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.

Theorizing race, marginalization, and language in the digital media

Abstract: Digitization of the communication medium has transformed the mute, marginalized ‘audience’ into a heterogeneous and credible content ‘producer.’ Drawing on this dynamics and operation of the digital media, it has urged the need to re-theorize ‘marginalization’ and ‘race.’ Hence, this paper critiques the digital-media tool, blogs, using a rhetoric-textual analysis method and critical discourse analysis method for the fictional text, Americanah. These methods employ the psychoanalytical-Althusserian critique of Adichie’s fictional narrative, Americanah. In the psychoanalytical sense, blog-writing can qualify as a mechanism of ‘sublimation’ in the post-modern world. In the Althusserian sense, blogs become persuasive mechanisms for a subject’s interpellation into non-dominant ideology. Among the plethora of marginalized global communities, African-Americans are enormously embracing the virtual communication trends for socio-political motives. This paper theorizes the correlations between race-related blogging, psychoanalytic sublimation, and the socio-political repudiation of power structure by employing the literary text as material evidence. Accordingly, the literary study has concluded that digital-mediums (i.e., in this case, political blogs) can depose the power vested in the ideological-state-apparatuses and impose a high potential for expression of unrestrained, credible, and democratic voice of the marginalized. It also validates that blogs/blogging influences and moulds national/political/racial discourses by lending a liberated voice and context-independent perspective to the racially oppressed.

Status of the Elderly and Emergence of Old Age Homes in India

Abstract: There has been a rapid ageing of the earth's population and in a few decades, Asia could become the oldest region in the world. In India, due to the reorganization of the family system, the traditional joint family system is on the decline. Due to the emergence of the nuclear family and the high cost of living, family members who previously cared for the elderly need to find employment outside the home. A rapid increase in nuclear families and an exceptional increase in the number of ‘older adults’ in the country have compelled them to live in old age homes. Literature has accentuated the difficulties and apprehensions experienced by older adults during the ageing process and the need for old age homes in order to create an environment that fosters a meaningful existence for them in their twilight years. India's old age homes are trying to uphold the needs, desires and values of older adults. There is a lack of studies that attempt to give older adults a chance to communicate their experiences in a care home. Older adults are an invaluable resource for younger generations and change is needed in society's attitude towards ageing. This review can help psychologists, social workers and caregivers gain insight into the needs of older adults in terms of mental wellbeing, economic and social security and elder abuse and create awareness among the people. Int. J. Soc. Sc. Manage. Vol. 5, Issue-1: 1-4

Friedman and Wilcoxon Evaluations Comparing SVM, Bagging, Boosting, K-NN and Decision Tree Classifiers

Abstract: Abstract This paper describes a number of experiments to compare and validate the performance of machine learning classifiers. Creating machine learning models for data with wide varieties has huge applications in predictive modelling across multiple domain of science. This work reviews state of the art techniques in machine learning classifiers methods with several extent of magnitude in statistics and key findings that will be helpful in establishing best methodological practices for class predictions. Comprehensive comparative review analysis with statistical validations for various machine learning algorithm for SVM, Bagging, Boosting, Decision Trees and Nearest Neighborhood algorithm on multiple data sets is carried out. Focus on the statistical analysis of the results using Friedman-Test and Wilcoxon Test as well as other interpretative metrics like classification rate, ROC, F-measure are evaluated to benchmark results.