• Geomechanics and Engineering
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• v.14 no.4
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• pp.337-344
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• 2018

The study of the mining effect influenced by a normal fault has great significance concerning the prediction and prevention of fault rock burst. According to the occurrence condition of a normal fault, the stress evolution of the working face and fault plane, the movement characteristics of overlying strata, and the law of fault slipping when the working face advances from footwall to hanging wall are studied utilizing UDEC numerical simulation. Then the inducing-mechanism of fault rock burst is revealed. Results show that in pre-mining, the in situ stress distribution of two fault walls in the fault-affected zone is notably different. When the working face mines in the footwall, the abutment stress distributes in a "double peak" pattern. The ratio of shear stress to normal stress and the fault slipping have the obvious spatial and temporal characteristics because they vary gradually from the higher layer to the lower one orderly. The variation of roof subsidence is in S-shape which includes slow deformation, violent slipping, deformation induced by the hanging wall strata rotation, and movement stability. The simulation results are verified via several engineering cases of fault rock burst. Moreover, it can provide a reference for prevention and control of rock burst in a fault-affected zone under similar conditions.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.119-132
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• 2009

Owing to the GIS technology, a vast volume of spatial data has been accumulated, thereby incurring the necessity of spatial data mining techniques. In this paper, we propose a new spatial data mining system named SD-Miner. SD-Miner consists of three parts: a graphical user interface for inputs and outputs, a data mining module that processes spatial mining functionalities, a data storage model that stores and manages spatial as well as non-spatial data by using a DBMS. In particular, the data mining module provides major data mining functionalities such as spatial clustering, spatial classification, spatial characterization, and spatio-temporal association rule mining. SD-Miner has own characteristics: (1) It supports users to perform non-spatial data mining functionalities as well as spatial data mining functionalities intuitively and effectively; (2) It provides users with spatial data mining functions as a form of libraries, thereby making applications conveniently use those functions. (3) It inputs parameters for mining as a form of database tables to increase flexibility. In order to verify the practicality of our SD-Miner developed, we present meaningful results obtained by performing spatial data mining with real-world spatial data.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.39-52
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• 2006

With the recent the use of spatio-temporal data mining which can extract various knowledge such as movement patterns of moving objects in history data of moving object gets increasing. However, the existing movement pattern extraction methods create lots of candidate movement patterns when the minimum support is low. Therefore, in this paper, we suggest the STMPE(Spatio-Temporal Movement Pattern Extraction) algorithm in order to efficiently extract movement patterns of moving objects from the large capacity of spatio-temporal data. The STMPE algorithm generalizes spatio-temporal and minimizes the use of memory. Because it produces and keeps short-term movement patterns, the frequency of database scan can be minimized. The STMPE algorithm shows more excellent performance than other movement pattern extraction algorithms with time information when the minimum support decreases, the number of moving objects increases, and the number of time division increases.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.200-203
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• 2008

최근 전력산업에서의 에너지 가격 및 공급과 수요의 변동, 그리고 기후의 변화에 의해서 부하 예측은 전력회사 경영방침 계획에 있어 중요한 요소가 되었다. 이 논문에서 전력계통의 최적 운용 계획을 위하여 우리가 제안한 기법은 다차원 분석이 가능한 3D 큐브 마이닝과 시간의 변화에 따른 패턴 예측이 가능한 캘린더 기반 시간 데이터 마이닝 기법이다. 이를 통하여 무선 부하 감시 시스템의 부하 데이터의 다차원 분석이 가능하고, 시간 변화에 따른 서로 다른 부하 패턴의 예측이 가능하도록 한다.

• Asian Journal of Innovation and Policy
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• v.11 no.2
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• pp.202-221
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• 2022

The media has depicted an abrupt socio-technological change in the Republic of Korea with the 4th Industrial Revolution. Because technologies cannot realize their potential without social acceptance, studying conflicts incurred by such a change is imperative. However, little literature has focused on conflicts caused by technologies. Therefore, the current study investigated media coverage regarding conflicts related to the 4th Industrial Revolution from 2016 to 2020 in the Republic of Korea, applying text-mining techniques. We found that the overall amount and coverage pattern conforms to the issue attention cycle. Also, the three major topics ("SMEs & Startups," "Mobility Conflict," and "Human & Technology") indicate quarrels between conflicting social entities. Moreover, the temporal change in media coverage implies the political use of the term rather than technological. However, we also found the media's deliberative discussion on the socio-technological impact. This study is significant because we expanded the discussion on media coverage of technologies to the realm of social conflicts. Furthermore, we explored the news articles of the recent five years with a text-mining approach that enhanced the objectivity of the research.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.38-44
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• 2002

고객관계관리(CRM)나 마케팅과 같은 경영방식에서도 대용량의 공간 데이터베이스를 사용하는 지리정보시스템(GIS)과 같은 응용분야를 접목하고 있다. gCRM은 지리정보시스템과 고객관계관리를 결합한 것으로, 이러한 실정을 단적으로 보여 주고 있는 경영방식이다. gCRM은 대용량의 데이터베이스로부터 관심 있는 분야를 찾아내고 분석하게 된다. 그러기 위해서는 데이터마이닝이라는 기술이 필요하다. 하지만, gCRM은 일반적인 데이터베이스뿐만 아니라 공간 데이터베이스 역시 많이 사용되어진다. 이러한 공간데이터베이스로부터 관심 있는 부분이나 관계 그리고 특성 등을 찾아내기 위해서는 공간데이타마이닝이 요구된다. 본 논문에서는 gCRM 솔루션들의 기능을 중심으로 다양한 공간데이타마이닝 기법과 어떠한 관계가 있는지를 살펴봄으로써 gCRM과 공간데이타마이닝이 접목할 수 있는 부분에 대하여 정리하였다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.229-231
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• 1998

시간지원 데이터베이스내에는 다양한 유형의 시간 정보가 내포되어 있다. 이 논문은 다양한 시간 정보를 기반으로 하는 시간 연관규칙 탐사에 관한연구이다. 기존의 연관규칙 탐사에 관한 연구는 현실세계에 존재하는 사건을 탐사 대상으로 하면서도 시간 개념을 지니지 않은 형태의 데이터 집합을 대상으로 하고 있다. 그리고 단순히 단일 시점의 트랜잭션 시간마을 고려하여 순차패턴을 추출해내는 연구가 진행되었다. 이러한 연구는 시간 데이터의 시간 간격 특성과 시간 위상 특성을 간과하게 된다. 또한 시간 종속적인 데이터에 관한 정보의 탐사 시에는 한계점을 지니게 된다. 따라서 이 논문에서는 시간 간격과 시간 위상을 지니는 시간지원 데이터베이스로부터 추출될 수 있는 시간 정보 유형을 제시하고 이에 기반한 다양한 유형의 연관규칙을 제시한다. 또한 시간 연관규칙을 정의하고 이를 탐사하는 과정을 설명하며 궁극적으로 시간지원 데이터베이스에서의 시간 연관규칙 탐사 시스템을 소개한다.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• Ocean and Polar Research
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• v.32 no.4
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• pp.337-350
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• 2010

This study conducted sedimentological and geophysical surveys for 3 years (2006-2008) in southern Gyeonggi Bay, Korea to elucidate temporal changes in subaqueous dune morphology on a sand ridge trending northeast to southwest that has been excavated by marine sand mining. The sand ridge (~20 m in height, ~2 km in width and 3~4 km in length) has a steep slope on the NW side and a gentle slope on the SE side, creating an asymmetric profile. Large (10~100 m in length) and very large (>100 m in length) dunes occurring on the SE side of the ridge show a northeastward asymmetrical shape, whereas dunes on the NW side destroyed by marine sand mining display a southwestward asymmetry. The comparison between Flemming (1988)'s correlation and the height-length correlation of this study indicates that tidal current and availability of sand sediment are major controlling factors to the development and maintenance of dunes. Depth and sedimentary characteristics (grain size) are not likely to be major controlling factors, but indirectly influence dune growth by hydrological and sedimentary processes. The length and the height of dunes decrease toward the southeastern trough away from the crest of the ridge. These features result from the decrease of tidal current and sediment availability. The length and the height of dunes on the southeast side decrease gradually over time. This is a result of the interaction between tidal current and the decrease in sediment availability due to sediment extraction by marine sand mining. Marine sand mining has destroyed the dunes directly, causing irregular shapes of shorter length and lower height. The coarse fraction of suspended sediments is transported and deposited very close to the sand pit. By contrast, relatively fine sediments are transported by the tidal current and deposited over a wide range by the settling-lag effect, resulting in a decrease of sediment grain size in the area where suspended sediments are deposited. In addition, marine sand mining, decreases the height of dunes. Therefore, morphological and sedimentological characteristics of dunes around the sand pits will be significantly changed by future sand mining activities.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.113-122
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• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.