I. INTRODUCTION Wind waves are very complex in nature. The representation of a wave field is normally done by significant wave height and significant time period which retains much of the insight gained from theoretical studies. Wave prediction is the prediction of wave parameters based on the meteorological and oceanographic data. Wave forecasting is extremely useful in the planning and maintenance of the marine activities. The representation of a wave field by significant height and period has the advantages of retaining much of the insight gained from theoretical studies. Its value has been demonstrated in the solution of many engineering problems. A significant wave height is defined as the average height of the one-third highest waves and it is about equal to the average height of the waves as estimated by an experienced observer. During recent decades, some black-box models have been applied to simulate the wave and the wave heights.
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- Date of Publication: 08 October 2017
- Vinay Anand DhanvadaApplied Mechanics and Hydraulics Department, National Institute of Technology Karnataka, Surathkal, Karnataka, India.
- Dr. Paresh Chandra DekaAssociate Professor, Applied Mechanics and Hydraulics Department, National Institute of Technology Karnataka, Surathkal, Karnataka, India
. Aussem, A., Murtagh, F., (1997). Combing neural network forecasts on wavelet transformed time series. Connect Sci 10(1): 113-121. . Aytek, A., Kisi, O., (2008). A genetic programming approach to suspended sediment modelling. J. Hydrol. 351, 288-298. . Babovic, V., Kanizares, R., Jenson, H. R., Klinting, A., (2001). Neural networks as routine for error updating of numerical models. J. Hydrol. Eng. 127(3), 181-193. . Banzhaf, W., Nordin, P., Keller, R. E., and Francone, F. D. (1998), Genetic Programming: An Introduction: On the Automatic Evolution of Computer Programs and its Applications, Morgan Kaufmann. . Barricelli, Nils Aall (1954), Esempi numerici di processi di evoluzione, Methodos, pp. 45–68. . Brameier, M. and Banzhaf, W. (2007), Linear Genetic Programming, Springer, New York. . Cannas, B., Fanni, A., See. L., Sias, G., (2006). Data preprocessing for river flow forecasting using neural network: wavelet transforms and data partitioning. Phys Chem Earth 31(18): 1164-1171. . Chen, B. F., Wang, H. D., Chu, C. C., (2007). Wavelet and artificial neural network analysis of tide forecasting and supplement of tides around Taiwan and South China Sea.Ocean Engineering 34, 2161-2175. . Crosby, Jack, L. (1973), Computer Simulation in Genetics, John Wiley & Sons, London. . Cramer, Nichael Lynn (1985), "A representation for the Adaptive Generation of Simple Sequential Programs" in Proceedings of an International Conference on Genetic Algorithms and the Applications, Grefenstette, John J. (ed.), Carnegie Mellon University . Deka, P. C., Mandal, S., Prahlada, R., (2010). Multiresolution Wavelet-ANN model for significant wave height forecasting. Proceedings of National conference on hydraulics and water resources, HYDRO-2010, Dec 16-18th, 230-235. . Deka, P. C., Prahlada, R., (2012). Discrete Wavelet neural network approach in significant wave height forecasting for multistep lead time. Ocean Engineering 43, 32-42. . Deo, M. C., Naidu, C. S., (1999). Real time wave forecasting using neural network. Ocean Engineering 35, 191-203. . Falco, D., Cioppa, A. D., and Tarantino, E., (2005). A genetic programming system for time series prediction and its application to El Nino forecast. Adv. Soft Comput. 32(2005), 151-162. . Fogel, David B. (2000) Evolutionary Computation: Towards a New Philosophy of Machine Intelligence IEEE Press, New York. . Fogel, David B. (editor) (1998) Evolutionary Computation: The Fossil Record, IEEE Press, New York . Gaur, S., Deo, M. C., (2008). Real time wave forecasting using genetic programming. Ocean Engineering 35, 1166-1172. . Huang. M. C., (2002). Wavelet parameters and functions in wavelet analysis. Science Direct, Ocean engineering 31 (2004). 111-115. . Jain, P., and Deo, M. C., (2008), Artificial Intelligence Tools to Forecast Ocean Waves in Real Time. The Open Ocean Engineering Journal, 2008, 1, 13-20. . Kim, T., Valdes, J. B., (2003). Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks. ASCE journal of hydrology engineering 8 (6), 319-328. . Kinsman, B., (1965). Wind waves. Prentice Hall, Englewood Cliffs, NJ Kisi. O., (2009). Neural Networks and wavelet conjunction model for intermittent stream flow forecasting. ASCE journal of hydrology 14, 773-782. . Kisi O., Shiri J. and Nazemi A. H., (2011). Wavelet-Genetic programming model for predicting short-term and long-term air temperatures.Journal. Civil Eng. Urban. 1(1):25-37. . Labat, D., (2005). Recent advances in wavelet analysis, Part-I: A review of concepts. J Hydrol 314 (1-4): 275-288. . Lee, H. S., and Kwon, S. H., (2003). Wave profile measurement by wavelet transforms. Science Direct, Ocean Engineering 30 (2003).2313-2328. . Legates, D. R., and McCabe, G. J. Jr., (1999). Evaluating the use of goodness-of-fit measures in hydrologic and hydro climatic model validation. Water resource Research. 35(1), 233-241. . Mallet, S., (1998). A wavelet tour of signal processing. 2nd Ed., Academic Press, SanDiego, CA. . Massel, S. R., (2001). Wavelet analysis for processing of ocean surface wave records. Ocean Engineering 28, 957-987. . Nason. G. P., and Von Sachs. R., (1999). Wavelets in time series analysis. Philes. Trans. R. Soc., 357(1760), 2511-2526. . Nourani, V., Komasi, M., Mano, A., (2009). A multivariate ANN-Wavelet Approach for Rainfall-runoff modeling. Water resource Manage 23:2877-2894. Doi 10.1007/s11269-009-9414-5. . Nourani, V., Komasi, M., Kisi, O., (2011). Two hybrid artificial intelligence approaches for modeling rainfall-runoff process. Journal of hydrology 402, 41-59. . Nourani, V., Komasi, M., Mohammad Taghi Alami, (2012). Hybrid Wavelet-Genetic Programming approach to optimize ANN modeling of rainfall-runoff process. Journal of Hydrologic Engineering. (2012).17:724-741. . Ozger, M., (2010). Significant wave height forecasting using wavelet fuzzy logic approach. Ocean Engineering 37, 1443-1451. . Savic, A. D., Walters, A. G., Davidson, J. W., (1999). A genetic programming approach to rainfall-runoff modelling. Water Resour. Manage 13, 219-231. . Shaw. D., Miles. J., and Gray. A., (2004). Genetic programming within civil engineering. Organization of the adaptive computing in design and manufacture Conf. IEEE, New York. . Sivanandam. S. N., and Deepa. S. N., (2008). Introduction to genetic algorithms. Springer. Berlin, Heidelberg, Germany. . Shore Protection Manual. Coastal Engineering Research Centre, US Army Corps of Engineers, Washington, DC. . Suttasupa, Y., Rungraungsilp, S., Pinyopan, S., Wungchusunti, P., and Chongstitvatana, P., (2011). A Comparative Study of Linear Encoding in Genetic Programming, Ninth International Conference on ICT and Knowledge. ISBN 978-1 4577-2162-5/11. . Wang, W. and Ding. J., (2003). Wavelet network model and its application to the prediction of hydrology. Nature and science, 1(1). . Whigham, P. A., Crapper, P. F., (2001). Modeling rainfall-runoff using genetic programming. Mathematical and Computer Modeling 33(6-7): 707-721. . Zhou, H. C., Peng Y., and Liang, G. H., (2008). The research of monthly discharge Predictor-Corrector model based on wavelet decomposition. Water resource management (2008). 22:217-227.
Vinay Anand Dhanvada, Dr. Paresh Chandra Deka "A Hybrid Wavelet GP Model for Enhancing Forecasting Accuracy of Time Series Significant Wave Heights" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, October 2017 pp.01-04 URL: https://www.ijltemas.in/DigitalLibrary/Vol.6Issue10/01-04.pdf
ATM banking is a crucial aspect of today’s applied technology that offers unlimited possibilities as a strategy to attract and retain customers. In addition to that it has changed the pattern in performing their business. The Ethiopian banking industry is also shifting in the advent of this ATM technology to put both the banks and the customers in a win-win situation. Hence, the researcher attempted to study on the adoption of Automated Teller Machine (ATM) in Commercial Bank of Ethiopia (CBE) in Addis Ababa. The study was descriptive in nature and data were gathered through questionnaires and document analysis. In order to achieve the objective of the study, mixed use sampling techniques were used. A sample size of the study was (n = 320). Data collected with structured questionnaire was analysis by inferential statistics. The major results were the determinant variables have significantly affected the adoption of ATM in CBE in the case of Addis Ababa customers. Based on these findings, conclusions were drawn and some feasible recommendations were made. .
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- Date of Publication: 08 October 2017
- Professor (Dr.) K. S. Chandrasekar Professor and Head, Institutes of Management in Kerala (IMK), University of Kerala
- Essayas Taye Research Scholar in Institutes of Management in Kerala (IMK), University of Kerala.
. Abor, J.,(2004). Technological innovations and banking in Ghana: An evaluation of customers’ perceptions. American Academy of Financial Management, 1, 1-16, 2004. . Commercial Bank of Ethiopia (CBE): www.combanketh.et . Commercial Bank of Ethiopia (CBE): Annual report, 2016. https://www.combanketh.et/AboutUs/Publications/tabid/82/ItemId/16/Default.aspx . El-Haddad, A., and Almahmeed, M., (1992).ATM Banking Behaviour in Kuwait: A Consumer Survey. International Journal of Bank Marketing, Vol. 10 Issue: 3, pp.25-32 . Friday, D., and Mary, O., (2013). Adoption of automated teller machine in Nigerian banks: use enhancements and limitations. International Journal of Computer Science and Mobile Computing.Vol. 2, Issue. 8, August 2013, pg.14 – 23 . Horton, R. P., Buck, T., Waterson, P. E., & Clegg, C. W. (2001).Explaining intranet use with the technology acceptance model. Journal of Information Technology, 16(4), 237-249. . https://en.wikipedia.org/wiki/automatic teller machine. . Jamal, A., and Naser, K., (2002). Customer satisfaction and retail banking: an assessment of some of the key antecedents of customer satisfaction in retail banking. International Journal of Bank Marketing 20 (4) , pp. 146-160 . Judith J. Marshall, Louise A. Heslop, (1988) "Technology Acceptance in Canadian Retail Banking: A Study of Consumer Motivations and Use of ATMs", International Journal of Bank Marketing, Vol. 6 Issue: 4, pp.31-41 . Kolodinsky, J. M., Hogarth, J. M., and Hilgert, M. (2004). "The Adoption of Electronic Banking Technologies by US Consumers," The International Journal of Bank Marketing 22:(4), pp. 238- 259. . McKenzie, J. (2001). How teacher learn technology best. From Now On: The Educational Technology Journal, 10(6). . Olatokun and gbinedion (2009), The Adoption of Automatic Teller Machines in Nigeria: An Application of the Theory of Diffusion of Innovation. Issues in Informing Science and Information Technology Volume 6, 2009 . Rogers, Everett M. (1983) Diffusion of Innovations. Third Edition, Free Press, New York. . Sherry, L. (1997). The boulder valley internet project: Lessons learned. THE Technological Horizons in Education Journal, 25(2), 68-73. . www.americanbanker.com
Professor Dr. K. S. Chandrasekar, Essayas Taye "The Adoption of Automatic Teller Machines in Commercial Bank of Ethiopia" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.05-09 2017
Hbase is a distributed column-oriented database built on top of HDFS. Hbase is the Hadoop application to use when you require real-time random access to very large datasets. Hbase is a scalable data store targeted at random read and writes access of fully structured data. It's invented after Google's big table and targeted to support large tables, on the order of billions of rows and millions of columns. This paper includes step by step information to the HBase, Detailed architecture of HBase. Illustration of differences between apache Hbase and a traditional RDBMS, The drawbacks of Relational Database Systems, Relationship between the Hadoop and Hbase, storage of Hbase in physical memory. This paper also includes review of the Other cloud databases. Various problems, limitations, advantages and applications of HBase. Brief introduction is given in the following section.
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- Date of Publication: 08 October 2017
- Neseeba P.BDepartment of Computer Science & Engineering, P. A. College of Engineering, Mangalore, 574153, India
- Dr. Zahid AnsariDepartment of Computer Science & Engineering, P. A. College of Engineering, Mangalore, 574153, India
. Huang, Jian, et al. "High-performance design of hbase with rdma over infiniband." Parallel & Distributed Processing Symposium (IPDPS), 2012 IEEE 26th International.IEEE,2012 . Leavitt, Neal. "Will NoSQL databases live up to their promise?." Computer 43.2 (2010). . Lämmel, Ralf. "Google’s MapReduce programming model—Revisited." Science of computer programming 70.1 (2008): 1-30. . Carstoiu, D., A. Cernian, and A. Olteanu. "Hadoop hbase-0.20. 2 performance evaluation." New Trends in Information Science and Service Science (NISS), 2010 4th International Conference on. IEEE, 2010. . Lineland, HBaseArchitecute – 101 – Storage, Oct 12, 2009, https://www.larsgeorge.com/2009/10/hbase-architecture-101-storage.html . Junqueira, Flavio, and Benjamin Reed. ZooKeeper: distributed process coordination. " O'Reilly Media, Inc.", 2013. . Yingjie Shi, XiaofengMeng, Jing Zhao, Xiangmei Hu, Bingbing Liu and Haiping Wang, Benchmarking Cloud-based Data Management Systems, in Proceeding CloudDB ’10 Proceedings of the second international workshop on Cloud data management . Chris Bunch, Jonathan Kupferman and Chandra Krintz, Active Cloud DB: A Database-Agnostic HTTP API to Key-Value Datastores, April 2010 UCSB Tech Report 2010-07 . Hypertable.Eben Hewitt, Cassandra: The Definitive Guide, O’Reilly Media, November 2010, ISBN: 978-1-4493-904 Cassandra. https://cassandra.apache.org/ . Khetrapal, Ankur, and Vinay Ganesh. "HBase and Hypertable for large scale distributed storage systems." Dept. of Computer Science, Purdue University (2006): 22-28. . Wei-ping, Zhu, L. I. Ming-Xin, and Chen Huan. "Using MongoDB to implement textbook management system instead of MySQL." Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on. IEEE, 2011. . George, Lars. Hbase: The Definitive Guide: Random Access to Your Planet-Size Data. " O'Reilly Media, Inc.", 2011. . MemcacheDB.https://memcachedb.org/. . Voldemort. https://project-voldemort.com/. . AvinashLakshman and Prashant Malik, Cassandra: a decentralized structured storage system, ACM SIGOPS Operating Systems Review Volume 44 Issue 2, April 2010. . Blazhievsky, Serge. "Introduction to Hadoop, MapReduce and HDFS for Big Data Applications." SNIA Education (2013). . Nguyen, Phuong, et al. "A hybrid scheduling algorithm for data intensive workloads in a MapReduce environment." Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing. IEEE Computer Society, 2012.
Neseeba P.B, Dr. Zahid Ansari "Performance Analysis of Hbase" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.10-14 2017
Data-intensive computing is a paradigm to address the data gap and a platform to allow the advancement in research to process massive amounts of data and implement such applications which previously analyzed to be impractical or infeasible.The existing one-pass analytics algorithm observed to be data-intensive and contrarily requires the ability to efficiently process high volumes of data. MapReduce is supposed to be a programming model for processing large datasets using a cluster of machines. However, the existing MapReduce model is considerably not well-suited for high volume trimmer data, since it is towards batch processing and requires the data set to be fully loaded into the cluster before running analytical queries. This paper examines, from anefficiency standpoint, what the architectural design changes are necessary to bring the benefits of the MapReduce model and streaming algorithm to incremental, the existing MR algorithms. .
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- Date of Publication: 14 October 2017
- Mahesh S Nayak Research and Development Centre, Bharathiar University, Coimbatore – 641 046, India
- Dr. M. Hanumanthappa Professor, Department of Computer Science & Applications, Bangalore University, Bangalore, India
- Dr. B R Prakash Assistant Professor, Department of MCA, Sri Siddhartha Institute of Technology, Tumkur, India
- Dattasmita HV Assistant Professor, Govt. First Grade College, Tumkur, India
. A.M. Middleton. "Data-Intensive Technologies for Cloud Computing," Handbook of Cloud Computing. Springer, 2010. . Vinton Cerf. An Information Avalanche. IEEE Computer, Vol. 40, No. 1, 2007, pp. 104-105. . J.F. Gantz, D. Reinsel, C. Chute, W. Schlichting, J. McArthur, S. Minton, J. Xheneti, A. Toncheva, and A. Manfrediz, IDC. The Expanding Digital Universe Archived , March 10, 2013, at the Wayback Machine, White Paper, 2007. . P. Lyman, and H.R. Varian.How Much Information? 2003, University of California at Berkeley, Research Report, 2003. . F. Berman. Got Data? A Guide to Data Preservation in the Information Age, by Communications of the ACM, Vol. 51, No. 12, 2008, pp. 50-56. . Boduo Li, Edward Mazur, YanleiDiao, Andrew McGregor, Prashant Shenoy. A Platform for Scalable One-Pass Analytics using MapReduce,URL: https://people.cs.umass.edu/~mcgregor/ papers/11-sigmod.pdf . Alon Halevy, Peter Norvig, and Fernando Pereira. The unreasonable effectiveness of data, Communications of the ACM, 24(2):8–12, 2009. . Jimmy Lin and Chris Dyer. Data-Intensive Text Processing with MapReduce, April 11, 2010. URL: https://lintool.github.io/MapReduceAlgorithms/MapReduce-book-final.pdf. . Arthur Asuncion, Padhraic Smyth, and Max Welling. Asynchronous distributed learning of topic models , In Advances in Neural Information Processing Systems 21 (NIPS 2008), pages 81–88, Vancouver, British Columbia, Canada, 2008. . Ricardo Baeza-Yates, Carlos Castillo, Flavio Junqueira, VassilisPlachouras, and FabrizioSilvestri. Challenges on distributed web retrieval, In Proceedings of the IEEE 23rd International Conference on Data Engineering (ICDE 2007), pages 6–20, Istanbul, Turkey, 2007. . MapReduce Algorithm.URL: https://www.tutorialspoint.com/map_reduce /map_reduce_algorithm.htm . NogaAlon, Yossi Matias, and Mario Szegedy. The Space Complexity of Approximatingthe Frequency Moments. Journal of Computer and System Sciences, 58(1):137–147, 1999. 30, 116 . M.R. Henzinger, P. Raghavan, and S. Rajagopalan. Computing on data streams. Technical report, Digital Systems Research Center, 1998. URL https://www.eecs.harvard.edu/~michaelm/E210/ datastreams.pdf. 30 . J Feigenbaum, S Kannan, A McGregor, S Suri, and J Zhang. On Graph Problems in a Semi-Streaming Model. Theoretical Computer Science, 348(2-3):207– 216, 2005. 30 . Jon Feldman, S. Muthukrishnan, AnastasiosSidiropoulos, Clifford Stein, and ZoyaSvitkina. On the Complexity of Processing Massive, Unordered, Distributed Data. Arxiv, 2007. 30 . Brian Babcock, ShivnathBabu, MayurDatar, Rajeev Motwani, and Jennifer Widom. Models and issues in data stream systems. In PODS ’02: 21st Symposium on Principles of Database Systems, pages 1–30, New York, New York, USA, June 2002. ACM Press. ISBN 1581135076. 30 . Leonardo Neumeyer, Bruce Robbins, A. Nair, and A. Kesari. S4: Distributed Stream Computing Platform. In ICDMW ’10: 10th International Conference on Data Mining Workshops, pages 170–177. IEEE, 2010. 15, 23, 31 . Gul Agha. ACTORS: A Model of Concurrent Computation in Distributed Systems. MIT Press, December 1986. ISBN 0-262-01092-5. 23, 32, 118 . Data Intensive Computing. URL: https://en.wikipedia.org/wiki/Data-intensive_computing# cite_note-1 . Leonardo Neumeyer, Bruce Robbins, A. Nair, and A. Kesari. S4: Distributed Stream Computing Platform. In ICDMW ’10: 10th International Conference on Data Mining Workshops, pages 170–177. IEEE, 2010. 15, 23, 31 . MEster, H P Kriegel, J Sander, and X Xu. A density-based algorithm for discovering clusters in large spatial databases with noise. In KDD ’96: 2nd International Conference on Knowledge Discovery and Data mining, volume 1996, pages 226– 231. AAAI Press, 1996. . MihaelAnkerst, Markus M Breunig, Hans-Peter Kriegel, and Jörg Sander. OPTICS: Ordering points to identify the clustering structure. In SIGMOD ’99: 25th ACM International Conference on Management of Data, SIGMOD ’99, pages 49–60, New York, NY, USA, 1999. ACM. ISBN 1-58113-084-8. . Tamer Elsayed, Jimmy Lin, and Douglas W Oard. Pairwise document similarity in large collections with MapReduce. In HLT ’08: 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies, pages 265–268. Association for Computational Linguistics, June 2008. . RaresVernica, Michael J. Carey, and Chen Li. Efficient parallel set-similarity joins using MapReduce. In SIGMOD ’10: 36th International Conference on Management of Data, pages 495–506, New York, New York, USA, 2010. ACM Press. ISBN 9781450300322. . Gianmarco De FrancisciMorales .Big Data and theWeb: Algorithms forData Intensive Scalable Computing, IMT Institute for Advanced Studies Lucca, Italy2012.
Mahesh S Nayak, Dr. M. Hanumanthappa, Dr. B R Prakash, Dattasmita HV "Big Data and Web: An Efficient Algorithm Design for DISC" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.15-20 2017
In this paper we provide an efficient scheme for transmission of bit map images over MIMO system by employing spatial multiplexing. The image under test is compressed using bmp compression algorithm and all the pixels are transmitted with an optimal unequal power allocation algorithm. V BLAST or ZF receiver is selected for symbol detection and the image is reconstructed by decompression algorithm at the receiver. First of all the image to be transmitted is converted into bits and then headers and markers are added to the obtained bits. These bits are transmitted through the MIMO channel consisting of two transmitting and two receiving antennas. Spatial multiplexing technique is employed. Zero forcing equalization technique is employed at the receiver to get the output bits at the receiver then the reverse process is done to get the output image.
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- Date of Publication: 02 November 2017
- Harshal NigamAssistant Professor, Department of Electronics & Communication Engineering Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, Rajasthan, India
. G.J.Foschini, “Layered space-time architecture for wireless communication in a fading environment when using multielement antennas," BLTJ, Autumn, 1996 . David Tse and Pramod Viswanath”Fundamentals of Wireless Commu-nication”, Cambridge Universtiy Press, 2005 . X.Li, H.Huang, G.J.Foschini, and R.A.Valenzu,”Effects of Iterative Detection and Decoding on the Performance of BLAST", IEEE Global Telecommunications Conference, vol.2, pp.1061-10066, Nov 2000. . W.Yan and S.Sun,”Iterative Interference Cancellation and Decoding for Convolutional Coded VBLAST Systems", Information, Communications and Signal Processing 2003, vol.3, pp.1511-1515, Dec 2003. . S. Loyka and F. Gagnon. “Performance Analysis of the V-BLASTAlgorithm: An Analytical Approach”. 2002 International Zurich Seminar on Wireless Broadband. . Nirmalend. B and Rabindranath B. “Capacity and V-BLAST Techniques for MIMO Wireless Channel”. Journal of Theoretical and Applied Information Technology, 2005- 2010. . P. W. Wolniansky. G. J. Foschini. G. D. Golden and R. A. Valenzuela “V-BLAST: An Architecture for Realizing Very High Data Rates Over the Rich-Scattering Wireless Channel”. Bell Laboratories. . S. Loyka and F. Gagnon. “Performance Analysis of the V-BLASTAlgorithm: An Analytical Approach”. 2002 International Zurich Seminar on Wireless Broadband. . Taekyu Kim and Sin-Chong Park. “Reduced Complexity Detection for V-BLAST D Systems from Iteration Canceling”. 2008.
Harshal Nigam "Analysis of V Blast Technique for MIMO Structure through Image Processing at Various SNR" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.21-24 2017
This paper aims at implementing a Switched Reluctance Motor drive in sensor-based mode using dsPIC30F6010 motor control demo-board. For this purpose, initially the sensor-based and sensor-less control technique for the SRM drive have been studied. The simulation model in sensor-based operation has been developed in SIMULINK/MATLAB environment and the responses of the drive for different load torques and reference speeds have been obtained. The impact of varying firing angles, ON and OFF, of the control devices in each of the phases also has been analyzed. The sensor-less control technique that has been used here is Flux-current-theta method. This has also been simulated in the SIMULINK/MATLAB environment. Initially, the motor is run in stepper mode and later on it is run in open-loop with the help of rotor position signals. The sensor-based scheme also has been successfully implemented with outer speed loop and inner current loop. .
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- Date of Publication: 02 November 2017
- Shantanu Choudhary Lecturer (Electrical Engineering), Govt. Polytechnic College, Government of Rajasthan, Jodhpur, India – 302017
. Mahesh Krishnamurthy, Chris S. Edrington, and Babak Fahimi,“Prediction of Rotor Position at Standstill and Rotating Shaft Conditions in Switched Reluctance Machines”, IEEE Transactions On Power Electronics, Vol. 21, No. 1, pp. 225-233, January 2006. . T. A. Lipo, “Recent progress in the development of solid state AC motor drives”, IEEE Transactions on Power Electronics, Vol.3, No.2, pp. 105-117, January 1988. . B. K. Bose,“Evaluation of modern power semiconductor devices and future trends of converters”, IEEE Transactions on Industry Applications, Vol. IA-28, No. 2, pp. 403-413, March-April 1992. . T. J. E. Miller,“Switched Reluctance Motor and their control”, Magna Physics Publishing and Clarendon Press, Oxford, 1993. . Bimal K. Bose,T. J. E. Miller,Paul M. Szczesny andWilliam H. Bicknell, “Micro Computer Control Of Switched Reluctance Motor”, IEEE Transactions On Industry Applications, Vol. IA-22, No. 4, pp. 708-714, July-August 1986. . T. J. E. Miller, “Electronic control of Switched Reluctance Motor– A reference book of collected papers”, Reed Educational and Professional Publishing Ltd., Oxford, 2001. . F. Soaresand P.J. Costa Branco,“Simulation of a 6/4 Switched Reluctance Motor based on Matlab/Simulink Environment”, IEEE Transaction on Aerospace and Electronic Systems, Vol.37, No.3, pp. 989-1009, 2001. . G. Bhuvaneshwari,Sarit Guha Thakurta,P. Srinivasa Rao and S. S. Murthy, “Modeling of switched reluctance motor in sensorless and ‘with sensor’ modes”, Journal of Power Electronics, Vol. 6 No. 4, JPE 6-4-5, pp. 315-321, October 20, 2006. . Debiprasad Panda and V. Ramanarayanan, “An Accurate Position Estimation Method for Switched Reluctance Motor Drive”, International Conference on Power Electronics Drives and Energy Systems (PEDES'98), Perth, Australia, pp. 523-528, December, 1998. . Debiprasad Panda and V. Ramanarayanan,“Sensor less control of Switched reluctance motor drive with self –measured flux – linkage characteristics” in PESC Record - IEEE Annual Power Electronics Specialists Conference, pp. 1569-1574, 2000. . B. J. Baliga, “Power semiconductor devices for variable frequency drives”, Proceedings of IEEE Conference, Vol. 82, No. 8, pp. 1112-1122, August 1994. . T. Kanokvate,K. Seubsuang, J. Prapon, S. Pakasit, Akira Chiba and Fukao Tadashi, “An Improvement on Position Estimation and Start up Operation for Switched Reluctance Motor Drives” IEEE Power Engineering Society General Meeting, pp. 1-6, June 2007. . V. Ramnarayanan, L. Venkatesha and Debiprasad Panda,“Flux Linkage characteristics of Switched Reluctance Motor”, Proceedings of the 1996 International Conference on PEDES for Industrial Growth 1996,, Vol.1, pp. 281-285, 8-11 January 1996. . Virendra Kumar Sharma,S. S. Murthy and Bhim Singh. “An Improved Method for the Determination of Saturation Characteristics of Switched Reluctance Motors”, IEEE Transactions on Instrumentation and Measurement, Vol. 48, No. 5, pp. 995-999, October 1999. . Komatsuzaki, T. Bamba and I. Miki, “A Position Sensor-less Speed Control for Switched Reluctance Motor at Low Speeds”, Proceeding of IEEE Power Engineering Society General Meeting, pp. 1-7, June 2007. . J. T. Bas, M. Ehsani and T. J. E. Miller, “Robust torque control of Switched reluctance motors without a shaft position sensor”, IEEE Transaction on Industrial Electronics, Vol.1E-33, No. 3, pp. 212-216, August 1986. . Hamid, Ehsan,Akhter, Virendra K. Sharma, A. Chandra and Al-Haddad,“Performance Simulation of Switched Reluctance motor Drive system Operating With Fixed Angle Control Scheme”,PCIM, USA, pp. 373-378, 2001. . Jin-Wo Ahn, Young-Joo An, Cheol-Je Jeo and Young Moon Hwang, “Fixed Switching Angle Control Scheme for SRM Drive”, IEEE Conference Record of Applied Power Electronics Conference (APEC’96), pp. 963-967, 1996. . V. K. Sharma, “Analysis and Control of Switched Reluctance Motors” Ph.D Thesis, Dept. of Electrical Engg., IIT DELHI, December 1999. . P. Srinivasa Rao, “Simulation and DSP based implementation of SRM Drive” M.S. Thesis, Dept. of Electrical Engg., IIT DELHI. . T. J. E. Miller, “Brushless Permanent-Magnet and Reluctance Motor Drives.” Clarendon Press, Oxford, 1989
Shantanu Choudhary "“A Study of Response of Switched Reluctance Motor SRM In Sensor-Based and Sensor-Less Control Mode”" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.25-30 2017
The thermoplastic materials, which has the capacity to withstand tensile pressure of more than 400 Kg/cm2 and temperature of more than 1000C considered as engineering thermoplastics. In this paper, a new composite of Nylon 66 has been prepared by adding micron-sized calcium carbonate (CaCO3) filler aiming in improvement of the mechanical properties of Nylon 66. Directly a standard specimen is prepared by injection moulding process, it is a cyclic process of forming plastic into a desired shape by forcing the material under pressure into a cavity.
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- Date of Publication: 04 November 2017
- Ranjan MajhiAsst. Professor, Department of Mechanical Engg. Bhubaneswar Engineering College, Bhubaneswar, Odisha, India
- B.P. MishraAsst. Professor, Department of Mechanical Engg. Bhubaneswar Engineering College, Bhubaneswar, Odisha, India
- P. PandaAsst Professor, Department of Mechanical Engg, Government College of Engineering, Odisha, India
. Cho, M.H., Bahadur, S., 2005. Study of the tribological synergistic effects in nano CuO-filled and fibre-reinforced polyphenylene sulphide composites. Wear 258, 835–845. . Cho, M.H., Bahadur, S., Pogosian, A.K., 2005. Friction and wear studies using Taguchi method on polyphenylene sulphide filled with a complex mixture of MoS2, Al2O3, and other compounds. Wear 258, 1825 – 35. . Difallah, B., Kharrat, M., Dammak, M., Monteil, G., 2012. Mechanical and tribological response of ABS polymer matrix filled with graphite powder. Materials and Design 34, 782–787. . Jiang, L., Lam, Y.C., Tam, K.C., Chua, T.H., Sim, G.W., Ang, L.S., 2005. Strengthening acrylonitrile-butadiene-styrene (ABS) with nano-sized and micron-sized calcium carbonate. Polymer Journal 46 243–252. . Liang, J., 2005. Mechanical properties of hollow glass bead-filled ABS composites. Journal of Thermoplastics Composites Material 18, 407-416. . Lin, Y., Gao, C., Li, N., 2006. Influence of CaCO3 whisker content on mechanical and tribological properties of polyether-ketone composites. Journal of Material Science Technology 22, 584–588. . Minitab User Manual., 2001. Making data analysis easier, MINITAB Inc., USA. Ozcelik, B., Sonat, I., 2009. . Warpage and structural analysis of thin shell plastic in the plastic injection moulding. Materials and Design 30, 367–375. . Rashmi, N., Renukappa, M., Suresha, B., Devarajaiah, R.M., Shivakumar, K.N., 2011. Dry sliding wear behaviour of organo-modified montmorillonite filled epoxy nanocomposites using Taguchi’s techniques. Materials and Design 32, 4528–3.
Ranjan Majhi, B.P. Mishra, P. Panda "Preparation and Study of Mechanical Properties of Nylon 66 / CaCO3 Engineering Thermoplastic Composite" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.31-34 2017
Wood is natural organic material which is obtained from tree stem; it is used for various purpose, and sawmill is the place where wood is brought into required shape and size, with the help of rotating saw blades. Worker’s during giving feed to the saw blade, accidents are prone to occur, if their hands are moving near the saw blade, which may result in hand amputation, and to avoid the consequence this design of saw blade assembly which include IR sensors comes handy and increases safety, these sensors are placed near the saw blade, if unknowingly, worker’s hands come close to the blade while feeding wood, it recognises the human hand and stops the rotating saw blade immediately and avoids accidents. .
- Page(s): 35-37
- Date of Publication: 04 November 2017
- K M ChethanAssistant Professor, Department of Mechanical Engineering, PA college of Engineering, Mangalore, India
- N RudreshaAssistant Professor, Department of Mechanical Engineering, PA college of Engineering, Mangalore, India
- Yathin KrishnaAssistant Professor, Department of Mechanical Engineering, PA college of Engineering, Mangalore, India
- AvinashAssistant Professor, Department of Mechanical Engineering, PA college of Engineering, Mangalore, India
. Infrared detectors, second edition, by Antonio Rogalski. . Sensors and transducers, third edition, by R.Sinclair. . N. Maluf,”An Introduction To Microelectromechanical Systems Engineering” (Second ed.) , Artech House, Boston (2004). . Theory of Machines, fourth edition, by SS Rattan. . Schajer, 1992, G.S. Schajer, North American techniques for circular saw tensioning and leveling: practical measurement methods Holz als Roh-und Werkstoff, 50(3)(1992),pp. 111
K M Chethan, N Rudresha, Yathin Krishna, Avinash "Application of Infrared Sensors to Improve Safety in Saw Mill" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.35-37 2017
To cater the needs of industry as well as society, it’s the proper time to deploy the IOT based technology to monitor different operations. Automation concept is coming in each and every sector to automate every operation. The leading technology partners such as Amazon, Microsoft & IBM have invented different IOT based platforms to automate the processes as well as operations.Now a day, every industry is trying their best to deploy IOT based services to connect each and every thing. By using AWS IOT platform, it’s very easy to interface different gateways such as Raspberry Pi and Arduino board. In this paper the Raspberry Pi is connected with AWS IOT platform for remote monitoring of any industrial as well as commercial application. Connections with remote locations can easily achieved by using messaging protocol such as MQTT (Message Queue Telemetry Transport). The publish-subscribe pattern requires a message broker. The broker is responsible for distributing messages to interested clients based on the topic of a message.
- Page(s): 38-42
- Date of Publication: 02 November 2017
- Deepak B. AndoreBalaji Institute of Telecom & Management, Pune, 411033, India
. Q. Jing, A. V. Vasilakos, J. Wan, J. Lu, and D. Qiu, “Security of the internet of things: perspectives and challenges,” WirelessNetworks, vol. 20, no. 8, pp. 2481–2501, 2014. . C.-W. Tsai, C.-F. Lai, and A. V. Vasilakos, “Future internet of things: open issues and challenges,” Wireless Networks, vol. 20, no. 8, pp. 2201–2217, 2014. . ABI Research. 9 May 2013 . Gartner. 10 November 2015. Retrieved 21 April 2016 . Davies, Nicola. "How the Internet of Things will enable 'smart buildings'". Extreme Tech. . "Molluscan eye". Retrieved 26 June 2015 . Li, Shixing; Wang, Hong; Xu, Tao; Zhou, Guiping (2011. “Application study on Internet of Things in Enviornment Protection Field”. Lecture Notes in Electrical Engineering Volume. Lecture Notes in Electrical Engineering. 133: 99–106. ISBN 978-3-642-25991-3. doi:10.1007/978-3-642-25992-0_13 . Gubbi, Jayavardhana; Buyya, Rajkumar; Marusic, Slaven; Palaniswami, Marimuthu (24 February 2013). "Internet of Things (IoT): A vision, architectural elements, and future directions". Future Generation Computer Systems. . V. M. Rohokale, N. R. Prasad, and R. Prasad, “A cooperative internet of things (IoT) for rural healthcare monitoring and control,” in Wireless Communication, Vehicular Technology, Information Theory and Aerospace &Electronic Systems Technology (Wireless VITAE), Second International Conference on. IEEE, 2011, pp. 1–6. . C. Doukas and I. Maglogiannis, “Bringing IoT and cloud computing towards pervasive healthcare,” in Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), Sixth International Conference on. IEEE, 2012, pp. 922–926. . S. Amendola, R. Lodato, S. Manzari, C. Occhiuzzi, and G. Marrocco, “RFID technology for IoT-based personal healthcare in smart spaces,” IEEE Internet of Things Journal, vol. 1, no. 2, pp. 144–152, 2014. . A. N. Andy Stanford-Clark, “MQTT Version 3.1.1”, OASIS Std., October 2014. [Online]. Available: https://docs.oasisopen.org/mqtt/mqtt/v3.1.1/mqtt-v3.1.1.html . R. Fielding, J. Gettys, J. Mogul, H. Frystyk, L. Masinter, P. Leach, and T. Berners-Lee, “Hypertext transfer protocol–http/1.1,” 1999. . Z. Shelby, K. Hartke, and C. Bormann, “The constrained application protocol (CoAP),” 2014. . N. De Caro, W. Colitti, K. Steenhaut, G. Mangino, and G. Reali, “Comparison of two lightweight protocols for smartphone-based sensing,” in Communications and Vehicular Technology in the Benelux (SCVT), Twentieth Symposium on. IEEE, 2013, pp. 1–6.
Deepak B. Andore "AWS IOT Platform based Remote Monitoring by using Raspberry Pi" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.38-42 2017
Exploiting computational precision can improve performance significantly without losing accuracy in many applications. To enable this, we propose an innovative arithmetic logic unit (ALU) architecture that supports true dynamic precision operations on the fly. The proposed architecture targets fixed-point ALUs. In this paper we focus mainly on the precision controlling mechanism and the corresponding implementations for fixed-point adders and multipliers. We implemented the architecture on Xilinx Virtex-5 XC5VLX110T FPGAs, and the results show that the area and latency overheads are 1% ~ 24% depending on the structure and configuration. This implies the overhead can be minimized if the ALU structure and configuration are chosen carefully for specific applications. The VHDL coded synthesizable RTL code of the Fixed Point Arithmetic core has a complexity. We verified the functions of the Fixed Point Arithmetic by a simulation with a single instruction test as the first step and implemented the Fixed Point Arithmetic with the FPGA.
- Page(s): 43-45
- Date of Publication: 02 November 2017
- Neelesh Kumar KachhwahaM. Tech (VLSI Design) Gyan Ganga Institute of Technology and Sciences Jabalpur, MP India
- Prof. Sunil Shah Dept. of ECE Gyan Ganga Institute of Technology and Sciences Jabalpur, MP India
. Accuracy-aware processor customisation for fixed-point arithmetic Shervin Vakili ✉, J.M. Pierre Langlois, Guy Bois IET Comput. Digit. Tech., 2016, Vol. 10, Iss. 1, pp. 1–11 . J. Kurzak and J. Dongarra, "Implementation of mixed precision in solving systems of linear equations on the Cell processor: Research Articles," Concurr. Comput. : Pract. Exper., vol. 19, pp. 1371-1385, 2007. . J. Langou, J. Langou, P. Luszczek, J. Kurzak, A. Buttari, and J. Dongarra, "Exploiting the performance of 32 bit floating point arithmetic in obtaining 64 bit accuracy (revisiting iterative refinement for linear systems)," presented at the Proceedings of the 2006 ACM/IEEE conference on Supercomputing, Tampa, Florida, 2006. . J. Lee and G. D. Peterson, "Iterative Refinement on FPGAs,"in Application Accelerators in High-Performance Computing (SAAHPC), 2011 Symposium on, 2011, pp. 8-13. . A. R. Lopes, A. Shahzad, G. A. Constantinides, and E. C.Kerrigan, "More flops or more precision? Accuracy parameterizable linear equation solvers for model predictive control," in IEEE Symposium on Field Programmable Custom Computing Machines, Napa, California, 2009. . J. Sun, G. D. Peterson, and O. O. Storaasli, "High-Performance Mixed-Precision Linear Solver for FPGAs,"IEEE Trans. Comput., vol. 57, pp. 1614-1623, 2008. . Yiannacouras, P., Steffan, J.G., Rose, J.: ‘Exploration and customization of FPGA-based soft processors’, IEEE Trans. Comput.-Aided Design Int. Circuits Syst., 2007, 26, (2), pp. 266–277 . Mishra, P., Dutt, N.: ‘Architecture description languages for programmable embedded systems’, IEE Proc. Comput. Digit. Tech., 2005, 152, (3), pp. 285–297 . Lee, D.U., Gaffar, A.A., Cheung, R.C.C., Mencer, O., Luk, W., Constantinides, G. A.: ‘Accuracy-guaranteed bit-width optimization’, IEEE Trans. Comput.-Aided Design Integr. Circuits Syst., 2006, 25, (10), pp. 1990–2000 . Yu, P., Radecka, K., Zilic, Z.: ‘An efficient method to perform range analysis for DSP circuits’. Int. Conf. on Electronics, Circuits, and Systems (ICECS), December 2010, pp. 855–858 . Vakili, S., Langlois, J.M.P., Bois, G.: ‘Customised soft processor design: a compromise between architecture description languages and parameterisable processors’, IET Comput. Digit. Tech., 2013, 7, (3), pp. 122–131 . Cong, J., Gururaj, K., Liu, B., et al.: ‘Evaluation of static analysis techniques for fixed-point precision optimization’. IEEE Symp. on Field Programmable Custom Computing Machines, 2009, pp. 231–234. . Le Gal, B., Casseau, E.: ‘Word-length aware DSP hardware design flow based on high-level synthesis’, J. Signal Process. Syst., 2011, 62, (3), pp. 341–357. . Menard, D., Herve, N., Sentieys, O., Nguyen, H.N.: ‘High-Level synthesis under fixed-point accuracy constraint’, J. Electr. Comput. Eng., 2012, pp. . Vakili, S., Langlois, J.M.P., Bois, G.: ‘Finite-precision error modeling using affine arithmetic’. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), May 2013, pp. 2591–2595
Neelesh Kumar Kachhwaha, Prof. Sunil Shah "Implementation of Efficient Fixed Point ALU with 32 Bit Processing Capability" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 10, pp.43-45 2017