• 재활복지
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• v.18 no.4
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• pp.221-235
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• 2014

Recently, the frequency of stroke disease is increased due to the rapid aging population, and is contributed to the major occurrence factors of the posteriori acquired disability. This study is about an postural change device for the control of supine posture which is an assisted equipment using in daily rehabilitation process for overcoming the disability by the aftereffects of the stoke disease. In this paper, the existing domestic and Japan postural appliances is examined and its comparison and categorization is performed according to its functions and purposes. Here, in order to control the supine posture state, the design method for advanced multi functional system is proposed, which is devised to have an unified mattress control operations of combining the bedsore prevention tube with the supine posture tilting tube. And also, in addition of an smart function, it is designed to enable to perform an RF functions such as the monitoring of the present device state, the alteration of the basic position and the control of alternative floating and supine posture. This system control hardware consists of three main parts : the sensor detection part, the motor driving /control part, and the system control part for bluetooth communication. In results, we confirmed that the system designed by this research is possible to make it practical as an advanced smart postural change device combined by IoT technology in the application field of the recent IT technology.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.