1,720,963 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
Покращення розпізнавання дій на основі скелета за допомогою гібридних реальних та згенерованих наборами даних
No full textThis research addresses the critical challenge of recognizing mutual actions involving multiple individuals, an important task for applications such as video surveillance, human-computer interaction, autonomous systems, and behavioral analysis. Identifying these actions from 3D skeleton motion sequences poses significant challenges due to the necessity of accurately capturing intricate spatial and temporal patterns in diverse, dynamic, and often unpredictable environments. To tackle this, a robust neural network framework was developed that combines Convolutional Neural Networks (CNNs) for efficient spatial feature extraction with Long Short-Term Memory (LSTM) networks to model temporal dependencies over extended sequences. A distinguishing feature of this study is the creation of a hybrid dataset that which combines real-world skeleton motion data with synthetically generated samples, produced using Generative Adversarial Networks (GANs). This dataset enriches variability, enhances generalization, and mitigates data scarcity challenges. Experimental findings across three different network architectures demonstrate that our method significantly enhances recognition accuracy, mainly due to the integration of CNNs and LSTMs alongside the broadened dataset. Our approach successfully identifies complex interactions and ensures consistent performance across different perspectives and environmental conditions. The improved reliability in recognition indicates that this framework can be effectively utilized in practical applications such as security systems, crowd monitoring, and other areas where precise detection of mutual actions is critical, particularly in real-time and dynamic environmentsЦе дослідження стосується критичної проблеми розпізнавання взаємних дій за участю кількох осіб, важливого завдання для таких програм, як відеоспостереження, взаємодія людини з комп’ютером, автономні системи та аналіз поведінки. Ідентифікація цих дій із тривимірних послідовностей рухів скелета створює значні проблеми через необхідність точного захоплення складних просторових і часових моделей у різноманітних, динамічних і часто непередбачуваних середовищах. Щоб вирішити цю проблему, було розроблено надійну структуру нейронної мережі, яка поєднує згорткові нейронні мережі (CNN) для ефективного вилучення просторових ознак із мережами довготривалої короткочасної пам’яті (LSTM) для моделювання часових залежностей у розширених послідовностях. Відмінною рисою цього дослідження є створення гібридного набору даних, який поєднує дані про рух скелета в реальному світі з синтетично згенерованими зразками, створеними за допомогою генеративних змагальних мереж (GAN). Цей набір даних збагачує варіативність, покращує узагальнення та пом’якшує проблеми дефіциту даних. Експериментальні результати в трьох різних мережевих архітектурах демонструють, що запропонований в даному дослідженні метод значно підвищує точність розпізнавання, в основному завдяки інтеграції CNN і LSTM разом із розширеним набором даних. Такий підхід успішно визначає складні взаємодії та забезпечує стабільну продуктивність у різних точках зору та в умовах навколишнього середовища. Підвищена надійність розпізнавання вказує на те, що цю структуру можна ефективно використовувати в практичних програмах, таких як системи безпеки, моніторинг натовпу та інших областях, де точне виявлення взаємних дій є критичним, особливо в реальному часі та динамічних середовища
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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