• Proceedings of the KAIS Fall Conference
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• 2010.05a
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• pp.436-439
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• 2010

본 논문에서는 Ubiquitous Computing 환경 하에서 이종 시스템 간의 통합을 위한 데이터 관리 기법 모델을 제안하였다. 이종 시스템 간의 통합이 이루어지면 방대한 양의 데이터를 모든 시스템이 공유해야 하기 때문에 무분별한 데이터의 중복과 저장으로 인해 프로세스의 데이터 처리 성능 및 데이터 무결성을 보장받지 못 하는 등의 문제점이 발생한다. 이를 보완하기 위해 Minimal cost Spanning tree의 원리를 적용하여 시스템 통합에 따른 데이터 처리 및 무결성 문제 해결을 위한 메커니즘을 제시하고자 한다.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.193-199
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• 2014

In the application development process is an important task to improve the quality of the data is the principal means for achieving the functional requirements of the wireless sensor network applications because it is the data obtained in the real world. It should be possible to meet the requirements for the quality improvement to those detailed for improving the quality in a short period of time for developing a prototype of an application and low cost. However, development of the existing methods can not be satisfied simultaneously in order to use a consistent abstraction because antinomical relation between ability of description and ease of description. In this paper, we propose a meta-data designed to support the improvement of data quality through abstract modeling language is also used in combination to a multiple of the other.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.311-320
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• 2008

A LIDAR can rapidly generate 3D points by densely sampling the surfaces of targets using laser pulses, which has been efficiently utilized to reconstruct 3D models of the targets automatically. Due to this advantage, LIDARs are increasingly applied to the fields of Defense and Security, for examples, being employed to intelligently guided missiles and manned/unmanned reconnaissance planes. For the prior verification of the LIDAR applicability, this study aims at generating simulated LIDAR data. Here, we derived the sensor equation by modelling the geometric relationships between the LIDAR sub-modules, such as GPS, IMU, LS and the systematic errors associated with them. Based on this equation, we developed a program to generate simulated data with the system parameters, the systematic errors, the flight trajectories and attitudes, and the reference terrain model given. This program had been applied to generating simulated LIDAR data for urban areas. By analyzing these simulated data, we verified the accuracy and usefulness of the simulation. The simulator developed in this study will provide economically various test data required for the development of application algorithms and contribute to the optimal establishment of the flight and system parameters.

• Journal of KIISE
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• v.42 no.9
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• pp.1147-1161
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• 2015

The ISO/IEC 11179 Metadata registry (MDR) is an international standard that was developed to register and share metadata. ISO/IEC 11179 represents an MDR as a metamodel that is an object model. However, it is difficult to develop an MDR based on ISO/IEC 11179 because the standard has no clear criteria to transform the metamodel into a database. In this paper, we suggest the design of an MDR data model that is based on object-relational transformation methodology (ORTM) for the MDR implementation. Hence, we classify the transformation methods of ORTM according to the corresponding relationships. After classification, we propose modeling rules by defining the standard use of the transformation. This paper builds the relational database tables as an implementation result of an MDR data model. Through experiments and evaluation, we verify the proposed modeling rules and evaluate the suitability of the created table structures. As the result, the proposed method shows that the table structures preserve classes and relationships of the standard metamodel well.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.179-184
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• 2022

The accurate wing flexure model is required to improve the transfer alignment performance of guided weapon system mounted on a wing of fighter aircraft or armed helicopter. In order to solve this problem, mechanical or stochastical modeling methods have been studying, but modeling accuracy is too low to be applied to weapon systems. The deep learning techniques that have been studying recently are suitable for nonlinear. However, operating fighter aircraft for deep-learning modeling to secure a large amount of data is practically difficult. In this paper, it was used to generate amount of flexure data samples that are similar to the actual flexure data. And it was confirmed that generated data is similar to the actual data by utilizing "measures of similarity" which measures how much alike the two data objects are.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.221-229
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• 2022

With the recent full-fledged MyData service, interest in the use of personal data is increasing. However, studies on MyData are still in the early stages, focusing on legal and institutional discussions, and studies from a comprehensive perspective are insufficient. Therefore, this study aimed at finding the potential topics formed by social discussions by analyzing news data from 2018 to the present. News data analysis using LDA topic modeling were conducted and 6 potential topics including digital transformation in finance, scope of Mydata business license, amendments and data-related laws, safe use of big data, data economy promotion policy and strategy of the financial industry were derived. This study has significance in that it comprehensively viewed the issues that emerged with the MyData and deriving gaps in previous discussion. Future research is expected to identify changes after the launch of MyData service and provide specific implications through research by specific industries.

• Korean Chemical Engineering Research
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• v.53 no.5
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• pp.545-552
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• 2015

Process modeling and simulation is a powerful methodology to quantitatively predict the change of process variables when operating and design conditions are changed. In this study, considering drawbacks of currently used process simulator for combined cycle plants, we developed process modeling system equipped with an ease of use and flexibility for model development. For this purpose, the analysis of combined cycle processes was carried out and consequently, mathematical models and libraries were developed. Furthermore, in view of the fact that the level of the abstraction of process models depends on the purpose of simulation as well as the available data, simple and rigorous models were also developed for some important units. In use of reference combined plant, we executed process simulation using the developed modeling system and the comparison was made between the results of simulation and the reference data. Less than 1% marginal error was identified and we concluded that the modeling system can be applied for commercial combined cycle processes.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.27-33
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• 2024

The environment of academic research is continuously changing due to the increase of information, which raises the need for an effective way to analyze and organize large amounts of documents. In this paper, we propose Performance Improvement of Topic Modeling using BART(Bidirectional and Auto-Regressive Transformers) based Document Summarization. The proposed method uses BART-based document summary model to extract the core content and improve topic modeling performance using LDA(Latent Dirichlet Allocation) algorithm. We suggest an approach to improve the performance and efficiency of LDA topic modeling through document summarization and validate it through experiments. The experimental results show that the BART-based model for summarizing article data captures the important information of the original articles with F1-Scores of 0.5819, 0.4384, and 0.5038 in Rouge-1, Rouge-2, and Rouge-L performance evaluations, respectively. In addition, topic modeling using summarized documents performs about 8.08% better than topic modeling using full text in the performance comparison using the Perplexity metric. This contributes to the reduction of data throughput and improvement of efficiency in the topic modeling process.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.184-186
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• 2011

부하 모델링을 위해서는 구성요소기반 부하모델링과 측정기반 부하모델링 두 가지 방법이 사용된다. 구성요소기반 부하모델링은 모선에 부하의 구성비에 기반으로 하는 부하모델 기법이고, 측정기반 부하모델링은 부하가 설치된 모선의 전압과 소비전력의 측정값으로부터 관계를 수학적으로 모델링하는 기법이다. 본 논문에서는 부하모델을 위해 복합부하모델이 적용되었다. 복합부하모델은 정적부하모델과 동적부하모델을 모두 포함하고 있으며, 정적부하모델로서는 ZIP 모델이 사용되고, 동적 부하모델로는 유도전동기 모델이 사용되었다. 측정기반 부하모델의 파라미터 추정을 위해 TSAT(trensient security assessment tool) 프로그램으로부터 얻은 측정데이터를 이용해 파라미터 추정을 한다. 또한 사용자 편의를 위한 GUI(graphical user interface)의 적용을 통한 부하모델 파라미터 추정 프로그램을 개발하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.337-339
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• 2005

하이브리드 시스템이란 연속적인 변화와 이산적인 변화가 함께 존재하는 시스템으로 많은 임베디드 시스템이 하이브리드 시스템으로 모델링 된다. 이러한 하이브리드 시스템을 모델링하고 타당성을 검사(validation) 할 수 있는 도구의 제안은 시스템 개발자들에게 하이브리드 시스템의 복잡한 변화로 인한 시스템의 복잡성을 간소화 시킬 수 있는 방법을 제공하고, 고품질의 제어 소프트웨어를 개발할 수 있도록 해준다. 본 논문에서 소개하는 ASADAL/OBJ Hybrid는 고신뢰성 하이브리드 시스템 모델링을 위한 도구로써 객체지향 모델링에 따라 여러 하이브리드 시스템을 객체로 모델링하며, 이들 간의 통신은 이벤트와 데이터 전송으로 이루어지도록 한다. 환경 객체의 경우 3D 형태 정보를 가지고 있어서 3D 시뮬레이션을 통해 시스템의 변화 양상을 개발자에게 직관적으로 제공하도록 하고 있다.