Contextual motivation in physical activity by means of association rule mining

The primary thrust of this work is to demonstrate the applicability of association rule mining in public health domain, focusing on physical activity and exercising. In this paper, the concept of association rule mining is shown assisting to promote the physical exercise as regular human activity. Specifically, similar to the prototypical example of association rule mining, market basket analysis, our proposed novel approach considers two events – exercise (sporadic) and sleep (regular) as the two items of the frequent set; and associating the former, exercise event, with latter, the daily occurring activity sleep at night, helps strengthening the frequency of the exercise patterns. The regularity can further be enhanced, if the exercising instruments are kept in the vicinity of the bed and are within easy reach

Does SNAP eligibility have racial or ethnic gradients: a geospatial social exploratory

Recently, much discussion has centred on disproportionate dependence of certain racial groups on SNAP programme. This racial overture is sparked by comments made during the Fox News-Wall Street Journal Republican Presidential debate by Newt Gingrich, former Speaker of the House, who asserted that President Obama is a ‘food stamp president’. This stereotypic SNAP overture is posting a larger narrative about government assistance and disproportionate dependence of some racial minority groups on government programmes. However, are majority of SNAP recipients fit minority profiling? We explain this overarching question through geospatial study of racial and spatial equity in government welfare programmes on food stamp. Specifically, this study explains the variations in participation votes in the food stamp programme using census tract data for counties and metropolitan areas as case examples. In addition to profiling the food stamp population across state, this study provides information required for developing the targeted nutrition education campaign.This article is published as Sharma, Sugam, Udoyara Sunday Tim, Shashi Gadia, and Johnny Wong. "Does SNAP eligibility have racial or ethnic gradients: a geospatial social exploratory." International Journal of Information and Communication Technology 6, no. 2 (2014): 189-212. DOI: 10.1504/IJICT.2014.060399. Posted with permission.</p

A Brief Review on Leading Big Data Models

Today, science is passing through an era of transformation, where the inundation of data, dubbed data deluge is influencing the decision making process. The science is driven by the data and is being termed as data science. In this internet age, the volume of the data has grown up to petabytes, and this large, complex, structured or unstructured, and heterogeneous data in the form of “Big Data” has gained significant attention. The rapid pace of data growth through various disparate sources, especially social media such as Facebook, has seriously challenged the data analytic capabilities of traditional relational databases. The velocity of the expansion of the amount of data gives rise to a complete paradigm shift in how new age data is processed. Confidence in the data engineering of the existing data processing systems is gradually fading whereas the capabilities of the new techniques for capturing, storing, visualizing, and analyzing data are evolving. In this review paper, we discuss some of the modern Big Data models that are leading contributors in the NoSQL era and claim to address Big Data challenges in reliable and efficient ways. Also, we take the potential of Big Data into consideration and try to reshape the original operationaloriented definition of “Big Science” (Furner, 2003) into a new data-driven definition and rephrase it as “The science that deals with Big Data is Big Science.”This article is from Data Science Journal. 13, pp.138–157. DOI: http://doi.org/10.2481/dsj.14-041. Posted with permission.</p

Contextual motivation in physical activity by means of association rule mining

The primary thrust of this work is to demonstrate the applicability of association rule mining in public health domain, focusing on physical activity and exercising. In this paper, the concept of association rule mining is shown assisting to promote the physical exercise as regular human activity. Specifically, similar to the prototypical example of association rule mining, market basket analysis, our proposed novel approach considers two events – exercise (sporadic) and sleep (regular) as the two items of the frequent set; and associating the former, exercise event, with latter, the daily occurring activity sleep at night, helps strengthening the frequency of the exercise patterns. The regularity can further be enhanced, if the exercising instruments are kept in the vicinity of the bed and are within easy reach.This article is from Egyptian Informatics Journal 16 (2015): 243–251, doi:10.1016/j.eij.2015.06.003. Posted with permission.</p