• Journal of Radiation Protection and Research
• /
• v.41 no.1
• /
• pp.71-79
• /
• 2016

Background: It is necessary to analyze radioactivity of naturally occurring radioactive materials (NORM) in products to ensure radiological safety required by Natural Radiation Safety Management Act. The pretreatments for the existing analysis methods require high technology and time. Such destructive pretreatments including grinding and dissolution of samples make impossible to reuse products. We developed a rapid and simple procedure of radioactivity analysis for thorium series in the products containing NORM. Materials and Methods: The developed method requires non-destructive or minimized pretreatment. Radioactivity of the product without pretreatment is initially measured using gamma spectroscopy and then the measured radioactivity is adjusted by considering material composition, mass density, and geometrical shape of the product. The radioactivity adjustment can be made using scaling factors, which is derived by radiation transport Monte Carlo simulation. Necklace, bracelet, male health care product, and tile for health mat were selected as representative products for this study. The products are commonly used by the public and directly contacted with human body and thus resulting in high radiation exposure to the user. Results and Discussion: The scaling factors were derived using MCNPX code and the values ranged from 0.31 to 0.47. If radioactivity of the products is measured without pretreatment, the thorium series may be overestimated by up to 2.8 times. If scaling factors are applied, the difference in radioactivity estimates are reduced to 3-24%. Conclusion : The developed procedure in this study can be used for other products with various materials and shapes and thus ensuring radiological safety.

• Journal of Sericultural and Entomological Science
• /
• v.53 no.1
• /
• pp.50-54
• /
• 2015

Mulberry fruit is common to keep a frozen storage because of the very high water content. Because freezing-storing cost is generated before the processing or sales, farmers of mulberry fruit production are weighted in financial burden. In addition, mulberry fruit has difficulty in expanding consumption by made in the simple processed products like the mulberry jam, mulberry juice, mulberry enzyme, alcohol, etc. Recent, frozen fruits including frozen blueberries, frozen strawberries, frozen mango, frozen rich, frozen mulberry fruit has been started to sell in the large discount stores and convenience stores. However, there is restricted sales in only special place that have the frozen distribution facilities. So, for the income improvement and consumption promotion of mulberry farmers facing these difficult situations, we developed the processing method of semi-dried mulberry fruit using the vacuum freezing dryer. The frozen mulberry fruit which was stored below $-40^{\circ}C$ is to dry in a vacuum freeze dryer, at $30{\sim}35^{\circ}C$, 23 ~ 24 hours. Semi-dried mulberry fruit seperated respectively. It had soft texture, and maintained shape, size and flavor. In particular, semi-dried mulberry fruit can be stored at room temperature.

• Korean Journal of Remote Sensing
• /
• v.40 no.2
• /
• pp.229-241
• /
• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.