• 한국산학기술학회논문지
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• 제22권1호
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• pp.409-414
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• 2021

수상함이 전투 환경에서 우수한 임무수행능력과 생존성을 구현하기 위해서는 구획을 차단하는 수밀/기밀 성능이 중요하다. 위와 같은 요구사항을 충족을 위해 함정 건조 후 시운전에서 구조요소(격실 및 탱크)에 대한 밀폐성과 특정부위에 대한 강도의 적합성을 검사하며, 특히 수선에 인접한 격실들의 격실기밀시험(Air test)을 수행한다. 격실기밀시험은 대상 격실에 공기를 주입하여 시운전 평가서 상의 요구압력까지 압을 적용하고, 일정 시간동안 압력강하 값을 확인하여 해당 구역의 요구조건 충족여부를 판단한다. 검사 기준은 10분 동안 감소된 압력이 시운전 평가서의 압력강하 허용치 이내이어야 한다. 하지만 외기온도의 영향이 큰 여름철에 격실기밀시험 진행 간 유입되는 열이 내부 공기의 온도를 상승시키고, 이로 인해 공기가 팽창하여 격실 내 압력이 증가하는 현상이 식별되었다. 이러한 현상은 격실기밀시험에서 최종 압력강하 값을 정확히 판단할 수 없게 하고 평가결과에 대한 신뢰성을 결여시킬 수 있다. 본 연구를 통해 격실 내 온도변화 영향을 보정하기 위한 시스템을 고안하였다. 개발된 시스템은 격실 내 온도변화에 의한 압력 변화량을 계산하여 보정값을 출력한다. 이상기체 방정식을 통해 압력변화량을 계산하며, 격실기밀시험 간 온도유지 및 증가/감소를 반영할 수 있도록 개발되었다. 계산된 압력 보정값을 NIST REFPROP의 데이터 베이스와 비교하였을 때, 최소 0.126 %에서 최대 0.253 %의 차이를 보였다.

• ETRI Journal
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• 제33권4호
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• pp.476-486
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• 2011

The quality of navigation service is determined by the accuracy of the available data. For existing navigation services, a full map update is provided in order to keep the map data of mobile devices current. As content and services of mobile devices have recently been diversifying, the size of map data managed in mobile devices has increased, reaching several gigabytes in size. It generally takes tens of minutes to write several gigabytes of data into mobile device storage. For traditional navigation systems, a complicated storage structure called a physical storage format (PSF) is used to assure maximum processing performance of map data in mobile devices within limited resources. Consequently, even though modified navigation map data actually affects only a portion of a map, the full map data is updated because partial updates are not possible. In this paper, a navigation system is studied to solve this difficult partial map update problem. The map air update navigation system, which is the result of this study, provides real-time partial map updating using wireless communications.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.35-43
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• 2023

This paper emphasizes that information received in disaster situations can lead to disparities in the effectiveness of communication, potentially causing damage. As a result, there is a growing demand for disaster and safety information among citizens. A user-centered disaster and safety information application service is designed to address the rapid dissemination of disaster and safety-related information, bridge information gaps, and alleviate anxiety. Through the Open API (Open Application Programming Interface), we can obtain clear information about the weather, air quality, and guidelines for disaster-related actions. Using chatbots, we can provide users with information and support decision-making based on their queries and choices, utilizing cloud APIs, public data portal open APIs, and solution knowledge bases. Additionally, through Mashup techniques with the Google Maps API and Twitter API, we can extract various disaster-related information, such as the time and location of disaster occurrences, update this information in the disaster database, and share it with users.

• 한국정보통신학회논문지
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• 제25권12호
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• pp.1935-1941
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• 2021

최근 다양한 분야에 적용되고 있는 딥러닝을 활용한 알고리즘 개발을 위해서는 양질의 풍부한 학습데이터가 갖춰져야 한다. 본 논문은 딥러닝 알고리즘 개발 시 활용도가 높고 정보 도출 시 유용한 광학 영상, 열화상, 음성 등의 생체신호 데이터를 동시에 수집하여 서버에 전송하는 생체신호 수집시스템을 제안한다. 수집기의 이동성을 높이기 위해 라즈베리 파이를 기반으로 제작하였고, 수집한 데이터는 무선 인터넷을 통해 서버로 전송한다. 복수의 수집기에서 동시에 데이터 수집이 가능하도록 피실험자별로 로그인을 위한 아이디를 부여했고, 이를 데이터베이스에 반영하여 데이터 관리가 용이하게 하였다. 제안하는 수집시스템의 활용방안을 보이기 위해 피로도 측정을 위한 생체신호 데이터 수집의 예시를 보인다.

• 산업경영시스템학회지
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• 제46권3호
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• pp.186-197
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• 2023

In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

• 한국환경보건학회지
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• 제44권5호
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• pp.421-432
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• 2018

Objectives: In this study, we started to develop an indoor garden integrated IoT solution based on IAQ (indoor air quality) and interconnection with an environmental database for smart management of indoor gardens. The purpose of this study was to develop and apply an integrated solution for customized air purification from an indoor garden through big data analysis using IoT technology. Methods: An IoT-based IAQ monitoring system was established in three households within a new apartment building. Based on real-time and long-term data collected, $PM_{2.5}$, $CO_2$, temperature, and humidity changes were compared to those of indoor garden applications and the analyzed results were indexed. Results As a result of the installation, all three households had no results exceeding the standard for indoor air pollution on average $PM_{2.5}$ and $CO_2$ indices. In the case of indoor garden installation, the IAQ index increased to the "Good" section after the installation, and readings in the "Bad" section shown before the installation disappeared. The comfort index also did not dip into the "Uncomfortable" section, where it had been preinstallation, and significantly lowered the average score from "Uncomfortable for sensitive groups" to "Good". Overall, the IAQ composite index for the generation of installations decreased the "Good" interval, but "Bad" did not appear. Conclusions In this study on developing an integrated solution for IAQ based on IoT indoor gardens, big data was analyzed to determine IAQ and comfort indexes and an IAQ composite index. Through this process, it became understood that it is necessary to monitor IAQ based on IoT.

• 한국지반공학회논문집
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• 제31권10호
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• pp.37-47
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• 2015

최근 콘크리트의 성능 향상 및 현장 공사 품질관리 개선으로 인해 현장타설말뚝의 콘크리트 품질이 많이 향상되었지만 아직까지도 콘크리트에 대하여 기존에 보수적인 품질관리 기준을 적용하고 있다. 본 연구에서는 콘크리트 타설시 슬럼프량, 염분량, 공기량, 외기온도 등이 콘크리트 공시체 강도에 미치는 영향을 분석하였다. 이를 위해서 인천 송도지역 기초시공현장에서 6개월 이상 동안 시공된 현장타설말뚝 타설시 제작한 공시체 200개 이상의 자료를 분석하여 데이터베이스를 구축하고 통계 분석하였다. 굵은 골재 최대치수 25mm, 압축강도 40MPa, 슬럼프 180mm 기준으로 배합한 콘크리트 공시체 자료로부터 재령일별 압축강도 분포와 외기온도, 콘크리트 온도, 슬럼프, 공기량, 염분량 등의 인자가 콘크리트 압축강도에 미치는 영향을 조사하였다. 조사 결과 "콘크리트 타설시 콘크리트 온도와 외기온도의 차이"가 공시체 7일과 28일 압축강도에 미치는 영향이 가장 큰 것으로 확인되었다.

• 방사성폐기물학회지
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• 제17권2호
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• pp.235-243
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• 2019

원자력 사고 후 대기로 누출된 방사성물질이 지표 토양내 침적된 후 강우에 의하여 주변 환경으로 이동하여 지표수계를 오염시킨다. 지표 토양내 침적된 방사성핵종의 거동 평가를 위하여 수립된 지표 수계 및 토양 유실 모델의 주요 입력자료를 수집하여 분석하였다. 월성 원전이 위치한 낙동강권역의 하천과 호수에서의 물리적 특성과 주요 생물상의 변화를 파악하기 위해서 원전 주변 수생 환경의 조사 및 분석을 수행하였다. 이를 위해 국내 여러 기관에서 제공하는 수치지도, 수문자료, 수질 및 생태환경자료 등을 수집 분석하여 자료간 상호 연계성을 갖도록 체계적인 DB를 구축하였다. 구축된 수생환경 자료는 지표수계에 흡착된 방사성물질의 중장기 거동 평가를 위하여 수립된 지표수계 유동, 토사유실 및 생태계 모델의 기본 입력자료로 제공되어 종합적인 방사선영향평가에 활용될 예정이다.

• 기본간호학회지
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• 제24권3호
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• pp.167-180
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• 2017

Purpose: The aim of this study was to synthesize the best available evidence for active warming interventions during cesarean section. Methods: A database search was done for randomized controlled trials utilizing active warming interventions. Maternal temperature, shivering and neonatal temperature were evaluated as outcome variables. Data were analyzed using Cochrane Review Manager software Version 5.3. Results: Thirteen studies including 1306 patients were reviewed. The degree of lowering of maternal temperature decreased in the warmed fluids (MD 0.51; p=.004) and warming mattress interventions (MD 0.22; p<.001) compared with control groups. Incidence of shivering was also lower in the active warming group (OR 0.55; p=.003). There was no statistically significant difference in maternal temperature with a forced air warming intervention (MD 0.64; p=.15) or in neonatal temperature (MD 0.12; p=.26). Conclusion: Findings show that with warmed fluids and warming mattresses applied during cesarean sections maternal temperature decline was reduced and also the incidence of shivering declined, but no significant effect was observed for forced air warming interventions. These findings provide a basis for developing a warming guideline for women having a cesarean section and will help to improve the quality of care for cesarean section patients.

• 한국대기환경학회지
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• 제19권4호
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• pp.387-396
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• 2003

A field study was conducted during the summer time of 2002 to determine compositions of volatile organic compounds (VOCs) emitted from vehicles and to develop source emission profiles that is applied to CMB model to estimate the source contribution of certain area. Source emission profile is widely used for the estimation of source contribution by the chemical mass balance model and have to be developed applicable for the target area of estimation. This study was aimed to develop source emission profile and estimation of source contribution of VOCs after application of the chemical mass balance (CMB) receptor model. After considering the emission inventory and other research results for the VOCs in Seoul, Korea, the sources like vehicle emission (tunnel), gas station (gasoline, diesel), solvent usage (painting operation, dry cleaning, graphic art), and gas fuels were selected for the major VOCs sources. Furthermore, ambient air samples were simultaneously collected from 09:00 to 11:00 for four days at eight different official air quality monitoring sites as receptors in Seoul during summer of 2001. Source samples were collected by canisters, and then about seventy volatile organic compounds were analyzed by gas chromatography with flame ionization detector (GC/FID). Based on both the developed source profiles and the database of the receptors, CMB model was intensively applied to estimate mass contribution of VOCs sources. Examining the source profile from the vehicle, the portion of alkanes of VOCs was highest, and then the portion of aromatics such toluene, m/p-xylene were followed. In case of gas fuel. they have their own components; the content of butane, propane, ethane was higher than any other component according to the fuel usage. The average of the source apportionment on VOCs for 8 sites showed that the major sources were vehicle emission and gas fuels. The vehicle emission source was revealed as having the highest contribution with an average of 49.6%, and followed by solvent with 21.3%, gas fuel with 16.1%, gasoline with 13.1%.