• Journal of KIISE:Software and Applications
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• v.26 no.9
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• pp.1105-1113
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• 1999

객체 지향 소프트웨어의 확장과 더불어 소프트웨어의 재사용성의 중요도가 부각되면서 소프트웨어를 콤포넌트 단위로 구현하는 추세이다. 따라서 콤포넌트 기반의 소프트웨어 개발에서의 통합 테스트가 중요한 이슈로 떠오르고 있다. 그러나 콤포넌트들의 통합 테스트에 대한 연구는 미흡한 상태이다. 본 논문에서는 UML을 기반으로 체계적인 통합 테스트 모형을 제안하고. 나아가 본 논문에서는 "멀티미디어 정보처리 시스템"의 사례를 본 논문의 콤포넌트 통합 테스트 모형에 적용한 결과를 분석하여 기술한다. 콤포넌트 통합 테스트 모형은 UML(Unified Modeling Language)의 순서도(sequence diagram)와 협력도(collaboration diagram)를 이용하여 전체 시스템에서 UML의 사건흐름을 구성하는 콤포넌트들 사이의 인터페이스 영역에 존재하는 오류들을 추출한다. 그리고 UML을 기반으로 통합 테스트를 수행함으로써, 테스트 준비 작업을 줄이고, 기존의 UML 지원 도구들과 연계하여 테스트 자동화 도구의 구현을 앞당길 수 있다. 또한 시스템의 순차적 흐름 뿐 아니라, 동시에 수행되는 흐름에 대한 정보까지 모두 수용하여 테스트함으로써, 콤포넌트 기반의 분산 환경의 특성에 적합하다. Abstract As the object-oriented approach to software development becomes more mature, software development from pre-existing, independently developed components becomes an important aim of software engineering. Therefore, integration testing becomes an important aspect of component-based software development. However, there has been little work done in the area of the component-based integration testing. In this paper, we propose the "component integration test model" which is based on UML. Furthermore, we describe a case study on "Multimedia Information Processing System" conducted to analyse the result from which our model is applied. Our model extracts the faults, which exist in interfaces of components, using sequence diagram and collaboration diagram of UML(Unified Modeling Language). As our model is based on UML, the preparation effort for testing is reduced and its test-tools can be implemented more easily through linking existing UML tool. And our model accepts the information of concurrent flow represented by collaboration diagram as well as sequential flow, so it is more suitable to component-based distributed environment.based distributed environment.

• 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 applied mathematics & informatics
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• v.14 no.1_2
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• pp.377-386
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• 2004

A technique that provides prediction intervals based on a model called an empirical linear model is discussed. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. HELP can be viewed as a technique that provides prediction (and confidence) intervals based on a factor analysis models do not typically have justifiable theory due to nonidentifiability, we show that the intervals are justifiable asymptotically.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.386-397
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• 2007

One major development in bridge life cycle cost analysis (LCCA) in recent years is to develop deterioration model for bridge components so that the times of repair/replacement throughout a component's life span can be properly determined. Taiwan also developed her own bridge LCCA model in 2003, integrating with the bridge inspection database in the local bridge management system (T-BMS). Under the framework of the local LCCA model, this study employs the reliability method in developing a deterioration model of bridge components. A component deteriorates through time in its reliability, which represents the probability of a component's condition index exceeds a user specified threshold. Model assumptions and rationale are described in the paper. The steps for applying the developed model are explained in detail. Results and findings are reported.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.780-785
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• 2010

The OPRoS (Open Platform for Robotic Services) framework is proposed as an application runtime environment for service robot systems. For the successful deployment of the OPRoS framework, fault tolerance support is crucial on top of its basic functionalities of lifecycle, thread and connection management. In the previous work [1] on OPRoS fault tolerance supports, we presented a framework-based fault tolerance architecture. In this paper, we extend the architecture with component-based fault tolerance techniques, which can provide more simplicity and efficiency than the pure framework-based approach. This argument is especially true for fault detection, since most faults and failure can be defined when the system cannot meet the requirement of the application functions. Specifically, the paper applies two widely-used fault detection techniques to the OPRoS framework: 'bridge component' and 'process model' component techniques for fault detection. The application details and performance of the proposed techniques are demonstrated by the same application scenario in [1]. The combination of component-based techniques with the framework-based architecture would improve the reliability of robot systems using the OPRoS framework.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.98-105
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• 2021

Using the frequency-based decomposition, I decompose the consumption growth to explain well-known patterns of stock returns in the Korean market. To be more specific, the consumption growth is decomposed by its half-life of shocks. The component over four years of half-life is called the business-cycle consumption component, and the components with half-lives under four years are short-run components. I compute the long-run and short-run components of stock excess returns as well and use component-by-component sensitivities to price stock portfolios. As a result, the business-cycle consumption risk with half-life of over four years is useful in explaining the cross-section of size-book-to-market portfolios and size-momentum portfolios in the Korean stock market. The short-run components have their own pricing abilities with mixed direction, so that the restricted one short-term factor model is rejected. The explanatory power with short- and long-run components is comparable to that of the Fama-French three-factor model. The components with one- to four-year half-lives are also helpful in explaining the returns. The results about the long-run components emphasize the importance of long-run component in consumption growth to explain the asset returns.

• Genomics & Informatics
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• v.18 no.1
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• pp.11.1-11.3
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• 2020

In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.65-84
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• 2006

In this paper, we present an improved image formation model and propose a color image enhancement based on the model. In the presented image formation model, an input image is represented as a product of global illumination, local illumination, and reflectance. In the proposed color image enhancement, an input RGB color image is converted into an HSV color image. Under the assumption of white-light illumination, the H and S component images are remained as they are and the V component image only is enhanced based on the image formation model. The global illumination is estimated by applying a linear LPF with wide support region to the input V component image and the local illumination by applying a JND (just noticeable difference)-based nonlinear LPF with narrow support region to the processed image, where the estimated global illumination is eliminated from the input V component image. The reflectance is estimated by dividing the input V component image by the estimated global and local illuminations. After performing the gamma correction on the three estimated components, the output V component image is obtained from their product. Histogram modeling is next executed such that the final output V component image is obtained. Finally an output RGB color image is obtained from the H and S component images of the input color image and the final output V component image. Experimental results for the test image DB built with color images downloaded from NASA homepage and MPEG-7 CCD color images show that the proposed method gives output color images of very well-increased global and local contrast without halo effect and color shift.

• 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 Korea Society of Computer and Information
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• v.12 no.5
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• pp.113-119
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• 2007

Framework has constructive and extendable code. It is consist of the variable design collections. In the aspect of the classes's collection, it is similar to the class library. but it is different to provide the architecture which is possible to develop the application rather than the collection of the simple classes. In framework it is very important factor to develop and control the component library. In this paper, we design the usable component model through defining the meta-relation between components and proposed the sample case using this model.