• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2281-2293
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• 1999

Many applications such as nuclear power plant monitoring, plant process control, stock market management, and network data management require a database system supporting both temporal data model and active rule processing. There have been some efforts to extend the temporal functionalities of the active database system, but an active database system based on temporal database, especially the one applied to the real application is rare. In this paper, we proposed an active temporal rule model based on bi-temporal database. And a rule language following the proposed rule model was described with its execution semantics. Then, how to apply to the nuclear power plant monitoring system was given as the examples.

• Journal of Internet Computing and Services
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• v.1 no.1
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• pp.15-26
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• 2000

To efficiently manage data varying over time and process event driven transactions, some of the various database applications recently emerged require database systems supporting both a temporal data model and active rule processing. There has been much progress in independent research on temporal databases and active databases, but studies on databases which support both functions, have been rare. In this paper, an active temporal rule model supporting both active rule processing and temporal data model is presented with its rule expression language. This active temporal rule model contributes to the active function extension of the temporal database, and to establishing the concept of data access events which refer temporal attributes of data in active rules.

• Spatial Information Research
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• v.18 no.1
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• pp.77-87
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• 2010

Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1671-1679
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• 1998

Temporal databases support an efficient hist0rical representation and operation for an object in the real world. Especiallv, temporal aggregates generate In additional by information by means of computations from objects that is valid at past as well as current time. It is one of important areas to serve to users as various type of aggregates as possible so that they enhance the overall system performance and efficiency. In this paper, we not only introduce temporal aggregate tree strategy as an efficient processing technique for given temporal aggregate query, but also analyze the ovemll processing cost and then evaluate its perfomlance.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.168-170
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• 2003

In this paper, we discuss the concept of Spatio-Temporal Data Warehouse and analyze the organization model of spatio-temporal data. Based on the above, we found the framework of Spatio-Temporal Data Warehouse composed of data source, processing tools and application, which covers the whole process from building warehouse to supplying services.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.163-171
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• 1994

The paper describes a design and implementation of a user interface system between a temporal database management system (DBMS) and a graphical display system. This interfacing system consists of a temporal DBMS, a graphical display system, and an interface control system. The temporal DBMS supports time and the graphical display system draws a graphic using an icon. The interfacing system shows the graphical animation with time factors by using a graphical knowledgeable. We describe how to interface them as well as the structure of temporal DBMS and graphical display system.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1661-1664
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• 2000

내용 기반의 비디오 검색에 있어 텍스처는 중요한 변수로 사용될 수 있다. 모든 물체의 표면은 독특한 성질을 보유하고 있으므로, 텍스처는 형상이나 색과 더불어 중요한 변수로 사용될 수 있다. 어떤 영상의 특징을 올바르게 추출하고 잘 분류하여 표현하는 것은 비디오 검색에 있어서 매우 중요하다. Temporal texture는 무한한 시공간적 범위의 복잡하고, 추상적인 움직임 패턴이며 자연 세계에 흔히 나타난다. 그러므로 이를 특징화시킬 수 있고, temporal texture 패턴을 얼마나 잘 이용할 수 있느냐는 비디오 검색의 성능에 많은 영향을 끼칠 수 있다. 본 논문은 temporal texture 모델링들 중 서로 다른 특징을 가진 세 가지의 모델을 선정하여 비교, 분석한다. 특히, 특징 추출의 분류가 정확하게 이루어지느냐에 초점을 맞추어서 분석하였다. 분류의 성능은 두 가지 변수 즉, 어떤 성질의 모델이며 비디오 데이터인가에 따라 달라지게 된다. 이들 모델링이 분류하기까지 걸리는 시간의 차이는 무시할 수 있을 정도의 시간차이므로, 정확도를 위주로 성능을 분석했다.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.395-411
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• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

• The Journal of the Acoustical Society of Korea
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• v.16 no.1E
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• pp.3-8
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• 1997

Three new classification methods for multi temporal images are proposed. They are named as a likelihood addition method, a likelihood majority method and a Dempster-Shafer's rule method. Basic strategies using these methods are to calculate likelihoods for each temporal data and to combine obtained likelihoods for final classification. These three methods use different combining algorithms. From classification experiments, following results were obtained. The method based on Dempster-Shafer's rule of combination showed about 12% improvement of classification accuracies compared to a conventional method. This method needed about 16% more processing times than that of a conventional method. The other two proposed method showed 1% to 5% increase of classification accuracies. However processing times of these two proposed method showed 1% to 5% increase of classification accuracies. However processing times of these two methods are almost the same with that of a conventional method. Among the newly proposed three methods, the Dempster-Shafer's rule method showed the highest classification accuracies with more processing time than those of other methods.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.143-148
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• 2006

The goal of this paper is to analyze, through simulations and experiments, GNSS interference mitigation performance under various types of antenna structures against wideband and narrowband interferences using spatial-temporal adaptive signal processing (STAP) techniques. The STAP approach, which combines spatial and temporal processing, is a viable means of GNSS array signal processing that enhancing the desired signal quality and providing protection against interference. In this paper, we consider four types of 3D antenna array structure - Uniform Linear Array (ULA), Uniform Rectangular Array (URA), Uniform Circular Array (UCA), and the Single-Ring Cylindrical Array (SRCA) under an interference environment. Analytical evaluation and simulations are performed to investigate the system performance. This is followed by simulation GPS orbits in interfered environment are used to evaluate the STAP performance. Furthermore, experiments using a 2x2 URA hardware simulator data show that with the removal of wideband and narrowband interference through the STAP techniques, the signal tracking performance can be enhanced.