• Journal of Plant Biotechnology
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• v.42 no.3
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• pp.245-256
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• 2015

In the agricultural industries, LEDs are used as supplementary, as well as main lighting sources in closed cultivation systems. In cultivation using artificial light sources, various light qualities have been tried to supplement fluorescent lamps to promote plant growth and metabolism. Microarray analysis of Brassica rapa seedlings under blue and fluorescent mixed with blue light conditions identified changes in three genes of the glucosinolate pathway. This attracted attention as functional materials highly expressed 3.6-4.6 fold under latter condition. We selected four more genes of the glucosinolate pathway from the Brassica database and tested their expression changes under fluorescent light mixed with red, green, and blue, respectively. Some genes increased expression under red and blue mixed conditions. The Bra026058, Bra015379, and Bra021429; the orthologous genes of CYP79F1, ST5a, and FMOGS-OX1 in Arabidopsis, are highly expressed in Brassica rapa under fluorescent mixed with blue light conditions. Further, Bra029355, Bra034180, Bra024634, and Bra022448; the orthologous genes of MAM1, AOP3, UGT74B1, and BCAT4 in Arabidopsis, are highly expressed in Brassica rapa under fluorescent mixed with red light conditions. The various light conditions had unique effects on the varieties of Brassica, resulting in differences in glucosinolate synthesis. However, in some varieties, glucosinolate synthesis increased under mixed blue light conditions. These results will help to construct artificial light facilities, which increase functional crops production.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 1996.10a
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• pp.76-80
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• 1996

공정육묘는 기후의 영향을 쉽게 받는 자연광하에서 대부분의 생산이 이루어지기 때문에 계획적인 묘생산이 어렵게 된다. 향후 식물공장(Plant factory) 또는 폐쇄생태계생명유지시스템(Controlled ecological life support system, CELSS)과 같이 폐쇄도가 높은 식물생산 시스템에서는 식물종묘 생산의 대부분이 인공광을 이용한 조건에서 이루어질 것으로 예상된다. (중략)

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.825-832
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• 2022

In this paper, we discuss the design and implementation of predictive and diagnostic models for realizing intelligent predictive models by collecting and storing the power output of agricultural photovoltaic power generation systems. Our model predicts the amount of photovoltaic power generation using RNN, LSTM, and GRU models, which are recurrent neural network techniques specialized for time series data, and compares and analyzes each model with different hyperparameters, and evaluates the performance. As a result, the MSE and RMSE indicators of all three models were very close to 0, and the R2 indicator showed performance close to 1. Through this, it can be seen that the proposed prediction model is a suitable model for predicting the amount of photovoltaic power generation, and using this prediction, it was shown that it can be utilized as an intelligent and efficient O&M function in an agricultural photovoltaic system.

• Journal of Sensor Science and Technology
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• v.2 no.1
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• pp.75-80
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• 1993

This study describes a non-invasive optical sensor and system in order to obtain oxygen saturation of blood, in-vitro. The sensor contains LED 665nm and 805nm of wavelength for light source and PIN photodiode for light detector in flat pack. The sensor system for measurement of oxygen saturation has breadboarded, including signal amplifier, filter, displayer, A/D converter, microprocessor and memory. Experimental set-up for non-invasive measurement of oxygen saturation in-vitro was done. When the variation of oxygen saturation is compared with that of each wavelength, the variation of 665nm is more than that of 805nm by five times. As oxygen saturation varies from 100% to 60%, and the reflection ratio (R805/R665) is changed linearly. The oxygen saturation in $100%{\sim}60%$ range can be measured with about 5% resolution by the developed sensor, such that if this sensor connects with the main artery and vein, the artificial heart can be controlled rapidly and precisely from measurement of the sensor.

• Journal of Korean Electronics
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• v.3 no.8
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• pp.5-11
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• 1983

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.67-72
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• 2005

자연채광 성능평가의 연구 방법으로는 현장측정, 축소모형실험, 수학적 알고리즘에 기초한 컴퓨터 시뮬레이션 등이 있다. 현장측정과 축소모형실험은 비교적 높은 신뢰도를 얻을 수 있는 방법이지만, 변화가 많은 자연광의 특성으로 인해 객관성 있는 측정결과를 얻는 것에 제한적이었다. 인공천공돔(Sky Simulator, Artificial Sky Dome)은 축소모형 실험 시 이러한 문제점의 보완을 위한 평가 시설이며 천공의 상태를 일관성 있게 조정함으로써 보다 객관성 있는 자연채광연구를 실시할 수 있다. 이에 따라 K대학에서는 직경 6[m], 높이 3.7[m]의 인공천공돔을 자체 개발 제작하여 연구에 사용하고 있다. 본 연구에서는 인공천공돔 기존사례에 대한 고찰과 이를 바탕으로 제작된 K대학 인공천공돔의 개요를 소개하고 기본적인 물리량 측정을 통해 인공천공돔의 신뢰성을 검증하고 유용성을 제시하였다.

• Journal of the korean academy of Pediatric Dentistry
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• v.32 no.4
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• pp.611-619
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• 2005

The aim of this study was to apply the quantitative light-induced fluorescence(QLF) and use of fluorescein-enhanced QLF method for quantitative assessment of early enamel demineralization in vitro, comparing effectiveness of light sources : argon laser, halogen lamp, light emitting diode (LED) and plasma arc lamp. Sixty extracted teeth were used, prepared by gentle pumicing and coating in an acid-resistant nail-varnish, except for an exposure to a demineralizing solution. Teeth were removed at regular intervals (24, 48 and 72hrs), air-dried and QLF image were taken. Mineral loss, as measured by difference of optical density, was recorded. For dyeenhanced QLF a 0.075% sodium fluorescein dye was applied after QLF examination and mineral loss was recorded. The following result were obtained : 1. Comparing with mean difference of optical density, plasma arc lamp was higher than other light sources in all group (p<0.05). 2. Comparing each group with mean difference of optical density, there was significant different using plasma are lamp and halogen lamp. 3. For use of dye-enhanced QLF, comparing with mean difference of optical density, plasma arc lamp were higher than other light sources in all group(p<0.05). 4. With this model dye-enhanced QLF compared with QLF in optical density, dye-enhanced QLF was higher than QLF in optical density. From the results presented in this paper, it was concluded that plasma light source was more effective compared with other light source for the detection and the quantification of early enamel caries.

• Journal of Bio-Environment Control
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• v.20 no.4
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• pp.346-351
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• 2011

This research was done to identify the mass propagation method in winter daphne (Daphne odora Thunb) using its softwood cuttings and to investigate its plant characters established at different light and soil conditions as an indoor plant. Cuttings from winter daphne were taken and grown in different treatment consisted of rooting media (perlite, vermiculite, perlite + vermiculite (1 : 1) and commercial horticulture media soil), indole butyric acid (IBA) hormone concentrations (0, 100, 500, 1000 ppm and Rootone) and date of cutting. Transplants were grown at different light intensities (100, 1000, 2500 lux and control) and growing media. Results showed that cuttings grown in perlite + vermiculite (1 : 1) gave higher percentage (100%) rooting. Cuttings treated with Rootone and IBA 100 ppm showed good rooting growth and cutting taken in June, 25 gave the highest rooting (96.7%). The best plant growth obtained at 1000 lux (56~60 ${\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$) followed by 2500 lux (125~130 ${\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$) and scoria mixed with commercial horticulture media soil showed better growth of transplants.

• Horticultural Science & Technology
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• v.30 no.6
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• pp.673-679
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• 2012

This study was conducted to examine the effect of artificial light source and photoperiod on the growth of leaf lettuce (Lactuca sativa L.) 'Seonhong Jeokchukmyeon' in a closed-type plant production system. Seedlings were grown under 3 light sources, fluorescent lamp (FL, Philips Co. Ltd., the Netherlands), WL #1 (Hepas Co. Ltd., Korea), and WL #2 (FC Poibe Co., Ltd., Korea), each with 3 photoperiods, 12/12, 18/6, and 24/0 (Light/Dark). An irradiance spectrum analysis showed that FL has various peaks in the 400-700 nm range, while WL #1 and WL #2 have only one monochromatic peak at 450 and 550 nm, respectively. The greatest plant height, fresh and dry weights were obtained in the 24/0 (Light/Dark) photoperiod. The 24/0 (Light/Dark) photoperiod treatment promoted vegetative growth of the leaf area. Length of the longest root, number of leaves, fresh weight, and total anthocyanin contents were greater in FL than in either WL #1 or #2. The greatest chlorophyll fluorescence (Fv/Fm) was found in the 12/12 (Light/Dark) photoperiod with FL treatment. The energy use efficiency of the LED increased by about 35-46% as compared to FL. Results suggest a possibility of LED being used as a substitute light source for fluorescent lamp for lettuce cultivation in a plant factory system.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).