50,280 research outputs found
Embedded Network Test-Bed for Validating Real-Time Control Algorithms to Ensure Optimal Time Domain Performance
The paper presents a Stateflow based network test-bed to validate real-time
optimal control algorithms. Genetic Algorithm (GA) based time domain
performance index minimization is attempted for tuning of PI controller to
handle a balanced lag and delay type First Order Plus Time Delay (FOPTD)
process over network. The tuning performance is validated on a real-time
communication network with artificially simulated stochastic delay, packet loss
and out-of order packets characterizing the network.Comment: 6 pages, 12 figure
A modified Next Reaction Method for simulating chemical systems with time dependent propensities and delays
Chemical reaction systems with a low to moderate number of molecules are
typically modeled as discrete jump Markov processes. These systems are
oftentimes simulated with methods that produce statistically exact sample paths
such as the Gillespie Algorithm or the Next Reaction Method. In this paper we
make explicit use of the fact that the initiation times of the reactions can be
represented as the firing times of independent, unit rate Poisson processes
with internal times given by integrated propensity functions. Using this
representation we derive a modified Next Reaction Method and, in a way that
achieves efficiency over existing approaches for exact simulation, extend it to
systems with time dependent propensities as well as to systems with delays.Comment: 25 pages, 1 figure. Some minor changes made to add clarit
Increasing resilience of ATM networks using traffic monitoring and automated anomaly analysis
Systematic network monitoring can be the cornerstone for
the dependable operation of safety-critical distributed
systems. In this paper, we present our vision for informed
anomaly detection through network monitoring and
resilience measurements to increase the operators'
visibility of ATM communication networks. We raise the
question of how to determine the optimal level of
automation in this safety-critical context, and we present a
novel passive network monitoring system that can reveal
network utilisation trends and traffic patterns in diverse
timescales. Using network measurements, we derive
resilience metrics and visualisations to enhance the
operators' knowledge of the network and traffic behaviour,
and allow for network planning and provisioning based on
informed what-if analysis
Simulation of networks of spiking neurons: A review of tools and strategies
We review different aspects of the simulation of spiking neural networks. We
start by reviewing the different types of simulation strategies and algorithms
that are currently implemented. We next review the precision of those
simulation strategies, in particular in cases where plasticity depends on the
exact timing of the spikes. We overview different simulators and simulation
environments presently available (restricted to those freely available, open
source and documented). For each simulation tool, its advantages and pitfalls
are reviewed, with an aim to allow the reader to identify which simulator is
appropriate for a given task. Finally, we provide a series of benchmark
simulations of different types of networks of spiking neurons, including
Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based
or conductance-based synapses, using clock-driven or event-driven integration
strategies. The same set of models are implemented on the different simulators,
and the codes are made available. The ultimate goal of this review is to
provide a resource to facilitate identifying the appropriate integration
strategy and simulation tool to use for a given modeling problem related to
spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of
Computational Neuroscience, in press (2007
A hierarchy for modeling high speed propulsion systems
General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery, such as inlets, ramjets, and scramjets. The discussion is separated into four areas: (1) computational fluid dynamics models for the entire nonlinear system or high order nonlinear models; (2) high order linearized models derived from fundamental physics; (3) low order linear models obtained from the other high order models; and (4) low order nonlinear models (order here refers to the number of dynamic states). Included in the discussion are any special considerations based on the relevant control system designs. The methods discussed are for the quasi-one-dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, including moving normal shocks, hammershocks, simple subsonic combustion via heat addition, temperature dependent gases, detonations, and thermal choking. The report also contains a comprehensive list of papers and theses generated by this grant
The impact of using pair programming on system evolution a simulation-based study
In this paper we investigate the impact of pair--programming on the long term evolution of software systems. We use system dynamics to build simulation models which predict the trend in system growth with and without pair programming. Initial results suggest that the extra effort needed for two people to code together may generate sufficient benefit to justify pair programming.Peer reviewe
Simulating Impacts of Extreme Weather Events on Urban Transport Infrastructure in the UK
Urban areas face many risks from future climate change and their infrastructure will be placed under more pressure
due to changes in climate extremes. Using the Tyndall Centre Urban Integrated Assessment Framework, this paper
describes a methodology used to assess the impacts of future climate extremes on transport infrastructure in
London. Utilising high-resolution projections for future climate in the UK, alongside stochastic weather generators
for downscaling, urban temperature and flooding models are used to provide information on the likelihood of future
extremes. These are then coupled with spatial network models of urban transport infrastructure and, using thresholds
to define the point at which systems cease to function normally, disruption to the networks can be simulated.
Results are shown for both extreme heat and urban surface water flooding events and the impacts on the travelling
population, in terms of both disruption time and monetary cost
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