@Research Paper
<#LINE#>Scalable Compression Method for Hyperspectral Images<#LINE#>Ganeshraj@P.,A.@Sivasankar<#LINE#>1-5<#LINE#>1.ISCA-RJEngS-2013-012.pdf<#LINE#> Department of Information & Communication, Engineering, Anna University Chennai Regional, Center Madurai Madurai, INDIA <#LINE#>18/2/2013<#LINE#>12/3/2013<#LINE#> In this paper, we propose a low complexity compression method to hyperspectral images using distributed source coding (DSC). DCT was applied to the hyperspectral images. Set-partitioning-based approach was utilized to reorganize DCT coefficients into wavelet like tree structure. Cellular automata (CA) for bits and bytes error correcting codes (ECC) to high through put rate. The CA-based scheme can easily be extended for correcting more than two byte errors. Its performance is comparable to that of the DSC scheme based on informed quantization at low bit rate.<#LINE#> @ @ Abrardo M. Barni, Magli E. and Nencini F., Error resilient and low-complexity onboard lossless compression of hyperspectral images by means of distributed source coding, IEEE Trans. Geosci. Remote Sens., 48(4), 1892–1904 (2010) @No $ @ @ Pan W., Zou Y. and Lu A., A compression algorithm of hyperspectral remote sensing image based on 3-D wavelet transform and fractal, in Proc. 3rd Int. Conf. Intell. Syst. Knowl. Eng., Xiamen, China, 1237–1241 (2008) @No $ @ @ Zhang J., Li H. and Chen C.W., Progressive distributed coding of multispectral images, in Proc. 5th ICST Mobile Multimedia Commun. Conf., London, U.K., (2009) @No $ @ @ Zhang J., Li H. and Chen C.W., Distributed coding techniques for onboard lossless compression of multispectral images, in Proc. ICME, New York, 141–144 (2009) @No $ @ @ Jaydeb Bhaumik and Dipanwita Roy Chowdhury,New Architectural Design of CA-Based Codec, IEEE transactions on very large scale integration (VLSI) systems, 18(7)( 2010) @No $ @ @ Cheung N.M., Tang C. and Ortega A., Efficient wavelet-based predictive Slepian–Wolf coding for hyperspectral imagery, Signal Process., 86(11), 3180–3195 (2006) @No $ @ @ Abrardo, Barni M. and Magli E., Low-complexity lossy compression of hyperspectral images via informed quantization, in Proc. IEEE ICIP, Siena, Italy, 505–508 (2010) @No $ @ @ Penna T. Tillo and Magli E., Transform coding techniques for lossy hyperspectral data compression, IEEE Trans. Geosci. Remote Sens., 45(5), 1408–1421 (2007) @No $ @ @ Tang Cheung N.M. and Ortega A., Efficient inter-band prediction and wavelet-based compression for hyperspectral imagery: A distributed source coding approach, in Proc. IEEE Data Compression Conf., Los Angeles, CA, 37–446, (2005) @No $ @ @ Liu W. and Zeng W., Scalable non-binary distributed source coding using Gray codes, in Proc. IEEE Int. Workshop Multimedia Signal Process., Columbia, MO, 1–4 (2005) @No $ @ @ Chen J. and Wu C., An efficient embedded subband coding algorithm for DCT image compression, in Proc. SPIE— Image Compression and Encryption Technologies, 4551, 44–48 (2001) @No $ @ @ Varodayan D., Aaron A. and Girod B., Rate-adaptive distributed source coding using low-density parity-check codes, in Proc. 39th Asilomar Conf. Signals, Syst. Compute., Pacific Grove, CA, 1203–1207 (2005) @No $ @ @ Gupta Rajani, Mehta Alok K. and Tiwari VebhavVocoder (LPC) Analysis by Variation of Input Parameters andSignals, ISCA Journal of Engineering Science,s1(1),57-61 (2012) @No $ @ @ Pooja Malik Puri, Himanshu Khajuria, Biswa Prakash Nayak and Ashish Badiye, “Stereolithography: Potential Applications in Forensic Science”, Research Journal of Engineering Sciences 1(5), 47-50 (2012) @No $ @ @ Adedjouma Sèmiyou A., John O.R. Aoga and Mamoud A. Igue, Part-of-Speech tagging of Yoruba Standard, Language of Niger-Congo family, Res. Journal of Computer & IT Sciences ,1(1), 2-5 (2013) @No $ @ @ Rangamma M., Mallikarjun Reddy G. and Srikanth Rao P.,Occasionally Weakly Compatible Maps in Fuzzy Metric Spaces, Res. J. Mathematical & Statistical Sciences,1(1),7-13 (2013) @No
<#LINE#>Contactless Hand Based Multimodal Biometrics Identification System<#LINE#>Ruth@KarunyaS,S.@Veluchamy<#LINE#>6-10<#LINE#>2.ISCA-RJEngS-2013-013.pdf<#LINE#> Department of Information and Communication Engineering, Anna University Chennai, Regional Center Madurai Madurai, INDIA <#LINE#>18/2/2013<#LINE#>12/3/2013<#LINE#>Biometrics is an emerging technology that is used to identify people by their physical and/or behavioural characteristics and, so, it inherently requires that the person to be identified is physically present at the point of identification. A new approach for multimodal based personal identification using hand images is presented. This paper attempts to improve the performance of hand based verification system by integrating palm print, hand geometry and knuckle print features from user’s hand. Unlike other multimodal biometric systems, the users do not have to undergo the inconvenience of using two different sensors since the palm print, hand geometry and Knuckle Print features can be acquired from the same image, at the same time. Individual matching scores are then combined using a new dynamic fusion approach. The experimental results showed the effectiveness of the system in terms of equal error rate. <#LINE#> @ @ Adams Kong and David Zhang and Mohamed Kamel, A survey of palmprint recognition Pattern Recognition, 42,1408-1418, (2009) @No $ @ @ Kong and Zhang D. and Lu G. , A study of identical twins palm print for personal verification Pattern Recognition, 39, 2149-2156, (2006) @No $ @ @ Han C.C. and Cheng H.L. and Lin C.L. and Fan K.C., Personal authentication using palm-print features Pattern Recognition, 36, 371—381, (2003) @No $ @ @ Kung S.Y. and Shang-Hung Lin and Ming Fang., A neural network approach to face/palm recognition. Neural Networks for Signal Processing V. Proceedings of the IEEE Workshop, 323 -332 (1995) @No $ @ @ Wu X. and Wang K. and Zhang D., Fuzzy direction element energy feature (FDEEF) based palmprint identification Proc. Int. Conf. Pattern Recognition, 95—98 (2002) @No $ @ @ Connie T. and Jin A.T.B. and Ong M.G.K. and Ling D.N.C., An automated palmprint recognition system Image and Vision Computing, 23, 501—515 (2005) @No $ @ @ Manisha P. Dale and Madhuri A. Joshi and Neena Gilda, Texture Based Palmprint Identification Using DCT Features, Proc. Int. Conf. Advances in Pattern Recognition, pages 221—224 (2009) @No $ @ @ Aglika Gyaourova and Arun Ross, Index Codes for Multi biometric Pattern Retrieval IEEE Transactions on Information Forensics And Security, 7(2), (2012) @No $ @ @ Ajay Kumar and David Zhang,“Personal Recognition Using Hand Shape and Texture” IEEE Transactions on Image Processing, 15(8),(2006) @No $ @ @ Ajay Kumar and Sumit Shekhar, Personal Identification Using Multi biometrics Rank level fuson IEEE Transactions On Man And Cybernetics—Part C: Applications And Reviews, 41(5), (2011) @No $ @ @ Ajay Kumar and Yingbo Zhou, Human Identification Using Finger Images IEEE Transactions On Image Processing,21(4),(2012) @No $ @ @ Anil K. Jain, Arun Ross, and Salil Prabhakar, An Introduction to Biometric recognition IEEE Transactions On Circuits and Systems For Video Technology, 14(1),(2004) @No $ @ @ Erdem Yörük, Ender Konukolglu, Bülent Sankur and Jérôme Darbon,“Shape–based Hand recognition IEEE Transactions On Image Processing, 15(7),(2006) @No $ @ @ Gang Zheng, Chia-Jiu Wang, and Terrance Boult.E, Application of projective invariants in hand geometry Biometrics IEEE Transactions On Information Forensics And Security, 2(4), (2007) @No $ @ @ Jifeng Dai and Jie Zhou, Multi feature-Based High-Resolution Palm print Recognition IEEE Transactions On Pattern Analysis And Machine Intelligence 33(5), (2011) @No $ @ @ Xiangqian Wu and Zhang, D. and Kuanquan Wang, Palm line extraction and matching for personal authentication IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 36(5), 978 -987 (2006) @No $ @ @ Nobuyuki Otsu, A Threshold selection method based on gray level his Histogram IEEE Transactions On Systems, Man, And Cybernetics, Smc-9(1),(1979) @No $ @ @ Richard M. Jiang, Abdul H. Sadka, and Danny Crookes, Multimodal Biometric Human Recognition for Perceptual Human–Computer Interaction IEEE Transactions On Systems, Man And Cybernetics—Part C: Applications And Reviews, 40(6), (2010) @No $ @ @ Slobodan Ribaric and Ivan Fratric, A Biometric Identification based on eigen palm and eigen finger features IEEE Machine Transactions On Pattern Analysis Intelligence, 27(11), (2005) @No $ @ @ Yingbo Zhou and Ajay Kumar, Human Identification Using Palm- Vein Images IEEE Transactions On Information Forensics And Security, 6(4),(2011) @No $ @ @ Vivek Kanhangad, Ajay Kumar and David Zhang, Contactless and Pose Invariant Biometric Identification Using Hand Surface, IEEE Transactions on Image Processing, 20(5),(2011) @No $ @ @ Paigwar Shikha and Shukla Shailja, Neural Network based Offline Signature Recognition and verification system, Research Journal of Engineering Sciences, 2(2), 11-15 (2013) @No $ @ @ Singh Amarendra and Verma Nupur, Ear Recognition for automated Human Identification, Research Journal of Engineering Sciences,1(5), 44-46, (2012) @No $ @ @ Yadav Sunil Kumar and Rizvi Syed Azhar Abbas, Cybernetics Security Requirements and Reuse for Improving Information Systems Security, Research Journal of Engineering Sciences, 1(5), 51-54, (2012) @No
<#LINE#>A New Approach of Image Registration for Biomedical Images Using Saliency Information<#LINE#>Anitha@S.,S.@Veluchamy<#LINE#>11-15<#LINE#>3.ISCA-RJEngS-2013-014.pdf<#LINE#> Department of Information and Communication Engineering, Anna University Chennai Regional Center Madurai Madurai, INDIA<#LINE#>18/2/2013<#LINE#>12/3/2013<#LINE#>In this paper we propose a Markov Random Field based Automatic Registration method. This is an elastic registration method that uses the combination of saliency and gradient information. This Intensity-based registration of images is done by linear transformations, based on a discrete Markov random field (MRF) formulation. Here, the challenge arises from the fact that optimizing the energy associated with this problem requires a high-order MRF model. Currently, methods for optimizing such high-order models are less general, easier to use, and efficient, than methods for the popular second-order models. Automatic registration of dynamic contrast enhanced magnetic resonance (DCE-MR) images is a challenging task due to the rapid changes of the images which are characterized by intensity changes over time, thus posing challenges for conventional intensity-based registration methods. Saliency information contributes to a contrast invariant metric to identify similar regions inspiteof contrast enhancement. Saliency is used in optimization framework to identify relevant pixels for registration, thus reducing the computation time. Experimental results on real patient images demonstrate superior registration accuracy with a combination of saliency and gradient information over other similarity metrics. <#LINE#> @ @ Glocker B., Komodakis N., Navab N., Tziritas G. and Paragios N., Dense image registration through MRFs and efficient linear programming, Med. Image Anal., 12(6),731–741 (2008) @No $ @ @ Boykov Y. and Veksler, Fast approximate energy minimization via graph cuts, IEEE Trans. Pattern Anal. Mach. Intell., 23(11), 1222–1239 (2001) @No $ @ @ Holden M., A review of geometric transformations for nonrigid body registration, IEEE Trans. Med. Imag., 27(1), 111–128 (2008) @No $ @ @ Itti L., Koch C. and Niebur. E, Model of saliency-based visual attention for rapid scene analysis, IEEE Trans. Pattern Anal .Mach. Intell.,20(11), 1254–1259 (1998) @No $ @ @ Itti L. and Koch C., A saliency-based search mechanism for overt and covert shifts of visual attention, Vis. Res., 40,1489–1506 (2000) @No $ @ @ Kadir T. and Brady M., Saliency, scale and image description, Int. J. Comput. Vis., 45, 83–105 (2001) @No $ @ @ Rohde G., Aldroubi A. and Dawant B., The adaptive bases algorithm for intensity based nonrigid image registration, IEEE Trans. Med. Imag., 22(11), 1470–1479 (2003) @No $ @ @ Rueckert D., Sonoda I., Hayes C., Hill D.L.G., Leach M.O. and Hawkes D.J., Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imag., 18(8), 712–721 (1999) @No $ @ @ Shekhovtsov A., Kovtun I. and Hlav´ac V., Efficient MRF deformation model for non-rigid image matching, Comput.Vision Image Understand.,112(1), 91–99 (2008) @No $ @ @ SunY., Jolly M.P. and Moura J., Contrast-invariant registration of cardiac and renal MR perfusion images, in Proc. Med. Image Comput. Comput.-Assisted Intervention (MICCAI), 903–910 (2004) @No $ @ @ J.P., Image matching as a diffusion process: an analogy with Maxwell’s demons, Med. Image Anal.,2, 243–260 (1998) @No $ @ @ Woods R.P., Mazziotta J.C. and Cherry S.R., Mri-pet registration with automated algorithm, J. Comput. Assist. Tomogr., 17(4), 536–546 (1993) @No $ @ @ Dinkar A., Bhattacharyya S., Kumar D., Kumar A., Gupta P., Banerjee G.1 and Singh M., Pneumonia caused by Candida Kefyr ion pediatric patient with acute Lymphoblastic Leukaemia: Case Report”, Inernational Research journal of Engineering sciences, 1(1), 18-19 (2013) @No $ @ @ Uma R. and Pravin B, Invitro Cytotoxic Activity of Marsilea Quadrifolia Linn of MCF-7 Cells of Human Breast Cancer International Research Journal of Medical Sciences, 1(1), 10-13 (2013) @No $ @ @ Budi Setiyono, Mochamad Hariadi and Mauridhi Hery Purnomo, “Investigation of Superresolution using Phase based Image Matching with Function Fitting”, Research Journal Engineering Sciences, 1(3), 38-44 (2012) @No
<#LINE#>Security System Based on Iris Recognition<#LINE#>SophiaS.@SheebaJeya,S.@Veluchamy<#LINE#>16-21<#LINE#>4.ISCA-RJEngS-2013-015.pdf<#LINE#> Communication Engineering, Anna University Chennai Regional Center Madurai<#LINE#>18/2/2013<#LINE#>21/3/2013<#LINE#>Iris recognition is a biometric system for access control that uses the most unique characteristic of the human body, the iriemployed in automated border crossings, national ID systems, etc. of iris recognition system based on stationary images using NI Laband localization of iris using canny edge detection is performed. And normalization of iris is performed using the Gabor filter. Local binary pattern (LBP) is used for feature vectors extraction and Learning Vector Quantization (LVQ) performs classification. Here, matching is performed using the hamming distance. Also we create a Labinformation of the users. All the images used in this paper were collected from the Chinese Academy Automation (CASIA) iris database VI.0 with 108 subjects in it. <#LINE#> @ @ Adams W.K. Kong Member, IEEE, David Zhang, Fellow, IEEE, and Mohamed S. Kamel, Fellow, IEEE, An Analysis of Iriscode, IEEE transactions on image processing, 19(2),(2010) @No $ @ @ Amol D. Rahulkar and Raghunath S. Holambe, Half-Iris Feature Extraction and Recognition Using a New Class of Biorthogonal Triplet Half-Band Filter Bank and Flexible k-out-of-n:A Postclassifier, IEEE Trans. on information forensics and security, 7(1), (2012) @No $ @ @ Karen P. Hollingsworth, Kevin W. Bowyer, Fellow, IEEE, and Patrick J. Flynn, Senior Member, IEEE, The Best Bits in an Iris Code, IEEE Trans. on pattern analysis and machine intelligence, 31(6), (2009) @No $ @ @ Ma. L., Tan. T, Wang. Y and Zhang. D, Efficient iris recognition by characterizing key local variations, IEEE Trans. Image Process, 13(6),739–750 (2004) @No $ @ @ Monro D. Rakshit S. and Zhang D., DCT-based iris recognition, IEEE Trans. Pattern Anal. Mach. Intell., 29(4), 586-595 (2007) @No $ @ @ Natalia A. Schmid, Member, IEEE, Ketkar Manasi V., Singh Harshinder and Bojan Cukic, Member IEEE, Performance Analysis of Iris-Based Identification System at the Matching Score Level, IEEE Trans. on inf. forensics and security 1(2),(2006) @No $ @ @ Daugman J, High confidence visual recognition of persons by a test of statistical independence, IEEE Trans. Pattern Analy. Machine Intell., 15, 1148–1161 (1993) @No $ @ @ Statistical richness of visual phase information: update on recognizing persons by iris patterns, Int. J. Comput. Vis., 45(1), 25–38 (2001) @No $ @ @ Demodulation by complex-valued wavelets for stochastic pattern recognition, Int. J.Wavelets, Multi-Res. and Info. Processing, 1(1), 1–17 (2003) @No $ @ @ Flom L. and Safir A., Iris Recognition system, U.S. Patent, , 641 394 (1987) @No $ @ @ Kumar B., Xie C. and Thornton J., Iris verification using correlation filters, in Proc. 4th Int. Conf. Audio- and Video-Based Biometric Person Authentication, 697–705 (2003) @No $ @ @ Park C., Lee J., Smith M. and Park K., Iris- based personal authentication using a normalized directional energy feature, in Proc. 4th Int. Conf. Audio- and Video-Based Biometric Person Authentication, 224–232, (2003) @No $ @ @ Sanchez-Avila C. and Sanchez-Reillo R., Iris-based biometric recognition using dyadic wavelet transform, IEEE Aerosp. Electron. Syst. Mag., 17, 3–6 (2002) @No $ @ @ Tangsukson T. and Havlicek J., AM-FM image segmentation, in Proc. EEE Int. Conf. Image Processing, 104–107, (2000) @No $ @ @ Tisse C., Martin L., Torres L. and Robert M., Person identification technique using human iris recognition, in Proc. Vision Interface, 294–299 (2002) @No $ @ @ Boles W. and Boashash B., A human identification technique using images of the iris and wavelet transform, IEEE Trans. Signal Processing, 46, 1185–1188, (1998) @No $ @ @ Havlicek J., Harding D. and Bovik A., The mutli-component AM-FM image representation, IEEE Trans. Image Processing 5, 1094–1100 (1996) @No $ @ @ Yulin Si, Jiangyuan Mei and Huijun Gao, Senior Member, IEEE, Novel Approaches to Improve Robustness, Accuracy and Rapidity of Iris Recognition Systems IEEE Trans. on Ind. Inf., 8(1),(2012) @No $ @ @ Paigwar Shikha and Shukla Shailja, Neural Network based Offline Signature Recognition and verification system, Research Journal of Engineering Science, 2(2)11-15 (2013) @No $ @ @ Singh Amarendra and Verma Nupur, Ear Recognition for automated Human Identification, Research Journal of Engineering Science, 1(5), 44-46 (2012) @No $ @ @ Yadav Sunil Kumar and Rizvi Syed Azhar Abbas, Cybernetics Security Requirements and Reuse for Improving Information Systems Security, Research Journal of Engineering Sci.,1(5), 51-54 (2012) @No
<#LINE#>The Stress Fields obtained from Strain Fields by Virtual Fields Method and Compared with Fem<#LINE#>Michaela@Stamborska,Mares@Vratislav,Miroslav@Kvicala<#LINE#>22-27<#LINE#>5.ISCA-RJEngS-2013-018.pdf<#LINE#>Department of Material Engineering, Faculty of Metallurgy and Materials Engineering, VŠB-Technical University of Ostrava, 17. Listopadu,Ostrava – Poruba, CZECH REPUBLIC @ Department of Non-ferrous Metals, Refining and Recycling, Faculty of Metallurgy and Materials Engineering, VŠB-Technical University ofOstrava, 17. Listopadu, 70833 Ostrava, CZECH REPUBLIC<#LINE#>20/2/2013<#LINE#>5/3/2013<#LINE#>This paper presents comparison of the stress and strain fields gained by a digital image correlation (DIC) and FEM. This method was used to determine strain fields in narrow range of planar specimen. These strain fields were used for calculation of the stress fields by virtual fields method (VFM). The specimen was made from the hypoeutectoid ferrite-pearlite steel, which was used in production of train wheels. The analysis was carried out using two-dimensional DIC by which were obtained values of the strain fields. These values were measured on the surface of specimen in the elastic and plastic domain. Based on measured strain fields the stress fields were determined by Matlab software. Values obtained by this method were subsequently compared with those achieved by FEM. <#LINE#> @ @ Purkar T.S. and Pathak S., Analysis of Crack Initiation in Fretting Fatigue Specimen, ISCA J. Engineering Sci., 1(1), 26-34 (2012) @No $ @ @ Lakshmanan N., Ramachandran G.M. and Saravanan K., Dynamic Stress Analysis of a Multi cylinder Two-stage Compressor Crankshaft, Research J. Engineering Sci., 1(4), 34-40 (2012) @No $ @ @ Lakshmanan N. and Saravanan K., Cause and Effect Assessment after a Complex Failure of a Trunk Piston in Oil Free Compressor, Research J. Engineering Sci., 1(6), 56-60 (2012) @No $ @ @ Nikhil D. and Vivek S., Graph Theoretic approach (GTA) A Multi-Attribute Decision Making (MADM) Technique Attri Rajesh, Res. J. Engineering Sci., 2(1), 50-53 (2013) @No $ @ @ Sreenivasulu R. and Rao Ch. S., Design of Experiments based Grey Relational Analysis in Various Machining Processes - A Review, Res. J. Engineering Sci., 2(1), 21-26 (2013) @No $ @ @ Gmiterko A.K. and Virgala M.I., The snake rectilinear motion modeling on the flat in clined surface, International Journal of Mechanics and Applications., 2(4), 39-42, (2012) @No $ @ @ Holzmann M., Jurášek L. and Dlouhý I., Fracture behaviour and cleavage initiation in hypoeutectoid pearlitic steel, International Journal of Fracture, 148, 13-28 (2007) @No $ @ @ Zaretsky E.V., Rolling bearing steels a technical and historical perspective, Materials Science and Technology, 28, 58-69, (2012) @No $ @ @ Abouridouane M., Klocke F., Lung D. and Adams O., A new 3D multiphase FE model for micro cutting ferritic–pearlitic carbon steels, CIRP Annals - Manufacturing Technology, 61, 71–74 (2012) @No $ @ @ Ghadbeigi H., Pinna C. and Celotto S., Quantitative Strain Analysis of the Large Deformation at the Scale of Microstructure: Comparison between Digital Image Correlation and Microgrid Techniques Experimental Mechanics,52, 1483-1492 (2012) @No $ @ @ Rossi M. and Pierron F., Identification of plastic constitutive parameters at large deformations from three dimensional displacement fields, Comput Mech,49, 53-71 (2012) @No $ @ @ Sozen S. and Guler M., Determination of displacement distributions in bolted steel tension elements using digitalimage techniques, Optics and Lasers in Engineering, 49, 1428–1435 (2011) @No $ @ @ Sutton M.A., Orteu J.J. and Schreier H.W., Image correlation for shape, motion and deformation measurements, Springer(2009) @No $ @ @ Štamborská M., Šimák F., Kalina M. and Schrötter M., Identification of the Stress Fields from the Strain Fields in the Isotropic Materials, Procedia Engineering, 48, 665-672 (2012) @No $ @ @ Tarantino M.G.,Beretta S., Foletti S. and Papadopoulos I., Experiments under pure shear and rolling contact fatigue conditions: Competition between tensile and shear mode crack growth, International Journal of Fatigue,46, 67-80 (2013) @No $ @ @ Wang J., Levkovitch V., Reusch F., Svendsen B., Huétink J. and Van Riel M., On the modeling of hardening in metals during non-proportional loading, International Journal of Plasticity, 24(6), 1039-1070 (2008) @No
<#LINE#>Thermoluminescence (TL) study of CeSO4Cl: Dy Phosphor for γ-radiation dosimetry<#LINE#>S.C.@Gedam<#LINE#>28-31<#LINE#>6.ISCA-RJEngS-2013-019.pdf<#LINE#>K.Z.S. Science College Kalmeshwar, Nagpur 441501, INDIA<#LINE#>20/2/2013<#LINE#>25/2/2013<#LINE#>CeSO4Cl: Dy phosphor is prepared by wet chemical method. The thermoluminescence (TL) study of CeSO4Cl:Dy phosphor has been presented in this paper. The strong sensitivity of the CeSO4Cl: Dy phosphor is obtained with the broadness of the glow peak for various concentrations of Dy and different γ-rays doses. The phosphors CeSO4Cl: Dy has a simple TL glow curve structure with a single prominent peak at around the temperature 169°C indicating single trapping sites. The phosphor may be quite suitable for use in dosimetry of ionizing radiations. <#LINE#> @ @ Blasse G., Lumin, Inorg. Solids, 475, 215-220 (1978) @No $ @ @ Dhopte S.M., Muthal P.L., Kondawar V.K., Moharil S.V., Sahare P.D., Mechanism of thermoluminescence in CaSO4: Dy, J. Phys. D: Appl. Phys,24 1869-1878 (1991) @No $ @ @ Dhoble S.J., Dhopte S.M., Muthal P.L., Kondawar V.K. and Moharil S.V., Preparation and Characterization of the K3Na (SO4) 2: Eu Phosphor, Phys. Stat. Sol. A,135, 289-292 (1993) @No $ @ @ Atone M.S., Dhoble S.J., Dhopte S.M., Muthal P.L., Kondawar V.K., Moharil S.V., Sensitization of Luminescence of CaSO: Dy, Phys. Stat. Sol. A,135, 299-305 (1993) @No $ @ @ Dhoble S.J., Moharil S.V. and Gundurao T.K., Correlated ESR, PL and TL studies on K3Na(SO4)2: Eu, J. Lumin,93, 43-46 (2001) @No $ @ @ Klement R., Naturwissenschaften, F. Miner, 27, 568-574 (1939) @No $ @ @ Schneider W., Jahrb N., The crystal structures of cesanite and its synthetic analogue, F. Miner.Monatschefte, 284 (19678.Schneider W., Jahrb N., Formation, Crystallization, andMigration of Melt in the Mid-orogenic, F. Miner. Monatschefte, 58 (1969) @No $ @ @ Kim H.J., Jeong D. Zalar Y., Blin B.R.C. and Choh S.H., Rb NMR study of phase transitions below roomtemperature in a LiK0.9Rb0.1SO4 mixed crystal, Phys. Rev. B,61, 9307-9304 (2000) @No $ @ @ Piotrowski A., Kahlenberg V. and Fischer R.X., The Solid Solution Series of the Sulfate Apatite system Na6.45Ca3.55(SO4)6(FxCl1 x)1.55 J Solid-state chem. 163 398-306 (2002) @No $ @ @ Gedam S.C., Dhoble S.J. and Moharil S.V., Synthesis and effect of Ce3+ co-doping on photoluminescence characteristics of KZnSOCl: M (M = Dy3+ or Mn2+) new phosphors, J. lum,121(2), 450-457 (2006) @No $ @ @ Gedam S.C., Dhoble S.J. and Moharil S.V., Dy3+ and Mn2+emission in KMgSOCl phosphor, J.lum.,124(1), 120-126 (2007) @No $ @ @ Dhoble S.J., Gedam S.C., Nagpure I.M., Godbole S.V., Bhide M.K., Moharil S.V., Luminescence of Cu+ in halosulphate phosphor, J. Mater Sci.,43, 3189–3196 (2008) @No $ @ @ Gedam S.C.,Optical study of Gd3+ and Tb3+ in KZnSOCl: Ce3+ Phosphor, Res. J. Physical Sci., 1(1), 6-10, (2013) @No
<#LINE#>Effect of Insulation on Rotary Drum Dryer's Performance<#LINE#>C.D.@Deshmukh<#LINE#>32-36<#LINE#>7.ISCA-RJEngS-2013-035.pdf<#LINE#>M – Tech student, GCOE Amravati, Maharashtra, INDIA<#LINE#>11/3/2013<#LINE#>20/3/2013<#LINE#>This paper is about the rotary drum cotton seed dryer. Here in this research work one experiment was taken on the drying mechanism of the cotton seeds in rotary drum type dryer. For this experimentation one setup was assembled and performance of the dryer was checked in the form of amount of moisture extracted from the seeds. This performance estimation was done with and without the insulation of the surface area of the drum. Also these experiments were done for different mass flow rate and different temperthat the moisture extraction rate goes on increasing with the increase in the air flow rate and temperature. It was concludedat the end that the best performance was observmentioned in this paper will clear the results and observations. <#LINE#> @ @ Akosman C., Togrul T.I. and Pehlivan D., Development and testing of a solar air-heater with conical concentrator, Renewable Energy, 29, 263–275 (2004) @No $ @ @ Aktaa M., Ceylanb I. and Yilmazb S., Determination of drying characteristics of apples in a heat pump and solar dryer, Desalination, 239, 266–275 (2009) @No $ @ @ Franks G.N. and Shaw C.S., Cottonseed Drying and Storage at Cotton Gins, Agricultural research service (United States Department of Agriculture) technical bulletin no. (1262) @No $ @ @ Ortega M.G., Castano F., Vargas M. and Rubio F.R., Multivariable robust control of a rotary dryer: Analysis and design, Control Engineering Practice,15, 487–500(2007) @No $ @ @ Sivill L., Ahtila P. and Taimisto M., Thermodynamic simulation of dryer section heat recovery in paper machines, Applied Thermal Engineering,25, 1273–1292(2005) @No
@Research Article
<#LINE#>Modeling and Simulation of Productivity in the Turning of Ferrous and Nonferrous Material using Artificial Neural Network and Response Surface Methodology<#LINE#>M.MangeshR@Phate.,Tatwawadi@V.H.,J.P.@Modak<#LINE#>37-44<#LINE#>8.ISCA-RJEngS-2013-027.pdf<#LINE#>Dept. Of Mechanical Engg, TSSM’s, PVPIT, Bavdhan, Pune, Maharashtra, INDIA @ Dr.Babasaheb Ambedkar College of Engg and Research, Nagpur, Maharashtra, INDIA @ Mechanical Engg, Dept, Priyadarshni College of Engineerig, Nagpur, INDIA <#LINE#>28/2/2013<#LINE#>6/3/2013<#LINE#> Traditional machining is a complex phenomenon which includes the workers who operates the machines and his working environment such as atmospheric parameters, work piece parameters, cutting process parameters, tool parameters and etc In the India and other country the majority of total machining operation are still executed manually which needs to be focused and develop a mathematical model referred as Field data based Model) to identify the strengths and weaknesses of the present method. The formulated field data based Model (FDBM ) correlates the various input parameters with the output parameters . The present paper aimed to propose improvement in methods of performing these activities by developing mathematical simulation from data collected while the work was actually being executed in the field. Once the generalized model using all possible parameters developed, the weaknesses of the present method identified and improvement is possible. The main contribution of this paper is to develop the mathematical model for the turning of ferrous and nonferrous material. The validation of the formulated Field Data Based Mathematical model (FDBM) is achieved by comparing with the Artificial Neural Network and response surface model. The aim of the paper is to find out the mathematical model for the productivity i.e. machining time and the machining cost required for turning the ferrous and nonferrous work piece. Out of so many parameters mentioned above we would like to find out which of these are most important for increasing the productivity. Simultaneously it would be interesting to know influence of one parameter over the other. <#LINE#> @ @ Adeel H. Suhail, N. Ismail, S.V. Wong and N.A. Abdul Jalil, American Journal of Engineering and Applied Sciences,3(1), 102-108 (2010) @No $ @ @ E. Daniel Kirby, Journal of Industrial Technology, 26(1), 1-11 (2010) @No $ @ @ Singh Hari, in International Multi Conference of Engineers and Computer Scientists, II, IMECS, 19-21(2008) @No $ @ @ Dalgobind Mahto and Anjani Kumar: ARISER, 4(2), 61-75 (2008) @No $ @ @ Thamizhmanii S., Saparudin S. and Hasan S., Journal of Achievements in Materials and Manufacturing Engineering, 20(1-2), 503-506 (2007) @No $ @ @ Petropoulos G., Ntziantzias I. and Anghel C., in: International Conference on Experiments/ Process/ System Modelling/ Simulation/Optimization, Athens (2005) @No $ @ @ H. Schenck Jr., Theories of Engineering a experimentation, McGraw Hill Book Co ,New York(1954) @No $ @ @ Sundaram R.M., An application of goal programming technique in metal cutting, Int. J. Prod. Res., 16, 375 382(1978) @No $ @ @ Agapiou J.S., The optimization of machining operations based on a combined criterion, Part 1 The use of combined objectives in single-pass operations, Part 2: Multi-pass operations. J. Eng Ind., Trans. ASME, 1(14), 500–513 (1992) @No $ @ @ Brewer R.C. and Rueda R., A simplified approach to the optimum selection of machining parameters, Eng Dig., 24(9), 133–150 (1963) @No $ @ @ Klir G.J and, Yuan B. , Fuzzy system and fuzzy logic – theory and practice (Englewood Cliffs, NJ: PrenticeHall), (1998) @No $ @ @ Petropoulos P.G., Optimal selection of machining rate Variable by geometric programming. J Prod. Res., 11,305–314 (1973) @No $ @ @ Phate M.R., Tatwawadi V.H., Modak J.P., Formulation of A Generalized Field Data Based Model For The Surface Roughness of Aluminum 6063 In Dry Turning Operation, New York Science Journal, 5(7), 38-46 (2012) @No $ @ @ Tatwawadi V.H., Modak J.P. and Chibule S.G., Mathematical Modeling and simulation of working of enterprise manufacturing electric motor, International Journal of Industrial Engineering, 17(4), 341-35 (2010) @No $ @ @ Walvekar A.G. and Lambert B.K., An application of geometric programming to machining variable selection. Int. J. Prod. Res., 8(3),(1970) @No $ @ @ Gilbert W.W., Economics of machining. In Machinin – Theory and practice.Am. Soc. Met. 476–480(1950) @No $ @ @ Muwell K.F.H., Nature of Ergonomics, Ergonomics (Man In His Working Environment), Chapman and Hall, London, New York, (1956) @No
@Review Paper
<#LINE#>Application of Grey Based - Taguchi Method to Determine Multiple Performance Characteristics in Drilling of Aluminium Alloys - Review<#LINE#>Sreenivasulu@Reddy,Ch.Srinivasa@Rao<#LINE#>45-51<#LINE#>9.ISCA-RJEngS-2012-103.pdf<#LINE#>Department of Mechanical Engineering, R.V.R. and J.C.College of Engineering (Autonomous) Guntur, AP, INDIA @ Department of Mechanical Engineering, University College of Engineering (Autonomous) Andhra University, Visakhapatnam, AP, INDIA<#LINE#>3/11/2012<#LINE#>21/11/2012<#LINE#> Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Aluminium alloys widely used for automotive and aerospace industries which durability, strength, and light weight are desired and these materials subjected to machining operations where the criterion of minimization of lubricant or coolant use is becoming more topicality. Manufacturer have desired to work without any lubricant because of reasons such as the cost of using it, supply and maintenance of the lubricant, hazard arising from the lubricant and the disposal of used lubricant, therefore an alternative methods of machining is either dry machining or machining with less lubricant. In this study, minimum quantity lubricant mixing with water technique in drilling process using Grey based - Taguchi method is used. A statistical technique, fractional factorial experiments and analysis of variance (ANOVA), has been employed to investigate the influence of cutting parameters. This paper presents a literature review on drilling of Aluminum alloys. <#LINE#> @ @ Hamade R.F. and Ismail F., A case for aggressive drilling of aluminum, Journal of Materials Processing Technology, 166, 86-97 (2005) @No $ @ @ Pande S.S. and Relekar H.P., Investigations on reducing burr formation in drilling, International Journal of Machine Tool Design Research,26(3) 339–348 (1986) @No $ @ @ Lauderbaugh L. Ken An Exit Burr Model for Drilling of Metals, Transaction of the ASME, Journal of Manufacturing Science and Engineering, 23, 562-66 (2001) @No $ @ @ Lauderbaugh L., Ken Analysis of the effect of process parameters on exit burrs in drilling using a combined simulation and experimental approach, Journal of Materials Processing Technology, 209, 1909-1919 (2009) @No $ @ @ Nouri M., List G. and Gehin D., Effect of machining parameters and coating on wear mechanisms in dry drilling of aluminum alloys, International Journal of Machine Tools and Manufacturing,45, 1436-1442 (2005) @No $ @ @ List G., Nouri M., Gehin D., Gomez S., Manaud J.P., Petitcorps Y. L. and Girot F., Wear behavior of cemented carbide tools in dry machining of aluminum alloys, International Wear, 259, 1177-1189 (2005) @No $ @ @ Nair V.N., Abraham B., MacKay J., Nelder J.A., Box G. and Phadke M.S., et al. Taguchi’s parameter design: A panel discussion, Techno metrics, 34(2), 127–161 (1992) @No $ @ @ Rao Sathish U. and Rodrigues L.L. Raj, Applying wear maps in the optimization of machining parameters in drilling of polymer matrix composites – Review,Res.J.Recent Sci, 1(5) 75-82 (2012) @No $ @ @ Murthy B.R.N., Lewlyn L.R. Rodrigues and Anjaiah Devineni, Process Parameters optimization in GFRP drilling through integration of Taguchi and Response surface methodology, Res.J.Recent Sci.,1(6) 7-15 (2012) @No $ @ @ Kilickap E., Mesut H. and Ahmet Y., Optimization of drilling parameters on surface roughness in drilling of AlSi 1045 using response surface methodology and genetic algorithm, International Journal of Advanced Manufacturing Technology, 52, 79-88 (2011) @No $ @ @ Sofronas A., The Formation and Control of Drilling Burrs, Ph.D. Dissertation, The University of Detroit, (1975) @No $ @ @ Lee G.B., Digital Control for Burr Minimization in Drilling, Ph.D. Dissertation, Dept. of Mech. 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Grey System, 1(1), 1-24 (1989) @No $ @ @ Montgomery D.C., Design and Analysis of Experiments ,5th Ed., Wiley, New York, (2000) @No $ @ @ Myers R.H. and Montgomery D.C., Response surface methodology Process and Product optimization using designed experiments, Wiley, New York, Machinery’s Handbook, 25th Edition (2002) @No $ @ @ Deepak S.S.K., Application of different optimization methods for metal cutting operation – A Review,Res.J.Recent Sci., 1(3) 52-58 (2012) @No $ @ @ Rodrigues L.L.R, Kantharaj A.N., Kantharaj B., Freitas W.R.C. and Murthy B.R.N., Effect of Cutting Parameters on surface roughness and cutting force in turning Mild Steel, Res. J. Recent Sci.,1(10) 19-26 (2012) @No
<#LINE#>Bangladeshi Local Apparel Products Need Proper Branding to Sustain in the Competitive Market<#LINE#>Md.Mazedul@Islam,AdnanMaroof@Khan<#LINE#>52-57<#LINE#>10.ISCA-RJEngS-2013-005.pdf<#LINE#>Lecturer, Department of Textile Engineering, Daffodil International University, BANGLADESH<#LINE#>21/1/2013<#LINE#>2/2/2013<#LINE#> The importance of the textile industry in the economy of Bangladesh is very high. Local clothing brands are flourishing on the back of increasing demand from domestic buyers The rapid growth of the RMG industry in the country has not been enough supported by the growth of backward linkage facilities. Environmental changes, intensive international competition, unpredictable consumer demand, and market trends of variety and short product life cycles, compel the Bangladeshi textile and apparel industry to focus increasingly on the consumer as a way to meet these challenges. So, proper branding and manufacturing the quality product is mandatory to sustain in this global competitive market. Attracting the customer through proper branding with quick response has established new business strategies, new relationships and new procedures to speed the flow of information and merchandise between retailers and manufacturers of apparel and textiles. The objective of this paper is to briefly review competitive strategies in branding that are relevant to the Bangladeshi apparel industry, focusing specifically on differentiation and branding methods. Applications to both textile and apparel firms are made and a potential structures by which local brands like Cat's Eye, Westecs, Artisti, Kay Kraft, Aarong, Banglar Mela, Dorjibari, Lubnan, Artness, etc, may develop brands potentiality is introduced. This paper will aid industry in the development of textile and apparel brands, as well as recommendations on brand strategy and creation. A general overview of this paper is given below. <#LINE#> @ @ http:// www.asiantextilejournal.com (2008) @No $ @ @ http://www.fahsionudyoginbangla.com(2011) @No $ @ @ http://www.fiber2fashion.com(2009) @No $ @ @ http://www.localapparelbrand.bd.com (2010) @No $ @ @ Beath J. and Katsoulacos Y., The Economic Theory of Product Differentiation. Cambridge University Press, Cambridge, England (1991) @No $ @ @ Centre for Policy Dialogue (CPD) Bangladesh, Contribution of the RMG Sector to Bangladesh Economy, Paper 50, http://www.cpd-bangladesh.org/ publications/ op/OP50.pdf(2002) @No $ @ @ Porter M., Competitive Advantage of Nations, New York: The Free Press, 35 (1990) @No $ @ @ Schultz D., Understanding total brand value’ Marketing Management, 13, 10 (2004) @No $ @ @ Standard and Poor’s, Textiles Industry Survey Monthly Investment Review, January (2004) @No $ @ @ Bain J., (1956) Barriers to new competition, Harvard University Press Ansoff, H. Corporate, (1965) @No $ @ @ Parrish E., Cassill N. and Oxenham W., Opportunities in the international textile and apparel marketplace for niche markets, Journal of Fashion Marketing and Management, 8, 41-57 (2004) @No $ @ @ Bloom P., Retailer power and supplier, The Journal of Industrial Economics,33, 339-148 (2001) @No $ @ @ Dawson J., Viewpoint: retailer power, manufacturer power, competition and some questions of economic analysis, International Journal of Retail & Distribution Management, 28, 5 (2000) @No $ @ @ Keller K.L., Strategic Brand Management: Building, Measuring, and Managing Brand Equity New Jersey: Prentice Hall (1998) @No $ @ @ Mariotti J., Smart things to know about brands & branding. New Hampshire: Capstone US. (1999) @No $ @ @ Nilson H.N., Competitive Branding: Winning in the Market Place with Value-Added Brands, New York: John Wiley & Sons (1998) @No $ @ @ Elliott C., Vertical product differentiation and advertising, International Journal of the economics of Business, 11, 37 (2004) @No $ @ @ Randall G., Branding: a practical guide to planning your strategy, London: Kogen Page Limited (1997) @No $ @ @ Aaker D. and Jachimsthaler E., Brand Leadership, New York: The Free Press (2000) @No $ @ @ Murphy J., Branding: A Key Marketing Tool, New York: McGraw-Hill Book Company (1987) @No $ @ @ Roberts J.H. and Morrison P.D.,Assessing market structure and company fit based on consumer perceptions in dynamic information technology, Journal of Business Research, 55(8) 679 (2003) @No $ @ @ Stuart J., How great brands got to be that way, Advertising Research Council (1997) @No $ @ @ Rohwedder C., Making Fashion Faster, The Wall Street Journal, February 24, 15 (2004) @No $ @ @ Gad T., 4-D Branding. New York: Prentice Hall (2001) @No $ @ @ LePla F. and Parker L., Integrated Branding: Becoming Brand-Driven Through Companywide Action Westport: Quorum Books (1999) @No