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Low-temperature Atomic Layer Deposition of TiO₂, Al₂O₃, and ZnO Thin Films
Taewook Nam,김재민,김민규,Woo-Hee Kim,김형준 한국물리학회 2011 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.59 No.21
We studied low-temperature atomic layer deposition (LT-ALD) of TiO₂, Al₂O₃, and ZnO thin films at temperatures down to room temperature, mainly focusing on the growth characteristics and the film’s properties. Here, two kinds of ALD deposition systems were introduced. Initially,for the thermal ALD (T-ALD) process using a commercial ALD system, a very long purging time of up to 300 s was required to entirely evacuate the remaining H₂O vapors at room temperature due to the large volume and the complicated inner structure of the commercial ALD chamber. For the realization of LT-ALD with a short process time, a plasma-enhanced ALD (PE-ALD) process using O2 plasma was employed, which enabled us to effectively remove the residual reactants at temperatures down to room temperature. As another method, we specifically designed a homemade ALD system with a small volume and a simple inner structure, thereby being able to use T-ALD to synthesize TiO₂, Al₂O₃, and ZnO thin films by using H₂O with very short H₂O purging times even at room temperature, which reveals that the chamber size and design are the critical factors enabling LT-ALD with a short process time. The LT-ALD processes produced highly-pure Al₂O₃,TiO₂, and ZnO films without any C and N impurities by complete elimination of ligands and exhibited excellent conformality in 3-dimensional nanoscale via holes.
Multiple Conjunctural Impact on Digital Social Innovation: A Comparative Study of OECD Countries
( Taewook Huh ) 한국정책학회 2019 한국정책학회 춘계학술발표논문집 Vol.2019 No.-
This study aims to explore the influencing factors of multidisciplinary digital social innovation (DSI) in the OECD member countries in light of the socio-technical system transition theory. It sets up the eight variables of the four areas that comprise the DSI, and identifies the causal conditions (arrangements) based on the empirical findings through the fuzzy-set multi-conjunctural analysis. In short, it concludes that if OECD member countries have high level of democracy and e-participation, high GDP and business-friendly environment, high social expenditure, and high level of ICT development and patent applications, they are much likely to achieve a sufficient level of digital social innovation. On the other hand, the factors of the social domain (especially ‘social capital’) appear to have a relatively insignificant impact (low statistical consistency). This paper suggests that citizen interaction and social change can be newly formed through technology innovation in a multi-dimensional way, and that more in-depth discussion about the new context of 'digital citizen' may be required.
Taewook Kim,Kiseop Choi,Kidoo Kang,Jonghyun Ha 한국방사성폐기물학회 2008 방사성폐기물학회지 Vol.6 No.1
고밀도폴리 에틸렌 고건전성용기에 담은 폐수지의 운반을 위해 원전 폐수지의 방사능 분석결과를 사용하여 운반물 등급 분류방법을 도출하였다. 원전 폐수지의 방사능 분석결과로부터 폐수지 내 핵종 존재비를 구하였고, 폐수지의 표면선량률로 핵종재고량을 평가하기 위해 MCNP 코드로 방사능대선량 환산인자를 모사하였다. 이로부터 고밀도폴리에틸렌 고건전성용기에 담은 폐수지에 대한 A형 운반물과 B형 운반물의 경계값은 1.19 TBq 이고 이를 표면선량으로 환산한 결과는 124.2 mSv/h임을 알 수 있었다. In order to transport spent resin in a high integrated container made of high density polyethylene, a method for determining transportation grade by radioactivity analysis was developed. Ratios of radioisotopes in spent resin were derived from radioactivity analysis on spent resin. Associated curie-to-dose factors were determined to estimate radioisotope inventory from surface dose rates of spent resin. From the results, Activity limit of type A package was derived to be 1.19 TBq for HIC, and the corresponding surface dose rate was found to be 124.2 mSv/h.
Taewook Hwang,Sangkeun Jung,Yoon-Hyung Roh 한국정보과학회 2022 Journal of Computing Science and Engineering Vol.16 No.3
Text visualization is a complex technique that helps in data understanding and insight, and may lead to loss of information. Through the proposed low-dimensional vector representation learning method, deep learning and visualization through low-dimensional vector space construction were simultaneously performed. This method can transform a task-oriented dialogue dataset into low-dimensional coordinates, and based on this, a deep learning vector space can be constructed. The low-dimensional vector representation deep learning model found the intent of a sentence within a dataset and predicted the sentence components well in 3 out of 5 datasets. In addition, by checking the prediction results in the low-dimensional vector space, it was possible to improve the understanding of the data, such as identifying the structure or errors in the data.
Multidimensional Analysis of Consumers' Opinions from Online Product Reviews
Taewook Kim,김동성,Donghyun Kim,김종우 한국경영정보학회 2019 Asia Pacific Journal of Information Systems Vol.29 No.4
Online product reviews are a vital source for companies in that they contain consumers' opinions of products. The earlier methods of opinion mining, which involve drawing semantic information from text, have been mostly applied in one dimension. This is not sufficient in itself to elicit reviewers' comprehensive views on products. In this paper, we propose a novel approach in opinion mining by projecting online consumers' reviews in a multidimensional framework to improve review interpretation of products. First of all, we set up a new framework consisting of six dimensions based on a marketing management theory. To calculate the distances of review sentences and each dimension, we embed words in reviews utilizing Google's pre-trained word2vector model. We classified each sentence of the reviews into the respective dimensions of our new framework. After the classification, we measured the sentiment degrees for each sentence. The results were plotted using a radar graph in which the axes are the dimensions of the framework. We tested the strategy on Amazon product reviews of the iPhone and Galaxy smartphone series with a total of around 21,000 sentences. The results showed that the radar graphs visually reflected several issues associated with the products. The proposed method is not for specific product categories. It can be generally applied for opinion mining on reviews of any product category.