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Many institutions will be providing data to the National Spatial Data Infrastructure (NSDI). Current technical background of the NSDI is based on syntactic web services. It is expected that this will be replaced by semantic web services. The quality of the data provided is important in terms of the decision-making process and the accuracy of transactions. Therefore, the data quality needs to be tested. This topic has been neglected in Turkey. Data quality control for NSDI may be done by private or public "data accreditation" institutions. A methodology is required for data quality evaluation. There are studies for data quality including ISO standards, academic studies and software to evaluate spatial data quality. ISO 19157 standard defines the data quality elements. Proprietary software such as, 1Spatial's 1Validate and ESRI's Data Reviewer offers quality evaluation based on their own classification of rules. Commonly, rule based approaches are used for geospatial data quality check. In this study, we look for the technical components to devise and implement a rule based approach with ontologies using free and open source software in semantic web context. Semantic web uses ontologies to deliver well-defined web resources and make them accessible to end-users and processes. We have created an ontology conforming to the geospatial data and defined some sample rules to show how to test data with respect to data quality elements including; attribute, topo-semantic and geometrical consistency using free and open source software. To test data against rules, sample GeoSPARQL queries are created, associated with specifications.
To evaluate the spatial resolution of proton CT using both a prototype proton CT scanner and Monte Carlo simulations. A custom cylindrical edge phantom containing twelve tissue-equivalent inserts with four different compositions at varying radial displacements from the axis of rotation was developed for measuring the modulation transfer function (MTF) of a prototype proton CT scanner. Two scans of the phantom, centered on the axis of rotation, were obtained with a 200 MeV, low-intensity proton beam: one scan with steps of 4°, and one scan with the phantom continuously rotating. In addition, Monte Carlo simulations of the phantom scan were performed using scanners idealized to various degrees. The data were reconstructed using an iterative projection method with added total variation superiorization based on individual proton histories. Edge spread functions in the radial and azimuthal directions were obtained using the oversampling technique. These were then used to obtain the modulation transfer functions. The spatial resolution was defined by the 10% value of the modulation transfer function (MTF 10% ) in units of line pairs per centimeter (lp/cm). Data from the simulations were used to better understand the contributions of multiple Coulomb scattering in the phantom and the scanner hardware, as well as the effect of discretization of proton location. The radial spatial resolution of the prototype proton CT scanner depends on the total path length, W, of the proton in the phantom, whereas the azimuthal spatial resolution depends both on W and the position, u - , at which the most-likely path uncertainty is evaluated along the path. For protons contributing to radial spatial resolution, W varies with the radial position of the edge, whereas for protons contributing to azimuthal spatial resolution, W is approximately constant. For a pixel size of 0.625 mm, the radial spatial resolution of the image reconstructed from the fully idealized simulation data ranged
Coarse grain (CG) models allow long-scale simulations with a much lower computational cost than that of all-atom simulations. However, the absence of atomistic detail impedes the analysis of specific atomic interactions that are determinant in most interesting biomolecular processes. In order to study these phenomena, it is necessary to reconstruct the atomistic structure from the CG representation. This structure can be analyzed by itself or be used as an onset for atomistic molecular dynamics simulations. In this work, we present a computer program that accurately reconstructs the atomistic structure from a CG model for proteins, using a simple geometrical algorithm. The software is free and available online at Supplementary data are available at Bioinformatics online. lula@qi.fcen.uba.ar. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Landmark point-pairs provide a strategy to assess deformable image registration (DIR) accuracy in terms of the spatial registration of the underlying anatomy depicted in medical images. In this study, we propose to augment a publicly available database (www.dir-lab.com) of medical images with large sets of manually identified anatomic feature pairs between breath-hold computed tomography (BH-CT) images for DIR spatial accuracy evaluation. Ten BH-CT image pairs were randomly selected from the COPDgene study cases. Each patient had received CT imaging of the entire thorax in the supine position at one-fourth dose normal expiration and maximum effort full dose inspiration. Using dedicated in-house software, an imaging expert manually identified large sets of anatomic feature pairs between images. Estimates of inter- and intra-observer spatial variation in feature localization were determined by repeat measurements of multiple observers over subsets of randomly selected features. 7298 anatomic landmark features were manually paired between the 10 sets of images. Quantity of feature pairs per case ranged from 447 to 1172. Average 3D Euclidean landmark displacements varied substantially among cases, ranging from 12.29 (SD: 6.39) to 30.90 (SD: 14.05) mm. Repeat registration of uniformly sampled subsets of 150 landmarks for each case yielded estimates of observer localization error, which ranged in average from 0.58 (SD: 0.87) to 1.06 (SD: 2.38) mm for each case. The additions to the online web database (www.dir-lab.com) described in this work will broaden the applicability of the reference data, providing a freely available common dataset for targeted critical evaluation of DIR spatial accuracy performance in multiple clinical settings. Estimates of observer variance in feature localization suggest consistent spatial accuracy for all observers across both four-dimensional CT and COPDgene patient cohorts.
In response to two White Papers submitted to the Astro2010 Decadal Survey (1,2), a new AAS Working Group on Astroinformatics and Astrostatistics (WGAA) has been approved by the AAS Council at the 220th Meeting, June 2012, in Anchorage. The motivation for this WG is the growing importance of the interface between astronomy and various branches of applied mathematics, computer science and the emerging field of data science. With the new data-intensive projects envisioned for the coming decade, the need for advice derived from the focused attention of a group of AAS members who work in these areas is bound to increase. The Working Group is charged with spreading awareness of rapidly advancing computational techniques, sophsticated statistical methods, and highly capble software to further the goals of astronomical and astrophysical research. The three main strategic goals adopted by the WGAA Steering Committee for the next few years are to: (i) develop, organize and maintain methodological resources (such as software tools, papers, books, and lectures); (ii) enhance human resources (such as foster the creation of career paths, establish a Speakers' Bureau, establish and maintain an archived discussion forum, enable periodic news distribution); and (iii) organize topical meetings. The WGAA Steering Committee at this time includes twelve members: Kirk Borne, George Djorgovski, Eric Feigelson, Eric Ford, Alyssa Goodman, Joe Hilbe, Zeljko Ivezic (chair), Ashish Mahabal, Aneta Siemiginowska, Alex Szalay, Rick White, and Padma Yanamandra-Fisher. I will summarize our accomplishments since July 2012. (1) Astroinformatics: A 21st Century Approach to Astronomy (Borne & 90 coauthors), (2) The Astronomical Information Sciences: A Keystone for 21st-Century Astronomy (Loredo & 72 coauthors)
The AAS Working Group on Accessibility and Disability (WGAD) was formed in January of 2016 with the express purpose of seeking equity of opportunity and building inclusive practices for disabled astronomers at all educational and career stages. In this presentation, we will provide a summary of current activities, focusing on developing best practices for accessibility with respect to astronomical databases, publications, and meetings. Due to the reliance of space sciences on databases, it is important to have user centered design systems for data retrieval. The cognitive overload that may be experienced by users of current databases may be mitigated by use of multi-modal interfaces such as xSonify. Such interfaces would be in parallel or outside the original database and would not require additional software efforts from the original database. WGAD is partnering with the IAU Commission C1 WG Astronomy for Equity and Inclusion to develop such accessibility tools for databases and methods for user testing. To collect data on astronomical conference and meeting accessibility considerations, WGAD solicited feedback from January AAS attendees via a web form. These data, together with upcoming input from the community and analysis of accessibility documents of similar conferences, will be used to create a meeting accessibility document. Additionally, we will update the progress of journal access guidelines and our social media presence via Twitter. We recommend that astronomical journals form committees to evaluate the accessibility of their publications by performing user-centered usability studies. 2b1af7f3a8
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