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My Motherhood, My Way: A Sociological Study of Contemporary Employed Mothers in Kolkata
Motherhood in India has been understood primarily by placing mothers in the domestic space. A mother is constructed as a protector and the complete caregiver of her children. But there have been significant changes in the status of Indian women recently. In the 21st century, with suitable qualifications and employment opportunities, women have the choice to be economically independent and career-driven, which has a profound impact on their roles and responsibilities as protectors and caregivers in the home. It is essential to study and document how women in this generation have started to redefine their roles and negotiate what a mothers duties are at home. This study aims to make a systematic inquiry to understand the issues and challenges faced by employed mothers in everyday life and how they balance their career and childcare activities. Researchers investigate this through a qualitative study on mothers employed in different types of professions in the city of Kolkata. Data was collected by conducting in-depth interviews of around twenty-nine urban, upper-middle class employed mothers from different professional backgrounds to have a set of diverse narratives about their experiences and struggles. The key findings of this study provide an insight into the challenges that mothers face and their balancing mechanisms. Such studies have the scope to motivate many employed mothers by presenting some cases of women who have succeeded in breaking the stereotypical ideas of motherhood and are redefining their stories in more humane terms. 2021. Journal of International Womens Studies. -
Linkage between enterpreneurial orientation and export performance of South Asian countries
Purpose: South Asian economies has witnessed export dependence over the past several years and the dependence has increased manifold. Export performance is the most preferred modes of internationalisation in developing economies as it is directly linked to getting access to international markets with limited resources and capabilities thereby contributing to the economic productivity of the country. This paper examines co-integration between the export performance and entrepreneurial orientation in South Asian nations explaining it as the main enabler of export. Entrepreneurial Orientation has been considered an important criterion for promoting export as EO requires innovation, proactiveness and risk taking which provides competitive advantage to enterprises. Design/Methodology/Approach: The research employed an econometric panel cointegration investigation to analyse the long run relationship of economic orientation and export performance among these nations. Findings: The research confirmed positive long run causality between the innovativeness, proactiveness and risk taking as three dimensions of entrepreneurial orientation and export concentration ratio as an indicator for export performance among South Asian nations. So, if these developing nations continue to diversify their product & market mix in exporting products and services the concentration ratio would improve that would result in growing further economic productivity. Practical implications: This research will serve as an aid to policy makers and entrepreneurs of South Asian nations to focus on the diverse mix of variety of products, services and markets to help South Asian nations prosper. Originality/Value: The policy makers and entrepreneurs of South Asian nations have accorded high priority to export performance. This research is one of the few studies that highlights access to EO as the basis for better export performance of South Asian nations. 2021, Allied Business Academies. All rights reserved. -
A multilevel analysis of hiv1-miR-H1 miRNA using KPCA, K-means, Random Forest and online target tools
The goal of this study was to propose a workflow using machine learning to identify and predict the miRNA targets of Human Immunodeficiency virus 1. miRNAs which is ~21 nt long are attained from larger hairpin RNA precursors and is maintained in the secondary structure of their precursor relatively than in primary chain of successions. The proposition approach for identification and prediction of miRNA targets in hiv1-miR-H1is based on secondary structure and E-value through machine learning. Data Linearity of Length and e-value for sequence match with hiv1-mir-H1 is verified using Kernel PCA. miRNA targets were grouped into clusters thereby indicating similar targets using K-means algorithm. Classification model using Random Forest was implemented regards to each secondary features variable considering feature relevance. A learning methodology is put forward that assimilate and integrate the score returned by various machine learning algorithms to predict cellular hiv1-miR-H1 targets. Gene targets results using TargetScan, miRanda, PITA, DIANA microT and RNAhybrid are also explored for multiple parameters. 2021 Inderscience Enterprises Ltd. -
Solar pv tree: Shade-free design and cost analysis considering Indian scenario
In this paper, the performance and the cost-effectiveness of a solar PV tree for supplying the energy demand of a flood lighting system at a basketball court in the School of Engineering and Technology, Christ (Deemed to be University) at Bangalore, India, are analyzed. Also, the energy demand of a flood lighting system for year 2017 is estimated (16 kWh/day), and the design of 4 individual trees of 1 kWp each is proposed, which saves around 40 sq.m area of land near to the basketball court. The experimental data was collected from June 1st, 2018 to May 31st, 2019, using a data acquisition system and processed to calculate the monthly cost of energy produced by each tree. In order to reduce the complexity in design and allow it to be shade-free, all the panels of a tree were oriented at the same azimuth angle. Based on technical and economical assessments with respect to rooftop systems, the solar PV tree presented reasonable results and could be a future adoptable technology for high population density areas, as well as for remote applications. Later, the adoptability of the proposed solar PV tree was simulated for 2 kWp, considering the climatic conditions of 2020, for different rural and urban locations of India. From the techno-economic-environmental analysis, it is highlighted that the annual energy yield is more with the solar PV tree model than with a land-mounted SPV system. The cost savings and greenhouse gas (GHG) reduction are also higher with the proposed oak tree-based solar PV tree in urban areas than in rural areas recommending it for practical applications. 2021, Walailak University. All rights reserved. -
Social groupwork for promoting psychological well-being of adolescents enrolled in sponsorship programs
Background: The dearth of data on adolescents highlighted in the UN's data disaggregation against the agenda 'no one left behind' calls for research on 'the second decade'. Moreover, India is a country with the world's largest adolescent population, and as such, studies and policies for developing competencies of adolescents are crucial to the country's development; interventions instilling confidence to aspire to a better future in underprivileged adolescents are vital to mitigate inequity. Methods: This intervention study adopted a quasi-experimental design to measure the effectiveness of social groupwork in raising the psychological well-being of adolescents in child sponsorship programs in Kerala. Forty adolescents from a Child Sponsorship Program (CSP) center in Kochi were recruited for the study. Those suggested by the CSP center considering their poor academic performance and behavior problems were allocated to the intervention group and the rest to the comparison group. The intervention was designed in response to the information garnered through a preliminary study and administered to the intervention group (n=20). We conducted pre-test and post-test for both the intervention group and comparison group (n=20). Results: Comparison between pre- and post-measurements carried out using paired sample t-test for the intervention group and comparison group separately gave a p-value of <0.05 for the intervention group and >0.05 for the comparison group. Thus, it was proved that psychological well-being of participants in the intervention group was raised significantly due to the social group work intervention. Conclusions: Applying refined granularity, this research adds data specifically on adolescents enrolled in child sponsorship programs and sets a blueprint for social groupwork to improve their psychological well-being. Proposing a conceptual framework for child sponsorship programs, this study recommends further research in all aspects of its functioning, and interventions at group, family, and community levels, for the well-being and empowerment of marginalized adolescents. 2021 Joseph S and Karalam DSRB. -
Crime analysis and forecasting on spatio temporal news feed dataan indian context
Social media is a platform where people communicate, interact, share ideas, interest in careers, photos, videos, etc. The study says that social media provides an opportunity to observe human behavioral traits, spatial and temporal relationships. Based on study Crime analysis using social media data such as Facebook, Newsfeed articles, Twitter, etc. is becoming one of the emerging areas of research across the world. Using spatial and temporal relationships of social media data, it is possible to extract useful data to analyse criminal activities. The research focuses on implementing textual data analytics by collecting the data from different news feeds and provides visualization. This researchs motivation was identified based on relevant work from different social media crime and Indian government crime statistics. This article focuses on 68 types of different crime keywords for identifying the type of crime. Nae Bayes classification algorithm is used to classify the crime into subcategories of classes with geographical factors, and temporal factors from RSS feeds. Mallet package is used for extracting the keywords from the news-feeds. K-means algorithm is used to identify the hotspots in the crime locations. KDE algorithm is used to identify the density of crime, and also our approach has overcome the challenges in the existing KDE algorithm. The outcome of research validated the proposed crime prediction model with that of the ARIMA model and found equivalent prediction performance. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. -
Creating inclusive spaces in virtual classroom sessions during the COVID pandemic: An exploratory study of primary class teachers in India
The research paper reports insights into the primary class teachers experiences and inclusive methodologies in India during virtual class sessions. Teaching online during the COVID pandemic has turned out to be an adaptive and transformative challenge for teachers. Though Indian teachers are used to the chalk-and-talk method, an online setup has compelled them to discover innovative strategies to maintain an inclusive classroom. It was found that teachers are using puppetry, storytelling, energizers, ice-breakers in their sessions to make it engaging. An in-depth study was undertaken to understand the experiences of five primary class teachers from private schools in India. Data thus collected were analyzed qualitatively. The study results demonstrated that the teachers had improved professionally they have become independent in using the internet and exploring new ways of teaching them per their needs. Nevertheless, it was also found that the schools lack support, fear among the teachers of being asked to quit the job, blocking students from the online class if they fail to pay the fees, and exorbitant salary cuts. The challenges related to young students were - lack of proper resources for online sessions, low attention span, technical distractions, lack of physical development, excessive interference of the parents and lack of socialization. The paper concludes with policy proposals regarding standardized online education platforms and provisions for proper resources for virtual class sessions to marginalized families to minimize India's digital divide. 2021 -
A succinct analysis for deep learning in deep vision and its applications
Introduction: Deep learning methodologies can achieve forefront results on testing deep vision issues, for instance, picture portrayal, an object area, face affirmation, Natural Language Processing, Visual Data Processing and online life examination. ConvNet, Stochastic Hopfield network with hidden units, generative graphical model and sort of artificial neural network castoff to absorb competent information coding in an unproven way are deep learning plans used in deep vision issues. Objection: This paper gives a succinct survey of without a doubt the most critical Deep learning structures. Deep vision assignments, for instance, object revelation, face affirmation, Natural Language Processing, Visual Data Processing, web-based life examination and their utilization of this task are discussed with a short record of the historic structure, central focuses and impairments. Future headings in arranging Deep learning structures for Deep vision issues and the troubles included are analysed. Method: This paper consists of surveys. In Section two, Deep Learning Approaches and Changes are audited. In section three, we tend to portray the uses of Applications of deep learning in deep vision. In Section four, Deep learning challenges and directions are mentioned. At long last, Section five completes the paper with an outline of the results. Results and Conclusion: Though deep learning can recall a huge proportion of data and info, its feeble cognitive and perception of the data makes it a disclosure answer for certain applications. Deep learning despite everything encounters issues in showing various erratic facts modalities at the equal period. Multimodal profound learning is an extra notable heading in progressing deep learning research. IJCRR. -
Development and validation of multi-dimensional scale of grit
Positive psychology nurtures the potent qualities of individuals and aids them in carving a niche for themselves. Based on this theoretical foundation, a non-cognitive trait-like grit plays an imperative role in attaining high achievement. Previous studies have identified three dimensions of grit: perseverance of effort, consistency of interest and adaptability to situations. Recent research has criticized the dimension consistency of interest in a collectivist context. The present study provides an account of grit in view of eastern perspectives to check the suitability of the construct in India. Current findings provide a framework for the development and validation of Multi-Dimensional Scale of Grit reveals four dimensions of grit, namely, adaptability to situation, perseverance of effort, spirited initiative and steadfastness in adverse situations. It also provides an insight regarding the duration of goal attainment with respect to grit. The research conducted over three studies included Indian university students to develop and examine the psychometric properties of grit. Study 1 focused on item analysis and development of the factor structure through exploratory factor analysis. Study 2 confirmed the previously obtained factor structure through confirmatory factor analysis. In study 3, the psychometric properties of the scale were measured through test-retest reliability and validity, criterion, convergent and divergent. Results indicated that Multi-Dimensional Scale of Grit is a reliable and valid measure. It also indicated that the obtained 12 items and four dimensions were in synchronization with the relevant eastern perspective. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Properties of high strength concrete with reduced amount of Portland cement a case study
In the last 15years Bangalore city has systematically modernized its concrete production process with the help of ready-mix concrete (RMC) facility. However, one of the present requirements of these facilities is to lower its carbon footprint by reducing consumption of Portland cement in the concrete production process. Further, the demand for high-strength concrete (HSC) has increased due to construction of high-rise buildings and other major infrastructure projects in the urban areas of the city. Therefore, this study presents the experimental test results of HSC mixes proportioned with reduced consumption of Portland cement. Four types of concrete mixes with 50% of Portland cement replaced by ground granulated blast furnace slag (GGBS) were considered. Additionally, two control mixes without GGBS replacement were also tested. Fresh, hardened, and durability properties of all the mixes were experimental determined and presented. The results showed that concrete mixes proportioned with 50% GGBS obtained a maximum 28-day compressive strength of 77 MPa. Further, all the mixes with GGBS exhibited superior durability properties when compared to control mixes. Thus, concrete mixes with 50% GGBS replaced for Portland cement are favourable for producing HSC at RMC facilities at Bangalore city. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Overt dependence of health insurance industry on healthcare system
A vast majority of the population in the developing economies remains uninsured. Moreover, the informal sector that employs a larger section of the society is untouched by any of the government scheme. In this study, we use health belief model to examine the factors that induce willingness to buy health insurance among the illness and the non-illness group. A cross-sectional study was conducted on 1,339 participants above 20 years of age of which 351 had contracted illness in the past and 988 had not. Data was collected using questionnaire from four highly populated districts in India. The questionnaire was developed based on the constructs of health belief model. The data was statistically analysed. Kendalls Tau-b correlation technique was used to explore the relationship between perceived vulnerability and product aversion. Logistic regression was used to find out the odds at which each independent variable, categorised based on the health belief model, contributes to willingness to buy. The model was able to predict 15% of the variance for willingness-to-buy among the illness and 27% among the non-illness groups. Findings suggest that the perceived vulnerability reduced product aversion among the illness group. Mere presence of primary and super-specialty hospitals was not sufficient for the illness group to subscribe for health insurance. Income perceptions emerged as a significant predictor among the illness group. Presence of well-established hospital, income perceptions, and subjective norms were significant predictors among the non-illness group. The growth of the health insurance industry largely depends upon the presence of well-established hospitals. In the absence of adequate healthcare facilities, attempts by the insurers to promote insurance covers will become futile. Insurers should also consider alternate segmentation patterns albeit the present socio-demographic pattern, as the health risk experience differs among individuals. Asian Academy of Management and Penerbit Universiti Sains Malaysia, 2021. -
Design and Evaluation of Wi-Fi Offloading Mechanism in Heterogeneous Networks
In recent years, WiFi offloading provides a potential solution for improving ad hoc network performance along with cellular network. This paper reviews the different offloading techniques that are implemented in various applications. In disaster management applications, the cellular network is not optimal for existing case studies because the lack of infrastructure. MANET Wi-Fi offloading (MWO) is one of the potential solutions for offloading cellular traffic. This word combines the cellular network with mobile ad hoc network by implementing the technique of Wi-Fi offloading. Based on the applications requirements the offloading techniques implemented into mobile-to-mobile (M-M), mobile-to-cellular (M-C), mobile-to-AP (M-AP). It serves more reliability, congestion eliminated, increasing data rate, and high network performance. The authors also identified the issue while implementing the offloading techniques in network. Finally, this paper achieved the better performance results compared to existing approaches implemented in disaster management. Copyright 2021, IGI Global. -
Highly luminescent ZnS:Mn quantum dots capped with aloe vera extract
This study demonstrates the optical properties of ZnS:Mn2+ qquantum dots synthesized by simple and eco-friendly chemical precipitation method using aloe vera (AV) extract as the stabilizing agent. The nanoparticles have been characterized by transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy, diffuse reflectance spectroscopy (DRS), photoluminescence (PL) and time-resolved PL spectroscopy. Increase in band gap energy with decrease in particle size was observed from DRS studies due to quantum confinement effect. Dominant yellow emission was observed from characteristic 4T1?6A1 transitions of the Mn2+ions in the ZnS:Mn/AV nanoparticles. The results provide insight to the quantum confinement effect that occur and how it affect decay life time of the ZnS:Mn2+/AV nanoparticles. 2020 Elsevier Ltd -
Grey Wolf optimization-Elman neural network model for stock price prediction
Over the past two decades, assessing future price of stock market has been a very active area of research in financial world. Stock price always fluctuates due to many variables. Thus, an accurate prediction of stock price can be considered as a tough task. This study intends to design an efficient model for predicting future price of stock market using technical indicators derived from historical data and natural inspired algorithm. The model adopts Elman neural network (ENN) because of its ability to memorize the past information, which is suitable for solving stock problems. Trial and error-based method is widely used to determine the parameters of ENN. It is a time-consuming task. To address such an issue, this study employs Grey Wolf optimization (GWO) algorithm to optimize the parameters of ENN. Optimized ENN is utilized to predict the future price of stock data in 1day advance. To evaluate the prediction efficiency, proposed model is tested on NYSE and NASDAQ stock data. The efficacy of the proposed model is compared with other benchmark models such as FPA-ELM, PSO-MLP, PSOElman,CSO-ARMA and GA-LSTM to prove its superiority. Results demonstrated that the GWO-ENN model provides accurate prediction for 1day ahead prediction and outperforms the benchmark models taken for comparison. 2020, Springer-Verlag GmbH Germany, part of Springer Nature. -
IoT-based smart alert system for drowsy driver detection
In current years, drowsy driver detection is the most necessary procedure to prevent any road accidents, probably worldwide. The aim of this study was to construct a smart alert technique for building intelligent vehicles that can automatically avoid drowsy driver impairment. But drowsiness is a natural phenomenon in the human body that happens due to different factors. Hence, it is required to design a robust alert system to avoid the cause of the mishap. In this proposed paper, we address a drowsy driver alert system that has been developed using such a technique in which the Video Stream Processing (VSP) is analyzed by eye blink concept through an Eye Aspect Ratio (EAR) and Euclidean distance of the eye. Face landmark algorithm is also used as a proper way to eye detection. When the drivers fatigue is detected, the IoT module issues a warning message along with impact of collision and location information, thereby alerting with the help of a voice speaking through the Raspberry Pi monitoring system. Copyright 2021 Anil Kumar Biswal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. -
Total domination coloring of graphs
A total domination coloring of a graph G is a proper coloring of G in which open neighbourhood of each vertex contains at least one color class and each color class is dominated by at least one vertex. The minimum number of colors required for a total domination coloring of G is called the total domination chromatic number of G and is denoted by ctd(G). In this paper, we study the total domination chromatic number of some graph classes. The bounds of total domination chromatic number with respect to the graph parameters such as the domination number, chromatic number, total dominator chromatic number and total domination number are also studied. 2021 the author(s). -
Structure-based virtual screening, pharmacokinetic prediction, molecular dynamics studies for the identification of novel EGFR inhibitors in breast cancer
Breast cancer is one of the most prevalent malignancy cancer types especially affecting women globally. EGFR is a proto onco gene as well as the first identified tyrosine kinase receptor. It plays a dynamic role in many biological tasks such as apoptosis, cell cycle progression, differentiation, development and transcription. Somatic mutation in the EGFR kinase domain derails the normal kinase activity and over expression leads to the progression of cancer especially breast cancer. EGFR is one of the well-known therapeutic targets for breast cancer. In this scenario, we attempt to identify novel potent inhibitors of EGFR. Initially, we performed structure-based virtual screening and identified four potential compounds effective against EGFR. Further, the compounds were subjected to ADME prediction as part of evaluation of the druggability and all the four compounds found to fall under satisfactory range with predicted pharmacokinetic properties. Eventually, the conformational stability of proteinligand complex was analyzed at different time scale by using Gromacs software. Molecular dynamics simulation run of 20 ns is carried out and results were analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF) to signify the stability of proteinigand complex. The stability of the proteinligand complex is more stable throughout entire simulation. From the results obtained from in silico studies, we propose that these compounds are exceptionally useful for further lead optimization and drug development. Communicated by Ramaswamy H. Sarma. 2020 Informa UK Limited, trading as Taylor & Francis Group. -
Factors Influencing Association of Intermediaries in the Supply Chain of Consumer Healthcare Brands
Purpose: The rural market in India provides tremendous scope for FMCG consumer healthcare companies to market their products because of a significant increase of rural purchasing power. Many empirical studies in this area highlight the challenges and opportunities for marketers in the FMCG space. Research articles are not in abundance to understand intermediaries' expectations in the supply chain specific to consumer healthcare products. The existing literature did not significantly address the challenges of channel partners in the rural market. The present study aims to determine the retailer expectations from manufacturers and channel members' mutual expectations in the FMCG distribution channel. Research design and Methodology: The present study adopted a qualitative research methodology. Fifty respondents from each level of distribution channel such as super-stockist, distributors and retailers in central India were identified and an interview method was adopted to collect the data. Results: Nineteen factors were identified to influence the intermediaries for involvement in the business with any FMCG brand. Factors like Profit margin, reverse logistics, credit terms, return on investment, timely payments were crucial for managing the expectations of all intermediaries. This study provides academic as well as practical implications in terms of enabling the industry to align its channel management strategies accordingly 2021 The Author(s) A. S. Suresh. All Rights Reserved. -
Sustainable tourism development in the backwaters of South Kerala, India: The local government perspective
Improper waste management continues to be a major challenge in the backwater destinations of South Kerala, India and the local government has been identified as a key player having a strong influence on sustainable tourism development initiatives in the destination. The study examines the major obstacles encountered while implementing sustainable tourism development practices in the backwater destinations of South Kerala, India. Qualitative data collected with the support of semi-structured interviews with top government officials of the Tourism Industry is used for the study. The findings from the study show that improper waste management affects sustainable tourism development in the backwater destinations, and that community involvement and community support are pre-requisites for implementing solid waste management practices in the backwater destinations of the state. The study also enlightens the roles of various stakeholders in waste management so as to develop a strong perspective of sustainable tourism development in the region. 2020 Editura Universitatii din Oradea. All rights reserved. -
How well the log periodic power law works in an emerging stock market?
A growing body of research work on Log Periodic Power Law (LPPL) tries to predict market bubbles and crashes. Mostly, the fitment parameters remain con?ned within certain specific ranges. This paper examines these claims and the robustness of the reformulated LPPL model of Filimonov & Sornette (2013) for capturing large falls in the S&P BSE Sensex, an Indian heavyweight index over the period 20002019. Thirty-five mid to large-sized crashes are identified during this period, forming a clear LPPL signature. This confirms the possibility to predict the embedded risk of future uncertain events in the Indian stock market with the LPPL approach. 2020 Informa UK Limited, trading as Taylor & Francis Group.