1,721,175 research outputs found
Organizing and delivering diabetes education and self-care support: findings of scoping project
No full textObjective: To provide an overview of current research and development on the organization and delivery of diabetes education and self-care support, incorporating stakeholder perspectives. MethodFour methods were used: literature review (159 papers and 52 grey literature items); patient participation event (n = 38); online survey of professionals (n = 423) and patients (n= 495); and, a conference. ResultsThe literature review identified themes relating to the organization and delivery of diabetes and self-care support: structure and flexibility in models of education; accessibility; patient choice; integrating self-care within the overall care system; quality improvement; peer educators; health literacy; efficiency in delivery; telecare models; feedback technologies; care planning; psychological intervention; and self-care outcome measures. This generated four models to provide a framework to help shape the development of diabetes self-care: a diabetes education pathway; integrating self-care and clinical care; choice as a method of optimizing care; and an integrated framework for delivering diabetes self-care. ConclusionThe clinical benefit of the identified models need to be evaluated
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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Improving VR Social Interactions with Architectural Spacing Strategies
Full text linkVirtual Reality (VR)-based social platforms, such as VR Chat, heavily rely on thirdpartycontent creators that sometimes reference the VR-inefficient design approaches
of real-life venues without fully considering VR-specific design modifications. This
project proposes that additional architectural design and spacing modifications should
be implemented in the development of Social Virtual Reality Environments (SVRE)
to further facilitate and improve social interactions in VR-based social platforms. The
findings from this study indicate that open-space hotspot (OSH)-based design
implementations in SVREs can improve VR social interaction and user experience by
facilitating open-spaced grouped formations (OSGF), which are essentially a type of
user formation catalyst for VR social interactions
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SlimeArt
Full text linkSlimeArt is a Casual Creator generative art tool that allows users to create dynamic, particle designs with the Monte Carlo Physarum model using a particle brush and a deposit brush. Casual Creators are creativity support tools that value the feeling of enjoyment, the support of exploration, and usability of the interface. Through a user study (N=15), SlimeArt was evaluated with the Creativity Support Index showing it supported exploration, immersion, and enjoyment above expressiveness, results worth effort, and collaboration as hypothesized beforehand. By observing users’ questions, suggestions, and behaviors in the tool, we were able to identify insights as to how we should redesign the presentation of the particle deposit strength slider to help users better understand how the particles and deposit interact. In addition to the usability study, the SlimeArt Encouragement Study placed users into two conditions to evaluate if the presence of an encouraging virtual agent, SlimeBot, affected users’ creative self-efficacy, perception of ownership over their art, or level of exploration. While SlimeBot did not affect users’ creative self-efficacy and perception of ownership, it did show a significant effect on how users reported SlimeArt’s support of exploration in the Creativity Support Index. A thorough investigation into the usability of SlimeArt and the effects of SlimeBot presented the issues with the first design which led us to identify the ways SlimeArt’s redesign could better support users to create evolving network designs modeled after slime mold
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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Interactive Analysis Tools for Visualizing the Universe
Full text linkThis thesis introduces three novel interactive astronomy data visualization tools for exploring and analyzing information from telescope observations and cosmological simulations. The amount of data produced by modern telescopes and simulations is tremendous and can be challenging for experts and non-experts to explore comprehensively without the help of accessible, interactive techniques and tools. Given the size and complexity of these data, it often requires advanced technical expertise to access, query, view, and analyze the information. Furthermore, working with large-scale simulations requires powerful computing resources that may not be accessible on basic consumer hardware. The projects described in this thesis leverage advances in consumer graphics hardware and browser-based rendering to provide lightweight, accessible tools to the astronomy community that are designed to simplify analytic workflows, reduce cognitive load and the need for users to code, and contextualize the data meaningfully. In Chapter 1, the introduction, a brief history of astronomy visualization methods from the stone age to now, is preceded by a description of the three interactive browser-based visualization tools introduced in this thesis: IGM-Vis (chapter 2) contextualizes the impact of galaxies in observational absorption spectra through the introduction of "skewer sightlines"; CosmoVis (chapter 3) is a cosmological simulation volume and particle visualizer that allows users to place "skewer sightlines" in the volume and return absorption spectra and other physical properties; and finally, a temporal animation extension to CosmoVis (chapter 4) that allows for exploring the evolution of cosmological simulations. For each project, the scientific motivations and background are detailed for a visualization audience and contextualized with related software tools. We identify astronomy-based analysis tasks that each tool solves, along with details of the design and implementation of the systems as they relate to enabling the tasks. Finally, a set of scientific use cases and user and performance evaluations are provided
Cosmological Data Generation With Generative Adversarial Networks
Full text linkCosmological data is comprised of dark matter and ordinary matter forming halos, filaments, sheets and voids under the influence of gravity over large periods of time, termed as the "Cosmic Web." Direct observations and experiments over the cosmic web are not possible, making computational models of the underlying processes extremely important in studying evolution of the universe. N-body simulations, which are the ubiquitously used model, are computationally expensive, having to evolve the position of millions of particles of matter over cosmic time while considering effects of various physical interactions. Thus, N-body simulations are a major bottleneck in such cosmological experiments. Generative Adversarial Networks (GANs), which have been successfully used to generate synthetic data from sparse inputs, are proposed as a possible alternative to such simulations in this thesis. We perform the training of GANs in three separate experiments, first training over normalized 2D slices, then over 2D slices of high-dynamic range data, and finally training over 3D voxels of data. We use a 1024^3 block of data of size 180 Mpc generated using Bolshoi-Planck simulation as the input to train all the models. All the trained models take much less amount of time to generate synthesized data with high visual quality. We also discuss several metrics that can be used to compare summary statistics of synthetic data with the input
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