1,720,956 research outputs found
Enhancing Robot Collaboration by Improving Human Motion Prediction Through Fine-Tuning
No full textIn Collaborative Robotics, 3D Human Motion Prediction (HMP) is of paramount importance to enable proactive robot assistance. It exploits past knowledge to provide insight into future body trajectories to integrate automation and humans. Unfortunately, data collection for robotics is often expensive and time-consuming, and only limited information is available. In this work, we propose a fine-tuning approach to improve the prediction accuracy for HMP in context-specific datasets. A state-of-the-art Deep Learning model, namely Position-Velocity Recurrent Encoder-Decoder (PVRED), is first pre-trained on the Human 3.6M dataset for HMP, and then tuned to suit specific motions. The experiments involved three smaller target datasets, considered in portions of increasing size, and two different levels of the PVRED architecture complexity. Compared to a scratch approach, the results showed that fine-tuning (i) reduced the number of training epochs, (ii) lowered the prediction error, and (iii) required a smaller dataset size. Moreover, the fine-tuned model showed even more advantages than increasing the PVRED complexity for scratch training. The proposed approach successfully transferred knowledge from the source domain to the fine-tuned model to predict human motion from a smaller target dataset. This demonstrates the significant potential of the proposed solution in practical applications with minimal training data for Collaborative Robotics
Enhancing Real-Time Body Pose Estimation in Occluded Environments Through Multimodal Musculoskeletal Modeling
Full text linkIn recent years, there has been a growing interest in Human-Robot Collaboration (HRC). One of the main challenges in developing effective tools for HRC is accurately estimating human pose in real-time, ensuring both human safety and efficient collaboration. To address this, we propose a novel approach enabling accurate and robust full-body pose estimation in real-time, even in the presence of occlusions. Our system combines information from RGB-D cameras and inertial measurement units, leveraging it to control a musculoskeletal model of the human through a multimodal inverse kinematics optimization. This approach ensures improvements in the anatomical realism and accuracy of the tracked movement while allowing flexibility in accommodating various sensor configurations. The consideration of the underlying anatomical structure also enhances the ability to estimate body poses in occluded environments. We conducted several HRC experiments where the operator's view was obstructed by various types of occlusions. The outcomes demonstrate how our methodology significantly improves pose estimation accuracy, even with a limited set of sensors and in the presence of occlusions in the scene. Our work aims to facilitate advanced HRC applications that require a precise understanding of human movement
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
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
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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