• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.60-72
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• 2007

In general, the importance of geological information is emphasized not only for national SOC construction, underground space development and energy resources development but also in areas related to environmental disasters such as mine damage, ground subsidence and landslides. Although geological information is highly useful in developing industrial raw materials, national land management and people's welfare, there is no unified governmental institution in charge of collecting and managing geological information in the national level. For this, this paper study: first, to analyze geological demand for common experts; second, to analyze geological demand for public institution; and third, to set priority for geological informatization. In the result of surveying demand for geological information, we need to improve laws and systems for collecting and reporting geology-related materials, making thematic maps, and maintaining and managing geological information we need to establish national strategies and build an integrated system for interoperability of databases and systems. Accordingly, we will guideline on future direction of strategies for the national integration of geological information management system.

• Culinary science and hospitality research
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• v.23 no.2
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• pp.159-168
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• 2017

This study was conducted to compare the food quality of domesticated species. Consumers surveyed for safe food intake and proper culture of food distribution. The results of the comparison study are as follows. Muscle moisture content, protein content, and fat content. K, P, and C showed relatively high values in the muscle of the sea bream. Fe showed low contents. As a result of measuring heavy metal component, Cd was not detected in sea bream and mullet, but $0.01{\pm}0.00mg/kg$ was detected in red mine. Other heavy metals were below the reference value or were not detected. Electrophoresis results showed that the band appeared at in red minefish. In the case of sea bream and swordfish, no distinctive features of the band were shown. In the case of sea bream, there was little difference in food science between the similar fish species and the red sea bream fish, but price was different. An environment should be created for consumers to buy the right ingredients at the price they want. It is necessary to educate consumers about food ingredients immediately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.768-773
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• 2020

In large-scale land development for the rational use and management of national land resources, the use of geospatial information is essential for the efficient management of projects. Recently, drone LiDAR (Light Detection And Ranging) has attracted attention as an effective geospatial information construction technique for large-scale development areas, such as housing site construction and open-pit mines. Drone LiDAR can be classified into a method using SLAM (Simultaneous Localization And Mapping) technology and a GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit) method. On the other hand, there is a lack of analytical research on the application of drone LiDAR or the characteristics of each method. Therefore, in this study, data acquisition, processing, and analysis using SLAM and GNSS/IMU type drone LiDAR were performed, and the characteristics and utilization of each were evaluated. As a result, the height direction accuracy of drone LiDAR was -0.052~0.044m, which satisfies the allowable accuracy of geospatial information for mapping. In addition, the characteristics of each method were presented through a comparison of data acquisition and processing. Geospatial information constructed through drone LiDAR can be used in several ways, such as measuring the distance, area, and inclination. Based on such information, it is possible to evaluate the safety of large-scale development areas, and this method is expected to be utilized in the future.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.5
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• pp.345-350
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• 2012

To investigate the exposure and health risk assessment for the residents near the D-asbestos mine in Chungbuk, Korea. We analyzed asbestos in the 20 ambient air and 23 activity based samples near the mine. The airborne sample results are showed that 8 of 20 samples ranged between 0.0025 to 0.0029 f/cc (fiber per cubic centimeter) and the others were below the detection limit by phase contrast microscopy (PCM). In addition, asbestos fibers were under the detection limit or not being by transmission electron microscopy (TEM). Based on interview and survey targeting the local residents, we made the activity based sampling (ABS) scenarios fit to the conditions of field. At the same time, we calculated the excess lifetime cancer risk (ELCR) of these ABS scenarios according to the ELCR average value and 95% upper confidence limit (UCL). At the case of weed whacking, soil digging and sweeping yard scenario, 95% UCL of ELCR exceeded the $1{\times}10^{-4}$, acceptable risk range for exposure. Based on our study results, it is necessary safety measures such as risk communication, abatement or management of naturally occurring asbestos (NOA).

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• The Korean Journal of Archival Studies
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• no.8
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• pp.137-180
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• 2003

The term 'Business Archives' is not familiar with us in our society. Some cases can be found that materials are collected for publishing the history of a firm on commemoration of some decades of its foundation. However, the appropriate management of these collected materials doesn't seem to be followed in most of companies. The Records and archives management is inevitable in order to maximize the utility of Information and knowledge in the business world. The interest in records management has been grown, especially in the fields of business management and information technology. However, the importance of business archives hasn't been conceived yet. And also no attention has been paid to the business archives as social resources and the responsibility of the society as a whole for their preservation. The company archives doesn't have a long history in Germany although the archives of the nation, the aristocracy, communes and churches have a long tradition. However the company archives of Krupps which was established in 1905, is regarded as the first business archives in the world, It means that Germany has taken a key role to lead the culture of business archives. This paper focuses on the process of the establishment of business archives in Germany and its characteristics. The business archives in Germany can be categorized in three types: company archives, regional business archives and branch archives. It must be noted here that each type of these was generated in the context of the accumulation of the social resources and its effective use. A company archives is established by an individual company for the preservation of and use of the archives that originated in the company. The holdings in the company archives can be used as materials for decision making of policies, reporting, advertising, training of employees etc. They function not only as sources inside the company, but also as raw sources for the scholars, contributing to the study of the social-economic history. Some archives of German companies are known as a center of research. A regional business archives manages materials which originated m commerce chambers, associations and companies in a certain region. There are 6 regional business archives in Germany. They collect business archives which aren't kept in a proper way or are under pressure of damage in the region for which they are responsible. They are also open to the public offering the sources for the study of economic history, social history like company archives, so that they also play a central role as a research center. Branch business archives appeared relatively late in Germany. The first one is established in Bochum in 1969. Its general duties and goals are almost similar with ones of other two types of archives. It has differences in two aspects. One is that the responsibility of the branch business archives covers all the country, while regional business archives collects archives in a particular region. The other is that a branch business archives collects materials from a single industry. For example, the holdings of Bochum archives are related with the mining industry. The mining industry-specialized Bochum archives is run as an organization in combination with a museum, which is called as German mine museum, so that it plays a role as a cultural center with the functions of exhibition and research. The three types of German business archives have their own functions but they are also closely related each other under the German Association of Business Archivists. They are sharing aims to preserve primary materials with historical values in the field of economy and also contribute to keeping the archives as a social resources by having feed back with the public, which leads the archives to be a center of information and research. The German case shows that business archives in a society should be preserved not only for the interest of the companies, but also for the utilities of social resources. It also shows us how business archives could be preserved as a social resource. It is expected that some studies which approach more deeply on this topic will be followed based on the considerations from the German case.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.221-229
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• 2008

The three dimensional model method is widely applied in resource development for feasibility study, mine design, excavation planning and process management by constructing the database of various data in 3 dimensional space. Most of geophysical surveys for the purpose of engineering and resource development are performed in 2 dimensional line survey due to the restriction of the field situation, technical or economical situation and so on. The acquired geophysical data are used as the input for the 2 dimensional inversion under the 2 dimensional assumption. But the geophysical data are affected by 3 dimensional space. Therefore in order to reduce the error caused by 2 dimensional assumption, the 2 dimensional inversion result must be interpreted considering the additional information such as 3 dimensional topography, geological structure, borehole survey etc. The applicability and usability of 3 dimensional modeling method are studied by reviewing the case study to the geophysical data acquired in field of engineering and resource development.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.855-862
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• 2010

The objectives of this study were to analyze vegetation types and stand structures of the red pine (Pinus densiflora) in Kangwon southern region for stable and sustainable forest management. The pine forests in study sites were classified into 4 communities, 2 groups, so total 6 vegetation units. Species with high constance degree were Quercus mongolica, Rhus trichocarpa, Lindera obtusiloba, Lespedeza maximowiczii, Quercus serrata, Spodiopogon sibiricus, Aster scaber and Fraxinus sieboldiana. In the importance value(I.V.) analysis of each layer, P. densiflora showed highly in tree layer while in other layers competitive broad-leaved species such as Quercus spp. were high. P. densiflora also showed large size of DBH, while broad-leaved species distributed middle and small DBH. The annual ring growths of P. densiflora and competitive broadleaved species were variable according to area, site condition, tree year and species, it is considered that appropriate silvicultual practice methods should be employed to remove rival broad-leaved species for maintenance of sustainable red pine forests considering the characteristics of each stand.

• Economic and Environmental Geology
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• v.42 no.3
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• pp.273-282
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• 2009

To render more valuable information, a spatial database is being constructed from digitalized maps in the geographic areas. Transferring file-based maps into a spatial database, facilitates the integration of larger databases and information retrieval using database functions. Geological mapping is the graphical interpretation results of the geological phenomenon by geological surveyors, which is different from other thematic maps produced quantitatively. These features make it difficult to construct geologic databases needing geologic interpretation about various meanings. For those reasons, several organizations in the USA and Australia are suggesting the data model for the database construction. But, it is hard to adapt to a domestic environment because of the representation differences of geological phenomenon. This paper suggests the data model adaptive in domestic environment analyzing 1:50,000 scales of geologic maps and more detailed mine geologic maps. The suggested model is a logical data model for the ArcGIS GeoDatabase. Using the model it can be efficiently applicable in the 1:50,000 scales of geological maps. It is expected that the geologic data model suggested in this paper can be used for integrated use and efficient management of geologic maps.