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• Open Access   Article

  Faulty Link Detection in Cluster based Energy Efficient Wireless Sensor Networks

  Manju Bhardwaj

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.1-8, Jun-2017

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  Advancement in electronics and WSNs has enabled the improvement of lower cost and lower power, high transmission. Also in large scale wireless networks, dynamic monitoring of system degradation and detection of bad links proves very difficult. One of the most important challenges in WSN is to design faulty link detection in cluster based energy efficient wireless sensor network to increase the network efficiency, reliability and lifetime. Hot spot in WSNs leads the location having heavy traffic load. Sensor nodes in heavy traffic area drain there energy very quickly, leading in failure link detection of network services and affect WSNs performance including transmitting and receiving of information. Cluster based routing algorithms is utilized to perform energy-efficient routing in WSN and link detection sequentially checks all potential links incurs high transmission. In cluster based routing algorithm, cluster head (CH) represents all nodes in the cluster and data is collected from them. To balance the traffic load and the energy consumption in the network, the size of the cluster should be carefully determined and the rotation of CH among all nodes within the cluster in the network. In this paper, we propose faulty link detection in cluster based energy efficient wireless sensor network algorithm. In WSNs maximum energy is consumed for transmission and reception and energy is non-linear function (exponential) of transmission range. So, in faulty link detection in cluster based energy efficient wireless sensor network election of CH and faulty link detection is based onto the residual energy and optimal CH distance of every node. In addition, Link fails arises in the network if the energy of sensor node falls below threshold value is considered and next shortest routing path is used for transmission for increasing the network lifetime and reliability. Furthermore, the energy consumption of being a CH is equally spread among the cluster members. Performance results show faulty link detection in energy efficient cluster based wireless sensor network scheme reduces the end to end energy consumption, prolong the network lifetime and increase reliability of multi hop network compared to the well-known clustering algorithms LEACH.

  Key-Words / Index Term
  Clustering, Energy efficiency Network lifetime, Fault link, Routing, and Wireless Sensor Networks

  References
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  Manju Bhardwaj, "Faulty Link Detection in Cluster based Energy Efficient Wireless Sensor Networks," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.1-8, 2017

• Open Access   Article

  Classification of a Retinal Disease based on Different Supervised Learning Techniques

  Amey Samant, Sushma Kadge

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.9-13, Jun-2017

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  This paper is based on classification of a retinal disease observed in premature infants named as “Retinopathy of Prematurity” (ROP). According to current market survey very few hospitals are associated in dealing with this disorder and is costly. So, the main aim here is to provide a simple yet effective MATLAB based algorithm for detection and classification of this disease. Here for computational purpose authors have used 30 affected and 30 normal images. These images are pre-processed using various MATLAB functions and commands and blood vessels are extracted. Later the tortuosity of these vessels is estimated and stored. These signals are further given to supervised learning classifiers, accuracy and error rate of the algorithm is estimated using different kernels.

  Key-Words / Index Term
  Premature, infants, Retinopathy of Prematurity, Supervised Learning, Tortuosity

  References
  [1]. S. Prabakar, K. Porkumaran, Parag K. Shah, V. Narendran, “Optimized Imaging Techniques to Detect and Screen the Stages of Retinopathy of Prematurity”, Human-Centric Machine Vision, India, pp.-12-19, 2012.
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  Citation
  Amey Samant, Sushma Kadge, "Classification of a Retinal Disease based on Different Supervised Learning Techniques," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.9-13, 2017

• Open Access   Article

  Diagnosis of Parkinson’s Disease using Acoustic Analysis of Voice

  Chaitanya Gupte, Shruti Gadewar

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.14-18, Jun-2017

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  Acoustic analysis of voice is one of the cost effective method for detecting Parkinson disease. It is also a noninvasive, reliable and easy to use method. Also voice deviation from normal one is the earliest indicator of Parkinson. Voice data of sustained phonation has been collected from 8 healthy and 23 Parkinson subjects. The voice database is analyzed using PRAAT Software and 26 acoustic features are extracted. Some of the features being Jitters, Shimmers, Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR), Autocorrelation (AC). The values of these parameters show variation among two groups. A row vector is prepared using these parameters and fed to the classifiers. Classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), k-nearest neighbors (kNN), Adaboost, Decision trees and Random Forest have been tested and it was found that SVM is the best which gives the accuracy of 90%. Performances of classifiers are evaluated in terms of accuracy, precision, recall and total execution time.

  Key-Words / Index Term
  Parkinson’s disease, PRAAT, Acoustic features, Support Vector Machine, Neural Networks

  References
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  Citation
  Chaitanya Gupte, Shruti Gadewar, "Diagnosis of Parkinson’s Disease using Acoustic Analysis of Voice," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.14-18, 2017

• Open Access   Article

  A Study on Web Based Image Search by Re-Ranking Techniques

  John Bosco.P., S.K.V. Jayakumar

  Survey Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.19-26, Jun-2017

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  the continuing growth of online digital photos, video data and image retrieval an active research area. The ever-growing importance of rich visual information in today’s web is evidenced by the popularity of social web image retrieval. I focus primarily on the process of searching and retrieving images using a visual query known as content-based image retrieval our primary aiming is reducing the semantic gap between the low-level visual features and high-level image features. This paper proposed for comprehensive survey In this paper is to focus on the survey of various existing methods and technologies and application along with has been discussed some new clustering techniques, distance metrics methods, also of these various re-ranking methods also addressed.Finally,we have been details discussed ten journals paper.

  Key-Words / Index Term
  Re-Ranking, Distance Metrics (DM), TBIR

  References
  [1] Lixin Duan,Wen Li, Ivor Wai-Hung Tsang,Dong Xu, “Improving Web Image Search by Bag-Based Re-Ranking”, In: IEEE Trans.Syst., Vol. 20, No.11,pp.3280-3290, 2011.
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  [7] Xiang-Yang Wang, Lin-lin Liang, Wei-Yi Li, Dong-Ming Li, Hong-Ying Yang, “A new SVM based relevance feedback image retrieval using probabilistic feature and weighted kernel function”, Journal of Visual Communication and Image Representation, Vol.38, Issue.7, pp.256-275, 2016.
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  Citation
  John Bosco.P., S.K.V. Jayakumar, "A Study on Web Based Image Search by Re-Ranking Techniques," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.19-26, 2017

• Open Access   Article

  An Improved Approch For Fraud Detection In Health Insurance Using Data Mining Techniques

  Namrata Ghuse, Pranali Pawar, Amol Potgantwar

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.27-33, Jun-2017

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  Abstract
  Nowadays there is huge amount of data stored in real world databases and this amount continues to grow fast. The major use of anomaly or outlier detection is fraud detection. Health care fraud leads to substantial losses of money each year in many countries. Effective fraud detection is important for reducing the cost of Health care system. Fraud and abuse on medical claims became a major concern for health insurance companies last decades. Fraud involves intentional deception or misrepresentation intended to result in an unauthorized benefit. It is shocking because the incidence of health insurance fraud keeps increasing every year. Data mining which is divided into two learning techniques viz., supervised and unsupervised is employed to detect fraudulent claims. Basically random forest algorithm and logistics regression algorithm techniques are used for fraud detection in health insurance. Data mining automatically filtering through immense amounts of data to find known/unknown patterns bring out valuable new perceptions and make predictions.

  Key-Words / Index Term
  Data Mining; Random Forest Algorithm; Health Insurance Fraud; Supervised; Unsupervised; Clustering; Logistics Regression Algorithm

  References
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  Citation
  Namrata Ghuse, Pranali Pawar, Amol Potgantwar, "An Improved Approch For Fraud Detection In Health Insurance Using Data Mining Techniques," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.27-33, 2017

• Open Access   Article

  Efficient Image Processing Based Liver Cancer Detection Method

  Namrata Ghuse, Yogita Deore, Amol Potgantwar

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.33-38, Jun-2017

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  Abstract
  Cancer treatment has a great significance due to the prevalent episodes of the diseases, very high death rate and reappearance after treatment. In the large world scale, cancer stands in the fifth position which causes death. Among the various cancers, liver cancer stands in the third position. Liver cancer is generally diagnosed by three different test like blood test, image test and biopsy. To make the different task of detecting the liver cancer simpler, less time consuming, an effective and efficient approach is adopted for the same. In this research an Image processing system for detecting liver cancer is put forward. The proposed detection methodology makes use of MRI and CT. Region growing technique is adopted so as to segment the images in order to capture the region of interest. Later, wavelet transform is considered to compute the threshold values for the region of interest. After processing and measuring it gives the correct result with in the efficient time period.

  Key-Words / Index Term
  Image; Region Growing; CT Image; Image processing; Segmentation

  References
  [1] Nelofar Kureshi, Syed Sibte Raza Abidi, “A Predictive Model for Personalized Therapeutic Interventions in Non-small Cell Lung Cancer”, IEEE Journal of Health Informatics Vol. 20, No.1, pp. 424-431, 2016.
  [2] PR Anisha, CKK Reddy, LVN Prasad, "A pragmatic approach for detecting liver cancer using image processing and data mining techniques", International Conference on Signal Processing And Communication Engineering Systems (SPACES), India, pp.1-6, 2015.
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  Citation
  Namrata Ghuse, Yogita Deore, Amol Potgantwar, "Efficient Image Processing Based Liver Cancer Detection Method," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.33-38, 2017

• Open Access   Article

  Big Data Analysis Using Distributed Approach on Weather Forecasting Data

  Amit Palve, Ajit Patil, Amol Potgantwar

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.39-43, Jun-2017

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  Abstract
  Data than it seems at first, and extracting the useful information in an efficient manner leads a system toward a major computational challenges, such as to analyze, aggregate, and store, where data are remotely collected. Keeping in view the above mentioned factors, there is a need for designing a system architecture that welcomes both real-time, as well as offline data processing. Big data is data whose characteristics force us to look beyond the traditional methods that are prevalent at the time. Online news, micro-blogs, search queries are just a few examples of these continuous streams of user activities. Evolving data streams methods are becoming a low-cost, green methodology for real time online prediction and analysis. Heterogeneity, scale, timeliness, complexity, and privacy problems with Big Data impede progress at all phases of the pipeline that can create value from data. The problems start right away during data acquisition, when the data tsunami requires us to make decisions, currently in an ad hoc manner, about what data to keep and what to discard, and how to store what we keep reliably with the right metadata.

  Key-Words / Index Term
  Big data, ETL, Data processing unit, RSDU, DADU, real-time

  References
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  Citation
  Amit Palve, Ajit Patil, Amol Potgantwar, "Big Data Analysis Using Distributed Approach on Weather Forecasting Data," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.39-43, 2017

• Open Access   Article

  Performance Analysis of Self Adaptive Image Encryption Technique

  Rashmi P., Bharathi R.K., Shruthi Prabhakar, Reshma Banu, Rachana C.R.

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.44-58, Jun-2017

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  Abstract
  This paper presents an efficient Self Adaptive Image Encryption Technique based on multiple chaotic maps. An efficient and fast encryption algorithm is designed with the help of traditional methods of permutation-diffusion and double simple 2D chaotic systems. Existing methods which are found in secure upon chosen-plain text or known-plain text attack in the process of permutation or diffusion. The key streams are dependent on the plain-image. Consequently, different plain-images will have different key streams in both processes. This design can solve the problem of fixed chaotic sequence produced by the same initial conditions but for different images. The mathematical experiments and performance analysis demonstrate that the proposed algorithm is large enough to resist the brute-force attack and has excellent encryption performance.

  Key-Words / Index Term
  Image Encryption, chaotic map, Permutation, Diffusion

  References
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  Citation
  Rashmi P., Bharathi R.K., Shruthi Prabhakar, Reshma Banu, Rachana C.R., "Performance Analysis of Self Adaptive Image Encryption Technique," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.44-58, 2017

• Open Access   Article

  Braid Group Based Nominative Proxy Signature Scheme

  Vandani Verma

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.57-60, Jun-2017

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  Abstract
  Braid groups are highly non-commutative groups, they can be found in our daily life in jewellery, in hair braid and in many more. Nominative proxy signatures is a special type of proxy signatures in which the original signer delegates his signing rights to proxy signer and proxy signer on behalf of the original signer generates the signatures intended for nominee in such a way that only the nominee can verify the signatures and if required he is the only one to prove the validity of the signatures to third party. These signatures are different from designated verifier signatures as the validity of the signatures can be proved to third party when asked. In this paper, we combine the two concepts nominative proxy and braid groups and present the maiden nominative proxy signatures based on braid groups. We also analyse the security aspects of the proposed scheme and showed that the conjugacy decomposition problem, conjugacy search problem and base problem 1 in braids are not solvable for the proposed scheme.

  Key-Words / Index Term
  nominative proxy signatures, braid group, conjugacy search problem

  References
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  [4]. I.A. Ismail, S.F. El-Zoghdy, A.A. Abdo, “A Secure Nominative Proxy Signature Scheme for Distributed Shared Object Systems”, International Journal of Advanced Networking and applications, vol.2, Issue.1, pp.411-418, 2010.
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  [9]. Zuo-Wen Tan, Tan Liu, Zhuo-Jun Liu, “Nominative proxy signature schemes”, Cryptography eprint Archive Report, US, pp.1-128, 2004.
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  Citation
  Vandani Verma , "Braid Group Based Nominative Proxy Signature Scheme," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.57-60, 2017

• Open Access   Article

  Optimizes NP Problem with Integration of GPU Based Parallel Computing

  Santosh Kumar, S.S. Dhable, Amol D. Potgantwar

  Research Paper | Journal (IJSRNSC)

  Vol.5 , Issue.3 , pp.61-67, Jun-2017

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  Abstract
  There are different number of optimization problems are present those are NP problems. Graph theories are most commonly studied combinational problems. An NP-hard problem takes exponential time for computation to get best solution. Heuristics algorithms provides great alternative to tackle NP hard problems with optimized solution in a limited time. GPU architecture boosts computation of heuristics algorithms with single program multiple data approach. By applying solution level parallelism to traveling salesman problem with global and shared memory level optimizations. Inside this paper given that the innovative move towards to resolve these combinational troubles through GPU based parallel computing via CUDA architecture. Evaluating those problem with significant to the transfer rate, effectual memory utilization and speedup etc. to attain the supreme achievable solution. The algorithm for the optimization problem is in consideration is 2-opt algorithm which is used to grasp the capable memory management, coordinated completing, saving time and growing speedup of execution. The experimental results are compared with the performance of different number of datasets with the execution time as well as the parameter values such as size of blocks. So that the speedup factor is develop in addition to search out the paramount most favorable solution.

  Key-Words / Index Term
  Graph Theory, CUDA, GPU, Parallel metaheuristic

  References
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  Citation
  Santosh Kumar, S.S. Dhable, Amol D. Potgantwar, "Optimizes NP Problem with Integration of GPU Based Parallel Computing," International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.61-67, 2017