• Journal of Korean Society of Forest Science
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• v.94 no.3 s.160
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• pp.197-204
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• 2005

This study was conducted to investigate the effect of tsunami which occurred in coastal area of the East Sea in Korea, the function of coastal forest for the reduction of tsunami's speed and energy, and the non-structural measures through the research data of tsunami in Japan. The results showed that tsunami which occurred in the East Sea in 1983 and 1993 reached coastal area of Korea one hour and fifty minutes later from Japan, and caused a loss of lives and property and flooding damage. If 60 m width of coastal forest was formed, the speed was decreased by 30%, the energy by 10%. Therefore, the width of coastal forest must be at least 60 m, of which the stand structure is the multiple-layered forest of mixed-forest, and the wave preventing measures have to be constructed together. In addition, non-structural measures as tsunami warning and survival strategies must be prepared.

• Journal of Korean Academy of Nursing
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• v.51 no.4
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• pp.395-407
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• 2021

The COVID-19 curve seesawed and reached the fourth pandemic in July 2021. Since the first three waves, the focus has been on achieving herd immunity through vaccination while a lot of manpower is used for quarantine. However, we have not been able to prevent the fourth wave. The causes are thought to be related to people who doubt the safety of the vaccine and refuse it or violate quarantine guidelines such as social distancing. This study examined guidelines for preventing and controlling COVID-19, the accuracy of vaccination-related information, and described quarantine measures including for those who completed vaccination. In conclusion, prevention and vaccination are the most effective countermeasures against COVID-19. We recommend people vaccination with self-quarantine. Also, it is necessary to make large investments to protect and support nurses in future pandemics.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.137-144
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• 2007

Objectives : According to Rowe and Kahn (1998), successful aging is the combination of a low probability of disease, high functioning, and active engagement with life. The purpose of this study was to assess the relationship between active engagement with life and functioning among the community-dwelling elderly. Methods : Data were collected from Wave 2 of the Suwon Longitudinal Aging Study (SLAS), consisting of a sample of 645 persons aged 65 and older living in the community. A social activity checklist and social support inventory were used as measures of engagement with life, along with the Physical Functioning (PF) scale as a measure of functioning. The effects of social support and social activity on physical functioning, taking into account the covariates, were analyzed by hierarchical linear regression analysis. Results : Maintenance of social activity and social support were significantly associated with higher physical function, after adjusting for sociodemographic and health-related covariates. Social support appeared to be more prominent than social activity in predicting physical functioning. Conclusions : Social support and social activity are potentially modifiable factors associated with physical function in older persons. Studies examining the role social engagement may play in preventing disability are warranted.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.433-440
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• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.