On the environmental valuation of catastrophe: revisiting mining disasters in the United Kingdom, 1851-1962

In the context of environmental valuation of natural disasters, an important component of the evaluation procedure lies in determining the periodicity of events. This paper explores alternative methodologies for determining such periodicity, illustrating the advantages and the disadvantages of the separate methods and their comparative predictions. The procedures employ Bayesian inference and explore recent advances in computational aspects of mixtures methodology. The procedures are applied to the classic data set of Maguire et al (Biometrika, 1952) which was subsequently updated by Jarrett (Biometrika, 1979) and which comprise the seminal investigations examining the periodicity of mining disasters within the United Kingdom, 1851-1962.

A combined Bayesian Markovian approach for behaviour recognition

Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although these techniques are extremely powerful and well developed, both have important limitations. By fusing these techniques together to form Bayes-Markov chains, the advantages of both techniques can be preserved, while reducing their limitations. The Bayes-Markov technique forms the basis of a common, flexible framework for supplementing Markov chains with additional features. This results in improved user output, and aids in the rapid development of flexible and efficient behaviour recognition systems.

The future of video analytics for surveillance and its ethical implications

The current state of the art and direction of research in computer vision aimed at automating the analysis of CCTV images is presented. This includes low level identification of objects within the field of view of cameras, following those objects over time and between cameras, and the interpretation of those objects’ appearance and movements with respect to models of behaviour (and therefore intentions inferred). The potential ethical problems (and some potential opportunities) such developments may pose if and when deployed in the real world are presented, and suggestions made as to the necessary new regulations which will be needed if such systems are not to further enhance the power of the surveillers against the surveilled.

Parametric preference functionals under risk in the gain domain: a Bayesian analysis

The performance of rank dependent preference functionals under risk is comprehensively evaluated using Bayesian model averaging. Model comparisons are made at three levels of heterogeneity plus three ways of linking deterministic and stochastic models: the differences in utilities, the differences in certainty equivalents and contextualutility. Overall, the"bestmodel", which is conditional on the form of heterogeneity is a form of Rank Dependent Utility or Prospect Theory that cap tures the majority of behaviour at both the representative agent and individual level. However, the curvature of the probability weighting function for many individuals is S-shaped, or ostensibly concave or convex rather than the inverse S-shape commonly employed. Also contextual utility is broadly supported across all levels of heterogeneity. Finally, the Priority Heuristic model, previously examined within a deterministic setting, is estimated within a stochastic framework, and allowing for endogenous thresholds does improve model performance although it does not compete well with the other specications considered.

Multicamera trajectory analysis for semantic behaviour characterisation

In this paper we propose an innovative approach for behaviour recognition, from a multicamera environment, based on translating video activity into semantics. First, we fuse tracks from individual cameras through clustering employing soft computing techniques. Then, we introduce a higher-level module able to translate fused tracks into semantic information. With our proposed approach, we address the challenge set in PETS 2014 on recognising behaviours of interest around a parked vehicle, namely the abnormal behaviour of someone walking around the vehicle.

A Filter for Visual Tracking Based on a Stochastic Model for Driver Behaviour

A driver controls a car by turning the steering wheel or by pressing on the accelerator or the brake. These actions are modelled by Gaussian processes, leading to a stochastic model for the motion of the car. The stochastic model is the basis of a new filter for tracking and predicting the motion of the car, using measurements obtained by fitting a rigid 3D model to a monocular sequence of video images. Experiments show that the filter easily outperforms traditional filters.

Comparative analysis by protocol and key of seed storage behaviour of sixty Vietnamese tree species

Seed storage behaviour of 5 1 native and 9 introduced tree species in Vietnam was investigated using a brief protocol developed to aid biodiversity conservation in circumstances where little is known about the seeds. Of the 60 species, 34 appeared to show orthodox (Acacia auriculaeformis, Adenanthera pavonina, Afzelia xylocarpa, Bauhinia purpurea, Callistemon lanceolatus, Cananga odorata, Canarium nigrum, Cassia fistula, Cassia javanica, Cassia splendida, Chukrasia tabularis, Dalbergia bariaensis, Dialium cochinchinensis, Diospyros mollis, Diospyros mun, Dracuntomelon duperreanum, Erythrophleum fordii, Khaya senegalensis, Lagerstroemia speciosa, Leucaena leucocephala, Livistona cochinchinensis, Markhamia stipulata, Melaleuca cajuputi, Millettia ichthyotona, Peltophorum pterocarpum, Peltophorum tonkinensis, Pinus khasya, Pinus massoniana, Pinus merkusii, Pterocarpus macrocarpus, Sindora siamensis, Sophora tonkinense, Sterculia foetida, Swietenia macrophylla), 13 recalcitrant (Avicennia alba, Beilschmiedia roxburghiana, Caryota mitis, Dimocarpus sp., Diospyros malabarica, Dipterocarpus chartaceus, Dypsis pinnatifrons, Hopea odorata, Lithocarpus gigantophylla, Machilus odoratissimus, Melanorrhoea laccifera, Melanorrhea usitata, Syzygium cinereum) and 13 intermediate (Anisoptera cochinchinensis, Aphanamixis polystachya, Averrhoa carambola, Carissa carandas, Chrysopylum cainito, Cinnamomum camphora, Citrofortunella microcarpa, Citrus grandis var. grandis, Elaeis guineensis, Hydnocarpus anthelmintica, Madhuca floribunda, Manilkara achras, Mimusops elengi) seed storage behaviour. A double-criteria key to estimate likely seed storage behaviour showed good agreement with the above: the key can reduce the workload of seed storage behaviour identification considerably.

An exploration of the drivers to bio-security collective action among a sample of UK cattle and sheep farmers

At present, collective action regarding bio-security among UK cattle and sheep farmers is rare. Despite the occurrence of catastrophic livestock diseases such as bovine spongiform encephalopathy (BSE) and foot and mouth disease (FMD), within recent decades, there are few national or local farmer-led animal health schemes. To explore the reasons for this apparent lack of interest, we utilised a socio-psychological approach to disaggregate the cognitive, emotive and contextual factors driving bio-security behaviour among cattle and sheep farmers in the United Kingdom (UK). In total, we interviewed 121 farmers in South-West England and Wales. The main analytical tools included a content, cluster and logistic regression analysis. The results of the content analysis illustrated apparent 'dissonance' between bio-security attitudes and behaviour.(1) Despite the heavy toll animal disease has taken on the agricultural economy, most study participants were dismissive of the many measures associated with bio-security. Justification for this lack of interest was largely framed in relation to the collective attribution or blame for the disease threats themselves. Indeed, epidemic diseases were largely related to external actors and agents. Reasons for outbreaks included inadequate border control, in tandem with ineffective policies and regulations. Conversely, endemic livestock disease was viewed as a problem for 'bad' farmers and not an issue for those individuals who managed their stock well. As such, there was little utility in forming groups to address what was largely perceived as an individual problem. Further, we found that attitudes toward bio-security did not appear to be influenced by any particular source of information per se. While strong negative attitudes were found toward specific sources of bio-security information, e.g. government leaflets, these appear to simply reflect widely held beliefs. In relation to actual bio-security behaviours, the logistic regression analysis revealed no significant difference between in-scheme and out of scheme farmers. We concluded that in order to support collective action with regard to bio-security, messages need to be reframed and delivered from a neutral source. Efforts to support group formation must also recognise and address the issues relating to perceptions of social connectedness among the communities involved. (c) 2008 Elsevier B.V. All rights reserved.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.

Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.

Bayesian analysis of an inverse Gaussian correlated frailty model

In survival analysis frailty is often used to model heterogeneity between individuals or correlation within clusters. Typically frailty is taken to be a continuous random effect, yielding a continuous mixture distribution for survival times. A Bayesian analysis of a correlated frailty model is discussed in the context of inverse Gaussian frailty. An MCMC approach is adopted and the deviance information criterion is used to compare models. As an illustration of the approach a bivariate data set of corneal graft survival times is analysed. (C) 2006 Elsevier B.V. All rights reserved.

Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo

We describe a Bayesian method for investigating correlated evolution of discrete binary traits on phylogenetic trees. The method fits a continuous-time Markov model to a pair of traits, seeking the best fitting models that describe their joint evolution on a phylogeny. We employ the methodology of reversible-jump ( RJ) Markov chain Monte Carlo to search among the large number of possible models, some of which conform to independent evolution of the two traits, others to correlated evolution. The RJ Markov chain visits these models in proportion to their posterior probabilities, thereby directly estimating the support for the hypothesis of correlated evolution. In addition, the RJ Markov chain simultaneously estimates the posterior distributions of the rate parameters of the model of trait evolution. These posterior distributions can be used to test among alternative evolutionary scenarios to explain the observed data. All results are integrated over a sample of phylogenetic trees to account for phylogenetic uncertainty. We implement the method in a program called RJ Discrete and illustrate it by analyzing the question of whether mating system and advertisement of estrus by females have coevolved in the Old World monkeys and great apes.