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
Machine learning-based lung cancer diagnosis
No full textCancer is one of the leading health problems, occurring in various organs and tissues of the body, and its incidence is increasing worldwide. Lung cancer is one of the deadliest types of cancer. Due to its worldwide prevalence, increasing number of cases, and deadly consequences, early detection of lung cancer, as with all other cancers, greatly increases the chances of survival. As with all other diseases, the diagnosis of cancer is only possible after the appearance of various symptoms and an examination by specialists. Known symptoms of lung cancer are shortness of breath, coughing, wheezing, jaundice in the fingers, chest pain, and difficulty swallowing. The diagnosis is made by an expert on site based on these symptoms and additional tests. The aim of this study is to detect the disease at an earlier stage based on the symptoms present, to assess more cases with less time and cost, and to achieve results in new situations that are as successful or even faster than those of human experts by deriving them from existing data using different algorithms. The aim is to develop an automated model that can detect early-stage lung cancer based on machine learning methods. The developed model includes nine different machine learning algorithms (NB, LR, DT, RF, GB, and SVM). The success of the classification algorithms used was evaluated using the metrics of accuracy, sensitivity, and precision calculated using the parameters of the confusion matrix. The results obtained show that the proposed model can detect cancer with a maximum accuracy of 91%. © Author(s) 2023
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
Optimized anfis model with hybrid metaheuristic algorithms for facial emotion recognition
Get PDFEmotion recognition from facial images is an important and active area of research. Facial features are widely used in computer vision for emotion interpretation, cognitive science, and social interaction. To obtain accurate analysis of facial expressions (happy, angry, sad, surprised, disgusted, fearful, and neutral), a complex method based on human-computer interaction and data is required. It is still difficult to develop an effective and computationally simple mechanism for feature selection and emotion classification. In this paper, an emotion recognition model using adaptive neuro-fuzzy inference system optimized with particle swarm optimization is proposed. The proposed model was compared with many classification algorithms (ANNs, SVMs, and k-Nearest Neighbor (k-NN) and their subcomponents). The confusion matrix was used to evaluate the performance of these classifiers. The proposed model was evaluated using the MUG database. The model achieved a prediction accuracy of 99.6%
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
Prediction of NOx emissions from gas turbines of a combined cycle power plant using an ANFIS model optimized by GA
No full textCombined cycle power plants, which combine gas and steam turbines, have negative impacts on surrounding
populations and structures. Control of NOx emissions is an important issue for these gas-fired power plants.
Accurate estimation of NOx emissions is critical for developing incinerators and reducing the environmental
impact of existing plants. The objective of this study is to model ANFISGA and estimate NOx emissions from a
natural gas-fired combined cycle power plant using emission monitoring system (PEMS) data. First, Adaptive
Neuro Fuzzy Inference System (ANFIS) models were developed using fuzzy C-Means (FCM). Then, the parameters
were optimized using a genetic algorithm (GA) to reduce the error. The proposed ANFISGA system was created,
trained, and tested with PEMS datasets. The developed models were compared using several statistical performance criteria, including correlation coefficient (R2
), mean squared error (MSE), error mean (EM), root mean
square error (RMSE), standard deviation of error (STD), and mean absolute percentage error (MAPE). The obtained results show that the coefficient of determination varies between 0.79933 and 0.90363 for the data
separated into test and training data with different rates. The minimum values of the criteria MSE, RMSE, EM,
STD, and MAPE were found to be 24.8379, 4.9838, 3.4625e-05, 4.9839, and 5.1660, respectively, for the training
data. The minimum values of these criteria for the test data were 26.5961, 5.1571, 0.065696, 5.157, and 5.3695,
respectively. The collected results show that the proposed ANFISGA models have high potential for NOx prediction. Thus, the results show that GA has a great im
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
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