Predictability of Volcano Eruption: lessons from a basaltic effusive volcano

Volcano eruption forecast remains a challenging and controversial problem despite the fact that data from volcano monitoring significantly increased in quantity and quality during the last decades.This study uses pattern recognition techniques to quantify the predictability of the 15 Piton de la Fournaise (PdlF) eruptions in the 1988-2001 period using increase of the daily seismicity rate as a precursor. Lead time of this prediction is a few days to weeks. Using the daily seismicity rate, we formulate a simple prediction rule, use it for retrospective prediction of the 15 eruptions,and test the prediction quality with error diagrams. The best prediction performance corresponds to averaging the daily seismicity rate over 5 days and issuing a prediction alarm for 5 days. 65% of the eruptions are predicted for an alarm duration less than 20% of the time considered. Even though this result is concomitant of a large number of false alarms, it is obtained with a crude counting of daily events that are available from most volcano observatoriesComment: 4 pages, 4 figure

Comparing the effectiveness of testing methods in improving programs: the effect of variations in program quality

We compare the efficacy of different testing methods for improving the reliability of software. Specifically, we use modelling to compare “operational” testing, in which test cases are chosen according to their probability of occurring in actual use of the software, against “debug” testing methods, in which the testers look for test cases which they consider likely to cause failure, or that satisfy some coverage criterion. We base our comparisons on the reliability reached by the program at the end of testing. Differently from previous studies, we consider the probability distribution of the achieved reliability, and thus the probability of satisfying specific requirements, rather than just the average reliability achieved. We take account of two sources of variation. The variation between the actual test histories that are possible for a given program and a given test method: and the fact that different programs start testing with different faults and initial reliability levels. By necessity, we use very simplified models of reality. Yet, we can show some interesting conclusions with important practical consequences. In general, there are stronger arguments in favor of operational testing than previous studies have show

Public officials and their institutional environment - an analytical model for assessing the impact of institutional change on public sector performance

To perform well, public officials must be confident enough about the future, to be able to see a relationship between their efforts, and an eventual outcome. Their expectations are shaped by their institutional environment. If the rules are not credible, or are unlikely to be enforced, of if they expect policies to be contradicted, or resources to flow unpredictably, results will be uncertain, so there is little point in working purposefully. The authors present an analytical framework, used to design a series of surveys of public officials'views of their institutional environment, and to analyze the information generated in fifteen countries. They describe how survey results help map public sector's strengths, and weaknesses, and offer an approach to identifying potential payoffs from reforms. The framework emphasizes how heterogeneous incentives, and institutional arrangements are within he public sector. It emphasizes how important it is for policymakers to base decisions on information (not generalizations) that suggests what is most likely to work, and where. In building on the premise that public officials'actions - and hence their organization's performance - depend on the institutional environment in which they find themselves, this framework avoids simplistic anti-government positions, bur doesn't defend poor performance. Some public officials perform poorly, and engage in rent seeking, but some selfless, and determined public officials, work hard under extremely difficult conditions. This framework offers an approach for understanding both bad performance, and good, and for presenting the results to policymakers in a format that leadsto more informed choices, about public sector reform. Types of reforms discussed include strengthening the credibility of rules for evaluation, for record management, for training, and for recruitment; ensuring that staff support government policy; preventing political interference, or micro-management; assuring staff that they will be treated fairly; and, making government policies consistent.Public Health Promotion,Decentralization,Educational Sciences,Enterprise Development&Reform,Health Monitoring&Evaluation,Educational Sciences,National Governance,Governance Indicators,Poverty Assessment,Health Monitoring&Evaluation

Searching for invariants using genetic programming and mutation testing

Invariants are concise and useful descriptions of a program's behaviour. As most programs are not annotated with invariants, previous research has attempted to automatically generate them from source code. In this paper, we propose a new approach to invariant generation using search. We reuse the trace generation front-end of existing tool Daikon and integrate it with genetic programming and a mutation testing tool. We demonstrate that our system can find the same invariants through search that Daikon produces via template instantiation, and we also find useful invariants that Daikon does not. We then present a method of ranking invariants such that we can identify those that are most interesting, through a novel application of program mutation

Regulatory effectiveness : the impact of regulation and regulatory governance arrangements on electricity industry outcomes

The authors review a number of studies on the effectiveness of utility regulatory agency and governance arrangements for the electricity industry, particularly for developing countries. They discuss governance criteria and their measurement, both legal frameworks and surveys of regulatory practice. They also discuss the results from econometric studies of effectiveness for regulatory agencies in the electricity and telecommunications industries and compare these with the results from econometric studies of independent central banks and their governance. The authors conclude with a discussion of policy implications and of priorities for information collection to improve understanding of these issues.National Governance,Banks&Banking Reform,Governance Indicators,Administrative&Regulatory Law,Municipal Financial Management

Degradation of learned skills. A review and annotated bibliography

An overview of the literature dealing with the retention of learned skills is presented. Basic effects of task type, training, retention interval, and recall variables are discussed, providing a background against which more recent literature dealing with operational spaceflights tasks is compared and assessed. Detailed and summary abstracts of research reports having particular relevance to the problem of spaceflight skill retention are provided

Stateful Testing: Finding More Errors in Code and Contracts

Automated random testing has shown to be an effective approach to finding faults but still faces a major unsolved issue: how to generate test inputs diverse enough to find many faults and find them quickly. Stateful testing, the automated testing technique introduced in this article, generates new test cases that improve an existing test suite. The generated test cases are designed to violate the dynamically inferred contracts (invariants) characterizing the existing test suite. As a consequence, they are in a good position to detect new errors, and also to improve the accuracy of the inferred contracts by discovering those that are unsound. Experiments on 13 data structure classes totalling over 28,000 lines of code demonstrate the effectiveness of stateful testing in improving over the results of long sessions of random testing: stateful testing found 68.4% new errors and improved the accuracy of automatically inferred contracts to over 99%, with just a 7% time overhead.Comment: 11 pages, 3 figure