• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.159-166
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• 2008

Recently, according to the rapid development of location positioning technology and wireless communications technology and increasement of usage of moving object data, many researches and developments on the real-time locating systems which provides real time service of moving object data stream are under proceeding. However, MO (Moving Object) DBMS used based system in the in these systems is the inefficient management of moving object data streams, and the existing DSMS (Data Stream Management System) has problems that spatio-temporal data are not handled efficiently. Therefore, in this thesis, we designed and implemented spatio-temporal DSMS for efficient real-time management of moving object data stream. This thesis implemented spatio-temporal DSMS based STREAM (STanford stREam dAta Manager) of Stanford University is supporting real-time management of moving object data stream and spatio-temproal query processing and filtering for reduce the input loading. Specifically, spatio-temporal operators of the spatio-temporal DSMS support standard interface of SQL form which extended "Simple Feature Specification for SQL" standard specifications presented by OGC for compatibility. Finally, implemented spatio-temporal DSMS in this thesis, proved the effectiveness of the system that as applied real-time monitoring areas that require real-time locating of object data stream DSMS.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.5 s.23
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• pp.17-28
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• 2002

Time is regarded as an essential feature of land information enabling to track historical landmarks of land uses, ownerships, and taxations based on cadastral maps. Object-oriented temporal modeling helps to simulate and imitate time-varying cadastral data in a chronological and persistent manner. The aim of study is to analyze the role of temporal cadastre tracing footprints of foregoing events in response to various needs and demands associated with historical information of cadastral transactions. In this paper, temporal cadastral object model (TCOM) is proposed to delineate object version history. As an evidence of a new approach and conceptual idea for the importance of temporal cadastre, a part of spatio-temporal processes is illustrated to explain major changes of cadastral map. The feasibility and application of the approach is confirmed by proof-of-concept of temporal cadastre in land information management.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.564-566
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• 2003

There are no immutable phenomena in reality. A lot of applications are dealing with data characterized by spatial and temporal and/or uncertain features. Currently, there has no any data model accommodating enough those three elements of spatial objects to directly use in application systems. For such reasons, we introduce a fuzzy spatio -temporal data model (FSTDM) and a method of integrating temporal and fuzzy spatial operators in a unified manner to create fuzzy spatio -temporal (FST) operators. With these operators, complex query expression will become concise. Our research is feasible to apply to the management systems and query processor of natural resource data, weather information, graphic information, and so on.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.877-882
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• 2005

We propose a strategy to manage temporal data which are occurred on scientific applications. Firstly, We define LB and RB to separate temporal data, and entity versions to be stored in past, current, future segments. Also, We describe an algorithm to migrate temporal data with hotspot distribution among segments. The performance evaluation of average response time and space utilization is conducted. Average response time between two methods is similar, and space is saved in proposed method.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.252-264
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• 1999

The key characteristic of video data is its spatial/temporal relationships. In this paper, we propose an content based video retrieval system based on hierarchical data structure for specifying the temporal semantics of video data. In this system, video data's hierarchical structure temporal relationship, inter video object temporal relationship, and moving video object temporal relationship can be represented. We also implemented these video data's temporal relationship into an object-relational database management system using inheritance, encapsulation function overloading, etc. So more extended and richer temporal functions can be used to support a broad range of temporal queries.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.80-80
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• 1999

As Temporal DataBase Systems(TDBSs) manages both the historical versions and the current version of each data item, a temporal transaction may access more data records than atransaction in traditional database systems. Hence, the concurrency control subsystem of temporaldatabase management system should be able to correctly and efficiently detect actual conflicts amongconcurrent temporal transactions while the cost of detecting conflicts is maintained in low levelwithout detecting false conflicts which cause severe degradation of system throughput.In this paper, Two-Level Conflict Detection(TLCD) scheme is proposed for efficient conflictdetection between concurrent temporal transactions in TDBs. In the proposed TLCD scheme, sincechecking conflict between concurrent temporal transactions is performed at two levels, i, e., logicallevel and physical level, conflicts between concurrent temporal transactions are efficiently and correctlydetected,Furthermore, we also evaluate the performance of the proposed TLCD scheme with those oftraditional conflict detection schemes, logical-level conflict detection scheme and physical-level conflictdetection scheme by simulation approach, The result of the simulation study shows that the proposedTLCD scheme outperforms the previous conflict detection schemes with respect to the averageresponse time.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.753-758
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• 2005

This study attempts at building an integrated GIS computing framework for evaluating space-time accessibility of an individual with the approach of time geography model. The proposed method is based on the integration of mobile GIS and object-relational spatio-temporal database. Three components are central to our system: ( i ) mobile GIS application that transmits spatio-temporal trajectory data of an individual; ( ii ) spatio-temporal database server that incorporates the time geography model; and (iii) geovisualization client that provides time geographic queries to the spatio-temporal database. As for the mobile GIS application, spatio-temporal trajectory data collected by GPS-PDA client is automatically transmitted to the database server through mobile data management middleware. The spatio-temporal database server implemented by extending a generic DBMS provides spatio-temporal objects, functions and query languages. The geovisualization client illustrates 3D visual results of the queries about space-time path. space-time prism and space-time accessibility. This study shows a method of integrating mobile GIS and DBMS for time geography application, and presents an appropriate spatio-temporal data model for evaluating space-time accessibility of an individual.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.535-544
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• 2018

As the spread of mobile devices equipped with various sensors and high-quality wireless network communications functionsexpands, the amount of spatio-temporal data generated from mobile devices in various service fields is rapidly increasing. In conventional research into processing a large amount of real-time spatio-temporal streams, it is very difficult to apply a Hadoop-based spatial big data system, designed to be a batch processing platform, to a real-time service for spatio-temporal data streams. This paper extends the MapReduce online framework to support real-time query processing for continuous-input, spatio-temporal data streams, and proposes a load management method to distribute overloads for efficient query processing. The proposed scheme shows a dynamic load balancing method for the nodes based on the inflow rate and the load factor of the input data based on the space partition. Experiments show that it is possible to support efficient query processing by distributing the spatial data stream in the corresponding area to the shared resources when load management in a specific area is required.

• Spatial Information Research
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• v.16 no.2
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• pp.219-236
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• 2008

Data stream collected from sensors contain a large amount of useful information including causality relationships. The causality join query for data stream is to retrieve a set of pairs (cause, effect) from streams of data. A part of causality pairs may however be lost from the query result, due to the delay from sensors to a data stream management system, and the limited size of sliding windows. In this paper, we first investigate spatial, temporal, and spatio-temporal aspects of the causality join query for data stream. Second, we propose several strategies for sliding window management based on these observations. The accuracy of the proposed strategies is studied by intensive experiments, and the result shows that we improve the accuracy of causality join query in data stream from simple FIFO strategy.