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Enhancing Gender Classification in Social Networks
S. Nalini,K. Sandhya,P. Ganesh Kumar 한국산업정보학회 2014 한국산업정보학회 학술대회논문집 Vol.2014 No.1
Posts in social networking sites are informal, personal writings that people post on their own blog or sites. Nowadays, blogging in Social Networks are an important online activity. With the rapid growth of blogs in Social Network, their value as an important source of information is increasing. A large amount of research work has been devoted to blogs in the Natural Language Processing (NLP) and other communities. There are also many commercial companies that exploit information in blogs to provide value-added services, e.g. search, topic tracking, and sentiment analysis of people’s opinions on products and services. The goal of our system is to identify author gender of posts in social networks coming from a wide variety of source. The dataset used is from the popular social network, Twitter. Using the parts of speech of the dataset the gender of the site user is found. Empirical evaluation using a real-life blog data set shows that these two techniques improve the classification accuracy of the current state-of the-art methods significantly.
I.S.R.Punitha1,,Nalini Bhat3,,K.Rajendran1,,Arun Shirwaikar2,,Annie Shirwaikar1 한국생약학회 2005 Natural Product Sciences Vol.11 No.3
The aqueous extract of Coscinium fenestratum was studied for its antioxidant status in STZ-nicotinamide induced type 2 diabetic rats at two dose levels of 250 mg/kg and 500 mg/kg. At the end of theexperimental period, diabetic rats treated with aqueous extract at both dose levels showed a significant increase insuperoxide dismutase and catalase as compared to the untreated control. Similarly, a significant increase was alsoobserved in the levels of the non enzymatic antioxidants ceruloplasmin, ascorbic acid and tocopherol. The resultssuggest that the aqueous stem extract of C. fenestratum prevents type 2 diabetes mellitus induced oxidative stress.
Monteiro Tanya S.,Nalini R. 한국사회복지학회 2021 Asian Social Work and Policy Review Vol.15 No.2
In India, sanitation work is predominantly undertaken by persons from oppressed castes whose customary roles relegate them to stigmatized occupations. Women sanitation workers, comprising nearly half of the urban workforce, grapple with multiply marginalized identities and social positions. Marginalized at the intersections of caste, gender, and occupation, they contend with violence and socio-economic discrimination. The literature on the occupational and psychosocial risks of sanitation workers indicates that the mental health concerns of women sanitation workers remain largely unaddressed in research and public policy. This paper draws on an analytical review of research on women sanitation workers’ occupational and psychosocial risks with the objective of conceptualizing the relationship between marginalization and mental health. Utilizing intersectionality and social systems theories to present women sanitation workers as a critical case, their experiences of marginalization at the intersections of caste, gender, and occupation are analyzed. Consequently, a conceptual model of mental health outcomes at the intersections of multiply marginalized identities and social positions is developed to analyze the implications of marginalization for mental health. Guidelines for action to inform public policy and social work practice are suggested, emphasizing the need for intersectional interventions and a social justice framework in mental health care for marginalized groups.
V.Saranya,S.Ramya,R.G. Suresh Kumar,T.Nalini 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.3
Cloud computing is a technology in which the Cloud Service Providers (CSP) provide many virtual servers to the users to store their information in the cloud. The faults occurring on the assignment and dismission of the virtual machines, the processing cost in the allocation of resources must also be considered. The parallel processing of the information on the virtual machines must be done effectively and in an efficient manner. A variety of systems were developed to facilitate Many Task Computing (MTC). These systems aim to hide the issues of parallelism and fault tolerant and they are used in many applications. In this paper, we introduced Nephele, a data processing framework to exploit dynamic resource provisioning offered by IaaS clouds. The performance evaluation of the virtual machines has been evaluated and the allocation and de-allocation of job tasks to the specific virtual machines has also been considered. A performance comparison with the well known data processing framework hadoop has been done. Thus this paper tells about the effective and efficient manner of processing the data by parallel processing and allocating the correct resources for the desired task. It also helps to reduce the cost of resource utilization by exploiting the dynamic resource utilization.