• Journal of Life Science
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• v.18 no.12
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• pp.1631-1636
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• 2008

Rhei Rhizoma (RR; 大黃) consists of the underground parts (rhizome and root) of Rheum officinale Baill. and Rheum palmatum L. (Polygonaceae), and is widely used in Southeast Asian folk medicine to alleviate liver and kidney damages. In this study, we investigated into the efficacy and mechanism of RR water extract in supporting neuronal survival in a hypoxia model of cultured rat hippocampal neurons. RR exhibited no cytotoxicity up to 10 ${\mu}g$/ml and exhibited neurosupportive effects at 2.5 ${\mu}g$/ml in normoxia. When RR was added to the culture media on 10 days in vitro (DIV10) and given a hypoxic shock (2% $O_2$/5% $CO_2$, 3 hr, $37^{\circ}C$) on DIV13, RR exhibited neuroprotective effects on 5 days post-shock. $H_2DCF$ stainings indicated that RR effectively prevents ROS production in both normoxia and hypoxia. JC-1 stainings showed that RR prevents dissipation of MMP in hypoxia. These results indicate that RR protects neurons by suppressing ROS production and MMP loss.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Journal of the Korean Applied Science and Technology
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• v.37 no.1
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• pp.102-113
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• 2020

In this study, anti-arthritic effect of the mixed extract of radiation mutant Perilla frutescens var. crispa and Atractylodes macrophala koidz was investigated. Cell viability was determined by MTT assay in RAW 264.7 cells. The anti-inflammatory effect of mixed extracts was determined through measurement of the levels of reactive oxygen species (ROS) and nitric oxide (NO), release of inflammatory cytokines and expression of NF-κB, COX-2 and iNOS in LPS-induced RAW 264.7 cells after treatment of mixed extracts (5, 10, 25 ㎍/㎖). We showed that the mixed extracts was not toxic in the dose of 5, 10, 25 ug/ml, and significantly inhibited production of nitric oxide and ROS, cytokines including IL-1β, IL-6, TNF-α, and inflammatory proteins including NF-κB, COX-2 and iNOS in LPS-induced RAW 264.7 cells. Moreover, the mixed extract inhibited the type II collagen induced arthritis in DBA mice in the dose of 66.5 and 133mg/kg/day. Therefore, we suggest that mixed extract of radiation mutant Perilla frutescens var. crispa and Atractylodes macrophala koidz can be developed as a raw material for health functional food and therapeutics to treat the inflammatory arthritis.

• Microbiology and Biotechnology Letters
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• v.44 no.2
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• pp.201-207
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• 2016

The aim of this study was to investigate the potential of lactic acid bacteria (LAB) strains as probiotics. Two strains were isolated from healthy chicken cecum and their acid and bile tolerance, residual organic acids, antibacterial activity against pathogenic bacteria, and immunomodulation activity were measured. Identification of the isolated strains was performed using the API 50CHL system and phylogenetic analysis using 16S rDNA sequencing. The isolates were determined to be Lactobacillus sakei strains. The acid tolerance of strains L2 and L8 was high enough that 75% of the inoculum survived in pH 2 for 2 h. The bile tolerance of both strains was observed at a 1% Oxgall concentration in MRS broth. The production of organic acids (lactic acid and acetic acid) and pH changes during growth were monitored and the maximum concentrations were obtained after 48 h of incubation. Culture supernatants of the two LAB strains showed strong antibacterial activity against pathogenic bacteria. The heat-killed LAB cells also induced high levels of immune cell proliferation compared with the control, and stimulated IL-6 and TNF-α production in mouse macrophages. Therefore, L. sakei strains L2 and L8 can be considered suitable probiotic bacteria.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.74-87
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• 2003

A model of STS (Science-Technology-Society) creativity education program for the gifted and talented children has been developed, based on GENEPLORE thinking process and Knowledge development theory. The GENEPLORE creative thinking process, developed by Finke et al. (1990, 1992), has two phases such as generative phase and exploratory phase. And The knowledge development theories of Piaget (1977) and Gallagher(1981) assume that knowledge-bases are developed on the basis of empirical as well as reflective abstraction, which could imply that knowledge-bases are crucial in creative thinking process. The creativity education model for the gifted and talented of the present study attempted to integrate 'the individual, creative thinking process, and social/scientific technology' by employing topics of the science-technology-society such as computer, network, biotech, robot, e-business, e-education, e-health, nanotech and entertainment and the structure and contents of the program are proposed

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.423-429
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• 2006

The systems in the ubiquitous computing environment need to provide users with context-aware services, intelligently interacting with the surrounding environment. Therefore, the systems in the ubiquitous computing environment require context-awareness ability in order to gather and analyze context information in various situations and environments. However, existing context-aware systems lack the ability to systematically generate and handle various types of context information, and only a few systems have ability learning from environment. In this paper, a general context model is defined to describe various contexts and a context-awareness framework is implemented based in the model, which makes it straightforward to handle and generate various types of context from diverse sensor. The framework is designed to allow a system to sensed, combined, inferred, and learned context information, in order to provide users with services in dynamic environments. We have implemented the proposed framework and applied it to a u-Health management system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.271-277
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• 2017

As a result of rapid industrialization, air pollutants are seriously threatening the health of the people, the forecast is becoming more and more important. In forecasting air quality, it is very important to create a reliable initial field because the initial field input to the air quality forecasting model affects the accuracy of the forecast. There are several methods for enhancing the initial field input. One of the necessary techniques is data assimilation. The number of operations and the time required for such data assimilation is exponentially increased as the forecasting area is widened and the number of observation sites increases. Therefore, as the forecast size increases, it is difficult to apply the existing sequential processing method to a field requiring fast processing speed. In this paper, we propose a method that can process Cresman's method, which is one of the data assimilation techniques, in real time using CUDA. As a result, the proposed parallel processing method using CUDA improved at least 35 times faster than the conventional sequential method and other parallel processing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.149-152
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• 2017

Big data analysis is an effective analysis techniques of unstructured data such as internet, social network services, web documents generated in mobile environment, e-mail, and social data, as well as formal data well organized in the database. Thus, meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result of integrating and analyzing many quantitative research results. Today, regardless of gender and age is increasing interest in whether you can lead a younger and healthier life. With this change of life which has been developed with a variety of functional health food. Aronia melanocarpa called black chokeberry is a fruit of berry plants belonging to the Rosaceae originally growing in the North America region. In the studies for factors related to quality characteristics and antioxidant activities as the extracts of Aronia in this study, which it is only targeted factors as total sugar, acidity, polyphenol, anthocyanin, antioxidant. Thus, we present the theoretical and practical implications of these results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.187-198
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• 2018

Recently, financial transactions and electronic commerce in cyberspace are being performed more quickly and conveniently, with the development in diverse types of fintech and biometric authentication. But user authentication using passwords still occupies a big proportion even in these new services. therefore, safe creation and management of passwords is fundamental and indispensable to protect personal information and asset. This study examined the patterns of password usage by conducting a survey and analyzed factors influencing password security behavior intentions using the heath belief model. As a result, perceived susceptibility, perceived severity, perceived benefits, and perceived barriers significantly affected security behavior intentions, and especially, perceived severity had a moderating effect in other factors.