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간호대학생의 에니어그램 성격유형에 따른스트레스 대처방식
김희주,박가영,박지영,송예빈,심지현,이수연,이지영,장주희,정영민 이화여자대학교 간호과학대학 2011 이화간호학회지 Vol.- No.45
The purpose of this study is to analyze the relationship between stress coping behaviors and Enneagram personality types. The subject of the study is 342 college students who are attending 4-year nursing colleges in Seoul, Korea, and 198 students among them are qualified for the study. Typified statistical tools SPSS, chi-square, and ANOVA are used as analyzing methods in the study. The research results are as follows: 1. In nursing students, freshman class is the highest population in the study with 63 students(31.82 %), and the highest percentage of population does not have a religion(89 students, 44.95 %). 120 students (60.61 %) answered that their interpersonal relationships are good, and 105 students(53.03 %) are satisfied with the nursing major. 2. In Enneagram personality type, 9 type is the highest(42.42 %). 3. Problem focused coping type is the highest in stress coping behaviors(28.12(±20.16) points). 4. Problem focused coping behavior and social support coping behavior show significance. 5. Social support coping behavior shows significance, and 3 type scored the highest(17.67(±2.66) points). Further studies are suggested based on above results: First, in order to achieve more accurate results, the research of Enneagram and stress coping behavior with representative for sample Korean nursing students is necessary. Second, Development and verification the effect of stress coping program based on Enneagram personality types among nursing students are necessary.
HMM을 이용한 연속 음성인식 시스템의 화자적응화에 관한 연구
심장엽,김상범,김주성,김수훈,이영재,이종진,허강인 동아대학교 공과대학 부설 한국자원개발연구소 1995 硏究報告 Vol.19 No.2
It is hard to collect sufficient speech data for training a speaker-dependent (SD) model from the same speaker. In contrast, to trains a speaker-independent (SI) model need not collect a large amount of speech data per speaker but from many speakers. Speaker-adaptation (SA) is an additional training technique from SI model by a small amount of adaptation speech. It has proved to be a powerful tool for achieving good recognition performance without the high cost of SD training. In this study, a speaker adaptation algorithm (MAPE) which trains it by every utterance sequentially without hand-labelling is introduces. The hand-labelling is performed automatically by Concatenation training and Viterbi-segmentation. The secuential-training is performed by MAPE(Maximum A Posteriori probability Estimation). We can train it using any small amount of adaptation speech data. For newspaper editorial continuous speech, the recognition rates of adaptation of HMM was 62.5% respectively which is approximately 32.5% improvement over that of unadapated HMM.
Kim, J.,Lee, J.,Chae, S.,Shim, J.Y.,Lee, D.Y.,Kim, I.,Kim, H.J.,Park, S.H.,Suh, H. IPC Science and Technology Press 2016 Polymer Vol.83 No.-
Polymers using 6-(2-thienyl)-4H-thieno[3,2-b]indole (TTI) with high planarity were synthesized and utilized for the photovoltaics. Push-pull types of conjugated polymers (PTTICN, PTTICNR and PTTIFR) containing TTI as electron pushing unit and 2-pyriminecarbonitrile or 2-fluoropyrimidine as electron pulling unit were synthesized. We designed pyrimidine derivatives with strong electron-withdrawing group (C?N or fluorine) for the generation of strong electron pulling property. By the combination with the electron pushing unit, the pyrimidines with strong electron pulling units will provide low highest occupied molecular orbital (HOMO) energy levels for higher open-circuit voltages (V<SUB>OC</SUB>). For the syntheses of the polymers, the electron pushing and the electron pulling units were combined by Stille coupling reaction with Pd(0)-catalyst. The polymers of PTTICN and PTTICNR with CN unit show higher V<SUB>OC</SUB> than the polymer with fluorine unit. The device comprising PTTICNR and PCBM (1:4) with diiodooctane (DIO) additive showed a V<SUB>OC</SUB> of 0.82 V, a J<SUB>SC</SUB> of 6.38 mA/cm<SUP>2</SUP>, and a fill factor (FF) of 0.53, giving a power conversion efficiency of 2.81%.