• 한국정보과학회논문지:소프트웨어및응용
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• 제37권2호
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• pp.148-154
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• 2010

불확실성 데이터베이스의 의미론 정의는 보통 주어진 불확실성 데이터베이스를 여러 개의 관계형데이터베이스로 변환하는 산술적 접근방법을 취한다. 이 논문에서는 불확실성데이터베이스를 논리이론으로 변환하는 논리적 접근방법을 통해서 불확실성 데이터베이스의 의미론을 정의하고자 한다. 본 논문에서 제안하는 의미론의 가장 특징적인 면은 기존의 논리적 접근방법에서 사용해온 명제논리 대신에 선형논리를 논리적 근간으로 이용한다는 점이다. 선형논리는 논리식을 불변진리가 아닌 소비가능한 자원으로 해석하기 때문에 불확실성 데이터베이스의 의미론을 정의하는데 적합하다. 본 논문의 핵심 결과는 선형논리에 기반한 불확실성 데이터베이스의 의미론이 산술적 접근방식에서 설명하는 불확실성 데이터베이스의 의미론과 동등하다는 것이다.

• Journal of Astronomy and Space Sciences
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• 제20권4호
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• pp.403-416
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• 2003

There are common features, in both imaging surveys and image processing, between astronomical observations and remote sensing. Handling large amounts of data, in an easy and fast way, has become a common issue. Implementing pipeline software can be a solution to the problem, one which allows the processing of various kinds of data automatically. As a case study, the development of pipeline software for the EIS (European Southern Observatory Imaging Survey) is introduced. The EIS team has been conducting a sky survey to provide candidate targets to the 250 VLTs (Very Large Telescopes) observations. The survey data have been processed in a sequence of five major data corrections and reductions, i.e. preprocessing, flat fielding, photometric and astrometric corrections, source extraction, and coaddition. The processed data are eventually distributed to the users. In order to provide automatic processing of the vast volume of observed data, pipeline software has been developed. Because of the complexity of objects and different characteristic of each process, it was necessary to analyze the whole works of the EIS survey program. The overall tasks of the EIS are identified, and the scheme of the EIS pipeline software is defined. The system structure and the processes are presented, and in-depth flow charts are analyzed. During the analyses, it was revealed that handling the data flow and managing the database are important for the data processing. These analyses may also be applied to many other fields which require image processing.

• 상하수도학회지
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• 제31권6호
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• pp.619-628
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• 2017

As the 3D laser scanning technology capable of databaseing large sewage box culverts becomes possible, it is necessary to develop a standardization manual that can clearly distinguish the structural and operational defect types of box culver and analyze the defect data. In this study, we collected and analyzed defects in sewage box culverts of 14,827m in total by selecting three districts in Korea. The major defects were surface damages, and their defect densities were $2.17m^2/m$, $0.27m^2/m$ and $0.10m^2/m$ for aggregate exposure, Steel reinforcement exposure, and Steel reinforcement projecting. In order to support the decision of the box culverment management, it was divided into five grades and each defect code and defect score were allocated. The results of this study are useful for the diagnosis of the sewage box culverts in Korea and it is expected to support a decision making for management.

• 전자공학회논문지
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• 제52권10호
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• pp.148-158
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• 2015

수중음향 채널환경에서 운영되는 검파시스템 성능분석은 실험의 제약으로 인해 모의 도구를 활용하여 시스템 성능을 결정한다. 본 논문은 수중음향 채널에 대한 탐지 효과도 분석을 위하여 수중환경 데이터베이스를 기반 수중음향 탐지 효과도 분석 모의 도구를 제안한다. 먼저, HYCOM 수중환경 데이터베이스 기반으로 수중 환경을 구축하고, 음선이론을 이용하여 수중음향 전달 경로/음압 계산을 통한 다중경로 지연 특성을 고려하였다. 또한, 실 환경에서 발생하는 수중 잡음 특성을 반영하기 위해 운용 주파수에 따른 수중청음기/수중음향 채널 잡음 특성인 열잡음/수중 주변 잡음을 적용하였다.

• 터널과지하공간
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• 제9권3호
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• pp.214-220
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• 1999

본 연구에서는 RMR system항목들의 타당성을 평가하였고 국내현장에서 측정한 데이터에 대한 적용성을 검토하였다. 데이터베이스는 전국에 걸쳐 지하철, 철도, 도로 터널로 구분하여 139개 현장으로부터 작성하였다. Bieniawsk의 원분류는 경험적으로 도출되었지만 비교적 타당한 것으로 분석되었다. 그러나 국내 현장에 적용할 때에는 상당한 차이가 있어서 국내의 데이터베이스로 추론한 새로운 암반분류 시스템 KRMR1과 KRMR2를 제안하였다. KRMR1에서는 인자들의 등 급비중을 조정하였으며 KRMR2에는 2개의 인자를 추가하였다. 이 과정에서 암반의 성질을 평가하는 ‘특성치’의 선택이 어려워 인공신경 망을 이용하여 추론하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 The 6th International Symposium of East Asian Resources Recycling Technology
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• pp.693-698
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• 2001

This paper establishes a coding method system including the liberation and size distribution of recycling materials in the shredder operation. Every particle in the shredded product becomes a code number using the liberation model and size distribution equation transforming of weight percentage into particles number percentage. One set of database can be obtained after all particles have been coded. This database is suitable for the size reduction operation in the process simulation of waste recycling. Coupling with the developed air classification, sizing and separating operations, the whole process simulation will be completely established for diversified application. A typical simulation for the rolling cutting shredder product of waste TV had been demonstrated under this coding system. The breakage size distribution of Gaudin and Schumann equation were selected for the shredding operation simulation. The Gaudin's liberation model was suitable fur the liberation simulation. Both of these equations were transformed weight percentage into particles distribution for the necessary of particle coding method. A better recycling operation for this shredded solid waste can be concluded from the comparison of simulation results with their sorted grade, recovery or economic of materials in different processes.

• 대한기계학회논문집B
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• 제27권3호
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• pp.398-405
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• 2003

A fast response analyzer for measuring carbon dioxide concentration has been developed for transient characteristic and researches tested on internal combustion engine. The analyzer uses the well known NDIR(Non-Dispersive Infrared) method with miniaturized detection system, giving a time constant of approximately 30 microsecond, and sampling module consists of capillary tube. Since the transit time and the time constant of the sampling system depend on the sampling conditions, it is necessary to investigate the characteristics of sampling system before applied to exhaust gas measurement in engine. A unique method was designed to study the influence of the diameter of transfer sample line and operating conditions of the FRNDIR on transit time and time constant. A database of transit time and time constant was built up for different measured and simulated pressure conditions. The database can be used for correcting eventual $CO_2$ concentration measurement.

• 한국정보통신학회논문지
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• 제9권4호
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• pp.865-870
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• 2005

최근 GPS 및 무선통신 기술과 더불어 위치 정보시스템의 발전은 텔레매틱스 응용의 급속한 진전을 이루었다. 텔레매틱스를 위한 이동체 데이터베이스에서는 사용자에게 이동체의 실시간 현재 위치 정보를 제공하는 것만큼 그 질의 결과의 유효시간 또한 매우 중요하다. 따라서 본 논문에서는 질의 점과 객체가 동시에 이동 중일 때 현재 질의 결과를 계산하는 방법과 그 질의 결과의 유효시간 및 유효시간 후의 질의 결과를 검객하는 방안을 제안한다. 이동 객체는 실시간으로 변화하기 때문에 현재 질의 결과가 조금만 시간이 지나도 잘 못된 정보가 될 수 있고 미래의 결과를 반복연산에 의해 계산하기 어렵기 때문에 우리는 수학식으로 유효 시간을 예측하고자 하는 것이다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권10호
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• pp.1167-1167
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• 1999

Although spatial databases support an efficient spatial management on objects in the real world, they have a characteristic that process only spatial information valid at current time, So in case of change in the spatial domain, it is very hard to support an efficient historical management for time-varying spatial information because they delete an old value and then replace with new value that is valid at current time. To solve these problems, there are rapidly increasing of interest for spatiotemporal databases, which serve historical functions for spatial information as well as spatial management functions for an object. However most of them presented in an abstract time-varying spatial phenomenon, but have not presented a concrete policy in spatiotemporal databases. In this paper, we propose a spatiotemporal data model that supports bitemporal time concepts in three dimensional architecture. In the proposed model, not only data types and their operation for object of spatiotemporal databases have been classified, but also mathematical expressions using formal semantics for them have been given. Then, the data structures and their operations based on relational database model as well as object-oriented database model are presented.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.594-597
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• 2007

We present in this paper a novel mid and long term power load prediction method using temporal pattern mining from AMR (Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.