• Title/Summary/Keyword: 업데이트

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A Study for Standardizing and Efficient Maintaining Multi-dimensional Geospatial River Data (다차원 하천공간정보 표준화 및 효율적 유지관리 기술 연구)

  • Kim, Dongsu;Kim, Kyungdong;You, Hojun;Yeo, Hong-koo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.56-56
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    • 2021
  • 하천단면이나 하상변동 추적 등 하천공간정보는 유량이나 강우 등 수문시계열 정보와 더불어 계획홍수위 산정이나 하천구조물 신설로 인한 하천의 변화를 추적하는 데 있어 근간을 이루는 주요 정보로 국가차원의 유지 및 관리가 필요하다. 국내의 하천공간정보는 RIMGIS, WAMIS, 하천 일람, WINS와 같은 웹기반 시스템에서 정보화 되어 관리되고 있다. 그러나, RIMGIS는 여러 가지 문제점을 노정하고 있어 개선을 적극적으로 검토해볼 시점이라고 볼 있다. 우선, RIMGIS는 구축이 10년 이상된 기술로 구성되어 온라인 시스템 실행속도가 느리고, 물관리 일원화 와중에 관리주체가 불분명해진 상태이며, 제공되는 정보도 하천망이나 유역 정도로 차원 및 정확도도 낮고 활용도 및 현행화도 부족한 상태이다. 또한 공간정보 관리 DB표준으로 효율적인 관계형 구조 대신 하천대장 등을 수치화한 개념의 레이어 단위의 주제도로 관리하다보니 자료중복이 불가피하여 시스템이 무겁고, 자료간 연관검색이 거의 불가하고, 신속한 하천지형 변화 업데이트가 어려운 상태이다. 최근 진행되고 있는 RIMGIS 개선 사업은 여전히 종래의 레이어 단위의 주제도들을 추가하거나 개정하는 데 머물고 있는 상태이다. 이러다 보니 현재 우리나라의 대표적인 하천정보시스템인 RIMGIS의 실무 활용도는 낮은 것으로 알려져 있다. 가장 실무활용도를 저하시키고 현행화 상의 문제로 지적되는 부분은 하천정비기본계획 수립 시 발생한 공간자료 관리 부실이다. 현재 RIMGIS에서는 하천기본계획보고서만 PDF 형태로 제공할 뿐, 실제 지형자료는 과업을 수행한 설계사에 개별 보관되어 활용도뿐만아니라 망실의 우려가 높은 상황이다. 본 연구에서는 하천기본계획수립 시 측량되는 단면을 포함한 다양한 공간자료를 관계형으로 표준화 DB에 효율적으로 저장할 수 있게 하는 방안을 제시하고자 한다.

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Adaptive Operation of Boryeong Dam Water Supply Adjustment Standards against Multi-year Droughts (다년 가뭄 대비 보령댐 용수공급 조정기준의 적응형 운영방안)

  • Kim, Gi Joo;Lee, Jae Hwang;Lee, Joohyung;Kim, Young-Oh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.373-373
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    • 2022
  • 전세계적으로 기후변화로 인해 3년 이상의 기간동안 지속되는 다년 가뭄의 빈도와 심도가 증가하고 있으며, 이로 인한 피해도 증가하고 있다. 본 연구에서는 이를 반영하여 전국 다목적댐 및 용수댐에서 모두 주요 가뭄 대응 대책으로 사용되고 있는 현행 용수공급 조정기준을 개선하는 방안을 제안하고자 한다. 가장 먼저, 장기 기억 반영이 가능한 시계열 모형인 ARFIMA(Autoregressive Fractional Integrated Moving Average) 모델을 사용하여 다양한 강도의 장기 기억을 가지고 있는 연간 유입량을 생성하였다. 이후, 연간 유입량을 k-최근접 이웃 방법 기반의 배분 도구를 사용하여 10일 단위 유입량으로 분배하였으며 이를 대체 용수공급 조정기준을 생성하기 위한 입력 변수로 사용하였다. 새로운 용수공급 조정기준은 매 시점마다 새롭게 업데이트되는 정보를 통해 현행 기준과 함께 적응형으로 저수지 운영에 사용되었다. 다년 가뭄이 반영된 유입량으로 적응형으로 저수지 운영을 관측 유입량 하에서 빈도와 크기의 측면에서 분석을 시행하였다. 그 결과, 심각한 실패(물 부족 비율 30% 이상)의 빈도의 경우 현행 기준 운영 시 6.14%에서 적응형 운영 시행 시 2.99%로 개선되었지만, 전체 기간 동안의 신뢰도는 적응형 운영보다(26.42%) 현행 운영 하에서 더욱 나은 결과를 보였다(41.19%). 위와 같은 분석 결과는 심각한 실패의 빈도와 크기를 줄이는 용수공급 조정기준을 시행하는 원론적인 목적과 일치하기에, 본 연구에서 제안하는 다년 가뭄에 대비한 적응형 운영 방안은 향후 길게 지속되는 가뭄 조건에서 저수지 운영 정책으로 활용될 수 있음을 확인하였다.

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Proposal of a method of using HSV histogram data learning to provide additional information in object recognition (객체 인식의 추가정보제공을 위한 HSV 히스토그램 데이터 학습 활용 방법 제안)

  • Choi, Donggyu;Wang, Tae-su;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.6-8
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    • 2022
  • Many systems that use images through object recognition using deep learning have provided various solutions beyond the existing methods. Many studies have proven its usability, and the actual control system shows the possibility of using it to make people's work more convenient. Many studies have proven its usability, and actual control systems make human tasks more convenient and show possible. However, with hardware-intensive performance, the development of models is facing some limitations, and the ease with the use and additional utilization of many unupdated models is falling. In this paper, we propose how to increase utilization and accuracy by providing additional information on the emotional regions of colors and objects by utilizing learning and weights from HSV color histograms of local image data recognized after conventional stereotyped object recognition results.

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A Study of the Application of Machine Learning Methods in the Low-GloSea6 Weather Prediction Solution (Low-GloSea6 기상 예측 소프트웨어의 머신러닝 기법 적용 연구)

  • Hye-Sung Park;Ye-Rin, Cho;Dae-Yeong Shin;Eun-Ok Yun;Sung-Wook Chung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.5
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    • pp.307-314
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    • 2023
  • As supercomputing and hardware technology advances, climate prediction models are improving. The Korean Meteorological Administration adopted GloSea5 from the UK Met Office and now operates an updated GloSea6 tailored to Korean weather. Universities and research institutions use Low-GloSea6 on smaller servers, improving accessibility and research efficiency. In this paper, profiling Low-GloSea6 on smaller servers identified the tri_sor_dp_dp subroutine in the tri_sor.F90 atmospheric model as a CPU-intensive hotspot. Applying linear regression, a type of machine learning, to this function showed promise. After removing outliers, the linear regression model achieved an RMSE of 2.7665e-08 and an MAE of 1.4958e-08, outperforming Lasso and ElasticNet regression methods. This suggests the potential for machine learning in optimizing identified hotspots during Low-GloSea6 execution.

Development of maintenance concept and procedures for KASS (KASS 유지보수 정의 및 절차 개발)

  • Minhyuk Son;Youngsun Yun;ByungSeok Lee
    • Journal of Advanced Navigation Technology
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    • v.26 no.6
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    • pp.373-379
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    • 2022
  • KASS (korea augmentation satellite system) is an SBAS (satellite based augmentation system) that must ensure the performance of aviation service in accordance with the International Civil Aviation Organization's SARPs (standards and recommended practices) Annex 10 - Aeronautical Telecommunications. In order to guarantee the target service performance, the operating system must be operated, maintained and managed stably, and a maintenance system must be established for this purpose. From the maintenance point of view, the KASS subsystems were developed to consist of replacement units, and the maintenance organization and procedures to manage those subsystems and units were defined. In addition, the maintenance task for each the replacement unit was developed to ensure the availability performance required for the successful KASS operation, and the developed tasks were verified to sufficiently cover the activities to maintain the previously defined replacement units. The maintenance tasks developed through this study will be continuously verified in the actual operation preparation process prior to the full-scale provision of aviation services in the end of 2023, and will be updated accordingly.

Creative Destruction in the Culture of Charity is Needed in Asia (아시아 기부 문화에 필요한 창조적 파괴)

  • Sim, Hyena;Areshidze, Giorgi
    • Journal of Venture Innovation
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    • v.3 no.2
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    • pp.177-195
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    • 2020
  • This paper discusses the reasons why a disparity in commitment to charitable giving exists between two regions : the East and the West. In explaining the regional difference, this paper particularly focuses on the social, economic, and political factors forming the trend?for instance, Asians' deep-rooted distrust in charity foundations and the lack of government policies incentivizing philanthropic giving in Asia. After analyzing why and how significantly Asia lags behind in charity compared to other parts of the globe, the paper proves that "creative destruction" is needed in the Asian philanthropy market. Additionally, this paper shows that it is an opportune time for an innovative start-up to introduce a new form of technology, an easy-to-access application with registered partnership foundations, thereby introducing creative destruction in the culture of charity in Asia. This paper finally examines the obstacles this start-up may face as it tries to grow into a monopoly and the socio-political implications it may bring to the world.

A New Healthcare Policy in Korea Part 1: Expanded Reimbursement Coverage of Brain MRI, Brain/Neck MRA, and Head and Neck MRI by National Health Insurance (새로운 건강보험 보장성 강화 대책 1부: 뇌 MRI, 뇌혈관/경부혈관 MRA, 두경부 MRI 급여 확대)

  • Eunhee Kim
    • Journal of the Korean Society of Radiology
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    • v.81 no.5
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    • pp.1053-1068
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    • 2020
  • In accordance with the new healthcare policy of government (Moon Jae-In Care) to strengthen health insurance coverage, the National Health Insurance (NHI) coverage of brain magnetic resonance imaging (MRI), brain/neck MR angiography (MRA), and head and neck MRI have been expanded since 2018 in Korea. This article has been reviewed focusing on the "Detailed matter concerning criteria and method for providing reimbursed services in the NHI. Some revisions" regarding reimbursement for MRI, which was revised from October 2018 to April 2020 and is currently in effect. It included the MRI reimbursement system in Korea, recent adjustment of the reimbursement coverage for patients with headache or dizziness, and reimbursement coverage, standard imaging, and radiologic report of brain MRI, brain/neck MRA and head and neck MRI. This article could help radiologists gain knowledge on health insurance to protect the expertise of the radiologist and to play a leading role in the hospital. As the policy changes, detailed matter concerning criteria and method for providing reimbursed services in the NHI may be revised. Therefore, radiologists should update issues related to insurance reimbursement for MRI continuously.

Retained Message Delivery Scheme utilizing Reinforcement Learning in MQTT-based IoT Networks (MQTT 기반 IoT 네트워크에서 강화학습을 활용한 Retained 메시지 전송 방법)

  • Yeunwoong Kyung;Tae-Kook Kim;Youngjun Kim
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.131-135
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    • 2024
  • In the MQTT protocol, if the retained flag of a message published by a publisher is set, the message is stored in the broker as a retained message. When a new subscriber performs a subscribe, the broker immediately sends the retained message. This allows the new subscriber to perform updates on the current state via the retained message without waiting for new messages from the publisher. However, sending retained messages can become a traffic overhead if new messages are frequently published by the publisher. This situation could be considered an overhead when new subscribers frequently subscribe. Therefore, in this paper, we propose a retained message delivery scheme by considering the characteristics of the published messages. We model the delivery and waiting actions to new subscribers from the perspective of the broker using reinforcement learning, and determine the optimal policy through Q learning algorithm. Through performance analysis, we confirm that the proposed method shows improved performance compared to existing methods.

Comparative Analysis of Reliability Predictions for Quality Assurance Factors in FIDES (FIDES의 품질 보증 인자에 대한 신뢰도 예측 비교 분석)

  • Cheol-Hwan Youn;Jin-Uk Seo;Seong-Keun Jeong;Hyun-Ung Oh
    • Journal of Aerospace System Engineering
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    • v.18 no.2
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    • pp.21-28
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    • 2024
  • In light of the rapid development of the space industry, there has been increased attention on small satellites. These satellites rely on components that are considered to have lower reliability compared to larger-scale satellites. As a result, predicting reliability becomes even more crucial in this context. Therefore, this study aims to compare three reliability prediction techniques: MIL-HDBK-217F, RiAC-HDBK-217Plus, and FIDES. The goal is to determine a suitable reliability standard specifically for nano-satellites. Furthermore, we have refined the quality assurance factors of the manufacturing company. These factors have been adjusted to be applicable across various industrial sectors, with a particular focus on the selected FIDES prediction standard. This approach ensures that the scoring system accurately reflects the suitability for the aerospace industry. Finally, by implementing this refined system, we confirm the impact of the manufacturer's quality assurance level on the total failure rate.

Improve the Reliability Measures of Bus Arrival Time Estimation Model (버스도착시간 추정모형의 신뢰도 향상방안 연구)

  • Kim, Jisoo;Park, Bumjin;Roh, Chang-Gyun;Kang, Woneui
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.597-604
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    • 2014
  • In this study, we investigate to show the limitations of current bus arrival time estimation model based on each bus route, and to propose a bus arrival time estimation model based on a bus stop to overcome these limitations. Using the characteristic of bus arrival time calculated on travel time between two bus stops, we develop a model to estimate bus arrival times with the data of all buses traveling the same section regardless of bus route numbers. In the proposed model, an estimated arrival time is calculated by weighted moving average method, and verification between observed value and estimated time is performed on the basis of RMSE. Error was reduced by up to 20% compared to the existing models and the data update period was reduced by more than half that is related to the accuracy of bus arrival time information. We expect to solve the following problems with the suggested method: sudden increase or decrease in arrival time of the bus, the difference of the expected arrival times at the same stop between two or more buses having different route numbers, and impossibility of offering information of a bus if the bus is not operated with the designated schedule.