• 청정기술
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• 제17권3호
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• pp.280-282
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• 2011

광에너지를 이용하여 바이오원료 및 바이오케미컬을 생산하려는 새로운 시도가 많은 관심을 받고 있다. 특히, 광합성기작을 이용한 다양한 바이오유래 물질을 생산하려는 연구가 진행되고 있다. 본 연구에서는 광합성기작을 갖고 있는 해양 미생물인 Salinibacter ruber의 세포막에서 retinal과 salinixanthin의 작용으로 광전자를 흡수하는 역할을 하는 잔토로돕신을 수성 이상계 계면 농축법을 이용하여 효율적으로 분리하였다. 분리된 잔토로돕신을 생물학적 세포막인 레시틴으로 리포좀을 생성하여 잔토로돕신의 광전자흡수 활성을 그대로 갖는 인위적인 잔토로돕신-레시틴 리포좀을 제작하였다.

• 한국태양에너지학회 논문집
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• 제28권6호
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• pp.48-57
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• 2008

The research analyzed the distribution of the indoor temperatures of a radiant floor cooling system through mock-up experiments. It investigated the temperature difference of feed water, the vertical temperature difference of indoor air, the temperature difference of floor surface, and so on. The following is the results of the research. First, the research shows that the difference between indoor temperature and outside temperature was the smallest when the temperature of feed water was set at 16$^{\circ}C$. In addition, the temperature changes according to indoor positions (wall, room, floor, and ceiling) were the most uniform. Thus, the research found that the cold water temperature of 16$^{\circ}C$ is the most proper. In addition, it confirmed that the feed water temperature of 18$^{\circ}C$ is effective because the temperature can lower the temperature of a room to 13.55$^{\circ}C$, which is lower than the temperature of a non-cooling mode. Second, an investigation on the temperature distribution of vertical air in indoor space shows that the temperature distribution had a difference of 0.2 to 1.9$^{\circ}C$ on the average, which satisfies the range of 3.0$^{\circ}C$ in the standard of ISO.

• 한국태양에너지학회 논문집
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• 제28권2호
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• pp.19-27
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• 2008

This study aims at examining the correlation between air temperature and urban structure such as land cover. For this, it measured summer air temperature by using data log type thermometer installed the inside of instrument screen, in the 9 points of elementary school in Haeundae, Busan. The accomplished results of this study are followings. 1) As altitude goes up 100m, air temperature drops to $0.6{\sim}1.0^{\circ}C$. 2) As building coverage ratio increases 10%, air temperature increases $0.3{\sim}0.4^{\circ}C$. 3) As floor space index increases 100%, air temperature increases $0.4{\sim}0.5^{\circ}C$. 4) As artificial coverage ratio increases 10%, air temperature increases $0.1{\sim}0.2^{\circ}C$. 5) As natural coverage ratio increases 10%, air temperature decreases $0.1{\sim}0.2^{\circ}C$.

• 한국태양에너지학회 논문집
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• 제39권6호
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• pp.67-82
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• 2019

This study aims to examine the impacts of built environmental features on the nocturnal and diurnal temperatures during the heat wave season in Gwangju, Korea. Built environmental measures are summarized at micro-scale level, such as 50 meters and 100 meters from temperature monitoring spots. Regressing the built environment on nocturnal and diurnal temperatures, we estimate how the artificial constructs contribute to temperature either day and night times. We found that impervious surface ratio is positively and negatively associated with nocturnal and diurnal temperatures, respectively. Buildings and structures tend to construct high thermal mass and absorb heat during day time and emit it for the night time. This property contributes to the nocturnal temperature model. On the other hand, urban areas with more vertical structure tend to block sun radiation more than rural, and it is more likely to find the negative relationship between impervious surface ratio and the diurnal temperatures.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2008년도 추계학술대회 논문집
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• pp.199-201
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• 2008

In this paper proposed the solar tracking system to use direct fuzzy control order to increase an output of the PV (Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a DFC(Direct Fuzzy Control)controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.272-272
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• 2013

The attractive features of photosynthetic reaction center proteins for energy application make them useful in solar energy conversion to hydrogen fuel or electrical energy. Almost unity charge separation quantum yield and its rapid speed of ~1ns, absorbance region in visible light (480~740 nm) and high proportion of photosynthetically active solar energy of 48.5% allowed photosystem1 to exploited as a bio-material for photo-energy devices. Directionality of photosystem1 in electron transfer can solve main problem in two-step water splitting process where back reaction deteriorates the overall efficiency. In the study, photosystem1 was extracted from spinach and the photo-induced excited electron in the reaction center was utilized in various field of light energy application. First, hydrogen evolving system realized by photodeposition of platinum at the end of the electron transfer chain, with combining specific semiconductor to oxidize water in the first step of Z-scheme. The evaluation by gas-chromatography demonstrated hydrogen evolution through the system. For the further application of photoelectrical material on electrode, photosystem1 have been controlled by copper ion, which is expected to assemble photosystem in specific orientation followed by maximized photoelectrical ability of film. The research proposed concrete methods for combining natural protein and artificial materials in one system and suggested possibility of designing interface between biological and inorganic materials.

• 천문학회지
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• 제53권6호
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• pp.139-147
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• 2020

The sunspot area is a critical physical quantity for assessing the solar activity level; forecasts of the sunspot area are of great importance for studies of the solar activity and space weather. We developed an innovative hybrid model prediction method by integrating the complementary ensemble empirical mode decomposition (CEEMD) and extreme learning machine (ELM). The time series is first decomposed into intrinsic mode functions (IMFs) with different frequencies by CEEMD; these IMFs can be divided into three groups, a high-frequency group, a low-frequency group, and a trend group. The ELM forecasting models are established to forecast the three groups separately. The final forecast results are obtained by summing up the forecast values of each group. The proposed hybrid model is applied to the smoothed monthly mean sunspot area archived at NASA's Marshall Space Flight Center (MSFC). We find a mean absolute percentage error (MAPE) and a root mean square error (RMSE) of 1.80% and 9.75, respectively, which indicates that: (1) for the CEEMD-ELM model, the predicted sunspot area is in good agreement with the observed one; (2) the proposed model outperforms previous approaches in terms of prediction accuracy and operational efficiency.

• Smart Structures and Systems
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• 제32권2호
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• pp.83-99
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• 2023

The temperature prediction approaches of three important locations in an operational longitudinal slab track-bridge structure by using three typical neural network methods based on the field measuring platform of four meteorological factors and internal temperature. The measurement experiment of four meteorological factors (e.g., ambient temperature, solar radiation, wind speed, and humidity) temperature in the three locations of the longitudinal slab and base plate of three important locations (e.g., mid-span, beam end, and Wide-Narrow Joint) were conducted, and then their characteristics were analyzed, respectively. Furthermore, temperature prediction effects of three locations under five various meteorological conditions are tested by using three neural network methods, respectively, including the Artificial Neural Network (ANN), the Long Short-Term Memory (LSTM), and the Convolutional Neural Network (CNN). More importantly, the predicted effects of solar radiation in four meteorological factors could be identified with three indicators (e.g., Root Means Square Error, Mean Absolute Error, Correlation Coefficient of R2). In addition, the LSTM method shows the best performance, while the CNN method has the best prediction effect by only considering a single meteorological factor.

• 조명전기설비학회논문지
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• 제22권5호
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• pp.86-94
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• 2008

본 논문은 PV(Photovoltaic) 어레이의 출력을 높이기 위해 PC 기반의 퍼지제어를 이용한 태양추적 시스템을 제안한다. 태양 추적시스템은 광센서의 신호에 의해 구동하는 두 개의 DC 모터로 동작한다. 두 축의 제어는 파라미터의 불확실성 및 비선형 특성 때문에 쉽지 않다. 최근 퍼지제어, 신경회로망 및 유전자 알고리즘 등의 인공지능 제어에 대한 연구가 많이 이루어지고 있다. 그 중 퍼지제어는 비선형 제어를 원활하게 수행할 수 있으며 파라미터 변동 및 비선형 특성에 대한 강인성 및 고성능의 특징을 가지고 있다. 따라서 퍼지제어는 설정된 오차 값과 비선형의 고도각 및 방위각 오차 값을 비교하여 추적 시스템 구동을 위해 사용된다. 본 논문에서는 PV 어레이의 출력 향상을 위해 퍼지제어기를 설계하고 종래의 Pl 제어기와 성능을 비교하며 평가한다. 실험을 통한 데이터는 제시한 제어기의 타당성을 입증한다.

• 한국전자통신학회논문지
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• 제19권2호
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• pp.383-388
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• 2024

본 논문은 전라남도에서 측정한 태양광 발전 데이터를 기반으로 발전량 예측값을 도출하기 위한 연구이다. 발전량 측정을 위해 인버터에서 직류, 교류, 환경데이터와 같은 다변량 변수를 측정하였고, 측정값의 안정성과 신뢰성 확보를 위한 전처리 작업을 수행하였다. 상관관계 분석은 부분자기상관함수(PACF: Partial Autocorrelation Function)을 활용하여 시계열 데이터에서 발전량과 상관성이 높은 데이터만을 예측을 위해 사용하였다. 태양광 발전량 예측을 위해 딥러닝 모델을 이용하여 발전량을 측정했고, 예측 정확도를 높이기 위해 각 다변량 변수의 상관관계 분석 결과를 이용하였다. 정제된 데이터를 활용한 학습은 기존 데이터를 그대로 사용했을 때 보다 안정되었고, 상관관계 분석 결과를 반영하여 다변량 변수 중 상관성이 높은 변수만을 활용하여 태양광 발전량 예측 알고리즘을 개선하였다.