• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2012년도 추계학술대회
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• pp.75-76
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• 2012

본 논문에서는 MIMO(multi-input multi-output) RQD(rotation constellation and Q-delay) 시스템을 적용하여 지상파 UHDTV 시스템을 구현하기 위한 전송 시스템의 성능을 분석한다. 차세대 UHDTV 시스템이 필요로 하는 높은 전송량을 달성하기 위하여 STBC(space time block code)를 사용하는 기존의 MISO(multi-input single-output)와 MIMO(multi-input multi-output) 시스템에 RQD 기술을 더하여 성능을 개선한다. 개선된 MISO RQD 기법과 MIMO RQD 기법의 성능을 컴퓨터 시뮬레이션을 통하여 비교 분석하였다. 또한 실험 결과를 통하여 앞으로 차세대 지상파 UHDTV를 위한 방향을 제시한다.

• 한국통신학회논문지
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• 제32권12A호
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• pp.1238-1243
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• 2007

본 논문에서는 zero-forcing (ZF) 기반 다중 사용자 MIMO (multiple-input multiple-output) 시스템에서, 송신-처리-행렬을 구하기 위한 간단한 순차적 (recursive) nulling 행렬 계산 알고리즘을 제안한다. 제안한 방식은 채널 행렬의 부분 행렬을 써서 구한 nulling 행렬을 이용하여 전체 행렬의 nulling 행렬과 송신-처리-행렬을 구하는 방식으로써, 전체 채널 행렬을 이용하여 송신-처리-행렬을 구하는 기존 방식에 비해 계산량을 줄일 수 있다.

• 농촌계획
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• 제16권1호
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• pp.9-20
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• 2010

The aim of this paper is to identify Korean agricultural and agri-manufacturing cluster using a multi-regional input-output model. This paper derives a representative set of five agricultural and agri-manufacturing clusters in Korea in terms of spatial and industrial interdependency. The results show that agriculture and agri-manufacturing clusters agglomerated in Seoul Metropolitan Area and Chungcheong Area are linked both production and manufacture functions, whereas Gangwon Area is more focused on production and Jeolla Area is more concentrated on manufacture.

• 한국융합학회논문지
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• 제7권4호
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• pp.191-198
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• 2016

국가 기간산업 중 하나인 전력산업은 산출물인 전력을 각 산업부문에 중간재로 공급하고 있으므로 전력의 공급지장이 국민경제에 미치는 영향은 큰 편이다. 만약 전력 공급이 원활치 못하게 되면 직접적으로는 생산 차질, 원료 공급 불안, 각종 장비 고장 등의 생산 및 공정상의 문제를 일으키고 간접적으로는 생산 차질에 따른 전력 관련 산업의 생산 손실부터 실업 및 물가 상승 등의 문제까지 등장할 수 있다. 이에 본 논문에서는 전력산업 산출물 1원어치의 공급지장이 타 산업에 미치는 부정적 생산차질 효과를 의미하는 공급지장효과를 분석하고자 한다. 이를 위해 산업간 중간재의 흐름을 하나의 표로 나타낸 산업연관표를 활용한 산업연관분석을 적용하고자 한다. 보다 구체적으로는 OECD 주요국을 대상으로 공급유도형 모형을 활용하여 공급지장 효과를 분석한다. 공급지장효과의 값은 덴마크가 1.682로 가장 크며 다음으로 한국, 일본, 호주, 영국 순으로 나타났다.

• 무역학회지
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• 제46권1호
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• pp.83-111
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• 2021

This paper conducts a Structural Dcomposition Analysis on the structure of factors contributing to the output growth of Korean Maritime and Port Industry during year 2000~ year 2017. Some of results are as follows. The output growth rates of the industry (yearly average 4.3%) was far lower than the average growth rates of Service as well as of Manufacturing Industries (yearly average 9% and 6.8%, respectively) due to the lower output growth of Maritime Industry. Among the growth contributing factors, change in domestic demand for final goods is the first contributing factor, and then change in technology, change in export and import substitution for intermediate goods are followed in order, but import substitution for final goods decreased its output. However, in each respective sub-periods of pre-global financial crisis and post-global financial crisis, change in the export, especially change in the export of Maritime Industry is the dominant determinant of output change in the Maritime and Port Industry in opposite ways. In the periods of the former the increase in the export of Maritime Industry overwhelmingly led the output growth of the Maritime and Port industry, but in the periods of the latter the decrease in its export was the culprit of lower output growth of the industry. On the other hand, among all industries of service and manufacturing sectors, Wholesale and Retail industry is the leading industry in contributing to the output growth of the Maritime and Port Industry, and Transportation Equipment industry is the leading industry among all manufacturing industries.

• Journal of information and communication convergence engineering
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• 제7권1호
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• pp.46-51
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• 2009

In this paper, the two-axis theory is adopted to analyze the secondary excited induction generator applied to random wave input generation system. The analysis by the two-axis theory helps to know the transmitted power of the induction machine. The electric variables, like as primary and secondary currents, voltages, and electric output power, were able to express as equations. These equations are help to simulate the generation system numerical model and to know the transient state of the system. As it is preferred to stabilize the output voltage and frequency in the constant level, microcomputer controlled VSI connected to the secondary windings supplies the secondary current with slip frequency. For testing the appropriateness of this method, the input torque simulator in the laboratory to drive the secondary excited results show the advantage of secondary excited induction generator system for the random input wave generation system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.242-245
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• 1995

In this paper the multiple three rectifiers for the power factor correction are proposed, analyzed and designed. The multiple three phase rectifiers draw sinusoidal ac currents from the ac voltage sources with nearly unity input power factor and operate with PWM making the control circuit simple and system cost low. Outstandingly it reduces the rated power capacity of devices and the input filter size by reducing input current ripples. Moreover design rules can be obtained from input and output current equations. With the proposed rules, input power factor and output power capacity are determined approximately. Finally these design rules are verified with computer simulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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• pp.2033-2036
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• 1997

In this paper, we proposed a novel current-fed DC-DC converter with multi-output. It has two winding reactor in series with the input source of the converter. By using the 2nd winding recycling the energy stored in the reactor to the input, the double-outputs DC-DC converter can be created, which makes it a good choice for a multi-output power supply with more outputs and has savings in cost and space. The steady state and dynamic characteristics of the converter are analyzed in detail by using the state space averaging method. It is found that the maximum value of $V_{o2}$ exists in the 2nd output and also during the MOSFET off period, the energy stored in the magnetizing inductance is reset through auxiliary winding $N_3$, so the duty cycle is restricted to 50%. Theoretical and experimental results were taken from the converter rated at switching frequency 50kHz. input voltage 50V. output voltage 5V. 12V and output power 65W. As a result, both results were well consistent. Therefore, it is varified the validity of the proposed converter in this paper.

• 대한산업공학회지
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• 제36권3호
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.26-26
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• 2023

General circulation models (GCMs) are widely used in hydrological prediction, however their coarse grids make them unsuitable for regional analysis, therefore a downscaling method is required to utilize them in hydrological assessment. As one of the downscaling methods, convolutional neural network (CNN)-based downscaling has been proposed in recent years. The aim of this study is to generate the process of dynamic downscaling using CNNs by applying GCM output as input and RCM output as label data output. Prediction accuracy is compared between different input datasets, and model structures. Several input datasets with key atmospheric variables such as precipitation, temperature, and humidity were tested with two different formats; one is two-dimensional data and the other one is three-dimensional data. And in the model structure, the hyperparameters were tested to check the effect on model accuracy. The results of the experiments on the input dataset showed that the accuracy was higher for the input dataset without precipitation than with precipitation. The results of the experiments on the model structure showed that substantially increasing the number of convolutions resulted in higher accuracy, however increasing the size of the receptive field did not necessarily lead to higher accuracy. Though further investigation is required for the application, this paper can contribute to the development of efficient downscaling method with CNNs.