• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1207-1217
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• 2022

Vegetation indices using the reflectance of selected wavelength, associating with the monitoring purpose such as identifying the progress of crop growth, on the vegetation canopy surface is widely used in the digital agriculture technology. However, the surface reflectance anisotropy can distort the true value of vegetation index related to the condition of surface, even though the surface property be unchanged. That causes difficulty to observe accurately crop growth on the monitoring system. In this study, a simple type goniometer was designed to measure the reflectance from the anisotropic surface according to various zeniths and azimuths of sun and viewing sensor in the field. On the tarp like as Lambertian surface, the reflectance of Blue, Green, Red, Near-Infrared band was similar to the tarps' reflectance properties. However, the reflectance was slightly overestimated in the cloudy day. The relative difference values of vegetation indices on grass were overestimated for the forward viewing and underestimated for the backward viewing. In addition, enhanced vegetation index (EVI) showed less sensitive according to the positions of sun and sensor viewing. Field observation with a goniometer will be helpful to understand the anisotropy characteristics on the vegetation surface.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.367-372
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• 2022

With the recent advent of the New Normal era, realistic technologies and non-contact technologies are receiving social attention. However, the hair styling field focuses on the direction of the hair itself, individual movements, and modeling, focusing on hair simulation. In order to create an improved practice environment and demand of the times, this study proposed a non-contact hair styling VR system. In the theoretical review, we studied the existing cases of hair cut research. Existing haircut-related research tend to be mainly focused on force-based feedback. Research on the interactive haircut work in the virtual environment as addressed in this paper has not been done yet. VR controllers capable of finger tracking the movements necessary for beauty enable selection, cutting, and rotation of beauty tools, and built a non-contact collaboration environment. As a result, we conducted two experiments for interactive hair cutting in VR. First, it is a haircut operation for synchronization using finger tracking and holding hook animation. We made position correction for accurate motion. Second, it is a real-time interactive cutting operation in a multi-user virtual collaboration environment. This made it possible for instructors and learners to communicate with each other through VR HMD built-in microphones and Photon Voice in non-contact situations.

• Trans-
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• v.12
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• pp.81-106
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• 2022

The possibility of metaverse system to be a catalyst for hyper-connected society will be dependent on the speed of connected technological development and its social utilization in the same manner as AI technology. Putting these technical realization processes in brackets, this paper focus on some philosophical-political issues in connection with cognitive-ecological changes in the future cinema which will be influenced by the complexive techno-socio couples of accelerated development of metaverse system. Generally speaking, essence of metaverse system seems to be the degree of immersion by technical accuracy, but is not true. In perspective of cognitive-ecology, flow degree of a picture or photograph is relied not on 'accuracy of representation' but on its message's contextual link-up. In this aspect, real potentiality of metaverse system shall be understood in the context of cognitive-ecological changes of human brain's multi-intelligence networking abilities(intersection of augmentation-simulation and outside-inside) which will be activated in the new structure of natural-social-technological coupling of metaverse system. These cognitive-ecological potentialities have been partially actualized in the cinematic process of tripod mimesis for the longest time, [real contradiction/conflicts (Mimesis-1) -->fictional solutions of cinema (Mimesis-2) --> selective interpretation of spectator's wish fulfillment (Mimesis-3) --> real change (Mimesis-1')]. Therefore metaverse's real potentiality must be considered to be dependent on the possibility of deepening and extending of cinematic circulation between real seperation/problems and ideal connection/solutions. In this context, advanced metaverse system can be compared as a modern technical version of ideal circulation of physics and metaphysics

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.333-343
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• 2022

For water resource management, the design flood is calculated using the flood frequency analysis technique and the rainfall runoff model. The method by design flood frequency analysis calculates the stochastic design flood by directly analyzing the actual discharge data and is theoretically evaluated as the most accurate method. Actual discharge data frequency analysis of the measured flow was limited due to data limitations in the existing flood flow analysis. In this study, design flood frequency analysis was performed using the measured flow data stably secured through the water level-discharge relationship curve formula. For the frequency analysis of design flood, the parameters were calculated by applying the bayesian inference, and the uncertainty of flood volume by frequency was quantified. It was confirmed that the result of calculating the design flood was close to that calculated by the rainfall-runoff model by applying long-term rainfall data. It is judged that hydrological analysis can be done from various perspectives by using long-term actual flow data through hydrological survey.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.3
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• pp.127-137
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• 2022

Zirconia is fabricated through various processes. Each element in fabricating process can affect the physical properties of the definitive prosthesis. In particular, both the milling process and the sintering process can affect the final integrity of the zirconia prosthesis. Most of the milling machines adopt the ultra-precision 5-axis machining method, and the results vary depending on which milling method was used and how the milling equipment was managed. Milling blocks are selected according to cutting efficiency and aesthetic reproducibility. The sintering method can affect the grain growth and optical properties, and an accurate evaluation can be made only with additional research on the recent speed sintering procedure. Not only the sintering temperature but also the temperature holding time can affect the quality of definitive prosthesis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.251-260
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• 2022

Although the number of trees affected by pine wilt disease is decreasing, the affected area is expanding across the country. Recently, with the development of deep learning technology, it is being rapidly applied to the detection study of pine wilt nematodes and dead trees. The purpose of this study is to efficiently acquire deep learning training data and acquire accurate true values to further improve the detection ability of U-Net models through learning. To achieve this purpose, by using a filtering method applying a step-by-step deep learning algorithm the ambiguous analysis basis of the deep learning model is minimized, enabling efficient analysis and judgment. As a result of the analysis the U-Net model using the true values analyzed by period in the detection and performance improvement of dead pine trees of wilt nematode using the U-Net algorithm had a recall rate of -0.5%p than the U-Net model using the previously provided true values, precision was 7.6%p and F-1 score was 4.1%p. In the future, it is judged that there is a possibility to increase the precision of wilt detection by applying various filtering techniques, and it is judged that the drone surveillance method using drone orthographic images and artificial intelligence can be used in the pine wilt nematode disaster prevention project.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.24-35
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• 2022

For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.147-155
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• 2022

In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.316-316
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• 2023

2022년 8월 수도권 이상폭우로 인해 서울 도심지역의 지하시설, 도로, 주택 등에 침수가 발생하면서 인명 및 재산피해가 발생하였으며, 특히 동서로 가로지르는 정체전선으로 좁고 긴 비구름이 집중되면서 국지적으로 피해가 집중되었다. 서울시의 경우 도시화에 따른 불투수지역 증가 및 내수배제 불량에 따른 빗물 역류로 인한 피해가 지속적으로 발생하고 있으며, 최근에는 기후변화에 따른 방재성능목표 강우량을 초과하는 빈도의 이상폭우로 인해 하천범람과 내수배제 불량에 따른 복합적인 원인으로 침수피해 가중되고 있는 실정이다. 또한 서울시의 경우 전체 자연적, 사회적, 경제적, 환경적 요인 등의 지역적 편차가 매우 큰 도시로 지형적인 특성뿐만 아니라 취약시설(병원, 학교 등), 수방시설물(하천, 배수시설, 빗물펌프장 등) 및 방재시설(대피소, 구호소 등) 밀도 등에 따른 침수 취약성 및 위험성 등의 편차가 매우 크기 때문에 지역특성에 대한 피해사례가 다원화 되고 있는 실정이다. 본 연구에서는 30년 이상의 종관기상관측(ASOS)과 서울시 자치구별 20년 이상의 방재기상관측(AWS)자료를 기반으로 CMIP6 SSP(Shared Socioeconomic Pathways, 공통사회 경제경로)시나리오에 따른 극한기후 지수(강수강도, 호우일수, 지속기간, 1일 최대강수량, 95퍼센타일 강수일수 등)에 대한 재현성을 평가하고 공간자기상관분석 등 시공간적인 강우특성에 대한 변화를 전망하였다. 특히 여름철 강우의 경우 자치구별 편차가 크게 나타났고 이를 통해 대도시의 도심지역의 경우 세분화하여 지역의 정확한 강우특성을 파악하는 것이 필요하다는 것을 확인할 수 있었다. 본 연구의 결과는 도심지의 방재성능 초과강우 정의와 기준을 수립하고, 장기적인 수자원 및 도시계획 차원의 대책을 마련하는데 활용될 수 있을 것으로 판단된다. 기후위기에 따른 기록적인 호우(지역별 방재성능을 초과하는 강우)에 따른 재해는 구조적인 대책을 통해 모두 저감할 수 없는 한계가 있다. 하지만 인명피해를 최소화하는 것을 목표로 기후위기에 대한 적응단계로 인식하고 수리·수문학적, 사회경제학적 등 지역특성에 따른 방재성능목표 강우량에 대한 재검토와 더불어 법제도(풍수해보험, 저류조설치 의무화 등), 개인별 재해예방, 취약계층 안전망 확보, 반지하주택 침수안전대책, 재해지도 개선 등 구조적/비구조적인 대책을 통합 수립 및 보완하는 것이 필요한 시점이다.