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OLED 레이저 실링용 글라스 프릿에서 V<sub>2</sub>O<sub>5</sub> 함량 및 가소성 분위기가 접합 특성에 미치는 영향
정현진,이미재,이영진,김진호,전대우,황종희,이정수,양윤성,육수경,박태호,문윤곤,Jeong, HyeonJin,Lee, Mijai,Lee, Youngjin,Kim, Jin-Ho,Jeon, Dae-Woo,Hwang, Jonghee,Lee, Jungsoo,Yang, Yunsung,Youk, Sookyung,Park, Tae-Ho,Moon, Yun-Gon 한국전기전자재료학회 2016 전기전자재료학회논문지 Vol.29 No.8
In this study, the effect of vanadium oxide ($V_2O_5$) content and pre-sintering atmosphere on sealing property of glass frit that consisted of $V_2O_5-BaO-ZnO-P_2O_5-TeO_2-CuO-Fe_2O_3-SeO_2$ was investigated by XPS (X-ray photoelectron spectroscopy). The content of V2O5 was changed to 15, 30, and 45 mol%, and the pre-sintering was carried out in air and $N_2$ condition, respectively. XPS analysis conducted before and after laser irradiation with identical sample. Before laser treatment, glass frits that were pre-sintered at air condition showed both $V^{4+}$ and $V^{5+}$, but the valence state was changed to $V^{5+}$ after laser irradiation when the glass frits contained 30 and 45 mol% $V_2O_5$; this change led to non-adhesive property. On the other hand, glass frits that were pre-sintered at $N_2$ condition exhibited only $V^{4+}$ and it showed fine adhesion irrespective of the $V_2O_5$ content. As a result, the existence of $V^{4+}$ seems to be a major factor for controlling the adhesive property of glass frit for laser sealing.
BaO-ZnO-B<sub>2</sub>O<sub>3</sub>-SiO<sub>2</sub>계 유리에서 TiO<sub>2</sub>의 첨가가 색변환 유리의 광특성에 미치는 영향
정현진,임태영,김진호,이미재,황종희,황평하,박태호,신동욱,Jeong, HyeonJin,Lim, Tae-Young,Kim, Jin-Ho,Lee, MiJai,Hwang, Jonghee,Hwang, Pyeong Ha,Park, Tae-Ho,Shin, Dongwook 한국재료학회 2014 한국재료학회지 Vol.24 No.12
The effect of titanium dioxide ($TiO_2$) on the properties of color conversion glasses was examined for glasses based on $BaO-ZnO-B_2O_3-SiO_2$. One glass sample, containing 25 mol% of each component, was used as a reference; the other three glass samples contained 1, 3, and 5 mol% $TiO_2$, respectively. The four color conversion glass samples were prepared by sintering a mixture of glass frits and a $YAG:Ce^+$ phosphor. The characteristics of the color conversion glass samples, such as luminous efficacy, luminance, CIE (Commission International de I'Eclairage) chromaticity, CCT (Correlated Color Temperature), and CRI (Color Rendering Index) were analyzed according to the PL spectrum. The refractive index of the glass samples was found to increase with the titanium dioxide content. In conclusion, luminous efficacy of color conversion glasses increased as the content of $TiO_2$ was raised in the glass matrix.
류준호(Junho Ryu),김보민(Bomin Kim),정현진(Hyeonjin Jeong),이인석(Inseok Lee),김민영(Minyoung Kim) 한국정보기술학회 2022 Proceedings of KIIT Conference Vol.2022 No.12
본 논문에서는 사용자에게 생수를 제조하는 업체에서 이루어진 수질검사 경고 이력들을 보여줌으로써 수질정보를 제공한다. 또한, 환경청의 수질검사에서 경고받지 않은 공장의 생산된 제품 중 저렴한 제품들을 선별하고, 그에 대한 정보를 사용자에게 제공함으로써 사용자가 안전하고 합리적인 소비를 할 수 있도록 도모한다. 더 나아가 생수를 제조하는 공장들이 위생에 대한 경각심을 가질 수 있도록 일깨우고 위생 및 가격 경쟁심을 촉구하여 경제 발전에 이바지하고자 한다. In this paper, water quality information is provided to the user by showing the water quality inspection warning histories made by companies that manufacture bottled water. In addition, cheap products are selected among the products produced by factories that have not been warned by the Environment Agencys water quality inspection, and information is provided to users so that users can safely and rationally consume. Furthermore, it is intended to contribute to economic development by awakening factories that manufacture bottled water to be aware of hygiene and urging the spirit of hygiene and price competition.
장기요양기관 내 CCTV 의무 설치에 대한 이해관계자의 인식 비교
김정희(Junghee Kim),권진희(Jin-Hee Kwon),이정석(Jung-Suk Lee),정현진(Hyeonjin Jeong) 한국노인간호학회 2023 노인간호학회지 Vol.25 No.1
Purpose: This study aimed to investigate the status of closed-circuit television (CCTV) installation and operation in long-term care facilities and to compare the differences in stakeholders' perceptions of CCTV mandatory installation. Methods: The participants included 743 heads of facilities, 802 care workers, and 864 family caregivers. The questionnaire included CCTV installation and operation status and perceptions on CCTV installation in long-term care facilities. For the data analysis, descriptive statistics and chi-squared tests were performed through SAS Enterprise Guide 7.1. Results: For the mandatory installation of CCTV in long-term care facilities, 96.5% of family caregivers, 83.2% of care workers, and 65.0% of heads of facilities agreed (x2=273.71, p<.001). There was no difference in opinion among the stakeholders that a living room and program room should have CCTV installed. All stakeholders agreed that the items to punish CCTV information leakage should be included in the guidelines for installation and operation of CCTV in long-term care facilities. In addition, more than 90% agreed on the preparation of confidentiality obligation for viewing CCTV in all groups. However, there were differences in opinions among stakeholders on composing the guidelines in accordance with the Child Care Act and restricting CCTV installation to the outside of bedrooms. Conclusion: This study confirms that there was a difference in stakeholders’ perceptions of mandatory CCTV installation in long-term care facilities. To increase the effectiveness of mandatory CCTV installation in long-term care facilities, it is necessary to strengthen education on human rights and safety for older adults and improve care workers’ working environment.
김태훈(Taehun Kim),김난이(Nani Kim),송지연(Jiyeon Song),정현진(Hyeonjin Jeong),이은민(Eunmin Lee) 한국자료분석학회 2023 Journal of the Korean Data Analysis Society Vol.25 No.4
본 연구는 기계학습 중 하나인 랜덤 포레스트 모델을 통해 성인의 우울을 예측하고자 시도되었다. 모델의 학습을 위한 연구 대상은 국민건강영양조사 8기(2019-2021) 자료 중 2주 이상의 우울감을 가진 대상자 1,086명, 가지고 있지 않은 대상자 8,826명으로 전체 9,896명으로 입력 변수는 20개였다. 본 연구의 모델 구축 및 평가를 위해 모든 코드는 Python 3.9.7로 작성되었으며, 통계 및 모델 구축을 위해 SciPy 1.614, ELI5, Scikit-learn 1.2.2, 패키지가 사용되었다. 분석은 학습에 사용될 원시 자료의 상관관계와 평균, 표준편차, 빈도, 비율, 그리고 모델의 예측에 영향을 주는 변수들의 값과 모델의 종합적 성능을 평가하였다. 연구결과 우울증 예측에 영향을 주는 요인들로 스트레스, 성별, 직업, 신체활동, 건강 상태가 확인되었으며, 가장 큰 영향을 주는 요인은스트레스(0.099±0.008; 0.081±0.008)였다. 모델의 전반적 성능(AUC)은 0.920(95% CI, 0.919–0.921)로 정확도는 0.921(95% CI, 0.920-0.922)로 나타났다. 구축된 모델은 우울증의 패턴을 찾아낼 수있었으며, 임상 현장에서 우울증 선별에 있어 신속하고 정확한 결정을 지원할 수 있을 것이다. This study attempted to predict depression in adults using a random forest model, a type of machine learning. The research subjects for training the model were 1,086 subjects with depression for more than 2 weeks and 8,826 subjects without depression, totaling 9,896 subjects from the 8th Korea National Health and Nutrition Examination Survey (2019-2021), and 20 input variables. For model building and evaluation in this study, all code was written in Python 3.9.7, and packages SciPy 1.614, ELI5, and Scikit-learn 1.2.2 were used for statistics and model building. The analysis evaluated the correlations, means, standard deviations, frequencies, proportions, and values of the variables affecting the prediction of the model and the overall performance of the model. The results showed that stress, gender, occupation, physical activity, and health status were identified as factors affecting the prediction of depression, with stress being the most influential (0.099±0.008; 0.081±0.008). The overall performance (AUC) of the model was 0.920 (95% CI, 0.919-0.921) with an accuracy of 0.921 (95% CI, 0.920-0.922). The built model was able to detect patterns of depression and could support rapid and accurate decisions in screening for depression in clinical settings.