Nano-Mite Technologies, Llc
Nano-Mite Technologies, Llc
Suvarna M.,Nano-Mite Technologies, Llc |
Venkategowda N.,Nano-Mite Technologies, Llc |
Deepak L.,TATA Elaxsi Ltd
2016 International Conference on Systems in Medicine and Biology, ICSMB 2016 | Year: 2017
The chemical burn is one of the major accidents and life treating process in the modern world. The proposed research attempts to find an automated solution for classifying chemical skin burn as superficial, partial thickness and full thickness. The design and development of such a classifier is clinically very significant particularly, when it is used in remote areas and under emergencies. Towards achieving this aim, a database of chemical skin burn images has been created by collecting images from hospitals. The pattern analysis or pattern classifier technique called Support Vector Machine (SVM) is used in the study. © 2016 IEEE.
Purushotham G.,Nano-Mite Technologies, Llc |
Applied Mechanics and Materials | Year: 2014
History is often marked by the materials and technology that reflect human capability and understanding. Many a times scales begins with the stone age, which led to the bronze, iron, steel, aluminium and alloy ages as improvements in refining, smelting took place. Science made all these possible to move towards finding more advanced materials. Therefore in the present research work, an investigation has been carried out to fabricate and evaluate the microstructure, strength, micro hardness of chilled composites consisting of nickel matrix and fused SiO2 particles as the reinforcement (size 40-150 μm) in the matrix. The reinforcement being added ranges from 3 to 9 wt. % in steps of 3%. The resulting composites cast in moulds containing metallic chill blocks (MS, SiC & Cu) were tested for their microstructure and mechanical properties. The main objective of the present research is to obtain fine grain Ni/SiO2 chilled sound composite having very good mechanical properties. A detail of melting and composite preparation is described elsewhere by number of researchers. After melting the matrix material in an induction furnace at around 1600 °C in an inert atmosphere, coated fused SiO2 particles preheated to 500 °C were introduced evenly into the molten metal alloy by means of special feeding attachments. The moulds for the plate type of castings 150*20*20 mm (American Foundrymen Society standard) were prepared using silica sand with 5% bentonite as binder and 5% moisture and finally they were dried in an air furnace at a temperature of 1580 °C, which was cooled from one end by a chill block set in the mould. After solidification the specimens of chill end were tested for various mechanical and microstructural studies. © (2014) Trans Tech Publications, Switzerland.
Suvarna M.,Nano-Mite Technologies, Llc |
Venkategowda N.,Mangalore University
Procedia Computer Science | Year: 2015
Chemical burn injury is one of the major accidents in the world. The aim of this research is to develop an automated method of determining the severity of chemical skin burns. The severity of the chemical skin burn can be classified into three grades, namely Superficial, Partial thickness and Full thickness. Towards achieving this aim, a database of chemical skin burn images has been created by collecting images from various Hospitals. The initial pre-processing involves the contrast enhancement in L∗a∗b colour space. The pattern classifier technique namely K-Nearest Neighbour Classifier (KNN), has been applied on chemical skin burn images to classify them as Superficial, Partial and Full thickness burns. The help of dermatologists and plastic surgeons has been taken to label the images with chemical skin burn grades and the labelled images are used to train the classifiers. From the many features that were extracted from the images, two significant features such as the mean and then DCT were selected that best embody the differing characteristics of the three grades of chemical skin burns. The algorithms are optimized on features of pre-labelled images, by fine-tuning the classifier parameters. The efficiency of the analysis and classification of the KNN method is about 67.5% for grade1, 82.5% for grade 2 and 75% for grade 3. The design and development of such a classifier is clinically very significant particularly, when it is used in emergency remote areas. © 2015 The Authors.
Nandini R.,Nano-Mite Technologies, Llc |
Vishalakshi B.,Mangalore University
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2010
The interactions of Acridine Orange with Sodium Alginate and Pinacyanol Chloride with Heparin have been investigated by spectrophotometric method. The polymers induce metachromasy in the dye as evidenced from the considerable blue shift in the absorption maxima of the corresponding dyes. The interaction constant and thermodynamic parameters of polymer-dye interactions have been determined. The effect of additives such as alcohols, and urea on the reversal of metachromasy has been studied. The data has been used to determine the stability of the metachromatic complex and the nature of binding. The thermodynamic parameters of interaction revealed that binding between Acridine Orange and Sodium Alginate involved only electrostatic forces while that between Pinacyanol Chloride involved both electrostatic and hydrophobic forces. The reversal studies using surfactants indicated the involvement of both electrostatic and hydrophobic forces in binding. Based on the results it can be concluded that Pinacyanol Chloride is more effective inducing metachromasy than Acridine Orange. © 2009 Elsevier B.V. All rights reserved.
Agency: Department of Health and Human Services | Branch: | Program: STTR | Phase: Phase I | Award Amount: 183.07K | Year: 2014
DESCRIPTION (provided by applicant): Obesity is recognized as a national and global epidemic, as approximately 65% of adults in the United States are classified as overweight or obese as defined by body mass index (BMI). In fact, in the year 2000, the human race reached a historical landmark, when for the first time in history the number of adults with excess weight surpassed the number of those who were underweight. Obesity is linked with several cardiovascular risk factors cumulatively recognized as the metabolic syndrome. While obesity is associated with increased risk for metabolic syndrome and cardiovascular disease; consequently, weight loss in obese subjects has been demonstrated to reduce or reverse health risk factors. Fundamentally, irrespective ofthe method by which weight loss occurs, even a modest reduction in body weight has been shown to consistently reduce or reverse risk factors. In the 1930s it was recognized that increasing the body's basal metabolism using mitochondrial uncouplers, d
Nandini R.,Nano-Mite Technologies, Llc |
Vishalakshi B.,Nano-Mite Technologies, Llc
Journal of Polymer Engineering | Year: 2011
The interaction of two cationic dyes, namely crystal violet (CV), with anionic polyelectrolytes, namely sodium carrageenate (NaCar) and sodium heparinate (NaHep), has been investigated by spectrophotometric method. The polymers induced metachromasy in the dye resulting in the shift of the absorption maxima of the dyes towards shorter wavelengths. The stability of the complexes formed between crystal violet and sodium carrageenate was found to be greater than that formed between crystal violet and sodium heparinate. This fact was further confirmed by reversal studies using alcohols, urea surfactants and electrolytes. The interaction parameters revealed that binding between crystal violet and sodium carrageenate was mainly due to electrostatic interaction while that between crystal violet and sodium heparinate is found to involve both electrostatic and hydrophobic forces. © 2011 by Walter de Gruyter. Berlin. Boston.
Raghavendra U.,Manipal University India |
Mahesh P.K.,Nano-Mite Technologies, Llc |
Gudigar A.,Nano-Mite Technologies, Llc
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST | Year: 2012
Here an efficient and novel approach was considered as a combination of PCA, LDA and support vector machine. This method consists of three steps: I) dimension reduction using PCA, ii) feature extraction using LDA, iii) classification using SVM. Combination of PCA and LDA is used for improving the capability of LDA when new samples of images are available and SVM is used to reduce misclassification caused by not linearly separable classes. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2012.
Purushotham G.,Nano-Mite Technologies, Llc
IET Conference Publications | Year: 2013
Aluminum silica alloys have wide-spread applications in tribological components such as clutches, cylinder liners & pistons in the automotive industry owing to its relative lightness & good thermal conductivity. The presence of silicon results in reduction of the co-efficient of thermal expansion of aluminum & produces an alloy with good casting machining & corrosion characteristics. Further it is reported that addition of lead, improves the mechanical properties which in turn has profound influence on the mechanical characteristics of Al-Si alloys. Meager information is available as regards the tribological chacterstics & mechanical properties of heat treated Al-Si- Pb alloy. In the light of above the present investigation deals with preparation of cast Al-Si-Pb alloy from LM13 Aluminum alloy for different weight % of Lead followed by heat treatment. Micro structural studies, tensile test, micro hardness tests were conducted to evaluate the mechanical properties of Al-Si-Pb alloy before & after heat treatment. Addition of lead followed by heat treatment has resulted in improved tensile strength, micro hardness of Al-Si alloy.
Nagesh H.R.,Nano-Mite Technologies, Llc |
Bharath Kumar M.,Nano-Mite Technologies, Llc |
Ravinarayana B.,Nano-Mite Technologies, Llc
Communications in Computer and Information Science | Year: 2013
Data mining is the process of extracting interesting and previously unknown patterns and correlations from data stored in Data Base Management Systems (DBMSs). Association Rule Mining is the process of discovering items, which tend to occur together in transactions. Efficient algorithms to mine frequent patterns are crucial to many tasks in data mining. The task of mining association rules consists of two main steps. The first involves finding the set of all frequent itemsets. The second step involves testing and generating all high confidence rules among itemsets. Our paper deals with obtaining both the frequent itemsets as well as generating association rules among them. In this paper we implement the FORC (Fully Organized Candidate Generation) algorithm, which is a constituent of the Viper algorithm for generating our candidates and subsequently our frequent itemsets. Our implementation is an improvement over Apriori, the most common algorithm used for frequent item set mining. © 2013 Springer-Verlag Berlin Heidelberg.
Kanbargi S.G.,Nano-Mite Technologies, Llc |
Sunil Kumar S.,Nano-Mite Technologies, Llc
International Conference on Trends in Automation, Communication and Computing Technologies, I-TACT 2015 | Year: 2015
Our world generating a lot of different kinds of data. These data can be analyzed and processed for valuable information. The traditional systems like data base, which has been used to store and process, are failing to handle these huge data which ranges in tera and peta bytes and also known as Big-data. We have many tools which can be used to analyze Big-Data. The apache's hadoop is one of the most used Big-data analyzing frameworks, Hadoop uses large number of libraries to handle and manage Big-data processes. It also handles different kinds of failures which may occur in the system. It uses map-reduce programing paradigm to analyze, distributed processing and storage of Big-Data. Big-data will be divided in different blocks and distributed within the network. The mapper functions runs in parallel on each block of Big-data and parse it to filter out the required data, which can be used for further processing. The reducer function accepts the data from mapper functions and processes it for required or expected results. It has been observed that, the intermediate data generated by mapper while processing on same Big-Data is always same. Hence, system doing redundant operations and generates same results, which is not an efficient use of resources and it delays the performance speed of the system. The proposed system creates a novel cache, which stores the intermediate data or mapper's output into a novel cache. Whenever the system needs to analyze same Big-data set, It fetches already processed data from novel cache rather than running mapper function on whole Big-data set again. © 2015 IEEE.