1,721,381 research outputs found
Jenkinson, M I, VX37904
This record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/395180Surname: JENKINSON. Given Name(s) or Initials: M I. Military Service Number or Last Known Location: VX37904. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 39328.228978
Item: [2016.0049.27473] "Jenkinson, M I, VX37904
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
Normalised accurate measurement of longitudinal brain change
PURPOSE:
Quantitative measurement of change in brain size and shape (e.g., to estimate atrophy) is an important current area of research. New methods of change analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method has been developed that achieves high estimation accuracy.
METHOD:
A fully automated method of longitudinal change analysis is presented here, which automatically segments brain from nonbrain in each image, registers the two brain images while using estimated skull images to constrain scaling and skew, and finally estimates brain surface motion by tracking surface points to subvoxel accuracy.
RESULTS AND CONCLUSION:
The method described has been shown to be accurate ( approximately 0.2% brain volume change error) and to achieve high robustness (no failures in several hundred analyses over a range of different data sets)
Evaluating and reducing the impact of white matter lesions on brain volume measurements.
MR-based measurements of brain volumes may be affected by the presence of white matter (WM) lesions. Here, we assessed how and to what extent this may happen for WM lesions of various sizes and intensities. After inserting WM lesions of different sizes and intensities into T1-W brain images of healthy subjects, we assessed the effect on two widely used automatic methods for brain volume measurement such as SIENAX (segmentation-based) and SIENA (registration-based). To explore the relevance of partial volume (PV) estimation, we performed the experiments with two different PV models, implemented by the same segmentation algorithm (FAST) of SIENAX and SIENA. Finally, we tested potential solutions to this issue. The presence of WM lesions did not bias measurements for registration-based method such as SIENA. By contrast, the presence of WM lesions affected segmentation-based brain volume measurements such as SIENAx. The misclassification of both gray matter (GM) and WM volumes varied considerably with lesion size and intensity, especially when the lesion intensity was similar to that of the GM/WM interface. The extent to which the presence of WM lesions could affect tissue-class measures was clearly driven by the PV modeling used, with the mixel-type PV model giving a lower error in the presence of WM lesions. The tissue misclassification due to WM lesions was still present when they were masked out. By contrast, refilling the lesions with intensities matching the surrounding normal-appearing WM ensured accurate tissue-class measurements and thus represents a promising approach for accurate tissue classification and brain volume measurements
Variations on the Author
“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
We 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
We 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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