1,721,009 research outputs found
Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals
Full text linkVibration measurement and monitoring are essential in a wide variety of applications. Vibration measurements are critical for diagnosing industrial machinery malfunctions because they provide information about the condition of the rotating equipment. Vibration analysis is considered the most effective method for predictive maintenance because it is used to troubleshoot instantaneous faults as well as periodic maintenance. Numerous studies conducted in this vein have been published in a variety of outlets. This review documents data-driven and recently published deep learning techniques for vibration-based condition monitoring. Numerous studies were obtained from two reputable indexing databases, Web of Science and Scopus. Following a thorough review, 59 studies were selected for synthesis. The selected studies are then systematically discussed to provide researchers with an in-depth view of deep learning-based fault diagnosis methods based on vibration signals. Additionally, a few remarks regarding future research directions are made, including graph-based neural networks, physics-informed ML, and a transformer convolutional network-based fault diagnosis method
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Personal recommender system via convolutional autoencoder with conditioning augmentation : Recommender system and representation learning with convolutional autoencoder
Full text linkDepartment of Industrial EngineeringRecently, volume of various types of information, including reviews, images, and videos containing sound, also known as unstructured data, have been increased in an explosive manner . Even though, unstructured data is difficult to utilize without proper preprocessing, many applications adopted it as a source of information to extract value from it, such as recommender systems, natural language processing and computer visions . The recent prosperity of deep learning techniques has accelerated the progress in this field by making the preprocessing parts and feature extraction parts simple and easy . Moreover, the emergence of generative adversarial network has led to improved general performance of unsupervised learning models which makes many applications to make use of diverse forms of data
Along with this context, concerns of this article focused on (i) developing a recommender system based on modified autoencoder which is a typical deep learning technique applied to this research field that presents exceptional performance in the feature extraction process and (ii) applying data augmentation to this field which is frequently used to deal with data scarcity or limitation problem which is one of the main challenges of recommender systems [3].(iii) Lastly, the proposed model can be applied to both tasks, collaborative filtering and contents-based filtering proved to present compliant performance Modified convolutional autoencoder-based recommender system learns features of samples that represented by reviews of users or user-item rating matrices. The proposed model takes vanilla autoencoder as a base structure conbined with convolutional layer to extract feature that takes encoded vector as input which is represented by preprocessed reviews or ratings. Afterward, the conditioning augmentation process, which is an augmentation technique for embedded vectors, is applied that goes through a decoder that produces final predictions based on the encoded input vector from the previous encoder The contribution of the paper can be summarized as three points. (i)Conditioning augmentation which is data augmentation technique utilizing encoded vector to deal with
data scarcity problem that is mainly concerned in recommender system field. (ii)Proposed model can take both types of inputs which are contents-based encoded vector or ratingbased encoded vector. Contents-based vector can represent features of item such as review, quality, and various types of categorical feature to corresponding product. Rating-based vector indicates evaluation of consumer based on numeric value. (iii)Lastly, performance of proposed model is compliant compared to state of the arts of several bench mark open dataset.ope
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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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No full textDepartment of Industrial Engineeringope
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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