• KOREAN JOURNAL OF CROP SCIENCE
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• 제62권4호
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• pp.333-345
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• 2017

The potato tuber is known as a rich source of essential nutrients, used throughout the world. Although potato-breeding programs share some priorities, the major objective is to increase the genetic potential for yield through breeding or to eliminate hazards that reduce yield. Glycoalkaloids, which are considered a serious hazard to human health, accumulate naturally in potatoes during growth, harvesting, transportation, and storage. Here, we used the AMMI (additive main effects and multiplicative interaction) and GGE (Genotype main effect and genotype by environment interaction) biplot model, to evaluate tuber yield stability and glycoalkaloid content in six potato cultivars across three locations during 2012/2013. The environment on tuber yield had the greatest effect and accounted for 33.0% of the total sum squares; genotypes accounted for 3.8% and $G{\times}E$ interaction accounted for 11.1% which is the nest highest contribution. Conversely, the genotype on glycoalkaloid had the greatest effect and accounted for 82.4% of the total sum squares), whereas environment and $G{\times}E$ effects on this trait accounted for only 0.4% and 3.7%, respectively. Furthermore, potato genotype 'Superior', which covers most of the cultivated area, exhibited high yield performance with stability. 'Goun', which showed lower glycoalkaloid content, was the most suitable and desirable genotype. Results showed that, while tuber yield was more affected by the environment, glycoalkaloid content was more dependent on genotype. Further, the use of the AMMI and GGE biplot model generated more interactive visuals, facilitated the identification of superior genotypes, and suggested decisions on a variety of recommendations for specific environments.

• Microbiology and Biotechnology Letters
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• 제40권1호
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• pp.1-9
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• 2012

This study's aim was to isolate microorganisms producing agarase with a high activity, with possible applications in improving the performance of the pretreatment processes for bioethanol production. Marine algaes were collected from the south coast of Korea, from which three kinds of microorganisms were isolated. After a 4-day culture of these strains at $25^{\circ}C$, crude enzymes were obtained from culture supernatant or cell-free extract by ammonium sulfate precipitation and membrane dialysis. Agarase activity was observed in these crude enzymes. Notably higher specific activity was observed in the crude enzyme obtained from the culture supernatant rather than that from the cell-free extract. This indicates that a secreted enzyme has a much greater activity than a cellular enzyme. Crude enzymes from the GNUM08122 strain were inferred to have ${\alpha}$-agarase activity because release of p-nitrophenol was observed, possibly due to the cleavage of p-nitrophenyl-${\alpha}$-D-galactopyranoside. The 16S rRNA sequence of GNUM08122 showed a close relationship to Pseudoalteromonas issachenkonii KMM 3549 (99.8%) and Pseudoalteromonas tetraodonis IMA 14160 (99.7%), which led us to assign it to the genus Pseudoalteromonas. Biochemical and physiological study revealed that this strain can grow well at $40^{\circ}C$ under a wide range of pH (pH 4~8) in high-salt conditions (10% NaCl).

• Journal of the Korean Association of Geographic Information Studies
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• 제22권3호
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

• Journal of Intelligence and Information Systems
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• 제25권3호
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• The Journal of the Korean Institute of Forest Recreation
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• 제22권4호
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• pp.71-81
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• 2018

It is necessary to build a quality-enhancing forest leisure sports facility according to values that value life quality, national forest policy. Vita Parcours (fitness trails) is found to be the activities highly convenient, so their introduction and promotion in Korea should be highly considered. field survey was necessary to explore the possibility of installing Vita Parcours. Several sites were selected, such as Asean recreational forest, Unaksan recreational forest, Yumyeongsan recreational forest, Saneum recreational forest, Jungmisan recreational forest and National center for forest therapy. At these locations, we explored the current status of forest facilities and forest trails. A total number of 31 exercise facilities has been identified and surveyed, some of which are located on the trails (2), alongside the trail (9), alongside trail boundaries (2) or represent facilities suitable for both outdoor and indoor exercise within the forest (18), all of whom provide location for 44 different exercise routines (flexibility exercises (23), endurance (12) and strength exercises (9)). Field work also included identification of forests paths, the total number of whom was 34 paths - 30 identified as trails, 2 as hiking trails, 1 as a forest path for relaxation and healing and 1 as an exploratory path. Regarding the structure and shape of these trails, 32 was straight in shape and only 2 designed as a circular forest trails. Average length of these trails was 652.2m with the highest and the lowest point altitude difference of 60m, on average. Saneum recreational forest provide the most suitable site/environment for Vita Parcours and as a result of this, Saneum recreational forest is proposed as a location to support the endeavors in promotion of these valuable forest fitness trails. Among the forest paths at this site, a forest path which has a length of 1.84km and 73.0m the highest and the lowest point altitude difference was selected as the most suitable, and may be equipped with necessary stations for exercise or obstacles. In addition, if these trails are to be introduced and welcomed by its users, we must assure that they are properly maintained.

• Journal of the Society of Disaster Information
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• 제18권1호
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• pp.182-193
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• 2022

Purpose: By measuring and evaluating the risk of biodiesel through non-volatile residue (NVR) and flash point and explosion limit measurement at a specific temperature according to ASTM test standards, the risk of chemical fire causative substances is identified and a universal evaluation method By derivation and securing the risk-related data of the material, it can be used for the identification and analysis of the cause of the fire, and it can be applied to the risk assessment of other chemical substances Method: In order to measure the risk of biodiesel, it was measured using the non-volatile residue(NVR) measurement method, which measures how much flammable liquid is generated at a specific temperature. Heating was tested by applying KS M 5000: 2009 Test Method 4111. In addition, the flash point was measured using the method specified in ASTM E659-782005, and the energy supply method was measured using the constant temperature method. In addition, the explosion limit measurement was conducted in accordance with ASTM E 681-04 「Standard test method for concentration limits of flammability of chemicals(Vapors and gases)」 test standard. Result: As a result of checking the amount of combustible liquid by the non-volatile residue (NVR)measurement method, the non-volatile residue(NVR) of general diesel when left at 105±2℃ for 3 hours was about 30% (70% of volatile matter) and about 4% of biodiesel. In addition, similar results were obtained for the non-volatile residue(NVR)heating temperature of 150±2℃, 3 hours and 200±2℃ for 1 hour, and white smoke was generated at 200℃ or higher. In addition, similar values were obtained as a result of experimentally checking the explosion (combustion) limits of general diesel, general diesel containing 20% biodiesel, and 100% biodiesel. Therefore, it was confirmed that the flammability risk did not significantly affect the explosion risk. Conclusion: The results of this study suggested the risk judgment criteria for mixtures through experimental research on flammable mixtures for the purpose of securing the effectiveness, reliability, and reproducibility of the details of the criteria for determining dangerous substances in the existing Dangerous Materials Safety Management Act. It will be possible to provide reference data for the judgment criteria for flammable liquids that are regulated in the field. In addition, if the know-how for each test method is accumulated through this study, it is expected that it will be used as basic data in the research on risk assessment of dangerous substances and as a basis for research on the determination of dangerous substances.

• Analytical Science and Technology
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• 제34권6호
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• pp.259-266
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• 2021

Cannabis (Marijuana) is one of the most widely used drugs in the world, and its distribution has been controlled in South Korea since 1976. Identification of 11-nor-Δ⁹-carboxy-tetrahydrocannabinol (THCCOOH) in urine can provide important proof of cannabis use, and it is considered scientific evidence in the forensic field. In this study, we describe a simultaneous quantitative method for identifying THCCOOH and THCCOOH-glucuronide in urine, using simple liquid-liquid extraction (LLE), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). THCCOOH-D₃ and THCCOOH-glucuronide-D₃ were used as internal standards. Validation results of the matrix effect, as well as recovery, linearity, precision, accuracy, process efficiency, and stability were all satisfactory. No carryover, endogenous or exogenous interferences were observed. The limit of detection (LOD) of THCCOOH and THCCOOH-glucuronide were 0.3 and 0.2 ng/mL, respectively. The developed method was applied to 28 authentic human urine samples that tested positive in immunoassay screening and gas chromatography/mass spectrometry (GC/MS) tests. The ranges of concentrations of THCCOOH and THCCOOH-glucuronide in the samples were less than LOQ~266.90 ng/mL and 6.43~2133.03 ng/mL, respectively. The concentrations of THCCOOH-glucuronide were higher than those of THCCOOH in all samples. This method can be effectively and successfully applied for the confirmation of cannabinoid use in human urine samples in the forensic field.

• Conservation Science in Museum
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• 제29권
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• pp.133-152
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• 2023

This study references preceding studies to examine the history of paint application techniques using various paints in the past, with the aim to contribute to the long-term preservation of large military cultural heritage assets situated outdoors. To this end, the study compared the findings of preceding research with the findings of an analysis conducted on a H-13 helicopter housed at the War Memorial of Korea. Upon collecting and analyzing samples from three grounded WWII aircraft from above-ground by preceding studies, it was confirmed from each sample that the various chemical properties of chrome ensured the effectiveness of the protective coating. The compound was first tested as a corrosion-inhibiting pigment in the early 1940s and proved its excellent moisture-resistant properties over the course of 80 years, despite the deterioration of the paint layer and long-term exposure to the natural environment. For this reason, it has been widely used as a corrosion inhibitor for aluminum alloys in the aviation industry. In other word, the most widely-used material for preventing corrosion was an organic primer containing chromate. In this study, based on the paint analysis of a H-13 helicopter operated in the Korean War, it was shown that the second layer, consisting of the primer, contains chromium oxide (Cr₂O₃). In addition, it was estimated that red lead tetraoxide (Pb₃O₄) was used for the vehicle. Analysis results and data from previous studies can help to confirm the continued effectiveness of corrosion prevention function provided by chromate. Meanwhile, the result of infrared spectroscopy analysis confirmed the use of alkyd resin. In the future, comparisons with a more diverse range of artifacts will allow the identification of changes in the manufacturing technology of paints used to protect alloys from corrosion.

• Journal of Venture Innovation
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• 제6권2호
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• pp.41-65
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• 2023

This study was conducted to empirically analyse the factors that influence SMEs' intention to adopt ESG. For this purpose, we first derived the variables of usefulness of ESG and ease of adoption. In addition, we adopted CEO's will because of the importance of CEO's role in decision-making in SMEs. In addition, we added customer's request, government support, and credit evaluation reflection as institutional factors for ESG management. To examine the mediating role of attitudes and employees' innovation resistance in these relationships and how they affect ESG adoption, we set up a research model. These factors were used in the empirical analysis with 368 valid responses from the survey. Hierarchical regression analysis method using SPSS 24.0 was used for statistical analysis, and Process Macro 4.0 based on SPSS 24 was used for mediation and moderation effects. The results of the empirical analysis of this study showed that the usefulness of ESG adoption, ease of adoption, CEO's will, customer's request, government support, and credit evaluation reflection all had a positive and significant effect on the intention to adopt ESG management. In particular, among the variables affecting ESG adoption, CEO's will was found to be the most influential. Attitudes were also found to play a mediating role between the influencing factors and intention to adopt ESG management, as well as the mediating effect of employee' innovation resistance. The academic implications of this study include the identification and empirical testing of each of the influencing variables of ESG management adoption in the scarce literature on ESG in SMEs, and the prioritisation of the influence of these factors on adoption intention, which can be used to promote the adoption of ESG management. In terms of practical implications, it is important for SMEs to have a win-win relationship with large corporations, an ecosystem such as government support, in order to improve CEO awareness and motivate the CEO's will, and for smooth introduction of ESG management, it is necessary to find ways to reduce resistance through sufficient communication with organizational members to make them aware of the need.

• Korean Journal of Heritage: History & Science
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• 제56권3호
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• pp.158-171
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• 2023

Pottery filled with organic materials was excavated from the G-2 building site of Yongjangseong Fortress, Jingo, a relic of the Goryeo Dynasty. In this study, the characteristics of organic material were confirmed by a scientific analysis of organic material in pottery found at the palace in Yongjangseong, Jindo. In addition, it was intended to review the analysis method to identify the natural resin and to secure characteristic components(biomarkers) for each natural resin and use them as basic data in the future. The organic materials in the pottery were analyzed using attenuated total reflectance Fourier-transformed infrared spectroscopy(ATR-FTIR) and gas chromatography mass spectrometry(GC-MS). The infrared spectral characteristics were estimated to be natural resin, and biomarkers of organic materials were identified as sesquiterpene-based compounds(C₁₅H₂₄, MW 204) and derivatives. The lacquer(T.vemicifluum) is composed mainly of alkenes, alkanes, and catechol. Pine resin(P.densiflora), on the other hand, is primarily composed of diterpenoid(abietic acid, pimaric acid) and Whangchil(yellow lacquer) is identified to have sesquiterpenes(such as selinene, muurolene, calamenene) as its main components. So, the organic material in the pottery can be identified as Whangchil by comparing their compounds with modern resin materials from Dendropanax. morbifera that correspond with the results. Whangchil, which is exuded from the Dendropanax. morbifera, has been used as a natural coating materials since ancient times, and it has been confirmed that the characteristic components are well preserved even 700 years later. It can be assumed that the interior Whangchil was stored not for use as a coating, but rather for ritual purposes when the building was constructed, because the pottery was found near the cornerstone. Furthermore, based on simplified sample preparation using pyrolysis-gas chromatography mass spectrometry(Py-GC-MS), the thermal decomposition products were found to be similar to the characteristic components, suggesting that this method can be applied to the identification of natural resins used in historic artifacts.