A novel technique to classify time series with imprecise hidden Markov models is presented. The learning of these models is achieved by coupling the EM algorithm with the imprecise Dirichlet model. In the stationarity limit, each model corresponds to an imprecise mixture of Gaussian densities, this reducing the problem to the classification of static, imprecise-probabilistic, information. Two c...

Current digital currency schemes provide instantaneous exchange on precise commodity, in which ”precise” means a buyer can possibly verify the function of the commodity without error. However, imprecise commodities, e.g. statistical data, with error existing are abundant in digital world. Existing digital currency schemes do not offer a mechanism to help the buyer for payment decision on precis...

Hybrid systems are a widely used model to represent and reason about control-command systems. Most of the work in this domain is devoted to compute reachable sets of hybrid automata or equivalent models. However, in an industrial context, control-command systems are often implemented in Simulink and their validity is checked using numerical simulation. In this article, we present a tool named H...

Elicitation When uncertainties are elicited from experts, they are typically quantified as probabilities. Eliciting probabilities directly from domain experts as precise numbers is often problematic due to a lack of familiarity with probability theory and the absence of a concrete context. Moreover, even some of the most ardent ‘precise’ probabilists agree that imprecise-probabilistic technique...

The initial chemical steps in Tn5 transposition result in blunt end cleavage of the transposon from the donor DNA. We demonstrate that this cleavage occurs via a hairpin intermediate. The first step is a 3' hydrolytic nick by transposase. The free 3'OH then attacks the phosphodiester bond on the opposite strand, forming a hairpin at the transposon end. In addition to forming precise hairpins, T...

This paper introduces discretionary imprecise data in Data Envelopment Analysis (DEA) and discusses the efficiency evaluation of Decision Making Units (DMUs) with non-discretionary imprecise data. Then, suggests a method for evaluation the efficiency of DMUs with non-discretionary imprecise data. When some inputs and outputs are imprecise and non-discretionary, the DEA model becomes non-linear ...