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Volume-5 Issue-1 Published on October 30, 2015
10
Volume-5 Issue-1 Published on October 30, 2015
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S. No

Volume-5 Issue-1, October 2015, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Nasser. R.A., Hee. H.C., Ervina Junaidi, Martin Anyi

Paper Title:

Hydro Rice Milling Machine

Abstract: It has been reported that 41% of the countryside and isolated areas in Sarawak which still have no electricity coverage, compared to only 10% in Peninsular Malaysia. Furthermore, most of the Sarawak rural communities are farmers and families are feeding on the harvesting of paddies. The harvesting of paddies in rural area of Sarawak is inefficiency as compared to other parts of the world due to insufficient supply of electricity. This study investigates the feasibility of of implementing hydropower generated rice milling machine in rural area of Sarawak through laboratory testing on minimum power required to run the rice milling machine and the power that can be supplied from the open channel. The results show that with the current open channel flume and the structure of the rice milling machine, it is feasible to replace traditional methods (beating or foot husk) and more modern methods (gasoline powered engine or electricity dependence rice miller) with the hydro rice milling machine.

Keywords:
   harvesting of paddies, Hydropower, Open channel, Rice milling machine.


References:

1.       Sarawak Government. (n.d.). Climate and rainfall. Available: http://www.sarawak.gov.my/web/home/article_view/159/176/
2.       S. K. Goyal, S. V. Jogdand, A. K. Agrawal. (2012). Energy use pattern in rice milling industries – a critical appraisal. Journal of Food Science and Technology. Columbia: Springer Science & Business Media, 2012.

3.       M. H. Chaudhry. Open channel flow. Columbia: Springer Science & Business Media, 2007.

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2.

Authors:

A. Chennakesava Reddy

Paper Title:

Effects of Adhesive and Interphase Characteristics between Matrix and Reinforced Nanoparticle of AA2124/AlN Nanocomposites: Mathematical and Experimental Validation

Abstract: Interphase around the reinforcement has significant influence on the interfacial stress, displacement and stiffness of composites. In this article two types of RVE models have been implemented using finite element analysis. Aluminum nitride nanoparticles were used as a reinforcing material in the matrix of AA2124 aluminum alloy. It has been observed that the nanoparticle did not overload during the transfer of load from the matrix to the nanoparticle via the interphase due to interphase between the nanoparticle and the matrix. The maximum tensile strengths of AlN/AA2124 nanocomposite have been found 535.40 MPa without interphase and 561.57 MPa with interphase. The transverse modulus has been established lower than the longitudinal modulus of AA2124/AlN nanocomposites. The results obtained from the finite element analysis were validated with mathematically derived and experimental results.

Keywords:
RVE models, AlN nanoparticle, AA2124, finite element analysis, interphase, transverse modulus.


References:

1.        Chennakesava Reddy, “Mechanical properties and fracture behavior of 6061/SiCp Metal Matrix Composites Fabricated by Low Pressure Die Casting Process,” J. Manuf. Technol. Res., vol.1 (3/4), 2009, pp. 273-286.
2.        A.Chennakesava Reddy and Essa Zitoun, “Tensile properties and fracture behavior of 6061/Al2O3 metal matrix composites fabricated by low pressure die casting process, Int. J. Mater. Sci., vol.6(2), 2011, pp. 147-157.

3.        X. Deng and N. Chawla, “Modeling the effect of particle clustering on the mechanical behavior of SiC particle reinforced Al matrix composites,” J. Mater. Sci., vol.41, 2006, pp.5731–5734.

4.        A.J.Reeves, H.Dunlop and T.W. Clyne, “The effect of interfacial reaction layer thickness on fracture of titanium–SiC particulate composites,” Metall. Trans. A, vol.23, 1992, pp.977–88.
5.        Kotiveerachari and A. Chennakesava Reddy, “Interfacial effect on the fracture mechanism in GFRP composites,} CEMILAC Conference, Ministry of Defense, India. 1999, 1(b), pp.85-87.
6.        Chennakesava Reddy, Analysis of the Relationship Between the Interface Structure and the Strength of Carbon-Aluminum Composites, NATCON-ME, Bangalore, 13-14th March, 2004, pp.61-62.

7.        S. Ren, X. Shen, X. Qu and X. He, “Effect of Mg and Si on infiltration behavior of Al alloys pressureless infiltration into porous SiCp preforms,” Int. J. Miner. Metall. Mater. Vol.18 (6), (2011, pp.703–708.

8.        N. Sobczak, M. Ksiazek, W. Radziwill, J. Morgiel, W. Baliga, and L. Stobierski, “Effect of titanium on wettability and interfaces in the Al/ SiC system,” in: Proceedings of the International Conference High Temperature Capillarity, Cracow, Poland, 29 June–2 July 1997.

9.        A.M. Davidson and D. Regener, “A comparison of aluminium based metal matrix composites reinforced with coated and uncoated particulate silicon carbide. Compos. Sci. & Technol., vol.60(6), 2000, pp.865-869.

10.     M. Romanowicz, “Progressive failure analysis of unidirectional fiber-reinforced polymers with inhomogeneous interphase and randomly distributed fibers under transverse tensile loading,” Compos. A, vol.41, 2010, pp.1829-1838.

11.     R. Hill, “Elastic properties of reinforced solids: some theoretical principles,” J. Mech. Phys. Solids, vol.11, 1963, pp.357-372.

12.     Y.J. Liu and X.L. Chen, “Evaluations of the effective material properties of carbon nanotube-based composites using a nanoscale representative volume element,”
Mech. Mater., vol.35, 2003, pp.69–81.

13.     Chennakesava R Alavala,   “Finite element methods: Basic concepts and applications,” PHI Learning Pvt. Ltd., New Delhi, 2008.

14.     Chenna kesava Reddy, “Cause and Catastrophe of Strengthening Mechanisms in 6061/Al2O3 Composites Prepared by Stir Casting Process and Validation Using FEA,” Int. J. Sci. & Res., vol.4(2), 2015, pp.1272-1281.

15.     Chennakesava Reddy, “Influence of Particle Size, Precipitates, Particle Cracking, Porosity and Clustering of Particles on Tensile Strength of 6061/SiCp Metal Matrix Composites and Validation Using FEA,” Int. J. Mater. Sci.& Manuf. Eng., vol.42(1), 2015, pp. 1176-1186.

16.     Zhengang Liuy, Guoyin Zu, Hongjie Luo, Yihan Liu and Guangchun Yao, “Influence of Mg Addition on Graphite Particle Distribution in the Al Matrix Composites,” J. Mater. Sci. & Technol., vol.26 (3), 2010, pp.244-250.

17.     Chennakesava Reddy and Essa Zitoun, “Matrix alloys for alumina particle reinforced metal matrix composites,” Indian Foundry J., vol.55 (1), 2009, pp.12-16.

18.     Z. Hashin, “Thermoelastic Properties of Fiber Composites With Imperfect Interface," Mech. of Mater., vol. 8, 1990, pp. 333-348.

19.     C.M. Landis and R.M. McMeeking, “Stress concentrations in composites with interface sliding, matrix stiffness, and uneven fiber spacing using shear lag theory, “. Int. J. Solids Structures, vol.41, 1999, pp. 6289-6313.


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3.

Authors:

David R. Tuigong, Thomas K. Kipkurgat

Paper Title:

Viability of Using Solar Photovoltaic Systems in Textiles Industries in Kenya: a Case of Rivatex East Africa Limited

Abstract: The low supply and the high cost of electricity create a huge gap between demand and supply in Kenya, making industries to look for alternative ways of generating cheap and renewable power. This paper attempts to identify the challenges and drivers of the using solar photovoltaic system in textiles industries with a case of Rivatex East Africa Limited. The study adopted a qualitative research method in order to achieve the intended objectives. Data was collected using interviews. The findings indicates that for textiles industries to operate optimally and cut down on the production cost, there is need for alternative means of generating power and one of the options is to purchase and install solar PVC’s. Another factor that motivates the textiles industry to invest on PVC is the sustainability that solar energy creates. The study also reveals that inadequate policies to encourage subsidies by the government, high cost of installation, challenges to access funding, high and fluctuating interest rates for loans to invest on renewable technology were identified as the major barriers to industries adapting to solar energy. Furthermore, the study revealed other barriers such as lack of awareness and inappropriate information concerning solar energy coupled with poor implementation of policies were also factors that were identified in the study. The study recommends that appropriate structures and policies that encourage subsidies for industries to be put in place to encourage such industries to invest in renewable energy. The government should also give support to industries in terms of funding renewable energy investments.

Keywords:
 Renewable energy, Textiles industries, Photovoltaic, Rivatex, Solar energy


References:

1.        Chaurey A., Kandpal T., (2010). Assessment and evaluation of PV based decentralized rural electrification: and overview. Indian institute of Technology. Renewable and sustainable Energy Reviews Volume 14, Issue 8, pp 2266-2278.
2.        Duffie, J.A., Beckman, W.A. (1991). Solar Engineering of Thermal Processes, John Wiley and Sons, New York.

3.        GOK (Government of Kenya). (2011). Scaling-Up Renewable Energy Program (SREP):               Investment Plan for Kenya. Government Printer, Nairobi.

4.        Haar, N. & Theyel, G. (2006). U.S. electric utilities and renewable energy: drivers for adoption. International Journal of Green Energy, 3,271-28.

5.        Kirui, H. W. (2006). Assessment of Solar and Wind Energy Potential in the Central Rift Valley of Kenya. M.Sc Thesis. Egerton University, Kenya.

6.        Martinot, E. & McDoom, O. (1999). Promoting Energy Efficiency and Renewable       Energy: GEF Climate Change Projects and Impacts Washington, DC.: Global Environmental Facility.

7.        Neville, R. C., (1995). Solar Energy Conversion. Elsevier Science B. V. Publishers, Netherlands.

8.        Randolph J., Masters G. (2008). Energy for sustainability: Technology, Planning,        Policy. Island Press.

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4.

Authors:

Amit J. Modak, H. P. Inamdar

Paper Title:

Optimal Simulated Design of RBF Neural Network Classifier Block for Assessment of State of Degradation in Stator Insulation of Induction Motor

Abstract: In the present work the design of discrete ‘ANN’ simulation model is done for the classification and qualitative assessment of the state of degradation of insulation in the respective phases of three-phase ac induction motor. The extraction of mathematical parameters of stator current data pattern, which are simulating the specific state of degradation of insulation based on Park’s current transformation model, are presented in the previous research papers. The methodology adopted towards the optimal design process of the discrete neural network classifier blocks of discrete ‘ANN’ simulation model , which are designed on the basis of  ‘radial basis function’ (RBF) type of neural network architecture for the qualitative assessment of the state  of degradation of stator insulation is described in the present research paper.

Keywords:
induction motor, stator insulation, radial basis function, artificial neural network, Park’s current transformation


References:

1.        G. C. Stone, H. G. Sedding, B.A. Lloyd and B.K. Gupta, “The ability of diagnostic tests to estimate the remaining life of stator insulation,” IEEE Trans. Energy Conversion, vol.3, no.4, Dec.1988, pp. 833 - 841.
2.        Yoshida, H. and K. Umemoto, "Insulation Diagnosis for Rotating Machine Insulation," IEEE Trans. Electrical Insulation, vol. 21, no.6, Dec. 1986, pp. 1021-1025.

3.        Tsukui, T., M. Takamura and Y. Kako, "Correlations between Nondestructive and Destructive Tests on High-Voltage Coil Insulations for Rotating Machines," IEEE Trans. Electrical Insulation, vol. 15, no. 2, April 1980, pp. 118-124.

4.        A.J. Modak and H.P. Inamdar, “Performance Evaluation of Computer Simulated Extracted Features of Induction Motor with Intermediate State of Degradation Present in Any One-Phase,” International Journal of Applied Information Systems (IJAIS), Foundation of Computer Science FCS, New York, USA vol. 1, no.2, January 2012, (ISSN : 2249-0868)

5.        A.J. Modak and H.P. Inamdar, “Performance Evaluation of Computer Simulated Extracted Features of Induction Motor with Healthy State of Insulation Present in Any Two-Phases,” International Journal of Computer and Electrical Engineering (IJCEE), International Association of Computer Science and Information Technology Press (IACSIT), Singapore, vol.4, no.1, February 2012, pp. 65-74, DOI:10.7763/IJCEE.2012.V4.453, (ISSN: 1793-8163)

6.        A.J. Modak and H.P. Inamdar, “Computer Simulated Extracted Parameters of Induction Motor for Unequal Variation in State of Degradation of Insulation in all Three-phases,” Proc. 7th IEEE Int. Conf.  Industrial Electronics and Applications (ICIEA), Singapore, July 2012, pp. 1229-1235, IEEE Catalog Number: CFP1220A-CDR,
(ISBN: 978-1-4577-2119-9/12)

7.        [NEUROSOLUTIONS, 5.0]:  NEUROSOLUTION Version 5.0,http:// www.neurosolutions.com, NeuroDimension, Inc. 3701 NW 40th Terrace, Suite 1, Gainesville, FL 32606.


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5.

Authors:

Malini S, Lizy Abraham, R.S. Moni

Paper Title:

Multiresolution Color Denoising using Biorthogonal Wavelets for Satellite Images

Abstract: Satellite images are required to be of high quality since most of the databases created by different countries are using the images especially for Geographical Information System (GIS) applications and military purposes. Recently available high resolution multi spectral imaging sensors facilitate greatly the process of feature extraction which is given as the input to the database systems. But because of the sensor vibrations, different angle of inclinations, influence of clouds & shadows and many unwanted factors create noise in satellite images which ultimately affects the quality of feature extraction process. In this paper a novel method of multiresolution colour image denoising using bi-orthogonal wavelets is discussed. The method is compared with other orthogonal wavelet denoising schemes and existing techniques based on patch processing. Experimental analysis and visual inspection of images validates the superior performance of the proposed method.

Keywords:
 Multispectral, Biorthogonal, Daubechies, Decomposition, Multispec32, Quality Measures


References:

1.       S. Shrestha, “Image Denoising using New Adaptive based Median Filter”, An International Journal of Signal & Image Processing (SIPIJ), Vol.5, NO.4, PP. 1-13, Aug. 2014.
2.       V. Govindaraj and G. Sengottaiyan, “Survey of Image Denoising using Different Filters”, International Journal of Science, Engineering and Technology Research (IJSETR), Vol.2, NO. 2, pp. 344-351, Feb.2013.

3.       B. K. Shreyamsha Kumar, “Image Denoising based on Gaussian/Bilateral Filter and its Method for Noise Thresholding”, Signal, Image and Video Processing , Springer, vol.7, no.6, pp 1159-1172, 2012.

4.       Huaibin Wang, Yuanquan Wang and Wenqi Ren, Image Denoising Using Anisotropic Second and Fourth Order Diffusions Based on Gradient Vector Convolution, ComSIS, Vol. 9, No. 4, Special Issue, pp.1493-1511, Dec.2012.

5.       Seongjai Kim and Hyeona Lim, “Fourth Order Partial Differential Equations for Effective Image Denoising”,  Seventh Mississippi State - UAB Conference on Differential Equations and Computational SIMULATIONS, Conf. 17, PP. 107–121, 2009.

6.       Norouzi, M. Shafry, M.Rahim, A. Altameem, T. Saba, A. Rad, A. Rehman and M. Uddin, “Medical Image Segmentation Methods, Algorithms, and Applications”, IETE Journal of Technical Review, vol.31, no. 3, pp. 199-213,  June 2014.

7.       D. Radford,A. Kurekin, D. Marshall and K. Lever, ”A New DCT-based Multiresolution Method for Simultaneous Denoising and Fusion of SAR Images,” 9th
International Conf. on Information Fusion,Florence, pp. 1-8, 2006.

8.       S. Kother Mohideen, S. Arumuga Perumal, and M. Mohamed Sathik, “Image De-noising using Discrete Wavelet Ttransform”, IJCSNS International Journal of Computer Science and Network Security, VOL.8, No.1, pp. 213-216, Jan.2008.

9.       J. N. Ellinas, T. Mandadelis, A. Tzortzis and L. Aslanoglou, “Image De-noising using Wavelets”, T.E.I. of Piraeus Applied Research Review, vol. IX, no. 1, pp. 97-109, 2004.

10.    L. Abraham and M.  Sasikumar, “Analysis of Satellite Images for the Extraction of Structural Features”, IETE Journal of Technical Review, pp. 118 – 127, vol.31, no.2, APRIL 2014.

11.    M. Vijay and L. Saranya Devi, “Speckle Noise Reduction in Satellite Images Using Spatially Adaptive Wavelet Thresholding”, International Journal of Computer Science and Information Technologies, Vol. 3, NO. 2, PP. 3432-3435, 2012.

12.    Parthasarathy Subashini and Marimuthu Krishnaveni, “Image Denoising Based on Wavelet Analysis for Satellite Imagery, Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology, Dumitru Baleanu (Ed.), ISBN: 978-953-51-0494-0, INTECH., PP. 449-474, 2012.

13.    Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “BM3D Image denoising by 3D transform-domain collaborative Filtering”, IEEE Trans. Image Processing, vol. 16, no. 8, pp.2080-2095,  Aug. 2007.

14.    Rajwade,  A. Rangarajan  and A. Banerjee., “Image Denoising Using the Higher Order Singular Value Decomposition”, IEEE Trans. Pattern Analysis and Machine Intel., vol.35 ,  no.4, pp.849 – 862, April 2013.

15.    Kugu, E. , “Satellite Image Denoising using Bilateral Filter with SPEA2 Optimized Parameters”, 6th International Conference on Recent Advances in Space Technologies (RAST), pp. 217 – 223, 2013.

16.    T. Sree Sharmila, K. Ramar, “Efficient Analysis of Hybrid Directional Lifting Technique for Satellite Image Denoising”, Signal, Image and Video Processing , Springer, vol. 8, no. 7, pp. 1399-1404, Aug.2012.

17.    Daubechies, “Ten Lectures on Wavelets”, CBMS, SIAM, 61, 1994.

18.    S.V.Narasimham, Nandini Bazumallick & S. Veena, “Introduction to Wavelet Transform: A Signal Processing Approach”, Naroza Publishing House, New Delhi, 2011.

19.    http://cobweb.ecn.purdue.edu/~biehl/MultiSpec

20.    Nai-Xiang Lian, Zagorodnov, V., Yap-Peng Tan, “Color Image Denoising using Wavelets and Minimum Cut Analysis”, IEEE Signal Processing Letters, vol.12 , no.11 , pp.741 – 744, Nov. 2005.

21.    Chang, S.G.,Bin Yu, Vetterli, M., “Adaptive Wavelet Thresholding for Image Denoising and Compression”, IEEE Trans.Image Processing, vol.9 , no.9, pp.1532 – 1546, Sept. 2000.

22.    Z. Wang, A. C., Bovik, H. R., Sheikh & E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity", IEEE Transactions on Image
Processing, vol. 13, no. 4, pp. 600-612, Apr. 2004.

23.    Janwei Ma & Gerlind Plonka, "The Curvelet Transform", IEEE Signal Processing Magazine, pp.118-133, March 2010.


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6.

Authors:

ASM Delowar Hossain

Paper Title:

Consolidation of Accreditation Activities to Improve Assessment of Student Learning Outcomes in Technical Disciplines

Abstract: Lack of coordination in accreditation activities results in assessment being a burdensome and inefficient process. This work emphasizes the need of a preemptive and coordinated effort to consolidate various accreditation activities to make the assessment process more streamlined and efficient within the context of technical discipline. Specifically, this work demonstrates common grounds of assessment activities between the regional standards and ABETS accreditation criteria to attain assessment efficiency.

Keywords:
Assessment, Accreditation, Engineering Education


References:

1.        http://chea.org/pdf/Overview%20of%20US%20Accreditation%2003.2011.pdf
2.        http://ope.ed.gov/accreditation/FAQAccr.aspx

3.        http://www.50states.com/college-resources/accreditation.htm#.VRcAdNgtH_s

4.        The Chronicle of Higher Education Almanac, Issue 2010-2011, August 27, 2010

5.        http://www.chea.org/pdf/2014-2015_Directory_of_CHEA_Recognized_Organizations.pdf, 2014

6.        www.msche.org

7.        http://www.abet.org/accrediation

8.        http://www.abet.org/uploadedFiles/Accreditation/Accreditation_Step_by_Step/Accreditation_Documents/Current/2014_-_2015/T001%2014-15%20ETAC%20Criteria%2010-26-13.pdf, 2014

9.        Kuh, G. D., & Ikenberry, S. O., “More than you think, less than we need:  Learning outcomes assessment in American higher education”, Urbana, IL: University of Illinois and Indiana University, National Institute for Learning Outcomes Assessment, October 2009.

10.     “2011 outcomes assessment accreditation handbook”, http://atmae.org/index.php?option, October 24, 2011

11.     Middle States Commission on Higher Education (MSCHE), “Characteristics of excellence in higher education: Requirements of affiliation and standards for accreditation”, http://www.msche.org/publications/CHX06_Aug08REVMarch09.pdf, 2009

12.     Brumm, T., Mickelson, S., Steward, B., & Kaleita, A, “ Competency-based outcomes assessment for agricultural engineering programs. International Journal of Engineering Education”, 22(6), 1163–1172, 2006.


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7.

Authors:

Lakshmi HV

Paper Title:

Detection of Intrusion and Honey Net Architecture Approach to Defend in Virtual Network Systems

Abstract: Security in cloud is one of the most important issues that drawn interest of research and development in past years. Hackers can explore vulnerabilities of cloud system and to deploy large-scale Distributed Denial-of-Service they compromise virtual machines. Distributed Denial-of-Service attacks involve early stage actions as multi-step exploitation, less frequency vulnerability scanning, and compromising insecure virtual machines, and Distributed Denial-of-Service attacks through the compromised VMs. In cloud system, the detection of zombie attacks is difficult. Because users may install insecure applications on their VMs to avoid insecure virtual machines from being compromised in the cloud, we propose a multi-phase distributed vulnerability finding, and Honey Net approach to fight back the attack. Honeypot is a data system resource and its value lies in unauthorized use of that resource of system. Honey nets are “a security resource whose value lies in being attacked”. Honeypots and honey nets are used to collect data about threats that organizations might face and hence protect them.

Keywords:
 Network Security, Honey Pot, Honey Net, Cloud Computing, Intrusion Detection

References:

1.        Cloud Security Alliance, “Top threats to cloud computing v1.0,”  https://cloudsecurityalliance.org/topthreats/csathreats.v1.0.pdf, March 2010.
2.        M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Kon- winski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “A view of cloud computing,” ACM Commun., vol. 53, no. 4, pp. 2010.

3.        R.Thomas, B. Mark, T. Johnson. NetBouncer: client-legitimacy- based high-performance DDoS filtering [J]. In Pro of DARPA information Survivability Conference and Exposition. Washington, DC, 2003:14-25.

4.        T. Peng, C, Leckie, K. Ramamohanarao. Protection from distributed denial of service attacks using history-based IP filtering [J]. In Pro of IEEE International Conference on Communications (ICC03), Anchorage, Alaska, USA, 2003:482-486.

5.        Zhu Ge Jianwei. Honeypot and honeynet technology description [J].Peking University Institute of Computer Technology, 2006.

6.        Shi Weiqi, Chengjie Ren. Honeypot technologies and applications[J]. Computer Engineering and Design, 2008,29 (22) :5725-5728.

7.        J. Mirkovic, G. Prier, P. Reiher. Source-end DDoS defense [J]. In Pro of IEEE International Symposium on Network Computing and Applications (NCA2003). Ca mbridge, Massachusette, 2003:171-178.1989.

8.        Yang Shangsen, Hu Bei. Based on Intrusion Deception active honeypot technology system design [J]. Computer Applications and Software, 2008,25 (1) :259-260.


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8.

Authors:

M. Jagannadha Rao, B. Gopal Krishna

Paper Title:

Synthesis of Copper Silicate (CuSiO3.H2O) using Copper Oxide, Quartz and Microbes

Abstract: Microbes like bacteria, algae, fungi and virus play an important role to catalyst chemical reactions. In Nature, ores or minerals of different compounds are formed due to microbial environment and other factors like weathering. Microbial environment is also instrumental in forming copper containing silicate minerals. Chemical reactions occur under microbial environment because microbes have the ability to control or modify different factors like pH, chemical potential and temperature during reactions. In this paper, synthesis of copper silicate (CuSiO3.H2O) using copper oxide (CuO) and quartz (SiO2) under microbial environment in the laboratory is being adopted to produce the material. XRD technique is used to confirm the formation of CuSiO3.H2O.

Keywords:
 Copper oxide, Quartz, CuSiO3, microbes, XRD

References:

1.        R . M .Atlas, and R . Bartha, Microbial ecology. Fundamentals and Applications. Benjamin/Cumming Pub. Co., Inc.,1998.
2.        L .Bhatnagar, and B . Z .Fathepure, Mixed cultures in Detoxification of hazardous   waste. In: Mixed Cultures in Biotechnology, Zeikus, G. and Johnson, E. A., eds., McGraw-Hill, Inc. ,   p. 293-340,  1991.

3.        T.D. Brock, Biology of Microorganisms. 2/e. Prentice-Hall, Englewood Cliffs, NJ.,1974.

4.        E.S. Deevey Jr., Mineral cycles. Sci. Amer., 223(3) , p.149-158, 1991.

5.        R.L. Dimmick, H. Wolochow, and M.A. Chatigny, Evidence that bacteria can form new cells in airborne particles. Appl. Environ. Microbiol., 37, p.924-927, 1979.

6.        P.N. Hobson, and N.J.Poole, In: Microorganisms in action: Concepts and applications in Microbial Ecology. Blackwell Sci. Pub., Oxford.,  p.302, 1988.

7.        W.E. Krumbein, On the precipitation of aragonite on the surface of marine bacteria. Naturwissenschafen., 61, p.167, 1970.

8.        S.I. Kuznetsov, M.V. Ivanov, and  N.N. Lyalikova, Introduction to Geological Microbiology. McGraw Hill, New York., p. 26, 1963.

9.        R. Lynd Lee, J. Weimer Paul, H. van Zyl Willem,  and S. Pretorius Isak, Microbial Cellulose Utilization: Fundamentals and Biotechnology. Microbiol. Mol. Biol. Rev., 66 (3), p.506-577, 2000.

10.     R.Y. Morita, Calcite precipitation by marine bacteria. Geomicrobiol. J., 2 , p. 63-82, 1980.

11.     D.M. Webley, R .B. Duff, and W.A. Mitchell,  A plate method for studying the breakdown of synthetic and natural silicates by soil bacteria. Nature , 188,  p.766-767, 1960.

12.     T. Yanagita, Natural Microbial Communities: Ecological and physiological features. Japan Sci. Soc. Press, Tokyo and Spriger-Verlag, Berlin,  p. 417-425, 1990.

13.     R .H. Sillitoe,  Epochs of intrusion-related copper mineralization in the Andes: Journal of South American Earth Sciences, 1,  p. 89–108, 1988.

14.     R.H. Sillitoe, Supergene oxidized and enriched porphyry copper and related deposits: Economic geology, 100 , p. 723–768, 2005.

15.     R.H. Sillitoe, Studies on the controls and mineralogy of the supergene alteration of copper deposits, northern Chile: [Dissertation], London, England, University College London,,p.498, 1969.

16.     C. Mortimer, The Cenozoic history of the southern Atacama desert, Chile: London, Journal of the Geological Society, 129, p. 505–526, 1973.

17.     A.H. Clark, R.M. Tosdal, E. Farrar, and V.A. Plazolles, Geomorphologic environment and age of supergene enrichment of the Cuajone, Quellaveco, and  
Toquepala porphyry copper deposits, southeastern Peru: Economic geology, 85 ,  p.1604–1628, 1990.

18.     D.W. Newberg, Geochemical implications of chrysocolla-bearing alluvial gravels: Economic geology, 62 ,p. 932–956, 1967.

19.     D.B. Johnson, and K.B. Hallberg, The microbiology of acidic mine waters: Research in Microbiology, 154, p. 466–473, 2003.

20.     D.L. Kelley, K.D. Kelley,  W.B. Coker,  B. Caughlin, and M.E. Doherty,  Beyond the obvious limits of ore deposits: The use of mineralogical geochemical, and biological features for the remote detection of mineralization, Economic geology, 101 ,  p. 729–752, 2006.

21.     M.J. Pemberton, and R . Schmidt, Catabolic Plasmids, Encyclopedia of Life Sciences, John Wiley & Sons, Ltd.,2001.

22.     Svetlozar Velizarov, Electrical and Magnetic fields in microbial biotechnology: possibilities, limitations and perspectives, Electro and  Magnetobiology, 18(2) , p.185-212, 1999.

23.     Lukas Fojt, Ludek  Strasak, Vladimir  Vetterl , and Jan Samarda,  Comparison of the low-frequency magnetic field effects on bacteria Escherichia coli, Leclercia adecarboxylata and Staphylococcus aureus, Bioelectrochemistry, 63,  p.337– 341, 2004.

24.     S.R. Gopishetty, M.T. Louie, and M.V. Subramanian, Microbial Transformations of Natural Products, Phytochemistry and pharmacognosy, Encyclopedia of life support systems.

25.     Mohamed,S. Mervat, Degradation of methomyl by the novel bacterial strain Stenotrophomonas maltophilia M1, Electronic Journal of Biotechnology, 12 ()2009.

26.     Naama Shlomovitch, Miryam Bar Matthews, Amit  Segev, and Alan Matthews,  Sedimentary and epigenetic copper mineral assemblages in the Cambrian Timna Formation, southern Israel, Isr. J. Earth Sci., 48,  p.195–208, 1999.

27.     J.E. Bailey, and D.F. Ollis,  Biochemical Engineering Fundamentals, McGraw-Hill, New York, 1986.

28.     E.H. Battley,  Energetics of Microbial Growth, Wiley, NewYork, 1987.

29.     P.L. McCarty,  Stoichiometry of biological reactions, , Prog. Water Technol., 7, pp.157-172.


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9.

Authors:

Christy James Jose, Jijo Francis, Rajasree M.S

Paper Title:

Digraph Approximation with an Adaptation Technique for Mobile User Authentication through Keystroke Dynamics

Abstract: Mobile devices have evolved at a proliferating rate and are now used in almost all aspects of life. With these the ability to store potentially private or sensitive information on these devices has also increased. Hence an intrusion detection and prevention system is a necessity for preserving the confidentiality and integrity of users. Keystroke dynamics which refers to detailed typing pattern of a person is used to model user behavior and use the so formed footprint for user identification and intrusion detection. A neural network based system using monograph and digraph timings with digraph approximation and adaptation technique is proposed for keystroke dynamics in mobile devices for free text data.  With adaptation mechanism, the missing monographs and digraphs and also the time bound variations of user keystroke time variations are captured and adapted. The combined use of digraph approximation and adaptation yields a False Acceptance Rate (FAR) and False Rejection Rate (FRR) of 0% for 22 users. The impact of adaptation on other performance measures like accuracy, specificity, sensitivity and Mean Square Error(MSE) is also studied.

Keywords:
 Keystroke Dynamics, Intrusion Detection, Adaptation Mechanism, Keystroke Authentication

References:

1.           G. O. Young, “Synthetic structure of industrial plastics (Book style with paper title and editor),”  in Plastics, 2nd ed. vol. 3, J. Peters, Ed.  New York: McGraw-Hill, 1964, pp. 15–64.
2.           Canalys, “Smart phones overtake client PCs in 2011”, http://www.canalys.com/newsroom/smart-phones-overtakeclient-pcs-2011 , Feb. 2012.

3.           Kruegel, Christopher, Fredrik Valeur, and Giovanni Vigna, “Intrusion detection and correlation: challenges and solutions”, Vol. 14, Springer Science & Business Media, 2005.

4.           Clarke, Nathan L., and Steven M. Furnell. "Authentication of users on mobile telephones–A survey of attitudes and practices." Computers & Security 24, no. 7 (2005): 519-527.

5.           Boatwright, Michelle, and Xin Luo. "What do we know about biometrics authentication?." In Proceedings of the 4th annual  conference on Information security curriculum development, p. 31. ACM, 2007.

6.           Gaines, R. Stockton, William Lisowski, S. James Press, and Norman Shapiro. “Authentication by keystroke timing: Some preliminary results”, No. RAND-R-2526-NSF. RAND CORP SANTA MONICA CA, 1980.

7.           Deutschmann, Ingo, Peder Nordstrom, and Lina Nilsson. "Continuous authentication using behavioral biometrics." IT Professional 15, no. 4 (2013): 12-15.

8.           Monrose, Fabian, and Aviel Rubin. "Authentication via keystroke dynamics." In Proceedings of the 4th ACM conference on Computer and communications security, pp. 48-56. ACM, 1997.

9.           Robinson, John, Vicky M. Liang, J. Chambers, and Christine L. MacKenzie. "Computer user verification using login string keystroke dynamics." Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on 28, no. 2 (1998): 236-241.

10.        Monrose, Fabian, and Aviel D. Rubin. "Keystroke dynamics as a biometric for authentication." Future Generation computer systems 16, no. 4 (2000): 351-359.

11.        Ahmed A. Ahmed and Issa Traore, "Biometric Recognition based on free-text Keystroke Dynamics", IEEE transactions on cybernetics, vol. 44, no. 4, April 2014, 458-472.

12.        Araújo, Lívia CF, Luiz HR Sucupira, Miguel Gustavo Lizarraga, Lee Luan Ling, and João Baptista T. Yabu-Uti. "User authentication through typing biometrics features." Signal Processing, IEEE Transactions on 53, no. 2 (2005): 851-855.

13.        Campisi, P., E. Maiorana, M. Lo Bosco, and A. Neri. "User authentication using keystroke dynamics for cellular phones." Signal Processing, IET 3, no. 4 (2009): 333-341.

14.        Pedernera, Gissel Zamonsky, Sebastian Sznur, Gustavo Sorondo Ovando, Sebastían García, and Gustavo Meschino. "Revisiting clustering methods to their application on keystroke dynamics for intruder classification." In Biometric Measurements and Systems for Security and Medical Applications (BIOMS), 2010 IEEE
Workshop on, pp. 36-40. IEEE, 2010.

15.        Obaidat, M. S., and D. T. Macchairolo. "A multilayer neural network system for computer access security." Systems, Man and Cybernetics, IEEE Transactions on 24, no. 5 (1994): 806-813.

16.        Obaidat, Mohammad S., and Balqies Sadoun. "Verification of computer users using keystroke dynamics." Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on 27, no. 2 (1997): 261-269.

17.        Syed, Zahid, Sean Banerjee, and Bojan Cukic. "Leveraging variations in event sequences in keystroke-dynamics authentication systems." In High-Assurance Systems Engineering (HASE), 2014 IEEE 15th International Symposium on, pp. 9-16. IEEE, 2014.

18.        Chang, J. Morris, Chi-Chen Fang, Kuan-Hsing Ho, Nicholas Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen Gilbert, Ahmed E. Kamal, and Sun-Yuan Kung. "Capturing cognitive fingerprints from keystroke dynamics." IT Professional 15, no. 4 (2013): 24-28.


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10.

Authors:

Davood Kaviani, Majid Saghi, Maryam Sabonian, Mohammad Hosein Bigtan, Behzad Padidaran a

Paper Title:

Orthogonal Array Design for the Optimization of Solvent-Assisted Dispersive Solid Phase Extraction for the Determination of Copper Ions in Water and Vegetable Food Samples using Flame Atomic Absorption Spectrometry

Abstract: A simple and efficient dispersive solid -phase micro extraction technique was developed and combined with flame atomic absorption spectrometry, for the extraction and determination of trace amounts of copper in real samples.2-(5Bromo-2-pyridylazol)-5-(diethyl amino)-phenol (5-Br-PADAP) was used as chelating agent and banzophenon was selected as extraction solvent. Several possible influential factors such as the type and amount of extraction solvent, amount of autistic agent, sample pH, were optimized using orthogonal array design (OAD) with OA16(4)5 matrix. Under optimum conditions, an enrichment factor of 13 was obtained. The analytical curves were linear between 5-2000 μg L-1. Based on three SD of the blank, the detection limits was 1.2 μg L-1. The relative SDs for eight replicate measurements of 100 μg L-1 of metal ions was 3.2%. The proposed method was successfully applied for determination of copper in environmental waters and some vegetable samples including Pepper, Tomato, Thyme, Aloe vera gel, Morus.

Keywords:
Solvent-assisted dispersive solid phase extraction, Copper (II), Flame atomic absorption spectrometry, Food and environmental water samples.

References:

1.           C.L. Arthur, Pawliszn, Anal. Chem., 62 (1990) 2145.
2.           J. Pawlyszyn, Anal. Chem., 75 (2003) 2543.

3.           J. Pawlyszyn, Anal. Chem., 75 (2003) 2543.

4.           S.B. Hawthorne, Anal. Chem., 62 (1990) 633 A.

5.           Robert L. Grob, Eugene F. Barry, Modern practice of gas chromatography, Fourth edition, John Wiley & Sons, Inc, 2004.

6.           J.L.Manzoori , A.Bavili.Tabrizi , J.Anal.Chem. , 470(2002) 2150.

7.           M. A, Jeannot. F.F. Cantwell, Anal. Chem., 71 (1999) 388.

8.           Y. He, H.K. Lee, Anal. Chem, 69 (1997) 4634.

9.           H. Lui, P.K. Dasgupta, Anal. Chem, 68 (1996) 1817.

10.        M.A, Jeannot. F.F. Cantwell, Anal. Chem., 68 (1996) 2236.

11.        H. Lord, J. Pawlyszyn, J. Chromatogr, A 902 (2000) 17.

12.        M. A, Jeannot. F.F. Cantwell, Anal. Chem., 70 (1999) 3912.

13.        Francisco Pena-Pereir, Isela Lavill, Carlos Bendicho, Miniaturized preconcentration methods based on liquid–liquid extraction and their application in inorganic ultratrace analysis and speciation: A review, Spectrochimica Acta Part B 64 (2009) 1–15.

14.        Zhefeng Fan, Xuejuan Liu, Determination of methylmercury and phenylmercury in watersamples by liquid–liquid–liquid microextraction coupledwith capillary electrophoresis, Journal of Chromatography A, 1180 (2008) 187–192.

15.        YanLiu,Yuki Hashi, Jin-Ming Lin,Continuous-flow icroextraction and gas romatographic –massspectrometricdetermination of polycyclic aromatichydrocarbon compounds in water, Analytica Chimica Acta 585 (2007) 294–299.

16.        H. Kataoka, H.L. Lord, J. Pawlyszyn, J. Chromatogr., A 880 (2000) 35.

17.        M .Otto, Chemoetrics:Statistical andcomputer Application in Analytical Chemistry ,Johnwiley ,Newyork,1999.

18.        K.Goto,Y.Fukue.H.Watanabe,Talanta ,24(1977)752.

19.        H.Watanabe,H.Talanta, 25(1978)585.

20.        H.Watanabe,Solution behavior of surfactants,Plenmun Press, New York, USA, 1982.

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22.        Y.Wang, Y.C. Kwok, Y. He, H.K. Lee, Anal. Chem., 70 (1998) 4610.

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24.        M. A, Jeannot. F.F. Cantwell, Anal. Chem., 71 (1999) 388.

25.        W. Liu, H.K . Lee. Anal. Chem., 72 (2000) 4462.

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27.        Przyjazny, J.M. Kokosa, J. Chromatogr., A 977 (2002) 143.


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11.

Authors:

Davood Kaviani, Majid Saghi, Maryam Sabonian, Mohammad Hosein Bigtan, Behzad Padidaran a

Paper Title:

Performance and Emission Characteristics of CI Engine Operated with Waste Cooking oil Methyl-Ester and Diesel Blends

Abstract: Biodiesel from bio-oils are considered as the promising renewable alternative fuel for CI engine. However the damped waste cooking oil poured in the earth is one of the contributors of water and environmental pollution. In this study, biodiesel from waste cooking oil (WCO) is produced by transesterification reaction and blended with diesel fuel (B10, B20, B30, B40, B50). These blends were tested in single cylinder, 4-stroke, water cooled  CI engine at different loads with 1500rpm constant engine speed to evaluate the performance and emission characteristics. Performance study contains brake thermal efficiency, specific fuel consumption while emission study consider NOx, CO, CO2 emission. During experimentation it was found that an increase of load leads to increase of brake thermal efficiency and decrease in specific fuel consumption. It was also observed that the results using biodiesel have similar characteristics to that of diesel. The NOx emission increases as load increases, while CO emission decreases for B10, B20 as blending increases.CO follows the trend similar to that of diesel. Also CO2 emission increases at partial and medium loading condition.

Keywords:
 Waste cooking oil, waste cooking oil methyl ester, transesterification, emission

References:

1.        .C.Meher,D. VidyaSagar, S.N. Naik, “Technical aspects of biodiesel production by transesterification”,  Renewable and Sustainable Energy Reviews, 10 (2006) 248–268.
2.        Y. Zhang, M.A. Dube, D.D. McLean, M. Kates, “Biodiesel production from waste cooking oil:  2.Economic assessment and sensitivity analysis, Bioresour”, Technol. 90 (2003) 229–240.

3.        Ozer Can, “Combustion characteristics, performance and exhaust emissions of a diesel engine   fueled with a waste cooking oil biodiesel mixture”,  Energy Conversion and Management, 11/2014; 87:676-686.

4.        K. Hamasaki, E. Kinoshita, H. Tajima, K. Takasaki, D. Morita, “Combustion characteristics of diesel engines with waste vegetable oil methyl ester, The fifth International Symposium on Diagnostics and Modeling of Combustion in Internal Combustion Engines” , (COMODIA), 2001, pp. 410–416.

5.        S. Pehan, M. Jerman, M. Kegl, B. Kegl, “Biodiesel influence on tribology characteristics of a   diesel engine”, Fuel 88 (2009) 970–979.

6.        R. Dinkov, G. Hristov, D. Stratiev, V. Aldayri, “Effect of commercially available antioxidants over biodiesel/diesel blends stability”,  Fuel 88(2009) 732–737.

7.        MaginLapuerta, Jose Rodriguez-Fernandez, John R. Agudelo, “Diesel particulate emissions from used cooking oil biodiesel”,  Bioresource Technology, Volume 99, Issue 4 March (2008), PP 731-740

8.        Zafer Utlu , and Mevlüt Süreyya Koçak, “The effect of biodiesel fuel obtained from waste frying oil on direct injection diesel engine performance and exhaust emissions”, Renewable Energy , Volume 33, Issue 8, August (2008), PP: 1936-194.

9.        Drapcho C, Nghiem J, Walker T., “ Biofuels engineering  process technology”,  New York: McGraw-Hill Professional; 2008.

10.     Jagannath Hirkude, Atul S. Padalkar, “ Experimental investigation of the effect of compression ratio on performance and emissions of CI engine operated with waste fried oil methyl ester blend”, Applied Energy 2012, 90: 68-72.

11.     Abu-Jrai, Jehad A. Yaminb, Alaa H. Al-Muhtaseb, Muhanned A. Hararaha, “Combustion characteristics and engine emissions of a diesel engine fueled with diesel and treated waste cooking oil blends”, Chemical Engineering Journal, 172:129-136.

12.     Joonsik Hwang, Donghui Qi, Yongjin Jung, ChoongsikBae, “Effect of injection parameters on the combustion and emission characteristics in a compression ignition engine fueled with waste cooking oil biodiesel”,  Fuel 109 (2013.7) 616-626.

13.     H. An, W.M. Yang, J. Li, S.K. Chou, K.J. Chua, “Performance, combustion and emission characteristics of biodiesel derived from waste cooking oil”, Applied Energy 112, 493-499, 2013.

14.     SukumarPuhan, N. Vedaraman, G. Sankaranarayanan, V. Boppana, Bharat Ram, “Performance and emission study of Mahua oil (Madhucaindica oil) ethyl ester in a 4-stroke natural aspirated direct injection diesel engine”,  Renewable Energy 30 (2005) 1269–1278.

15.     A.A. Reefat, N.K. Attia, H.A. Sibak, S.T. Sheltawy, G.I. Diwani, “Production optimization and quality assessment of biodiesel from waste vegetable oil”,  International Journal of Environmental Science and Technology 5 (2008) 75–82.

16.     Ma F, Hanna MA, “Biodiesel production: a review”,  Bioresour Technol 1999;70:1–15.

17.     Palash SM, Masjuki HH, Kalam MA, Masum BM, Sanjid A,  Abedin MJ,  “State of the art of NOx mitigation technologies and  their effect on the performance and emission characteristics of biodiesel-fueled compression ignition engines”,  Energy Conversion and  Management 2013;76:400–20.

18.     Rakopoulos CD, Antonopoulos KA, Rakopoulos DC, “Multi-zone modeling of diesel engine fuel spray development with vegetable oil, bio-diesel or diesel fuels”,  Energy Conversion and  Management 2006;47:1550–73.

19.     Mueller CJ, Boehman AL, Martin GC “ An experimental investigation of theorigin of increased NOx emissions when fueling a heavy-duty compression–ignition engine with soybiodiesel”,  SAE Paper 2009:01–1792.
20.     Majewski WA, Khair MK, “Diesel emissions and their control” Warrendale(USA): SAE International; 2006.

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12.

Authors:

Jagadishchandra S. Naik, N. K. Misra

Paper Title:

Interactive Terrain Surface Visualization using Haptics Assisted Display

Abstract: In this paper we present a novel method to handle terrain surface features using haptic feedback providing interaction for the purpose of navigation of terrain over a virtual 3D environment. This system uses Phantom Haptics Desktop Device for touch bound interactions using force feedback stylus, which acts as a pointer that allows the user to feel the deformations over the terrain surface. The advantage of haptic feedback is that it works in 3D environment and provides better control with the force compared to mouse and other hardware.

Keywords:
 Haptics Visualization, Navigation, Terrain classification.

References:

1.        , HU, LAHAMY and LICHTI, et al, “Haptic and Gesture-Based Interactions for Manipulating Geological Datasets”  Web: www.uqac.ca/bamenela/papers
2.        ALLISON M. OKAMURA and MARK R. CUTKOSKY, et al, “Haptics Exploration of Fine Surface Features” Web: www-cdr.stanford.edu/html/Touch/publications

3.        BENES, DORJGOTOV, ARNS, BERTOLINE, et al, “Granular Material Interactive Manipulation: Touching Sand with Haptic Feedback” WSCG 2006 conference proceedings, January 30-February 3, Plzen, Czech Republic.

4.        PURCHART, KOLIGEROVA, BENES, et al, “Interactive Sand covered Terrain Surface Model with Haptic Feedback” GIS Ostrava 2012-Surface Models for Geosciences, January23-25.,2012 Ostrava

5.        FAETH, OREN, HARDING, et al, “Combining 3-D geovisualization with force feedback driven user interaction”  Web: www.vrac.iastate.edu/

6.        LECUYER, BURCHARDT, ETIENNE et al,” Feeling Bumps and Holes without a Haptic Interface: the Perception of Pseudo-Haptic Textures” Web: people.rennes.inria.fr/Anatole.Lecuyer/

7.        YOO, JUNG, ROEMMERMANN, RAST, KIRCHNER,ROSSMAN, et al, ”Developing a Virtual Environment for Extraterrestrial Legged Robot with Focus on Lunar Crater Exploration”  i-SAIRAS 2010 August 29-September 1, 2010, Sapporo, Japan

8.        EL-SANA, VARSHNEY, et al, “Continuously-Adaptive Haptic Rendering” Web: wwwold.cs.umd.edu/gvil/papers/

9.        YANNIER, BASDOGAN, TASIRAN and SEN, et al,” Using Haptics to Convey Cause and Effect Relations in Climate Visualization” IEEE Transactions on Haptics Web: network.ku.edu.tr/~stasiran/publications/

10.     NEWCOMB,  et al, A Masters thesis on “A multi-modal interface for road planning tasks using vision, haptics and sound “, 2010

11.     THOMSON, et al, A Doctoral thesis on” The Integration of Visual and Haptic Feedback for Teleoperation” 2001

12.     TSETSERUKOU, KAWAKAMI, TACHI, et al, “iSoRA: Humanoid Robot Arm for Intelligent Haptic Interaction with the Environment”, Advanced Robotics 23 (2009) 1327–1358

13.     SRIKANTH, MATHIAS, NATARAJAN, NAIDU, et al, “Visibility Volumes for Interactive Path Optimization” Web: vgl.serc.iisc.ernet.in/

14.     JORRISEN, BOECK, LAMOTTE, et al,” Bringing haptics and physical simulation together: haptic travel through physical worlds” Computer Animation And  Virtual Worlds Comp. Anim. Virtual Worlds 2006; 17: 179–187 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cav.121


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13.

Authors:

Harsh Deep, Varsha

Paper Title:

Tabu Search Based General Self-Organized Tree-Based Energy-Balance Routing Protocol (GSTEB) for Wireless Sensor Networks

Abstract: GSTEB has shown quite necessary results over the on the market WSNs protocols. but it's neglected many issues. thus on beat the constraints of the sooner work a completely unique improved technique is planned throughout this analysis work. The planned technique has the flexibility to beat the constraints of the GSTEB routing protocol by pattern clump and TABU search. The comparison square measure drawn among the current and planned techniques. The comparisons has clearly shown that the planned technique outperforms over the on the market techniques. The experimental results has shown an 20.37% improvement in network time period

Keywords:  GSTEB, PASCCC, WIRELESS SENSOR NETWORK ,TABU SEARCH .

References:

1.           Tang, ShaoJie, et al. "DAWN: energy economical information aggregation in WSN with mobile sinks." Quality of Service (IWQoS), 2010 eighteenth International Workshop on. IEEE, 2010.
2.           Xibei, Jia, Zhang Huazhong, and Zhang Jingchen. "Research of knowledge aggregation routing protocol in wsn data-related applications." computing and data Technology (ICCSIT), 2010 third IEEE International Conference on. Vol. 1. IEEE, 2010.

3.           Bista, Rabindra, Kim Hee-Dae, and Jae-Woo Yangtze River. "A new personal information aggregation theme for wireless device networks." laptop and data Technology (CIT), 2010 IEEE tenth International Conference on. IEEE, 2010.

4.           Xiao, Haitao, et al. "The health observation system supported distributed information aggregation for WSN employed in bridge identification." SICE Annual Conference 2010, Proceedings of. IEEE, 2010.

5.           Zanjani, Motahareh Bahrami, Reza Monsefi, and Arash Boustani. "Energy efficient/highly secure information aggregation technique victimisation tree-structured orthogonal codes for Wireless device Networks." code Technology and Engineering (ICSTE), 2010 second International Conference on. Vol. 2. IEEE, 2010.

6.           Hasenfratz, David, et al. "Analysis, comparison, and improvement of routing protocols for energy harvest wireless device networks." device Networks, Ubiquitous, and Trustworthy Computing (SUTC), 2010 IEEE International Conference on. IEEE, 2010.

7.           Raju, G. T., et al. "Wireless device network time period improvement." Advances in Recent Technologies in Communication and Computing (ARTCom 2011), third International Conference on. IET, 2011.

8.           Zhu, Liehuang, and Meng Li. "An energy economical and integrity-preserving aggregation protocol in wireless device networks." Performance Computing and Communications Conference (IPCCC), 2011 IEEE thirtieth International. IEEE, 2011.

9.           Nie, Pin, and Bo Li. "A cluster-based information aggregation design in WSN for structural health observation." Wireless Communications and Mobile Computing
Conference (IWCMC), 2011 seventh International. IEEE, 2011.

10.        Chu, Hung-Chi, et al. "Design ANd implementation an energy-aware routing mechanism for star wireless device networks." High Performance Computing and Communications (HPCC), 2011 IEEE thirteenth International Conference on. IEEE, 2011.

11.        Mathapati, Basavaraj S., Siddarama R. Patil, and V. D. Mytri. "Energy economical Reliable information Aggregation Technique for Wireless device Networks."Computing Sciences (ICCS), 2012 International Conference on. IEEE, 2012.

12.        Tamilselvan, G. M., and S. Kiruthika. "An energy economical information aggregation primarily based medium access management protocol victimisation centre at nearest supply approach for device networks during a lattice topology." Computing, Communication and Applications (ICCCA), 2012 International Conference on. IEEE,
2012.

13.        Eu, Zhi Ang, and Hwee-Pink Tan. "Adaptive expedient routing protocol for energy harvest wireless device networks." Communications (ICC), 2012 IEEE
International Conference on. IEEE, 2012.

14.        Mantri, Dnyaneshwar, Neeli Rashmi Prasad, and Ramjee Prasad. "BHCDA: information measure economical heterogeneousness aware cluster primarily based information aggregation for Wireless device Network." Advances in Computing, Communications and science (ICACCI), 2013 International Conference on. IEEE, 2013.

15.        Said, Adel Mounir Sareh, et al. "Dynamic aggregation protocol for wireless device networks." Advanced info Networking and Applications (AINA), 2013 IEEE twenty seventh International Conference on. IEEE, 2013.

16.        Wu, Yin, and Wenbo Liu. "Routing protocol supported genetic algorithmic program for energy harvesting-wireless device networks." IET Wireless device Systems3.2 (2013): 112-118.

17.        Mantri, Dnyaneshwar, Neeli R. Prasad, and Ramjee Prasad. "Grouping of clusters for economical information aggregation (GCEDA) in wireless device
network."Advance Computing Conference (IACC), 2013 IEEE third International. IEEE, 2013.

18.        Hooman Ghaffarzadeh and Ali Doustmohammadi , “Two-phase information traffic improvement of wireless device networks for prolonging network lifetime”, 2013.

19.        Han, Zhao, Jie Wu, Jie Zhang, Liefeng Liu, and Kaiyun Tian. "A General Self-Organized Tree-Based Energy-Balance Routing Protocol for Wireless device Network." (2014)


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14.

Authors:

Saloni Bindra,     Priyanka Karmarkar, Abhishek Kumar Verma, Laxmi Grover

Paper Title:

Social Media Mining for Opinion Analysis

Abstract: Here we describe a method which involves determining the sentiment of a review about Banks by extracting the phrases with a noun-adjective relationship, Identifying if the noun is present in the domain specific Ontology tree and then determining the polarity of the adjective, aggregating the polarity. The results so obtained are thus summarized and then categorized by characteristic feature pertaining to the Bank. This reduces the human efforts to go through them and a result specific to a particular Bank; sub-categorized by Peculiar features of it with polarity alongside each individual characteristic. Thus the fruits of the reviews are gained even without reading them.

Keywords:
Sentiment, Polarity, Domain Ontology, Opinion Mining.

References:

1.           Bing Liu, “Sentiment Analysis and Opinion Mining”, Morgan & Claypool Publishers, May 2012.
2.        WeiWei, Jon Atle Gulla,” Sentiment Learning on Product Reviews via Sentiment Ontology Tree”, Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 404–413, Uppsala, Sweden, 11-16 July 2010.

3.        Vipin Kumar,  Sonajharia Minz, ” Mood Classification of Lyrics using SentiWordNet”, 2013 International Conference on Computer Communication and Informatics (ICCCI - 2013), Jan. 04 – 06, 2013, Coimbatore, INDIA

4.        “Stanford typed dependencies manual”, Marie-Catherine de Marne_e and Christopher D. Manning, September 2008.

5.        Zhongchao Fei,Xuanjing Huang, and Lide wu, “Mining the Relation between Sentiment Expression and Target Using Dependency of Words”, Department of Computer Science and Technology, Fudan University, Shanghai, 200433, China.

6.        “Reviews” [online] Available         http://www.mouthshut.com/

7.        SentiWordNet”[online]Availablehttp://sentiwordnet.isti.cnr.it

8.        PDFforOWL”Available http://protege.stanford.edu/plugins/owl/publications/DL2004-protege.owl.pdf

9.        “Customer sentiment on bank” Shalu Chopra, Deepshikha Chaturvedi.

10.        Sentiment strength detection in Informal Texts, Thelwall, M., Buckley, K., Paltoglou, G. Cai, D., & Kappas, A. (2010).


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15.

Authors:

Praveen S S, Aparna P R

Paper Title:

Single Digital Image Multi-focusing Using Point to Point Blur Model Based Depth Estimation

Abstract: The proposed paper focuses on Multi-focusing, a technique that restores all-focused images from defocused ones and generates images focused at different depths. The method proposed in the paper can be applied to images taken with an ordinary camera and does not require any specialized hardware. The method deviates from the existing de-convolution process for obtaining multi-focused images and highlights procuring a focused image by using only a single image. Blur map estimation is the core of the proposed method. Initially, a rough blur map is obtained which gives the blur amount at edge locations and by propagating the blur amount at edge locations to the entire image, the full blur map of the scene can be recovered. In order to produce photographs at different depths, a depth map is required. Since the amount of blur is proportional to the distance from the plane of focus, the blur map can be used as a cue for depth. The depth map is calculated using the blur map and the camera parameter information embedded in the defocused image. Using the depth map, multi-focused images can be obtained.

Keywords:
 Multi-focusing, Depth estimation, blur estimation

References:

1.        Y. Cao, S. Fang, and Z. Wang “Digital Multi-Focusing From a Single Photograph taken with an Uncalibrated Conventional Camera”, IEEE Trans. on image processing, vol. 22, no. 9, Sept. 2013
2.        S. Zhuo and T. Sim, “Defocus map estimation from a single image,” Pattern Recognit., vol. 44, no. 9, pp. 1852–1858, 2011.

3.        S. W. Hasinoff and K. N. Kutulakos, “Confocal stereo,” Int. J. Comput. Vis., vol. 81, no. 1, pp. 82–104, 2009.

4.        Levin, D. Lischinski, and Y. Weiss, “A closed form solution to natural image matting,” in Proc. IEEE Comput. Soc. Conf. CVPR, Jun. 2006, pp. 61–68.

5.        V. P. Namboodiri and S. Chaudhuri, “Recovery of relative depth from a single observation using an uncalibrated (real-aperture) camera,” in Proc. CVPR, Jun. 2008, pp. 1–6.

6.        A. Saxena, M. Sun, and A. Ng, “Make3D: Learning 3-D scene structure from a single still image,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 5, pp. 824–840, May 2009.


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Authors:

Bharti Nagpal, Manoj Kumar, Priyank Pandey, Sonakshi Vij, Vaishali

Paper Title:

Minutiae vs. Correlation: Analysis of Fingerprint Recognition Methods in Biometric Security System

Abstract: Identification and verification of a user’s identity in an organization is a big challenge. Earlier, it was done through passwords that had various limitations for example it could be cracked or stolen. Biometric technology has replaced all the existing technologies with greater advantage. Fingerprint technique, so far, is recognised as a better technique than others and is widely used. It provides accurate results and has less false rate as compared to other techniques. This paper aims to analyse the two main methods of fingerprint recognition in biometric security systems which are minutiae based and correlation based methods. An analysis of these two has been summarized and it shows the pros and cons of both the methods, with respect to factors such as computational power, poor quality image evaluation etc. The paper concludes all the features of both these methods and explains the process followed by them

Keywords:
 biometric system, correlation based fingerprint, minutiae based.

References:

1.        K. Mali and S. Bhattacharya, “Comparative study of different biometric features”, international journal of advanced research in computer and communication engineering (IJARCCE) Vol. 2, Issue 7, 2013.
2.        M Kaur, M Singh, A Girdhar and P.S sandhu, “Fingerprint verification system using minutiae extraction technique”, published at world academy of science engineering and technology, issue 46, 2008.

3.        T.Y Jea and V Govndaraaju, “A minutia-based partial fingerprint recognition system”, published at Elsevier in pattern recognition issue, 2005.

4.        J Ravi, K Raja and K. R venugopal, “fingerprint recognition using minutia score matching”, international journal of engineering science and technology, vol. 1,issue 2, 2009.

5.        P Verma, M dubey and P verma, “Correlation based method for identification of fingerprint- A biometric approach” international journal of engineering and advanced technology (IJEAT), vol. 1, issue 4, 2012.

6.        A.M. Bazen, G. T. B Verwaaijen and S.H Gerez et al, “A correlation based fingerprint verification system”, published at Proceedings of the ProRIsc, IEEE workshop, 2000.


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17.

Authors:

Anwar Al-Shrouf

Paper Title:

Noise-Immune ECG Classifier Using Wavelet Transform and Neural Networks

Abstract: This paper proposes a novel algorithm for automatic classification of electrocardiogram (ECG) beats recorded by Holter systems. The algorithm is based on a combination of neural network and discrete wavelet transform. Discrete wavelet transform coefficients are used as an input of the neural network to perform the classification task. The proposed classifier wastested by both real ECG signals andartificially generated signals. Five Hermite functionswereused in generating the ECG artificial testing signals. Different levels of noise were added to the signals to examine the noise immunity of the classifier. The main advantage of the proposed classifier is that it is noise immune and accurate. The testing results on the proposed classier show that it is capable of recognising 40 beats, and it works properly in the classification of the ECG signal with a classification ratio of 100% for an SNR of more than 6 dB.

Keywords:
Wavelet transforms, neural networks, ECG beat classification, arrhythmia, white noise, Hermite functions.

References:

1.           M. Hadhoud, M. Eladawy, A. Farag, “Computer aided diagnosis of cardiac arrhythmias,” in IEEE Int. Conf. Computer Engineering and Systems, 2006, pp. 262–265.
2.           R. J. Martis, U. R. Acharya, and L. C. Min, “ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform,” Biomed. Signal Process. Control, vol. 8, no. 5, pp. 437–448, 2013.

3.           P. D. C. P. De Chazal, M. O’Dwyer, and R. B. Reilly, “Automatic classification of heartbeats using ECG morphology and heartbeat interval features,” IEEE Trans. Biomed. Eng., vol. 51, no. 7, pp. 1196–1206, 2004.

4.           H. M. Rai, “ECG Signal Classification using Wavelet Transform and Back Propagation Neural Network,” vol. 3, pp. 212–215.

5.           V. Dubey and V. Richariya, “A Neural Network Approach for ECG Classification,” vol. 3, no. 10, pp. 189–196, 2013.

6.           G. K. Jaiswal and R. Paul, “Artificial neural network for ecg classification,” vol. 6, no. 1, pp. 36–38, 2014.

7.           R. E. Klabunde, “Cardiovascular Physiology Concepts.” [Online]. Available: http://www.cvphysiology.com/Arrhythmias/A009.htm.
8.           X. Tang and L. Shu, “Classification of Electrocardiogram Signals with RS and Quantum Neural Networks,” vol. 9, no. 2, pp. 363–372, 2014.
9.           S. Osowski and T. H. Linh, “ECG beat recognition using fuzzy hybrid neural network,” IEEE Trans. Biomed. Eng., vol. 48, pp. 1256–1271, 2001.

10.        M. R. Risk, J. F. Jamil F. Sobh, and J. P. Saul, “Beat Detection and Classification of ECG Using Self Organizing Maps,” in 19th International Conference of the IEEE Engineering in Medicine and Biology, 1997, pp. 89–91.

11.        Z. Frankiewicz and A. AL-Shrouf, “ECG Beat Classification Using Linear Prediction Error Signal,” in Medical Informatics Europe, 1991, pp. 465–470.

12.        M. Javadi, S. A. A. A. Arani, A. Sajedin, and R. Ebrahimpour, “Classification of ECG arrhythmia by a modular neural network

13.        based on Mixture of Experts and Negatively Correlated Learning,” Biomed. Signal Process. Control, vol. 8, no. 3, pp. 289–296, 2013.

13.

14.        S. M. Ahmed, A. Al-Shrouf, and M. Abo-Zahhad, “ECG data compression using optimal non-orthogonal wavelet transform,” Med. Eng. Phys., vol. 22, no. 1, pp. 39–46, 2000.

15.        S. Mallat, “Theory of multiresolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 2, pp. 674–693, 1989.

16.        Al-Shrouf, M. Abo-Zahhad, and S. M. Ahmed, “A novel compression algorithm for electrocardiogram signals based on the linear prediction of the wavelet coefficients,” Digit. Signal Process., vol. 13, no. 4, pp. 604–622, 2003.

17.        M. S. Hossain, “ECG Signal Compression using Energy Compaction Based Thresholding of the Wavelet Coefficients,” vol. 1, no. 2, pp. 14–18, 2011.

18.        S.-L. Hung, C. S. Huang, and C. M. Wen, “13 th World Conference on Earthquake Engineering,” no. 2580, 2004.

19.        Khaing and Z. Naing, “Quantitative Investigation of Digital Filters in Electrocardiogram with Simulated Noises,” Int. J. Inf. Electron. …, vol. 1, no. 3, pp. 210–216, 2011.

20.        G. Bortolan, I. Christov, I. Simova, and I. Dotsinsky, “Noise processing in exercise ECG stress test for the analysis and the clinical characterization of QRS and T wave alternans,” Biomed. Signal Process. Control, vol. 18, pp. 378–385, 2015.

21.        J. Wang, Y. Ye, X. Pan, and X. Gao, “Parallel-type fractional zero-phase filtering for ECG signal denoising,” Biomed. Signal Process. Control, vol. 18, pp. 36–41, 2015.

22.        M. Lagerholm and G. Peterson, “Clustering ECG complexes using hermite functions and self-organizing maps,” IEEE Trans. Biomed. Eng., vol. 47, no. 7, pp. 838–848, 2000.

23.        Gil, G. Caffarena, G. M. David, and A. Otero, “Hermite Polynomial Characterization of Heartbeats with Graphics Processing Units,” 2014.

24.        T. Kohonen, K. Makisara, O. Simula, and J. Kangas, “Self-organizing maps: Optimization approaches,” Artif. Neural Networks, pp. 981–990, 1991.

25.        M. K. Sarkaleh and A. Shahbahrami, “ClSSIFICATION OF ECG ARRHYTHMIAS USING DISCRETE WAVELET TRANSFORM AND NEURAL NETWORKS,” Int. J. Comput. Sci. Eng. Appl., vol. 2, no. 1, pp. 1–13, 2012.

26.        E. D. Ubeyli, “Implementing wavelet transform/mixture of experts network for analysis of electrocardiogram beats,” Expert Syst., vol. 25, pp. 150–162, 2008.


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18.

Authors:

Esam Elsheh, Saddek Elbendago, Marwan Ali.H.Omer

Paper Title:

On the Security of Image Encryption Using Discrete Fourier Transform and Fractional Fourier Transform

Abstract: Recent developments of different forms of discrete Fourier transform, have encouraged many researchers to design image encryption algorithms based on a discrete fractional or multiple fractional Fourier transforms. One of these algorithms is proposed by Ashutosh and Sharma, (International Journal of Engineering and Advanced Technology, Vo. 2, Issue. 4, 2013). In this paper, we show that this algorithm represents a classic textbook example of insecure cipher; all the building blocks of this scheme are linear, and thus, breaking this scheme, using a known plaintext attack, is equivalent to solving a set of linear equations. We also invalidate several of the security and performance advantages claimed by the authors, namely, the efficiency, key sensitivity, and the complexity.                  

Keywords:
 Image processing, encryption, discrete transforms, linear cipher.


References:

1.        H.M. Ozaktas and D. Mendlovic, “Fractional Fourier transforms and their optical implementation,” Journal of the Optical Society of America A: Optics and Image Science, and Vision. vol. 10, no. 12, pp. 2522-2531, 1993.
2.        B. Zhu, S. Liu and Q. Ran, “Optical image encryption based on multifractional Fourier transforms,” Opt. Lett., vol. 25, pp. 1159-1161, 2000.

3.        Z. Liu and S. Liu, “Random fractional Fourier trans form,” Opt. Letters., vol. 32, pp. 2088-2090, 2007.

4.        R. Tao, J. Lang and Y. Wang, ”Optical image encryption based on the multiple-parameter fractional Fourier transform,” Opt. Letters., vol. 33, pp. 581-583, 2008.

5.        R. Ashutosh and D. Sharma, “Image Encryption Using Discrete Fourier Transform and Fractional Fourier Transform,” International Journal of Engineering and Advanced Technology, vol. 2, no. 4, 2013.

6.        B. W. Dickinson and K. Steiglitz, “Eigenvectors and functions of the discrete Fourier transform,” IEEE Trans. Acoust., Speech, Signal Process., vol. ASSP-30, no. 1, pp. 25–31, 1982.

7.        S.C. Pei and W.L. Hsue “The Multiple-Parameter Discrete Fractional Fourier Transform,” IEEE Signal Processing Letters, vol. 13, no.. 6, 2006.

8.        B. Schneier, Applied Cryptography, 2nd edition. New York,Wiley, 1996.

9.        Menezes, P. van Oorschot and S. Vanstone, Handbook of Applied Cryptographic Research. Boca Raton, FL: CRC, 1996.

10.     R. Ashutosh and D. Sharma, “Robust Technique for Image Encryption and Decryption Using Discrete Fractional Fourier Transform with Random Phase Masking,”
Procedia Technology, vol. 10, pp. 707-714, 2013.

11.     A.M. Youssef, “On the Security of a Cryptosystem Based on Multiple-Parameters Discrete Fractional Fourier Transform,” Signal Processing Letters, IEEE , vol.15, no., pp.77-78, 2008.

12.     E. Elsheh, and A. Youssef, “On the security of image encryption schemes based on Multiple Parameters Transforms,” Signal Processing and Information Technology (ISSPIT), 2010 IEEE International Symposium on , pp.97-101, 2010.

13.     A.F.Webster and S.E. Tavares, “On the design of S-boxes”, Advances in Cryptology– CRYPTO ’85 (LNCS 218), pp. 523–534, 1986.

14.     National Institute of Standards and Technology, FIPS-197: Advanced Encryption Standard, November 2001.

15.     S. Babbage, C. Canniere, A. Canteaut , C. Cid, H. Gilber, T. Johansson, M. Parker, B. Preneel, V. Rijmen, and M. Robshaw: The eSTREAM Portfolio, 2009.


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Authors:

Athira R, Lekshmy D Kumar

Paper Title:

Secure Data Storage in Cloud using Centralized Access Control with Anonymous Authentication

Abstract: Cloud computing’s multi-tenancy feature which provides privacy, security and access control challenges because of sharing of physical resources among untrusted tenants. Much of the data stored in clouds is highly sensitive particularly in the case of medical records and social networks. Security and privacy are very important issues in cloud computing. In one hand, the user should authenticate itself before initiating any transaction, and on the other hand, it must be ensured that the cloud does not tamper with the data that is outsourced. User privacy is also required so that the cloud or other users do not know the identity of the user. The validity of the user who stores the data is also verified. In order to achieve safe storage, a suitable encryption technique with key management should be applied before outsourcing the data. A new decentralized access control scheme is implemented for secure data storage in clouds, which supports anonymous authentication. In this scheme, the cloud verifies the authenticity of the user without knowing the user’s identity before storing data. The scheme also has the added feature of access control in which only valid users are able to decrypt the stored information. The scheme prevents replay attacks and supports creation, modification and reading data stored in the cloud. User revocation is also addressed. Moreover, the authentication and access control scheme is decentralized and robust, unlike other access control schemes designed for clouds which are centraliz

 Keywords:  Attribute based encryption, Access control, Authentication.

References:

1.           S. Ruj, M. Stojmenovic, and A. Nayak, “Privacy Preserving Access Control with Authentication for Securing Data in Clouds,” Proc.IEEE/ACM Int’l Symp. Cluster, Cloud and Grid Computing, pp. 556-563, 2012.
2.           C. Wang, Q. Wang, K. Ren, N. Cao, and W. Lou, “Toward Secure and Dependable Storage Services in Cloud Computing,”IEEE Trans. Services Computing, vol. 5, no. 2, pp. 220-232, Apr.-June 2012.

3.           J. Li, Q. Wang, C. Wang, N. Cao, K. Ren, and W. Lou, “Fuzzy Keyword Search Over Encrypted Data in Cloud Computing,”Proc. IEEE INFOCOM, pp. 441-445, 2010.

4.           S. Kamara and K. Lauter, “Cryptographic Cloud Storage,”Proc.14th Int’l Conf. Financial Cryptography and Data Security,pp. 136-149, 2010.

5.           C. Gentry, “A Fully Homomorphic Encryption Scheme,” PhD dissertation, Stanford Univ., http://www.crypto.stanford.edu/craig, 2009.D. Chaum and E.V. Heyst, “Group Signatures,” Proc. Ann. Int’lConf. Advances in Cryptology (EUROCRYPT), pp. 257-265, 1991.

6.           H.K. Maji, M. Prabhakaran, and M. Rosulek, “Attribute-Based Signatures: Achieving Attribute-Privacy and Collusion-Resistance,”IACR Cryptology ePrint Archive, 2008.[24] H.K. Maji, M. Prabhakaran, and M. Rosulek, “Attribute-Based Signatures,” Topics in Cryptology - CT-RSA, vol. 6558, pp. 376-392,2011.

7.           Beimel, “Secure Schemes for Secret Sharing and Key Distribution,”PhD thesis, Technion, Haifa, 1996.

8.           Sahai and B. Waters, “Fuzzy Identity-Based Encryption,” Proc.Ann. Int’l Conf. Advances in Cryptology (EUROCRYPT), pp. 457-473,2005.

9.           V. Goyal, O. Pandey, A. Sahai, and B. Waters, “Attribute-Based Encryption for Fine-Grained Access Control of Encrypted Data,”Proc. ACM Conf. Computer and Comm. Security, pp. 89-98, 2006.

10.        J. Bethencourt, A. Sahai, and B. Waters, “Ciphertext-Policy Attribute-Based  encryption,” Proc. IEEE Symp. Security and Privacy, pp. 321-334, 2007.

11.        X. Liang, Z. Cao, H. Lin, and D. Xing, “Provably Secure and Efficient Bounded Ciphertext Policy Attribute Based Encryption,”Proc. ACM Symp. Information, Computer and Comm. Security (ASIACCS), pp 343-352, 2009.

12.        M. Chase, “Multi-Authority Attribute Based Encryption,” Proc.Fourth Conf. Theory of Cryptography (TCC), pp. 515-534, 2007.

13.        H. Lin, Z. Cao, X. Liang, and J. Shao, “Secure Threshold Multi-Authority Attribute Based Encryption without a Central Authority,”Proc. Progress in Cryptology Conf. INDOCRYPT), pp. 426-436,2008.

14.        M. Chase and S.S.M. Chow, “Improving Privacy and Security in Multi-Authority Attribute-Based Encryption,” Proc. ACM Conf.Computer and Comm. Security, pp. 121-130, 2009.

15.        K. Yang, X. Jia, and K. Ren, “DAC-MACS: Effective Data Access Control for Multi-Authority Cloud Storage Systems,” IACR Cryptology ePrint Archive, p. 419, 2012.

16.        A.B. Lewko and B. Waters, “Decentralizing Attribute-Based Encryption,” Proc. Ann. Int’l Conf. Advances in Cryptology (EUROCRYPT),pp. 568-588, 2011.


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20.

Authors:

Ruchal G. Humbare, Suraj R. Gurav, S. B. Trimbakeac

Paper Title:

Analysis of Heat Transfer Enhancement in Tube-in-tube Helical Coil Heat Exchangers

Abstract: The heat exchangers most widely used are shell and tube heat exchangers which are larger in size and offer lesser heat transfer rate.  Also, in shell and tube heat exchanger dead zone is produced which further reduces heat transfer rate and in order to improve heat transfer rate some active techniques are required. Helical heat exchanger is more compact, offer better heat transfer rates and heat transfer rate can be further improved by passive techniques. Its shape offers advantages such as more fluid contact, elimination of dead zones, and secondary turbulence. An experimental test rig was developed for evaluation of tube-in-tube helical coil heat exchanger. This paper deals with parametric analysis and its effect on performance of tube-in-tube helical coil heat exchanger. 

Keywords: Tube-in-tube helical coil, Dean Number, Dimensionless pitch, Curvature ratio, Effectiveness, Secondary turbulence, Heat transfer coefficient, Nusselt number.

References:

1.           B. Chinna Ankanna, B. Sidda Reddy, “Performance Analysis of Fabricated Helical Coil Heat Exchanger”, International Journal of Engineering Research, Volume 3, Issue no: Special 1, March 2014.
2.           B. S. V. S. R. Krishna, “Prediction of Pressure Drop in Helical Coil with Single Phase Flow of Non-Newtonian Fluid”, International Journal of Applied Research in Mechanical Engineering, Volume-2, Issue-1, 2012.

3.           Bibin Prasad, Sujith V, Mohammed Shaban K, Saju Haneef, Sandeep N, Vishnu Raj, “ Comparison of Heat Transfer Between a Helical and Straight tube Heat exchanger”, International Journal of Engineering Research and Technology, Volume 6, Number 1, 2013.

4.           Dr. Prabhanjan, “Influence of Coil Characteristic on Heat Transfer to Newtonian Fluids”, McGill University, Canada, August 2000.

5.           Hui Zhu, Hanqing Wang, Guangxiao Kou, “Experimental Study on the Heat Transfer Enchancement by Dean Vortices in Spiral Tubes”, International Journal of Energy and Environment, Volume 3, Issue no: Special 1, March 2014.
6.           J. S. Jayakumar, Helically Coiled Heat Exchanger, Heat Exchanger – Basics Design Applications, Dr. Jovan Mitrovic(Ed.), March 2012.
7.           James R. Lines, “Helically Coiled Heat Exchangers Offer Advantages”, Graham Manufacturing Co. Inc.

8.           M. Kannan, S. Ramu, S. Santhanakrishnan, G. Arunkumar, Vivek M., “Experimental and Analytical comparison of Heat Transfer in Double Pipe Heat Exchanger”, Internal Journal of Mechanical Engineering Applications Research, Volume 3, Issue 3, July 2012.

9.           M. Necati Ӧzisik, “Heat Transfer – a Basic Approach”,  McGraw-Hill, New York, 1985

10.        Mrunal P. Kshirsagar, Trupti J. Kansara, Swapnil M. Aher, “Fabrication and Analysis of Tube-in-tube Helical Coil Heat Exchanger”, International Journal of Engineering Research and General Science, Volume 2, Issue 3, April- May 2014.

11.        N. D. Shirgire, P. Vishwanath Kumar, “Review on Comparative Study between Helical Coil and Straight Tube Heat Exchanger”, IOSR Journal of Mechanical and Civil Engineering, Volume 8, Issue 2, August 2013.

12.        Pramod S. Purandare, Mandar M. Lele, Rajkumar Gupta, “ Parametric Analysis of Helical Coil Heat Exchanger”, International Journal of Engineering Research and Technology, Volume 1, Issue 8, October 2012.

13.        Prof. Jung Yang San, “Type of Heat Exchanger and LMTD Design Method”, Mechanical Engineering Dept, National Chung Hsing University

14.        R. Thundil Karuppa Raj, Manoj Kumar S., Aby Mathew C. and T. Elango,“ Numerical Analysis of Helically Coiled Heat Exchanger Using CFD Technique”, ARPN Journal of Engineering and Applied Sciences, Volume 9, Number 3, March 2014.
15.        Ramachandra K. Patil, B. W. Shende, Prasanta K. Ghosh, “Designing a Helical Coil Heat Exchangers”, December 1982.
16.        Ramesh K. Shah, Dušan P. Sekulić, “Fundamentals of Heat Exchangers Design”, John Wiley and Sons Inc.,2003.

17.        Sadik Kakac, Hongtan Liu “Heat Exchangers: Selection, Rating and Thermal Design”, CRC Press, Second Edition.

18.        Shinde Dijvijay D., Dange H.M., “Heat Transfer Analysis of a Cone Shaped Helical Coil Heat Exchanger”, International Journal of Innovations in Engineering and Technology, Volume 3. Issue 1, October 2013.

19.        Souyma Ranjan Mohanty, “CFD Analysis of Heat Exchanger Using Fluent”, National Institute of Technology, 2013. (M. Tech Report)

20.        Yong Ju Hong, Seong Je Park, Young-Don Choi, “A numerical Study of the Performance of a Heat Exchanger for a Miniature Joule-Thomson Refrigeration”, International Cryocooler Conference, Inc. Boulder Co., 2009.

21.        Timothy J. Rennie, “Numerical Experimental Studies of Double Pipe Helical Heat Exchanger”, Department of Bioresearch Engineering, McGill University, Montreal, August 2004.

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21.

Authors:

A. A. Elsayed

Paper Title:

Structural Behavior of High Strength Self – Compacting Concrete Beams

Abstract: This research presents an experimental and theoretical studies on the structural behavior of high strength self- compacted concrete I-beams. The main objective is to arrive the mode of failure of I beams which reinforced with and without web reinforcement. The experimental program presents the obtained results of tested eight high strength self compacting concrete I- beams specially reinforced to ensure a shear failure.  All  beams were tested simply supported along span 2400mm and subjected to four lines loadings until failure. The main variables were web thickness. The presence of web reinforcement in concrete beams increases its shear capacity and improves the ductility of the beam. Increasing the loading span to depth ratio decreased the failure load of concrete beams with web reinforcement, increasing the loading span to depth ratio decreased the failure load of concrete beams with web reinforcement, increasing (a/d) ratio from 2.4 to 2.9 led to a decrease in failure load by 33.3%. The effect of the studied variables are presented and discussed.

Keywords:
  High strength concrete; Self compacting concrete; Beams; Shear failure; Stirrups; Cracking.

References:

1.           Hajime Okamura, Masahiro Ouchi, “Self Compacting Concrete” Journal of Advanced Concrete Technology Vol. 1, No.1, 5-15, April 2008.
2.           Ahmad, S.H., Khaloo, A.R., and Poveda, A. (1986): "Shear Capacity of Reinforced High Strength Concrete Beams.”ACI J., v. 83, no. 2, Mar.-Apr. 1986, pp. 297-305.

3.           Bernhardt, C. J. and Fynboe, C. C. High strength concrete beams. Nordic Concrete Research Publication No. 5, Nordic Concrete Federation, Oslo, 1996. pp. 19-26.

4.           B. K. Teoh, M. A. Mansur, and T. H. Wee: “Behavior of High-Strength Concrete I-Beams with Low Shear Reinforcement” ACI J., V. 99, no. 3, May.-June. 2002,       pp. 299-307.

5.           Egyptian Code of Design and construction of reinforced concrete structures,        ECP-203 2010.

6.           American Concrete Institute, ACI building code requirements for reinforced concrete, ACI 318-08.

7.           British Standard BS 8110: 97 Structural use of concrete, code of practice for design and construction.

8.           Michael P. Collins, Evan C. Bentz, and Edward G. Sherwood (2008), “Where is Shear Reinforcement Required? Review of Research Results and Design Procedures”, ACI Structural Journal, Vol.105, No. 5, Sept.-Oct. 2008. pp.590-600.

9.           Ozcebe, G., Ersoy, U., and Tankut, T., Evaluation of Minimum Shear Reinforcement Requirements for Higher Strength Concrete, American Concrete Institute Structural Journal, V. 96, No. 3, May-Jun. 2009, pp. 361-368

10.        Roller, J. J. and Russell, H. G. Shear strength of high-strength concrete beams with    web reinforcement. ACI Structural Journal, Vol. 87, No. 2, March-April 1990, pp. 191-8.

11.        Thorenfeldt, E., and Drangsholt, G. (2011):" Shear Capacity of Reinforced High Strength Concrete Beams." ACI 2nd Int. Symp. on HSC, ACI SP 121.8, pp. 129-154.

12.        Youssef Choulli, Antonio R. Mari and Antoni Cladera, “Shear behaviour of full-scale prestressed I-beams made with self compacting concrete” Materials and Structures (2008) 41:131–141.

13.        A.Cladera, A.R.Mari “Experimental Study on high strength concrete beams failing in shear” Engineering Structures 27 (2012).

14.        BASF Construction Chemicals, product reference Glenuim C315. Web site: www.basfcc.co.uk

15.        The European guidelines for self compacting concrete, www.efnarc.org

16.        Egyptian Code of Design and construction of reinforced concrete structures,        ECP-203 2007.

17.        American Concrete Institute, ACI building code requirements for reinforced concrete, ACI 318-08.

18.        British Sta Shiny Sara Jacob, P Sandhyandard BS 8110: 97 Structural use of concrete, code of practice for design and construction.


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22.

Authors:

Shiny Sara Jacob, P Sandhya

Paper Title:

Postion Sensorless Direct Torque With Indirect Flux Control Of BLDC Motor In Three Phase Conduction Mode

Abstract: In this work, an analysis on position sensorless direct torque control of BLDC Motor with indirect flux control have been studied using two level, six switch Voltage Source Inverter (VSI). By adopting the indirect flux control in direct torque control, the stator flux can be effectively controlled in the constant torque region. This scheme is adapted to three phase conduction mode of VSI. Maximum torque efficiency can be obtained in this method since the torque is estimated in the dq reference frame. In direct torque with indirect flux control of BLDC in three phase conduction mode, the commutation torque ripple can be minimized as well as torque ripple can be effectively reduced. Since the scheme is position sensorless, the electrical rotor position is estimated using stator winding inductance, stationary reference frame currents and flux linkages. The voltage vector selection is set up in the look-up table so that fast torque response is possible. Since the neutral point of the motor is not available, conventional 2×3 matrix is replaced by 2×2 Park’s and Clarke’s transformations for the balanced systems. The experimental results are validated in MATLAB/SIMULINK

Keywords:
Brushless DC (BLDC) Motor, Constant torque region, Direct Torque Control (DTC), Three phase conduction mode, Voltage Source Inverter (VSI).


References:

1.        Ozturk, Salih Baris. "Direct torque control of permanent magnet synchronous motors with non-sinusoidal back-EMF." PhD diss., Texas A&M University, 2008.
2.        Anitpal Singh, Shakti Singh, “Direct Torque Control of PMSM with a Two-Level Inverter  Matlab/Simulink”,IJEIT,Vol.2,pp.10-15,2010.

3.        Y. Liu, Z. Q. Zhu and D. Howe, "Direct torque control of brushless DC drives with reduced torque ripple," IEEE Trans. on Industry Applications, Vol.41, No.2, March/April, 2005, pp.599-608.

4.        S. B. Ozturk and H. A. Toliyat, “Direct torque control of brushless dc motor with non-sinusoidal back-EMF,” in Proc. IEEE IEMDC Biennial Meeting, Antalya, Turkey, May 3–5, 2007, vol. 1, pp. 165–171.

5.        S. Baldursson, ―BLDC Motor Modeling and Control – A MATLAB/Simulink Implementation, Master Thesis, May, 2005.

6.        S.B.Ozturk and H.A.Toliyat,“”Sensor less direct torque and indirect flux control of brushless dc motor with non-sinusoidal back-EMF,”in Proc.IEEE IECON,Orlando,FL,Nov.9-11,2008,pp.1373-178.

7.        P. Vas. Sensorless Vector and Direct Torque Control. London, U.K.: Oxford Univ. Press, 1998.

8.        http://www.microsemi.com/document-portal/doc_view/130909-sf-foc-pmsm-hall-ug


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23.

Authors:

Michael A. Gragasin, Romualdo C. Martinez

Paper Title:

Design and Testing of Improved Village-Type Dehuller- Degerminator for Dry-Milling Process of Corn

Abstract: Majority of the available village-type corn mills in the Philippines have failed to fully satisfy the minimum product recovery and degerminator efficiency of 64% and 80%, respectively, as set by the Philippine Agricultural Engineering Standard (PAES). This resulted in the production of poor quality corn grits with high postharvest losses. Vital in improving the performance of existing village-type corn mills is the development of efficient dehuller-degerminator that responsible in the separation of germ and hull including the tip cap from the endosperm. The major part of the corn kernel that causes irritation when cooked corn grits are served in the table is primarily the tip cap and not the hull alone.  The results of laboratory and field trials revealed that the developed dehuller-degerminator has a milling capacity of 367 kg/h and capable of providing milling recovery of 79.2% and degerminator efficiency of 83.8%.  Significant reduction in aflatoxin level was also observed once corn kernels with high level of aflatoxin have pass through the developed dehuller-degerminator. The innovative design features a hexagonal-dented screen-huller with counter-flow auger and suction blower to efficiently separate the tip cap, germ, and hull from the endosperm.

Keywords:
  Corn dehuller-degerminator, Corn mill, Dry-milling process, Postharvest


References:

1.        DA-Corn Program, “White Corn Industry Development Roadmap”, Department of Agriculture, Philippines, 2014.
2.        F.R. Earle, J.J. Curtis, and J.E. Hubbard, “Composition of the Component Parts of the Corn Kernel”, Cereal Chemistry, vol. 23, pp.504-511, 1946.

3.        AMTEC, “Philippine Agricultural Engineering Standard Specification for Cornmill (PAES 210:2000)”, Agricultural Machinery Testing and Evaluation Center, University of the Philippines at Los Banos, Laguna, Philippines, 2001.   

  

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24.

Authors:

A. A. Elsayed

Paper Title:

Study of Isolation Methods of Underground Structures By using Concrete Admixtures

Abstract:  Waterproofing of underground structures is frequently a problem and a range of solutions have been tried in the last two decades. Dominating the market are PVC and HDPE (high density poly ethylene) sheet membranes, but recently the alternative, is concrete admixtures for water permeability reducing and so that use in concrete isolation (waterproofing), the longevity of a concrete structure is influenced by the permeability of the concrete. The main objectives of the research are to study the mechanical properties of concrete and the improvement these properties by adding waterproofing using various mount percentages and two types of waterproofing (ADDICRETE DM2-PLASTOCRET-N) series of experimental studies were carried out on plain concrete with added, ADDICRETE DM2 and PLASTOCRETE-N in order to investigate their properties and influence on the water permeability of concrete. In this study, it has been addition ADDICRETE   DM2 and PLASTOCRETE N to the mixture by difference ratio. 1%, 0.5%, 0.45% ,0.35% of cement weight, constant ratio from , sand, gravel, cement and water W/C equal to 0.45  in all tests that used in the research . The study of these tests by measuring the permeability of concrete specimens prepared in the laboratory. Many tests were carried out and the results were presented.

Keywords:
  waterproofing; ADDICRETE DM2, PLASTOCRETE-N, permeability, concrete.


References:

1.           AASHTO T277-89 “Standard Method of Test for Rapid Determination of the Chloride Permeability of Concrete”, American Association of State Highway and Transportation Officials, AASHTO T277-89, Washington, DC.
2.           ACI 211.4R-93. "Guide for Selecting Properties for High-Strength Concrete with Portland Cement and Fly Ash," ACI Manual of Concrete Practice, Part 1. American Concrete Institute, Detroit, Michigan, 1996.

3.           Astad U, Heimi P: Waterproofing of tunnels by the use of shotcrete Proc.Tunnels Water,Madrid Serrano(ed),Balkema 1988

4.           ASTM C618-92a. "Standard Specification for Fly Ash and Raw or Calcined Natural Pozzolan For Use as Mineral Admixture in Portland Cement Concrete," American Society for Testing and Materials, Annual Book of ASTM Standards, Volume 04.02, West Conshohocken, Pennsylvania, 2004

5.           Ball, D. (1999) "New Ultra-Low Permeable Concrete" Proceedings of International Congress on Creating with Concrete University of Dundee, (ed. Dhir & McCarthy) pp. 265- 278.

6.           Darmawan ludirdja , Richard l . berger, and j . francis young "simple method for measuring water permeability of concrete " ACI Materials journal , v. 86, N0 .1989

7.           Dr. Dieter Schmid,Gorge Blendermann, "Evolution of Drainage and Waterproofing Systems in Tunnels around Neuchatel," 16 TH CONGRESS OF IABSE, LUCERNE, 2000

8.           Egyptian standard specifications; concrete aggregate from natural sources, No.1109, 2011.

9.           ELE International, "civil and Engineering Test Equipment-9th Edition catalogue", I.T.C., CAIRO-EGYPT, 1993

10.        Eng. Emrah Ertin,"Sprayed Applied waterproof For Underground structures", Egyptian tunneling society, 29/11/2005.

11.        Figg, j w., Method of measuring the air and water permeability of concrete, magazine of concrete research , (London) ,v. 25, no.85, Dec.2003 , pp. 213-219.

12.        Gomes A R. A.: waterproofing and drainage systems for transport tunnels- a review of current practices. Felsbau 23,No 3, 2005

13.        Gouda M.Ghanem; Tarek E1-Sayed; Mona E1-Hamid,"Notes of Experiments for PROPERTIES AND STRENGTH OF MATERIALS LABORATORY", Helwan university, 1996.

14.        Holland, T.C.,1988, "practical Considerations for Using silica Fume in Field Concrete, " Portland Cement Concrete Modifiers, Transportation Research Record 1204,Transportation Research Board, washington D.C.,PP.1-7.

15.        K.Mostsfa, B.Nassif& partners "ADDICRETE DM2 waterproofing and anti-chemical agent for concrete and mortar", chemicals for modern building.

16.        Lemke S.Bracher G, Klapperich H:Technologies for waterproofing systems of underground structures. Felsbau 23, No3, 2005.

17.        LYDON F.D, "CONCRETE MIX DESIGN-2nded", department of civil Engineering and Building Technology, University of Wales Institute of science and Technology
Cardiff, 2002.

18.        Martin.J.Roach, BSc, CEng, MICE ,,The strengthening of Brunl,s thames tunnel,, Proc.Instn Civ. Engrs Transp.,1998,129,May.

19.        Miao-Buquan; Chern-Jenn Chuan; Yang-ChenAn ,,Influences of fiber content on properties of self-compacting steel fiber reinforced concrete,, ,Journal of the Chinese Institute of Engineers, v 26,n 4, p 523-530,July, 2013.

20.        Mc Grath,P.F.,2000.Water permeability vs.waterproof Xypex chemical Corporation, Richmond B.C., Canda.

21.        Mott MacDonald,"Product Evaluation of MASTERSEAL 345,"Application and Specification, March 2004.

22.        Naoyuki YAGUCHI, Masaru TATEYAMA,"Adhesive waterproof sheeting for preventing water leakage into underground structures ", Railway Technology Avalanche No.March 1, 2005

23.        Song-PS; Hwang-S,"Mechanical properties of high-strength steel fiber-reinforced concrete", construction and Building Materials, v 18,n 9,p669-673, November 2008.

24.        Sika Egypt for construction chemicals s.a.e "plastocrete- N waterproofing concrete Admixture, Edition 10. 2003.


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25.

Authors:

Swapna P S, Sakuntala S. Pillai

Paper Title:

Downlink Resource Allocation Scheme for OFDMA System

Abstract:   Orthogonal Frequency Division Multiple Access (OFDMA) is a promising multiple access technique for next generation wireless communication such as WiMAX, LTE, IMT-A etc because of its high spectral efficiency and inherent robustness against frequency selective fading. Inclusion of relays into the system further improves the system performance. The asymmetric radio resource allocation problem for cooperative relay assisted OFDMA wireless networks with the objective of maximizing the data rate is addressed in this paper. In cooperative communication the transmission from base station to mobile stations is assisted by decode-and-forward relays. To reduce the computational complexity of its optimal solution, the proposed scheme is sub-divided into three subsections. The first section is to select the relays and then the subcarrier is allocated to the selected relays. As the next step,  power is allocated to each subcarrier. Simulation results shows that the proposed scheme achieves better performance than the existing techniques.

Keywords:
Hungarian algorithm, Interference computation, OFDMA, Resource Allocation, Water filling algorithm. .


References:

1.           Md Shamsul Alm, Xuemin Shen, “Relay Selection and Resource Allocation for multiuser Cooperative OFDMA Networks, IEEE Transactions on Wireless Communications, Vol 12, No. 5, May 2013.
2.           Nidhal Odeh, Mehran Abolhasan and Farzad Safaei, “Low Complexity Interference Aware Distributed Resource Allocation for Multi-Cell OFDMA Cooperative Relay Networks”, WCNC 2010 proceedings.        

3.           Long Gao, Shuguang Cui and Feifei Li, “A Low-complexity Adaptive Subcarrier, Bit, and Power Allocation Algorithm for OFDMA Systems”,IEEE GLOBECOM 2006 proceedings.

4.           Bo Bai, Wei Chen and Khaled B. Lataief, “Achieving High Frequency Diversity with Subcarrier Allocation in OFDMA Systems”, IEEE GLOBECOM 2008 proceedings, pp. 1-5.

5.           Shenghong Li and Ross D. Murch, “Realizing Cooperative Multiuser OFDMA Systems with Subcarrier Resource Allocation”, IEEE Transactions on Wireless Communications Vol.12, No.4, April 2013,pp 1923-1935.

6.           Ahmad M. El-Hajji and Zaher Dawy, “Dynamic Joint Switching Point Configuration and Resource Allocation in TDD-OFDMA Wireless Networks”, IEEE GLOBECOM 2011 proceedings.

7.           Lukai Xu, Guanding Yu and Yuhuan Jiang, “Energy-Efficient Resource Allocation in Single-Cell OFDMA Systems:ulti-Objective Approach, IEEE Transactions on Wireless Communications,2015.

8.           Zheng, Chang, Tapani, Restaniemi, “Asymmetric resource allocation for OFDMA networks with collaborative relays”, The 10th Annual IEEE CCNC-Wireless Networking track, 2013.

9.           Dapeng, Zhang, Laurie, Cuthbert, ”Dynamic subcarrier and power allocation in LTE networks”, IEEE 5th International Conference on Wireless Communication,
Networking and Mobile Computing, pp 1-4,

10.        Lihan Liu, Zhuwei Wang, Xing Zhang and Hong Wu, “Radio Resource Management for the Uplink OFDMA System with Imperfect CSI”, 2015 IEEE Wireless Communications and Networking Conference.

11.        C. Y. Ng and C. W. Sung, “Low Complexity Subcarrier and Power Allocation for Utility Maximization in Uplink OFDMA Systems”, IEEE Transactions in Wireless Communication, Vol.7, No.5, pp. 1667- 1675,May 2008.

12.        Hojoong Kwon and Byeong Gi Lee,” Distributed Resource Allocation through Noncooperative Game Approach in Multi-cell OFDMA Systems,” IEEE conference publications,2006.

13.        P Xu, X Fang, M Chen, Y Xu, “A Stackelberg game-based spectrum allocation scheme in macro/femtocell hierarchical networks” Computer Communication 36, 1552–1558 (2013)


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26.

Authors:

Anita Ganpati, Jyoti Sharma

Paper Title:

A Hybrid Implementation of K-Means and HAC Algorithm and Its Comparison with other Clustering Algorithms

Abstract: There is a huge amount of data which is being produced everyday in Information Technology industry but it is of no use until converted into useful information. Data mining is defined as the process of extracting of hidden predictive information from large databases. Data mining provides an easy and timesaving concept to extract the useful information from large database instead of going through the whole database. There are various data mining techniques and clustering is one of them. Clustering algorithms especially draws significant attention of researchers all around the world because it makes an easy availability of the same data in form of clusters. There are various types of clustering algorithms available in the literature, with each algorithm having its own pro and cons. In this research paper, a hybrid implementation of k-Means and HAC clustering algorithm is presented. Also, the hybrid approach is compared with four other clustering algorithm namely k-Means, DT, HAC, VARCHA. The hybrid implementation has been done using Python scripting language and SCIKIT LEARN open source tool was used for the performance comparison of the algorithms. The various parameters used for comparison were accuracy, precision, recall and f-score. The results show that the performance of hybrid algorithm is found to be quite better than the existing ones.   

Keywords:
  Data Mining, Clustering, k-Means, DT, HAC, VARCHA, Python and SCIKIT


References:

1.           http://www.tutorialspoint.com/data_mining/dm_cluster_analysis.html.
2.           Lior Rokach, Oded Maimon, “Clustering Methods”, http://www.ise.bgu.ac.il/faculty/liorr/hbchap15.pdf.

3.           Aastha Joshi, “A Review: Comparative Study of Various Clustering Techniques in Data Mining”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue 3, March 2013.

4.           Bhavani Thuraisingham, “Data Mining-Technologies, Techniques, Tools and Trends”, CRC, 1999.
5.           Jyoti Sharma and Anita Ganpati, “An Analysis of Grid Based Clustering Algorithms In Data Mining”, National Seminar on Web Based Technologies: Present & The Future, St. Bede’s College, Aptil 30th 2015- May 1st 2015, Shimla.
6.           M.Sathya Deepa, “Comparative Studies of Various Clustering Techniques and Its Characteristics”, International Journal Advanced Networking and Applications, Vol. 5, Issue 6, 2014.

7.           Margaret H. Dunham,“Data mining Introductory and Advanced Topics”,  Pearson Publication, 2005.

8.           Pang-Ning-Tan, Michael Steinbach, Vipin Kumar, “Introduction to Data Mining”, Pearson Publication, 2009.

9.           Ravindra Jain, “A Hybrid Clustering Algorithm for Data Mining”, IEEE Transaction on Neural Networks, June 2012.

10.        Manju Kaushik and Mrs. Bhawana Mathur, “Comparative Study of K-Means and Hierarchical Clustering Techniques”, International Journal of Software & Hardware Research in Engineering (IJSHRE), Vol. 2, Issue 6, 2014.

11.        Bharat Chaudhari and Manan Parikh, “A Comparative Study of Clustering Algorithms Using Weka Tool , International Journal of Application or Innovation in Engineering & Management (IJAIEM), Vol. 1, Issue 2, October 2012.

12.        S. Revathi, “Performance Comparison of Various Clustering Algorithm”, International Journal of Advanced Research in Computer Science and Software Engineering,  Vol. 3, Issue 2, February 2013.

13.        T. Kanungo, D. Mount, N. Netanyahu, C. Piatko, R. Silverman, and A. Wu, “An efficient k-Means Clustering Algorithm: Analysis and Implementation”, IEEE Transaction Pattern Analysis and Machine Intelligence, Vol. 24, No. 7, July 2000.

14.        Yuhua Feng, “Analysis on Algorithm and Application of Cluster in Data Mining”, Journal of Theoretical and Applied Information Technology, Vol. 46, No.1, December 2012.

15.        http://gerardnico.com/wiki/data_mining/cluster, Accessed on 15.09.2015 at 21:10.


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27.

Authors:

Nikita Lemos, Kavita Sonawane, Bidisha Roy

Paper Title:

Novel Approach to Secure Data Transmission using Video

Abstract: Internet is being widely used for transmitting sensitive data. The data transferred online is prone to attacks. This paper presents a novel technique where steganography and cryptography are clubbed together to get achieve dual level security. Steganography hides the existence of data and cryptography scrambles the data and makes it difficult to interpret it even if the attacker gets hold of the data. Since videos are used widely today and are a popular on social media we have used video as a cover to the hide the secret data Text data is stored in video frames. The data is subjected to steganography and cryptography which are simple and novel techniques and then stored in the video frames using a random fashion using simple linear probing techniques.

Keywords:
   Steganography, cryptography, cover, security threats


References:

1.           Petitcolas, F.A.P.: “Introduction to Information Hiding”. In: Katzenbeisser, S and Petitcolas, F.A.P (ed.) (2000) Information hiding Techniques for Steganography and Digital Watermarking. Norwood: Artech House, INC.
2.           Ashish T. Bhole, Rachna Patel, “Design and Implementation of Steganography Over Video File”, The Indian Journal of Technical Education, Special Issue for NCEVT’ 12, pp. 69-72, April 2012.

3.           Natarajan Meghanathan, Lopamudra Nayak, “Steganalysis Algorithms for Detecting the Hidden Information in Image, Audio And Video Cover Media”, International Journal of Network Security and its Applications (IJNSA),Vol.2, No.1,pp. 43-55, January 2010.

4.           R. Balaji and G. Naveen,” Secure Data Transmission Using Video Steganography”, Electro/Information Technology IEEE International Conference , 2011

5.           Nikita lemos, Kavita sonawane and Bidisha Roy,”Secure data transmission using video”, Eight International Conference on Contemporary Computing (IC3)  IEEE ,2015


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28.

Authors:

Hakeemuddin Ahmed, N. Seetha Ramaiah, M. Manzoor Hussain

Paper Title:

Experimental Investigation of Surface Integrity of End milled CFRP Composites

Abstract: In general, the quality of the surface produced during machining is affected by the process variables and the vibrations of the tool. The surface finish is affected by the undesired vibrations that occur especially   when a rotating tool like drill/ milling cutter is involved. Machining of fiber reinforced composites plays a vital role in obtaining fine tolerances on their components so as to assemble and integrate them with the other components. Carbon Fiber Reinforced Polymer (CFRP) composites are rapidly substituting the conventional materials as they meet high performance requirements due to their high specific stiffness, strength and corrosion resistance. In this study, the effect of process parameters on the dimensional accuracy and surface finish of the slots produced by end milling on CFRP laminate is studied. Experimental investigation is carried out to determine the relationship between spindle speed and feed which minimizes the surface roughness and delamination factor. The variation of the cutting forces involved is also studied in relation with the process variables to derive the regression equations

Keywords:
  CFRP, Delamination factor, End Milling, Surface Integrity


References:

1.           Azmi, A.I., R.J.T. Lin, and D. Bhattacharyya, “Experimental Study of Machinability of glass fibre reinforced composites by End milling”, Materials and Manufacturing Processes, Vol 27, 2012, pp1045-1050
2.           Calzada, K.A., J. Samuel, S.G. Kapoor, and R.E. Devor, “Failure mechanisms encountered in micro-milling of aligned carbon fiber reinforced polymers”.Transaction of NAMRI/SME 2010, 38, pp 221-228.

3.           Carlos Santiuste , Xavier Soldani , Maria Henar Miguélez, “Machining FEM model of long fiber composites for aeronautical components”, Composite Structures  92 (2010)  pp 691–698

4.           H.Y. Puw and H. Hocheng, “Machinability test of carbon fiber reinforced plastics in milling”. Materials and Manufacturing Processes, 1993 pp 103-108.

5.           J.Paulo Davim, Pedro Reis, C.Conceicao Antonio, A study on milling of GFRP by hand layup using ANOVA, Composite Structures, Vol. 64, 2004. pp 493-500

6.           Karpat, Y., O. Bahtiyar, and B. Değer, “Mechanistic force modeling for milling of unidirectional carbon fiber reinforced polymer laminates”. International Journal of Machine Tools and Manufacture. Vol 56, 2012, pp 79-93

7.           Kalla, D., J. Sheikh-Ahmad, and J. Twomey, “Prediction of cutting forces in helical end milling fiber reinforced  polymers”. International Journal of Machine Tools and Manufacture, Vol 50, 2010 pp 882-891

8.           Koplev, A., A. Lystrup, and T. Vorm, “The cutting  process, chips, and cutting forces in machining CFRP Composites”, Composites,1983, Vol14, pp 371-376

9.           N.Feito, J.Lopez-Puente Numerical prediction of  delamination in CFRP drilling, Composite Structures, Vol 108, 2014, pp 677-683

10.        Rahman, M., S. Ramakrishna, J.R.S. Prakash, and      D.C.G. Tan, “Machinability study of carbon fiber reinforced composite”. Journal of Materials Processing Technology, 1999, pp 292-297.

11.        Rawat, S. and H. Attia, “Wear mechanisms and tool life management of WC-Co drills during dry high speed drilling of woven carbon fibre composites”. Wear 2009, 267 (5-9), pp 1022-1030.

12.        R.Madoliat, S.Hayati, A.Ghasemi Galebahman        “Investigation of chatter suppression in slender end mill via a frictional damper”, Scientia Iranica B, Vol.18,
2011, pp 1069-1077

13.        Takeyama, N. Ijima, “Machinability of GFRP and application of Ultrasonic machining”, Annals of CIRP, 1998,37(1), pp 93-96

14.        Tsao, C.C., “Investigation into the effects of drilling parameters on delamination by various step-core drills”, Journal of Materials Processing Technology, 2008. 206(1-3), pp. 405-411.

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29.

Authors:

Rashmi Kalia

Paper Title:

Persistent Organic Pollutants: A Review

Abstract: Persistent organic pollutants (POPs) are toxic chemicals that adversely affect human health and the environment around the world. Most of the POPs are released due to anthropogenic activities, while others are produced as a result of secondary emission. Because they can be transported by wind and water, most POPs generated in one country can and do affect people and wildlife far from where they are used and released. They persist for long periods of time in the environment and can accumulate and pass from one species to the next through the food chain.

Keywords:
Persistent Organic Pollutants, Pesticides, Hazards


 References:

1.        Beyer, A., Mackay, D., Matthies, M., Wania, F., Webster, E. (2000). Assessing Long-Range Transport Potential of Persistent Organic Pollutants. Environmental Sciences & Technology. 34(4), 699–703.
2.        Dewan, Jain V,; Gupta P; Banerjee BD. (February 2013). "Organochlorine pesticide residues in maternal blood, cord blood, placenta, and breastmilk and their
relation to birthsize". Chemosphere 90 (5): 1704-1710

3.        Damstra, T. (2002). Potential Effects of Certain Persistent Organic Pollutants and Endocrine Disrupting Chemicals on Health of Children. Clinical Toxicology. 40(4), 457–465

4.        El-Shahawi, M.S., Hamza, A., Bashammakhb, A.S., Al-Saggaf, W.T. (2010). An overview on the accumulation, distribution, transformations, toxicity and analytical methods for the monitoring of persistent organic pollutants. Talanta. 80, 1587–1597

5.        Francis, O., A, 2004. Boon or Bane? The Environmental and Health Impacts of Persistent Organic Pollutants (POPs), Human Ecology Review, Vol. 11, No. 1, 27-35

6.        Wania, F., Mackay, D. (1996). Tracking the Distribution of Persistent Organic Pollutants. Environmental Science & Tech
nology. 30 (9), 390A–396A.

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30.

Authors:

Zuhair Issa Ahmed, Ali Malik Saadoon

Paper Title:

Optimization Process Parameters of Submerged Arc Welding Using Taguchi Method

Abstract: Submerged arc welding (SAW) process is an essential metal joining processes in industry. The quality of weld is a very important working aspect for the manufacturing and construction industries, the challenges are made optimal process environment. Design of experimental using Taguchi method (L9 orthogonal array (OA)) considering three SAW parameter are (welding current, arc voltage and welding speed) and three levels (300-350-400 Amp. , 32-36-40 V and 26-28-30 cm/min). The study was done on SAW process parameters on the mechanical properties of steel type comply with (ASTM A516 grade 70). Signal to Noise ratio (S/N) was computed to calculate the optimal process parameters. Percentage contributions of each parameter are validated by using analysis of variance (ANOVA) technique. The experimental results were analyzed by using Minitab 16 software.

Keywords:
  ANOVA, SAW, S/N, Taguchi Method, Welding Process Parameters


 References:

1.           Syarul Asraf Mohamata, Izatul Aini Ibrahima, Amalina Amira and Abdul Ghaliba, “The Effect of (FCAW) processes on different Parameters”, 2012 (IRIS 2012), 1497 – 1501.
2.           Shahnwaz Alam and Mohd.Ibrahim Khan, “Prediction of the Effect of SAW Process Parameters on Weld Bead Width for M.S. 1018 Steel”, (IJEIT) Volume 1, Issue 5, may 2012, 2277-3754.

3.           R. S. Chandel, H. P. Seow and F. L. Cheong, J Mater Process Technol, 72 (1997)124-128.

4.           L. J. Yang, R. S. Chandel and M. J. Bibby, J. Weld, 72 (1993) 11s-18s.

5.           Saurav Datta, Asish Band and Pradip Kumar Pal, “Modeling and optimization of features of bead geometry including percentage dilution in SAW using mixture of fresh flux and fused slag”, IJAMT, 2008 DOI 10.1007/s00170-006-0917-4, 36:1080–1090.

6.           Keshav Prasadand and D. K. Dwivedi, “Some investigations on microstructure and mechanical properties of SAW HSLA steel joints”, IJAMT, 2008 DOI 10.1007/s00170-006-0855-1.
7.           S. Kumanan, J. K. Gowthaman and Edwin Raja Dhas, “Determination of SAW process parameters using Taguchi method and regression analysis”, IJEMS, vol. 14, June 2007, 177-183

8.           Ravinder Pal Singh, R.K. Garg and D.K. Shukla, “Parametric Effect on Mechanical Properties in Submerged arc welding process - A review”, (IJEST) Feb.2012, Vol.
4 No.02 0975-5462.

9.           N. Murugan, V. Gunaraj and J. Mater Process Technology, 168 (2005) 478-487.

10.        Y. S.Tarng,; W.H. Yang, studies the “Application of the Taguchi Method to the Optimization of the SAW’. Materials and Manufacturing Processes. 13 (3), 455-467 (1998).

11.        Ankita Singh; Saurav Datta; Siba Sankar Mahapatra; Tapan Singha and Gautam Majumdar.: “Optimization of bead geometry of SAW using fuzzy based
desirability function approach. J Intell Manuf. DOI 10.1007/s10845-011-0535-3.

12.        R.S. Chandel; H.P. Seow; F.L. Cheong, studies the “Effect of increasing deposition rate on the bead geometry of SAW’. (JMPT). 72,124-128 (1999).

13.        R.S. Parmar, "Welding Processes and Technology", third edition, Khanna publishers, Delhi, India, P. 221, 2012.


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