title: Terrorism and maritime shipment of nuclear material

authors: Smith, Ron C.

subjects: terrorism

abstract: Opponents of the nuclear industry often claim that material in transit is vulnerable to attack by
terrorist groups who might seek to take the cargo and make a bomb, or otherwise cause a
radiological incident. This paper lays out a range of conceivable objectives or attack scenarios in
the context of maritime transportation and examines these in the light of what is known of the
relevant security arrangements. It concludes that these arrangements provide a very substantial
deterrent to any attempt at diversion or sabotage and that any such attempt would have little
prospect of success, beyond the immediate media impact of whatever might have occurred.

text: Terrorism and maritime shipment of nuclear material Opponents of the nuclear industry often claim that material in transit is vulnerable to attack by
terrorist groups who might seek to take the cargo and make a bomb, or otherwise cause a
radiological incident. This paper lays out a range of conceivable objectives or attack scenarios in
the context of maritime transportation and examines these in the light of what is known of the
relevant security arrangements. It concludes that these arrangements provide a very substantial
deterrent to any attempt at diversion or sabotage and that any such attempt would have little
prospect of success, beyond the immediate media impact of whatever might have occurred.

year: 2007

title: Online estimation of discrete densities

authors: Geilke, Michael

subjects: (ensembles of) classifier chains

abstract: We address the problem of estimating a discrete joint density online, that is, the algorithm is only provided the current example and its current estimate. The proposed online estimator of discrete densities, EDDO (Estimation of Discrete Densities Online), uses classifier chains to model dependencies among features. Each classifier in the chain estimates the probability of one particular feature. Because a single chain may not provide a reliable estimate, we also consider ensembles of classifier chains and ensembles of weighted classifier chains. For all density estimators, we provide consistency proofs and propose algorithms to perform certain inference tasks. The empirical evaluation of the estimators is conducted in several experiments and on data sets of up to several million instances: We compare them to density estimates computed from Bayesian structure learners, evaluate them under the influence of noise, measure their ability to deal with concept drift, and measure the run-time performance. Our experiments demonstrate that, even though designed to work online, EDDO delivers estimators of competitive accuracy compared to batch Bayesian structure learners and batch variants of EDDO.

text: Online estimation of discrete densities We address the problem of estimating a discrete joint density online, that is, the algorithm is only provided the current example and its current estimate. The proposed online estimator of discrete densities, EDDO (Estimation of Discrete Densities Online), uses classifier chains to model dependencies among features. Each classifier in the chain estimates the probability of one particular feature. Because a single chain may not provide a reliable estimate, we also consider ensembles of classifier chains and ensembles of weighted classifier chains. For all density estimators, we provide consistency proofs and propose algorithms to perform certain inference tasks. The empirical evaluation of the estimators is conducted in several experiments and on data sets of up to several million instances: We compare them to density estimates computed from Bayesian structure learners, evaluate them under the influence of noise, measure their ability to deal with concept drift, and measure the run-time performance. Our experiments demonstrate that, even though designed to work online, EDDO delivers estimators of competitive accuracy compared to batch Bayesian structure learners and batch variants of EDDO.

year: 2013

title: Sharemilking with the Te Raparahi Lands Trust (Wāotū)

authors: Hutcheson, Gail Yvonne

subjects: Place

abstract: This paper discusses sharemilking  in New Zealand.

text: Sharemilking with the Te Raparahi Lands Trust (Wāotū) This paper discusses sharemilking  in New Zealand.

year: 2017