1,720,954 research outputs found
Pixelating to the Edge - Generative AI Art on Edge Devices
No full textGenerative AI is now changing the landscape of how people are getting things done. In this study we are focusing on one of the most popular application of generative AI which is text to image generation, a technology which created huge craze in 2021. Even after 3 years, it is not as effective and speedy on the edge devices like mobile as its own web version. In this research, we will compare a number of model variations and analysis what factors affect the inference speed of the image generation. Currently Mobile diffusion, although commercially not available, has claimed that it can achieve 0.02 seconds of speed. I tried to study if any architectural changes and sampling techniques can improve the inference speed while maintaining quality of image. The changes in the sampling operations like changing the scheduler from PNDMS to DDIM gave a 6.57 percent increase in inference speed with a bit of degradation in FID and CLIP score. The architectural changes gave significant improvement of up to 15.24 percent increase and good results with FID and CLIP score. This research will explore the much needed generative AI technology’s requirement on edge devices
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
Pixelating to the Edge: Generative AI Art on Edge Devices
Get PDFGenerative AI is transforming the way people accomplish tasks, reshaping numerous industries and workflows. In this study, we focus on one of the most popular applications of generative AI: text-to-image generation, a technology that gained significant attention in 2021. Despite its popularity, even after three years, text-to-image generation remains less efficient and slower on edge devices like mobile phones compared to its web-based counterparts. This research investigates various model variations and analyzes the factors influencing inference speed in image generation. While Mobile Diffusion, though not yet commercially available, claims to achieve an impressive inference speed of 0.02 seconds, we explore whether architectural modifications and sampling techniques can further enhance performance without compromising image quality. Our findings indicate that adjustments to sampling operations, such as switching the scheduler from PNDMS to DDIM, resulted in a 6.57% increase in inference speed, albeit with a slight degradation in FID and CLIP scores. In contrast, architectural changes yielded significant improvements, achieving up to a 15.24% increase in speed while maintaining favorable results in FID and CLIP scores
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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