• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.275-292
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• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.9-24
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• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.188-199
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• 2022

Purpose: This study investigated the relationship between 3 major constructs of the theory of planned behavior (TPB), i.e., attitude, subjective norms and perceived behavioral control (PBC) and past experience of healthy eating and intentions of healthy eating in the short-term and long-term in adults living in Shanghai and parts of Anhui Province, China. Methods: The online study questionnaire for this cross-sectional study was based on previously validated items. A total of 408 Chinese adults (aged 18-64 years) residing in Shanghai and parts of Anhui Province, China were included to examine relationships between 3 major constructs of TPB and past experience of healthy eating, and short-term and long-term intentions of healthy eating. Multiple linear regression model adjusted for age and body mass index (BMI) was employed to test relationships. Results: Only PBC among 3 major constructs of TPB was significantly related to short-term (p < 0.001) and long-term (p = 0.002) intention of healthy eating after adjustment for age and BMI. Past experience of healthy eating was more significantly related to long-term intention (p < 0.001) compared to short-term (p = 0.020) intention of healthy eating. The short-term and long-term intention models explained 70.5% and 48.8% of the variance, respectively. Conclusion: PBC is a potential determinant of both short-term and long-term behavioral intention of healthy eating regardless of past experience of healthy eating in adults residing in Shanghai and parts of Anhui Province, China. Our results indicate that programs promoting healthy eating to Chinese adults incorporate PCB to perform healthy eating under his or her control.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.65-80
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• 2022

Objective : This study examined the psychometric properties of the 12-item Coping Orientation to Problems Experienced Scale (COPE) using Rasch analysis. COPE is one of the instruments used to measure stress-coping skills. Methods : The study participants were 480 community-dwelling older adults. We tested the instrument's unidimensionality assumption using principal component analysis (PCA). Item fit was examined using infit-and-outfit mean-square (MnSq) and standardized fit statistics (ZSTD). The precision and item difficulty hierarchies of the instrument were examined. The item-difficulty hierarchy was investigated to identify the easy and difficult items. We tested differential item functioning (DIF) for sex and age groups. Results : PCA revealed that the instrument met the unidimensionality assumption (eigenvalue = 1.78). Among the 12 items, item 2 was removed because of misfit (Infit MnSq = 1.33, Infit ZSTD = 5.05, Outfit MnSq = 1.56, Outfit ZSTD = 7.15). The remaining 11 items demonstrated a conceptual item-difficulty hierarchy. The person strata value was 3.10, which is equivalent to a reliability index value of 0.81. There was no DIF for the sex and age groups (DIF contrast <0.27). Conclusion : The findings indicated that the revised COPE-11 has adequate item-level psychometric properties and can accurately measure stress coping skills.

• Journal of Environmental Health Sciences
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• v.48 no.4
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• pp.236-243
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• 2022

Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.161-169
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• 2022

The purpose of this study performed to confirm the effect of caffeine intake and stress on sleep quality of college students. Research respondents and data collection were conducted on 269 college students through Google questionnaires from February 14 to March 13, 2022, and the research design is a descriptive survey study. Statistical analysis was performed using the SPSS 27.0 version as t-test and one way ANOVA. As a result of the study, it was found that most college students consume more caffeine than the average daily caffeine intake of Korean adults, although it is far below the recommended daily caffeine intake of Korean adults. The quality of sleep of college students is stress (r=.32, p=<).001) and caffeine intake (r=.204, p=.001). It was found that there was a positive correlation. Factors affecting sleep quality are body mass index (β=.1.19, p<.001) Stress (β=.3.37, p<.001), smoking (β=-.18, p=.001), caffeine intake (β=.15, p=.005) It was in order, and the explanatory power of the model was 24.8%.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.411-417
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• 2022

This study aimed to learn and evaluate the effectiveness of VGGNet in the detection of pulmonary emphysema using low-dose chest computed tomography images. In total, 8000 images with normal findings and 3189 images showing pulmonary emphysema were used. Furthermore, 60%, 24%, and 16% of the normal and emphysema data were randomly assigned to training, validation, and test datasets, respectively, in model learning. VGG16 and VGG19 were used for learning, and the accuracy, loss, confusion matrix, precision, recall, specificity, and F1-score were evaluated. The accuracy and loss for pulmonary emphysema detection of the low-dose chest CT test dataset were 92.35% and 0.21% for VGG16 and 95.88% and 0.09% for VGG19, respectively. The precision, recall, and specificity were 91.60%, 98.36%, and 77.08% for VGG16 and 96.55%, 97.39%, and 92.72% for VGG19, respectively. The F1-scores were 94.86% and 96.97% for VGG16 and VGG19, respectively. Through the above evaluation index, VGG19 is judged to be more useful in detecting pulmonary emphysema. The findings of this study would be useful as basic data for the research on pulmonary emphysema detection models using VGGNet and artificial neural networks.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.163-190
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• 2023

This study analyzed the effect of technology preparation and technology acceptance factors on the intention of public library librarians to use artificial intelligence-based technology using the technology acceptance model. To this end, a survey was conducted on public library librarians, and a total of 202 survey data were used for statistical analysis. As a result of the hypothesis test, first, optimism has a significant positive (+) effect on perceived usefulness, and discomfort has a significant negative (-) effect. Optimism and innovation on perceived ease of use were found to have a significant positive (+) effect, and discomfort was found to have a significant negative (-) effect. Second, perceived ease of use was found to have a significant positive (+) effect on perceived usefulness, and both perceived usefulness and perceived ease of use had a significant positive (+) effect on the intention to use. Third, optimism was found to have a significant positive (+) effect on the intention to use, and anxiety was found to have a significant negative (-) effect. This study is expected to provide basic data on the use of artificial intelligence technology in the future by empirically analyzing public library librarians' perceptions of artificial intelligence-based technology.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.325-350
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• 2023

This study focuses on the impact of research data metadata quality evaluation index on the revitalization of K-BDS, a research data platform in the bio field, and examines the mediating effect of motivation factors for utilizing the platform. The investigation employs a structural equation model analysis and bootstrap analysis to explore the interrelationships among the three variables. The findings demonstrate that researchers who prioritize the quality of metadata display higher motivation to use the research data platform, leading to an intention to activate the platform. The study also confirms the mediating effect of motivation factors. Moreover, a comprehensive understanding of the sub-factors within each variable is attained through regression analysis and Sobel test. The results highlight that enhancing searchability is crucial to activate research data sharing in the bio field, while improving discoverability is vital for research data reuse. Interestingly, the study reveals that citationability does not significantly impact platform activation. As a conclusion, to foster platform activation, it is imperative to provide systematic support by enhancing metadata quality. This improvement can not only increase trust in the platform but also institutionally solidify the benefits of citation.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.