• Journal of Digital Convergence
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• v.14 no.6
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• pp.325-333
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• 2016

This study was conducted to provide the base line for the use of prophylactic antibiotics and the standard of antibiotic use and the evaluation based on analysis of current use, quality assessment and periodic changes of prophylactic antibiotics in a university hospital. We chose the year 2008, 2009, 2010, 2012, and 2014 as the study periods since the primary evaluation on the first year of implementation in 2007. For this study, healthcare benefit quality assessment data from the Health Insurance Review and Assessment Service was used. We analyzed the differences each year of treatment period; one category for initial treatment timing, three categories for selecting antibiotics, and two categories for the length of treatment from multiple evaluation indices of gastric surgeries, colorectal surgeries, and cholecystectomy. The analysis revealed the followings: Regarding length of antibiotics treatment, total days of treatment decreased down to 1.5, 1.5, and 0.6 days in the year 2014, from 13.5, 12.8, and 6.9 days in the year 2007, for gastric surgeries, colorectal surgeries, and cholecystectomy. Based on these outcomes, the efforts to devise efficient delivery and distribution of the recommendations or indices which medical staff could adhere for quality improvement of the prophylactic antibiotics would be necessary. Also implementing monitoring system to help the hospitals to acknowledge their own faults may be helpful.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.63-69
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• 2018

This study is to examine the determinants of the elderly poverty by using the Decision-tree analysis. In line with this perspective, this study includes individual characteristics, family characteristics, working characteristics, and periodic income characteristics after retirement as determinants for senior poverty. The study uses data from the Korean Retirement and Income Study based on panel survey and employs the Decision-tree analysis to explain the causes of the elderly poverty. As the result of analysis, earned wage has the greatest effect on the elderly poverty. Depending on status of the earned wage, there are 2 different variable groups. One with no earned wage includes public pension, education, and residence, paid employee and gender in the other with earned wage. Based on the analytical results, the study suggests measures to address the elderly poverty.

• Journal of The Korean Astronomical Society
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• v.36 no.3
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• pp.81-87
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• 2003

It is suggested that a flying-by star in a hot accretion disk may cool the hot accretion disk by the Comptonization of the stellar emission. Such a stellar cooling can be observed in the radio frequency regime since synchrotron luminosity depends strongly on the electron temperature of the accretion flow. If a bright star orbiting around the supermassive black hole cools the hot disk, one should expect a quasi-periodic modulation in radio, or even possible an anti-correlation of luminosities in radio and X-rays. Recently, the unprecedentedly accurate infrared imaging of the Sagittarius A$\ast$ for about ten years enables us to resolve stars around it and thus determine orbital parameters of the currently closest star S2. We explore the possibility of using such kind of observation to distinguish two quite different physical models for the central engine of the Sagittarius A$\ast$, that is, a hot accretion disk model and a jet model. We have attempted to estimate the observables using the observed parameters of the star S2. The relative difference in the electron temperature is a few parts of a thousand at the epoch when the star S2 is near at the pericenter. The relative radio luminosity difference with and without the stellar cooling is also small of order $10^{-4}$, particularly even when the star S2 is near at the pericenter. On the basis of our findings we tentatively conclude that even the currently closest pass of the star S2 is insufficiently close enough to meaningfully constrain the nature of the Sagittarius A$\ast$ and distinguish two competing models. This implies that even though Bower et al. (2002)have found no periodic radio flux variations in their data set from 1981 to 1998, which is naturally expected from the presence of a hot disk, a hot disk model cannot be conclusively ruled out. This is simply because the energy bands they have studied are too high to observe the effect of the star S2 even if it indeed interacts with the hot disk. In other words, even if there is a hot accretion disk the star like S2 has imprints in the frequency range at v $\le$ 100 MHz.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.96-107
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• 2015

Brownfield sites are beginning to be considered as potentially useful areas for landscape design and planning, with post-industrial areas such as water treatment facilities and military training bases being converted into useful landscapes such as parks and recreation areas. These redevelopments bring broad benefits through revitalizing communities and increasing property values, thus, increasing the demand for comprehensive management and planning policies. This study examines changes in U.S. brownfield policies and programs and, identifies their periodic characteristics over the thirty years since the Superfund program was introduced in 1980. A descriptive and interpretive approach was utilized, focusing specifically on a time sequential analysis of the data gathered from the overview of the Environmental Protection Agency's web-based documents and related literature. The primary changes in and characteristics of programs and policies were analyzed and divided into three periods : environmental protection, remediation and reuse, and comprehensive planning. Four major features were identified: relaxation and readjustment of regulation, diversification of support programs, a mix of top-down and bottom-up approaches, and database system building. The study examines how common brownfield problems such as site identification difficulties and assessment and remediation cost have been dealt with in the regulatory context and has implications for future policies and programs for effective brownfield planning and management in Korea.

• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.575-587
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• 2019

This study evaluated the effect of a mother wavelet in the wavelet analysis of various times series made by combining white noise and/or sine function. The result derived is also applied to short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). This study, different from previous studies evaluating one or two mother wavelets, considers a total of four generally-used mother wavelets, Bump, Morlet, Paul, and Mexican Hat. Summarizing the results is as follows. First, the Bump mother wavelet is found to have some limitations to represent the unstationary behavior of the periodic components. Its application results are more or less the same as the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the non-stationary behavior of the periodic components. Finally, the Mexican Hat mother wavelet is found to be too complicated to interpret. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelet is most frequently used in the wavelet analysis research.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.901-912
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• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.6
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• pp.545-550
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• 2012

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

• Journal of KIISE
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• v.42 no.1
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• pp.97-106
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• 2015

Recently, research on database encryption for data protection and query result authentication methods has been performed more actively in the database outsourcing environment. Existing database encryption schemes are vulnerable to order matching and counting attack of intruders who have background knowledge of the original database domain. Existing query result integrity auditing methods suffer from the transmission overhead of verification object. To resolve these problems, we propose a group-order preserving encryption index and a query result authentication method based on the encryption index. Our group-order preserving encryption index groups the original data for data encryption and support query processing without data decryption. We generate group ids by using the Hilbert-curve so that we can protect the group information while processing a query. Finally, our periodic function based data grouping and query result authentication scheme can reduce the data size of the query result verification. Through performance evaluation, we show that our method achieves better performance than an existing bucket-based verification scheme, it is 1.6 times faster in terms of query processing time and produces verification data that is 20 times smaller.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.409-417
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• 2009

In this study it was assessed the accuracy of the Chukwooki rainfall data in Seoul by comparing with tree-ring width index data, sunspot numbers, southern oscillation index (SOI) and global temperature anomaly. And it was investigated the correlations of climatic change and change characteristics in past north-east asia by comparisons of tree-ring width index data in near Korea. The results of this study shows that Chukwooki rainfall data has the strong reliance since the trends and depths of change are very well matched with other comparative data. And with the results by compared with tree-ring width index data in six sites of near Korea, climates of north-east asia are changed with strong correlations as being temporal and spatial and longterm periodic possibility of reproducing are exist on those changes. However characteristics of climate change post 1960 A.D. are investigated as represented differently to past although statistical moving characteristics or changing criterion are within the limitations of reproducing phase in the past since they represent the different trends and irregularity and their frequencies are increase. The results of this study are widely used on long-term forecasting for climate change in north-east asia.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.4
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• pp.133-142
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• 2023

In this paper, we built a data-driven artificial intelligence model using RNN-LSTM (Recurrent Neural Networks-Long Short-Term Memory) to predict the Lorenz system, and examined the possibility of whether this model can replace chaotic dynamic models. We confirmed that the data-driven model reflects the chaotic nature of the Lorenz system, where a small error in the initial conditions produces fundamentally different results, and the system moves around two stable poles, repeating the transition process, the characteristic of "deterministic non-periodic flow", and simulates the bifurcation phenomenon. We also demonstrated the advantage of adjusting integration time intervals to reduce computational resources in data-driven models. Thus, we anticipate expanding the applicability of data-driven artificial intelligence models through future research on refining data-driven models and data assimilation techniques for data-driven models.