Christ University

About: Christ University is a education organization based out in Bengaluru, India. It is known for research contribution in the topics: Computer science & Convection. The organization has 2267 authors who have published 2715 publications receiving 14575 citations. The organization is also known as: Christ College & Christ University.

Role of Infrared Spectroscopy in Coal Analysis—An Investigation

Abstract: Fourier transform infrared (FT-IR) spectroscopy is a widely used analytical technique for determining the different functional groups of a coal structure. This method, being able to reveal carbo-hydrogenated structures (aromatic and aliphatic) and heteroatomic functions (mainly oxygenated), as well as to detect the presence of minerals, is currently one of the most powerful techniques for coal characterization and thus is of paramount importance in the various utilization procedures of coal (industrial combustion, coke production processes, etc.). FT-IR study shows the presence of aliphatic -CH, -CH2 and -CH3 groups, aliphatic C-O-C stretching associated with -OH and -NH stretching vibrations and HCC rocking. It is conjectured that, the two-stage leaching using HNO3 followed by HF remarkably reduced the ash content as well as the minerals including Al, Si and Ca. The solubilization of samples with buffered EDTA could not eliminate the minerals in coal. The silicate and kaolinite bands showed a systematic lowering on EDTA and carboxylic acid treatment. The fungal leaching was most beneficial for aromatic molecules with different degrees of substitution. The intensity of bands due to carbonyl groups was increased, when treated with fungi, whereas that due to oxygen functional groups showed a reverse trend. The mineral bands due to silicates also decreased in intensity, on post treatment with fungal culture.

Radiated flow of chemically reacting nanoliquid with an induced magnetic field across a permeable vertical plate

Abstract: Impact of induced magnetic field over a flat porous plate by utilizing incompressible water-copper nanoliquid is examined analytically. Flow is supposed to be laminar, steady and two-dimensional. The plate is subjected to a regular free stream velocity as well as suction velocity. Flow formulation is developed by considering Maxwell–Garnetts (MG) and Brinkman models of nanoliquid. Impacts of thermal radiation, viscous dissipation, temperature dependent heat source/sink and first order chemical reaction are also retained. The subjected non-linear problems are non-dimensionalized and analytic solutions are presented via series expansion method. The graphs are plotted to analyze the influence of pertinent parameters on flow, magnetism, heat and mass transfer fields as well as friction factor, current density, Nusselt and Sherwood numbers. It is found that friction factor at the plate is more for larger magnetic Prandtl number. Also the rate of heat transfer decayed with increasing nanoparticles volume fraction and the strength of magnetism.

Nonlinear convective and radiated flow of Tangent Hyperbolic liquid due to stretched surface with convective condition

Abstract: The current study compacts with effect of nonlinear convection and radiation on tangent hyperbolic fluid flow of through a convectively heated vertical surface. The converted set of boundary layer equations are solved numerically by Runge-Kutta-Fehlberg method. The effect of various pertinent parameters on flow and heat transfer characteristics are discussed with tabulated numerical values and deliberate figures. Additionally, the skin friction coefficient and Nusselt number are also presented. We noticed that, the skin friction factor and heat transfer rates are higher in presence of nonlinear convection than its absence. Further, velocity profile decreases by increasing power law index but establishes opposite results for skin friction.

Auto-Diagnosis of COVID-19 Using Lung CT Images With Semi-Supervised Shallow Learning Network

Abstract: In the current world pandemic situation, the contagious Novel Coronavirus Disease 2019 (COVID-19) has raised a real threat to human lives owing to infection on lung cells and human respiratory systems. It is a daunting task for the researchers to find suitable infection patterns on lung CT images for automated diagnosis of COVID-19. A novel integrated semi-supervised shallow neural network framework comprising a Parallel Quantum-Inspired Self-supervised Network (PQIS-Net) for automatic segmentation of lung CT images followed by Fully Connected (FC) layers, is proposed in this article. The proposed PQIS-Net model is aimed at providing fully automated segmentation of lung CT slices without incorporating pre-trained convolutional neural network based models. A parallel trinity of layered structure of quantum bits are interconnected using an $\mathcal {N}$ -connected second order neighborhood-based topology in the suggested PQIS-Net architecture for segmentation of lung CT slices with wide variations of local intensities. A random patch-based classification on PQIS-Net segmented slices is incorporated at the classification layers of the suggested semi-supervised shallow neural network framework. Intensive experiments have been conducted using three publicly available data sets, one for purely segmentation task and the other two for classification (COVID-19 diagnosis). The experimental outcome on segmentation of CT slices using self-supervised PQIS-Net and the diagnosis efficiency (Accuracy, Precision and AUC) of the integrated semi-supervised shallow framework is found to be promising. The proposed model is also found to be superior than the best state-of-the-art techniques and pre-trained convolutional neural network-based models, specially in COVID-19 and Mycoplasma Pneumonia (MP) screening.