2,628 research outputs found
Second-Order Belief Hidden Markov Models
Hidden Markov Models (HMMs) are learning methods for pattern recognition. The
probabilistic HMMs have been one of the most used techniques based on the
Bayesian model. First-order probabilistic HMMs were adapted to the theory of
belief functions such that Bayesian probabilities were replaced with mass
functions. In this paper, we present a second-order Hidden Markov Model using
belief functions. Previous works in belief HMMs have been focused on the
first-order HMMs. We extend them to the second-order model
Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People
The purpose of this study is to provide an accessibility measure of
web-pages, in order to draw disabled users to the pages that have been designed
to be ac-cessible to them. Our approach is based on the theory of belief
functions, using data which are supplied by reports produced by automatic web
content assessors that test the validity of criteria defined by the WCAG 2.0
guidelines proposed by the World Wide Web Consortium (W3C) organization. These
tools detect errors with gradual degrees of certainty and their results do not
always converge. For these reasons, to fuse information coming from the
reports, we choose to use an information fusion framework which can take into
account the uncertainty and imprecision of infor-mation as well as divergences
between sources. Our accessibility indicator covers four categories of
deficiencies. To validate the theoretical approach in this context, we propose
an evaluation completed on a corpus of 100 most visited French news websites,
and 2 evaluation tools. The results obtained illustrate the interest of our
accessibility indicator
Evidential-EM Algorithm Applied to Progressively Censored Observations
Evidential-EM (E2M) algorithm is an effective approach for computing maximum
likelihood estimations under finite mixture models, especially when there is
uncertain information about data. In this paper we present an extension of the
E2M method in a particular case of incom-plete data, where the loss of
information is due to both mixture models and censored observations. The prior
uncertain information is expressed by belief functions, while the
pseudo-likelihood function is derived based on imprecise observations and prior
knowledge. Then E2M method is evoked to maximize the generalized likelihood
function to obtain the optimal estimation of parameters. Numerical examples
show that the proposed method could effectively integrate the uncertain prior
infor-mation with the current imprecise knowledge conveyed by the observed
data
Belief Hierarchical Clustering
In the data mining field many clustering methods have been proposed, yet
standard versions do not take into account uncertain databases. This paper
deals with a new approach to cluster uncertain data by using a hierarchical
clustering defined within the belief function framework. The main objective of
the belief hierarchical clustering is to allow an object to belong to one or
several clusters. To each belonging, a degree of belief is associated, and
clusters are combined based on the pignistic properties. Experiments with real
uncertain data show that our proposed method can be considered as a propitious
tool
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Trading risks: The value of relationships, models and face-to-face interaction in the global reinsurance market
Over the past 20 years, the reinsurance industry has experienced three profound forces for change. First,
technological change has improved information distribution and strengthened connections between global
markets. Second, regulatory emphasis on global equivalence in trading practices has generated pressure for
convergence across different marketplaces. Third, the widespread acceptance of vendor property catastrophe
models has led to more standardised approaches to the evaluation of reinsurance risks, levelling the playing
field for decision-making on at least some classes of business.
These changes have intensified competition between reinsurance markets. Reinsurance trading centres in remote
geographic locations, such as Bermuda, where it is more difficult to transact business face-to-face, have been
able to write risk via electronic communications and now have very significant positions in the global reinsurance
market. Simultaneously, Lloyd’s of London, one of the original reinsurance markets that is still very much based
on the face-to-face approach, has demonstrated its capability to weather financial shocks and downturns and
remains an important player in global reinsurance
Post-grooming furunculose bij een hond
A five-year-old, intact, male labrador retriever was presented on emergency with general complaints of fever, lethargy and anorexia. During clinical examination, very painful skin lesions were noticed dorsally on the neck and back, and there was also a clear left apical systolic murmur with a degree of 4/6. On histopathological examination of the lesional skin, there was rupture of the follicle wall surrounded with a pronounced suppurative inflammation. The dog was diagnosed with post-grooming furunculosis and mitral valve endocardiosis ACVIM stage B2. Culture of the lesional skin and the shampoo used to wash the dog prior to the onset of the skin lesions revealed the presence of the same bacteria, evidencing a clear link between the bathing and development of the skin lesions
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Charting new territory for organizational ethnography : Insights from a team-based video ethnography
Purpose: Increasing complexity, fragmentation, mobility, pace, and technological intermediation of organizational life make “being there” increasingly difficult. Where do ethnographers have to be, when, for how long, and with whom to “be there” and grasp the practices, norms, and values that make the situation meaningful to natives? These novel complexities call for new forms of organizational ethnography. The purpose of this paper is to discuss the above issues.
Design/methodology/approach: In this paper, the authors respond to these calls for innovative ethnographic methods in two ways. First, the paper reports on the practices and ethnographic experiences of conducting a year-long team-based video ethnography of reinsurance trading in London.
Findings: Second, drawing on these experiences, the paper proposes a framework for systematizing new approaches to organizational ethnography and visualizing the ways in which they are “expanding” ethnography as it was traditionally practiced.
Originality/value: The paper contributes to the ethnographic literature in three ways: first, the paper develops a framework for charting new approaches to ethnography and highlight its different dimensions – site, instrument, and fieldworker. Second, the paper outlines the opportunities and challenges associated with these expansions, specifically with regard to research design, analytical rigour, and communication of results. Third, drawing on the previous two contributions, the paper highlights configurations of methodological expansions on the aforementioned dimensions that are more promising than others in leveraging new technologies and approaches to claim new territory for organizational ethnography and enhance its relevance for understanding today's multifarious organizational realities
Limited sampling strategies to estimate glomerular filtration rate in cats with low, normal and high glomerular filtration rates
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