• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.1
• /
• pp.57-61
• /
• 2009

To increase the efficiency of mining process and derive accurate spatio-temporal patterns, continuous values of attributes should be discretized prior to mining process. In this paper, we propose a discretization method which improves the mining efficiency by reducing the data size without losing the correlations in the data. The proposed method first s original trajectories into approximations using line simplification and then groups them into similar clusters. Our experiments show that the proposed approach improves the mining efficiency as well as extracts more intuitive patterns compared to existing discretization methods.

• The Journal of the Korea Contents Association
• /
• v.11 no.1
• /
• pp.16-25
• /
• 2011

Some context is characterized by a single event in computing environment, but many other contexts are determined by a lot of things which occur with a space and a time. The Realtime Embedded System context-awareness service that interacts with the physical space can have property such as time. The exceptional behaviors of the system that interact with physical space can result in critical damage and cause danger to the operation of an embedded system. we propose an approach which should include spatio-temporal property and exceptional management in the context model, and verify its effectiveness using an expanded Petri-Net. The context-awareness service modeling of an embedded system is discussed the properties of model such as basic Petri-Net, patterned Petri-Net, or Spatio-temporal Petri-Net for the exceptional behaviors of the system. The proposed methodology demonstrated using an example that is emergency medical service. The use of expanded Petri-Net will contribute not only to develop the application but also to model the spatio-temporal context awareness for the exceptional handling.

• Spatial Information Research
• /
• v.20 no.3
• /
• pp.95-106
• /
• 2012

Recently, with increase and development of the wireless access network area, u-GIS Service is supported in various fields. Especially, spatio-temporal data is used in the mobile environment for the u-GIS service. However, there is no standard for the spatio-temporal data used in different spaces, spatio-temporal data processing technology is necessary to makes interoperability among mobile u-GIS services. Furthermore, it is also necessary to develop the system of gathering, storing, and managing the spatio-temporal data in consideration of small capacity and low performance of mobile devices. Therefore, in this paper, we designed and implemented a spatio-temporal query processing system based on GML to manage spatio-temporal data efficiently in the mobile environment. The spatio-temporal query processing system based on GML can offer a structured storage method which maps a GML schema to a storage table and a binary XML storage method which uses the Fast Infoset technique, so as to support interoperability that is an important feature of GML and increase storage efficiency. we can also provide spatio-temporal operators for rapid query processing of spatio-temporal data of GML documents. In addition, we proved that this system can be utilized for the u-GIS service to implement a virtual scenario.

• Journal of Intelligence and Information Systems
• /
• v.10 no.2
• /
• pp.15-37
• /
• 2004

With the growth in the size of datasets, data mining has recently become an important research topic. Especially, interests about spatio-temporal data mining has been increased which is a method for analyzing massive spatio-temporal data collected from a wide variety of applications like GPS data, trajectory data of surveillance system and earth geographic data. In the former approaches, conventional clustering algorithms are applied as spatio-temporal data mining techniques without any modification. In this paper, we focused to SOM that is the most common clustering algorithm applied to clustering analysis in data mining wet and develop the spatio-temporal data mining module based on it. In addition, we analyzed the clustering results of developed SOM module and compare them with those of K-means and Agglomerative Hierarchical algorithm in the aspects of homogeneity, separation, separation, silhouette width and accuracy. We also developed specialized visualization module fur more accurate interpretation of mining result.

• Spatial Information Research
• /
• v.18 no.1
• /
• pp.77-87
• /
• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• Proceedings of the Korean Society of Fisheries Technology Conference
• /
• 2000.05a
• /
• pp.379-380
• /
• 2000

최근 수산자원의 이용, 관리 및 환경보전 등의 문제를 생태계 보존이라는 관점에서 해석하고 풀려고 하는 시도가 활발히 이루어지고 있다. 따라서 단위 생태계의 구조와 기능을 이해하고 밝히는 것이 주요한 연구과제로 대두하고 있다. 특히, 생태계의 하부 영양구조인 영양염-식물플랑크톤-동물플랑크톤의 상호관계를 밝히는 것은 어류 등과 같은 상부 영양구조의 변동을 파악, 예측하는데 있어 매우 중요하다. 본 연구는 한국 연근해의 영양염-식물플랑크톤-동물플랑크톤의 시공간적 변동 특성과 이들의 상호관계를 논의하였다. (중략)

• Spatial Information Research
• /
• v.14 no.2 s.37
• /
• pp.223-234
• /
• 2006

In order to examine spatio-temporal characteristics of coastal water quality, we applied GIS spatial analysis to the water quality data collected from observation points located on Korean coastal area during 1997$\sim$2004. The water quality parameters measured included: chlorophyll-a, pH, DO, COD, SS, dissolved inorganic nitrogen, dissolved inorganic phosphorous, salinity, temperature. The water quality data used in this paper was obtained only at selected sites even though they are potentially available at any location in a continuous surface. Thus, it is necessary to estimate the values at unsampled locations so as to analyze spatial distribution patterns of coastal water quality, Owing to this reason, we applied IDW(inverse distance weighted) interpolation method to water quality data and evaluated the usefulness of IDW method. After IDW interfolation method was applied, we divided the Korean coastal area into 46 sections and examined spatio-temporal patterns of each section using GIS visualization technique. As a result of evaluation, we can blow that IDW interpolation and GIS are useful for understanding spatial and temporal distribution characteristics of coastal water quality data which is collected from a wide area far many years.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.11a
• /
• pp.105-108
• /
• 2004

데이터 양이 급증함에 따라 축적된 데이터로부터 의미있는 지식을 추출해 내고자 하는 데이터 마이닝에 대한 연구가 활발하게 진행되어 왔다. 특히 최근, 환경이 이동 분산화 되어감에 따라 감시${\cdot}$모니터링 시스템, 기상 관측 시스템, GPS 시스템과 같은 다양한 응용 시스템으로부터 방대한 양의 시공간 데이터가 발생하게 되었고, 이른 효율적으로 분석하고자 하는 시공간 데이터 마이닝 연구에 대한 관심이 더욱 높아지고 있다. 기존의 데이터 마이닝 기법의 경우 문자나 숫자 데이터를 대상으로 최적화 되어있기 때문에 시${\cdot}$공간 속성을 동시에 가지는 데이터를 분석하기에는 한계가 있는 것이 사실이다. 본 논문에서는 SOM(Self-Organizing Map)을 적용하여 시공간 클러스터링 모듈을 개발하고, 개발된 모듈의 성능 및 클러스터링 정확성을 다른 세 가지 군집분석 알고리즘과 비교, 분석하였다. 또한 가시화 모듈을 개발하여 입력 데이터의 특성과 결과를 더욱 정확하게 분석할 수 있도록 하였다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.1543-1547
• /
• 2007

지금까지 돌발홍수는 주로 강우의 시공간적인 특성들을 고려한 기후학적 측면에서 관심을 가지고 연구가 진행되어 왔을 뿐 유출의 시각에서 돌발홍수를 평가하기 위한 노력은 매우 미흡하였다고 할 수 있다. 본 연구의 목적은 Bhaskar 등(2000)의 연구를 우리나라에 적용하여 유출수문곡선에 의해 돌발홍수를 설명하고, 다른 홍수사상과 돌발홍수 사상을 구별하고자 하는데 있다. 즉, 유출수문곡선의 특성을 이용해 홍수사상에 대한 돌발홍수지수(flash flood index)를 산정함으로써 돌발홍수의 심각성 정도를 정량화하고자 하였다. 이를 위해 본 논문에서는 한강유역의 과거 101개의 홍수사상에 대해 돌발홍수의 상대심도(relative severity)를 파악하기 위하여 돌발홍수지수를 산정하였으며 또한, 2006년 7월의 집중호우에 의해 발생한 홍수사상의 돌발홍수 심도를 시공간적으로 정량화하였다. 분석 결과, 한강유역의 다른 지역에 비해 강원도 지역의 홍수 유출수문곡선들이 돌발홍수 심도를 크게 나타내었으며 중랑천 등과 같은 도시유역에서도 돌발심도가 크게 나타남을 확인 할 수 있었다. 2006년 7월 집중호우에 의한 한강유역의 돌발홍수지수를 7월 전반기, 중반기 그리고 하반기로 나누어 시공간적 공간분포를 분석한 결과, 7월 전반기의 경우 서울 주변지역의 돌발심도가 크게 나타났으며 7월 중반기의 경우 강원도 지역의 돌발홍수 심도가 크게 나타났다.

• Spatial Information Research
• /
• v.10 no.2
• /
• pp.185-199
• /
• 2002

The objective of this study is to investigate the suitable spatio-temporal analysis method considering the zoning effect of spatial analysis termed the modifiable areal unit problem(MAUP). In former studies of spatio-temporal analysis, there were disagreement between attribute data with spatial data, because of variation of administrative district aggregating attribute data. It is need to consider how the analysis zone effects spatial characteristics and spatio-temporal variation of urban region through land price variation analysis. This study considers MAUP through basic mesh system, which is composed of micro grid. Mesh system can solve disagreement of resolution between spatial data and attribute data.