Xavier Institute of Social Service

Ranchi, India

Xavier Institute of Social Service

Ranchi, India
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Kumar A.,Xavier Institute of Social Service
Journal of Evidence-Informed Social Work | Year: 2016

The existing gender analysis frameworks start with a premise that men and women are equal and should be treated equally. These frameworks give emphasis on equal distribution of resources between men and women and believe that this will bring equality which is not always true. Despite equal distribution of resources, women tend to suffer and experience discrimination in many areas of their lives such as the power to control resources within social relationships, and the need for emotional security and reproductive rights within interpersonal relationships. These frameworks believe that patriarchy as an institution plays an important role in women’s oppression, exploitation, and it is a barrier in their empowerment and rights. Thus, some think that by ensuring equal distribution of resources and empowering women economically, institutions like patriarchy can be challenged. These frameworks are based on proposed equality principle which puts men and women in competing roles. Thus, the real equality will never be achieved. Contrary to the existing gender analysis frameworks, the Complementing Gender Analysis framework proposed by the author provides a new approach toward gender analysis which not only recognizes the role of economic empowerment and equal distribution of resources but suggests to incorporate the concept and role of social capital, equity, and doing gender in gender analysis which is based on perceived equity principle, putting men and women in complementing roles that may lead to equality. In this article the author reviews the mainstream gender theories in development from the viewpoint of the complementary roles of gender. This alternative view is argued based on existing literature and an anecdote of observations made by the author. While criticizing the equality theory, the author offers equity theory in resolving the gender conflict by using the concept of social and psychological capital. © Taylor & Francis Group, LLC.


Das R.,Xavier Institute of Social Service | Walia E.,University of Saskatchewan
Neural Computing and Applications | Year: 2017

Managing colossal image datasets with large dimensional hand-crafted features is no more feasible in most of the cases. Content based image classification (CBIC) of these large image datasets calls for the need of dimensionality reduction of features extracted for the purpose. This paper identifies the escalating challenges in the discussed domain and introduces a technique of feature dimension reduction by means of identifying region of interest in a given image with the use of reconstruction errors computed by sparse autoencoders. The automated process identifies the significant regions in an image for feature extraction. It not only improves the dimension of useful features but also contributes to increased classification results compared to earlier approaches. The reduction in number of one kind of features easily makes space for the inclusion of other features whose fusion facilitates improved classification performance compared to individual feature extraction techniques. Two different datasets, i.e. Wang dataset and Corel 5K dataset have been used for the experiments. State-of-the-art classifiers, i.e. Support Vector Machine and Extreme Learning Machine are used for CBIC. The proposed techniques are evaluated and compared in the context of both the classifiers and analysis of results suggests the appropriateness of the proposed methods for real time applications. © 2017 The Natural Computing Applications Forum


Thepade S.,College of Engineering, Pune | Das R.,Xavier Institute of Social Service | Ghosh S.,University of Calcutta
International Journal of Intelligent Computing and Cybernetics | Year: 2017

Purpose: Current practices in data classification and retrieval have experienced a surge in the use of multimedia content. Identification of desired information from the huge image databases has been facing increased complexities for designing an efficient feature extraction process. Conventional approaches of image classification with text-based image annotation have faced assorted limitations due to erroneous interpretation of vocabulary and huge time consumption involved due to manual annotation. Content-based image recognition has emerged as an alternative to combat the aforesaid limitations. However, exploring rich feature content in an image with a single technique has lesser probability of extract meaningful signatures compared to multi-technique feature extraction. Therefore, the purpose of this paper is to explore the possibilities of enhanced content-based image recognition by fusion of classification decision obtained using diverse feature extraction techniques. Design/methodology/approach: Three novel techniques of feature extraction have been introduced in this paper and have been tested with four different classifiers individually. The four classifiers used for performance testing were K nearest neighbor (KNN) classifier, RIDOR classifier, artificial neural network classifier and support vector machine classifier. Thereafter, classification decisions obtained using KNN classifier for different feature extraction techniques have been integrated by Z-score normalization and feature scaling to create fusion-based framework of image recognition. It has been followed by the introduction of a fusion-based retrieval model to validate the retrieval performance with classified query. Earlier works on content-based image identification have adopted fusion-based approach. However, to the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work. Findings: The proposed fusion techniques have successfully outclassed the state-of-the-art techniques in classification and retrieval performances. Four public data sets, namely, Wang data set, Oliva and Torralba (OT-scene) data set, Corel data set and Caltech data set comprising of 22,615 images on the whole are used for the evaluation purpose. Originality/value: To the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work. The novel idea of exploring rich image features by fusion of multiple feature extraction techniques has also encouraged further research on dimensionality reduction of feature vectors for enhanced classification results. © 2017, © Emerald Publishing Limited.


Lucas K.T.,Xavier Institute of Social Service | Jana P.K.,Indian School of Mines
Journal of Supercomputing | Year: 2010

We present two parallel algorithms for finding all the roots of an N-degree polynomial equation on an efficient model of Optoelectronic Transpose Interconnection System (OTIS), called OTIS-2D torus. The parallel algorithms are based on the iterative schemes of Durand-Kerner and Ehrlich methods. We show that the algorithm for the Durand-Kerner method requires (N0.75 + 0.5N0.25 - 1) electronic moves + 2(N0.5 -1) OTIS moves using N processors. The parallel algorithm for Ehrlich method is shown to run in (N0.75 + 0.5N0.25 - 1) electronic moves + 2(N 0.5 - 1) OTIS moves with the same number of processors. The algorithms have lower AT cost than the algorithms presented in Jana (Parallel Comput 32:301-312, 2006). The scalability of the algorithms is also discussed. © 2009 Springer Science+Business Media, LLC.


Lucas K.T.,Xavier Institute of Social Service | Jana P.K.,Indian School of Mines
Parallel Processing Letters | Year: 2010

OTIS (optical transpose interconnection system) is a popular model of optoelectronic parallel computers that has gained enormous attention in the recent years. Several parallel algorithms have been published for many fundamental problems on this architecture. In this paper, first we propose a parallel algorithm for sparse enumeration sort on OTIS-Mesh of Trees (OTIS-MOT). For N (= n2) data elements, our sorting algorithm requires 4 log N$ electronic moves + 3 OTIS moves. We next present a shortest path routing algorithm that runs also in logarithmic time. © 2010 World Scientific Publishing Company.


Thepade S.D.,College of Engineering, Pune | Das R.K.K.,University of Calcutta | Das R.K.K.,Xavier Institute of Social Service | Ghosh S.,University of Calcutta
Communications in Computer and Information Science | Year: 2013

Incredible escalation of Information Technology leads to generation, storage and transfer of enormous information. Easy and round the clock access of data has been made possible by virtue of world wide web. The high capacity storage devices and communication links facilitates the archiving of information in the form of multimedia. This type of information comprises of images in majority and is growing in number by leaps and bounds. But the usefulness of this information will be at stake if maximum information is not retrieved in minimum time. The huge database of information comprising of multiple number of image data is diversified mix in nature. Proper Classification of Image data based on their content is highly applicable in these databases to form limited number of major categories. The novel ternary block truncation coding (Ternary BTC) is proposed in the paper, also the comparison of Binary block truncation coding (Binary BTC) and Ternary Block Truncation Coding is done for image classification. Here two image databases are considered for experimentation. The proposed ternary BTC is found to be better than Binary BTC for image classification as indicated by higher average success rate. © 2013 Springer-Verlag Berlin Heidelberg.


Kumar A.,Xavier Institute of Social Service | Haque Nizamie S.,Central Institute of Psychiatry | Srivastava N.K.,Central Institute of Psychiatry
Mental Health and Prevention | Year: 2013

Violence against women is a serious social and mental health problem and human rights abuse worldwide. It is an extremely complex phenomenon, deeply rooted in gender based power relations, sexuality, self-identity, and social institutions that pose a serious threat to women's mental health. This paper discusses the various factors behind violence against women with some cases and its consequences on women's mental health and wellbeing. The paper suggests that recognizing violence against women as a mental health issue is an essential first step which requires concerted and multi-sector responses backed by strong political commitment aimed at ending discrimination and violence against women. © 2013 Elsevier GmbH.


Kumar A.,Xavier Institute of Social Service | Srivastava K.,Freelance Development Professional
Social Work in Public Health | Year: 2011

The study attempts to find out the existing social and cultural practices regarding menstruation, awareness levels, and the behavioral changes that come about in adolescent girls during menstruation, their perception about menarche, how do they treat it, and the various taboos, norms, and cultural practices associated with menarche. The study was conducted on 117 adolescent girls (age 11-20 years) and 41 mothers from various communities and classes in Ranchi comprising residential colonies and urban slums. The findings unfolds many practices: cultural and social restrictions associated with menstruation, myth, and misconception; the adaptability of the adolescent girls toward it; their reaction, reaction of the family; realization of the importance of menstruation; and the changes that have come in their life after menarche and their resistance to such changes. The article also suggests the strategies to improve menstrual health and hygiene among adolescent girls. The study concludes that cultural and social practices regarding menstruation depend on girls' education, attitude, family environment, culture, and belief. Copyright © Taylor & Francis Group, LLC.


Kumar A.,Xavier Institute of Social Service
Social Work in Public Health | Year: 2012

This article reviews and discusses the problems, responses, and concerns of orphans and vulnerable children in India. The article shows that HIV/AIDS programs and interventions are vital for survival and welfare of orphan and vulnerable children, but they have reached only to a small fraction of the most vulnerable children. The article suggests a number of measures that government and civil society could take to address the problems and emphasizes the need to learn from other countries' experience and initiatives in developing appropriate policy and programmes for orphan and vulnerable children. Copyright © Taylor & Francis Group, LLC.


Lucas K.T.,Xavier Institute of Social Service
Communications in Computer and Information Science | Year: 2010

OTIS (optical transpose interconnection system), as a model of optoelectronic parallel computers, has gained tremendous popularity and is widely accepted among researchers. A rich literature on various parallel algorithms proposed for different OTIS models is available. In this paper, we propose a parallel algorithm for enumeration sort on N-processor OTIS-Hypercube architecture. The first algorithm Sort1 is for sparse enumeration sort of √N data elements. Algorithm Sort2, the second algorithm, is for sorting N data elements on the same architecture. Here, the time complexity of the algorithms are analyzed by the number of data movements required on the electronic links and optical links. The data movements required through electronic link and that required through optical link are expressed as electronic moves and optical moves respectively. The first proposed algorithm, Sort1, requires 4log √N electronic moves and 3 OTIS moves. Sort2, the second algorithm requires √N + (N + 10√N) log √N electronic moves and 3√N OTIS moves. © 2010 Springer-Verlag Berlin Heidelberg.

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