• 한국수소및신에너지학회논문집
• /
• 제25권6호
• /
• pp.609-619
• /
• 2014

In the present study, the frequency of the undesired accident was estimated for a quantitative risk assessment of a large-scale hydrogen liquefaction plant. As a representative example, the hydrogen liquefaction plant located in Ingolstadt, Germany was chosen. From the analysis of the liquefaction process and operating conditions, it was found that a $LH_2$ storage tank was one of the most dangerous facilities. Based on the accident scenarios, frequencies of possible accidents were quantitatively evaluated by using both fault tree analysis and event tree analysis. The overall expected frequency of the loss containment of hydrogen from the $LH_2$ storage tank was $6.83{\times}10^{-1}$times/yr (once per 1.5 years). It showed that only 0.1% of the hydrogen release from the $LH_2$ storage tank occurred instantaneously. Also, the incident outcome frequencies were calculated by multiplying the expected frequencies with the conditional probabilities resulting from the event tree diagram for hydrogen release. The results showed that most of the incident outcomes were dominated by fire, which was 71.8% of the entire accident outcome. The rest of the accident (about 27.7%) might have no effect to the population.

• 한국컴퓨터정보학회논문지
• /
• 제29권6호
• /
• pp.113-120
• /
• 2024

정보통신 기술이 발전함에 따라 우리는 일상에서 다양한 형태의 데이터를 손쉽게 생성하고 있다. 이처럼 방대한 데이터를 효율적으로 관리하려면, 체계적인 카테고리별 분류가 필수적이다. 효율적인 검색과 탐색을 위해서 데이터는 트리 형태의 계층적 구조인 범주 트리로 조직화되는데, 이는 뉴스 웹사이트나 위키피디아에서 자주 볼 수 있는 구조이다. 이에 따라 방대한 양의 문서를 범주 트리의 단말 노드로 분류하는 다양한 기법들이 제안되었다. 그러나 범주 트리를 대상으로 하는 문서 분류기법들은 범주 트리의 높이가 증가할수록 단말 노드의 수가 기하급수적으로 늘어나고 루트 노드부터 단말 노드까지의 길이가 길어져서 오분류 가능성이 증가하며, 결국 분류 정확도의 저하로 이어진다. 그러므로 본 연구에서는 사용자의 요구 분류 정확도를 만족시키면서 세분화된 분류를 구현할 수 있는 새로운 노드 확장 기반 분류 알고리즘을 제안한다. 제안 기법은 탐욕적 접근법을 활용하여 높은 분류정확도를 갖는 노드를 우선적으로 확장함으로써, 범주 트리의 분류 정확도를 극대화한다. 실데이터를 이용한 실험 결과는 제안 기법이 단순 방법보다 향상된 성능을 제공함을 입증한다.

• Mycobiology
• /
• 제40권1호
• /
• pp.82-84
• /
• 2012

The tulip tree ($Liriodendron$ $chinense$) has been widely cultivated in Korea as a street or garden tree for its large flowers, which have a superficial resemblance to tulips. Occurrence of anthracnose disease on the leaves of tulip trees growing on the campus of Gyeongsang National University, Jinju, Korea, has been observed. Based on mycological characteristics, pathogenicity, and internal transcribed spacer sequence, the causal fungus was identified as $Colletotrichum$ $gloeosporioides$. This is the first report on anthracnose disease caused by $C.$ $gloeosporioides$ on tulip trees in Korea.

• 한국경영과학회지
• /
• 제25권4호
• /
• pp.15-25
• /
• 2000

In this paper, we introduce a point-to-multipoint minimum cost flow problem with convex and demand splitting. A source node transmits the traffic along the tree that includes members of the point-to-multipoint connection. The traffic is replicated by the nodes only at branch points of the tree. In order to minimize the sum of arc costs, we assume that the traffic demand can be splitted and transmitted to destination nodes along different trees. If arc cost is linear, the problem would be a Steiner tree problem in networks eve though demand splitting is permitted. The problem would be applied in transmitting large volume of traffic from a serve to clients in Internet environments. Optimality conditions of the problem are presented in terms of fair tree routing. The proposed algorithm is a finite terminating algorithm for $\varepsilon$-optimal solution. convergence of the algorithm is obtained under monotonic condition and strict convexity of the cost function. Computational experiences are included.

• 한국경영과학회지
• /
• 제18권2호
• /
• pp.183-203
• /
• 1993

One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rule-tree. A splitting algorithm is developed using the pruning measure based on a total amount of information gain and the measure of existing algorithms. A user can easily adjust the size of the resulting rule-tree according to his(her) preferences and problem domains. The algorithm is applied to a market segmentation problem of a medium-large computer market. The algorithm is illustrated step by step with a sales data of a computer market and is analyzed.

• 품질경영학회지
• /
• 제19권2호
• /
• pp.96-107
• /
• 1991

At the design stage of a plant, the plausible causes and pathways of release of hazardous materials are not clearly known. Thus there exist large amount of uncertainties on the consequences resulting from the operation of a fusion plant. In order to better handle such uncertain circumstances, we utilize the Probabilistic Risk Assessment(PRA) for the safety analyses on fusion power plant. In this paper, we concentrate on the tritium release accident. We develop a simple model that describes the process and flow of tritium, by which we figure out the locations of tritium inventory and their vulnerability. We construct event tree models that lead to various levels of tritium release from abnormal initiating events. Branch parameters on the event tree are assessed from the fault tree analysis. Based on the event tree models we construct influence diagram models which are more useful for the parameter updating and analysis. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of consequences resulting from the operating a fusion power plant. We also discuss the way to utilize the results of testing on sub-systems to reduce the uncertain ties on over all system.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2005년도 가을 학술발표논문집 Vol.32 No.2 (2)
• /
• pp.100-102
• /
• 2005

데이터베이스에 저장되어 있는 데이터들을 통해서 의미있는 정보를 찾는 것이 데이터 마이닝이다. 많은 데이터 마이닝 기법들 중에 연관규칙을 다루는 연구가 많이 이루어지고 있다. 연관규칙 기법도 다양하게 연구되고 있는데 그 중 빈발 패턴 트리(FP-Tree)라는 방법을 이용하여 빈발 패턴을 찾아내는 연구가 활발히 진행되고 있다. 빈발 패턴 트리는 기존에 잘 알려져있는 연관규칙 생성 기법인 Apriori 기법보다 우수한 성능을 가지는 방법이다. 그러나 빈발 패턴 트리도 몇가지 문제점을 가지고 있다. 본 논문에서는 빈발 패턴 트리의 문제점 중 하나인 과도한 FP-Tree 생성을 줄이려 한다. 조건부 패턴 베이스를 통해 얻어지는 조건부 FP-Tree의 생성을 줄여 기존의 FP-Tree보다 더 나은 성능을 얻기 위해서 적절한 클리스터링을 이용하려 한다. 클러스터링 기법은 비트 트랜잭션을 이용한 클러스터링 방법을 이용한다.

• 대한산업공학회지
• /
• 제40권4호
• /
• pp.375-381
• /
• 2014

Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1993년도 하계학술대회 논문집 B
• /
• pp.1130-1133
• /
• 1993

In this paper, it is discussed the correlation between shape of tree and internal partial discharge in low density polyethylene(LDPE) blended with organic compounds that used to improve the effect of resistance to treeing. Initiation and growing of tree are retarded in specimens blended with organic compounds that comprised radical having large electron affinity, and also discharge magnitude and counts of discharging pulse per unit time in these samples are more than those in others. It is observed that the shape of tree in these samples is bush type, but in case of pure LDPE samples dendrite type.

• 한국가스학회지
• /
• 제5권2호
• /
• pp.1-8
• /
• 2001

공정의 위험성 평가를 위한 이상트리 작성은 많은 시간과 인력을 요하는 작업으로 대규모 화학공장에 적용하기가 매우 힘들다. 본 연구에서는 화학공정의 이상트리 합성을 위해 장치에서 발생할 수 있는 공정변수의 이탈 및 장치이상에 대한 원인-결과 관계를 나타내는데 필요한 객체지향 지식기반의 프레임워크를 제안하였다. 이상에 대한 원인을 탐색하기 위하여 장치의 객체지향 모델링과 장치간의 연결관계를 이용하여 이탈을 전파하고 이를 통해 이상트리를 합성하였다. 제안된 방법론을 질산 냉각 공정에 적용하여 그 유효성을 검증하였다.