1,720,956 research outputs found
Knowledge Integration into deep learning in dynamical systems: an overview and taxonomy
No full textDespite the sudden rise of AI, it still leaves a question mark to many newcomers on its widespread adoption as it exhibits a lack of robustness and interpretability. For instance, the insufficient amount of training data usually hinders its performance due to the lack of generalization, and the black box nature of deep neural networks does not allow for a precise explanation behind its mechanism preventing a new scientific discovery. Such limitations have led to the development of several branches of deep learning one of which include physics-informed neural networks that will be covered in the rest of this paper. In this overview, we defined the general concept of informed deep learning followed by an extensive literature survey in the field of dynamical systems. We hope to make a contribution to our mechanical engineering community by conveying knowledge and insights on this emerging field of study through this survey paper.
Modulation of saliva pattern and accurate detection of ovulation using an electrolyte pre-deposition-based method: a pilot study
No full textWe developed an electrolyte pre-deposition-based saliva pattern modulation method to detect ovulation with high accuracy and reliability. Ovulation tests using human saliva have advantages in terms of the earlier ovulation detection and more convenient sample collection procedure; however, accuracy is low, which is a critical limitation given that the concentrations of salivary constituents can vary depending on the health status of the tested individual and subjective user judgement of the test result. In this study, we quantitatively analyzed saliva patterns according to the concentrations of electrolytes and proteins in the ovulation test and found that changes in the saliva pattern during the ovulatory period can be controlled by sodium chloride (NaCl) pre-deposition, which directly affects the accuracy of ovulation detection. The 100 nmol NaCl pre-deposition condition proved optimal, being two-fold more sensitive to changes in saliva pattern versus the non-pre-deposition condition (accuracy of ovulation detection = 66.6% and 33.3%, respectively). Although accuracy remained insufficient for actual applications compared to the urine-based ovulation detection method, we expect that the electrolyte pre-deposition method will greatly contribute to enhancing the performance of saliva-based ovulation detection tests, toward a commercially satisfactory level of accuracy.11Nsciescopu
Single domain generalizable and physically interpretable bearing fault diagnosis for unseen working conditions
No full textState-of-the-art deep learning methods have demonstrated impressive performance in the intelligent fault diagnosis of rolling element bearings. However, in previous studies, critical issues such as domain discrepancy and the inability to interpret a classification decision made it difficult to apply deep learning in real industrial scenarios. Although domain adaptation and domain generalization-based methods have been investigated to solve domain discrepancy, collecting labeled data for various domains (especially continuous and non-stationary working conditions) is extremely difficult in an engineering application. Furthermore, since the classification decision cannot be physically explained, serious reliability problems arise for unseen working conditions (i.e., target domain with domain discrepancy). This study proposes the single domain generalizable and physically interpretable (SDGPI) framework. The proposed model embeds prior knowledge into the neural network combined with signal-preprocessing, which simultaneously enables single source domain generalization and domain interpretation with physical guarantees. Comprehensive case studies demonstrate that domain generalizable representation leads to 1) superior performance and robustness compared with existing methods for various untrained working conditions, as well as 2) efficient data inference even with small data size. Finally, the diagnosis results could be physically understood by displaying the classification decision in terms of the theoretical characteristic fault frequency (i.e., the characteristic fault order), indicating that SDGPI is a versatile and reliable diagnostic tool for unseen working conditions.
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
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