http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Analyses of physiological wrist tremor with increased muscle activity during bench press exercise
손혜원,김지수,홍규석,박원일,윤성진,임기원,박종훈 한국운동영양학회 2019 Physical Activity and Nutrition (Phys Act Nutr) Vol.23 No.1
[Purpose] To date, there have been no studies on the response of wrist tremor to increased muscle activity during exercise. This study aimed to evaluate the wrist tremor response with increasing muscle activity during bench press exercise. [Methods] Triceps muscle activity and wrist tremor response were measured by electromyography and an accelerometer, respectively, during bench press exercise in 11 healthy men without weight-training experience. Subjects performed bench press at 30% repetition maximum (RM), and the rating of perceived exertion (RPE) and lactate concentration were measured before and after exercise. One week later, an equivalent number of bench presses at 30% RM was performed without weight load as a control trial (CT). [Results] RPEs and lactate concentrations significantly increased after resistance exercise (30% RM) from 7.4 to 14.3 and 1.7 to 4.9, respectively (P<.01), but no such difference was observed in the CT. Muscle activity linearly increased during the 30% RM exercise, and wrist tremors were shown to linearly decrease. A strong negative correlation was observed between the two variables (r=−0.88, P<.001). [Conclusion] We found that wrist tremors during resistance exercise, as measured using an accelerometer, can be used to predict muscle activity.
코로나바이러스감염증-19 상황에서 대학생의 감염불안, 충동성, 의사결정유형이 인터넷에서의 건강정보추구행위에 미치는 영향
박완주,손혜원,변채영,손혜리,이승현,이예진 경북대학교 간호혁신연구소 2021 경북간호과학지 Vol.25 No.1
Purpose: This study investigated the influencing factors of COVID-19 infection anxiety, impulsivity, and decisionmaking type on health information-seeking behavior on the internet. Methods: This study was conducted by 178 college students of 5 cities in Korea using a self-reporting survey with structured questionnaires of COVID-19 anxiety, impulsiveness, decision-making style, and health information-seeking behavior on the internet. SPSS 25 was used for the statistical analysis. Results: The results showed that non-planning impulsivity(ß=-.25, p<.001), dependent decision-making types(ß=.23, p<.001), and COVID-19 infection anxiety(ß=.22, p=.001) had statistically significant effects on health information-seeking behavior on the internet with 33.6% overall explanatory power. Conclusion: Findings of this study indicate that college students’ dependent decision-making types, COVID-19 infection anxiety had a positive effect, and non-planning impulsivity had a negative effect on health information-seeking behavior on the internet. Based on the results of this study, it is necessary to identify and compare health information-seeking behavior on the internet based on infection and self-quarantine experiences.
금속층 두께에 따른 ITO/Ag/ITO 다층 투명 전극의 발열 특성 연구
민혜진,강예지나,손혜원,신소현,황민호,이현용 한국전기전자재료학회 2022 전기전자재료학회논문지 Vol.35 No.1
In this study, we investigated the optical, electrical and exothermic characteristics of ITO/Ag/ITO multilayer structures prepared with various Ag thicknesses on quartz and PI substrates. The transparent conducting properties of the ITO/Ag/ITO multilayer films depended on the thickness of the mid-layer metal film. The ITO/Ag (14 nm)/ITO showed the highest Haccke’s figure of merit (FOM) of approximately 19.3×10–3 Ω-1. In addition, the exothermic property depended on the substrate. For an applied voltage of 3.7 V, the ITO/Ag (14 nm)/ITO multilayers on quartz and PI substrates were heated up to 110℃ and 200℃, respectively. The bending tests demonstrated a comparable flexibility of the ITO/Ag/IT multilayer to other transparent electrodes, indicating the potential of ITO/Ag/ITO multilayer as a flexible transparent conducting heater.
이희원(Hee-Won Lee),정규철(Kyu-chul Jung),이현정(Hyun-Jung Lee),손혜원(Hye-Won Son),윤희진(Hee-Jin Yoon),안상태(Sangtae Ahn) 한국정보기술학회 2022 Proceedings of KIIT Conference Vol.2022 No.12
본 연구에서는 수요에 비해 작은 주차 부지를 최대한으로 활용하기 위하여 딥러닝 기반 차세대 주차관리 시스템을 개발하였다. 수행된 연구의 결과는 토대로 대형 쇼핑몰 등 유동 인구가 많은 상업지역에서의 활용할 수 있고, 주차 관리와 관련된 다양한 기술의 발전을 촉진할 수 있을 것이다. In this work, we develop a next-generation parking management system using deep learning to optimize limited parking lots. Based on the results of this work, we expect that the developed parking management system could be used for commercial areas such as shopping malls and accelerating the technologies related to parking management.