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Exploring Innovation| ISSN:2249-8958(Online)| Reg. No.:61902/BPL/CE/2011| Published By BEIESP| Impact Factor: 5.02
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Volume-6 Issue-5 Published on June 30, 2017
01
Volume-6 Issue-5 Published on June 30, 2017

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S. No

Volume-6 Issue-5, June 2017, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Shubhangi Pandhare, Abhishek Gautam, Sayali Chavan, Shital Sungare

Paper Title:

Co-Operative Content Downloading Framework Over Cellular Network

Abstract: The multifold advancement over wireless communication has in a way, predicted to use smartphones, laptops, and tabs vastly for downloading purpose. But due to confined data transfer capacity, the statistics of downloading quantity approximately for a distinctive person is constrained and time taking for a high precision video. The co-operative content downloading framework will permit the requested joiners inside the network to download a section of the file independently. This may aid the potential to download the document with cost effectiveness and with a reduced time consumption component. The above mentioned framework will additionally trace the real process how the transfer speed (bandwidth) will be distributed within the joiners and one requestor. The entire framework will deliver the efficient utilization of bandwidth in specific environments.

Keywords:
 Segmentation, Cluster formation, Adhoc network, Sequencing.


References:

1.       Haibo Zhou, Student Member, IEEE, Bo Liu, Member, IEEE, Tom H. Luan, Member,, “ChainCluster: Engineering a Cooperative Content Distribution Framework for Highway Vehicular Communications”, IEEE transactions on intelligent transportation systems, 2014.
2.       Chao-Hsien Lee, Chung-Ming Huang, Senior Member, IEEE, Chia-Ching Yang, and Hsiao-Yu Lin,,“ The K-hop Cooperative Video Streaming Protocol Using H.264/SVC Over the Hybrid Vehicular Networks,” , IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 6, JUNE 2014.

3.       Aarti R. Thakur,  Prof. Jagdish Pimple, “Performing vehicle to vehicle communication based on two tier approach with high security using aodv protocol in VANET”, 1) International Journal of Emerging Research in Management &Technology ISSN: 2278-9359 (Volume-3, Issue-7),July 2014

4.       J. Luo and D. Guo, “Neighbor discovery in wireless ad-hoc networks based on group testing,” in Proc. 46th Annu. Allerton Conf.Communication, Control, Computing, Urbana-Champaign, IL, USA Sep. 2008, pp. 791–797.

5.       R. Khalili, D. L. Goeckel, D. Towsley, and A. Swami, “Neighbor discovery with reception status feedback to transmitters,” in Proc. 29th IEEE Conf. INFOCOM, San Diego, CA, USA, Mar. 2010,pp. 2375–2383

6.       C.-M. Huang, C.-C. Yang, and H.-Y. Lin, “A K-hop bandwidth aggregation scheme for member-based cooperative transmission over vehicular networks,” in Proc. 17th IEEE ICPADS, Tainan, Taiwan, 2011, pp. 436–443.

7.       Nandan, S. Das, G. Pau, M. Gerla, and M. Y. Sanadidi, “Cooperative downloading in vehicular ad-hoc wireless networks,” in Proc. 2nd Annu. Conf. WONS, Washington, DC, USA, 2005 pp. 32–41

8.       M. F. Tsai, N. Chilamkurti, J. H. Park, and C. K. Shieh, “Multi-path transmission control scheme combining bandwidth aggregation and packet scheduling for real-time streaming in multi-path environment,” Instit. Eng. Technol. Commun., vol. 4, no. 8, pp. 937–945, 2010.

9.       M. Y. Hsieh, Y. M. Huang, and T. C. Chiang, “Transmission of layered video streaming via multi-path on ad-hoc networks,” Multimedia Tools Appl., vol. 34, no. 2, pp. 155–177, 2007.

10.    D. Fan, V. Le, Z. Feng, Z. Hu, and X. Wang, “Adaptive joint session scheduling for multimedia services in heterogeneous wireless networks, in Proc. 70th IEEE VTC, Anchorage, AK, USA, Sep. 2009, pp. 1–5.

11.    M. Li, Z. Yang, and W. Lou, “Codeon: Cooperative popular content distribution for vehicular networks using symbol level network coding,” IEEE J. Sel. Areas Commun., vol. 29, no. 1, pp. 223–235, Jan. 2011.

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2.

Authors:

Cini K.

Paper Title:

Value Based Reliability Evaluation of Primary Power Distribution System

Abstract: Distribution system reliability is concerned with the availability and quality of power supply at each customer’s service entrance. Analysis of customer failure statistics shows that failure in distribution system contribute as much as 90% towards the unavailability of supply to a load as compared with each part of electric systems. These statistics reinforces the need for reliability evaluation of distribution systems. In recent years with the advent of smart grids the significance of distribution system has enhanced because of the importance of co generation and distributed generation. The different causes and duration of failures are analysed season wise. The failure rate of the different feeders of the system under study was calculated and the reliable feeders were identified. Suggestions are given to improve the reliability of the feeders. This type of analysis will help the operation and maintenance engineers to maintain the quality service to the customers and schedule the maintenance services.  

Keywords:
Distribution Systems, Reliability Indices, Failure Rate, Availability.

References:

1.       Biyun Chen; Qianyi Chen “The whole-process reliability evaluation  of  power  system including generation, transmission, transformation and distribution” IEEE 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), pp 482-487
2.       H. 2. Andrews, Laura, Samuel” Novel Power System Reliability Indices calculation method” 23rd International Conference on Electricity Distribution, Lyon  15-18, June .

3.       Roy Billinton and Peng Wang “ Distribution System Reliability Cost/worth analysis Using Analytical and sequential Simulation Techniques” IEEE transactions on power systems, Vol.13, No.4, November 1998,pp1245-1250.

4.       R. Billinton and J. E. Billinton, “Distribution System Reliability Indices”, IEEE Trans. on Power Delivery, Vol. 4, No. 1, Jan. 1989, pp. 561-568.

5.       Vito Longo ,Walter R. Puntel, “Evaluation of Distribution System Enhancements Using Value-Based Reliability Planning” Procedures IEEE Transactions on Power
systems, vol. 15, no. 3, august 2000.

6.       Billinton, R., and Allan, R. N., "Reliability Evaluation of Power Systems",Pitman Books, New York and London, 1984.

7.       Billinton, R., "Evaluation of Reliability Worth in an Electric Power system". Reliability Engineering and System Safety, Vol. 46, No. 1, 1994.

8.       Carlos Eduardo Paida Tenemaza “State of Art, Reliability In Electrical Distribution Systems Based On Markov Stochastic Model”  IEEE Latin America Transactions, Volume: 14, Issue: 2, pp 799-804.

9.       Farajollah Soudi and Kevin Tomsovic  “Optimal Trade-Offs in Distribution Protection Design” IEEE  transactions on power delivery, vol. 16, no. 2, April 2001.

10.    Amir Safdarian; Mohammad Farajollahi; Mahmud Fotuhi-Firuzabad “ Impacts of Remote Control Switch Malfunction on Distribution System Reliability” IEEE Transactions on Power Systems, Volume: 32, Issue: 2, 2017, pp 1572-1573.

11.    Siripha Junlakarn; Marija Ilić , “Distribution System Reliability Options and Utility Liability”  IEEE Transactions on Smart Grid , Volume: 5, Issue: 5, 2014, pp 2227-2234.


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3.

Authors:

S. L. Deshpande, D S Chaudhari

Paper Title:

Wireless Nodes Assisted Micro-Irrigation System: an IoT Approach

Abstract: Irrigation systems deployed with Wireless Sensor Network (WSN) while transforming them to Micro-Irrigation systems are emerging as fruitful solution to ongoing ground water crisis. Field parameters like soil moisture, temperature and humidity can be monitored taking help of sensor array and can be fed back to decision making control system. Organized parametric results can help the optimized use of the water. By using wireless communication and environmental energy harvesting techniques, sensor network can be made totally wireless. Internet of Things (IoT) is another emerging technology that goals to extend the application of internet from complex computational machines (computer) to the stand alone devices such as consumer electronics. Integrating IoT to WSN not only can provide remote access but also allow two distinct information systems to frequently collaborate and provide common services. Also the user can be provided with flexible interface like mobile application. The miniaturization in technology and even more reliable communication are the strongest suits of such sensor network. This paper reviews for various technologies to fulfil requirement of such application and the shows some system characteristics.

Keywords:
 WSN, IoT, Irrigation, Moisture, Humidity, Energy Harvesting, etc.


References:

1.       Basic Botany, Physiology, and Environmental Effects on Plant Growth, AZ master gardner manual, The University of Arizona, AZ, 1998.
2.       M. Morris. (2006). Soil Moisture Monitoring: Low-Cost Tools and Methods [Online]. Available FTP: attra.ncat.org Directory: attra-pub/PDF File: soil moisture.pdf

3.       Y. Kim, R. Evans and W. Iversen, "Remote Sensing and Control of an Irrigation System Using a Distributed Wireless Sensor Network," in IEEE Transactions on Instrumentation and Measurement, vol. 57, pp. 1379ꟷ1387, July 2008.

4.       W. Wang and S. Cao, "Application Research on Remote Intelligent Monitoring System of Greenhouse Based on ZIGBEE WSN," 2nd International Congress on Image and Signal Processing, Tianjin, pp. 1-5, 2009.

5.       Yu, Y. Cui, L. Zhang and S. Yang, "ZigBee Wireless Sensor Network in Environmental Monitoring Applications," 5th International Conference on Wireless Communications, Networking and Mobile Computing, Beijing, pp. 1ꟷ5, 2009.

6.       Z. Rasin, H. Hamzah and M. Aras, "Application and evaluation of high power Zigbee based wireless sensor network in water irrigation control monitoring system," IEEE Symposium on Industrial Electronics & Applications, Kuala Lumpur, pp. 548ꟷ551, 2009.

7.       M. Zorzi, A. Gluhak, S. Lange and A. Bassi, "From today's INTRAnet of things to a future INTERnet of things: a wireless- and mobility-related view," in IEEE Wireless Communications, vol. 17, no. 6, pp. 44-51, December 2010.

8.       G. Kortuem, F. Kawsar, V. Sundramoorthy and D. Fitton, "Smart objects as building blocks for the Internet of things," in IEEE Internet Computing, vol. 14, no. 1, pp. 44-51, Jan.-Feb. 2010.

9.       K. Langendoen, A. Baggio and O. Visser, "Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture," Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, Rhodes Island, pp. 1ꟷ8, 2006.

10.    L. Li, H. Xiaoguang, C. Ke and H. Ketai, "The applications of WiFi-based Wireless Sensor Network in Internet of Things and Smart Grid," 6th IEEE Conference on Industrial Electronics and Applications, Beijing, pp. 789-793, 2011

11.    M. Lee, J. Hwang and H. Yoe, "Agricultural Production System Based on IoT," IEEE 16th International Conference on Computational Science and Engineering, Sydney, NSW, pp. 833-837, 2013.

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4.

Authors:

Sajith A.G, Hariharan S

Paper Title:

A Region based Active Contour Approach for Liver CT Image Analysis Driven by Local likelihood Image Fitting Energy

Abstract: Computer tomography images are widely used in the diagnosis of liver tumor analysis because of its faster acquisition and compatibility with most life support devices. Accurate image segmentation is very sensitive in the field of medical image analysis. Active contours plays an important role in the area of medical image analysis. It constitute a powerful energy minimization criteria for image segmentation. This paper presents a region based active contour model for liver CT image segmentation based on variational level set formulation driven by local likelihood image fitting energy. The neigh bouring intensities of image pixels are described in terms of Gaussian distribution. The mean and variances of intensities in the energy functional can be estimated during the energy minimization process. The updation of mean and variance guide the contour evolving toward tumor boundaries. Also this model has been compared with different active active contour models. Our results shows that the presented model achieves superior performance in CT liver image segmentation. 

Keywords:
Active Contours, Chan-Vese model, Level sets


References:

1.       Kass, M., Witkin, A., and Terzopoulos, D.: ‘Snakes: Active contour models’, International journal of computer vision, 1988, 1, (4), pp. 321-331
2.       Osher, S., and Sethian, J.A.: ‘Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations’, Journal of computational
physics, 1988, 79, (1), pp. 12-49

3.       Caselles, V., Kimmel, R., and Sapiro, G.: ‘Geodesic active contours’, International journal of computer vision, 1997, 22, (1), pp. 61-79

4.       Kimmel, R., Amir, A., and Bruckstein, A.M.: ‘Finding shortest paths on surfaces using level sets propagation’, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17, (6), pp. 635-640

5.       Li, C., Xu, C., Gui, C., and Fox, M.D.: ‘Distance regularized level set evolution and its application to image segmentation’, IEEE transactions on image processing, 2010, 19, (12), pp. 3243-3254

6.       Malladi, R., Sethian, J.A., and Vemuri, B.C.: ‘Shape modeling with front propagation: A level set approach’, IEEE transactions on pattern analysis and machine intelligence, 1995, 17, (2), pp. 158-175

7.       Vasilevskiy, A., and Siddiqi, K.: ‘Flux maximizing geometric flows’, IEEE transactions on pattern analysis and machine intelligence, 2002, 24, (12), pp. 1565-1578

8.       Xu, C., and Prince, J.L.: ‘Snakes, shapes, and gradient vector flow’, IEEE Transactions on image processing, 1998, 7, (3), pp. 359-369

9.       Chan, T.F., and Vese, L.A.: ‘Active contours without edges’, IEEE Transactions on image processing, 2001, 10, (2), pp. 266-277

10.    Cremers, D., Rousson, M., and Deriche, R.: ‘A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape’, International journal of computer vision, 2007, 72, (2), pp. 195-215

11.    He, L., Peng, Z., Everding, B., Wang, X., Han, C.Y., Weiss, K.L., and Wee, W.G.: ‘A comparative study of deformable contour methods on medical image segmentation’, Image and Vision Computing, 2008, 26, (2), pp. 141-163

12.    Li, C., Huang, R., Ding, Z., Gatenby, J.C., Metaxas, D.N., and Gore, J.C.: ‘A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI’, IEEE Transactions on Image Processing, 2011, 20, (7), pp. 2007-2016

13.    Li, C., Kao, C.-Y., Gore, J.C., and Ding, Z.: ‘Minimization of region-scalable fitting energy for image segmentation’, IEEE transactions on image processing, 2008, 17, (10), pp. 1940-1949

14.    Paragios, N., and Deriche, R.: ‘Geodesic active regions and level set methods for supervised texture segmentation’, International Journal of Computer Vision, 2002, 46, (3), pp. 223-247

15.    Ronfard, R.: ‘Region-based strategies for active contour models’, International journal of computer vision, 1994, 13, (2), pp. 229-251

16.    Samson, C., Blanc-Féraud, L., Aubert, G., and Zerubia, J.: ‘A variational model for image classification and restoration’, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22, (5), pp. 460-472

17.    Tsai, A., Yezzi, A., and Willsky, A.S.: ‘Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification’, IEEE transactions on Image Processing, 2001, 10, (8), pp. 1169-1186

18.    Vese, L.A., and Chan, T.F.: ‘A multiphase level set framework for image segmentation using the Mumford and Shah model’, International journal of computer vision, 2002, 50, (3), pp. 271-293

19.    Li, C., Kao, C.-Y., Gore, J.C., and Ding, Z.: ‘Implicit active contours driven by local binary fitting energy’, in Editor (Ed.)^(Eds.): ‘Book Implicit active contours
driven by local binary fitting energy’ (IEEE, 2007, edn.), pp. 1-7

20.    Wang, L., He, L., Mishra, A., and Li, C.: ‘Active contours driven by local Gaussian distribution fitting energy’, Signal Processing, 2009, 89, (12), pp. 2435-2447

21.    Zhang, K., Song, H., and Zhang, L.: ‘Active contours driven by local image fitting energy’, Pattern recognition, 2010, 43, (4), pp. 1199-1206

22.    Mumford, D., and Shah, J.: ‘Optimal approximations by piecewise smooth functions and associated variational problems’, Communications on pure and applied mathematics, 1989, 42, (5), pp. 577-685


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5.

Authors:

Ogundare A.B, Ihiovi M.M

Paper Title:

Design of a 3 Phase Automatic Change-Over Switch using a PIC Microcontroller (PIC16F877A)

Abstract: Change over process involves switching electrical load from one power source to another, when the load is powered by two alternative sources (main utility and stand by generator). The process can be complex if it involves starting and stopping of source like generator and monitoring of mains. This paper presents a method to ease this rigorous process. A 3 phase automatic change over which uses generator control mechanism is designed to select between two available sources of power in this case, generator and utility with preference to the utility. The system monitors the utility mains supply and checks for complete failure as well as phase failure upon which it automatically start the generator, run it on idle for a minute, then switch the load to it. The system keeps monitoring the utility source for power restoration, it also monitor the generator output for failure upon any of which it switches back the load to utility supply and automatically switch off the generator. Once power is restored, the system delays for two minute before transferring the load to the utility supply. Success was recorded as the above processes were automated. This was achieved with the combination of discrete electrical and electronics components

Keywords:
 Electrical Load, Utility, Generator, Electrical and Electronics Components.


References:

1.       Ahmed M.S., Mohammed A.S. and Agusiobo O.B. (2006) ‘’Development of a Single Phase Automatic Change-Over Switch’’. AU J.T. 10(1): 68-74. Federal University of Technology Minna, Nigeria. (Jul. 2006)
2.       Amos, S.W. and James, M. (1981). Principles of transistor circuit: Introduction to the design of amplifiers, receivers and digital circuits. 6th ed., Hartnolls ltd., bodmin.UK.

3.       Atser A. Roy et-al, (2014). Design and Implementation of a 3-Phase Automatic Power Change-over Switch. e-ISSN : 2320-0847 p-ISSN : 2320-0936 Volume-3, Issue-9, pp-07-14

4.       Ezema L.S., Peter B.U., Harris O.O. (2012). Design of automatic change over switch with Generator control mechanism. SAVAP international.

5.       L.S. Ezema et-al, (2012). Design of Automatic Change Over Switch with Generator Control Mechanism. ISSN-L: 2223-9944. Vol.3, No.3, November 2012.

6.       Faissler, W.L. (1991). An introduction to modern Electronics, Willey, New York, NY, USA.

7.       Horowitz, P. and Winfield, H. (2002). The Art of Electronics, 2nd ed. Cambridge Univ. Press, Cambridge, UK

8.       Owen, B. (1995). Beginner’s Guide to Electronics 4th Ed. A Newness Technical Book, McGraw-Hill Companies Inc. New York, N.Y, USA.

9.       Oduobuk, E. J. et-al (2014). Design and Implementation of Automatic Three Phase Changer over Using LM324 Quad Integrated Circuit. International Journal of
Engineering and Technology Research Vol. 2, No. 4, April 2014, pp. 1 - 15, ISSN: 2327 – 0349.

10.    Rocks G. and Mazur G., (1993). Electrical motor controls. American Technical Publication, New-York, N.Y, USA.

11.    Ragnar, H. (1958). Electric Contacts Handbook. 3rd Edition, Springer-Verlag, Berlin/ Göttingen /Heidelberg. pp. 331-342.

12.    Theraja, B.L.; and Theraja, A.K. 2002. Electrical Technology, 21st ed. Ranjendra Ravida, New Delhi, India.


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6.

Authors:

Pooja C.S, K. R. Prassana Kumar 

Paper Title:

Survey on Load Balancing and Auto Scaling techniques for cloud Environment

Abstract: Cloud computing became now first choice and priority for every person who access the internet, one of the advantageous features of cloud computing is its scalability and flexibility. Auto scaling offers the facility to the individuals to scale up and scale down the resources as per their requirements, using only the needed resouce and paying for what they have used i.e "pay-as-you-use". As everything take place in automatic manner, so human involvement errors are less and reduce the manpower and costs. so to make use of elasticity user must use auto scaling technique that balances the incoming workload, and reduce the total cost and maintain the Service Level Agreement (SLA).In this work main ideas revolve around the problems in scalable cloud computing systems. In modern days, management of resources is in boom and most talked topic in cloud environment. we present some of the existing load balancing policies and about Autoscaling categories.

Keywords:
cloud computing, scaling, auto scaling, load balancing.


References:

1.    Fang Liu, Jin Tong, Jian Mao, Robert Bohn, John Messina, Lee Badger and Dawn Leaf,"NIST Cloud Computing Reference Architecture", NIST Special Publication 500-292, September 2011.
2.    M.Kriushanth, L. Arockiam and G. JustyMirobi,"Auto Scaling in Cloud Computing: An Overview", International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 7, July 2013, ISSN (Print): 2319-5940,ISSN (Online) : 2278-1021.

3.    Tania Lorido-Botran, Jose Miguel-Alonso , Jose A. Lozano, "A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments", ARTICLE in JOURNAL OF GRID COMPUTING DECEMBER 2014, Impact Factor: 1.51 • DOI: 10.1007/s10723-014-9314-7.

4.    ChenhaoQu, Rodrigo N. Calheiros, and RajkumarBuyya,"A Reliable and Cost-Ecient Auto-Scaling System for Web Applications Using Heterogeneous Spot Instances", Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computing and Information Systems, The University of Melbourne, Australia, September 17, 2015.

5.    Gunpriya Makkar, Pankaj Deep Kaur,"A Review of Load Balancing in Cloud Computing", Guru Nanak Dev University, Jalandhar, India, Volume 5, Issue 4, 2015 ISSN: 2277 128X.

6.    Priyanka P. Kukade and Geetanjali Kale “Survey of Load Balancing and Scaling approaches in cloud” vol.4 Feb 2015.

7.    Ashalatha R Evaluation of Auto Scaling and Load Balancing Features in Cloud” vol.117 may 2015.

8.    Dr. D .Ravindran, Ab Rashid Dar loud Based Resource Management with Autoscaling vol.2 .


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7.

Authors:

Ahmed Mohmad Aliywy

Paper Title:

Design and Analysis of NACA0016 Wing Rib and Stringers by using al-7075 and Kevlar

Abstract:  The aircraft wing consists of multiple airfoils shapes that are called “ribs”. These ribs are connected with stringers to form a shape of Skelton and then cover it with aluminium-alloy sheets to make a wing. In this paper, a NACA0016 airfoil ribs with stringers were designed in CATIA V5 by using three types of aluminium-alloys (AL-2024, AL-6061, and AL-7075) and then analysed in ANSYS workbench to determine the deformation, stress and safety factor values. The stringer's material was then changed from al-alloy to cfrp and Kevlar in order to find which combination of materials will give less deformation, stress and high safety factor. The results show that using cfrp material can reduce the weight up to 30% but the stress will increase while using Kevlar nearly reduces stress, deformation and weight up to 252Mpa, 25% and 33%, respectively.  It concluded that AL-7075-t6 and Kevlar materials give less stress and high strength to weight ratio.

Keywords:
Ribs, Stringers, NACA0016, Al-alloys, cfrp, Kevlar, Ansys, CATIA, Design foil.


References:

1.       Nathan logsdon, “a procedure for numerically analyzing airfoils and Wing sections,” The Faculty of the Department of Mechanical &Aerospace Engineering University of Missouri – Columbia, December 2006.
2.       Michael Chun-Yung Niu, “Airframe Stress Analysis and Sizing,” Lockheed Aeronautical Systems Company, California, 1997.

3.       Mr. P.Sujeeth reddy, Mr. M. Ganesh, “Design & Structural Analysis of a Wing Rotor by using ANSYS & CATIA,” International Research Journal of Engineering and Technology, Volume: 02 Issue: 06, sep-2015.

4.       J. Fazil and V. Jayakumar, “INVESTIGATION OF AIRFOIL PROFILE DESIGN USING REVERSE ENGINEERING BEZIER CURVE,” ARPN Journal of Engineering and Applied Sciences, VOL. 6, NO. 7, JULY 2011.

5.       Mohamed Hamdan A1, Nithiyakalyani S2, “Design and Structural Analysis of the Ribs and Spars of Swept Back Wing,” International Journal of Emerging Technology and Advanced Engineering, Volume 4, Issue 12, December 2014.

6.       Ambri, Ramandeep Kaur, “Spars and Stringers- Function and Designing,” International Journal of Aerospace and Mechanical Engineering, Volume 1 – No.1, September 2014.

7.       Megson, T.H.G., “Aircraft structures for engineering students,” Elsevier Aerospace Engineering Series, Fourth edition, 2007.

8.       Muhammad Sohaib, “Parameterized Automated Generic Model for Aircraft Wing Structural Design and Mesh Generation for Finite Element Analysis,” Linköping Studies in Science and Technology, 2011.

9.       Erdogan Madenci, Ibrahim Guven, “The Finite Element Method and Applications in Engineering Using Ansys,” The University of Arizona, Springer Science +Business Media, LLC, 2006.


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8.

Authors:

Deekshitha Dasireddygari

Paper Title:

Practical Immitation Checking and Data Consistency

Abstract: At in attendance Cloud Storage Systems are in front of two main tribulations one is Data steadfastness and the other is storage space. So that many companies are preferring 3-way replica scheme here the main negative aspect is the storage space of facts in Cloud is ever-increasing a lot, it even requires superfluous storage space cost. So we are going through the data trustworthiness and to overcome this problem, in this document we are going all the way through the data supervision which is cost effective and its named as PRCR which is normalized Data steadfastness Model. So we are forthcoming Proactive Replica algorithm, where the transparency is minor at PRCR, and also PRCR gives bare minimum imitation data at the cloud summit of view, which also known as yardstick of cost helpfulness at replication come within reach of. So here our work indicates, comparing both the three-replica tactic with PRCR which to the highest degree reduces the Cloud storage space from one by third to two by third, so it plainly shows the lowering of Storage Cost.

Keywords:
Data Minimum replication, Proactive Replica Checking, data Reliability, Cloud Computing, Cost effectiveness storage


References:

1.       Amazon. (2011). Amazon Simple Storage Service (Amazon S3). [Online]. Available: http://aws.amazon.com/s3/, 2011.
2.       R. Bachwani, L. Gryz, R. Bianchini, and C. Dubnicki, “Dynamically quantifying and improving the reliability of distributed storage systems,” in Proc. IEEE Symp. Rel. Distrib. Syst., 2008, pp. 85–94.

3.       Balasubramanian and V. Garg, “Fault tolerance in distributed systems using fused data structures,” IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 4, pp. 701–715, Apr.
2013.

4.       E. Bauer and R. Adams, Reliability and Availability of Cloud Computing. Piscataway, NJ, USA: IEEE Press, 2012.

5.       Borthakur. (2007). The Hadoop Distributed File System: Architecture and Design [Online]. Available: http://hadoop.apache.org/common/docs/r0.18.3/hdfs_design.html

6.       G. Chun, F. Dabek, A. Haeberlen, E. Sit, H. Weatherspoon, M. F. Kaashoek, J. Kubiatowicz, and R. Morris, “Efficient replica maintenance for distributed storage systems,” in Proc. Symp. Netw. Syst. Des. Implementation, 2006, pp. 45–58.

7.       J. G. Elerath and S. Shah, “Server class disk drives: How reliable are they?” in Proc. Annu. Symp. Rel. Maintainability, 2004, pp. 151– 156.

8.       J. Gantz and D. Reinsel, “Extracting value from chaos,” IDC iview, vol. 1142, pp. 9–10, 2011.

9.       Gharaibeh, S. Al-Kiswany, and M. Ripeanu, “ThriftStore: Finessing reliability trade-offs in replicated storage systems,” IEEE Trans. Parallel Distrib. Syst., vol. 22, no. 6, pp. 910–923, Jun. 2011.

10.    S. Ghemawat, H. Gobioff, and S. Leung, “The Google file system,” in Proc. ACM Symp. Oper. Syst. Principles, 2003, pp. 29–43.


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9.

Authors:

Prachi Patil, Sojwal Pajai, Surabhi Sanger, Dimpal Shinde

Paper Title:

Smart Medi Friend: An Automated Healthcare System, Implementation and Results

Abstract:  In the current era, one of the greatest concerns in healthcare is global aging and prevalence of chronic diseases A smart medi-friend is an all-inclusive healthcare application consisting android devices, cloud server and medi-box(NFC). This system works as an assistance application for healthcare and also as a medicine remainder, eliminating the possibility of taking wrong medicine. One of the five main modules, Admin, will manage doctors’ and patients’ info stored in database through server. Doctors will be able to give prescription, update prescription and timing, view report and history of patient from patient list. Patients will be able to identify medicines using NFCs, upload reports and view latest prescription. Patient’s app will generate an alert according to the medicine time uploaded by the doctor. ANN algorithm will predict the highest probable disease when symptoms are given as input. This project will reduce the burden on hospital resources, save time and money of patients and will act as a perfect assistance tool in healthcare services.

Keywords:
 NFC, ANN, JDBC, J2SE.


References:

1.        Geng Yang, Li Xie, Matti M¨antysalo, Xiaolin Zhou, Zhibo Pang, Li Da Xu, Sharon Kao- Walter, Qiang Chen, Lirong Zheng, “A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor and Intelligent Medicine Box”, 2013, IEEE
2.        Tania Cerquitelli, Elena Baralis, Lia Morra and Silivia Chiusano, “Data Mining for Better Healthcare: A Path Towards Automated Data Analysis?”, 2016, IEEE

3.        Amiya Kumar Tripathy, Rebeck Carvalho, Keshav Pawaskar, Suraj Yadav, Vijay Yadav, “Mobile Based Healthcare Management using Artificial Intelligence”, 2015, IEEE.

4.        Prethi.M, Ranjith Balakrishan, “Cloud Enabled Patient-Centric EHR Management System”, 2014, IEEE.

5.        Gillian Pearce, Lela Mirtskhulava, Koba Bakuria, Julian Wong, Salah Al-Majeed, Nana Gulua, “Artificila Neural Network and Mobile Applications in Medial Diagnosis”, 2015, IEEE.

6.        Qiang YE, Tao LU, Yijun LI, Wenjun SUN, “Neural Network with Forgetting: An ANN Algorithm for Customers”, 2005, IEEE.

7.        https://en.wikipedia.org.


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10.

Authors:

Jilna T Joy, Sumi M, Harikrishnan A. I.

Paper Title:

Microstrip Low Pass Filter using Defective Ground Structures

Abstract: Low pass filter forms the primary and vital component of a transceiver system. Three different methods to design compact microstrip low pass filter are discussed in this paper. All three prototypes contain defective ground structure (DGS) in the ground plane. Type I filter structure is designed with three fingered interdigital slot the ground plane. Type II low pass filter design contains circular DGS pattern, while type III low pass filter consist of many fingered interdigital slots on ground plane. Interdigital slot consists of metal fingers, which enhances the performance of the filter. The resonant frequency can easily be changed by tuning the length of the metal fingers. Based on the comparative study, it is found that the insertion loss is minimum for type III filter design i.e. 0.1dB. The return loss is found to be 26dB, 35.8dB and 21dB for type I, type II and type III low pass filter respectively.

Keywords:
Low pass filter, Defective ground structure, Interdigital slots, Insertion loss, Return loss


References:

1.          Prachi Tyagi, “Design and Implementation of Low Pass Filter using Microstrip Line”,International Journal of Latest Trends in Engineering and Technology,2015
2.          Aswini kumar,A.K varma, “Design of Compact Seven Poles Low Pass Filter using Defected Ground Structure” electro-2009

3.          Xue hui Guan, Guohui Li, Zhewang Ma,”Optimized Design of a Low-Pass Filter Using Defected Ground Structures”,APMC 2005

4.          Jong-Sik Lim, Chul-Soo Kim,Dal Ahn, Yong-Chae Jeong, Sangwook Nam,”Design of Low-Pass Filters Using Defected Ground Structure,”,IEEE transaction on microwave theory and techniques, Vol. 53, No. 8, Aug2005

5.          Fu-Chang Chen, Hao-Tao Hu, Jie-Ming Qiu Qing-Xin Chu,”High- Selectivity Low-Pass Filters With Ultrawide Stopband Based on Defected Ground Structures”, IEEE transaction on components, manufacturing and packing technology,2015

6.          Tamasi Moyra, Susanta Kumar Parui, and Santanu Das,”Design and Development of Lowpass Filter and Harmonics Reduction,” International Journal on Electrical Engineering and Informatics Volume 3, Number 3,2011.
7.          David M Pozar,” Microwave engineering,4th edition. Kiran P.Singh Anurag Paliwal Madhur Deo Upadhyay,” Novel Approach for Loss Reduction in LPF for Satellite Communication System”,IACC 2013
8.          Xi Tian,Yuzhu Wang,Tianyiyi He,”A  Rectangular coaxial line low pass filter with simple structure” ,ICEPT 2015

9.          Deepthi Gupta,Aneesha upadhyay,Manisha Yadav,Dr. P K singhal,”Design and analysis of low pass planar microstrip filter using left handed SRR structures”,MedCOM 2014.

10.       Deepthi Gupta,Aneesha upadhyay,Manisha Yadav,Dr. P K singhal,” CSRR Based Microstrip Low Pass Filter with Wide Stopband and High Attenuation”  ICCIS,2015

11.       Faisal Ali,Rajat Jain,Deepti Gupta,Alk Agarwal,,”Design and analysis of low pass elliptical filter” ,CICT 2016.

12.       Shuai Liu, Jun Xu , Zhitao Xu,” Sharp roll-off lowpass filter using interdigital DGS slot”, Electronics letters ,Vol. 51 No. 17, 20th August 2015


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11.

Authors:

Anju G. R, Karthik M.

Paper Title:

Dynamically Building Facets from Their Search Results

Abstract:  People are very passionate in searching new things and gaining new knowledge. They usually prefer search engines to get the results. Search engines become an important way to get the information. But many search engines fail to give some request to the users since there are same words which have different meaning such as apple, say it’s a fruit, mobile, laptop. So if there is ranking based on these, the searching will be a pleasing experience’s.  There are some methods for these such as searching based on facets. There are some exiting methods to gain facets from the search results and display the facets such that the user can select corresponding facets. Then the search results will be refined to those particular facets only. In this paper mainly focus on those facets that mean after the facets generation, the facets will be checked before displaying to the user. There are some facets such as “women watch, women’s watch “ , “Season one, season 1” these two have same meaning so before displaying the facets these similarities should be checked and only one facets should be displayed. Part of speech is also checked. Experimental results shows that checking these type similarities improve the facets thus it can improve the searching experiences in many ways.      

Keywords:
 Faceted search, Facets, Intent


References:

1.    “Automatically Mining Facets for Queries from Their Search Results” IEEE Transactions On Knowledge And Data Engineering, Vol. 28, No. 2, February 2016 Zhicheng Dou, Member, IEEE, Zhengbao Jiang, Sha Hu, Ji-Rong Wen, and Ruihua Song
2.    “Facets Mining From Search Results Using BatchSTS Algorithms” in IJARTET, Volume 4, Special Issue 6, April 2017, Anju G R, Karthik M

3.    “Comparison: QT (Quality Threshold) And Batch STS Algorithm For Facets Generation” JETIR (ISSN-2349-5162) April 2017, Volume 4, Issue 04, Anju G R, Karthik M

4.    W. Kong and J. Allan, “Extracting query facets from search results,” in Proc. 36th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2013, pp. 93–102.

5.    https://en.wikipedia.org/wiki/Discounted_cumulative_gain Google Wikipedia

6.    O. Ben-Yitzhak, N. Golbandi, N. Har’El, R. Lempel, A. Neumann,S. Ofek-Koifman, D. Sheinwald, E. Shekita, B. Sznajder, and S.Yogev, “Beyond basic faceted search,” in Proc. Int. Conf. Web Search Data Mining, 2008, pp. 33–44.

7.    W. Kong and J. Allan, “Extending faceted search to the general web,” in Proc.ACMInt. Conf. Inf. Knowl. Manage., 2014, pp. 839–848.

8.    “Mining Queries From Search Results : A Survey” Imperial Journal of Interdisciplinary Research (IJIR) Vol-2, Issue-12, 2016, Anju G R, Karthik M


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12.

Authors:

Yogeshwar Patil, Bhushan Pawar, Dipak Chaudari, Bhuvan Mahajan, Khemraj Patil

Paper Title:

Electrical Design and Implementation & Installation of 5kw Solar System

Abstract: Solar photovoltaic power generation system is one of the burning research fields these days, even governments are also making plans toward increasing the amount of power generation from renewable energy sources because in future viability and crisis of conventional energy sources will increase. Further government liberalization and technical developments encourage the use of renewable sources for power generation in terms of distributed generation system. In order to rigging the present energy crisis one renewable method is to develop an efficient manner in which power extracts from the incoming son light radiation calling Solar Energy. This thesis deals with the design and hardware implementation of a simple and efficient solar photovoltaic power generation system for isolated and small load up to 5 KW. It provides simple basic theoretical studies of solar cell and its modeling techniques using equivalent electric circuits. Solar Photovoltaic (PV) power generation system is comprising several elements like solar panel, DC-DC converter, MPPT circuit and load, and DC-DC (Boost) converter, MPPT circuit using microcontroller and sensors adopting perturbation and observation method and single phase inverter for AC loads are implemented in hardware in simple manner.

Keywords:
(PV), CDC-DC (Boost), MPPT, AC loads, Solar photovoltaic, government KW.


References:

1.    www.google.com
2.    Israel D. Vagner, B.I. Lembrikov, Peter Rudolf Wyder,Electrodynamics of Magneto active Media, Springer,2003, ISBN 3540436944

3.    "Energy Sources: Solar" Department of Energy” Retrieved 19 April 2011.

4.    International Energy Agency (2014). "Technology Roadmap: Solar Photovoltaic Energy" (PDF). IEA. Archived from the original on 7 October 2014. Retrieved 7 October 2014.

5.    Solar Cells and their Applications Second Edition, Lewis Fraas, Larry Partain, Wiley, 2010, ISBN 978-0-470-44633-1 , Section10.2.

6.    "sss Magic Plates, Tap Sun for Power". Popular Science. June 1931. Retrieved 19 April 2011.


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13.

Authors:

Sheela S, Ravi V.

Paper Title:

Efficient XML Interchange as Encoding Scheme in DDS

Abstract: Data Distribution Services has a world wide application in distributed embedded and real time applications. These systems communicate data between computing nodes over a network. DDS when used in time-critical applications like military systems, there is always a need for data being communicated to be delivered in real time. In this article we propose a novel scheme where efficient XML interchange can be used for compression of the data before being communicated between the publisher and the subscriber. This scheme helps in increasing the efficiency of the data transfer by reducing the file size along with encryption of plain text so that unintended person can be avoided reading the data.

Keywords:
 middleware, QoS parameters, participant, pre-compression, publisher, subscriber, data-centric


References:

1.       G. Pardo-Castellote, “OMG data distribution service: architectural overview,” IEEE Military Communications Conference, 2003. MILCOM 2003.
2.       Hadeel T. El Kassabi; Ikbal Taleb; Mohamed Adel Serhani; Rachida Dssouli, “Policy-based QoS enforcement for adaptive Big Data Distribution on the Cloud”, IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService), Year 2016

3.       Nanbor Wang; Douglas C. Schmidt; Hans van't Hag; Angelo Corsaro, “Toward an adaptive data distribution service for dynamic large-scale network-centric operation and warfare (NCOW) systems,” 2008 IEEE Military Communications Conference, Year 2008

4.       Paolo Bellavista; Antonio Corradi; Luca Foschini; Alessandro Pernafini, “Data Distribution Service (DDS):A Performance Comparison of Open Splice and RTI Implementations,” I IEEE Symposium on Computers and Communications (ISCC), Year 2013

5.       Gerardo Pardo-Castellote, Ph.D., “Data distribution service advanced tutorial”, Real-Time Innovations, Inc. http://www.rti.com”

6.       Juan Ingles-Romero; Adrian Romero-Garces; Cristina Vicente-Chicote; Jesus Martinez,  “A Model-Driven Approach to Enable Adaptive QoS in DDS-Based Middleware”, IEEE Transactions on Emerging Topics in Computational  Intelligence.


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14.

Authors:

Shyju S., Prathibha S Nair

Paper Title:

Packet Dropping and Intrusion Detection using Forensic and Flow Based Classification Techniques

Abstract:  Internal Intrusion detection is one of the serious problems in the computer network areas. Most of the computer system uses username and password as login pattern to enter in to the system. This is one of the weakest points of computer security. Some studies claimed that analyzing system calls (SCs) generated by commands can identify these commands and obtains the features of an attack. This paper propose a security system, named the Internal Intrusion Detection and Protection System(IIDPS) to detect insider attacks at SC level by using data mining and forensic techniques in networked data. The IIDPS creates users' personal profiles to keep track of users' usage habits as their forensic features and determines whether a valid login user is the account holder or not by comparing users current computer usage behaviors with the patterns collected in the account holder's personal profile. The idea behind the inside attacker detection in wireless sensor network by exploiting the spatial correlation between the packet ratio, which help to detecting dynamic attacking behaviors The routing is performed to identify the shortest path between each source node and their destination address and residual energy is calculated for each node in the network.

Keywords:
Insider attacks, intrusion detection, Flow based classification and System calls.


References:
1.       Q. Wang, L. Vu, K. Nahrstedt, and H. Khurana, “MIS: Malicious nodes identification scheme in network-coding-based peer-to-peer streaming,” in Proc. IEEE INFOCOM, San Diego, CA, USA, 2010, pp. 1–5.
2.       Z. A. Baig, “Pattern recognition for detecting distributed node exhaustion attacks in wireless sensor networks,” Comput. Commun., vol. 34, no. 3, pp. 468–484, Mar. 2011.

3.       S. Kang and S. R. Kim, “A new logging-based IP traceback approach using data mining techniques,” J. Internet Serv. Inf. Security, vol. 3, no. 3/4, pp. 72–80, Nov. 2013.

4.       K. A. Garcia, R. Monroy, L. A. Trejo, and C. Mex-Perera, “Analyzing log files for postmortem intrusion detection,” IEEE Trans. Syst., Man,Cybern., Part C: Appl. Rev., vol. 42, no. 6, pp. 1690–1704, Nov. 2012.

5.       M. A. Qadeer, M. Zahid, A. Iqbal, and M. R. Siddiqui, “Network traffic analysis and intrusion detection using packet sniffer,” in Proc. Int. Conf.Commun. Softw. Netw., Singapore, 2010, pp. 313–317.

6.       S. O’Shaughnessy and G. Gray, “Development and evaluation of a data set generator tool for generating synthetic log files containing computer attack signatures,” Int. J. Ambient Comput. Intell., vol. 3, no. 2, pp. 64–76, Apr. 2011.

7.       S. X. Wu and W. Banzhaf, “The use of computational intelligence in intrusion detection systems: A review,” Appl. Soft Comput., vol. 10, no. 1, pp. 1–35, Jan. 2010.

8.       Z. B. Hu, J. Su, and V. P. Shirochin “An intelligent lightweight intrusion detection system with forensics technique,” in Proc. IEEE Workshop Intell. Data Acquisition Adv. Comput. Syst.: Technol. Appl., Dortmund, Germany, 2007, pp. 647–651.

9.       T. Giffin, S. Jha, and B. P. Miller, “Automated discovery of mimicry attacks,” Recent Adv. Intrusion Detection, vol. 4219, pp. 41–60, Sep. 2006.

10.    U. Fiore, F. Palmieri, A. Castiglione, and A. D. Santis, “Network anomaly detection with the restricted Boltzmann machine,” Neurocomputing, vol. 122, pp. 13–23, Dec. 2013.

11.    M. A. Faisal, Z. Aung, J. R. Williams, and A. Sanchez, “Data-streambased intrusion detection system for advanced metering infrastructure in smart grid: A feasibility study,” IEEE Syst. J., vol. 9, no. 1, pp. 1–14,Jan. 2014.

12.    S. Khan, N. Mast, and J. Loo, “Denial of service attacks and mitigation techniques in IEEE 802.11 Wireless mesh networks,” Information,vol.12,pp.1–8,2009.

13.    S. Khan and J. Loo, “Cross layer secure and resource-aware ondemand routing protocol for hybrid wireless mesh networks,” Wireless Personal Communications,vol.62,no.1,pp.201–214,2010.

14.    S. Khan, N. Mast, K.-K. Loo, and A. Silahuddin, “Passive  security threats and consequences in IEEE 802.11 wireless mesh networks,” International Journal of Digital Content Technology and Its Applications,vol.2,no.3,pp.4–8,2008.

15.    S. E. Robertson, S. Walker, M. M. Beaulieu, M. Gatford, and A. Payne, “Okapi at TREC-4,” in Proc. 4th text Retrieval Conf., 1996, pp. 73–96.

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15.

Authors:

Arya V J, Subha V

Paper Title:

Tracking the Path of Launch Vehicle using Pulse Compression Technique

Abstract: Pulse Compression is one of the key steps in the signal processing of a Radar system. Radar system uses Pulse compression techniques to provide the benefits of larger range detection and high range resolution. This is gained by modulating the transmitted signal and after that matching the received echo with the transmitted signal. Matched filter is used as the pulse compression filter which provides high SNR at the output. Matched Filter is a time reversed and conjugated version of the received radar signal. There are several methods of pulse compression that have been used in the past, out of which most popular technique is Linear Frequency Modulation (LFM). This paper deals with the design to develop and simulate pulse compression and matched filter algorithm in MATLAB to study the LFM pulse compression technique. Matched filter is used as the pulse compression filter which provides high SNR at the output. Matched Filter is mathematically equivalent to convolving the received signal with a conjugated time-reversed version of the reference signal. The main application of pulse compression Radars includes tracking of launch vehicles, unwanted particles in space, Missile guidance etc. Here, in this paper we are discussing the pulse compression application in tracking the launch vehicle so as to check whether it had followed the predetermined path or not.

Keywords:
 Correlation, Chirp, LFM, Matched Filter, Pulse Compression, Radar


References:

1.       Kiran Patel., Usha Neelakantan.,Shalini Gangele, J.G Vacchani, N.M. Desai “Linear Frequency Modulation Waveform Synthesis” . IEEE Int’l.Conf, Electrical, Electronics and Computer Science,2012.
2.       Vijay Ramya K, A. K. Sahoo, G. Panda, “A New Pulse Compression Technique for Polyphase Codes in Radar Signals”, International Symposium on Devices MEMS, Intelligent Systems & Communication (ISDMISC) 2011 Proceedings published by International Journal of Computer Applications (IJCA), Vol. 2, Issue 4, pp.15-17, 2011.

3.       R. Jeffrey Keeler , Charles A. Hwang,” Pulse Compression for Weather Radar”,IEEE International Radar Conference , 1995.

4.       N. J. Bucci and H. Urkowitz, “Testing of doppler tolerant range sidelobe suppression in pulse compression meteorological radar,” in Proc. IEEE

5.       Nat. Radar Conf., Boston, MA, Apr. 1993, pp. 206–211.

6.       H.D. Griffiths , L. Vinagre,” Design of low-sidelobe pulse compression waveforms”, ELECTRONICS LE77ERS 9th June 1994 Vol. 30 No. 12

7.       Vikas Baghel, Ankita Panda, Ganapati Panda,” An Efficient Hybrid Adaptive Pulse Compression Approach to Radar Detection”,IEEE international conference on signal processing and communication (ICSC), 2013.

8.       Adnan Orduyılmaz., G¨okhan Kara., Ali Cafer G¨urb¨uz.,Murat Efe TOBB ETU¨ Real-Time Pulse Compression Radar Waveform Generation and Digital Matched Filtering IEEE, (2015).

9.       Mya Mya Aye , Thiri Thandar Aung  ,” Digital Filters for Radar Signal Processing”, International Research Journal of Engineering and Technology (IRJET),  Volume: 03 Issue: 11 | Nov -2016.

10.    H. A. Said., A. A. El-Kouny.,A. E. El-Henawey Design and Realization of Digital Pulse Compression in Pulsed Radars Based on Linear Frequency Modulation (LFM) Waveforms Using FPGA . ICAICTE, Jul-Aug,2013.

11.    Fu Ning.,Wang Yuze, Xu Hongwei, Qiao Liyan,Jin Hong Method of LFM Pulse Compression Implementation Based on FPGA . IEEE Int’l Conf, Electronic Measurement Instruments , 2013.

12.    Amit kumar, Ms. Nidhi Radar Pulse Compression Technique for Linear Frequency Modulated Pulses, International Journal of Engineering and Technical Research (IJETR), Volume-3, Issue-8, August 2015.

13.    Jun Wang, Duoduo Cai, Yaya Wen . Comparison of Matched Filter and Dechirp Processing Used in Linear Frequency Modulation IEEE 2011.


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16.

Authors:

Sagar G. Rautrao, Bhagwan R. Shinde

Paper Title:

Numerical Study of Exhaust Manifold using Conjugate Heat Transfer

Abstract:  The Exhaust manifold in the engines is an important component which has a considerable effect on the performance of the I.C engine. The exhaust system of an automobile consists of an exhaust manifold, catalytic converter, resonator & a muffler connected with tail pipe. Hot exhaust gas along with sound waves generated at the end of exhaust stroke is sent to the exhaust manifold through exhaust valve. The exhaust manifold operates under high temperature and pressure conditions. The design of exhaust manifold almost always has to be executed by trial and error through many experiments & analysis. In this paper we have to did numerical study by compare the result fluid analysis with conjugate heat transfer & thermal analysis with conjugate heat transfer using Abaqus software.

Keywords:
 Exhaust Manifold, Conjugate Heat transfer, Numerical study, Coupling, Abaqus


References:

1.       Vivekanand Navadagi, siddaveersanganad  “Cfd analysis of exhaust manifold of multicylinder petrol engine for optimal geometry to reduce back pressure” Intrnational journal of engineering Research and Technology (IJERT) March-2014
2.       BinzouYaqian Hu, Zhien Liu Fuwu Yan and chaowang.”The imapctof  Temperture effect on exhaust manifold Thermal modal analysis” Research journal of applied
science Engineering and Technology Aug 20, 2013

3.       SwathiSatishmani ,prithviraj and shridharhari “comparison of prediction obtained on an exhaust manifold analysis using conformal and indirect mapped interface”. International congress on computionalmechnics and simulation(ICCMS),IIT hydrabad 10-12 Dec 2012

4.       Xueyuan ZHANG YuLUO And Jianhua Wang “Coupled Thermal-fluid-solid Analysis of engine Exhaust manifold considering welding Residual stresses” Transaction of JWRI special issue on WSE2011(2011)

5.       Gopaal , MMM Kumara varma , “Exhaust manifold design –FEA Approch”(IJETT) Volume 17 number 10 – november.

6.       Zhi-EN Liu, Xue-Nili “Numerical simulation For exhust manifold based on the serial coupling of STAR-CCM+ AND ABAQUS Reasearch”  journal of Applied sciences ,Engineering & Technology , Nov 10 ,2013

7.       Gopaal, MMM Kumara verma “Thermal and structural Analysis of An Exhaust manifold of A multicylinder engine” (IJMET) vol 5 12 DEC(2014)

8.       Dr.Rajadurai, “Non-linear Thermal modal analysis for Hot End Exhaust System” International journal of emreging trends in engineering Research vol 2. Jan 2014

9.       AshwanikumarArunkumar “Thermo-mechnical Analysis of 321-Austenitic stainless steel Exhaust manifolds of a Diesl Engine based on FEA” Dehradun india.

10.    J.DavidRathnaraj “Thermomechniacl fatigue analysis of stainless steel exhaust manifolds (ESTIJ) vol 2. April 2012

11.    Jian Min xu “An analysis of the vibration charecterstics of suspension points” the open mechanical Engineering journal 2014.


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17.

Authors:

Sabitha S V, Jeena R S

Paper Title:

Automatic Detection and Localization of Tuberculosis in Chest X-Rays

Abstract: Tuberculosis is a major health threat in many regions of the world. Opportunistic infections in immune compromised HIV/AIDS patients and multi-drug-resistant bacterial strains have exacerbated the problem, while diagnosing tuberculosis still remains a challenge. When left undiagnosed and thus untreated, mortality rates of patients with tuberculosis are high. Standard diagnostics still rely on methods developed in the last century. They are slow and often unreliable. In an effort to reduce the burden of the disease, this thesis work presents an automated approach for detecting and localizing  tuberculosis in conventional postero -anterior chest raadiographs. A set of features are extracted  from the lung region, which enable the X-rays to be classified as normal or abnormal using a binary classifier. Then if the chest x-ray is classified as abnormal again a set of  local features are extracted to localize the affected regions . Thus it become easy to diagnose and treat the disease. An accuracy of 90% is achieved by this method.

Keywords:
 Graph cut segmentation, Classification, Local feature extraction.


References:

1.       Sema Candemir1, Stefan Jaeger2, Kannappan Palaniappan1, Sameer Antani2, and George Thoma2””Graph Cut Based Automatic Lung Boundary Detection in Chest Radiographs” 1st Annual IEEE Healthcare Innovation Conference of the IEEE EMBS Houston, Texas USA, 7 - 9 November, 2012
2.       Ramya R, Dr. Srinivasa Babu P “Tuberculosis Screening Using Graph Cut and Cavity Segmentation for Chest Radiographs “ International Journal of Advanced Research in Computer Science and Software Engineering  Volume 5, Issue 2, February 2015]

3.       Sema Candemir, Kannappan Palaniappany, and Yusuf Sinan Akgul Lister Hill National Center for Biomedical Communications, U. S. National Library of Medicine, National Institutes of Health, Bethesda, MD, USA Department of Computer Science, University of Missouri-Columbia, MO, USA Department of Computer Engineering, Gebze Institute of Technology, Gebze, Turkey “multi-class regularization parameter learning for graph cut image segmentation” 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro San Francisco, CA, USA, April 7-11, 2013

4.       Wai Yan Nyein Naing, Zaw Z. Htike “Advances in Automatic Tuberculosis Detection in Chest X-ray Images” Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.6, December 2014]  

5.       Stefan Jaeger*, Alexandros Karargyris, Sema Candemir, Les Folio, Jenifer Siegelman, Fiona Callaghan,Zhiyun Xue, Kannappan Palaniappan, Rahul K. Singh, Sameer Antani, George Thoma, Yi-Xiang Wang,Pu-Xuan Lu, and Clement J. McDonald “Automatic Tuberculosis Screening Using Chest Radiographs” IEEE  Transactions on Medical Imaging, vol. 33, no. 2, February 2014

6.       Laurens Hogeweg, Clara I. S´anchez, Pragnya Maduskar, Rick Philipsen, Alistair Story, Rodney Dawson, Grant Theron, Keertan Dheda, Liesbeth Peters-Bax and Bram van Ginneken “Automatic detection of tuberculosis in chest radiographs using a combination of textural, focal, and shape abnormality analysis” This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TMI.2015.2405761, IEEE Transactions on Medical Imaging.

7.       Amani Al-Ajlan, Ali El-Zaart “Image Segmentation Using Minimum Cross-Entropy Thresholding” Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics San Antonio, TX, USA - October 2009]

8.       Bram van Ginneken*, Shigehiko Katsuragawa, Bart M. ter Haar Romeny, Kunio Doi, and Max A. Viergever, Member, IEEE  “Automatic Detection of Abnormalities in Chest Radiographs Using Local Texture Analysis” IEEE transactions on medical imaging, vol. 21, no. 2, February 2002

9.       Manik Varma and Andrew Zisserman,” A Statistical Approach to Texture Classi_cation from Single Images Robotics Research Group Dept. of Engineering Science University of Oxford Oxford, OX1 3PJ, UK

10.    Manuel J. Marín-Jiménez and Nicolás Pérez de la Blanca,” Empirical Study of Multi-scale Filter Banks for Object Categorization” Technical Report VIP-121505 December 2005 

11.    W. K. Pratt, “Image Segmentation,” in Digital image processing, 4nd ed. Wiley, 2008, pp. 579 622.

12.    C. Pantofaru, M. Hebert, A comparison of image segmentation algorithms, Tech. Rep. CMU RI TR 05 40, CMU (2005). 2, 14

13.    Shi. J, and Malik. J, "Normalized cuts and image segmentation", IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society, voI.22(8), 2000, pp.888 905.

14.    William T.Freeman and Edward H Adelson “The Design and Use of Steerable Filters” IEEE Transaction on Pattern Analysis and Machine Intelligence ,Vol 13 No 9,September 1991

15.    Li Tang, Meindert Niemeijer, Joseph M. Reinhardt, Senior Member, IEEE, Mona K. Garvin, Member, IEEE, and Michael D. Abràmoff*, Senior Member, IEEE “Splat Feature Classification With Application to Retinal Hemorrhage Detection in Fundus Images” IEEE Transactions on medical imaging, vol. 32, no. 2, february 2013


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