• Journal of Conservation Science
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• v.37 no.3
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• pp.232-244
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• 2021

This study examined the physical attributes and heat treatment characteristics of glass beads excavated from the Gimhae area, which is the location of Geumgwan Gaya. This enabled classification of surface characteristics of the beads based on the investigation of the color, size, and shape. The glass beads were classified into eight color systems, with purplish-blue beads as the representative color. Bead size was categorized into three types depending on the outer diameter and how it increased over time. Bead shapes were categorized as round, tubular, or doughnut-shaped based on the inner diameter and length, with round being the typical shape. According to the degree of heat treatment, there are three types of cross-section for glass beads that are manufactured by the drawing technique, most of which are the HT-III type. In addition, it is estimated that the heat treatment technology has more considerable effects than other methods. Through non-destructive analysis, the chemical composition was obtained and categorized as flux, stabilizer, and colorant. Analysis confirmed the presence of 63 and 9 pieces in the potash and soda glass groups, respectively. Overall findings from the study highlighted a correlation between the chemical composition and the external factors such as color, size, shape, and manufacturing technology of glass beads recovered from Geumgwan Gaya, revealing characteristics related to that time and region.

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

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.446-452
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• 2021

As a higher standard for food consumption is required, the consumption of chicken meat that can satisfy the subdivided food preferences is increasing. In March 2003, the quality criteria for chicken carcasses notified by the Livestock Quality Assessment Service suggested quality grades according to fecal contamination and the size and weight of blood and bruises. On the other hand, it is too difficult for human inspection to qualify mass products, which is key to maintaining consistency for grading thousands of chicken carcasses. This paper proposed the computer vision algorithm as a non-destructive inspection, which can identify chicken carcass parts according to the detailed standards. To inspect the chicken carcasses conveyed at high speed, the image calibration was involved in providing robustness to the side effect of external lighting interference. The separation between chicken and background was achieved by a series of image processing, such as binarization based on Expectation Maximization, Erosion, and Labeling. In terms of shape analysis of chicken carcasses, the features are presented to reveal geometric information. After applying the algorithm to 78 chicken carcass samples, the algorithm was effective in segmenting chicken carcass against a background and analyzing its geometric features.

• Journal of the Korean Recycled Construction Resources Institute
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• v.8 no.4
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• pp.498-505
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• 2020

Aggregate occupies about 70-85% of the concrete volume and is an important factor in reducing the drying shrinkage of concrete. However, when constructing high-rise buildings, it acts as a problem due to the high load of natural aggregates. If the load becomes large during the construction of a high-rise building, creep may occur and the ground may be eroded. Material costs increase and there are financial problems. In order to reduce the load on concrete, we are working to reduce the weight of aggregates. However, artificial lightweight aggregates affect the interface between the aggregate and the paste due to its higher absorption rate and lower adhesion strength than natural aggregates, affecting the overall strength of concrete. Therefore, in this study, in order to grasp the interface between natural aggregate and lightweight aggregate by type, we adopted a method of measuring electrical resistance using an EIS measuring device, which is a non-destructive test, and lightweight bone. The change in the state of the interface was tested on the outside of the material through a blast furnace slag coating. As a result of the experiment, it was confirmed that the electric resistance was about 90% lower than that in the air-dried state through the electrolyte immersion, and the electric resistance differs depending on the type of aggregate and the presence or absence of coating. As a result of the experiment, the difference in compressive strength depending on the type of aggregate and the presence or absence of coating was shown, and the difference in impedance value and phase angle for each type of lightweight aggregate was shown.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.61-66
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• 2022

Sesamin and sesamolin are major lignan components with a wide range of potential biological activities of sesame seeds. Near infrared reflectance spectroscopy (NIRS) is a rapid and non-destructive analysis method widely used for the quantitative determination of major components in many agricultural products. This study was conducted to develop a screening method to determine the lignan contents for sesame breeding. Sesamin and sesamolin contents of 482 sesame samples ranged from 0.03-14.40 mg/g and 0.10-3.79 mg/g with an average of 4.93 mg/g and 1.74 mg/g, respectively. Each sample was scanned using NIRS and calculated for the calibration and validation equations. The optimal performance calibration model was obtained from the original spectra using partial least squares (PLS). The coefficient of determination in calibration (R²) and standard error of calibration (SEC) were 0.963 and 0.861 for sesamin and 0.875 and 0.292 for sesamolin, respectively. Cross-validation results of the NIRS equation showed an R² of 0.889 in the prediction for sesamin and 0.781 for sesamolin and a standard error of cross-validation (SECV) of 1.163 for sesamin and 0.417 for sesamolin. The results showed that the NIRS equation for sesamin and sesamolin could be effective in selecting high lignan sesame lines in early generations of sesame breeding.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.400-414
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• 2021

Under high-level radioactive waste repository conditions, bentonite as an engineered barrier material undergoes thermal, hydrological, mechanical, and chemical processes. We report the applications of X-ray Computed Tomography (CT) imaging technique on the characterization and analysis of bentonite over the past decade to provide a reference of the utilization of this technique and the recent research trends. This overview of the X-ray CT technique applications includes the characterization of the bentonite either in pellets or powder form. X-ray imaging has provided a means to extract grain information at the microscale and identify crack networks responsible for the pellets' heterogeneity. Regarding samples of pellets-powder mixtures under hydration, X-ray CT allowed the identification and monitoring of heterogeneous zones throughout the test. Some results showed how zones with pellets only swell faster compared to others composed of pellets and powder. Moreover, the behavior of fissures between grains and bentonite matrix was observed to change under drying and hydrating conditions, tending to close during the former and open during the latter. The development of specializing software has allowed obtaining strain fields from a sequence of images. In more recent works, X-ray CT technique has served to estimate the dry density, water content, and particle displacement at different testing times. Also, when temperature was added to the hydration process of a sample, CT technology offered a way to observe localized and global density changes over time.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.10
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• pp.701-708
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• 2022

Since the propellant tank structure of the projectile is mainly subjected to a compressive force, there is a high risk of damage due to buckling. Large and lightweight structures such as propellant tank have a complex manufacturing process. So it requires a non-destructive test method to predict buckling load to use the structure after testing. Many studies have been conducted on Vibration Correlation Technique(VCT), which predicts buckling load using the relationship between compressive load and natural frequency, but it requires a large compressive load to predict the buckling load accurately, and it tends to decrease prediction accuracy with increasing internal pressure in structure. In this paper, we analyzed the causes of the decrease in prediction accuracy when internal pressure increases and proposed a method increasing prediction accuracy under the low compressive load for being usable after testing, through VCT combined testing and FEA result. The prediction value by the proposed method was very consistent with the measured actual buckling load.

• Journal of Forest and Environmental Science
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• v.38 no.3
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• pp.184-194
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• 2022

Triplochiton scleroxylon K. Schum is the plant species most affected by logging activities in the East Region of Cameroon due to its market value. This logging has impacted the ecological niche of the fern plant for which limited research has been done. The aim of this study is to contribute towards improving knowledge of fern richness and biomass on T. scleroxylon within the Central African sub-region. Fern data collection was done on 20 felled/harvested T. scleroxylon where, in addition to fern inventory, fern biomass was collected by the destructive method. The diameter and height of T. scleroxylon measured were used as explanatory variables in allometric equations for fern biomass estimation. Fern inventory was characterized using diversity index. Eight fern species were recorded on T. scleroxylon (≈5 species/T. scleroxylon). The minimum diameter where fern could be found is 59.4 cm. The average fern biomass found was 23.62 kg/T. scleroxylon. Pearson correlation coefficient showed a positive correlation (r>0.55) between fern biomass and T. scleroxylon diameter. For allometric equation, the logarithmic model improved better the adjustment than the non-logarithmic model. However, the quality of the adjustment is improved more when only the diameter is considered as an explanatory variable. Fern biomass is estimated to 90.08 kg/ha^-1 with 76.02 kg/ha^-1 being lost due to T. scleroxylon exploitation in the study area. This study is a contribution towards increasing knowledge of fern diversity specific to T. scleroxylon, and also fern biomass contribution to climate change mitigation and the potential carbon loss due to T. scleroxylon exploitation.

• Journal of Conservation Science
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• v.37 no.3
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• pp.270-281
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• 2021

The Yongjam of Oejae, Yi Dan-ha's wife, is an ornamental hairpin with a dragon-shaped engraving; designated as National Folklore Cultural Heritage No. 4. It is also a component of the ceremonial costume, and an artifact of great value as it clearly identifies the position of the wearer and the period of this artifact. The Yongjam has been well preserved in general; however, various pollutants and corrosive products have affected the engraved patterns, requiring conservation treatment. Furthermore, a non-destructive analysis was conducted to identify the components of the materials and the manufacturing techniques used in the ornament. The Yongjam is hollow inside to reduce its weight when placed in the hair and has a color contrast of gold, red, and black. The decorative part and the body were made separately. That is, the body was made from an alloy of copper, silver, and zinc, and its joint was elaborately connected without any overlaps. In the decorative part, different alloy ratios were identified in the dragon's face, beard, horn, body, and fin. Further, for the dragon's face with its delicate patterns, an alloy of silver and copper was used, likely to make the face appear as realistic as possible.