• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.245-253
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• 2022

Objectives: This study was conducted to find out if the dietary iron intake of Koreans estimated by 2 different methods (iron content sources) using the food intake data from the Korea National Health and Nutrition Examination Survey (KNHANES) are comparable. One method was based on the KNHANES's Food & Nutrient Database (FND) derived mainly from the Korean Food Composition Table and the other used the iron content (IC) of food samples processed in the Korean Total Diet Study (KTDS). Methods: Dietary intake data from the 2013-2016 KNHANES was used to select representative foods (RFs) in KTDS for iron analysis. Selection of the RFs and cooking methods for each RF (RF × cooking method pair) was performed according to the 'Guidebook for Korean Total Diet Studies' and resulted in a total of 132 RFs and 224 'RF × cooking method' pairs. RFs were collected in 9 metropolitan cities nationwide once or twice (for those with seasonality) in 2018 and made into 6 composites each, based on the origin and season prior to cooking. Then, the RF composites prepared to a 'table ready' state for KTDS were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Dietary iron intake of the Korean population was estimated using only RFs' intake data based on the 2 sources of iron content, namely FND-KNHANES and IC-KTDS. Results: RFs in KTDS covered 92.0% of total food intake of Koreans in the 2016-2018 KNHANES. Mean iron intake of Koreans was 7.77 mg/person/day by IC-KTDS vs 9.73 mg/person/day by FND-KNHANES. The major food groups contributing to iron intake were meats (21.7%), vegetables (20.5%), and grains & cereals (13.4%) as per IC-KTDS. On the other hand, the latter source (FND-KNHANES) resulted in a very different profile: grains & cereals (31.1%), vegetables (16.8%), and meats (15.3%). While the top iron source was beef, accounting for 8.6% in the former, it was polished rice (19.2%) in the latter. There was a 10-fold difference in the iron content of polished rice between 2 sources that iron intakes excluding the contribution by polished rice resulted in very similar values: 7.58 mg/person/day by IC-KTDS and 7.86 mg/person/day by FND-KNHANES. Conclusions: This study revealed that the dietary iron intake estimated by 2 different methods were quite comparable, excluding one RF, namely polished rice. KTDS was thus proven to be a useful tool in estimating a 'closer-to-real' dietary intake of nutrients for Koreans and further research on various nutrients is warranted.

• Journal of the Korean Wood Science and Technology
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• v.32 no.5
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• pp.29-38
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• 2004

In this study, we investigated the thermal properties of corn-starch filled polybutylene succinate-adipate (PBS-AD) bio-composites. Thermal analysis (TA) is used to describe the analytical method for measuring the chemical property and weight loss of composite materials as a function of temperature. The thermal stability of corn-starch was lower than that of pure PBS-AD. As corn-starch loading increased, the thermal stability and degradation temperature of the bio-composites decreased and the ash content increased. It can be seen that the degree of compatibility and interfacial adhesion of the bio-composites decreased because of the increasing mixing ratio of the corn-starch. As the content of corn-starch increased, there was no significant change in the glass transition temperature (T_g) and the melting temperature (T_m) for the bio-composites. The storage modulus (E') and loss modulus (E") of the corn-starch flour filled PBS-AD bio-composites were higher than those of PBS-AD, because of the incorporation of corn-starch increased the stiffness of the bio-composites. At higher temperatures, the decreased storage modulus (E') of bio-composites was due to the increased polymer chain mobility of the matrix polymer. From these results, we can expect that corn-starch has potential as a reinforcing filler for bio-composites. Furthermore, we recommend using a coupling agent to improve the interfacial adhesion between corn-starch and biodegradable polymer.

• Journal of Pharmacopuncture
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• v.25 no.3
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• pp.242-249
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• 2022

Objectives: The aim of this work is to evaluate the in vitro antioxidant, hypoglycemic, and antiobesity effects of Euphorbia resinifera extracts and investigate the phenolic constituents and the toxicity of these extracts. Methods: Phytochemical screening was performed to detect polyphenols and flavonoids. Antioxidant activity was evaluated by four methods (DPPH, ABTS, H₂O₂, and xanthine oxidase inhibition). The hypoglycemic effect was determined by the inhibition of α-amylase and α-glucosidase enzymes in vitro and via a starch tolerance study in normal rats. The antiobesity effect was estimated by in vitro inhibition of lipase. Results: Phytochemical screening revealed that the ethanolic extract was rich in polyphenols (99 ± 0.56 mg GEA/g extract) and tannins (55.22 ± 0.17 mg RE/g extract). Moreover, this extract showed higher antioxidant activity in different tests: the DPPH assay (IC₅₀ = 53.81 ± 1.83 ㎍/mL), ABTS assay (111.4 ± 2.64 mg TE/g extract), H₂O₂ (IC₅₀ = 98.15 ± 0.68 ㎍/mL), and xanthine oxidase (IC₅₀ = 10.26 ± 0.6 ㎍/mL). With respect to hypoglycemic effect, the aqueous and ethanolic extracts showed IC₅₀ values of 119.7 ± 2.15 ㎍/mL and 102 ± 3.63 ㎍/mL for α-amylase and 121.4 ± 1.88 and 56.6 ± 1.12 ㎍/mL for α-glucosidase, respectively, and the extracts lowered blood glucose levels in normal starch-loaded rats. Additionally, lipase inhibition was observed with aqueous (IC₅₀ = 25.3 ± 1.53 ㎍/mL) and ethanolic (IC₅₀ = 13.7 ± 3.03 ㎍/mL) extracts. Conclusion: These findings show the antioxidant, hypoglycemic, and hyperlipidemic effects of E. resinifera extracts, which should be investigated further to validate their medicinal uses and their pharmaceutical applications.

• Journal of Naturopathy
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• v.11 no.2
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• pp.100-108
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• 2022

Background: It has been reported that various substances exist in wild Conyza canadensis, but I think that the overall compositional analysis is still insufficient. Purposes: This study was to set extraction conditions and search for various nutritional components in the wild C. canadensis. Methods: Various extracts were extracted and analyzed using different analytical instruments to suggest and study the conditions for component analysis. Results: As for the general nutritional components of C. canadensis leaf extract, carbohydrates were 46.4%, crude protein 26.5%, moisture 16.3%, raw meal 9.5%, and natural fat 1.2%. The dietary fiber content was 30.76%. Free fructose, glucose, sucrose, and maltose were separated, and the amount of fructose was as high as 4,144.2 mg/100 g. In addition, we found 64.87 mg/g of K, 4.09 mg/g of P, 1.77 mg/g of Mg, and 0.16 mg/g of disodium in the extracts. A total of 20 fatty acids have appeared. In addition, unsaturated fatty acids (octadecenoic acid, octadecadienoic acid, and linolenic acid) were detected. Linolenic acid was high at 54.1%. The saturated fatty acid content was 0.39 g/100 g, and the trans fatty acid content was 0.01 g/100 g. No cholesterol was found in the plant. Riboflavin was at 0.4 mg/100 g, with six essential amino acids and 24 amino acids. Conclusions: As a result of the primary research on the plant, various nutritional and functional ingredients exist in the extract, and natural healing uses are available.

• Journal of Korea Port Economic Association
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• v.37 no.2
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• pp.133-152
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• 2021

The purpose of this study is to investigate the factors affecting the wages of workers in the logistics industry and to identify the current status of employment and wages in the logistics industry. Based on this, it sought to find analytical factors on the wages of workers in the logistics industry and explain their impact on the wage gap. The analysis data were interpreted as cross-sectional data from the National Statistical Office over the past decade and the analysis data were set to three types. The results of the analysis could be explained that three factors understood as wage discrimination factors that do not directly affect productivity generally have a significant impact on wage gap among workers in the logistics industry. Air and water transport industries received high salaries due to factors in the industry. The very low-paid sector for that was the land transport industry, and the courier industry as a detailed sector. Due to the nature of job factors, technicians and assistants received lower wages than other jobs. Due to the nature of the company's size factors, companies with 51 or more employees received higher wages than companies with 50 or less employees. In testing the effectiveness of multiple sources of ANOVA, the common 'industry × enterprise size' variable was explained to have a significant effect on gaps in wages for workers in the logistics industry. In addition, the comparison of the influence of the main effects of the three factors put into the analysis model shows that the industry has the most influence.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.165-175
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• 2021

Purpose: The purpose of this study is to quantitatively present the carbon dioxide(CO₂) emission change according to the application of autonomous driving technology at the network level for waste vehicles in the metropolitan area. Method: The target year was set to 2030, and the analysis method estimated the carbon dioxide (CO₂) emissions for each road link through user equilibrium assignment when unapplied scenario. The application scenario performed traffic assignment using route data on the premise that the group was running in accordance with the application of autonomous driving technology to waste vehicles. In addition, the other means estimated the carbon dioxide emissions through user balance allocation by reflecting the results of the waste vehicle allocation. Result: As a result of the analysis, carbon dioxide(CO₂) emissions were found to be reduced by about 56.9ton/day from the national network level, and the Seoul metropolitan area was analyzed to be reduced by about 54.7ton/day. Conclusion: This study quantitatively presented environmental impacts among various social effects that autonomous driving technology will bring, and in the future, development of various analytical methodologies and related studies should be continuously conducted.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.189-199
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• 2023

This study aimed to identify the development direction of Arduino-based boards relating to artificial intelligence based on social awareness identified using big data analytical methods. For the purpose, big data were extracted through the Textom website, focusing on keywords that included 'Arduino + artificial intelligence' and 'Arduino + AI', and these data were refined and analyzed using the Textom website and the UNICET program. In this study, big data analyses, including frequency analysis, TF-IDF analysis, Degree Centrality analysis, N-gram analysis, and CONCOR analysis, were performed. The analyses' results confirmed that keywords relating to education and coding education, keywords relating to making and experience based on Arduino, and keywords relating to programs were the main keywords used in Arduino- and artificial intelligence-related Internet documents, and clusters were formed based on these keywords confirmed. The social awareness of Arduino and artificial intelligence was evaluated, and the direction of board development was identified based on this social awareness. This study is meaningful in that it identified various factors of board development based on the general public's social awareness, which was evaluated using a big data analysis method. This study may serve as a point of reference for future researchers or developers wishing to understand user needs using big data analysis methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.261-273
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• 2022

This study aims to predict the land use demand of Seongnam-city using system dynamics and to simulate the effect of changes in family structure and land use density adjustment policy on land use demand. This study attempted to construct causal loop diagrams and an analysis model. The changes in land use demand over time were predicted through simulation results. As a result of the analysis, as of 2035, an additional supply of 2.08 km² for residential land and 1.36 km² for commercial land is required. Additionally, the current supply area of industrial land can meet the demand. Three policy experiments were conducted by changing the variable values in the basic model. In the first policy experiment, it was found that when the number of household members decreased sharply compared to the basic model, up to 7.99 km² of additional residential land were required. In the second policy experiment, if the apartment floor area ratio was raised from 200% to 300%, it was possible to meet the demand for residential land with the current supply area of Seongnam-city. In the third policy experiment, it was found that even if the average number of floors in the commercial area was raised from four to five and the building-to-land ratio in the commercial area was raised from 80% to 85%, the demand for commercial land exceeded the supply area of the commercial area in Seongnam-city. This study is meaningful in that it proposes a new analytical model for land use demand prediction using system dynamics, and empirically analyzes the model by applying the actual urban planning status and statistics of Seongnam-city.

• Journal of Conservation Science
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• v.38 no.2
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• pp.117-123
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• 2022

In this study, investigated the possibility of quantitatively and qualitatively analyzing Korean ancient glasses via Raman Spectroscopy. We subjected four categories of Korean traditional glasses, namely, lead-BaO, lead, potash, and soda glasses (3, 3, 10, and 10 pieces, respectively), to this analytical technique. The results showed significant differences between the stretching and bending Raman vibration regions corresponding to these different Korean ancient glass types. Specifically, the stretching vibration regions corresponding to lead-BaO and lead glasses showed peaks at 1040 and 1000 cm^-1, respectively; the stretching vibration region of normal glass appears at 1100 cm^-1. The bending vibration regions corresponding to potash and soda glass showed Raman peaks at 490 and 560 cm^-1, respectively. Furthermore, the Raman spectra of the lead and lead-BaO glasses showed red shifts, which depended on the amount of PbO present. Thus, our findings highlighted the possibility of quantitatively determining the amount of PbO, a major component of lead glasses, via Raman Spectroscopy.

• Journal of Environmental Impact Assessment
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• v.31 no.1
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• pp.47-62
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• 2022

Wind power has been rapidly growing over last decade in the world as well as in South Korea as a feasible renewable energy source. Providing sustainable energy to all while securing environmental sustainability requires evidence based policy making and innovative solutions. Through analysis of 58 cases of South Korean Environmental Impact Assessment (EIA) Report, this paper seeks to identify answers to the following two questions. What are the key characteristics for inland windfarm? Is there a way of measuring environmental sustainability to compare each location to reduce negative environmental impact? Variables related to environmental sustainability of each windfarm case were collected from EIA report and the factor analysis of environmental variables was conducted to calculate the weight for each variable to build environmental sustainability index (ESI) to provide as evidence-based tools for decision making on the location of inland windfarm. 58 cases were categorized as three types 1) Mountain type 2) Ranch Type and 3) Coastal Type depending on their height and degree of naturalness. For analytical research, first, it was successfully calculated environmental sustainability of each windfarm case ranging from 1.04 (#33, Ranch type) to -1.44 (#55, Mountain type). Second, the analysis results showed that ranch type is most environmentally sustainable (Average ESI = 0.4551), followed by coastal type (Ave ESI = 0.3712) and lastly mountain type (Average ESI = -0.3457). These findings are consistent with the previous researches on inland windfarms and provides substantive policy implication on the renewable energy policies.