Visual support for the understanding of simulation processes

Current visualization systems are typically based on the concept of interactive post-processing. This decoupling of data visualiza-tion from the process of data generation offers a flexible applica-tion of visualization tools. It can also lead, however, to information loss in the visualization. Therefore, a combination of the visual-ization of the data generating process with the visualization of the produced data offers significant support for the understanding of the abstract data sets as well as the underlying process. Due to the application-specific characteristics of data generating processes, the task requires tailored visualization concepts. In this work, we focus on the application field of simulating biochemical reaction networks as discrete-event systems. These stochastic processes generate multi-run and multivariate time-series, which are analyzed and compared on three different process levels: model, experiment, and the level of multi-run simulation data, each associated with a broad range of analysis goals. To meet these challenging characteristics, we present visualization concepts specifically tailored to all three process levels. The fundament of all three visualization concepts is a compact view that relates the multi-run simulation data to the characteristics of the model structure and the experiment. The view provides the visualization at the experi-ment level. The visualization at the model level coordinates mul-tiple instances of this view for the comparison of experiments. At the level of multi-run simulation data, the views gives an overview on the data, which can be analyzed in detail in time-series views suited for the analysis goals. Although we derive our visualization concepts for one concrete simulation process, our general concept of tailoring the visualization concepts to process levels is generally applicable for the visualization of simulation processes

A User-Based Look at Visualization Tools for Environmental Data and Suggestions for Improvement - An Inventory among City Planners in Gothenburg

With a growing interest in environmental data and the need to consider various environmental factors earlier in the planning processes, it becomes more important to disseminate this type of information to different target groups in a comprehensible way. To support easier decision making, many cities and municipalities are increasingly using digital city models where it is possible to integrate different types of information based on simulation and visualization of future scenarios. Such tools have high potential, but the visual representation of data still needs to be developed. In this paper, we investigate how professionals within urban planning currently use visualization to communicate environmental data, and what their needs are regarding tools and visual representation. We discuss challenges for representing environmental data in urban development processes, with the aim of contributing to a better understanding of these issues. We base our investigation on a literature study, an inventorying survey and a focus group discussion with professionals within urban planning. This study provides an end-user perspective among urban planners and valuable insights on tool usage and visualization. Results show that applications used for environmental visualization still can be improved regarding, e.g., user friendliness and information handling, which may increase their efficiency

Modelling and simulating unplanned and urgent healthcare: the contribution of scenarios of future healthcare systems.

The current financial challenges being faced by the UK economy have meant that the NHS will have to make £20 billion of savings between 2010 and 2014 requiring it to be innovative about how it delivers healthcare. This paper presents the methodology of a research project that is simulating the whole healthcare system with the aim of reducing waste within urgent unscheduled care streams whilst understanding the impact of such changes on the whole system. The research is aimed at care commissioners who could use such simulation in their decision-making practice, and the paper presents the findings from early stakeholder discussions about the scope and focus of the research and the relevance of stakeholder consultation and scenarios in the development of a valid decision-support tool that is fit for purpose

A multi-faceted approach to optimising a complex unplanned healthcare system

Unscheduled and urgent health care represents the largest area of activity and cost for the UK’s National Health Service (NHS). Like typical complex systems unplanned care has the features of interdependence and having structures at different scales which requires modelling at different levels. The aim of this paper is to discuss the development of a multifaceted approach to study and optimise this complex system. We aim to integrate four different methodologies to gain better understanding of the nature of the system and to develop ways to enhance its performance. These methodologies are: (a) Lean/ Flow theory to look at the process and patients and other flows; (b) Simulation/ System Dynamics to undertake analytical analysis and multi-level modelling; (c) stakeholder consultation and use of system thinking to analyse the system and identify options, barriers and good practice; and (d) visual analytic modelling to facilitate effective decision making in this complex environment. Of particular concern are the boundary issues i.e. how changes in unplanned care will impact on the adjacent facilities and ultimately on the whole Healthcare system

At the mercy of strategies: the role of motor representations in language understanding

Classical cognitive theories hold that word representations in the brain are abstract and amodal, and are independent of the objects\u2019 sensorimotor properties they refer to. An alternative hypothesis emphasizes the importance of bodily processes in cognition: the representation of a concept appears to be crucially dependent upon perceptual-motor processes that relate to it. Thus, understanding action-related words would rely upon the same motor structures that also support the execution of the same actions. In this context, motor simulation represents a key component. Our approach is to draw parallels between the literature on mental rotation and the literature on action verb/sentence processing. Here we will discuss recent studies on mental imagery, mental rotation, and language that clearly demonstrate how motor simulation is neither automatic nor necessary to language understanding. These studies have shown that motor representations can or cannot be activated depending on the type of strategy the participants adopt to perform tasks involv- ing motor phrases. On the one hand, participants may imagine the movement with the body parts used to carry out the actions described by the verbs (i.e., motor strategy); on the other, individuals may solve the task without simulating the corresponding movements (i.e., visual strategy). While it is not surprising that the motor strategy is at work when par- ticipants process action-related verbs, it is however striking that sensorimotor activation has been reported also for imageable concrete words with no motor content, for \u201cnon- words\u201d with regular phonology, for pseudo-verb stimuli, and also for negations. Based on the extant literature, we will argue that implicit motor imagery is not uniquely used when a body-related stimulus is encountered, and that it is not the type of stimulus that automat- ically triggers the motor simulation but the type of strategy. Finally, we will also comment on the view that sensorimotor activations are subjected to a top-down modulation

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

A MATLAB graphical user interface for battery design and simulation; from cell test data to real-world automotive simulation

This paper describes a graphical user interface (GUI) tool designed to support cell design and development of manufacturing processes for an automotive battery application. The GUI is built using the MATLAB environment and is able to load and analyze raw test data as its input. After data processing, a cell model is fitted to the experimental data using system identification techniques. The cell model's parameters (such as open-circuit-voltage and ohmic resistance) are displayed to the user as functions of state of charge, providing a visual understanding of the cell's characteristics. The GUI is also able to simulate the performance of a full battery pack consisting of a specified number of single cells using standard driving cycles and a generic electric vehicle model. After a simulation, the battery designer is able to see how well the vehicle would be able to follow the driving cycle using the tested cells. Although the GUI is developed for an automotive application, it could be extended to other applications as well. The GUI has been designed to be easily used by non-simulation experts (i.e. battery designers or electrochemists) and it is fully automated, only requiring the user to supply the location of raw test data

The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling

Multiple roles of motor imagery during action observation

Over the last 20 years, the topics of action observation (AO) and motor imagery (MI) have been largely studied in isolation from each other, despite the early integrative account by Jeannerod (1994, 2001). Recent neuroimaging studies demonstrate enhanced cortical activity when AO and MI are performed concurrently (“AO+MI”), compared to either AO or MI performed in isolation. These results indicate the potentially beneficial effects of AO+MI, and they also demonstrate that the underlying neurocognitive processes are partly shared. We separately review the evidence for MI and AO as forms of motor simulation, and present two quantitative literature analyses that indeed indicate rather little overlap between the two bodies of research. We then propose a spectrum of concurrent AO+MI states, from congruent AO+MI where the contents of AO and MI widely overlap, over coordinative AO+MI, where observed and imagined action are different but can be coordinated with each other, to cases of conflicting AO+MI. We believe that an integrative account of AO and MI is theoretically attractive, that it should generate novel experimental approaches, and that it can also stimulate a wide range of applications in sport, occupational therapy, and neurorehabilitation