Informatics Publishing Limited

E. Jasmine Vasantha Rani ¹, K. Seethalakshmi ¹, R. Padmavathy ¹, N. Radha ²

Affiliations
1 Department of Physics, Seethalakshmi Ramaswami College, Tiruchirapalli-2.
2 Department of Chemistry, Seethalakshmi Ramaswami College, Tiruchirapalli-2.

Abstract

Infrared spectroscopic techniques are widely used as a tool with unique capability and sensitivity. In the present study, FT-IR spectra are recorded for 1-butyl-3-methyl imidazolium chloride and its solution in non-aqueous solution in the wave number region from 4000cm^-1 to 450cm^-1. The ultrasonic velocity, density and viscosity of imidazolium halide in non-aqueous solution were measured at different temperatures with various concentrations. The thermo acoustic parameters such as adiabatic compressibility, intermolecular free length, specific acoustic impedance, Rao's Constant, Wada's Constant, internal pressure and free volume were computed with the help of ultrasonic velocity, viscosity and density. From the computation that there is a strong solute-solvent interaction due to high cohesive energy exists. The results are also compared with FT-IR spectrum. The results obtained from FTIR analysis are found to be in good agreement with acoustic and thermodynamic studies.

Keywords

Ultrasonic Velocity, Adiabatic Compressibility, Specific Acoustic Impedance, Vibrational Spectra

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N. Gomathy ¹, N. Radha ¹

Affiliations
1 Department of computer science, PSGR Krishnammal College of arts and science, Coimbatore, IN

Abstract

Objectives: Cancelable unimodal and Multiple Biometric Using Distortion Transformation Algorithm solve the problem of raucous data, non-universality and unacceptable error rate during authentication.

Methods: Distortion Transformation algorithm used for generate key from multiple biometrics.

Results: The cryptographic key generation of multiple finger print and palm print of the same person. It gives more authentications.

Conclusion: The features are extracted from the palm print and multiple finger print of same person. The extracted features are used to generate the key using distortion algorithms which are used for further authentication. This cryptographic key is stored in the database and used for verification process.

Keywords

Security Analysis, Palm Print, Biometric System, Multiple Fingerprints, Fusion.

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R. Deepa Lakshmi ¹, N. Radha ²

Affiliations
1 P.S.G.R. Krishnammal College for Women, Coimbatore-4, IN
2 GR Govindarajulu School of Applied Computer Technology, PSGR Krishnammal College for Women, Coimbatore-4, IN

Abstract

Data mining process discovers useful information from the hidden data, which can be used for future prediction. Machine learning provides methods, techniques and tools, which help to learn automatically and to make accurate predictions based on past observations. This paper presents an implementation of various data mining tools in real time datasets. The main purpose of this paper is to provide a comparison of some commonly employed classification algorithms under the same conditions. Such comparison helps to provide the accurate result in algorithms. Hence comparing the algorithms for such a classifier is a tedious task, for real time dataset. The classification models were experimented by using 365 datasets. The predicted values for the classifiers were evaluated and the results were compared.

Keywords

Audit Selection Strategy, Machine-Learning Techniques, Open Source Tools, Data Mining, Naive Bayes, Tax Audit.

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R. Deepa Lakshmi ¹, N. Radha ²

Affiliations
1 PSGR Krishnammal College for Women, Coimbatore-4, IN
2 G. R. Govindarajulu School of Applied Computer Technology, PSGR Krishnammal College for Women, Coimbatore-4, IN

Abstract

The “Car Manufacturing” sector occupies a prime position in the development of automobile industry. In this paper, a proposed data mining application in car manufacturing domain is explained and experimented. The datasets are retrieved from UCI Machine learning repository. The purpose of this paper is to establish a classifier that is much more reliable in classifications for future objects. The classifier should provide sophisticated prediction to indicate the car data for a new input instance with some attributes, such as car type, body-style, horsepower and fuel. Such analysis helps in providing car market with base for more accurate result for the future market. The physical characteristics of a car viz. aspiration, number of doors, body-style, normalized losses, car-type, drive wheels, engine-location, wheel-base, curb-weight, horse-power, bore, stroke, city-mpg, highway-mpg, price, engine size, etc., are considered to determine the performance of a car. Hence development of such a classifier, though a voluminous task, is immensely essential in car manufacturing realm. Machine learning techniques can help in the integration of computer-based systems in predicting the quality of car and to improve the efficiency of the system. The classification models were trained by using 214 datasets. The predicted values for the classifiers were evaluated using 10-fold cross validation and the results were compared.

Keywords

Machine Learning Techniques, Navies Bayes, J48, BF Trees, Decision Trees, Car Market, Data Mining, WEKA Classification.

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T. Rubya ¹, N. Radha ², S. Shantha Kumari ²

Affiliations
1 P S G R Krishnammal College for Women, Coimbatore-4, IN
2 GR Govindarajulu School of Applied Computer Technology, P S G R Krishnammal College for Women, Coimbatore-4, IN

Abstract

Data mining techniques are used to manipulate the existing a large volume of data. Biomedical datasets pretense an elite challenge for machine learning and data mining techniques in order to extract accurate, understandable and hidden knowledge. This paper extensively investigates the role of a biomedical dataset (diabetes dataset) has been taken for finding the classification accuracy of that disease. Diabetes is a common disorder caused by a lack of insulin or insulin resistance leading to impaired glucose metabolism. Glucose (a simple sugar) is the key component used by the body’s cells to make energy. In order for glucose to move from the blood into most cells insulin is required (exceptions are the brain and exercising muscles). Insulin is a hormone made in the cells of the pancreas and is secreted into the blood in response to the blood glucose level increasing. According to that the whole dataset were classified to predict the accuracy of disease. The data are retrieved from the real time environmental setup especially it consists of information about glucose, cholesterol and insulin secretion level in blood. These are all considered as attributes. Machine learning provides methods techniques and tools, which help to learn automatically and to make accurate predictions based on past observations. The data mining classification algorithms of Weka were used to classify the data. The predicted values of the classifiers were evaluated using Weka tool with respect to the specific algorithms. Comparison has been made among various algorithms from three different categories of classifiers such that Function, Rule, and Meta. In this paper the conclusion is made as to infer which algorithm provides the maximum accuracy of the disease.

Keywords

Accuracy Prediction, Data Classification, Insulin Deficiency, Machine Learning Techniques, and Weka Classifiers.

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R. S. Pranitha ¹, N. Radha ²

Affiliations
1 PSGR, Krishnammal College for Women, Coimbatore-4, IN
2 GR Govindarajulu School of Applied Computer Technology, PSGR Krishnammal College for Women, Coimbatore-4, IN

Abstract

Biometric authentication is a technology that measure and analyzes human physical and behavioral characteristics for recognition and authentication to provide security. The main benefit of the biometric technology is that, it is more safe and comfortable than the traditional systems like password and tokens such as smart cards, magnetic stripe cards, photo ID cards, physical keys and can be lost, stolen, duplicated, or left at home. Cancelable biometrics may be a good approach to address the security and privacy concerns on biometric authentication. The security of cancelable biometrics lies on noninvertibility of the transformed templates. So the transforms should be noninvertible and the original template cannot be recovered. In this paper, fuzzy vault scheme, Fuzzy Vault with Minutiae Descriptors, Irrevocable Cryptographic Key Generation from Cancelable Fingerprint Templates, steganography, cancelable iris biometrics, Palm print based Cancelable Biometric, mobile fingerprint template protection, secure authentication for fingerprint and face are reviewed.

Keywords

Cancelable Biometrics, Fuzzy Vault Scheme, Irrevocable Cryptographic Key Generation, Steganography, and Secure Authentication.

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N. Radha ¹, A. Shahina ¹, A. Nayeemulla Khan ²

Affiliations
1 Department of Information Technology, SSN College of Engineering, Chennai, IN
2 School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, IN

Abstract

Objectives: This paper proposes a method to improve the performance of a Visual Speech Recognition (VSR) system by combining the pixel-based and geometry-based features, so as to augment the performance of audio based Automatic Speech Recognition (ASR) systems in adverse conditions. Methods/Statistical Analysis: A video database comprising of 11000 utterances of isolated words, collected from 20 speakers, is used in this study. Pixel based features (DCT and DWT) and geometric features (Active Shape Model or ASM) are fused at two levels, one at the feature level and the other at the decision level. A simple Gaussian mixture HMM word model is built for feature level fusion, while a two stream HMM model is built for decision level fusion. Findings: The VSR system built using the combined features shows a significant improvement in performance when compared to individual VSR systems built using pixel and geometric based features. The accuracy of the individual system is 76% for geometric features, 64% for DCT and 72% for DWT pixel-based features. The performance improves for combined features with an accuracy of 80% for ASM+DCT and 84.7% for DWT+ASM. A weighted decision level fusion result in further improvement, with an accuracy of 84% for ASM+DCT and 92% for ASM+DWT. Application/Improvements: The combined VSR could be preferred over individual pixel/geometric feature based systems to augment the performance of audio based Automatic Speech Recognition (ASR) systems in adverse conditions. Further studies on improving the VSR system, which could be used in lieu of audio-based ASR systems in adverse situations, are being carried out.

Keywords

HMM, Pixel and Geometric Features, Visual Speech Recognition.

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N. Radha ¹, M. Swaminathan ²

Affiliations
1 Department of Chemistry, Alagappa Government Arts College, Karaikudi, Tamil Nadu, IN
2 Nanomaterials Laboratory, International Research Centre, Kalasalingam Univeristy, Krihnankoil, Tamil Nadu, IN

Abstract

Fluorescence quenching of four naphthalenediols [1,5-; 1,7-; 2,7-; and 2,3- Naphthalenediols (NDs)] by inorganic anions [Cl−, Br−, SO₄ ²⁻ SO₃ ²⁻, S₂O₂ ²⁻, CO₃ ²⁻, NO₃ ⁻, and HPO₄ ²⁻] have been studied in 95% (v/v) water -ethanol mixture medium. The quenching was found to be dynamic in all systems. The plots of log k_q values with singlet transition energy (E_s) of the fluorophore and with ECTTS of the quencher are linear indicating the presence of electron transfer quenching mechanism. ΔG_TH values for charge transfer quenching have been determined for naphthalenediols.

Keywords

Fluorescence Quenching, Naphthalenediols, Anionic Quenching, Electron Transfer Mechanism.

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N. Radha ¹, S. Karthikeyan ¹

Affiliations
1 Department of Computer Science and Engineering, Karpagam University, IN

Abstract

The increasing popularity of biometrics and cryptography is driven by the widespread stipulation on information security. Abundant efforts have been made in developing successful methods in these areas in order to accomplish an enhanced level of information security. There are two dominant issues in information security enhancement. One is to defend the user ownership and control the access to information by authenticating an individual's identity. The other is to make sure the privacy and integrity of information and to secure communication. Cryptography is the science of writing in secret code. Secret-key cryptography and public-key cryptography are the two most important cryptographic architectures. The security of a cryptographic system is reliant on the secrecy of the cryptographic key. Biometric authentication or simply biometrics refers to establishing automatic personal recognition based on the physical and behavioral characteristics of an individual (e.g. face, voice, fingerprint, gait, hand geometry, iris, gene, etc.). Biometrics offers superior security and easier than traditional identity authentication systems (based on passwords and cryptographic keys).Since biometrics characteristics are naturally related with a particular individual, making them insusceptible to being stolen, forgotten, lost or attached. This paper presents a survey on various techniques proposed earlier in developing an authentication system for ensuring individual's information security by combining biometric characteristics of that particular individual and the cryptographic techniques. In addition, it provides some fundamental idea for future research that may help in eliminating the problems associated with the present authentication systems.

Keywords

Authentication, Cancelable Biometrics, Bio-Cryptosystems, Fuzzy Vault, Multimodal Biometrics, Soft Biometrics.

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