Advancing Critical Care in the ICU: A Human-Centered Biomedical Data Visualization Systems

The purpose of this research is to provide medical clinicians with a new technology for interpreting large and diverse datasets to expedite critical care decision-making in the ICU. We refer to this technology as the medical information visualization assistant (MIVA). MIVA delivers multivariate biometric (bedside) data via a visualization display by transforming and organizing it into temporal resolutions that can provide contextual knowledge to clinicians. The result is a spatial organization of multiple datasets that allows rapid analysis and interpretation of trends. Findings from the usability study of the MIVA static prototype and heuristic inspection of the dynamic prototype suggest that using MIVA can yield faster and more accurate results. Furthermore, comments from the majority of the experimental group and the heuristic inspectors indicate that MIVA can facilitate clinical task flow in context-dependent health care settings

Quantifying the Performance of Individual Players in a Team Activity

Teamwork is a fundamental aspect of many human activities, from business to art and from sports to science. Recent research suggest that team work is of crucial importance to cutting-edge scientific research, but little is known about how teamwork leads to greater creativity. Indeed, for many team activities, it is not even clear how to assign credit to individual team members. Remarkably, at least in the context of sports, there is usually a broad consensus on who are the top performers and on what qualifies as an outstanding performance.In order to determine how individual features can be quantified, and as a test bed for other team-based human activities, we analyze the performance of players in the European Cup 2008 soccer tournament. We develop a network approach that provides a powerful quantification of the contributions of individual players and of overall team performance.We hypothesize that generalizations of our approach could be useful in other contexts where quantification of the contributions of individual team members is important

Geocoronal H-A [Alpha] Intensity Measurements Using the Wisconsin H-A [Alpha] Mapper Fabry-Perot Facility

The Wisconsin H-a [alpha] Mapper (WHAM), a remotely operable, semi-automated Fabry-Perot located at Kitt Peak Observatory, has been making an all-sky survey of interstellar hydrogen Balmer a [alpha] (H-a [alpha]) emissions since 1997. Using the annular summing spectroscopy technique, WHAM has acquired ~[approx.] 37,000 spectra to date, spanning almost 100 nights of observations. Since all of the galactic emission spectral data contain the terrestrial H-a [alpha] (6562.7 Å) emission line, these measurements constitute a rich source of geocoronal data for investigating natural variability in the upper atmosphere. The WHAM observations also serve as a benchmark for comparison with future data. Analysis of the first year of WHAM data shows only small day-to-day variations after shadow altitude variations are taken into account. For example, at shadow altitudes of 2000 and 3000 km, the RMS scatter is within approximately +/- 20%; this variability is expected to be reduced with accurate accounting of the smaller-scale effects of observational slant path, zenith angle, and azimuth on the H-a [alpha] intensity. This result is consistent with past midlatitude Wisconsin data sets but different from observations made by other observers and instruments at the low-latitude Arecibo site. The multiple viewing geometries of the observations provide stringent modeling constraints, useful in testing current modeling capabilities. Modeling of the WHAM data with a global nonisothermal resonance radiation transport code (lyao_rt) indicates that the signal-to-noise of the data is sufficient to determine relative variations in upper atmospheric atomic hydrogen column densities to better than 5%. This paper describes the WHAM aeronomy program and its observational scheme, analysis procedures, and results from data taken in 1997. Case study comparisons are made with past data sets and with predictions from the lyao_rt resonant radiation transport modeling code of Bishop [1999]

Impression management and retrospective sense-making in corporate annual reports: banks' graphical reporting during the global financial crisis

This study investigates two potentially complementary reporting scenarios in annual reports: reactive impression management and retrospective sense-making. It examines stock market performance graphs in European listed banks? annual reports before and during the global financial crisis. Our results indicate that banks reacted to the global financial crisis by omitting stock market performance graphs from the annual report and from its most prominent sections. On the other hand, banks reduced favorable distortions and favorable performance comparisons. No significant evidence of retrospective sense-making is found. Overall, the findings are consistent with impression management incorporating human cognitive biases, with companies preferring misrepresentation by omission over misrepresentation by commission. Under high public scrutiny, banks appear to seek to provide a more favorable view by concealing negative information rather than by favorable distortions or comparisons. The study contributes to the development of impression management theories. It uses a psychological interpretation that incorporates human cognitive biases, rather than adopting a purely economically based perspective

The role of usability engineering in the development of an intelligent decision support system

This paper presents an overview of the usability engineering process for the development of a personalised clinical decision support system for the management of type 1 diabetes. The tool uses artificial intelligence (AI) techniques to provide insulin bolus dose advice and carbohydrate recommendations that adapt to the individual. We describe the role of human factors and user-centred design in the creation of medical systems that must adhere to international standards. We focus specifically on the formative evaluation stage of this process. The preliminary analysis of data shows promising results

An abductive process of developing interactive data visualization: a case study of market attractiveness analysis

Part 4: Business Intelligence and AnalyticsInternational audienceData visualization has been widely utilized in various scenarios in data analytics for business purposes, especially helping novice readers make sense of complex dataset with interactive functions. However, due to an insufficient theoretical understanding of the process of developing interactive functions and visual presentations, interactive data visualization tools often display all available automatic graphing functions in front of users, instead of guiding them to choose a visualization based on their demands. Thus, this paper is intended to construct a process of developing interactive visualization with a specific focus on enabling the interoperation between design and interpretation. Stemmed from organizational semiotics, an abductive process will be portrayed in this paper to interpret the process of developing interactive data visualization. Especially the interactive functions will be employed in an iterative process, where producers can be aware of and respond to readers’ information demands on semantic, pragmatic and social levels

How to write an ICS/IUGA conference abstract

Contains fulltext : 88292.pdf (publisher's version ) (Closed access)INTRODUCTION: This article aims to condense the lectures and discussions from workshops on good reporting at IUGA Como 2009 and ICS San Francisco 2009, providing practical advice for the novice researcher summarising their data for the first time. CONCLUSIONS: Drafting an abstract can be a time consuming process. Formal guidance, such as CONSORT and STROBE, exists for the kinds of information that should be included regarding almost all designs of clinical trials. Follow the abstract submission rules closely to avoid outright rejection. Plan to highlight the novelty, scientific merit and clinical impact of the work. Try not to overstate the importance of the findings. Do not forget to publish the work in a peer reviewed journal.1 mei 201

Thermal simulation software outputs: a conceptual data model of information presentation for building design decision-making

Building simulation outputs are inherently complex and numerous. Extracting meaningful information from them requires knowledge which mainly resides only in the hands of experts. Initiatives to address this problem tend either to provide very constrained output data interfaces or leave it to the user to customize data organisation and query. This work proposes a conceptual data model from which meaningful dynamic thermal simulation information for building design decision-making may be constructed and presented to the user. It describes how the model was generated and can become operational, with examples of its applications to practical problems. The paper therefore contains useful information for software developers to help in specifying and designing simulation outputs which better respond to building designers’ needs