Perceptual user interface framework for immersive information retrieval environments (An experimental framework for testing and rapid iteration)

The use of perceptual inputs is an emerging area within HCI that suggests a developing Perceptual User Interface (PUI) that may prove advantageous for those involved in mobile serious games and immersive social network environments. Since there are a large variety of input devices, software platforms, possible interactions, and myriad ways to combine all of the above elements in pursuit of a PUI, we propose in this paper a basic experimental framework that will be able to standardize study of the wide range of interactive applications for testing efficacy in learning or information retrieval and also suggest improvements to emerging PUIs by enabling quick iteration. This rapid iteration will start to define a targeted range of interactions that will be intuitive and comfortable as perceptual inputs, and enhance learning and information retention in comparison to traditional GUI systems. The work focuses on the planning of the technical development of two scenarios, and the first steps in developing a framework to evaluate these and other PUIs for efficacy and pedagogy.

Enabling Scientific Workflow Sharing through Coarse-Grained Interoperability

E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.

Development of user-friendly, high throughput screening for ligands and inhibitors of carbohydrate modifying enzymes

This paper describes the impact of cloud computing and the use of GPUs on the performance of Autodock and Gromacs respectively. Cloud computing was applicable to reducing the ‘‘tail’’ seen in running Autodock on desktop grids and the GPU version of Gromacs showed significant improvement over the CPU version. A large (200,000 compounds) library of small molecules, seven sialic acid analogues of the putative substrate and 8000 sugar molecules were converted into pdbqt format and used to interrogate the Trichomonas vaginalis neuraminidase using Autodock Vina. Good binding energy was noted for some of the small molecules (~-9 kcal/mol), but the sugars bound with affinity of less than -7.6 kcal/mol. The screening of the sugar library resulted in a ‘‘top hit’’ with a-2,3-sialyllacto-N-fucopentaose III, a derivative of the sialyl Lewisx structure and a known substrate of the enzyme. Indeed in the top 100 hits 8 were related to this structure. A comparison of Autodock Vina and Autodock 4.2 was made for the high affinity small molecules and in some cases the results were superimposable whereas in others, the match was less good. The validation of this work will require extensive ‘‘wet lab’’ work to determine the utility of the workflow in the prediction of potential enzyme inhibitors.

Crowdsourcing User-Contributed Solutions to Aerospace Product Development Issues through Micro-Blogging

Revenue and production output of the United Kingdom’s Aerospace Industry (AI) is growing year on year and the need to develop new products and innovative enhancements to existing ranges is creating a critical need for the increased utilisation and sharing of employee knowledge. The capture of employee knowledge within the UK’s AI is vital if it is to retain its pre-eminent position in the global marketplace. Crowdsourcing, as a collaborative problem solving activity, allows employees to capture explicit knowledge from colleagues and teams and also offers the potential to extract previously unknown tacit knowledge in a less formal virtual environment. By using micro-blogging as a mechanism, a conceptual framework is proposed to illustrate how companies operating in the AI may improve the capture of employee knowledge to address production-related problems through the use of crowdsourcing. Subsequently, the framework has been set against the background of the product development process proposed by Maylor in 1996 and illustrates how micro-blogging may be used to crowdsource ideas and solutions during product development. Initial validation of the proposed framework is reported, using a focus group of 10 key actors from the collaborating organisation, identifying the perceived advantages, disadvantages and concerns of the framework; results indicate that the activity of micro-blogging for crowdsourcing knowledge relating to product development issues would be most beneficial during product conceptualisation due to the requirement for successful innovation.