1,720,995 research outputs found
What’s New in Temporal Databases?
No full textTemporal databases has been an active research area since many decades, ranging from research work on query processing, most dominantly on selection and join queries, to new directions in models and semantics, such as for instance temporal probabilistic or streaming data. At the same time more database vendors have been integrating temporal features into their systems, most notably, the temporal features of the SQL standard. In this paper, we summarize the latest research developments as presented in 30 research papers over the last five years in the context of temporal relational databases. Additionally, we also describe the developments of industrial database systems and vendors
Efficient Computation of All-Window Length Correlations
No full textThe interactive exploration of time series is an important task in data analysis. In this paper, we concentrate on the investigation of linear correlations between time series. Since the correlation of time series might change over time, we consider the analysis of all possible subsequences of two time series. Such an approach allows identifying, at different levels of window length, periods over which two time series correlate and periods over which they do not correlate. We provide a solution to compute the correlations over all window lengths in O(n2) time, which is the size of the output and hence the best we can achieve. Furthermore, we propose a visualization of the result in the form of a heatmap, which provides a compact overview on the structure of the correlations amenable for a data analyst. An experimental evaluation shows that the tool is efficient to allow for interactive data exploration
Cache-efficient sweeping-based interval joins for extended Allen relation predicates
No full textWe develop a family of efficient plane-sweeping interval join algorithms for evaluating a wide range of interval predicates such as Allen’s relationships and parameterized relationships. Our technique is based on a framework, components of which can be flexibly combined in different manners to support the required interval relation. In temporal databases, our algorithms can exploit a well-known and flexible access method, the Timeline Index, thus expanding the set of operations it supports even further. Additionally, employing a compact data structure, the gapless hash map, we utilize the CPU cache efficiently. In an experimental evaluation, we show that our approach is several times faster and scales better than state-of-the-art techniques, while being much better suited for real-time event processing
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
Estimation of Mass and Lengths of Sintered Workpieces Using Machine Learning Models
Full text linkPowder metallurgy (PM) is the branch of metallurgy that deals with the design/production of near-net-shaped sintered workpieces with different shapes and characteristics. The produced sintered workpieces are used in the automotive, aviation, and aerospace industries, just to name a few. The quality of the produced sintered workpieces largely depends on powder compaction techniques and the accurate adjustments of process parameters. Currently, adjustments of these process parameters are done manually and thus resulting in laborious and time-intensive effort. To this end, this article explores the use of machine learning (ML) in the compaction process and proposes an accurate and lightweight ML-based pipeline to estimate the quality characteristics (QCs) of the produced workpieces in the PM domain. More specifically, it presents a pipeline for workpiece's mass and lengths estimation by exploiting some novel hand-crafted features and comparing well-selected ML prediction models, namely, random forest (RF), AdaBoost (ADA), and gradient boosting (GB). The chosen models are trained on a combination of features extracted from environmental and sensory raw data to estimate the mass and lengths of the next produced workpiece. We have implemented and evaluated our scheme on a dataset collected in a real production environment and we have found that GB is the most consistent and accurate one with the lowest root-mean-squared error (approximate to 0.0886%). The results of extensive experimentation have proven the relevance of the selected features and the accuracy of GB
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