• Atmosphere
• /
• v.31 no.5
• /
• pp.593-606
• /
• 2021

The Korea Meteorological Administration/National Institute of Meteorological Sciences (KMA/NIMS) has monitored atmospheric CO₂ at Anmyeondo (AMY) World Meteorological Organization (WMO) Global Atmosphere Watch Programme (GAW) regional station since 1999, and expanded its observations at Jeju Gosan Suwolbong station (JGS) in the South and at Ulleungdo-Dokdo stations in the East (ULD and DOK) since 2012. Due to a recent WMO CO₂ scale update and a new filter (NIMS) to select baseline levels at each station, the 22 years of CO₂ data are recalculated. After correction for the new CO₂ scale, we confirmed that those corrected records are reasonable within the compatibility goal (±0.1 ppm of CO₂) between KMA/NIMS and National Oceanic and Atmosphereic Administration (NOAA) flask-air measurements with the new scale. With the new NIMS filter, CO₂ baseline levels are now more representative of the large-scale background compared to previous values, which contained large CO₂ enhancements. Atmospheric CO₂ observed in South Korea is 4 to 8 ppm greater than the global average while the amplitude of seasonal variation is similar (10~13 ppm) to the amplitude averaged over a comparable latitude zone (30°N-60°N). Variations in CO₂ growth rate are also similar, increasing and decreasing similar to global values, as it reflects the net balance between terrestrial respiration and photosynthesis. In 2020, atmospheric CO₂ continued increasing despite the COVID-19 pandemic. Even though fossil emission was reduced (around -7% globally), we still emitted large amounts of anthropogenic CO₂. Overall, since CO₂ has large natural variations and its source was derived from not only fossil fuel but also biomass burning, the small fossil emission reduction could not affect the atmospheric level directly.

• Journal of Korean Academy of Nursing
• /
• v.37 no.3
• /
• pp.414-421
• /
• 2007

Background: Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups. Purpose: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. Method: An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching. Results: The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not. Conclusion: This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.

• Journal of Aerospace System Engineering
• /
• v.8 no.1
• /
• pp.36-41
• /
• 2014

KAFASAT is a CubeSat which has a high level mission of testing the possibility of establishing the LEO satellite constellation providing the role of communication nodes and quasi-realtime image recognition of battlefield in accordance with the aspect of future-war-environment. The high level mission is developed using the Pugh selection method, which is one of system engineering tools. In order to accomplish the high level mission objectives and deduce engineering level requirements, system engineering tools such as Analytic Hierarchy Process and Quality Function Deployment are used. The subsystem synthesis in the context of system engineering process is done using a developed integrated design environment. The paper also includes the conceptual design results of the KAFASAT, which can be used as a baseline for upcoming preliminary design.

• Journal of Korea Multimedia Society
• /
• v.5 no.5
• /
• pp.512-522
• /
• 2002

In this paper, we propose a hybrid method which is mixed with frame selection and weighting model rank method, based on GMM(gaussian mixture model), for real-time text-independent speaker recognition system. In the system, maximum likelihood estimation was used for GMM parameter optimization, and maximum likelihood was used for recognition basically Proposed hybrid method has two steps. First, likelihood score was calculated with speaker models and test data at frame level, and the difference is calculated between the biggest likelihood value and second. And then, the frame is selected if the difference is bigger than threshold. The second, instead of calculated likelihood, weighting value is used for calculating total score at each selected frame. Cepstrum coefficient and regressive coefficient were used as feature parameters, and the database for test and training consists of several data which are collected at different time, and data for experience are selected randomly In experiments, we applied each method to baseline system, and tested. In speaker recognition experiments, proposed hybrid method has an average of 4% higher recognition accuracy than frame selection method and 1% higher than W method, implying the effectiveness of it.

• Journal of Periodontal and Implant Science
• /
• v.23 no.1
• /
• pp.109-126
• /
• 1993

Refractory periodontitis manifest progressive attachment loss in a rapid and unrelenting manner regardless of the type or frequency of therapy applied. The purpose of this study was ta evaluate the relation between the level of cytokines in GCF and periodontopathic microflora with disease activity of refractory periodontitis. Selection of patients with refractory periodontitis (7 males, 3 females) were made by long term clinical observation including conventional clinical history and parameters. Teeth that showed pocket depth greater than 6mm were selected as sample teeth. Subjects were examined at baseline and after 3 months. Prior to baseline test, individual acrylic stent was fabricated. Reference grooves were made on each sample tooth site. Pocket depth and attachment loss were measured by Florida Probe. Gingival index was measured at 4 sites each sample teeth. Disease activity was defined as attachment loss of ${\ge}$ 2.1mm, as determined by sequential probing and tolerance method. The pattern and amount of alveolar bone resorption was observed with quantitative digital subtraction image processing radiography. Morphological analysis of subgingival bacteria was taken by phase contrast microscopy. Predominant cultivable bacterial distribution and frequency were compared between disease-active and disease-inactive site using immunofluorescence microscopy and selective microbial culturing. Levels of $interleukin-l{\beta}$, 2, 4, 6 and $TNF-{\alpha}$ in GCF and blood serum sample were quantified by ELISA. In active sites, P. intermedia was significantly increased to compare with inactive site. $IL-1{\beta}$, IL-2, IL-6 and $TNF-{\alpha}$ in GCF were increased in active sites and IL-2 in serum was increased in active patients significantly. Alveolar bone loss in active site was correlated with $IL-1{\beta}$, IL-2 in GCF. And loss of attachment in active site was correlated with IL-2 in GCF. These results demonstrate that IL-2 in serum, $IL-1{\beta}$, IL-2, IL-6 and $TNF-{\alpha}$ in GCF, P, intermedia might be used as possible predictors of disease activity in refractory periodontitis before it is clinically expressed as attachment loss and quantitative alveolar bone change.