• 가정과삶의질연구
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• 제23권1호
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• pp.1-18
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• 2005

The purpose of this study was to construct the Marital Relationship Enhancement Program based on PREP(Prevention and Relationship Enhancement Program), and to examine the effect of it for couples in the early marriage stage. To perform this program, six session of time-limited(two hour) were carried out experimental group. and subjects were assigned to experimental group(N=6 couples) and control group(N=6 couples). Scales of PREPARE II (PREmarital Personal And Relationship Evaluation), Couple Communication Scales and Commitment Scales were used as pre-post-follow instruments of this study. Major finding were as follows : 1. Marital Relationship Enhancement Program for couples in the early marriage stage has meaningful consequences for the improvement of participants' couple relationship. 2. Marital Relationship Enhancement Program had meaningful consequence for the improvement of participants' realistic expectation of marriage, communication and conflict resolution skills and leisure activities. These positive effects maintained at follow-up. However, it hadn't meaningful consequence for the improvement of participants' marital commitment. 3. Marital Relationship Enhancement Program had also meaningful consequence for the improvement of the wives' realistic expectation of marriage, communication and conflict resolution skills and leisure activities, of the husbands' communication and conflict resolution skills.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.621-632
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• 2013

In this paper, we introduce advanced architectures of genetically-oriented Fuzzy Neural Networks (FNNs) based on fuzzy set and fuzzy relation and discuss a comprehensive design methodology. The proposed FNNs are based on 'if-then' rule-based networks with the extended structure of the premise and the consequence parts of the fuzzy rules. We consider two types of the FNNs topologies, called here FSNN and FRNN, depending upon the usage of inputs in the premise of fuzzy rules. Three different type of polynomials function (namely, constant, linear, and quadratic) are used to construct the consequence of the rules. In order to improve the accuracy of FNNs, the structure and the parameters are optimized by making use of genetic algorithms (GAs). We enhance the search capabilities of the GAs by introducing the dynamic variants of genetic optimization. It fully exploits the processing capabilities of the FNNs by supporting their structural and parametric optimization. To evaluate the performance of the proposed FNNs, we exploit a suite of several representative numerical examples and its experimental results are compared with those reported in the previous studies.

• Journal of Korea Trade
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• 제26권7호
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• pp.93-108
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• 2022

Purpose - This paper examines the admissibility of restitution as the legal consequence where a contract is frustrated under the Law of Reform (Frustrated Contracts) Act 1943 in comparison with Korean Civil Code (KCC). In order to provide practical guidelines and advice regarding choice of and application of law for contracting parties in international trade, the paper comparatively evaluates requirements and the scope of restitution under the Act 1943 and KCC. Design/methodology - This paper executes a comparative study to analyze whether the parties may claim restitution of money paid or non-money benefit obtained before or after the time of discharge under English law and KCC. To achieve the purpose, it focuses on the identifying characteristics of each statute, thereby providing guidelines to overcome difficulties in legal application and interpretation as to restitution as the consequence of frustration. Findings - Under English law, the benefit may be restituted according to Art 1943 or the common law rule, mistake of fact or law. Under the KCC, restitution is considered based on the principle of the obligation to recover the original obtained regardless of the time when the benefit is conferred. Whilst Act 1943 does not require careful analysis of the grounds of restitution, requirements to justify restitution according to the principle of unjust enrichment, mistake of fact or law, and the KCC should be met. Meanwhile, the KCC may provide more opportunities to award restitution because it does not require the burden of proof related to the defendant's good faith, unlike the principle of unjust enrichment. Originality/value - Where the contract is frustrated by the effect of COVID-19, one legal issue is a consequence of frustration. Therefore, this paper analyzes requirements and the scope of restitution under English law as compared with the KCC in a timely manner. It provides contracting parties with practical guidelines and advice to reduce unpredictability when they choose the governing law in a contract.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.201-203
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• 2007

The paper concerns the successive optimization for structure and parameters of fuzzy inference systems that is based on parallel Genetic Algorithms (PGA) and information data granulation (IG). PGA is multi, population based genetic algorithms, and it is used tu optimize structure and parameters of fuzzy model simultaneously, The granulation is realized with the aid of the C-means clustering. The concept of information granulation was applied to the fuzzy model in order to enhance the abilities of structural optimization. By doing that, we divide the input space to form the premise part of the fuzzy rules and the consequence part of each fuzzy rule is newly' organized based on center points of data group extracted by the C-Means clustering, It concerns the fuzzy model related parameters such as the number of input variables to be used in fuzzy model. a collection of specific subset of input variables, the number of membership functions according to used variables, and the polynomial type of the consequence part of fuzzy rules, The simultaneous optimization mechanism is explored. It can find optimal values related to structure and parameter of fuzzy model via PGA, the C-means clustering and standard least square method at once. A comparative analysis demonstrates that the Dnmosed algorithm is superior to the conventional methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2633-2635
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• 2003

In this study, we propose a fuzzy polynomial neural networks (FPNN) and a genetically optimized fuzzy polynomial neural networks(GoFPNN) for identification of non-linear system. GoFPNN architecture is designed by a FPNN based on fuzzy set and its structure and parameters are optimized by genetic algorithms. A fuzzy neural networks(FNN) based on fuzzy set divide into two structures that is simplified inference structure and linear inference structure. The proposed FPNN is resulted from integration and extension of simplified and linear inference structure of FNN. The consequence structure of the FPNN consist of polynomials represented by networks using connection weights for rules. The networks comprehend simplified(Type 0), linear (Type 1), and quadratic(Type 3) inferences. The proposed FPNN can select polynomial type of consequence part for each rule. Therefore, proposed scheme can offer flexible structure design capability for a system characteristics. Moreover, GAs is applied to networks structure and parameters tuning of proposed FPNN, and its efficient application method is discussed, these subjects are result in GoFPNN that is optimal FPNN. To evaluate proposed model performance, a numerical experiment is carried out.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3465-3473
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• 2021

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning-Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

• 한국가스학회지
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• 제18권3호
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• pp.67-74
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• 2014

인구가 밀집되어 있는 도심지역에 매설된 천연가스 공급배관은 외부 또는 내부 결함으로 인한 가스의 누출, 확산, 화재, 폭발로 발생되는 재산과 인명피해의 큰 잠재위험을 지니고 있다. 사고를 미연에 방지하기 위해 정량적 평가에 기초한 위험관리를 실시하고 있으며, 매설배관의 정량적 위험성을 평가하기 위해서는 우선적으로 사고피해영향 분석을 통한 화학물질의 누출량 계산, 확산 분석, 화재 및 폭발로 인한 복사열과 압력파 계산이 필요하다. 본 논문에서는 CCPS, TNO에서 제안하는 model 들을 통하여 실제 San Bruno 매설배관 폭발 사고 시나리오를 기반으로 천연가스의 누출량, Fireball의 복사열 계산을 수행하고 결과 값을 실제 피해결과와 비교분석 하였다.

• 제어로봇시스템학회논문지
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• 제8권2호
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• pp.126-135
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• 2002

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Korean Chemical Engineering Research
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• 제57권2호
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• pp.225-231
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• 2019

우리나라의 경우 지상에 설치된 고압 천연가스 배관과 건축물 간의 최소 이격거리는 가스기술기준(KGS code)에 의해 규제된다. 이 논문을 통해 이러한 최소 이격거리를 관련된 KGS 코드를 개정한 기술적 근거를 보여주고자 한다. 이격거리를 설정하는 접근 방법으로 합리적 사고 시나리오에 의한 피해기반 접근법을 적용하였는데 배관에 부착된 1인치 분기 라인이 파손되어 제트화재가 발생한 시나리오를 선정하였다. 여기서 공업지역에 종사하는 작업자에 대해 비공업지역에 있는 사람들보다 더 높은 허용가능 복사열 플럭스를 적용하였다. 그 이유는 공업지역에 종사하는 근로자는 일반 대중들 보다 더 짧은 시간 안에 비상 대피가 가능하기 때문이다. 이 사고 시나리오에 대한 피해영향 분석 결과로부터 지상에 설치된 고압 천연가스 배관과 건축물 간의 최소 이격거리로서 비공업지역에서는 30 m, 공업지역에서는 15 m로 KGS 코드 개정을 제안하였다. 코드 개정안은 KGS 코드 위원회(가스기술기준위원회)에 채택되어 현재 시행 중이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1473-1476
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• 1997

This paper presents a scheme for continuous-time fuzzy modelling of nonlinear systems, based on the adjustment technique and the genetic algorithm technque. The fuzzy model is characterized by fuzzy "If-then" rules whcih represent locally linear input-output relations whose consequence part is defined as subsystem of a nonlinear system. To compute the final output and deal with the initialization and unmeasurable signal problems in on-line estimatio of the fuzzy model, a discrete-time model is obtaned. Then the parameters of both the premis and consequence of the fuzzy model are adjusted on-line by a genetic algorithm. A simulation work is carried out to demonstrate the effectiveness of the proposed method.ed method.