Sensor Network (WBANs) are used to measure the biological parameters of a human body in a critical health situation. Sensors use an antenna and electromagnetic radiations to drive the response towards the sink node. Our research focuses on the overheating problem of body tissues due to the electromagnetic field generated by electromagnetic radiations. When sensor nodes continuously send and receive the data, it not only influences the communication between the nodes by stimulating high attenuation for signal transmission, but also conduits various health problems. These health issues may include reducing blood flow, affecting the enzymatic reactions, brain tumor, damaging the sensitive tissues and leading to tissue cancer. The exposition of such issues are addressed in our research called iBTTA (Improved Body Tissue Temperature Aware)routing scheme, where not only the temperature of a body tissues is controlled under the threshold value but significantly improves the performance in terms of its throughput, end- to- end delay and transmission loss. The scheme is an extension of our previously published scheme BTTA. The validation of our scheme iBTTA is done through comparison with already existing techniques SIMPLE (Stable Increased-throughput Multi-hop Protocol for Link Efficiency in WBANs) and LAEEBA (Link-Aware and Energy Efficient scheme for WBANs). In iBTTA we have improved the problem of the body tissues temperature, utilization of battery power and load balancing techniques in WBANs.


Tissues temperature,Attenuation,WSNs,Load balancing,Network Lifetime,residual energy,


I.Abdellah, Ezzati, S. A. I. D. Benalla, AbderrahimBeniHssane, and MoulayLahcenHasnaoui. “Advanced low energy adaptive clustering hierarchy.”Proceedings of the International Journal on Computer Science and Engineering (IJCSE)2, no. 7 (2010): 2491-2497.6.

II.Adhikary, Sriyanjana, SankhayanChoudhury, and SamiranChattopadhyay. “A new routing protocol for WBAN to enhance energy consumption and network lifetime.” InProceedings of the 17th International Conference on Distributed Computing and Networking, p. 40. ACM, 2016.16.

III.Afridi, A., NadeemJavaid, S. Jamil, M. Akbar, Zahoor Ali Khan, and Umar Qasim. “HEAT: Horizontal Moveable Energy-efficient Adaptive Threshold-Based Routing Protocol for Wireless Body Area Networks.” InAdvanced Information Networking and Applications Workshops (WAINA),2014 28th International Conference on, pp. 474-478. IEEE, 2014.17.

IV.Ahmed, S., Nadeem Javaid, SidrahYousaf, Ashfaq Ahmad, Muhammad Moid Sandhu, Muhammad Imran, Zahoor Ali Khan, and N. Alrajeh. “Co-LAEEBA: Cooperative link aware and energy efficient protocol for wireless body area networks.”Computers in Human Behavior51 (2015): 1205-1215.3

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XIII.Qureshi, KashifNaseer, Faisal Bashir, and Abdul Hanan Abdullah. “An energy and link aware next node selection protocol for body area networks.” InInformation Networking (ICOIN), 2018 International Conference on, pp. 721-726. IEEE, 2018.9.

XIV.Sahndhu, Muhammad Moid, NadeemJavaid, Muhammad Imran, Mohsen Guizani, Zahoor Ali Khan, and Umar Qasim. “BEC: A novel routing protocol for balanced energy consumption in Wireless Body Area Networks.” InWireless Communications and Mobile Computing Conference (IWCMC), 2015 International, pp. 653-658. IEEE, 2015.15.

XV.Smail, Omar, AddaKerrar, Youssef Zetili, and Bernard Cousin. “ESR: Energy aware and Stable Routing protocol for WBAN networks.”InWireless Communications and Mobile Computing Conference (IWCMC), 2016 International, pp. 452-457. IEEE, 2016.11.

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XVII.Thotahewa, Kasun MS, Jean-Michel Redoutè, and Mehmet RasitYuce. “Propagation, power absorption, and temperature analysis of UWB wireless capsule endoscopy devices operating in the human body.”IEEE Transactions on Microwave Theory and Techniques63, no. 11 (2015): 3823-3833.13.

XVIII.ul Islam, Saif, Ghufran Ahmed, MahamShahid, Najmul Hassan, Muhammad Riaz, Hilal Jan, and AzfarShakeel. “Implanted Wireless Body Area Networks: Energy Management, Specific Absorption Rate and Safety Aspects.” InAmbient Assisted Living and Enhanced Living Environments, pp. 17-36. 2017.18.

XIX.Wu, Tin-Yu, and Cheng-Han Lin. “Low-SAR path discovery by particle swarm optimization algorithm in wireless body area networks.”IEEE Sensors Journal15, no. 2 (2015): 928-936.19.

XX.Yousaf, S., S. Ahmed, M. Akbar, Nadeem Javaid, Zahoor Ali Khan, and Umar Qasim. “Co-CEStat: Cooperative Critical Data Transmission in Emergency in Static Wireless Body Area Network.” InBroadband and Wireless Computing, Communication and Applications (BWCCA), 2014 Ninth International Conference on, pp. 127-132. IEEE, 2014.14

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An Efficient Camera Identification Technique using Krawtchouk Moment Invariants


Megha Borole, Prof. S. R. Kolhe



In late years, camera identification methods have drawn attention in the area of digital forensics. To detect the source camera through which the picture is caught, Photo-Response Non uniformity (PRNU) noise is utilized as a camera, impression, as it is a particular component that recognizes pictures taken from the comparable cameras. This paper introduces a camera identification technique which is based on Krawtchouk Moment invariant features. The Photo Response Non-Uniformity (PRNU) noise is a type of sensor finger impression, which permits to extraordinarily distinguish the camera that took an image. It is estimated from the denoised images using a denoised filter. Then estimate the Krawtchouk Moment invariants from the PRNU noise pattern. The Krawtchouk Moments are invariant to scaling, translation, rotation, and shear. These invariants are fed to Fuzzy Min-Max Neural Network with Compensatory Neuron (FMCN) and by performing ten-fold cross-validation technique, verification is made out. The experimental results show that the proposed technique achieves an average accuracy of 93.3% for first experiment and 98.3% for the second experiment.


Camera identification,photo response non-uniformity (PRNU),Krawtchouk moments,fuzzy min-max neural networkwith compensatory neuron (FMCN),


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XVIII.S. Saito, Y. Tomioka and H. Kitazawa, “A Theoretical Framework for Estimating False Acceptance Rate of PRNU-Based Camera Identification,” in IEEE Transactions on Information Forensics and Security, vol. 12, no. 9, pp. 2026-2035, Sept. 2017.

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XXI.X. Kang, Y. Li, Z. Qu and J. Huang, “Enhancing Source Camera Identification Performance with a Camera Reference Phase Sensor Pattern Noise”, in IEEE Transactions on Information Forensics and Security, vol. 7, no. 2, pp. 393-402, April 2012.

XXII.Y. Sutcu, S. Bayram, H. T. Sencar and N. Memon, “Improvements on Sensor Noise Based Source Camera Identification,” 2007 IEEE International Conference on Multimedia and Expo, Beijing, 2007, pp. 24-27.

XXIII.Yoichi Tomioka, Yuya Ito, and Hitoshi Kitazawa, “Robust Digital Camera Identification Based on Pairwise Magnitude Relations of Clustered Sensor Pattern Noise”, IEEE Transactions on Information Forensics and Security, Vol. 8, No. 12, December 2013.

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Influence of Lime on Low Plastic Clay Soil Used as Subgrade


Adnan Asad, ArshadHussain, Abdul Farhan, Adeel Ahmed Bhatti, Mehr-E-Munir



Weak clayey soil can cause premature failure in subgrade so their removal or proper treatment is necessary for the efficiency of structure. Soil stabilization is an excellent choice and economical in many circumstances for treatment and proper behavior of weak subgrade soil as recommended by many researchers. Lime is the oldest and well known additive for stabilization of many type of soils. This paper presents geotechnical investigation of low plastic clay soil being used as subgrade stabilized with lime. The low plastic clayey subgrade soil was stabilized with different percentages of lime and results show that soil can be satisfactorily stabilized with the addition of 6% lime. The Atterberg’s limit, compaction characteristics and strength tests including unconfined compressive strength (UCS) and California bearing ratio (CBR) tests were performed. Results indicate that addition of lime reduce plasticity index. An increase in OMC was observed with the decrease in maximum dry density (MDD). CBR and unconfined compressive strength of soil (qu)values improved significantly with the addition of lime.


Soil Stabilization,Lime,Subgrade Stabilization,Low Plastic Clay,


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IV.Harichane, K., Ghrici, M., Kenai, S., & Grine, K. (2011). Use of natural pozzolana and lime for stabilization of cohesive soils.Geotechnical and geological engineering,29(5), 759-769.

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XI.Tuncer, E. R., & Basma, A. A. (1991). Strength and stress-strain characteristics of a lime-treated cohesive soil.Transportation Research Record, (1295).

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Analysis of Effect of Ground Granulated Blast Furnace Slag (GGBFS) on the Mechanical Properties of Concrete using Destructive and Non-destructive Tests


Tarun Yadav, Jatin Singh, Sandeep Panchal, Md. Mohsin Khan, Shilpa Pal



Ground granulated furnace slag is a waste material which is rich in Calcium. Aim of this study is to observe the effect of mixing of ground granulated blast furnace slag as a replacement of cement in concrete. The study is conducted on M-30 grade concrete. The cement is replaced partially by the ground granulated blast furnace slag to obtain a cost-effective mix. The concrete mixes are prepared by replacing the cement by 15%, 30%, 45%, 60% and 75 % ground granulated blast furnace slag. The tests are performed to know the compressive strength, flexural strength and workability of concrete. Non-destructive tests like rebound hammer test and ultrasonic pulse velocity tests are also performed to understand the post hardening characteristics of the concrete. It is found that the replacement of cement GGBFS reduces the initial strength of concrete but increases the ultimate strength if mixed in optimum amount. The optimum percentage of ground granulated furnace slag in M-30 concrete is found to be 45%. The workability increases as the amount of GGBFS is increased in the mix. The post hardening tests show the better performance of concrete at 30% and 45% mixing of GGBFS in concrete.


GGBFS,waste management,concrete,flexural strength,compression strength ,


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IV.H. Sethi, P.P. Bansal, R. Sharma, “Effectof Addition of GGBS and Glass Powder on the Properties of Geo-polymer Concrete”, Iranian Journal of Science and Technology, Transactions of Civil Engineering, pp. 1-11, November 2018.

V.H. Wang, J. Wang, X. Sun, W. Jin, “Improving Performance of Recycled Aggregate Concrete with Superfine Pozzolanic Powders”, Journal of Central South University, Vol. 20, No. 12, pp. 3715-3722, December 2013

VI.L. Black, P. Purnell, J. Hill, “Current Themes in Cement Research”, Advances in Ceramics, Vol. 109, No. 5, pp. 253-259, 2010.

VII.M.R. Antonyamaladhas, S. Chachithanantham, A. Ramaswamy, “Performance and Behaviour of Ground Granulated Blast Furnace Slag Imparted to Geopolymer Concrete Structural Elements and Analyzed with ANSYS”, Advances in Material Science and Engineering, Vol. 2016, pp. 1-9, August 2016.

VIII.M.Arizoumandi, S.A.Volz, “Effect of Fly Ash Replacement Level on the Fracture Behavior of Concrete”, Frontiers of Structural and Civil Engineering, Vol. 7, No. 4, pp. 411-418,December 2003.

IX.M. Elchalakani, T. Aly, E. Abu-Aisheh, “Sustainable concrete with high volume GGBFS to build Masdar City in the UAE”, Case Studies in Construction Materials, Vol. 1, pp. 10-24, December 2013.

X.O.Kayali,“Effect of High Volume Fly Ash on Mechanical Properties of Fiber Reinforced Concrete”, Materials and Structures, Vol. 37, No. 5, pp. 318-327, June 2004.

XI.O.M. Omar, G. D. AbdElhameed, M. A Sherif, H.A. Mohamadien, “Influence of limestone waste as partial replacement material for sand and marble powder in concrete properties”, HRBC Journal,Vol. 8, No. 3, pp. 193-203, December 2003.

XII.R. Siddique, D. Kaur, “Properties of Concrete Containing Ground Granulated Blast Furnace Slag (GGBFS) at Elevated Temperatures”, Journal of Advanced Research, Vol. 3, No. 1, pp. 45-51, January 2012.

XIII.S.A. Zareei, F.Ameri, F. Dorostkar, M. Ahmadi, “Rice Husk Ash as a Partial Replacement of Cement in High Strength Concrete containing Micro Silica: Evaluating Durability and Mechanical Properties”, Case Studies in Construction Materials, Vol. 7, pp. 73-81, December 2017.

XIV.S.P. Dunuweera, R.M.G. Rajapakse, “Cement Types, Composition, Uses and Advantages of Nano-cement, Environmental Impact on Cement Production, and Possible Solutions”, Advances in Material Science and Engineering, Vol. 2018, pp. 1-13, April 2018.

XV.S.V. Deo, “Parametric Study of Glass Fiber Reinforced Concrete”, Advances in Structural Engineering, In: Matsagar V. (eds), Springer, New Delhi, pp. 1909-1916, December 2004.

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A Modification of the Generalized Kudryashov Method for the System of Some Nonlinear Evolution Equations


H. M. Shahadat Ali, M. A.Habib, M. Mamun Miah, M. Ali Akbar



In this study, a comparatively new technique named the generalized Kudryashov method (gKM) has been effectively implemented to explore the exact traveling wave solutions to some nonlinear evolution equations (NLEEs) in the field of nonlinear science and engineering. The effectiveness of the new functional method has been demonstrated by investigating single as well as coupled equations with arbitrary parameters explicitly the coupled Higgs field equation, the Benney-Luke equation, and the Drinfel'd-Sokolov-Wilson (DSW) equation. As a matter of fact, the solution attained in this article thrust into the abundant wave solutions which includes kink, singular kink, periodic and solitary wave solutions. Moreover, the characteristics of these analytic solutions are interpreted depicting some 2D and 3D graph by using computer symbolic programming Wolfram Mathematica. The computational work ascertained that the employed method is sturdy, simple, precise, and wider applicable. Also, the prominent competence of this current method ensures that practically capable to reducing the size of the computational task and can be solved several nonlinear types of new complex higher order partial differential equations that originating in applied mathematics, computational physics and engineering.


Thegeneralized Kudryashov method,Coupled Higgs field equation,Benney-Luke equation,DSW equation, Traveling wave solution,Solitary wave solution,Exact solution,


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III.A. H. Arnous, M. Mirzazadeh, M. Eslami,”The Backlund transformation method of Riccati equation applied to Coupled Higgs field and Hamiltonian amplitude equations”,Comput. Methods Diff. Equat.,Vol.: 2, Issue: 4,pp.: 216-226, 2014.

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VII.D. Lu, D. Kang, B. Hong,”New exact solutions of the Drinfel’d SokolovWilson equation”,J. Informa. Comput. Sci., Vol.:18, pp.: 5955-5962, 2013.

VIII.E. Aksoy, M. Kaplan, A. Bekir,”Exponential rational function method for space-time fractional differential equations”,Waves Rand. Compl. Media, Vol.: 26, pp.: 142-151, 2016.

IX.E. Babolian, A. Azizi, J. saeidian,”Some notes on using the homotopy perturbation method for solving time-dependent differential equations”, Math. Comput. Model., Vol.; 50, Issue: 1-2, pp.: 213-224, 2009.

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XII.E. M. E. Zayed,A. G. A. Nowehy,”The solitary wave ansatz method for finding the exact bright and dark soliton solutions of two nonlinear Schrodinger equations”,J. Assn. Arab Univ. Basic Appl. Sci., Vol.: 24, Issue:1, pp.:184-190, 2017.

XIII.F. Mahmud,M. Samsuzzoha, M. A. Akbar, “The generalized Kudryashov method to obtain exact traveling wave solutions of the PHI-four equation and the Fishers equation”,Res. Phys., Vol.: 7, pp.: 4296-4302, 2017.

XIV.G. Allah,R. Musa, Elzaki, M. Tarig, “Application of new homotopy perturbation method for solving partial differential equations”, J. Comput. Theor. Nanosci., Vol.: 15, Issue: 2, pp.: 500-508, 2018.

XV.H. Mao,Q. P. Liu, “Backlund-Darboux transformation and discretizations of 𝑁=2, 𝑎=−2supersymmetric KdV equation”,Phys. Lett. A, Vol.:382, Issue: 5, pp.: 253-258, 2018.

XVI.H. Naher,F. A. Abdullah, M. A. Akbar, “The exp function method for the new exact solution of the nonlinear partial differential equations”, Int. J. Phys. Sci., Vol.: 6, Issue: 29,pp.:6706-6716, 2011.

XVII.H. Triki,A. Yildirim, T. Hayat, O. M. Aldossary, A. Biswas, “Shockwave solution of Benney-Luke equation”,Romanian J. Phys., Vol.: 57, Issue: 7-8, pp.: 1029-1034, 2012.

XVIII.I. Hasim,”Adomian decomposition method for solving BVPs for fourth-order integrodifferential equations”,J. Comput. Appl. Math., Vol.: 193, Issue: 2,pp.:658-664, 2006.

XIX.J. H.He, “Homotopy perturbation technique”,Comput. Methods Appl. Mech. Eng., Vol.:178, Issue: 3-4,pp.:257-262, 1999.

XX.K. A. Gepreel, T. A. Nofal, A. A. Alasmari,”Exact solutions for nonlinear integro-partial differential equations using the generalized Kudryashov method”,J. Egypt. Math. Soc., Vol.: 25, pp.: 438-444, 2017.

XXI.K. Khan, M. A. Akbar, N. H. M. Ali,”The modified simple equation for exact and solitary wave solution of nonlinear evolution equation: the GZK-BBM equation and right-handed non-commutative Burgers equations”,ISRN Math. Phys., pp: 5, Article ID 146704, 2013.

XXII.K. R. Raslan,”The application of He’s exp function method for mKdV and Burgers equations with variable coefficients”,Int. J. Nonlinear Sci., Vol.: 7, Issue: 2, pp.: 174-181, 2009.

XXIII.L. Xu,”He’s parameter expanding methods for strongly nonlinear oscillators”,J. Comput. Appl. Math., Vol.: 207, Issue: 1, pp.: 148-154, 2007.

XXIV.M. A. Akbar, N. H. M. Ali,”The improved F-expansion method with the Riccati equation and its applications in mathematical physics”,Cogent Math. Vol.: 4, ID.: 1282577, 2017

XXV.M. A. Khater, A. R. Seadawy, D. Lu,”Dispersive solitary wave solutions of new coupled Konno-Ono,Higgs field and Maccari equations and their applications”,J. King Saud Univ. Sci., Vol.: 30, pp.: 417-423, 2018.

XXVI.M. Kaplan, A. Bekir, A. Akbulut, E. Aksoy,”The modified simple equation method for nonlinear fractional differential equations”,Romanian J. Phys., Vol.: 60, Issue: 9-10,pp.:1374-1383, 2015.

XXVII.M. K. Elboree,”The Jacobi elliptic function method and its application for two-component BKP hierarchy equations”,Comput. Math. Appl., Vol.: 62, Issue: 12,pp.: 4402-4414, 2011.

XXVIII.M. Koparan, M. Kaplan, A. Bekir, O. Guner,”A novel generalized Kudryashov method for exact solutions of nonlinear evolution equations”,AIP Con. Proc., Vol.: 1798, Issue: 1, 2017.

XXIX.M. M. Kabir, A. Khajeh, E. Aghdam, A. Y. Koma,”Modified Kudryashov method for finding exact solitarywave solutions of higher order nonlinear equations”,Math. Methods Appl. Sci., Vol.: 34, Issue: 2, pp.: 213-219, 2011.

XXX.M. S. Islam, K. Khan, M. A. Akbar,”Application of the improved F-expansion method with Riccati equation to find the exact solution of the nonlinear evolution equations”,J. Egypt. Math. Soc.,Vol.:25, pp.: 13-18, 2017.

XXXI.N. Ahmed, S. Bibi, U. Khan, S. T. Mohyud-din,”A new modification in the exponential rational function method for nonlinear fractional differential equations”,Eur. Phy. J. Plus, Vol.: 133, Issue: 45, 2018.

XXXII.N. Taghizadeh, M. Mirzazadeh,”The first integral method to some complex nonlinear partial differential equations”,J. Comput. Appl. Math., Vol.: 235,pp.:4871-4877, 2011.

XXXIII.O. A. Taiwo,”A parameter expansion method for two-point nonlinear singularly perturbed boundary value problems”,Int. J. Comput. Math., Vol.:55, Issue: 3-4, pp.: 189-196, 1995.

XXXIV.S. H. Dong,”The ansatz method for analyzing Schrodinger’s equation with three anharmonic potentials in D dimensions”,J. Genetic Counse., Vol.: 15, Issue: 4, pp.: 385-395, 2002.

XXXV.S. Kumar, K. Sing, R. K. Gupta,”Coupled Higgs field equations and Hamiltonian amplitude equation: Lie classical approach and (𝐺′/𝐺)-expansion method”,Prama. J. Phys., Vol.: 79, Issue: 1, pp.: 41-60, 2012.

XXXVI.S. Kutluay, A. Esen,”Exp function method for solving the general improved KdV equation”,Int. J. Nonlinear Sci. Numer. Simul., Vol.: 10, Issue: 6, pp.: 717-725, 2009

XXXVII.S. Sirisubtawee, S. koonprasert,”Exact traveling wave solution of certain nonlinearpartial differential equations using the (𝐺′𝐺2)-expansion method”,Advan. Math. Phys., Article ID 7628651, pp.:15, 2018.

XXXVIII.X. J. Yang, H. M. Srivastava, J. H. He, D. Baleanu,”Cantor-type cylindrical co-ordinate method for differential equations with local fractional derivatives”,Phys. Lett. A, Vol.: 377, Issue: 28-30, pp.: 1696-1700, 2013.

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XL.Z. Islam,M. M. Hossain, M. A. W. Seikh, “Exact traveling wave solution to Benney-Luke equation”,J. Bangladesh Math. Soc., Vol.: 37, pp.:1-14, 2017.

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Towards Risk Adjusted Performance Appraisal of Indian Mutual Funds


Atanu Das



This paper is based on the study of mutual funds in India which is understood to be one of the most vibrant in the money market. This paper analyses a set of representative schemes from heterogeneous group of different fund houses. There are well established criteria to judge their performance absolutely and also in relative terms. This paper deals with the analysis of risk-returns parameters of different mutual fund schemes and the relation between the risk preference of the investors and the risk adjusted performance (RAP) measure based on real time data. Various tests are applied to evaluate the performance of mutual funds based on well established measures and those tests have been used to rank the funds accordingly. Some hypotheses are constructed and tested to find out whether there are significant differences in their absolute and RAP. The paper also proposed an easy and practical path to solve an optimal portfolio problem containing the various mutual fund schemes. The analysis is carried out with the help of William Sharpe’s single index model and result could of use to substantial investors who are choosing an optimum portfolio of various mutual funds.


Mutual fund,Risk adjusted performance,Sharp index,Optimal portfolio,


I.A. Shah, S. Thomas, M. Gorham, India‟s Financial Market: An Insider‟s Guide, How the Markets Work, Academic Publishers, 2008.

II.B. Roy and S. S. Deb, “Conditional Alpha and Performance Persistence for Indian Mutual Funds: Empirical Evidence”, ICFAI Journal of Applied Finance, pp. 30-48, January, 2004.

III.E.Thanou,“Mutual Fund Evaluation During Up and Down Market Conditions: The Case of Greek Equity Mutual Funds”, International Research Journal of Finance and Economics, Vol.:13, pp. 84-93, 2008.

IV.G. Elton, G. Brown, “Modern portfolio theory and investment analysis”, 7th edition, John Wiley & Sons, Inc, 2007.

V.J. A. Haslem, Mutual funds: risk and performance analysis for decision making. John Wiley & Sons, 2009.

VI.J. D. Jobson, and B. Korkie, “Performance Hypothesis Testing with the Sharpe and Treynor Measures”, Journal of Finance, 36, 888-908, 1981.

VII.K. Daniel, M. Grinblatt, S. Titman and R. Wermers, “Measuring mutual fund performance with characteristic-based benchmarks”, Journalof Finance 52, 1035–1058, 1997.

VIII.L. Chan, H. Chen and J. Lakonishok, “On Mutual Fund Investment Styles”, The Review of Financial Studies, Vol.: 15, Issue: 5, pp. 1407-1437, 2002.

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X.M. Jayadev, “Mutual Fund Performance: An Analysis of Monthly Returns”, Finance India, Vol.: X, No.: 1, pp. 73–84, 1996

XI.N. D.Rao, “Investment Styles and Performance of Equity Mutual Funds in India”, available at SSRN, 2006.

XII.P. K. Muthappan and E. Damodharan, “Risk-Adjusted Performance of Indian Mutual Funds Schemes”,Finance India,Vol.: 20, Issue: 3, 2006.

XIII.R. Bahadur, P. S. Koirala, “Application of Markowitz and Sharpe Models in Nepalese Stock Market”, The Journal of Nepalese Business Studies, Vol.: III, No.: 1, 2006.

XIV.S. D. Groot, and A. Plantinga, Risk-Adjusted Performance Measures and Implied Risk-Attitudes”, available at, Nov 2001.

XV.S. H. Thomas and A. P. Ralph, “Equity Mutual Fund Historical Performance Ratings as Predictors of Future Performance”, Journal of Financial and Strategic Decisions, Vol.: 9, No.: 1, 1996.

XVI.S. Lee, and S. Stevenson, “Testing the Statistical Significance of Sector and Regional Diversification. Journal of Property Investment, and Finance, Vol.: 23, Issue: 5, pp. 394–411, 2005.

XVII.S. Sankaran, Indian Mutual Funds Handbook , A Guide For Industry Professionals And Intelligent Investors, 2nd ed., Vision Books, 2008.

XVIII.W. F. Sharpe, “The Sharpe Ratio”, Journal of Portfolio Management, Vol.: 21, 1994.

XIX.W. Sharpe, G. J. Alexander, J. W. Bailey, Investment, PHI (2006).

XX.Y. Ali, “Simplifying the Portfolio Optimization Process via Single Index Model”, available, 2008.

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An Enhanced Data Access Control and Privacy Preserving Mechanism in Cloud Using Uncrackable Cipher Dynamic Double Encryption Standard


P. Jhansi Rani, Dr. M. Akkalakshmi



Cloud computing is the evolving paradigm that provides the services in which cloud consumers can remotely save their data into the cloud and access the on-demand high-quality applications. In the existing technique explained an Extendable Access Control System procedure supposed that the authority is the trusted party, but in many cases, they may perform an illegal action which causes the data loss. The proposed work encrypted the data through Uncrackable Cipher Dynamic Double Encryption Standard (UCDDES). Generally, the UCDDES contains the key length of 32, 40 and 48. To randomly select the key length reduced the data security issues. After dynamically selecting the key length the data governor sent the key request to the authority. Then based on the obtained key length the data governor generated the partial secret key. It is further used to decrypt the data and stored in the cloud storage. The results improve the security of cloud and access control. It reduces the issue of unauthorized user/ hackers accessing data. It increases the cloud security and prevents from dictionary attacks, brute force attacks, collision attacks, and so on.


Cloud computing,data security issues,UCDDES based data encryption,cloud network security,


I.Cui, H., Deng, R. H., & Li, Y. (2018). Attribute-based cloud storage with secure provenance over encrypted data.Future Generation Computer Systems,79, 461-472.

II.Di Vimercati, S. D. C., Foresti, S., Jajodia, S., Paraboschi, S., &Samarati, P. (2007, November). A data outsourcing architecturecombining cryptography and access control. InProceedings of the 2007 ACM workshop on Computer security architecture(pp. 63-69). ACM.

III.Divya, S. V., Shaji, R. S., &Venkadesh, P. (2018). An Efficient Data Storage and Forwarding Mechanism Using Fragmentation-Replication and DADR Protocol for Enhancing the Security in Cloud. Journal of Computational and Theoretical Nanoscience,15(1), 111-120.

IV.Goyal, V., Pandey, O., Sahai, A., & Waters, B. (2006, October). Attribute-based encryptionfor fine-grained access control of encrypted data. InProceedings of the 13th ACM conference on Computer and communications security(pp. 89-98). Acm.

V.Hur, J. (2013). Improving security and efficiency in attribute-based data sharing.IEEE transactions on knowledge and data engineering,25(10), 2271-2282.

VI.Iyapparaja, M., Navaneethan, C., Meenatchi, S., Kumar, P. J., &Suganya, P. (2017). A Privacy-Preserving Secure Access Control Mechanism in Cloud.

VII.Kumar, K., & Lu, Y. H. (2010). Cloud computing for mobile users: Can offloading computation save energy?.Computer,43(4), 51-56.

VIII.Mell, Peter, and Tim Grance. “The NIST definition of cloud computing.” (2011).

IX.Ning, J., Cao, Z., Dong, X., Liang, K., Wei, L., & Choo, K. K. R. (2018). CryptCloud+: Secure and Expressive Data Access Control for Cloud Storage.IEEE Transactions on Services Computing.

X.Patil, P., Narayankar, P., Narayan, D. G., &Meena, S. M. (2016). A comprehensive evaluation of cryptographic algorithms: DES, 3DES, AES, RSA, andBlowfish.Procedia Computer Science,78, 617-624.

XI.Qiu, M., Gai, K., Thuraisingham, B., Tao, L., &Zhao, H. (2018). Proactive user-centric secure data scheme using attribute-based semantic access controls for mobile clouds in financialindustry.Future Generation Computer Systems,80, 421-429.

XII.Sahai, A., & Waters, B. (2005, May). Fuzzy identity-based encryption. InAnnual International Conference on the Theory and Applications of Cryptographic Techniques(pp. 457-473). Springer, Berlin, Heidelberg.

XIII.Shiraz, M., Sookhak, M., Gani, A., & Shah, S. A. A. (2015). A study on the critical analysis of computational offloading frameworks for mobile cloud computing.Journal of Network and Computer Applications,47, 47-60.

XIV.Sookhak, M., Akhunzada, A., Gani, A., Khurram Khan, M., &Anuar, N. B. (2014). Towards dynamic remote data auditing in computational clouds.The Scientific World Journal,2014.

XV.Sookhak, M., Gani, A., Khan, M. K., &Buyya, R. (2017). Dynamic remote data auditing for securing big data storage in cloud computing.Information Sciences,380, 101-116.

XVI.Sookhak, M., Gani, A., Talebian, H., Akhunzada, A., Khan, S. U., Buyya, R., &Zomaya, A. Y. (2015). Remote data auditing in cloud computing environments: a survey, taxonomy, and open issues.ACM Computing Surveys (CSUR),47(4), 65.

XVII.Sookhak, M., Talebian, H., Ahmed, E., Gani, A., & Khan, M. K. (2014). A review on remote data auditing in single cloud server: Taxonomy and open issues.Journal of Network and Computer Applications,43, 121-141.

XVIII.Sookhak, M., Yu, F. R., Khan, M. K., Xiang, Y., &Buyya, R. (2017). Attribute-based data access control in mobile cloud computing: Taxonomy and open issues.Future Generation Computer Systems,72, 273-287.

XIX.Srinivasan, S., & Raja, K. (2018). An Advanced Dynamic Authentic Security Method for Cloud Computing. InCyber Security: Proceedings of CSI 2015(pp. 143-152).Springer Singapore.

XX.Tang, H., Sun, Q. T., Yang, X., & Long, K. (2018). A Network Coding and DES Based Dynamic Encryption Scheme for Moving Target Defense.IEEE Access,6, 26059-26068.

XXI.Wang, C., Ren, K., Lou, W., & Li, J. (2010). Toward publicly auditable secure cloud data storage services.IEEE Network,24(4).

XXII.Whaiduzzaman, M., Sookhak, M., Gani, A., &Buyya, R. (2014). A survey on vehicular cloud computing.Journal of Network and Computer Applications,40, 325-344.

XXIII.Yuan, D., Song, X., Xu, Q., Zhao, M., Wei, X., Wang, H., & Jiang, H. (2018). An ORAM-based privacy-preservingdata sharing scheme for cloud storage.Journal of information security and applications,39, 1-9.

XXIV.Zhou, Z., & Huang, D. (2012, October). Efficient and secure data storage operations for mobile cloud computing. InProceedings of the 8th International Conference on Network and Service Management(pp. 37-45). International Federation for Information Processing.

XXV.Zuo, C., Shao, J., Liu, J. K., Wei, G.,& Ling, Y. (2018). Fine-Grained Two-Factor Protection Mechanism for Data Sharing in Cloud Storage.IEEE Transactions on Information Forensics and Security,13(1), 186-196.

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Demystifying Deep Learning Frameworks- A Comparative Analysis


Divyanshu Sinha, JP Pandey, Bhavesh Chauhan



Deep learning is a rapidly growing field of machine learning which finds the application of its methods to provide solutions to numerous problems related to computer vision, speech recognition, natural language processing, and others. This paper gives a comparative analysis of the five deep learning tools on the grounds of training time and accuracy. Evaluation includes classifying digits from the MNIST data set making use of a fully connected neural network architecture (FCNN). Here we have selected five frameworks— Torch ,Deeplearning4j, TensorFlow, Caffe & Theano (with Keras), to evaluate their performance and accuracy. In order to enhance the comparison of the frameworks, the standard MNIST data set of handwritten digits was chosen for the classification task. When working with the data set, our goal was to identify the digits (0–9) using a fully connected neural network architecture. All computations were executed on a GPU. The key metrics addressed were training speed, classification speed, and accuracy.


Deep Learning, Feedforward MLP,Keras,Tensorflow,Theano,Caffe,Deeplearning4j,Torch,


I.Anuj Dutt, AashiDutt. “Handwritten Digit Recognition Using Deep Learning. ” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 6, Issue 7, July 2017.

II.Alexander K. Seewald, “On the Brittleness of Handwritten Digit Recognition Models,”ISRN Machine Vision, vol. 2012, Article ID 834127, 2012.

III.Li DengMicrosoft Research, Redmond, Washington USA. ” The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]” IEEE Signal Processing Magazine(Volume: 29,Issue: 6, Nov. 2012).

IV.Muhammad Ramzan, Shahid Mehmood Awan,Hikmat Ullah Khan , Waseem Akhtar, Ammara Zamir,Mahwish Ilyas. “A Survey on using Neural Network based Algorithms for Hand Written Digit.” International Journal of Advanced Computer Science and Applications, Vol. 9, No. 9, 2018.

V.Subhransu Maji and Jitendra Malik EECS Department University of California, Berkeley Technical Report No. UCB/EECS-2009-159 November 25, 2009

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