Exact and heuristic approaches to detect failures in failed k-out-of-n systems

This paper considers a k-out-of-n system that has just failed. There is an associated cost of testing each component. In addition, we have apriori information regarding the probabilities that a certain set of components is the reason for the failure. The goal is to identify the subset of components that have caused the failure with the minimum expected cost. In this work, we provide exact and approximate policies that detects components’ states in a failed k-out-of-n system. We propose two integer programming (IP) formulations, two novel Markov decision process (MDP) based approaches, and two heuristic algorithms. We show the limitations of exact algorithms and effectiveness of proposed heuristic approaches on a set of randomly generated test instances. Despite longer CPU times, IP formulations are flexible in incorporating further restrictions such as test precedence relationships, if need be. Numerical results illustrate that dynamic programming for the proposed MDP model is the most effective exact method, solving up to 12 components within one hour. The heuristic algorithms’ performances are presented against exact approaches for small to medium sized instances and against a lower bound for larger instances

Multiple Fault Isolation in Redundant Systems

Fault diagnosis in large-scale systems that are products of modern technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption

Multiple Fault Isolation in Redundant Systems

Fault diagnosis in large-scale systems that are products of modem technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption

Integrated analysis of error detection and recovery

An integrated modeling and analysis of error detection and recovery is presented. When fault latency and/or error latency exist, the system may suffer from multiple faults or error propagations which seriously deteriorate the fault-tolerant capability. Several detection models that enable analysis of the effect of detection mechanisms on the subsequent error handling operations and the overall system reliability were developed. Following detection of the faulty unit and reconfiguration of the system, the contaminated processes or tasks have to be recovered. The strategies of error recovery employed depend on the detection mechanisms and the available redundancy. Several recovery methods including the rollback recovery are considered. The recovery overhead is evaluated as an index of the capabilities of the detection and reconfiguration mechanisms

A Minimum of Rivalry: Evidence from Transition Economies on the Importance of Competition for Innovation and Growth

This paper examines the importance of competition in the growth and development of firms. We make use of the large-scale natural experiment of the shift from an economic system without competition to a market economy to shed light on the factors that influence innovation by firms and their subsequent growth. Using a dataset from a survey of nearly 4,000 firms in 24 transition countries, we find evidence of the importance of a minimum of rivalry in both innovation and growth: the presence of at least a few competitors is effective both directly and through improving the efficiency with which the rents from market power in product markets are utilised to undertake innovation.competition, productivity growth, innovation, rivalry, transition

Designing screening protocols for amphibian disease that account for imperfect and variable capture rates of individuals

The amphibian chytrid fungus, Batrachochytrium dendrobatidis, is one of the main factors in global amphibian decline. Accurate knowledge of its presence and prevalence in an area is needed to trigger conservation actions. However, imperfect capture rates determine the number of individuals caught and tested during field surveys, and contribute to the uncertainty surrounding estimates of prevalence. Screening programs should be planned with the objective of minimizing such uncertainty. We show how this can be achieved by using predictive models that incorporate information about population size and capture rates. Using as a case study an existing screening program for three populations of the yellow-bellied toad (Bombina variegata pachypus) in northern Italy, we sought to quantify the effect of seasonal variation in individual capture rates on the uncertainty surrounding estimates of chytrid prevalence. We obtained estimates of population size and capture rates from mark-recapture data, and found wide seasonal variation in the individual recapture rates. We then incorporated this information in a binomial model to predict the estimates of prevalence that would be obtained by sampling at different times in the season, assuming no infected individuals were found. Sampling during the period of maximum capture probability was predicted to decrease upper 95% credible intervals by a maximum of 36%, compared with least suitable periods, with greater gains when using uninformative priors. We evaluated model predictions by comparing them with the results of screening surveys in 2012. The observed results closely matched the predicted figures for all populations, suggesting that this method can be reliably used to maximize the sampling size of surveillance programs, thus improving their efficiency

Dispensing practices and antibiotic use

The regulation on prescribing and dispensing of antibiotics has a double purpose: to enhance access to antibiotic treatment and to reduce the inappropriate use of drugs. Nevertheless, incentives to dispensing physicians may lead to inefficiencies. We sketch a theoretical model of the market for antibiotic treatment and empirically investigate the impact of self-dispensing on the per capita outpatient antibiotic consumption using data from small geographic areas in Switzerland. We find evidence that a greater proportion of dispensing practices is associated with higher levels of antibiotic use. This suggests that health authorities have a margin to adjust economic incentives on dispensing practices in order to reduce antibiotic misuse.Dispensing, Antibiotic use

Fairtrade and market failures in agricultural commodity markets

This paper concerns an NGO intervention in agricultural commodity markets known as Fairtrade. Fairtrade pays producers a minimum unit price and provides capacity building support to member cooperative organizations. Fairtrade's organizational capacity support targets those factors believed to reduce the commodity producer's share of returns. Specifically, Fairtrade justifies its intervention in markets like coffee by claiming that market power and a lack of capacity in producer organizations'marks down'the prices producers receive. As the market share of Fairtrade coffee grows in importance, its intervention in commodity markets is of increasing interest. Using an original data set collected from fieldwork in Costa Rica, this paper assesses the role of Fairtrade in overcoming the market factors it claims limits producer returns. Features of the Costa Rican input market for coffee permit a generalization of the results. The empirical results find that market power is a limiting factor in the Costa Rican market and that Fairtrade does improve the efficiency of cooperatives, thereby increasing the returns to producers. These results do not depend on the minimum price policy of Fairtrade and therefore can inform on its organizational support activities. Finally, the results also suggest that producers selling to vertically integrated, multinational coffee mills face lower producer price'mark-downs'compared with domestically owned non-cooperative mills. This result contradicts the popular view that the increasing concentration of vertically integrated multinational firms accounts for a decline in producers'share of coffee returns.Markets and Market Access,Crops&Crop Management Systems,Access to Markets,Commodities,Economic Theory&Research