1,720,983 research outputs found
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Görsel tanıma problemlerine yakın ve uzun mesafeli kanıtların entegre edilmesi
No full textThis thesis presents HoughNet, a one-stage, anchor-free, voting-based, bottom-up object detection method. Inspired by the Generalized Hough Transform, HoughNet determines the presence of an object at a certain location by the sum of the votes cast on that location. Votes are collected from both near and long-distance locations based on a log-polar vote field. Thanks to this voting mechanism, HoughNet is able to integrate both near and long-range, class-conditional evidence for visual recognition, thereby generalizing and enhancing current object detection methodology, which typically relies on only local evidence. On the COCO dataset, HoughNet`s best model achieves 46.4 AP (and 65.1 AP_50), performing on par with the state-of-the-art in bottom-up object detection and outperforming most major one-stage and two-stage methods. We further validate the effectiveness of our proposal in other visual detection tasks, namely, video object detection, instance segmentation, 3D object detection, keypoint detection for human pose estimation and whole-body human pose estimation, face detection and an additional ``labels to photo`` image generation task, where the integration of our voting module consistently improves performance in all cases. In order to show the effectiveness of our proposal on whole-body human pose estimation task, we developed a bottom-up, one-stage method called HPRNet. In HPRNet, we build a hierarchical regression mechanism, where we define each of the whole-body keypoints with a relative location (i.e. offset) to a specific point on the person box. In the context of this thesis we also propose a one-stage, anchor-free object detector, PPDet, which integrates short-range interactions through voting. PPDet sum-pools predictions stemming from individual features into a single prediction which allows the model to reduce the contributions of non-discriminatory features during training.Bu tez, tek-aşamalı, sınırlayıcı kutu içermeyen, oylamaya dayalı, aşağıdan-yukarıya nesne tanıma yöntemi olan HoughNet`i sunar. Genelleştirilmiş Hough Dönüşümü`nden esinlenen HoughNet, belirli bir konumdaki bir nesnenin varlığını, o konuma verilen oyların toplamına göre belirler. Oylar, log-polar oy alanına dayalı olarak hem yakın hem de uzak mesafelerden toplanır. Bu oylama mekanizması sayesinde, HoughNet görsel tanıma için hem yakın hem de uzun mesafeli, sınıf koşullu kanıtları entegre edebilir, böylece tipik olarak yalnızca yerel kanıtlara dayanan mevcut nesne algılama metodolojisini genelleştirir ve geliştirir. COCO veri kümesinde, HoughNet`in en iyi modeli 46.4 AP (ve 65.1 AP_50) elde ederek aşağıdan-yukarıya nesne tanıma yöntemleri ile benzer seviyede başarım göstermiş ve bir çok ana tek-aşamalı ve iki-aşamalı nesne tanıma yöntemlerini geride bırakmıştır. Önerdiğimiz yöntemin etkinliğini diğer görsel tanıma problemlerinde, yani videolarda nesnesi tanıma, nesne bölütleme, 3B nesne tanıma, insan pozisyon kestirimi, tüm-vücut insan pozisyon kestirimi, yüz tanıma ve ek olarak ``etiketten fotoğrafa`` görüntü oluşturma probleminde doğruladık. Buna göre, oylama modülümüz entegre edildiği her durumda performansı sürekli olarak iyileştirmiştir. Önerimizin tüm-vücut insan pozisyon kestirimi için etkinliğini göstermek için HPRNet adını verdiğimiz aşağıdan-yukarıya tek-aşamalı bir yöntem geliştirdik. HPRNet`te, tüm-vücut ana noktalarının her birini, insan sınırlayıcı kutu üzerindeki belirli noktalara göreli bir konumla tanımladığımız hiyerarşik bir regresyon mekanizması oluşturuyoruz. Bu tez bağlamında ayrıca, oylama yoluyla kısa mesafeli etkileşimleri entegre eden, tek-aşamalı, sınırlayıcı kutu içermeyen bir nesne tanıma yöntemi olan PPDet`i öneriyoruz. PPDet, tekil özniteliklerden elde edilen tahminleri tek bir tahminde toplar, bu sayede eğitim sırasında ayırt edici olmayan özniteliklerin katkılarının azaltmasına olanak tanır.Ph.D. - Doctoral Progra
Unsupervised segmentation and ordering of cervical cells : Serviks hücrelerinin öğreticisiz olarak bölütlenmesi ve sıralanması
Get PDFCataloged from PDF version of article.Includes bibliographical references leaves 69-73.Cervical cancer is the second most common cause of cancer death among women
worldwide, and it can be prevented if it is detected and treated in the precancerous
stages. Pap smear test is a common, efficient and easy manual screening
examination technique which is used to detect dysplastic changes in cervical
cells. However, manual analyses of thousands of cells in Pap smear test slides by
cyto-technicians is difficult, time consuming and subjective. To overcome these
problems, we aim to automate the screening process and provide an ordered nuclei
list to help the cyto-experts. Automating the screening procedure has been a
longstanding challenge because of complex cell structures where current methods
in the literature mostly consider the problem as the segmentation of single isolated
cells and leave real challenges of Pap smear images such as poor contrast,
inconsistent staining, and unknown number of cells unaddressed.
We propose an unsupervised method to accurately segment the nuclei and
order them according to their abnormality degree in Pap smear images. The
method first uses a multi-scale hierarchical segmentation algorithm for accurate
identification of the nuclei. The Pap smear images captured at high level magni-
fication have more detailed texture but worse contrast. Contrast is an important
property for segmentation and detailed texture is an important property for feature
extraction. Therefore, as a solution to the segmentation problem, we proceed
in two steps. First, we segment the Pap smear images at low (20x) magnification
and eliminate non-nucleus regions based on several features. Then, we switch to
high (40x) magnification and obtain a more detailed segmentation of the remaining
nuclei. Following segmentation, we extract features for each resulting nucleus.
Unlike related works that require a learning phase for classification, our method
performs an unsupervised ordering of the nuclei based on features extracted at
40x magnification. We compare different ordering algorithms for ranking the nucleus regions according to their abnormality degrees.
We evaluate our segmentation and ordering methods using two data sets.
Our results show that the proposed method provides promising results for both
segmentation and ordering steps.Samet, Nermi
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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