Search results for "Bayesian"

Using recursive Bayesian estimation for matching GPS measurements to imperfect road network data

2010

Map-matching refers to the process of projecting positioning measurements to a location on a digital road network map. It is an important element of intelligent transportation systems (ITS) focusing on driver assistance applications, on emergency and incident management, arterial and freeway management, and other applications. This paper addresses the problem of map-matching in the applications characterized by imperfect map quality and restricted computational resources - e.g. in the context of community-based ITS applications. Whereas a number of map-matching methods are available, often these methods rely on topological analysis, thereby making them sensitive to the map inaccuracies. In …

An adaptive probabilistic graphical model for representing skills in PbD settings

2010

Learning Bayesian Metanetworks from Data with Multilevel Uncertainty

2006

Managing knowledge by maintaining it according to dynamic context is among the basic abilities of a knowledge-based system. The two main challenges in managing context in Bayesian networks are the introduction of contextual (in)dependence and Bayesian multinets. We are presenting one possible implementation of a context sensitive Bayesian multinet-the Bayesian Metanetwork, which implies that interoperability between component Bayesian networks (valid in different contexts) can be also modelled by another Bayesian network. The general concepts and two kinds of such Metanetwork models are considered. The main focus of this paper is learning procedure for Bayesian Metanetworks.

A Bayesian Learning Automata-Based Distributed Channel Selection Scheme for Cognitive Radio Networks

2014

We consider a scenario where multiple Secondary Users SUs operate within a Cognitive Radio Network CRN which involves a set of channels, where each channel is associated with a Primary User PU. We investigate two channel access strategies for SU transmissions. In the first strategy, the SUs will send a packet directly without operating Carrier Sensing Medium Access/Collision Avoidance CSMA/CA whenever a PU is absent in the selected channel. In the second strategy, the SUs implement CSMA/CA to further reduce the probability of collisions among co-channel SUs. For each strategy, the channel selection problem is formulated and demonstrated to be a so-called "Potential" game, and a Bayesian Lea…

Multiscale variation in drought controlled historical forest fire activity in the boreal forests of eastern Fennoscandia

2017

Forest fires are a key disturbance in boreal forests, and characteristics of fire regimes are among the most important factors explaining the variation in forest structure and species composition. The occurrence of fire is connected with climate, but earlier, mostly local-scale studies in the northern European boreal forests have provided little insight into fire-climate relationship before the modern fire suppression period. Here, we compiled annually resolved fire history, temperature, and precipitation reconstructions from eastern Fennoscandia from the mid-16th century to the end of the 19th century, a period of strong human influence on fires. We used synchrony of fires over the network…

Upper limits on the isotropic gravitational-wave background from Advanced LIGO and Advanced Virgo's third observing run

2021

We report results of a search for an isotropic gravitational-wave background (GWB) using data from Advanced LIGO's and Advanced Virgo's third observing run (O3) combined with upper limits from the earlier O1 and O2 runs. Unlike in previous observing runs in the advanced detector era, we include Virgo in the search for the GWB. The results are consistent with uncorrelated noise, and therefore we place upper limits on the strength of the GWB. We find that the dimensionless energy density $\Omega_{\rm GW}\leq 5.8\times 10^{-9}$ at the 95% credible level for a flat (frequency-independent) GWB, using a prior which is uniform in the log of the strength of the GWB, with 99% of the sensitivity comi…

The role of loudness in detection of surprising events in music recordings

2009

The abrupt change of loudness is a salient event that is not always expected by a music listener. Therefore loudness is an important cue when seeking for events in a music stream that could violate human expectations. The concept of expectation and surprise in music has become recently the subject of extensive research, however mostly using symbolic data. The aim of this work is to investigate the circumstances when a change of sound intensity could be surprising for a listener. Then, using this knowledge, we aim to build a computational model that analyzes an audio stream and points to potential violations of human expectation. In order to check the quality of human prediction, an online (…

Search for heavy neutrinos with the T2K near detector ND280

2019

This paper reports on the search for heavy neutrinos with masses in the range 140<MN<493  MeV/c2 using the off-axis near detector ND280 of the T2K experiment. These particles can be produced from kaon decays in the standard neutrino beam and then subsequently decay in ND280. The decay modes under consideration are N→ℓ±απ∓ and N→ℓ+αℓ−β(−)ν(α,β=e,μ). A search for such events has been made using the Time Projection Chambers of ND280, where the background has been reduced to less than two events in the current dataset in all channels. No excess has been observed in the signal region. A combined Bayesian statistical approach has been applied to extract upper limits on the mixing elements of heav…

Natural induction: An objective bayesian approach

2009

The statistical analysis of a sample taken from a finite population is a classic problem for which no generally accepted objective Bayesian results seem to exist. Bayesian solutions to this problem may be very sensitive to the choice of the prior, and there is no consensus as to the appropriate prior to use.

Bayesian Hierarchical Models for Random Routes in Finite Populations

1996

In many practical situations involving sampling from finite populations, it is not possible (or it is prohibitely expensive) to access, or to even produce, a listing of all of the units in the population. In these situations, inferences can not be based on random samples from the population. Random routes are widely used procedures to collect data in absence of well defined sampling frames, and they usually have either been improperly analyzed as random samples, or entirely ignored as useless. We present here a Bayesian analysis of random routes that incorporates the information provided but carefully takes into account the non- randomness in the selection of the units.