Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.     

Time series joins,motifs, discords and shapelets: a unifying view that exploits the matrix profile

The last decade has seen a flurry of research on all-pairs-similarity-search (or similarity joins) for text, DNA and a handful of other datatypes, and these systems have been applied to many diverse data mining problems. However, there has been surprisingly little progress made on similarity joins for time series subsequences. The lack of progress probably stems from the daunting nature of the problem. For even modest sized datasets the obvious nested-loop algorithm can take months, and the typical speed-up techniques in this domain (i.e., indexing, lower-bounding, triangular-inequality pruning and early abandoning) at best produce only one or two orders of magnitude speedup. In this work we introduce a novel scalable algorithm for time series subsequence all-pairs-similarity-search. For exceptionally large datasets, the algorithm can be trivially cast as an anytime algorithm and produce high-quality approximate solutions in reasonable time and/or be accelerated by a trivial porting to a GPU framework. The exact similarity join algorithm computes the answer to the time series motif and time series discord problem as a side-effect, and our algorithm incidentally provides the fastest known algorithm for both these extensively-studied problems. We demonstrate the utility of our ideas for many time series data mining problems, including motif discovery, novelty discovery, shapelet discovery, semantic segmentation, density estimation, and contrast set mining. Moreover, we demonstrate the utility of our ideas on domains as diverse as seismology, music processing, bioinformatics, human activity monitoring, electrical power-demand monitoring and medicine.     

Performances,Preservation, and Policy Implications: Digital Curation and Preservation Awareness and Strategy in the Performing Arts

Digital assets in contemporary performing arts practice may suffer damage and disappearance, eroding the record of contemporary practice. This study seeks to assess this threat and suggest solutions. We examined digital curation and preservation awareness and practice in a sample of performing arts professionals, establishing that digital objects are highly prized but levels of sustainable digital curation and preservation practice are low. We argue that competent digital curation and preservation is relevant to arts career sustainability, research, and wider cultural heritage. This article is intended to be relevant to policy and skills development in communities of creative practice beyond the academy.     

Irrevocable-choice algorithms for sampling from a stream

The problem of sampling from data streams has attracted significant interest in the last decade. Whichever sampling criteria is considered (uniform sample, maximally diverse sample, etc.), the challenges stem from the relatively small amount of memory available in the face of unbounded streams. In this work we consider an interesting extension of this problem, the framework of which is stimulated by recent improvements in sensing technologies and robotics. In some situations it is not only possible to digitally sense some aspects of the world, but to physically capture a tangible aspect of that world. Currently deployed examples include devices that can capture water/air samples, and devices that capture individual insects or fish. Such devices create an interesting twist on the stream sampling problem, because in most cases, the decision to take a physical sample is irrevocable. In this work we show how to generalize diversification sampling strategies to the irrevocable-choice setting, demonstrating our ideas on several real world domains.     

Gas absorption in the plunging liquid jet reactor

A pseudo first-order gas absorption survey has been made of the contacting system formed when a coherent liquid jet plunges through an ambient reactive gaseous atmosphere into a bath of jet liquid. Using the hypochlorite ion catalysed reaction between pure carbon dioxide and a carbonate ion-bicarbonate ion buffer solution, the reactor has been found to be analogous to a gas sparged stirred tank contactor with the plunging jet acting as both the reactor agitator and gas bubble generator. Resolution of the gas—liquid interfacial area and rate of surface renewal absorption parameters was thus made possible. Specific interfacial areas in the range 20–110 m^?1 and rates of surface renewal in the range 40–160 sec^?1 for the subsurface reactor have been related to the plunging jet surface roughness and velocity or the entrainment rate of the plunging jet.     

Reliable early classification of time series based on discriminating the classes over time

The goal of early classification of time series is to predict the class value of a sequence early in time, when its full length is not yet available. This problem arises naturally in many contexts where the data is collected over time and the label predictions have to be made as soon as possible. In this work, a method based on probabilistic classifiers is proposed for the problem of early classification of time series. An important feature of this method is that, in its learning stage, it discovers the timestamps in which the prediction accuracy for each class begins to surpass a pre-defined threshold. This threshold is defined as a percentage of the accuracy that would be obtained if the full series were available, and it is defined by the user. The class predictions for new time series will only be made in these timestamps or later. Furthermore, when applying the model to a new time series, a class label will only be provided if the difference between the two largest predicted class probabilities is higher than or equal to a certain threshold, which is calculated in the training step. The proposal is validated on 45 benchmark time series databases and compared with several state-of-the-art methods, and obtains superior results in both earliness and accuracy. In addition, we show the practical applicability of our method for a real-world problem: the detection and identification of bird calls in a biodiversity survey scenario.     

Stress test optimization using an integrated production test and field reliability model

Numerous papers and texts have been written in the reliability literature regarding the determination of the optimum test duration for a production stress or a burn‐in test. The techniques presented have largely been based on the identification of the change point at which infant mortality has largely been removed from the units. The time‐on‐test is typically the only factor that influences this decision. Few of these models have attempted to integrate the field performance or the influence of warranty costs into this decision. This paper proposes and validates a methodology that integrates the influence of the production test failures and the field performance including their respective costs into a single unified model. The objective is to identify a production test duration that minimizes the overall cost. A Weibull model is initially developed for the production test that incorporates the failure observations in different time segments of the test based on the ability to detect latent defects in the product. A separate Weibull model is then developed for the product's performance in the field that includes the lifetime of the unit. This paper identifies how both these Weibull models can be combined into a single model including both test and field costs with the objective of minimizing the overall cost. The advantage of the proposed technique is that it does not require one to track individual units from production through to the field in order to develop an integrated test and field cost model. Copyright © 2009 John Wiley & Sons, Ltd.     

Synthesis and characterization of a random terpolymer of L‐lactide, ϵ‐caprolactone and glycolide

A random terpolymer of L ‐lactide (LL), ?‐caprolactone (CL) and glycolide (G) has been synthesized in bulk at 130 °C using stannous octoate as the coordination–insertion initiator. The terpolymer, poly(LL‐ran‐CL‐ran‐G), has been characterized by a combination of analytical techniques: GPC, ¹H NMR, ¹³C NMR, DSC and TG. Molecular weight characterization by GPC shows a unimodal molecular weight distribution with values of M _n = 1.01 × 10⁵ g mol^?1 and M _w / M _n = 2.17. Compositional and microstructural analysis by ¹H NMR and ¹³C NMR, respectively, reveal a terpolymer composition of LL:CL:G = 74:15:11 (mol%) with a chain microstructure consistent with random monomer sequencing. This latter view is supported by the terpolymer temperature transitions (T_g and T_m) from DSC and the thermal decomposition profile from TG. The results and, in particular, the conclusion that it is a random rather than a statistical terpolymer are discussed in the light of current theories regarding the mechanism of this type of polymerization. © 2001 Society of Chemical Industry     

The validity and reliability of the Dutch Effort–Reward Imbalance Questionnaire.

The reliability and validity of the Effort–Reward Imbalance Questionnaire were tested in 775 blue- and white-collar workers in the Netherlands. Cronbach's alpha revealed sufficient internal consistency of all subscales except Need for Control. With exploratory probabilistic scaling (Mokken) analysis, the psychometric qualities of the Need for Control scale were improved. With confirmatory factor analysis, the factorial validity of the Extrinsic Effort and Reward subscales was confirmed. A model with 3 separate dimensions for reward (status control, esteem reward, and monetary gratification) proved adequate, emphasizing the importance of distinguishing subscales. The congruent validity of the subscales and a hypothesized relationship with an external construct, health functioning, were confirmed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Impact of Administered <Emphasis Type="Italic">Bifidobacterium</Emphasis> on Murine Host Fatty Acid Composition

Recently, we reported that administration of Bifidobacteria resulted in increased concentrations of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in murine adipose tissue [1]. The objective of this study was to assess the impact of co-administration of Bifidobacterium breve NCIMB 702258 and the substrate for EPA, α-linolenic acid, on host fatty acid composition. α-Linolenic acid-supplemented diets (1%, wt/wt) were fed to mice (n = 8), with or without B. breve NCIMB 702258 (daily dose of 10⁹ microorganisms) for 8 weeks. Two further groups received either supplement of B. breve alone or unsupplemented diet. Tissue fatty acid composition was assessed by gas liquid chromatography. Dietary supplementation of α-linolenic acid resulted in higher (P < 0.05) α-linolenic acid and EPA concentrations in liver and adipose tissue and lower (P < 0.05) arachidonic acid in liver, adipose tissue and brain compared with mice that did not receive α-linolenic acid. Supplementation with B. breve NCIMB 702258 in combination with α-linolenic acid resulted in elevated (P < 0.05) liver EPA concentrations compared with α-linolenic acid supplementation alone. Furthermore, the former group had higher (P < 0.05) DHA in brain compared with the latter group. These results suggest a role for interactions between fatty acids and commensals in the gastrointestinal tract. This interaction between administered microbes and fatty acids could result in a highly effective nutritional approach to the therapy of a variety of inflammatory and neurodegenerative conditions.