• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.363-368
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• 2003

We have successfully developed a more effective algorithm to extract the lineament in the area covered by wide alluvial deposits characterized by a relatively narrow range of brightness in the Landsat TM image, while the currently used algorithm is limited to the mountainous areas. In the new algorithm, flat areas mainly consisting of alluvial deposits were selected using the Local Enhancement from the Digital Elevation Model (DEM). The aspect values were obtained by 3${\times}$3 moving windowing of Zevenbergen & Thorno's Method, and then the slopes of the study area were determined using the aspect values. After the lineament factors in the alluvial deposits were revealed by comparing the threshold values, the first rank lineament under the alluvial deposits were extracted using the Hough transform In order to extract the final lineament, the lowest points under the alluvial deposits in a given topographic section perpendicular to the first rank lineament were determined through the spline interpolation, and then the final lineament were chosen through Hough transform using the lowest points. The algorithm developed in this study enables us to observe a clearer lineament in the areas covered by much larger alluvial deposits compared with the results extracted using the conventional existing algorithm. There exists, however, some differences between the first rank lineament, obtained using the aspect and the slope, and the final lineament. This study shows that the new algorithm more effectively extracts the lineament in the area covered with wide alluvlal deposits than in the areas of converging slope, areas with narrow alluvial deposits or valleys.

• Journal of the Korean earth science society
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• v.28 no.2
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• pp.187-201
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• 2007

The first magnetotelluric (MT) transect across the Korean Peninsula was obtained traversing from the East Sea shoreline to the Yellow Sea shoreline. The MT survey profile was designed perpendicular to the strike of the principal geologic structure of the Korean Peninsula $(N30^{\circ}E)$, so-called 'China direction'. MT data were achieved at 50 sites with spacings of $3{\sim}8km$ along the 240 km survey line. The impedance responses are divided into four subsets reflecting typical geological units: the Kyonggi Massif, the Okchon Belt, the western part of the Kyongsang Basin, and the eastern part of the Kyongsang Basin. In the western part of the Kyongsang Basin, the thickness of the sedimentary layer is estimated to be about 3 km to 8 km and its resistivity is a few hundred ohm-m. A highly conductive layer with a resistivity of 1 to 30 ohm-m was detected beneath the sedimentary layer. The MT data at the Okchon Belt show peculiar responses with phase exceeding $90^{\circ}$. This feature may be explained by an electrically anisotropic structure which is composed of a narrow anisotropic block and an anisotropic layer. The Kyonggi Massif and the eastern part of Kyongsang Basin play a role of window to the deep geoelectrical structure because of the very high resistivity of upper crust. The second layers with highest resistivities in 1-D conductivity models occupy the upper crust with thicknesses of 13 km in the Kyonggi Massif and 18 km in the eastern Kyongsang Basin, respectively.

• Progress in Medical Physics
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• v.16 no.1
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• pp.24-31
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• 2005

The stereotactic radiosurgery (SRS) describes a method of delivering a high dose of radiation to a small tar-get volume in the brain, generally in a single fraction, while the dose delivered to the surrounding normal tissue should be minimized. To perform automatic plan of the SRS, a new method of multi-isocenter/shot linear accelerator (linac) and gamma knife (GK) radiosurgery treatment plan was developed, based on a physical lattice structure in target. The optimal radiosurgical plan had been constructed by many beam parameters in a linear accelerator or gamma knife-based radiation therapy. In this work, an isocenter/shot was modeled as a sphere, which is equal to the circular collimator/helmet hole size because the dimension of the 50% isodose level in the dose profile is similar to its size. In a computer-aided system, it accomplished first an automatic arrangement of multi-isocenter/shot considering two parameters such as positions and collimator/helmet sizes for each isocenter/shot. Simultaneously, an irregularly shaped target was approximated by cubic structures through computation of voxel units. The treatment planning method by the technique was evaluated as a dose distribution by dose volume histograms, dose conformity, and dose homogeneity to targets. For irregularly shaped targets, the new method performed optimal multi-isocenter packing, and it only took a few seconds in a computer-aided system. The targets were included in a more than 50% isodose curve. The dose conformity was ordinarily acceptable levels and the dose homogeneity was always less than 2.0, satisfying for various targets referred to Radiation Therapy Oncology Group (RTOG) SRS criteria. In conclusion, this approach by physical lattice structure could be a useful radiosurgical plan without restrictions in the various tumor shapes and the different modality techniques such as linac and GK for SRS.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Korean Journal of Environment and Ecology
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• v.38 no.2
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• pp.204-216
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• 2024

Understanding the trade-off effect in ecosystem services and measuring the interrelationships between services are crucial for managing limited environmental resources. Accordingly, in this study, we identified the dominant trends and increases and decreases in ecosystem services derived from changes in land cover over about 30 years and tracked changes in the relationships between ecosystem services that occurred over time. Through it, we determined the relationship between land cover changes and ecosystem service changes, as well as the distinct characteristics of service changes in different areas. The research primarily utilized the InVEST model, an ecosystem service assessment model. After standardizing the evaluation results between 0 and 1, it went through principal component analysis, a dimensionality reduction technique, to observe the time-series changes and understand the relationships between the services. According to the research results, the area of urbanized regions dramatically increased between 1989 and 2019, while forests showed a significant increase between 2009 and 2019. Between 1989 and 2019, the national ecosystem service supply witnessed a 13.9% decrease in water supply, a 10.5% decrease in nitrogen retention, a 2.6% increase in phosphorus retention, a 0.9% decrease in carbon storage, a 1.2% increase in air purification, and a 3.4% decrease in habitat quality. Over the past 30 years, South Korea experienced an increase in urbanized areas, a decrease in agricultural land, and an increase in forests, resulting in a trade-off effect between phosphorus retention and habitat quality. This study concluded that South Korea's environment management policies contribute to improving ecosystem quality, which has declined due to urbanization, and maximizing ecosystem services. These findings can help policymakers establish and implement forestry policies focusing on sustainable environmental conservation and ecosystem service provision.

• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.917-929
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• 2019

Denitrification in streams is of great importance because it is essential for amelioration of water quality and accurate estimation of $N_2O$ budgets. Denitrification is a major biological source or sink of $N_2O$, an important greenhouse gas, which is a multi-step respiratory process that converts nitrate ($NO_3{^-}$) to gaseous forms of nitrogen ($N_2$ or $N_2O$). In aquatic ecosystems, the complex interactions of water flooding condition, substrate supply, hydrodynamic and biogeochemical properties modulate the extent of multi-step reactions required for $N_2O$ flux. Although water flow in streambed and residence time affect reaction output, effects of a complex interaction of hydrodynamic, geomorphology and biogeochemical controls on the magnitude of denitrification in streams are still illusive. In this work, we built a two-dimensional water flow channel and measured $N_2O$ flux from channel sediment with different bed geomorphology by using static closed chambers. Two independent experiments were conducted with identical flume and geomorphology but sediment with differences in dissolved organic carbon (DOC). The experiment flume was a circulation channel through which the effluent flows back, and the size of it was $37m{\times}1.2m{\times}1m$. Five days before the experiment began, urea fertilizer (46% N) was added to sediment with the rate of $0.5kg\;N/m^2$. A sand dune (1 m length and 0.15 m height) was made at the middle of channel to simulate variations in microtopography. In high- DOC experiment, $N_2O$ flux increases in the direction of flow, while the highest flux ($14.6{\pm}8.40{\mu}g\;N_2O-N/m^2\;hr$) was measured in the slope on the back side of the sand dune. followed by decreases afterward. In contrast, low DOC sediment did not show the geomorphological variations. We found that even though topographic variation influenced $N_2O$ flux and chemical properties, this effect is highly constrained by carbon availability.

• Journal of Environmental Impact Assessment
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• v.29 no.6
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• pp.414-429
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• 2020

For the management of rivers, the target water quality is set by establishing the total amount of water pollution and water environment basic plan. For Geumho river T-P has achieved the target water quality, but for BOD, COD, TOC the target water quality of the water environment basic plan has been exceed for the past five years. Therefore, the flow rate for satisfying the target water quality was simulated by analyzing the load, load density, and pollution contribution rate of the Geumho river using BOD, COD, TOC and by utilizing QUAL-MEV a one-dimensional water quality model. According to the analysis of the load, the BOD, COD and TOC all showed the highest levels at the Geumho C point at 9,832.2 kg/day 20,656.6 kg/day, and 15,545.1 kg/day. The load density was highest at 9.47 kg/day/㎢, 37.55 kg/day/㎢, 30.20 kg/day/㎢, and 17.19 kg/day/㎢, 39.14 kg/day/㎢ in Dalseocheon stream during the wet seasons and dry seasons. Pollution contribution rate was highest at about 25 percent for Palgeocheon stream during the wet season and about 50 percent for Dalseocheon stream during the dry season. In addition, the correlation analysis between organic materials showed in the main stream and tributaty of the Geumho river that COD-TOC was 0.8 or higherthan BOD-COD and BOD-TOC in both the wet seasons and dry seasons. And after surveying the total amount of water pollution and the target quality of the water environment basic plan at Geumho C, it was analyzed that an additional flow tate of 14 times and 22 times was needed as of April 2019 (3.46 ㎥/sec).

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Journal of Korean Society of Forest Science
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• v.85 no.3
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• pp.539-551
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• 1996

In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.

• Spatial Information Research
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• v.11 no.3
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• pp.261-274
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• 2003

The effective probability-based tile pre-fetching algorithm and the collaborative cache replacement algorithm are able to reduce the response time for user's requests by transferring tiles which will be used in advance and determining tiles which should be removed from the restrictive cache space of a client based on the future access probabilities in Web GISs(Geographical Information Systems). The Web GISs have multi-level abstracted data for the quick response time when zoom-in and zoom-out queries are requested. But, the previous pre-fetching algorithm is applied on only two-dimensional pre-fetching space, and doesn't consider expanded pre-fetching space for multi-level abstracted data in Web GISs. In this thesis, a probability-based pre-fetching algorithm for multi-level abstracted in Web GISs was proposed. This algorithm expanded the previous two-dimensional pre-fetching space into three-dimensional one for pre-fetching tiles of the upper levels or lower levels. Moreover, we evaluated the effect of the proposed pre-fetching algorithm by using a simulation method. Through the experimental results, the response time for user requests was improved 1.8%∼21.6% on the average. Consequently, in Web GISs with multi-level abstracted data, the proposed pre-fetching algorithm and the collaborative cache replacement algorithm can reduce the response time for user requests substantially.