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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-6 (December 2014)
    Title: Review on Moving Relay Nodes in LTE-Advanced
    Authors: Anika Aneja, Jolly Parikh and Anuradha Basu
    Abstract: 3GPP aims to meet ITU (International Telecommunication Union) requirements for availing backward compatibility along with increased data rates and minimal data latency and losses. LTE-Advanced aims to achieve increased data rates for DL (upto 3Gbps) and UL (upto 1.5 Gbps), higher spectral efficiency, increased network capacity and improved cell-edge performance. The main new functionalities introduced in LTE-Advanced are Carrier Aggregation (CA), MIMO techniques and support for Relay Nodes (RN). Relay nodes ensure fair extended cell coverage and capacity. Moving Relay Nodes (MRN’s) are RNs deployed on top of a moving public transportation vehicle. The use of MRNs is expected to enhance the performance of vehicular UEs. This paper reviews the work done on MRNs and investigations done up-till date. Paper also speaks about the possible solutions to overcome the challenges faced with MRNs so as to contribute towards an improved global communication system.
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    Title: Quantitative Assessment of Trend Approach for Intelligent Fault Diagnosis in Sugar Industry
    Authors: Dr. Tarun Chopra
    Abstract: Fault diagnosis is an important and difficult task in process engineering involving decision making procedure with analysis of time series databases. Further-more, the task of fault diagnosis is made difficult by the fact that the time series obtained through process measurements may often be insufficient, incomplete and/or unreliable due to a variety of causes such as sensor biases or failures. In this paper, the quantitative assessment of trends has been carried out in Sugar plant by using logistic regression technique as it is more robust than other statistical techniques.
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    Title: A Review: Achieving Data using DES and RSA Algorithm
    Authors: Smita Chourasia and Prof. Kedar Nath Singh
    Abstract: Data security is the major concern today. There are several security protocols are available today. But data protection from unauthorized access is the major concern and several research works are in progress in this direction. In the modern internet scenario several methods and security mechanism are available but there are still some drawbacks and need to strengthen the capability of encryption techniques. Our paper main aim is to decipher the advantages and fond out the problem formulation. Based on the problem formulation we also provide a detail analysis and suggest some future enhancement. We also discuss Data Encryption Standard (DES) and RSA algorithm was publicly described in 1977 by Ron Rivest, Adi Shamir, and Leonard Adleman at MIT; the letters RSA are the initials of their surnames. Based on DES and RSA encryption we can suggest some better hybrid framework for data security. Hybrid encryption is better because it can combine the attributes of two different security concerns.
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    Title: Enhancement of Underwater Images by Preserving Edge Component and Enhancing Contrast and Resolution
    Authors: Mr. Bhupendra Sahu, Dr. Samar Upadhyay, Prof. Nitin Shukla and Prof. Bharat Solanki
    Abstract: As we know that, clarity of images are degraded by light absorption and scattering in underwater. Due to which one colour is dominating in the image. For improving the perfection of underwater images, the proposed approach is divided into 4 steps. Firstly, we remove the unwanted noise and blur present in input image by applying lots of noise and blur removal filter then in second step, contrast stretching of RGB algorithm is applied to equalize the colour contrast in images. In third step, different edge preserving algorithms are applied to enhance the sharpness of edges, and then finally the saturation and intensity stretching of input images is used to increase the true colour and solve the problem of lighting. Today restoration methods typically only concentrate on non uniform lighting or colour correction and often require additional knowledge of the environment. The algorithm proposed here reduces underwater perturbations, and improves image quality. It is composed of several consecutive independent processing steps which acceptable non uniform illumination, suppress noise, enhance contrast and adjust colours. Performances of different filters, at each step are analyzed on different parameters like PSNR, MSE etc.
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    Title: Face Hallucination using Cuckoo Search
    Authors: Jaskiran Kaur and Asst. Prof. Manish Mahajan
    Abstract: In many cases the face images captured by live cameras are often of low resolutions due to the environment or equipment limitations. How to recover human faces automatically has become an important problem for the further works such as face analysis and recognition. Face hallucination is super-resolution of face images or clarifying the details of a face from a low-resolution image. The technique of Sparse Coding can be used, Because of the importance of face images in facial recognition systems and other applications as well. The Face hallucination has become an area of research. Primitive approaches to design face hallucination system which aims at utilizing a best individual techniques have some drawbacks. In this work, we will be performing face hallucination using super-resolution model to get high hallucination parameters and cuckoos search to optimize the results and we are implementing this by using MATLAB.
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    Title: A Real Time Image Steganalysis by Chi-Square Test (CTSI) Method
    Authors: Sabyasachi Samanta, Saurabh Dutta and Goutam Sanyal
    Abstract: Steganography is the art of hiding data in data in an untraceable way. Main concern of steganography is hiding the existence of hidden message. Steganalysis is the art and science of detecting hidden messages from stego-systems. It also attempts to find hidden message such as the type of embedding algorithm, the length of the message, the content of the message or the secret key used from the carrier (like image, text, video etc.). In this paper we have discussed about the steganalysis by using Chi-square Test based Steganalysis for Image (CTSI) Method.
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    Title: Local and Global mean selection for contrast enhancement in medical images
    Authors: Manjeet Singh Walia and Prof. Manish Mahajan
    Abstract: Contrast enhancement plays a crucial role medical image analysis, LCD display processing, scientific visualization and electron microscopy images and even our real life photographic pictures, suffer from poor contrast. The principal objective of image enhancement is to modify attributes of an image to make it more suitable for a given task and a specific observer. During this process, different attributes of the image are modified. The selection of attributes and the way they are modified are specific to a given task. Nowadays, medical image enhancement plays a vital role for diagnosis. In medical images, source generates the x-ray energy and passes through patient body and makes the image through the sensor. This may lead to have a poor image contrast due to this the images may lead to overexposure & underexposure [1]. Some parts having soft tissues generate high contrast while some other parts having hard tissue generate low contrast. None of single method can work as generalized for image enhancement. So we need a method that could generate contrast for local means. Local means make an effect over small changed level of gray values. In the current paper we are going to implement the new method of image contrast enhancement that uses the concept of Global mean and global variance by using localization functions. The proposed has been applied on complex (medical) images and is checked for different metrics such as CNR, quality Index and structural content.
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    Title: Hybrid of Contourlet and Curvelet Transformation with Fuzzy logic for Image Fusion
    Authors: Rohit Dubey and Manish Mahajan
    Abstract: Image fusion has wide range of application in satellite images, general photography, medical images etc. Image fusion is the process in which we combine two or more images or some features of images to form a single image which is free from distortion and does not loses its information. Images which are taken from different angles sometimes needs to be fused together to form a single image which has all the detail information to create accurate description of the image. Its application lie for medical imaging, satellite images, general photography etc. Nowadays, medical image fusion plays a vital role for diagnosis. There are number of issues related to image fusion that needs to resolve. None of single method can work as generalized for image fusion. In the current paper we are going to hybrid two methods: contourlet transformation and curvelet transformation for better fused images. Fuzzy logic is being implemented to provide better coefficient extraction.
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    Title: Performance Evaluation on various Route Optimization Techniques in Network Mobility (NEMO)
    Authors: Subhrananda Goswami and Chandan Bikash Das
    Abstract: Mobile IP provides the basic solution for mobility of certain node, whereas network mobility (NEMO) refers to the concept of collective mobility of a set of nodes. In the simplest scenario, a mobile network moves as a single unit with one mobile router (MR) that connects it to the global Internet. NEMO Basic Support Protocol, proposed by IETF as an extension to Mobile IPv6, suffers with the problem of Pinball Routing (Dog Leg Problem). Since the packets have to come through the Home Agents (HA) of all the superior MRs before coming to the subordinate MR, this increases packet transmission delay, amount of memory used, signalling cost etc. This paper targets to analyze network mobility issues and requirements. The aim is to explore the idea of route optimization (RO) in NEMO. After discussing the need of route optimization in NEMO, different solutions provided so far are discussed and analyzed. Still a lot of work is required to be done in the field of route optimization in NEMO. All these issues are explained to provide a future scope of studies in this field.
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    Title: An Investigation on Pattern Classification and Recognition by using Least Mean Square Algorithm
    Authors: N.S.Murtisarma, S.Leninbabu and S.P.Venu Madhava Rao
    Abstract: Objective is to construct Radial Basis Function (RBF) network for the classification of a given set of objects and recognition of an object from a known set of objects.. The outputs at the hidden neurons are generated with ‘Gaussian function’. The selection of centers or the neurons can be made by the well known clustering algorithm K-means.
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    Title: An efficient Optimization technique for Web Log Data based on ACO and PSO
    Authors: Prashant Sharma
    Abstract: The globe is relying on World Wide Web. It describes the passion of information sharing online. It is now trending also. Google trends also provide the trending of the people on the concern web. The optimization on the web is the process for improving their rank in the globe and it is the way of increasing their visitors also. So in this paper we have created a framework for web optimization prediction which can help us suggest that the level of optimization can be achieved based on the Google trends visit. We have applied two famous optimization algorithm named ACO and PSO.
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    Title: Document Clustering Techniques for Web Data Mining
    Authors: Narasimha Murthy GK, B R Prakash and Sridevi T N & Kalpana K
    Abstract: 1 2B R Prakash 3Conventional Information retrieval systems return long lists of ranked documents that users are forced to go through to find relevant documents. The majority of today's Web search engines follow this paradigm. The Web search engines coupled with the ranked list presentation make it hard for users to find the information they are looking for. Our goal is to make search engine results easy to browse by clustering them. Clustering is the process of grouping objects together in such a way that the objects belonging to the same group are similar and those belonging to different groups are dissimilar. Clustering technique can be used in many applications. One of these application types is Web clustering where different types of objects can be clustered into different groups for various purposes. This paper deals with the different aspects of Web data mining and provides an overview about the various techniques used in this field.
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    Title: Trusted Computing
    Authors: Chaithra.N, Brahammanand B S and Pradeep Biradar
    Abstract: Trusted Computing (TC) is a technology developed and promoted by the Trusted Computing Group. The term is taken from the field of trusted systems and has a specialized meaning. With Trusted Computing, the computer will consistently behave in expected ways, and those behaviours will be enforced by computer hardware and software. Enforcing this behaviour is achieved by loading the hardware with a unique encryption key inaccessible to the rest of the system. TC is controversial as the hardware is not only secured for its owner, but also secured against its owner. Such controversy has led opponents of trusted computing, such as free software activist Richard Stallman, to refer to it instead as treacherous computing, even to the point where some scholarly articles have begun to place scare quotes around "trusted computing".
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    Title: Issues with `Trusted Computing'
    Authors: Subhankar Ghosh and Shipra Mehata
    Abstract: It is widely realised that provenance systems can benefit from greater awareness of security principles and the use of security technology. In this paper, we argue that Trusted Computing, a hardware-based method for establishing platform integrity, is not only useful, but immediately applicable. We demonstrate how existing Trusted Computing mechanisms can be used for provenance, and identify the remarkable similarity and overlap between the two research areas. This is accomplished through presenting architectural ideas for a trusted provenance system, and by comparing the respective requirements and capabilities of trusted systems and provenance systems.
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    Title: Development of an Online Static Power System Security Assessment Module Using Artificial Neural Networks in 118- Bus Test System
    Authors: Lekshmi M, Sowmya and Dr. M.S. Nagaraj
    Abstract: Contingency analysis is an important task in today’s power system. Fast and accurate contingency analysis is some of the major issues. In this paper two types of Artificial Neural Network (ANN) viz. Multilayer feed forward neural network (MLFFN) and Radial basis function network (RBFN) are used to implement online static security assessment. Newton Raphson (NR) method is done on an IEEE 118-test bus system and Composite Security Index (CSI) is calculated. Loads are varied from the base case values and for each load condition, line flow and bus voltages are calculated using a model based on the NR load flow method for training an ANN with the help of back propagation algorithm. Expected range of load variation and randomly selected 20-contingencies are tested in the training ANN model. The results obtained by the above ANN methods are matched with NR methods. The CSI is found out for various loads and contingencies in MLFFN and RBFN. The computation time required for MLFFN and RBFN is compared with NR method and found that RBFN is using less computation time average of 35.67291s.
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    Title: Modification in FKP
    Authors: Shikha Kumari, Gulista Tabassum,Akanksha Tiwari and Preeti Kumari Yadav
    Abstract: This paper proposed the use of multi-instance feature level fusion as to improve the performance of (FKP) verification. A log-Gabor filter has been used to extract the image local orientation information, & represent the FKP features. Experiments are performed by using the FKP database, which contain 7,920 images which gives the result, multi-instance verification approach out-performs higher performance than using any single instance. The influences on bio-metric performance using feature level fusion under different fusion rules have been demonstrate in the paper.
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