Techniques and tools for parallelizing software

With the emergence of multicore and manycore processors, engineers must design and develop software in drastically new ways to benefit from the computational power of all cores. However, developing parallel software is much harder than sequential software because parallelism can't be abstracted away easily. Authors Hans Vandierendonck and Tom Mens provide an overview of technologies and tools to support developers in this complex and error-prone task. © 2012 IEEE.

JISC Workshop Report: E-Research Resources, Tools and Methods for Historic Place Name Analysis

A substantial amount of the 'critical mass' of digital data available to scholarship contains place-names, and it is now recognised that spatial and temporal data points, including place-names, are a vital part of the e-research infrastructure that supports the use, re-use and advanced analysis of data using ICT tools and methods. Place-names can also be linked semantically to contribute to the web of data, and to enrich content through linking existing data, and identifying new collections for digitization to strategically enhance existing digital collections. However, existing e-projects rely on modern gazetteers limiting them to the modern and the near-contemporary. This workshop explored how to further integrate the wealth of historical place-name scholarship, and the resulting digital resources generated within UK academia, so enabling integration of local knowledge over much longer periods.

Accessibility and Health: Towards Walkability Tools for Planning Practice

There is increasing research interest in how we can most effectively intervene in the built environment to change behaviours such as physical activity and improve health. Much of this work has focussed around the concept of walkability and the identification of those attributes of our cities that encourage pedestrian activity, including density, connectivity and the aesthetic of the urban realm (Saelens et al 2003, Frank et al 2010). Much of the existing research has clarified the strength of the relationships between various environmental attributes and the differential impact on different demographic groups (e.g. Panter et al 2011). This has not yet been effectively translated into tools to help integrate the concepts of walkability into decision-making by statutory authorities that can help shape the spatial development and delivery of public services which can support more active lifestyles. A key reason for this has been that standard models for transport planning and accessibility are based on networks of road infrastructure, which provides a weak basis for modelling pedestrian accessibility (Chin et al 2008).

This paper reports the findings of Knowledge Exchange project funded by UK’s Economic and Social Research Council (ES/J010588/1) and partners including Belfast and Derry City Councils and Northern Ireland’s Public Health Agency, the Department of Regional Development and Belfast Healthy Cities, that has attempted to address this problem. This project has mapped city-wide footpath networks and used these to assist partner organisations in developing the evidence base for making decisions on public services based on health impacts and pedestrian access. The paper describes the tool developed, uses a number of examples to highlight its impact on areas of decision-making and evaluates the benefits of further integrating walkability into planning and development practice.

Using Mesh-Geometry Relationships to Transfer Analysis Models between CAE Tools

Integrating analysis and design models is a complex task due to differences between the models and the architectures of the toolsets used to create them. This complexity is increased with the use of many different tools for specific tasks during an analysis process. In this work various design and analysis models are linked throughout the design lifecycle, allowing them to be moved between packages in a way not currently available. Three technologies named Cellular Modeling, Virtual Topology and Equivalencing are combined to demonstrate how different finite element meshes generated on abstract analysis geometries can be linked to their original geometry. Establishing the equivalence relationships between models enables analysts to utilize multiple packages for specialist tasks without worrying about compatibility issues or rework.

Parallels between machine and brain decoding

We report some existing work, inspired by analogies between human thought and machine computation, showing that the informational state of a digital computer can be decoded in a similar way to brain decoding. We then discuss some proposed work that would leverage this analogy to shed light on the amount of information that may be missed by the technical limitations of current neuroimaging technologies. © 2012 Springer-Verlag.

Decoding semantics across fMRI sessions with different stimulus modalities:a practical MVPA study

Both embodied and symbolic accounts of conceptual organization would predict partial sharing and partial differentiation between the neural activations seen for concepts activated via different stimulus modalities. But cross-participant and cross-session variability in BOLD activity patterns makes analyses of such patterns with MVPA methods challenging. Here, we examine the effect of cross-modal and individual variation on the machine learning analysis of fMRI data recorded during a word property generation task. We present the same set of living and non-living concepts (land-mammals, or work tools) to a cohort of Japanese participants in two sessions: the first using auditory presentation of spoken words; the second using visual presentation of words written in Japanese characters. Classification accuracies confirmed that these semantic categories could be detected in single trials, with within-session predictive accuracies of 80-90%. However cross-session prediction (learning from auditory-task data to classify data from the written-word-task, or vice versa) suffered from a performance penalty, achieving 65-75% (still individually significant at p « 0.05). We carried out several follow-on analyses to investigate the reason for this shortfall, concluding that distributional differences in neither time nor space alone could account for it. Rather, combined spatio-temporal patterns of activity need to be identified for successful cross-session learning, and this suggests that feature selection strategies could be modified to take advantage of this.