1,720,964 research outputs found
A Multi-Agent Simulation System for Prediction and Scheduling of Aero Engine Overhaul
No full textThe Aero Repair and Overhaul industry is facing an increasing challenge of prediction and scheduling of engine overhauls to remain competitive in a complex business arena. An appropriate technology solution is required to achieve efficient schedules while satisfying multiple opposing constraints in a highly dynamic environment. In this paper, we describe Overhaul Prediction and Scheduling, an agent-based simulator developed to tackle this challenge. Using negotiation strategies, it deals with the multi-dimensional scheduling optimisation problem by trading off repair costs, capacity and capability of overhaul bases, among others, in light of in-service unforseen events. It supports effective strategic decision-making via business scenario modelling
Data quality assessment from provenance graphs
No full textProvenance is a domain-independent means to represent what happened in an application, which can help verify data and infer data quality. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. This paper presents an application-independent methodology for analyzing data based on the network metrics of provenance graphs to learn about such patterns and to relate them to data quality in an automated manner. Validating this method on the provenance records of CollabMap, an online crowdsourcing mapping application, we demonstrated an accuracy level of over 95% for the trust classification of data generated by the crowd therein
Interpretation of Crowdsourced Activities Using Provenance Network Analysis
No full textUnderstanding the dynamics of a crowdsourcing application and controlling the quality of the data it generates is challenging, partly due to the lack of tools to do so. Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer their quality. It can also reveal the processes that led to a data item and the interactions of contributors with it. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. This paper presents an application-independent methodology for analysing provenance graphs, constructed from provenance records, to learn about such patterns and to use them for assessing some key properties of crowdsourced data, such as their quality, in an automated manner. Validating this method on the provenance records of CollabMap, an online crowdsourcing mapping application, we demonstrated an accuracy level of over 95% for the trust classification of data generated by the crowd therein
Network analysis on provenance graphs from a crowdsourcing application
Get PDFCrowdsourcing has become a popular means for quickly achieving various tasks in large quantities. CollabMap is an online mapping application in which we crowdsource the identification of evacuation routes in residential areas to be used for planning large-scale evacuations. So far, approximately 38,000 micro-tasks have been completed by over 100 contributors. In order to assist with data verification, we introduced provenance tracking into the application, and approximately 5,000 provenance graphs have been generated. They have provided us various insights into the typical characteristics of provenance graphs in the crowdsourcing context. In particular, we have estimated probability distribution functions over three selected characteristics of these provenance graphs: the node degree, the graph diameter, and the densification exponent. We describe methods to define these three characteristics across specific combinations of node types and edge types, and present our findings in this paper. Applications of our methods include rapid comparison of one provenance graph versus another, or of one style of provenance database versus another. Our results also indicate that provenance graphs represent a suitable area of exploitation for existing network analysis tools concerned with modelling, prediction, and the inference of missing nodes and edges
Predicting orthostatic vasovagal syncope with signal processing and physiological modelling
Get PDFOrthostatic vasovagal syncope is the sudden loss of consciousness resulting from a temporary impairment of cerebral blood flow, within approximately an hour of standing. Patients who suffer from this problem have "vasovagal syndrome". The purpose of this thesis was to devise a method to detect the syndrome following the assumption of upright position. Data from 106 syncopal patients undergoing head-up tilt table testing (HUT) were acquired, including electrical activity of the heart (electrocardiogram), blood pressure, oxygen saturation, and cerebral perfusion parameters from near-infrared spectroscopy (NIRS). The data set was examined with the aim of generating automatic diagnoses. Comparison of the rate-pressure product (blood pressure multiplied by heart rate) during the time of syncope with a recommended threshold, in addition to comparison with monitoring the fall of systolic blood pressure during prolonged tilt, yielded an 84% accuracy rate for vasovagal syndrome. The thesis reviewed the techniques used on the aforementioned time series by previous researchers, emphasising the concepts underlying "time-frequency analysis", a method for analysing nonstationary signals. Since even healthy patients experience time-varying frequency information in their haemodynamics, a transform known as the Smoothed Pseudo-Wigner Ville Distribution (SPWVD) is well suited to their analysis. This distribution was applied to RR tachograms, plots of heart period against time. After the smoothing parameters of the SPWVD were chosen based on artificial data, the optimised transform was then applied to a second artificial tachogram to calculate the LF/HF (low- to high-frequency) ratio, an indicator of heart rate variability. The computed LF/HF ratio tracked the expected value within an error margin of 3.6%. Finally, by applying the same transform to clinical data, it was proved to offer better resolution than an alternative known as the Lomb periodogram. Classical techniques from the literature predicting vasovagal syncope were found to fail on the current data set: out of 29 tests, only two yielded statistically significant differences between the two patient groups. These were compared with the author's time-frequency analysis of RR tachograms, linear regression of heart rate, and examination of NIRS oscillations and changes on tilt. Of these, the ICFV during time period P3 was found to perform best (negative predictive value: 0.86). A linear classifier was used to combine the best four predictors; it achieved an overall accuracy of 0.88. Following the data-driven approach, an analytical modelling approach was undertaken. In order to define an appropriate model that traded off simplicity with comprehensiveness, the mechanisms of vasovagal syncope were reviewed. A model of orthostasis was developed, validated, and used toward parameter estimation from patient data. Three parameters (baroreceptor operating point, cardiac effectiveness, and baroreflex gain) were gleaned from the supine baseline recording to "normalise" the model for a given patient, before four new parameters (sympathetic and parasympathetic gains at the sino-atrial node, peripheral vasoconstriction gain, and total blood volume) were estimated from the data collected in the upright position. The expectation was that this approach would improve feature extraction (and hence prediction accuracy) as well as the clinical interpretation of the results. However, the modelling approach was found to offer no significant improvement upon the data-driven signal processing results: a linear classifier on the four post-tilt parameters yielded a negative predictive value of just 0.69. This result may have been due to inaccuracies in the time series data owing to instrumentation error. It is also possible that the modelling approach was not able to provide the quality of feature extraction necessary for predicting vasovagal syncope in the elderly. Finally, methods to predict syncope during mid- to late HUT were examined. Using information derived from heart rate and baroreflex sensitivity, a technique was developed to ease patient comfort by terminating the test approximately 2 minutes before syncope was expected to occur
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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