• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.231-237
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• 2020

In this paper, we provide an efficient hybrid video blending scheme to improve the naturalness of composite video in Poisson equation-based composite methods. In image blending process, various blending methods are used depending on the purpose of image composition. The hybrid blending method proposed in this paper has the characteristics that there is no seam in the composite video and the color distortion of the object is reduced by properly utilizing the advantages of Poisson blending and alpha blending. First, after blending the source object by the Poisson blending method, the color difference between the blended object and the original object is compared. If the color difference is equal to or greater than the threshold value, the object of source video is alpha blended and is added together with the Poisson blended object. Simulation results show that the proposed method has not only better naturalness than Poisson blending and alpha blending, but also requires a relatively small amount of computation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.942-948
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• 2020

In this paper, we propose a clustered algorithm that possible more efficient user distinction within clustering using context-aware attribute information. In typically, the data provided to classify interrelationships within cluster information in the process of clustering data will be as a degrade factor if new or newly processing information is treated as contaminated information in comparative information. In this paper, we have developed a clustering algorithm that can extract user's recognition information to solve this problem in using K-means algorithm. The proposed algorithm analyzes the user's clustering attributed parameters from user clusters using accumulated information and clustering according to their attributes. The results of the simulation with the proposed algorithm showed that the user management system was more adaptable in terms of classifying and maintaining multiple users in clusters.

• Plant Journal
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• v.18 no.1
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• pp.43-49
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• 2022

In this study, the operational characteristics of the 7.48 MW fuel cell power plant consisting of 17 units of 440 kW Phosphoric Acid Fuel Cell (PAFC) in operation since its commercial operation in December 2017 were explained and the heat recovery process of the plat using Organic Rankine Cycle (ORC)was simulated. The fuel cell system performance improvement and economic assessment were analyzed by calculating the amount of heat recovery and electric power available when connecting a 125 kW XLT Model ORC for hot water heat sources with 105℃, 40.8 t/h. The result of the study shows that integrating the 125 kW ORC to PAFC power plant would improve generating efficiency by about 0.6% through annually 851,472 kWh of electricity produced by ORC, and fuel cell and ORC integrated systems were calculated to have a 0.35% higher Internal Return Ratio and more Net Present Value of 1,249 million KRW than not installing ORC despite installation costs.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1677-1689
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• 2022

Air pollution is social issue that has long-term and short-term harmful effect on the health of animals, plants, and environments. Chimneys are the primary source of air pollutants that pollute the atmosphere, so their location and type must be detected and monitored. Power plants and industrial complexes where chimneys emit air pollutants, are much less accessible and have a large site, making direct monitoring cost-inefficient and time-inefficient. As a result, research on detecting chimneys using remote sensing data has recently been conducted. In this study, YOLOv5-based chimney detection model was generated using BUAA-FFPP60 open dataset create for power plants in Hebei Province, Tianjin, and Beijing, China. To improve the detection model's performance, data split and data augmentation techniques were used, and a training strategy was developed for optimal model generation. The model's performance was confirmed using various indicators such as precision and recall, and the model's performance was finally evaluated by comparing it to existing studies using the same dataset.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.83-88
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• 2022

Internet of Things (hereinafter referred to as IoT) related technologies are continuously developing in line with the recent development of information and communication technologies. IoT system sends and receives unique data through network based on various sensors. Data generated by IoT systems can be defined as big data in that they occur in real time, and that the amount is proportional to the amount of sensors installed. Until now, IoT systems have applied data storage, processing and computation through centralized processing methods. However, existing centralized processing servers can be under load due to bottlenecks if the deployment grows in size and a large amount of sensors are used. Therefore, in this paper, we propose a distributed processing system for applying a data importance-based algorithm aimed at the high availability of the system to efficiently handle real-time sensor data arising in IoT environments.

• 지역과문화
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• v.8 no.1
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• pp.55-76
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• 2021

The purpose of this study is to analyse the complexity of Vietnam's cultural policy in the socio-economic context of socialism-oriented reform with a focus on the case of 'socialization'(xa hoi hoa) cultural policy. The Vietnamese socialization policy has been adopted to mobilise resources and participation from 'the whole society' in order to promote the development of culture and arts. Although there remains the discourse of its definition, the socialization policy has showed its achievements in mobilizing financial resources, privatization, enhancing decentralization, and revitalizing the private investment, and thus help improve cultural services in both quantity and quality. The socialization policy illuminates the leadership of the state, yet gradually improved in promoting and practicing cultural policy. This study is expected to enhance understanding of Vietnam's cultural policy after reform to the Korean scholars, therefore it contributes to boosting the cooperation and cultural exchange between Vietnam and Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.344-344
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• 2023

최근 기후변화에 따라 극한 강우로 전 세계적으로 국지적 홍수 피해가 증가하고 있다. 또한 극한 강우 발생시 다양한 건설 현장의 상황에 따라 침수 취약성이 나타나 인적 물적 피해로 이어질 수 있다. 특히, 시공에 따른 현장 지형 변화에 대해 실시간으로 침수 예측이 불가하여 위험 판단이 어려운 실정이며, 극한 강우 발생에 대비하기 위해 강우 정보 획득 및 분석을 효율화하여 강우예측 정확성을 높일 필요가 있다. 이러한 필요성에 따라 본 연구에서는 건설 현장의 침수 피해를 최소화하기 위해 침수 위험을 판정하고 예측하는 방법을 제시하고자 한다. 본 연구의 침수 위험 판정 방법은 건설 현장에서 실시간 지형변화 정보 확보와 침수 위험 판정의 정확도를 높이기 위한 침수심 분석에 인공 신경망 기법을 활용하였다. 또한, 침수판정 알고리즘은 지형, 강우 분석 모듈과 침수판정 모듈로 구성하였다. 지형 분석 모듈은 건설 현장이 시공진행에 따른 지형 데이터의 변화를 고려하기 위해 실시간 영상 정보의 객체 탐지를 구분하는 인공 신경망 기법을 적용해 지형 분석 모듈을 구축하였다. 강우 분석 모듈은 다양한 강우 정보를 취합할 수 있는 서버를 구축하여 강우 임베딩 정보를 실시간으로 분석하도록 고안하여 정확도를 높였다. 이러한 자료를 바탕으로 강우-유출해석에 의한 침수심 값과 실측값, 침수 지표를 활용하여 인공 신경망 기법으로 침수 위험을 판정하도록 제시하였다. 본 연구를 통해 건설 현장에서 지형 상태의 지속적인 변화와 강우데이터의 정확도 향상에 대응할 수 있는 침수 위험 판정이 가능하고 인적 물적 피해 최소화를 기대할 수 있다. 향후, 본 연구에서 제시된 방법은 건설 현장에서 분석 시스템과 실측 모니터링에 의해 검증되어야 할 것이며, 건설 현장 외에도 스마트 도시 및 지하 공간에서 확대하여 적용할 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.221-221
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• 2023

기후변화에 관한 정부 간 협의체 6차 보고서에 따르면 강우 변동성이 증가함에 따라 홍수 피해가 빈번해질 것으로 예상된다. 집중호우, 태풍, 장마 등 물 관련 재해의 발생빈도와 규모가 댐의 홍수조절능력을 초과하는 경우 홍수량을 예측하고 댐 모의 운영을 통해 댐 방류량을 결정하기 어렵다. 그러므로 댐의 안정성 확보를 위해 기존의 댐 운영방식을 검토하고 개선하여 홍수조절용량을 확보하는 과정이 필요하다. 본 연구의 목적은 기존의 저수지 운영방식을 분석하고 극한의 홍수에 대비하여 저수지 운영 방식을 개선하는데 있다. 연구 대상 댐으로는 합천댐과 섬진강댐을 선정하였다. 합천댐과 섬진강댐은 홍수조절을 위해 Rigid ROM(일정률-일정량 방식)을 사용하고 있으며 200년 빈도 홍수량에 맞춰 설계되었다. 그러나 합천댐은 계획방류량(6,200 m³/sec)이 댐 하류지역의 설계홍수량(2,885 m³/sec)보다 2배 이상 크기 때문에 계획방류량만큼 방류하지 않더라도 하류에서 홍수피해가 발생하는 문제가 있다. 2020년, 섬진강댐은 200년 빈도의 홍수량보다 작은 홍수가 발생했음에도 불구하고 하류 지역에서 홍수 피해가 발생하였다. 본 연구에서는 우리나라에서 홍수기에 일반적으로 사용되는 저수지 운영 방식 - Auto ROM, Rigid ROM, Technical ROM -을 적용하여 댐의 안정성과 하류 홍수피해를 최소화하기 위한 최적의 운영 방안을 검토하였다. 200년 빈도 홍수량과 2020년 홍수 자료를 이용하고 저수지 운영 방식의 변경을 통해 홍수조절효과를 검토하였다. 또한, 홍수조절효과가 미약할 시 사전 방류를 통해 홍수조절효과를 향상시켰다. 본 연구는 안전하고 효율적인 댐 운영 방식을 분석함으로써, 타 다목적 댐 운영에 대한 참고자료로 활용될 수 있을 것으로 기대된다.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.219-225
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• 2009

The primary purpose of this study is to build computer models referring overall flow of complex and various semiconductor wafer manufacturing process and to implement a educational model which operates with a presentation tool showing device design. It is important that Korean semiconductor industries secure high competitive power on efficient manufacturing management and to develop technology continuously. Models representing the FAB processes and the functions of each process are developed for Seoul National University Semiconductor Research Center. However, it is expected that the models are effective as visually educational tools in Korean semiconductor industries. In addition, it is anticipated that these models are useful for semiconductor process courses in academia. Scalability and flexibility allow semiconductor manufacturers to customize the models and perform simulation education. Subsequently, manufacturers save budget.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.149-155
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• 2009

Attacks in wireless sensor networks (WSN), are similar to the attacks in ad-hoc networks because there are deployed on a wireless environment. However existing security mechanism cannot apply to WSN, because it has limited resource and hostile environment. One of the typical attack in WSN is setting up wrong route that using wormhole. To overcome this threat, Ji-Hoon Yun et al. proposed WODEM (WOrmhole attack DEfense Mechanism) which can detect and counter with wormhole. In this scheme, it can detect and counter with wormhole attacks by comparing hop count and initial TTL (Time To Live) which is pre-defined. The selection of a initial TTL is important since it can provide a tradeoff between detection ability ratio and energy consumption. In this paper, we proposed a fuzzy rule-based system for TTL determination that can conserve energy, while it provides sufficient detection ratio in wormhole attack.