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Conventional pensiveness queries, like contrast search and nearby neighbor retrieval involve completely on conditions imposed on objects of geometric properties. Nowadays, various applications absorb new types of queries that aspire to hunt out objects satisfying every generalization predicate and a predicate on connected texts. as Associate in Nursing example, instead of considering all the restaurants, a nearest neighbor question would instead elicit the edifice that is the utmost among those whose menu contain “steak, spaghetti, sprite” all at a similar time. Presently the foremost effective resolution to such queries is based on the IR2-tree, which, as shown throughout this paper, aims at a couple of deficiencies that seriously impact its efficiency. motivated by this, we have a tendency to tend to develop a replacement access methodology called the abstraction inverted index with the intention of extends the quality inverted index to deal with flat data, and comes with algorithms that will answer nearby neighbor queries through keywords in real time. As verified by experiments, the projected techniques outgo the IR2-tree and are subjected to significantly, generally by a component of, orders of magnitude.

SI Index,IR Tree, Fast Nearest, Neighbor

[1] J. Lu, Y. Lu, and G. Cong. Reverse spatial and textual k nearest neighbor search. In Proc. of ACM Management of Data SIGMOD) pages 349–360, 2011
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[3] G. Bhalotia, A. Hulgeri, C. Nakhe, S. Chakrabarti, and S. Sudar- shan. Keyword searching and browsing in databases using banks. In Proc. of International Conference on Data ngineering (ICDE), pages 431–440, 2002.
[4] V. Maniraj, R .Mary, "Productive K-Nearest Neighbor (PKNN) and Index Based Positioning for Keyword Search", International Journal of Computer Sciences and Engineering, Vol.4(4), pp.379-383, Apr -2016
[5] X. Cao, G. Cong, and C. S. Jensen. Retrieving top-k prestige-based relevant spatial web objects. PVLDB, Vol. 3(1):373–384, 2010.
[6] X. Cao, G. Cong, C. S. Jensen, and B. C. Ooi. Collective spatial keyword querying. In Proc. of ACM Management of Data (SIG-MOD), pages 373–384, 2011.
[7] B. Chazelle, J. Kilian, R. Rubinfeld, and A. Tal. The bloomier filter: an efficient data structure for static support lookup tables. In Proc. of the Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 30–39, 2004.
[8] Y.-Y. Chen, T. Suel, and A. Markowetz. Efficient query processing in geographic web search engines. In Proc. of ACM Management of Data (SIGMOD), pages 277–288, 2006.
[9] E. Chu, A. Baid, X. Chai, A. Doan, and J. Naughton. Combining keyword search and forms for ad hoc querying of databases. In Proc. of ACM Management of Data (SIGMOD), 2009.

S.P. Reddy, P. Govindarajulu , "Implementation of Nearest Neighbor Retrieval," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.51-57, 2017.

Advance in technology, there is a different aspect of designing and allotting number plates to the vehicle of their country. For the several respective regular administrative tasks, the license number plate is used by various government offices for purposes of tracking of number plates, for the analysis of theft case, for the collection and management of parking vehicles. The unique number is given for each motorized vehicle in India. Vehicles play a vital role because of population growth. For various security purposes vehicle number has to be stored. The number plate is recognized to extract number of the plate faster. The character recognition technique is used to recognize numbers and character from number plate. Then recognized the number and character is stored in a cloud storage system as and used for further needs.

Character Recognition, Cloud Storage

[1] Kerav Shah, Gourav Inani, Darshan Rupareliya, Rupesh Bagwe and Bharathi H, “RFID Based Toll Automation System”, International Journal of Computer Sciences and Engineering, Vol.4(4), pp.51-54, April 2016.
[2] Sagar Badgujar,Amol Mahalpure, Priyaka Satam, Dipalee Thakar, Swati jaiswal, “Real time number plate recognition and tracking vehicle system” SSRG International Journal of Computer Science and Engineering ,vol.2(12), Dec 2015
[3] N.Nagaraju, M.S.Kiruthika , R.Gowthami , S.Mala , K.Pavithra, “Auto Payment of Tolls with Tracking of Theft Vehicles & Proximity Detection for Avoiding Accidents”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol.3(4),April 2014
[4] Dr. P.K.Suri, Dr. Ekta Walia, Er. Amit Verma,” Vehicle Number Plate Detection using Sobel Edge Detection Technique”, International Journal of Computer Science and Technology,Vol.1(2), Dec 2010.
[5] Amol A. Chapate, D.D. Nawgaje,” Electronic Toll Collection System Based on ARM”, International Journal of Science, Engineering and Technology Research, Vol.4(1), Jan 2015.
[6] Devika Mhatre, “Electronic Toll Collection Using Barcode Reader”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.5(2), pp.124-127, Feb2015.
[7] AungMyint Win,et.al, “RFID based automated toll plaza system”, International Journal of Scientific and Research Publications, Vol.4(6),pp.1-7 June 2014.

R.M. Newlin, M. Ranjani, K.V. Venkatesa , "Toll Gate Vehicle Monitoring System – A Preview," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.58-60, 2017.

This paper discusses the Fuzzy logic concept based on the fuzzy set theory. Here, Fuzzy logic is discussed as a mathematical theory for the representation of uncertainty. This paper also contains a design outlook for fuzzy controller design.

Fuzzy Logic, Fuzzy Sets, Fuzzy Predicates, Fuzzy Truth Values, Fuzzy Quantifiers,Fuzzy Controller

[1] Zadeh L A., "Fuzzy logic= computing with words." IEEE transactions on fuzzy systems Vol.4(2), pp.103-111,1996.
[2] Mendel J M., "Fuzzy logic systems for engineering: a tutorial." Proceedings of the IEEE, Vol.83(3),pp.345-377, 1995.
[3] Lee C C., "Fuzzy logic in control systems: fuzzy logic controller. I." IEEE Transactions on systems, man, and cybernetics, Vol.20(2), pp. 404-418, 1990.
[4] Sugeno M., Takahiro Y., "A fuzzy-logic-based approach to qualitative modeling." IEEE Transactions on fuzzy systems Vol.1(1), pp. 7-31, 1993.
[5] Zadeh, L. A., Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy sets and systems, Vol.90(2), pp.111-127, 1997.
[6] Kumthekar Y., Patil A N., Notani Y., Fating J., Das S., "Traffic Signal Optimization and Flow Control using Fuzzy Logic", International Journal of Computer Sciences and Engineering, Vol4(5), pp.153-156, May -2016.
[7] Mamdani E H., "Application of fuzzy logic to approximate reasoning using linguistic synthesis." Proceedings of the sixth international symposium on Multiple-valued logic. IEEE Computer Society Press, Bijing, 1976.
[8] Lin C-T., George L., "Neural-network-based fuzzy logic control and decision system." IEEE Transactions on computers, Vol. 40(12), pp.1320-1336, 1991.
[9] Jasmine J.S., "Application of Fuzzy Logic in Neural Network Using Data Mining Techniques: A Survey", International Journal of Computer Sciences and Engineering, Vol.4(4), pp. 333-341, Apr -2016.

S. Hemba, N. Islam , "Fuzzy Logic: A Review," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.61-63, 2017.

In modern era of wireless communications Viterbi decoder (VD) is widely used to decode Binary Convolution Codes (BCC) in many Wi-Fi systems such as WLAN 802.11a/n/ac/ah, Satellite communications, Mobile communications etc. To obtain high decoding performance, the constraint length of BCCs is basically quite long. Whereas the complexity of VD is exponentially affected by BCCs constraint length. Therefore Viterbi decoding of BCCs with long constraint length cannot be used for systems or devices like Internet of Things (IoT) sensors, that require low power and less hardware cost. In this work a less-complex Kmin Viterbi Decoder (KVD) is proposed in which the decoder`s complexity is inconsiderably affected by constraint length. For the decoding performance evaluation such as Packet Error Rate (PER) and Bit Error Rate (BER) of the proposed decoder, a BCC with constraint length k = 7 is used. This code is required in Wi-Fi systems such as IEEE 802.11a/n/ac/ah. A new standard 802.11ah for IoT applications is considered for simulation. The PER performance of proposed KVD decoder in relation with several factors such as channel type, modulation type, decoder`s trace-back length and packet size has been evaluated. The proposed KVD achieves the same PER performance as the orthodox VD does, while its complexity is reduced by approximately 12.80 times to 21.33 times shown in result analysis.

kmin Viterbi Decoder (KVD); Binary Convolution Code (BCC); IoT sensors; Packet Error Rate (PER); Bit Error Rate (BER); Wireless Transceiver; 802.11 a/n/ac/ah WLAN

[1] Liu T.Y., Zhou G.: “Key Technologies and Applications of Internet of Things”. In the Proceedings of fifth Int. Conf. on Intelligent Computation Technology and Automation (ICICTA-2012) , Xian, pp.197–200, 2012.

[2] Girau R, Martis S, Atzori L, “Lysis: a platform for IoT distributed applications over socially connected objects”, IEEE Internet of Things Journal (IoTJ), Vol.4(1), pp. 1-12, 2016.

[3] Tran T. H., Nagao Y., Kurosaki M., Sai, B., Ochi, H.: “ASIC Implement of 600Mbps IEEE 802.11n 4x4 MIMO Wireless LAN System”. In the Proceedings of 14th IEEE Int. Conf. on Advan. Commu. Tech. (ICACT-2012), Korea, pp. 360–363, 2012.

[4] Viterbi, A.: “Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory” Vol.1(1) pp. 260-269, 1967.

[5] Dutta R., Van Der Mast C., “Virtex 4 FPGA Implementation of Viterbi Decoded 64-bit RISC for High Speed Application using Xilinx”, International Journal of Computer Applications (IJCA), Vol.88(14), pp. 30-35, 2014.

[6] Maharatna K., Troya A., Krstic M., Grass E.: “On the implementation of a low-power IEEE 802.11a compliant Viterbi decoder”. In the Proceedings of 19th Int. Conference on VLSI Design (DOI:10.1109/VLSID). Bombay, pp.124, 2006.

[7] Chakraborty D, Raha P, Bhattacharya A, Dutta R; “Speed Optimization of a FPGA based modified Viterbi Decoder”, in the Proc. of IEEE Int. Conf. on Computer, Communication and Informatics (ICCCI-2013), Coimbatore, pp. 321-326; 04-06 January, 2013. ISBN: 978-1-4673-2907-1.
[8] Sandesh, Y.M., Kasetty, R.: “Implementation of Convolution Encoder and Viterbi Decoder for Constraint Length 7 and Bit Rate ½”, Int. Journal of Engineering Research and Applications Vol.3(4), pp. 42-46, 2013.

[9] IEEE 802.11 committee: Part 11: “Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications”. IEEE Std. 802.11a, Vol.38(6), 1999.

[10] Tran T.H., Nagao Y., Ochi H.: “Algorithm and Hardware Design of A 2D Sorter-based K-best MIMO Decoder”. EURASIP Journal on Wireless Communications and Networking DOI: 10.1186/1687-1499-2014-93, Vol.8(3), 2014.

[11] Dutta R, Pradhan PC, Sharma P, Guha S: “VoIP Technology based modified CAC scheme for IEEE 802.11 Wireless LANs”, In the Proceedings of Int. Conf. on Computation and Communication Advancement (IC3A) – 2013, West Bengal, pp. 174-180, 2013.

[12] Dutta R, Chaudhuri D, Mohanto B, Das M; “A Proposed DLCCS Algorithm for High Speed Operation & Implementation on FPGA”, International Journal Nanotechnology & Applications (IJNA), Vol.8(1), pp. 01-12, 2014.

[13] Liu Y.S., Tsai Y.Y.: “Minimum decoding trellis length and truncation depth of wrap-around Viterbi algorithm for TBCC in mobile WiMAX”, EURASIP Journal on Wireless Communications and Networking, Vol. 44(8) DOI: 10.1186/1687-1499-2011-111, 2011.

R. Dutta, S.C. Konar, K. Mitra , "PER/BER Performance Evaluation of Less-Complex KVD Decoding Architecture for IEEE 802.11 a/n/ac/ah WLANs," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.64-76, 2017.

In existence of instability within the financial dealings, a reasonable harmony among risks and returns has to be managed by an investor to derive at an optimum standpoint. Although there is a predominant instability, the advantage lies in the correlation of the combination of financial instruments/assets in a financial portfolio within a specific market condition. Portfolio management targets the risk-reward accord in allocation of investments directed towards numerous assets for maximizing returns or minimizing risks within a stipulated investment period. This article delineates the particle swarm optimization algorithm, followed by optimized portfolio asset distribution within a changeable market condition. The suggested way is consolidated for optimization of the Conditional Value-at-Risk (CVaR) measurement within divergent market conditions established on numerous targets and restraints. Results are compared to the values obtained by the optimization of Value-at-Risk (VaR) measurement of the portfolios under consideration.

Portfolio Management, Risk-return paradigm, Value-at-Risk, Conditional Value-at-risk, Particle Swarm Optimization

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[10] Dorigo M., Maniezzo V., and Colorni A., "Ant System: Optimization by a Colony of Cooperating Agents", IEEE Transactions on Systems, Man, and Cybernetics–Part B, Vol.26 (1), pp. 29–41, 1996.
[11] Clerc M., and Kennedy J., "The particle swarm-explosion, stability and convergence in a multi-dimensional complex space", IEEE Transactions on Evolutionary Computation, Vol.6 (1), pp. 58–73, 2002.
[12] Krusienski D.J., and Jenkins W.K., "Design and performance of adaptive systems based on structured stochastic optimization strategies", IEEE Circuits and Systems Magazine, Vol.5 (1), pp.8-20, 2005.
[13] Kennedy.J., and Eberhart.R.C., "Particle swarm optimization", Proceedings of the 1995 IEEE Neural Networks IV. Pisctway, NJ, pp.1942-8,1995.
[14] Ray J., and Bhattacharyya S., “Value-at-Risk Based Portfolio Allocation Using Particle Swarm Optimization”, International Journal of Computer Sciences and Engineering (E-ISSN: 2347-2693), vol. 3, special issue 1, pp. 1-9, 2015.
[15] Christopher C., "Time Series Forecasting", Chapman and Hall/CRC, pp.181-214, 2001.

J. Ray, S. Bhattacharyya , "Particle Swarm Optimization Technique for Optimizing Conditional Value-at-Risk Based Portfolio," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.77-85, 2017.

the historical periods of surveying have been accounted in literatures like Ardhasastra. Monotonously, whether North India or South India they speaks on hastha units to linear measurements. There were, however, especially in Tamilnadu indeed a specific measurements have had used to land survey those known by feet based. Opposite to this we have hastha oriented that is fore arm based scales used especially in structural field which were accounted in silpa and vastu sastras. Surveying land could be a usual one however surveying a whole country was obviously very rare and a prestigious one. Performing ashvameta yaga and surveying a country was considered as great royal proud then. Besides, rarely this was expressed in art by few Kings according to Tamilnadu. Such of these glorious achievements were celebrated in those days style with their prideful medium of art. The introduction of striding sculpture of Vishnu as a presiding deity specifically in Kanchipuram is the matter of interpretation to this effort. Therefore this research paper lenses a new unviewed a historical great event of the Pallavas and Cholas which was celebrated through religious art architecture seems ambiguous and double entendre.

Survey, Nandivarman Pallava, Kulothunga Chola I,Coding,Recoding, Striding Vishnu

[1] Kunwar Deo Prasad, “Taxation in Ancient India”, Mittal Publications, First Edition, 1987, ISBN: 81-7099-006-8, p 39.
[2] ASI, Measures in Ancient India, Ajanta Publications, Delhi, 1979, p 36.
[3] Ibid p 41.
[4] [4] Ibid p 41.
[5] Kunwar Deo Prasad, p 43.
[6] T.V. Sadhasiva Pandarathar, Pirkalach chozhar sarithiram (Tamil), Ramaiya Pathippagam, Chennai, First Edition, 2008, pp 147, 148.
[7] T.V. Sadhasiva Pandarathar, Pirkalach Chozhar Sarithiram (Tamil), Ramaiya Pathippagam, Chennai, First Edition, 2008, p 55.
[8] S.I.I. Vol, V. No. 990.
[9] S.I.I. Vol. VII, Ins. 132 of 1929 – 30.
[10] Ibid. Ins. 340 of 1917.
[11] Dr.S.A.V. Elanchezian, “Chronological – Sculptural - Structural - Distinctions of Three Perumal Temples”, International Journal of Innovative Research in Science, Engineering and Technology, Vol.5, Issue-7, pp.13912-13930, Jul 2016.
[12] T.N.Subramanian, (Special Editor), Pallava Copper Plates Thirty (Tamil), Tamil Historical Centre, Chennai, 1999, p 260.
[13] T.V. Mahalingam, Kanchipuram in Early South Indian History, Asia Publishing House, New York 1963, pp 139, 140.
[14] Tamilnadu varalarruk kuzhu, Tamizhnattu varalaru, First Vol, Tamilvalarchi Iyakkagam, Chennai, p 181
[15] Ibid, p 189.
[16] T. N. Subramanian, (Special Editor), Pallava Copper Plates Thirty, p 261.
[17] SA. Kirushnamurthy, Tholliyal nokil Kanchipura Mavattam, (Tamil), Meyyappan Pathippagam, Chidambaram, 2010, p 249.
[18] Thamizhnattu Varalarrukkuzhu, Thanizhnattu Varalaru, p 383.
[19] SA. Kirushnamurthy, Tholliyal nokil Kanchipura Mavattam, (Tamil), Meyyappan Pathippagam, Chidambaram, 2010, p 249.
[20] K.A.Nilakanta Sastri, A History of South India, Oxford University Press, Madras, Fourth Edition, 1976, p 187.
[21] K.A.Nilakanta Sastri, The Colas, University of Madras, Madras, 1955, p 285.
[22] [22] K.A.Nilakanta Sastri, The Colas, p 316.
[23] கலிங்கத்துப்பரணி, காண்டம் – 6, செய்யுள் எண் – 152 (நான்கு அடிகளைக்கொண்ட செய்யுளில் முதலாம் அடி).
[24] K.A. Nilakanta Sastri, A History of South India, p 192.
[25] Puliyur Kesigan, Sayangondar’s Kalingaththupparani, Pari nilaiyam, Chennai, 1965, verse no: 240, p 121.
[26] Suraj S. Gaikwad, Amar R. Buchade, “Survey on Securing Data using Homomorphic Encryption in Cloud Computing”, International Journal of Computer Sciences and Engineering, Vol.4, Issue-1, pp.17-21, Jan 2016.

S.A.V. Elanchezian, V.E.V. Rajaraja , "Ulagalantha Perumal Temple - The Chola’s Royal Code of a Historical Survey and Surveyors," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.86-94, 2017.

Due to the high growth of Internet and its applications over the network, there is a need of high level of security whilw doing the data to transfer between the networks. Steganography is a technique of hiding the data over the medium so that no one knows that there is any communication going on except the sender and receiver. This paper gives an approach for Image Steganography to improve the level of security for information exchange over the web. The 24-bit RGB image is picked as a cover picture which hides the encrypted secret message inside red, green and blue pixel values. The combination approach of DWT, Masking, Artificial Neural Network (ANN) and Genetic Algorithm (GA) has been implemented on cover image and text data that is to be hidden in cover image is encrypted with Elgamal and AES algorithm (hybrid approach). This technique gives a level of security to the mystery message which makes it troublesome for the gatecrashers to remove the concealed data. A Peak Signal-to-Noise Ratio, Mean Square Error and Decryption Time is calculated which measures the quality of images used. Larger PSNR and lower MSE value indicates lower distortion and hence a better quality of image.

Cover image, Stego image, PSNR, MSE, LSB insertion, DWT, Masking, ANN, GA, AES, Elgamal

[1]. Dagar E. and Dagar S. , “ LSB Based Image Steganography Using X-Box Mapping”, In the Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI) , India, pp. 351-355. 2014.
[2]. Mandeep Kaur Gill and Rupinder Kaur Randhawa , "Comparative Study of Multibit LSB Steganography with Cryptography", International Journal of Computer Sciences and Engineering, Vol.3, Issue-7, pp.120-123, Jul -2015.
[3]. Ross J. Anderson and Fabien A.P. Petitcolas, " On the Limits of Steganography”, IEEE Journal of Selected Areas in Communications, May 1998., Vol.16, No.4, pp. 474-481.
[4]. Vinod. L. B and Nithyanada. C. R, "Visual Cryptographic Authentication for Online Payment System", International Journal of Computer Sciences and Engineering, Vol.03, Issue-8, pp.109-114, Aug -2015
[5]. Nameer N. EL-Emam , “Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm”, World Academy of Science, Engineering and Technology, Vol.2, No.11, Nov 2008, pp. 566-577.
[6]. Imran Khan, “An Efficient Neural Network based Algorithm of Steganography for image”, International Journal of Computer Technology and Electronics Engineering (IJCTEE), Vol.1, No.2, pp. 63-67.
[7]. Atallah M., Shatnawi A., “A New Method in Image Steganography with Improved Image Quality”, Applied Mathematical Sciences, Vol.6, No.79, 2012, pp. 3907-3915 .
[8]. Saravanan V. and Neeraja A., “ Security Issues In Computer Networks And Steganography”, In the Proceedings of the 2013 Intelligent Systems and Control (ISCO), India, pp. 363-366, 2013.
[9]. Wu H. , Huang J. , “Secure Jpeg Steganography By Lsb+ Matching And Multi-Band Embedding” In the Proceedings of the 2011 International Conference on Image Processing (ICIP) , India, pp. 2737-2740, 2011.
[10]. Manoj gowtham. G.V, Senthur.T, Sivasankaran.M, Vikram.M, Bharatha Sreeja.G, “AES BASED STEGANOGRAPH” , International Journal of Application or Innovation in Engineering & Management (IJAIEM), Vol.2, No.1, January 2013.
[11]. Arvind Kumar , Km. Pooja, “Steganography-A Data Hiding Technique”, International Journal of Computer Applications, Vol.9, No.7, November 2010.
[12]. Ajit Singh, Swati Malik, “Securing Data by Using Cryptography with Steganography” International Journal of Advanced Research in Computer Science and Software Engineering , Vol.3, No.5, May 2013 .
[13]. Mohammad Ali Bani Younes and Aman Jantan, “A New Steganography Approach for Image Encryption Exchange by Using the Least Significant Bit Insertion” , IJCSNS International Journal of Computer Science and Network Security, Vol.8, No.6, June 2008.

Sakshi and A. Kaur , "Secure Data Hiding Using Neural Network and Genetic Algorithm in Image Steganography," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.95-99, 2017.

Water scarcity is becoming a grave problem in India due to monsoon effect and increasing population. More over the rainfall in the country is also unevenly distributed. As a result the regions receiving heavy precipitation are facing floods resulting in huge amount of water runs into the sea at the same time lack of rain fall regions are suffering with droughts and famines. To overcome the problems in the distribution of water, National Water Development Agency (NWDA) put a proposal of water transfer from surplus region to deficit regions. The total length of the present study is 483km. between Pennar (somasila) and Cauvery (Grand Anicut) and it consists of 10 km. buffer on both sides of the canal and it covers 17,215.68 sq. km. out of which area of 10,105.96 sq.km.is the proposed command area falling in Chittoor, Chengalpattu, North Arcott and South Arcott districts. The characteristics of the rocks, lineaments, drainage, settlements and land use/land cover are demarcated using IRS-P6, LISS-III data for better analysis. The study reveals that Current fallow land of 5340.14 km2 and 6307.98 km2 of cropland will be benefited for cultivation which is more than what NWDA estimated. The canal will provide water for irrigation and drinking to 4597 villages and 244 villages to be reclocated. 119 culverts and 24 aqueducts have to be constructed across the canal.

Land use/ Land cover, Remote Sensing, rehabilitation, Lineaments

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S.V.J.S.S. Rajesh, B.S.P. Rao, K. Niranjan, "Remote Sensing Study on Interlinking of rivers From Pennar to Cauvery," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.100-111, 2017.

In recent years, Brain Tumor has become one of the most common deadly diseases and MRI is commonly used to diagnose it. Automated recognition of brain tumors from MRI is a difficult task because of the variability of size, shape, and contrast of the tumor. On the other hand, it has a huge impact in helping the physicians by assessing the type, size, exact topological location and other related parameters of the tumor. Image segmentation techniques are often applied in identifying the tumor from the MRI images in addition to other techniques. There are numerous segmentation techniques available for this purpose such as: (i) Region based (ii) Edge based (iii) Threshold based. Here a threshold based approach has been designed and proposed to do the segmentation of edema, where the threshold is determined by MAXNET, a Self Organization Map (SOM) based artificial neural network.

Artificial Neural Network (ANN), Brain Tumor, Least centre distance method, Magnetic resonance imaging, MAXNET, segmentation, Self Organizing Map (SOM)

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[13] Sarkar, K, Ardhendu Mandal, and Rakesh Kumar Mandal, “Histogram Peak Normalization Based Threshold to Detect Brain Tumor from T1 Weighted MRI”, International Journal of Computer Sciences and Engineering. Vol. 4(1), pp. 16-24. 2016.
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K. Sarkar, R.K. Mandal, A. Mandal and S. Sarkar , "Least Centre Distance Based MAXNET Architecture to Obtain Threshold for Brain Tumor Edema Segmentation From FLAIR MRI," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.112-120, 2017.

Malignant Brain Tumor is one of the most lethal diseases on the Earth. Identifying such a tumor at an early stage is highly necessary in order to treat it properly. Medical imaging plays an important role to detect brain tumors. Although, MRI (Magnetic Resonance Imaging) is often considered to be the most suitable technique to diagnose such a tumor, it has its own limitations. On the other hand, PET (Positron Emission Tomography) has emerged as a more efficient technique to detect a brain tumor both in its pre and post treatment stages. The present work has been carried out with an objective to plan a strategy to identify brain tumors using Artificial Neural Network (ANN) and segmented PET images.

Malignant Brain Tumor, (Magnetic Resonance Imaging), PET (Positron Emission Tomography), Artificial Neural Network (ANN)

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D. Moitra, R. Mandal , "Review of Brain Tumor Detection using Pattern Recognition Techniques," International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.121-123, 2017.