Fault Trees vs. Event Trees in Reliability Analysis

Reliability analysis is the study of both the probability and the process of failure of a system. For that purpose, several tools are available, for example, fault trees, event trees, or the GO technique. These tools are often complementary and address different aspects of the questions. Experience shows that there is sometimes confusion between two of these methods: fault trees and event trees. Sometimes identified as equivalent, they, in fact, serve different purposes. Fault trees lay out relationships among events. Event trees lay out sequences of events linked by conditional probabilities. At least in theory, event trees can handle better notions of continuity (logical, temporal, and physical), whereas fault trees are most powerful in identifying and simplifying failure scenarios. Different characteristics of the system in question (e.g., a dam or a nuclear reactor) may guide the choice between fault trees, event trees, or a combination of the two. Some elements of this choice are examined, and observations are made about the relative capabilities of the two methods.     

Ensemble Habitat Mapping of Invasive Plant Species

Ensemble species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. Ensemble models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species‐environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and ensemble modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are based on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, ensemble models were the only models that ranked in the top three models for both field validation and test data. Ensemble models may be more robust than individual species‐environment matching models for risk analysis.     

On the parameterized complexity of the Multi-MCT and Multi-MCST problems

The comparison of tree structured data is widespread since trees can be used to represent wide varieties of data, such as XML data, evolutionary histories, or carbohydrate structures. Two graph-theoretical problems used in the comparison of such data are the problems of finding the maximum common subtree (MCT) and the minimum common supertree (MCST) of two trees. These problems generalize to the problem of finding the MCT and MCST of multiple trees (Multi-MCT and Multi-MCST, respectively). In this paper, we prove parameterized complexity hardness results for the different parameterized versions of the Multi-MCT and Multi-MCST problem under isomorphic embeddings.     

Monte Carlo Sensitivity Analysis of Unknown Parameters in Hazardous Materials Transportation Risk Assessment

The US Department of Transportation was interested in the risks associated with transporting Hydrazine in tanks with and without relief devices. Hydrazine is both highly toxic and flammable, as well as corrosive. Consequently, there was a conflict as to whether a relief device should be used or not. Data were not available on the impact of relief devices on release probabilities or the impact of Hydrazine on the likelihood of fires and explosions. In this paper, a Monte Carlo sensitivity analysis of the unknown parameters was used to assess the risks associated with highway transport of Hydrazine. To help determine whether or not relief devices should be used, fault trees and event trees were used to model the sequences of events that could lead to adverse consequences during transport of Hydrazine. The event probabilities in the event trees were derived as functions of the parameters whose effects were not known. The impacts of these parameters on the risk of toxic exposures, fires, and explosions were analyzed through a Monte Carlo sensitivity analysis and analyzed statistically through an analysis of variance. The analysis allowed the determination of which of the unknown parameters had a significant impact on the risks. It also provided the necessary support to a critical transportation decision even though the values of several key parameters were not known.     

Improved approximation algorithm for maximum agreement forest of two rooted binary phylogenetic trees

Given two rooted binary phylogenetic trees with identical leaf label-set, the maximum agreement forest (MAF) problem asks for a largest common subforest of the two trees. This problem has been studied extensively in the literature, and has been known to be NP-complete and MAX SNP-hard. The previously best ratio of approximation algorithms for this problem is 3. In this paper, we make full use of the special relations among leaves in phylogenetic trees and present an approximation algorithm with ratio 2.5 for the MAF problem on two rooted binary phylogenetic trees.     

Are Nuclear-Weapon States not Parties to the Non-proliferation Treaty Ready to Renounce to the Possession of Nuclear Weapons?

The situation of nuclear-weapon states not parties to the NPT is different from the situation of the nuclear-weapon states parties to that treaty. This last group of countries has signed and ratified a treaty that encourage them to begin negotiations in good faith for the discussion of concrete measures that lead them to nuclear disarmament, while the first group of states have made no commitment to do that. In other words, nuclear-weapon states not parties to the NPT have made no commitment to nuclear disarmament and are not obliged to report anything related to the possession of nuclear weapons to the any specific body or organ or to the international community. Taking into account the position of nuclear-weapon states parties to the NPT regarding the possession of nuclear weapons, there is no possibility to convince nuclear-weapon states not parties to this treaty to renounce to the possession of this type of weapons under the present circumstances.     

When Costs Are Unequal and Unknown: A Subtree Grafting Approach for Unbalanced Data Classification*

In binary classifications, a decision tree learned from unbalanced data typically creates an important challenge related to the high misclassification rate of the minority class. Assigning different misclassification costs can address this problem, though usually at the cost of accuracy for the majority class. This effect can be particularly hazardous if the costs cannot be specified precisely. When the costs are unknown or difficult to determine, decision makers may prefer a classifier with more balanced accuracy for both classes rather than a standard or cost‐sensitively learned one. In the context of learning trees, this research therefore proposes a new tree induction approach called subtree grafting (STG). On the basis of a real bank data set and several other data sets, we test the proposed STG method and find that our proposed approach provides a successful compromise between standard and cost‐sensitive trees.     

利用上凸函数对决策树算法的改进

针对决策树分类方法的计算效率进行深入研究,根据信息增益计算的特点,引入了上凸函数的概念,用于提高决策树分类过程中信息增益的计算效率。利用我们所提出的“一致性定理”和“特殊一致性定理”,从理论上证明了利用上凸函数对信息增益计算进行改进后,构造的决策树与原决策树具有相同的分类准确率。同时我们通过对大数据集的实验,发现在相同规模的数据集下,改进后的决策树算法比原算法有更高的计算效率,并且这种计算效率的提高有随着数据集规模的增加而增加的趋势。     

Alternative Methods for Computing the Sensitivity of Complex Surveillance Systems

Stochastic scenario trees are a new and popular method by which surveillance systems can be analyzed to demonstrate freedom from pests and disease. For multiple component systems—such as a combination of a serological survey and systematically collected observations—it can be difficult to represent the complete system in a tree because many branches are required to represent complex conditional relationships. Here we show that many of the branches of some scenario trees have identical outcomes and are therefore redundant. We demonstrate how to prune branches and derive compact representations of scenario trees using matrix algebra and Bayesian belief networks. The Bayesian network representation is particularly useful for calculation and exposition. It therefore provides a firm basis for arguing disease freedom in international forums.     

(1+ε)-competitive algorithm for online OVSF code assignment with resource augmentation

This paper studies the online Orthogonal Variable Spreading Factor (OVSF) code assignment problem with resource augmentation introduced by Erlebach et al. (in STACS 2004. LNCS, vol. 2996, pp. 270–281, 2004). We propose a (1+1/α)-competitive algorithm with help of (1+?α?)lg^? h trees for the height h of the OVSF code tree and any α≥1. In other words, it is a (1+ε)-competitive algorithm with help of (1+?1/ε?)lg^? h trees for any constant 0<ε≤1. In the case of α=1 (or ε=1), we obtain a 2-competitive algorithm with 2lg^? h trees, which substantially improves the previous resource of 3h/8+2 trees shown by Chan et al. (COCOON 2009. LNCS, vol. 5609, pp. 358–367, 2009). In another aspect, if it is not necessary to bound the incurred cost for individual requests to a constant, an amortized (4/3+δ)-competitive algorithm with (11/4+4/(3δ)) trees for any 0<δ≤4/3 is also designed in Chan et al. (COCOON 2009. LNCS, vol. 5609, pp. 358–367, 2009). The algorithm in this paper gives us a new trade-off between the competitive ratio and the resource augmentation when α≥3 (or ε≤1/3), although the incurred cost for individual requests is bounded to a constant.     

b-Tree Facets for the Simple Graph Partitioning Polytope

The simple graph partitioning problem is to partition an edge-weighted graph into mutually disjoint subgraphs, each consisting of no more than b nodes, such that the sum of the weights of all edges in the subgraphs is maximal. In this paper we introduce a large class of facet defining inequalities for the simple graph partitioning polytopes _n (b), b 3, associated with the complete graph on n nodes. These inequalities are induced by a graph configuration which is built upon trees of cardinality b. We provide a closed-form theorem that states all necessary and sufficient conditions for the facet defining property of the inequalities.     

Measurement error, skewness, and risk analysis: coping with the long tail of the distribution.

Probabilistic risk analyses often construct multistage chance trees to estimate the joint probability of compound events. If random measurement error is associated with some or all of the estimates, we show that resulting estimates of joint probability may be highly skewed. Joint probability estimates based on the analysis of multistage chance trees are more likely than not to be below the true probability of adverse events, but will sometimes substantially overestimate them. In contexts such as insurance markets for environmental risks, skewed distributions of risk estimates amplify the "winner's curse" so that the estimated risk premium for low-probability events is likely to be lower than the normative value. Skewness may result even in unbiased estimators of expected value from simple lotteries, if measurement error is associated with both the probability and pay-off terms. Further, skewness may occur even if the error associated with these two estimates is symmetrically distributed. Under certain circumstances, skewed estimates of expected value may result in risk-neutral decisionmakers exhibiting a tendency to choose a certainty equivalent over a lottery of equal expected value, or vice versa. We show that when distributions of estimates of expected value are, positively skewed, under certain circumstances it will be optimal to choose lotteries with nominal values lower than the value of apparently superior certainty equivalents. Extending the previous work of Goodman (1960), we provide an exact formula for the skewness of products.     

Improved algorithms for ranking and unranking (k, m)-ary trees in B-order

Journal of Combinatorial Optimization - Du and Liu (Eur J Comb 28:1312–1321, 2007) introduced (k,&nbsp;m)-ary trees as a generalization of k-ary trees. In a (k,&nbsp;m)-ary tree,...     

Taking into account the rescheduling problem during the scheduling phase

The scheduling problem in production management has been studied for a considerable time, and several types of software are used. A problem arises in updating the production planning, or &lsquo;rescheduling&rsquo;, when an unexpected event occurs in the shop control. Solving this problem is difficult because the implications of such events are usually impossible to forecast. To prevent this problem, we propose to manipulate a set of equivalent schedules during the short time schedule. Then, if an unexpected event prevents realization of a given schedule, it will be possible to find an equivalent one, without full rescheduling. The primary requirement is to find a formal representation of a set of schedules. This has already been explored using CPM graphs with nodes associated to a set of tasks. We propose in this paper to use an extension of such graphs, PQR trees, that represent both precedence and group constraints. We first reiterate the notion of PQR trees. We present methods to take into account date constraints in such a structure, and we give a model for the general job-shop problem.     

A Comparative Analysis of PRA and Intelligent Adversary Methods for Counterterrorism Risk Management

In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions.     

The Minimal Spanning Tree Preservation Approaches for DNA Multiple Sequence Alignment and Evolutionary Tree Construction

In this paper, we propose a new criterion, namely the minimal spanning tree preservation approach, for both of the DNA multiple sequence alignment and the construction of evolutionary trees. It is our aim to keep the proximity information among the sequences or species via our approach. The basic idea behind this approach is that those distances among species which are close to one another are more informative than the others.     

The value of accuracy in information for planning and control

In the operation of planning and control systems we have to utilize information which in many categories possesses errors. It is important, therefore, to be able to assess the impact of inaccurate information on our plans. The author discusses some approaches to this problem when the planning system involves formulae of the management accounting type or models of the operational research variety. The value of information is clearly related to its accuracy and the most appropriate method for quantifying information value in management information systems is through Bayesian analysis and decision trees.     

A New Creation or an Image and Likeness? The Maltese Experience of Establishing Local Government in a Centralized Micro-State

Small states vary among themselves as to whether they have significant local government systems. While government in Malta has been historically a very centralized activity, a network of local councils was established in the early 1990s as part of a more general public sector reform movement. Unlike some other small states, Malta has strong political parties, and they have played an important part in the affairs of the local councils as well as of the central government. Their establishment has therefore done little to reduce political polarization or promote decentralist values, as was hoped when they were first established.     

Evaluating the Cost,Safety, and Proliferation Risks of Small Floating Nuclear Reactors

It is hard to see how our energy system can be decarbonized if the world abandons nuclear power, but equally hard to introduce the technology in nonnuclear energy states. This is especially true in countries with limited technical, institutional, and regulatory capabilities, where safety and proliferation concerns are acute. Given the need to achieve serious emissions mitigation by mid‐century, and the multidecadal effort required to develop robust nuclear governance institutions, we must look to other models that might facilitate nuclear plant deployment while mitigating the technology's risks. One such deployment paradigm is the build‐own‐operate‐return model. Because returning small land‐based reactors containing spent fuel is infeasible, we evaluate the cost, safety, and proliferation risks of a system in which small modular reactors are manufactured in a factory, and then deployed to a customer nation on a floating platform. This floating small modular reactor would be owned and operated by a single entity and returned unopened to the developed state for refueling. We developed a decision model that allows for a comparison of floating and land‐based alternatives considering key International Atomic Energy Agency plant‐siting criteria. Abandoning onsite refueling is beneficial, and floating reactors built in a central facility can potentially reduce the risk of cost overruns and the consequences of accidents. However, if the floating platform must be built to military‐grade specifications, then the cost would be much higher than a land‐based system. The analysis tool presented is flexible, and can assist planners in determining the scope of risks and uncertainty associated with different deployment options.     

Mitigating the environmental and social footprint of brownfields: The case for a peripheral CSR approach

Industrial plant closures create a largely unexplored challenge for corporate social responsibility (CSR) strategy. Such plant closures lead to brownfield sites: economic assets and large pieces of land that often cannot be redeployed for alternative purposes, except by incurring significant costs. The direct effects of plant closures typically include a rise in unemployment and value chain disturbance (or dismantling), but brownfields are usually also associated with additional social effects and environmental pollution. Here, a proactive CSR strategy means reducing or mitigating the joint, negative social and environmental footprint of industrial plant closures beyond what is mandated by law (which has tended primarily to address direct effects). We assess the various strategies firms can pursue to mitigate negative, post-closure footprints and we distinguish between two alternative strategic options beyond the ‘legal obligations’ approach, namely the ‘core business related’ (core) CSR approach, and the ‘peripheral CSR’ approach. We explore the case of a plant closure by Bekaert S.A., a large, Belgian industrial firm, which adopted a peripheral CSR approach to manage and redevelop a brownfield site. In this context, we identify four enabling conditions for peripheral CSR to be implemented effectively.