{"title":"Dual biometric authentication scheme for privacy protection","authors":"K. Sasireka, R. Rajesh","doi":"10.1109/CNT.2014.7062734","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062734","url":null,"abstract":"Preserving the privacy of biometric data becomes a critical work. To increase the privacy of the biometric data, novel method is proposed. In this proposed method, two different biometric data such as features from fingerprint and face are combined. In the face, the features like eyes, lips and brow are extracted. In the fingerprint, orientation feature is extracted. The database contains the training images. The ELM classifier is used to combine these features and matches with the training image.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116282796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A capacitive fed printed loop antenna for ISM band","authors":"A. Kamalaveni, M. Ganesh Madhan","doi":"10.1109/CNT.2014.7062713","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062713","url":null,"abstract":"This paper describes a novel approach for the design of a compact microstrip loop antenna for 5.8 GHz ISM band applications. This antenna has been designed in a Flame Retardant (FR4) substrate which is placed above the ground plane with air dielectric. The resonant frequency of the proposed antenna depends on the radiating loop. A gap-coupled capacitive feeding mechanism, for achieving higher bandwidth is also studied. Full wave 3D simulation is carried out based on FDTD modeling technique. The designed antenna has been fabricated and the results obtained by experiments are found to be agreeing well with the simulation.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114774981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Photonic processing of ultra wide band signals to mitigate interference and to improve efficiency","authors":"T. Sabapathi, I. Thanga Dharsni","doi":"10.1109/CNT.2014.7062743","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062743","url":null,"abstract":"UWB signal generation in optical domain is an emerging technique and finds immense advantages due to the elimination of complex optical-electrical and electrical-optical conversion devices. The generated UWB finds application in short range communications, offering advantages of high bandwidth and low power consumption. Satisfying these intentions, this paper provides the generation of Ultra Wide Band signals using photonic processing techniques. In this paper, the generation of reconfigurable highorder UWB signals using semiconductor optical amplifier and a Mach-Zehnder modulator (SOA-MZM) structure is demonstrated. The generation technique is compact, simple, and requires only a single wavelength input. UWB signal of higher orders is generated from the scheme.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133837709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pattern recognition: Advanced development, techniques and application for image retrieval","authors":"A. Khodaskar, S. Ladhake","doi":"10.1109/CNT.2014.7062728","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062728","url":null,"abstract":"Objective of our paper is to discuss latest pattern recognition applications, techniques and development. Pattern recognition has been demanding field from many years. We are also discuss driving force behind its swift development, that is pattern recognition is used to give human recognition intelligence to machine which is soul of today's many modern application. It acts as wheel of many techniques and applications in different fields. Pattern Recognition is recognition process which recognizes a pattern using a machine or computer. It is a study of ideas and algorithms that provide computers with a perceptual capability to put abstract objects, or patterns into categories in a simple and reliable way. The development and demand of pattern recognition technology is very fast and applications of pattern recognition are increase day by day. To fulfill this need, more and more researchers and scientists are evolved new pattern recognition techniques and apply them to many real life applications such as agriculture, robotics, biometrics, medical diagnosis, life form analysis, image processing, process control, information management systems, aerial photo interpretation, weather prediction, sensing of life on remote planets, behavior analysis, , Speech recognition, automatic diseases detection system in the infected plants, cancer detection system etc. with combination of other technology. Particular, in image retrieval system, pattern recognition play important for improving accuracy of image retrieval by using variety of recent techniques and their combination.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128785188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recognition of isolated words of esophageal speech using GMM and gradient descent RBF networks","authors":"P. Malathi, G. Suresh","doi":"10.1109/CNT.2014.7062749","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062749","url":null,"abstract":"Speech signal can be represented as a combination of acoustic parameters extracted from the speech signal. The parameter vectors are assumed to be the constituents of the speech signal over a specified duration during which it is stationary. Typical representations are Mel Frequency Cepstral Coefficients, Linear Prediction Coefficients etc. The process of isolated word recognition involves the mapping of these parameters with speech but it cannot because there are large variations in the realized speech waveform due to speaker variability, modulation, context, etc. The parametric speech vectors corresponding to each vector is modeled using Gaussian Mixture Model and its distribution is observed. The Expectation Maximisation algorithm is used in the Radial Basis Function network to best fit the test vector. The gradient descent algorithm applied on Radial Basis Function Neural Network is proposed to approximate the functions which have high non-linear order. The learning rates of the network are made proportional to the probability densities obtained from the Gaussian Mixture Model. Isolated words of esophageal speech appear to be recognized better in this method compared to previous methods since it consists of non linear components.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129604814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A scheme for source separation of ground borne vibrations","authors":"M. Krishna Kumar, R. S. Geethu, K. Pramod","doi":"10.1109/CNT.2014.7062752","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062752","url":null,"abstract":"The source separation of low level ground borne vibration signals is a tricky problem. This can be viewed as a complex version of the classical source separation problem, the `cocktail party problem'. An extension of the basic Independent Component Analysis (ICA), a Blind Source Separation method is proposed in this particular case, as the damping of the ground borne vibration signals is significant. The separation of a set of signals from a set of observed signal mixtures, without the information about the source signals or the mixing process is known as Blind Source Separation (BSS). The performance of the FastICA algorithm for various sources - sensor distance is analysed in this paper.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129996269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Text independent voice based students attendance system under noisy environment using RASTA-MFCC feature","authors":"S. Nidhyananthan, R. Shantha, Selva Kumari","doi":"10.1109/CNT.2014.7062751","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062751","url":null,"abstract":"This paper motivates the use of RASTA-MFCC (RelAtive SpecTrA-Mel Frequency Cepstral Coefficients) feature and GMM-UBM modeling for text independent voice based students' attendance system under noisy environment. MFCC has been identified as an efficient feature for identifying the speaker because it extracts speaker specific information. The performance of even best speaker identification system with MFCC feature degrades in uncontrolled communication environment. RASTA processing of speech improves the performance of identification system even in the presence of convolutional and additive noise. This paper combines the best of these two processes to yield RASTA-MFCC feature which is robust to noise and also contributes speaker dependent information to identify the speaker efficiently. GMM-UBM (Gaussian Mixture Model-Universal Background Model) modeling technique is used for its faster training and relatively easier updating of new speakers. Experimental result of 93.2% accuracy for Triangular filter bank and 94.5% accuracy for Gaussian filter bank are obtained for 50 speakers of MEPCO speech database in presence of additive and convolutive noise in the context of voice based students' attendance entry.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127761461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A hybrid super resolution technique using adaptive sharpening algorithm based on steering kernel regression for restoration","authors":"A. Geetha Devi, T. Madhu, K. Lal Kishore","doi":"10.1109/CNT.2014.7062730","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062730","url":null,"abstract":"A conceptually simple hybrid Super Resolution (SR) algorithm is proposed using an adaptive edge sharpening algorithm. Most of the existing Super resolution algorithms are not robust to handle the high noisy conditions due to the ambiguity between the sharpening and denoising processes. The Low Resolution (LR) images are applied with the adaptive edge sharpening algorithm that is capable of capturing the local image statistics and adjusts the sharpening process accordingly. The restored LR images are then registered using Scale Invariant Feature Transform (SIFT) based registration to position all LR pixel values to a common spatial grid. The registered LR images are fused using Singular Value Decomposition (SVD) based Fusion algorithm. The experimental results show the efficacy of the developed algorithm, produces better results than the existing algorithms under high noisy conditions.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127764850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ground bouncing noise reduction in combinational MTCMOS circuits","authors":"P. Sreenivasulu, K. Srinivasa Rao, A. Vinaya babu","doi":"10.1109/CNT.2014.7062768","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062768","url":null,"abstract":"As technology scales into the nanometer regime ground bounce noise and noise immunity are becoming important metric of comparable importance to leakage current, active power, delay and area for the analysis and design of complex arithmetic logic circuits. In this paper, low leakage 1bit full adder cells are proposed for mobile applications with low ground bounce noise and a novel technique has been introduced with improved staggered phase damping technique for further reduction in the peak of ground bounce noise. Noise immunity has been carefully considered since the significant threshold current of the low threshold voltage transition becomes more susceptible to noise. We introduced a new transistor resizing approach for 1bit full adder cells to determine the optimal sleep transistor size which reduce the leakage power and ground bounce noise. The simulation results depicts that the proposed design also leads to efficient 1bit full adder cells in terms of standby leakage power, active power, ground bounce noise and noise margin. We have performed simulations using Cadence Spectre 90nm standard CMOS technology at room temperature with supply voltage of 1V.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124622896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mitigation of fiber non linear effects by Maximum Likelihood Sequence Detection","authors":"T. Sabapathi, G. Jaya, Brindha P G Student","doi":"10.1109/CNT.2014.7062744","DOIUrl":"https://doi.org/10.1109/CNT.2014.7062744","url":null,"abstract":"Maximum Likelihood Sequence Detection (MLSD) in the optical receiver has been proposed to combat the nonlinear effects in optical channels. The MLSD is typically implemented through a Viterbi algorithm. In this paper, it is shown that a low-complexity maximum likelihood sequence detector with proper metrics can achieve better results. Computational complexity grows exponentially with the length of the channel impulse response and makes it unsuitable for high data rates. To practically enable uncompensated long haul with MLSD, complexity must be minimized. While in the linear regime such a model is available and linear impairments such as chromatic dispersion and polarization-mode dispersion can be almost fully compensated by adaptive equalizers, this is not the case for nonlinear impairments, whose mitigation is essentially based on heuristic strategies. Fiber nonlinearity remains as one of the major limitations for long haul transmission.","PeriodicalId":347883,"journal":{"name":"2014 International Conference on Communication and Network Technologies","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121109176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}