• Korean Journal of Microbiology
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• v.42 no.3
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• pp.205-209
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• 2006

For measuring the viable cells in lakes, quantitative direct viable count (qDVC) method is applied. In the qDVC process, the final concentration of glycine is fixed as 2%. For confirming the effectiveness of qDVC for enumerating the viable cells, the viable bacterial numbers were measured by plate count, CTC reduction method and qDVC method at 5 different lakes. Among these 3 methods, the bacterial numbers by qDVC is $2.4{\sim}6.0$ times higher than those by the other 2 methods. And by the qDVC method, the viable cells were easily discriminated from dead or dormant cells.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.103-113
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• 2021

In this study, the Q method is used to investigate the types of perceptions of liberal arts education perceived by college students and to investigate the characteristics of each type. 33 Q samples were extracted from the Q population collected through literature research, open questionnaires, and deep interviews. Q classification was conducted for 27 students of A University located in B City. The data was analyzed using the QUANL program. In the research, the types of awareness of liberal arts education were derived as "pursuit of various experiences", "pursuit of practical studies", "pursuit of accident expansion", and "pursuit of social change". The results of this study re-establish the meaning of liberal arts education in university education and suggest that it is necessary to consider various educational contents and teaching learning methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.895-899
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• 2000

A method of measuring Q of a two port cavity by scattering parameters is proposed. The scattering parameters of a two port cavity resonator are derived by a lumped equivalent circuit model as a function of cavity parameters, including the cavity Q. These can be also obtained by direct measurement with a modern network analyzer, The results show good agreement with those from other well-known methods. This two port measurement can provide additional information such as the coupled power ratio, which is one of the important parameters for the beam accelerating cavities.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.4
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• pp.442-450
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• 2008

In this paper, the phase diverisity in a direct-conversion receiver for a UHF RFID reader is analyzed and the optimal I/Q signal combining methods is presented with respect to tag modulation. At first, fading characteristics of a single channel receiver is shown to prove the importance of phase diversity due to the phase relationship between the backscattered signal and the local oscillator. And the optimal signal combining methods are presented in order to overcome the signal power reduction due to phase diversity. In case of ASK, the power combining method is presented for the optimal I/Q combining. And the arctangent and principal component combining methods using covariance matrix of I and Q channels are presented for the optimal I/Q combining in case of PSK. In order to analyze the performance of suggested methods, the selection diversity and the optimal combining methods are compared. According to analysis and simulation results, the optimal combining methods have a maximum 3 dB SNR enhancement than selection diversity.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.43-48
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• 2012

This paper presents an iterative single-frequency continuous-wave signal-based I/Q regeneration method for improving image-rejection performance of multi-port junction-based direct receivers (MPDRs). This paper analyzes I/Q regeneration in MPDRs as I/Q mismatch compensation for direct conversion receivers. Based on the analysis, this paper evaluates the accuracy of I/Q regeneration in terms of the image-rejection ratio (IRR). The proposed method improves the IRR performance more than 20 dB compared to existing I/Q regeneration methods. Simulation results show that MPDRs using the proposed method can achieve an IRR of more than 70 dB, and that the bit error rate performances are almost the same as those of conventional coherent demodulators, even in fading channels.

• Geophysics and Geophysical Exploration
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• v.14 no.3
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• pp.242-248
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• 2011

By applying analytic method to the uniform model, the intrinsic and scattering quality factor ($Q_i^{-1}$ and $Q_s^{-1}$) was separated for the southeastern part of Korean Peninsula. The Multiple Lapse Time Window Analysis method was used to fit theoretical values with observations obtained 759 earthquake data. While previous study for the Korean Peninsula showed very low $Q_i^{-1}$ and $Q_s^{-1}$ reflecting inactive seismicity, southeastern Korea exhibited relatively high $Q_i^{-1}$ and $Q_s^{-1}$ values interpreted as higher seismicity than the other region in the peninsula.

• Asia Marketing Journal
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• v.1 no.3
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• pp.120-140
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• 1999

Q 방법은 인간의 태도와 행동을 연구하기 위해 철학적, 심리학적, 통계적, 그리고 심리측정과 관련된 개념을 통합한 방법론으로서 인간의 주관성을 정량적으로 분석할 수 있는 특수한 통계기법이다. 소비자의 인식, 가치, 태도, 신념과 같은 개념을 객관적으로 연구할 수 있는 방법으로서 가설 생성을 위한 탐색적 연구와 이론의 검증과 같은 확인적 연구에서도 적용될 수 있다. 많은 수의 표본을 대상으로 한 횡단적 R 방법에 비하여 개인이나 소집단에 대한 깊이 있는 탐구가 가능하다는 점에서 소비자 행동 연구에 유용성이 매우 높다. 개인의 주관성을 바탕으로 한 소비자 개인의 특성과 차별성을 이해하는 것이 마케팅 분야의 핵심을 이루고 있음에도 불구하고 그 동안 소비자의 주관성에 대한 깊이 있는 접근이 이루어지지 못하였다. 1935년에 심리학 분야에서 개발된 Q방법은 이를 분석할 수 있는 컴퓨터 패키지의 보급과 더불어 사회과학 전반에 걸쳐 그 활용이 확산되어 가고 있다. 이에 Q 방법의 과학철학적 특성과, 현재 널리 이용되고 있는 변수 중심의 R 방법과의 차이, 그리고 컴퓨터 분석을 포함한 구체적인 Q 분석방법 및 관리적 활용상의 문제점에 대해 논의하였다

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.162-165
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• 2002

Q-learning은 강화학습의 한 방법으로서, 여러 분야에 널리 응용되고 있는 기법이다. 최근에는 Linear Quadratic Regulation(이하 LQR) 문제에 성공적으로 적용된 바 있는데, 특히, 시스템모델의 파라미터에 대한 구체적인 정보가 없는 상태에서 적절한 입력과 출력만을 가지고 학습을 통해 문제를 해결할 수 있어서 상황에 따라서 매우 실용적인 대안이 될 수 있다. Neural Q-learning은 이러한 Q-learning의 Q-value를 MLP(multilayer perceptron) 신경망의 출력으로 대치시킴으로써, 비선형 시스템의 최적제어 문제를 다룰 수 있게 한 방법이다. 그러나, Neural Q방식은 신경망의 구조를 먼저 결정한 후 역전파 알고리즘을 이용하여 학습하는 절차를 취하기 때문에, 시행착오를 통하여 신경망 구조를 결정해야 한다는 점, 역전파 알고리즘의 적용으로 인해 신경망의 연결강도 값들이 지역적 최적해로 수렴한다는 점등의 문제점을 상속받는 한계가 있다. 따라서, 본 논문에서는 Neural-0 학습의 도구로, 역전파 알고리즘으로 학습되는 MLP 신경망을 사용하는 대신 최근 들어 여러 분야에서 그 성능을 인정받고 있는 서포트 벡터 학습법을 사용하는 방법을 택하여, $\varepsilon$-SVR(Epsilon Support Vector Regression)을 이용한 Q-value 근사 기법을 제안하고 관련 수식을 유도하였다. 그리고, 모의 실험을 통하여, 제안된 서포트 벡터학습 기반 Neural-Q 방법의 적용 가능성을 알아보았다.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.635-642
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• 2003

Reinforcement learning got successful results in a lot of applications such as control and scheduling. Various function approximation methods have been studied in order to improve the learning speed and to solve the shortage of storage in the standard reinforcement learning algorithm of Q-Learning. Most function approximation methods remove some special quality of reinforcement learning and need prior knowledge and preprocessing. Fuzzy Q-Learning needs preprocessing to define fuzzy variables and Local Weighted Regression uses training examples. In this paper, we propose a function approximation method, Fuzzy Q-Map that is based on on-line fuzzy clustering. Fuzzy Q-Map classifies a query state and predicts a suitable action according to the membership degree. We applied the Fuzzy Q-Map, CMAC and LWR to the mountain car problem. Fuzzy Q-Map reached the optimal prediction rate faster than CMAC and the lower prediction rate was seen than LWR that uses training example.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.37-47
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• 2013

A Q-Q plot is an effective and convenient graphical method to assess a distributional assumption of data. The primary step in the construction of a Q-Q plot is to obtain a closed-form expression to represent the relation between observed quantiles and theoretical quantiles to be plotted in order that the points fall near the line y = a + bx. In this paper, we introduce a Q-Q plot to assess goodness-of-fit for inverse Gaussian distribution. The procedure is based on the distributional result that a transformed random variable $Y={\mid}\sqrt{\lambda}(X-{\mu})/{\mu}\sqrt{X}{\mid}$ follows a half-normal distribution with mean 0 and variance 1 when a random variable X has an inverse Gaussian distribution with location parameter ${\mu}$ and scale parameter ${\lambda}$. Simulations are performed to provide a guideline to interpret the pattern of points on the proposed inverse Gaussian Q-Q plot. An illustrative example is provided to show the usefulness of the inverse Gaussian Q-Q plot.