• Resources Recycling
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• v.32 no.1
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• pp.42-49
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• 2023

The glass ceramic secondary resource containing Li-Al-Si is used in inductor, fireproof glass, and transparent cookware and accounts for 14% of the total consumption of Li, which is the second most widely used after Li-ion batteries. Therefore, new Li resources should be explored when the demand for Li is exploding, and extensive research on Li recovery is needed. Herein, we recovered Li from fireproof Li-Al-Si glass ceramic, which is a new secondary resource containing Li. The fireproof glass among all Li-Al-Si glass ceramics was used as raw material that contained 1.5% Li, 9.4% Al, and 28.9% Si. The process for recovering Li from the fireproof glass was divided into two parts: (1) calcium salt roasting and (2) water leaching. In calcium salt roasting, a sample of fireproof glass was crushed and ground below 325 mesh. The leaching efficiency was compared based on the presence or absence of heat treatment of the fireproof glass. Moreover, the leaching rates based on the input ratios of calcium salt, Li-Al-Si glass, and ceramics and the leaching process based on calcium salt roasting temperatures were compared. In water leaching, the leaching and recovery rates of Li based on different temperatures, times, solid-liquid ratios, and number of continuous leaching stages were compared. The results revealed that fireproof glass ceramics containing Li-Al-Si should be heat treated to change phase to beta-type spodumene. CaCO₃ salt should be added at a ratio of 6:1 with glass ceramics containing Li-Al-Si, and then leached 4 times or more to achieve a recovery efficiency of Li over 98% from a solution containing 200 mg/L of Li.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.148-169
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• 2023

Hayeob pigment is known as one of the traditional dark green pigments, but the color, raw material, and manufacturing method have not been clearly identified. However, comparing the analysis results of the particle shape and constituent minerals of Hayeob pigments revealed through pigment analysis studies of colored cultural properties such as Dancheong, Gwaebul, and paintings, Hayeob pigments appear to be the same as Dongrok pigments produced by salt corrosion. Therefore, in order to restore Hayeob pigment, the manufacturing method of Dongrok pigment was studied based on the records of old literature. The Dongrok pigment manufacturing method confirmed in the old literature records is a natural corrosion method in which copper powder and a caustic are mixed and then left in a humid condition to corrode. Based on this, artificial corrosion using a corrosion tester was adopted to corrode the copper powder more efficiently, and an appropriate mixing ratio was selected by analyzing the state of corrosion products according to the mixing ratio of the caustic agent. In addition, the manufacturing method of Dongrok pigment was established by adding a salt removal process to remove residual caustic agents and a purification process to increase chroma during pigment coloring. The prepared Dongrok pigments have a bluish green or green color, show an elliptical particle shape and a form in which small particles are aggregated, and a porous surface is observed. The main constituent elements are copper(Cu) and chlorine(Cl), and the main constituent mineral is identified as atacamite [Cu₂Cl(OH)₃]. As a result of an accelerated weathering test to evaluate the stability of the prepared Dongrok pigments, it was found that the greenness partially decreased and the yellowness significantly increased as deterioration progressed. Before deterioration, the Dongrok pigments had lower yellowness compared to the Hayeob pigments of the old Dancheong, but after deterioration, yellowness increased significantly, and it was found to have a similar chromaticity range as Dancheong's Hayeob pigments. As a result, the prepared Dongrok pigments were confirmed to be similar to Dancheong's Hayeob pigments in terms of color as well as particle shape and constituent minerals.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.123-130
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• 2023

Salmonella spp. are prevalent foodborne pathogens that are infective at relatively low concentrations, thus posing a serious health threat, especially to young children and the elderly. In several countries, the management and regulation of Salmonella spp. in food, including seafood, adhere to a negative detection standard. The risk of infection is particularly high when seafood is consumed raw, which underscores the importance of timely detection of pathogenic microorganisms, such as Salmonella. Accordingly, this study aimed to develop a combined pre-treatment and detection method that includes pre-culture and DNA extraction in order to detect five species of Salmonella at concentrations below 10 CFU/mL in seafood. The effectiveness of the proposed method was assessed in terms of the composition of the enrichment (pre-culture) medium, minimum incubation time, and minimum cell concentration for pathogen detection. Furthermore, a practical DNA extraction method capable of effectively handling high salt conditions was tested and found to be successful. Through polymerase chain reaction, Salmonella spp. Were detected and positively identified in shellfish samples at cell concentrations below 10 CFU/g. Thus, the proposed method, combining sample pre-treatment and cell culture with DNA extraction, was shown to be an effective strategy for detecting low cellular concentrations of harmful bacteria. The proposed methodology is suitable as an economical and practical in situ pre-treatment for effective detection of Salmonella spp. in seafood.

• Korean Journal of Breeding Science
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• v.51 no.4
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• pp.386-394
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• 2019

Rehmannia glutinosa, one of the major medicinal crops in Korea, can be classified into three types: fresh, dried and prepared Rehmannia root. In this study, the quality characteristics of prepared rehmannia root were evaluated using four different cultivars that are commonly used in the market. In making prepared rehmannia root, roots of Jihwang 1, Kokang, Togang, and Dagang were dried, soaked in rice wine, and steamed nine times. At each stage, physiochemical properties were analyzed, including yield, which is one of the most important industrial factors to consider. The yield was the highest in Togang at 23.61% and the lowest in Dagang at 21.16%. These yield values showed a highly negative correlation with the moisture content of roots. The fructose and glucose contents were increased during the 3^rd, 4^th and 5^th steaming but then decreased. The sucrose, raffinose, and stachyose content gradually decreased during the first three steaming and were not detected during the 4^th steaming. Additionally, the catalpol content was not detected after the 4^th steaming. On the contrary, the 5-hydroxymethylfurfural content was not detected in the raw root but increased during the steaming. Jihwang1 and Togang exceeded the 0.1% Korean Pharmacopoeia standard after the 5^th steaming, reaching it faster than did the other cultivars. Overall, Togang was the optimal cultivar considering the overall characteristics of its high yield and short steaming time. These results could provide useful information for the industrial use of prepared Rehmannia root based on the requirements and characteristics of each cultivar.

• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.483-488
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• 2023

The status of residual pesticides was investigated in four pepper seed oil samples and 36 pepper-flavored oil samples oil distributed on the market from August to December 2022. A total of 179 pesticides were monitored in 40 samples, and 14 pesticides were detected in 39 of the samples, with a detection range of 0.01-2.16 mg/kg. In chili seed oil, 10 pesticides were detected 27 times with a range of 0.11-2.16 mg/kg, and in pepper-flavored oil, 9 pesticides were detected 94 times with a range of 0.01-0.80 mg/kg. The most frequently detected pesticides were tebuconazole, ethion, and difenoconazole, with ethion being detected in large concentrations in products using Chinese raw materials. Ethion, an unregistered pesticide in the Republic of Korea, has not been detected in the Gyeonggi-do area in the past 10 years. It is thought that the detection of ethion can be utilized as an indicator of products made in China. Peppers are a representative agricultural product for which many pesticides are used, and if the pesticides transferred to pepper seeds are not removed, the probability of detecting various types of pesticides in pepper seed oil is very high. Therefore, continuous research is needed to ensure the safety of pepper seed oil.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.543-553
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• 2023

The current status of domestic a agalmatolite mines in South Korea was investigated with a view to establishing a stable supply of agalmatolite and managing its demand. Most mined agalmatolite deposits were formed through hydrothermal alteration of Mesozoic volcanic rocks. The physical characteristics of pyrophyllite, the main constituent mineral of agalmatolite, are as follows: specific gravity 2.65~2.90, hardness 1~2, density 1.60~1.80 g/cm³, refractoriness ≥29, and color white, gray, grayish white, grayish green, yellow, or yellowish green. Among the chemical components of domestic agalmatolite, SiO₂ and Al₂O₃ contents are respectively 58.2~67.2 and 23.1~28.8 wt.% for pyrophyllite, 49.2~72.6 and 16.5~31.0 wt.% for pyrophyllite + dickite, 45.1 and 23.3 wt.% for pyrophyllite + illite, 43.1~82.3 and 11.4~35.8 wt.% for illite, and 37.6~69.0 and 19.6~35.3 wt.% for dickite. Domestic agalmatolite mines are concentrated mainly in the southwest and southeast of the Korean Peninsula, with some occurring in the northeast. Twenty-one mines currently produce agalmatolite in South Korea, with reserves in the order of Jeonnam (45.6%) > Chungbuk (30.8%) > Gyeongnam (13.0%) > Gangwon (4.8%), and Gyeongbuk (4.8%). The top 10 agalmatolite-producing mines are in the order of the Central Resources Mine (37.9%) > Wando Mine (25.6%) > Naju Ceramic Mine (13.4%) > Cheongseok-Sajiwon Mine (5.4%) > Gyeongju Mine (5.0%) > Baekam Mine (5.0%) > Minkyung-Nohwado Mine (3.3%) > Bugok Mine (2.3%) > Jinhae Pylphin Mine (2.2%) > Bohae Mine. Agalmatolite has low thermal conductivity, thermal expansion, thermal deformation, and expansion coefficients, low bulk density, high heat and corrosion resistance, and high sterilization and insecticidal efficiency. Accordingly, it is used in fields such as refractory, ceramic, cement additive, sterilization, and insecticide manufacturing and in filling materials. Its scope of use is expanding to high-tech industries, such as water treatment ceramic membranes, diesel exhaust gas-reduction ceramic filters, glass fibers, and LCD panels.

• The Korean Journal of Food And Nutrition
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• v.36 no.6
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• pp.551-560
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• 2023

This study was performed to investigate antioxidant and anti-inflammatory activities of perilla(Perilla frutescens L.) seed, flower and leaf according to extraction condition. Perilla seed extracts(PSE), perilla flower extracts(PFE), perilla leaf extracts(PLE) was extracted by stirring extraction (STE, 25℃), shaking extraction (SHE, 80℃), and sonication assisted extraction(SAE, 25℃) with 94% ethanol, 60% ethanol and distilled water, followed by analysis of total polyphenol and flavonoid and testing radical scavenging activities. The highest total polyphenol content (5.47, 9.36, 38.58 mg gallic acid equivalent/g), total flavonoid content(5.77, 8.62, 46.44 mg catechin equivalent/g), ABTS(10.68, 19.46, 63.56 mg trolox equivalent/g) and DPPH(6.51, 7.69, 79.73 mg trolox equivalent/g) radical scavenging activity of PSE, PFE and PLE was observed in the HWE with 60% ethanol,. Among the three extraction method, SHE provided the best results for yield, polyphenol, flavonoid content of perilla seed, flower, leaf in comparison to STE or SAE. SHE with 60% ethanol of perilla seed, flower, leaf more effectively inhibited secretion of nitric oxide(NO) and pro-inflammatory cytokine in RAW 264.7 macrophage exposed to LPS compared to other extraction solvent and method. Therefore, these extracts obtained from perilla seed, flower, leaf could be used antioxidant and anti-inflammatory ingredients in the food industry.