• Journal of the Korean Solar Energy Society
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• v.37 no.2
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• pp.13-22
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• 2017

Two-step water splitting thermochemical cycle with $CeO_2/ZrO_2$ foam device was investigated by using a solar simulator composed of 2.5 kW Xe-Arc lamp and mirror reflector. The hydrogen production of $CeO_2/ZrO_2$ foam device depending on heat recovery of Thermal-Reduction step and Water-Decomposition step was analyzed, and the hydrogen production of $CeO_2/ZrO_2$ and $NiFe_2O_4/ZrO_2$ foam devices was compared. Resultantly, the quantity of hydrogen generation increased by 52.02% when the carrier gas of Thermal-Reduction step is preheated to $200^{\circ}C$ and, when the $N_2/steam$ is preheated to $200^{\circ}C$ in the Water-Decomposition step, the quantity of hydrogen generation increased by 35.85%. Therefore, it is important to retrieve the heat from the highly heated gases discharged from each of the reaction spaces in order to increase the reaction temperature of each of the stages and thereby increasing the quantity of hydrogen generated through this.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.266-266
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• 2012

오늘날 도시는 인간 중심적으로 환경을 고려하지 않은 채 개발위주의 발전이 계속되고 있으며 도시화가 진행됨에 따라 도심지에 콘크리트와 아스팔트의 비율이 증가하고 농경지와 녹지가 감소하는 등 도시주변의 피복 변화가 빠르게 일어나고 있다. 이와 같이 열 환경을 고려하지 않은 도시의 급성장은 각종 인공 열과 대기오염 물질의 증가와 함께 도시상공의 기온을 상승시켜 도시의 기온이 주변 지역보다 높아지는 열섬현상의 원인이 되고 있다. 이에 따라 최근 미국, 유럽 등의 선진국을 비롯하여 아시아지역에서도 도시열섬현상 대책수립이 활발히 진행되어오고 있으며 국내에서도 열섬완화 대책 수립의 중요성이 인식되고 있다. 그러나 자연토지피복은 농경지, 나지, 수면과 같은 다양한 종류의 피복으로 구성되며 각 피복특성에 따라 도시내부에 영향을 미치는 정도가 다르게 나타나므로 도시계획에 반영될 수 있는 자연피복의 종류와 피복비율의 적정조합을 도출할 필요가 있다. 따라서 본 연구에서는 청주시를 대상으로 농경지를 포함하는 녹지의 감소, 공업단지의 증가에 따른 열 환경 영향을 분석하기 위하여 청주시의 연도별 토지피복 분포 현황과 과거 기상자료를 통해 토지피복 분포변화에 따른 온도 변화를 조사하였다. 토지피복은 농경지, 녹지, 주거지, 공업 단지 및 수역으로 분류하였으며, 대상지역의 기후 특성 파악을 위하여 청주시 총 면적에 대한 면적비율의 증감추이와 그에 따른 온도 변화를 정량적으로 파악하였다. 그 결과, 청주시는 녹지의 경우 정체 또는 감소추세를 나타낸 반면 공업단지는 지속적인 증가추세를 나타내었다.

• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.95-101
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• 2008

The wind speed reduction capability of forest belt of Caragana Korshinskili Kom in Yanchi, Ningxia province in China is as follows. 1. At the height of 0.5 m, the windbreak effect is 3-Strip (30.22%) > 2-Strip (26.53%) > 1-Strip (16.28%) from 1H (H = Tree Height) to 5H, and the windbreak effect is 2-Strip (16.11%) > 3-Strip (12.79%) > 1-Strip (9.82%) for greater than 7H. Further analysis of 2-Strip and 3-Strip revealed that the wind reduction effect of 2-Strip spread to 44H and 3-Strip spread to 27H. This result implies that 3-Strip is most effective for short distances and 2-Strip is most effective for long distances. 2. At the height of 1.0m, the wind speed was relatively constant and the reduction rate of wind speed had a minimal variation, with the reduction rate of 1-Strip (8.04%), 2-Strip (8.23%), and 3-Strip (7.43%). 3. The sandbreak effect is 2-Strip (55.28%) > 3-Strip (37.13%) > 1-Strip (20.87%). Especially, The rate of sandbreak of 1H (86.06%) of 2-Strip is most effective value in whole data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1248-1254
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• 2022

Efforts are being made to prevent traffic accidents in the school zone in advance. However, traffic accidents in school zones continue to occur. If the driver can know the situation information in the child protection area in advance, accidents can be reduced. In this paper, we design a camera that eliminates blind spots in school zones and a number recognition camera system that can collect pre-traffic information. It is designed by improving the LIDAR system that recognizes vehicle speed and pedestrians. It collects and processes pedestrian and vehicle image information recognized by cameras and LIDAR, and applies artificial intelligence time series analysis and artificial intelligence algorithms. The artificial intelligence traffic accident prevention system learned by deep learning proposed in this paper provides a forced push service that delivers school zone information to the driver to the mobile device in the vehicle before entering the school zone. In addition, school zone traffic information is provided as an alarm on the LED signboard.

• Journal of Space Technology and Applications
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• v.4 no.2
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• pp.169-183
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• 2024

Korea Astronomy and Space Science Institute (KASI) developed the Geochang satellite laser ranging (SLR) system for the scientific research on the space geodesy as well as for the national space missions including precise orbit determination and space surveillance. The operation system was developed based on the server-client communication structure, which controls the SLR subsystems, provides manual and automatic observation modes based on the observation algorithm, generates the range data between satellites and SLR stations, and carry out the post-processing to remove noises. In this study, we analyzed the requirements of operation system, and presented the development environments, the software structure and the observation algorithm, for the server-client communications. We also obtained laser ranging data for the ground target and the space geodetic satellite, and then analyzed the ranging precision between the Geochang SLR station and the International Laser Ranging Service (ILRS) network stations, in order to verify the operation system.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.101-110
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• 1999

Recently, there are a lot of studies to use a satellite image data in order to investigate a simultaneous change of a wide range area as a lake. However, in many cases of the water quality research there is one problem occured when extracting the water quality factors from the satellite image data because the atmosphere scattering exert a bad influence on a result of analysis. In this study, an attempt was made to select the relative atmospheric correction method, extract the water quality factors from the satellite image data. And also, the time-series analysis of the water quality factors was performed by using the multi-temporal image data.

• Ecology and Resilient Infrastructure
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• v.5 no.3
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• pp.125-133
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• 2018

Artificial neural network (ANN) is a powerful model to predict time series data and have been frequently adopted to predict groundwater level (GWL). Many researchers have also tried to improve the performance of ANN prediction for GWL in many ways. Dummies are usually used in ANN as input to reflect the seasonal effect on predicted results, which is necessary for improving the predicting performance of ANN. In this study, the effect of Dummy on the prediction performance was analyzed qualitatively and quantitatively using several graphical methods, correlation coefficient and performance index. It was observed that results predicted using dummies for ANN model indicated worse performance than those without dummies.

• Journal of the Korean housing association
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• v.22 no.3
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• pp.113-122
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• 2011

This study aimed to develop AI- (Artificial Intelligence) based thermal control logics and test their performance for identifying the optimal thermal control method in buildings. For this objective, a conventional Two-Position On/Off logic and two AI-based variable logics, which applied ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System), have developed. Performance of each logic was tested in a typical two-story residential building in U.S.A. using the computer simulation incorporating MATLAB and IBPT (International Building Physics Toolbox). In the analysis of the test results, AI-based control logic presented the advanced thermal comfort with stability compared to the conventional logic while they did not show significant energy saving effects. In conclusion, the predictive and adaptive AI-based control logics have a potential to maintain interior air temperature more comfortably, and the findings in this study could be a solid foundation for identifying the optimal thermal control method in buildings.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.113-118
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• 2021

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.826-829
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• 2020

스포츠팀 운영에 있어서 경기 중 상황에 대한 통계와 분석을 통해 좋은 성과를 내는 것은 스포츠 야구 종목의 Sabermetrics를 통해 이미 증명된 바가 있다. 한편, 축구에서는 최근 들어 선수의 역량을 평가하기 위하여 객관적인 시각에서 슈터(Shooter)에게 주어진 기회, 즉 슈팅 상황을 바라보는 기대 득점(Expected Goal; 이하 xG)이라는 지표가 등장하였으나, 객관성이라는 평가 의도와 다르게 경기 내 각각의 슈팅 상황을 정의하는 것에 있어 축구 분석관들의 주관성에 의존하는 한계성을 지녔다. 본 논문은 xG를 산출하는 방식에 있어서 기존의 주관성을 배제하고 인공지능을 통해 상황을 정의하여 객관적인 평가지표를 지향하며 유의미한 통계적 수치를 지닌 xG를 도출함으로써 결과 위주의 분석만이 존재하던 축구 종목에 있어서 경기 중 상황에 대한 객관적인 판단 및 정의에 대한 방향성을 제시한다. 또한, 본 논문에서의 인공지능은 국내 K리그 슈팅 데이터를 통해 학습되어 K리그 내 전략적인 상황들에 대한 특화된 xG를 도출하며, 이를 웹을 통해 K리그 내 선수 개개인에 대해서 시계열, 상대 팀, 슈팅 위치별 그래프로 시각화하여 제공하는 시스템을 구축함으로써 K리그를 기준으로 선수에 대한 평가 및 경기 운영에 기여할 수 있는 기대 득점 분석 서비스를 제공한다.