161,405 research outputs found
Route Planning in Transportation Networks
We survey recent advances in algorithms for route planning in transportation
networks. For road networks, we show that one can compute driving directions in
milliseconds or less even at continental scale. A variety of techniques provide
different trade-offs between preprocessing effort, space requirements, and
query time. Some algorithms can answer queries in a fraction of a microsecond,
while others can deal efficiently with real-time traffic. Journey planning on
public transportation systems, although conceptually similar, is a
significantly harder problem due to its inherent time-dependent and
multicriteria nature. Although exact algorithms are fast enough for interactive
queries on metropolitan transit systems, dealing with continent-sized instances
requires simplifications or heavy preprocessing. The multimodal route planning
problem, which seeks journeys combining schedule-based transportation (buses,
trains) with unrestricted modes (walking, driving), is even harder, relying on
approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4,
previously published by Microsoft Research. This work was mostly done while
the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at
Microsoft Research Silicon Valle
Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines
In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using Integer Programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of-the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work.Universidad de Málaga. Campus de Excelencia Internacional AndalucÃa Tech. Partially funded by the Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2014-57341-R, the University of Málaga, AndalucÃa Tech and the Spanish Network TIN2015-71841-REDT (SEBASENet)
Global and regional brain metabolic scaling and its functional consequences
Background: Information processing in the brain requires large amounts of
metabolic energy, the spatial distribution of which is highly heterogeneous
reflecting complex activity patterns in the mammalian brain.
Results: Here, it is found based on empirical data that, despite this
heterogeneity, the volume-specific cerebral glucose metabolic rate of many
different brain structures scales with brain volume with almost the same
exponent around -0.15. The exception is white matter, the metabolism of which
seems to scale with a standard specific exponent -1/4. The scaling exponents
for the total oxygen and glucose consumptions in the brain in relation to its
volume are identical and equal to , which is significantly larger
than the exponents 3/4 and 2/3 suggested for whole body basal metabolism on
body mass.
Conclusions: These findings show explicitly that in mammals (i)
volume-specific scaling exponents of the cerebral energy expenditure in
different brain parts are approximately constant (except brain stem
structures), and (ii) the total cerebral metabolic exponent against brain
volume is greater than the much-cited Kleiber's 3/4 exponent. The
neurophysiological factors that might account for the regional uniformity of
the exponents and for the excessive scaling of the total brain metabolism are
discussed, along with the relationship between brain metabolic scaling and
computation.Comment: Brain metabolism scales with its mass well above 3/4 exponen
Metabolic analyzer
An apparatus is described for the measurement of metabolic rate and breathing dynamics in which inhaled and exhaled breath are sensed by sealed, piston-displacement type spirometers. These spirometers electrically measure the volume of inhaled and exhaled breath. A mass spectrometer analyzes simultaneously for oxygen, carbon dioxide, nitrogen and water vapor. Computation circuits are responsive to the outputs of the spirometers, mass spectrometer, temperature, pressure and timing signals and compute oxygen consumption, carbon dioxide production, minute volume and respiratory exchange ratio. A selective indicator provides for read-out of these data at predetermined cyclic intervals
Denial of Service in Voice Over IP Networks
In this paper we investigate denial of service (DoS) vulnerabilities in Voice over IP (VoIP) systems, focusing on the ITU-T H.323 family of protocols. We provide a simple characterisation of DoS attacks that allows us to readily identify DoS issues in H.323 protocols. We also discuss network layer DoS vulnerabilities that affect VoIP systems. A number of improvements and further research directions are proposed
Data-driven modelling of biological multi-scale processes
Biological processes involve a variety of spatial and temporal scales. A
holistic understanding of many biological processes therefore requires
multi-scale models which capture the relevant properties on all these scales.
In this manuscript we review mathematical modelling approaches used to describe
the individual spatial scales and how they are integrated into holistic models.
We discuss the relation between spatial and temporal scales and the implication
of that on multi-scale modelling. Based upon this overview over
state-of-the-art modelling approaches, we formulate key challenges in
mathematical and computational modelling of biological multi-scale and
multi-physics processes. In particular, we considered the availability of
analysis tools for multi-scale models and model-based multi-scale data
integration. We provide a compact review of methods for model-based data
integration and model-based hypothesis testing. Furthermore, novel approaches
and recent trends are discussed, including computation time reduction using
reduced order and surrogate models, which contribute to the solution of
inference problems. We conclude the manuscript by providing a few ideas for the
development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and
Multiscale Dynamics (American Scientific Publishers
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