• Journal of Life Science
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• v.15 no.3 s.70
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• pp.359-364
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• 2005

Spatial autocorrelation was applied to microgeographic variations of Sasa borealis populations in Korea. Separate counts of each type of join (combination of genotypes at a single locus) for each allele, and for each distance class of separation, were tested for significant deviation from random expectations by calculating the Standard Normal Deviation. Moran's I was significantly different from the expected value in 25 of 150 cases $(16.7\%)$. Seven of these values $(4.7\%)$ were negative, indicating genetic dissimilarity among pairs of individuals in the ten distance classes. Populations of S. borealis are small in Korea, and are distributed with occasional cutting of seed-bearing stems used for sieves. Thus, artificial disturbance may contribute to the fact that the S. borealis population of Jirisan is unusual in lacking spatial genetic structure.

• Aerospace Engineering and Technology
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• v.3 no.1
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• pp.188-196
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• 2004

To optimize and limit the axial length of baffle in KSR-III engine, stability rating tests using pulse gun as one of artificial disturbance devices have been done. Decay time and other parameters for the evaluation of stabilization ability of engine to external perturbation have been analyzed to quantify stabilization capacity of engine, in other words, dynamic stability margin. If baffle does not cover flame zone enough which can be considered as collision region of injector, it wasn't be able to suppress external perturbation sufficiently. The limit of combustion stability margin of engine is assumed to be 50 mm length baffle.

• Korean System Dynamics Review
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• v.15 no.3
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• pp.61-79
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• 2014

This paper deals with system thinking in the resilience of the SES (Social-Ecological Systems) around Mt. Gariwang, located in Jeongseon County, Gangwon Province, in particular with the disturbance that a new ski slope is planned to be built for the PyeongChang 2018 Winter Olympic. It first performs a literature survey and newspaper article search to summarize the controversy with regards to credible environmental and socio-economical impacts of the plan, and then elaborates a series of CLDs (Causal Loop Diagrams) to infer the dynamics of the impacts. The results imply that the natural restoration seems to be hard because the development activities can cause a great deal of damage to the ecosystem mainly due to soil degradation and the mitigation of icy valley effects with water exploitation for making artificial snow and so on. Moreover most of the households near the planned site seem to leave with land compensation, thus more policy efforts are needed to enhance the resilience of the ecosystem and the nearby society based on ecotourism.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.494-501
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• 1999

In this research, ANN modeling method of SMES unit is developed for stability analysis, and the optimal site is selected to maximize stabilization effect of SMES unit. The ANN is trained by learning data which is obtained through the application of complex test function into the traditional mathematical mode. In order to verify the validity of proposed modeling method, fault data of sample power system is applied to both the traditional and the ANN models. When the response of traditional and proposed models are compared, the average error for the active and reactive power are 2.51[%], and 0.24[%], respectively. From the comparison, the relevance of proposed method is validated. For the transient stability analysis, an application method of the proposed model is presented, and the transient stability performance index, which describes system stabilization effect of SMES at disturbance, is also suggested, and optimal site selection method of SMES is presented. In the viewpoint of the voltage stability, system stabilization criterion of local bus is presented from P­V curve, and then optimal site which can maximize the voltage stabilization of the whole power system, is decided from the proposed voltage stability performance index.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2126-2128
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• 2001

This paper suggests that the immune network algorithm based on fuzzy set can effectively be used in tuning of a PID controller for multivariable process or nonlinear process. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that from a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. Along with these, this paper used the fuzzy set in order that the stimulation and suppression relationship between antibody and antigen can be more adaptable controlled against the external condition, including noise or disturbance of plant. The immune network based on fuzzy set suggested here is applied for the PID controller tuning of multivariable process with two inputs and one output and is simulated.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.315-320
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, NNPI controller proposes a new method based neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fired gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.404-407
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation even under ideal field oriented conditions. This paper is proposed adaptive fuzzy controller(AFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaptation mechanism(FAM), AFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, AFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Journal of the Korean Institute of Landscape Architecture
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• v.21 no.2
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• pp.107-119
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• 1993

This study was conducted to increase to increase the plant species diversity, which was based on the analysis of plant community structure and the survey of human's disturbance degree in Mt. Yongma and Mt. Acha urban nature park, Seoul. The plant community were divided into four groups by TWINSPAN and DCA. These groups were Pinus rigida-P. densiflora community, Quercus mongolica-Q.aliena-Q.accutissima community, Robinia pseudoacaia-Q.accutissima-Poplus${\times}$albaglandulosa community and R.pseudoacacia community. The successional trends of tree species seems to be from P.densiflora, P.rigida, Sorbus alniflora to Q.mongolica, Q.aliena and from P.${\times}$albaglandulosa, R.pseudoacacia, through Q.accutissima, to Q. mongolica, Q.aliena. The species diversity of plant community was high in natual plant community but was low in artificial planting community respectively. Number of species, number of species individuals, indices of species diversity was lowered and soil hardness was increased by the user's trampling, undercutting work and planting P.koraiensis after thinning. In the basis of study results, we proposed the management plan for the urban forest.