• Journal of KIISE
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• v.43 no.9
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• pp.963-973
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• 2016

Providing a semantic knowledge system using media ontologies requires not only conventional axiom reasoning but also knowledge extension based on various types of reasoning. In particular, spatio-temporal information can be used in a variety of artificial intelligence applications and the importance of spatio-temporal reasoning and expression is continuously increasing. In this paper, we append the LOD data related to the public address system to large-scale media ontologies in order to utilize spatial inference in reasoning. We propose an RDFS/Spatial inference system by utilizing distributed memory-based framework for reasoning about large-scale ontologies annotated with spatial information. In addition, we describe a distributed spatio-temporal SPARQL parallel query processing method designed for large scale ontology data annotated with spatio-temporal information. In order to evaluate the performance of our system, we conducted experiments using LUBM and BSBM data sets for ontology reasoning and query processing benchmark.

• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.643-652
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• 2006

Decision trees are mainly used for the classification and prediction in data mining. The distribution of spatial data and relationships with their neighborhoods are very important when conducting classification for spatial data mining in the real world. Spatial decision trees in previous works have been designed for reflecting spatial data characteristic by rating Euclidean distance. But it only explains the distance of objects in spatial dimension so that it is hard to represent the distribution of spatial data and their relationships. This paper proposes a decision tree based on spatial entropy that represents the distribution of spatial data with the dispersion and dissimilarity. The dispersion presents the distribution of spatial objects within the belonged class. And dissimilarity indicates the distribution and its relationship with other classes. The rate of dispersion by dissimilarity presents that how related spatial distribution and classified data with non-spatial attributes we. Our experiment evaluates accuracy and building time of a decision tree as compared to previous methods. We achieve an improvement in performance by about 18%, 11%, respectively.

• Spatial Information Research
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• v.19 no.1
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• pp.107-116
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• 2011

Due to development of environment of wireless Internet, location based services on the basis of spatial data have been increased such as real time traffic information as well as CNS(Car Navigation System) to provide mobile user with route guidance to the destination. However, the current application adopting the file-based system has limitation of managing and storing the huge amount of spatial data. In order to supplement this challenge, research which is capable of managing large amounts of spatial data based on embedded database system is surely demanded. For this reason, this study aims to suggest the lossless compression technique by using the hybrid approach of BytePacking and Lempel-Ziv which can be applicable in DBMS so as to save a mass spatial data efficiently. We apply the proposed compression technique to actual the Seoul and Inchcon metropolitan area and compared the existing method with suggested one using the same data through analyzing the query processing duration until the reconstruction. As a result of comparison, we have come to the conclusion that suggested technique is far more performance on spatial data demanding high location accuracy than the previous techniques.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.407-414
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• 2014

The aim of the present study was to carry out quantitative analysis of spatial resolution for the influence of the focus size and digital image post-processing on the Computed Radiography (CR). The modulation transfer functions of an edge measuring method (MTF) was used for the evaluation of the spatial resolution. The focus size of X-ray tube was used the small focus (0.6 mm) and the large focus (1.2 mm). We evaluated the 50% and 10% of MTF for the enhancement of edge and contrast by using multi-scale image contrast amplification (MUSICA) in digital image post-processing. As a results, the edge enhancement than the contrast enhancement were significantly higher the spatial resolution of MTF 50% in all focus. Also the spatial resolution of the obtained images in a large focus were improved by digital image processing. In conclusion, the results of this study should serve as a basic data for obtain the high resolution clinical images, such as skeletal and chest images on the CR.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.107-118
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• 2005

Various spatial data are utilized, through geographic information system, for the process to make a decision related to space. Generally, spatial data is large in quantity and it costs high and takes quite a long time for producing and maintaining it. An existing spatial data management system, tile-based one, for digital map manages spatial data being separated by a uniform data unit called tile. These systems can be implemented easily but have many problems such as they can directly store and manage feature included in tile. Therefore, in this paper, we suggest a feature-based spatial data management system for digital map. The proposed system is able to store and manage spatial data in the unit of feature directly. Hence this system is able to immediately update any change in the data and to supply users with the updated data without any delay. The proposed system can not only support a function of data input, management, supplying and update but also support unity origin coordinate conversion, UFID creation, feature unifying, feature dividing and metadata input which is not supported by the existing tile-based system. The proposed system can easily manage spatial data and can increase efficiency in processing and application.

• Journal of Digital Contents Society
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• v.12 no.1
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• pp.77-83
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• 2011

Providing services in a wireless environment with existing wired-based GIS solutions have many limitations such as slow communication, processing rates, and screen size. Among the components, data is considered to be the most important factor in GIS. In this paper, I describe MVF, the most recent technology pioneered by GIS researchers. MVF is a format for efficient usage of spatial object in order to express, save and transform in mobile GIS. First, I describe the definition of MVF syntax, then the implementation of Header Section Generation Module and Main Section Generation Module through the API. Since the issues of network traffic and Hangul processing in mobile GIS are important, I especially consider development of MVF in terms of spatial data size.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.1-10
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• 2004

According to the evolution of the Internet and wireless mobile communication technology, techniques for mobile databases and wireless web services are issued for them. Recently, these changes of geographic application environment increase the needs for development of new GIS database system for the web services and embedded system. In this paper, we proposed a Jana-based web database systems that can be used in the web-based GIS and mobile databases. This proposed system has been implemented using the Java to be displayed easily into the portable computing devices and Java-based web application servers and using OpenGIS for web data interoperability. Also, it can efficiently process web-based spatial queries by developing a spatial query processor including schema manager and a spatial object storage module.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1269-1275
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• 2003

This paper addresses several issues on data caching and consistency of cached data in order to process client's queries efficiently in client/server environments. For the purpose, first of all, materialized spatial views are adapted in a client side for data caching, which is called client views. Also, an incremental update scheme using derivation relationships is applied to keep cached data of clients consistent with the rest of server databases. Materialized views support efficient query processing in a client side, however, it is difficult to keep consistent their contents by the update of a server database. In this paper, we devise cost functions on query execution and view maintenance based the cost of spatial operators so as to process client's queries efficiently. When request the client's query, in our query processing scheme, the server determines whether or not materialize it as a view due to evaluation using the related cost functions. Since the scheme supports a hybrid approach based on both view materialization and re-execution, hence, it should improve query execution times in client/server environments.

• Spatial Information Research
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• v.19 no.4
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• pp.45-54
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• 2011

In this paper, we propose a hybrid index structure, called the SQMR-tree(Spatial Quad MR-tree) that can process spatial data efficiently by combining advantages of the MR-tree and the SQR-tree. The MR-tree is an extended R-tree using a mapping tree to access directly to leaf nodes of the R-tree and the SQR-tree is a combination of the SQ-tree(Spatial Quad-tree) which is an extended Quad-tree to process spatial objects with non-zero area and the R-tree which actually stores spatial objects and are associated with each leaf node of the SQ-tree. The SQMR-tree consists of the SQR-tree as the base structure and the mapping trees associated with each R-tree of the SQR-tree. Therefore, because spatial objects are distributedly inserted into several R-trees and only R-trees intersected with the query area are accessed to process spatial queries like the SQR-tree, the query processing cost of the SQMR-tree can be reduced. Moreover, the search performance of the SQMR-tree is improved by using the mapping trees to access directly to leaf nodes of the R-tree without tree traversal like the MR-tree. Finally, we proved superiority of the SQMR-tree through experiments.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.591-602
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• 2003

Delay and discontinuance phenomenon of service are cause by sudden increase of the network communication amount and the quantity consumed of resources when Internet users are driven excessively to a conventional single large database sewer. To solve these problems, spatial database cluster consisted of several single nodes on high-speed network to offer high-performance is risen. But, research about spatial join operation that can reduce the performance of whole system in case process at single node is not achieved. So, in this paper, we propose efficient parallel spatial join processing method in a spatial database cluster system that uses data partitions and replications method that considers the characteristics of space data. Since proposed method does not need the creation step and the assignment step of tasks, and does not occur additional message transmission between cluster nodes that appear in existent parallel spatial join method, it shows performance improvement of 23% than the conventional parallel R-tree spatial join for a shared-nothing architecture about expensive spatial join queries. Also, It can minimize the response time to user because it removes redundant refinement operation at each cluster node.