3,858 research outputs found
sj-docx-1-jpc-10.1177_21501319211066658 – Supplemental material for Pathways of Teach-Back Communication to Health Outcomes Among Individuals With Diabetes: A Pathway Modeling
No full textSupplemental material, sj-docx-1-jpc-10.1177_21501319211066658 for Pathways of Teach-Back Communication to Health Outcomes Among Individuals With Diabetes: A Pathway Modeling by Young-Rock Hong, Ara Jo, Jinhai Huo, Michelle I. Cardel and Arch G. Mainous in Journal of Primary Care & Community Health</p
Supplementary_Files - Use of Social Media in Health Communication: Findings From the Health Information National Trends Survey 2013, 2014, and 2017
No full textSupplementary_Files for Use of Social Media in Health Communication: Findings From the Health Information National Trends Survey 2013, 2014, and 2017 by Jinhai Huo, Raj Desai, Young-Rock Hong, Kea Turner, Arch G. Mainous and Jiang Bian in Cancer Control</p
Effects of outliers on the identification and estimation of GARCH models
No full textThis paper analyses how outliers affect the identification of conditional heteroscedasticity and the estimation of generalized autoregressive conditionally heteroscedastic (GARCH) models. First, we derive the asymptotic biases of the sample autocorrelations of squared observations generated by stationary processes and show that the properties of some conditional homoscedasticity tests can be distorted. Second, we obtain the asymptotic and finite sample biases of the ordinary least squares (OLS) estimator of ARCH(p) models. The finite sample results are extended to generalized least squares (GLS), maximum likelihood (ML) and quasi-maximum likelihood (QML) estimators of ARCH(p) and GARCH(1,1) models. Finally, we show that the estimated asymptotic standard deviations are biased estimates of the sample standard deviations. Copyright 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.
MeasureIt-ARCH: A Tool for Facilitating Architectural Design in the Open Source Software Blender
No full textThis thesis discusses the design and synthesis of MeasureIt-ARCH, a GNU GPL licensed software add-on developed by the author in order to add functionality to the Open Source 3D modeling software Blender that facilitates the creation of architectural drawings. MeasureIt-ARCH adds to Blender simple tools to dimension and annotate 3D models, as well as basic support for the definition and drawing of line work. These tools for the creation of dimensions, annotations and line work are designed to be used in tandem with Blender's existing modelling and rendering tool set. While the drawings that MeasureIt-ARCH produces are fundamentally conventional, as are the majority of the techniques that MeasureIt-ARCH employs to create them, MeasureIt-ARCH does provide two simple and relatively novel methods in its drawing systems. MeasureIt-ARCH provides a new method for the placement of dimension elements in 3D space that draws on the dimension's three dimensional context and surrounding geometry order to determine a placement that optimizes legibility. This dimension placement method does not depend on a 2D work plane, a convention that is common in industry standard Computer Aided Design software. MeasureIt-ARCH also implements a new approach for drawing silhouette lines that operates by transforming the silhouetted models geometry in 4D 'Clip Space'.
The hope of this work is that MeasureIt-ARCH might be a small step towards creating an Open Source design pipeline for Architects. A step towards creating architectural drawings that can be shared, read, and modified by anyone, within a platform that is itself free to be changed and improved. The creation of MeasureIt-ARCH is motivated by two goals. First, the work aims to create a basic functioning Open Source platform for the creation of architectural drawings within Blender that is publicly and freely available for use. Second, MeasureIt-ARCH's development served as an opportunity to engage in an interdisciplinary act of craft, providing the author an opportunity to explore the act of digital tool making and gain a basic competency in this intersection between Architecture and Computer Science.
To achieve these goals, MeasureIt-ARCH's development draws on references from the history of line drawing and dimensioning within Architecture and Computer Science. On the Architectural side, we make use of the history of architectural drawing and dimensioning conventions as described by Mario Carpo, Alberto Pérez Gómez and others, as well as more contemporary frameworks for the classification of architectural software, such as Mark Bew and Mervyn Richard's BIM Levels framework, in order to help determine the scope of MeasureIt-ARCH's feature set. When crafting MeasureIt-ARCH, precedent works from the field of Computer Science that implement methods for producing line drawings from 3D models helped inform the author’s approach to line drawing. In particular this work draws on the overview of line drawing methods produced by Bénard Pierre and Aaron Hertzmann, Arthur Appel's method for line drawing using 'Quantitative Invisibility', the techniques employed in the Freestyle line drawing system created by Grabli et al. as well as other to help inform MeasureIt-ARCH's simple drawing tools.
Beyond discussing MeasureIt-ARCH's development and its motivations, this thesis also provides three small speculative discussions about the implications that an Open Source design tool might have on the architectural profession.
We investigate MeasureIt-ARCH's use for small scale architectural projects in a practical setting, using it's tool set to produce conceptual design and renovation drawings for cottages at the Lodge at Pine Cove. We provide a demonstration of how MeasureIt-ARCH and Blender can integrate with external systems and other Blender add-ons to produce a proof of concept, dynamic data visualization of the Noosphere installation at the Futurium center in Berlin by the Living Architecture Systems Group. Finally, we discuss the tool's potential to facilitate greater engagement with the Open Source Architecture (OSArc) movement by illustrating a case study of the work done by Alastair Parvin and Clayton Prest on the WikiHouse project, and by highlighting the challenges that face OSArc projects as they try to produce Open Source Architecture without an Open Source design software
ARCH-COMP21 Category Report: Stochastic Models
No full textThis report presents the results of a friendly competition for formal verification andpolicy synthesis of stochastic models. It also introduces new benchmarks within this category, and recommends next steps for this category towards next year's edition of the competition. The friendly competition took place as part of the workshop Applied Verification for Continuous and Hybrid Systems (ARCH) in Spring/Summer 2021.Air Transport & Operation
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