1,720,970 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
EDL-Det: A Robust TTS Synthesis Detector Using VGG19-Based YAMNet and Ensemble Learning Block
No full textVarious audio deep fake synthesis algorithms exist, such as deep voice, tacotron, fastspeech, and imitation techniques. Despite the existence of various spoofing speech detectors, they are not ready to distinguish unseen audio samples with high precision. In this study, we suggest a robust model, namely an Ensemble Deep Learning Detector (EDL-Det), to detect text-to-speech (TTS) and categorize it into spoofed and bonafide classes. Our proposed model is an improved method based on Yet Another Multi-scale Convolutional Neural Network (YAMNet) employing VGG19 as a base network combined with two other deep learning(DL) techniques. Our proposed system effectively analyzes the audio to extract better artifacts. We have added an ensemble learning block that consists of ResNet50 and InceptionNetv2. First, we convert speech into mel-spectrograms that consist of time-frequency representations. Second, we train our model using the ASVspoof-2019 dataset. Ultimately, we classified the audios, transforming them into mel-spectrograms using our trained binary classifier and a majority voting scheme by three networks. Due to ensemble architecture, our proposed model effectively extracts the most representative features from the mel-spectrograms. Furthermore, we have performed extensive experiments to assess the performance of the suggested model using the ASVspoof 2019 corpus. Additionally, our proposed model is robust enough to identify the unseen spoofed audios and accurately classify the attacks based on cloning algorithms
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Lung-RetinaNet: Lung Cancer Detection Using a RetinaNet With Multi-Scale Feature Fusion and Context Module
No full textLung cancer is one of the terrible diseases in various countries around the globe, and timely detection of the illness is still a challenging process. The oncologists consider the blood test results and CT scans to assess the tumor, which is time-consuming and involves extra human effort. Therefore, an automated system should be developed to efficiently recognize lung tumors and assess their severity to reduce mortality. Although various researchers have proposed lung disease detection systems, the existing techniques still lack significant detection accuracy for early-stage tumors. Thus, this study proposes a novel and efficient lung tumor detector based on a RetinaNet, namely Lung-RetinaNet. A multi-scale feature fusion-based module is introduced to aggregate various network layers, simultaneously increasing the semantic information from the shallow prediction layer. Moreover, a dilated and lightweight algorithm is employed for the context module to combine contextual information with each network stage layer to improve features and effectively localize the tiny tumors. The proposed methodology attained 99.8% accuracy, 99.3% recall, 99.4% precision, 99.5% F1-score, and 0.989 Auc. We evaluated our suggested model and matched the performance with state-of-the-art DL-based methods. The outcomes show that our technique provides more substantial results than existing methods
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