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Volumetric data processing demands for a higher degree of robustness in monitoring and controlling the data traffic under the distributed environment. In the process of exchanging the data the issue of handling traffic concurrency is very much predominant. Due to inherent variations in local databases, traffic monitoring and controlling is needed to be robust enough to optimize resource utilization and operational performance of the mining system. The distributed databases contain variant information at different locations of the system. Because of this processing an integrated modelling of these distributed units is required simultaneously to formulate a Federated Database.The issue of concurrency in such systems lead to a dead lock condition and to a system failure. In the proposed work a new monitoring and controlling mechanism for controlling the concurrency of transactions and overcoming the issue of dead lock condition is developed. A probabilistic modelling of concurrent transactions for trafficking is developed.

Concurrency, Databases, Distributed units, Monitoring and controling

[1] K.Ali and b.Ahmad,”A Concurrency Control Method Based on Commitment Ordering in MobileDatabases”, International Journal of Database Management Systems IJDMS) vol.3, no.4, November 2011.
[2] K. N. Satone, "Modern Graph Databases Models," International Journal of Engineering Research and Applications, 2014.
[3] Kai Zhang, Kaibo Wang, Yuan Yuan, Lei Guo, Rubao Lee, Xiaodong Zhang. Mega-KV: a Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores. Proceedings of the VLDB Endowment 8 (11), 1226-1237, 2015.
[4] A.Larson, S. Blanas, C. Diaconu, C. Freedman, J. M. Patel, et al. High-Performance Concurrency Control Mechanisms for Main-Memory Databases. PVLDB, 5(4), 2011.
[5] Arun Kumar Yadav& Ajay Agarwal, An Approach for Concurrency Control in Distributed Database System, Vol. 1, No. 1, January June (2010).
[6] Asroor Hussain, Dongmei Chen, Angela Cheng, Hui Wei, David Stanley, 2013, Change detection from remotely sensed images: From pixel-b ase d to object-based approaches, ISPRS Journal of Photo-grammetry and Remote Sensing, Volume 80, June 2013, pp. 91-106, ISSN 0924-2716.
[7] B. S. Tjan, L. Breslow, S. Dogru, V. Rajan, K. Rieck, J. R. Slagle and M. O. Poliac, ‘A data-flow graphical user interface for querying a scientific database. in 1993 IEEE Symposium on Visual Languages, Norway, August 1993, IEEE Computer Society, pp. 49–54.

P L Kishan Kumar Reddy, T. V. Rao, A. Ananda Rao, "Analysis and Validation of Data access in Federated Database," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.86-94, 2018.

Ethernet has been the most dominating network technology since its debut; but in recent times the demand of wireless communication has grown rapidly due to its mobility and portability factors. The IEEE 802.11 Wireless Local Area Network (WLAN) standards, has become eminent technology bridge to the classic Ethernet. The Infrastructure mode of 802.11 uses an Access Point (AP) to coordinate all communications between the wired network and mobile stations. With the emerging real-time applications like VoIP and Video conferencing the access to the Internet through WiFi has become even more interesting and indispensible. Now days in many private as well as public organizations are deploying 802.11 standards to the existing networks availing internet access to its mobile users. In an organization, different users access an AP with different traffic types and different bandwidth requirements. As a matter of fact the categories of mobile users always vary in such networks having more priorities over others on the basis of their bandwidth requirement and purpose of the internet access. Therefore some dynamic and intelligent bandwidth management scheme may be incorporated alongside the current 802.11 so that users of higher priority can be serviced with adequate bandwidth by squeezing some bandwidth from lower priority users as and when needed. In this paper we proposed a dynamic technique for bandwidth management in 802.11wireless LAN. The proposed method has been implemented by means of simulations using OPNET Network Simulator.

Bandwidth, 802.11 WLAN, Quality of Service (QoS), Load, Delay, Retransmission Attempts, Traffic

[1] Brian P. Crow, Indra Widjaja, Jeong Geun Kim, Prescott T. Sakai, “IEEE 802.11 Wireless Local Area Networks”.
[2] Adalbert Engel,”Bandwidth Management And Quality Of Service”, Edith Cowan University,2000.
[3] Xiaomei Yu, Doan B. Hoang, David D. Feng, “Weight-Based Fair Intelligent Bandwidth Allocation for Red Adaptive Video Traffic”, 2006.
[4] Bo Fan ; Supeng Leng ; Kun Yang, “A dynamic bandwidth allocation algorithm in mobile networks with big data of users and networks”, IEEE Network, Volume: 30, Issue: 1, January-February 2016.
[5] Mohammed Awad, Abdelmunem Abuhasan, “A Smart Clustering Based Approach to Dynaic Bandwidth Allocation in Wireless Networks”, International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.1, January 2016.
[6] Elias, F. Martignon, and A. Capone, “An Efficient Dynamic Bandwidth Allocation Algorithm for Quality of Service Networks”.
[7] Niharika Kumar, K N Balasubramanya Murthy, Amitkeerti Mahaveer, ”User Oriented Network Aware Bandwidth Allocation in WiMAX”, Bangalore, India, Int. J. on Recent Trends in Engineering & Technology, Vol. 05, No. 01, Mar 2011.
[8] Vikas Sharma1, Vikram Kumar, Balvir Singh Thakur, ”Need of bandwidth management and formulation of policy framework for effective utilisation of internet services within a university campus”, Himachal Pradesh University, India, International Journal of Computer Science and Communication Vol. 2, No. 1, January-June 2011, pp. 173-178.
[9] S. Rawat1, P. Chaturvedi, "Performance Analysis of QoS Parameters in OFDM Based Network", IJSRNSC,Volume-5, Issue-3, June 2017.

Satyajit Sarmah, Shikhar Kumar Sarma, "Dynamic Bandwidth Management in 802.11Wireless LAN," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.95-99, 2018.

The utilization of Multispectral sensors technology has become more and more significant in recent decades due to the extensive usage of capturing Multispectral images used in remote sensing applications. This research work explores a different view of investigating lossy multispectral image compression from a perspective of extracting spectral information. It is an exploitation-based lossy compression which further develops spectral/spatial multispectral image compression to preserve the significant spectral information of objects. In this paper, we present a transformed based DWT with Improved SPIHT algorithm for various existing discrete wavelets. The proposed algorithm, a lossy multispectral image compression method yields better performance results for PSNR, MSE, CR, ENTROPY(H), SSIM and CC with sym8 wavelet when compared with previous well-known compression methods and existing discrete wavelets.

Multispectral Images, DWT, ISPIHT, LIBT, LIST

[1] Xiaoli Tang and William A. Pearlman, “Hyperspectral Data Compression Three-Dimensional Wavelet-Based Compression,” Chapter in Hyperspectral Images,Kluwer Academic Publishers 2005.
[2] Francesco Rizzo, Bruno Carpentieri, Giovanni Amott and Jame A. Storer, “Low-Complexity Lossless Compression of Hyperspectral Imagery via Linear Prediction,” IEEE Signal Processing Letters, vol.12,February 2005.
[3] Ian B and Joan S S 2010 IEEE Trans. Geosci. Remote Sens. 487 2854.
[4] M. Ben-Ezra, Z. C. Lin, and B. Wilburn. Penrose pixels: Superresolution in the detector layout domain. In ICCV,2007.
[5] H. Chang, D. Y. Yeung, and Y. Xiong. Super-resolution through neighbour embedding. In CVPR, volume 1, pages 275–282,2004.
[6] Jian Sun, Jian Sun and Heung-Yeung “Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement,” IEEE TIP, Vol. 20, pp 1529-1542,2011.
[7] S.G. Mallat, “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, ” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, No. 7, July1989.
[8] C.K. Chui, An Introduction to Wavelets, Wavelet Analysis and its Applications, Volume 1, Academic Press,1992.
[9]. Kareen Lees,”Image Compression using Wavelets” in may 2002.
[10] Sonal and Dinesh Kumar,”A study of various Image compression techniques”, Guru Jhmbheswar university of science and technology, Hisar
[11] Marta Mrak and Sonia Grig,”Picture quality Measures in image compression systems”, EUROCON 2003 Ljubljana, Slovenia.
[12] Michail Shnaider, Andrew P Paplinski,”Wavelet transform in image coding”.
[13] Priyanka singh, Priti singh,” JPEG image Compression based on Biorthogonal, coiflets and Daubechies Wavelets”..
[14] Faisal Zubir Quereshi, “Image Compression using Wavelet Transform”.
[15] Mahesh S.Chavan, Nikos Mastorakis, Manjusha N.Chavan,”Implementation of SYMLET Wavelets to Removal of Gaussian Additive Noise from Speech Signal”.
[16] K.Sayood, “Introduction to Data Compression”, 2nd edition, Academic Press, Morgan Kaufman Publishers,2000.
[17] “Multispectral Image Compression for various band images with high Resolution Improved DWT SPIHT”. SERSC: Science & Engineering Research Support Society International Journal of signal processing, image processing and pattern recognition ISSN: 2005-4254 Volume 9, No.2 (2016) pp.271-286

Bhagya Raju V, Dr. K. Jaya Sankar, and Dr. C. D. Naidu, "Multispectral Image Compression with Discrete Wavelet Transformed Improved SPIHT using various Wavelets," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.100-106, 2018.

Information security is the one of the ultimate generous apprehension in each turf of today’s period. In order to shelter the data broadcast over the ambiguous passage, formerly abundant cryptographic procedures are accomplished. But several limits present in the currently asymmetric and symmetric encryption procedures. The key transaction is a prime delinquent of symmetric cryptographic techniques though quicker in ciphering. Prolonged encryption interval is foremost delinquent convoyed with asymmetric methods but key transaction is simple & secure. Now, to incredulous these anomalies, in this paper a hybrid model is projected which agreements extreme security with decreased key maintenance problem and encryption time using unification of the together symmetric and asymmetric cryptographic procedures. To achieve the embryonic security services as authentication, integrity, and confidentiality in this hybrid model message digest, encryption methods and digital signature respectively is used and a digital envelope is also incorporated which involves all of this to transfer them confidently over the connection.

Hybrid Cryptography, Information Security, Asymmetric cryptographic technique, Symmetric cryptographic technique, Digital signature, Digital envelope

[1] K. Kaur, Er. Seema “Hybrid Algorithm with DSA, RSA and MD5 Encryption Algorithm for wireless devices” International Journal of Engineering Research and Applications (IJERA) Vol. 2, Issue 5, pp.914-917 , Sept-Oct 2012.
[2] S. Sharma, V. Kapoor “A Novel Approach for Improving Security by Digital Signature and Image Steganography” International Journal of Computer Applications , Volume 171 – No. 8, August 2017.
[3] S. Subasree, N. K. Sakthivel “Design of New Security Protocol Using Hybrid Cryptographic Algorithm” IJRRAS 2 (2) February 2010.
[4] Dr. V. Kapoor, R. Yadav “A Hybrid Cryptography method to Support Cyber Security Infrastructure” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 4 Issue 11, November 2015.
[5] A.M.S. Rahma, R.N. Farhan, H. J. Mohammad “Hybrid Model For Securing E-Commerse Transaction” International Journal of Advances in Engineering & Technology, Vol. 1, Issue 5, pp. 14-20, Nov 2011.
[6] S.Deshmukh, Prof. R.Patil “Hybrid cryptography method using modified Diffie-Hellman and RSA” International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014,.
[7] G. Mateescu, M. Vladescu “A Hybrid Approach of System Security for Medium and Small Enterprises: combining different Cryptography method” Federated Conference on Computer Science and Information Systems pp. 659–662, 2013.
[8] M. Gobi, Dr. K. Vivekanandan “A New Digital Envelope Approach for Secure Electronic Medical Records” International Journal of Computer Science and Network Security, VOL.9 No.1, January 2009.
[9] Md. G. Rashed, S. Ullah “ Secured message data transactions with a Digital Envelope (DE) - High level cryptographic method” International Conference on Engineering Research, Innovation and Education 2013, Bangladesh, 11 ̶ 13 January 2013.
[10] R. Ganesan, M. Gobi, K. Vivekanandan “A Novel Digital Envelope Approach for Secure E-Commerce Channel”. International Journal of Network Security, Vol.11, No.3, PP.121–127, Nov. 2010.
[11] L.M. Bottasso “A public-key cryptography tool for personal use: A true-world implementation of ECC for secure file exchange”. E-Business and Telecommunications (ICETE), 12th International Joint Conference on 2016, July 2015.
[12] F. Li, M. Shirase, T. Takagi “Identity-Based Hybrid Signcryption” Availability, Reliability and Security, 2009. ARES `09. International Conference on March 2009.

S.M. Bhat, V. Kapoor, "Design and Implementation of Hybrid Cryptographic Model based on Data Authentication, Integrity and Privacy Schemes," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.107-112, 2018.

Text Summarization is an active and interesting research area that has emerged to in recent times .There is an increase in trend of online shopping. Before buying any product or service online users prefer to read opinions about that product of service. But problem is that there are millions of reviews for same product is available over different websites and users do not have the time to read all the reviews. So need of review summarization is there. Text summarization method summarizes the content of reviews of people with help of similarity and clustering methods and guide them whether to purchase that product or not. Text summarization can be of many types. This research work proposes an extractive improved text summarization method which performs better than existing text summarization methods. This is done by including some improvements in the text summarization method like in this research work, those sentences are retained which have at least one noun, one adjective, one verb and one adverb. This stops the elimination of some of the important reviews. Also this research work is combining STASIS similarity and LDA technique for calculating semantic and context similarity respectively. After that similarity score generated by both the techniques is combined and an overall similarity score is calculated. Sentences are assessed using this similarity score and conflicting sentences are eliminated. And most important improvement of this research work is to improve k-means clustering by including Levenshtein distance instead of Euclidean distance. After doing this improvements both the existing and improved text summarization methods are applied on datasets of reviews and their performance is compared using factors like Rand Measure, Precision, Recall, F-measure, Review Importance Factor and it is proved that proposed method is better than existing method.

Text Summarization, Data Mining,Extractive Summarization,Text Mining

[1] Abhishek Kauirik, Sudhanshu Naithani, “A comprehensive study of text mining approach”, IJCSNS International Journal of Computer Science and Network Security, Vol. 16,Isuue 2,Feb 2016
[2] Alaa F. Alsaqer, Sreela Sasi. “Movie review summarization and sentiment analysis using rapidminer”, 2017 International Conference on Networks & Advances in Computational Technologies, ISSN: 978-1-5090-6590-5, July 2017
[3] D. Gaikwad and C. Mahender, "A review paper on text summarization", International Journal of Advanced Research in Computer and Communication Engineering, Vol. 5,Issue 3, March 2016
[4] A. Shetty, R. Bajaj, "Auto text summarization with categorization and sentiment analysis", International Journal of Computer Applications,Vol.130, Issue 7 ,2015
[5]Xiaoye Wanga, Xiaorui Chaia, Ching-Hsien Hsua, Yingyuan Xiaoa, Yukun Lia,"cluster analysis based on opinion mining", 8th International Conference on Ubi-Media Computing,ISSN:978-1-4673-8270-0,2015
[6]https://onlinecourses.science.psu.edu/stat555/node/86
[7] A.Dharmarajan, T.Velmurugan, “Applications of partition based clustering algorithms: a survey" , IEEE International Conference on Computational Intelligence and Computing Research, ISSN:978-1-4799-1597-2,2013
[8] Preeti Arora, Dr. Deepali, Shipra Varshney,"Analysis of k-means and k-medoids algorithm for big data", International Conference on Information Security & Privacy, Dec 2015
[9]S. Sethi, A. Dixit,“ An adaptive web search system based on web usages mining” International journal of computer engineering and application , Vol. X , Issue. 1, ISSN: 23213469 ,2016
[10] S. Sethi, A. Dixit, “An Automatic User Interest Mining Technique for Retrieving Quality Data” International Journal of Business Analytics. Vol. 4, Issue. 2, pp 62-79, ISSN: 2334-4547, 2017

B. Batra, S. Sethi, A.Dixit, "Improved Text Summarization Method for Summarizing Product Reviews," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.113-122, 2018.

This paper discusses optimization of parameters concerning simplified model of bio-mimetic fish robot propelled by rigid 3 link segments. Considering theoretical aspects of hydrodynamics and practical challenges in engineering realization, rigid segments optimal link-length ratio and motion parameters are numerically calculated using an enhanced rigid body fitting method (RBFM). Further the 3-linked robot fish like structure is simulated in BhT(bio-hydro dynamics simulator) to optimize and improve swimming speed of the robot fish effectively by considering various parameters such as no of joints, body length, shape of tail fin etc.

Biohydrodynamics, robotic fish, rigid body fitting, link length ratio

[1] Abhra Roy Chowdhury, Wang Xue, Manasa Ranjan Behera, S. K. Panda, “Hydrodynamics study of a BCF mode bioinspired robotic-fish underwater vehicle using Lighthill’s slender body model”, Journal of Marine Science and Technology, Vol. 21, pp. 102-114, March 2016.
[2] A Munnier, “Locomotion of Deformable Bodies in an Ideal Fluid: Newtonian versus Lagrangian Formalisms“, Vol 19, December 2009,pp 665-663.
[3] A Anu Priya, S Raja Mohamed, “A Survey on Various Robotic Fish Models based on Oscillatory Motion”, International Journal of Computer Applications, Volume 142, Issue 2, May 2016, pp.37-42.
[4] D. Barrett, M. Grosenbaugh, and M. Triantafyllou, “The optimal control of a flexible hull robotic undersea vehicle propelled by an oscillating foil,” in Proc. 1996 IEEE AUV Symp., pp. 1–9.
[5] G. Xie, “An improved constrained cyclic variable method,” Mechanics, vol. 28, No. 1, pp. 19–21, 2001 (in Chinese).
[6] Hirata, K.: Design and Manufacturing of a Small Fish Robot, Processing of Japan Society for Design Engineering, No.99, pp.29-32.2001
[7] https://en.wikipedia.org/wiki/Bio-inspired_robotics, accessed on 20 Feb 2016.
[8] Korkmaz, D.; Koca, Ozmen, G.; Akpolat, Z. H.: Robust Forward Speed Control of a Robotic Fish, Sixth International Advanced Technologies Symposium, Elazig/Turkey, May 16-18, 2011, pp.33-38.
[9] Lighthill, M. J.: Note on The Swimming of Slender Fish, J. Fluid Mech., Vol.9, 1960, pp.305-317.
[10] M. Sfakiotakis, D. M. Lane, and J. B. C. Davies, “Review of fish swimming modes for aquatic locomotion,” IEEE Journal of Oceanic Engineering, vol. 24, No. 2, pp. 237–252, Apr. 1999.
[11] S Swarnamugi, S Raja Mohamed, P Raviraj, “ A Survey on undulatory motion based robotic fish design”, Vol. 3, May 2016, pp. 1-10.
[12] Triantafyllou, M. S.; Triantafyllou, G. S.: An Efficient Swimming Machine, Scientific American, Vol.272, 1995, pp.64-70.
[13] Yu, J.; Wang, L.: Parameter Optimization of Simplified Propulsive Model for Biomimetic Robot Fish, Proceedings of the IEEE International Conference on Robotics and Automation, Barcelona, April, 2005, pp.3317-3322.
[14] Yu, S.; Ma, S.; Li, B.; Wang, Y.: An Amphibious Snakelike Robot: Design and Motion Experiments on Ground and in Water, Proceedings of the IEEE International Conference on Information and Automation, Zhuhai/Macau, China, June 22-25, 2009, pp.500-505.

S. Raja Mohamed, P. Raviraj, "Optimized curve fitting for rigid body segments of robotic fish using biohydrodynamics simulator," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.123-128, 2018.

Due to the rapid increase in the use of wireless technologies, we require the appropriate usage of radio spectrum. For the appropriate usage of radio spectrum, one of the technique called cognitive radio come into existence. As we know number of users are increasing progressively but our available spectrum are becoming abundant. Research says that almost of the authorized spectrum persists spare for lots of the time and thus decreasing the efficiency. By using the cognitive radio we can provide this unoccupied spectrum to the unlicensed user without causing any interference to the other network. To accomplish this we need to perform the spectrum sensing and for this many spectrum sensing techniques has been proposed by the researchers. This paper will give the brief introduction about the various spectrum sensing techniques. At last the result is provided in this paper by comparing the functioning of energy detection technique on Rayleigh and AWGN channels by using Receiver Operating Characteristics Curve in MATLAB software by varying SNR and number of samples “n” values.

Cognitive radio, matched filter, energy detection, spectrum sensing

[1] Lu et al., “Ten years of research in spectrum sensing and sharing in cognitive radio,” EURASIP Journal on Wireless Communications and Networking, 2012.
[2] H. Celebi, Ismail Guvenc, S. Gezici and H. Arslan, “Cognitive-Radio Systems for Spectrum, Location and Environmental Awareness”, IEEE Antennas and Propagation Magazine, vol. 52, pp. 41-61, 2010.
[3] Y-C Liang, K-C Chen, G. Ye Li and P. Mahonen, “Cognitive Radio Networking and Communications: An Overview”, IEEE Transactions on Vehicular Technology, vol. 60, no. 7, pp.3386-3407, 2011.
[4] Nazar Radhi, “Implementation of Spectrum Sensing Techniques for Cognitive Radio Systems,” Brunel University, London, July 2011.
[5] Sajjad Ahmad Ghauri, I M Qureshi, M. Farhan Sohail, SherazAlam, M. Anas Ashraf, “Spectrum Sensing for Cognitive Radio Networks over Fading Channels”, IJCER Vol. 2, Issue. 1, 2013
[6] Mr. Pradeep Kumar Verma, Mr. Sachin Taluja, Prof. Rajeshwar Lal Dua, “Performance analysis of Energy detection, Matched filter detection & Cyclostationary feature detection Spectrum Sensing Techniques” IJCER, Vol.2 Issue. 5, 2012
[7] J Ma, GD Zhao, YG Li, “Soft combination and detection for cooperative spectrum sensing in cognitive radio networks”, IEEE Transactions on Wireless Communications, Vol. 7, Issue. 11, pp. 4502–4506 (2008).
[8] Tulika Mehta, Naresh Kumar, Surender S Saini, “Comparison of Spectrum Sensing Techniques in Cognitive Radio Networks”, IJECT Vol. 4, Issue Spl - 3, 2013
[9] Garima Nautiyal, Rajesh Kumar, “Spectrum Sensing In Cognitive Radio Using Matlab”, International Journal of Engineering and Advanced Technology (IJEAT), Vol.2, Issue.5, 2013.
[10] Md. Shamim Hossain, Md. Ibrahim Abdullah, and Mohammad Alamgir Hossain, “Energy Detection Performance of Spectrum Sensing in Cognitive Radio”, I.J. Information Technology and Computer Science, Vol. 4, Issue. 11, pp. 11-17, 2012.
[11] Omkar S. Vaidya, Vijaya M. Kulkarni, “Analysis of Energy Detection based Spectrum Sensing over Wireless Fading Channels in Cognitive Radio Network” , International Journal of Emerging Technology and Advanced Engineering, Vol. 2, Issue. 3, 2013.
[12] Dong-Chan Oh and Yong-Hwan Lee, “Energy Detection Based Spectrum Sensing for Sensing Error Minimization in Cognitive Radio Networks,” International Journal of Communication Networks and Information Security (IJCNIS) Vol. 1, Issue. 1, 2009.
[13] Sajjad Ahmad Ghauri, et al.,” Spectrum Sensing For Cognitive Radio Networks Over Fading Channels” International Journal of Computer and Electronics Research, Vol. 2, Issue. 1, 2013.
[14] F.F.Digham, M.S.Alouini and M.K.Simon,” On the Energy Detection of unknown Signals over Fading Channels” IEEE Transactions on Communications, Vol. 55, Issue. 1, pp.21-24, 2007.
[15] A. Papoulis and S.U.Pillai,” Probability, Random Variables and Stochastic Processes”, New York: McGraw-Hill, ed. 4th,2002.
[16] J.G.Proakis, Digital Communication, New York:McGraw-Hill, ed. 4th,2001.
[17] Z.Han, R.Fan and H.Jang, ”Replacement of Spectrum Sensing in Cognitive radio”, IEEE Transactions on Wireless Communications, Vol. 8, Issue.6, pp.2819-2826, 2009.

Shelly Berwal, Vikas Sindhu, "Analysis of Performance of Energy Detection over Distinct Channels in Cognitive Radio," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.129-136, 2018.

The drive industry appears to invite a need for assuaging greater flexibility of its entities. Despite the astounding spurt in the control mechanism for operating the converter, it still requires and further enhancements to realize better performances of the drive system. The significant interest centers around an emphasis to address the switching effects on the output voltage ripple. The reduction in ripple can allow a better voltage or speed regulation of the drive motor power from chosen two stage dc-dc converter. The attempt envisages exploring the usage of a fresh sigma delta based pulse generation methodology for the power devices in the converter. It orients to evaluate its performance using MAT LAB simulation and exhibit its suitability in terms of its indices and characteristics of the drive motor for establishing its claim in the utility world.

Sigma-Delta controller, interleaved converter, PMDC Motor

[1] V. Grigore, J. Hatonen, J. Kyyra, and T. Suntio, “Dynamics of a buck converter with a constant power load,” in Proc. IEEE 29th Annu. Power Electron. Spec. Conf., vol. 1, pp. 72–78, May 1998.
[2] S. Hadavi, M.J.Sanjari, “A Novel Approach for Interleaved Buck Step-Down Converter Switching using the Sigma-Delta Method”, Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran 2,3 Faculty of Electrical Engineering, University Teknologi Malaysia, Johor Bahru, Johor DarulTakzim, Malaysia.
[3] Giorgio Spiazzi, IEEE “Analysis of the Interleaved Isolated Boost Converter with Coupled Inductors” VOL. 62, NO. 7, JULY 2015.
[4] R. Saadi, M. Bahri1, M.Y. Ayad, M. Becherif, O. Kraa1, A. Abouboul.”Implementation and Dual Loop Control of Two Phases Interleaved Boost Converter for Fuel cell Applications” Department of Electrical Engineering MSE Laboratory, Mohamed khider University Biskra, Algeria.
[5] Rafael Pena-Alzola, Peter Ksiazek and Martin Ordonez “Introducing State-Trajectory Control for the Synchronous Interleaved Boost Converter” Department of Electrical and Computer Engineering The University of British ColumbiaVancouver Canada, BC V6T 1Z4.
[6] Jul-Ki Seok, “Modeling and Control of the Average Input Current for Three-Phase Interleaved Boost Converters”, 10.1109/TIA.2014.2365635,IEEE.
[7] Yie-Tone Chen*, Wei-Cheng Lin and Ruey-Hsun Liang Department of Electrical Engineering, “An interleaved high step-up DC-DC converter with double boost paths”, National Yunlin University of Science and Technology, Douliu City, Yunlin 64002, Taiwan.
[8] M. Godoy Simões; C. L. Lute; A. N. Alsaleem, “Bidirectional Floating Interleaved Buck-Boost DC-DC Converter Applied to Residential PV Power System Center for Advanced Control of Energy and Power Systems” Colorado School of Mines Golden, USA.
[9] Koki Ishikawa, Yohhei Mochizuki, Kohji Higuchi1 KamonJirasereeamornkul, KosinChamnongthai, “Design of Approximate 2-Degree-of-Freedom Controller for Interleaved PFC Boost Converter”, The University of Electro-Communications 1-5-1, Chofugaoka, Chofu, Tokyo, 182-8585, Japan.
[10] Chong-Eun Kim, Deok-Ki Yang, Jae-Bum Lee, and Gun-Woo Moon, “High Efficiency Two Inductor PFC Boost Converter Employing SPDT Relay”, Server Power Development Team, Samsung Electro-Mechanics, Suwon,Korea, 10.1109/TPEL.2014.2368567, IEEE.
[11] Donny Radianto Student Member, IEEE Kyushu University, “Neural network based a two phase interleaved boost converter for photovoltaic system”, Japan State Polytechnic of Malang , Indonesia, Milwakuee, USA 19-22 Oct 2014.
[12] Laszlo Huber, Member, IEEE, Brian T. Irving, and Milan M. Jovanovic, “Fellow Open-Loop Control Methods for Interleaved DCM/CCM Boundary Boost PFC Converters”, IEEE.
[13] BoualemSalhia, Hassan El Fadilb, University of MouloudMammeri, Automatic Department, Tizi-Ouzou, “Adaptive Output Feedback Control of Interleaved Parallel Boost Converters Associated with Fuel Cell”, Algeria, Electric Power Components and Systems, 43(8–10):1141–1158, 2015.
[14] Denis De Castro Pereira, Marico Renato Da Silva, Elder Mateus Silva and Fernando Lassa Tofoli, “Comprehensive review of high power factor ac-dc boost converters for PFC applications”, CEP 36307-352 26 October 2014.
[15] MiodragNikoli´c, ReinhardEnne, Bernhard Goll, Member, IEEE, and Horst Zimmermann, Senior Member, IEEE. A Nonlinear-Average-Current-Controlled Multi-Phase Boost Converter with Monolithically Integrated Control and Low-Side Power.

G. Rajalakshmi, R. Ashok Kumar, K. Asokan, "Sigma-Delta Controller for Speed Regulation of Interleaved Converter Fed PMDC Motor Drive," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.137-140, 2018.

U-Shaped plate represents an important class of machine members which find their application in components such as crane hook, C – clamp, frames of presses and etc. The stress analysis of the critical section of the curved beam is a crucial step in its design. There are two methodical used for stress analysis of curved beams: a plane elasticity formulation and Winkler’s theory. The Winkler’s theory has long been the primary means of curved beam stress analysis in engineering practice. This paper describes the stress analysis of a U – shaped specimen, the base of which represents a curved beam using the standard Winkler’s theory and follow on experimental stress analysis using strain gauges. The specimen is loaded such that a known bending moment is applied to it. The circumferential stresses along the critical section of the curved beam are determined using Winkler’s theory. The experimental procedure of an aluminium U – shaped specimen is instrumented with several strain gauges along the critical section. The gauges are used to measure the circumferential strains along the critical section. The circumferential stresses are then calculated using Hooke’s law. In this paper analytical method and experimental method illustrates many essential elements of experimental stress analysis of a U shaped curved beam.

Strain Gauges, Winkler’s Theory, Circumferential Stress, Wheatstone Bridge, Strain Indicator etc

[1] Mark E. Tuttle, “Illustrating Essentials of Experimental Stress Analysis Using A U-Shaped Beam” SEM Annual Conference, Indianapolis, IN, 7-9 June 2010.
[2] Joseph Edward Shigley et al., “Mechanical Engineering Design” 8th edition, Tata McGraw- Hill, 2008.
[3] James W Dally and William F Riley, “Experimental Stress
Analysis”, 3rd Revised Edition, McGraw-Hill, 1991.
[4] Professor Milivoje M Kostic, “Calibration of and Measurement with Strain Gauges”.
[5] Joseph R Davis, “Aluminium and Aluminium Alloys”, Metals Handbook, ASM International, 1988.
[6] Machine Design Data Hand Book by K. Lingaiah Vol. II
[7] Experimental Stress Analysis by Sadhu Sing, Khanna Publishers.
[8] B. Celiktas, N. Unlu, E. Karacuha “An Anti-Ransomware Tool Design by Using Behavioral and Static Analysis Methods“, Isroset- Journal (IJSRCSE) Vol.6 , Issue.2 , pp.1-9, Apr-2018.

Vijendra kumar, Badri Prasad, Mohammad Ghouse, Badarinarayan, Prajwal, Mallikarjun, "Experimental Verification and Analysis of A U-Shaped Curved Beam Plate by Using FEA Tool," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.141-146, 2018.

In the competitive situation of an aircraft is no longer dominated by economic criteria. To an economic consideration, there are several criteria needed to be taken into account in aircraft design and evaluation of decision making processes. To solve complex real-world decision making problems, multi-attribute decision making (MADM) methods have been developed. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is among the most widely used methods at present which provides valuable outputs in different application areas. Here we improve the performance of the overall system, identify the set of important parameters of the decision making system using TOPSIS. Moreover, we calculate the distance of each alternative from the positive ideal solution (PIS) and negative ideal solution (NIS). We use a numerical experiment to demonstrate the methodology of the suggested approach.

Decosion Making, MADM, NIS. PIS, TOPSIS

[1] European Aeronautics: a vision for 2020. Meeting society`s needs and winning global leadership, Luxembourg: Office for Official Publications of the European Communities, 2001.
[2] M. R. Kirby. A Methodology for Technology Identification, Evaluation, and Selection in Conceptual and Preliminary Aircraft Design. PhD thesis, Aerospace Systems Design Laboratory, School of Aerospace Engineering, Georgia Institute of Technology, 2001.
[3] Y. Li. An Intelligent Knowledge-based Multiple Criteria Decision Making Advisor for Systems Design. PhD thesis, Aerospace Systems Design Laboratory, School of Aerospace Engineering, Georgia Institute of Technology, 2007.
[4] C.L. Hwang, K. Yoon, “Multiple attribute decision making: Methods and Applications”, Springer-Verlag , 1981.
[5] C.T. Chen, “Extensions of the TOPSIS for group decision-making under fuzzy environment”, Fuzzy Sets and Systems, Vol. 114, pp.01-09, 2010.
[6] D.L. Olson, “Comparison of Weights in TOPSIS Models”, Mathematical and Computer Modelling, Vol. 40, pp.721-727, 2004.
[7] I. Ertugrul, N. Karakasoglu, “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”, Expert Systems with Applications, Vol. 36, pp.702-715, 2009.
[8] M. Ehrgott, J. Figueira, S. Greco, “Trends in Multiple Criteria Decision Analysis”, Springer, 2010.
[9] V. Belton, T. J. Stewart, Multiple Criteria Decision Analysis - An Integrated Approach, Kluwer Academic Publishers, 2002.
[10] J.-W. Wang, C.-H. Cheng, H.K. Cheng, “Fuzzy hierarchical TOPSIS for supplier selection”, Applied Soft Computing, Vol. 9, Issue 1, pp.377-386, 2009.
[11] F. Herrera, E. Herrera-Viedma, J.L. Verdegay, “A model of consensus in group decision making under linguistic assessments”, Fuzzy Sets and Systems, Vol. 78, pp. 73-87, 1996.
[12] J. Wang, S.Y. Liu, J. Zhang, “An extension of TOPSIS for MCDM based on vague set theory”, Journal of System Science and System Engineering, Vol. 14, pp. 73-84, 2005.
[13] M. Delgado, J.L. Verdegay, M.A. Vila, “Linguistic decision-making models”, International journal of Intelligent System, Vol. 7, Issue 5, pp. 479-492, 1992.
[14] P.K. Parida, S.K. Sahoo, “Fuzzy multiple attributes decision making models using TOPSIS technique”, International Journal of Applied Engineering Research, Vol. 10, Issue 2, pp. 2433-2442, 2015.
[15] P.K. Parida, S.K. Sahoo, B. Behera, “Multi-criteria decision making models using fuzzy TOPSIS technique”, Journal of Altra Scientist of Physical Sciences, Vol. 28, Issue 5, pp. 286-293, 2016.
[16] R.A. Krohling, G.C.P. Andre, “A-TOPSIS-An approach based on TOPSIS for ranking evolutionary algorithms”, Procedia Computer Science, Vol. 55, pp. 308-317, 2015.
[17] T.C. Chu, Y.C. Lin, “Improved extensions of the TOPSIS for group decision making under fuzzy environment”, Journal of Information and Optimization Sciences, Vol. 23, pp. 273-286, 2013.

P.K. Parida, D. Mishra, B. Behera, "Some Generalized Results on TOPSIS Method Involving Multi-Attributes Decision Making Problem," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.147-152, 2018.