Volume-5 , Issue-10 , Oct - 2017 Go Back

In recent times, the drivers and passengers of vehicles are not confined to only travelling in their vehicles. They are feeling the need for enhanced services on the go. As a result, the time has come when it is necessary to bring about improvements in the current Intelligent Transport System (ITS). Handoff in VANET is one of the common areas that require attention of researchers. During the Handoff process, it is necessary to ensure that the vehicle maintains continuous connection with the network. This will decrease the amount of packet loss thus ensuring Quality of Service (QoS). In this paper we have proposed a novel scheme; Cluster Based Vehicular Handoff (CBVH) for reducing load on a single backbone device using the concept of clustering. The scheme also reduces packet loss during handoff by proactively caching packets intended for the node that is participating in the handoff process.

VANET, Ad-hoc, Networking, Addressing, Cluster, Handoff, Vehicle

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[3] Pradeep Chouksey, "A Brief Introduction of MANET", International Journal of Scientific Research in Network Security and Communication, Vol.4, Issue.2, pp.15-18, 2016.
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[5] G.A. Khiratkar, S.S. Mahajan, "Performance Analysis of Cluster Based Routing Protocol for Ad hoc Networks", International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.141-143, 2014.
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[7] P. Roy, S. Midya, K. Majumder, “WiMAX Based Scanning Schemes in Vehicular Ad-Hoc Network: A Survey”, International Conference on Smart Trends for Information Technology and Computer Communications. Springer, Singapore, pp. 315-322, 2016.
[8] P. Roy, S. Midya, K. Majumder, “Handoff Schemes in Vehicular Ad-Hoc Network: A Comparative Study”, The International Symposium on Intelligent Systems Technologies and Applications, Springer International Publishing, pp. 421-432, 2016.
[9] A. Moravejosharieh, H. Modares, “A proxy MIPv6 handover scheme for vehicular ad-hoc networks”, Wireless personal communications,75(1), pp. 609-626, 2014.
[10] H. Lee, Y. U. Chung,Y. H. Choi, “A seamless Handover Scheme for IEEE WAVE Networks based on multi-way Proactive Caching”, Fifth International Conference on Ubiquitous and Future Networks (ICUFN), IEEE, pp. 356-361, 2013.
[11] L. Banda, M. Mzyece, G. Noel, “Fast handover management in IP-based vehicular networks”, IEEE International Conference on Industrial Technology (ICIT), IEEE, pp. 1279-1284, 2013.
[12] Ahmed, S. Hassan, S. H. Bouk, D. Kim, "Reducing scanning latency in WiMAX enabled VANETs”, Conference on Research in Adaptive and Convergent Systems.ACM, 2014.
[13] Z. Y. Rawashdeh, S. M. Mahmud, “A novel algorithm to form stable clusters in vehicular ad hoc networks on highways”, EURASIP Journal on Wireless Communications and Networking, Vol. 15, 2012.
[14] B. Ramakrishnan, R. S. Rajesh, R. S. Shaji, “CBVANET: A cluster based vehicular adhoc network model for simple highway communication”, International Journal of Advanced Networking and Applications, Vol. 2, Issue. 4, pp. 755-761, 2011.
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[18] P. Malhotra, A. Dureja, “A survey of weight-based clustering algorithms in MANET”, IOSR Journal of Computer Engineering (IOSR-JCE), Vol. 9, Issue. 6, pp. 34-40, 2013.
[19] M. Chatterjee, S. K. Das, D. Turgut, “WCA: A weighted clustering algorithm for mobile ad hoc networks”, Cluster computing, Vol. 5, Issue. 2, pp. 193-204, 2002.
[20] N. Kumar, J. H. Lee, “Peer-to-peer cooperative caching for data dissemination in urban vehicular communications”, IEEE Systems Journal, Vol. 8, Issue. 4, pp. 1136-1144, 2014.
[21] B. Mukunthan, B. Radha, S. Govindaraju, "Probabilistic B-Tree Based Clustering Algorithm for Vehicular Ad-Hoc Network with Data Aggregation", International Journal of Computer Sciences and Engineering, Vol.5, Issue.7, pp.82-87, 2017.
[22] J. Choi, H. Lee, “Supporting handover in an IEEE 802.11 p-based wireless access system”, Proceedings of the seventh ACM international workshop on VehiculArInterNETworking, pp. 75-80, 2011.
[23] Amol B.Suryawanshi, Baljit Kaur Saini, "Survey on Various Routing Protocols in Ad-hoc Networks", International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.174-178, 2017.
[24] S. Agarwal, B. L. Swami, “Road traffic noise, annoyance and community health survey-A case study for an Indian city”, Noise and health, Vol.13 Issie.53, pp.272, 2011.
[25] R. Miucic, Z. Popovic, S. M. Mahmud, “Experimental characterization of DSRC signal strength drops”, 12th International IEEE Conference on Intelligent Transportation Systems (ITSC), IEEE, pp. 1-5, 2009.
[26] A. Lipowski, D. Lipowska, “Roulette-wheel selection via stochastic acceptance”, Physica A: Statistical Mechanics and its Applications, Vol. 391, Issue.6, pp. 2193–6, 2012.
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P. Roy, P. Santra, D. Hazra, P. Mahata, "A Cluster-Based Vehicular Ad-hoc Network Handoff Scheme Inspired by Ant Colony Optimization," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.73-94, 2017.

In medical image processing, image denoising has become an essential requirement for correct diagnosis. This paper proposes a hybrid filter which employs Wavelet Packet Transforms and Wiener Filters for removal of noise in ultrasound images. Wavelet Packet Transforms is a generalization of the wavelet transforms that offers a rich set of decomposition structure. On the other hand, the Wiener filter tries to build an optimal estimate of the original image by enforcing a minimum mean-square error constraint between estimate and original image. In the first step, the multiplicative noise is modelled into an additive one followed by application of Discrete Wavelet Packet transforms. This is followed by application of Wiener Filter to the output obtained in the previous stage. The proposed algorithm is tested on different images and is found to produce better results in terms of the qualitative and quantitative measures of the image for both low and high values of noise variance in comparison to many existing techniques.

Speckle noise, Wavelet Packet Transforms, Noise variance, Wiener Filter, PSNR, Ultrasound

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Sandip Mehta, "Speckle Noise Reduction Using Hybrid Wavelet Packets-Wiener Filter," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.95-99, 2017.

This paper presents a new technique of segmentation and feature extraction for classification of melanoma and non-melanoma. Both segmentation and feature extraction is done by the concept of average value since average is the number closer to every number. Here we have also compared K-means segmentation technique with new the technique. In experimental part we evaluate 80.897% average accuracy through neural network classification.

Segmentation, Global + Local Segmentation, Center Starting Feature Extraction, K-means Segmentation, Feature Extraction

[1] S. Ramteke Nilkamal and V. Jain Shweta, “Analysis of Skin Cancer Using Fuzzy and Wavelet Technique-Review and Proposed New Algorithm”, International Journal of Engineering Trends and Technology, volume 4, issue 6, june 2013.
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A. Singh, R. Maurya, R. Yadav, V. Srivastava, "Innovative Technique of Segmentation and Feature Extraction for Melanoma Detection," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.100-104, 2017.

In the present era of modern concrete technology Ultra High Performance Fibre Reinforced Concrete (UHPFRC) is new cement based material. An inclusion of fibers shows to increases both mechanical and durability properties of UHPFRC. The aim of this study is to determine durability of UHPFRC containing fly ash and Metakaolin. Durability of UHPFRC after exposed to extreme temperature is evaluated. UHPFRC gives better fire resistance. The specimens were exposed to high temperature, specially 200ºC, 400ºC, and 600ºC for 1 hour. The fire resistance of specimen was classified on the basis of their compressive strength and weight loss. Strength loss was not significant at low temperature; up to 200ºC.Metakaolin shows the better performance as compared with fly ash. SEM analysis was also carried out to study effect of extreme temperature on microstructure of UHPFRC.

Compressive strength, Fly ash, Metakaolin, Steel fibres, UHPFRC, SEM

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A.P. Shelorkar, V.R. Chaudhary, P.D. Jadhao, "Evaluation of Durability of Ultra High Performance Fibre Reinforced Concrete (UHPFRC) Through Extreme Temperature," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.105-109, 2017.

In this article the implementation of the functions for identification of duplicate chunks based on block, file and content approach have been discussed. The main core of the Deduplication algorithms is chunking and hashing functions. It is also referred as Deduplication granularity. The analysis of these three methods show that the content approach for deduplication is bit slow but the accuracy is good as compared to file and block strategies. It can be seen that the content method of identifying duplicate chunks is about 0.2-0.3% slower but its accuracy is higher by 1-2 % when duplicate finding method of block and file are considered. This work is useful for building duplicate content –aware applications. Especially, when it is used for checking multiple patterns, matching paraphrased content and plagiarism. The proposed methods here can be used for inline as well in the post processing type of Deduplication and it can be extended to include the concept of background and foreground processing.

Data Deduplication, Duplicate Chunks, Hashing, Execution Time, Polynomial Chunking

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Gagandeep Kaur, Mandeep Singh Devgan, "Identification of Duplicate Chunks Using Content Approach," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.110-117, 2017.

Quality assurance is a way of preventing errors and avoiding problems when distributing software to clients. The term quality assurance is refers to ways of ensuring the quality of a product. Here we detect the brain tumor detection with segmentation using genetic algorithm and testing that application output by ANN. Brain is the central nervous system of a human being one of the major causes of death among people is brain tumor. In medical field like this kind of causes are struggling to detect automatically with quality. Here provided solution to detect the tumor automatically the same way testing the automated output by ANN for improving the quality of software. Proposed method integrates image pre-processing, future extraction, segmentation, classification and testing.

Quality assurance,Artificial Nural Networks,Pre-processing,Segmantation,Feture extraction,Classification,testing

[1] Parveen and Amritpal singh, "detection of brain tumor in MRI images using combination of fuzzy C-Means and SVM," 2015 2nd International Conference on Signal Processing and Integrated Networks,978-1-4799-5991-4/15/$31.00©2015 IEEE.
[2] Anupurba Nandi, "detection of human brain tumor in MRI image segmentation and morphological operators," 2015 IEEE International Conference on Computer Graphics, Vision and Information Security,978-1-4673-7437-8/15/$31.00©2015 IEEE.
[3] Kalpana U. Rathod and Y. D. Kapse, “MATLAB Based Brain Tumour Extraction Using Artificial Neural Network," International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 4 Issue: 3, IJRITCC | March 2016.
[4] Shweta Jain, “Brain cancer classification using GLCM based feature extraction in artificial neural network,” International Research Journal of Mathematics, Engineering and IT (IRJMEIT) ISSN: (2349-0322) Vol. 3, Issue 7, July 2016.
[5] J. Mohana Sundaram and Dr. T. Karthikeyan, “general study on MRI scan for brain tumor using artificial neural network,”International Research Journal of Mathematics,Engineering and IT,ISSN:2349-0322 Vol.3,Issue 7,July 2016 © Associated Asia Research Foundation.
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[7] 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.

V. Praba, S. Sivakumar, "To Achieve Software Quality Assurance in Brain Tumor Detection Using Artificial Neural Networks," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.118-121, 2017.

In today’s mobile communication world, desired as well as interfering signals are mobile. Therefore, a fast tracking system is needed to constantly estimate the directions of those users and then adapt the radiation pattern of the antenna to direct multiple beams to desired users and nulls to sources of interference so that desired users get better quality signal with high SNR and to achieve this Artificial Neural Networks come to rescue to precisely predict which antenna element and the number of antenna elements in circular array to be activated to form better combined radiation pattern to be directed to user.

Circular Array, Neural Network, SNR

[1] Mohamed A. Suliman, Ayed M. Alrashdi, Tarig Ballal, and Tareq Y. Al-Naffouri, “SNR Estimation in Linear Systems with Gaussian Matrices”, Issue 99, DOI 10.1109/LSP.2017.2757398, IEEE Signal Processing Letters
[2] A.H.EL Zooghby, C. G. Christodoulou, and M. Georgiopoulos, “Neural network-based adaptive beamforming for one- and two-dimensional antenna arrays”, IEEE Transactions on Antennas and Propagation, Year: 1998, Vol. 46, Issue. 12, pp. 1891 – 1893, 1998.
[3] R.W. P King, “Super gain antennas and the Yagi and circular array”, IEEE Transaction, Antennas and Propagation, vol. 37, No 2, pp. 178-186, 1989.
[4] Ashraf Sharaqa, Nihad Dib, “Design of linear and circular antenna arrays using biogeography based optimization”, IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), pp. 1-6, 2011.
[5] D. Mandal, S. K. Ghoshal, S. Das, S. Bhattacharjee, and A. K. Bhattacharjee, “ Improvement of Radiation Pattern for Linear Antenna Arrays Using Genetic Algorithm”, 2010 International Conference on Recent Trends in Information, Telecommunication and Computing, IEEE, pp. 126-129, 2010.
[6] S. H. Zainud-Deen; H. A. Malhat; K. H. Awadalla; E. S. El-Hadad, “Direction of arrival and state of polarization estimation using Radial Basis Function Neural Network (RBFNN)”, National Radio Science Conference, pp. 1-8, 2008.
[7] C A Balanis, “Antenna Theory and Design” John Wiley & Sons, New York, pp. 321-330, 1997.
[8] S Haykin, “Neural Networks: A Comprehensive Foundation” 2nd edition, Prentice Hall, 1999.
[9] N.V. Saiteja Reddy and T. Srikanth, “Class Label Prediction using Back Propagation Algorithm: A comparative study with and without Thresholds (Bias)”, International Journal of Computer Sciences and Engineering, Vol. 3, Issue. 7, pp.65-70, 2015.

Kavita Devi, Rajneesh Talwar, "A Neural Adaptive Circular Array for Enhancing SNR and Reducing Interference," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.122-127, 2017.

Unstructured product reviews are difficult to analyse. By applying feature-based opinion mining on product reviews, we can analyse product reviews. In Feature Based Opinion Mining, method of extracting features plays very important role. Performance of feature based opinion mining is depends on how features are extracted from product reviews. In this paper, we discussed how Latent Dirichlet Allocation topic model can be used for product features extraction. We discussed a methodology to extract product features using Latent Dirichlet Allocation topic model. We applied basic Latent Dirichlet Allocation (LDA) topic model on 24259 product reviews of 7 product categories to extract product features. We inferred the model using Gibbs Sampler. The result shows that LDA model extracts product reviews efficiently.

Feature-Based Opinion Mining, Aspect-Based Sentiment Analysis, Topic Models, Latent Dirichlet Allocation

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[3] Liu, Bing, Minqing Hu, and Junsheng Cheng. "Opinion observer: analyzing and comparing opinions on the web." In Proceedings of the 14th international conference on World Wide Web, pp. 342-351. ACM, 2005.
[4] Baccianella, Stefano, Andrea Esuli, and Fabrizio Sebastiani. "Multi-facet Rating of Product Reviews." In ECIR, vol. 9, pp. 461-472. 2009.
[5] Jiang, Peng, Chunxia Zhang, Hongping Fu, Zhendong Niu, and Qing Yang. "An approach based on tree kernels for opinion mining of online product reviews." In Data Mining (ICDM), 2010 IEEE 10th International Conference on, pp. 256-265. IEEE, 2010
[6] Titov, Ivan, and Ryan McDonald. "Modeling online reviews with multi-grain topic models." In Proceedings of the 17th international conference on World Wide Web, pp. 111-120. ACM, 2008.
[7] Brody, Samuel, and Noemie Elhadad. "An unsupervised aspect-sentiment model for online reviews." In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 804-812. Association for Computational Linguistics, 2010.
[8] Jo, Yohan, and Alice H. Oh. "Aspect and sentiment unification model for online review analysis." In Proceedings of the fourth ACM international conference on Web search and data mining, pp. 815-824. ACM, 2011.
[9] Tan, Shulong, Yang Li, Huan Sun, Ziyu Guan, Xifeng Yan, Jiajun Bu, Chun Chen, and Xiaofei He. "Interpreting the public sentiment variations on twitter." IEEE transactions on knowledge and data engineering 26, no. 5 (2014): 1158-1170. 2014.
[10] Blei, David M., Andrew Y. Ng, and Michael I. Jordan. "Latent dirichlet allocation." Journal of machine Learning research 3, no. Jan (2003): 993-1022.2003

Padmapani P. Tribhuvan, Sunil G. Bhirud, Ratnadeep R.Deshmukh, "Product Features Extraction for Feature Based Opinion Mining using Latent Dirichlet Allocation," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.128-131, 2017.

Cloud computing has transformed into a well-known in area of high performance, cloud computing as it offers on-request access to shared pool of resources over web in a self-service, dynamically scalable. One of the important research issues which need to be focused for its efficient performance on task scheduling which plays the key role for increase the efficiency of whole cloud computing facilities. implies that to assign best suitable resources for the requested task to be execute with the various parameters like time, cost, scalability, makespan, reliability, resource utilization, accessibility, throughput etc. In this paper, we give survey and relative studies of a few task scheduling using metaheuristic algorithms for cloud computing.

Cloud Computing, Task Scheduling, Meta-heuristic, hyper heuristic, PSO, GA, ACO.

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[31] R. Raju, R.G. Babukarthik, D. Chandramohan, P. Dhavachelvan, T. Vengattaraman, “Minimizing the Makespan using Hybrid Algorithm for Cloud Computing”, 3rd International Advance Computing Conference (IACC) IEEE, Feb 2013.
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A. Jain, A. Upadhyay, "Cloud Scheduling using Meta Heuristic Algorithms," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.132-139, 2017.

Poom Kuman, [Poom Kuman , Nguyen van Dung, A generalization of Ciric Fixed Point theorems, Filomat 29:7 (2015), 1549-1556] has established the generalized version of the result by Ciric [ L. B. Ciric, A generalization of Banach’s contraction principle, Proc. Amer. Math. Soc. 45 (1974) 267-273.]. By considering the most general form of quasi-contraction viz. n-quasi contraction, the authors have established the existence of unique fixed point in T- orbitally complete spaces in this paper.

Fixed Point, n-quasi contraction, T-Orbitally Complete space

[1] L. B. Ciric, “A generalization of Banach’s contraction principle”, Proceedings of the American Mathematical Society, Vol. 45, Issue. 2, pp. 267-273, 1974.
[2] V. Berinde, “General constructive fixed point theorems for Ciri´c-type almost contractions in metric spaces”, Carpathian Journal of Mathematics, Vol. 24, Issue. 2, pp. 10 – 19, 2008.
[3] V. Lakshmikantham and L. Ciri ´ c,”Coupled fixed point theorems for nonlinear contractions in partially ordered metric spaces”, Nonlinear Analysis, Vol. 70, Issue. 12, pp. 4341 – 4349, 2009.
[4] Poom Kuman, “Nguyen van Dung, A generalization of Ciric Fixed Point theorems”, Filomat Vol. 29, Issue. 7, pp. 1549-1556, 2015.
[5] L. B. Ciric, “Non-self mappings satisfying non-linear contractive condition with applications”, Nonlinear Analysis, Vol. 71, Issue. 7, pp. 2927 – 2935, 2009.

P.L. Powar, G.R.K. Sahu, Akhilesh Pathak, "Ciric Fixed Point Theorems in T- Orbitally Complete Spaces with n-quasi contraction," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.140-143, 2017.