• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.871-881
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• 2023

This study investigates the geomorphic changes and Bed Relief Index of the river downstream of the Yeongju Dam by Nays2DH, a two-dimensional numerical model, in order to grasp the dynamics of the downstream river while applying various flow patterns such as pulse discharge. It shows that the geomorphic and the bed elevations changes are the largest under the condition of the normalized pulse discharge. The total change in the riverbed is 29.88 m for uniform flow, 27.46 m for normalized hydrograph, 29.63 m for pulse flow and 31.87 m for pulse flow with normalized hydrograph which result in the largest variation in scour and deposition. The Bed Relief Index (BRI) increases with time under conditions of uniform flow, pulse flow and pulse flow with normalized hydrograph. However, BRI increased rapidly until 30 hrs after the peak flow (14 hrs), but decreased from 56 hrs under the condition of normalized hydrograph. Therefore, the condition of normalized hydrograph gives greater dynamics than the condition of a single flood or constant flow, and the dynamics increase downstream than upstream, resulting in an effect on improving the environment of the river downstream of the dam.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.246-246
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• 2021

본 연구는 강우 발생시 유량을 추정하는 것에 목적이 있다. 이를 위해 본 연구는 선행연구의 모형 개발방법론에서 벗어나 딥러닝 알고리즘 중 하나인 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 유량을 추정하였다. 합성곱 신경망은 일반적으로 분류 문제 (classification)을 해결하기 위한 목적으로 개발되었기 때문에 불특정 연속변수인 유량을 모의하기에는 적합하지 않다. 이를 위해 본 연구에서는 합성곱 신경망의 완전 연결층 (Fully connected layer)를 개선하여 연속변수를 모의할 수 있도록 개선하였다. 대부분 합성곱 신경망은 RGB (red, green, blue) 사진 (photograph)을 이용하여 해당 사진이 나타내는 것을 예측하는 목적으로 사용하지만, 본 연구의 경우 일반 RGB 사진을 이용하여 유출량을 예측하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이를 위해 본 연구에서는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는 수문학적 이미지는 입력자료로 활용했다. 합성곱 신경망의 구조는 Convolution Layer와 Pulling Layer가 5회 반복하는 구조로 설정하고, 이후 Flatten Layer, 2개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 다시 1개의 Dense Layer가 이어지는 구조로 설계하였다. 마지막 Dense Layer의 활성화 함수는 분류모형에 이용되는 softmax 또는 sigmoid 함수를 대신하여 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 이와 함께 각 층의 활성화 함수는 정규화 선형함수 (ReLu)를 이용하였으며, 모형의 학습 평가 및 검정을 판단하기 위해 MSE 및 MAE를 사용했다. 또한, 모형평가는 NSE와 RMSE를 이용하였다. 그 결과, 모형의 학습 평가에 대한 MSE는 11.629.8 m3/s에서 118.6 m3/s로, MAE는 25.4 m3/s에서 4.7 m3/s로 감소하였으며, 모형의 검정에 대한 MSE는 1,997.9 m3/s에서 527.9 m3/s로, MAE는 21.5 m3/s에서 9.4 m3/s로 감소한 것으로 나타났다. 또한, 모형평가를 위한 NSE는 0.7, RMSE는 27.0 m3/s로 나타나, 본 연구의 모형은 양호(moderate)한 것으로 판단하였다. 이에, 본 연구를 통해 제시된 방법론에 기반을 두어 CNN 모형 구조의 확장과 수문학적 이미지의 개선 또는 새로운 이미지 개발 등을 추진할 경우 모형의 예측 성능이 향상될 수 있는 여지가 있으며, 원격탐사 분야나, 위성 영상을 이용한 전 지구적 또는 광역 단위의 실시간 유량 모의 분야 등으로의 응용이 가능할 것으로 기대된다.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.29-38
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• 2015

The Energy Storage System stores electricity for later use. This system can store electricity from legacy electric power systems or renewable energy systems into a battery device when demand is low. When there is high electricity demand, it uses the electricity previously stored and enables efficient energy usage and stable operation of the electric power system. It increases the energy usage efficiency, stabilizes the power supply system, and increases the utilization of renewable energy. The recent increase in the global interest for efficient energy consumption has increased the need for an energy storage system that can satisfy both the consumers' demand for stable power supply and the suppliers' demand for power demand normalization. In general, an energy storage system consists of a Power Conditioning System, a Battery Management System, a battery cell and peripheral devices. The specifications of the subsystems that form the energy storage system are manufacturer dependent. Since the core component interfaces are not standardized, there are difficulties in forming and operating the energy storage system. In this paper, the design of the profile structure for energy storage system and realization of private profiling system for energy storage system is presented. The profiling system accommodates diverse component settings that are manufacturer dependent and information needed for effective operation. The settings and operation information of various PCSs, BMSs, battery cells, and other peripheral device are analyzed to define profile specification and structure. A profile adapter software that can be applied to energy storage system is designed and implemented. The profiles for energy storage system generated by the profile authoring tool consist of a settings profile and operation profile. Setting profile consists of configuration information for energy device what composes energy saving system. To be more specific, setting profile has three parts of category as information for electric control module, sub system, and interface for communication between electric devices. Operation profile includes information in relation to the method in which controls Energy Storage system. The profiles are based on standard XML specification to accommodate future extensions. The profile system has been verified by applying it to an energy storage system and testing charge and discharge operations.

• Journal of the Korean Orthopaedic Association
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• v.54 no.3
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• pp.269-275
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• 2019

Purpose: This study analyzed the treatment effects of drain insertion in the posteromedial portal after an arthroscopic synovectomy and posterior septum resection for pyogenic arthritis. Materials and Methods: From June 2005 to December 2016, 56 cases (55 patients, 1 case of bilateral knee) were diagnosed with pyogenic arthritis and arthroscopic treatment was performed. Fourteen patients (25.0%) were identified with causative organisms. The average follow-up period was 12.3 months, and the mean age was 67.8 years old. Twenty-four cases were males and 31 cases were females. Kellgrene-Lawrence grade (K-L grade) I was 6 patients, II was 20 patients, III was 11 patients, and IV was 18 patients. Surgery was performed through six portal. The posterior septum was removed and a drainage tube was inserted from the posterior medial side to the posterior side of the joint. The Lysholm score was used after surgery for a functional evaluation. The K-L grade at the time of admission and at the last follow-up were compared for a radiological evaluation. Results: The mean normalization period of the C-reactive protein was 59.8 days (6-164 days). Intravenous antibiotics were used for an average of 37.1 days. The results of the functional evaluation revealed a mean Lysholm score of 64.5 (30-98) in a total of 56 cases. Two reoperations was performed, but the treatment was completed with same method in all patients. The K-L grade was similar at the time of surgery and at the last follow-up (p>0.05). Conclusion: The method of drain insertion in the posteromedial portal after arthroscopic synovectomy and posterior septum resection for pyogenic arthritis is an effective technique that can obtain satisfactory results by inducing proper exudate discharge.