1,721,302 research outputs found
Uncertainty Quantification in State-Specific Modeling of Thermal Relaxation and Dissociation of Oxygen
Leveraging Tactile Sensors for Low Latency Embedded Smart Hands for Prosthetic and Robotic Applications
Tactile sensing is a crucial perception mode for robots and human amputees in need of controlling a prosthetic device. Today, robotic and prosthetic systems are still missing the important feature of accurate tactile sensing. This lack is mainly due to the fact that the existing tactile technologies have limited spatial and temporal resolution and are either expensive or not scalable. In this article, we present the design and implementation of a hardware-software embedded system called SmartHand. It is specifically designed to enable the acquisition and real-time processing of high-resolution tactile information from a hand-shaped multisensor array for prosthetic and robotic applications. During data collection, our system can deliver a high throughput of 100 frames per second, which is 13.7x higher than previous related work. This has allowed the collection of a new tactile dataset consisting of 340000 frames while interacting with 16 objects from everyday life during five different sessions. Together with the empty hand, the dataset presents a total of 17 classes. We propose a compact yet accurate convolutional neural network that requires one order of magnitude less memory and 15.6x fewer computations compared with related work without degrading classification accuracy. The top-1 and top-3 cross-validation accuracies on the collected dataset are, respectively, 98.86% and 99.83%. We further analyze the intercession variability and obtain the best top-3 leave-one-out-validation accuracy of 77.84%. We deploy the trained model on a high-performance ARM Cortex-M7 microcontroller achieving an inference time of only 100 ms minimizing the response latency. The overall measured power consumption is 505 mW. Finally, we fabricate a new control sensor and perform additional experiments to provide analyses on sensor degradation and slip detection. This work is a step forward in giving robotic and prosthetic devices a sense of touch by demonstrating the practicality of a smart embedded system that uses a scalable tactile sensor with embedded tiny machine learning
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
Metabolic Score for Insulin Resistance Is Correlated to Adipokine Disorder and Inflammatory Activity in Female Knee Osteoarthritis Patients in a Chinese Population [Corrigendum]
Ding L, Gao YH, Li YR, Huang YF, Wang XY, Qi X. Diabetes Metab Syndr Obes. 2020;13:2109–2118.
The authors have advised that the Funding statement was missed on page 2116 of the published paper. The funding statement should read as follows:
FundingThis study was supported by the Jilin Provincial Natural Science Foundation (Project Title: “Effects and Mechanisms of Leptin/ObR on the Pathological Progression of Knee Osteoarthritis via the AMPK Signaling Pathway”, Grant No. 20200201548JC)
Variations on the Author
“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
We 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
We 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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