Volume-5 , Issue-6 , Dec 2017, ISSN 2320-7639 (Online) Go Back

• Open Access   Article

  OTU Clustering: A window to analyse uncultured microbial world

  Ashaq Hussain Bhat, Puniethaa Prabhu

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.6 , pp.62-68, Dec-2017

  CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v5i6.6268

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Clustering is the technique used to deal with higher amounts of data by partitioning the data into some groups based on some attributes. Clustering technique has many applications in different fields of science and technology. It is an important tool in genomics and metagenomics which performs taxonomic profiling of the microbial world by grouping 16S RDNA amplicon reads into clusters called as Operational Taxonomic Units (OTUs). With the help of Next Generation Sequencing (NGS) tools and clustering it has become easy for scientists to find the microbial diversities in different environments without culturing the microbes. Assignment of 16s rDNA sequences to the clusters called as OTUs is the main task in metagenomics algorithms and is also the main bottleneck for analysing microbial communities. Taxonomic profiling of 16S rDNA is an important step in Metagenomic pipeline analysis. There are several OTU clustering algorithms which clusters the amplicon reads of 16S rDNA into OTUs, each algorithm use a specific type of clustering technique to cluster the sequence reads. Some of the mostly used algorithms are Uclust, swarm, SUMACLUST, SortMeRNA, USEARCH. In this paper, we first give a brief overview of major clustering techniques and their types. Furthermore, we provide a comprehensive overview of OTU clustering algorithms.

  Key-Words / Index Term
  16S rDNA; OTUs; Uclust; SUMACLUST; SortMeRNA; USEARCH; taxonomic profiling

  References
  [1] P. D’haeseleer, “How does gene expression clustering work?” Nat. Biotechnol., vol. 23, pp. 1499–501, 2005.
  [2] N. D. Heintzman, G. C. Hon, R. D. Hawkins, P. Kheradpour, A. Stark, L. F. Harp, Z. Ye, L. K. Lee, R. K. Stuart, and C. W. Ching, “Histone modifications at human enhancers reflect global celltype- specific gene expression,” Nature, vol. 459, no. 7243, pp. 108–112, 2009.
  [3] R. K. Chodavarapu, S. Feng, Y. V. Bernatavichute, P.-Y. Chen, H. Stroud, Y. Yu, J. a. Hetzel, F. Kuo, J. Kim, S. J. Cokus, D. Casero, M. Bernal, P. Huijser, A. T. Clark, U. Kramer, S. S. Merchant, X. Zhang, S. E. Jacobsen, and M. Pellegrini, “Relationship between nucleosome positioning and DNA methylation,” Nature, vol. 466, pp. 388–92, 2010.
  [4] X. Wang, G. O. Bryant, M. Floer, D. Spagna, and M. Ptashne, “An effect of DNA sequence on nucleosome occupancy and removal,” Nat. Publishing Group, vol. 18, pp. 507–509, 2011.
  [5] A. S. Shirkhorshidi, S. Aghabozorgi, T. Y. Wah, T. Herawan, “Big Data Clustering: A Review” Computational Science and Its Applications – ICCSA 2014Volume 8583 of the series Lecture Notes in Computer Science pp 707-720.
  [6] M. L. Sogin, H. G. Morrison, J. A. Huber, D. Mark Welch, S. M. Huse, P. R. Neal, J. M. Arrieta, and G. J. Herndl, “Microbial diversity
  [7] in the deep sea and the underexplored ‘rare biosphere’”, Proc. Nat. Acad. Sci. USA, vol. 103, no. 32, pp. 12115– 12120, 2006.
  [8] S. M. Huse, D. M. Welch, H. G. Morrison, and M. L. Sogin. (2010).Ironing out the wrinkles in the rare biosphere through improved OTU clustering,” Environmental Microbiol., vol. 12, no. 7, pp. 1889–1898.
  [9] J. G. Caporaso, J. Kuczynski, J. Stombaugh, K. Bittinger, F. D. Bushman, E. K. Costello, N. Fierer, A. G. Pena, J. K. Goodrich, J. I. Gordon, G. A. Huttley, S. T. Kelley, D. Knights, J. E. Koenig, R. E. Ley, C. A. Lozupone, D. McDonald, B. D. Muegge, M. Pirrung, J. Reeder, J. R. Sevinsky, P. J. Turnbaugh, W. A. Walters, J. Widmann, T. Yatsunenko, J. Zaneveld, and R. Knight, “QIIME allows analysis of high-throughput community sequencing data,” Nature Methods, vol. 7, no. 5, pp. 335–336, May 2010.
  [10] R. C. Edgar. (2010). “Search and clustering orders of magnitude faster than BLAST” Bioinformatics, vol. 26, no. 19, pp. 2460–2461.
  [11] R. C. Edgar, “UPARSE: highly accurate OTU sequences from microbial amplicon reads,” Nat. Methods, vol. 10, no. 10, pp. 996– 8, Oct. 2013.
  [12] P. D. Schloss, S. L. Westcott, T. Ryabin, J. R. Hall, M. Hartmann, E. B. Hollister, R. A. Lesniewski, B. B. Oakley, D. H. Parks, C. J. Robinson, J. W. Sahl, B. Stres, G. G. Thallinger, D. J. V. Horn, and C. F. Weber, “Introducing mothur: Open-source platform-independent community supported software for describing and comparing microbial communities”, Appl. Envir. Microbiol., vol. 75, no. 23, pp. 7537–7541, 2009.
  [13] Y. Sun, Y. Cai, L. Liu, F. Yu, M. L. Farrell, W. McKendree, and W. Farmerie, “ESPRIT: Estimating species richness using large collections of 16S rRNA pyrosequences”, Nucleic Acids Res., vol. 37, no. 10, p. e76, 2009.
  [14] Y. Cai and Y. Sun., “ESPRIT-Tree: Hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time” Nucleic Acids Res., vol. 39, no. 14, p. e95, 2011.
  [15] R. C. Edgar., “MUSCLE: Multiple sequence alignment with high accuracy and high throughput”, Nucleic Acids Res., vol. 32, no. 5, pp. 1792–1797, 2004.
  [16] Y. Sun, Y. Cai, S. M. Huse, et al., “A large-scale benchmark study of existing algorithms for taxonomy-independent microbial community analysis,” Briefings in Bioinformatics, vol. 13, no. 1, pp. 107–121, 2011.
  [17] T. Zhang, R. Ramakrishnan, and M. Livny, “BIRCH: A new data clustering algorithm and its applications”, Data Mining Knowl. Discovery, vol. 1, no. 2, pp. 141–182, 1997.
  [18] W. Li and A. Godzik., “Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences”, Bioinformatics, vol. 22, no. 13, pp. 1658–1659, 2006.
  [19] Schloss PD, Handelsman J., “Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness” Appl Environ Microbiol 71:1501–1506. http://dx.doi.org/ 10.1128/AEM.71.3.1501, 2005.
  [20] Albanese D, Fontana P, De Filippo C, Cavalieri D, Donati C., “Micca: a complete and accurate software for taxonomic profiling of metagenomic data”, Sci Rep 5:9743, http://dx.doi.org/10.1038/srep09743, 2015.
  [21] Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M., “Swarm: robust and fast clustering method for amplicon-based studies”, PeerJ 2:e593, http://dx.doi.org/10.7717/peerj.593, 2014.
  [22] Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M., “Swarm v2: highly-scalable and high-resolution amplicon clustering”, PeerJ 3:e1420, http://dx.doi.org/10.7717/peerj.1420, 2015.
  [23] Kopylova E, Noé L, Touzet H., “SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data”, Bioinformatics 28:3211–3217. http://dx.doi.org/10.1093/bioinformatics/bts611, 2012.
  [24] Hobohm U, Scharf M, Schneider R, Sander C., “Selection of representative protein data sets” Protein Sci 1, 409 – 417, http:// dx.doi.org/10.1002/pro.5560010313, 1992.
  [25] Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R., “UCHIME improves sensitivity and speed of chimera detection” BioInformatics 27, 2194–2200,
  [26] Legendre P, Legendre L., “Numerical ecology”, 2nd ed, Developments in environmental modelling, vol 20, p . Elsevier Science, Amsterdam, The Netherlands, 1998
  

  Citation
  Ashaq Hussain Bhat, Puniethaa Prabhu, "OTU Clustering: A window to analyse uncultured microbial world," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.6, pp.62-68, 2017

• Open Access   Article

  An Overview and Analysis Based on Biometric Framework Technique and Fingerprint Biometric Technology

  Nitin Tiwari

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.5 , Issue.6 , pp.69-74, Dec-2017

  CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v5i6.6974

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Biometric technique area a strange and reliable structure and creation biometric, recognition has pulled in various researchers and achieved great success. This paper of overview of analysis work is to how is process, biometric are review and principal of the biometric techniques, taking both secure information and personal integrity into consideration. But my point of view every individual has unique characteristics. It is more secure and often more convenient. Biometrics are extra of high accuracy in today`s can be used for identification biometric framework. The reason for our paper is to overview and analysis to know how to use biometric system and working for creation assessment whether the combination of structure and creation and unique mark biometric method used success execution that may not be believable utilizing a friendless technique innovation. The term biometrics encompasses together which means that Biometric information is more and more useful and can replace passwords identity verification of user’s. This improves privacy for both user and administrator. Various method are used to discover and study and outcome result, biometric functions are advantage and for their strength and properly working in the completion of the biometric technology.

  Key-Words / Index Term
  Network Security, Biometric Technique, Fingerprinting Biometric, Numerous Biometric System, New and Emerging Biometric Techniques

  References
  [1] S. Prabhakar, S. Pankanti, and A. K. Jain, “Biometric Recognition: Security and Privacy Concerns”, IEEE Security and Privacy Magazine, Vol. 1, No. 2, pp. 33-42, 2003
  [2] Fingerprint Matching Using Two Methods Mrs. Hemlata Patel*, Pallavi Asrodia**International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 pp 857-pp560
  [3] D. Landgrebe, Hyper spectral Image data analysis. IEEE process vol. 19, pp. 17–pp 28, 2002.
  [4] Kalyani Mali Samayita Bhattacharya International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 7, July 2013 pp162-pp172
  [5] A. K. Jain, L. Hong, S. Pankanti, and R. Bolle, An identity authentication system using fingerprints Proc. IEEE, vol. 85, no. 9, pp.1365–pp1388, Sep. 1997.
  [6]. T. Nakamoto, A. Fukunda, and T. Moriizumi. Perfume and FlavorIdentification by Odor-Sensing System Using Quartz-Resonator Sensor Array and Neural Network Pattern Recognition. Volume18/19, pp. 282-pp290, 1994
  [7] P.Inbavalli1, G.Nandhini2International Journal of Computer Science and Information Technologies, Vol. 5 , 2014, pp 6270-pp6274 Body Odor as a Biometric Authentication
  [8] Ramya M*; Dr. V. Krishnaveni**; Dr. K. S. Sridharan*** Effective Approches and Challenges Focued in IRIS Image Recognition – A Survey Asian Journal of Research in Social Sciences and Humanities Vol. 6, No. 11, November 2016, pp. 565-580.
  [9] S. Garg, A. Kumar, and M. Hanmandlu. Biometric authentication using finger nail surface. International conference on Intelligent Systems Design and Applications (ISDA), . IEEE pages 497–502, Nov. 2012.
  [10] Joseph Kalunga*, Simon Tembo American Journal of Bioinformatics Research Development of Fingerprint Biometrics Verification and Vetting Management System Joseph, 6(3): pp99-pp112 ,2016
  [11] Rupinder Saini , Narinder Rana “Comparison of Various Biometric Methods”. International Journal of Advances in Science and Technology (IJAST) ISSN 2348-5426 pp24-pp30
  [12] Rabia Jarfi and Hamid R. Arabina, “A Survey of Face Recognition Techniques”, Journal of Information Processing Systems, Vol.5, No.2, pp41-69 June 2009.
  [13] Michal Choras (2009) ,” The lip as a biometric”. February 2010, issue 1 Volume 13 pp 105–111
  [14] Dr.Haitham Kareem Ali1,Dr.Yasir Khalil Ibrahim2 Energy Conservation using Voice RecognitionJournal of Information Engineering and Applications www.iiste.org ISSN 2224-5782 (print) ISSN 2225-0506 (online) Vol.3, No.11 pp59-62, 2013
  [15] Montri Phothisonothai, "An investigation of using SSVEP for EEG-based user authentication system", Signal and Information Processing Association Annual Summit and Conference (APSIPA) 2015 Asia-Pacific, pp. 923-926, 2015.
  [16]S. Marcel and J. D. R. Millan. Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation. IEEE Trans.Pattern Anal. MachIntell. 29(4) pp743-pp 752, April 2007.
  [17] Nitin Tiwari, Overview & Comparison of Inactive and Active Finger Stamping. International journal of scientific engineering Research IJSER March vol-3 issue 3 2012
  [18] Nitin Tiwari, an overview An Overview of Techniques for Framework of Finger Stamping international journal of electronics and computer science engineering June 2012. ISSN code 2229-5518

  Citation
  Nitin Tiwari , "An Overview and Analysis Based on Biometric Framework Technique and Fingerprint Biometric Technology," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.6, pp.69-74, 2017

• Open Access   Article

  Design and Simulations of Solid Oxide Fuel Cell connected to 3-phase electrical power system

  Shubham Joshi, D.K. Rai

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.5 , Issue.6 , pp.75-78, Dec-2017

  CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v5i6.7578

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  The integration of the fuel cell system is to provide the continuous power supply to the load as per the demand. In this paper, design and modeling of Solid Oxide Fuel cell (SOFC) is discussed for the distributed generation applications. Modeling and simulations are carried out in MATLAB Simulink platform. Solid oxide fuel cells operate at temperatures near l0000C these are highly efficient combined heat and electric power. Modeling of SOFC is done by using by using Nernst equation. In that the output power of the fuel cell can be controlled by controlling the flow rate of the fuels used in the process. The power generation from the fuel cell system is an electrochemical reaction between hydrogen and oxygen with the bi-product of water vapour molecule. But the output power from the solar system is very low for this numbers of cell are connected in series. This paper proposes a concept of boost inverter topology for converting fuel dc supply to a three phase supply. The main advantage of the proposed boost inverter method include ability to deliver the operations of both boosting and inversion of the power in only one stage, compactness, and economical. The output voltage from the fuel cell is a voltage controlled method and output from the battery is a current controlled method. Analysis and Simulation are taken from a 1kW prototype.

  Key-Words / Index Term
  Battery Storage System, Boost-Inverter, Fuel Cell, SOFC, Distributed Generator, DC-DC converter

  References
  [1] Rajendra Aparnathi and Ved vyas Dwivedi, ”L-C-L filter base 3-Phase Inverter,” ebook in Germany lambert publication, 8th Oct-2012
  [2] Bin Lu , Yaoyu Li, Xin Wu and Zhongzhou Yang, “A Review of Recent Advances in Wind Turbine Condition Monitoring and Fault Diagnosis”
  [3] Hector A. Pulgar-Painemal, Peter W. Sauer, “Doubly- Fed Induction Machine in Wind Power Generation”
  [4] D.Aouzellag , K.Ghedamsi, E.M.Berkouk” Power Control of a Variable Speed Wind Turbine Driving an DFIG”
  [5] Kenneth E. Okedu “Stability Enhancement of DFIGbased Variable Speed Wind Turbine with a Crowbar by FACTS Device as Per Grid Requirement” International Journal Of Renewable Energy Research, Vol.2, No.3, 2012
  [6] J. T. Brown “Solid Oxide Fuel Cell Technology, ”IEEE Transactions on Energy Conversion, Vol. 3, No. 2, June
  [7] Yulei Sun, Sathyendra Ghantasala and Nael H. El-Farra “Networked Control of Distributed Energy Resources: Application to Solid Oxide Fuel Cells” 2009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA, June 10-12, 2009.
  

  Citation
  Shubham Joshi, D.K. Rai, "Design and Simulations of Solid Oxide Fuel Cell connected to 3-phase electrical power system," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.6, pp.75-78, 2017

• Open Access   Article

  Design and Simulations of Load Management Impact on Power System

  Deepak Pawar and D.K. Rai

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.5 , Issue.6 , pp.79-82, Dec-2017

  CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v5i6.7982

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  The growth in the demand for electricity in India during the last decade witnessed a dramatic growth in the national`s annual residential development has played a major role in boosting the demand for electric power. The domestic sector in India already accounts for approximately 39 percent of electricity demand. To meet the projected demand for electrical power to cope with, the development plans, increases in the population and the rising in the living standards, government will have to accomplish new power generating units. Comparing with the high budget of constructing new generating power units, load management system it would be attractive resource that should be seriously considered as an important part of national energy program, where demand growth rate exceeds the supply since it is playing an increasing role around the world as a valuable and cost-effective energy resource. Hence, was light projecting on power load management program, for its benefit in reducing the energy demand at peak time?.

  Key-Words / Index Term
  Load Management, Maximum Demand, Demand Factor, Tariffs, Load Shifting, Load Reduction

  References
  [1] “POWER LOAD MANAGEMENT Techniques and Methods in Electric Power System” Montaser .Atta . kassem1. International Research Journal of Engineering and Technology (IRJET), Volume: 02 Issue: 09 | Dec-2015
  [2] Abdelfatah Ali Elahwil „Load management implementation, a method of improving financial performance in power system,?IAS?95 conference record of the 1995 IEEE industry application conference p.2249-54 vol.53.
  [3] “Load Management”,M.A. Ekhlat, M.M. El-madhoun. S.S. Ben Nasair and M.A. El-Zaidi, Energy and life Journal No. 7.Sept 1996(in Arabic)
  [4] [Sorri and Salo, 1992] V.Sorri and T.Salo. Infl uence of the cost control tariffs on the control of electricity consumption in Finland. In Proceedings of DA/DSM?92,January 1992.
  [5] [ Talukdar and Gellings,1987] S. Talukdar and C.w. Gellings. Load Management. IEEE Press. New York, 1987.
  [6] [Wafa,1996] A.R.A Wafa. Optimum load management securing minimum revenue loss in industry. In Proceedings of DA/DSM „ 96. Pen Well Conferences and Exhibitions, October 1996.
  [7] J. Skeer, “Highlights of the International Energy Agency Conference on Advanced Technologies for Electric Demand-side Management,” in Proceeding of Advanced Technologies for Electric Demand-side Management, Sorrento, Italy: International Energy Agency, 1991.
  [8] C. W. Gellings, and J. H. Chamberlin, Demand-side Management: Concepts and Methods. Lilburn, Georgia: Fairmont Press, Inc., 1993.
  

  Citation
  Deepak Pawar and D.K. Rai, "Design and Simulations of Load Management Impact on Power System," International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.6, pp.79-82, 2017