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Structural, optical and photoelectrochemical studies on the nanodispersed titania
Lee, Gi-Won,Bang, So-Yeon,Lee, Chaehyeon,Kim, Won-Mok,Kim, Donghwan,Kim, Kyungkon,Park, Nam-Gyu Elsevier 2009 Current Applied Physics Vol.9 No.5
<P><B>Abstract</B></P><P>Nanodispersion of aggregated TiO<SUB>2</SUB> powders has been performed by microbead milling and its effect on photovoltaic performance has been investigated with dye-sensitized solar cell. Plasma-treated 30 μm-diameter zirconia beads are used to disperse the aggregated nanocrystalline TiO<SUB>2</SUB> powders in ethanolic medium. Particle size distribution, surface area, film morphology, porosity, transmittance and haze are investigated with different milling speed. Microbead milling leads to a reduction of particle size, narrow size distribution and increase of surface area. A slight crystal phase transformation from anatase to rutile is also observed after microbead milling. Optical property is found to be influenced by microbead milling speed, where transmittance increases and haze decreases with increasing milling speed. Compared with photovoltaic performance of dye-sensitized solar cells based on titania before and after microbead milling, overall conversion efficiency is substantially improved from 4.46% to 6.31% after microbead milling at 2490rpm for 90min, corresponding to 42% increment, which is mainly due to a noticeable increase in photocurrent density, associated with highly dispersed characteristics. According to the photocurrent and photovoltage transient spectroscopic study, time constant for electron transport is hardly affected, while that for recombination is slightly decreased due to the increased surface area by nanodispersion.</P>
Chaehyeon Lee,Gi-Won Lee,강위경,이도권,고민재,김경곤,박남규 대한화학회 2010 Bulletin of the Korean Chemical Society Vol.31 No.11
The core-shell SnO2@AO (A = Ni, Cu, Zn and Mg) films were prepared and the effects of coatings on photovoltaic properties were investigated. Studies on X-ray photoelectron spectroscopy, energy dispersive X-ray analysis and transmission electron microscopy showed the formation of divalent oxides on the surface of SnO2 nanoparticles. It was commonly observed that all the dye-sensitized core-shell films exhibited higher photovoltage than the bare SnO2 film. Transient photovoltage measurements confirmed that the improved photovoltages were related to the decreased time constants for electron recombination.
Lee, Chaehyeon,Shin, Eui-Cheol,Ahn, Soo-Young,Kim, Seonghui,Kwak, Dongyun,Kwon, Sangoh,Choi, Yunjin,Choi, Gibeom,Jeong, Hyangyeon,Kim, Jin-Soo,Lee, Jung Suck,Cho, Suengmok The Korean Society of Fisheries and Aquatic Scienc 2022 Fisheries and Aquatic Sciences Vol.25 No.3
Sea mustard (Undaria pinnatifida), an important edible seaweed belonging to the brown algal family of Alariaceae, contains copious physiologically active substances. It has long been popular in Korea as a food and is frequently consumed in the form of soup. It is also commercially available as a home meal replacement. In this study, we developed a seasoning key base with a high degree of sensory preference from sea mustard using the extrusion cooking process. Extrusion cooking conditions were optimized through response surface methodology. Barrel temperature (X<sub>1</sub>, 140℃-160℃) and screw speed (X<sub>2</sub>, 158-315 rpm) were set as independent variables, and overall preference was determined as the dependent variable (Y, points). An optimal condition was obtained at X<sub>1</sub> = 148.5℃ and X<sub>2</sub> = 315 rpm, and the dependent variable (Y, overall acceptance) was 7.95 points, similar to the experimental value of 7.81. Umami taste had a relationship with the overall acceptance of sea mustard seasoning. In the electronic nose and tongue, increased sourness and umami intensities were associated with the highest sensory score. The samples were separated well by each characteristic via principal component analysis. Collectively, our study provides imperative preliminary data for the development of various seasonings using sea mustard.
딥러닝 기반 벵골어 수기 문자 인식 : Kaggle Bengali.AI 대회를 중심으로
이채현(Chaehyeon Lee),최재협(Jaehyeop Choi),정희철(Heechul Jung) 대한전자공학회 2020 전자공학회논문지 Vol.57 No.9
최근 Kaggle에서는 벵골어 인식을 위한 새로운 데이터 셋이 공개되었고 Bengali.AI라는 국제적인 대회가 열렸다. 본 연구에서는 Bengali.AI 대회에 참가하여 달성한 결과에 대해 공유하고자 한다. 벵골어 문자는 다른 언어에 비해 구조가 복잡하기 때문에 다른 언어의 인식보다 벵골어 문자에 대한 인식이 더 어렵다. 벵골 수기 데이터 셋에 대한 인식 알고리즘을 개발하기 위해서는 주어진 수기 벵골 영상에서 그래핌 루트(Grapheme root), 모음 디아크리틱스(Vowel diacritic), 자음 디아크리틱스(Consonant diacritic) 세 가지 성분을 개별적으로 분류해야 했다. 본 연구에서는 이러한 벵골 수기 데이터 세트에 대해 세 개의 출력을 갖는 branch를 갖는 모델을 기반으로 GhostNet, EfficientNet, SENet 등 세 가지 backbone 아키텍처를 이용하여 인식을 수행하였다. 나아가 Mixup, Cutout, Cutmix, GridMask 등 4가지 데이터 증강 방법에 대해 비교 분석하여 인식률 향상을 꾀하였다. 결론적으로 우리는 GridMask 데이터 증강 기법을 사용한 EfficientNet-B5 1개, SE-ResNeXt-50 2개를 이용한 앙상블 네트워크를 기반으로 93.74%의 최고 정확도를 달성하였으며, 이 결과는 Kaggle 벵갈리 대회에 참가하는 2,059개 팀 중 상위 3.1%에 해당한다. Recently, a new dataset for a Bengali recognition was released at Kaggle and an international challenge called Bengali.AI was held. In this paper, we share the results of our participation in the competition. Since Bengali character has a more complex structure than other languages, recognition of Bengali character is more challenging than the recognition of other languages. To develop the recognition algorithm on Bengali handwritten dataset, we had to classify three components individually: Grapheme root, Vowel diacritics, and Consonant diacritics from a given handwritten Bengali image. We propose a method to improve the performance of recognition for Bengali handwritten dataset in this paper. In order to compare the quality of different models and find the optimal strategy to get better accuracies, we have trained several models based on three modern architectures (GhostNet, EfficientNet, SENet). Furthermore, we have analyzed four kinds of data augmentation methods such as Mixup, Cutout, Cutmix, and GridMask. Finally, we have achieved the best accuracy of 93.74% based on an ensemble network using one EfficientNet-B5 and two SE-ResNeXt-50 with GridMask data augmentation, and this result is the top 3.1% of the 2,059 teams participating in the Kaggle Bengali.AI challenge.
High-quality SNP calling from olive flounder, Paralichthys olivaceus, in Jeju Island, South Korea
Sukkyoung Lee,Taehyug Jeong,W.K.M. Omeka,D.S. Liyanage,Chaehyeon Lim,Kishanthini Nadarajapillai,H.M.V. Udayantha,W.M. Gayashani Sandamalika,Seong-Rip Oh,David B. Jones,Dean R. Jerry,Jehee Lee 한국수산과학회 양식분과 2021 한국수산과학회 양식분과 학술대회 Vol.2021 No.4