• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1271-1278
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• 2006

Recently, a profit analysis in hospital management is considered as an important marketing concept. When spatial variability is presented, we must analyze the hospital data with spatial statistical methods. In this study, we present a regression model using spatial covariance for adjustment. And we compare the nonspatial model with spatial model.

• Journal of KIISE
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• v.42 no.6
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• pp.781-790
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• 2015

In recent times, microblogs have become popular owing to the development of the Internet and mobile environments. Among the various types of microblog data, those containing location data are referred to as spatial social Web objects. General aggregations of such microblog data include data aggregation per user for a single piece of information. This study proposes a spatial aggregation algorithm that combines a general aggregation with spatial data and uses the Geohash and MapReduce operations to perform spatial social analysis, by using microblog data with the characteristics of a spatial social Web object. The proposed algorithm provides the foundation for a meaningful spatial social analysis.

• Korean Institute of Interior Design Journal
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• v.20 no.5
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• pp.143-151
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• 2011

Since it is important to understand data acquiring characteristics through relationship between spatial types and spatial elements and apply it to spatial plans for smooth communication between designer and user of space, the conclusions gained from analysis of data acquiring characteristics of spatial elements through image evaluation by types of interior space can be summarized as in the followings: First, for the amount of acquired data by types of interior space, it shows that the acquired amount of data is to change by types and data acquiring method (phrase and image) even though the spatial elements are same. Second, for the data acquiring process of spatial types by gender, it shows that there is a big difference in acquiring of data according to the evaluation method by phrase and image. Third, for the amount of acquired data of spatial types by gender, it shows that there is a difference between male and female, which is by "classic ${\rightarrow}$ modern ${\rightarrow}$ natural" in case of male and "classic ${\rightarrow}$ natural ${\rightarrow}$ modern" in case of female. regarding both of phrase and image. Fourth, for the evaluation by gender, it shows that there is a deviation in the value of difference according to the elements by which data acquiring characteristics evaluate space. It is considered that this deviation characteristic is in need of reflection in the process of spatial evaluation. This study analyzed data acquiring characteristics of space user's spatial elements through image evaluation by types of space to understand how data acquiring would be changed of spatial elements according to type and gender. Through this study, it expects to make clear that, when a designer is planning a certain space, if the space can be a space for the user by understanding of which elements should be exposed to users by types to acquire more data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.43-54
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• 2001

In this paper we study the use of polyinstantiation for spatial data, for the purpose of solving cover in topology channel in multilevel secure spatial database systems. Spatial database system with topological structure has a number of spatial analysis function using spatial data and neighbored one\`s each other. But. it has problems that information flow is occurred by topological relationship in spatial database systems. Geographic Information System(CIS) must be needed mandatory access control because there ,are many information flow through positioning information And topological relationship between spatial objects. Moreover, most GIS applications also graphe user interface(GUI). In addressing these problems, we design the MLS/SRDM(Multi Level Security/Spatial Relational Data Model) and propose polyinstantiation for spatial data for solving information flow that occurred by toplogical relationship of spatial data.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.29-36
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• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8370-8377
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• 2015

In spatial data stream management systems, it is needed appropriate load shedding algorithm because real-time input spatial data streams could exceed the limitation of main memory. However previous researches, lack regard for input ratio and spatial utilization rates of spatial data streams, or the characteristics of data source which generates data streams with spatial information efficiently, can lead to decrease the performance and accuracy of spatial data stream query. Therefore, multi-level load shedding scheme for spatial data stream management systems is proposed to increase the spatial query performance and accuracy. This proposed scheme limits overloads in relation to the input rate and the characteristics of data source first, and then, if needed, query data representing low query participation probability based on spatial utilizations are dropped relatively. Our experiments show that the proposed method could decrease load shedding frequency for previous researches by more than 11% despite query results accuracy and query performance are superior at 0.04% and 3%.

• Spatial Information Research
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• v.12 no.4 s.31
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• pp.307-319
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• 2004

Managing GML data in traditional database systems is not efficient since It has not only characteristics of spatial data but also features of (semi) structured n documents. XML enabled database systems can manage U data efficiently, however they cannot handle spatial data. Spatial database systems are good at spatial data handling but those are inefficient for XML data. This paper proposes a storage method of GML data for spatial database systems in order to solve the problems. The proposed method generates spatial database schemas from GML application schemas and store GML data into SDBMS through the generated schemas. A prototype of the storage method has been implemented on the Postgre SQ/SPE system to show the proposed method is appropriate for storing GML data. As a result, the implemented system was able to store various GML data which had diverse XML structures and different size. Stored data size was smaller than GML files. Furthermore, spatial, non-spatial, and mixed content queries could be performed over the stored GML data as quickly.

• Spatial Information Research
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• v.23 no.6
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• pp.109-116
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• 2015

In this study, define the concept of spatial big data and special feature of spatial big data, examine information visualization methodology for increase the insight into the data. Also presented problems and solutions in the visualization process. Spatial big data is defined as a result of quantitative expansion from spatial information and qualitative expansion from big data. Characteristics of spatial big data id defined as 6V (Volume, Variety, Velocity, Value, Veracity, Visualization), As the utilization and service aspects of spatial big data at issue, visualization of spatial big data has received attention for provide insight into the spatial big data to improve the data value. Methods of information visualization is organized in a variety of ways through Matthias, Ben, information design textbook, etc, but visualization of the spatial big data will go through the process of organizing data in the target because of the vast amounts of raw data, need to extract information from data for want delivered to user. The extracted information is used efficient visual representation of the characteristic, The large amounts of data representing visually can not provide accurate information to user, need to data reduction methods such as filtering, sampling, data binning, clustering.

• Journal of Information Technology Services
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• v.7 no.1
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• pp.205-218
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• 2008

This paper proposes a geospatial data visualization system supporting validation of GML documents. GIS systems manage and use both of spatial and non-spatial data. Currently, most GIS systems represent spatial data in GML (Geography Markup Language) developed by OGC. GML is a language for representation and sharing of spatial information, and until now many systems have been developed in GML. GML does not support expression of non-spatial data, i.e., relational information of spatial objects, and thus most systems extend GML to describe non-spatial information. However, it causes an issue that the systems only accepting standard GML documents cannot process the extended documents. In this paper, we propose a new GIS data visualization system to resolve the aforementioned Issue. Our proposed system allows the representation of both types of data supporting independency of spatial data and non-spatial data. It enhances interoperability with other relevant systems. Therefore, we can develop a rich and high Quality geospatial information services.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.3
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• pp.39-46
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• 2022

This study aims to derive basic living service facility items in rural areas and construct related spatial data. To do this, a literature review on the laws and systems related to the residential environment and services in rural areas, rural spatial planning, and the 'Rural Convention' strategic plan reports for the Jeolla and Gyeongsang Region in 2021 was conducted. Primary data collection and review on the list of basic living service items in rural areas derived from the analysis were conducted. After data collection, 12 sectors and 44 types of rural basic living service items were derived; the data selection was carried out based on the clarity of the subject of data management, whether it was established nationwide, whether it was disclosed and provided, whether it was periodically updated, and whether it was an underlying law. Afterwards, data on the derived rural basic living service items were constructed. Afterwards, spatial data on the derived rural basic living service items were constructed. Because open data provided through various institutions were employed, data structure unification such as data attribute values and code names was needed, and abnormal data such as address errors and omissions were refined. After that, the data provided in text form was converted into spatial data through geocoding, and through comparative review of the distribution status of the converted data and the provided address, spatial data related to rural basic living services were finally constructed for about 540,000 cases. Finally, implications for data construction for diagnosing rural living areas were derived through the data collection and construction process. The derived implications include data unification, data update system establishment, the establishment of attribute values necessary for rural living area diagnosis and spatial planning, data establishment plan for facilities that provide various services, rural living area analysis method, and diagnostic index development. This study is meaningful in that it laid the foundation for data-based rural area diagnosis and rural planning, by selecting the basic rural living service items, and constructing spatial data on the selected items.