A fuzzy extractor is a security primitive that allows for reproducible extraction of an almost uniform key from a non-uniform noisy source. We analyze a fuzzy extractor scheme that uses universal hash functions for both information reconciliation and privacy amplification. This is a useful scheme when the number of error patterns likely to occur is limited, regardless of the error probabilities...

Recently, most of part-of-speech tagging approaches, such as rule-based, probabilistic, and neural network approaches, have shown very promising results. In this paper, we are particularly interested in probabilistic approaches, which usually require lots of training data to get reliable probabilities. We alleviate such restriction of probabilistic approaches by introducing a fuzzy network mode...

The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain ("fuzzy") genotypes, like those resulting from AFLP scores, can be...

Welch & Peers (1963) used a root-information prior to obtain posterior probabilities for a scalar parameter exponential model and showed that these Bayes probabilities had the confidence property to second order asymptotically. An important undercurrent of this indicates that the constant information reparameterization provides location model structure, for which the confidence property ...

Station autonomous computer system is the core of centralized traffic control (CTC) system. The working mode dual hot standby, and its reliability very important. Due to dynamic fuzzy issue with analysis station system, a method formulated based on fault tree (DFT) Markov model. First, structure principle standby double 2-vote-2 are analyzed, two systems DFT formulated. Then, failure rates dete...

⎯This paper presents a new approach for solving the paradoxical Blackman's Association Problem. It utilizes the recently defined new class fusion rule based on fuzzy Tconorm/T-norm operators together with DezertSmarandache theory based, relative variations of generalized pignistic probabilities measure of correct associations, defined from a partial ordering function of hyper-power set. The abi...

In the automatic speech recognition (ASR) problem, the task of constructing one wordor sentence-level probability from the available phoneme-level probabilities is a very important one. Here we try to improve the performance of ASR systems by applying operators taken from fuzzy logic which have the sort of properties this problem requires. In this paper we do this by using the Generalized Dombi...

We present a new financial decision making model by using the fuzzy generalized probabilistic weighted averaging (FGPWA) operator. The main advantage of this new approach is that it is able to deal with probabilities (objective information) and weighted averages (subjective information) in the same formulation. Moreover, it is also able to deal with an uncertain environment that can be assessed...

This paper handles the problem of uncertainty in assessment the safety systems using Generalized Stochastic Petri Nets (GSPN). The basic probabilities usually treated to define transition in petri nets (PNs) are substituted by fuzzy number. Experts represent the uncertainties regarding the parameters of the components of systems to assess the influence of this uncertainty on safety system unava...

Detecting the beginning and the end of the business cycle is an important and di cult economic problem. One of the reasons why this problem is di cult is that for each year, we have only expert estimates (subjective probabilities) indicating to what extent the economy was in growth or recession. In our previous papers, we used fuzzy techniques to process this uncertain information; namely, we u...