1,720,957 research outputs found
A Time-Aware Data Clustering Approach to Predictive Maintenance of a Pharmaceutical Industrial Plant
No full textPredictive maintenance is one of the most active fields of study for Industry 4.0, as it is expected to significantly decrease the maintenance costs of the equipment. Often, it is not possible to accurately predict the deterioration of a component, as the reliability of predictive models strongly depends on the available sensory data and on the specific characteristics of the monitored component. In this paper, we present a clustering-based approach with the aim of predicting the time-Aware evolution of the health status of a machine component in a pharmaceutical plant. The developed strategy allows to obtain a time segmentation of the component's operational points, which are then clustered using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). In particular, this approach has the advantage of being general and making use of a limited amount of features extracted from a single sensor signal. The proposed approach becomes attractive when the quantity of single sensory collected data is not sufficient to build a physical model capable of identifying changes in the system status
On Sensor Data Clustering for Machine Status Monitoring and Its Application to Predictive Maintenance
Full text linkPredictive maintenance is one of the main approaches on which Industry 4.0 is based since it aims at reducing unplanned downtime and maintenance costs of industrial machines. In this work, a time-aware clustering-based approach to the analysis of sensor data is presented for the purpose of monitoring the time evolution of the health status of an industrial machine. A possible application of the proposed framework to predictive maintenance is then proposed. As a relevant representative application scenario, the focus is on one of the key machines in a pharmaceutical plant: a freeze dryer. The illustrated procedure allows for carrying out a time segmentation of the properly sensed data. More precisely, the corresponding operational points (associated with features of the sensed data) are clustered using various algorithms, among which density-based spatial clustering of applications with noise (DBSCAN) turns out to be the best. The benefits of the proposed approach are: 1) its general nature and 2) the limited amount of needed features that have to be extracted from a single sensor signal. The proposed procedure is attractive when the collected data (e.g., from a single sensor) are not sufficient to build an accurate physical model of the monitored component
Grande Espetáculo de Ballet Eleonora Oliosi e João Luiz Rolla (1950) - Programa
No full textPrograma impresso em papel sulfite na cor branca medindo 23 cm x 21 cm. Apresenta marcas de envelhecimento. O documento integra o acervo doado por Maria Celeste Etges.Programa de Espetáculo de Eleonora Oliosi e João Luiz Rolla em beneficio da Associação de Caridade Santa Casa do Rio Grande, contendo a descrição das coreografias apresentadas de autoria de Tony Seitz Petzhold. O espetáculo foi realizado no dia 17 de Novembro de 1950 no Cine Teatro Carlos Gomes em Porto Alegre.DoaçãoDanç
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
Simulation-based Analysis of Experimental 5G NR Downlink CSI-RSRP-based Handover Performance
No full textVariations 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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