• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.3
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• pp.12-19
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• 2006

Micro-source units having power ratings in thousands of watts can provide power quality with higher reliability and efficiency than the conventional large scale units. This paper develops switching level model of micro-source and studies the characteristics of the micro-grid consisting of multiple micro-sources and interfaced with electric power system. The developed model adopts the space vector PWM to fully utilize the capacity of inverter. The interaction of the grid connected micro-sources and the characteristics of the control system parameters are investigated. Micro-sources and micro-grid are implemented using PSCAD/EMTDC. Simulation results show that the proposed model is efficient for studying micro-grid system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.62-69
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• 2009

For the fault diagnosis of power transformer, we develop a diagnosis algorithm based on support vector machine. The proposed fault diagnosis system consists of data acquisition, fault/normal diagnosis, and identification of fault. In data acquisition part, concentrated gases are extracted from transformer for data gas analysis. In fault/normal diagnosis part, KEPCO based decision rule is performed to separate normal state from fault types. The determination of fault type is executed by multi-class SVM in identification part. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

• Nuclear Engineering and Technology
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• v.49 no.4
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• pp.817-824
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• 2017

Residual stress is a critical element in determining the integrity of parts and the lifetime of welded structures. It is necessary to estimate the residual stress of a welding zone because residual stress is a major reason for the generation of primary water stress corrosion cracking in nuclear power plants. That is, it is necessary to estimate the distribution of the residual stress in welding of dissimilar metals under manifold welding conditions. In this study, a cascaded support vector regression (CSVR) model was presented to estimate the residual stress of a welding zone. The CSVR model was serially and consecutively structured in terms of SVR modules. Using numerical data obtained from finite element analysis by a subtractive clustering method, learning data that explained the characteristic behavior of the residual stress of a welding zone were selected to optimize the proposed model. The results suggest that the CSVR model yielded a better estimation performance when compared with a classic SVR model.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.715-717
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• 2005

Support vector machine(SVM)은 최근 각광받는 기계학습 방법 중 하나로서, kernel function 이라는 사상(mapping)을 이용하여 입력 공간의 벡터를 classification이 용이한 특징 (feature) 공간의 벡터로 변환하는 것을 근간으로 한다. SVM은 이러한 특징 공간에서 두 클래스를 구분 짓는 hyperplane을 일련의 최적화 방법론을 사용하여 찾아내며, 주어진 문제가 convex problem 인 경우 항상 global optimal solution 을 보장하는 등의 장점을 지닌다. 한편 bioinformatics 연구에서 주로 사용되는 데이터는 측정 오류 등 일련의 오류를 포함하고 있으며, 이러한 오류는 기계학습 방법론이 어떤 decision boundary를 찾아내는가에 영향을 끼치게 된다. 특히 SVM의 경우 이러한 오류는 특징 공간 벡터간의 관계를 나타내는 Gram matrix를 변화로 나타나게 된다. 본 연구에서는 입력 공간에 오류가 발생할 때 그것이 SVM 의 decision boundary를 어떻게 변화시키는가를 대표적인 두 가지 kernel function, 즉 linear kernel과 Gaussian kernel에 대해 분석하였다. Wisconsin대학의 유방암(breast cancer) 데이터에 대해 실험한 결과, 데이터의 오류에 따른 SVM 의 classification 성능 변화 양상을 관찰하여 커널의 종류에 따라 SVM이 어떠한 특성을 보이는가를 밝혀낼 수 있었다. 또 흥미롭게도 어떤 조건 하에서는 오류가 크더라도 오히려 SVM 의 성능이 향상되는 것을 발견했는데, 이것은 바꾸어 생각하면 Gram matrix 의 일부를 변경하여 SVM 의 성능 향상을 꾀할 수 있음을 나타낸다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1577-1584
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• 2015

In this paper, we propose a method for generating pattern classifier based on LFSR. The proposed pattern classifier bosed on LFSR is easy to see non-reachable state, and we can obtain dependency vector by using the 0-basic path. Also, we propose a method for generating pattern classifiers based on LFSR which correspond to given dependency vector.

• Journal of Power Electronics
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• v.3 no.4
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• pp.239-248
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• 2003

This paper presents a novel prototype of three-phase voltage source type zero voltage soft-switching inverter with the auxiliary resonant snubbers suitable for high-power applications with IGBT power module packages in order to reduce their switching power losses as well as electromagnetic conductive and radiative noises. A proposed single inductor-assisted resonant AC link snubber circuit topology as one of some auxiliary resonant commutation snubbers developed previously to achieve the zero voltage soft-switching (ZVS) for the three-phase voltage source type sinewave PWM inverter operating under the instantaneous space voltage vector modulation is originally demonstrated as compared with the other types of resonant AC link snubber circuit topologies. In addition to this, its operation principle and unique features are described in this paper. Furthermore, the practical basic operating performances of the new conceptual instantaneous space voltage vector modulation resonant AC link snubber-assisted three-phase voltage source type soft-switching PWM inverter using IGBT power module packages are evaluated and discussed on the basis of switching voltage and current waveforms, output line to line voltage quality, power loss analysis, actual power conversion efficiency and electromagnetic conductive and radiative noises from an experimental point of view, comparing with those of conventional three-phase voltage source hard-switching PWM inverter using IGBT power modules.

• Journal of KIISE
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• v.42 no.1
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• pp.86-92
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• 2015

A level set tree provides a useful representation of a multidimensional density function. Visualizing the data structure as a tree offers many advantages for data analysis and clustering. In this paper, we present a level set tree estimation algorithm for use with a set of data points. The proposed algorithm creates a level set tree from a family of level sets estimated over a whole range of levels from zero to infinity. Instead of estimating density function then thresholding, we directly estimate the density level sets using one-class support vector machines (OC-SVMs). The level set estimation is facilitated by the OC-SVM solution path algorithm. We demonstrate the proposed level set tree algorithm on benchmark data sets.

• Korean Journal of Plant Tissue Culture
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• v.22 no.4
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• pp.195-200
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• 1995

The mammalian adenosine deaminase(ADA) gene was stably expressed in transgenic tobacco plane. The chimeric ADA gene 35S/35S/AMV/ADA/Tnos, has been constructed. This chimeric gene was introduced into the binary vector pRD400, which was thereafter mobilized into Agrobacterium tumefaiens strain MP90 harboring disarmed Ti-plasmid. The resulting strains were used to transform Nicofiana tabacum L. using the leaf disc. Incorporation of the chimeric gene into plant were confirmed by PCR and Northern blot analyses. Immunoblot analysis showed that ADA protein was successfully synthesized in the transgenic tobacco plants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5143-5149
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• 2011

In this paper, using the adaptive sliding mode observer for speed sensorless vector control is proposed. Adaptive sliding mode observer of the motor stator coordinate system using the voltage equations of the rotor flux components are observed. Motor speed was obtained by the Lyapunov function is estimated by the relationship further. In order to establish such a control scheme based on the way conventional PI controller and sliding mode observer annexing characteristics of the system through simulation and experiment were compared. According to analysis by comparison with the usefulness of the system was confirmed.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1879-1888
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• 2018

With power level of grid-connected converters rising, the switching frequency of the switching devices is commonly greatly reduced to improve its power capacity. However, this results in serious couplings of the dq current components, which leads to degradation of the static and dynamic performances of grid-connected converters and fluctuations of the reactive power in dynamic processes. In this paper, complex vector models under low switching frequency are established for an L/LCL grid-connected converter, and the relationship between the switching frequency and the coupling degree is analyzed. In addition, a series decoupling current control strategy is put forward. It is shown that the proposed control strategy can eliminate the couplings, improve the performances and have good robustness to parameter variations through static and dynamic characteristics analyses and a sensitivity analysis. Experimental and simulation results also verify the correctness of the theoretical analyses and the superiority of the proposed control strategy.