Building information modelling framework: A research and delivery foundation for industry stakeholders

https://escholarship.org/content/qt4h56k1ch/qt4h56k1ch.pdf

Advanced monitoring of machining operations

This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE). MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence of software development and business analysis. The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away. The book is organized into two main parts. The first part discusses the foundations of MDSE in terms of basic concepts (i.e., models and transformations), driving principles, application scenarios and current standards, like the well-known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes. The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain-specific modeling language, to the description of Model-to-Text and Model-to-Model transformations, and the tools that support the management of MDSE projects. The book is targeted to a diverse set of readers, spanning: professionals, CTOs, CIOs, and team managers that need to have a bird's eye vision on the matter, so as to take the appropriate decisions when it comes to choosing the best development techniques for their company or team; software analysts, developers, or designers that expect to use MDSE for improving everyday work productivity, either by applying the basic modeling techniques and notations or by defining new domain-specific modeling languages and applying end-to-end MDSE practices in the software factory; and academic teachers and students to address undergrad and postgrad courses on MDSE. In addition to the contents of the book, more resources are provided on the book's website http://www.mdse-book.com/, including the examples presented in the book. Table of Contents: Introduction / MDSE Principles / MDSE Use Cases / Model-Driven Architecture (MDA) / Integration of MDSE in your Development Process / Modeling Languages at a Glance / Developing your Own Modeling Language / Model-to-Model Transformations / Model-to-Text Transformations / Managing Models / Summary

Model-Driven Software Engineering in Practice

of “Roadmap for Provision of Safer Healthcare Information Systems: Preventing eIatrogenesis” Joan S. Ash, Ph.D., M.L.S., M.B.A.; Charles M. Kilo, M.D., M.P.H.; Michael Shapiro, M.A., M.S.; Joseph Wasserman, B.A.; Carmit McMullen, Ph.D.; William Hersh, M.D. BACKGROUND AND METHODS e-Iatrogenesis, defined as “patient harm caused at least in part by the application of health information technology” (Weiner et al., 2007), is of increasing concern as more and more hospitals are implementing health information systems (HIS). This report assesses how HIS can be designed, developed, implemented, monitored, and maintained to maximize safety. We specifically focus on hospital electronic health records (EHRs), clinical decision support (CDS), and computerized provider order entry (CPOE) systems. This white paper is intended to provide background for an Institute of Medicine (IOM) report on how the use of health information technology affects the safety of patient care by answering the following IOM-posed questions: • What are the risks of health care information systems that arise from workflow and related issues? • How have organizations acted to implement health care information systems safely? • What are the impacts of customization on safety? • What is the industry approach to managing change and customization? A recent literature review by Harrington et al. (2011) has summarized the EHR safety literature, so we first reviewed all papers cited in their report. Of their 43 references, we identified 37 that were relevant to the scope of this article. We analyzed the bibliographies of these selected papers and performed a reverse bibliography search on the articles deemed most relevant and published since 2000. In total, we identified over 100 sources relevant to the scope of this report. We then targeted topics for which published evidence was lacking and conducted several interviews with experts to help fill the knowledge gaps. 1 Full commissioned paper can be found in this project’s Public Access File. C-2 HEALTH IT AND PATIENT SAFETY PREPUBLICATION COPY: UNCORRECTED PROOFS RESULTS What Are the Risks of Health Information Systems That Arise from Workflow and Related Issues? We found seven publications (Chuo and Hicks, 2008; Joint Commission on Accreditation of Healthcare Organizations, 2008; Magrabi et al., 2010; Myers et al., 2011; Santell et al., 2009; Walsh et al., 2006; Zhan et al., 2006) presenting results of assessments of e-iatrogenic risk. All are studies of large databases of reported errors and they consistently indicate low levels of HISrelated risk, under 1 percent of all errors. All point to the need for human diligence when using HIS. Specifically, they indicate that HIS-related errors are due to inadequate staffing levels, lack of user experience, mislabeled bar-codes on medications, human distraction, inaccurate data entry, system downtime, and missing data. How Have Organizations Acted to Implement Health Information Systems Safely? Prior to implementation, health care organizations can mitigate risk. There is a large literature base devoted to the risks inherent in commercial EHR systems, and also warnings about their impact on workflow. Many publications offer guidance to hospitals about assessing workflow, selecting systems for purchase, conducting simulation tests, training, and other mechanisms for ensuring safe HIS implementation. Numerous publications exist to guide the implementation process itself, but there are also several pointing to the risks of rapid implementation without appropriate preparation. Finally, after implementation, continuous monitoring and improvement can mitigate safety risks. What Are the Impacts of Customization on Safety? The literature indicates that customization of the EHR to fit local situations seems to be necessary for many reasons, but there is scant research on how much customization or what form of customization is needed to optimize EHR use and what the risks are from either too much or too little customization. The content of CDS likewise needs adaptation, especially to avoid alert fatigue. Any customization must be done with care so that system upgrades can be accommodated. What Is the Industry Approach to Managing Change and Customization? The current industry approach is fragmented; a report sponsored by the Agency for Healthcare Research and Quality describes a wide variety of vendor practices related to usability of systems (McDonnell et al., 2010). Because purchasers must usually customize systems to fit local workflows and regulations, HIS safety depends on a combination of industry and local diligence.

Health IT and Patient Safety: Building Safer Systems for Better Care

Microbial communities comprise an interwoven matrix of biological diversity modified by physical and chemical variation over space and time. Although these communities are the major drivers of biosphere processes, relatively little is known about their structure and function, and predictive modeling is limited by a dearth of comprehensive ecological principles that describe microbial community processes. Here we discuss working definitions of central ecological terms that have been used in various fashions in microbial ecology, provide a framework by focusing on different types of interactions within communities, review the status of the interface between evolutionary and ecological study, and highlight important similarities and differences between macro- and microbial ecology. We describe current approaches to study microbial ecology and progress toward predictive modeling.

/pdf/rules-of-engagement-interspecies-interactions-that-regulate-4tmo6jmj20.pdf

Rules of Engagement: Interspecies Interactions that Regulate Microbial Communities

IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries

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IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries