• ETRI Journal
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• 제22권1호
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• pp.1-11
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• 2000

The Satellite Operation System (SOS) has been developed for a low earth orbiting remote sensing satellite, Korea Multipurpose Satellite-I, to monitor and control the spacecraft as well as to perform the mission operation. SOS was designed to operate on UNIX in the HP workstations. In the design of SOS, flexibility, reliability, expandability and interoperability were the main objectives. In order to achieve these objectives, a CASE tool, a database management system, consultative committee for space data systems recommendation, and a real-time distributed processing middle-ware have been integrated into the system. A database driven structure was adopted as the baseline architecture for a generic machine-independent, mission specific database. Also a logical address based inter-process communication scheme was introduced for a distributed allocation of the network resources. Specifically, a hotstandby redundancy scheme was highlighted in the design seeking for higher system reliability and uninterrupted service required in a real-time fashion during the satellite passes. Through various tests, SOS had been verified its functional, performance, and inter-face requirements. Design, implementation, and testing of the SOS for KOMPSAT-I is presented in this paper.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.433-436
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• 2008

A demand on the spatial data management has been rapidly increased with the introduction and diffusion process of ITS, Telematics, and Wireless Sensor Network, and many different people use the digital map that offers various thematic spatial data. Spatial data for digital map can manage to tile-based and feature-based data. The existing tile-based digital map management systems have difficult problems of data construction, history management, and updating based on a spatial object. In order to solve these problems, this paper proposed the data model for the feature-based digital map management system that is designed for feature-based seamless map, history management, real-time updating of spatial data, and analyzed the validity and utility of the proposed model.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.363-369
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• 2024

In this paper, we develope a LOB(Limit Order Book) analyzing tool for an automated trading system, which features real-time and offline analysis of LOB data in conjunction with execution data. The 10-tier LOB data analyzer developed in this paper, which contains ask/bid prices and the execution data, receivs transaction requests in real-time from the Kiwoom Open API+ server. In the OnReceiveTrData event, the transaction data from the server is received and processed. The real-time data, triggered by the transaction, is received and processed in the OnReceiveRealData event. These two types of data are stored in a database and replayed in the same way as if it were a real-time situation in simulation mode. The LOB data are selectively read and analyzed in a necessary time points. The tool provides various features such as bar chart analysis and pattern analysis of the total shares on the bid side and ask side, which are used to develop a tool to accurately determine the timing of stock trading.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.49-52
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• 2003

In this research, we propose a mechanism to develop an inference engine and expert systems based on relational database and SQL (structured query language). Generally, former researchers had tried to develop an expert systems based on text-oriented knowledge base and backward/forward (chaining) inference engine. In these researches, however, the speed of inference was remained as a tackling point in the development of agile expert systems. Especially, the forward inference needs more times than backward inference. In addition, the size of knowledge base, complicate knowledge expression method, expansibility of knowledge base, and hierarchies among rules are the critical limitations to develop an expert systems. To overcome the limitations in speed of inference and expansibility of knowledge base, we proposed a relational database-oriented knowledge base and forward inference engine. Therefore, our proposed mechanism could manipulate the huge size of knowledge base efficiently, and inference with the large scaled knowledge base in a short time. To this purpose, we designed and developed an SQL-based forward inference engine using relational database. In the implementation process, we also developed a prototype expert system and presented a real-world validation data set collected from medical diagnosis field.

• 한국전자통신학회논문지
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• 제2권4호
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• pp.244-249
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• 2007

HL7은 병원정보 시스템에서 사용되는 정보와 관련된 표준화된 프로토콜이다. Central Monitor로부터 전송되어진 환자의 생체정보 Raw Data가 HIS의 데이터 수신 모듈을 통해 사용가능한 데이터로 재구성될 수 있도록 설계가 이루어져 있다. 환자 생체정보에 대한 실시간성과 생체정보에 대한 생체정보 데이터의 연속성을 부여함으로서 베드 사이트의 환자에게서 발생된 모든 생체정보에 의해 환자 관리가 이루어진다. 또한 보다 많은 검사장비의 데이터를 데이터베이스를 이용하여 전산화함으로서 해당 환자의 광범위한 자료 검색이 이루어지므로 획기적인 원격진료로 활용이 가능하다.

• Journal of Information Processing Systems
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• 제6권2호
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• pp.163-176
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• 2010

Nowadays due to the rapid advances in the field of information systems, transactional databases are being updated regularly and/or periodically. The knowledge discovered from these databases has to be maintained, and an incremental updating technique needs to be developed for maintaining the discovered association rules from these databases. The concept of Temporal Association Rules has been introduced to solve the problem of handling time series by including time expressions into association rules. In this paper we introduce a novel algorithm for Incremental Mining of General Temporal Association Rules (IMTAR) using an extended TFP-tree. The main benefits introduced by our algorithm are that it offers significant advantages in terms of storage and running time and it can handle the problem of mining general temporal association rules in incremental databases by building TFP-trees incrementally. It can be utilized and applied to real life application domains. We demonstrate our algorithm and its advantages in this paper.

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.265-272
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• 2022

The most effective method to improve information system capabilities is to enable instant access to several relational database sources and transform data with a logical structure into multiple target relational databases. There are numerous data transformation tools available; however, they typically contain fixed procedures that cannot be changed by the user, making it impossible to fulfill the near-real-time data transformation requirements. Furthermore, some tools cannot build object references or alter attribute constraints. There are various situations in which tool changes in data type cause conflicts and difficulties with data quality while transforming between the two systems. The R-programming language was extensively used throughout this study, and several different relational database structures were utilized to complete the proposed study. Experiments showed that the developed study can improve the performance of information systems by interacting with and exchanging data with various relational databases. The study addresses data quality issues, particularly the completeness and integrity dimensions of the data transformation processes.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.384-387
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• 2003

Most of the real world phenomena change over time. The ability to represent and to reason geographic data becomes crucial. A large amount of non-standard applications are dealing with data characterized by spatial, temporal and/or uncertainty features. Non-standard data like spatial and temporal data have an inner complex structure requiring sophisticated data representation, and their operations necessitate sophisticated and efficient algorithms. Current GIS technology is inefficient to model and to handle complex geographic phenomena, which involve space, time and uncertainty dimensions. This paper concentrates on developing a fuzzy spatio-temporal data model based on fuzzy set theory and relational data models. Fuzzy spatio-temporal operators are also provided to support dynamic query.

• International Journal of Reliability and Applications
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• 제3권4호
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• pp.155-164
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• 2002

This paper focuses on how modem data mining can be integrated with real-time relational databases and commercial data warehouses to improve reliability in real-time. An important Issue for many manufacturers is the development of relational databases that link key product attributes with real-time process parameters. Helpful data for key product attributes in manufacturing may be derived from destructive reliability testing. Destructive samples are taken at periodic time intervals during manufacturing, which might create a long time-gap between key product attributes and real-time process data. A case study is briefly summarized for the medium density fiberboard (MDF) industry. MDF is a wood composite that is used extensively by the home building and furniture manufacturing industries around the world. The cost of unacceptable MDF was as large as 5% to 10% of total manufacturing costs. Prevention can result In millions of US dollars saved by using better Information systems.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.69-74
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• 2003

This study is aimed to develop a system to position and manage object flow in real time. Logistics management system which position objects and vans using GPS is required to load, unload and keep freight effectively and in real time at sea or airport. In this study, a management system which is consisted of five sub-systems is developed; GPS position analysis system, GPS interface system, mapping system, network system and database management system.