1,298 research outputs found

    Achieving a New Standard in Primary Care for Low-Income Populations -- Case Studies of Redesign and Change Through a Learning Collaborative

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    Describes four case studies that focus on improving patient care delivery systems through learning collaboratives that were undertaken by New York City's nonprofit Primary Care Development Corporation

    A digital motion control system

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    Object Manipulation using a Multirobot Cluster with Force Sensing

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    This research explored object manipulation using multiple robots by developing a control system utilizing force sensing. Multirobot solutions provide advantages of redundancy, greater coverage, fault-tolerance, distributed sensing and actuation, and reconfigurability. In object manipulation, a variety of solutions have been explored with different robot types and numbers, control strategies, sensors, etc. This research involved the integration of force sensing with a centralized position control method of two robots (cluster control) and building it into an object level controller. This controller commands the robots to push the object based on the measured interaction forces between them while maintaining proper formation with respect to each other and the object. To test this controller, force sensor plates were attached to the front of the Pioneer 3-AT robots. The object is a long, thin, rectangular prism made of cardboard, filled with paper for weight. An Ultra Wideband system was used to track the positions and headings of the robots and object. Force sensing was integrated into the position cluster controller by decoupling robot commands, derived from position and force control loops. The result was a successful pair of experiments demonstrating controlled transportation of the object, validating the control architecture. The robots pushed the object to follow linear and circular trajectories. This research is an initial step toward a hybrid force/position control architecture with cluster control for object transportation by a multirobot system

    Enacting Politics through Art: Encounters between Queer and Trans of Color Organizers and the Canadian City.

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    This ethnographic study investigates the role of the arts in the relationship between urban governmental institutions and queer and transgender people of color (QTPOC) community organizations. Toronto is a fitting site for this project given that the city is intensively mobilizing the arts to foster urban economic development and that it is uniquely emblematic of Canada’s regulatory embrace of racialized, gendered and sexual minorities. The findings from this study are derived from two years of ethnographic fieldwork and 63 semi-structured interviews carried out between 2012 and 2014 among state arts institutions, funding bodies and community arts initiatives. Drawing from the fields of social work, anthropology, queer studies, and critical ethnic studies, I argue that the arts operate as a means of constructing the neoliberal welfare state through the incorporation of QTPOC. These inclusionary creative citizenship practices enable QTPOC to engage in a feelings-based mode of community development in ways that are nevertheless constrained by how state institutions administer the programs that fund these initiatives. Each chapter of this dissertation is organized around an ethnographic dilemma that brings into focus how the arts surface as the solution to the diverse challenges that government institutions and minority community organizations face. As a uniquely elastic mode of social action, the arts serve as the linchpin between QTPOC efforts to counter the intertwined mechanisms of racism, sexism, transphobia and homophobia, and municipal imperatives to promote economic growth and address the social exclusion of marginalized populations. By using the arts to explore the interrelated workings of urban government and grassroots collectives, this study demonstrates how questions of space, time, feelings, humanity and political economy are deeply implicated in the politics of making racialized, gendered and sexual difference.PhDSocial Work and AnthropologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120709/1/chinm_1.pd

    Ethanol Ablation of a Peripheral Nerve Sheath Tumor Presenting as a Small Bowel Obstruction.

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    Ethanol has historically been used as an ablative agent for a variety of lesions. One of the more common applications of this technique is celiac plexus neurolysis; however, recent reports have suggested a role for the endoscopic alcohol ablation of a variety of solid and cystic lesions. We report a novel case of endoscopic ethanol ablation of a peripheral nerve sheath tumor presenting as a small bowel obstruction

    A Proposed Model and Measurement Instrument for the Formation of IS Satisfaction: The Case of End-User Computing Satisfaction

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    This paper presents a model that explicitly defines satisfaction and the antecedent factors that help form it. The model distinguishes between the notions of expectations and desires and argues that both have an impact on overall satisfaction in the form of the difference between priors and post hoc usage perceptions coupled with the individual’ s evaluation of these discrepancies. These two types of satisfaction, in turn, will have both direct and multiplicative impact on overall satisfaction. Given this understanding, we highlight possiblelimitations in existing instruments and provide a solution for creating new measures that should overcome these limitations. A complete set of measures is provided in this paper for future empirical testing, which are general enough to allow researchers to create measures for other aspects related to IS satisfaction beyond those targeted in this paper. We employ our model within the context of the five satisfaction areas outlined by Doll and Torzadeh (1988). Building upon their initial set of perceptual measures, we examine whether there are indeed two types of discrepancy effects, whether there are multiplicative effects for each discrepancy, and whether there is a higher order interaction between the two discrepancy components. Partial least squares analyses of data consisting of over 200 instructional staff member at a large university related to their satisfaction with an online grading system are employed and the results presented at the conference

    BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading

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    Diabetic retinopathy (DR) is a common retinal disease that leads to blindness. For diagnosis purposes, DR image grading aims to provide automatic DR grade classification, which is not addressed in conventional research methods of binary DR image classification. Small objects in the eye images, like lesions and microaneurysms, are essential to DR grading in medical imaging, but they could easily be influenced by other objects. To address these challenges, we propose a new deep learning architecture, called BiRA-Net, which combines the attention model for feature extraction and bilinear model for fine-grained classification. Furthermore, in considering the distance between different grades of different DR categories, we propose a new loss function, called grading loss, which leads to improved training convergence of the proposed approach. Experimental results are provided to demonstrate the superior performance of the proposed approach.Comment: Accepted at ICIP 201
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