1,720,956 research outputs found
Stress level regulation and workplace wellbeing: A project proposal considering wearable and smart biosensors useful in monitoring stress and maintaining effects of the Progressive Muscle Relaxation Training
No full textUsing Machine Learning Models to identify people who suffer from Hoarding Disorder based on trans-diagnostic constructs.
No full textEstimating Activity Start Timestamps in the Presence of Waiting Times via Process Simulation
No full textProcess Mining aims to analyze and improve processes to enable organizations to provide better services or products. The starting point of Process Mining is an event log that is extracted from the organization’s information systems that support the process’ executions. Several techniques require event logs to record the timestamp when process’ activities have started and been completed. Unfortunately, information systems do not always record the timestamps when process activities start, preventing the application of these techniques. This paper reports on a technique based on process simulation that aims to estimate the start event timestamps when missing. In a nutshell, the idea is to build an accurate process model from the initial event log without start timestamps, to simulate it with alternative activity-duration profiles, and to select the model with the profile that generates the runs that are the closest to the initial log. This activity-duration profile is used to add the missing, start timestamps to the initial log. Experiments were conducted with two event logs with start timestamps, and aimed at their rediscovery: the results show our estimation of the start event timestamps is more accurate than the state of the art
A Framework to Improve the Accuracy of Process Simulation Models
No full textBusiness process simulation is a methodology that enables analysts to run the process in different scenarios, compare the performances and consequently provide indications into how to improve a business process. Process simulation requires one to provide a simulation model, which should accurately reflect reality to ensure the reliability of the simulation findings. This paper proposes a framework to assess the extent to which a simulation model reflects reality and to pinpoint how to reduce the distance. The starting point is a business simulation model, along with a real event log that records actual executions of the business process being simulated and analyzed. In a nutshell, the idea is to simulate the process, thus obtaining a simulation log, which is subsequently compared with the real event log. A decision tree is built, using the vector of features that represent the behavioral characteristics of log traces. The tree aims to classify traces as belonging to the real and simulated event logs, and the discriminating features encode the difference between reality, represented in the real event log, and the simulation model, represented in the simulated event logs. These features provide actionable insights into how to repair simulation models to become closer to reality. The technique has been assessed on a real-life process for which the literature provides a real event log and a simulation model. The results of the evaluation show that our framework increases the accuracy of the given initial simulation model to better reflect reality
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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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