• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.99-108
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• 2008

To extend our detailed knowledge for the Hwasan caldera, we carried out magnetotelluric (MT) survey, which is pretty sensitive to electrical property variation in both horizontal and vertical direction of subsurface, across the Hwasan caldera with the direction of EW. The 2-D inversion results of observed MT data lead to following conclusions. Firstly, the depth of the basin basement inferred by the MT inversion results matches well with that suggested by previous potential studies, but the basement resistivity seems fairly low when compared to that of general case. This feature might be related with the large-scaled, highly conductive layer beneath the Euisung Sub-basin suggested by the previous MT study. Secondly, the high resistivity zones reaching to 4000 $\Omega{\cdot}m$ are imaged around two external ring fault boundaries. These zones are thought of as the response of the rhyolitic dykes intruding along the ring fault, and in the previous gravity data correspond to relatively high density anomalies. Thirdly, low resistivity zone reaching to 200 $\Omega{\cdot}m$ is detected around a depth of 1km beneath the central part of the caldera, which has not been yet reported in korean geophysical literatures. If we take account of the evolution model of the Hwasan caldera, this zone is regarded as the past sedimentary layer that subsided during the period of forming external ring fault system. In addition, the relatively low density anomaly observed in the central part of the caldera may be attributed to this sedimentary layer.

• Journal of Korea Technology Innovation Society
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• v.12 no.4
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• pp.788-818
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• 2009

Renewable energy refers to solar energy, biomass energy, hydrogen energy, wind power, fuel cell, coal liquefaction and vaporization, marine energy, waste energy, and liquidity fuel made out of byproduct of geothermal heat, hydrogen and coal; it excludes energy based on coal, oil, nuclear energy and natural gas. Developed countries have recognized the importance of these energies and thus have set the mid to long term plans to develop and commercialize the technology and supported them with drastic political and financial measures. Considering the growing recognition to the field, it is necessary to analysis up-to-now achievement of the government's related projects, in the standards of type of renewable energy, management of sectional goals, and its commercialization. Korean government is chiefly following suit the USA and British policies of developing and distributing renewable energy. However, unlike Japan which is in the lead role in solar rays industry, it still lacks in state-directed support, participation of enterprises and social recognition. The research regarding renewable energy has mainly examinedthe state of supply of each technology and suitability of specific region for applying the technology. The evaluation shows that the research has been focused on supply and demand of renewable as well as general energy and solution for the enhancement of supply capacity in certain area. However, in-depth study for commercialization and the increase of capacity in industry followed by development of the technology is still inadequate. 'Cost-benefit model for each energy source' is used in analysis of technology development of renewable energy and quantitative and macro economical effects of its commercialization in order to foresee following expand in related industries and increase in added value. First, Investment on the renewable energy technology development is in direct proportion both to the product and growth, but product shows slightly higher index under the same amount of R&D investment than growth. It indicates that advance in technology greatly influences the final product, the energy growth. Moreover, while R&D investment on renewable energy product as well as the government funds included in the investment have proportionate influence on the renewable energy growth, private investment in the total amount invested has reciprocal influence. This statistic shows that research and development is mainly driven by government funds rather than private investment. Finally, while R&D investment on renewable energy growth affects proportionately, government funds and private investment shows no direct relations, which indicates that the effects of research and development on renewable energy do not affect government funds or private investment. All of the results signify that although it is important to have government policy in technology development and commercialization, private investment and active participation of enterprises are the key to the success in the industry.

• The Korean Journal of Petroleum Geology
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• v.2 no.2 s.3
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• pp.51-57
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• 1994

Analysis of the aeromagnetic data aquired by US Navy in the year 1969 permits us to predict a new sedimentary basin, Heugsan Basin, south of the known Gunsan Basin in Block Ⅱ. The basin appears to consist of three sub-basins trending NNW-SSE. The results of our analysis provide not only an independent assessment of the Gunsan Basin, but also new important information on the tectonic origin and mechanism for the two basins as well as for the entire region. The basin forming tectonic style is interpreted as rhombochasm associated with double overstepped left-lateral wrench faults. From the magnetic evidence, a few NE-SW trending major onshore faults are extended to the study area. We also interpreted the nature of the faults to be left-lateral wrenches. This new gross structural style is consistent with the results of recent Yeongdong Basin analysis by Lee. The senses of fault movement are also supported by the paleomagnetic evidence that the Philippine Sea had experienced an 80-degree clockwise rotation since the Eocene. Based on a 2 $\frac{1}{2}$ model study the probable maximum thickness of the sediments in the Gunsan Basin is approximately 7500 meters. We believe that the new Heugsan Basin was left unidentified because a high velocity layer may be overlying the basin. Because the overall structural configuration of the Heugsan Basin appears to be favorable for hydrocarbon accumulation, a detailed airborne magnetic survey is recommended in the area in order to verify the magnetic expression of this thick basin. A detailed subsequent marine gravity survey is also recommended in order to delineate the sedimentary section and to acquire supplemental data to the magnetic method only if an overlying high velocity layer is confirmed. Otherwise a high energy source seismic survey may be more effective.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.147-152
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• 2015

Nitrogen (N) loading from domestic, agricultural and industrial sources can lead to excessive growth of macrophytes or phytoplankton in aquatic environment. Many studies have used nitrogen stable isotope ratios to identify anthropogenic nitrogen in aquatic systems as a useful method for studying nitrogen cycle. In this study to evaluate the precision and accuracy of Kjeldahl processes, two reference materials (IAEA-NO-3, N-1) were analyzed repeatedly. Measured the ${\delta}^{15}N-NO_3$ and ${\delta}^{15}N-NH_4$ values of IAEA-NO-3 and IAEA-N-1 were $4.7{\pm}0.2$‰ and $0.4{\pm}0.3$‰, respectively, which are within recommended values of analytical uncertainties. Also, we investigated spatial patterns of ${\delta}^{15}N-NO_3$ and ${\delta}^{15}N-NH_4$ in effluent plumes from a waste water treatment plant in Han River, Korea. ${\delta}^{15}N-NO_3$ and ${\delta}^{15}N-NH_4$ values are enriched at downstream areas of water treatment plant suggesting that dissolved nitrogen in effluent plumes should be one of the main N sources in those areas. The current study clarifies the reliability of Kjeldahl analytical method and the usefulness of stable isotopic techniques to trace the contamination source of dissolved nitrogen such as nitrate and ammonia.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.