• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.04a
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• pp.28-34
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• 1995

Behavior of underground structural systems is usually complicated because of various unknown parameters. In order to construct those structural systems safely and economically, exact identification of the system parameters and accurate analysis of the system behaviors are essentially required. In this study, a forward analysis program, which is able to eliminate numerical errors due to far field boundary effect, is developed by coupling finite and boundary elements. In this coupled analysis, boundary elements are used in the semi-infinite domain where stress variation is small, and finite elements in the stress concentration region where material nonlinearity should be considered. Then, a back analysis program which can identify the system parameters is developed using the direct method to be combined with the forward analysis program. The elastic modulus and initial stress, which are most important in the description of the behavior of underground structures, are taken as the system parameters. A simple example is examined 0 show that the method can be used effectively.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.77-85
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• 1993

In this paper, we present a method to solve a convexly combined fuzzy relational equation with generalized connectives. For this, we propose a neural network whose structure represents the fuzzy relational equation. Then we derive a learning algorithm by using the concept of back-propagation learning. Since the proposed method can be used for a general form of fuzzy relational equations, such fuzzy max-min or min-max relational equations can be treated as its special cases. Moreover, the relational structure adopted in the proposed neurocomputational approach can work in a highly parallel manner so that real-time applications of fuzzy sets are possibles as in fuzzy logic controllers, knowledge-based systems, and pattern recognition systems.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.135-141
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• 2015

The objective of this study is to develop an early warning system for rainfall induced landslides. For this study, we suggested an analysis process using rainfall forecast data. 1) For a selected slope, safety factor with saturated depth was analyzed and safety factor threshold was established (warning FS threshold=1.3, alarm FS threshold=1.1). 2) If rainfall started, saturated depth and safety factor was calculated with rainfall forecast data, 3) And every hour after safety factor is compared with threshold, then warning or alarm can issued. In the future, we plan to make a early warning system combined with the in-situ inclinometer sensors.

• International Journal of Contents
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• v.14 no.1
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• pp.18-27
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• 2018

The objective of this study was to derive approximate closed-form error rates for M-ary burst symbol transmission (MBST) of dual-hop adaptive decode-and-forward (ADF) cooperative relay systems over quasi-static Rayleigh fading channels. Within a burst, there are pilot symbols and data symbols. Pilot symbols are used for channel estimation schemes and each relay node's transmission mode selection schemes. At first, our focus was on ADF relay systems' error-events at relay nodes. Each event's occurrence probability and probability density function (PDF) were then derived. With error-event based approach, we derived a tractable form of PDF for combined signal-to-noise ratio (SNR). Averaged error rates were then derived as approximate expressions for arbitrary link SNR with different modulation orders and numbers of relays. Its accuracy was verified by comparison with simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.340-343
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• 2000

본 논문에서는 선박에서 퍼지 데이터베이스를 이용하여 지능형 화재진압통제시스템의 성능을 개선시키는 방법에 대하여 논의하였다. 규칙과 사례가 통합된 화재진압통제 전문가시스템(C-FFES)에서는 사례기반 추론을 하기 위한 사례베이스가 일반적인 데이터베이스로 구성되어 있어서, 이전에 화재가 발생했던 사례와 현재의 사례가 유사한지를 구별하기가 쉽지 않은 문제점을 지니고 있다. 제안하는 시스템에서는 예외적인 상황에서 화재가 발생하는 사례를 퍼지데이터베이스로 구성하고, 현 상황과 예외적인 상황에서 화재가 발생하는 사례를 조회하기 위하여 퍼지 유사도 개념을 적용하여 현재 입력된 사례와 가장 유사한 사례가 조회될 수 있도록 하였다. 또한 기존의 규칙 기반 FFES(Fire Fighting Expert System), 사례기반 추론에 의해 확장된 C-FFES(Combined-Fire Fighting Expert System) 그리고 제안하는 A-FFES(Advanced Fire fighting Expert System)를 비교를 통해, 제안하는 A-FFES가 화재탐지율을 향상시킴을 보였다.

• Journal of Korean Academy of Nursing
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• v.33 no.6
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• pp.731-742
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• 2003

Purpose: This ethnography is aimed at describing the health care seeking behavior of elderly details in their socio-cultural context. The research question is 'under what conditions did elderly informants decide to use certain professional health care services and how do they make use of all the available resources?' Method: 10 sessions of fieldwork were conducted in the two agricultural villages between Sep. 1999 and Oct. 2002. The data for this paper came from participant observation with 14 informants. In the process of analysis I used proxemic and taxonomic techniques. Result: Informants decided to use a certain health care system according to their folk definition of illness. They prefer to use the health services where they felt more comfortable and free. They wished to be care from intuitive and holistic healers. Social network and having health resources was also important factor. Conclusion: We need more comprehensive research model to reach a plausible explanation. Combined qualitative-quantitative research is needed to get practical data to develop effective health care systems for the elderly.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.170-175
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• 1998

Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.296-301
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• 1998

The Rough Set theory suggested by Pawlak in 1982 has been useful in AI, machine learning, knowledge acquisition, knowledge discovery from databases, expert system, inductive reasoning. etc. The main advantages of rough set are that it does not need any preliminary or additional information about data and reduce the superfluous informations. but it is a significant disadvantage in the real application that the inference result form is not the real control value but the divided disjoint interval attribute. In order to overcome this difficulty, we will propose approach in which Rough set theory and Neuro-fuzzy fusion are combined to obtain the optimal rule base from lots of input/output datum. These results are applied to the rule construction for infering the temperatures of refrigerator's specified points.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.347-351
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• 1998

Dynamic programming is applicable to any situation where items from several groups must be combined to form an entity, such as a composite investment or a transportation route connecting several districts. The most desirable entity is constructed in stages by forming sub-entities that are candidates for inclusion in the most desirable entity are retained, and all other sub-entities are discarded. In the paper, the fuzzy dynamic programming is applied to the situation where each investment in the set has the following characteristics : the amount to be invested has several possible values, and the rte of return varies with the amount invested. Each sum that may be invested represents a distinct level of investment , and the investment therefore has multiple levels. A numeric example constructing a combination of multilevel investments is given in the paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.485-488
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• 1998

Elementary school pupils frequently have difficult acquiring creative writing skills, i.e. how to develop the idea to be expressed, how to compose the materials of the outcome or contents. In this paper, we focus on the problems of how to support creative writing work to arrange materials in order to formulate ideas as the stories develop. the stories develop. The basic ideas behind the method are that(1) a basic story is automatically generated by GA-based operations and shown to a user as sequences of pictures, (2) IGA(Interactive Genetic Algorithm) is used to evaluate and select a preferred story, (3) the results are combined with previously stored stories using case-based techniques. Based on these ideas, we have developed a computer supported environment for this purpose and conducted related experiments.