• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.541-548
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• 2021

Recently, multispectral cameras are being actively utilized in various application fields such as agriculture, forest management, coastal environment monitoring, and so on, particularly onboard UAV's. Resultant multispectral images are typically georeferenced primarily based on the onboard GPS (Global Positioning System) and IMU (Inertial Measurement Unit)or accurate positional information of the pixels, or could be integrated with ground control points that are directly measured on the ground. However, due to the high cost of establishing GCP's prior to the georeferencing or for inaccessible areas, it is often required to derive the positions without such reference information. This study aims to provide a means to improve the georeferencing performance of a multispectral camera images without involving such ground reference points, but instead with the simultaneously onboard high resolution RGB camera. The exterior orientation parameters of the drone camera are first estimated through the bundle adjustment, and compared with the reference values derived with the GCP's. The results showed that the incorporation of the images from a high resolution RGB camera greatly improved both the exterior orientation estimation and the georeferencing of the multispectral camera. Additionally, an evaluation performed on the direction estimation from a ground point to the sensor showed that inclusion of RGB images can reduce the angle errors more by one order.

• Applied Chemistry for Engineering
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• v.33 no.3
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• pp.235-241
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• 2022

According to the World Water Development Report 2015 released by the United Nations, drinking water is expected to decrease by 40% by 2030. This does not mean that the amount of water decreases, but rather that the water source is contaminated due to environmental pollution. Because microbes are deeply related to water quality, the analysis of microbe is very important for water quality management. While the most common method currently used for microbial analysis is microscopic examination of the shape and feature after cell culture, as the gene analysis technology advances, quantitative polymerase chain reaction (qPCR) can be applied to the microscopic microbiological analysis, and the application method has been studied. Among them, a reverse transcription (RT) step enables the analysis of RNA by RT-PCR. Integrated cell culture (ICC)-qPCR shortens the test time by using it with microbial culture analysis, and viability qPCR can reduce the false positive errors of samples collected from natural water source. Multiplex qPCR for improved throughput, and microfluidic qPCR for analysis with limited amount of sample has been developed In this paper, we introduce the case, principle and development direction of the qPCR method applied to the analysis of microorganisms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.127-134
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• 2022

Recently, policies and research to prevent increasing construction accidents have been actively conducted in the domestic construction industry. In previous studies, the prediction model developed to prevent construction accidents mainly used only structured data, so various characteristics of construction sites are not sufficiently considered. Therefore, in this study, we developed a machine learning-based construction accident prediction model that enables the characteristics of construction sites to be considered sufficiently by using both structured and text-type unstructured data. In this study, 6,826 cases of construction accident data were collected from the Construction Safety Management Integrated Information (CSI) for machine learning. The Decision forest algorithm and the BERT language model were used to train structured and unstructured data respectively. As a result of analysis using both types of data, it was confirmed that the prediction accuracy was 95.41 %, which is improved by about 20 % compared to the case of using only structured data. Conclusively, the performance of the predictive model was effectively improved by using the unstructured data together, and construction accidents can be expected to be reduced through more accurate prediction.

• Journal of the Korean Applied Science and Technology
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• v.38 no.2
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• pp.368-377
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• 2021

The present study aimed to evaluate the effects of radiation mutant Perilla frutescens var. crispa and Atractylodes macrocephala Koidzumi complex extract(Perilla frutescens var. crispa complex extract) on the mediators related to degenerative arthritis in a monosodium iodoacetate-induced rat model of degenerative arthritis. Perilla frutescens var. crispa complex extract was administered orally at doses of 25, 50 or 100 mg/kg/day for 2 weeks before direct injection of monosodium iodoacetate (3 mg/50 µl of 0.9% saline) into the intra-articular space of the rats' right knees. The rats subsequently received the same doses of oral Perilla frutescens var. crispa complex extract for another 4 weeks. It was evaluated that the treatment effects based on serum bio-markers, and morphological and histopathological analysis of the knee joints. Compared with those in negative control rats, the Perilla frutescens var. crispa complex extract treatments significantly reduced the serum levels of inflammation, bone metabolism markers (i.e., TNF-α, MMP-3, COX-2, PGE₂, COMP, and Aggrecan). Otherwise, it was significantly increased the production of CTX-2 in cartilage absorption mediators. In addition, the Perilla frutescens var. crispa complex extract treatments effectively preserved the knee cartilage and synovial membrane. As a result, it indicates that the Perilla frutescens var. crispa complex extract improved degenerative arthritis symptoms. Thus, the Perilla frutescens var. crispa complex can be used in food material for the management of degenerative arthritis.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.405-413
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• 2022

Since the COVID-19 outbreak, the active utilization of new health care service utilizing the ICT technology and data science such as telemedicine, smart hospital, AI dignosis has been increasingly found. In this study we examined the business model of Amazon healthcare which leads disruptive innovation in U.S. health care industry with the introduction of hybrid model of telemedicin, in-person care and customer-centric online drug delivery, home-use diagnostic kit, characterized by the integrated model combining medical care, drug delivery and the use of diagnostic kit. We showed using the multiproduct competition model that the synergy effect between the Amazon's original business areas and the healthcare business area causes the active market penetration and the increase in the customer value from utilization of the Amazon care. Using Hotelling's spatial competition model, we also showed that the competition in the health care market can be greater when consumer's choice of health care providers are available in telemedicine platform. In the long, run the issue of competition being weakened due to the exit of less competent healthcare providers may arise, to which the policymakers in the charge of fair competition in health care industry should pay attention.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.525-541
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• 2022

This study aimed to develop simulation practice program with PBL (S-PBL) for nursing students and evaluate the effect of the program on their problem solving ability, clinical performance competency, learning satisfaction and confidence. The participants were nursing students who applied for simulation practice courses at an university in J province. The study was a mixed-method design using a nonequivalent one group pretest-posttest design (n=91) and focus group interview (n=12). Quantitative data were analyzed using SPSS 23.0 program and qualitative data thematic analysis. Quantitative data showed S-PBL was effective in improving clinical performance competency, learning satisfaction and confidence of the participants, but not in improving problem solving ability. As a result of the qualitative study, four themes and eight sub-themes were derived, and the themes were "Learn integrated nursing care based on priority", "Experience team cooperation through communication," "Learn vividly critical care" and "Improved nursing competency". The S-PBL could be effective in practical education for nursing students. In further study, it is necessary to develop various simulation practice programs based on PBL through a mixed-method design and apply them to nursing curriculum.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.234-243
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• 2022

In Korea, hail damage occurs every year, and in the case of agriculture, it causes severe field crop and cultivation facility losses. Therefore, it is necessary to develop a hail information service system customized for Korea's primary production and crop-growing areas to minimize hail damage. However, the observation of hail is relatively more difficult than that of other meteorological variables, and the available data are also spatially and temporally variable. A hail information service system was developed to understand the temporal and spatial distribution of hail occurrence. As part of this, a hail observation database was established that integrated the observation data from Korea Meteorological Administration with the information from newspaper reports. Furthermore, a hail risk map was produced based on this database. The risk map presented the nationwide distribution and characteristics of hail showers from 1970 to 2018, and the northeastern region of South Korea was found to be relatively dangerous. Overall, hail occurred nationwide, especially in the northeast and some inland areas (Gangwon, Gyeongbuk, and Chungbuk province) and in winter, mainly on the north coast and some inland areas as graupel (small and soft hail). Analyzing the time of day, frequency, and hailstone size of hail shower occurrences by region revealed that the incidence of large hail stones (e.g., 10 cm at Damyang-gun) has increased in recent years and that showers occurred mainly in the afternoon when the updraft was well formed. By integrating multidisciplinary data, the temporal and spatial gap in hail data could be supplemented. The hail risk map produced in this study will be helpful for the selection of suitable crops and growth management strategies under the changing climate conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.751-762
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• 2022

Welded head studs are mainly used as shear connectors to bond steel girders and concrete slabs in steel-concrete composite bridges. For welded shear connectors, environmental problems include noise and scattering dust which are generated during the removal of damaged or aged slabs. Therefore, it is necessary to develop demountable shear connectors that can easily replace aged concrete slabs for efficient maintenance and thus for better management of environmental problems and life cycle costs. The buried nut method is commonly studied in relation to bolted shear connectors, but this method is not used in civil structures such as bridges due to low rigidity, low shear resistance, and increased initial slip. In this study, in order to mitigate these problems, a demountable bolted shear connector is proposed in which the buried nut is integrated into the stud column and has a tapered shape at the bottom of an enlarged column shank. To verify the performance of the proposed demountable stud bolts in terms of static shear strength and slip displacement, a horizontal shear test was conducted, with the performance outcomes compared to those of conventional welded studs. It was confirmed that the proposed demountable bolted shear connector is capable of excellent shear performance and that it satisfies the slip displacement and ductility design criteria, meaning that it is feasible as a replacement for existing welding studs.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1115-1124
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• 2022

The impact of climate change on water resources was evaluated for Chungju Dam and Soyang-gang Dam basins by constructing an integrated modeling framework consisting of a dam inflow prediction model based on the Variable Infiltration Capacity (VIC) model, a distributed hydrologic model, and an LSTM based dam outflow prediction model. Considering the uncertainty of future climate data, four models of CMIP6 GCM were used as input data of VIC model for future period (2021-2100). As a result of applying future climate data, the average inflow for period increased as the future progressed, and the inflow in the far future (2070-2100) increased by up to 22% compared to that of the observation period (1986-2020). The minimum value of dam discharge lasting 4~50 days was significantly lower than the observed value. This indicates that droughts may occur over a longer period than observed in the past, meaning that citizens of Seoul metropolitan areas may experience severe water shortages due to future droughts. In addition, compared to the near and middle futures, the change in water storage has occurred rapidly in the far future, suggesting that the difficulties of water resource management may increase.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1137-1147
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• 2022

River and groundwater stages are the main elements in the hydrologic cycle. They are spatially correlated and can be used to evaluate hydrological and agricultural drought. Stochastic simulation is often performed independently on hydrological variables that are spatiotemporally correlated. In this setting, interdependency across mutual variables may not be maintained. This study proposes the Bayesian vector autoregression model (VAR) to capture the interdependency between multiple variables over time. VAR models systematically consider the lagged stages of each variable and the lagged values of the other variables. Further, an autoregressive model (AR) was built and compared with the VAR model. It was confirmed that the VAR model was more effective in reproducing observed interdependency (or cross-correlation) between river and ground stages, while the AR generally underestimated that of the observed.