• 한국노년학
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• 제39권2호
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• pp.231-240
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• 2019

The study aimed to identify risk factors for falls as well as hospitalization status according to disease and demographic characteristics of demented inpatients by investigating the in-depth Injury Patient Surveillance System data collected by Korea Centers for Disease Control and Prevention(KCDC). Older adults over 60 years old who were diagnosed with dementia were included(n=1,732). Their data were analyzed after being assigned to either a fall group or a non-fall group. STATA was used for statistical analyses, such as frequency analysis, chi-square (χ²) test, and logistics regression. It was found that 8.0% of the demented inpatients experienced falls. According to the analysis on category of fall and non-fall group were statistically significant difference in age and Charlson Comorbidity Index(CCI) and bone density deficiency. Based on the logistic regression analysis of factors affecting falls, older adults over 80 are 2.386 times more likely to fall and based on a target with a CCI of 0, the risk of falls is 0.421 times lower, finally based on those without bone density disorder, the fall risk for those with bone density disorder was 3.581 times higher. Therefore, we expect that the important about the factors relating to falls identified in this can not only be found valuable for educating inpatients with dementia and care-givers, but also be used as reference that supports clinical professionals to make decisions on falls management for patients with dementia.

• Asia Marketing Journal
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• 제12권4호
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• pp.113-136
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• 2011

Product harm crises can distort long standing favorable equality perceptions, tarnish a company's reputation, cause major revenue and market-share losses, lead to costly product recalls, and devastate a carefully nurtured brand equity. However, in spite of the devastating impact of product-harm crises, little systematic research exists to asses its marketing consequences. So, this study focuses on the negative publicity about companies and their products. Namely, this study presented how inclusion effect supported the relationship between negative publicity and consumers' response, market performance. According to the results, after negativity publicity was happened, it was appeared that the negativity image spread into other product lines(spillover effect; inclusion effect). Also, when they contact with the negative publicity, respondents negatively evaluated both production evaluation and corporate evaluation. And, in that case of the products with negativity publicity, compared with refutation strategy(defense strategy<study 2>), improving strategy(correction notice) had positive influence on recovery of sales, product evaluation, and corporate evaluation. Finally, as the reaction time toward negativity publicity was faster, the market performance got worse. Especially, according to two-way interaction, when the reaction time was fast, the difference between refutation strategy(defense strategy<study 2>) and improving strategy was not existed in product evaluation and corporate evaluation. However, when the reaction time was late(after a month), improving strategy had more positive evaluation than defense strategy in product evaluation, and corporate evaluation.

• Journal of Korea Water Resources Association
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• 제56권8호
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• The Korea Journal of Herbology
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• 제38권6호
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• pp.61-71
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• 2023

Objectives : This study aimed to find out the future direction of accreditation system of Extramural herbal dispensaries (EHD) by comparing the current criteria of EHD and the existing Korea good manufacturing practice (GMP) regulations. Methods : Among the accreditation criteria of EHD, criteria of general herbal medicine was compared with the pharmaceutical GMP of Korea. The regulations of the accreditation of EHD and the regulations of KGMP were compared and organized with similar things based on the index of KGMP. All criteria from both were extracted for each element, classified into key-words and evaluated by dividing them into the same, similar one and no-matching. Results : Among the 189 criteria of KGMP, 77 criteria were consistent with the accreditation of EHD, and 15 criteria were similar. Based on the accreditation of EHD, 70.4% of the criteria were consistent or similar to KGMP. There were a total of 27 key-words only in the GMP criteria and not in the EHD one. Hence, a total of 25 key-words only in the EHD criteria and not in the GMP one. There were 12 similar key-words, and among them, there were 4 key-words in which accreditation of EHD was more specific than the KGMP. Conclusions : The criteria of general herbal medicine in EHD showed a similar or equivalent level of accreditation criteria compared to that of pharmaceutical GMP in Korea, and it ts believed that it should be considered at the current level to reflect the characteristics of herbal medicine.

• Knowledge Management Research
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• 제24권3호
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• pp.195-215
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• 2023

In the telecommunications service industry, until now, it has been possible for Network Operators (NOs) to secure a competitive advantage to increase subscribers and profits through network investment. However, amid a big change to digital economy, network investment fails to lead to increase profits. These days platform companies without holing network infrastructure have a more competitive advantage and take more profits. This makes NOs gradually lose interest in network investment. The purpose of this paper is to find policy measures to promote network investment in digital economy. Specifically, we identify the factors influencing the network investment and promising policy measures energizing the investment, and then analyze their priorities and derive policy implications through Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). The results of this paper show that market competition is more preferred to public intervention in promoting network investment. However, in order to guarantee and expand the universal access to network, it is necessary to consider expanding the role of the public, focusing on non-economic areas.

• Korean Journal of Mineralogy and Petrology
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• 제36권3호
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• pp.199-212
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• 2023

Diffusion is a powerful tool to understand geological processes recorded in terrestrial rocks as well as extraterrestrial materials. Since the diffusive exchange of elements or isotopes may have occurred differently in the solar nebula (high temperature and rapid cooling) and on the parent bodies (fluid-assisted thermal metamorphism at relatively low temperature), it is particularly important to model elemental or isotopic diffusion profiles within the mineral grains to better understand the evolution of the early solar system. A numerical model with the finite difference method for the fast grain boundary diffusion was established for the exchange of elements or isotopes between constituent minerals in a closed system. The fast grain boundary diffusion numerical model was applied to 1) ²⁶Mg variation in plagioclase of an amoeboid olivine aggregate (AOA) from a CH chondrite and 2) Fe-Mg interdiffusion between chondrules, AOA, and matrix minerals in a CO chondrite. Equilibrium isotopic fractionation and equilibrium partitioning were also included in the numerical model, based on the assumption that equilibrium can be reached at the interfaces of mineral crystals. The numerical model showed that diffusion profiles observed in chondrite samples likely resulted from the diffusive exchange of elements or isotopes between the constituent minerals. This study also showed that the closure temperature is determined not only by the mineral with the slowest diffusivity in the system, but also strongly depends on the constituent mineral abundances.

• Journal of the Korean Recycled Construction Resources Institute
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• 제11권3호
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• pp.192-201
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• 2023

In this paper, the strength properties of porous concrete containing natural fine aggregates and bottom ash aggregates were investigated, The material properties of natural fine aggregates and bottom ash were identified then used as aggregates for porous concrete. The water-binder ratio was constant at 0.25, and the com paction level of 0.5, 1.5, and 2.5 MPa was applied to produce a porous concrete specimen. Test of unit weight, ultrasonic velocity, compressive strength, and flexural tensile strength were perform ed and analyzed. The unit weight, ultrasonic velocity, com pressive strength, and flexural tensile strength increased as the compaction level increased and also the replacement rate of bottom ash with sand(fine aggregate) increased. In addition, through regression analysis, the correlation between the unit weight, compressive strength, and flexural tensile strength of bottom ash porous concrete was presented. Unit weight and strength properties are proportional to each other and showed an increasing correlation. In addition, the correlation coefficient (R²) value of regression analysis was calculated based on the experimental results of this study and those of other research papers.

• Journal of the Korean Recycled Construction Resources Institute
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• 제11권4호
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• pp.289-298
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• 2023

In this study, the development of a self-healing concrete waterproofing agent was examined, focusing on its manufacturing and waterproofing properties. The optimal ratio using microcapsules for the concrete waterproofing agent was determined through assessments of flow, compressive strength, and permeability conducted during the mortar stage. These findings aimed to provide fundamental data for evaluating the self-healing properties of the concrete waterproofing agent designed for use in concrete structures. The self-healing concrete waterproofing agent was comprised of three types of inorganic materials commonly used for repair purposes. From experimental results, a composition ratio with a high potassium silicate content, referred to as SIM-2, was found suitable. A surfactant mixing ratio of 0.03 % was identified to enhance the dispersibility of the concrete waterproofing agent, while a mixing ratio of 0.2 % distilled water was deemed suitable for viscosity adjustment. For the magnetic self-healing concrete waterproofing agent's healing agent, using microcapsules in the range of 0.5 % to 0.7 % met the KS F 4949 and KS F 4926 standards.

• Korean Journal of Ecology and Environment
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• 제56권4호
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• pp.339-347
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• 2023

Dissolved organic matter (DOM) is a key component in the biogeochemical cycling in freshwater ecosystem. However, it has been rarely explored, particularly complex river watershed dominated by natural and anthropogenic sources, such as various effluent facility and livestock. The current research developed a new analytical method for TOC/TN (Total Organic Carbon/Total Nitrogen) stable isotope ratio, and distinguish DOM source using stable isotope value (δ¹³C-DOC) and spectroscopic indices (fluorescence index [FI] and biological index [BIX]). The TOC/TN-IR/MS analytical system was optimized and precision and accuracy were secured using two international standards (IAEA-600 Caffein, IAEA-CH-6 Sucrose). As a result of controlling the instrumental conditions to enable TOC stable isotope analysis even in low-concentration environmental samples (<1 mgC L^-1), the minimum detection limit was improved. The 12 potential DOM source were collected from watershed, which includes top-soils, groundwater, plant group (fallen leaves, riparian plants, suspended algae) and effluent group (pig and cow livestock, agricultural land, urban, industry facility, swine facility and wastewater treatment facilities). As a result of comparing characteristics between 12 sources using spectroscopic indices and δ¹³C-DOC values, it were divided into four groups according to their characteristics as a respective DOM sources. The current study established the TOC/TN stable isotope analyses system for the first time in Korea, and found that spectroscopic indices and δ¹³C-DOC are very useful tool to trace the origin of organic matter in the aquatic environments through library database.

• Journal of the Korean Geotechnical Society
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• 제39권10호
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.