• Journal of Information Processing Systems
• /
• v.16 no.2
• /
• pp.406-420
• /
• 2020

In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.

• The KIPS Transactions:PartD
• /
• v.16D no.2
• /
• pp.191-200
• /
• 2009

Location based services (LBSs) have drawn huge attention as the growing number mobile devices and wireless technology demand more pervasive information access. In LBSs, Constraint nearest neighbor queries are one of the important queries of human to fulfill his desired quickly through wireless technology. We propose new query processing of constrained nearest neighbor query on the air to support mobile clients which demand optimal uses of wireless broadcast channel and using minimum battery power of client. First we proposed NN query processing with constrained region and then explain the novel NN query processing with various types of constraints. We have proposed novel algorithms to support Constrained Nearest Neighbor queries on the air based on Distributed Spatial Index and Bitmap-based Spatial Index.

• Journal of the Economic Geographical Society of Korea
• /
• v.10 no.3
• /
• pp.319-331
• /
• 2007

Nowadays, urbanized area expands its boundary, and distribution of urbanized area is gradually transformed into more complicated pattern. In Korea, SMA(Seoul Metropolitan Area) has outstanding urbanized area since 1960. But it is ambiguous whether urban distribution is clustered or dispersed. That is to say, it is difficult to understand spatial distribution pattern of urbanized area, although urbanized area has grown gradually. This study aims to show the way in which expansions of urbanized area impact on spatial distribution pattern of urbanized area. We use GIS analysis based on raster dataset, quadrat analysis, and nearest neighbor analysis to know distribution pattern of urbanized area in time-series urban growth. Experiments show that cohesion of SMA's urbanized area had increased to the early 1980s, but has decreased from the middle 1980s. Also, urban growth of SMA has been characterized not by spillover growth but by leapfrogging growth and road-influenced growth since the middle 1980s.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.4
• /
• pp.11-19
• /
• 2008

Recently, advances in mobile devices and wireless communication technologies require research on various location-based services. As a result, many studies on processing k-nearest neighbor query, which is most im portant one in location-based services, have been done. Most of existing studies use pre-computation technique to improve retrieval performance by computing network distance between POIs and nodes beforehand in spatial networks. However, they have a drawback that they can not deal with effectively the update of POIs to be searched. In this paper, we propose a distributed grid scheme using S-GRID to overcome the disadvantage of the existing work as well as to manage the location information of a large number of moving objects in efficient way. In addition, we describe a k-nearest neighbor(k-NN) query processing algorithm for the proposed distributed grid scheme. Finally, we show the efficiency of our distributed grid scheme by making a performance comparison between the k-NN query processing algorithm of our scheme and that of S-GRID.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.1
• /
• pp.203-209
• /
• 2012

Recently, k-nearest neighbors query methods based on wireless broadcasting environment are actively studied. The advantage of wireless broadcasting environment is the scalability that enables collective query processing for unspecified users connected to the server. However, in case existing k-NN query is applied in wireless broadcasting environment, there can be a disadvantage that backtracking may occur and consequently the query processing time is increasing. In this paper proposes a hierarchical bitmap-based spatial index in order to efficiently process the k-NN queries in wireless broadcasting environment. HBI reduces the bitmap size using such bitmap information and tree structure. As a result, reducing the broadcast cycle can reduce the client's tuning time and query processing time. In addition, since the locations of all the objects can be detected using bitmap information, it is possible to tune to necessary data selectively. For this paper, a test was conducted implementing HBI to k-NN query and the proposed technique was proved to be excellent by a performance evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.12
• /
• pp.2946-2952
• /
• 2014

Among the Example based Super Resolution(SR) techniques, Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the Learning Sparse-Neighbor Image Representation baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we first use bicubic interpolation to synthesize its high resolution version. We extract the patches from this synthesized image and determine whether each patch corresponds to regions with high or low spatial frequencies. After the weight of each patch is obtained by our method, we used to learn separate SVR models. Finally, we update the pixel values using the previously learned SVRs. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.1
• /
• pp.117-126
• /
• 2018

The purpose of this study is to analyze the spatial distribution characteristics and spatial changes of Automatic Weather Stations (AWS) in mountainous areas with altitude more than 200 meters in South Korea. In order to analyze the spatial distribution patterns, spatial analysis was performed on 203 Automatic Mountain Meteorology Observation Station (AMOS) points from 2012 to 2016 by Euclidean distance analysis, nearest neighbor index analysis, and Kernel density analysis methods. As a result, change of the average distance between 2012 and 2016 decreased up to 16.4km. The nearest neighbor index was 0.666632 to 0.811237, and the result of Z-score test was -4.372239 to -5.145115(P<0.01). The spatial distributions of AMOSs through Kernel density analysis were analyzed to cover 129,719ha/a station in 2012 and 50,914ha/a station in 2016. The result of a comparison between 2012 and 2016 on the spatial distribution has decreased about 169,399ha per a station for the past 5 years. Therefore it needs to be considered the mountainous regions with low density when selecting the site of AMOS.

• The Korean Journal of Applied Statistics
• /
• v.29 no.5
• /
• pp.873-885
• /
• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.1-16
• /
• 2018

The standard shift-share analysis decomposes a region's sectoral growth into three components: national, industry-mix, and regional-shift effects. Nevertheless, the three components of the traditional shift-share are not related to the behavior of the regional economies that are neighbors of the region under analysis. We incorporate a spatial structure within this basic formulation, and consider spatial interaction in the decomposition analysis. Daesan Port's export grew steadily at an annualized average rate of 4.0% during 2011-2017, and its rank, in terms of export performance, was 13 in 2010; this rose to 6 in 2016, then declined slightly to 7 in 2017 before reaching 6 as of June, 2018. However, not all ports have a similar growth path. The Onsan Port's share declined from 27.4% in 2011 to 21.0% to 2017, whereas the share of petroleum product exports of Daesan Port increased rapidly, from approximately 8.5% in 2011 to 16.0% in 2017. The standard shift-share analysis shows that petroleum products and basic petrochemicals have a positive regional in dustry-mix effect, but petrochemistry materials and synthetic resins have a negative sign, indicating that the former's exports grow faster than national export, while the increase of the latter's export is slower than national one. The spatial shift-share model indicates that for both petroleum products and basic petrochemicals, Incheon and Ulsan Ports have a positive value for the neighbor-nation regional shift effect and a positive value for the region-neighbor regional shift effect. This paper also shows that Yeosu Port for petroleum products; Ulsan Port for basic petrochemicals; Ulsan, Onsan and Yeosu Ports for petrochemistry materials; and Ulsan, Busan, and Incheon Ports for synthetic resins have a positive value for the neighbor-nation regional shift effect but a negative value for the region-neighbor regional shift effect.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.162-169
• /
• 2009

The real-time traffic data is generated continuous and unbounded stream data type while intelligent transport system (ITS) needs to provide various and high quality services by combining with spatial information. Traditional database techniques in ITS has shortage for processing dynamic real-time stream data and static spatial data simultaneously. In this paper, we design and implement an advanced traffic monitoring system (ATMS) with the integration of existed data stream management system (DSMS) and spatial DBMS using IntraMap. Besides, the developed ATMS can deal with the stream data of DSMS, the trajectory data of relational DBMS, and the spatial data of SDBMS concurrently. The implemented ATMS supports historical and one time query, continuous query and combined query. Application programmer can develop various intelligent services such as moving trajectory tracking, k-nearest neighbor (KNN) query and dynamic intelligent navigation by using components of the ATMS.