• New & Renewable Energy
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• v.7 no.1
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• pp.36-44
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• 2011

Technology is developed from the efficient interaction with other technology files while building up its own research field. This study analyzes the structure of solar cell research area and describes its paths of the technology development in terms of interdisciplinary diversity using the Co-Classification method during 1979-2009. As a results, 1,380 studies are determined as the interdisciplinary among the 2,605 studies. It shows that 52.98% of the solar cell researches have interdisciplinary relationships with two or more research fields. In addition, we show that the research area of solar cell technology is composed by Material Science, Multidisciplinary and Energy & Fuel, Physics, Applied, Chemistry, Physical from the Co-Classification matrix and network analysis. It means the complexity of the technological knowledge production increased with the concept of interdisciplinary. The results can be used for the planning of the efficient solar cell technology development.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.267-268
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• 1998

In this paper, we analysis 3 types of magnetic resonance image for determining whether brain infarction period is hyperacute or not. If its peirod is hyperacute, we can predict brain infarction transition direction. We use EPI(Echo Planar Image) for prediction of brain infarction transition direction. EPI is a good image for detecting brain infarction because EPI can detect the moving of water in brain which play an important role in deciding method of medical treatment. We utilize characteristics of 3 type of MRI and their relation in brain infarction patient for determining brain infarction period. By this method, we obtain each period characteristics and predict brain infarction transition direction more accurately comparing past method.

• Journal of Microbiology and Biotechnology
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• v.21 no.9
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• pp.995-1000
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• 2011

The bioremediation potential of crude oil by Polyporus sp. S133 pre-grown in wood meal was investigated in two separate experiment trials; liquid medium and soil. The effect of three nutrients (glucose, polypeptone, and wood meal), oxygen flow, and some absorbent on the efficiency of the process was also evaluated. Degradation of crude oil in soil was significantly increased with an addition of oxygen flow and some absorbent (kapok and pulp). The highest degradation rate of crude oil was 93% in the soil with an addition of 10% kapok. The present study clearly demonstrates that, if suitably developed, Polyporus sp. S133 could be used to remediate soil contaminated with crude oil.

• Journal of Electrochemical Science and Technology
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• v.2 no.3
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• pp.163-167
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• 2011

Nicotinamide adenine dinucleotide, $NAD^+$, and its reduced form, NADH, play important roles as coenzymes in many enzymatic reactions. Electrochemical methods for $NAD^+$ or NADH detection or generation are drawn attention because it can provide the simple and low cost platform with fairly good sensitivity. In this study, the polysiloxane viologen polymer/diaphorase/hydrophilic polyurethane (PSV/DI/HPU) modified electrodes were simply prepared and demonstrated for bio-electrocatalytic $NAD^+$ sensors. The electrodes were co-immobilized with diaphorase and polysiloxane viologen polymer as an electron mediator followed by the overcoating with HPU membrane. The mixture of the enzyme and the electron mediator was well stabilized within HPU membrane and exhibited good reversibility and stability. The sensitivity was 0.2 $nA{\cdot}{\mu}M^{-1}$ and the detection limit was 28 ${\mu}M$ with a response time of 50 s ($t_{90%}$). The capability for NADH sensor was also observed on the PSV/DI/HPU electrode.

• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1224-1241
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• 2021

Recent development of deep learning techniques for image generation has led to straightforward generation of sophisticated deepfakes. However, as a result, privacy violations through deepfakes has also became increased. To solve this issue, a number of techniques for deepfake detection have been proposed, which are mainly focused on RGB channel-based analysis. Although existing studies have suggested the effectiveness of other color model-based analysis (i.e., Grayscale), their effectiveness has not been quantitatively validated yet. Thus, in this paper, we compare the effectiveness of Grayscale channel-based analysis with RGB channel-based analysis in deepfake detection. Based on the selected CNN-based models and deepfake datasets, we measured the performance of each color model-based analysis in terms of accuracy and time. The evaluation results confirmed that Grayscale channel-based analysis performs better than RGB-channel analysis in several cases.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.1
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• pp.39-46
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• 2022

This study compared the effects of cocopeat and perlite growth media on the storability and quality of sweet pepper fruit stored using modified atmosphere packages (MAP) and carton boxes. The fruits were stored at 8℃ for 35 and 30 days, respectively. Perlite-grown fruits had a significantly lower size at harvest due to the medium's inability to hold plenty of water during the growing stage. Contrary to what is expected for small fruits, the result shows box-stored perlite-grown fruits to have lower weight loss and a longer shelf life than cocopeat-grown fruits, while MAP fruits have indifference. Perlite fruits also had a higher quality in terms of dry matter, soluble solids, and vitamin C, while box-stored fruits had a better visual quality. As expected, respiration and ethylene production rates were high, and fruits had similar after-storage firmness values. Based on the findings, perlite-grown sweet pepper fruits may have a better quality and give preference in a box storage condition.

• Mycobiology
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• v.51 no.3
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• pp.178-185
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• 2023

The cell wall integrity (CWI) signaling pathway plays important roles in the dissemination and infection of several plant pathogenic fungi. However, its roles in the pepper fruit anthracnose fungus Colletotrichum scovillei remain uninvestigated. In this study, the major components of the CWI signaling pathway-CsMCK1 (MAPKKK), CsMKK1 (MAPKK), and CsMPS1 (MAPK)-were functionally characterized in C. scovillei via homology-dependent gene replacement. The ΔCsmck1, DCsmkk1, and ΔCsmps1 mutants showed impairments in fungal growth, conidiation, and tolerance to CWI and salt stresses. Moreover, ΔCsmck1, ΔCsmkk1, and ΔCsmps1 failed to develop anthracnose disease on pepper fruits due to defects in appressorium formation and invasive hyphae growth. These results suggest that CsMCK1, CsMKK1, and CsMPS1 play important roles in mycelial growth, conidiation, appressorium formation, plant infection, and stress adaption of C. scovillei. These findings will contribute to a better understanding of the roles of the CWI signaling pathway in the development of pepper fruit anthracnose disease.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.76-81
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• 2020

법률 전문 지식이 없는 사람들이 법률 정보 검색을 성공적으로 하기 위해서는 일반 용어를 검색하더라도 전문 용어가 사용된 법령정보가 검색되어야 한다. 하지만 현 판례 검색 시스템은 사용자 선호도 검색이 불가능하며, 일반 용어를 사용하여 검색하면 사용자가 원하는 전문 자료를 도출하는 데 어려움이 있다. 이에 본 논문에서는 일반용어가 사용된 질의문과 전문용어가 사용된 판례를 자동으로 연결해 주고자 하였다. 질의문과 연관된 판례를 자동으로 연결해 주기 위해 전문용어가 사용된 전문가 답변을 바탕으로 문서분류에 높은 성능을 보이는 Doc2Vec을 이용한다. Doc2Vec 문서 임베딩 기법을 이용하여 전문용어가 사용된 전문가 답변과 유사한 답변을 제안하여 비슷한 주제의 답변들끼리 분류하였다. 또한 전문가 답변과 유사도가 높은 판례를 제안하여 질의문에 해당하는 판례를 자동으로 연결하였다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.357-362
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• 2020

자연어 처리 응용 시스템이 패러프레이즈 표현을 얼마나 정확하게 포착하는가에 따라 응용 시스템의 성능 측면에서 차이가 난다. 따라서 자연어 처리의 응용 분야 전반에서 패러프레이즈 표현에 대한 중요성이 커지고 있다. 시스템의 성능 향상을 위해서는 모델을 학습시킬 충분한 말뭉치가 필요하다. 특히 이러한 패러프레이즈 말뭉치를 구축하기 위해서는 정확한 패러프레이즈 추출이 필수적이다. 따라서 본 연구에서는 패러프레이즈를 추출을 위한 언어 자원으로 키프레이즈 데이터셋을 제안하고 이를 기반으로 유사한 의미를 전달하는 패러프레이즈 관계의 문장을 추출하였다. 구축한 키프레이즈 데이터셋을 패러프레이즈 추출에 활용한다면 본 연구에서 수행한 것과 같은 간단한 방법으로 패러프레이즈 관계에 있는 문장을 찾을 수 있다는 것을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.749-752
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• 2021

오늘날 인공지능(Artificial Intelligence, AI) 분야에서 가장 구현하기 어려운 분야 중 하나는 추론이다. 근래 추론 분야에서 영상과 언어가 결합한 다중 모드(Multi-modal) 환경에서 영상 기반의 질의 응답(Visual Question Answering, VQA) 과업에 대한 AI 모델이 발표됐다. 얼마 지나지 않아 VQA 모델의 성능을 개선한 GVQA(Grounded Visual Question Answering) 모델도 발표됐다. 하지만 아직 GVQA 모델도 완벽한 성능을 내진 못한다. 본 논문에서는 GVQA 모델의 성능 개선을 위해 VCC(Visual Concept Classifier) 모델을 ViT-G(Vision Transformer-Giant)/14로 변경하고, ACP(Answer Cluster Predictor) 모델을 GPT(Generative Pretrained Transformer)-3으로 변경한다. 이와 같은 방법들은 성능을 개선하는 데 큰 도움이 될 수 있다고 사료된다.