466 research outputs found

    Open Data and Big Data Programs in Local Government Policy Analysis

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    This paper examines the development of policy around the open data programs for local government. Through a literature review, a survey of large municipalities in Ontario, and in-depth interviews, the research attempts to identify if there are factors that ensure whether the policy development process is more likely to be implemented along with the program or if there is a lack of policy development as a result of it. The findings reveal a definite lack of policy development with the open data program, which is likely due to the challenge for policy makers to ensure appropriate access and privacy protection, as technology makes information more accessible, and there are also emerging social issues that result from different generational expectations and values

    Muscatine Melon: A Case Study of a Place-based Food in Iowa

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    This special project of the Leopold Center\u27s Marketing and Food Systems Initiative (2004-MSP09) looks at the 120-year history of melon production in southeast Iowa and potential for promotion

    Economic analysis of current and potential Muscatine melon market

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    The Muscatine melon traditionally has been one of Iowa\u27s best known produce items. As the number of acres and producers decline, melon producers are looking for ways to make their product a more attractive economic production option, and place-based marketing may be helpful. Melon producers, however, need to ask themselves if they are willing to cooperatively develop and market a place-based product in order to achieve higher prices and profitability

    Ethics in community nursing

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    The purpose of this theoretical paper is to explore the ethics in a community nursing. Nursing, a practice discipline recognizes caring, morals, and values as integral to the practice of all nurses. The ethical principles of beneficence, autonomy, advocacy, and social justice will be discussed from the lens of caring. Caring nursing theorists, such as Jean Watson, Ann Boykin, and Savina Schoenhofer, articulate the importance of understanding communities and individuals as whole and autonomous. These theorists and others challenge nursing to engage in a responsive, ethical and philosophical discourse when the community is viewed as autonomous

    Child's play: Harnessing play and curiosity motives to improve child handwashing in a humanitarian setting.

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    In humanitarian emergency settings there is need for low cost and rapidly deployable interventions to protect vulnerable children, in- and out-of-school, from diarrhoeal diseases. Handwashing with soap can greatly reduce diarrhoea but interventions specifically targeting children's handwashing behaviour in humanitarian settings have not been tested. Traditional children's handwashing promotion interventions have been school-focused, resource-intensive and reliant on health-based messaging. However, recent research from non-humanitarian settings and targeting adults suggests that theory-based behaviour change interventions targeting specific motives may be more effective than traditional handwashing interventions. In this proof-of-concept study we test, for the first time, the distribution of a modified soap bar, designed to appeal to the motives of play and curiosity, in a household-level, rapidly deployable, handwashing promotion intervention for older children in a humanitarian setting - an internally displaced persons camp in Iraqi Kurdistan. Out of five total blocks within the camp, one was assigned to intervention and one to control. 40 households from each assigned block were then randomly chosen for inclusion in the study and the practice of handwashing with soap at key times was measured at baseline and four weeks after intervention delivery. Children in intervention households received transparent soaps with embedded toys, delivered within a short, fun, and interactive household session with minimal, non-health-based, messaging. The control group received plain soap delivered in a short standard, health-based, hygiene promotion session. At the 4-week follow-up, children in the intervention group were 4 times more likely to wash their hands with soap after key handwashing occasions than expected in the counterfactual (if there had been no intervention) based on the comparison to children in the control group (adjusted RR = 3.94, 95% CI 1.59-9.79). We show that distributing soaps with toys embedded inside, in a rapidly deployable intervention, can improve child handwashing behaviour in a humanitarian emergency context. Further studies are needed to determine the longer-term behavioural and health impact of such an intervention when delivered at a greater scale in a humanitarian context

    Eating Smart and Moving More for Head Start: A Pilot Study

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    Our study examined the relationship between improved personal health behaviors of Head Start teachers’ and the promotion of positive health behaviors in their classroom. Thirty-three Head Start teachers across 7 centers received six 30-minute nutrition education lessons. Dietary intake, physical activity, and self-efficacy for promoting positive health behaviors in the classroom were measured at baseline and post-intervention. Significant improvements were observed for dietary intake and physical activity. Self-efficacy for promoting health behaviors in the classroom did not significantly improve. Additional education is needed to improve health promotion practices. Lessons learned contributed to program refinement. Implications for Extension are discussed

    Phase Transitions in Chemisorbed Systems

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    Contains reports on six research projects.Joint Services Electronics Program (Contract DAAG29-83-K-0003

    Identifying Documents In-Scope of a Collection from Web Archives

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    Web archive data usually contains high-quality documents that are very useful for creating specialized collections of documents, e.g., scientific digital libraries and repositories of technical reports. In doing so, there is a substantial need for automatic approaches that can distinguish the documents of interest for a collection out of the huge number of documents collected by web archiving institutions. In this paper, we explore different learning models and feature representations to determine the best performing ones for identifying the documents of interest from the web archived data. Specifically, we study both machine learning and deep learning models and "bag of words" (BoW) features extracted from the entire document or from specific portions of the document, as well as structural features that capture the structure of documents. We focus our evaluation on three datasets that we created from three different Web archives. Our experimental results show that the BoW classifiers that focus only on specific portions of the documents (rather than the full text) outperform all compared methods on all three datasets.Comment: 10 page

    Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews

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    This study aims to investigate the contributions of online promotional marketing and online reviews as predictors of consumer product demands. Using electronic data from Amazon.com, we attempt to predict if online review variables such as valence and volume of reviews, the number of positive and negative reviews, and online promotional marketing variables such as discounts and free deliveries, can influence the demand of electronic products in Amazon.com. A Big Data architecture was developed and Node.JS agents were deployed for scraping the Amazon.com pages using asynchronous Input/Output calls. The completed Web crawling and scraping data-sets were then preprocessed for Neural Network analysis. Our results showed that variables from both online reviews and promotional marketing strategies are important predictors of product demands. Variables in online reviews in general were better predictors as compared to online marketing promotional variables. This study provides important implications for practitioners as they can better understand how online reviews and online promotional marketing can influence product demands. Our empirical contributions include the design of a Big Data architecture that incorporate Neural Network analysis which can used as a platform for future researchers to investigate how Big Data can be used to understand and predict online consumer product demands
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