OBJECTIVE [(18)F]Fluorodeoxyglucose positron emission tomography-computerized tomography (PET-CT) scan is a tool widely used in the diagnosis and staging of lung cancer. Referral bias is present when the results of a diagnostic study affect the decision to proceed with definitive testing. This bias artificially increases the sensitivity and decreases the specificity, and may inappropriately alt...

I Markov Chains and Stochastic Sampling 2 1 Markov Chains and Random Walks on Graphs . . . . . . . . . . . 2 1.1 Structure of Finite Markov Chains . . . . . . . . . . . . . 2 1.2 Existence and Uniqueness of Stationary Distribution . . . 10 1.3 Convergence of Regular Markov Chains . . . . . . . . . . 14 1.4 Transient Behaviour of General Chains . . . . . . . . . . 17 1.5 Reversible Markov Chains...

Abstract The Critically Endangered western long-beaked echidna Zaglossus bruijnii is believed to be distributed throughout the Vogelkop Peninsula in Indonesian Province of West Papua, but there had formerly been no confirmed sightings species since 1980s. We aimed establish whether survives this area. Fieldwork was carried out during January–April 2018 Tambrauw Regency north and Teluk Bintuni s...

Gibbs sampling is a Markov chain Monte Carlo technique commonly used for estimating marginal distributions. To speed up Gibbs sampling, there has recently been interest in parallelizing it by executing asynchronously. While empirical results suggest that many models can be efficiently sampled asynchronously, traditional Markov chain analysis does not apply to the asynchronous case, and thus asy...

Although Markov chain Monte Carlo methods have been widely used in many disciplines, exact eigen analysis for such generated chains has been rare. In this paper, a special MetropolisHastings algorithm, Metropolized independent sampling, proposed first in Hastings (1970), is studied in full detail. The eigenvalues and eigenvectors of the corresponding Markov chain, as well as a sharp bound for t...

In 1996, Propp and Wilson came up with a remarkably clever method for generating exact samples from the stationary distribution of a Markov chain [17]. Their method, called “perfect sampling” or “exact sampling” avoids the inherent bias of samples that are generated by running the chain for a large but fixed number of steps. It does so by using a strategy called “coupling from the past”. Althou...

Human experts as autonomous agents in a referral network must decide whether to accept a task or refer to a more appropriate expert, and if so to whom. In order for the referral network to improve over time, the experts must learn to estimate the topical expertise of other experts. This thesis extends concepts from Multi-agent Reinforcement Learning and Active Learning to referral networks. Amo...

Supply Chain Management, which is concerned with material and information flows between facilities and the final customers, has been considered the most popular operations strategy for improving organizational competitiveness nowadays. With the advanced development of computer technology, it is getting easier to derive an acceptance sampling plan satisfying both the producer’s and consumer’s qu...