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'BioNessie(G) - a grid enabled biochemical networks simulation environment
The simulation of biochemical networks provides insight and
understanding about the underlying biochemical processes and pathways
used by cells and organisms. BioNessie is a biochemical network simulator
which has been developed at the University of Glasgow. This paper
describes the simulator and focuses in particular on how it has been
extended to benefit from a wide variety of high performance compute resources
across the UK through Grid technologies to support larger scale
simulations
Supporting security-oriented, collaborative nanoCMOS electronics research
Grid technologies support collaborative e-Research typified by multiple institutions and resources seamlessly shared to tackle common research problems. The rules for collaboration and resource sharing are commonly achieved through establishment and management of virtual organizations (VOs) where policies on access and usage of resources by collaborators are defined and enforced by sites involved in the collaboration. The expression and enforcement of these rules is made through access control systems where roles/privileges are defined and associated with individuals as digitally signed attribute certificates which collaborating sites then use to authorize access to resources. Key to this approach is that the roles are assigned to the right individuals in the VO; the attribute certificates are only presented to the appropriate resources in the VO; it is transparent to the end user researchers, and finally that it is manageable for resource providers and administrators in the collaboration. In this paper, we present a security model and implementation improving the overall usability and security of resources used in Grid-based e-Research collaborations through exploitation of the Internet2 Shibboleth technology. This is explored in the context of a major new security focused project at the National e-Science Centre (NeSC) at the University of Glasgow in the nanoCMOS electronics domain
BioNessie - a grid enabled biochemical networks simulation environment
The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations
Federated authentication and authorisation for e-science
The Grid and Web service community are defining a range of standards for a complete solution for security. The National e-Science Centre (NeSC) at the University of Glasgow is investigating how the various pre-integration components work together in a variety of e-Science projects. The EPSRC-funded nanoCMOS project aims to allow electronics designers and manufacturers to use e-Science technologies and expertise to solve problems of device variability and its impact on system design. To support the security requirements of nanoCMOS, two NeSC projects (VPMan and OMII-SP) are providing tools to allow easy configuration of security infrastructures, exploiting previous successful projects using Shibboleth and PERMIS. This paper presents the model in which these tools interoperate to provide secure and simple access to Grid resources for non-technical users
Gates to Gregg High Voltage Transmission Line Study
The usefulness of LANDSAT data in the planning of transmission line routes was assessed. LANDSAT digital data and image processing techniques, specifically a multi-date supervised classification aproach, were used to develop a land cover map for an agricultural area near Fresno, California. Twenty-six land cover classes were identified, of which twenty classes were agricultural crops. High classification accuracies (greater than 80%) were attained for several classes, including cotton, grain, and vineyards. The primary products generated were 1:24,000, 1:100,000 and 1:250,000 scale maps of the classification and acreage summaries for all land cover classes within four alternate transmission line routes
On the Interpretation of Supernova Light Echo Profiles and Spectra
The light echo systems of historical supernovae in the Milky Way and local
group galaxies provide an unprecedented opportunity to reveal the effects of
asymmetry on observables, particularly optical spectra. Scattering dust at
different locations on the light echo ellipsoid witnesses the supernova from
different perspectives and the light consequently scattered towards Earth
preserves the shape of line profile variations introduced by asymmetries in the
supernova photosphere. However, the interpretation of supernova light echo
spectra to date has not involved a detailed consideration of the effects of
outburst duration and geometrical scattering modifications due to finite
scattering dust filament dimension, inclination, and image point-spread
function and spectrograph slit width. In this paper, we explore the
implications of these factors and present a framework for future resolved
supernova light echo spectra interpretation, and test it against Cas A and SN
1987A light echo spectra. We conclude that the full modeling of the dimensions
and orientation of the scattering dust using the observed light echoes at two
or more epochs is critical for the correct interpretation of light echo
spectra. Indeed, without doing so one might falsely conclude that differences
exist when none are actually present.Comment: 18 pages, 22 figures, accepted for publication in Ap
HypTrails: A Bayesian Approach for Comparing Hypotheses About Human Trails on the Web
When users interact with the Web today, they leave sequential digital trails
on a massive scale. Examples of such human trails include Web navigation,
sequences of online restaurant reviews, or online music play lists.
Understanding the factors that drive the production of these trails can be
useful for e.g., improving underlying network structures, predicting user
clicks or enhancing recommendations. In this work, we present a general
approach called HypTrails for comparing a set of hypotheses about human trails
on the Web, where hypotheses represent beliefs about transitions between
states. Our approach utilizes Markov chain models with Bayesian inference. The
main idea is to incorporate hypotheses as informative Dirichlet priors and to
leverage the sensitivity of Bayes factors on the prior for comparing hypotheses
with each other. For eliciting Dirichlet priors from hypotheses, we present an
adaption of the so-called (trial) roulette method. We demonstrate the general
mechanics and applicability of HypTrails by performing experiments with (i)
synthetic trails for which we control the mechanisms that have produced them
and (ii) empirical trails stemming from different domains including website
navigation, business reviews and online music played. Our work expands the
repertoire of methods available for studying human trails on the Web.Comment: Published in the proceedings of WWW'1
Enabling quantitative data analysis through e-infrastructures
This paper discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities which are central to quantitative data analysis, referred to as ‘data management’, can benefit from e-infrastructure support. We conclude by discussing how these issues are relevant to the DAMES (Data Management through e-Social Science) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences
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