Gandhi Institute of Technology and Management

About: Gandhi Institute of Technology and Management is a education organization based out in Visakhapatnam, Andhra Pradesh, India. It is known for research contribution in the topics: Computer science & Heat transfer. The organization has 3392 authors who have published 4043 publications receiving 29139 citations. The organization is also known as: GITAM & GITAM College.

Significance of nanoparticle’s radius, heat flux due to concentration gradient, and mass flux due to temperature gradient: The case of Water conveying copper nanoparticles

Abstract: The performance of copper selenide and effectiveness of chemical catalytic reactors are dependent on an inclined magnetic field, the nature of the chemical reaction, introduction of space heat source, changes in both distributions of temperature and concentration of nanofluids. This report presents the significance of increasing radius of nanoparticles, energy flux due to the concentration gradient, and mass flux due to the temperature gradient in the dynamics of the fluid subject to inclined magnetic strength is presented. The non-dimensionalization and parameterization of the dimensional governing equation were obtained by introducing suitable similarity variables. Thereafter, the numerical solutions were obtained through shooting techniques together with 4th order Runge-Kutta Scheme and MATLAB in-built bvp4c package. It was concluded that at all the levels of energy flux due to concentration gradient, reduction in the viscosity of water-based nanofluid due to a higher radius of copper nanoparticles causes an enhancement of the velocity. The emergence of both energy flux and mass flux due to gradients in concentration and temperature affect the distribution of temperature and concentration at the free stream.

Thyroid disease diagnosis via hybrid architecture composing rough data sets theory and machine learning algorithms

Abstract: This work is a hybrid architecture design furnished successfully using artificial intelligence techniques, rough data sets theory and machine learning algorithms. The purpose of this work is to bring the spotless and smart approach in identifying the thyroid disease in a human. There are several mechanisms implemented on thyroid data sets which produced astonished outcomes, but the data considered for the thyroid disease diagnoses (TDD) is inconsistent, redundant and consists of missing attribute values as per my literature survey. The proposed work is to construct an expert advisory system of hybrid architecture, which is to determine the optimistic disease growth because of the thyroid gland. A string matching system (SMS) was at the outset developed, which can predict the actual TDD based on the knowledge available. If the SMS fails, an individual approaches using artificial bee colony optimization and particle swarm optimization are developed to achieve the accuracy of results appreciating the measure values as 65 and 93 %, but the results obtained using the above said approaches are calculated using some missed attribute values which are not included in the knowledge likewise left blank and hence the proposed work continues to first generate the missing attribute value in the knowledge by using rough data sets theory and the obtained data (missed attribute values) is given to predict optimistic disease along with its prevention and its curing methods. However, the data generated cannot predict the optimal disease and hence it is proposed to use a machine learning algorithm so that, obtained result is hygienic. The knowledge for implementation of this work is gathered from Intelligent System Laboratory of K.N. Toosi University of Technology, Imam Khomeini Hospital. A questionnaire form is developed for providing an interface for user so they can contribute the data.

Evaluation of Anti-Inflammatory Properties of Isoorientin Isolated from Tubers of Pueraria tuberosa

Abstract: Inflammation is the major causative factor of different diseases such as cardiovascular disease, diabetes, obesity, osteoporosis, rheumatoid arthritis, inflammatory bowel disease, and cancer. Anti-inflammatory drugs are often the first step of treatment in many of these diseases. The present study is aimed at evaluating the anti-inflammatory properties of isoorientin, a selective cyclooxygenase-2 (COX-2) inhibitor isolated from the tubers of Pueraria tuberosa, in vitro on mouse macrophage cell line (RAW 264.7) and in vivo on mouse paw edema and air pouch models of inflammation. Isoorientin reduced inflammation in RAW 264.7 cell line in vitro and carrageenan induced inflammatory animal model systems in vivo. Cellular infiltration into pouch tissue was reduced in isoorientin treated mice compared to carrageenan treated mice. Isoorientin treated RAW 264.7 cells and animals showed reduced expression of inflammatory proteins like COX-2, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), 5-lipoxygenase (5-LOX), and interleukin 1-β (IL-1-β) both in vitro and in vivo. The antioxidant enzyme levels of catalase and GST were markedly increased in isoorientin treated mice compared to carrageenan treated mice. These results suggest that isoorientin, a selective inhibitor of COX-2, not only exerts anti-inflammatory effects in LPS induced RAW cells and carrageenan induced inflammatory model systems but also exhibits potent antioxidant properties.