• Communications of the Korean Institute of Information Scientists and Engineers
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• v.4 no.2
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• pp.34-44
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• 1986

A data base system for a minicomputer, designed on the basis of the concept of Relational model, is proposed in this thesis. It is a module of reentrant programs, which can serve multi-users concurrently and interactivelv. Relational calculus is chosen as a data sublanguage. The inverted-list file structure is used for the physical storage structuse with the technique of seperating data and their relationships, while data model records, which contain the information of the logical data organization and linkage to a physical structure, con struct the data model. The retrieval is performed mainly with these.

• Journal of the Korean Society for Nondestructive Testing
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• v.9 no.2
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• pp.67-72
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• 1989

In nuclear power plants, nondestructive examinations(NDE) plays an important role in ensuring the integrity and reliability operation. As the number of plants and operational time increased, manual handling of voluminous data associated with PSI/ISI(preservice/inservice inspection) could result in many errors or mistakes in writing the examination plan or other reports. Several new approaches to process the data have been attempted and DBMS(Data Base Management System) has been well known concept with a faster and more accurate data processing. This paper proposes an application program, called NDTSYS designed with DBMS in micro computer. The program could be used for a tool to add new records to a data base, change existing records, delete records and request reports with the data base. It would be helpful to the user who manage the PSI/ISI data with minimal time and effort.

• Nuclear Engineering and Technology
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• v.24 no.1
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• pp.1-13
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• 1992

A one-group cross section data base of the ORIGEN2 computer code was developed for research reactor applications. For this, ENDF/B-IV and -V data were processed using the NJOY code system into 69-group data. The burnup-dependent weighting spectra for KMRR were calculated with the WIMS-KAERI computer code, and then the 69-group data were collapsed to one-group using the spectra. The ORIGEN2-predicted burnup-dependent acti-nide compositions of KMRR spent fuel using the newly developed data base show a good agreement with the results of detailed multigroup transport calculation. In addition, the burnup characteristics of KMRR spent fuel was analyzed with the new data base.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1063-1072
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• 2002

Characteristics of a guitar sound changes according to the internal structure a guitar. The developed system uses a PC to analyze a guitar sound, which will have different characteristics in accordance with the internal structure of the guitar and the material that the guitar made, and make a data base. The developed system consist of three parts; a mechanical body which holds a guitar and the internal structure of the guitar can be changed easily; DSP sound acquisition boards which have multi channel sound input and A/D converting abilities with RS232C data transfer to PC abilities; and software which runs on a PC to analyze the input sound and make a data base.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.59-67
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• 2013

Compared to the conventional Hardware-oriented base stations, Software Defined Radio (SDR)-based base station provides various advantages especially in flexibility and expandability. It enables the multimode capability required in 4th-generation (4G) environment which aims at a convergence network of various kinds of communication standards. However, since a single base station processes all data required in various multiple waveforms, the SDR base station faces a problem of data processing speed. In this paper, we propose a new concept of SDR base station system which adopts a parallel processing technology of clustering environment. We implemented a WiMAX system with SDR concept which adopts the Message Passing Interface (MPI) technology which enables the speed-up operations. In order to maximize the efficiency of parallel processing in signal processing, we analyze how the algorithm at each of modules is related to data to be processed. Through the implemented system, we show a drastic improvement in operation time due to parallel processing using the proposed MPI technology. In addition, we demonstrate a feasibility of SDR system for 4G or even beyond-4G as well.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1336-1345
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• 2002

Materialized views in data warehouse play important roles in rapidly answering to users's requests for information Processing. More views in data warehouse, can respond to the users more rapidly because the user's requests may be processed by using only the materialized views with higher probabilities rather than accessing base relations. The limited duration, during which the materialized views are updated due to base relations's changes, limits the number of materialized views in data warehouse. In this paper, we propose efficient policy for updating the materialized views, which can save the update duration of views although MIN/MAX values frequently change in base relation. The policy updates the materialized views by distinguishing whether MIN/MAX values's changes in the base relation are insert value or delete value. Then, the number of accesses to the base relation is descreased when updating the MIN/MAX values in the materialized views.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.247-250
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• 2003

Due to the increasing use of very large databases, mining useful information and implicit knowledge from databases is evolving. However, most conventional data mining algorithms identify the relationship among features using binary values (TRUE/FALSE or 0/1) and find simple If-THEN rules at a single concept level. Therefore, implicit knowledge and causal relationships among features are commonly seen in real-world database and applications. In this paper, we thus introduce the mechanism of mining fuzzy association rules and constructing causal knowledge base form database. Acausal knowledge base construction algorithm based on Fuzzy Cognitive Map(FCM) and Srikant and Agrawal's association rule extraction method were proposed for extracting implicit causal knowledge from database. Fuzzy association rules are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. It integrates fuzzy set concept and causal knowledge-based data mining technologies to achieve this purpose. The proposed mechanism consists of three phases: First, adaptation of the fuzzy membership function to the database. Second, extraction of the fuzzy association rules using fuzzy input values. Third, building the causal knowledge base. A credit example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstration the effectiveness of the proposed algorithm.

• Journal of computational fluids engineering
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• v.20 no.2
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• pp.16-22
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• 2015

The pressure is generally lower than that of the freestream at the base of a missile body due to the energy loss by the flow separation around the edge of the base. The base pressure changes in the presence of the thrust jet due to the interaction between the base flow of the missile and the jet flow. In this study, behavior of the missile base pressure by the change of the jet exit pressure and the freestream condition is investigated using the CFD(Computational Fluid Dynamics) method. Effects of the grid type and the freestream condition are tested. The results are compared with the semi-empirical predictions and the flight test data. The CFD results agree well with the flight test data. The semi-empirical predictions overestimate the base pressure when jet thrust is strong for low freestream speed.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.13-34
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• 1999

Building a knowledge base effectively has been an important research area in the expert systems field. A variety of approaches have been studied including rules, semantic networks, and frames to represent the knowledge base for expert systems. As the size and complexity of the knowledge base get larger and more complicated, the integration of knowledge based with database technology cecomes more important to process the large amount of data. However, relational database management systems show many limitations in handing the complicated human knowledge due to its simple two dimensional table structure. In this paper, we propose Object-Oriented Knowledge Store (OOKS), a knowledge base model on the basis of a frame sturcture using an object-oriented database. In the proposed model, managing rules for inferencing and facts about objects in one uniform structure, knowledge and data can be tightly coupled and the performance of reasoning can be improved. For building a knowledge base, a knowledge script file representing rules and facts is used and the script file is transferred into a frame structure in database systems. Specifically, designing a frame structure in the database model as it is, it can facilitate management and utilization of knowledge in expert systems. To test the appropriateness of the proposed knowledge base model, a prototype system has been developed using a commercial ODBMS called ObjectStore and C++ programming language.