활천가족실 / 황혼의 언덕에 서서(수필)

김규희 기독교대한성결교회 활천사 1995 활천 Vol.497 No.-

농촌지역 만성정신장애인을 위한 사회복귀전략 탐색

김규희 한국정신건강사회복지학회 2003 한국정신건강사회복지학회 학술발표논문집 Vol.2003 No.11

국민전선의 에토스 변화 연구 - Jean-Marie Le Pen과 Marine Le Pen의 인칭대명사 je의 사용을 중심으로

김규희,최윤선 서울대학교 불어문화권연구소 2016 불어문화권연구 Vol.26 No.-

Dans cette étude, nous avons appliqué dans les discours politiques du Front National la répartition des éthos proposée par Roitman et en avons analysé l’élaboration de l’image du Front National à l’aide de l’emploi du pronom « je ». En comparant l’usage de l’éthos du pronom personnel « je » chez Jean-Marie Le Pen et celui de Marine Le Pen, nous avons pu constater un changement dans la stratégie de la constitution de l’image du parti. La conclusion que nous en avons tirée est la suivante. Dans le discours politique de Jean-Marie Le Pen, l’emploi de l’éthos émotionnel est le plus notable. Le recours au je de l’indignation (21%) et au je de l’engagement émotionnel (17%) s’élève à près de 40%. En revanche, l’éthos que nous retrouvons caractéristiquement chez Marine Le Pen correspond au je de l’idéologue (24%), je de la volonté (18%), je de l’action et de la force (15%). Ainsi, nous pouvons constater que chez Jean-Marie Le Pen, l’emploi de l’éthos émotionnel est dominant alors que chez Marine Le Pen, l’éthos rationnel qui dévoile les idées et l’orientation politiques est le plus utilisé en formant un contraste avec celui du premier. De plus, nous avons pu voir que la manière dont Marine Le Pen constitue son éthos est similaire à celle des autres candidats des principaux partis politiques comme Sarkozy et Hollande tandis que l’usage de l’éthos chez Jean-Marie Le Pen correspond plus à celui des candidats des petits partis politiques tels que Joly, Dupont-Aignan et Laguiller. Ainsi, nous avons pu conclure que l’emploi de l’éthos varie plutôt en fonction de la stature des candidats que de leurs idées politiques. Sur ce point, une étude plus élaborée devra être abordée ultérieurement.

Correlation Between Accompanying Symptoms of Facial Nerve Palsy, Clinical Assessment Scales and Surface Electromyography

김규희,박정현,김태경,이은주,Jung Su-Eun,Seo Jong Cheol,Kim Cheol Hong,최유민,윤현민 대한침구의학회 2022 대한침구의학회지 Vol.39 No.4

Background: This retrospective study aimed to determine whether there were correlations between the number and type of accompanying symptoms of peripheral facial nerve palsy, and surface electromyography (SEMG) and clinical assessment scales to help diagnosis.Methods: There were 30, cases of peripheral facial nerve palsy at Visit 1 to the Korean Medicine Hospital, Dong-eui University, 22 cases at Visit 2 and 10 cases at Visit 3. The study period was from July 19, 2021 to November 31, 2021. Symptoms were evaluated three times (with two-week intervals which began 7 days from onset) using SEMG, clinical assessment scales and accompanying symptoms. In this study, the House-Brackmann grading system (HBGS), and the Yanagihara’s unweighted grading system (Y-score) clinical assessment scales were used. The Pearson or Spearman correlation was used for statistical analysis.Results: On Visit 1, the number of accompanying symptoms of peripheral facial nerve palsy had no significant correlation with other measures. On Visits 1-3, the HBGS score had a significant negative correlation with the Y-score. On Visit 2, most of the mean values measured had significant correlations with each other although not between SEMG-Z and SEMG-O that Z means a zygomaticus muscle and O means a orbicularis oris muscle. On Visit 3, the number of accompanying symptoms significantly correlated with the clinical assessment scales. The HBGS score, Y-score, and SEMG measurements (except SEMG-Z) had significant correlations with each other. A significant positive correlation between SEMG-Z and SEMG-T was noted.Conclusion: We predict accompanying symptoms can be used to diagnose the peripheral facial nerve palsy including both clinical assessment scales and SEMG measurements at 2-5 weeks after onset.

Crystallization and preliminary crystallographic analysis of IlvC, a ketol-acid reductoisomerase, from Streptococcus pneumoniae

김규희,이상호 한국구조생물학회 2017 Biodesign Vol.5 No.1

IlvC, a ketol-acid reductoisomerase, plays a critical role in alkyl migration and catalyzes the second step in the biosynthesisof branched amino acids such as leucine, valine and isoleucine. As an initial step to investigate whether IlvC is involved inpneumococcal growth and virulence from the structural background, ilvC from Streptococcus pneumoniae D39 (SpIlvC)was cloned and overexpressed in Escherichia coli. Crystals of SpIlvC were obtained by hanging-drop vapour diffusion in0.1 M HEPES pH 7.5, 0.1 M NaCl, 1.5 M ammonium sulfate and diffracted to 1.69 Å resolution. The SpIlvC crystal belongedto space group P212121 with unit cell parameters a = 69.1°, b = 104.3°, c = 110.9° and contained two molecules in theasymmetric unit.

공공임대주택에 대한 사회적 낙인 저감 방안 연구: 거주자 혼합을 중심으로

김규희,박준 국토연구원 2023 국토연구 Vol.116 No.-

The aim of this study is to draw practical policy implications in terms of the management of public rental housing to cope with internal and external stigma against tenants of public rental housing. This is based on the analysis was on physical features and the demographic/economic/social characteristics of the tenants in public rental housing in Seoul. The analysis reveal that there are structural factors that cause concentrations of specific groups of tenants with the same features in terms of income and age in certain types of public rental housing such as ‘permanent public rental housing’, and these factors give rise to social prejudices. Also, semi-structured interviews with residents and the managers of public rental housing were conducted to examine discrimination and marginalization. The study foundfindings include that 1) stigma matters not only in relation with private housing residents but also amongst residents in public rental housing, 2) more active engagement on the anti-social behaviors of a few residents is crucial, and 3) it is important to establish detailed and practical goals for social mixing policy when managing public rental housing. The study concludes with practical suggestions to alleviate this stigma by reallocating residents with a consideration of the size of housing units and household, and their locations. 공공임대주택에 대한 사회적 낙인은 주거불평등 완화를 위한 공공임대주택 공급확대의 한 걸림돌이 되어왔다. 이 연구의 목적은 서울시 공공임대주택의 유형별 지역별 분포, 거주자 특성에 대한 현황 분석, 거주자 및 관리자 면접조사를 통해 공공임대주택 내에서도 존재하는 사회적 낙인의 원인을 검토하고 이를 줄이기 위한 정책적 함의를 도출하는 것이다. 이 연구에서는 먼저 서울주택도시공사가 관리하는 공공임대주택의 물리적 특성 분석 및 거주자 특성 분석을 통해 사회적 낙인을 강화하는 요소를 검토했다. 소득과 연령 등 기준에서 특정 그룹 거주자가 영구임대 등 특정 공공임대주택 유형에 집중될 수밖에 없고 여기서 발생하는 사회적 편견이 전체적으로 확장되는 물리적 차원 및 입주자 관리 차원의 구조적 문제를 발견했다. 이후 공공임대주택 거주자 및 관리자들과의 면접조사를 통해 차별과 소외의 실태 및 현 제도상의 제약을 살펴봤다. 사회적 낙인의 문제는 분양주택과의 관계뿐 아니라 공공임대주택 내에서도 중요한 문제라는 점, 소수 거주자의 반사회적인 행동에 대한 보다 적극적인 대응 필요성, 사회적 혼합에 대한 구체적이고 실질적인 목표 설정의 필요성 등이 도출되었다. 이 연구에서는 분석을 통해 공공임대주택 공급 및 관리라는 제한된 여건 내에서 공실 발생, 신규 입주, 자발적 이주 차원에서 실질적으로 적용 가능한 사회적 혼합 제고 방안을 제시했다.

경북지역 알레르기 환자에서 피부단자검사, 혈청 총 면역 글로블린 E치 및 말초혈액 호산구수의 측정

김규희,박기흠,이예봉,양창헌,이창우,이영현 大韓家庭醫學會 1993 Korean Journal of Family Medicine Vol.14 No.3

증기 유속을 고려한 수평 핀응축관의 전열 성능 계산법 ( A Theoretical Model of Film Condensation on a Horizontal Finned Tubes Considering the Effect of Vapor Velocity )

김규희,유갑종 대한기계학회 1996 대한기계학회 춘추학술대회 Vol.- No.-

Molecular structural descriptor‐assisted machine learning for organic photovoltaics with perylenediimide acceptors

김규희,윤건호,이치형,남민우,고두현 대한화학회 2024 Bulletin of the Korean Chemical Society Vol.45 No.2

Although organic photovoltaics (OPVs) have evolved over the last two decades, the discovery of new materials and optimization of numerous considerations for high‐performance devices remain challenging. To reduce these laborious processes and expedite the advancement of OPVs, we constructed machine learning (ML) models that predict photovoltaic parameters. We designed a unique descriptor that divides the molecular structure into smaller units and translates them into a concise matrix. This allows the ML model to easily track structural units and understand which units are important for predicting target performance, enabling the ML model to prioritize crucial units. Therefore, without requiring additional data from measurements or calculations, the ML models can extract chemical properties from molecular structural information and accurately predict the photovoltaic parameters. The ML models that predict the photovoltaic parameters, including the open‐circuit voltage, short‐circuit current density, fill factor, and power conversion efficiency, all show remarkably superior prediction performance, with Pearson correlation coefficients exceeding 0.68. Consequently, in this article, we propose a highly precise and reliable predictive OPV‐ML platform that can robustly screen for unnecessary experiments and accelerate OPV development. Although organic photovoltaics (OPVs) have evolved over the last two decades, the discovery of new materials and optimization of numerous considerations for high-performance devices remain challenging. To reduce these laborious processes and expedite the advancement of OPVs, we constructed machine learning (ML) models that predict photovoltaic parameters. We designed a unique descriptor that divides the molecular structure into smaller units and translates them into a concise matrix. This allows the ML model to easily track structural units and understand which units are important for predicting target performance, enabling the ML model to prioritize crucial units. Therefore, without requiring additional data from measurements or calculations, the ML models can extract chemical properties from molecular structural information and accurately predict the photovoltaic parameters. The ML models that predict the photovoltaic parameters, including the open-circuit voltage, shortcircuit current density, fill factor, and power conversion efficiency, all show remarkably superior prediction performance, with Pearson correlation coefficients exceeding 0.68. Consequently, in this article, we propose a highly precise and reliable predictive OPV-ML platform that can robustly screen for unnecessary experiments and accelerate OPV development.

Fault Signal Classification for Rotating Machinery Using Transfer Learning

김규희,임성순,김원재,유재홍 대한산업공학회 2023 대한산업공학회 추계학술대회논문집 Vol.2023 No.11