• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.551-557
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• 2024

Hydrogen is a renewable energy source with various characteristics such as clean, carbon-free and high-energy, and is internationally recognized as a "future energy". With the rapid development of the hydrogen energy industry, more hydrogen infrastructure is needed to meet the demand for hydrogen. However, hydrogen infrastructure accidents have been occurring frequently, hindering the development of the hydrogen industry. HyRAM+, developed by Sandia National Laboratories, is a software toolkit that integrates data and methods related to hydrogen safety assessments for various storage applications, including hydrogen refueling stations. HyRAM+'s physics mode simulates hydrogen leak results depending on the hydrogen refueling station components, graphing gas plume dispersion, jet frame temperature and trajectory, and radiative heat flux. In this paper, hydrogen leakage data was extracted from a hydrogen refueling station in Samcheok, Gangwon-do, using HyRAM+ software. A hydrogen leakage simulator was developed using data extracted from HyRAM+. It was implemented as a dashboard that shows the data generated by the simulator using a database and Grafana.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1417-1421
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• 2009

최근 들어 유역의 정확한 수문현상을 파악하기 위하여 유역의 유출량 자료를 직접 유출과 기저유출로 분리한 후 수문 모형의 직접유출 및 기저유출의 수문컴포넌트 검증에 활용하는 연구가 많이 이루어지고 있다. 미국 국립지리국 (USGS) 에서 개발한 HYSEP 모형이 지난 수 년 동안 유출 컴포넌트 분리에 널리 이용되어 오고 있다. 그러나 USGS 기반의 HYSEP의 경우 능숙한 컴퓨터 사용자가 아닌 비전문가들이 HYSEP을 운영하기에는 여러 가지 많은 제한점이 있어 왔다. 그리하여 본 연구에서는 고해상도 위성영상 Google Map 기반의 기저유출분리 프로그램인 Web-based HYSEP 인터페이스를 개발하였다. 이 시스템에는 HYSEP에서 제공하는 3가지 방법인 Fixed Interval / Sliding Interval / Local Minimum 방법이 제공되고 있다. 본 연구에서 개발된 Google Map 기반의 HYSEP 시스템은 USGS 유량 관측지점들에 대해 XML 데이터 포맷으로 DB를 구축하여 Google Map 과 연계하였으며 이를 통해 사용자가 원하는 관측소의 실시간 유량자료를 다운로드 할 수 있도록 개발되어졌다. Google Map 기반의 HYSEP 기저유출 분리 시스템(http://www.EnvSys.co.kr/${\sim}$hysep)은 Perl/CGI 및 자바스크립트, Google Map script 등을 이용하여 개발되었다. 현재 개발된 Google Map 기반의 USGS HYSEP 시스템은 한 곳의 유량관측지점에 대해서 총 3가지 기저유출 모듈을 적용하여 결과를 제공하고 있으며, 그 결과를 테이블이나 그래프 형태로 제공하도록 되어 있다. 본 연구에서는 Google Map 기반의 USGS HYSEP 시스템을 이용하여 미국 인디애나 주의 Little Eagle Creek 유역의 유량자료와 Fixed Interval / Sliding Interval / Local Minimum 방법을 이용하여 기저유출을 분리하였으며, 기존에 널리 활용되는 기저유출 분리 프로그램인 Web 기반의 WHAT 시스템 (http://www.EnvSys.co.k.r/~what) 산정 기저유출량과 비교분석하였다. 분석결과 HYSEP 예측 기저유출치가 전반적으로 WHAT 예측치보다 크게 산정되었다. WHAT 시스템과 본 연구에서 개발한 Web 기반의 HYSEP 일단위 기저유출량을 비교해 본 결과 $R^{2}$가 0.56, EI는 0.52로 어느 정도 비슷한 경향을 나타냈으나, 유역의 특성을 반영하는 WHAT 시스템과는 달리 주어진 유량자료만을 이용하여 기저유출을 분리하는 Web 기반의 HYSEP 기저유출 분리모듈을 개선할 필요가 있는 것으로 판단된다.

• Journal of IKEEE
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• v.27 no.1
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• pp.116-121
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• 2023

In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (10⁸ or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 10⁸. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1147-1155
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• 2013

In this study, we designed and implemented a step detection analyzer that can compare and analyze the step detection rates and results among the step detection algorithms. The step detection analyzer converts 3-axes accelerometer data into continuous energy stream through SVM operation, shows the horizontal comparison among the step detection results for each step detection algorithms, and can make elemental detection analyses. For these processes, the step detection analyzer presents the continuous energy stream as energy waveform, checks the peak values and time location of the detected steps with step detection algorithms, and gives visual interface to get some possible causes in cases of step detection miss. It can also give the threshold graph for each algorithm to check the threshold value on missed cases directly and can help to get more appropriate threshold values or other adjustable parameters in step detection algorithm. This step detection analyzer can be applied efficiently on performance enhancement of step detection algorithm, on deciding an appropriate algorithm for a specific step counter system in the various step counter filed operations.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.146.2-146.2
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• 2012

2008년부터 2012년에 걸친 관측기간 동안 총 21일간 관측하여 AA UMa의 BVRI 광도 곡선을 획득하였다. AA UMa의 I 필터 광도 곡선은 이번에 처음으로 얻어진 것이다. 또한 극심시각을 추가적으로 획득하기 위하여 2005 ~ 2008년까지 총 8일간 AA UMa의 극심 부근의 측광관측을 수행하였고, SuperWASP에서 공개하는 AA UMa의 측광 자료를 수집하여 총 31개의 새로운 극심시각을 결정하였다. 우리의 새로운 극심시각을 포함하여 83년 동안의 AA UMa 극심시각을 수집하여 총 250개의 극심시각으로 주기 변화연구를 수행하였다. 그 결과 AA UMa 계는 $3.30{\times}10^{-11}d/yr$의 영년 주기 증가 위에 58.7년의 주기적인 변화가 겹쳐 발생한다. 주기적인 변화의 원인이 제3천체에 의해 발생한다고 가정했을 때 제3천체의 최소 질량은 $0.28M_{\odot}$이다. 이전 연구자의 광도곡선(Meinunger(1976), Wang et al.(1988), Lee et al(2011))을 수집하여 우리의 광도곡선(2008, 2012)과 함께 각각 주기변화가 보정된 통일된 기산점을 사용하여 광도곡선을 분석하였다. 모든 광도곡선에서 0.75 위상에서 밝기가 더 어두워지는 O'Connell effect가 발생하였고, 일부 광도곡선은 부식에서 식의 깊이가 주식보다 깊어지는 시기를 가진다. 이는 스펙트럼 유형이 F0-F5보다 만기형 별에서 흑점이 부식의 깊이에 영향을 주어 주식보다 깊어지는 AC Boo, TY UMa 등에서 보여 지는 특징이다. 우리는 WD 프로그램을 이용하여 광도곡선 중 B-V 색지수 그래프에서 식 이외부분에서 변화가 적고 광도곡선의 O'Connell effect의 크기가 작은 2008 광도곡선으로 광도해를 결정하였다. 전형적인 TY UMa형 별과 같이, 우리의 광도해 역시 W-subtype의 결과를 나타낸다. 결정된 광도해를 다른 광도곡선에도 적용시켜 광도곡선에 나타나는 흑점의 영향을 살펴보았다. 마지막으로 주기 분석 결과와는 달리 제 3천체의 광도는 검출 되지 않았다.

• Journal of Nutrition and Health
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• v.40 no.5
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• pp.475-482
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• 2007

This study was done to analyze nutrition counseling services in health promotion center and to investigate demands of subjects for nutrition services. Data was collected through the survey of 90 subjects. The results were as follows. The results of people receiving nutrition services showed that 58.5% of the counseling group and 46.4% of the non-counseling group answered having experience with nutrition services. And 50% of them received nutrition counseling through individual counseling. Diet therapy with health check-up results also appeared the highest in contents of nutrition counseling. As a source of nutrition information and health knowledge, subjects relied heavily or most on the TV, internet, books, magazines, and newspapers. On the other hand, they relied much less on advice from dietitians, nutritionists, medical doctors and nurses. The experience of receiving nutrition services and thinking about nutrition education related positively. It showed that the counseling group (95.1%) was significantly higher than the non-counseling group (80.5%) in necessity of nutrition assessment. But, necessity of nutrition counseling wasn't significantly different between the two groups. The method of nutrition counseling subjects preferred was individual consultation. The subjects answered to having need of analysis and evaluation of nutrient intake and calorie prescription in nutrition assessment and individual nutritional status results explanation in nutrition counseling. In conclusion all people visiting health promotion centers need nutrition service of some kind.

• Journal of the Korean Chemical Society
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• v.57 no.1
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• pp.40-51
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• 2013

In order to develop a quantitation method for Perfluorooctanesulfonic acid(PFOS) contained in plastics that are mainly used in electric and electronic equipment, this study consisted of conducting method validations with LDPE samples using soxhlet solvent extraction and LC/MS. As a result, the limits of detection and quantitation (LOD, LOQ) were $2.58{\mu}g/L$ and $7.82{\mu}g/L$, respectively. Additionally, the recovery was 96-102%. For the correlation coefficient of LC/MS, the $r^2$ value was 0.9992 in the concentration range of $7.82-100{\mu}g/L$, which confirmed its linearity. Furthermore, for the standardization of the analysis method for PFOS in electric and electronic equipment to correspond to EU environmental regulations, we conducted a proficiency test with a number of domestic and international testing laboratories. Three of the ten testing laboratories that participated in the proficiency test submitted outliers. Accordingly, we examined the cause of the outliers using the $^{19}F$ NMR, finding that the main cause was an error in the processing of the results for isomers in PFOS that existed in standard solutions and samples.

• Korean Journal of Food Science and Technology
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• v.28 no.3
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• pp.421-427
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• 1996

Ethyl carbamate is an animal carcinogen and a suspected human carcinogen found in fermented foods and beverages. For the determination of ethyl carbamate in typical Korean diet, an analytical method was established for the food as complex as Kimchi. Kimchi samples collected from various locations in the country were homogenized and extracted four times with ethyl acelate. Following concentration and reconstitution with water, the extract was loaded onto $C_{18}$ column. Fraction containing ethyl carbamate was eluted with methanol, while most of the red pigment of the sample was retained on the column. The eluent was further purified with alumina, followed by Florisil column. The final eluent was analyzed by gas chromatography mass spectrometry in the selected ion monitoring mode. None of the twenty Kimchi samples showed ethyl carbamate level higher than 4.6 ppb without correction for the recovery. The concentration of ethyl carbamate in Kimchi increased as pH decreased, suggesting fermentation dependent formation of ethyl carbamate.

• The Journal of Korean Institute of Information Technology
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• v.17 no.7
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• pp.1-11
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• 2019

With the development of smartphones and wearable devices, researches related to platforms that collect lifelogs from these devices and the visualization of the lifelog results have also been advanced. However, the existed researches were impossible to collect data from various devices because they depended on a specific device and platform when transmitting or receiving lifelog data. In addition, they do not provide visualized analysis results of specialized lifelogs in specific areas, such as the users' location information. To resolve the problems, this paper analyzes user location information from the lifelog collection platform and develops the interface and visualization tools for lifelog collection. To do this, we define and analyze the requirements of developing the proposed system. Then, based on the analyzed requirements, this paper develops a lifelog visualization tool using various graphs, maps and the RESTful API interface and shows its implemented results.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.525-535
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• 2017

The purpose of this study aims to examine consumer perception and current status of water park. The Naver and Daum were used for data collection channels and the keyword 'water park' was used for data retrieval. The data analysis period was limited to the study period from January 1, 2015 to December 31, 2016 for a total of two years. First, as a result of the frequency analysis, hidden cameras, Lotte water park, arrests, suspects, gimhae were in top 5 in 2015, Lotte water park, swimming, summer, opening, admission ticket were in top 5 in 2016. Second, as a result of the connection degree central analysis, hidden camera, arrest, suspect, female, shower room were in top 5 in 2015, swimming, Lotte water park, summer and One Mount, admission ticket were in top 5 in 2016. Third, as a result of the N-GRAM network graph, the water park/hidden camera, the hidden camera/hidden camera, the suspect/arrest, the Gimhae/Lotte water park, water park/suspect were in top 5 in 2015, and One Mount/water park, Gimhae/Lotte water park, water park/admission ticket, water park/water park, water park/opening were in top 5 in 2016. Fourth, as a result of the CONCOR analysis, three groups in 2015 and two groups in 2016 were formed.