• Tunnel and Underground Space
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• v.29 no.1
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• pp.1-11
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• 2019

This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

• The Korean Journal of Mycology
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• v.37 no.2
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• pp.161-166
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• 2009

The purpose of the present study is to develop a simple, fast and sensitive LC/MS method for simultaneous separation and the determination of an active component in the oriental medicinal mushroom Cordyceps militaris. Based on this work, the contents of cordycepin in Cordyceps militaris fruiting cultivated on various media were determined and compared. And also, the nutritional components such as minerals and vitamins were determined in order to provide useful information to consumer as a food material. The analysis methods of nutritional components were chosen on the basis of AOAC. The optimum separation for cordycepin was achieved using a solvent gradient consisting of the mixture of 0.1% formic acid in methanol (solvent B) in a background of 0.1% formic acid in water (solvent A) as a mobile phase and a 3.0${\times}$150 Waters XTera column. Selective ion monitoring (SIR) mode ([M+H]+ at m/z 252) was used for quantitative analysis of cordycepin. The cultivated Cordyceps militaris on various media contained 1~14 /g of cordycepin, 0.65~1.08% of thiamine, 0.86~7.17% of riboflavin, and 3.01~5.26% of niacin. The content of mineral components varied on categories, especially contained 500~3500% of potassium as a major mineral. Cordycepin, niacin and potassium were found much higher in the fruiting cultivated with soy power media (gold 10) than other media.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.564-575
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• 2018

Recently, the possibility of promoting inter-Korean economic cooperation is increasing because the tension between South and North Korea is being reduced. Consequently, the interest in North Korea's mine development projects is growing as one of the aspects of inter-Korean economic cooperation. In the promotion of cooperation in mining development, mine hazard risk management should be considered. However, there is a lack of information pertaining to mine hazards in North Korea. To this end, this study was performed to determine the status of mining-related hazards in 12 mines in North Korea by using the image analysis feature of Google Earth. From the results obtained, we observed some mining-related hazards such as tailing dam failures, yellow boy phenomenon, and land subsidence.

• Economic and Environmental Geology
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• v.57 no.1
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• pp.51-71
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• 2024

Seismic exploration is one of the widely used geophysical exploration methods with various applications such as resource development, geotechnical investigation, and subsurface monitoring. It is essential for interpreting the geological characteristics of subsurface by providing accurate images of stratum structures. Typically, geological features are interpreted by visually analyzing seismic sections. However, recently, quantitative analysis of seismic data has been extensively researched to accurately extract and interpret target geological features. Seismic attribute analysis can provide quantitative information for geological interpretation based on seismic data. Therefore, it is widely used in various fields, including the analysis of oil and gas reservoirs, investigation of fault and fracture, and assessment of shallow gas distributions. However, seismic attribute analysis is sensitive to noise within the seismic data, thus additional noise attenuation is required to enhance the accuracy of the seismic attribute analysis. In this study, four kinds of seismic noise attenuation methods are applied and compared to mitigate random noise of poststack seismic data and enhance the attribute analysis results. FX deconvolution, DSMF, Noise2Noise, and DnCNN are applied to the Youngil Bay high-resolution seismic data to remove seismic random noise. Energy, sweetness, and similarity attributes are calculated from noise-removed seismic data. Subsequently, the characteristics of each noise attenuation method, noise removal results, and seismic attribute analysis results are qualitatively and quantitatively analyzed. Based on the advantages and disadvantages of each noise attenuation method and the characteristics of each seismic attribute analysis, we propose a suitable noise attenuation method to improve the result of seismic attribute analysis.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.298-301
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• 2004

The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.55-66
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• 2007

There has been increasing concerns regarding marine mineral resources as the land energy resources has been depleting from worldwide energy crisis. Also, all the coastal countries around the world are getting into the high competition as EEZ implemented to widen each country's marine autonomy. Especially, the adoption of EEZ in UN's marine regulation agreement at the January of 1996 has aggravated conflicts among coastal countries and eventually resulted in critical agenda to determine the boundaries of EEZ among such countries. It is imperative for us to have negotiation with neighboring countries to determine the boundaries of EEZ. For the preparation of such negotiation, it is essential to have data such as mineral distribution, deep-sea geology, related agreement and marine laws, etc. Therefore, this study mainly concentrates on analyzing existing data of resources exploration and establishing standards for each type of data and manipulating data based on such standards, thereby building a database for more efficient management of EEZ data from marine resources survey. MRIS has also been developed to diversely analyze and visualize graphic and attribute data considering data usage and inter-relationship in the database. This system can provide various spatial analysis and spatial searching techniques to enable easier comparison of cost-benefit analysis and data provision of any area in EEZ thereby facilitating major policy making. In addition, the system can support sustainable management of marine resources of EEZ regions and data supply for systematic management of national marine resources. Furthermore, this will be very useful for negotiating with neighboring countries to determine EEZ boundaries to lead more favorable results.

• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.137-144
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• 2005

In this study, we offered the results of geophysical and geochemical survey on the municipal waste disposal area to delineate the size and extent of leachate contamination. Preliminary to intensive geochemical investigation, we performed two geophysical methods to characterize the survey area. Electromagnetic (EM) and magnetic method were used far site investigation. From the EM method, we can get the information of soil conductivity directly related to the leachate of the contaminations and from magnetic anomalies we can find the boundary of landfill which is not identified on the surface due to soil capping. The results of geophysical survey were well matched to those of geochemical method carried out inside and near the landfill. Electric conductivity (EC) of the groundwater sampled from low resistivity anomaly region of EM result was higher than background value and the border estimated from the magnetic survey showed good agreement with that estimated from the soil gas detection survey.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.99-106
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• 2012

The purpose of this study was to determine the evaluation parameters' osteoporosis predictability in accordance with measuring regions by analyzing the correlations between bone mineral density and trabecular patterns derived from different measuring regions. Experimental subjects were a total of 40 female patients after menopause aged over 40 years, and were classified into 20 control and 20 osteoporotic groups according to the T-score. Bone mineral density was measured on femoral neck, trochanter and ward's triangle by DEXA(Dual Energy X-ray Absorptiometry). We designated ROI(Region of Interest) with $50{\times}50$ pixel size on each measuring regions, and extracted trabecular patterns by using existing image processing method. We also selected a total of eight evaluation parameters that are categorized into structural(mean gray level, area, perimeter, thickness and terminal distance), skeletonized parameters(number, length) and fractal dimension. As a result, it was observed that area, perimeter, thickness, terminal distance, number, length and fractal dimension reflected the bone mineral density with high statistical validity(p<0.003). We also confirmed that the evaluation parameters could predict the osteoporosis more efficiently.

• 한국지구물리탐사학회:학술대회논문집
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• 2001.09a
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• pp.122-140
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• 2001

We have applied the geophysical survey, mainly electric and electromagnetic (EM) methods, to a test site contaminated by hydrocarbon waste disposal and local spill. The multi-frequency, moving source & receiver EM survey along with ground penetrating radar (GPR) showed a fairly good performance in detection of buried metal pipes and objects. Magnetic survey measuring vertical and horizontal gradients were so sensitive to the small metallic objects spread over the surface that it's hard to discriminate the buried pipe. We chose electrical resistivity, EM and GPR survey to examine the soil contamination. Depth slices of resistivity distribution as the results of the inversion of resistivity and EM data coincided each other and closely matched the contaminated area determined by chemical analysis of the soil samples. GPR images did not show the reflection events related with contamination plume since there are no distinct spill in this site. We inferred the contamination using the penetration depth of the GPR energy, which could be used as auxiliary information to the resistivity and EM results. We summarized the applicability of each survey methods based on this results and proposed a desirable survey scheme for the determination of hydrocarbon contaminated site.