• Journal of the Korean Statistical Society
• /
• v.29 no.2
• /
• pp.247-260
• /
• 2000

This paper is concerned with a modification of the k-spatial medians clustering. To find a suitable number of clusters, the number k of clusters is incorporated into the k-spatial medians clustering criterion through a weight function. Proposed method for the choice of the weight function offers a reasonable number of clusters. Some theoretical properties of the method are investigated along with some examples.

• Steel and Composite Structures
• /
• v.3 no.4
• /
• pp.277-287
• /
• 2003

The low boundary of load carrying capacity of the elastic-plastic spatial grid structures depend on numerous values and their variability assumed in designing process. Analysed influence all this values in searching for optimal variant of the structure lead to too great problem even taking into consideration actual computational power we have in disposal. Therefore one can take only a few values which have greatest influence on the optimal choice. In optimal analysis of the elastic-plastic spatial grid structures the previously proposed method with subsequent modification (Karczewski 1980), (Karczewski, Barszcz and Donten 1996), (Karczewski and Donten 2001) as well as computer program which was worked out by Donten K. to make possible practical utilisation this method was employed. The paper deal with evaluation of influence dimensions of particular values for choice of optimal variant of the structure. One among this values is distribution of the struts in the structure.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.721-724
• /
• 2005

In this study the spatial distribution characters of forest in forest damaged area were first considered by analyzing spatial data and monitoring forest landscape. Then suitable tree species on each site were selected through the weighted score analysis of GIS analysis methods. Finally, the best forest stand arrangement method could be presented on the 3D based simulation system for the advanced reforestation technology in Korea. For this purpose, the virtual reforestation system was implemented by using the concept of virtual GIS and CBD (Component Based Development) method. By use of this system the change offorest landscape of burnt forest area some years after reforestation practice could be detected and monitored by applying the site index and 3D modeling method.

• Journal of Korea Water Resources Association
• /
• v.32 no.1
• /
• pp.3-13
• /
• 1999

In this study, an alternative spatial analysis method against conventional methods such as Thiessen method, Inverse Distance method, and Kriging method, named Spatial-Analysis Neural-Network (SANN) is presented. It is based on neural network modeling and provides a nonparametric mean estimator and also estimators of high order statistics such as standard deviation and skewness. In addition, it provides a decision-making tool including an estimator of posterior probability that a spatial variable at a given point will belong to various classes representing the severity of the problem of interest and a Bayesian classifier to define the boundaries of subregions belonging to the classes. In this paper, the SANN is implemented to be used for analyzing a mean annual precipitation filed and classifying the field into dry, normal, and wet subregions. For an example, the whole area of South Korea with 39 precipitation sites is applied. Then, several useful results related with the spatial variability of mean annual precipitation on South Korea were obtained such as interpolated field, standard deviation field, and probability maps. In addition, the whole South Korea was classified with dry, normal, and wet regions.

• Steel and Composite Structures
• /
• v.18 no.4
• /
• pp.853-871
• /
• 2015

Up to now, Japan has more than 200 corrugated steel web composite beam bridges which are under construction and have been constructed, and China has more than 30 corrugated steel web composite beam bridges. The bridge type includes the simply supported beam, continuous beam, continuous rigid frame and cable stayed bridge etc. The section form has developed to the single box and multi-cell box girder from the original single box and single chamber. From the stress performance and cost saving, the span range of 50~150 m is the most competitive. At present, the design mostly adopts the computational analytical method combining the spatial bar system model, plane beam grillage model and solid model. However, the spatial bar system model is short of the refinement analysis on the space effect, such as the shear lag effect, effective distribution width problem, and eccentric load factor problem etc. Due to the similarity of the plane beam grillage method in the equivalence principle, it cannot accurately reflect the shearing stress distribution and local stress of the top and bottom plates of the box type composite beam. The solid model is very difficult to combine with the overall calculation. Moreover, the spatial grid model can achieve the refinement analysis, with the integrity of the analysis and the comprehensiveness of the stress checking calculation, and can make up the deficiency of the analytical method currently. Through the example verification of the solid model and spatial grid model, it can be seen that the calculation results for the stress and the displacement of two models are almost consistent, indicating the applicability and precision of the spatial grid model.

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.1
• /
• pp.29-36
• /
• 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 Korean Association for Spatial Structures
• /
• v.7 no.1 s.23
• /
• pp.7-13
• /
• 2007

• Korean Journal of Remote Sensing
• /
• v.26 no.6
• /
• pp.693-703
• /
• 2010

High spectral resolution of hyperspectral data enables analysis of complex natural phenomena that is reflected on the data nonlinearly. Although many manifold learning methods have been developed for such problems, most methods do not consider the spatial correlation between samples that is inherent and useful in remote sensing data. We propose a manifold learning method which directly combines the spatial proximity and the spectral similarity through kernel PCA framework. A gain factor caused by spatial proximity is first modelled with a heat kernel, and is added to the original similarity computed from the spectral values of a pair of samples. Parameters are tuned with intelligent grid search (IGS) method for the derived manifold coordinates to achieve optimal classification accuracies. Of particular interest is its performance with small training size, because labelled samples are usually scarce due to its high acquisition cost. The proposed spatial kernel PCA (KPCA) is compared with PCA in terms of classification accuracy with the nearest-neighbourhood classification method.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.194-197
• /
• 1999

In AVL, GIS analyze the information from the vehicles to provide commercial or other value far user. As spatial analysis functions in GIS make a new valuable information using the vehicle's position and geographic object's location, they perform an important roles to improve the management efficiency of vehicles. Most GIS however are used static data for the spatial analysis, so the research area on AVL used dynamic vehicle location has generated unsuitable result. In this study, we use GPS real time tracking data to perform spatial analysis between moving vehicle and static geographic object. The method proposed in this paper considers the driving direction of vehicle and creates the result which is located in forward of vehicle. In this paper, two spatial analysis functions, near and connectivity, are developed.

• Journal of Information Processing Systems
• /
• v.12 no.2
• /
• pp.263-274
• /
• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.