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Gopalakrishna Bhat N.,Srinivas Institute of Technology | Narayana B.,Mangalore University
Journal of the Indian Chemical Society | Year: 2012

An indirect complexometric method is described for the determination of cadmium(II), citric acid being used as masking agent. Cadmium(II) in a given sample solution is initially complexed with an excess of EDTA and the surplus EDTA is titrated with lead nitrate solution at pH 5.0-6.0 (hexamethylene tetramine), using xylenol orange as indicator. An excess 1% citric acid solution is then added and the EDTA released from the Cd-EDTA complex is titrated with standard lead nitrate solution. Results are obtained for 4.24-21.20 mg of cadmium with relative errors ±0.47% and standard deviations ≤ 0.05 mg. The method is applied for the determination of cadmium in alloys and alloy compositions as well as in its complexes.

Bhat S.,Srinivas Institute of Technology | Meenakshi M.,AIT Inc
2015 International Conference on Control Instrumentation Communication and Computational Technologies, ICCICCT 2015 | Year: 2015

Presently a day's need of the robot is expanding as a result of robot's effectiveness at work. The independent robot meets expectations without human intervention. Zones like military, ATM stalls, and atomic reactors so on are utilizing robots. This paper presents a novel applications based on robot in the hotel as a waiter and in military as a baggage carrier. These robots use Infrared (IR) sensor for their pathway planning in the hotel to serve the food and also for soldiers to carry their baggage in a war field. These robots are utilizing Microcontroller based Embedded System to perform the task. © 2015 IEEE.

Bhat S.,Srinivas Institute of Technology | Meenakshi M.,Dr. AIT
2015 International Conference on Pervasive Computing: Advance Communication Technology and Application for Society, ICPC 2015 | Year: 2015

This paper presents a novel approach for human classification based on skin colour identification technique. Next the same classifier is extended for the path planning and control of autonomous robots. The techniques for obstacle identification used in this work are Skin Colour Based (SCB), Pixel Count Based (PCB), Correlation Coefficient Based (CCB) and Histogram methods. In real- time obstacle detection, the Pixel Count Based (PCB) algorithm, Correlation Coefficient Based (CCB) and Skin Colour Based (SCB) algorithm are used. In this work CCB and PCB methods compare the similarities between two objects but SCB algorithm is to identify whether the tracked object is human or nonhuman in real time. Real time experimental results demonstrated the accuracy of CCB, PCB and SCB algorithms are 87.5% and 88.8% and 90.9% respectively and the time of CCB, PCB and SCB algorithms are 6.27sec, 6.50sec and 8.67sec respectively. © 2015 IEEE.

Dsouza K.J.,Srinivas Institute of Technology | Ansari Z.A.,P.A. College
Proceedings - 2015 IEEE International Conference on Cloud Computing in Emerging Markets, CCEM 2015 | Year: 2015

Text classification, which aims to assign a document to one or more categories based on its content, is a fundamental task for Web and/or document data mining applications. In natural language processing and information extraction fields Text classification is emerging as an important part, were we can use this approach to discover useful information from large database. These approaches allow individuals to construct classifiers that have relevance for a variety of domains. Existing algorithms such as SVM Light have less GUI support and take more time to perform classification task. In this presented work classification of multi-domain documents is performed by using weka-LibSVM classifier. Here to transform collected training set and test set documents into term-document matrix (TDM), the vector space model is used. In classifier TDM is used to generate predicted results. The results emerged from weka with its GUI support using TDM have quick response time in classifying the documents. © 2015 IEEE.

Naik P.S.,Anjuman Engineering College | Orangalu S.A.,National Institute of Technology Karnataka | Londhe N.V.,Srinivas Institute of Technology
Polymer Composites | Year: 2012

This article presents the synthesis of carbon-carbon (C/C) composites by preformed yarn (PY) method, by varying the percentage of carbon fiber weight fraction. The PY used was carbon fiber bundle surrounded by coke and pitch which was enclosed in nylon-6. Three types of samples with fiber weight fractions of 30, 40, and 50%, respectively, are fabricated and mechanical properties were studied. In each case, the PY was chopped and filled into a die of required shape and hot pressed at 500°C to get the preform composite. To obtain the carbonized and graphitic structure, the specimen was heat treated at 2500°C followed by soaking for 10 to 12 hrs. Further, two cycles pitch impregnation was done by hot isostatic pressing, to eliminate the voids and to increase the density hence to obtain good mechanical properties. The characteristics such as hardness, flexural strength, and impact strengths were studied. It is observed that, as the carbon fiber percentage increases, the properties also get improved, provided sintering is done at fairly higher temperatures such as 2700°C. The superiority of the new class of C/C composites made by the proposed PY technique over those obtained by the conventional methods is also demonstrated. Copyright © 2012 Society of Plastics Engineers.

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