1,720,977 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
Alzheimer’s Disease Diagnosis Assistance Through the Use of Deep Learning and Multimodal Feature Fusion
No full textPatients suffering from Alzheimer's disease (AD) lose their ability to think and frequently forget what they have learned during their life. There are currently no effective therapies available for this illness. The sooner the disease is recognized, the better the therapy alternatives and the greater the possibility of eliminating Alzheimer’s. Computer-assisted diagnosis, or CAD, is a method that integrates neuroimaging with deep learning algorithms trained on multimodal pictures. The CAD system is powered by deep learning algorithms that were trained to function by being exposed to a diverse spectrum of artistic outputs. Each component of the system affects the functioning of these algorithms. In recent years, several multimodal feature learning-based alternative techniques for extracting and integrating latent. We were able to achieve our aim because we devised several novel approaches. Here are some more detailed illustrations of imaging techniques: This diagnostic category includes imaging procedures such as MRI and PET scans. Given the complexities of the procedures utilized, providing a complete assessment of the immeasurable value of the data obtained is difficult. An image-based multimodal fusion approach is proposed as a result, our understanding of the brain’s structure and operation has grown significantly. The technique's primary emphasis is the grey matter of the brain. We were able to provide more accurate diagnoses to individuals suffering from neurological diseases. To accomplish our purpose, we use the registration and mask coding procedures. This had a direct impact on the creation of a well-rounded theory aimed primarily at the automobile sector. In addition, we put our image fusion approach to the test with a 3D basic convolutional neural network for binary classification and a 3D multi-scale CNN for multiple classification tasks. These two networks are linked by the fact that they are 3D convolutional neural networks. In a three-dimensional situation, both functions admirably. Using the ADNI dataset, researchers revealed that their suggested picture fusion algorithm outperformed cutting-edge approaches for detecting Alzheimer's disease. Furthermore, as compared to feature fusion and single-modal approaches, its overall performance is significantly superior.</p
Electroencephalogram Analysis Using Convolutional Neural Networks in Order to Diagnose Alzheimer’s Disease
No full textRecent technological advances have made it possible to collect biomarkers in the same geographic areas where a disease's earliest symptoms occur. Recent technical advances have enabled the collection of biomarkers in areas where early symptoms co-occur. This goal, which is important for finding Alzheimer's disease and its symptoms quickly and accurately, could be achieved in a way that is helpful. It is critical to attain this goal to have a way to treat Alzheimer’s disease and its symptoms. It is critical to recognize Alzheimer's disease and its symptoms accurately and immediately, while also maintaining a high degree of diagnostic accuracy. This goal's significance cannot be overemphasized. This severe impediment must be overcome to go forward. It will be critical to monitor the postsynaptic potential of hundreds of neurons grouped in the same spatial orientation to progress in this direction. This enables the calculation of the entire amount of time that the electrical activity happened during the measurement. This is since the total length of time may be calculated. Time-dependent power spectrum descriptors were employed in this study to provide a differential diagnosis of electroencephalogram signal function. This chapter will be delivered to you as verification of the accomplishments. You will be given this information in the form of a record after the findings have been tallied. Convolutional neural networks will be the focus of the third phase of the discussion on how to categorize people with Alzheimer’s disease. Following that, we'll conclude our investigation into this topic. These networks have just recently, if at all, been created and placed into service. Analyzing the data indicated that the initiative was a resounding and unequivocal success in every way. The absence of negative outcomes may lead to this conclusion. Look at this fantastic example: When convolutional neural networks are used as the analytical technique, the concept of correctness is accurate to an accuracy precision of 82.3%. This demonstrates that our understanding of the concept is correct. There was a lot of success in terms of obtaining the desired degree of precision. Only 85% of cases with moderate cognitive impairment are fully and totally recognized, compared to 75% of the population that is healthy and 89.1% of cases associated with Alzheimer’s disease.</p
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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