• 조명전기설비학회논문지
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• 제20권9호
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• pp.18-23
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• 2006

This paper presents an operator training simulator for power system restoration against massive blackout. The system is designed especially focused on the generality and convenient setting up for initial condition of simulation. The former is accomplished by using power flow calculation methodology, and PSS/E data is used to set up the initial state for easy setting. The proposed simulator consists of three major components-a power flow(PF), a data conversion(CONV), and, a GUI module. The PF module calculates power flow, and then checks over-voltages of buses and overloads of lines. The CONV module composes a Y-Bus array and a database at each restoration action. The initial Y-Bus array is composed from PSS/E data. A user friendly GUI module is developed including a graphic editor and a built-in operation manual. The maximum processing time for one step operation is 15 seconds, which is adequate for training purpose.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.181-183
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• 2003

This paper presents an operator training simulator for power system restoration against massive black-out. The system is designed especially focused on the generality and convenient setting up for initial condition of simulation. The former is accomplished by using on line calculation methodology, and PSS/E data is used to define the initial situation. The proposed simulator consists of three major components - the Power flow(PF) module, data conversion(CONV) module and CUI subsystem. PF module calculates power flow, and then checks overvoltage of buses and overflow of lines. CONV module composes an Y-Bus array and a data base at each restoration action. The initial Y-Bus array is constructed from PSS/E data. The user friendly GUI module is developed including graphic editor and built-in operation manual. As a result, the maximum processing time for one step operation is 15 seconds, which is adequate for training purpose. Comparison with PSS/E simulation proves the accuracy and reliability of the training system.

• 대한전기학회논문지:전력기술부문A
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• 제54권7호
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• pp.323-327
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• 2005

This paper presents an operator training simulator for power system restoration against massive black-out. The system is designed especially focused on the generality and convenient setting up for initial condition of simulation. The former is accomplished by using power flow calculation methodology, and PSS/E data is used to define the initial situation. The proposed simulator consists of three major components - the power flow(PF) module, data conversion(COW) module and GU subsystem. PF module calculates power flow, and then checks overvoltage of buses and overflow of lines. COW module composes an Y-Bus array and a data base at each restoration action. The initial Y-Bus array is constructed from PSS/E data. The user friendly GUI subsystem is developed including graphic editor and built-in operation manual. As a result, the maximum processing time for one step operation is 15 seconds, which is adequate for training purpose. Comparison with PSS/E simulation proves the accuracy and reliability of the training system.

• 멤브레인
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• 제29권2호
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• pp.96-104
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• 2019

본 연구는 분리막 성능 저하로 기능을 상실한 역삼투막의 힐링을 통한 복원의 가능성을 알아보고자 하는 데에 목적이 있다. 손상된 막은 양이온고분자인 poly(styrene sulfonic acid) sodium salt (PSSA)와 음이온고분자인 polyethyleneimine(PEI)를 염석법을 이용하여 이중으로 코팅했으며 또한 소재의 순서를 바꿔 코팅을 수행했다. 그리고 농도, 시간, 이온세기 등에 따라 코팅된 역삼투막의 투과도와 배제율을 측정하여 손상된 막으로부터 복원된 정도를 알아보았다. 또한 역삼투 평막에서 복원이 우수한 조건을 가정용 정수기 모듈에 적용하여 손상된 역삼투막 모듈에 또한 대하여 복원 가능성을 알아보았다. 이로부터 PEI 30,000 ppm (IS = 0.1)/PSSA 20,000 ppm (IS = 0.7) 코팅 조건에서 역삼투막 모듈에 적용했을 때 염 배제율은 69%에서 86% (손상 전 모듈의 경우 90%)까지 복원되었다.

• 한국물환경학회지
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• 제36권5호
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• pp.385-391
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• 2020

Soil loss is a serious problem frequently caused by local torrential rainfalls due to climate change. In particular, soil loss is occurring in agricultural areas rather than urban areas, and many pollutants are introduced into rivers, causing environmental problems. To reduce soil loss, the Ministry of Environment has designated and managed non-point source management areas. The Jaun-district in Hongcheon-gun, which was designed as a non-point pollution source management area in Gangwon-do, is located in the upper stream of Soyang Lake. Most of the agricultural fields are composed of highland agriculture fields. The highland agricultural fields in the Jaun-district are also composed of large-scale farming areas, and the ditches located near the agricultural fields have been illegally used for farmland. Therefore, the local government in Hongcheon-gun is conducting a project to restore the ditches occupied by agricultural fields. However, an analysis of the amount of soil loss that can be reduced by the restoration of the ditches has not been conducted yet. Thus, the purpose of this study was to analyze the effect of reducing the soil loss from the restoration of the ditches used as agricultural fields in the Jaun-district. The SATEEC L Module was used to analyze the reduction in soil loss by ditch restoration. The SATEEC L Module was constructed to estimate the LS factor using Moore and Burch's method after calculating the slope length using the digital elevation model and the maximum allowable slope length. The LS factor and the USLE formula were used to estimate the amount of soil loss that could be reduced by ditch restoration. The analysis showed that the ditch restoration could reduce about 16.6% of the soil loss in the Jaun-district. The results of this study will contribute to the study of methods to reduce soil loss in non-point pollution management areas.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.367-372
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• 2001

Feature restoration is that restore feature to 3D solid model using the feature information in STEP AP224. Feature is very important in CAPP, but feature information is defined very complicated in STEP AP224. This paper recommends the algorithm of extraction the feature information in physical STEP AP224file. This program import STEP AP224 file, parse the geometric and topological information, the tolerance data, and feature information line-by-line. After importation and parsing, store data into database. Feature restoration module analyze database including feature information, extract feature information, e.g. feature type, feature's parameter, etc., analyze the relationship and then restore feature to 3D solid model.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.339-343
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• 2015

To rapidly recover ceased functionality of a facility after a catastrophic seismic event, critical decisions on facility repair works are made within a limited period of time. However, prolonged damage assessment of facilities, due to massive damage in the surrounding region and the complicated damage judgment procedures, may impede restoration planning. To assist reliable structural damage estimation without a deep knowledge and rapid interactive analysis among facility damage and restoration operations during the approximate restoration project planning phase, we developed a prototype of distributed facility restoration simulations through the use of high-level architecture (HLA) (IEEE 1516). The simulation prototype, in which three different simulations (including a seismic data retrieval technique, a structural response simulator, and a restoration simulation module) interact with each other, enables immediate damage estimation by promptly detecting earthquake intensity and the restoration operation analysis according to estimated damage. By conducting case simulations and experiments, research outcomes provide key insights into post-disaster restoration planning, including the extent to which facility damage varies according to disaster severity, facility location, and structures. Additional insights arise regarding the extent to which different facility damage patterns impact a project's performance, especially when facility damage is hard to estimate by observation. In particular, an understanding of required type and amount of repair activities (e.g., demolition works, structural reinforcement, frame installation, or finishing works) is expected to support project managers in approximate work scheduling or resource procurement plans.

• 방송공학회논문지
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• 제27권3호
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• pp.351-360
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• 2022

영상 흐려짐은 피사체의 움직임, 카메라의 흔들림 등의 요인으로 발생하는 현상이다. 최근 합성곱 심층신경망(Convolution Neural Network, CNN)을 활용하여 흐려짐 현상을 복원하는 연구가 활발하게 진행되었으며, 원본과 정답 영상의 차이를 이용하여 복원 과정을 가이드하는 방법이 뛰어난 성능을 보였다. 본 논문에서는 왜곡 정보를 기반으로 흐려진 영상 복원 성능을 개선하는 방법을 제안한다. 이를 위해 학습 시, 원본과 정답 영상 차이에 대한 이진화를 수행하여 복원 과정을 가이드 할 수 있도록 하는 트랜스포머(Transformer) 기반 신경망 모듈을 설계하였다. 제안하는 방법은 학습 과정에서 잠재 특징을 기반으로 전역적 추론을 통해 예측한 왜곡 위치 정보 분포를 흐려짐 복원 과정에 반영한다. 다양한 영상 흐려짐 복원 신경망에 제안하는 모듈을 적용하여 복원 성능을 효과적으로 향상시킬 수 있음을 확인하였다.

• 한국환경복원기술학회지
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• 제8권6호
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• pp.34-44
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• 2005

The objective of this study is to analyze the thermal properties of various green roof type. The experimental districts, have different soil thickness, soil type, the existence of module and the different kinds of vegetation, had installed. A measurement was conducted in Seoul University to investigate the thermal impacts of rooftop greening. The measurement point of temperature were 30, located in soil surface, middle of the soil layer, under the module, hard surface and soffit surface of each experimental district. The experimental investigation lasted from 6th August to 29th August, a total of 24 days. The results showed that green roof can contribute thermal benefits by soil and vegetation and reduce building energy consumption by a role of insulation. It's also better to make soil thickness over 20cm and various vegetation that should be more effective. The district installed only soil also could be effective for reducing the temperature of roof surface. Therefore, the increase of soil thickness and various vegetation could reduce more temperature of roof surface and building energy consumption. Also, it's helpful to reduce temperature that plant coverage rate be raised.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.740-753
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• 2023

Text recognition in natural scene images is a challenging problem in computer vision. The accurate identification of ship number characters can effectively improve the level of ship traffic management. However, due to the blurring caused by motion and text occlusion, the accuracy of ship number recognition is difficult to meet the actual requirements. To solve these problems, this paper proposes a dual-branch network based on the CRNN identification network. The network couples image restoration and character recognition. The CycleGAN module is used for blur restoration branch, and the Pix2pix module is used for character occlusion branch. The two are coupled to reduce the impact of image blur and occlusion. Input the recovered image into the text recognition branch to improve the recognition accuracy. After a lot of experiments, the model is robust and easy to train. Experiments on CTW datasets and real ship maps illustrate that our method can get more accurate results.