• Title/Summary/Keyword: 평균 모델

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Analysis of the Contribution of Biomass Burning Emissions in East Asia to the PM10 and Radiation Energy Budget in Korea (동아시아의 생체연소 배출물에 대한 한국의 미세먼지 기여도 및 복사 에너지 수지 분석)

  • Lee, Ji-Hee;Cho, Jae-Hee;Kim, Hak-Sung
    • Journal of the Korean earth science society
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    • v.43 no.2
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    • pp.265-282
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    • 2022
  • This study analyzes the impact of long-range transport of biomass burning emissions from northeastern China on the concentration of particulate matter of diameter less than 10 ㎛ (PM10) in Korea using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Korea was impacted by anthropogenic emissions from eastern China, dust storms from northern China and Mongolia, and biomass burning emissions from northeast China between April 4-and 7, 2020. The contributions of long-range PM10 transport were calculated by separating biomass burning emissions from mixed air pollutants with anthropogenic emissions and dust storms using the zeroing-out method. Further, the radiation energy budget over land and sea around the Korean Peninsula was analyzed according to the distribution of biomass burning emissions. Based on the WRF-Chem simulation during April 5-6, 2020, the contribution of long-range transport of biomass burning emissions was calculated as 60% of the daily PM10 average in Korea. The net heat flux around the Korean Peninsula was in a negative phase due to the influence of the large-scale biomass burning emissions. However, the contribution of biomass burning emissions was analyzed to be <45% during April 7-8, 2020, when the anthropogenic emissions from eastern China were added to biomass burning emissions, and PM10 concentration increased compared with the concentration recorded during April 5-6, 2020 in Korea. Furthermore, the net heat flux around the Korean Peninsula increased to a positive phase with the decreasing influence of biomass burning emissions.

Automatic Drawing and Structural Editing of Road Lane Markings for High-Definition Road Maps (정밀도로지도 제작을 위한 도로 노면선 표시의 자동 도화 및 구조화)

  • Choi, In Ha;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.363-369
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    • 2021
  • High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.

Single Image Super Resolution Based on Residual Dense Channel Attention Block-RecursiveSRNet (잔여 밀집 및 채널 집중 기법을 갖는 재귀적 경량 네트워크 기반의 단일 이미지 초해상도 기법)

  • Woo, Hee-Jo;Sim, Ji-Woo;Kim, Eung-Tae
    • Journal of Broadcast Engineering
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    • v.26 no.4
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    • pp.429-440
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    • 2021
  • With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.

Crossplot Interpretation of Electrical Resistivity and Seismic Velocity Values for Mapping Weak Zones in Levees (제방의 취약구간 파악을 위한 전기비저항과 탄성파속도의 교차출력 해석)

  • Cho, Kyoung-Seo;Kim, Jeong-In;Kim, Jong-Woo;Kim, Ji-Soo
    • The Journal of Engineering Geology
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    • v.31 no.4
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    • pp.507-522
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    • 2021
  • Specific survey objectives often cannot be met using only one geophysical method, as each method's results are influenced by the specific physical properties of subsurface materials. In particular, areas susceptible to geological hazards require investigation using more than one method in order to reduce risks to life and property. Instead of analyzing the results from each method separately, this work develops a four-quadrant criterion for classifying areas of levees as safe or weak. The assessment is based on statistically determined thresholds of seismic velocity (P-wave velocity from seismic refraction and S-wave velocity from multichannel analysis of surface waves) and electrical resistivity. Thresholds are determined by subtracting the standard deviation from the mean during performance testing of this correlation technique applied to model data of four horizontal and inclined fracture zones. Compared with results from the crossplot of resistivity and P-wave velocity, crossplot analysis using resistivity and S-wave velocity data provides more reliable information on the soil type, ground stiffness, and lithological characteristics of the levee system. A loose and sandy zone (represented by low S-wave velocity and high resistivity) falling within the second quadrant is interpreted to be a weak zone. This interpretation is well supported by the N values from standard penetrating test for the central core.

Estimation and Evaluation of Reanalysis Air Temperature based on Mountain Meteorological Observation (산악기상정보 융합 기반 재분석 기온 데이터의 추정 및 검증)

  • Sunghyun, Min;Sukhee, Yoon;Myongsoo, Won;Junghwa, Chun;Keunchang, Jang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.4
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    • pp.244-255
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    • 2022
  • This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.

A CFD Study on Aerodynamic Performances by Geometrical Configuration of Guide Vanes in a Denitrification Facility (탈질 설비 내 안내 깃의 기하학적 형상에 따른 공력 성능에 대한 전산 해석적 연구)

  • Chang-Sik, Lee;Min-Kyu, Kim;Byung-Hee, Ahn;Hee-Taeg, Chung
    • Clean Technology
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    • v.28 no.4
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    • pp.316-322
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    • 2022
  • The flow pattern at the inlet of the catalyst layer in a selective catalytic reduction (SCR) system is one of the key parameters influencing the performance of the denitrification process. In the curved diffusing parts between the ammonia injection grids and the catalyst layers, guide vanes are installed to improve flow uniformity. In the present study, a numerical simulation has been performed to investigate the effect of the geometrical configuration of the guide vanes on the aerodynamic characteristics of a denitrification facility. This application has been made to the existing SCR process in a large-scaled coal-fired power plant. The flow domain to be solved covers the whole region of the flow passages from the exit of the ammonia injection gun to the exit of the catalyst layers. ANSYS-Fluent was used to calculate the three-dimensional steady viscous flow fields with the proper turbulence model fitted to the flow characteristics. The root mean square of velocity and the pressure drop inside the flow passages were chosen as the key performance parameters. Four types of guides vanes were proposed to improve the flow quality compared to the current configuration. The numerical results showed that the type 4 configuration was the most effective at improving the aerodynamic performance in terms of flow uniformity and pressure loss.

Development of Expandable Steel Pipe Piles to Improve Bearing Capacity (지지력 향상을 위한 확장형 강관말뚝에 관한 연구)

  • Kim, Uiseok;Kim, Junghoon;Kim, Jiyoon;Min, Byungchan;Choi, Hangseok
    • Journal of the Korean GEO-environmental Society
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    • v.22 no.12
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    • pp.5-13
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    • 2021
  • Expandable steel pipe piles have been developed to ensure stability and reduce construction costs during underground floor remodeling and extension work. Expandable steel pipe piles are more economical and stable than micropiles. Extensible steel pipe pile is a method of improving the performance of steel pipes by expanding steel pipes underground. In this paper, the changes in buckling strength according to the shape of steel pipes in an extended steel pipe pile were identified, a numerical analysis model was developed to determine the expended part effect of bumps due to steel pipe expansion, and the optimal steel pipe expansion was calculated through material tests. The larger the expansion diameter of the steel pipe and the greater the number of expanded part, the greater the buckling strength. Numerical results showed that the number of expanded part has a greater effect on buckling strength than the expansion rate. When the expansion rate is more than 1.2 times, it can be seen that as the number of expanded part increases, the effect of increasing buckling strength increases significantly. It was also noted that the expanded part effect of the bumps occur significantly when the extension angle is less than 45° and the expansion rate is 1.3 times higher. When the steel pipe is failure, the expanded rate is 20 to 32%, averaging 25.4%. Through the material test, it was analyzed that it is desirable to limit the maximum expansion rate for performing steel pipes to 16%.

Performance Comparison of Reinforcement Learning Algorithms for Futures Scalping (해외선물 스캘핑을 위한 강화학습 알고리즘의 성능비교)

  • Jung, Deuk-Kyo;Lee, Se-Hun;Kang, Jae-Mo
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.697-703
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    • 2022
  • Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.

Innopolis start-up's achievements and challenges over the past 16 years: the comparison before and after the quantitative expansion period (연구소기업 16년의 성과와 과제: 양적 팽창기 전후의 비교를 중심으로)

  • Seongsang Lee
    • Journal of Technology Innovation
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    • v.31 no.2
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    • pp.111-133
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    • 2023
  • Innopolis start-up has become a representative model and path for commercialization of public technology. Along with the quantitative growth of innopolis start-up, the importance of innopolis start-up in national policies and institutional strategies related to public technology commercialization has also increased. However, over the past 16 years, innopolis start-up's establishment and growth have taken place in different ways at different times. This study aims to compare and analyze changes in innopolis start-up over the past 16 years, focusing on comparisons before and after 2014, when the establishment of innopolis start-up began to increase rapidly. Main findings are as follows. First, in the early stage of the quantitative expansion period, policy changes related to innopolis start-up were the main factors for the increase in innopolis start-ups. In addition, the rapid increase in the establishment of innopolis start-up after 2016 was largely influenced by changes in the start-up environment and institutional changes related to innopolis start-up. Second, the time of registration and size of the capital of innopolis start-up had a statistically significant effect on the sales for 3 years after registration. This result shows that with the rapid increase in innopolis start-ups, the need to build a customized support system for innopolis start-ups by size or growth stage has increased.

Development of Verification Method for ADCP (ADCP 유량 측정기기의 검정 방안 개발)

  • Noel Kang;Chi Young Kim;Kyung Min Kang;Yo Han Cho;Chang-Hwan Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.305-305
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    • 2023
  • 수문조사기기 검정은 강수량, 수위, 유량 등과 같은 수문자료를 관측하는 수문조사기기가 대상지역의 수문상황을 정확하게 관측하는지를 검사하는 일련의 과정으로 「수자원의 조사 계획 및 관리에 관한 법률」 제12조에 법적 기반을 두고 있다. 검정 대상은 강수량, 수위, 유속, 유사량, 토양수분량, 증발산량, 증발량 측정기기 총 7종이며, 환경부장관으로부터 한강홍수통제소가 검정업무를 위임받고, 한국건설기술연구원과 한국수자원조사기술원이 위탁받아 운영중에 있다. 최근에는 증발산량, 토양수분량 및 유량 측정기기기 등이 첨단화되어 기존 검정 방식에 대한보완 및 신설에 대한 요구가 증가하고 있다. 특히, 유량 측정시 기존에 사용하였던 회전식 유속계는 ADCP(Acoustic Doppler Current Profiler) 유량측정기기로 대체되어 활용률이 2013년 24%에서2021년 67%로 약 2.8배 급격히 증가하였다. 하지만 수문조사기기 검정 관련 고시 내 ADCP에 대한검사방법 및 허용오차 등의 규정이 부재하여 수문조사기기의 검정 공백이 발생하는 등의 문제가 존재하고 있다. 이에 본 연구에서는 ADCP 운영 및 기술 현황, 현행 법령, 국외 사례 등을 검토하여 ADCP 유량측정기기의 검사방법 및 허용오차에 대한 방안을 제시하고자 한다. ADCP 검사방법은 총 5단계로 외관검사, 자가진단 검사, 온도센서 검사, 수심측정 검사, 유량비교측정 검사에 따라 검정을 실시한다. 첫 번째 외관검사시에는 기기 외관과 센서 등 물리적 손상을 점검하고, 두 번째 자가진단 검사에서는 센서 변환 매트릭스 값, 수신부 센서 테스트, RAM/ROM 테스트, 통신 테스트 등에 관한 정상값 산출 여부를 확인한다. 세 번째 온도센서 검사에서는 검증용 온도센서를 이용한 값과 ADCP에 부착된 온도센서 값과 차이를 확인하고 ±2℃초과시 재검사 또는 적절한 조치를 취한 후 다음 단계의 검사를 진행한다. 네 번째 수심측정 검사에서는 수조 내 수심 측정을 확인하여 실제 수심과의 오차를 확인하고 ±1% 초과시 재검사 또는 적절한 조치 후 다음 검사를 실시한다. 유량비교 측정검사에서는 각 기기 간의 평균유량의 상대오차를 평가하는 것으로 ±5%미만에는 합격, ±5이상 ±10%미만에서는 재검사, ±10%이상에서는 공장수리를 권고하도록 하고, 1~5 단계의 검사를 통과한 기기를 대상으로 인증서를 발급하도록 한다. 유량비교 측정검사시에는 매년 ADCP를 사용하는 일반기업 및 공공기관 등이 모여 ADCP의 성능을 상호간 비교하는 'ADCP 기술협력 워크숍'을 확장하여 실시할 수 있다. 각 검사 단계의 허용오차는 USGS 또는 제조사 기준과 2022년 ADCP 기술협력 워크숍 성능검사 분석 결과를 토대로 하였다. 본 ADCP 검정 방안은 향후 ADCP 모델별로 단계별 시범 검토를 통해 세부사항에 대한 제시가 필요하며, 온도센서 검사, 수심측정 검사, 유량 비교측정검사에 대한 허용오차에 대한 타당성에대한 검증 및 검토가 이루어져야 할 것으로 사료된다.

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