• Journal of Digital Contents Society
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• v.2 no.1
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• pp.21-30
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• 2001

This paper presents the automated component generation system to support development of web application by the Model 2 framework on distributed environment. Model 2 framework is based on MVC(Model View Controller) model and this model capsulate the functionality of web application and have the benefits like extensibility, maintainability, resuability. In this paper, we propose a framework which is adapted in JSP environment and implement the automated component generation system. This system can efficiently utilized for web application development which require extensibility, maintainability, resuability as well as rapid web application development.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.153-162
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• 2005

Component Based Development (CBD) is appealing as a technology to improve the productivity of software development through component reuse. Model Driven Architecture (MDA) is a new development paradigm which automatically generates application by transforming design models incrementally. Since both reusability of CBD and model transformation of MDA increase software productivity. integration of two technologies is desirable. To enable this technology integration, we need to devise a UML profile for specifying component design as a PIM. In this paper, we first define a meta-model for components, and propose a UML profile which is used to specify elements of component design as PIM. Since the proposed profile is based on Meta Object Facility (MOF) from which is MDA is derived, it is consistent and compatible with existing MDA methods and tools.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.205-213
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• 2007

In this paper, the normal mixture model subjected to general linear restriction for component-means based on linear regression is proposed, and its fitting method by EM algorithm and Lagrange multiplier is provided. This model is applied to gene clustering of microarray expression data, which demonstrates it has very good performances for real data set. This model also allows to obtain the clusters that an analyst wants to find out in the fashion that the hypothesis for component-means is represented by the design matrices and the linear restriction matrices.

• KIEE International Transactions on Power Engineering
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• v.2A no.4
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• pp.136-144
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• 2002

Load models are very important for improving the accuracy of stability analysis and load flow studies. Various loads are connected to a power bus and their characteristics of power consumption change with voltage and frequency. Thus, the effect of voltage/frequency changes must be considered in load modeling. In this work, artificial neural networks-ANNs- were used to construct the component load models for more accurate modeling. A typical residential load was selected and subjected to a test under variable voltage/frequency conditions. Acquired data were used to construct component models by ANNs. The aggregation process of separately determined load models is also presented in the paper. Furthermore, this paper proposes a method to transform a single load model constructed by the aggregation method into a mathematical load model that can be used in traditional power system analysis software.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.96-101
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• 1999

Load model is very important to improve accuracy of stability analysis and load flow study in power systems. A power system bus is composed by various loads, and loads have different power consumption due to voltage/frequency changing. Thus the effect of voltage/frequency changing must he considered to load mxleling. In this research, ANN was used to construct component load moddel for more accurate load mxleling. Typical residential load was selected, and characteristics exrerimented on voltage/frequency changing. Acquired data used to construct the component ANN model, and aggregation method of component load model was presented based on component load model and composition rate. Furthennore, it's transfomlation method to the mathematical load model to he used at the traditional power system analysis soft wares was also presented.sented.

• ETRI Journal
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• v.32 no.5
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• pp.646-656
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• 2010

A component is a reusable and replaceable software module accessed through its interface. Component-based development is expected to shorten the development period, reduce maintenance costs, and improve program reusability and the interoperability of components. This paper proposes a new robot software component platform in order to support the entire process of robot software development. It consists of specifications of a component model, component authoring tool, component composer, and component execution engine. To show its feasibility, this paper presents the analysis results of the component's communication overhead, a comparison with other robotic software platforms, and applications in commercial robots.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.159-164
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• 1998

The two-factor nested variance component model with equal numbers in the cells are given by $y_{ijk}\;=\;{\mu}\;+\;A_i\;+\;B_{ij}\;+\;C_{ijk}$ and the confidence intervals for the ratio of variance components, ${\sigma}^{2}_{A}/{\sigma}^{2}_{B}$ are obtained in various forms by many authors. This article shows the probability ranges of these confidence intervals on ${\sigma}^{2}_{A}/{\sigma}^{2}_{B}$ proved by the mathematical computation.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.489-501
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• 1999

In this paper, we consider the panel data regression model in which the disturbances have nested error component. We derive a Lagrange Multiplier(LM) test which is jointly testing for the presence of random individual effects and nested effects under the normality assumption of the disturbances. This test extends the earlier work of Breusch and Pagan(1980) and Baltagi and Li(1991). Further, it is shown that this LM test has the same asymptotic distribution without normality assumption of the disturbances.

• 한국IT서비스학회:학술대회논문집
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• 2003.05a
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• pp.584-590
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• 2003

CBSD의 핵심 연구 과제 중 하나인 컴포넌트 결합에 의한 응용 프로그램 개발에 대한 많은 연구가 진행되고 있지만 구체적 개발 환경에 대하여 아직 미비한 실정이다. 이에 본 논문에서는 CCM 컴포넌트들의 재귀적인 결합과 이에 기반을 둔 응용 프로그램 개발 방안을 제안하고자 한다. 이를 위해 컴포넌트 서비스의 기능적 결합을 기술하는 결합 명세서를 작성하고, 결합 명세서에 기반하여 컴포넌트를 결합하고자 한다. 또한 결합 컴포넌트의 결합성과 적합성을 검사하여 컴포넌트를 재구성하여 새로운 어플리케이션이나 컴포넌트를 자동으로 생성해 주는 응용 프로그램 개발 프레임웍을 제안하고자 한다.