• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.23-37
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• 2004

Location Based Services(LBSs) in mobile environments become very popular recently. For efficient LBSs, spatial database management systems must need a spatial indexing scheme such as R-trees in order to manage the huge spatial database. However, it may need unnecessary disk accesses since it needs to access objects which are not actually concerned to user's location-based queries. In this paper, to support the location-based queries efficiently, we propose a CLR-tree(Cell Leveling R-tree) in which a dynamic cell is built up within the minimum bounding rectangle of R-trees' node. The cell level of nodes is compared with the query's cell level in location-based query processing and determines the minimum search space. Also, we propose the insertion, split, deletion, and search algorithms for CRL-trees. From the experimental results, we see that a CLR-tree is able to decrease $5{\sim}20%$ of disk accesses from those of R-trees. So, a CLR-tree can be used for fast accessing spatial objects to user's location-based queries in LBSs.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.65-74
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• 2003

Location-based service is an important spatiotemporal database application area that provides the location-aware information of wireless terminals via positioning devices such as GPS. With the rapid advances of wireless communication systems, the requirement of mobile application areas including traffic, mobile commerce and supply chaining management became the center of attention for various research issues in spatiotemporal databases. In this paper we present the A-Quadtree, an efficient indexing method for answering location-based queries where the movement vector information (e.g., speed and velocity) is not presented. We implement the A-Quadtree with an index structure for object identifiers as a.Net component to apply the component to multiplatforms. We present our approach and describe the performance evaluation through various experiments. In our experiments, we compare the performance with previous approaches and show the enhanced efficiency of our method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.133-138
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• 2005

Automotive pulleys play a key role in driving the cooling pump, oil pump, air-conditioner and so on by using an engine power. Researches on design processes and technologies of the pulleys can be found in many literatures. On the other hand, the areas related to manufacturing processes of the pulleys have been treated negligently. Vast data extracted from various information systems are transformed, integrated, and summarized to become a special database for helping users make a decision. The database, namely the data warehouse has been popularly used in the marketing and customer management of enterprises and recently applied to improve the design and manufacturing processes. In this study the manufacturing process of pulleys were analyzed through the intensive investigation of shop-floors and the interviews with workers and managers. The defects generated during a manufacturing process were categorized in a few types and the causes of defects examined for extracting the dominant parameters in the setup process for producing pulleys. As the first step to construct the data warehouse for the manufacturing processes of pulleys, authors proposed its architecture focused on the reduction of defect rate during the setup process.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.21-30
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• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.331-334
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• 2007

As information renewal period comes to be quick recently, the need that IRS must have data management facilities such as transaction processing, join, view, trigger is extending. Therefore, DB-IR(Database ? Information Retrieval) Integration is a recent budding area of interest in the research fields of database area and information retrieval area. Since the role of DB-IR integration systems is different from those of DBMS or IRS, It is necessary to be a new design of structure for DB-IR integration system. We have designed a new server structure for efficiency and stability of DB-IR integration system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.151-156
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• 2017

In case of massive water leakage, it's crucial for field manager to quickly positioning the problematic valve and related ones. However, it's not easy for the system to find the corresponding valve and even if it's found, it can not respond quickly because it can't know the relevant information immediately. In this paper, we implement the system for identifying sluice valve positions using GPS and AR techniques. The proposed system is composed of hand held android device, remote database server and data acquisition device for DB creation. We utilize the android device's sensors including GPS, gyro, accelerometer, magnetic sensor. The system identifies the valve with matching between the position data from the remote database server, and current GPS locations of device. We use AR techniques to overlay the graphics pattern of valve positions and some additional informations on captured real scene. With this system, it will be fast and accurate for maintenance of sluice valve of municipal water system.

• Spatial Information Research
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• v.18 no.4
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• pp.141-149
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• 2010

One of recent trends in Web-based GIS is the system development using FOSS (Free and Open Source Software). Open Source software is independent from the technologies of commercial software and can increase the reusability and extensibility of existing systems. In this study, we developed a Web-based GIS for interactive visualization of geographic information using Google Earth and spatial DBMS(database management system). Google Earth Plug-in and Google Earth API(application programming interface) were used to embed a geo-browser in the Web browser. In order to integrate the Google Earth with a spatial DBMS, we implemented a KML(Keyhole Markup Language) generator for transmitting server-side data according to user's query and converting the data to a variety of KML for geovisualization on the Web. Our prototype system was tested using time-series of LAI(leaf area index), forest map, and crop yield statistics. The demonstration included the geovisualization of raster and vector data in the form of an animated map and a 3-D choropleth map. We anticipate our KML generator and system framework will be extended to a more comprehensive geospatial analysis system on the Web.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1189-1197
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• 2013

Data mining is the process of analyzing a huge database from different perspectives and summarizing it into useful information. One of the well-studied problems in data mining is association rule generation. Association rule mining finds the relationship among several items in massive volume database using the interestingness measures such as support, confidence, lift, etc. Typical applications for this technique include retail market basket analysis, item recommendation systems, cross-selling, customer relationship management, etc. But these interestingness measures cannot be used to establish a causality relationship between antecedent and consequent item sets. This paper propose causal association thresholds to compensate for this problem, and then check the three conditions of interestingness measures. The comparative studies with basic and causal association thresholds are shown by numerical example. The results show that causal association thresholds are better than basic association thresholds.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.473-482
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• 2001

Integrated heterogeneous database systems provide the unified interface for users and applications today in order to access the underlying diverse data sources located in different sites. The multiple heterogeneous data sources have the different and specialized data structures and transaction processing capabilities. Because of local autonomy, the local system does not have the capability of cooperation to control the global transaction. Hence designing the global transaction manager with supporting the global serializability is difficult task. To resolve the well-known indirect conflict, we define the global transaction model by using the characteristics of global integrity constraints. And then we propose the site-locking operation and its protocol to manage the global transaction. The correctness and analysis of our site-locking protocol is proved and performance gain over the related other methods is also estimated in this paper.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.121-128
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• 2010

Spatial data mining has been developed to support spatial association knowledge between spatial features or its non-spatial attributes for an application areas. At the present time, a number of researchers attempt to the data mining techniques apply to the several analysis areas, for examples, civil engineering, environmental, agricultural areas. Despite the efforts that, until such time as not existed practical systems for the gCRMDMs. gCRMDMs is merged with very large spatial database and CRM information system. Also, it is discovery the association rule for the predictions of customer's shopping pattern informations in a huge database consisted with spatial and non-spatial dataset. For this goal, gCRMDMs need spatial data mining techniques. But, nowadays, in a most case not exist utilizable model for the gCRMDMs. Therefore, in this paper, we proposed a practical gCRMDMs model to support a customer, store, street, building and geographical suited to the trade area.