Drilling is an important process for making and assembling components made from Glass Fiber Reinforced Plastic (GFRP). Various processes like conventional drilling, vibration assisted drilling and ultrasonic assisted drilling have been attempted in order to maintain the integrity of the material and obtain the necessary accuracy in drilling of GFRP. In conventional machining feed rate, tool material and cutting speed are the most influential factor in the machining of GFRP. This paper attempts to show effect of material thickness and ultrasonic machine parameters like amplitude and pressure on material removal rate while ultrasonic machining of glass fiber reinforced plastic.
B. V. Kavad
Mechanical Engineering Department, Dr. J. N. Mehta Government Polytechnic, Amreli, Gujarat, India.
K. S. Vaghosi
Mechanical Engineering Department, Government Engineering College, Rajkot, Gujarat, India.
**[1] ASM Handbook (2002). Volume: 21 composites (pp. 27–34, 940, 951). USA. [2] Pihtili, H., & Tosun, N. (2002). Investigation of the wear behaviour of a glass-fibrereinforced composite and plain polyester resin. Composites Science and Technology, 62, 367–370. [3] Faraz A, Biermann D and Weinert K. Cutting edge rounding: an innovative tool wear criterion in drilling CFRP composite laminates. Int J Mach Tools Manuf 2009; 49: 1185–1196. [4] J. Campos Rubioa,\_, A.M. Abraoa, P.E. Fariaa, A. Esteves Correiab, J. Paulo Davimc. Effects of high speed in the drilling of glass fibre reinforced plastic: Evaluation of the delamination factor. International Journal of Machine Tools & Manufacture 48 (2008) 715–720. [5] J. Ramkumara, S.K. Malhotra R. Krishnamurthy. Effect of work piece vibration on drilling of GFRP laminates. Journal of Materials Processing Technology 152 (2004) 329–332. [6] P. Mehbudia, V. Baghlania, J. Akbaria, A.R. Bushroab, N.A. Mardib. Applying ultrasonic vibration to decrease drilling-induced delamination in GFRP laminates. Procedia CIRP 6 ( 2013 ) 578 – 583. [7] B. V. Kavad, A.B.Pandey, M.V.Tadavi, H.C.Jakharia , A Review Paper on, “Effects of Drilling on Glass Fiber Reinforced Plastic”, Procedia Technology 14 (2014 ) 457 – 464. [8] K.S.Vaghosi and B. V. Kavad. Modeling Ultrasonic Machining Process using Fuzzy Inference System. International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) Volume VI, Issue VI, June 2017 | ISSN 2278-2540**
B. V. Kavad, K. S. Vaghosi "Effect of Material Thickness and Ultrasonic Machine Parameters on Material Removal Rate While Ultrasonic Machining of Glass Fiber Reinforced Plastic" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.01-05 2017
The aim of the current research is to extract the knowledge from stock market data to help investors make more profit. We have used NSE (National Stock Exchange) historical data for six years. We have also pre-processed stock market data. We have used hybrid method which consists of two widely used algorithms FP-growth to find frequent patterns and Discovery rule algorithm proposed by Agrawal’94 to get association rules for two different steps of association rule mining. The main focus in our research has been the accuracy of the rules. The goal of the research is to find dependencies among different stock companies in the stock market and generate rules from inter-day transactions that would benefit stock market traders. .
Pandya Jalpa P.
Asst. Professor, UCCC & SPBCBA & SDHG College of BCA & IT, Udhna, Surat, India
Morena Rustom D.
Professor, Department of Computer ScienceVeer Narmad South Gujarat University, Surat, India
Pandya Jalpa P., Morena Rustom D. "A Novel Hybrid Method for Generating Association Rules for Stock Market Data" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.06-15 2017
Divya Goyal, Dr. Pramod S Nair, D.Srinivasa Rao·July 2017·pp. 16-22
Text mining technique is used to detect the required patterns from the text documents. The nature of text document is an unstructured format where the data is represented in an unstructured manner. The text mining can be used for information retrieval, information extraction, search, classification, and categorization. In this context, an application of text mining is proposed in this work. That effectively analyzes the context of word utilization and provides their context as class label. The proposed work is a model of text classification for detection of illegal use of words in text communication. Thus the proposed technique works in two modules first it trained with the different context of the text and then uses the features to classify the upcoming text as testing. During training, the word probability and the word’s domain wise probability is estimated. Additionally, this information keeps preserved in a database for testing purpose. In the next, phase the testing of the system initiated through the training database and a test set supplied by the experimenter. During this process, all the sentences in a testing datasets are evaluated for computing the sentence probability and correlation estimation. Further, both the parameters are used to compute the weights. These weights are converted into a different indicator named as weight transform. Finally, a threshold is computed for making a decision. The proposed objectionable content detection technique using probability model and correlation is developed using JAVA environment. The implemented model is evaluated and compared with respect to their classical version of objectionable content detection. Results show the improvement made on traditional work improves their ability in terms of accuracy. Thus the model is acceptable for real world applications too.
Divya Goyal
Research Scholar, Department of CSE, MITM, Indore, M.P., India
Dr. Pramod S Nair
Professor, Department of CSE, MITM, Indore, M.P., India
D.Srinivasa Rao
Associate Professor, Department of CSE, MITM, Indore, M.P., India
**[1] Vishal Gupta and Gurpreet S. Lehal, “A Survey of Text Mining Techniques and Applications” Journal of Emerging Technologies in Web Intelligence, Vol. 1, No. 1, August 2009. [2] Delmater R and Hancock M, Data Mining explained-a manager’s guide to customer-centric business intelligence (Digital Press, Boston) 2002. [3] Tan, Ah-Hwee, "Text mining: The state of the art and the challenges", Proceedings of the PAKDD 1999 Workshop on Knowledge Discovery from Advanced Databases, Volume 8, 1999. [4] Duan, Jiangjiao, and Jianping Zeng, "Web objectionable text content detection using topic modeling technique", Expert Systems with Applications 40.15 (2013): 6094-6104. [5] D. Jurafsky and J. H. Martin, Speech and Language Processing: An introduction to Natural language Processing, Computational Linguistics and Speech Recognition. United States of America: Prentice Hall, 2009 [6] Amrut M. Jadhav and Devendra P. Gadekar, “A Survey on Text Mining and Its Techniques”, International Journal of Science and Research (IJSR), Volume 3 Issue 11, November 2014**
Divya Goyal, Dr. Pramod S Nair, D.Srinivasa Rao "Twitter Text Objectionable Content Detection using Domain Based Probability and Correlation Model" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.16-22 2017
Natural rubber (NR) vulcanizates prepared using non-regulated nitrosamine generating accelerators such as tertiarybutyl benzothiazolesulfenamide (TBBS) and tetrabenzyl thiuramdisulfide (TBzTD) are reported to be safe and non-carcinogenic. The difficulties during processing of silica-filled NR compounds could be overcome by incorporating silane coupling agent to the silica-rubber mix to improve the interactions between rubber and silica. The work reported in this paper is an attempt to replace the expensive silane coupling agent (Si69) with a modified form of natural rubber, i.e. epoxidised natural rubber (ENR) in safe accelerators incorporated formulation. The silica-filled ENR modified NR vulcanizates show lower optimum cure time compared to silane modified vulcanizate. Silica-filled NR vulcanizates modified with ENR show improved mechanical properties compared to the unmodified silica-filled natural rubber vulcanizate.
Abhitha K.
Department of Polymer Science and Rubber Technology, Cochin University of Science and Technology, Kochi –682022, Kerala, India
Thomas Kurian
Department of Polymer Science and Rubber Technology, Cochin University of Science and Technology, Kochi –682022, Kerala, India, , , **
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Abhitha K. and Thomas Kurian "Epoxidised Natural Rubber - A Substitute for Silane Coupling Agent in Safe Silica-Filled Natural Rubber Formulations" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.23-29 2017
As the interest for cloud computing keeps on increasing, cloud specialist organizations are confronted with the overwhelming test to meet the targeted SLA agreements, as far as dependability and convenient execution is concerned, while accomplishing cost and energy efficiency. This paper proposes Shadow Replication, a novel fault-tolerance mechanism for cloud computing, which flawlessly addresses fault at scale, while limiting energy utilization and lessening its effect on cost. Energy conservation is achieved by creating dynamic cores rather than static cores. Cores are created by the application of cloudlets. In other words proportionate cores are created. Core failure metrics are considered to be memory capacity, energy and power consumption. In case any of the parameter exceeded threshold value, core is supposed to be faulted and progress is maintained within shadow which is maintained 1 per VM. Progress of deteriorated core is shifted to next core within same VM. In case all the cores within the VM deteriorate, VM migration is performed. Results obtained by allocating cores dynamically reduce energy consumption, latency, cost and maximize fault tolerance rate because of reduced VM migration overhead.
Navpreet Kaur Gill
Department of Computer Engineering & Technology,Guru Nanak Dev University Amritsar, Punjab, India
Kamaljit Kaur
Department of Computer Engineering & Technology,Guru Nanak Dev University Amritsar, Punjab, India
**[1] Meroufel and Belalem, G., (2014). “Adaptive time-based coordinated checkpointing for cloud computing workflows,” Scalable Comput., vol. 15, no. 2, pp. 153–168. [2] Kliazovich, D., Bouvry, P., and Khan, S. U., (2012). “GreenCloud : A Packet-level Simulator of Energy- aware Cloud Computing Data Centers,” J. Supercomput., vol. 62, no. 3, pp. 1263–1283, [3] Milani, B. A. and Navimipour, N. J., (2016). “A comprehensive review of the data replication techniques in the cloud environments: Major trends and future directions,” J. Netw. Comput. Appl., vol. 64, pp. 229–238. [4] Zhu, Q. and Zhou, Y., (2005). "Power-Aware Storage Cache Management." IEEE Trans. Computers, vol. 54, no. 5, pp. 587-602 . [5] Brown, R., Masanet, E., Nordman, B., Tschudi, B. , Shehabi, A., Stanley, J., Koomey, J., Sartor, D., Chan., P., (2008). Report to Congress on Server and Data Center Energy Efficiency (LBNL-363E), public law 109–431, Lawrence Berkeley National Laboratory, Berkeley, CA . [6] Aupy, G., Benoit, A., Diouri, M. E. M., Glück, O., Lefèvre, L.,(2015).“Energy-Aware Checkpointing Strategies,” In Fault-Tolerance Techniques for High-Performance Computing, pp. 279-317, Springer International Publishing, pp. 279–317. [7] Diouri, M. E. M., Gluck, O. , Lefevre, L. and Cappello, F., (2013). “ECOFIT: A Framework to Estimate Energy Consumption of Fault Tolerance Protocols for HPC Applications,” Proc. IEEE/ACM thirteenth Int. Symp. Cluster, Cloud and Grid Computing (CCGrid 2013), pp. 522–529. [8] Diouri, M. E. M., Glück, O., Lefèvre, L. and Cappello, F.,(2013). “Towards An Energy Estimator for Fault Tolerance Protocols,” J. ACM SIGPLAN Notices, vol. 48, no. 8, pp. 313-314. [9] Ibtesham, D., Debonis, D., Arnold, D. and Ferreira, K. B., (2014). “Coarse-Grained Energy Modeling of Rollback/Recovery Mechanisms,” Proc. IEEE/IFIP Forty-forth Annu. Int. Conf. Dependable Systems and Networks (DSN 2014), pp. 708–713. [10] Diouri, M. E. M., Gluck, O., Lefevre, L. and Cappello, F., (2012). “Energy Considerations in Checkpointing and Fault Tolerance Protocols,” Proc. IEEE forty-two- Int. Conf. Dependable Systems and Networks Work. (DSN-W 2012), pp. 3–8. [11] Mills, B. N., Grant, R. E., Ferreira, K. B. and Riesen, R., (2013). “Evaluating Energy Savings for Checkpoint/Restart,” Proc. first Int. Work. Energy Efficient Supercomputing (E2SC 2013), pp. 61–68. [12] Saito, T., Sato, K., Sato, H., and Matsuoka, S., (2013). “Energy-Aware I/O Optimization for Checkpoint and Restart on a NAND Flash Memory System,” Proc. Third Work. Fault-tolerance for HPC at Extreme scale (FTXS ’13), pp. 41–48. [13] Helary, J. M., Mostefaoui, A., Netzer, R. H. B. and Raynal, M. , (1997). “Preventing Useless Checkpoints in Distributed Computations,” Proc. IEEE sixteenth Symp. Reliable Distributed Systems, pp. 183–190. [14] Sayed, N.E. and Schroeder, B., (2014). “To Checkpoint or Not to Checkpoint: Understanding Energy-Performance-I/O Tradeoffs in HPC Checkpointing,” Proc. IEEE Int. Conf. Cluster Computing (CLUSTER 2014), pp. 93–102, 2014. [15] Aupy, G., Benoit, A., Melhem, R., Renaud-Goud, P. and Robert, Y., (2013). “Energy-Aware Checkpointing of Divisible Tasks with Soft or Hard Deadlines,” Proc. IEEE Int. Conf. Green Comput. (IGCC 2013), pp.1-8. [16] Ananthanarayanan, G., Agarwal, S., Kandula, S., Greenberg, A., Stoica, I., Harlan, D., Harris, E., (2011). "Scarlett: coping with skewed content popularity in mapreduce clusters." Proc. ACM sixth Conf. Computer systems, pp. 287-300.. [17] Abad, C. L., Lu, Y. and Campbell, R. H., (2011). “DARE: Adaptive data replication for efficient cluster scheduling,” Proc. IEEE Int. Conf. Cluster Computing (ICCC), pp. 159–168. [18] Ranganathan, K., Iamnitchi, A. and Foster, I., (2002). “Improving data availability through dynamic model-driven replication in large peer-to-peer communities,” Proc. IEEE/ACM second Int. Symp. Cluster Computing and the Grid (CCGrid 2002), pp. 0–5. [19] Chang, R.S., Chang, H.P., Wang, Y.T., (2008). "A dynamic weighted data replication strategy in data grids." Proc. IEEE/ACS Int. conf. Computer Systems and Applications (AICCSA 2008), pp. 414-421. [20] Weddle, C., Oldham, M. , Qian, J. I. N., Wang, A. A., Reiher, P. and Kuenning, G., (2007). “PARAID : A Gear-Shifting Power-Aware RAID,” ACM Trans. Storage (TOS) , vol. 3, no. 3. [21] Kim, J. and Rotem, D.,(2012). “FREP: Energy proportionality for disk storage using replication,” J. Parallel and Distributed Computing, vol. 72, no. 8, pp. 960–974. [22] Wan, J., Yin, C., Wang, J., Xie, C., (2012). “A new high-performance, energy-efficient replication storage system with reliability guarantee,” Proc. IEEE Symp. Mass Storage Systems and Technologies (MSST), pp.1-6. [23] Boru, D., Kliazovich, D., Granelli, F., Bouvry, P. and Zomaya, A. Y., (2015). “Energy-efficient data replication in cloud computing datacenters,” J. Cluster Compuing ., vol. 18, no. 1, pp. 385–402. [24] Boru, D., Kliazovich, D., Granelli, F., Bouvry, P. and Zomaya, A. Y. (2013). “Energy-efficient data replication in cloud computing datacenters,” Proc. IEEE Work. Globecom Work. (GC Wkshps), pp. 446–451. [25] Lin, Y. and Shen, H., (2017). “EAFR: An Energy-Efficient Adaptive File Replication System in Data-Intensive Clusters,” IEEE Trans. Parallel and Distributed Systems, vol. 28, no. 4, pp. 1017–1030. [26] Kaushik, R. T., (2010). “GreenHDFS : Towards An Energy-Conserving , Storage-Efficient , Hybrid Hadoop Compute Cluster,” Proc. USENIX Int. conf. Power aware computing and systems (HotPower'10), pp. 1–9. [27] Lang, W., Patel, J. M. and Naughton, J. F., (2010). “On energy management, load balancing and replication,” J. ACM SIGMOD Record, vol. 38, no. 4, pp.35-42. [28] Cui, X., Mills, B. , Znati, T. and Melhem, R., (2014). “Shadow replication: An energy-aware, fault-tolerant computational model for green cloud computing,” J. Energies, vol. 7, no. 8, pp. 5151–5176. [29] Mills, B., Znati, T., Melhem, R. and Ferreira, K. B., (2013). “Shadow Computing An Energy-Aware Resiliency Scheme for High Performance Computing,” Sandia National Laboratories (SNL-NM), Albuquerque, New Mexico, United States. [30] Cui, X., Mills, B., Znati, T. and Melhem, R., (2014). “Shadows on the cloud: An energy-aware, profit maximizing resilience framework for cloud computing,” Proc. Forth Int. Conf. Cloud Computing and Services Science, pp. 15–26. [31] Mills, B., Znati, T., and Melhem, R., (2014). "Shadow computing: An energy-aware fault tolerant computing model." Proc. IEEE Int. Conf. Computing, Networking and Communications (ICNC), pp. 73-77. [32] Mills, B., Znati, T., Melhem, R., Ferreira, K. B. and. Grant, R. E , (2014). “Energy consumption of resilience mechanisms in large scale systems,” Proc. Twenty-two Euromicro Int. Conf. Parallel, Distributedand. Network-Based Processing ( PDP 2014), pp. 528–535, 2014. [33] Cui, X., Znati, T., and Melhem, R., (2016). “Adaptive and Power-Aware Resilience for Extreme-scale Computing.” Proc. IEEE Conf. Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), pp. 671-679. [34] Cui, X., (2016) “ADAPTIVE AND POWER-AWARE FAULT TOLERANCE FOR FUTURE EXTREME-SCALE COMPUTING” P.hd dissertation , Computer Science Department, University of Pittsburgh , Pennsylvania, America.**
Navpreet Kaur Gill, Kamaljit Kaur "Shadow Replication using Dynamic Core Allocation for Application Fault Tolerance in Virtual Environment" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.30-39 2017
The next generation of mobile communication is based on OFDM technology. It is an efficient method of data transmission for high speed communication system. Orthogonal frequency division multiplexing (OFDM) systems have been proposed in the recent past years for providing high spectral efficiency, less vulnerability to echoes, low implementation complexity and resistance to non linear distortion .However the main drawback of OFDM system is high peak to average power ratio (PAPR) of transmitted signals due to inter-symbol interference between the subcarriers as a result the amplitude of such a signal can have high peak values. Thus a power amplifier must be carefully manufactured to have a linear input output characteristics or to have large input output back-off. Drawback of high PAPR is that dynamic range of power amplifier and Digital to Analog (D/A) converter during the transmission and reception of the signal is higher. As a result total cost of transceiver increases with reduced efficiency. Discrete Fourier Transform (DFT) Spreading is one of the schemes to reduce the PAPR problem in OFDM system by using different subcarrier mapping schemes. In this paper we proposed combination of DFT spreading technique with FEC coding to reduce PAPR in OFDM system. Performance evaluation carried out in terms of SNR (signal to noise ratio) BER (bit error rate).
Priyanka Kar
M.Tech Student, Electronics and Telecommunication Department, Indira Gandhi Institute of Technology, Sarang, Odisha, India
Jyotirekha Das
Assistant Professor, Electronics and Telecommunication Department, Indira Gandhi Institute of Technology, Sarang, Odisha, India
**[1]. Yong Soo Cho, Jaekwon Kim, Won Young Yang, Chung G.Kang―MIMO-OFDM WIRELESS COMMUNICATIONS WITH MATLAB‖ John wiley & son s pvt ltd. [2]. OFDM and Its Wireless Applications: A Survey Taewon Hwang, Chenyang Yang, Senior Member, IEEE, Gang Wu, Member, IEEE, Shaoqian Li, and Geoffrey Ye Li, Fellow, IEEE [3]. Prajakta Shedashale, Dr.V.V.Patil, “ Analysis of Paper Reduction Scheme in OFDM using DFT Technique”, International Journal of Advanced Research in Science, Engineering and Technology, Vol. 3, Issue 1 , January 2016 [4]. Wang Yi Gu linfeng Blekinge Institute of Technology October 2009, “An Investigation of Peak-to-Average Power Reduction in MIMO-OFDM Systems”. [5]. Md. Ibrahim Abdullah, Md. Zulfiker Mahmud, Md. Shamim Hossain, Md. Nurul Islam, “Comparative Study of PAPR Reduction Techniques in OFDM”, ARPN Journal of Systems and Software, VOL. 1, NO. 8, November 2011. [6]. T. Jiang, W. Xiang, H. H. Chen, and Q. Ni, “Multicast broadcasting services support in OFDMA-based WiMAX systems,” IEEE Communications Magazine, vol. 45, no. 8, pp. 78-86, Aug. 2007. [7]. Amit Shukla, Vineeta Saxena Nigam, “PAPR Reduction in OFDM System Based on SLM Technique”, International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-3, Issue-4, September 2013. [8]. Myung, Lim, and Goodman, “Single Carrier FDMA for Uplink Wireless Transmission”, IEEE Vehicular Technology Magazine, September 2006, page 30- 38. [9]. Kanchan Choubey, Prashant Jain, “PAPR Reduction using Companding and FEC Coding in OFDM System”, International Journal of Scientific & Engineering Research, Volume 5, Issue 1, January-2014 . [10]. Lin, Xiao, Vucetic, and Sellathurai, “Analysis of Receiver Algorithms for LTE SC-FDMA Based Uplink MIMO Systems”, IEEE Transactions on Wireless Communications, Vol. 9, No. 1, January 2010. [11]. Deergha Agarwal, Nishant Sharan, Ponmani Raja M, Ankur Agarwal, “PAPR Reduction Using Precoding and Companding Techniques for OFDM Systems”, IEEE ,2015. [12]. Ramdas P.Karhale, Pradeep N.Narwade, “ A PEAK TO AVERAGE POWER RATIO (PAPR) REDUCTION IN OFDM SYSTEMS”, IRJET, Volume: 03 Issue: 01,Jan-2016. [13]. Yong Soo Cho,Jaekwon Kim, Won Young Yang,Chung-Gu Kang, “MIMO-OFDM wireless communications with Matlab”. [14]. Sachin Rawat, “Implementation of a FEC technique using convolutional encoding with viterbi decoding”, a thesis paper, March 2004.**
Priyanka Kar, Jyotirekha Das "PAPR Reduction using DFT Spreading with FEC for OFDM Systems" International Journal of Latest Technology in Engineering,Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.40-43 2017
Ovality generally known as ‘Out of Roundness’ is one of the most common defects in pipe manufacturing. Ovality in early stages makes manufacturing process time consuming and less efficient. After dispatching, because of improper handling, ovality turns into barrier of proper welding of two pipes on site. In this paper, there is inclusion of causes of ovality, stages of ovality, drawbacks of oval pipes, manufacturing difficulties due to ovality and how to control it is included.
Kawaljitsingh Randhawa
Mechanical Department, CSPIT, CHARUSAT, Changa, Gujarat, India
**[1] Pipe or tube ovality calculator, Available: https://www.cmrp.com/dompdf/ovalitycalc.php [2] M. Balachandran (2015), ‘Ovality Correction Methods for Pipes’, International Journal on Mechanical Engineering and Robotics (IJMER), Volume-3, Issue-1, pp. 33-38. [3] Chris Alexander (2012), ‘Evaluating the effects of ovality on the integrity of pipe bends’, 9th International Pipeline Conference, September 24 – 28, pp. 1-13. [4] A. V. Kale, H. T. Thorat (2014), ‘Control of ovality in pipe bending: a new approach’, 5th International & 26th All India Manufacturing Technology, Design and Research Conference (AIMTDR 2014), December 12-14, pp. 1-5 (192).**
Kawaljitsingh Randhawa "Ovality in Pipes" International Journal of Latest Technology in Engineering,Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.44-46 2017
New bacterial strains were isolated, identified and screened for their naphthalene degradation ability from the soil contaminated with oil (lubricating oil, petrol and diesel etc.) of 3 different vehicle service station sites of Chandigarh, India. Enriched media (0.5% peptone and 0.1% w/v naphthalene in basal salt mineral medium) was used to isolate the naphthalene degrading bacteria and the concentration of peptone was decreased to 0.25g, 0.1g and to 0.0g during successive enrichments. After one month of enrichment, out of the total 59 strains screened, only 3 strains were found to be potent naphthalene degrader. These 3 strains were further sub-cultured for 10 days and on the basis of naphthalene degradation (in percent), strain IR1 was found to degrade 74.8% naphthalene supplemented in BSM medium at 0.1% concentration (w/v) as sole source of carbon and energy and was identified as Pseudomonas sp. Antibiotic sensitivity test revealed that the strain IR1 - *Pseudomonas* sp. was resistant to cefadroxil and ampicillin among the seven antibiotics tested. Plasmid curing of the isolate lead to complete loss of plasmid and the naphthalene degradation activity suggesting that the plasmid could have a role in naphthalene degradation activity.
Rajesh Singla
Associate Professor - Microbiology and Head, Agriculture Department, S.S.D. College of Professional Studies, Bhokhra - 151201, Bathinda, Punjab, India
**[1]. Alquati, C., Papacchini, M., Riccardi, Spicaglia, C. and Bestetti, G. (2005) Diversity of naphthalene-degrading bacteria from a petroleum contaminated soil. Ann Microbiol. 55: 237-242. [2]. Bamforth, S.M. and Singleton, I. (2005). Bioremediation of poly aromatic hydrocarbons. Current knowledge and future directions. J. Chem. Technol. Biotechnol. 80: 723-736. [3]. Coral, G. and Karagoz, S. (2005). Isolation and characterization of phenanthrene-degrading bacteria from a petroleum refinery soil. Annals of Microbiology. 55(4): 255-259. [4]. Fujii, T., Takeo, M. and Maeda, Y. (1997). Plasmid-encoded genes sp.ecifying aniline oxidation from Actinetobacter sp. strain YAA. Microbiology. 143: 93-99. [5]. Gary, S., Sayler, Hooper, S.W., Layton, A.C. and Henry King, J.M. (1990). Catabolic plasmids of environmental and ecological significance. Microbial Ecol. 19: 1-207. [6]. Gomare, K.S. and Lahane, M.N. (2011). Degradation of Polyaromatic Hydrocarbons by Isolated Cultures from Contaminated Soils at Petrol Pump Stations. International Journal of Recent Trends in Science and Technology. 1(1): 09-13. [7]. Juhasz, A.L. and Naidu, R. (2000). Bioremediation of high molecular weight polycyclic aromatic hydrocarbons: a review of microbial degradation of benzopyrene. International Biodeterioration & Biodegradation. 45: 57-88. [8]. Kado, C.I. and Liu, S.T. (1981). Rapid procedure for the detection and isolation of large and small plasmids. J. Bacteriol. 145(3): 1365-1373. [9]. Leahy, J.G. and Colwell, R.R. (1990). Microbial degradation of hydrocarbons in the environment. Microbiological Reviews. 305-315. [10]. Manohar, S., Kim, C.K. and Karegoudar, T.B. (1999). Degradation of Anthracene by a Pseudomonas strain, NGK1. Journal of Microbiology. 37(2): 73-79. [11]. Mesas, J.M., Rodriguez, M.C. and Alegre, M.T. (2004). Plasmid curing of Oenococcus oeni. Plasmid. 51(1): 37-40. [12]. Mirdamadian, S.H., Emtiazi, G., Golabi, M.H. and Ghanavati, H. (2010). Biodegradation of Petroleum and Aromatic Hydrocarbons by Bacteria Isolated from Petroleum-Contaminated Soil. J. Pet. Environ. Biotechnol. 1:102. [13]. Miya, R.K. and Firestone, M.K. (2000). Phenanthrene-degrader community dynamics in rhizophere soil from a common annunal grass. J. Env. Qual. 29: 584-592. [14]. Moody, J.D., Freeman, J.P., Doerge, D.R. and Cerniglia, C.E. (2001). Degradation of Phenanthene and anthracene by cell suspensions of Mycobacterium sp. strain PYR-1. Appl. Environ. Microbiol. 67: 1476- 1483. [15]. Nadalig, T., Raymond, N., Ni’matuzahroh, G.M., Budzinski, H. and Bertrand, J.C. (2000). Degradation of phenanthrene, methylphenathrenes and dibenzothiophene by a Sphingomonas strain 2mpII. Appl. Microbiol. Biotechnol. 59: 79- 85. [16]. Safekordi, A. and Yaghmaei, S. (2001).Biodegradation of Polycyclic Aromatic Hydrocarbons (PAHs) by some Bacteria isolated from coal tar contaminated soil. Scientia Iranica. 8(3): 197 – 202. [17]. Sanseverino, J., Bruce, M.A., Henry King, J.M. and Sayler, G.S. (1993). Plasmid- mediated mineralization of naphthalene, phenanthrene and anthracene. Center for Environmental Technology and Dept. of Microbiology, University of Tennessee. [18]. Singleton, P. and Sainsbury, D. (2001). Dictionary of Microbiology and Molecular Biology (3rd ed.). Chichester, UK: John Wiley & Sons, Ltd. [19]. Sverdrup, L.E., Nielson, T. and Krogh, P.H. (2002). Soil ecotoxicity of polycyclic aromatic hydrocarbons in relation to soil sorption, lipophilicity and water solubility. Environ Sci. Technol. 36: 2429–2435.**
Rajesh Singla "Naphthalene Biodegradation by Novel Soil Isolate of Vehicle Service Station Sites" International Journal of Latest Technology in Engineering,Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.47-52 2017
Anshul Mishra, Dr. Devendra Agarwal, Dr. M. H. Khan·July 2017·pp. 53-57
The issue of security is essential for secure software. Measuring security of software system at design phase may help software developers to improve the security of software system. A security estimation model for object oriented design fault perspective has been developed in this paper. The proposed model correlates the Object Oriented Design constructs with Fault and Security. The security estimation process can be achieved by controlling the fault issues at design phase. This paper presents a multivariate linear regression for establishing the security estimation model in terms of Confidentiality, Integrity and Availability as attributes of security criteria to evaluate security of class diagram. Security estimation model is empirically validated and statistical significance of the study considers the high correlation for model acceptance.
Anshul Mishra
Research Scholar, School of Computer Application, BBDU, Lucknow, India
Dr. Devendra Agarwal
Director (Engg.) at BBDNIIT, BBDU, Lucknow, India
Dr. M. H. Khan
Professor, Department of Computer Science & Engineering, I.E.T, Lucknow, India
**[1]. The Security of Applications: Not All Are Created Equal. https://www.atstake.com. 2002. [2]. M. Masera and I. N. Fovino, “Parameters for Quantitative Security Assessment of Complex Systems”, “, Citeseers, 2010. [3]. S. Ahmed and R. A. Khan, “Security Improvement of Object Oriented Design using Refactoring Rules”, I.J. Modern Education and Computer Science, Vol 2, pp 24-31, Feb 2015. [4]. D. Pandey, U. Suman and A. K. Ramani, “Security Requirement Engineering Issues In Risk Management”, International Journal of Computer Applications, Foundation Of Computer Science, USA, ISBN:978-93-80747-89-4, Vol. 17, No. 5, Pp.11-14, 2011. [5]. A. Ekelhart, S. Fenz, M. Klemen, and E. Weippl, “Security Ontologies: Improving Quantitative Risk Analysis,” in HICSS ’07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences, 2007, pp. 1–7 [6]. Viega, J., McGraw and G. “Building Secure Software”, 2002. [7]. Adams, J. Risk. 1995. UCL Press. [8]. M. Masera and I. N. Fovino, “Parameters for Quantitative Security Assessment of Complex Systems”, IJCE, Apr 2010. [9]. A. Bond and N. Påhlsson, “A Quantitative Evaluation Framework for Component Security in Distributed Information Systems”, Thesis, Institute of Technology, link opening university, 2004. [10]. M. Al-Kuwaiti and S. Hussein, “A Comparative Analysis of Network Dependability, Fault Tolerance, Reliability, Security and Survivability”, IEEE, Vol. 11, No. 2, 2009. [11]. V. Verendel, “Quantified security is a weak hypothesis: a critical survey of results and assumptions,” in Proceedings of the 2009 workshop on New security paradigms workshop, ser. NSPW ’09. New York, NY, USA: ACM, 2009, [Online].Available: https://doi.acm.org/10.1145/1719030.1719036 [12]. ISO, ISO/IEC Std. ISO 27002:2005, Information Technology - Security Techniques - Code of Practice for Information Security Management. ISO, 2005. [13]. A. Agrawal, R. A. Khan and S. Chandra, “Software Security Process: Development Life Cycle Perspective”, CSI communications, pp. 39-42, August 2008. [14]. J. Breier and L. Hudec, “New Approach in Information System Security Evaluation”, IEEE, 2012. [15]. B. B. Madan, K. and K. S. Trivedi, “Modelling and Quantification of Security Attributes of Software Systems”, Proceedings of the International Conference on Dependable Systems and Networks (DSN’02), IEEE, pp.505-514, 2002. [16]. CERT. https://www.cert.org. [17]. S. A. Khan and R. A. Khan, “Integrity Quantification Model for Object Oriented Design”, ACM SIGSOFT Software Engineering Notes, Vol 37, No.2, Mar 2012. [18]. S A Khan and R A Khan, “Security Quantification Model‖”, International Journal of Software Engineering, ISSN: 2090-1801, Vol. 6, No. 2, pp: 75-89, 2013. [19]. A. Mishra, Dr. D. Agarwal and Dr. M. H. Khan, “A Critical Review of Fault Tolerance: Security Perspective”, International Journal of Computer Science and Information Technologies, Vol. 8 (1), 132-135, 2017. [20]. Weirich and Sasse “A. Pretty Good Persuasion: A first step towards effective password security in the real world”, New Security Paradigms Workshop 2001. [21]. Whitten, and A. Tygar “Why Johnny Can't Encrypt: A Usability Evaluation of PGP 5.0”, Proceedings of the 8th USENIX Security Symposium, August 1999. [22]. PPT Network Security, Available at: https://boardreader.com/tp/ppt%20network%20security.htmllast visit Oct 15 (2014). [23]. M. Jureczko and L. Madeyski, “Towards identifying software project clusters with regard to defect prediction”, IEEE, 2010. [24]. A. Mishra, D. Agarwal and M. H. Khan, “Confidentiality Estimation Model: Fault Perspective” International Journal of Advanced Research in Computer Science (IJARCS), Volume.8 Issue. 4, June 2017. [25]. A. Mishra, D. Agarwal and M. H. Khan, “Integrity Estimation Model: Fault Perspective”, International Journal on Recent and Innovation Trends in Computing and Communication, Vol 5, Issue 5, pp 1246-1249, May 2017 [26]. A. Mishra, D. Agarwal and M. H. Khan, “Availability Estimation Model: Fault Perspective”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 6, Issue 6, June 2017. [27]. N. Parveen, M. R. Beg and M. H. Khan, “Model to Quantify Availability at Requirement Phase of Secure Software”, American Journal of Software Engineering and Applications, Vol. 6, 2015. [28]. S. A. Khan and R. A. Khan, “Confidentiality Estimation Model for Object Oriented Design”, International Journal of Information and Education and Technology, Vol. 37, No. 2, March 2010.**
Anshul Mishra, Dr. Devendra Agarwal, Dr. M. H. Khan "Security Estimation Model: Fault Perspective" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.53-57 2017
Data mining is the transformation of large sizes of information into expressive patterns and rules. It is approximately describing the former and calculating the near future by means of information analysis. Data mining is really a multi-disciplinary area which combines, equipment understanding, data, database engineering and synthetic intelligence. The full total aim of the info exploration method is normally to extract information from the info set and convert it into a good understandable framework for more use. To predict bank failure events, apply the random forests method to the analysis of bank-level financial data in order to identify hidden patterns that can distinguish active and inactive banks. This paper mainly focuses on on to classify the customers as fake or fraud and non-fake or fraud. . By using J48 and Neural Networks to improve the accuracy rate further for detection of fraudulent customers.
Megha
Department of Computer Science & Engineering, Guru Nanak Dev University, Jalandhar, Punjab, India
Prof. Neena Madan
Department of Computer Science & Engineering, Guru Nanak Dev University, Jalandhar, Punjab, India
**[1]. Joel Janek Dabrowski, Conrad Beyers, Johan Pieter de Villiers, Systemic banking crisis early warning systems using dynamic Bayesian networks, Expert Systems with Applications, Volume 62, 15 November 2016, Pages 225-242, ISSN 0957-4174. [2]. Katsuyuki Tanaka, Takuji Kinkyo, Shigeyuki Hamori, Random forests-based early warning system for bank failures, Economics Letters, Volume 148, November 2016, Pages 118-121, ISSN 0165-1765. [3]. Graham R. Wilkinson, Mick Schofield, Peter Kanowski, Regulating forestry — Experience with compliance and enforcement over the 25 years of Tasmania's forest practices system, Forest Policy and Economics, Volume 40, March 2014, Pages 1-11, ISSN 1389-9341. [4]. Rosalind L. Bennett, Haluk Unal, The effects of resolution methods and industry stress on the loss on assets from bank failures, Journal of Financial Stability, Volume 15, December 2014, Pages 18-31, ISSN 1572-3089. [5]. Raymond A.K. Cox, Grace W.-Y. Wang, Predicting the US bank failure: A discriminant analysis, Economic Analysis and Policy, Volume 44, Issue 2, July 2014, Pages 202-211, ISSN 0313-5926. [6]. Kimie Harada, Takatoshi Ito, Shuhei Takahashi, Is the Distance to Default a good measure in predicting bank failures? A case study of Japanese major banks, Japan and the World Economy, Volume 27, August 2013, Pages 70-82, ISSN 0922-142. [7]. Robert DeYoung, Gökhan Torna, Nontraditional banking activities and bank failures during the financial crisis, Journal of Financial Intermediation, Volume 22, Issue 3, July 2013, Pages 397-421, ISSN 1042-9573. [8]. Shyang Chen, Ching-Hsue Cheng, Hybrid models based on rough set classifiers for setting credit rating decision rules in the global banking industry, Knowledge-Based Systems, Volume 39, February 2013, Pages 224-239, ISSN 0950-7051. [9]. Andreas Krause, Simone Giansante, Interbank lending and the spread of bank failures: A network model of systemic risk, Journal of Economic Behavior & Organization, Volume 83, Issue 3, August 2012, Pages 583-608, ISSN 0167-2681. [10]. Monica Fisher, Moushumi Chaudhury, Brent McCusker, Do Forests Help Rural Households Adapt to Climate Variability? Evidence from Southern Malawi, World Development, Volume 38, Issue 9, September 2010, Pages 1241-1250, ISSN 0305-750X. [11]. Melek Acar Boyacioglu, Yakup Kara, Ömer Kaan Baykan, Predicting bank financial failures using neural networks, support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey, Expert Systems with Applications, Volume 36, Issue 2, Part 2, March 2009, Pages 3355-3366, ISSN 0957-4174. [12]. P. Ravi Kumar, V. Ravi, Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review, European Journal of Operational Research, Volume 180, Issue 1, 1 July 2007, Pages 1-28, ISSN 0377-2217. [13]. Timothy J. Curry, Peter J. Elmer, Gary S. Fissel, Equity market data, bank failures and market efficiency, Journal of Economics and Business, Volume 59, Issue 6, November–December 2007, Pages 536-559, ISSN 0148-6195. [14]. Marcia Millon Cornett, Jamie John McNutt, Hassan Tehranian, Long-term performance of rival banks around bank failures, Journal of Economics and Business, Volume 57, Issue 5, September–October 2005, Pages 411-432, ISSN 0148-6195. [15]. Carlos A Molina, Predicting bank failures using a hazard model: the Venezuelan banking crisis, Emerging Markets Review, Volume 3, Issue 1, 1 March 2002, Pages 31-50, ISSN 1566-0141. [16]. David L. Martell, Chapter 15 - Forest Fire Management, In Forest Fires, edited by Edward A. Johnson and Kiyoko Miyanishi, Academic Press, San Diego, 2001, Pages 527-583, ISBN 9780123866608. [17]. Aigbe Akhigbe, Jeff Madura, Why do contagion effects vary among bank failures?, Journal of Banking & Finance, Volume 25, Issue 4, April 2001, Pages 657-680, ISSN 0378-4266. [18]. Charles E. Williams, Eric V. Mosbacher, William J. Moriarity, Use of turtlehead (Chelone glabra L.) and other herbaceous plants to assess intensity of white-tailed deer browsing on Allegheny Plateau riparian forests, USA, Biological Conservation, Volume 92, Issue 2, February 2000, Pages 207-215, ISSN 0006-3207.**
Megha, Prof. Neena Madan "Providing Banking Loan to Customers Based on J48 Classifier Algorithm Combined with Neural Networks" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.58-62 2017
Ami Munshi, Srija Unnikrishnan·July 2017·pp. 63-66
In this paper an endeavour is made to design and simulate SISO, MISO and MIMO OFDM systems. We have analysed and compared the performance of these systems for image transmission over AWGN and Rayleigh channels. The effect of LS channel estimation on the BER over a range of SNR for MIMO(2X2) systems is examined. We have also compared the performance based on various M-ary PSK modulation techniques for image transmission over Rayleigh channel in MIMO-OFDM system. The system performance is simulated in Matlab. The results of the simulation show that as the antenna diversity increases, the BER decreases and the channel capacity increases. Also, the BER obtained in MIMO-OFDM system is less when LS estimation is used.
Ami Munshi
SVKM’s NMIMS MPSTME, Mumbai, India
Srija Unnikrishnan
FRCRCE, University of Mumbai, India
**[1]. A.K Jaiswal, A. K. (2012). Performance Analysis of MIMO OFDM systems in Rayleigh fading Channels. International Journal of Scientific and Research Publications, 1-5. [2]. Casu, G., Georgescu, F., Nicolaescu, M., & Mocanu, A. (2015). A comparative performnce analysis of MIMO OFDM systems over different fading channels. 7th International Conference on Electronics, Computers and Artifical Intelligence (pp. 1-4). IEEE Conference Publications. [3]. Charan Langton, B. S. (2011, October). Finding MIMO. Retrieved from complextoreal: https://complextoreal.com/tutorials/tutorial-27-finding-mimo [4]. Jiang Xuehua, C. P. (2009). Study and Implementation of MIMO-OFDM System Based on Matlab. International Conference on Information Technology and Computer Science (pp. 554 - 557). IEEE Conference Publications. [5]. K Fazel, S. K. (2008). Multi-Carrier and Spread Spectrum Systems (2nd ed.). Wiley. [6]. N.Praba, K. (2016). Image transmisson in OFDM using M-ary PSK modulation shcemes- a comparative study. International Journal of Research in Engineering and Technology, 5(1), 193-197. [7]. Patil, P. K. (2013). Role of Contributing Factors MIMO-OFDM in 4G-LTE Wireless Transmission Technologies from Technical Perspective. International Journal of Advanced Research in Computer and Communication Engineering, 2(7). [8]. Poole, I. (n.d.). LTE OFDM, OFDMA SC-FDMA & Modulation. Retrieved April 27, 2017, from Radio-Electronics.com: https://www.radio-electronics.com/info/cellulartelecomms/lte-long-term-evolution/lte-ofdm-ofdma-scfdma.php [9]. Principles of Modern CDMA/MIMO/OFDM Wireless Communications. (n.d.). Retrieved April 27, 2017, from NPTEL: https://nptel.ac.in/courses/117104115/# [10]. S. Ramesh, R. S. (2016). PERFORMANCE ANALYSIS OF MIMO-OFDM FOR MULTIPLE ANTENNAS. International Journal of Pharmacy & Technology, 8(4), 23041-23053. [11]. Thiruvengadathan, R., & Srikanth, S. (2012). Performance of MIMO Channel Estimation in LTE Downlink. Computing Communication & Networking Technologies (ICCCNT), 2012 Third International Conference on (pp. 1-7). IEEE Conference Publications. [12]. Yong Soo Cho, J. K. (2010). MIMO-OFDM Wireless Communication with Matlab. Wiley.**
Ami Munshi, Srija Unnikrishnan "Design, Simulation and Evaluation of SISO/MISO/MIMO-OFDM Systems " International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.63-66 2017
Vinayak M. Patil, Prof. M.M. Joshi·July 2017·pp. 67-71
Limestone slurry is highly effective wet scrub to reduce toxic emissions because it is cheap plentiful, limestone is the most commonly used reagent for this purpose. The slurry reacts well with the toxic sulfur dioxide and makes the waste less hazardous to the environment. The waste then may be dewatered and deposited safely in landfills or sold as an ingredient for the manufacturing of gypsum wallboard and cement. It may even be used as a fertilizer additive. Limestone stays only slightly soluble in water. The slurry needs regular agitation, otherwise, the suspended particles soon settle out and form a solid. A limestone slurry tank designed with the objective of keeping the slurry agitated for storage purpose. Besides structural stability, the internal pressure indicates the risk of leakage and failure of slurry tank, hence FEA is used to identify the critical zone and hence be manipulated it through a structural modification to make the system safe. .
Vinayak M. Patil
Student of M.E. (Design Engineering), NBN SSoE, Ambegao -Pune, Savitribai Phule Pune University, India
Prof. M.M. Joshi
Faculty member of Mechanical Engineering, NBN SSoE, Ambegao -Pune, Savitribai Phule Pune University, India
**[1]. Jaroslave Mackerle, linkoping institute of technology,S-581 Linkoping, Swedan “ finite elements in the analysis of pressure vessel and piping” p .279-280 [2]. J.L. Gonzalez,S. Gomez, XXIV Italian group of fracture conference,1-3 march 2017,Italy.“Analysis of mechanical behavior of a delayed coker drum with circumferentially cracked skirt”.p 36-38 [3]. Michael A. Porter, Dennis H. Martens Article in American Society of Mechanical Engineers “On Using Finite Element Analysis for Pressure Vessel Design”. Pressure Vessels and Piping Division (Publication) PVP January 1999 [4]. Busuioceanu (Grigorie) Paraschivaa, Stefanescu Mariana-Florentinab, Ghencea Adrianc “ Study of Stresses and Stress Concentrations in Pressure Vessels.” Journal of Business Economics and Information Technology [5]. A.kazemi Ameri, C. Bucher Vienna doctoral programme on water resourse system,A-1040,Vienna,Astria.”A procedure for in situ wind load reconstruction from structural response only based on field testing data.”(2017)75-86. [6]. Kadhim Hussein Mukhirmesh\*1, Dr. P. Laxminarayana Kadhim Hussein Mukhirmesh et. al./ International Journal of engineering & science research “Design and analysis of welded joints of pressure vessel” IJESR/May 2015/ Vol-5/Issue-5/341-34 [7]. Dennis H. Martens Article in American Society of Mechanical Engineers “On Using Finite Element Analysis for Pressure Vessel Design”. Pressure Vessels and Piping Division (Publication). [8]. Arter Calnins, mechanical enng. Dept.lehigh university bathlehem “stress classification in pressure vessel and piping” PA 18015-3015. [9]. Manish M. Utagikar, Prof. S.B. Naik “Design and analysis of welded joints of pressure vessel.” IJESR/May 2015/ Vol-5/Issue-5/341-346**
Vinayak M. Patil, Prof. M.M. Joshi "Finite Element Analysis of Lime Stone Slurry Tank" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.67-71 2017
Cricket is the second most watched sport in the world after soccer, and enjoys a multi-million dollar industry. There is remarkable interest in simulating cricket and more importantly in predicting the outcome of cricket match which is played in three formats namely test match, one day international and T20 match. The complex rules prevailing in the game, along with the various natural parameters affecting the outcome of a cricket match present significant challenges for accurate prediction. Several diverse parameters, including but not limited to cricketing skills and performances, match venues and even weather conditions can significantly affect the outcome of a game. There are number of research paper on pre-match prediction of cricket match. Many papers on building a prediction model that takes in historical match data as well as the instantaneous state of a match, and predict match results. We know in the cricket match with shorter version match result keep on changing every ball. So, it is important to predict the outcome of the match on every ball. In this paper, I have developed a model that predicts match result on every ball played. Using Duckworth- Lewis formula match outcome will be predicted for live match. For every ball bowled a probability is calculated and probability figure is plotted. For betting industry this model and the probability figure will be very useful for bettor in deciding which team to on and how much to bet.
Parag Shah
Department of Statistics, H L College of Commerce, Ahmedabad, India
**[1] Akhtar S and Scarf PA (2012): “Forecasting test cricket match outcomes in play”. International Journal of Forecasting, 28(3), 632–643. [2] Bailey & Clarke (2006): “Predicting the match outcome in one day international cricket matches, while the match is in progress”. Journal of Science and Sports Medicine, 5, 480–487. [3] De Silva, B. M., and Swartz, T. B. (2001): “Estimation of the magnitude of the victory in one-day cricket”. Australian & New Zealand Journal of Statistics, 43, 1369-1373. [4] Duckworth, F. and Lewis, T. (1998): “A fair method for resetting the target in interrupted one-day cricket matches”. Journal of Operation Research Society, 49, 22-28. [5] Ganeshapillai G, Guttag J (2013): “A data-driven method for in game decision making in MLB: When to pull a starting pitcher”. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 973–979. [6] Kaluarachchi, Amal, and S. Varde Aparna(2010): “CricAI: A classification based tool to predict the outcome in ODI cricket”. 2010 Fifth International Conference on Information and Automation for Sustainability. IEEE. [7] Kimber, A. C. and Hansford A. R. (1993): “A statistics analysis of batting in cricket”. Journal of the Royal Statistical Society Series A, 156, 443-455. [8] Madan Gopal Jhawar, Vikram Pudi(2016): “Predicting the Outcome of ODI Cricket Matches: A Team Composition Based Approach”. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2016). [9] Sankaranarayanan VV, Sattar J. and Lakshmanan LVS (2014): “Autoplay - A data mining approach to ODI cricket simulation and prediction”. In: Proceedings of the 2014 SIAM International Conference on Data Mining, 1064– 1072. [10] Theja Tulabandhula and Cynthia Rudin (2014): “Tire Changes, Fresh Air, And Yellow Flags: Challenges in Predictive Analytics For Professional Racing”. Massachusetts Institute of Technology, Cambridge, Massachusetts. [11] Wood, G. H. (1945): “Cricket scores and geometrical progression”. Journal of the Royal Statistical Society Series A, 108, 12-22**
Parag Shah "Predicting Outcome of Live Cricket Match Using Duckworth- Lewis Par Score" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.72-75 2017
This paper presents the non linear response of hybrid plate system consist of Fiber Reinforced Polymer (FRP) and ferrocement act as shell for core Reinforced Concrete (RC) by using ATENA-3D software based on Finite Element Method (FEM). In this investigation, the load displacement response of RC plate system with internal stiffened beams was carried out in the first phase and in the second phase of study, analysis of different hybrid plate system reinforced with unidirectional basalt, unidirectional carbon and bidirectional glass fiber fabric as well with ferrocement sheet was presented. Hybrid plate system with unidirectional carbon sheet exhibited the maximum load carrying capacity. Also formation of cracks in the different plate systems was monitored and all systems failed in flexure with formation of cracks on positive moment region.
Inderpreet Kaur
Research Scholar, Department of Civil Engineering, Guru Nanak Dev Engineering College, I.K. Gujral Punjab Technical University, Kapurthala, India
Hardeep Singh Rai
Department of Civil Engineering, Guru Nanak Dev Engineering College, I.K. Gujral Punjab Technical University, Kapurthala, India
Harvinder Singh
Department of Civil Engineering, Guru Nanak Dev Engineering College, I.K. Gujral Punjab Technical University, Kapurthala, India
**[1] C. E. Bakis et al., “Fiber-Reinforced Polymer Composites for Construction — State-of-the-Art Review”, J. Compos. Constr., vol. 6, no. May 1,2002, pp. 73–87, 2002. [2] S. Z. Khalid, S. B. Shinde, and K. M. Pathan, “Civil Engineering Application and Research of FRP in India as Compared to China”, J. Mech. Civ. Eng., pp. 49–53, 1999. [3] M. Kachlakev, T. Miller, P.E. Solomon, Yim, K. Chansawat, T. Potisuk, “Finite Element Modeling of Reinforced Concrete Structures Strengthened with FRP laminates”, Final Report OREGON Department of transportation, 2001. [4] H. Singhal, “Finite Element Modeling of Retrofitted RCC Beams”, M.E. Thesis, Thapar University, Patiala, 2009. [5] R. Santhakumar, E. Chandrasekaran, and R. Dhanaraj, “Analysis of retrofitted reinforced concrete shear beams using carbon fiber composites”, Electronic journal of structural engineering, vol. 4,pp. 66-74, 2004. [6] Cervenka Vladimir, Jendele Libor and Cervenka Jan, ATENA theory manual, part 1.**
Inderpreet Kaur, Hardeep Singh Rai, Harvinder Singh "Finite Element Modeling and Analysis of Hybrid Plate System " International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.76-79 2017
Security concerns inhibit the fast adaption of RFID technology for many applications. the security and privacy in radio frequency identification (RFID) system are one of the main obstacles to be solved. therefore this thesis work has proposed the hybrid technique to prevent multiplicative RFID attacks using hybrid distance bounding (db) protocols and secure positioning protocols. the experimental results brings about the proposed technique that clearly shown the fact that proposed technique outperforms over the existing methods.
Deepika Bains
M.Tech Scholar, Department of Computer Science & Engineering, Guru Nanak Dev University, RC Campus, Jalandhar, Punjab, India
Er.Varinder Kaur Attri
Assistant Professor, Department of Computer Science & Engineering, Guru Nanak Dev University, RC Campus, Jalandhar, Punjab, India
**[1]. Jung-Sik Cho, Young-Sik Jeong, Sang Oh Park, Consideration on the brute-force attack cost and retrieval cost: A hash-based radio-frequency identification (RFID) tag mutual authentication protocol, Computers & Mathematics with Applications, Volume 69, Issue 1, January 2015. [2]. Saravanan Sundaresan, Robin Doss, Wanlei Zhou, Selwyn Piramuthu, Secure ownership transfer for multi-tag multi-owner passive RFID environment with individual-owner-privacy, Computer Communications, Volume 55, 1 January 2015. [3]. Cong GUO, Zi-jian ZHANG, Lie-huang ZHU, Yu-an TAN, Zhen YANG, A novel secure group RFID authentication protocol, The Journal of China Universities of Posts and Telecommunications, Volume 21, Issue 1, February 2014. [4]. Yi-Pin Liao, Chih-Ming Hsiao, A secure ECC-based RFID authentication scheme integrated with ID-verifier transfer protocol, Ad Hoc Networks, Volume 18, July 2014 [5]. Jia-li Zheng, Tuan-fa Qin, Guang-nan Ni, Tree-based backoff protocol for fast RFID tag identification, The Journal of China Universities of Posts and Telecommunications, Volume 20, Issue 2, April 2013. [6]. Thomas Plos, Christian Maierhofer, On measuring the parasitic backscatter of sensor-enabled UHF RFID tags, Information Security Technical Report, Volume 17, Issue 4, May 2013. [7]. M. Moessner, Gul N. Khan, Secure authentication scheme for passive C1G2 RFID tags.Computer Networks, Volume 56, Issue 1, 12 January 2012. [8]. Rolando Trujillo-Rasua, Agusti Solanas, Pablo A. Pérez-Martínez, Josep Domingo-Ferrer, Predictive protocol for the scalable identification of RFID tags through collaborative readers, Computers in Industry, Volume 63, Issue 6, August 2012. [9]. Vinod Namboodiri, Maheesha DeSilva, Kavindya Deegala, Suresh Ramamoorthy, An extensive study of slotted Aloha-based RFID anti-collision protocols, Computer Communications, Volume 35, Issue 16, 15 September 2012. [10]. Boyeon Song, Chris J. Mitchell, Scalable RFID security protocols supporting tag ownership transfer, Computer Communications, Volume 34, Issue 4, 1 April 2011. [11]. E. Masciari, SMART: Stream Monitoring enterprise Activities by RFID Tags, Information Sciences, Volume 195, 15 July 2012 . [12]. Woo-Yong Choi, Combining multipolling method with frame aggregation for collecting RFID tag information in IEEE 802.11 wireless LANs, AEU - International Journal of Electronics and Communications, Volume 65, Issue 4, April 2011. [13]. Ali Motamedi, Rakesh Saini, Amin Hammad, Bo Zhu, Role-based access to facilities lifecycle information on RFID tags, Advanced Engineering Informatics, Volume 25, Issue 3, August 2011. [14]. Pedro Peris-Lopez, Julio C. Hernandez-Castro, Juan M.E. Tapiador, Tieyan Li, Yingjiu Li, Vulnerability analysis of RFID protocols for tag ownership transfer, Computer Networks, Volume 54, Issue 9, 17 June 2010. [15]. Chuan-hai JIAO, Ke-ren WANG, Multi-branch query tree protocol for solving RFID tag collision problem, The Journal of China Universities of Posts and Telecommunications, Volume 15, Issue 4, December 2008. [16]. Won-Ju Yoon, Sang-Hwa Chung, Seong-Joon Lee, Implementation and performance evaluation of an active RFID system for fast tag collection, Computer Communications, Volume 31, Issue 17, 20 November 2008 . [17]. Selwyn Piramuthu, Protocols for RFID tag/reader authentication, Decision Support Systems, Volume 43, Issue 3, April 2007.**
Deepika Bains, Er.Varinder Kaur Attri "Hybrid Technique to Prevent Multiplicative RFID Attacks using Hybrid Distance Bounding (DB) Protocols and Secure Positioning Protocols" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.80-85 2017
Object detection is a very important application of image processing. It is of vital importance for object dynamic surveillance and other applications. So far, object detection has been widely researched. It shows an efficient coarse object locating method based on a saliency mechanism. The method could avoid an exhaustive search across the image and generate a small number of bounding boxes. After that, the trained DBN is used for feature extraction and classification on sub-images. This paper represents that the a variety of strategies based on object detection and efficiency of object detection framework using a saliency prior and DBNs for remote sensing images. This research works proposed an efficient object detection using the ant colony optimization and deep belief networks. The motivation behind the proposed approach is easy and efficient.
Er. Amarjot Kaur
M.Tech Scholar, Department of Computer Science & Engineering, Amritsar College of Engineering & Technology, Amritsar, Punjab, India
Er. Navleen Kaur
Associate Professor, Department of Computer Science & Engineering, Amritsar College of Engineering & Technology, Amritsar, Punjab, India
**[1] C. Farabet, C. Couprie, L. Najman, and Y. LeCun, “Learning hierarchical features for scene labeling,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 8, pp. 1915–1929, Aug. 2013. [2] J. R. Uijlings, K. E. van de Sande, T. Gevers, and A. W. M. Smeulders, “Selective search for object recognition,” Int. J. Comput. Vis., vol. 104, no. 2, pp. 154–171, Sep. 2013. [3] W. Zhang, X. Sun, K. Fu, C. Wang, and H. Wang, “Object detection in high-resolution remote sensing images using rotation invariant parts based model,” IEEE Geosci. Remote Sens. Lett., vol. 11, no. 1, pp. 74–78,Jan. 2014. [4] Cheng, Ming-Ming, et al. "ImageSpirit: Verbal guided image parsing." ACM Transactions on Graphics (TOG) 34.1 (2014): 3. [5] M.-M. Cheng, Z. Zhang, W.-Y. Lin, and P. Torr, “BING: Binarized normed gradients for objectness estimation at 300 fps,” in Proc. IEEECVPR, 2014, pp. 3286–3293. [6] Xia Lan, Huanfeng Shen, Liangpei Zhang, Qiangqiang Yuan, A spatially adaptive retinex variational model for the uneven intensity correction of remote sensing images, Signal Processing, Volume 101, August 2014, Pages 19-34, ISSN 0165-1684, [7] Ming Li, Jinhua Zhang, Wenying Wen, Cryptanalysis and improvement of a binary watermark-based copyright protection scheme for remote sensing images, Optik - International Journal for Light and Electron Optics, Volume 125, Issue 24, December 2014, Pages 7231-7234, ISSN. [8] Anisha M. Lal, S. Margret Anouncia, Semi-supervised change detection approach combining sparse fusion and constrained k means for multi-temporal remote sensing images, The Egyptian Journal of Remote Sensing and Space Science, Volume 18, Issue 2, December 2015, Pages 279- [9] Xia Lan, Zhiyong Zuo, Huanfeng Shen, Liangpei Zhang, Jing Hu, Framelet-based sparse regularization for uneven intensity correction of remote sensing images in a retinex variational framework, Optik - International Journal for Light and Electron Optics, Volume 127, Issue 3,2015 [10] Wei Wu, Xiaomin Yang, Kai Liu, Yiguang Liu, Binyu Yan, Hua hua, A new framework for remote sensing image super-resolution: Sparse representation-based method by processing dictionaries with multi-type features, Journal of Systems Architecture, Volume 64, March 2016, [11] Lei Zhu, Li Ma, Class centroid alignment based domain adaptation for classification of remote sensing images, Pattern Recognition Letters, Volume 83, Part 2, 1 November 2016, Pages 124-132, ISSN 0167-8655, [12] Weixing Wang, Nan Yang, Yi Zhang, Fengping Wang, Ting Cao, Patrik Eklund, A review of road extraction from remote sensing images, Journal of Traffic and Transportation Engineering (English Edition), Volume 3, Issue 3, June 2016, Pages 271-282, ISSN 2095-7564, [13] Ying Liu, Linzhi Wu, Geological Disaster Recognition on Optical Remote Sensing Images Using Deep Learning, Procedia Computer Science, Volume 91, 2016, Pages 566-575, ISSN 1877-0509, [14] Li Xie, Guangyao Li, Mang Xiao, Lei Peng, Novel classification method for remote sensing images based on information entropy discretization algorithm and vector space model, Computers & Geosciences, Volume 89, April 2016, Pages 252-259, ISSN 0098-3004, [15] Cuiping Shi, Junping Zhang, Ye Zhang, Content-based onboard compression for remote sensing images, Neurocomputing, Volume 191, 26 May 2016, Pages 330-340, ISSN 0925-2312, [16] Song Yu, Wu Yiquan, Dai Yimian, Automatic river target detection from remote sensing images based on image decomposition and distance regularized CV model, Computers & Electrical Engineering, Volume 54, August 2016, Pages 285-295, ISSN 0045-7906, [17] Keiller Nogueira, Otávio A.B. Penatti, Jefersson A. dos Santos, Towards better exploiting convolutional neural networks for remote sensing scene classification, Pattern Recognition, Volume 61, January 2017, Pages 539-556, ISSN 0031-3203, [18] Jian Yang, Yuhong He, John Caspersen, Region merging using local spectral angle thresholds: A more accurate method for hybrid segmentation of remote sensing images, Remote Sensing of Environment, Volume 190, 1 March 2017, Pages 137-148, ISSN 0034-4257, [19] Sami Khanal, John Fulton, Scott Shearer, An overview of current and potential applications of thermal remote sensing in precision agriculture, Computers and Electronics in Agriculture, Volume 139, 15 June 2017, Pages 22-32, ISSN 0168-1699, [20] Yong Chen, Ting-Zhu Huang, Liang-Jian Deng, Xi-Le Zhao, Min Wang, Group sparsity based regularization model for remote sensing image stripe noise removal, Neurocomputing, Available online 15 May 2017, ISSN 0925-2312, [21] Peter J. Weisberg, Thomas E. Dilts, Owen W. Baughman, Susan E. Meyer, Elizabeth A. Leger, K. Jane Van Gunst, Lauren Cleeves, Development of remote sensing indicators for mapping episodic die-off of an invasive annual grass (Bromus tectorum) from the Landsat archive, Ecological Indicators, Volume 79, August 2017, Pages 173-181, ISSN 1470-160X, [22] Bin Han, Yiquan Wu, Yu Song, A novel active contour model based on median absolute deviation for remote sensing river image segmentation, Computers & Electrical Engineering, Available online 19 April 2017, ISSN 0045-7906, [23] Ding Yanqing, Yao Guoqing, Zhao Yanjie, Remote Sensing Image Content Retrieval Based on Frequency Spectral Energy, Procedia Computer Science, Volume 107, 2017, Pages 448-453, ISSN 1877-0509, [24] Mingquan Wu, Wenjiang Huang, Zheng Niu, Yu Wang, Changyao Wang, Wang Li, Pengyu Hao, Bo Yu, Fine crop mapping by combining high spectral and high spatial resolution remote sensing data in complex heterogeneous areas, Computers and Electronics in Agriculture, Volume 139, 15 June 2017, Pages 1-9, ISSN 0168-1699.**
Er. Amarjot Kaur, Er. Navleen Kaur "Improved Object Detection Algorithm using Ant Colony Optimization and Deep Belief Networks Based Image Segmentaion" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.86-90 2017
Smart home innovation is developing quickly as an energizing new worldview. An extensive variety of perspectives that incorporates security, energy sparing, ventilation, shrewd kitchen is canvassed in this paper. The greater part of the above is executed with the assistance of keen gadgets, for example, remote control, security alerts, sensors and so forth. In this paper we exhibit the previously mentioned innovations and devices that can be incorporated in home frameworks which can give security energy optimization and other such keen parameters. Various scenarios in terms of case study is also present in this literature. Euclidean distance mechanism is used to analyse closest pairs with in smart home dataset for future abnormality predictions. Results in terms of energy consumption and time consumed show optimization through the energy conservation mechanisms incorporated.
Manpreet Kaur
Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar, Punjab, India
Kamaljit Kaur
Department of Computer Engineering & Technology, Guru Nanak Dev University, Amritsar, Punjab, India
**[1]. Min, Z., (2013). Design of multi-channel wireless remote switch control system for smarthome control system. 3rd Int. Conf. Consum. Electron. Commun. Networks, CECNet - Proc., pp. 274–277. [2]. Naglič M. and Souvent A., (2013). Concept of SmartHome and SmartGrids integration. IYCE - 4th Int. Youth Conf. Energy, pp. 1–5. [3]. Thomas B. D., Mcpherson R., Paul G., and Irvine J., (2016) . Consumption of Wi-Fi for IoT Devices. no. September, pp. 92–100. [4]. Robinson J. and Knightly E. W., (2007). A Performance Study of Deployment Factors in Wireless Mesh Networks. IEEE INFOCOM 2007 - 26th IEEE Int. Conf. Comput. Commun., pp. 2054–2062,. [5]. Mohammed J., Lung C.-H., Ocneanu A., Thakral A., Jones C., and Adler A., (2014). Internet of Things: Remote Patient Monitoring Using Web Services and Cloud Computing. 2014 IEEE International Conference on Internet of Things(iThings), and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom), pp. 256–263. [6]. Gia T. N., Rahmani A. M., Westerlund T., Liljeberg P., and Tenhunen H., (2015). Fault tolerant and scalable IoT-based architecture for health monitoring. SAS 2015 - 2015 IEEE Sensors Appl. Symp. Proc.. [7]. Lo B. P. L., Ip H., and Yang G.-Z., (2016). Transforming Health Care: Body Sensor Networks, Wearables, and the Internet of Things. IEEE Pulse, vol. 7, no. 1, pp. 4–8. [8]. Cook D. J., Augusto J. C., and Jakkula V. R., (2009). Ambient intelligence : Technologies , applications , and opportunities. Pervasive Mob. Comput., vol. 5, no. 4, pp. 277–298. [9]. Wang Z., Liu Z., and Shi L., (2010). The smart home controller based on zigbee. 2010 2nd Int. Conf. Mech. Electron. Eng., vol. 2, no. Icmee, pp. V2–300–V2–302. [10]. Albuquerque H. J. O. and De Aquino Junior G. S., (2014). A proxy-based solution for interoperability of smart home protocols. Proc. - 2014 8th Int. Conf. Complex, Intell. Softw. Intensive Syst. CISIS 2014, pp. 287–293. [11]. Pompili D., Hajisami A., and Tran T. X., (2016). Elastic Resource Utilization Framework for High Capacity and Energy Efficiency in Cloud RAN. no. January, pp. 26–32. [12]. Khalid K., Woungang I., Dhurandher S. K., Barolli L., Carvalho G. H. S., and Takizawa M., (2016). An Energy-Efficient Routing Protocol for Infrastructure-Less Opportunistic Networks. 2016 10th Int. Conf. Innov. Mob. Internet Serv. Ubiquitous Comput., pp. 237–244. [13]. Anzt H., Tomov S., and Dongarra J., (2016). On the performance and energy efficiency of sparse linear algebra on GPUs. Int. J. High Perform. Comput. Appl., no. 2, pp. 800–807. [14]. Zuo L., Shu L. E. I., and Dong S., (2015). A Multi-Objective Optimization Scheduling Method Based on the Ant Colony Algorithm in Cloud Computing. vol. 3. [15]. Guillet, S., Bouchard, B., & Bouzouane, A. (2016). Safe and Automatic Addition of Fault Tolerance for Smart Homes Dedicated to People with Disabilities. In Trends in Ambient Intelligent Systems (pp. 87-116). Springer International Publishing. [16]. Paradiso R., Loriga G., and Taccini N., (2005). A wearable health care system based on knitted integrated sensors. IEEE Trans. Inf. Technol. Biomed., vol. 9, no. 3, pp. 337–344. [17]. Variyar V. V. S., Haridas N., Aswathy C., and Soman K. P., (2016). Proceedings of the International Conference on Soft Computing Systems. Adv. Intell. Syst. Comput., vol. 397, pp. 909–917. [18]. Wibisono A., Jatmiko W., Wisesa H. A., Hardjono B., and Mursanto P., (2016). Knowledge-Based Systems Traffic big data prediction and visualization using Fast Incremental Model Trees-Drift Detection ( FIMT-DD ). Knowledge-Based Syst., vol. 93, pp. 33–46. [19]. Xu J. and Fortes J. A. B., (2010). Multi-objective Virtual Machine Placement in Virtualized Data Center Environments. [20]. Zhao S., Yu L., and Cheng B., (2016). An Event - driven Service Provisioning Mechanism for IoT ( Internet of Things ) System Interaction. vol. 3536, no. c. [21]. Chen G., Hay G. J., Carvalho L. M. T., and Wulder A., (2011). International Journal of Remote Object-based change detection. pp. 37–41. [22]. Ilic M., Spalevic P., Veinovic M., and Ennaas A. A. M., (2015). Data mining model for early fruit diseases detection. pp. 910–913. [23]. You C., Huang K., and Chae H., (2016). Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer. vol. 8716, no. c, pp. 1–14. [24]. Glitho R., Morrow M., and Polakos P., (2013). A Cloud Based - Architecture for Cost-Efficient Applications and Services Provisioning in Wireless Sensor Networks. [25]. Banos, O., Villalonga, C., Garcia, R., Saez, A., Damas, M., Holgado-Terriza, J. A., ... & Rojas, I. (2015). Design, implementation and validation of a novel open framework for agile development of mobile health applications. Biomedical engineering online, 14(2), S6. [26]. Iqbal, M. A., Asrafuzzaman, S. K., Arifin, M. M., & Hossain, S. A. (2016, May). Smart home appliance control system for physically disabled people using kinect and X10. In Informatics, Electronics and Vision (ICIEV), 2016 5th International Conference on (pp. 891-896). IEEE. [27]. Orpwood, R., Gibbs, C., Adlam, T., Faulkner, R., & Meegahawatte, D. (2005). The design of smart homes for people with dementia—user-interface aspects. Universal Access in the information society, 4(2), 156-164. [28]. Ullah, A. M., Islam, M. R., Aktar, S. F., & Hossain, S. A. (2012, December). Remote-touch: Augmented reality based marker tracking for smart home control. In Computer and Information Technology (ICCIT), 2012 15th International Conference on (pp. 473-477). IEEE. [29]. Hussein, A., Adda, M., Atieh, M., & Fahs, W. (2014). Smart home design for disabled people based on neural networks. Procedia Computer Science, 37, 117-126. [30]. Guillet, S., Bouchard, B., & Bouzouane, A. (2013). Correct by construction security approach to design fault tolerant smart homes for disabled people. Procedia Computer Science, 21, 257-264. [31]. Guillet, S., de Lamotte, F., Le Griguer, N., Rutten, E., Gogniat, G., & Diguet, J. P. (2012, July). Designing formal reconfiguration control using UML/MARTE. In Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC), 2012 7th International Workshop on (pp. 1-8). IEEE.**
Manpreet Kaur, Kamaljit Kaur "Abnormality Detection of Sensors in IOT Controllers using Fuzzy Approach for Smart Home" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.91-97 2017
Amar Kumar Das, Shovan Nandi, Amit Kumar Behera·July 2017·pp. 98-103
Recent challenges for fossil fuels, concerns over the environment issues and rising costs for energy demand encourages researchers to search for an alternate source of renewable energy . An attempt has been made to produce biogas from kitchen waste following anaerobic digestion process where the bacteria degrade organic matters in the absence of oxygen. Kitchen waste is used as the best raw material for the Bio-gas plant. Biogas contains around (55-85)% of methane (CH4), (30-40)% of carbon dioxide (CO2) , a trace of hydrogen sulphide (H2S) and moisture (H2O).The calorific value of biogas is around 4700 kcal or 20 MJ. In this paper, different samples of biogas have been taken to optimize methane (CH4) content by controlling the pH value, Temperature, concentration of slurry, retention time, C/N ratio and rate of loading. This experiment was done in a floating drum type anaerobic digester of 1cubicmeter capacity and it is made of fiber material. The maximum pH level is maintained to 7.3, maximum fermentation process at (30-35)°C , maximum Bio-gas produced 0.950m3 and the maximum methane(CH4) is found to be 85%
Amar Kumar Das
Department of Mechanical Engineering, Gandhi Institute for Technology (GIFT), Bhubaneswar, Odisha-752054, India
Shovan Nandi
Department of Mechanical Engineering, Gandhi Institute for Technology (GIFT), Bhubaneswar, Odisha-752054, India
Amit Kumar Behera
Department of Mechanical Engineering, Gandhi Institute for Technology (GIFT), Bhubaneswar, Odisha-752054, India
**[1]. Johnson, Owe, et al. "Sustainable gas enters the European gas distribution system." Danish Gas Technology (2002). [2]. T. R. Yadvika, K. Sreekrishnan, V. Sangeeta, and A. Rana,“Enhancement of biogas production from solid substrates using different techniques- a review,” Bioresource Technology, vol. 95, no. [3]. Production and Analysis of Biogas from Kitchen Waste Ziana Ziauddin1, Rajesh P2 1, pp. 1- 10, October 2004. Bagi, Zoltán, et al. "Biotechnological intensification of biogas production. “Applied microbiology and biotechnology 76.2 (2007): 473-482. [4]. Amar Kumar Das, Shovan Nandi, Subrat Kumar Patra, Scope of Biogas generation from Kitchen wastes and its economical adoptability , International Journal of Latest Engineering and Management Research (IJLEMR) ISSN: 2455-4847 www.ijlemr.com || Volume 02 - Issue 05 || May 2017 || PP. 01-05 [5]. I.J.Dioha, C.H.lkeme, T.Nati’u, N.I.Soba and Yusuf M.B.S, .aeaffect of carbon to nitrogen ratio on biogas production Energy Commission of Nigeria, Vol 1,PP.1-10(2013). [6]. K.Kaygusuz, A.kaygusuz, Renewable Energy.25 (2002)431-453. [7]. R.Alvarez, R.Villica, G, Liden, Biomass and Bioenrgy, 30(2006)66-75. [8]. Meena, K., Kumar, V., & Vijay, V. K. (2011, June). Anaerobic technology harnessed fully by using different techniques: Review. In Clean Energy and Technology (CET), 2011 IEEE First Conference on (pp. 78-82). IEEE. [9]. Bougrier, C., et al. "Effect of ultrasonic, thermal and ozone pre-treatments on waste activated sludge solubilisation and anaerobic biodegradability." Chemical Engineering and Processing: Process Intensification 45.8 (2006): 711-718. [10]. Li, Yebo, Stephen Y. Park, and Jiying Zhu. "Solid-state anaerobic digestion for methane production from organic waste." Renewable and sustainable energy reviews 15.1 (2011): 821-826.**
Amar Kumar Das, Shovan Nandi, Amit Kumar Behera "Experimental Study of Different Parameters Affecting Biogas Production from Kitchen Wastes in Floating Drum Digester and its Optimization" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.98-103 2017
Suvarna G Kanakaraddi, Suvarna S Nandyal·July 2017·pp. 104-109
The Natural Language Processing (NLP) includes scope of computational methods for examining and speaking to actually happening writings at least one levels of semantic investigation with the end goal of accomplishing human-like dialect preparing for a scope of assignments or applications. For performing sentence structure investigation, the Fuzzy LALR (FLALR) parser is the best-known and most proficient parsing instrument. Really, the progressions of the setting free preparations are required to outline the well-working FLALR parser. In this paper FLALR parser, is presented, and its application to common dialect parsing is talked about. A FLALR parser is a move diminish parser which is deterministically guided by a parsing table. A parsing table can be acquired consequently from a setting free expression structure linguistic use. FLALR parsers can't oversee vague sentence structures, for example, common dialect syntaxes, on the grounds that their parsing tables would have increase characterized sections, which block deterministic parsing. FLALR parser, be that as it may, can deal with duplicate characterized passages, utilizing a dynamic programming strategy. At the point when an input sentence is ambiguous, the parser delivers all conceivable parse trees without parsing any piece of the information sentence more than once similarly.
Suvarna G Kanakaraddi
BVB College of Engineering & Technology, Hubli-580031, Karnataka, India
Suvarna S Nandyal
PDA College of Engineering, Kalaburgi-585102, Karnataka, India
Suvarna G Kanakaraddi, Suvarna S Nandyal "Fuzzy LALR Parser for Parsing Natural Language Sentences of English Language" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.104-109 2017
V. G. Ganesan, S. Shyam Sundar, P. S. Sivakumar·July 2017·pp. 110-116
NOx is a major pollutant of atmosphere and hence to prevent the adverse effects that take place on life and property, it is necessary to keep NOx emissions in control in power plants. Boiler efficiency of a 210MW boiler is found by varying the operating process and obtaining the corresponding NOx emission. From these test data we will come to know that performance and NOx emissions of the boiler are considerably impacted by operating process. Tangential firing boiler burning Lignite with a high combustion temperature and high excessive air ratio creates the highest NOx emission among the tested boilers. Variation of lignite type and boiler operational parameters also have large effects on the boiler performance and the NOx emission. This project will demonstrate the NOx emission can be reduced by regulating the combustion conditions and also concentrates on the variation of the boiler efficiency on a day to day basis due to change in properties of lignite being inducted.
V. G. Ganesan
Assistant Professor, Department of Mechanical Engineering, Easwari Engineering College, Chennai, Tamil Nadu, India
S. Shyam Sundar
U.G. Student, Department of Mechanical Engineering, Easwari Engineering College, Chennai, Tamil Nadu, India
P. S. Sivakumar
U.G. Student, Department of Mechanical Engineering, Easwari Engineering College, Chennai, Tamil Nadu, India
**[1]. William Payne,Richard E. Thompson, “Efficient Boiler Operations Sourcebook”, Fairmont Press, 1996, pp.29-32, 45-49. [2]. Brad Buecker, “Basics of Boiler and HRSG Design”, PennWell Books, 2002,pp.98-103, 107-122. [3]. Gene Knight, “Selective Catalytic Reduction for the control of Nitrogen Oxide Emissions from Coal-Fired Boilers”, DIANE Publishing, 2000, pp.110, 17-21. [4]. Akira Tomita, “Emissions Reduction: NOX/SOX Suppression”, Elsevier, 2001 pp.13-71, 97-135, 177-269. [5]. R.K.Rajput, “Power System Engineering”, Firewall Media,2006, pp.16-35, 48-69. [6]. M.M. El-Wakil, “Powerplant Technology”, McGraw-Hill, Inc., 1985, pp.129- 234. [7]. J. Weisman and R. Eckart, “Modern Power Plant Engineering”, PrenticeHall of India, 1985 [8]. BlackandViatch, “Power Plant Engineering”, Chapman & all, N.Y., Indian Edition, CBS Publishers, 1998**
V. G. Ganesan, S. Shyam Sundar, P. S. Sivakumar "Variation of Boiler Efficiency and NOx Emission Control Method Due to Excess Air in a Pulverized Lignite Fired Boiler of 210 MW Capacity" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.6 issue 7s, pp.110-116 2017
