Big Data for Educational Applications in the Urban Indian Context

The booming development of data science and big data technology stacks has inspired continuous iterative updates of data science research or working methods. At present, the granularity of the labor division between data science and big data is more refined. Traditional work methods, from work infrastructure environment construction to data modelling and analysis of working methods, will greatly delay work and research efficiency. In this paper, we focus on the purpose of the current friendly collaboration of the data science team to build data science and big data analysis application platform based on microservices architecture for education or nonprofessional research field. In the environment based on microservices that facilitates updating the components of each component, the platform has a personal code experiment environment that integrates JupyterHub based on Spark and HDFS for multiuser use and a visualized modelling tools which follow the modular design of data science engineering based on Greenplum in-database analysis. The entire web service system is developed based on spring boot.

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Assessments of Health Impacts of Transportation Projects in an Urban Indian Context

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2452-10 ◽

2014 ◽

Vol 2452 (1) ◽

pp. 81-89 ◽

Cited By ~ 3

Author(s):

Veronica Conti ◽

Anjali Mahendra

Keyword(s):

Health Impacts ◽

Transportation Projects ◽

Indian Context ◽

Urban Indian

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Modelling Service Quality Offered by Signalized Intersections from Automobile Users’ Perspective in Urban Indian Context

Transportation Research Procedia ◽

10.1016/j.trpro.2020.08.109 ◽

2020 ◽

Vol 48 ◽

pp. 904-922

Author(s):

Manaswinee Kar ◽

Suprava Jena ◽

Abhishek Chakraborty ◽

Prasanta Kumar Bhuyan

Keyword(s):

Service Quality ◽

Signalized Intersections ◽

Indian Context ◽

Urban Indian

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Study of Analysing and Processing of Big Data by Organizations in Indian Context

International Journal for Research in Engineering Application & Management ◽

10.35291/2454-9150.2020.0324 ◽

2020 ◽

pp. 413-417

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Future Research ◽

Business Organization ◽

Indian Context ◽

Huge Data ◽

Enormous Amount ◽

Data Elements ◽

And Storage

Every business organization needs valuable data and insights for understanding audience intent and consumer’s likings. Big data in this acts as a significant part as it supports in precede the needs of customers for which the data needs to be well presented and appropriately analyzed. Big Data permits organization to segregate customers in broad way which permits a business to hold consumers in a real-time, as in this tough competitive time you need to treat customers how they want. In simplified term “Big Data is a mix of processes and tools by which huge data grid through various form with each other and enormous amount of heterogeneous and rationalized information is created which in addition, used to figure out the utmost valuable customers. It also provide assistance for businesses to innovate, create and pitch new experiences, services, and products. The availability of such information creates opportunities for organizations. The paper here discusses about big data elements, its maintenance, handling and storage of varieties of big data by organizations and gains of big data analytics to organizations. The paper also analyze about the velocity of data generated and analysis of big data by organizations to understand its impact on organization working and consumer decision respectively. The paper also gives avenues for future research by explaining the application and practices of organization in the era of big data analytics.

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Fuel choices in urban Indian households

Environment and Development Economics ◽

10.1017/s1355770x07003932 ◽

2007 ◽

Vol 12 (6) ◽

pp. 757-774 ◽

Cited By ~ 105

Author(s):

MEHDI FARSI ◽

MASSIMO FILIPPINI ◽

SHONALI PACHAURI

Keyword(s):

Discrete Choice ◽

Fuel Use ◽

Use Patterns ◽

Indian Context ◽

Liquid Petroleum Gas ◽

Model Fuel ◽

Urban Indian ◽

Main Factors ◽

Cooking Fuels ◽

Socio Demographic Factors

ABSTRACTThis paper applies an ordered discrete choice framework to model fuel choices and patterns of cooking fuel use in urban Indian households. The choices considered are for three main cooking fuels: firewood, kerosene, and LPG (liquid petroleum gas). The models, estimated using a large microeconomic dataset, show a reasonably good performance in the prediction of households’ primary and secondary fuel choices. This suggests that ordered models can be used to analyze multiple fuel use patterns in the Indian context. The results show that lack of sufficient income is one of the main factors that retard households from using cleaner fuels, which usually also require the purchase of relatively expensive equipments. The results also indicate that households are sensitive to LPG prices. In addition to income and price, several socio-demographic factors such as education and sex of the head of the household are also found to be important in determining household fuel choice.

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Effect of Big Data Analytics in Reverse Supply Chain - An Indian context

International Journal of Information Systems and Supply Chain Management ◽

10.4018/ijisscm.287128 ◽

2022 ◽

Vol 15 (1) ◽

pp. 0-0

Keyword(s):

Big Data ◽

Supply Chain ◽

Supply Chain Management ◽

Data Analytics ◽

Response Rate ◽

Big Data Analytics ◽

Reverse Supply Chain ◽

Chain Management ◽

Indian Context ◽

Indian Industries

The main purpose of this paper is to know about the recent status of big data analytics (BDA) on various manufacturing and reverse supply chain levels (RSCL) in Indian industries. In particular, it emphasises on understanding of BDA concept in Indian industries and proposes a structure to examine industries’ development in executing BDA extends in reverse supply chain management (RSCM). A survey was conducted through questionnaires on RSCM levels of 330 industries. Of the 330 surveys that were mailed, 125 completed surveys were returned, corresponding to a response rate of 37.87 percent, which was slightly greater than previous studies (Queiroz and Telles, 2018).The information of Indian industries with respect to BDA, the hurdles with boundaries to BDA-venture reception, and the connection with reverse supply chain levels and BDA learning were recognized.

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Mothers Parenting a Child With Intellectual Disability in Urban India: An Application of the Stress and Resilience Framework

Intellectual and Developmental Disabilities ◽

10.1352/1934-9556-55.5.325 ◽

2017 ◽

Vol 55 (5) ◽

pp. 325-337 ◽

Cited By ~ 12

Author(s):

Aesha John ◽

Martha Zapata Roblyer

Keyword(s):

Intellectual Disability ◽

Behavioral Problems ◽

Related Factors ◽

Indian Context ◽

Urban Indian ◽

Urban India ◽

Family Level ◽

Resilience Framework ◽

Indian Mothers

Abstract We examined relevance of the key constructs of the stress and resilience framework in the urban Indian context. Analyses of interviews with urban Indian mothers (N = 47) of a 3–6 year old child with intellectual disability generated themes on maternal appraisals of the child's disability, perceived stressors, and resources. Mothers seemed to utilize a combination of fact-based and religious explanation to make sense of their child's disability. Parental stressors ranged from child-related factors (diagnosis, behavioral problems) to financial and family-level challenges. However, participants also reported a number of personal, family-level, and societal resources that helped them cope with the stressors. Study findings are discussed in the context of implications for practice, policy, and research.

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