• 신재생에너지
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• 제6권1호
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• pp.38-45
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• 2010

Abstract Under the physical stress on photovoltaic (PV) module, it will be warped according to elongation of the front glass and then micro-crack will be occurred in the thermally sealed solar cell. This micro-crack leads to drop of short circuit current of the PV module. This is because of increase of resistance component by micro-crack. Micro-crack at specific solar cell in the module lessens the durability of PV module with reduced output, hot-spot caused by solar cell output mismatch and increased resistance component. This study shows the relation between electrical characteristics and micro- cracks due to mechanical stress on PV module.

• 정보처리학회논문지D
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• 제18D권6호
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• pp.443-450
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• 2011

모델 중심 컴포넌트 기반 개발 방법은 개발 대상 시스템을 하나의 추상컴포넌트로 보고, 재귀적인 컴포넌트의 분화(decomposition)와 정제(refinement) 과정을 통하여 물리적인 컴포넌트를 도출해내는 하향식 개발방식이다. 본 연구에서는 모델 기반 컴포넌트 개발기법을 근간으로 한 컴포넌트 정제 과정에서 정제 전 후의 추상컴포넌트들 간의 행위 일관성을 정형분석하기 위한 모델 변환기를 개발하였다. 이 모델변환기는 컴포넌트의 분화와 정제 전 과정에 걸쳐 사용되어 정제 전 후 컴포넌트 간의 상호작용 오류로 인한 잠재적인 결함을 조기에 발견하고 해결하는데 기여할 수 있다. 본 논문은 추상컴포넌트의 각 구성요소들을 정형검증기 SPIN의 구성요소로 변환하기 위해 사용된 변환방법들과 변환기의 구성요소들을 소개한다. 개발된 변환기는 자동차 거울조종시스템, 무선센서네트워크를 위한 운영체제 등의 사례연구에 적용되어 그 효용성을 입증하였다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제6권5호
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• pp.245-256
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• 2017

본 논문은 구조화된 체크리스트로부터 임베디드 시스템 테스팅을 위한 테스트 스크립트를 쉽게 생성할 수 있는 방법을 제안한다. 제안하는 방법은 체크리스트를 이벤트(Event), 컴포넌트(Component), 입력 명령어(Command) 사전을 기반으로 구성하고, 사전으로부터 계층적으로 테스트 스크립트를 생성한다. 계층 구조로 임베디드 시스템의 물리적 입력 계층이 상위 계층의 컴포넌트 및 이벤트 계층에서 추상화되어 복잡한 시스템 입력 정보를 사용하지 않고도 테스트 스크립트를 생성할 수 있다. 비슷한 종류의 입출력 정보를 가지는 임베디드 시스템을 테스트하기 위한 테스트 스크립트 생성은 재사용성이 높은 사전을 이용하여 매우 쉽게 할 수 있다. 제안하는 방법의 유용성은 실험을 통해 보인다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권9호
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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.

• 한국CDE학회논문집
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• 제9권1호
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• pp.51-61
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• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes.. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the second one of the two companion papers, describes the similarity assessment method using NFD.

• 한국CDE학회논문집
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• 제9권1호
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• pp.44-50
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• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the first one of the two companion papers, describes the similarity assessment methods using convex decomposition and FFD.

• Smart Structures and Systems
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• 제6권1호
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• pp.39-56
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• 2010

Structural Control relies, with a great deal, on the ability of the control algorithm to identify the current state of the system, at any given point in time. When such algorithms are designed to perform in a smart manner, several smart technologies/devices are called upon to perform tasks that involve pattern recognition and control. Smart pattern recognition is proposed to replace/enhance traditional state identification techniques, which require the extensive manipulation of intricate mathematical equations. Smart pattern recognition techniques attempt to emulate the behavior of the human brain when performing abstract pattern identification. Since these techniques are largely heuristic in nature, it is reasonable to ensure their reliability under real life situations. In this paper, a neural network pattern recognition scheme is explored. The pattern identification of three structural systems is considered. The first is a single bay three-story frame. Both the second and the third models are variations on benchmark problems, previously published for control strategy evaluation purposes. A Neural Network was developed and trained to identify the deformed shape of structural systems under earthquake excitation. The network was trained, for each individual model system, then tested under the effect of a different set of earthquake records. The proposed smart pattern identification scheme is considered an integral component of a Smart Structural System. The Reliability assessment of such component represents an important stage in the evaluation of an overall reliability measure of Smart Structural Systems. Several studies are currently underway aiming at the identification of a reliability measure for such smart pattern recognition technique.

• 한국정보통신학회논문지
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• 제18권6호
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• pp.1302-1309
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• 2014

본 논문에서는 다중 신호 분류 기반의 음성신호의 입사각 추정 향상 방법을 제안한다. 기본적으로 제안한 방식은 복소 대역통과 필터를 이용하여 신호 분석을 위한 협대역 신호를 생성한다. 또한, 공간 스펙트럼에서의 반향 성분 제거 및 2차 함수 기반의 응답 근사화를 사용하여 추정 각도의 정확도를 향상시켰다. 실험결과 제안한 방법은 일반화된 상호상관도 방식의 입사각 추정 알고리즘보다 검출 오차 및 검출 성공률 측면에서 더 좋은 성능을 보였다.

• 말소리와 음성과학
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• 제1권4호
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• pp.29-38
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• 2009

This study investigated the interaction between consonants and vowels in Korean syllable perception using a speeded classification task (Garner, 1978). Experiment 1 examined whether listeners analytically perceive the component phonemes in CV monosyllables when classification is based on the component phonemes (a consonant or a vowel) and observed a significant redundancy gain and a Garner interference effect. These results imply that the perception of the component phonemes in a CV syllable is not linear. Experiment 2 examined the further relation between consonants and vowels at a subphonemic level comparing classification times based on glottal features (aspiration and lax), on place of articulation features (labial and coronal), and on vowel features (front and back). Across all feature classifications, there were significant but asymmetric interference effects. Glottal feature.based classification showed the least amount of interference effect, while vowel feature.based classification showed moderate interference, and place of articulation feature-based classification showed the most interference. These results show that glottal features are more independent to vowels, but place features are more dependent to vowels in syllable perception. To examine the three-way interaction among glottal, place of articulation, and vowel features, Experiment 3 featured a modified Garner task. The outcome of this experiment indicated that glottal consonant features are independent to both the place of articulation and vowel features, but the place of articulation features are dependent to glottal and vowel features. These results were interpreted to show that speech perception is not abstract and discrete, but nonlinear, and that the perception of features corresponds to the hierarchical organization of articulatory features which is suggested in nonlinear phonology (Clements, 1991; Browman and Goldstein, 1989).

• 한국정보과학회논문지:시스템및이론
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• 제26권12호
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• pp.1447-1457
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• 1999

본 논문에서는 일반적인 네트워크에서 적응력 있는(adaptive) 분산형 시스템 레벨 결함 진단을 위한 분할 기법을 제안한다. 적응력 있는 분산형 시스템 레벨 결함 진단 기법에서는 시스템의 형상이 변경될 때마다 시험 할당 알고리즘이 수행되므로 적응력 없는 결함 진단 기법에 비하여 결함 감지를 위한 시험의 갯수를 줄일 수 있다. 기존의 시험 할당 알고리즘들은 전체 시스템을 대상으로 하는 비분할(non-partitioning) 방식을 이용하였는데, 이 기법은 불필요한 과다한 메시지를 생성한다. 본 논문에서는 전체 시스템을 이중 연결 요소(biconnected component) 단위로 분할한 후, 시험 할당은 각 이중 연결 요소 내에서 수행한다. 이중 연결 요소의 관절점(articulation point)의 특성을 이용하여 각 시험 할당에 필요한 노드의 수를 줄임으로서, 비분할 기법들에 비해 초기 시험 할당에 필요한 메시지의 수를 감소시켰다. 또한 결함이 발생한 경우나 복구가 완료된 경우의 시험 재 할당은 직접 영향을 받는 이중 연결 요소내로 국지화(localize) 시켰다. 본 논문의 시스템 레벨 결함 진단 기법의 정확성을 증명하였으며, 기존 비분할 방식의 시스템 레벨 결함 진단 기법과의 성능 분석을 수행하였다.Abstract We propose an adaptive distributed system-level diagnosis using partitioning method in arbitrary network topologies. In an adaptive distributed system-level diagnosis, testing assignment algorithm is performed whenever the system configuration is changed to reduce the number of tests in the system. Existing testing assignment algorithms adopt a non-partitioning approach covering the whole system, so they incur unnecessary extra message traffic and time. In our method, the whole system is partitioned into biconnected components, and testing assignment is performed within each biconnected component. By exploiting the property of an articulation point of a biconnected component, initial testing assignment of our method performs better than non-partitioning approach by reducing the number of nodes involved in testing assignment. It also localizes the testing reassignment caused by system reconfiguration within the related biconnected components. We show that our system-level diagnosis method is correct and analyze the performance of our method compared with the previous non-partitioning ones.