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ijmcs  IJMCS

Volume-5 & Issue-4 Published (Acceptance Ratio=47.36%)http://www.ijmcs.info/current_issue

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Submit your Paper Last date 20th June 2017 http://www.ijmcs.info/submit_your_paper

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Submit your Paper Last date 10th October 2015 http://www.ijmcs.info/submit_your_paper

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Volume-2 & Issue-4 Published (Acceptance Ratio=25%) http://www.ijmcs.info/current_issue

ijmcs  IJMCS

National Conference on (Advances in Modern Computing and Application Trends) Organised By Acharya Institute of Technology Bangalore, India

  • For More Detail Click Here
  • http://www.acharya.ac.in/Techman_2014.pdf

    Volume-2 Issue-3 (June 2014)
    Title: A Nobel Based Approach for Resource Management in Cloud Computing using Prediction Based ELB 
    Authors: Mr.Prassanna Kumar and Vandana.V
    Abstract: Load balancing is the core of virtual resource management and scheduling in cloud computing. For network applications, the cost of user would be greatly saved if load balancer could dynamically adjust cluster resources in accordance with the current applied load. The current load balancing products of cloud, such as Amazon’s ELB, can be used to manage virtual machines in the cloud. The main drawbacks are still only supporting template-based deployment of new virtual machines, not supporting the trend prediction, failing to gain resources dynamically, and not sufficiently providing the elastic management of resources. Since the virtual machine for load balancing management in cloud computing can be dynamically applied and released. A Nobel Based Approach using an algorithm of prediction-based elastic load balancing resource management (TeraScaler ELB) is presented to overcome the drawbacks. Experiments have shown that the required number of virtual machines change in compliance with the change of network load, thus TeraScaler ELB is able to dynamically adjust the processing capacity of back-end server cluster with the applied load. Besides it could make full use of the ‘use on demand’ feature of cloud computing, this approach leads to a better application of prediction based load balancing in cloud computing. It concludes that compared with the traditional elastic resource management algorithm, this approach is more reasonable for providing scalability and high availability.
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    Title: Brain Tumor Classification using Probabilistic Neural Network 
    Authors: C. Jothi Lakshmi and S.Princy Suganthi Bai
    Abstract: Magnetic Resonance images brain tumor classification is a difficult task due to the complexity and variance of tumors. The proposed approach to automated classification of brain tumor. This proposed work consists of various stages are (1) Preprocessing, anisotropic filter, (2) ROI segmentation, (3) Feature extraction, (4) feature reduction and classification. In the pre-processing step anisotropic filters applied for noise reduction. To improve the feature extraction using Region of interest of the area will be selected. Texture features can be extracted using Discrete Wavelet Transform and Law’s Energy Texture features. The process of feature reduction performed by Principal Component Analysis. At the last stage, the Probabilistic Neural Network classifier used to perform the classification. The performance of the PNN classifier was evaluated in terms of training performance and classification accuracies. Probabilistic Neural Network gives fast and accurate classification and is a promising tool for classification of the tumor.
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    Title: Routing Protocol in MANET: A Survey 
    Authors: Dr R.C.Poonia, Vijay Prakash Sharma and Priyanka Goyal
    Abstract:After 1990 research region of mobile ad-hoc networking has improved. This infrastructure less network provides a range of new functionality to provide very efficient end to end communication .It offer efficient communication in different areas like military application .It works accurately if some disaster condition arises in the network. The majority interesting vicinity in MANET is routing .It is very composite and wide part of research .We have a variety of protocol in mobile ad-hoc network worn in routing and various dispute of author on that protocol so it is complicated to find out which protocol is best .In this paper we current a small overview of routing protocol.
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    Title: Live Streaming With Receiver-Based Scalable Video over WIMAX networks 
    Authors: D.Stanely and S.Mahalakshmi
    Abstract:There are commercial peer-to-peer (p2p) systems for live video streaming which are introduced in recent years. The working nature of the systems is measured in the various measurement papers. Such studies are useful to compare the working nature of the different systems. Here we describes the network architecture of Zattoo one of the largest production live streaming providers in Europe. Zattoo system was heavenly loaded with as high 20,000 concurrent users on the single overlay, the remained joining delay was about2-5seconds. By using p2p network structure there may lead with the difficulty of selecting the optimal sub streams of scalable video streams under bandwidth constraints. By solving this problems we can able to transmit higher quality of vide or more number of videos at the same time. Broadcasting multiple scalable video streaming real times is the challenging one. The difficulty within this is further increased with the receiver size limitation which introduces the buffer overflow possibilities.
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    Title: A Better Performed Algorithm for Mining Frequent Itemsets 
    Authors: R. Prabamanieswari and P. Priya
    Abstract:Frequent itemset mining plays an important role in Market Basket Analysis. Apriori is the well-known algorithm for finding frequent itemsets. It uses hash-tree function for pruning candidate itemsets and finding frequent itemsets. Different variations of Apriori use different candidate pruning techniques such as prefix-trees, array list and their combination. But, all these techniques use complex data structures and they consume more memory. This paper focuses the simplest data structure array list, for pruning the unwanted candidate itemsets and for finding frequent itemsets. It finds the size of the frequent itemsets (Lk-1) list and infrequent itemsets (NLk-1) list and selects the smaller size list for checking the subsets of the candidate itemsets to find the frequent itemsets. It also compares the proposed approach with the Apriori. Finally, it concludes the proposed approach is better than Apriori.
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    Title: Evaluation of Similarity Measure for Text Processing & Cosine Similarity Measure for Text Processing 
    Authors: Ms. Rashmi. Harapanahalli and Mr. Rajshekhar S A
    Abstract:Text processing plays an important role in information retrieval, data mining, and web search. A document is usually represented as a vector in which each component indicates the value of the corresponding feature in the document. The feature value can be term frequency, relative term frequency. The high-dimensionality and scarcity of the document can be a severe challenge for similarity measure which is an important operation in text processing algorithms. To compute the similarity between two documents with respect to a feature, the used measures take the following three cases into account: a) The feature appears in both documents, b) the feature appears in only one document, and c) the feature appears in none of the documents.
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    Title: Performance of Enhanced Pre-emptive Dynamic Source Routing in RPGM model  
    Authors: Anusofiya.R, Fenila Janet.M, Gayathri.M and Edna Elizabeth.N
    Abstract:Dynamic Source Routing (DSR) is the most commonly used routing protocol in Mobile Adhoc Networks (MANET). But due to the delay in the route discovery mechanism, packet drop in DSR is high. Pre-emptive DSR (PDSR) detects link failure before the actual failure of link and uses a backup route immediately. Hence packet delivery ratio in PDSR is better than DSR. In this paper, we propose a modification to the existing PDSR such that the path is selected using the nodes near the destination which have the highest Received Signal Strength (RSS). We implement the enhanced PDSR in Reference Point Group Mobility (RPGM) model which creates the mobility scenario in a battlefield. The simulation results show that the enhanced PDSR has better performance compared to PDSR in terms of packet delivery ratio, normalized routing load and end to end delay.
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    Title: Analysis of Adult-Onset Diabetes Using Data Mining Classification Algorithms  
    Authors: Sathees Kumar B and Gayathri P
    Abstract:Diabetes Mellitus is one of the most serious health challenges in both developing and developed countries. In the medical field a predictive data mining is used to diagnose the disease at the earlier stage which helps the physicians in the treatment planning procedure. In today’s world people get affected by many diseases where the development of one may leads to various other complications. One among them is Adult-Onset Diabetes (Type II diabetes) which is the global health problem. In this paper several data mining approaches are used to help the physicians to detect the disease at the earlier stage which helps to reduce the probability of getting the type II diabetes.
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    Title: Soil Field Analysis Using Textural Properties   
    Authors: S. Malathi and N. Antony Sophia
    Abstract:Soil texture and soil structure are both unique properties of the soil that will have a profound effect on the behavior of soils, such as water holding capacity, nutrient retention and supply, drainage, and nutrient leaching. Soil texture has an important role in nutrient management because it influences nutrient retention. For instance, finer textured soils tend to have greater ability to store soil nutrients. Soil texture is the relative proportions of sand, silt, or clay in a soil. Our proposed method is to extract the textural features by using GLCM from soil image and the features are fed into the Neural Network (NN) classifier for analysis. Based upon the results the soil samples are shown with the availability of substance and possibility of crop yields. There are ten types of soil has been tested. And the promising results sows the better ability of the system.
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