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.

Nausea and Vomiting in Pregnancy

Abstract: Nausea and vomiting in pregnancy (NVP) is common medical condition during pregnancy and associated with hormonal change. Early recognition and active treatment is warranted because it can be associated with adverse healthy effect in both fetus and mother. First, the possibility of other gastrointestinal disorder should be considered and precipitating factor, renal and liver function should be evaluated. Primay recommended pharmacotherapy is the combination of oral pyridoxine hydrochloride and doxylamine succinate. Other options including dopamin (D2) receptor antagonist, antihistamine and serotonine 5 hydroxytryptamine 3-receptor (5-HT3) can be used. Fluid mixed with multivitamine including thiamine supplement should be considered in case of severe dehydration and hyperemesis gravidarum. Emotional support is also an important part in the management of NVP. The physician shoud apply individualized approach for the safest and most appripriate treatment. (Korean J Med 2012;82:525-531)

Processing Optimization and Antioxidant Activity of Chiffon Cake Prepared with Tomato Powder

Abstract: The purpose of this study was to determine the optimal mixing condition of tomato powder and sugar for producing chiffon cake. The experiment was designed according to the central composite design of response surface, which yielded ten experimental points, including two replicates. Physiochemical and sensory properties were measured, and theses values applied to mechanical models. A canonical form and perturbation plot showed the influence of each ingredient on the final product mixture. The results of the physiochemical analysis of each sample showed significant differences in sweetness (P

Stellar Interferometry for Gravitational Waves

Abstract: We propose a new method to detect gravitational waves, based on spatial coherence interferometry with stellar light, as opposed to the conventional temporal coherence interferometry with laser sources. The proposed method detects gravitational waves by using two coherent beams of light from a single distant star measured at separate space-based detectors with a long baseline. This method can be applied to either the amplitude or intensity interferometry. This experiment allows for the search of gravitational waves in the lower frequency range of $10^{-6}$ to $10^{-4}$ Hz. In this work, we present the detection sensitivity of the proposed stellar interferometer by taking the detector response and shot and acceleration noises into account. Furthermore, the proposed experimental setup is capable of searching for primordial black holes and studying the size of the target neutron star, which are also discussed in the paper.

News2Images: Automatically Summarizing News Articles into Image-Based Contents via Deep Learning

Abstract: Co mpact representation is a key issue for effective information delivery to users in mobile content-providing services. In particular, it is more severe when providing text documents such as news articles on the mobile service. Here we propose a method for generating compact image-based contents from news documents (News2Image). The proposed method consists of three modules for summarizing news into a few key sentences based on the sematic similarity and diversity, converting the sentences into images, and generating contents consisting of sentence-embedded images. We use word embedding for document summarization and convolutional neural networks (CNNs) for sentence-to-image transformation. These image-based contents improve the readability, thus effectively delivering the core contents of the news to users. We demonstrate the news-to-image content generation on more-than one million Korean news articles using the proposed News2Image. Experimental results show our method generates better image-contents semantically related to the given news articles compared to a baseline method. Furthermore, we discuss some directions for applying News2Images to a news recommendation system.

Operational Effectiveness Analysis of Field Artillery Ammunition Support Vehicle for K-55 Self-Propelled Artillery Using Simulation

Abstract: Korea army is operating K-10 FAASV (Field Artillery Ammunition Support Vehicle) for K-9 SP (Self-Propelled artillery) and examining employment of FAASV for K-55 SP. At present, the FAASV for K-55 SP has been developed as a prototype. To decide the employment of this FAASV for K-55 SP, previous research for operational effectiveness of this equipment is needed. Therefore in this paper, we presented the result of the operational effectiveness of the FAASV for K-55 SP using a wargame model, FEAM (Fire Execution Analytic Model) which is used to analyze formation, weapon system and operation in army artillery field. Based on the result of the FEAM simulation, we introduced the operational effectiveness of FAASV for K-55 SP, which is able to be applied to decide whether employ FAASV for K-55 SP or not.