• Journal of Korean Society of Forest Science
• /
• v.101 no.3
• /
• pp.412-425
• /
• 2012

Concrete Soil Erosion Control Dam, which blocks flow of debris flow in torrential stream, are reported to lose expected functions due to structural failure and collapses, caused by poor construction, material deterioration and external impacts. In this paper, an integrity assessment technique for debris barriers was proposed, which allows preliminary detection of problems inherent in debris barriers. The proposed integrity assessment technique is a non-destructive method based on SASW method, one of surface-wave tests. In this paper, a practical procedure and analysis guidelines in applying the SASW technique to debris barrier was proposed and its validity was verified using five decrepit debris barriers older than 20-year old. As a result, the SASW method was validated for the reliable grade evaluation method for concrete soil erosion control dam, and the resulting grades turned out to agree with the results determined by Sabang Associations.

• The Journal of the Korea Contents Association
• /
• v.21 no.6
• /
• pp.35-43
• /
• 2021

Citrus quality is generally determined by its sugar content and acidity. In particular, sugar content is a very important factor because it determines the taste of citrus. Currently, the most commonly used method of measuring citrus sugar content in farms is a portable juiced sugar meter and a non-destructive sugar meter. This method can be easily measured by individuals, but the accuracy of the sugar content is inferior to that of the citrus NongHyup official machine. In particular, there is an error difference of 0.5 Brix or more, which is still insufficient for use in the field. Therefore, in this paper, we propose an AI model that predicts the citrus sugar content of unmeasured days within the error range of 0.5 Brix or less based on the previously collected citrus sugar content and meteorological data (average temperature, humidity, rainfall, solar radiation, and average wind speed). In addition, it was confirmed that the prediction model proposed through performance evaluation had an mean absolute error of 0.1154 for Seongsan area and 0.1983 for the Hawon area in Jeju Island. Lastly, the proposed model supports an error difference of less than 0.5 Brix and is a technology that supports predictive measurement, so it is expected that its usability will be highly progressive.