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미용 전공 대학생의 학습동기가 학습몰입 및 진로결정자기효능감에 미치는 영향
윤영지(Youn, Young Ji),지정훈(Ji, Jeong Hun) 한국디자인문화학회 2023 한국디자인문화학회지 Vol.29 No.4
University education provides a structured and specialized curriculum that offers the foundation for students to grow into socially responsible individuals with professional knowledge, group consciousness, and a sense of responsibility. Moreover, effective learning motivation is crucial for students’ efficient learning and career choices. Successful learning leads to sound career decisions, which will be a significant factor when students choose their lifelong professions with confidence. Therefore, this study aims to investigate the impact of learning motivation on learning engagement and career decision-making self-efficacy among university students majoring in beauty. The objective is to provide fundamental data and information for effective career guidance and educational planning. The data analysis for this study was conducted using SPSS v. 25.0 statistical software. Various statistical methods were applied, including frequency analysis, multiple response analysis, exploratory factor analysis, calculation of cronbach’s α coefficient for reliability verification, descriptive statistics, correlation analysis, and regression analysis. The research focused on students currently enrolled at 2-year and 4-year beauty universities located in Gwangju, Busan, and Daegu metropolitan cities. A total of 260 questionnaires were collected and analyzed using a 5-point Likert scale. The main content of the study comprises theoretical backgrounds, research design, and analyses related to learning motivation, learning engagement, and career decision-making self-efficacy. The findings revealed significant relationships in the impact of learning motivation on learning engagement and career decision-making self-efficacy. In particular, it was evident that the intrinsic motivation, a sub-factor of learning motivation, played a significant role in influencing both learning engagement and career decision-making self-efficacy. Additionally, the study confirmed that learning engagement had a notable influence on career decision-making self-efficacy, affecting its sub-factors, such as problem-solving, future planning, occupational information, goal selection, and self-evaluation. Notably, intrinsic motivation, a sub-factor of learning motivation, emerged as a crucial factor affecting both learning engagement and career decision-making self-efficacy. These results emphasize the importance of fostering intrinsic motivation and effective learning engagement to establish successful career guidance and educational planning in beautyrelated university programs.
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전송률 제어 채널에서 비대칭 무선 링크 네트워크를 이용한 트래픽 성능 분석
정유선,윤영지,신보경,김혜민,박동석,나상동,Jeong, You-Sun,Youn, Young-Ji,Shin, Bo-Kyoung,Kim, Hye-Min,Park, Dong-Suk,Ra, Sang-Dong 한국정보통신학회 2008 한국정보통신학회논문지 Vol.12 No.8
전송률 기반의 흐름 제어 및 정체 제어 메커니즘을 사용하는 무선 네트워크에서 양방향 TCP/IP 연결의 성능을 연구한다. 전송률 기반의 흐름 제어를 이용하여 데이터의 흐름을 원활하게 유지함으로써, TCP 윈도우 흐름 제어에서 나타났던 다양한 유형의 버스트 현상을 제거하거나 완화시키는데 논하고, 대기열에서 전송률 제어 채널을 통해 실행되는 동안 버스트 반응에 의해 TCP ACK 압축 문제가 발생한다. 소스 IP 대기열의 주기적인 버스트 반응을 분석하여, 양방향 트래픽으로 인해 쓰루풋 저하됨으로써 향상된 퍼포먼스와 상황에 적용 가능한 쓰루풋 저하 예측을 나타내어 대기열의 최대값을 성능분석 한다. Performance of TCP/IP is studied on the wireless network using flow control and congestion control mechanism based on transmission rate. We discuss the elimination or the reduction of various phenomena of burst by flow controlling on transmission rate and verify that there are TCP ACK compression promblems on the queue by burst reaction while executing transmission rate controlled channels. Analyzing periodic burst reaction on the queue of source IP, the maximum value of queue is expected, which represents the applible expectation of throughput reduce and shows the improvement of performance by the reduce of throughput due to hi-directional traffic.
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유전자 네트워크에서 확률적 그래프 모델을 이용한 정보 네트워크 추론
나상동,박동석,윤영지,Ra Sang-Dong,Park Dong-Suk,Youn Young-Ji 한국정보통신학회 2006 한국정보통신학회논문지 Vol.10 No.8
This study is a numerical representative modelling analysis for applying the process that unravels networks between cells in genetics to WWW of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extends them to genetic representation data in the method of network modelling in informatics. 유전자 생물학 분야에서 여러 각도로 세포 간 네트워크를 입증하는 고 처리 정보공학 WWW에 응용하려는 수치학적인 표현 모델 분석 연구한다. 확률적 그래프 모델을 사용하여 데이터 네트워크로부터 생물학적 통찰력을 확률적 함수적으로 응용해 복잡한 세포 간 네트워크 보다 단순한 하부모델로 구성하여 유전자 베이스네트워크 논리를 유전자 표현 레벨로 나타낸다. 유전자 데이터로부터 확률적 그래프 모델들을 분석하여 유전자 표현 데이터를 정보 공학 네트워크 모델의 방법으로 확장 추론한다.
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