1,720,954 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
Design and development of an Amazon Alexa's skill for vocal interactions in business environment
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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
Data-Driven Predictive Modeling for Alzheimer's Disease Progression: Integrating Choroid Plexus Volume Analysis
No full textreservedIndividuals with Mild Cognitive Impairment (MCI) are at greater risk of developing Alzheimer’s disease (AD). Early detection of those more likely to develop AD holds great potential for preventative and/or therapeutic interventions. This thesis aims to explore demographic, neuroimaging, and neuropsychiatric data to identify the most informative factors influencing MCI to AD conversion. Using machine learning models, the research seeks to distinguish between MCI converters and non-converters, with a specific focus on exploring the potential association between choroid plexus volume and conversion. Choroid plexus volume was introduced as a representative measure of choroid plexus morphology, which may be linked to choroid plexus function and/or cerebrospinal fluid dynamics. The data involved come from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and only data from baseline visits are considered. The dataset includes 393 MCI patients who converted to AD and 130 MCI patients who did not convert to AD. The first step involves replicating the methodology of Matthew Velasquez et al. (2021). This process includes training different machine learning models (random forest, logistic regression, SVM, XGBoost) on distinct feature subsets and assessing their importance in predicting MCI conversion to AD. Choroid plexus volume measures are then incorporated into the most effective models to investigate their impact on predictive outcomes. Feature importance is explored with permutation importance, LIME, and SHAP algorithms. For the classification task without the choroid plexus feature, SVM and logistic regression gave the best performance, especially in terms of specificity (SVM6 = 0.942, LR6 = 0.885, SVM13 = 0.885, LR13 = 0.857). The most important features of these models were ADAS13, FAQ, Hippocampus, and APOE4. When including the choroid plexus variable in the four best models, performances in specificity slightly decreased (SVM7 = 0.885, LR6 = 0.885, SVM13 = 0.857, LR13 = 0.828), suggesting that choroid plexus volume may not provide useful information for predicting conversion to AD. From feature importance analysis,
ADAS13, FAQ, Hippocampus, and APOE4 confirmed their importance in the prediction,
while the choroid plexus volume had little impact on the model decision. This study showed that the choroid plexus volume may not play a central role in predicting the conversion of MCI patients to AD. It may be possible that disease-related changes to the choroid plexus that may be useful in prediction are not captured in the volume measure, and other measures of choroid plexus function or cerebrospinal fluid dynamics may be more informative. Further investigations into the role of the choroid plexus in MCI and AD are needed.Individuals with Mild Cognitive Impairment (MCI) are at greater risk of developing Alzheimer’s disease (AD). Early detection of those more likely to develop AD holds great potential for preventative and/or therapeutic interventions. This thesis aims to explore demographic, neuroimaging, and neuropsychiatric data to identify the most informative factors influencing MCI to AD conversion. Using machine learning models, the research seeks to distinguish between MCI converters and non-converters, with a specific focus on exploring the potential association between choroid plexus volume and conversion. Choroid plexus volume was introduced as a representative measure of choroid plexus morphology, which may be linked to choroid plexus function and/or cerebrospinal fluid dynamics. The data involved come from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and only data from baseline visits are considered. The dataset includes 393 MCI patients who converted to AD and 130 MCI patients who did not convert to AD. The first step involves replicating the methodology of Matthew Velasquez et al. (2021). This process includes training different machine learning models (random forest, logistic regression, SVM, XGBoost) on distinct feature subsets and assessing their importance in predicting MCI conversion to AD. Choroid plexus volume measures are then incorporated into the most effective models to investigate their impact on predictive outcomes. Feature importance is explored with permutation importance, LIME, and SHAP algorithms. For the classification task without the choroid plexus feature, SVM and logistic regression gave the best performance, especially in terms of specificity (SVM6 = 0.942, LR6 = 0.885, SVM13 = 0.885, LR13 = 0.857). The most important features of these models were ADAS13, FAQ, Hippocampus, and APOE4. When including the choroid plexus variable in the four best models, performances in specificity slightly decreased (SVM7 = 0.885, LR6 = 0.885, SVM13 = 0.857, LR13 = 0.828), suggesting that choroid plexus volume may not provide useful information for predicting conversion to AD. From feature importance analysis,
ADAS13, FAQ, Hippocampus, and APOE4 confirmed their importance in the prediction,
while the choroid plexus volume had little impact on the model decision. This study showed that the choroid plexus volume may not play a central role in predicting the conversion of MCI patients to AD. It may be possible that disease-related changes to the choroid plexus that may be useful in prediction are not captured in the volume measure, and other measures of choroid plexus function or cerebrospinal fluid dynamics may be more informative. Further investigations into the role of the choroid plexus in MCI and AD are needed
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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