• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.423-432
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• 2021

This study developed a scale to measure college students' perceived stress levels for adverse life events that may occur in their daily lives and confirmed its validity and reliability. The scale was developed in accordance with DeVellis' scale development guidelines. Data were collected from 1,242 students of a local university in 2020. The collected samples were randomly separated into two groups (A, B). Group A (N=620) was tested for an initial examination of the performance, exploratory factor analysis, multitrait-multimethod matrix, criterion-related validity, and reliability of each item; and verified with group B (N=622) for confirmatory factor analysis and reliability re-test. As a result, the final scale of 33 items and eight factors were developed. The KMO values were 0.92, and Bartlett's spherical test was significant (χ²=12532.42, p<.001); the number of factors with initial eigenvalues of 1.0 or higher was eight; the cumulative factor loadings of 71.5% and the commonality of each item was 0.56 or higher. The reliability of the scale was Cronbach's alpha 0.94; sub-factors' Cronbach's alpha was 0.78 to 0.90. Therefore, these findings suggest that the scale developed in this study would be useful for measuring the stress levels of daily life for college students.

• Animal Bioscience
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• v.34 no.6
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• pp.957-966
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• 2021

Objective: Ovarian follicular development, which dependent on the proliferation and differentiation of granulosa cells (GCs), is a complex biological process in which miRNA plays an important role. Our previous study showed that miR-458b-5p is associated with ovarian follicular development in chicken. The detailed function and molecular mechanism of miR-458b-5p in GCs is unclear. Methods: The luciferase reporter assay was used to verify the targeting relationship between miR-458b-5p and catenin beta-1 (CTNNB1), which is an important transcriptional regulatory factor of the Wnt/β-catenin pathway. The cell counting kit-8 (CCK-8) assay, flow cytometry with propidium iodide (PI) and annexin V-fluorescein isothiocyanate (FITC) labeling were applied to explore the effect of miR-458b-5p on proliferation, cell cycle and apoptosis of chicken GCs. Quantitative real-time polymerase chain reaction and Western blot were used to detect the mRNA and protein expression levels. Results: We demonstrated that the expression of miR-458b-5p and CTNNB1 showed the opposite relationship in GCs and theca cells of hierarchical follicles. The luciferase reporter assay confirmed that CTNNB1 is the direct target of miR-458b-5p. Using CCK-8 assay and flow cytometry with PI and Annexin V-FITC labeling, we observed that transfection with the miR-458b-5p mimics significantly reduced proliferation and has no effects on apoptosis of chicken GCs. In addition, miR-458b-5p decreased the mRNA and protein expression of CD44 molecule and matrix metallopeptidase 7, which are the downstream effectors of CTNNB1 in Wnt/β-Catenin pathway and play functional roles in cell proliferation. Conclusion: Taken together, the data indicate that miR-458b-5p regulates ovarian GCs proliferation through Wnt/β-catenin signaling pathway by targeting CTNNB1, suggesting that miR-458b-5p and its target gene CTNNB1 may potentially play a role in chicken ovarian follicular development.

• Journal of dental hygiene science
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• v.18 no.6
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• pp.367-373
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• 2018

The consumption of beverages among children is rising. The purpose of this study was to examine the effect of kid's drink on dental resin-based pit and fissure sealant. Pororo, I-kicker, Sunkist kids were included in the experimental groups, and Samdasu was included in the control group. A conventional dental sealant material ($Clinpro^{TM}Sealant^{(R)}$) was selected for this study. Resin specimens (8 mm in diameter and 1 mm in thickness) were prepared according to manufacturers' instructions and the initial roughness (Ra) was then measured. The pH of all the four groups was measured using a pH meter. The specimens were individually immersed in 5 ml of the experimental solutions and stored at $37^{\circ}C$ for 72 hours. Following this, the surface roughness of the resin specimens was measured by Surftest. The concentration of residual monomer released was determined by high performance liquid chromatography (HPLC). The surface morphology of the resin specimen was evaluated before and after storage by scanning electron microscopy (SEM). Data were statistically analyzed using Kruskal-Wallis and Duncan's test. The results showed that all the children's beverages examined in this study contained citric acid. The pH of I-kicker was the lowest ($3.03{\pm}0.01$), followed by that of Sunkist kids ($3.26{\pm}0.02$) and Pororo ($3.47{\pm}0.02$). We observed an increase in the surface roughness of resin specimens after 72 h of immersion in all the beverages tested (p<0.05). There was matrix degradation after immersion, visualized on SEM image, in all the beverage groups. Bisphenol-A-glycidyl methacrylate was not detected after 72 hours, but triethylene glycol dimethacrylate levels were increased in all the beverages tested during the 72 hours by HPLC. These results suggest that intake of beverages containing acid can cause degradation of the resin-based pit and fissure sealants in children.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.103-112
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• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.6
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• pp.55-69
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• 2018

As disaster risk and climate change volatility increase, there are more efforts to adapt to disasters such as forest fires, floods, and landslides. Most of the research, however, is about influence of human activities on disaster and there is few research on disaster adaptation for species. Previous studies focusing on biodiversity in selecting conservation areas have not addressed threats of disaster in the habitats for species. The natural disasters sometimes play role of drivers of ecological successions in the long run, but they might cause serious problems for the conservation of vulnerable species which are endangered. The purpose of this study is to determine whether soil loss (SL) is effective in selecting habitat management areas for amphibians and reptiles. RUSLE model was used to calculate soil loss (SL) and the distribution of each species (SD) was computed with MaxEnt model to find out the biodiversity index. In order to select the habitat management area, we estimated the different results depending if value of soil loss was applied or not by using MARXAN, a conservation priority selection tool. With using MARXAN, conservation goals can be achieved according to the scenario objectives, and the study has been made to meet the minimum habitat area. Finally, the results are expressed in two; 1) the result of soil loss and biodiversity with MATRIX method and 2) the result of regional difference calculated with MARXAN conservation prioritization considering soil loss. The first result indicates that the area with high soil loss and low species diversity have lower conservation values and thus can be managed as natural disturbances. In the area where soil loss is high and species diversity is also high, it becomes where a disaster mitigation action should be taken for the species. According to the conservation priorities of the second result, higher effectiveness of conservation was obtained with fewer area when it considered SL in addition to SD, compared to when considered only biodiversity. When the SL was not taken into consideration, forest area with high distribution of species were important, but when SL considered, the agricultural area or downstream of the river were represented to be a major part of habitats. If more species data or disaster parameters other than soil loss are added as variables later, it could contribute as a reference material for decision-making to achieve various purposes.

• Korean Journal of Environmental Agriculture
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• v.38 no.1
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• pp.34-37
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• 2019

BACKGROUND: A region can be divided into agroclimatic zones based on homogeneity in weather variables that have greatest influence on crop growth and yield. The agro-climatic zone has been used to identify yield variability and limiting factors for crop growth. This study was conducted to classify agro-climatic zones in the state of Mato Grosso in Brazil for predicting crop productivity and assessing crop suitability etc. METHODS AND RESULTS: For agro-climatic zonation, monthly mean temperature, precipitation, and solar radiation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1980 and 2010 were collected. Altitude and vegetation fraction of Brazil from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were temperature in the hottest month ($30^{\circ}C$), annual precipitation (600 mm and 1000 mm), and altitude (200 m and 500 m). The state of Mato Gross in Brazil was divided into 9 agro-climatic zones according to these criteria by using matrix classification method. CONCLUSION: The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield in the state of Mato Grosso in Brazil.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.1-14
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• 2021

Excessive development and urbanization have destroyed animal, plant, habitats and reduced biodiversity. In order to preserve species diversity, habitat prediction studies are have been conducted at home and overseas using various modeling techniques. This study was conducted to suggest optimal habitat modeling research by comparing HSI and MaxEnt, which are widely used among habitat modeling techniques. The study was targeted on the endangered species of Prionailurus bengalensis in nearby areas (5460.35km2) including Cheonan City, and the same data were used for analysis to compare those models. According to the HSI analysis, Prionailurus bengalensis's habitat probability was 74.65% for less than 0.5 and 25.34% for more than 0.5 and the top 30% were forest (99.07%). MaxEnt's analysis showed that 56.22% of those below 0.5 and 43.79% of those above 0.5 were found to have a high explanatory power of 78.3% of AUC. The Paired Wilcoxn test, which evaluated the significance of thoes models, confirmed that the mean difference between the two models was statistically significant (p<0.05). Analysis of the differences in the results of those models using the matrix table shows that score 24.43% HSI and MaxEnt was accordance,12.44% of the 0.0 to 0.2 section, 7.22% of the 0.2 to 0.4 section, 2.73% of the 0.4 to 0.6 section, 1.96% of the 0.6 to 0.8, and 0.08% of the 0.9 to 1.0. To verify where the score difference appears, the result values of those models were reset to values from 1 to 5 and overlaid. Overlapping analysis resulted in 30.26% of the Strongly agree values, 56.77% of the agree values, and 11.92% of the Disagree values. The places where the difference in scores occurs were analyzed in the order of forest (45.23%), agricultural land (34.57%), and urbanization area (7.65%). This confirmed that the analysis of the same target species within the same target site also has differences in forecasts depending on the modelling method. Therefore, a novel analysis method combining the advantages of each modeling in habitat prediction studies should be developed, and future study may be used to select Prionailurus bengalensis and species-protected areas and species protection areas in the future. Further research is judged to require higher accuracy studies through the use of various modeling techniques and on-site verification.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• Analytical Science and Technology
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• v.34 no.3
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• pp.134-141
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• 2021

In this study, the fatty acid (FA) composition of commercial sesame oils (n = 62) was investigated using gas chromatography with flame ionization detector (GC-FID). Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA), were applied to the chromatographic data of the FAs to discriminate the geographical origin of sesame oils. A statistically significant difference was observed in the content of C16:0, C18:0, C18:1, and C18:2 between domestic and imported sesame oils. A satisfactory recovery rate of 82.8-100.2 % was achieved for C16:0, C18:0, C18:1, C18:2, and C18:3. The correlation of C16:0, C18:1, and C18:2 in domestic sesame oils showed opposite trends compared to imported oils. The PCA plot demonstrated that sesame oils were clustered in distinct groups according to their origin. LDA was used to predict sesame oil samples in one of the two groups. C16:0 (Wilks λ = 0.361) and C18:1 (Wilks λ = 0.637) demonstrated the highest discriminant power for classifying the origin of the samples. The correct prediction rates were 88.9 % and 100 % for the domestic and imported samples, respectively. Further, 60 of the 62 sesame oil samples (96.8 %) were correctly classified, indicating that this approach can be used as a valuable tool to predict and classify the geographical origin of sesame oils.