• Proceedings of the Membrane Society of Korea Conference
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• 2008.05a
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• pp.176-179
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• 2008

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.32-32
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• 2017

2012년부터 도입된 "신재생에너지 의무할당제(RPS)"로 인하여 500MW이상의 설비 용량을 갖춘 발전소의 경우 총발전량에서 일정 비율을 신재생에너지로 공급하여야 한다. 이러한 신재생에너지 중 농업부산물은 목질계 바이오매스의 한 종류로 '탄소중립(Carbon Neutral)' 연료이며 기존 화석연료와 혼소로 활용 할 수 있는 장점을 지니고 있다. 그러나 낮은 발열량, 운송 및 저장비용, 일정하지 않은 연소특성의 문제로 인하여 대부분 노지에 방치되거나 버려지고 있다. 이러한 버려지는 농업부산물을 효율적으로 활용하기 위한 방법 중 하나로 반탄화(Torrefacation) 처리가 대두되고 있다. 반탄화 처리 시, 발열량이 증대되며, 저장과 이송에서의 이점을 갖게 된다. 그러나, 반탄화는 공정 과정중 질량손실에 따른 에너지 총량의 감소한다는 단점을 가지고 있다. 이에 본 연구에서는 효율적인 반탄화공정을 위한 질량감소모델을 제시 하고자한다. 승온 속도(heating rate)를 $7.5^{\circ}C/min$, $15^{\circ}C/min$, $22.5^{\circ}C/min$의 조건에서의 열중량분석 결과를 토대로 속도모델식(Arrhenius method, Ingraham & Marrier method 등)을 적용하여, 반응속도상수를 도출하였다. 이 반응속도상수를 이용하여 질량감소 모델을 정립하였고, 이를 실험결과와 비교, 검증하였다.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.79-79
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• 2017

국내 여름철의 고온다습한 기후환경으로 인하여 온실 내부의 냉방 및 제습이 필수적인데, 온실 냉방 방식 중 증발냉각 시스템이 가장 효율이 높다고 알려져 있다. 하지만 증발냉각 시스템은 건조한 기후 지역에서 발달한 방식으로, 작물의 증산작용으로 인한 온실 내부 습도 상승에 따른 문제점이 발생되어 다습한 여름철 국내 기후에는 반드시 냉각과 제습이 동시에 필요하다. 따라서 증발냉각 방식 중 Fan and Pad 방식과 리튬브로마이드 수용액을 이용한 온실 냉방 및 제습을 위한 복합시스템에 관한 연구가 진행중이다. 현재 리튬브로마이드 수용액 제습 시 발생되는 발열량과 수용액의 무게변화와 같은 수용액의 흡습성질 대한 정확한 지표가 나타나 있지 않다. 이에 연구를 진행하기에 앞서 리튬브로마이드 흡습성질에 관한 데이터 자료가 필요하다고 판단되어 기초실험을 진행하였고, 본 연구에서는 Pilot Scale의 재생 순환시스템을 통해 리튬브로마이드 수용액의 흡습성질을 이용한 재사용 방안을 제시하였고, 시스템 내에서 외부투입공기와 작동유체의 흡습성질에 의한 반응 전후 온도변화 예측 모델을 수립하였다. 따라서 본 연구를 통해 리튬브로마이드 수용액의 흡습성질을 분석하고, 이를 이 용한 재생 순환 시스템에 관한 연구를 진행할 예정이다.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.183-194
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• 2019

Adulteration of argan oil with some other cheaper oils with similar chemical compositions has resulted in increasing demands for authenticity assurance and quality control. Fast and simple analytical techniques are thus needed for authenticity analysis of high-priced argan oil. Raman spectroscopy is a potent technique and has been extensively used for quality control and safety determination for food products In this study, Raman spectroscopy in combination with a net analyte signal (NAS)-based methodology, i.e., hybrid linear analysis method developed by Goicoechea and Olivieri in 1999 (HLA/GO), was used to predict the different concentrations of olive oil (0 - 20%) added to argan oil. Raman spectra of 90 samples were collected in a spectral range of $400-400cm^{-1}$, and calibration and validation sets were designed to evaluate the performance of the multivariate method. The results revealed a high coefficient of determination ($R^2$) value of 0.98 and a low root-mean-square error (RMSE) value of 0.41% for the calibration set, and an $R^2$ of 0.97 and RMSE of 0.36% for the validation set. Additionally, the figures of merit such as sensitivity, selectivity, limit of detection, and limit of quantification were used for further validation. The high $R^2$ and low RMSE values validate the detection ability and accuracy of the developed method and demonstrate its potential for quantitative determination of oil adulteration.

• International Journal of Industrial Entomology and Biomaterials
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• v.26 no.1
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• pp.47-53
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• 2013

Silk sericin (SS) has been fabricated into beads using a 1 M LiCl/DMSO solvent and utilized as a heavy metal adsorbent. Among the various heavy metals, we targeted Cr(VI) for adsorption using SS beads and found that its adsorption depended on the coagulant used for the fabrication of the SS beads. When methanol was used as a coagulant, the beads had a better adsorption capacity than when ethanol was used except at pH 1. The adsorption behavior of Cr(VI) on the SS beads followed the BET isotherm. The maximum adsorption capacity was 33.76 mg/g at pH 2. The adsorption of Cr(VI) was confirmed by FT-IR and EDS analyses. Finally, the desorption was carried out using NaOH solution, and it was found that 73.19% of the adsorbed Cr(VI) could be detached.

• Journal of Applied Biological Chemistry
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• v.59 no.2
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• pp.145-147
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• 2016

Recently, conjugates of medicinal herb-derived bioflavonoids, such as quercetin, and gold nanoparticles (GNPs) have gained attention as targeted drug delivery systems. In the present study, because quercetin is an important flavonoid with anti-cancer, anti-inflammatory, and anti-oxidant properties, GNP-quercetin complexes (GNPQs) were synthesized to investigate possible adverse effects such as cytotoxicity. We found that while quercetin was cytotoxic, GNPQs were not cytotoxic towards the RAW 264.7 and THP-1 cell lines. Therefore, GNPQs may serve as a potential drug delivery system for cancer treatment.

• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.318-323
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• 2014

Purpose: This study was carried out to predict the growth period and fresh weight of sprouts grown in a cultivator designed to grow sprouts under optimal conditions. Methods: The temperature, light intensity, and amount of irrigation were controlled, and images of seed sprouts were acquired to predict the days of growth and weight from pixel counts of leaf area. Broccoli, clover, and radish sprouts were selected, and each sprout was cultivated in a 90-mm-diameter Petri dish under the same cultivating conditions. An image of each sprout was taken every 24 hours from the 4th day, and the whole cultivating period was 6 days, including 3 days in the dark. Images were processed by histogram inspection, binary images, image erosion, image dilation, and the overlay image process. The RGB range and ratio of leaves were adjusted to calculate the pixel counts for leaf area. Results: The correlation coefficients between the pixel count of leaf area and the growth period of sprouts were 0.91, 0.98, and 0.97 for broccoli, clover, and radish, respectively. Further, the correlation coefficients between the pixel count of leaf area and fresh weight were 0.90 for broccoli, 0.87 for clover, and 0.95 for radish. Conclusions: On the basis of these results, we suggest that the simple image acquisition system and processing algorithm can feasibly estimate the growth period and fresh weight of seed sprouts.

• Korean Journal of Agricultural Science
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• v.46 no.3
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• pp.689-703
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• 2019

The term quality or freshness of eggs in industrial production still poses concerns regarding whether washing is necessary. Therefore, the aims of this study were to examine the effects of different storage times and temperatures and to perform a comparison between washed and unwashed eggs. A total of 1000 washed and 1000 unwashed egg samples were stored at three different temperatures (5, 10, and $25^{\circ}C$) for 0 - 8 weeks and were used for the data collection. On the designated day, the eggs were processed to evaluate their internal and external quality traits, such as the Haugh unit, airspace volume, eggshell strength, pH, and microbiological profile. Significant differences (p < 0.05) were observed between the washed and unwashed eggs for each quality trait. The results indicate that storage between 5 and $10^{\circ}C$ better preserved the quality of eggs compared with the storage at $25^{\circ}C$ throughout the days of the storage. Overall, this study suggests that the storage time and temperature have a vital role in maintaining the quality of eggs which were significantly affected during storage. In addition, all the quality parameters differed between the washed and unwashed samples which is further responsible for deteriorating the quality of the eggs.

• Proceedings of the Korean Society of Sericultural Science Conference
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• 2005.11a
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• pp.43-43
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• 2005

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.18-28
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• 2002

Neural network based models were developed and evaluated for predicting corn yield from aerial images based on 1998 and 1994 image data. The model used images in multi-spectral bands such as R, G, B, and IR (Red, Green, Blue and Infrared). The inputs to the neural network consisted of mean and standard deviation of multispectral bands of the aerial images. Performances of several neural network architectures using back-propagation with momentum were compared. The maximum yield prediction accuracy obtained was 97.81%. The BPNN model prediction accuracy could be enhanced by using more number of observations to the model, other data transformation techniques, or by performing optical calibration of the aerial image.