• 한국정보처리학회논문지
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• 제6권11호
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• pp.2965-2980
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• 1999

There are several models and the corresponding diagrams to express software system in many kinds of viewpoints, but these are supposed to be integrated and implemented into only one system. Therefore, the software modelers should have the models ensuring the consistency between information in software development life cycle. To support the robust models for modelers using OO modeling methods, i.e. UML, and CASE tools, the meta models of the software architecture and the consistency rules between the models are suggested in this thesis. Finally, the rules are implemented in the OO CASE tool, DEBUTO(Design By UML Tool). It supports UML1.1 notations and has visual modeling editors that enable users make their own software model.

• 경영과학
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• 제17권3호
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• pp.147-160
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• 2000

These days, a modeling tool or environment has to know about the others on the market and build bridges to them with which their customers insist on sharing models and data. When it is based on a closed architecture, a tangle of import/export point translators is required. Using an exchange standard, we can design an open architecture for the interchange of models and data. XML(Extensible Markup Language) provides a framework for describing the syntax for creating and exchanging data structures. The explosive growth of XML-based business proposals and standards reflects the urgent requirements and its strength. This paper proposes an XML-based language for sharing decision models within the MSOR/DSS community. The language is able to allow applications and on-line analytic processing tools to models obtained from multiple sources without having to deal with individual differences between those sources. It is expected to be a medium for B2B integration by supporting flexible interchange of decision models.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.783-791
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• 2004

In this paper we review recent developments in nonlinear time series modeling on both conditional mean and conditional variance. Traditional linear model in conditional mean is referred to as ARMA(autoregressive moving average) process investigated by Box and Jenkins(1976). Nonlinear mean models such as threshold, exponential and random coefficient models are reviewed and their characteristics are explained. In terms of conditional variances, ARCH(autoregressive conditional heteroscedasticity) class is considered as typical linear models. As nonlinear variants of ARCH, diverse nonlinear models appearing in recent literature including threshold ARCH, beta-ARCH and Box-Cox ARCH models are remarked. Also, a class of unified nonlinear models are considered and parameter estimation for that class is briefly discussed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.675-678
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• 1997

In this research we continue the study of nuclear power plant steam generator's intelligent modeling. This model represents the input-output behavior and is a preliminary stage for intelligent control. Among many intelligent models available, we study neural network models that have been proven as universal function approximators. We select multilayer perceptrons, circular backpropagation networks, piecewise linearly trained networks and recurrent neural networks as the candidates for the steam generator's intelligent models. We take the input-output pairs from steam generator's reference model and train the neural network models. We validate trained neural network models as intelligent models of steam generator.

• Biotechnology and Bioprocess Engineering:BBE
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• 제10권5호
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• pp.408-417
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• 2005

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput 'omics' data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.

• Environmental Engineering Research
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• 제14권4호
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• pp.200-210
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• 2009

The modern era of water quality modeling in the United States began in the 1960s. Pushed by advances in computer technology as well as environmental sciences, water quality modeling evolved through five broad periods: (1) initial model development with mainframe computers (1960s - mid 1970s), (2) model refinement and generalization with minicomputers (mid 1970s - mid 1980s), (3) model standardization and support with microcomputers (mid 1980s - mid 1990s), (4) better model access and performance with faster desktop computers running Windows and local area networks linked to the Internet (mid 1990s - early 2000s), and (5) model integration and widespread use of the Internet (early 2000s - present). Improved computer technology continues to drive improvements in water quality models, including more detailed environmental analysis (spatially and temporally), better user interfaces and GIS software, more accessibility to environmental data from on-line repositories, and more robust modeling frameworks linking hydrodynamics, water quality, watershed and atmospheric models. Driven by regulatory needs and advancing technology, water quality modeling will continue to improve to better address more complicated water bodies and pollutant types, and more complicated management questions. This manuscript describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2186-2203
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• 2020

Security administrators of companies and organizations need to come up with proper countermeasures against cyber-attacks considering infrastructures and security policies in their possession. In order to develop and verify such countermeasures, the administrators should be able to reenact both cyber-attacks and defenses. Simulations can be useful for the reenactment by overcoming its limitations including high risk and cost. If the administrators are able to design various scenarios of cyber-attacks and to develop simulation models from their viewpoints, they can simulate desired situations and observe the results more easily. It is challenging to simulate cyber-security issues, because there is lack of theoretical basis for modeling a wide range of the security field as well as pre-defined basic components used to model cyber-attacks. In this paper, we propose a modeling method for cyber-security simulations by developing a basic component and a composite model, called Abstracted Cyber-Security Unit Model (ACSUM) and Abstracted Cyber-security SIMulation model (ACSIM), respectively. The proposed models are based on DEVS(Discrete Event systems Specification) formalism, a modeling theory for discrete event simulations. We develop attack scenarios by sequencing attack behaviors using ACSUMs and then model ACSIMs by combining and abstracting the ACSUMs from a security perspective. The concepts of ACSUM and ACSIM enable the security administrators to simulate numerous cyber-security issues from their viewpoints. As a case study, we model a worm scenario using ACSUM and simulate three types of simulation models based on ACSIM from a different security perspective.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.532-541
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• 2018

Decision support systems are a key focus of research on developing control rooms to aid operators in making reliable decisions and reducing incidents caused by human errors. For this purpose, models of complex systems can be developed to diagnose causes or consequences for specific alarms. Models applied in safety systems of complex and safety-critical systems require rigorous and reliable model building and testing. Multilevel flow modeling is a qualitative and discrete method for diagnosing faults and has previously only been validated by subjective and qualitative means. To ensure reliability during operation, this work aims to synthesize a procedure to measure model performance according to diagnostic requirements. A simple procedure is proposed for validating and evaluating the concept of multilevel flow modeling. For this purpose, expert statements, dynamic process simulations, and pilot plant experiments are used for validation of simple multilevel flow modeling models of a hydrocyclone unit for oil removal from produced water.

• Wind and Structures
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• 제35권2호
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• pp.131-146
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• 2022

Tornadic wind flow is inherently turbulent. A turbulent wind flow is characterized by fluctuation of the velocity in the flow field with time, and it is a dynamic process that consists of eddy formation, eddy transportation, and eddy dissipation due to viscosity. Properly modeling turbulence significantly increases the accuracy of numerical simulations. The lack of a clear and detailed comparison between turbulence models used in tornadic wind flows and their effects on tornado induced pressure demonstrates a significant research gap. To bridge this research gap, in this study, two representative turbulence modeling approaches are applied in simulating real-world tornadoes to investigate how the selection of turbulence models affects the simulated tornadic wind flow and the induced pressure on structural surface. To be specific, LES with Smagorinsky-Lilly Subgrid and k-ω are chosen to simulate the 3D full-scale tornado and the tornado-structure interaction with a building present in the computational domain. To investigate the influence of turbulence modeling, comparisons are made of velocity field and pressure field of the simulated wind field and of the pressure distribution on building surface between the cases with different turbulence modeling.

• 한국정보처리학회논문지
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• 제5권11호
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• pp.2954-2972
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• 1998

광대역 종합정보 통신망에서 주문형 비디오 서비스 등의 멀티미디어 서비스가 본격적으로 도입됨에 따라 압축된 비디오의 전송이 전체 통신망 트래픽의 상당 부분을 차지할 것으로 기대된다. 가변 비트율로 부호화된 비디오가 통계적 이득과 일정한 비디오 품질을 제공할 수 있는 장점 때문에 많이 사용이 될 것이다. 비디오 트래픽을 전송하기 위해서는 음성 및 데이터 보다 많은 대역폭을 요구하기 때문에 ATM 통신망에서의 적절한 자원 할당 기법의 설계를 위하여 비디오 소스의 특성화와 트래픽 모델링은 아주 중요하다. 그리고 셀 손실, 지연 및 지터 등과 같은 성능 척도를 분석하기 위하여도 적절한 통계적 소스 모델이 필요하다. 본 논문에서는 MPEG 비디오 소스에 대한 특성화와 트래픽 모델링에 대하여 분석 기술하였다. 모델들을 크게 두 가지 즉, 통계적 모델과 결정적 모델로 분류하였다. 통계적 모델에서는 AR(autoregnessive), Markov, Markov와 AR의 복합, TES, 그리고 자기유사 모델로 분류하였다. 결정적 모델에서는 $({\sigma},\;{\rho}$, 매개변수화된 모델, D-BND, Empirical Envelopes 모델로 분류하였다. 각 모델들에 대한 특성, 장점 및 단점을 분석하고, 각 모델의 복잡도에 대하여 비교 분석하였다.