A pragmatics' view of patient identification.

Patient identification is a central safety critical aspect of healthcare work. Most healthcare activities require identification of patients by healthcare staff, often in connection with the use of patient records. Indeed, the increasing reliance on electronic systems makes the correct matching of patients with their records a keystone for patient safety. Most research on patient identification has been carried out in hospital settings. The aim was to investigate the process of identification of patients and their records in the context of a primary healthcare clinic

Report on Scottish council elections 2012

This report to the Electoral Commission covers the Scottish council elections of May 2012. It considers aspects of the administration of the elections, turnout, patterns of candidature and party support and control of councils

FORGE: An eLearning Framework for Remote Laboratory Experimentation on FIRE Testbed Infrastructure

The Forging Online Education through FIRE (FORGE) initiative provides educators and learners in higher education with access to world-class FIRE testbed infrastructure. FORGE supports experimentally driven research in an eLearning environment by complementing traditional classroom and online courses with interactive remote laboratory experiments. The project has achieved its objectives by defining and implementing a framework called FORGEBox. This framework offers the methodology, environment, tools and resources to support the creation of HTML-based online educational material capable accessing virtualized and physical FIRE testbed infrastruc- ture easily. FORGEBox also captures valuable quantitative and qualitative learning analytic information using questionnaires and Learning Analytics that can help optimise and support student learning. To date, FORGE has produced courses covering a wide range of networking and communication domains. These are freely available from FORGEBox.eu and have resulted in over 24,000 experiments undertaken by more than 1,800 students across 10 countries worldwide. This work has shown that the use of remote high- performance testbed facilities for hands-on remote experimentation can have a valuable impact on the learning experience for both educators and learners. Additionally, certain challenges in developing FIRE-based courseware have been identified, which has led to a set of recommendations in order to support the use of FIRE facilities for teaching and learning purposes

Remote processing of firm microdata at the Bank of Italy

Providing the possibility to run personalised econometric/statistical analyses on the appropriate data sets by remote processing allows greater flexibility in the production of economic information. Binding confidentiality requirements are required with business survey data. The Bank of Italy's infrastructure allows its business survey data to be exploited, while preserving anonymity of individual data. The system is based on the LISSY platform and has been already adopted by the Luxembourg Income Study (LIS) and other research centres. Firms' privacy is safeguarded by forbidding potentially confidentiality-breaking programme statements and by denying the visualisation of individual data. Data confidentiality is protected by removing key identifiers from the database and by trimming data in the right tail of the distribution. The platform provides its services through plain-text e-mails. The authorised user sends an e-mail containing an identifying header followed by a statistical programme to a predetermined address. The system checks the validity of the header, strips out the code and submits it in a batch to one of the econometric/statistical packages available (SAS and Stata). The outputs are mailed back to the user after passing an array of automatic and manual checks.microdata, confidentiality, remote access

Application of Satellite Frost Forecast Technology to Other Parts of the United States Phase II: Introduction

The history and status of University of Michigan and University of Pennsylvania involvement in determining if P-model for front prediction used in Florida is applicable to those geographic locations is reviewed. The possibility of using the S-model to develop a satellite front forecast system that can recall the distribution of temperatures during previous freezes from a particular area and bring that cold climate climatology to bear on present forecasts is discussed as well as a proposed GOES satellite downlink system to sectionalize the data used in Florida