• Journal of Korean Society on Water Environment
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• v.32 no.2
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• pp.173-182
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• 2016

The objective of this study is to quantitatively analyze climate change effects by using statistical trends and a watershed model in the Yongdam dam watershed. The annual average air temperature was found to increase with statistical significance. In particular, greater increases were observed in autumn. Also, this study was performed to evaluate the potential climate change in the streamflow and water temperature using a watershed model (HSPF) with RCP climate change scenarios. The streamflow of Geum river showed a decrease of 5.1% and 0.2%, respectively, in the baseline data for the 2040s and 2080s. The seasonal impact of future climate change on the streamflow showed a decrease in the summer and an increase in the winter. The water temperature of Geum river showed an average increase of 0.7~1.0℃. Especially, the water temperature of Geum river showed an increase of 0.3~0.5℃ in the 2040s and 0.5~1.2℃ in the 2080s. The seasonal impact of future climate change on the water temperature showed an increase in winter and spring, with a decrease in summer. Therefore, it was determined that a statistical analysis-based meteorological and quantitative forecast of streamflow and water temperature using a watershed model is necessary to assess climate change impact and to establish plans for future water resource management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2689-2694
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• 2014

This study analyze the impact of omija(maximowiczia chinensis) market by Korea-China FTA and review the change of mid and long term supply-demand from 2014 to 2018. A scenario is also imported to simulate and measure the impacts of the Korea-China FTA. The scenario is that tariff rates for Chinese product(omija) will be zero after 5 years from 2014. A partial equilibrium model of Omija is specified to forecast mid and long term supply-demand and prices. Equations in the model were estimated by using econometric techniques. The results based on scenario are compared with the results by the baseline case(maintenance of current situation). Our study show that when the tariff rates for Chinese product(Omija) will be zero after 5 years from 2014, the cultivated area of Omija is forecasted to decline until 3,370ha in 2018, and the consumption is forecasted to increase up to 12,040.8MT in 2018, and also total revenue of about 9.8 billion korean won will be decreased during 5 years(2014-2018).

• Journal of the Korean Society of Propulsion Engineers
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• v.21 no.1
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• pp.26-35
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• 2017

The high-cycle fatigue cracking and the resonance generated in operation of a centrifugal compressor are main cause of the impeller damage. In order to prevent the damage, the impeller is designed or modified to have sufficient strength to withstand the operating condition. The damage prevent design will lead to a change of the flow condition and the performance characteristics of the compressor. In this study, the computational analysis were performed to identify the flow and the performance characteristics. The cases are a scalloped and a increased the blade thickness models with a closed type impeller. As the analysis results, the value of head coefficient and total to total efficiency for the increased the blade thickness model was decreased by each 0.5% and 0.1% than the values of the baseline model. Each value for the scalloped model was increased by 0.4% and was decreased by 1.6%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.

• Korean journal of dermatology
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• v.56 no.10
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• pp.609-613
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• 2018

Background: Psoriasis is a chronic inflammatory skin disease with an incidence of 0.5~3% of the worldwide population. The pathogenesis of psoriasis is related to dysregulated keratinocyte function and immune reactions. Notably, genetic factors are considered important etiological contributors. Globally, several researchers have recently performed genome-wide association studies (GWAS) to identify the genes related with psoriasis. Objective: We aimed to investigate the expression pattern of 2 candidate genes that were identified by GWAS. These include interleukin 28 receptor alpha (IL28RA) and CUB and Sushi multiple domains 1 (CSMD1). Methods: We applied imiquimod cream to develop a psoriasis-like mouse model and obtained skin tissue. We performed immunohistochemistry to detect the expression of IL-28A and CSMD1. Results: IL28RA expression increased at an early time point such as 1 day after the topical application of 5% imiquimod cream. However, its expression returned to baseline levels 2 weeks after the topical application of imiquimod cream. CSMD1 expression also increased after the topical application of imiquimod, with increased expression particularly observed in the upper epidermal layer. Notably, CSMD1 expression decreased 7 days after imiquimod cream application. Conclusion: These results suggest that IL28RA and CSMD1 may play key roles in the pathogenesis of psoriasis.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.4
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• pp.91-110
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• 2018

We proposed a video summarization algorithm based on an ERP (Event Related Potentials)-based topic relevance model, a MMR (Maximal Marginal Relevance), and discriminant analysis to generate a semantically meaningful video skim. We then conducted implicit and explicit evaluations to evaluate our proposed ERP/MMR-based method. The results showed that in the implicit and explicit evaluations, the average scores of the ERP / MMR methods were statistically higher than the average score of the SBD (Shot Boundary Detection) method used as a competitive baseline, respectively. However, there was no statistically significant difference between the average score of ERP/MMR (${\lambda}=0.6$) method and that of ERP/MMR (${\lambda}=1.0$) method in both assessments.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.189-195
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• 2019

In this work, the flow and combustion characteristics using a 3-D numerical simulation was evaluated for a shale gas fueled combustor in a commercial class gas turbine. The Standard k-e turbulence model, 2 step methane oxidation mechanism, Finite rate/Eddy dissipation reaction model, DTRM radiation model were employed and validated well at the baseline condition (Natural Gas, Pilot Ratio 0.2). Based on the validated models, the combustion characteristics of shale gas was evaluated for three pilot ratios cases. It was found that NOx concentrations for all shale gas cases were less than the that for city gas, which imply that, at the selected PRs, the condition for combustion stability is satisfied. In addition, for higher PR, whereas the average temperatures at the exit are the same, the NOx increases. It means that diffusion combustion portion increases due to the higher PR.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.1-10
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• 2021

Agricultural reservoirs have a great influence on the water circulation in the watershed. It is necessary to evaluate the impact on water circulation by the agricultural reservoir. Therefore, in this study, we simulated the agricultural watershed through linkage of Hydrological Simulation Program Fortran (HSPF) and Module-based hydrologic Analysis for Agricultural watershed (MASA) and evaluated the contribution of the agricultural reservoir to water circulation by watershed water circulation index. As a result of simulating the Idong reservoir watershed through the HSPF-MASA linkage model, the model performance during the validation period was R2 0.74 upstream, 0.78 downstream, and 0.76 reservoir water level, respectively. To evaluate the contribution of agricultural reservoirs, three scenarios (baseline, present state, and present state without reservoir) were simulated, and the water balance differences for each scenario were analyzed. In the evaluation through the agricultural water circulation rate in the watershed, it was found that the water circulation rate increased by 1.1%, and the direct flow rate decreased by 13.6 mm due to the agricultural reservoir. In the evaluation through the Budyko curve, the evaporation index increased by 0.01. Agricultural reservoirs reduce direct runoff and increase evapotranspiration, which has a positive effect on the water circulation.

• Journal of Radiation Protection and Research
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• v.48 no.2
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• pp.90-99
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• 2023

Background: Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations. In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into account uncertainties. We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection. Materials and Methods: SUMRAY has two versions of code written in R and Python. The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki. The confidence intervals associated with the evaluated risks were derived by propagating the statistical uncertainties in the risk model parameter estimates by the Monte Carlo method. Results and Discussion: SUMRAY was used to calculate the lifetime or time-integrated attributable risks of cancer under an exposure scenario (baseline rates, dose[s], age[s] at exposure, age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool, Radiation Risk Assessment Tool (RadRAT; National Institutes of Health), and showed a reasonable agreement within the estimated confidential interval. Compared with RadRAT, SUMRAY can be used for a wide range of applications, as it allows the risk projection with arbitrarily specified risk models and/or population reference data. Conclusion: The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes. The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.570-590
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• 2024

Breast cancer ranks among the most prevalent forms of malignancy and foremost cause of death by cancer worldwide. It is not preventable. Early and precise detection is the only remedy for lowering the rate of mortality and improving the probability of survival for victims. In contrast to present procedures, thermography aids in the early diagnosis of cancer and thereby saves lives. But the accuracy experiences detrimental impact by low sensitivity for small and deep tumours and the subjectivity by physicians in interpreting the images. Employing deep learning approaches for cancer detection can enhance the efficacy. This study explored the utilization of thermography in early identification of breast cancer with the use of a publicly released dataset known as the DMR-IR dataset. For this purpose, we employed a novel approach that entails the utilization of a pre-trained MobileNetV2 model and fine tuning it through transfer learning techniques. We created three models using MobileNetV2: one was a baseline transfer learning model with weights trained from ImageNet dataset, the second was a fine-tuned model with an adaptive learning rate, and the third utilized early stopping with callbacks during fine-tuning. The results showed that the proposed methods achieved average accuracy rates of 85.15%, 95.19%, and 98.69%, respectively, with various performance indicators such as precision, sensitivity and specificity also being investigated.