• Journal of Climate Change Research
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• v.1 no.2
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• pp.121-131
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• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.1
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• pp.18-26
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• 2021

Purpose: Generally, patients are noticed to store denture in water when removed from the mouth. However, few studies have reported the advantage of volumetric change in underwater storage over dry storage. To be a reference in defining the proper denture storage method, this study aims to evaluate the volumetric change and dimensional deformation in case of underwater and dry storage. Materials and methods: Definitive casts were scanned by a model scanner, and denture bases were designed with computer-aided design (CAD) software. Twelve denture bases (upper 6, lower 6) were printed with 3D printer. Printed denture bases were invested and flasked with heat-curing method. 6 upper and 6 lower dentures were divided into group A and B, and each group contains 3 upper and 3 lower dentures. Group A was stored dry at room temperature, group B was stored underwater. Group B was scanned at every 24 hours for 28 days and scanned data was saved as stereolithography (SLA) file. These SLA files were analyzed to measure the difference in volumetric change of a month and Kruskal-Wallis test were used for statistical analysis. Best-fit algorithm was used to overlap and 3-dimensional color-coded map was used to observe the changing pattern of impression surface. Results: No significant difference was found in volumetric changes regardless of the storage methods. In dry-stored denture base, significant changes were found in the palate of upper jaw and posterior lingual border of lower jaw in direction away from the underlying tissue, maxillary tuberosity of upper jaw and retromolar pad area of lower jaw in direction towards the underlying tissue. Conclusion: Storing the denture underwater shows less volumetric change of impression surface than storing in the dry air.

• Korean Journal of Environment and Ecology
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• v.35 no.1
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• pp.24-36
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• 2021

Countries around the world, including the Republic of Korea, are participating in efforts to preserve biodiversity. Concerning species, in particular, studies that aim to find potential habitats and establish conservation plans by conducting habitat suitability analysis for specific species are actively ongoing. However, few studies on mid- to long-term changes in suitable habitat areas are based on accumulated information. Therefore, this study aimed to analyze the time-series changes in the habitat suitable area and examine the otters' changing pattern (Lutra lutra) designated as Level 1 endangered wildlife in Gangwon-do. The time-series change analysis used the data on otter species' presence points from the 2nd, 3rd, and 4th national natural environment surveys conducted for about 20 years. Moreover, it utilized the land cover map consistent with the survey period to create environmental variables to reflect each survey period's habitat environment. The suitable habitat area analysis used the MaxEnt model that can run based only on the species presence information, and it has been proven to be reliable by previous studies. The study derived the habitat suitability map for otters in each survey period, and it showed a tendency that habitats were distributed around rivers. Comparing the response curves of the environmental variables derived from the modeling identified the characteristics of the habitat favored by otters. The examination of habitats' change by survey period showed that the habitats based on the 2nd National Natural Environment Survey had the widest distribution. The habitats of the 3rd and 4th surveys showed a tendency of decrease in area. Moreover, the study aggregated the analysis results of the three survey periods and analyzed and categorized the habitat's changing pattern. The type of change proposed different conservation plans, such as field surveys, monitoring, protected area establishment, and restoration plan. This study is significant because it produced a comprehensive analysis map that showed the time-series changes of the location and area of the otter habitat and proposed a conservation plan that is necessary according to the type of habitat change by region. We believe that the method proposed in this study and its results can be used as reference data for establishing a habitat conservation and management plan in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1423-1444
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• 2022

In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.303-317
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• 2022

Climate change caused by increased greenhouse gas emissions can alter the natural ecosystem, including the pollination ecosystem and agricultural ecology, which are ecological interactions between potted insects and plants. Many studies have reported that populations of wild bees, including bees and wasps (BW), which are the key pollinators, have gradually declined due to climate change, leading to adverse impacts on overall biodiversity, ultimately with agribusinesses and the life cycle of flowering plants. Therefore, we could infer that the rising temperature in Korean Peninsula (South Korea) due to global warming has led to climate change and influenced the wild bee's ecosystem. In this study, we surveyed the distributional pattern of BW (Superfamily: Apoidea, Vespoidea, and Chrysidoidea) at 51 sites from 2017 (37 sites) to 2018 (14 sites) to examine the effects of climatic factors on the nationwide distribution of BW in South Korea. Previous literature has confirmed that their distribution according to forest climate zones is significantly correlated with mean and accumulative temperatures. Based on the result, we predicted the effects of future climate changes on the BW distribution that appeared throughout South Korea and the species that appeared in specific climate zones using Shared Socioeconomic Pathways (SSPs). The distributions of wild BW predicted by the SSP scenarios 2-4.5 and 5-8.5 according to the BIOMOD species distribution model revealed that common and endemic species will shift northward from the current habitat distribution by 2050 and 2100, respectively. Our study implies that climate change and its detrimental effect on the ecosystem is ongoing as the BW distribution in South Korea can change, causing the change in the ecosystem in the Korean Peninsula. Therefore, immediate efforts to mitigate greenhouse gas emissions are warranted. We hope the findings of this study can inspire further research on the effects of climate change on pollination services and serve as the reference for making agricultural policy and BW conservation strategy

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.1
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• pp.1-17
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• 2023

Purpose. The purpose of this study was to examine the correlation between the finish line designs and the marginal adaptation of nonprecious metal alloy coping produced by different digital manufacturing methods. Materials and methods. Nonprecious metal alloy copings were made respectively from each master model with three different methods; SLS, milling and casting by computer aided design and computer aided manufacturing (CAD-CAM). Twelve copings were made by each method resulting in 72 copings in total. The measurement was conducted at 40 determined reference points along the circumferential margin with the confocal laser scanning microscope at magnification ×150. Results. Mean values of marginal gap of laser sintered copings were 11.8 ± 7.4 ㎛ for deep chamfer margin and 6.3 ± 3.5 ㎛ for rounded shoulder margin and the difference between them was statistically significant (P < .0001). Mean values of marginal gap of casted copings were 18.8 ± 20.2 ㎛ for deep chamfer margin and 33 ± 20.5 ㎛ for rounded shoulder margin and the difference between them was significant (P = .0004). Conclusion. Within the limitation of this study, the following conclusions were drawn. 1. The variation of finish line design influences the marginal adaptation of laser sintered metal coping and casted metal coping. 2. Laser sintered copings with rounded shoulder margin had better marginal fit than deep chamfer margin. 3. Casted copings with deep chamfer margin had better marginal fit than rounded shoulder margin. 4. According to the manufacturing method, SLS system showed the best marginal fit among three different methods. Casting and milling method followed that in order.

• Laboratory Medicine Online
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• v.2 no.1
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• pp.10-14
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• 2012

Background: Measurement of HbA_1c levels is widely used to diagnose diabetes mellitus and to evaluate and monitor plasma-glucose concentrations over 6-8 weeks. In this study, we evaluated the diagnostic performance of the newly developed latex immunoturbidimetric method by using Autolab HbA_1c. Methods: We analyzed and compared the diagnostic performance of Autolab HbA_1c with that of Toshiba 200FR between April 2009 and July 2009. According to guidelines (EP5-A2, EP6-P, EP9-A2) of the clinical and laboratory standards institute (CLSI), we compared linearity, precision and correlation of Autolab HbA_1c with those of G7 (Tosoh Corp., Kyoto, Japan) by using high-performance liquid chromatography (HPLC) method. Results: Data obtained using Autolab HbA_1c showed good linearity in mixtures of samples with low (3.1%) and high (15.1%) levels of HbA_1c (r²=0.9997). In the analysis of within-run precision of the samples with HbA_1c levels of 5.1% and 12.1%, the SDs were 0.04 and 0.06 and covariances of these samples were 0.8% and 0.5%, respectively. In the Deming regression model, the regression equation was as follows: Autolab HbA_1c=1.0859×Tosoh HPLC-0.6957. Conclusions: In this study, Autolab HbA_1c method showed better performance characteristics than Tosoh G7 did. In reference review, there was no interference of variant hemoglobin. The data acquisition time of Autolab HbA_1c was lower than that of Tosoh G7. The advantages of Autolab HbA_1c are that it can be used as an autoanlyzer in routine chemical analysis, it does not require pre-analytical treatment, and the samples are automatically treated with distilled water for hemolysis.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of Nutrition and Health
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• v.46 no.1
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• pp.50-60
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• 2013

The aims of this study were to estimate daily intake of macrominerals from beverages, liquid teas, and liquid coffees and to evaluate their potential health risks for Korean children and adolescents (1-to 19 years old). Assessment of dietary intake was conducted using the actual level of sodium, calcium, phosphorus, potassium, and magnesium in non-alcoholic beverages and (207 beverages, 19 liquid teas, and 24 liquid coffees) the food consumption amount drawn from "The Fourth Korea National Health and Nutrition Examination Survey (2007-2009)". To estimate the dietary intake of non-alcoholic beverages, 6,082 children and adolescents (Scenario I) were compared with 1,704 non-alcoholic beverage consumption subjects among them (Scenario II). Calculation of the estimated daily intake of macrominerals was based on point estimates and probabilistic estimates. The values of probabilistic macromineral intake, which is a Monte-Carlo approach considering probabilistic density functions of variables, were presented using the probabilistic model. The level of safety for macrominerals was evaluated by comparison with population nutrient intake goal (Goal, 2.0 g/day) for sodium, tolerable upper intake level (UL) for calcium (2,500 mg/day) and phosphorus (3,000-3,500 mg/day) set by the Korean Nutrition Society (Dietary Reference Intakes for Koreans, KDRI). For total children and adolescents (Scenario I), mean daily intake of sodium, calcium, phosphorus, potassium, and magnesium estimated by probabilistic estimates using Monte Carlo simulation was, respectively, 7.93, 10.92, 6.73, 23.41, and 1.11, and 95th percentile daily intake of those was, respectively, 28.02, 44.86, 27.43, 98.14, and 3.87 mg/day. For consumers-only (Scenario II), mean daily intake of sodium, calcium, phosphorus, potassium, and magnesium estimated by probabilistic estimates using Monte Carlo simulation was, respectively, 19.10, 25.77, 15.83, 56.56, and 2.86 mg/day, and 95th percentile daily intake of those was, respectively, 62.67, 101.95, 62.09, 227.92, and 8.67 mg/day. For Scenarios I II, sodium, calcium, and phosphorus did not have a mean an 95th percentile intake that met or exceeded the 5% of Goal and UL.