For a number field K and a finite abelian group G, we determine the probabilities of various local completions of a random G-extension of K when extensions are ordered by conductor. In particular, for a fixed prime ℘ of K, we determine the probability that ℘ splits into r primes in a random G-extension of K that is unramified at ℘. We find that these probabilities are nicely behaved and mostly ...

An approach providing fast reduction of the full ignorance in the target identification process is proposed. It uses the new Dezert-Smarandache theory (DSmT) for plausible and paradoxical reasoning, combined with fuzzy set theory. The approach utilizes the information from the adjoint sensor and the additional information obtained from a priori defined objective and subjective considerations. A...

After sketching the various probabilistic accounts of the design inference, including the Bayesian and Dembskian models, I make a stab at developing, in an admittedly crude form, a non-probabilistic model, based on a measure of ontological complexity, which, I conjecture, may more faithfully represent the design inference as found in such classical texts as Aquinas, Reid and Paley. I discuss th...

In location memory tasks, young children show biases toward reference axes, whereas older children show biases away from axes. As predicted by a dynamic systems model, this transition is gradual and varies across target location (Schutte & Spencer, 2009). Here we tested whether task context would influence the transition by testing children in a sandbox memory task that varied in several ways f...

The theory of belief functions has been formalized in continuous domain for pattern recognition. Some applications use assumption of Gaussian models. However, this assumption is reductive. Indeed, some data are not symmetric and present property of heavy tails. It is possible to solve these problems by using a class of distributions called α-stable distributions. Consequently, we present in thi...

This paper provides conditions for identification, and an associated estimator, of the average effect of a binary treatment or policy on a scalar outcome in models where treatment may be misclassified. Misclassification probabilities and the true probability of treatment are also identified. Misclassification occurs when treatment is measured with error, that is, some units are reported to have...

Random linear network coding is a feasible encoding tool for network coding, specially for the non-coherent network, and its performance is important in theory and application. In this letter, we study the performance of random linear network coding for the well-known butterfly network by analyzing the failure probabilities. We determine the failure probabilities of random linear network coding...

We consider the problem faced by a company selling a product with warranty and under partial information about the product reliability. The product can fail from multiple failure types, each of which is associated with an inherently different repair cost. If the product fails within the warranty duration, then the company is required to pay the repair cost. The company does not know the probabi...

The present paper investigates the reliability and sensitivity analysis of a coal handling unit of a thermal power plant using a probabilistic approach. Coal handling unit is the main block of a thermal power plant and it is necessary for a good function of a power plant that its power supply, which is dealt in coal handling unit, must function continuously without any obstacle. The configurati...