• Journal of applied mathematics & informatics
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• 제10권1_2호
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• pp.251-259
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• 2002

The fuzzification of an ideal in a Lie algebra is considered. Using a level subset of a fuzzy subset of a Lie algebra, we give a characterization of a fuzzy ideal, and using a family of ideals of a Lie algebra, we establish a fuzzy ideal. With relation to the ascending chain of ideals, a characterization for the set of values of any fuzzy ideal to be a well-ordered subset of the closed unit interval [0,1] is stated.

• 정보과학회지
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• 제3권1호
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• pp.12-17
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• 1985

본 논문은 서울工大 전자계산소에 있는 IBM1130에 ALGOL-60 언어를 사용 가능하게 하기 위하여 ALGOL-60 콤파이러(Compiler)를 만드는데 첫 단계 인 scanner와 analyzer에 관한 것이다. 과거에 콤파이러는 주로 기계어나 어ㅆ브 리어로 쓰여졌으나, 현재는 콤파이러를 만드는 시간과 디버깅하는 시간을 줄이기 위하여 고등연어(high-level language)를 사용하는 경향이다. 본 논문은 FORTRAN IV를 사용하였다. 2장에서는 콤파이러의 구성을 설명하고, 3장에서는 ANGOL-60(Sudset)을 정의하고, 4장에서는 scanner의 구성과 작업과정을, 5장에 서는 analyzer의 구성과 작업을 설명하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권5_6호
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• pp.587-597
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• 2003

일반적으로 C언어는 고신뢰도를 요구하는 소프트웨어에 적합하지 않다고 알려졌음에도 불구하고 적지 않은 수의 안전성이 중요시되는(safety-critical) 시스템들이 C언어로 구현되었거나 C언어를 기반으로 개발되고 있다. 본 연구의 목적은 C언어의 안전한 subset을 정의하고 이 subset 언어로 작성된 프로그램을 SPARK Ada로 변환하여 SPARK의 분석 도구들을 사용해 프로그램의 안전성을 분석하는 데 있다. SPARK은 Ada의 안전한 subset으로 고신뢰도를 요하는 시스템을 구현하는데 성공적으로 사용되어왔다. SPARK으로 변환된 C 프로그램은 SPARK 수준의 안전성을 갖게 되며 SPARK의 분석 도구인 Examiner를 통해 프로그램의 정확성 검증 등의 분석을 할 수 있다. 본 연구에서는 엘리베이터 컨트롤러 사례 연구를 통해 정의한 subset이 현실적인 시스템을 구현하기에 부족하지 않음을 발견하였으며, SPARK Ada로의 변환을 자동화해주는 변환기를 구현하였다.

• Structural Engineering and Mechanics
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• 제32권1호
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• pp.95-126
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• 2009

The present contribution addresses the parallelization of advanced simulation methods for structural reliability analysis, which have recently been developed for large-scale structures with a high number of uncertain parameters. In particular, the Line Sampling method and the Subset Simulation method are considered. The proposed parallel algorithms exploit the parallelism associated with the possibility to simultaneously perform independent FE analyses. For the Line Sampling method a parallelization scheme is proposed both for the actual sampling process, and for the statistical gradient estimation method used to identify the so-called important direction of the Line Sampling scheme. Two parallelization strategies are investigated for the Subset Simulation method: the first one consists in the embarrassingly parallel advancement of distinct Markov chains; in this case the speedup is bounded by the number of chains advanced simultaneously. The second parallel Subset Simulation algorithm utilizes the concept of speculative computing. Speedup measurements in context with the FE model of a multistory building (24,000 DOFs) show the reduction of the wall-clock time to a very viable amount (<10 minutes for Line Sampling and ${\approx}$ 1 hour for Subset Simulation). The measurements, conducted on clusters of multi-core nodes, also indicate a strong sensitivity of the parallel performance to the load level of the nodes, in terms of the number of simultaneously used cores. This performance degradation is related to memory bottlenecks during the modal analysis required during each FE analysis.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.717-723
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• 2011

When the Balise(the device to transmit information between the on-board equipment and the wayside equipment) failure occurs, it may not be able to transmit data(Telegram) required for the train running. And in some cases, it may be able to cause an accident. Therefore, both the Balise failure affecting train safety running and the hazard in accordance with Balise failure require some activities to establish them. General failure mode & hazard analysis associated with the Balise are described in UNISIG SUBSET-036 spec & UNISIG SUBSET-088 spec. And, with reference to these specifications, safety activities are being performed. In recent domestic railway, the train control system applying ETCS(European Train Control System) Level 1, 2 is being serviced and is being planned, and as part of this system, the Balise is being applied. The design-method of the Balise device for each manufacturer are different, therefore the Balise failure mode & failure rate are different, either. But the functionalities & transmission-data format(Telegram) of the Balise in ETCS Level 1, 2 application for each manufacturer are identical. Accordingly, the hazard caused by function-fail can be identical, either. In order to establish these hazard, in this paper, we analyzed the detailed functions of the Balise. And we analyzed the Balise failure types & failure effects in accordance with the detailed functions.

• 정보과학회지
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• 제4권2호
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• pp.65-73
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• 1986

Compiler 교육용 Compiler의 필요성은 강조할 필요가 있다. 이 교육용 Compiler가 가져야 할 성질은 다음과 같다. 첫째, Modular programming Technique사용하여 이해하기 쉬운 작은 program 형태로 만들어야 한다. 그렇게 함으로써 학생들이 상호결합(interface)변수와 형태를 알고 Compiler의 한 부분을 자신의 program으로 대치한 후 실험하여 볼 수 있다. 둘째; 내부에서 사용되는 Table은 간단한 형태로 구성한다. 세째; 다른 언어의 Compiler를 쓸때 사용하는 program(예를들면 parser generator)이 있어야 한다. 이것을 이용하여 학생들은 자신이 만든 언어의 Compiler를 학기중에 만들 수 있다. 넷째; REAL TIME clock을 이용하여 각 program module이 사용한 시간을 찍어낼 수 있어야 한다. 이렇게 함으로써 어떤 module이 가장 많은 시간을 소모하며, 이것을 개선하는 방 법을 찾아낼 수 있다. 다섯째; Compile된 결과를 Assembler 언어로도 출시시킬 수 있어야 한다. 위와 같은 교육용 Compiler의 제작 방법과 그 문제점에 대하여 서술하려고 한다.

• 호남수학학술지
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• 제42권2호
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• pp.197-211
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• 2020

The notions of hyper permeable subalgebraic value and hyper permeable idealistic value are introduced, and related properties are investigated. Given a pair of two numbers in a unit interval, conditions for the pair to be hyper permeable subalgebraic value and hyper permeable idealistic value are discussed. Given hyperfuzzy structures, conditions for their level sets to be subalgebraic energetic, idealistic energetic, right stable and right vanished are considered. Relations between hyper permeable subalgebraic value and hyper permeable idealistic value are studied.

• 대한수학회보
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• 제41권4호
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• pp.723-730
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• 2004

The definition of a D-admissible fuzzy subset for an operator domain D on a group G is modified to obtain new kinds of (${\in},\;{\in}\;{\vee}q$)-fuzzy subgroups such as an (${\in},\;{\in}\;{\vee}q$)-fuzzy normal subgroup, an (<${\in},\;{\in}\;{\vee}q$)-fuzzy characteristic subgroup, an (<${\in},\;{\in}\;{\vee}q$)-fuzzy fully invariant subgroup which are invariant under D. As results, some of the fundamental properties of such (${\in},\;{\in}\;{\vee}q$)-fuzzy subgroups are obtained.

• Structural Engineering and Mechanics
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• 제42권3호
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• pp.425-448
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• 2012

In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권2호
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• pp.173-183
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• 2018

Purpose: It is critical to design a set of experiments in Test and Evaluation Process for a weapon system. Because there is no sufficient resources in real-world, one must choose a subset of experiments which is considered to be more important. Methods: We introduce an optimization model for choosing the subset of experiments by considering a priority of experimental variable and level and restrictions of resources. We describe in detail how we construct objective function and constraints which must be a right realization of our logic and assumption. Conclusion: Since our optimization model turns out to be computationally difficult to solve, we introduce an algorithm for reducing the size of problem. Various computational results follows.