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Suresh S.,Loyola College | Ramanand A.,Loyola College | Jayaraman D.,Loyola Institute of Technology
Optoelectronics and Advanced Materials, Rapid Communications | Year: 2010

The mechanical properties of crystals were evaluated by mechanical testing. The fastest and simplest type of mechanical testing is hardness measurement. The Vickers microhardness studies have been carried out for L-Valine crystals grown by a slow evaporation technique over a load range of 10-100 g. The Vickers hardness number (H v) was found to increase with the increase in load. The Meyer's index number 'n' was calculated from Hv and yield strength (σ v). The Young's modulus was calculated using the Knoop hardness values. Hardness anisotropy has been observed in accordance with the orientation of the crystal. Source


Suresh S.,Loyola College | Ramanand A.,Loyola College | Jayaraman D.,Loyola Institute of Technology | Mani P.,Hindustan University
Optoelectronics and Advanced Materials, Rapid Communications | Year: 2010

Single crystals of Triglycine Sulfate (TGS) were grown in water by solution method with slow evaporation technique at room temperature. The grown crystals were characterized by XRD technique. The dielectric studies show that the dielectric constant and dielectric loss decrease exponentially with frequency at room temperature. Photoconductivity study confirms the negative photoconducting nature of the crystal which confirms the high degree of transparency of the material. Source


Vanitha L.,Loyola Institute of Technology | Suresh G.R.,Easwari Engineering College
ICACCS 2013 - Proceedings of the 2013 International Conference on Advanced Computing and Communication Systems: Bringing to the Table, Futuristic Technologies from Around the Globe | Year: 2014

In recent years, stress has become ingrained part of our life, being stressed by our financial worries, our job, etc. Stress causes physical illnesses, such as heart attacks, arthritis, and chronic headaches or psychological diseases like mental illness, anger, anxiety, and depression. There are several research works coming up to resolve the limitations on measuring, analyzing and identifying the human stress levels Amongst the many stress monitoring methods the more reliable method to determine the human stress level is to use physiological signals. In this work, Heart Rate Variability (HRV) determined from ECG signal, an efficient parameter to detect the stress level is used. The features extracted from HRV are given as input, to the two stage classifier, to classify the stress into one of the four levels as no stress, low stress, medium stress and high stress. In the first stage of the classifier, Self Organizing Map is used to classify the stress into two classes as 'stress level 1'(no stress & low stress) and 'stress level 2' (medium stress & high stress). In the second stage Support Vector Machine is used with RBF kernel to subdivide the 'stress level 1' into two classes 'No Stress' and 'Low Stress'. The stress level 2 is subdivided into twoclasses 'Medium Stress' and 'High Stress'. The performance of this hybrid structure is better and the efficiency of classification is 91%. © 2013 IEEE. Source


Navaneethasanthakumar S.,Sri Krishna College of Engineering And Technology | Mohanasundaram K.M.,Coimbatore Institute of Technology | Godwin Raja Ebenezer N.,Loyola Institute of Technology | Krishnaraj C.,Coimbatore Institute of Technology
European Journal of Scientific Research | Year: 2012

In this paper, a novel approach has been used for solving the forward kinematics mathematical model of SCORBOT ER V PLUS in its work space for various set of joint parameters. The obtained results are validated with ROBOCELL 3D graphic software and also using CAD 3D model in AutoCAD 2007. A system based on the theory of computer aided geometric method is proposed. Data generation in text format has been stored for all the joint parameter combinations for reviewing at anytime and also for determining workspace boundaries. The entire system has been modeled using LabVIEW2011. © 2012 EuroJournals Publishing, Inc. Source


Vanitha L.,Loyola Institute of Technology | Suresh G.R.,Easwari Engineering College
Proceedings of the IEEE International Caracas Conference on Devices, Circuits and Systems, ICCDCS | Year: 2014

Stress has become an embedded part of our life, being stressed by our financial worries, our job, etc. Stress causes physical illnesses, such as heart attacks, arthritis, and chronic headaches or psychological diseases like mental illness, anger, anxiety, and depression. There are several research works coming up to resolve the limitations on measuring, analyzing and identifying the human stress levels Amongst the many stress monitoring methods the more reliable method to determine the human stress level is to use physiological signals. The Heart Rate Variability (HRV) determined from ECG signal, an efficient parameter to detect the stress level is used in this work. The features extracted from HRV are given as input, to the Hierarchical classifier, to classify the stress into one of the four levels as no stress, low stress, medium stress and high stress. The performance of the hierarchical structure is better and the efficiency of classification is 92 %. © 2014 IEEE. Source

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