1,221,658 research outputs found
Projection predictive model selection for Gaussian processes
We propose a new method for simplification of Gaussian process (GP) models by
projecting the information contained in the full encompassing model and
selecting a reduced number of variables based on their predictive relevance.
Our results on synthetic and real world datasets show that the proposed method
improves the assessment of variable relevance compared to the automatic
relevance determination (ARD) via the length-scale parameters. We expect the
method to be useful for improving explainability of the models, reducing the
future measurement costs and reducing the computation time for making new
predictions.Comment: A few minor changes in tex
Magnetic energy-level diagrams of high-spin (Mn-acetate) and low-spin (V) molecules
The magnetic energy-level diagrams for models of the Mn12 and V15 molecule
are calculated using the Lanczos method with full orthogonalization and a
Chebyshev-polynomial-based projector method. The effect of the
Dzyaloshinskii-Moriya interaction on the appearance of energy-level repulsions
and its relevance to the observation of steps in the time-dependent
magnetization data is studied. We assess the usefulness of simplified models
for the description of the zero-temperature magnetization dynamics
Gauge Theories, Spin Glasses and Real Glasses
In this talk I will show that usual spin glasses are a peculiar kind of
Abelian gauge theory. I will shortly review the techniques used to study them.
At the end I will consider more general models (e.g. spin glasses based on non
Abelian gauge group) and I will discuss the relevance of these models to real
glasses. Finally I will derive from first principles a generalised
Vogel-Fulcher law for the divergence of the characteristic time near the glass
transition
Bounds on the Per-Sample Capacity of Zero-Dispersion Simplified Fiber-Optical Channel Models
A number of simplified models, based on perturbation theory, have been
proposed for the fiber-optical channel and have been extensively used in the
literature. Although these models are mainly developed for the low-power
regime, they are used at moderate or high powers as well. It remains unclear to
what extent the capacity of these models is affected by the simplifying
assumptions under which they are derived. In this paper, we consider single
channel data transmission based on three continuous-time optical models i) a
regular perturbative channel, ii) a logarithmic perturbative channel, and iii)
the stochastic nonlinear Schr\"odinger (NLS) channel. We apply two simplifying
assumptions on these channels to obtain analytically tractable discrete-time
models. Namely, we neglect the channel memory (fiber dispersion) and we use a
sampling receiver. These assumptions bring into question the physical relevance
of the models studied in the paper. Therefore, the results should be viewed as
a first step toward analyzing more realistic channels. We investigate the
per-sample capacity of the simplified discrete-time models. Specifically, i) we
establish tight bounds on the capacity of the regular perturbative channel; ii)
we obtain the capacity of the logarithmic perturbative channel; and iii) we
present a novel upper bound on the capacity of the zero-dispersion NLS channel.
Our results illustrate that the capacity of these models departs from each
other at high powers because these models yield different capacity pre-logs.
Since all three models are based on the same physical channel, our results
highlight that care must be exercised in using simplified channel models in the
high-power regime
Modeling bursts and heavy tails in human dynamics
Current models of human dynamics, used from risk assessment to
communications, assume that human actions are randomly distributed in time and
thus well approximated by Poisson processes. We provide direct evidence that
for five human activity patterns the timing of individual human actions follow
non-Poisson statistics, characterized by bursts of rapidly occurring events
separated by long periods of inactivity. We show that the bursty nature of
human behavior is a consequence of a decision based queuing process: when
individuals execute tasks based on some perceived priority, the timing of the
tasks will be heavy tailed, most tasks being rapidly executed, while a few
experiencing very long waiting times. We discuss two queueing models that
capture human activity. The first model assumes that there are no limitations
on the number of tasks an individual can hadle at any time, predicting that the
waiting time of the individual tasks follow a heavy tailed distribution with
exponent alpha=3/2. The second model imposes limitations on the queue length,
resulting in alpha=1. We provide empirical evidence supporting the relevance of
these two models to human activity patterns. Finally, we discuss possible
extension of the proposed queueing models and outline some future challenges in
exploring the statistical mechanisms of human dynamics.Comment: RevTex, 19 pages, 8 figure
Modelling public transport accessibility with Monte Carlo stochastic simulations: A case study of Ostrava
Activity-based micro-scale simulation models for transport modelling provide better evaluations of public transport accessibility, enabling researchers to overcome the shortage of reliable real-world data. Current simulation systems face simplifications of personal behaviour, zonal patterns, non-optimisation of public transport trips (choice of the fastest option only), and do not work with real targets and their characteristics. The new TRAMsim system uses a Monte Carlo approach, which evaluates all possible public transport and walking origin-destination (O-D) trips for k-nearest stops within a given time interval, and selects appropriate variants according to the expected scenarios and parameters derived from local surveys. For the city of Ostrava, Czechia, two commuting models were compared based on simulated movements to reach (a) randomly selected large employers and (b) proportionally selected employers using an appropriate distance-decay impedance function derived from various combinations of conditions. The validation of these models confirms the relevance of the proportional gravity-based model. Multidimensional evaluation of the potential accessibility of employers elucidates issues in several localities, including a high number of transfers, high total commuting time, low variety of accessible employers and high pedestrian mode usage. The transport accessibility evaluation based on synthetic trips offers an improved understanding of local situations and helps to assess the impact of planned changes.Web of Science1124art. no. 709
A Study on the Parallelization of Terrain-Covering Ant Robots Simulations
Agent-based simulation is used as a tool for supporting (time-critical) decision making in differentiated contexts. Hence, techniques for speeding up the execution of agent-based models, such as Parallel Discrete Event Simulation (PDES), are of great relevance/benefit. On the other hand, parallelism entails that the final output provided by the simulator should closely match the one provided by a traditional sequential run. This is not obvious given that, for performance and efficiency reasons, parallel simulation engines do not allow the evaluation of global predicates on the simulation model evolution with arbitrary time-granularity along the simulation time-Axis. In this article we present a study on the effects of parallelization of agent-based simulations, focusing on complementary aspects such as performance and reliability of the provided simulation output. We target Terrain Covering Ant Robots (TCAR) simulations, which are useful in rescue scenarios to determine how many agents (i.e., robots) should be used to completely explore a certain terrain for possible victims within a given time. © 2014 Springer-Verlag Berlin Heidelberg
Outflow boundary conditions for 3D simulations of non-periodic blood flow and pressure fields in deformable arteries
The simulation of blood flow and pressure in arteries requires outflow
boundary conditions that incorporate models of downstream domains. We
previously described a coupled multidomain method to couple analytical models
of the downstream domains with 3D numerical models of the upstream vasculature.
This prior work either included pure resistance boundary conditions or
impedance boundary conditions based on assumed periodicity of the solution.
However, flow and pressure in arteries are not necessarily periodic in time due
to heart rate variability, respiration, complex transitional flow or acute
physiological changes. We present herein an approach for prescribing lumped
parameter outflow boundary conditions that accommodate transient phenomena. We
have applied this method to compute haemodynamic quantities in different
physiologically relevant cardiovascular models, including patient-specific
examples, to study non-periodic flow phenomena often observed in normal
subjects and in patients with acquired or congenital cardiovascular disease.
The relevance of using boundary conditions that accommodate transient phenomena
compared with boundary conditions that assume periodicity of the solution is
discussed
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