• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.721-723
• /
• 2003

Aggregation is an operation that returns a result value through a computational process on the data which satisfy a certain condition. Recently many applications use aggregation to analyze spatiotemporal data. Although spatiotemporal data change its states over time, previous aggregation works have only dealt with spatial or temporal aspect of object. In this paper we propose spatiotemporal aggregate functions that operate on spatiotemporal data. The proposed algorithms are evaluated through some implementation results. The experiment results show that the proposed aggregate functions are applicable to spatiotemporal data efficiently.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.213-217
• /
• 1998

This study overviews existing evaluation methods of classification accuracy using confusion matrix proposed by Cohen in 1960's, and proposes ISDd(Index of Spatial Distribution by distance) and ISDs(Index of Spatial Distribution by scatteredness) for the evaluation of spatial distribution of satellite image classification errors, which has not been tried yet. Index of spatial distribution offers the basis of decision on adoption/rejection of classification results at sub-image level by evaluation of distribution, such as status of local aggregation of misclassified pixels. So, users can understand the spatial distribution of misclassified pixels and, can have the basis of judgement of suitability and reliability of classification results.

• Journal of the Korea Society of Computer and Information
• /
• v.4 no.4
• /
• pp.69-76
• /
• 1999

Recently, it has been studied the methods to materialize and precompute the query results for complexed spatial aggregation queries with high response time and the popular use in spatial data warehouse. In this paper, we propose extended selective materialization algorithm and present the way to materialize selectively which is considered access frequency and computation time of spatial operation according to spatial measures of spatial views for improvement of existing selective materialization algorithms.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.1
• /
• pp.38-50
• /
• 2018

Spatio-temporal load forecasting (STLF) is a foundation for building the prediction-based power map, which could be a useful tool for the visualization and tendency assessment of urban energy application. Constructing one point-forecasting model for each electricity cell in the geographic space is possible; however, it is unadvisable and insufficient, considering the aggregation features of electricity cells and uncertainties in input variables. This paper presents a new STLF method, with a data-driven framework consisting of 3 subroutines: multi-level clustering of cells considering their aggregation features, load regression for each category of cells based on SLS-SVRNs (sparse least squares support vector regression networks), and interval forecasting of spatio-temporal load with sampled blind number. Take some area in Pudong, Shanghai as the region of study. Results of multi-level clustering show that electricity cells in the same category are clustered in geographic space to some extent, which reveals the spatial aggregation feature of cells. For cellular load regression, a comparison has been made with 3 other forecasting methods, indicating the higher accuracy of the proposed method in point-forecasting of spatio-temporal load. Furthermore, results of interval load forecasting demonstrate that the proposed prediction-interval construction method can effectively convey the uncertainties in input variables.

• Journal of Korea Multimedia Society
• /
• v.19 no.9
• /
• pp.1647-1658
• /
• 2016

RGB+D database has been widely used in object recognition, object tracking, robot control, to name a few. While rapid advance of active depth sensing technologies allows for the widespread of indoor RGB+D databases, there are only few outdoor RGB+D databases largely due to an inherent limitation of active depth cameras. In this paper, we propose a novel method used to build outdoor RGB+D databases. Instead of using active depth cameras such as Kinect or LIDAR, we acquire a pair of stereo image using high-resolution stereo camera and then obtain a depth map by applying stereo matching algorithm. To deal with estimation errors that inevitably exist in the depth map obtained from stereo matching methods, we develop an approach that estimates confidence of depth maps based on unsupervised learning. Unlike existing confidence estimation approaches, we explicitly consider a spatial correlation that may exist in the confidence map. Specifically, we focus on refining confidence feature with the assumption that the confidence feature and resultant confidence map are smoothly-varying in spatial domain and are highly correlated to each other. Experimental result shows that the proposed method outperforms existing confidence measure based approaches in various benchmark dataset.

• Journal of Korea Spatial Information System Society
• /
• v.11 no.2
• /
• pp.99-110
• /
• 2009

Currently, there are many applications being developed based on sensor network technology. A tracking method for moving objects in sensor network is one of the main issue of this field. There is a little research on this issue, but most of the existing work has two problems. The first problem is a communication overhead for visiting sensor nodes many times to track a moving object. The second problem is an disability for dealing with many moving objects at a time. To resolve the problems, we, in this paper, propose a signature-based tracking method using efficient data aggregation for moving objects, called SigMO-TRK. For this, we first design a local routing hierarchy tree to aggregate moving objects' trajectories efficiently by using a space filtering technique. Secondly, we do the tracking of all trajectories of moving objects by using signature in a efficient way, our approach generates signatures to method. In addition, by extending the SigMO-TRK, we can retrieve the similar trajectories of moving objects for given a query. Finally, by using the TOSSIM simulator, we show that our signature-based tracking method outperforms the existing tracking method in terms of energy efficiency.

• Applied Biological Chemistry
• /
• v.29 no.2
• /
• pp.198-206
• /
• 1986

For the information on micellization at each ginsenoside level aqueous solution of purified saponin of Panax ginseng root was dialyzed through dialysis tubing (MW 12,000) or eluted through Bio-Gel P-2 (MW 200-2,000) and analysed for ginsenosides by high performance liquid chromatography. Ginsenosides can be classified into three groups depending upon molecular aggregation pattern and spatial arrangement of hydrophilic parts in molecule. Group I that is large micelle former(aggregation number: above 10) and one side hydrophilic part (HP) includes $ginsenoside\;Rb_1$, $Rb_2$, Rc and Rd (diols). Group II thai is small micelle former (aggregation number:>10-1) and semi-two sales HP includes $Rg_2$, Rf (triol) and $Rg_3$ (diol). Group III that is no micelle former (aggregation number: 1) and two sides HP includes Re and $Rg_1$ (triol).

• Horticultural Science & Technology
• /
• v.32 no.1
• /
• pp.84-90
• /
• 2014

Berchemia racemosa var. magna is only found in Anmyeon Island of South Korea. Genetic diversity and the spatial genetic structure of B. racemosa var. magna in Anmyeon Island were studied by I-SSR marker system. Fifty I-SSR amplicons were produced from 8 selected primers. We used 13 polymorphic markers to analyze the genetic structure. Distribution of 39 individuals in the study plot($90m{\times}70m$) showed aggregate pattern (aggregation index = 0.706). Total 21 genets were observed from 39 individuals through I-SSR genotyping. Proportion of distinguishable genotype (G/N), genotype diversity (D) and genotype evenness (E) were 53.8%, 0.966 and 0.946, respectively. In spite of the small number and the narrow distribution, Shannon's diversity index (I = 0.598) was relatively high as compared with those of the other plant species. For ex situ genetic conservation of B. racemosa var. magna, the sampling strategy based on spatial autocorrelation using Tanimoto distance is efficient at choosing the conserved individuals with a 6 meter interval between individual trees.

• Journal of Cadastre & Land InformatiX
• /
• v.47 no.1
• /
• pp.277-292
• /
• 2017

The development impact fee (DIF) zoning is a very beneficial public tool to provide the pre-planned urban infrastructures in those areas where significant urban sprawl had already taken place. In order to guarantee its benefit, however, it is required to designate the zone boundaries accurately and consistently. This study, in this context, tries to test the validity of the 50m-grid suggested in the official DIF manual, and to compare an alternative Hot Spot Analysis tool with the existing Spatial Aggregation method in configuring the zone boundaries. The results indicate that, unlike the case of population growth rate, current 50m grid size could not be much adequate in the case of using the development-permit increase rate to configure the primary DIF zones. Also, the optimal grid sizes seem to differ in the cases of Spatial Aggregation and Hot Spot Analysis. Further extended studies, in this regard, seem necessary to check the validity of the existing grid-size criteria as well as the boundary configuration methods.

• Korean journal of applied entomology
• /
• v.57 no.4
• /
• pp.361-372
• /
• 2018

Migratory insect pest populations migrate from the southern China to Korea through jet streams. In Korea, 5 major migratory insect species are important, i.e. Nilaparvata lugens, Sogatella furcifera, Laodelphax striatellus, Cnaphalocrocis medinalis and Mythimma separate, which are damages to the major crops, rice. This study was conducted from late July 2016 to early September 2016 and from July 2017 to August 2017 in rice paddy of Jeolla-province. C. medinalis and M. separata collected using pheromone traps, while N. lugens, S. furcifera and L. striatellus collected using 3 methods (visual surveys, sweeping surveys, sticky traps). SADIE (Spatial Analysis by Distance IndicEs) among geostatistics was used to analyze migratory insect pests. SADIE was used to analyze spatial distribution and index of aggregation $I_a$, index of clustering $V_i$, $V_j$ were used to investigate the spatial distribution. Also, the clustering indices were mapped as red-blue plot. C. medinalis and M. separata showed different distribution based on SADIE spatial aggregation analysis and red-blue plot analysis. Initial spatial distributions of L. striatellus and other planthoppers were differed for sampling location and time.