• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.5-20
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• 1999

Recently, the new software paradigm in information technology (IT) is the component-based development (CBD) technology that has brought as a result of the distributed computing environment (DCE). The CBD has reduced a program developing time and has been designed to make a distributed computing environment easier in the Internet and Intranet environments. These changes of software technology have influence on the geographic information system (GIS) and the CBD technology is highly needed as a point of view of the technique and policy of the geographic information system. In this paper, we designed and implemented an Enterprise Server for the efficient development and management of GIS components. Especially, the Enterprise Server was developed with the Enterprise JavaBeans Specification 1.1 that had been proposed as an industry standard by the Sun Microsystems. The Enterprise Server can allows users to manage the Unified Modeling Language (UML) and Design Patterns for the development of GIS components, develop a GIS component container which obeyed the Open Geodata Interoperability Specification (OpenGlS), manage spatial metadata through a spatial XML (eXtensible Markup Language) engine, and implement a TESTBED server for testing and verification of developed GIS components.

• Journal of Korea Spatial Information System Society
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• v.2 no.1 s.3
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• pp.5-16
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• 2000

OGC(Open GIS Consortium) suggests the 'OpenGIS Simple Feature Specification for CORBA' which is the OpenGIS implementation specification for CORBA to specify standard interfaces for reuse and interoperation among distributed heterogeneous GIS resources in the CORBA distributed computing environment. An OpenGIS server that supports this implementation specification moat correctly implement all interfaces defined in the OpenGIS implementation specification to be interoperable with wrapped GISs efficiently. In this paper, we have designed and implemented an OpenGIS server based an object relational GIS, called GEUS that integrates GIS and database technologies to provide spatial data types and spatial operators from the DBMS engine level. In the CORBA distributed computing environment, clients can access geospatial data stored in GIS wrapped by the OpenGIS server through the standard interfaces defined in the OpenGIS implementation specification for CORBA. In addition, clients can use geospatial operation features provided by a back-end GIS and interoperate with other GISs.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.87-97
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• 2018

Rainfall depth is an important meteorological information. Generally, high spatial resolution rainfall data such as road-level rainfall data are more beneficial. However, it is expensive to set up sufficient Automatic Weather Systems to get the road-level rainfall data. In this paper, we proposed to use deep learning to recognize rainfall depth from road surveillance videos. To achieve this goal, we collected two new video datasets, and proposed a new deep learning architecture named Temporal and Spatial Segment Networks (TSSN) for rainfall depth recognition. Under TSSN, the experimental results show that the combination of the video frame and the differential frame is a superior solution for the rainfall depth recognition. Also, the proposed TSSN architecture outperforms other architectures implemented in this paper.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.1-10
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• 2004

According to the evolution of the Internet and wireless mobile communication technology, techniques for mobile databases and wireless web services are issued for them. Recently, these changes of geographic application environment increase the needs for development of new GIS database system for the web services and embedded system. In this paper, we proposed a Jana-based web database systems that can be used in the web-based GIS and mobile databases. This proposed system has been implemented using the Java to be displayed easily into the portable computing devices and Java-based web application servers and using OpenGIS for web data interoperability. Also, it can efficiently process web-based spatial queries by developing a spatial query processor including schema manager and a spatial object storage module.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.36-40
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• 2008

SIMS manages data for various spatial and non-spatial as integral management system to support space information administration environment and support several application works. Without being limited to spatial data that existent spatial Data Mining question language advances handling in this paper, did so that can find useful information from various data connected with automatically data collection, artificial satellite side upside service, remote sensing, GPS. Mobile Computing and data about Spatio-Temporal. Also, we designed spatial Data Mining query language that support a spatial Data Mining exclusive use system based on SIMS.

• International Journal of Contents
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• v.1 no.1
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• pp.50-58
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• 2005

Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1284-1286
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• 2003

There is a growing demand on remotely sensed and GIS data services in modern society. However, conventional WEB applications based on client/server pattern can not meet the criteria in the future . Grid computing provides a promising resolution for establishing spatial information system toward future applications. Here, a new architecture of the distributed environment for remotely sensed data processing based on the middleware technology was proposed. In addition, in order to utilize the new environment, a problem had to be algorithmically expressed as comprising a set of concurrently executing sub-problems or tasks. Experiment of the algorithm was implemented, and the results show that the new environmental can achieve high speedups for applications compared with conventional implementation.

• Journal of KIISE:Databases
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• v.30 no.1
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• pp.64-79
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• 2003

In client-server computing environments, update transactions of spatial data have the following characteristics. First, a transaction to update maps needs interactive work, and therefore it nay take a long time to finish. Second, a long transaction should be allowed to read the dirty data to enhance parallelism of executing concurrent transactions. when %he transaction is rolled back, it should guarantee the cascading rollback of all of the dependent transactions. Finally, two spatial objects may have a weak dependency constraint, called the spatial relationship, based on geometric topology. The existing recovery approaches cannot be directly applied to this environment, due to the high rollback cost and the overhead of cascading rollbacks. Furthermore, the previous approaches cannot guarantee the data integrity because the spatial relationship, which is a new consistency constraint of spatial data, is not considered. This paper presents new recovery schemes for update transactions of spatial data. To guarantee the data integrity, this paper defines recovery dependency as a rendition of cascading rollbacks. The partial-rollback is alto suggested to solve the problem of high rollback cost. The recovery schemes proposed in this paper can remove the unnecessary cascading rollbacks by using undo-delta, partial -redo and partial-undo. Finally, the schemes are performed to ensure the correctness.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.397-406
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• 2014

In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.339-352
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• 2009

There are a number of formal methods for distributed real-time systems in ubiquitous computing to analyze and verify the behavioral, temporal and the spatial properties of the systems. However most of the methods reveal structural and fundamental limitations of complexity due to mixture of spatial and behavioral representations. Further temporal specification makes the complexity more complicate. In order to overcome the limitations, this paper presents a new formal method, called Timed Calculus of Abstract Real-Time Distribution, Mobility and Interaction(t-CARDMI). t-CARDMI separates spatial representation from behavioral representation to simplify the complexity. Further temporal specification is permitted only in the behavioral representation to make the complexity less complicate. The distinctive features of the temporal properties in t-CARDMI include waiting time, execution time, deadline, timeout action, periodic action, etc. both in movement and interaction behaviors. For analysis and verification of spatial and temporal properties of the systems in specification, t-CARDMI presents Timed Action Graph (TAG), where the spatial and temporal properties are visually represented in a two-dimensional diagram with the pictorial distribution of movements and interactions. t-CARDMI can be considered to be one of the most innovative formal methods in distributed real-time systems in ubiquitous computing to specify, analyze and verify the spatial, behavioral and the temporal properties of the systems very efficiently and effectively. The paper presents the formal syntax and semantics of t-CARDMI with a tool, called SAVE, for a ubiquitous healthcare application.