• Title/Summary/Keyword: 손실 원인

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Lessons from Data Repository GDR (Geoscience Data Repository) Building Experience (데이터 리포지토리 GDR 구축 경험과 교훈)

  • Han, JongGyu
    • Proceedings of the Korean Society for Information Management Conference
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    • 2017.08a
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    • pp.100-100
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    • 2017
  • 100년의 역사를 지닌 한국지질자원연구원(KIGAM)은 국내 유일의 지질자원 전문연구기관으로서 그간 생산한 조사 연구데이터는 우리나라 과학기술의 귀중한 역사적 학술적 가치가 큰 유산으로써 보존 가치가 매우 크다고 할 수 있다. 하지만 현재 KIGAM의 상황은 최종성과물 위주로 자료관리가 이루어지고 있으며, 조사 연구 과정에서 생산된 암석 토양 지하수샘플이나 조사 탐사장비를 통해 얻어지는 자료는 연구자 또는 연구실 팀에서 개별적으로 관리하고 있다. 이러한 자료관리체계는 자료의 공동 활용이 어렵고, 자료를 보유하고 있는 연구자의 퇴직이나, 조직개편으로 인한 팀 실의 분리 과정에서 자료의 손실과 훼손 가능성이 높고, 누가 어디에 어떤 자료를 무슨 형태로 보관하고 있는지 찾기 어려워 자료의 재활용도가 떨어질 뿐만 아니라, 이로 인한 중복 조사 연구 가능성도 배제할 수 없다. KIGAM은 지질자원분야 국가데이터센터 구축을 목표로 연구과정에서 생산되는 연구데이터의 체계적인 관리와 공유, 활용체계 구축을 위해 2015년도에 기획사업을 통해 중장기 로드맵을 포함한 추진전략을 수립하였으며, 한국과학기술정보연구원(KISTI)의 DataNest를 기술이전받아 지질자원 연구데이터 리포지토리 시스템(GDR: Geoscience Data Repository)를 개발하였다. GDR 시스템 개발을 위해 연구데이터 분류코드를 작성하였으며, 2016년부터 데이터관리계획(DMP: Data Management Plan)을 주요사업 연구계획서 양식에 포함시켜 제출하도록 하였다. 과거 KIGAM은 연구데이터를 수집, 관리하기 위해 몇 차례에 걸쳐 시도를 했지만 실패한 경험을 가지고 있다. 실패 요인에는 (1) 관련 정책, 제도, 조직, 인력, 예산 등 데이터 관리 인프라 부재, (2) 연구사업에서 생산된 데이터는 개인소유라는 인식 및 공유 의식 부족, (3) 데이터 관리 활동은 귀찮은 것이고, 시간 낭비라는 인식, (4) 데이터 관리 공개 공유 활동에 대한 보상체계 부재 등을 꼽을 수 있다. 즉, 제도를 포함한 인프라 부족과 경영진과 구성원의 인식부족이 제일 큰 원인으로 판단된다. 성공적인 연구데이터 관리를 위해서는 지속적이고 꾸준한 투자가 이루어져야 하지만 경영진의 의지에 따라 사업이 중단되기도 한다. 이러한 과거의 실패 요인에 대한 해결 없이 지난 1년 6개월 정도의 GDR 운영은 지지부진하였다. 이러한 문제점을 해결하기 위해서는 국가차원의 제도적 뒷받침이 따라야 한다. 즉 국가 R&D 성과물 관리차원에서 연구데이터를 주요 성과물로 관리해야 할 것으로 판단된다. 연구사업계획서에 DMP를 포함시키고, 연구주제 및 분야별로 데이터센터(혹은 데이터 리포지토리)를 지정하고, 국가 R&D에서 생산되는 연구데이터를 의무적으로 제출하도록 하는 것이다. 또한 데이터센터의 안정적이고 지속적인 운영을 위해 연구사업비 항목에 데이터 관리비를 신설하여 데이터센터의 운영비로 사용하도록 하면 예산문제도 어느 정도 해결 될 수 있을 것으로 본다. 또한 데이터 제출 및 인용도에 따라 데이터 생산부서 혹은 생산자에게 평가점수를 부여하는 등 보상체계 마련을 위한 연구도 필요할 것으로 보인다. 국가 R&D 연구데이터의 수집, 관리, 공유, 활용을 제대로 성공시키려면 국가 R&D 최고정책결정자의 지속적인 관심과 지원이 필수적이다.

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Analysis of Power System Stability by Deployment of Renewable Energy Resources (재생에너지원 보급에 따른 전력계통 안정도 분석)

  • Kwak, Eun-Sup;Moon, Chae-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.4
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    • pp.633-642
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    • 2021
  • Growing demand for electricity, when combined with the need to limit carbon emissions, drives a huge increase in renewable energy industry. In the electric power system, electricity supply always needs to be balanced with electricity demand and network losses to maintain safe, dependable, and stable system operation. There are three broad challenges when it comes to a power system with a high penetration of renewable energy: transient stability, small signal stability, and frequency stability. Transient stability analyze the system response to disturbances such as the loss of generation, line-switching operations, faults, and sudden load changes in the first several seconds following the disturbance. Small signal stability refers to the system's ability to maintain synchronization between generators and steady voltages when it is subjected to small perturbations such as incremental changes in system load. Frequency stability refers to the ability of a power system to maintain steady frequency following a severe system upset resulting in significant imbalance between generation and load. In this paper, we discusses these stability using system simulation by renewable energy deployment plan, and also analyses the influence of the renewable energy sources to the grid stability.

A Study on the Optimal Setting of Large Uncharged Hole Boring Machine for Reducing Blast-induced Vibration Using Deep Learning (터널 발파 진동 저감을 위한 대구경 무장약공 천공 장비의 최적 세팅조건 산정을 위한 딥러닝 적용에 관한 연구)

  • Kim, Min-Seong;Lee, Je-Kyum;Choi, Yo-Hyun;Kim, Seon-Hong;Jeong, Keon-Woong;Kim, Ki-Lim;Lee, Sean Seungwon
    • Explosives and Blasting
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    • v.38 no.4
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    • pp.16-25
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    • 2020
  • Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

Wafer bin map failure pattern recognition using hierarchical clustering (계층적 군집분석을 이용한 반도체 웨이퍼의 불량 및 불량 패턴 탐지)

  • Jeong, Joowon;Jung, Yoonsuh
    • The Korean Journal of Applied Statistics
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    • v.35 no.3
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    • pp.407-419
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    • 2022
  • The semiconductor fabrication process is complex and time-consuming. There are sometimes errors in the process, which results in defective die on the wafer bin map (WBM). We can detect the faulty WBM by finding some patterns caused by dies. When one manually seeks the failure on WBM, it takes a long time due to the enormous number of WBMs. We suggest a two-step approach to discover the probable pattern on the WBMs in this paper. The first step is to separate the normal WBMs from the defective WBMs. We adapt a hierarchical clustering for de-noising, which nicely performs this work by wisely tuning the number of minimum points and the cutting height. Once declared as a faulty WBM, then it moves to the next step. In the second step, we classify the patterns among the defective WBMs. For this purpose, we extract features from the WBM. Then machine learning algorithm classifies the pattern. We use a real WBM data set (WM-811K) released by Taiwan semiconductor manufacturing company.

A Study on AR Algorithm Modeling for Indoor Furniture Interior Arrangement Using CNN

  • Ko, Jeong-Beom;Kim, Joon-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.10
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    • pp.11-17
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    • 2022
  • In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

A global-scale assessment of agricultural droughts and their relation to global crop prices (전 지구 농업가뭄 발생특성 및 곡물가격과의 상관성 분석)

  • Kim, Daeha;Lee, Hyun-Ju
    • Journal of Korea Water Resources Association
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    • v.56 no.12
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    • pp.883-893
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    • 2023
  • While South Korea's dependence on imported grains is very high, droughts impacts from exporting countries have been overlooked. Using the Evaporative Stress Index (ESI), this study globally analyzed frequency, extent, and long-term trends of agricultural droughts and their relation to natural oscillations and global crop prices. Results showed that global-scale correlations were found between ESI and soil moisture anomalies, and they were particularly strong in crop cultivation areas. The high correlations in crop cultivation areas imply a strong land-atmosphere coupling, which can lead to relatively large yield losses with a minor soil moisture deficits. ESI showed a clear decreasing trend in crop cultivation areas from 1991 to 2022, and this trend may continue due to global warming. The sharp increases in the grain prices in 2012 and 2022 were likely related to increased drought areas in major grain-exporting countries, and they seemed to elevate South Korea's producer price index. This study suggests the need for drought risk management for grain-exporting countries to reduce socioeconomic impacts in South Korea.

Estimation of Economic Benefits Based on Appropriate Allocation of Emergency Medical Beds by Region in South Korea (지역별 응급의료병상 적정 분배에 따른 경제적 편익 추정)

  • Jeong Min Yang;Min Soo Kim;Jae Hyun Kim
    • Health Policy and Management
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    • v.34 no.1
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    • pp.17-25
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    • 2024
  • Background: This study aimed to assess the appropriate allocation of emergency medical beds across 17 provinces and presume the economic benefits associated with such allocation. Methods: To estimate the optimal allocation of emergency medical beds by province, data from the Statistics Korea's "cause of death statistics (2014-2021)," regional statistics on "area, population, gender, age," and "population projections" were utilized. The "number of emergency beds by city and district" provided by the Health Insurance Review and Assessment Service was also used. In estimating the economic benefits of preventing avoidable emergency deaths due to the expansion of emergency medical facilities, guidelines from the Korea Development Institute and the Korea Transport Institute were referenced to calculate the wage loss costs associated with emergency deaths and estimate the economic benefits. Results: The optimal ratio of emergency medical beds allocation by region was highest in Gyeonggi, Seoul, Gyeongnam, Gyeongbuk, and Busan, while Daejeon, Jeju, and Sejong showed lower ratios. Additionally, the prevention of avoidable deaths and economic benefits resulting from the increase in emergency medical facilities were highest in Gyeonggi, Seoul, Gyeongbuk, Gyeongnam, and Busan. However, when standardized by population, the prevention of avoidable deaths and economic benefits were analyzed to be highest in Gyeongbuk, Chungnam, Jeonnam, Gyeongnam, and Busan. Conclusion: The results of this study can serve as foundational data for future policy measures aimed at addressing the imbalance in the supply of emergency medical facilities across regions. Considering regional characteristics in the distribution of emergency medical facilities is expected to ultimately increase the efficiency of national finances and yield economic benefits.

A sea trial method of hull-mounted sonar using machine learning and numerical experiments (기계학습 및 수치실험을 활용한 선체고정형소나 해상 시운전 평가 방안)

  • Ho-seong Chang;Chang-hyun Youn;Hyung-in Ra;Kyung-won Lee;Dea-hwan Kim;Ki-man Kim
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.3
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    • pp.293-304
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    • 2024
  • In this paper, efficient and reliable methodologies for conducting sea trials to evaluate the performance of hull-mounted sonar systems is discussed. These systems undergo performance verification during ship construction via sea trials. However, the evaluation procedures often lack detailed consideration of variabilities in detection performance due to seabed topography, seasonal factors. To resolve this issue, temperature and salinity structure data were collected from 1967 to 2022 using ARGO floats and ocean observers data. The paper proposes an efficient and reliable sea trial method incorporating Bellhop modeling. Furthermore, a machine learning model applying a Physics-Informed Neural Networks was developed using the acquired data. This model predicts the sound speed profile at specific points within the sea trial area, reflecting seasonal elements of performance evaluation. In this study, we predicted the seasonal variations in sound speed structure during sea trial operations at a specific location within the trial area. We then proposed a strategy to account for the variability in detection performance caused by seasonal factors, using results from Bellhop modeling.

A Basic Study for the Introduction of Green Prescription and Establishment of Policy System in Korea - Through Comparative Analysis of U.K. and U.S. Cases - (국내 녹색처방 도입과 정책체계 수립을 위한 기초연구 - 영국과 미국 사례 비교 분석을 통해 -)

  • Kim, Hyo-Ju;Jung, Hae-Joon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.4
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    • pp.104-119
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    • 2024
  • The burden of medical expenses and the loss of social capital due to chronic diseases are becoming problems worldwide, and comprehensive and inclusive measures across various fields are required to prevent and manage their impacts. Social prescriptions have been shown to be effective in resolving the fundamental causes of health problems in patients with chronic diseases and in supporting existing treatments. In particular, green prescriptions that utilize the healing effects of nature and green spaces based on social prescriptions are being introduced in many countries overseas. Green prescription is the practice of a healthcare provider recommending activities in green spaces or experiences in the natural environment to patients for the prevention and management of chronic diseases. This study analyzed cases focusing on the policy system, the cases of the United Kingdom and the United States, which have introduced and operated green prescriptions under a national system. For this purpose, this study compared the background of green prescription introduction, related policies, and operation methods. Based on this, four implications were proposed to establish an effective plan for introducing green prescriptions in Korea. First, prior to establishing a policy for green prescriptions, interest in and research on green prescriptions are essential. Second, an implementation plan that fits the national health care system should be established, and policies should support the plan. Third, the introduction of green prescriptions from a long-term and gradual perspective is required. Fourth, comprehensive cooperation is required for the introduction and implementation of the green prescription system. This study can be used as basic data for discussion before introducing green prescriptions in Korea in the future.

Meteorological Constraints and Countermeasures in Major Summer Crop Production (하작물의 기상재해와 그 대책)

  • Shin-Han Kwon;Hong-Suk Lee;Eun-Hui Hong
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.27 no.4
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    • pp.398-410
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    • 1982
  • Summer crops grown in uplands are greatly diversified and show a large variation in difference with year and location in Korea. The principal factor for the variation is weather, in which precipitation and temperature play a leading role and such a weather factors as wind, sun lights also influence production of the summer crops. Since artificial control of weather conditions as a main stress factor for crop production is almost impossible, it must be minimized only by an improvement of cultivation techniques and crop improvement. Precipitation plays a role as one of the most important factor for production of the summer crops and it is considered in two aspects, drought and excess moisture. This country, which belongs to monsoon territory, necessarily encounter one of this stress almost every year, even though the level is different. Therefore, the facilities for both drought and excess moisture are required, but actually it is not easy to complete for them. On this account, crops tolerant to drought, excess moisture and pests should be considered for establishing summer crops. For the districts damaged habitually every season, adequate crops should be cultured and appropriate method of planting, drainage and weed control should be applied diversely. Injuries by temperature is mainly attributed to lower temperature particularly in late fall and early spring, although higher temperature often causes some damages depending upon the kind of crops. Sometimes, lower temperature in summer season playa critical role for yield reduction in the summer crops. However, certain crops are prevented to some extent from this kind of stress by improving varieties tolerant to cold, hot weather or early maturing varieties. As is often the case, control of planting time or harvesting is able to be a good management for escaping the stress. Lodging, plant diseases and pests are considered as a direct or indirect damage due to weather stress, but these are characters able to be overcome by means of crop improvement and also controlled by other suitable methods. In addition, polytical supports capable of improving constitution of agriculture into modern industry is urgently required by programming of data for the damages, establishment of damage forecasting and compensation system.

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