• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.51-51
• /
• 2017

지역빈도해석은 짧은 기간의 자료를 보유하고 있는 계측 지점이나 자료가 없는 미계측 지점에서의 확률수문량을 산정하기 위하여 많이 쓰여 진다. 지역빈도해석을 실시하기 위한 조건으로는 우선 수집된 하천유역들을 대상으로 수문학적 동질 지역을 구분하는 것이 중요하다. 그리고 구분되어진 지역에 포함되는 모든 지점들의 자료를 빈도해석 함으로써 관심 지점의 신뢰할 만한 확률수문량을 산정하는 것이다. 그동안의 지역빈도해석은 주로 비건조지역을 중심으로 홍수와 같은 재난재해 대비 그리고 수자원 관리를 위한 연구들을 실시해왔다. 본 연구의 주 목적은 건조지역의 수자원 관리를 위해 건조지역 하천유역을 중심으로 지역빈도해석을 실시하여 신뢰할만한 확률수문량을 산정하는 것이다. 확률수문량 산정값의 정확도를 향상시키기 위해 지역빈도해석 모델에 쓰여 지는 새로운 지형학적 변수들을 제공하였고 수문학적 동질 지역을 구분 위해 수집된 각 하천유역의 형상들을 확인하여 동질 지역을 정의하였다. 예를 들면, 수지형 유역, 부채형 유역, 격자형 유역과 같은 다른 형상들을 구분하여 각 유역 형상 종류별로 동질 지역을 만들었다. 건조지역의 지역빈도해석을 위해 미국 건조지역의 105개 하천유역 유량자료들을 수집 및 이용하였다. 확률수문량 산정을 위하여 앙상블 인경신경망 (Ensemble Artificial Neural Network)과 정준 상관 계수(Canonical Correlation Analysis)를 이용한 지역빈도해석 모델을 만들었다. 제안된 모델의 수행평가와 정확성 평가를 위해 리샘플링 기법인 10-겹 교차 검증 (10-fold cross-validation), 잭나이프 (Jackknife) 기법들을 이용하였고 모델로부터 산정된 확률수문량값을 편향 (Bias), 상대 편향(rBias), 평균 제곱근 오차 (RMSE), 상대 평균 제곱근 오차 (rRMSE)를 통하여 산정 값과 실제 관측 값의 차이를 분석하였다. 그 결과 건조지역의 지역빈도해석을 위해 새롭게 제시된 지형학적 변수들을 사용하였을 때 모델의 수행능력이 향상되었음을 확인하였다. 또한 하천유역 형상에 따라 동질 지역을 구분하였을 때 향상된 확률수문량이 산정되었다. 향상된 지역빈도해석 모델을 통해 건조지역의 신뢰할만한 확률수문량을 산정함으로써 건조지역의 효과적인 수자원 관리를 위한 수공시설물 설계에 중요한 정보들을 제공할 것이다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.6
• /
• pp.1045-1054
• /
• 2020

In this paper, we designed a TCP/IP based ring buffer system that can stably transfer bulk data streams in the unstable network environments. In the scheme we proposed, The observation data stream generated and output by each radio observatory's backend system as a UDP frame is stored as a UDP packet in a large capacity ring buffer via a socket buffer in the client system. Thereafter, for stable transmission to the remote destination, the packets are processed in TCP and transmitted to the socket buffer of server system in the correlation center, which packets are stored in a large capacity ring buffer if there is no problem with the packets. In case of errors such as loss, duplication, and out of order delivery, the packets are retransmitted through TCP flow control, and we guaranteed that the reliability of data arriving at the correlation center. When congestion avoidance occurs due to network performance instability, we also suggest that performance degradation can be minimized by applying parallel streams.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.427-427
• /
• 2022

하천에서 유사량 자료는 하천의 이·치수 목적으로 활용할 수 있는 기본 자료중 하나로서 하상 변동 예측, 저수지 퇴사량 추정, 하도 계획과 설계, 유사조절 계획 수립 및 기타 구조물 등의 영향 평가 등 다양하게 활용할 수 있다. 본 연구에서는 신뢰성 높은 유사량 자료를 생산하기 위하여 국가유사량관측망 중 27개 지점에 대하여 유사량의 측정 및 특성분석을 수행하였다. 유사량 측정과정은 사전조사, 현장측정, 실험실분석, 모형적용(총유사량 산정) 단계로 구분할 수 있다. 사전조사 단계에서는 현장관련 정보를 수집하여 현장측정 계획 및 현장 안전대책을 수립하고, 현장측정 단계에서는 사전조사 단계에서 수립한 계획을 바탕으로 유사량을 측정하였다. 유사량 측정시 측선은 ISO 기준 이상의 5~7개로 측선을 나누어 측정하였고, 측정장비는 D-74, DH-48 부유사 채취기를 이용하여 왕복수심적분법으로 수행하였다. 실험실분석은 한국수자원조사기술원 유사량 실험실에서 채취시료에 대한 농도, 레이저회절법을 이용한 입도분석, 하상토분석(체분석), 비중실험을 수행하였다. 총유사량 산정을 위한 모형적용 단계에서는 수정-아인슈타인법(Modified Einstein Method)을 적용하였다. 또한, 유량-부유사량 농도 변화양상과 부유사량 특성 분석을 이용한 부유사량 측정결과를 평가하였고 각 지점의 부유사량특성을 잘 나타낼 수 있는 지수식(Q_ss = aQ^b)을 이용하여 유량-부유사량관계곡선식을 개발하였다.

• Journal of Korea Water Resources Association
• /
• v.55 no.11
• /
• pp.855-863
• /
• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.4
• /
• pp.195-201
• /
• 2020

COVID-19 is hitting the world. In order to bring about new ways of innovation in the space sector, we need to analyze changes in the space sector and design new challenge strategies. COVID-19 exposes inherent vulnerabilities in the space sector. In particular, COVID-19 is causing supply chain shocks in the space industry, resulting in delays in the supply of systems, subsystems and parts due to a complete or partial interruption of a manufacturing unit. As the overall impact of New Normal on the industry is overall, we continue to look at it in the space sector. COVID is causing supply chain shock in the space industry. It causes a delay in the supply of systems, subsystems and parts due to a complete or partial interruption of a manufacturing unit. In the supply of launch services, the launch schedule is being delayed, but the main launch is still taking place. Demand for major applications such as environmental monitoring is soaring in the earth observation utilization sector. Analyzing the impact on manufacturing, the vendor-based contraction is bringing delays in the supply of systems, subsystems and components, and launch service providers are trying to minimize delays in the launch schedule.

• Journal of Korea Multimedia Society
• /
• v.9 no.7
• /
• pp.872-893
• /
• 2006

In this study, I classify the elements of physiognomic judgment of character with regard to form and meaning from a visual perspective based on physiognomic judgment of character study in 'the cosmic dual forces and the Five Elements theory'. Individual characters for each type are designed using graphic data. Based on that, design system of individual characters for each personality type is investigated using Neural Network system. Faces with O-Haeng (Five Elements) shapes are shown to constitute the system with ${\pm}0.3%$ degree of error tolerance for the non-loaming input data. For the shapes of Chinese characters 'tree, fire, soil, gold and water', their MSE(Mean Square Error) are 0.3, 0.3, 0.2, 0.5, 0.2. It seems to be the best regarding the scoring system which ranges from 0 to 5. Therefore, this system might be regarded to produce the most accurate facial shape of character automatically when we input character's personality we desire to make.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.3
• /
• pp.175-186
• /
• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.