Naver Corporation

About: Naver Corporation is a company organization based out in Seongnam-si, South Korea. It is known for research contribution in the topics: Terminal (electronics) & Computer science. The organization has 4038 authors who have published 4294 publications receiving 35045 citations. The organization is also known as: NAVER Corporation & NAVER.

Method, system and computer readable recording medium for determining major group under split-brain syndrome

Abstract: The present invention relates to a method, system and computer readable recording medium for determining a major group in a network split-brain situation that occurs in a network-based distributed computing environment. According to an aspect of the present invention, there is provided a method of determining a major group among at least two groups created by splitting an initial group consisting of a plurality of nodes in a network-based distributed environment, the method comprising the steps of comparing the number of nodes included in a first group with the number of nodes included in a second group; acquiring history information of the nodes included in the first and second groups; and determining whether the first group or the second group is the major group using at least one of a result of comparing the number of nodes and the history information.

The Effect of the Forced Pulmonary Function of young female, by Changes in Lung function Related to Postures and by Transverse Abdominis Activation in Standing Position

Abstract: Purpose : The purpose of this study was to investigate characteristics of the forced pulmonary function test effect by changes in lung function related to postures and by Transverse Abdominis(TrA). Contraction in standing position during forced inspiration and expiration with young female adults. Methods : 10 young female adults were recruited this study. pulmonary Function test was measured with a Master-screen Body (VIASYS Inc., CA, 미국). To check the changes in lung function with different postures, we tested pulmonary function in the standing and supine position each. In the standing position, while the transversus abdominis was activating, we compared the forced inspiration with the forced expiration. Statistical analysis was used Independent t-test to know difference between forced inspiration and expiration of activated TrA. Results : According to the study, the change of pulmonary function were statistically significant difference in the standing compared to the supine position. The contraction of the transversus abdominis causes decrease in the change of forced inspiration and increase in the change of forced expiration. Conclusion : These results indicate that spontaneous contraction of the TrA in standing position helps pulmonary function. And the selective contraction of the transversus abdominis at the end of forced inspiration makes increases in the forced expiration.

Proprioceptive Actuator Design in the MIT Cheetah: Impact Mitigation and High-Bandwidth Physical Interaction for Dynamic Legged Robots

Abstract: Designing an actuator system for highly dynamic legged robots has been one of the grand challenges in robotics research. Conventional actuators for manufacturing applications have difficulty satisfying design requirements for high-speed locomotion, such as the need for high torque density and the ability to manage dynamic physical interactions. To address this challenge, this paper suggests a proprioceptive actuation paradigm that enables highly dynamic performance in legged machines. Proprioceptive actuation uses collocated force control at the joints to effectively control contact interactions at the feet under dynamic conditions. Modal analysis of a reduced leg model and dimensional analysis of DC motors address the main principles for implementation of this paradigm. In the realm of legged machines, this paradigm provides a unique combination of high torque density, high-bandwidth force control, and the ability to mitigate impacts through backdrivability. We introduce a new metric named the “impact mitigation factor” (IMF) to quantify backdrivability at impact, which enables design comparison across a wide class of robots. The MIT Cheetah leg is presented, and is shown to have an IMF that is comparable to other quadrupeds with series springs to handle impact. The design enables the Cheetah to control contact forces during dynamic bounding, with contact times down to 85 ms and peak forces over 450 N. The unique capabilities of the MIT Cheetah, achieving impact-robust force-controlled operation in high-speed three-dimensional running and jumping, suggest wider implementation of this holistic actuation approach.

Quality Characteristics of Black Ginseng Jelly

Abstract: The principal objective of this study was to evaluate the quality characteristics of black ginseng jelly prepared with different 5 levels(0, 0.5, 1.0, 1.5, and 2.0%) of black ginseng extract. We assessed the ginsenosides level of white and black ginseng for comparison between white and black ginseng. And we conducted the pH, sugar content, Hunter's color values, the mechanical characteristics and sensory evaluation of black ginseng jelly samples. The levels of ginsenoside Rg 3 , Rh 1 , and Rh 2 of black ginseng were higher than those of white ginseng. The more black ginseng extract was increased, the sugar contents of black ginseng jelly were significantly increased(p<0.05). We noted that the luminance and Hunter's b values of jelly samples were decreased according to black ginseng extract was increased, but in Hunter's a values 0.5% black ginseng jelly was the highest of the all. With regard to the mechanical properties of the black ginseng jelly samples, the score of hardness, gumminess and chewiness were significantly increased. In color, taste and overall quality, the score of jelly with 1.0% black ginseng extract was significantly increased than those of the all. Key words: black ginseng extract, jelly, mechanical characteristics, sensory evaluation.Corresponding author: Ae-Jung Kim, Dept. of Food & Nutrition, Hyejeon College, Hongseong 350-702, Korea, Tel: +82-41- 630-5249, Fax: +82-41-630-5175, E-mail: aj5249@naver.com

Representation Learning of Music Using Artist Labels

Abstract: In music domain, feature learning has been conducted mainly in two ways: unsupervised learning based on sparse representations or supervised learning by semantic labels such as music genre. However, finding discriminative features in an unsupervised way is challenging and supervised feature learning using semantic labels may involve noisy or expensive annotation. In this paper, we present a supervised feature learning approach using artist labels annotated in every single track as objective meta data. We propose two deep convolutional neural networks (DCNN) to learn the deep artist features. One is a plain DCNN trained with the whole artist labels simultaneously, and the other is a Siamese DCNN trained with a subset of the artist labels based on the artist identity. We apply the trained models to music classification and retrieval tasks in transfer learning settings. The results show that our approach is comparable to previous state-of-the-art methods, indicating that the proposed approach captures general music audio features as much as the models learned with semantic labels. Also, we discuss the advantages and disadvantages of the two models.