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.

Attenuation parameters of polyvinyl alcohol-tungsten oxide composites at the photon energies 5.895, 6.490, 59.54 and 662 keV

Abstract: Abstract The growing demand for lightweight, non-toxic and effective X- and γ-ray shielding materials in various fields has led to the exploration of various polymer composites for shielding applications. In this study, tungsten filled polyvinyl alcohol (PVA) composites of varying WO3 concentrations (0 - 50 wt%) were prepared by solution cast technique. The structural, morphological, and thermal properties of the prepared composite films were studied using X-ray diffraction technique (XRD), Scanning electron microscopy (SEM) and Thermogravimetric analysis (TGA). The AC conductivity studies showed the low conductivity property of the composites. The X-ray (5.895 and 6.490 keV) and γ-ray (59.54 and 662 keV) attenuation studies performed using CdTe and NaI(Tl) detector spectrometers revealed a noticeable increase in shielding efficiency with increase in filler wt%. The effective atomic number (Zeff) calculated by the direct method agreed with the values obtained using Auto-Zeff software. The % heaviness showed that tungsten filled polyvinyl alcohol composites are lighter than traditional shielding materials.

Social performance and sustainability of Indian microfinance institutions: an interrogation

Abstract: This paper has come forward from the research proposal to understand the effect of social performance on the sustainability of microfinance institutions. It has been revealed that the conventional method of assessment of financial institutions is not applicable to the microfinance sector. Performance measurement of microfinance institutions has to be different from that of other financial institutions because of the social aspects involved besides profitability. Social performance has now become part of microfinance business along with business sustainability. Our whole study course is entitled “Effect of social performance on the sustainability of microfinance institutions.” In this paper, we elucidate the topic, find the underrepresented research areas and formulate a research hypothesis for understanding the relationship between social performance and the sustainability of microfinance institutions.

Influence of Product Placements in Films and Television on consumers Brand Awareness

Abstract: Today marketers are hugely making use of product placements in films and television. Product placements are being thought to be more beneficial as they are incorporated in the storyline and therefore this is hard to be missed by the viewers. The objective of the research is to find the reason for people to connect to products, their attitude towards product placements and how this attitude influences their brand awareness and buying. There have been studies before showing why marketers and consumers are preferring product placements over commercial advertisements however this study focusses on the effect of product placements on consumer brand awareness. The data for this research has been collected by a questionnaire that includes questions on general opinion as well as the influence of product placements on Brand awareness. The data has been analyzed using Advance Analytics Methods (Random Forest and Association Analysis). The former method helped in identifying the important factors and later method helped to see the various combination of factors influencing product placements in films and television.

Comparison of Gradient Boosting and Extreme Boosting Ensemble Methods for Webpage Classification

Abstract: Web page classification is an important task in various areas like web content filtering, contextual advertising and maintaining or expanding web directories etc. Machine Learning methods have been found to perform well to classify web pages, and ensemble models have been used to improve the results obtained from single classifiers. The Gradient Boosting and Extreme Boosting ensemble models are used in this work for binary classification. The dataset containing URLs of web pages have been collected manually. The comparison between the two boosting algorithms validated the improvement in accuracy and speed obtained through Extreme boosting. Extreme boosting has been found to be around ten times faster than Gradient boosting and also shows improvement in accuracy. The effect of three preprocessing techniques; lemmatization, stop words removal and regular expressions shows that these preprocessing techniques improves the accuracy of the results but not significantly.