http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
스마트폰 사용 및 인지기능이 노인의 우울감, 고독감에 미치는 영향
황순현 ( Hwang Soon-hyun ),이혜진 ( Lee Hye-jin ),하은희 ( Ha Eun-hee ),김소형 ( Kim So-hyeong ),정근경 ( Jung Geun-kyung ),최효진 ( Choi Hyo-jin ) 고령자·치매작업치료학회 2017 고령자.치매작업치료학회지 Vol.11 No.1
Objectives : The purpose of this study was to identify the effects of use of smartphone and cognitive function on depression, and Loneliness of life in elders. Methods : From August 18 to September 21, 2016, a total of 54 elderly people aged 65 years or older were interviewed at K Welfare Center in Busan, G Nursing Home, H Apartments in Gimhae, and D Apartment. The Korean version of Montreal Cognitive Assessment (MoCA-K), Korea UCLA Lonelines scale and Geriatric Depress Scale Short Korea Version (GDSSF-K) were used to evaluate the frequency, t-test, Pearson correlation , And regression analysis. Results : There was a significant correlation between cognitive function (p <0.001), depression (p <0.05), and loneliness (p <0.001) according to presence or absence of smartphone use. There was a significant correlation between cognitive function and loneliness, but there was no significant correlation between cognitive function and depression, depression and loneliness. Conclusion : The results suggest that an use of smartphone could be an effective improving and maintaining cognitive function, to decrease depression and Loneliness in old adults. We hope to encourage the old adults to use smartphones for healthy future ages and expect smartphone education to be activated.
심윤섭,변지환,황순현,전태보,Shim, Yun-Seop,Byeon, Ji-Hwan,Hwang, Soon-Hyun,Jeon, Tae-Bo 강원대학교 산업기술연구소 2011 産業技術硏究 Vol.31 No.2
Simulation plays a pivotal role in the analysis of complex systems. In this study, a job shop manufacturing system has been analyzed through DBR (Drum-buffer-rope) simulation. Specific attention has been put to examine the rate of due-date achievement. We first derived key factors affecting the system performance. We then developed ARENA simulation program based on DBR of TOC (Theory of Constraints) concepts. Based on the performance measure, factors, and experimental design, we obtained the results. We have drawn meaningful results through examination of the results. The results obtained from this study may provide a good base for practical applications.
김기동(Kim, Ki-Dong),황순현(Hwang, Soon-Hyun) 강원대학교 산업기술연구소 2013 産業技術硏究 Vol.33 No.1
There are two methods to make a distinction of deterioration of high-speed railway track. One is that an administrator checks for each attribute value of track induction data represented in graph and determines whether maintenance is needed or not. The other is that an administrator checks for monthly trend of attribute value of the corresponding section and determines whether maintenance is needed or not. But these methods have a weak point that it takes longer times to make decisions as the amount of track induction data increases. As a field of artificial intelligence, the method that a computer makes a distinction of deterioration of high-speed railway track automatically is based on machine learning. Types of machine learning algorism are classified into four type: supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. This research uses supervised learning that analogizes a separating function form training data. The method suggested in this research uses SVM classifier which is a main type of supervised learning and shows higher efficiency binary classification problem. and it grasps the difference between two groups of data and makes a distinction of deterioration of high-speed railway track.