• Journal of Biomedical Engineering Research
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• v.27 no.1
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• pp.22-29
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• 2006

This paper proposes an efficient array beamforming method using spatial matched filtering for ultrasound imaging. In the proposed method, ultrasound waves are transmitted from an array subaperture with fixed transmit focus as in conventional array imaging. At receive, radio frequency (RF) echo signals from each receive channel are passed through a spatial matched filter that is constructed based on the system transmit-receive spatial impulse response. The filtered echo signals are then summed. The filter remaps and spatially registers the acoustic energy from each element so that the pulse-echo impulse response of the summed output is focused with acceptably low side lobes. Analytical beam pattern analysis and simulation results using a linear array show that the proposed spatial filtering method can provide more improved spatial resolution and contrast-to-noise ratio (CNR) compared with conventional dynamic receive focusing (DRF) method by implementing two-way dynamically focused beam pattern throughout the field.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.245-253
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• 2016

Background in a novel is most important elements with characters and events, and means time, place and situation that characters appeared. Among the background, spatial background can help conveys topic of a novel. So, it may be helpful for choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels. In case of English text, It can be recognize spatial background easily because it use upper and lower case and words used with the spatial information such as Bank, University and City. But, in case Korean text, it is difficult to recognize that spatial background because there is few information about usage of letter. In the previous studies, they use machine learning or dictionaries and rules to recognize about spatial information in text such as news and text messages. In this paper, we build a nation dictionaries that refer to information such as 'Korean history' and 'Google maps.' We Also propose a method for recognizing spatial background based on patterns of postposition in Korean sentences comparing to previous works. We are grasp using of postposition with spatial background because Korean characteristics. And we propose a method based on result of morpheme analyze and frequency in a novel text for raising accuracy about recognizing spatial background. The recognized spatial background can help readers to grasp the atmosphere of a novel and to understand the events and atmosphere through recognition of the spatial background of the scene that characters appeared.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.89-98
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• 2009

As data stream is entered into system continuously and the memory space is limited, the data exceeding the memory size cannot be processed. In order to solve the problem, load shedding methods which drop a part of data to prevent exceeding the storage space have been researched. Generally, a traditional load shedding method uses random sampling with optimized rate according to data deviation. The method samples data not to distinguish those used in spatial query because the method uses only a random sampling with optimized rate according to data deviation. Therefore, the accuracy of query was reduced in u-GIS environment including spatial query. In this paper, we researched a new load shedding method improving accuracy of the query in u-GIS environment which runs spatial query and aspatial query simultaneously. The method uses a new sampling method that samples data having low probability used in query. Therefore proposed method improves spatial query accuracy and query processing speed as applying spatial filtering operation to sampling operator.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.472-482
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• 1997

Multi-dimensional data play a crucial role in various fields, as like computer graphics, geographical information system, and multimedia applications. Indexing method fur multi-dimensional data Is a very Important factor in overall system performance. What is proposed in this paper is a new dynamic access method for spatial objects called HL-CIF(Hierarchically Layered Caltech Intermediate Form) tree which requires small amount of storage space and facilitates efficient query processing. HL-CIF tree is a combination of hierarchical management of spatial objects and CIF tree in which spatial objects and sub-regions are associated with representative points. HL-CIF tree adopts "centroid" of spatial objects as the representative point. By reflecting objects′sizes and positions in its structure, HL-CIF tree guarantees the high spatial locality of objects grouped in a sub-region rendering query processing more efficient.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.505-513
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• 2017

Recently, numerous small area estimation studies have been conducted to obtain more detailed and accurate estimation results. Most of these studies have employed spatial regression models, which require a clear definition of spatial neighborhoods. In this study, we introduce the Delaunay triangulation as a method to define spatial neighborhood, and compare this method with the k-nearest neighbor method. A simulation was conducted to determine which of the two methods is more efficient in defining spatial neighborhood, and we demonstrate the performance of the proposed method using a land price data.

• Journal of Korea Spatial Information System Society
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• v.4 no.1 s.7
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• pp.39-46
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• 2002

In distributed spatial database systems, users nay issue a query that joins two relations stored at different sites. The sheer volume and complexity of spatial data bring out expensive CPU and I/O costs during the spatial join processing. This paper shows a new spatial join method which joins two spatial relation in a parallel way. Firstly, the initial join operation is divided into two distinct ones by partitioning one of two participating relations based on the region. This two join operations are assigned to each sites and executed simultaneously. Finally, each intermediate result sets from the two join operations are merged to an ultimate result set. This method reduces the number of spatial objects participating in the spatial operations. It also reduces the scope and the number of scanning spatial indices. And it does not materialize the temporary results by implementing the join algebra operators using the iterator. The performance test shows that this join method can lead to efficient use in terms of buffer and disk by narrowing down the joining region and decreasing the number of spatial objects.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.269-273
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• 2003

We consider an efficient parametric estimation method of spatial dependence in weak stationary processes. Spatial dependence is modeled through variogram and correlogram. Most of parametric estimation methods of correlogram use two step method; nonparametric estimation and parametric integration. We bind these two steps into one step by using GEE method instead of least squares type optimization. Our one step method is more efficient statistically and gives a clear interpretation of related concepts used in traditional two step methods.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.143-150
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• 2009

Spatial data warehouses are a system managing manufactured data through ETL step with extracted spatial data from spatial DBMS or various data sources. In load period, duplicated spatial data in the same subject are not useful in extracted spatial data dislike aspatial data and waste the storage space by the feature of spatial data. Also, in case of extracting source data on heterogeneous system, as those have different spatial type and schema, the spatial extract method is required for them. Processing a step matching address about extracted spatial data using a standard Geocoding DB, the exiting methods load formal data set. However, the methods cause the comparison operation of extracted data with Geocoding DB, and according to integrate spatial data by subject it has problems which do not consider duplicated data among heterogeneous spatial DBMS. This paper proposes efficient extracting method to integrate update query extracted from heterogeneous source systems in data warehouse constructer. The method eliminates unnecessary extracting operation cost to choose related update queries like insertion or deletion on queries generated from loading to current point. Also, we eliminate and integrate extracted spatial data using update query in source spatial DBMS. The proposed method can reduce wasting storage space caused by duplicate storage and support rapidly analyzing spatial data by loading integrated data per loading point.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.860-879
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• 2002

Traditionally, Geographical Information Systems can only process spatial data in a procedure-oriented way, and the data can't be treated integrally. This method limits the development of spatial data applications. A new and promising method to solve this problem is the spatial structural query language, which extends SQL and provides integrated accessing to spatial data. In this paper, the theory of spatial structural query language is discussed, and a new geographical data model based on the concepts and data model in OGIS is introduced. According to this model, we implemented a spatial structural query language G/SQL. Through the studies of the 9-Intersection Model, G/SQL provides a set of topological relational predicates and spatial functions for GIS application development. We have successfully developed a Web-based GIS system-WebGIS-using G/SQL. Experiences show that the spatial operators G/SQL offered are complete and easy-to-use. The BNF representation of G/SQL syntax is included in this paper.

• 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.