• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.

• Journal of Technology Innovation
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• v.29 no.3
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• pp.1-31
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• 2021

With the growing importance of technology innovation as a key factor for firms' competitive advantage, 'innovation persistence' became also an important research subject. 'Innovation Persistence' is a concept that indicates whether or not firms' innovation activity or performance continues. However, the data used for innovation studies are carried out as cross-sectional surveys in most countries. For this reason, studies dealing with longitudinal aspect of innovation persistence are rare. In particular, there is almost no research on innovation persistence using Korean innovation survey data. This study reviews the concepts and characteristics of innovation persistence based on extant literature, and perform an empirical analysis on the status and features of Korean firms' technology innovation persistence. Based on the data of the Korean Innovation Survey (KIS) conducted every other year from 2012 to 2018, panel data on 3,379 firms which observed multiple times are constructed. As a result, only part of the firms with persistent innovation were observed (for innovation performance 10~12%, for innovation activity 15~17%), and it was found that the persistence of non-innovation was remarkable(about 52~57%). And it was confirmed that the persistence of innovation activities is stronger than that of innovation performance. Besides, some features by sub-types of innovation appeared. Product innovation showed higher persistence than process innovation, and internal R&D also showed higher persistence than joint/external R&D. As a result of additional logit analysis to identify factors, it was found that radical or gradual product innovation is the most influential factor in persisting innovation in the next period. Since the sample selection bias due to a limitations of raw data might exist in the panel data constructed in this study, it should be noted that faulty generalization of the results are not allowed. Nevertheless, this is the first study to examine the technology innovation persistence targeting Korean firms and is expected to be a starting point for follow-up studies. It is anticipated that advanced research results will be drawn through the establishment of official panel data and improved methodologies.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1559-1572
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• 2021

The response of vegetation under the crop stress condition was evaluated using structural, biochemical, and physiological vegetation indices based on unmanned aerial vehicle (UAV) images and field-spectrometer data. A high concentration of herbicide was sprayed at the different growth stages of garlic to process crop stress, the above ground dry matter of garlic at experimental area (EA) decreased about 46.2~84.5% compared to that at control area. The structural vegetation indices clearly responded to these crop damages. Spectral reflectance at near-infrared wavelength consistently decreased at EA. Most biochemical vegetation indices reflected the crop stress conditions, but the meaning of physiological vegetation indices is not clear due to the effect of vinyl mulching. The difference of the decreasing ratio of vegetation indices after the herbicide spray was 2.3% averagely in the case of structural vegetation indices and 1.3~4.1% in the case of normalization-based vegetation indices. These results meant that appropriate vegetation indices should be utilized depending on the types of crop stress and the cultivation environment and the normalization-based vegetation indices measured from the different spatial scale has the minimized difference.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1243-1254
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• 2021

For water resources operation or agricultural water management, it is important to accurately predict evapotranspiration for a long-term future over a seasonal or monthly basis. In this study, reference evapotranspiration forecast (up to 12 months in advance) was performed using statistically predicted monthly temperatures and temperature-based Hamon method for the Han River basin. First, the daily maximum and minimum temperature data for 15 meterological stations in the basin were derived by spatial-temporal downscaling the monthly temperature forecasts. The results of goodness-of-fit test for the downscaled temperature data at each site showed that the percent bias (PBIAS) ranged from 1.3 to 6.9%, the ratio of the root mean square error to the standard deviation of the observations (RSR) ranged from 0.22 to 0.27, the Nash-Sutcliffe efficiency (NSE) ranged from 0.93 to 0.95, and the Pearson correlation coefficient (r) ranged from 0.97 to 0.98 for the monthly average daily maximum temperature. And for the monthly average daily minimum temperature, PBIAS was 7.8 to 44.7%, RSR was 0.21 to 0.25, NSE was 0.94 to 0.96, and r was 0.98 to 0.99. The difference by site was not large, and the downscaled results were similar to the observations. In the results of comparing the forecasted reference evapotranspiration calculated using the downscaled data with the observed values for the entire region, PBIAS was 2.2 to 5.4%, RSR was 0.21 to 0.28, NSE was 0.92 to 0.96, and r was 0.96 to 0.98, indicating a very high fit. Due to the characteristics of the statistical models and uncertainty in the downscaling process, the predicted reference evapotranspiration may slightly deviate from the observed value in some periods when temperatures completely different from the past are observed. However, considering that it is a forecast result for the future period, it will be sufficiently useful as information for the evaluation or operation of water resources in the future.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.232-245
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• 2021

The present study is about a brand development strategy that utilizes Korean traditional patterns. The global culturenomics phenomenon confirms the value of the cultural aspects of design when a national brand is established. People succeed with their unique aesthetic sense and reinterpret it in a modern view, and this design acts as today's national brands. In this way, people used traditional patterns and original designs, along with regional characteristics and formative style, in developing their designs. However, due to recent changes in the global environment, modern people live in an "untact" world, and consumption culture shifted toward online marketing. In this environment, where one is isolated from social activities, there needs to be a strong image that can dramatically change the mood of one's home. I would like to re-examine the Dan-Chung pattern, whose painting depends on the aesthetic characteristics of architecture to protect the wooden members of the framework in traditional architecture. The pattern and color of Dan-Chung, coated in traditional architecture, differs by the type of construction used, which includes a palace, a Buddhist temple, and a Confucianism Dan Chung. The Geummoon pattern contains aesthetic factors to add solemnity to the Main Buddhist Halls, which contain Buddha. This is a new medium that continues the current traditions instead of remaining in the past. Among different Dan Chung patterns, Geummoon has magnificent decoration consisting of the highest grade materials and unique composition; therefore, it is suitable to be reinterpreted in modern terms. The same pattern can be interpreted in different ways with different colors, so there is a great aesthetic impression in the Geummoon pattern. The value of preservation for exploration and theoretical study of the traditional pattern is important, but recreating the pattern into modern formative art can present a new angle of view and national brand, bearing pride in our cultural assets. The study used multidimensional molding methods for realistic presentation after going through the two-dimensional design process. The significant value of Korean molding beauty which hangs onto the past will play a crucial role in establishing our national brand.

• Korean Journal of Heritage: History & Science
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• v.54 no.4
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• pp.174-191
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• 2021

Gangdo (江都), a reproduction of Gaegyeong, was the capital of Goryeo for 39 years. However, due to the urgent wartime situation of the Mongol invasion and the geographical features of Ganghwa Island, the castle system and palace layout were somewhat different from those of Gaegyeong. Gangdo's castle can be understood as a triple castle system consisting of outer castle, middle castle, and inner castle. First, the outer castle was the first to be completed, and it was built at the forefront to prevent the Mongol army from invading in the first place. It is presumed that the section was between Huamdon and Hwadodon in the outer castle during the Joseon Dynasty. The middle castle can be seen as the present 'Middle Castle', a castle built of earth on the outskirts of the Ganghwa-mountain Castle. Considering the sophistication and robustness of the construction method confirmed in the archaeological research, this castle is thought to have been built under a meticulous plan. In other words, as the capital city, it was completed 'at last' as recorded in the Koryo History, after a long 18-year construction process to protect palaces, government offices, and private houses. The inner castle was a castle with the character of a palace. This corresponds to the Old Castle of Ganghwabu (江華府) during the Joseon Dynasty, and it almost coincided with the scale of the composition of Gaegyeong's palace castle. It was a complex functional space, featuring the integration of the palace and the imperial castle, where the main government offices and ancillary facilities, including the palace, were located. Based on the documentary record that these palaces were similar to Gaegyeong's palace, the palace map was overlapped with that of Gaegyeong. The central axis of the building from Seungpyeongmun (昇平門) to Seongyeongjeon (宣慶殿) coincided with Kim Sangyongsunjeol Monument in Ganghwa- Goryeo Palace. Therefore, it seems that the palace of Gangdo had the same basic structure as that of Gaegyeong. However, the inner palace and annexed buildings must have been arranged in consideration of the topographical conditions of Ganghwa, and this is estimated to be the Gunggol area in Gwancheong-ri.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.

• Journal of Marine Life Science
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• v.5 no.2
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• pp.35-42
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• 2020

17β-estradiol (E₂) is a natural hormone secreted by ovary, and continuously discharged from household and livestock wastewater into aquatic environment. Due to its strong estrogenic activity, it has adverse effects on development and reproduction in crustacean as an endocrine disrupting chemical. Although ecdysteroid signaling pathway play a key role in development in crustacean, little information on transcriptional modulation of ecdysteroid-related genes in response to E₂ is available in small crustacean. Here, we investigated the acute toxicity of E₂ to obtain 24-h LC_x values in the brackish water flea Diaphanosoma celebensis. Time-dependent expression patterns of seven ecdysteroid pathway - related genes (CYP314a1, EcRA, EcRB, USP, ERR, Vtg, VtgR) were further examined using quantitative real time reverse transcriptase polymerase chain reaction (qRT-PCR). As results, 24-h LC₅₀ and LC₁₀ values were 9.581 mg/l and 4.842 mg/l, respectively. The mRNA expression of CYP314a1, EcRA, USP, VtgR was significantly up-regulated at 12 or 24 h after exposure to E₂. These findings indicate that E₂ can affect their molting and reproduction by modulating the expression of ecdysteroid pathway - related in D. celebensis. This study will be useful for better understanding of molecular mode of action of endocrine disrupting chemicals on molting process in small crustacean.