Archive

Abstract:

Three different techniques were assessed for estimation of chlorophyll content from each leaf samples. In the first method SPAD-502 hand held meter was used to estimate SPAD values of leaf. In the second method flatbed scanner was used to acquire the sample leaf image for estimation of SPAD and Chlorophyll concentration. The third method was biochemical based spectrophotometric approach for estimating chlorophyll concentration.Extensive statistical analysis based on Information criterion theory was made for selection and evaluation of proposed RGB image processing based color model for estimating SPAD value and chlorophyll concentration. The resultsrevealed that image processing techniques has good potential in estimating SPAD and chlorophyll concentration values relative to biochemical method using spectroscopic technique and SPAD meter reading. The present study also pointed out the fact that for the SPAD value and chlorophyll concentration estimation using proposed image processing technique gives better results with dual color band as compared to single or triple color band.Furthermore, estimated SPAD value and chlorophyll concentration differ from Image processing technique (photometric) measurement of leaf samples by 5.538% (p<0.001) and 0.0185% (p<0.001), respectively.

Keywords:

Chlorophyll,SPAD,RGB,mage processing, AIC,BIC,

Refference:

I.Adkison, M. D., Peterman, R. M., Lapointe, M. F., Gillis, D. M., and Korman, J. (1996). Alternative models of climatic effects on sockeye salmon, Oncorhynchusnerka, productivity in Bristol Bay, Alaska, and the Fraser River, British Columbia.Fisheries Oceanography,5(3‐4), 137-152.

II.Afshari-Jouybari, H., and Farahnaky, A. (2011). Evaluation of Photoshop software potential for food colorimetry.Journal of Food Engineering,106(2), 170-175.

III.Bannari, A., Khurshid, K., Staenz, K., and Schwarz, J. (2006). Wheat Crop Chlorophyll Content Estimation From Ground-Based Reflectance Using Chlorophyll Indices, IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, 2006, pp. 112-115. doi: 10.1109/IGARSS.2006.34.

IV.Curran, P. J., Dungan, J. L., and Gholz, H. L. (1990). Exploring the relationship between reflectance red edge and chlorophyll content in slash pine. Tree Physiol., 7, 33–48.

V.Dey, A. K., Sharma, M., and Meshram, M. R. (2016a). Image Processing Based Leaf Rot Disease, Detection of Betel Vine (Piper BetleL.).Procedia Computer Science,85, 748-754.

VI.Dey, A. K., Sharma, M., and Meshram, M. R. (2016b). An Analysis of Leaf Chlorophyll Measurement Method Using Chlorophyll Meter and Image Processing Technique.Procedia Computer Science,85, 286-292.

VII.Filella, I., Serrano, I., Serra, J., and Peñuelas, J. (1995) Evaluating wheat nitrogen status with canopy relfectance indices and discriminant analysis. Crop Sci., 35, 1400–1405.

VIII.Gitelson, A. A., Gritz, Y., and Merzlyak, M. N. (2003). Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves.Journal of plant physiology,160(3), 271-282. http://dx.doi.org/10.1078/0176-1617-00887.

IX.Glatting, G., Kletting, P., Reske, S. N., Hohl, K., and Ring, C. (2007). Choosing the optimal fit function: comparison of the Akaike information criterion and the F-test.Medical physics,34(11), 4285-4292.

X.Graeff, S., Pfenning, J., Claupein, W., and Liebig, H. P. (2008). Evaluation of image analysis to determine the N-fertilizer demand of broccoli plants (Brassica oleraceaconvar. botrytis var. italica).Advances in optical technologies,2008, 8.doi:10.1155/2008/359760.

XI.Guendouz, A., Guessoum, S.,Maamari, K., and Hafsi, M. (2012). Predicting the efficiency of using the RGB (Red, Green and Blue) reflectance for estimating leaf chlorophyll content of Durum wheat (Triticum durum Desf.) genotypes under semi arid conditions.American-Eurasian Journal of Sustainable Agriculture, 102-107.Guha, P. (2006). Betel leaf: the neglected green gold of India.J Hum Ecol, 19 (2), 87-93.

XII.Gupta, S. D., Ibaraki, Y., and Pattanayak, A. K. (2013). Development of a digital image analysis method for real-time estimation of chlorophyll content in micropropagated potato plants.Plant biotechnology reports,7(1), 91-97.

XIII.Hu, H., Liu, H. Q., Zhang, H., Zhu, J. H., Yao, X. G., Zhang, X. B., and Zheng, K. F. (2010, December). Assessment of chlorophyll content based on image color analysis, comparison with SPAD-502. IEEE, 2nd International Conference onInformation Engineering and Computer Science (ICIECS), 1-3.

XIV.Kawashima, S., and Nakatani, M. (1998). An algorithm for estimating chlorophyll content in leaves using a video camera.Annals of Botany,81(1), 49-54.

XV.Liangliang, J., Chen, X., Zhang, F., Buerkert, A., and Romheld, V. (2004). Use of digital camera to assess nitrogen status on winter wheat in the northern china plain. Journal of Plant Nutrition 27: 441-450.

XVI.Pagola, M., Ruben, O., Ignacio, I., Humberto, B., Edurne, B., Pedro, A. T., Carmen, L., and Berta, L. (2009). New method to assess barley nitrogen nutrition status based on image color analysis comparison with SPAD-502. Computers and Electronics in Agriculture, 65, 213-218.

XVII.Peng, S., García, F. V., Laza, R. C., and Cassman, K. G. (1993). Adjustment for specific leaf weight improves chlorophyll meter’s estimate of rice leaf nitrogen concentration.Agronomy Journal,85(5), 987-990.

XVIII.Pydipati, R., Burks, T. F.,and Lee, W. S. (2006). Identification of citrus disease using color texture features and discriminate analysis. Computers and Electronics in Agriculture, 52, 49-59.

XIX.Ritz, C., and Spiess, A. N. (2008). qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis. Bioinformatics,24(13), 1549-1551.

XX.Sakamoto, Y., Ishiguro, M., and Kitagawa, G. (1986). Akaike Information Statistics. KTK Scientific Publishers, D. Reidel Publishing, Tokyo, Dordrecht.

XXI.Shukla, A. K., Ladha, J. K., Singh, V. K., Dwivedi, B. S., Balasubramanian, V., Gupta, R. K., and Padre, A. T. (2004). Calibrating the leaf color chart for nitrogen management in different genotypes of rice and wheat in a systems perspective.Agronomy Journal,96(6), 1606-1621.

XXII.Spiess, A. N., and Neumeyer, N. (2010). An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach.BMC pharmacology,10(1), 6.

XXIII.Su, C. H., Fu, C. C., Chang, Y. C.,Nair, G. R., Ye, J. L., Chu, I., and Wu, W. T. (2008). Simultaneous estimation of chlorophyll a and lipid contents in microalgae by three‐color analysis.Biotechnology and bioengineering,99(4), 1034-1039.

XXIV.Teoh, C. C., Daud, A. H., Mispan, M. R., and Jiken, J. J. (2015). Prediction of SPAD chlorophyll meter readings using remote sensing technique.Journal of Tropical Agriculture and Food Science,40, 127-136.

XXV.Vollmann, J., Sato, T., Walter, H., Schweiger, P., and Wagentristl, H. (2011). Soybean di-nitrogenfixation affecting photosynthesis and seed quality characters.Soil, Plant and Food Interactions, 496-502.

XXVI.Wang, Y., and Liu, Q. (2006). Comparison of Akaike information criterion (AIC) and Bayesian information criterion (BIC) in selection of stock–recruitment relationships.Fisheries Research,77(2), 220-225.

XXVII.Wang, Y., Wang, D., Shi, P., and Omasa, K. (2014). Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light.Plant methods,10(1), 1-11.

XXVIII.Wood, C. W., Reeves, D. W., and Himelrick, D. G. (1993). Relationships between chlorophyll meter readings and leaf chlorophyll concentration, N status, and crop yield: a review.Proceedings of the Agronomy Society of New Zealand, 23, 1-9.

XXIX.Yadav, S. P., Ibaraki, Y., and Gupta, S. D. (2010). Estimation of the chlorophyll content of micropropagated potato plants using RGB based image analysis. Plant Cell, Tissue and Organ Culture (PCTOC),100(2), 183-188.

XXX.Yoshida, S., Forno, D. A., and Cock, J. H. (1971). Laboratory manual for physiological studies of rice,Los Baños, Philippines.

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Abstract:

Thespace time fractional modified KdV equation and fractional Kolmogorov-Petrovskii-Piskunov(KPP)equation models the unidirectional and bidirectional waves on shallow water surfaces, long internal wavein a density-stratified ocean, ion acoustic waves in plasma, acoustic waves on a crystal lattice. The fractional derivatives are defined in the modified Riemann-Liouville sense.In this article, we obtain exact solution of these equations by means of the recently established two variables(G1/G,1/G)-expansion method.The solutions are obtained in the form of hyperbolic, trigonometric and rational functions involving parameters. When the parameters are assigned particular values, the solitary wave solutions are generated from the traveling wave solutions. The method indicates that it is easy to implement,computationally attractive and is the general form of theoriginal(G1/G)-expansion method.

Keywords:

Exact solution,fractional modified KdVequation,Kolmogorov-Petrovskii-Piskunov equation,modified Remann-Liouville derivative,traveling wave solution,solitary wave solution,

Refference:

I.Akbar, M. A., Ali, N. H. M., and Zayed, E. M. E. “A generalized and improved -expansion method for nonlinear evolution equation”. Math Probl. Eng., Vol. 20, No. 12, pp 12-22 (2012).

II.Akbar, M. A., Ali, N. H. M., and Zayed, E. M. E. “Abundant exact traveling wave solutions of the generalized Bretherton equation via the improved -expansion method”. Commun. Theor. Phys., Vol. 57, No. 2, pp 173-178 (2012).

III.Akbar, M. A., and Ali, N. H. M., “New solitary and periodic solutions of nonlinear evolution equation by Exp-function method”. World Applied Science Journal , Vol. 17, No. 12, pp 1603-1610 (2012).

IV.Arafa, A. A. M., Rida, S. Z. and Mohamed, H. “Homotopy analysis method for solving biological population model”. Commun. Theor. Phys., Vol.56, No.5, pp 797-800 (2011).

V.Aslan, I. “Discrete exact solutions to some nonlinear differential-difference equations via the -expansion method”. Appl. Math. Comp., Vol. 215, No. 8, pp 3140-3147 (2009).

VI.Ayhan, B. and Bekir, A. “The -expansion method for the nonlinear lattice equations”. Commun. Nonlinear Sci. Numer. Simulat., Vol. 17, pp 3490-3498 (2012).

VII.Bekir, A., Guner, O. and Cevikel, A. C. “Fractional Complex Transform and Exp-Function Methods for Fractional Differential Equations”. Abst. Appl. Anal., Vol. 13, pp 426-462 (2013).

VIII.Bekir, A., Guner, O. and Unsal, O. “The First Integral Method for exact Solutions of nonlinear Fractional Differential Equation”. J. Comp. Nonlin. Dyn., Vol. 10 (2015).

IX.Caputo, M. “Linear models of dissipation whose is almost frequency independent, Geophysics”. J.Roy. Astron. Soc. Vol. 13, No. 2, pp 529-539 (1967).

X.El-Sayedand, A. M. A., and Gaber, M. “The Adomian’s decomposition method for solving partial differential equation of fractional order in finite domains”. Phys. Lett. A, Vol.359, No.3, pp175-182 (2006).

XI.El-Sayed, A. M. A., Behiry, S. H., and Raslan, W. E: Adomian’s decomposition method for solving an intermediate fractional advection-dispersion equation, Computers and Mathematics with applications, Vol. 59, No. 5, pp 1759-1765 (2010)

XII.Erturk, V. S., Momani, S. and Odibat, Z. “Application of Generalized Transformation Method to Multi-order Fractional Differential Equations”. Commun. Nonlin. Sci. Numer. Simul., Vol. 13, No.8, pp1642-1654 (2008).

XIII.Feng, J., Li, W., and Wan, Q. “Using -expansion to seek traveling wave solution of Kadomtsev-Petviashvili-Piskunovequation”. Appl. Math. Comput, Vol. 217, pp 5860-5865 (2011).

XIV.Geprel, K.A. “The Homotopy Perturbation Method Applied to the Nonlinear fractional Kolmogorov-Petrovskii-Piskunov Equations”. Appl. Math. Lett., Vol.24, No.8, pp1428-1434 (2011).

XV.Gepreel, K. A and Omran, S. “Exact solutions for nonlinear partial fractional differential equations”. Chinese Phys. B, Vol. 21, No. 11 (2012).

XVI.Guo, S. and Mei, L. “The fractional variational iteration method using He’s polynomial”. Phys. Lett. A, Vol.375, No.3, pp309-313 (2011).

XVII.Guo, S. M., Mei, L. Q., Li, Y. and Sun, Y. F. “The improved fractional sub-equation method and its applications to the space-time fractional differential equations in fluid mechanics”. Phys. Lett. A, Vol.376, No.4, pp407-411 (2012).

XVIII.Gupta, P. K.and Singh, M. “Homotopy Perturbation Method for fractionalFornberg-Whitham Equation”. Comput. Math. Appl., Vol.61, No.2, pp250-254 (2011).

XIX.Hariharan, G. “The homotopy analysis method applied to the Kolmogorov-Petrovskii-Piskunov (KPP) equation and fractional KPP equations”. J. Math. Chem., Vol. 51, No. 3, pp 992-1000 (2013).

XX.Ji, J., Zhang, J. B. and Dong, Y. J. “The fractional variational iteration method improved with the Adomian series”. Appl. Math. Lett., Vol. 25, pp 2223-2226 (2012).

XXI.Jumarie, G. “Modified Riemann-Liouville derivative andfractional Taylor series of non-differentiable functions further results”. Comput. Math. Appl. Vol. 51, pp 1367-1376 (2006).

XXII.Kilbass, A. A, Srivastava, H. M, Trujillo, J. J: Theory and applications of fractional differential equations, Elsevier, Amsterdam, Netherlands (2006).

XXIII.Kudryshov, N. A. “A note on the -expansion method”. Appl. Math. Comput., Vol. 217, No. 4, pp 1755-1758 (2010).

XXIV.Li, L. X., Li, E. Q. and Wang, M. L. “The -expansion method and its application to travelling wave solutions of the Zakharov equation”. Appl. Math. B, vol. 25, No. 4, pp 454-462 (2010).

XXV.Lu, B. “Backlund transformation of fractional Riccati equation and its applications to nonlinear fractional partial differential equations”. Phys. Lett. A, Vol.376, pp2045-2048, (2012).

XXVI.Lu, B. “The first integral method for some time fractional differential equation” J. Math. Anal. Appl., Vol. 395, No. 2, pp 684-693 (2012).

XXVII.Miller, K. S. and Ross, B.: An introduction to the fractionalcalculus and fractional differential equations, Wiley, New York (1993).

XXVIII.Odibat, Z. and Momani, S. “Generalized Differential Transform Method for Linear Partian Differential Equations of fractional Order”. Appl. Math. Lett. Vol.21, No.2, pp194-199 (2008).

XXIX.Podlubny, I. : Fractional differential equations, Academic, San Diego, CA (1999).

XXX.Ray, S. S. “A new approach for the application of Adomian’s decomposition method for the solution of fractional space diffusion equation with insulated ends”. Appl. Math. Comput., Vol. 202, No. 2, pp 544-549 (2008).

XXXI.Seadawy,A.R. “Approximation solutions of derivative nonlinear Schrodinger equation with computational applications by variational method”. The Euro. Phys. J. Plus., Vol. 130, pp 182-187 (2015).

XXXII.Seadawy, A. R. “Stability analysis of traveling wave solutions for generalized coupled nonlinear KdV equations”. Appl. Math. Inf. Sci. Vol. 10, No. 1, pp 209-214 (2016).

XXXIII.Seadawy, A. R. and Dianchen, L. “Ion acoustic solitary wave solutions of three-dimensional nonlinear extended Zakharov-Kuznetsov dynamical equationin a magnetized two-ion-temperature dusty plasma”. Results in Phys., Vol. 6,pp 590–593 (2016).

XXXIV.Seadawy, A. R., Arshad, M. and Dianchen, L. “Stability analysis of new exact traveling Wave Solutions of new coupled KdV and new coupled Zakharov-Kuznetsov systems”. Eur. Phys. J. Plus vol. 132, pp 1-20 (2017).

XXXV.Seadawy, A. R. “Travelling wave solutions of a weakly nonlinear two-dimensional higher order Kadomtsev-Petviashvili dynamical equation for dispersive shallow waterwaves”. Eur. Phys. J. Plus., Vol.132, pp 29-35(2017).

XXXVI.Seadawy, A. R. “The generalized nonlinear higher order of KdV equations from the higher order nonlinear Schrodinger equation and its solutions, Optik”. Int. J. Light Elet. Opt., Vol. 139, pp 31-43 (2017).

XXXVII.Song, L. N. and Zhang, H. Q. “Solving the fractional BBM-Burger equation using the Homotopy analysis method”. Chaos. Solitons Fractals, Vol. 40, No. 4, pp 1616-1622 (2009).

XXXVIII.Uddin, M. H., Akbar, M. A., Khan, M. A. and Haque, M. A. “Close Form Solutionsof the Fractional Generalized Reaction Duffing Model and the Density Dependent Fractional Diffusion Reaction Equation”. Appl. Comput. Math., Vol. 6, No. 4, pp 177-184 (2017).

XXXIX.Wang, M. L., Li, X. Z., and Zhang, J. L., “The -expansion method and the traveling wave solutions of nonlinear evolution equations in mathematical physics” .Phys. Lett. A, Vol. 372, No. 4, pp 417-423 (2008).

XL.Wu, G. C. and Lee, E. W. M. “Fractional variational iteration method and its application”. Phys. Lett. A, Vol. 374,No. 25, pp 2506-2509 (2010).

XLI.Wu, G. C. “A fractional variational iteration method for solving fractional nonlinear differential equations”. Comput. Math. Appl., Vol. 61, No. 8, pp 2186-2190 (2011).

XLII.Zayed, E. M. E. “The -expansion method and its applications to some nonlinear evolution equations in the mathematical physics”. J. Appl. Math. Comput., Vol. 30, No. 1, pp 89-103 (2009).

XLIII.Zayed, E. M. E. and Abdelaziz, M. A. M. “The two variable -expansion method for solving the nonlinearKdV-mkdV, equation”.Math. Prob. Engineering, ID 725061, 14 pages (2012).

XLIV.Zhang, S., Zong, Q. A., Liu, D. and Gao, Q. “A Generalized Exp-Function Method for Fractional Riccati Differential Equations”. Commun. Fractional Calculus, Vol. 1, No. 1, pp 48-51 (2010).

XLV.Zhang, S. and Zhang, H. Q. “Fractional sub-equation method and its application to the nonlinear fractional PDEs”. Phys. Lett. A, Vol. 375, No. 7, pp 1069-1073 (2011).

XLVI.Zhang, B. “-expansion method for solving fractional partial differential equation in the theory of mathematical physics”. Comm. Theor. Phys., Vol. 58, pp 623-630 (2012).

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Abstract:

The communication in a clustered WBAN is performed at different levels through multiple nodes and controllers. This kind of multi-level involvement of nodes opens the nodes for security leaks. In this paper, a dual level security is integrated using hybrid cryptography method. A hybrid authentication and cryptography based method is defined for identity and information level security. The hybridization of security for clustered WBAN is achieved using RSA and hash key encoder. The RSA is here applied for node to controller for identification and verification whereas SHA is applied for reliable symmetric message encoding for node-to-controller and controller-to-controller communication. The proposed security model is applied in an integrated form to the clustered WBAN network to improve communication reliability. The proposed secure communication model has improved the performance of the network. The simulation is applied on clustered WBANs with different number of WBANs. The comparative simulation results show that the proposed model has effectively improved the packet communication and network life.

Keywords:

Body Area Network,Clustered,Secure, RSA,Hashcode,

Refference:

I.Ali, A. and Khan, F. A. (2015a). Key Agreement Schemes in Wireless Body Area Networks: Taxonomy and State-of-the-Art. Journal of Medical Systems.

II.Ali, A. and Khan, F. A. (2013b). Energy-efficient cluster-based security mechanism for intra-WBAN and inter-WBAN communications for healthcare applications. EURASIP Journal on Wireless Communications and Networking, 2013:216.

III.Al-Janabi, S., Al-Shourbaji, I., Shojafar, M. and Shamshirband, S. (2017). Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications. Egyptian Informatics Journal, 18(2), 113-122.

IV.Alsadhan,A.,andKhan, N. (2013). An LBP Based Key Management for Secure Wireless Body Area Network (WBAN), IEEE 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, Honolulu, HI, 2013,pp. 85-88.

V.Alshamsi, A. Z., and Barka, E. S. (2017). Implementation of energy efficient/lightweight encryption algorithm for wireless body area networks,” In Proc IEEE International Conference on Informatics, Health & Technology (ICIHT), Riyadh, 2017, pp.1-7.

VI.Challa, S., Das, A. K., Odelu, V., Kumar, N., Kumari, S., Khan, M. K., and Vasilakos, A. V. (2017). An efficient ECC-based provably secure three-factor user authentication and key agreement protocol for wireless healthcare sensor networks. Computers & Electrical Engineering.

VII.Drira, W., Renault, E. and Zeghlache, D. (2012). A Hybrid Authentication and Key Establishment Scheme for WBAN, IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications, Liverpool, 2012, pp. 78-83.

VIII.Fan, C., Wang, J., Huang, J., Tseng, Y., Juang, W., and Kikuchi, H. (2016). Flexible Authentication Protocol with Key Reconstruction in WBAN Environments, 6th International Conference on IT Convergence and Security (ICITCS), Prague, 2016, pp. 1-5.

IX.He, D., Zeadally, S., Kumar, N., and Lee, J. (2017). Anonymous Authentication for Wireless Body Area Networks With Provable Security. IEEE Systems Journal, 11(4), 2590-2601.

X.Khernane, N., Potop-Butucaru, M., and Chaudet, C. (2016). BANZKP: A Secure Authentication Scheme Using Zero Knowledge Proof for WBANs, IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Brasilia, 2016, pp. 307-315.

XI.Kompara, M., and Hölbl, M. (2018). Survey on security in intra-body area network communication. Ad Hoc Networks, 70, 23-43.

XII.Latre, B., Braem, B., Moerman, I., Blondia, C., and Demeester, P. (2011). A survey on wireless body area networks. Wireless Networks, 17(1), 1-18.

XIII.Li, X., Ibrahim, M. H., Kumari, S., Sangaiah, A. K., Gupta, V., and Choo, K. R.(2017). Anonymous mutual authentication and key agreement scheme for wearable sensors in wireless body area networks. Computer Networks, vol. 129, Part 2, 429-443.

XIV.Liu, J., Li, Q., Yan, R., and Sun, R. (2015). Efficient authenticated key exchange protocols for wireless body area networks. EURASIP Journal on Wireless Communications and Networking, 2015:188.

XV.Li, X., Peng, J., Kumari, S., Wu, F., Karuppiah, M., and Choo, K. R. (2017). An enhanced 1-round authentication protocol for wireless body area networks with user anonymity. Computers & Electrical Engineering, 61, 238-249.

XVI.Li, Z., and Wang, H. (2016). A key agreement method for wireless body area networks. IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), San Francisco, CA, 2016, pp. 690-695.

XVII.Li, Z., Wang, H., Daneshmand, M., and Fang, H. (2017). Secure and efficient key generation and agreement methods for wireless body area networks, IEEE International Conference on Communications (ICC), Paris, 2017, pp. 1-6.

XVIII.Li, Z., Wang, H., and Fang, H. (2017). Group-based Cooperation on Symmetric Key Generation for Wireless Body Area Networks. IEEE Internet of Things Journal, 4(6), 1955-1963.

XIX.Masdari, M., Ahmadzadeh, S., and Bidaki, M. (2017). Key management in wireless Body Area Network: Challenges and issues. Journal of Network and Computer Applications, 91, 36-51.

XX.Mehmood, A., Umar, M. M., and Song, H. (2017). ICMDS: Secure inter-cluster multiple-key distribution scheme for wireless sensor networks. Ad Hoc Networks, 55, 97-106.

XXI.Mukhtar, T. and Chaudhary, S. (2016). Energy efficient cluster formation and secure data outsourcing using TEOSCC and ECDH-IBT technique in WBAN. International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, 2016, pp. 596-602.

XXII.Prameela, S., and Ponmuthuramalingam, P. (2016). A robust energy efficient and secure data dissemination protocol for wireless body area networks, International Conference on Advances in Computer Applications (ICACA), Coimbatore, 2016, pp. 131-134.

XXIII.Raja, K. S. and Kiruthika, U. (2015). An Energy Efficient Method for Secure and Reliable Data Transmission in Wireless Body Area Networks Using RelAODV. Wireless Personal Communications, 83(4), 2975–2997.

XXIV.Salehi, S. A., Razzaque, M. A., Tomeo-Reyes, I., Hussain, N., and Kaviani, V. (2016). Efficient high-rate key management technique for wireless body area networks, 22nd Asia-Pacific Conference on Communications (APCC), Yogyakarta, 2016, pp. 529-534.

XXV.Shen, J., Chang, S., Shen, J., Liu, Q., and Sun, X. (2018). A lightweight multi-layer authentication protocol for wireless body area networks. Future Generation Computer Systems, 78(3), 956-963.

XXVI.Ullah, S., Higgins, H., Braem, B., Latre, B., Blondia, C., Moerman, I., Saleem, S., and Rahman, Z. (2012). A Comprehensive Survey of Wireless Body Area Networks. Journal of Medical Systems, 36(3), 1065-1094.

XXVII.Wei, F., Vijayakumar, P., Shen, J., Zhang, R., and Li, L. (2018). A provably secure password-based anonymous authentication scheme for wireless body area networks. Computers & Electrical Engineering, 65, 322-331.

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Abstract:

A big threat for the survival of mankind is the scarcity of power which is a serious matter to look into. Under this hard situation, the bioelectric energy is the most useful energy source instead of all the electronic power sources. Any electronic gadget can be activated with the help of bio-charger which is simple, portable and very much needed for the athletics. By recycling of energy and utilizing the energy conservation rule many problems related to energy consumption can be solved. The purpose of the research work is to make a bio-charger to preserve the bioelectric energy and to use it as the power source for any portable electronic gadget.

Keywords:

Lower Limb, Bioelectric Energy, Electromyography(EMG),Bio-charger,

Refference:

I.Alan G. Outten, Stephen J. Roberts and Maria J. Stokes (1996) “Analysis of human muscle activity”, Artificial Intelligence Methods for Biomedical Data Processing, IEE Colloquium, London .

II.A. H. Arieta, R. Katoh, H. Yokoi and Y. Wenwai (2006) “Development of a Multi D.O.F Electromyography Prosthetic System Using Adaptive Joint Mechanism”, Applied Bionics and Biomechanics, Vol. 3, Woodheads Publishing

III.Björn Gerdle, Stefan Karlsson, Scott Day and Mats Djupsjöbacka (1999) “Acquisition, Processing and Analysis of the Surface Electromyogram”. In: U. Windhorst, H. Johansson, editors. “Modern Techniques in Neuroscience Research”, Springer.

IV “Bagnoli EMG Systems Users Guide”, Delsys Incorporated, 2008.

V.Brian Dellon and Yoki Matsuoka (2007) “Prosthetics, Exoskeletons, and Rehabilitation-Now and the Future” IEEE Robotics & Automation Magazine, March, 2007.

VI.Carlo J. De Luca (1997) “Use of Surface Electromyography in Biomechanics” Journal of Applied Biomechanics, Vol.3.

VII.Carlo J. De Luca (2002) “Surface Electromyography: Detection and Recording”, Delsys Incorporated.

VIII.Carlo J. De Luca (2006) “Electromyography: Encyclopedia of Medical Devices and Instrumentation” (John G. Webster Ed.), John Wiley Publisher.

IX.Dr. Scott Day “Important Factors in Surface EMG Measurement”, Bortec Biomedical Incorporated.

X.D.J. Hewson, J.Y. Hoqrel and J. Duchene (2003) “Evolution in impedance at the electrode-skin interface of two types of surface EMG electrodes during long-term recordings” Journal of Electromyography and Kinesiology, Vol. 13, Issue 3 , pp. 273-279 .

XI.D.J. Hewson, J.Y. Hoqrel and J. Duchene (2003) “Evolution in impedance at the electrode-skin interface of two types of surface EMG electrodes during long-term recordings” Journal of Electromyography and Kinesiology, Vol. 13, Issue 3 , pp. 273-279 [17] (2009) “Instrumentation Amplifier Application Note”, Intersil Incorporated

XII.D. Edeer and C.W. Martin (2011) “Upper Limb Prostheses –A Review of the Literature with a Focus on Myoelectric Hands”, Worksafe BC Evidence-Based Practice Group

XIII.Gianluca De Luca (2001) “Fundamental Concepts in EMG Signal Acquisition”, Delsys Incorporated. XIV.“Instrumentation Amplifier Application Note”, Intersil Incorporated, 2009.

XV.Jarret Smith (2010) image title: “motor-unit-lg” Computational Intelligence in Electromyography Analysis –A Perspective on Current Applications and Future Challenges 448.

XVIM. E. Van Valkenburg (1982) “Analog Filter Design”, Holt, Rinehart & Winston.

XVIIMusslih LA. Harba and Goh Eng Chee (2002) “Muscle Mechanomyographic andElectromyography Signals Compared with Reference to Acting Potential Average Propagation Velocity”, Engineering in Medicine and Biology Society, 19th Annual International Conference of the IEEE, Vol.3.

XVIII. Nissan Kunju, Neelesh Kumar, Dinesh Pankaj, Aseem Dhawan,Amods Kumar (2009) “EMG Signal Analysis for Identifying WalkingPatterns of Normal Healthy Individuals” Indian Journal ofBiomechanics: Special Issue.

XIX.Nuria Masso, Ferran Rey, Dani Romero, Gabriel Gual, Lluis Costa and Ana German (2010) “Surface Electromyography and Applications in Sport” Apunts Medicina De L’Esport, Vol. 45: 127-136.

XX. Netter FH (1997) “Atlas of Human Anatomy” East Hanover, New Jersey: Novartis. [13] Elaine Marieb asnd Katja Hoehnss (2007) “Human Anatomy and Physiology” 7th Edition, Pearson Education .

XXI.P.R.S. Sanches, A.F. Müller, L. Carro, A.A. Susin, P. Nohama (2007) “Analog Reconfigurable Technologies for EMG Signal Processing” Journal of Biomedical Engineering, Vol. 23, pp. 153-157 [20] M. E. Van Valkenburg (1982) “Analog Filter Design”, Holt, Rinehart & Winston

XXII.Paul E. Barkhaus and Sanjeev D. Nandedkar (2000) “Electronic Atlas of Electromyography Waveforms” Vol. 2, 2nd Edition.

XXIII.P.R.S. Sanches, A.F. Müller, L. Carro, A.A. Susin, P. Nohama (2007) “Analog Reconfigurable Technologies for EMG Signal Processing” Journal of Biomedical Engineering, Vol. 23, pp. 153-157.

XXIV. S.L. Pullman, D.S. Goodin, A.I. Marquinez, S. Tabbal and M. Rubin (2000) “Clinical Utility of Surface EMG” Report of the Therapeutics and Technology Assessment, Subcommittee of the American Academy of Neurology, Neurology Vol. 55:171–177.

XXV.Sebastian Maier and Patrick van der Smagt (2008) “Surface EMG suffices to classify motion of each finger independently” Proceedings of MOVIC 2008, 9th International Conference on Motion and Vibration Control.

XXVI.Zahak Jamal, Asim Waris, Shaheryar Nazir, Shahryar Khan, Javaid Iqbal, Adnan Masood and Umar Shahbaz (2011) “Motor Drive using Electromyography for Flexion and Extension of Finger and Hand Muscles” 4th International Conference on Biomedical Engineering and Informatics, Vol. 3 pp. 1287-1291.

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Abstract:

Introducing modern transmission technology, it is possible to transmit some human sensual theme (sound, video, and picture) with support of signal processing aspects. It is quite difficult to transmit aroma introducing signal processing effort. We attempt to contribute a short prototype, which create a virtual effect of essence in receiving section. This paper mainly focuses with a case study manner towards the prototype development in techno commercial features. The specific patent review in this field is added it’s important. In addition, art work representation to working model based approaches is presented chronologically with appropriate technical information. Developed prototype and image processing technology behind this project is presented. The involvement of several interdisciplinary facts is carried towards the development of this prototype. Overall, this paper presents a case study towards the performance of one challenging product based preliminary prototype generation.

Keywords:

Essence effect,Internet technology,Odour,Image,Prototype,

Refference:

I. Anandan, P. (1985). Computing dense displacement fields with confidence measures in scenes containing occlusion.
II. Anandan, P. (1989). A computational framework and an algorithm for the measurement of visual motion. International Journal of Computer Vision, 2(3), 283-310.
III. Bodnar, A., Corbett, R., & Nekrasovski, D. (2004). AROMA: ambient awareness through olfaction in a messaging application. In Proceedings of the 6th international conference on Multimodal interfaces (pp. 183-190).
IV. Brown, M., & Lowe, D. G. (2002). Invariant Features from Interest Point Groups. In BMVC (No. s 1).
V. Brown, M., & Lowe, D. G. (2005). Unsupervised 3D object recognition and reconstruction in unordered datasets. In 3-D Digital Imaging and Modeling, 2005. 3DIM 2005. Fifth International Conference on (pp. 56-63).
VI. Brown, M., Szeliski, R., & Winder, S. (2005). Multi-image matching using multi-scale oriented patches. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on (Vol. 1, pp. 510-517).
VII. Brown, M., & Lowe, D. G. (2007). Automatic panoramic image stitching using invariant features. International journal of computer vision, 74(1), 59-73.
VIII. Das, Z., Manna, N., & Neogi, B. (2013). Model Representation and Study of Essence Effect Creation through Internet Technological Aspect. Innovative Systems Design and Engineering, 4(13), 25-33.

IX. E One Co. Ltd., “Perfume Emitting Device and Method”, KR20000023928, 2000.
X. Fawcett, T. (2006). An introduction to ROC analysis. Pattern recognition letters,27(8), 861-874.
XI. Gionis, A., Indyk, P., & Motwani, R. (1999). Similarity search in high dimensions via hashing. In VLDB (Vol. 99, pp. 518-529).
XII. Horn, B. K., & Schunck, B. G. (1981). Determining optical flow. International Society for Optics and Photonics.Technical symposium east (pp. 319-331).
XIII. Hua, G., Brown, M., & Winder, S. (2007). Discriminant embedding for local image descriptors. In Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on (pp. 1-8).
XIV. Jen, Y. H., Taha, Z., & Vui, L. J. (2008). VR-Based robot programming and simulation system for an industrial robot. International Journal of Industrial Engineering: Theory, Applications and Practice, 15(3), 314-322.
XV. Kulis, B., & Grauman, K. (2009). Kernelized locality-sensitive hashing for scalable image search. In Computer Vision, 2009 IEEE 12th International Conference on (pp. 2130-2137).
XVI. Lee C. (2001), “Aroma Distributor complementing internet operation is triggered by commandfrom audio decoder monitoring incoming data”, FR27971.
XVII. Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International journal of computer vision, 60(2), 91-110.
XVIII. Lucas, B. D., & Kanade, T. (1981). An iterative image registration technique with an application to stereo vision. In IJCAI (Vol. 81, pp. 674-679).
XIX. Mikolajczyk, K., & Schmid, C. (2004). Scale & affine invariant interest point detectors. International journal of computer vision, 60(1), 63-86.
XX. Okada, K., & Aiba, S. (2003). Toward the actualization of broadcasting service with smell information. Institute of Image information and Television Engineering of Japan Technical Report (in Japanese), 27(64), 31-34.
XXI. Raginsky, M., & Lazebnik, S. (2009). Locality-sensitive binary codes from shift-invariant kernels. In Advances in neural information processing systems (pp. 1509-1517).
XXII. Schmid, C., Mohr, R., & Bauckhage, C. (2000). Evaluation of interest point detectors. International Journal of computer vision, 37(2), 151-172.
XXIII. Shakhnarovich, G., Indyk, P., & Darrell, T. (2006). Nearest-neighbor methods in learning and vision: theory and practice.

XXIV. Shekar, A. (2012). Research-based enquiry in Product Development education: Lessons from supervising undergraduate final year projects. International Journal of Industrial Engineering: Theory, Applications and Practice. 19(1).
XXV. Shi, J., & Tomasi, C. (1994). Good features to track. In Computer Vision and Pattern Recognition, 1994. Proceedings CVPR’94., 1994 IEEE Computer Society Conference on (pp. 593-600).
XXVI. Snavely, N., Seitz, S. M., & Szeliski, R. (2006). Photo tourism: exploring photo collections in 3D. In ACM transactions on graphics (TOG) (Vol. 25, No. 3, pp. 835-846).
XXVII. Szeliski, R. (2010). Computer vision: algorithms and applications. Springer Science & Business Media.
XXVIII. Triggs, B. (2004). Detecting keypoints with stable position, orientation, and scale under illumination changes. Springer Berlin Heidelberg. In Computer Vision-ECCV 2004 (pp. 100-113).
XXIX. Torralba, A., Weiss, Y., & Fergus, R. (2008). Small codes and large databases of images for object recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
XXX. Yokoyama, S., Tanikawa, T., Hirota, K., & Hirose, M. (2004). Olfactory field simulation using wearable olfactory display. Trans. of Virtual Reality Society of Japan (in Japanese), 9(3), 265-274.

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Abstract:

An automated hybrid model, called the Plant Neural System Model (PNSM), is introduced in this approach. Plants can process biochemical signals throughcertain biological processes even they don’t have brains. Important biological processes, like seed germination, root growth, and nutrient absorption by the cell are considered as these are the foundations of neuron systems in plants. Neurobiological processes have been adapted to develop a hybrid black box model with time-dependent functions like Artificial Neural Network (ANN) and the use of some advanced optimization techniques. This model would be useful in the analysis of soil parametric relations with both seed germination and seed optimization in order to classify plant seeds.

Keywords:

Neurobiological,Plant Neural System, Artificial Neural Network,Hybrid model,

Refference:

I.Brady, S. M., & Provart, N. J. (2009). Web-queryable large-scale data sets for hypothesis generation in plant biology. The Plant Cell, 21(4), 1034-1051.

II.Bray, J. R. (1963). Root production and the estimation of net productivity. Canadian Journal of Botany, 41(1), 65-72.

III.Bar-Yosef, B., Lambert, J. R., & Baker, D. N. (1982). Rhizos: A simulation of root growth and soil processes. Sensitivity analysis and validation for cotton. Transactions of the ASAE, 25(5), 1268-1273.

IV.Coruzzi, G. M., Burga, A. R., Katari, M. S., & Gutiérrez, R. A. (2009). Systems biology: principles and applications in plant research. Plant Systems Biology, Annual Plant Reviews. London, UK: Wiley-Blackwell, 3-40.

V.Chen, D. X., & Lieth, J. H. (1992). Two-dimensional model of water transport in the root zone and plant for container-grown chrysanthemum. Agricultural and forest meteorology, 59(3-4), 129-148.

VI.Coile, T. S. (1952). Soil and the growth of forests. In Advances in Agronomy (Vol. 4, pp. 329-398). Academic Press.

VII.Demir, I., Mavi, K., Kenanoglu, B. B., & Matthews, S. (2008). Prediction ofgermination and vigour in naturally aged commercially available seed lots of cabbage (Brassica oleracea var. capitata) using the bulk conductivity method. Seed Science and Technology, 36(3), 509-523.

VIII.Gago, J. (2009). Biotecnología de Vitis vinifera L.: Modelización mediante Inteligencia Artificial (Doctoral dissertation, Doctoral Thesis, Universidade de Vigo, Vigo, Spain).

IX.Gago, J., Martínez-Núñez, L., Landín, M., & Gallego, P. P. (2010). Artificial neural networks as an alternative to the traditional statistical methodology in plant research. Journal of plant physiology, 167(1), 23-27.

X.Hammer, G. L., Sinclair, T. R., Chapman, S. C., & Van Oosterom, E. (2004). On systems thinking, systems biology, and the in silico plant. Plant Physiology, 134(3), 909-911.

XI.Johnson, I. R., & Thornley, J. H. M. (1985). Temperature dependence of plant and crop process. Annals of Botany, 55(1), 1-24.

XII.Kitano, H. (2002). Systems biology: a brief overview. Science, 295(5560), 1662-1664.

XIII.Meyer, F. H., & Gottsche, D. (1971). Distribution of root tips and tender roots of beech. Ellenberg, Heinz Integrated Experimental Ecology.

XIV.Prasad, V. S. S., & Gupta, S. D. (2008). Applications and potentials of artificial neural networks in plant tissue culture. In Plan Tissue Culture Engineering (pp. 47-67). Springer Netherlands.

XV.Struik, P. C., Yin, X., & de Visser, P. (2005). Complex quality traits: now time to model. Trends in Plant Science, 10(11), 513-516.

XVI.Samimy, C., Taylor, A. G., & Kenny, T. J. (1987). Relationship of germination and vigor tests to field emergence of snap beans (Phaseolus vulgaris L.). Journal of Seed Technology, 23-34.

XVII.Sehirali, S. (1991). Seed and seed technology. Turkish, Istanbul, 422

XVIII.Tardieu, F. (2003). Virtual plants: modelling as a tool for the genomics of tolerance to water deficit. Trends in plant Science, 8(1), 9-14.

XIX.Uzun, S., Marangoz, D., & Özkaraman, F. (2001). Modelling the time elapsing from seed sowing to emergence in some vegetable crops. Pakistan Journal of Biological Sciences, 4(4), 442-445.

XX.White, E. H., Pritchett, W. L., & Robertson, W. K. (1971). Slash pine root biomass and nutrient concentrations. Maine Agr Exp Sta Misc Rep.

XXI.Weidenhamer, J. D., Morton, T. C., & Romeo, J. T. (1987). Solution volume and seed number: Often overlooked factors in allelopathic bioassays. Journal of Chemical Ecology, 13(6), 1481-1491.

XXII.Westgate, M. E., & Boyer, J. S. (1985). Osmotic adjustment and the inhibition of leaf, root, stem and silk growth at low water potentials in maize. Planta, 164(4), 540-549.

XXIII.Yuan, J. S., Galbraith, D. W., Dai, S. Y., Griffin, P., & Stewart Jr, C. N. (2008). Plant systems biology comes of age. Trends in plant science, 13(4), 165-171.

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Abstract:

In the present investigation, steady two dimensional laminar natural convection flow resulting from non-linear stretching of a flat horizontal plate ina nanofluid is studied numerically. Boungiorno model [I] is employed that treats the nanofluid as a two-component mixture (base fluid plus nanoparticles), incorporating the effects of Brownian motion and thermophoresis.By appropriate similarity variables, the governing nonlinear partial differential equations of flow are transformed to a set of nonlinear ordinary differential equations. Subsequently they are reduced to a first order system and integrated using Newton Raphson and adaptive Runge-Kutta methods. The computer codes are developed for this numerical analysis in Matlab environment. Dimensionless stream function (s), longitudinal velocity (s′), temperature (θ) and nanoparticle volume fraction (f) are computed and illustrated graphically for various values of four dimensionless parameters, namely, Lewis number (Le), stretching parameter (n), Brownian motion Parameter (Nb), and thermophoresis parameter (Nt). The effects of the physical parameters on the rate of heat transfer(-θ́(0)) and mass transfer (-φ́(0)) is given in tabulated form.The results of the present simulation are in with good agreement with the previous reports available in literature.

Keywords:

Brownian motion,Boundary layer,Nanofluid,Non-linear Stretching,Thermophoresis,

Refference:

I. BuongiornoJ.,Convective transport in nanofluids, ASME J. Heat Transf. 128 (2006) 240–250.

II. ChoiS., Enhancing thermal conductivity of fluids with nanoparticle in: D.A. Siginer, H.P. Wang (Eds.), Developments and Applications of Non-Newtonian Flows, ASME MD vol. 231 and FED vol. 66, 1995, pp. 99–105.

III. Crane L J., Flow pas a stretching plate. Z. angew. Math. Phy., 21 (1970) 645-647

IV. Khan W. A. and Aziz A., Natural co

nvection flow of a nanofluid over a vertical plate with uniform surface heat flux,International Journal of Thermal Sciences, 50 (2011) 1207-1214.

V. Kuznetsov A.V. and Nield D.A., Natural convective boundary-layer flow of a nanofluid past a vertical plate, Int. J. Thermal Sciences, 49, (2010) 243–247.

VI. Nield D.A.andKuznetsov A.V., Thermal instability in a porous medium layer saturated by a nanofluid, Int.J.Heat Mass Transf, 52 (2009) 5796–5801.

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Abstract:

Patch miniaturization is an ongoing trend in modern communication technology nowadays. In this paper functional behavior of E slotted patch is presented. With additional ground irregularities multi resonating frequency response is attained at range of 1-8GHZ resulting at most gain of 3.43dB -4.71dB, directivity in 3.68dBi-5.66dBi range with good impedance bandwidth. With use of fractal patch technique FR4 is chosen as substrate bases. With help of implementing shortening pin technique reduction of antenna is accomplished to 60.60%. By changing location of shortening pin only different desired bands resonation can be achieved. This type of microstrip antenna has applications in mobile phone for, S-Band and C-Band applications

Keywords:

Miniaturization,Fractal patch, Gain, Directivity,Microstrip patch,Slot cutting,

Refference:

I.Cohen, Nathan. “Fractal antenna applications in wireless telecommunications.” Electronics Industries Forum of New England, 1997. Professional Program Proceedings. IEEE, 1997.

II.Dong, Yuandan, Hiroshi Toyao, and Tatsuo Itoh. “Design and characterization of miniaturized patch antennas loaded with complementary split-ring resonators.” IEEE Transactions on Antennas and Propagation 60.2 (2012): 772-785.

III.Ermutlu, M. E., et al. “Miniaturization of patch antennas with new artificial magnetic layers.” IWAT 2005. IEEE International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials, 2005.. IEEE, 2005.

IV.Hu, Jun, Chun-sheng Yan, and Qing-chun Lin. “A new patch antenna with metamaterial cover.” Journal of Zhejiang UniversitySCIENCE A7.1(2006): 89-94.

V.Li, Le-Wei, Ya-Nan Li, Tat Soon Yeo, Juan R. Mosig, and Olivier JF Martin. “A broadband and high-gain metamaterial microstrip antenna.” Applied Physics Letters96, no. 16 (2010): 164101.

VI.Mehr-e-Munir; Umar Farooq “Multiband microstrip patch antenna using DGS for L-Band, S-Band, C-Band & mobile applications”, in 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET),Ukraine,2016

VII.Mehr-e-Munir; Khalid Mahmood,” Miniaturized microstrip patch antenna using stack configuration for S-band, C-band & mobile applications”, in International Conference on Emerging Technologies (ICET),Peshawar,2015

VIII.M.Munir, S. S. Qurashie, S. H. Kiani, K. Mahmood, J. Khan, “Performance Analysis between Single and Dual Substrate Patches for Wireless Communication and Applications”, Sindh University Research Journal,vol.49, no.1, 2017.

IX.Saad Hassan Kiani, Khalid Mahmood, Sharyar Shafeeq, Mehre Munir and Khalil Muhammad Khan, “A Novel Design of Miniaturaized Patch Antenna Using Different Substrates for S-Band and C-Band Applications” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016.

X.S. Hassan, K. Mahmood, M. Munir and A. James, “A Novel Design of Patch Antenna using U-Slot and Defected Ground Structure”,International Journal of Advanced Computer Science and Applications, vol. 8, no. 3, 2017.

XI.W. Sang-Hyuk, et al., “Wideband Microstrip Patch Antenna With U-Shaped ParasiticElements,” Antennas and Propagation, IEEE Transactions on, vol. 55, pp. 1196-1199, 2007

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Abstract:

We have commenced an in-depth study through modeling and simulation to investigate the performance of a CdTe solar cell at different Schottky barrier heights for different combinations thicknesses of BSF as well as window layer and front contact oxide layer (TCO) .The inter relation between BSF layer and back contact schottky barrier height has been focused. Effect of the BSF layer regarding the tunneling of charges has been investigated. In the present paper, we achieved in our study the highest ƞ of 18.39%, Voc of 0.591 volt, Isc of 0.411 amp for 0.1 µm absorber and 1nm BSF layer thickness in presence of higher schottky barrier (0.6eV) with higher doping concentration of absorber layer. Thinning of the layers have always been better in terms of performance and cost. But it brings pinhole formation problems what we excluded here in our present work. Keywords : Thin film solar, CdS/CdTe, TCO, Window layer, Schottky Barrier, Back Surface Field (BSF).

Keywords:

Thin film solar,CdS/CdTe,TCO,Window layer,Schottky Barrier,Back Surface Field (BSF),

Refference:

I Amin N, Matin MA, Aliyu MM, Alghoul MA, Karim M, and Sopian K (2010) Prospects of Back Surface Field Effect in Ultra-Thin High-Efficiency CdS/CdTe Solar Cells from Numerical Modeling, Hindawi Publishing Corporation, International Journal of Photoenergy, Article ID 578580, 8 pages, doi:10.1155/2010/578580

II Batzner DL, Romeo A, Zogg H, Tiwari AN, Wendt R (2000) Development of Efficient and Stable Back Contacts on Cdte/Cds Solar Cells, Research gate, DOI: 10.1016/S0040-6090(01)00792-1

III Burgelman M, Nollet P, Degrave S (1999) Electronic behaviour of thin-film CdTe solar cells, Applied Physics A-Materials Science& Processing, A 69, 149–153 / Digital Object Identifier (DOI) 10.1007/s003399900063

IV ChanderSubhash, Dhaka M.S. (2017) Time evolution to CdCl2 treatment on Cd-based solar cell devices fabricated by vapor evaporation, Solar Energy, Volume 150, Pages 577-583, https://doi.org/10.1016/j.solener.2017.05.013

V ChanderSubhash, Dhaka M.S. (2015) Physical properties of vacuum evaporated CdTe thin films with post-deposition, Physica E: Low-dimensional Systems and Nanostructures, Volume 73, Pages 35-39, http://dx.doi.org/10.1016/j.physe.2015.05.008

VI ChanderSubhash, Dhaka M.S. (2015) Optimization of physical properties of vacuum evaporated CdTe thin films with the application of the thermal treatment for solar cells,MaterialsScienceinSemiconductorProcessing40 (2015)708–712,http://dx.doi.org/10.1016/j.mssp.2015.07.063

VII Demtsu SH, Sites JR(2006) Effect of back-contact barrier on thin-film CdTe solar cells,Science direct- Thin Solid Films 510: 320–324

VIII Fang Z, Wang XC, Wu HC, and Zhao CZ (2011) Achievements and Challenges of CdS/CdTe Solar Cells, Hindawi Publishing Corporation-International Journal of Photoenergy, Volume 2011, Article ID 297350, 8 pages, doi:10.1155/2011/297350.

IX Fardi H and Buny F(2013) Characterization and Modeling of CdS/CdTe Heterojunction Thin-Film Solar Cell for High Efficiency Performance, Hindawi Publishing Corporation, International Journal of Photoenergy, Volume 2013, Article ID 576952, 6 pages, http://dx.doi.org/10.1155/2013/576952

X Gessert TA, Dhere RG, Duenow JN, Kuciauskas D, Kanevce A, and Bergeson JD (2011) Comparison Of Minority Carrier Lifetime Measurements In Superstrate and Substrate CdTe PV Devices, 37th IEEE Photovoltaic Specialists Conference (PVSC 37), NREL/CP-5200-50747

XI Hadrich M, Heisler C, Reislohner C, Kraft C, Metzner H (2011) Back contact formation in thin cadmium telluride solar cells ,Thin Solid Films 519: 7156–7159

XII Hossain MS, Amin N, Razykov T (2011) Prospects of Back Contacts with Back Surface Fields in High Efficiency Znxcd1-Xs /Cdte Solar Cells from Numerical Modeling, Chalcogenide Letters, Vol. 8, No. 3, p. 187 – 198 .

XIII Huldt L (1968) Direct Electron-Hole Recombination in Cadmium Sulfide, Helvetica PhysicaActa, Vol. 41, PP. 942-945, http://doi.org/10.5169/seals-113951.

XIV Jones EW, Barrioz V, Irvine SJC, Lamb D (2009) Towards ultra-thin CdTe solar cells using MOCVD, Science Direct- Thin Solid Films 517: 2226–2230, doi:10.1016/j.tsf.2008.10.093

XV Islam MA, Sulaiman Y, Amin N (2011) A Comparative Study of BSF Layers For Ultra-Thin Cds:O/Cdte Solar Cells, Chalcogenide Letters, Vol. 8, No. 2, p. 65 – 75.

XVI Kim K, Kim IH,Yoon KY, Lee J and Jang JH (2015) a-Fe2O3 on patterned fluorine doped tin oxide for efficient photoelectrochemical water splitting, Journal of Materials Chemistry A, 3,7706, DOI: 10.1039/c5ta00027k

XVII Matin MA, Aliyu MM, Quadery AH, Amin N (2010) Prospects of novel front and back contacts for high efficiency cadmium telluride thin film solar cells from numerical analysis, Solar Energy Materials & Solar Cells 94: 1496–1500

XVIII MuhibbullahM, Choudhury M GolamMowla, Mominuzzaman Sharif M (2012), An equation of the width of the depletion layer for a step heterojunction, Trans. Mat. Res. Soc. Japan 37[3] 405-408.

XIX Niasse, O.A., Tankari, M.A., Dia, F., Mbengue, N., Diao, A., Niane, M., Diagne, M., Ba, B. And Levebvre, G. (2016) Optimization of Electrics Parameters CdS/CdTe Thin Film Solar Cell Using Dielectric Model. World Journal of Condensed Matter Physics, 6, 75-86, http://dx.doi.org/10.4236/wjcmp.2016.62011

XX Niemegeers A and Burgelman M (1997) Effects of the Au/CdTe back contact on IV and CV characteristics of Au/CdTe/CdS/TCO solar cells, Journal of Applied Physics 81, 2881; doi: 10.1063/1.363946.

XXI Niemegeers A and Burgelman M (1996) Numerical Modelling Of Ac-Characteristics Of CdTe And CIS Solar Cells, 25nd IEEE Photovoltaic Specialists Conference, Washington, pp. 901-904

XXII Noor N, Parkin I P (2013) Halide doping effects on transparent conducting oxides formed by aerosol assisted chemical vapour deposition, Thin Solid Films 532, 26–30, http://dx.doi.org/10.1016/j.tsf.2012.10.110

XXIII Streetman Ben G., (1982) Solid State Electronic Device, Prentice-hall, Eastern Economy Edition, 2nd Edition, Chapter 5,Junctions,pp. 140-145,

XXIV Tiwari AN, Khrypunov G, Kurdzesau F, Batzner DL, Romeo A , Zogg H (2004). CdTe Solar Cell in a Novel Configuration, Progress in Photovoltaics: Research and Applications 12:33–38 (DOI: 10.1002/pip.525)

XXV Zhang B, Tian Y, Zhang J, CaiW(2010) The FTIR studies on the structural and electrical properties of SnO2:F films as a function of hydrofluoric acid concentration, Optoelectronics And Advanced Materials – Rapid Communications Vol. 4, No. 8, p. 1158 – 1162.

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