• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.270-281
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• 2021

With the development of information technology, the size of insurance fraud is increasing rapidly every year, and the method is being organized and advanced in conspiracy. Although various forms of prediction models are being studied to predict and detect this, insurance-related information is highly sensitive, which poses a high risk of sharing and access and has many legal or technical constraints. In this paper, we propose a machine learning insurance fraud prediction model based on blockchain, one of the most popular technologies with the recent advent of the Fourth Industrial Revolution. We utilize blockchain technology to realize a safe and trusted insurance information sharing system, apply the theory of social relationship analysis for more efficient and accurate fraud prediction, and propose machine learning fraud prediction patterns in four stages. Claims with high probability of fraud have the effect of being detected at a higher prediction rate at an earlier stage, and claims with low probability are applied differentially for post-reference management. The core mechanism of the proposed model has been verified by constructing an Ethereum local network, requiring more sophisticated performance evaluations in the future.

• Journal of Ginseng Research
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• v.46 no.6
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• pp.771-779
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• 2022

Background: As a kind of common complication of the surgery of perianal diseases, perianal ulcer is known as a nuisance. This study aims to develop a kind of 20(S)-ginsenoside Rg3 (Rg3)-loaded hydrogel to treat perianal ulcers in a rat model. Methods: The copolymers PLGA₁₆₀₀-PEG₁₀₀₀-PLGA₁₆₀₀ were synthesized by ring-opening polymerization process and Rg3-loaded hydrogel was then developed. The perianal ulcer rat model was established to analyze the treatment efficacy of Rg3-loaded hydrogel for ulceration healing for 15 days. The animals were divided into control group, hydrogel group, free Rg3 group, Rg3-loaded hydrogel group, and Lidocaine Gel® group. The residual wound area rate was calculated and the blood concentrations of interleukin-1 (IL-1), interleukin-6 (IL-6), and vascular endothelial growth factor (VEGF) were recorded. Hematoxylin and eosin (H&E) staining, Masson's Trichrome (MT) staining, and tumor necrosis factor α (TNF-α), Ki-67, CD31, ERK1/2, and NF-κB immunohistochemical staining were performed. Results: The biodegradable and biocompatible hydrogel carries a homogenous interactive porous structure with 10 ㎛ pore size and five weeks in vivo degradation time. The loaded Rg3 can be released sustainably. The in vitro cytotoxicity study showed that the hydrogel had no effect on survival rate of murine skin fibroblasts L929. The Rg3-loaded hydrogel can facilitate perianal ulcer healing by inhibiting local and systematic inflammatory responses, swelling the proliferation of nuclear cells, collagen deposition, and vascularization, and activating ERK signal pathway. Conclusion: The Rg3-loaded hydrogel shows the best treatment efficacy of perianal ulcer and may be a candidate for perianal ulcer treatment.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.17 no.4
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• pp.79-90
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• 2021

This paper presents a study to reduce the effect of blast pressure on the blast valves installed in protection tunnels, where the shape of the tunnel entrance and the blast pocket is optimized based on the predetermined basic shape of the protective tunnels. The reliability of the numerical tunnel models was examined by performing analyses of mesh convergence and overpressure stability and with comparison to the data in blast-load design charts in UFC 3-340-02 (DoD, 2008). An optimal mesh size and a stabilized distance of overpressure were proposed, and the numerical results were validated based on the UFC data. A parametric study to reduce the blast overpressures in tunnel was conducted using the validated numerical model. Analysis was performed applying 1) the entrance slope of 90, 75, 60, and 45 degrees, 2) two blast pockets with the depth 0.5, 1.0, and 1.5 times the tunnel width, 3) the three types of curved back walls of the blast pockets, and 4) two types of the upper and lower surfaces of the blast pockets to the reference tunnel model. An optimal solution by combining the analysis results of the tunnel entrance shape, the depth of the blast pockets, and the upper and lower parts of the blast pockets was provided in comparison to the reference tunnel model. The blast overpressures using the proposed tunnel shape have been reduced effectively.

• Journal of Ginseng Research
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• v.46 no.2
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• pp.275-282
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• 2022

Background: Stroke is a neurological disorder characterized by brain tissue damage following a decrease in oxygen supply to brain due to blocked blood vessels. Reportedly, 80% of all stroke cases are classified as cerebral infarction, and the incidence rate of this condition increases with age. Herein, we compared the efficacies of Korean White ginseng (WG) and Korean Red Ginseng (RG) extracts (WGex and RGex, respectively) in an ischemic stroke mouse model and confirmed the underlying mechanisms of action. Methods: Mice were orally administered WGex or RGex 1 h before middle cerebral artery occlusion (MCAO), for 2 h; the size of the infarct area was measured 24 h after MCAO induction. Then, the neurological deficit score was evaluated and the efficacies of the two extracts were compared. Finally, their mechanisms of action were confirmed with tissue staining and protein quantification. Results: In the MCAO-induced ischemic stroke mouse model, WGex and RGex showed neuroprotective effects in the cortical region, with RGex demonstrating superior efficacy than WGex. Ginsenoside Rg1, a representative indicator substance, was not involved in mediating the effects of WGex and RGex. Conclusion: WGex and RGex could alleviate the brain injury caused by ischemia/reperfusion, with RGex showing a more potent effect. At 1,000 mg/kg body weight, only RGex reduced cerebral infarction and edema, and both anti-inflammatory and anti-apoptotic pathways were involved in mediating these effects.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4798-4808
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• 2022

The porous corrosion deposits (known as CRUD) adhered to the cladding have an important effect on the heat transfer from fuel rods to coolant in PWRs. The vapor film is the main constituent in the two-phase film boiling model. This paper presents a vapor film thickness correlation, associated with CRUD porosity, CRUD chimney density, CRUD particle size, CRUD thickness and heat flux. The dependences of the vapor film thickness on the various influential factors can be intuitively reflected from this vapor film thickness correlation. The temperature, pressure, and boric acid concentration distributions in CRUD can be well predicted using the two-phase film boiling model coupled with the vapor film thickness correlation. It suggests that the vapor thickness correlation can estimate the vapor film thickness more conveniently than the previously reported vapor thickness calculation methods.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.137-147
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• 2023

LiDAR is used in autonomous driving and various industrial fields to measure the size and distance of an object. In addition, the sensor also provides intensity images based on the amount of reflected light. This has a positive effect on sensor data processing by providing information on the shape of the object. LiDAR guarantees higher performance as the resolution increases but at an increased cost. These conditions also apply to LiDAR intensity images. Expensive equipment is essential to acquire high-resolution LiDAR intensity images. This study developed artificial intelligence to improve low-resolution LiDAR intensity images into high-resolution ones. Therefore, this study performed parameter analysis for the optimal super-resolution neural network model. The super-resolution algorithm was trained and verified using 2,500 LiDAR intensity images. As a result, the resolution of the intensity images were improved. These results can be applied to the autonomous driving field and help improve driving environment recognition and obstacle detection performance

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.233-254
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• 2023

Purpose - This study aims to verify whether the effect of tax avoidance on corporate value is non-linear in the Korean financial markets. Design/methodology/approach - This study believes that the cause of the inconsistent empirical analysis results of previous studies that verified the relationship between tax avoidance and firm value may be an error in assuming linearity, and verifies whether a nonlinear relationship exists. The sample company in this study is a December settlement corporation listed on the Korean stock market, and the analysis period is from 2000 to 2021. In the empirical analysis model, Tobin's Q is used as a proxy for corporate value, tax avoidance is used as the main independent variable, and a regression model is designed with corporate size, growth rate, and debt ratio set as control variables. Findings - As a result of the empirical analysis, it can be confirmed that there is an inverted U-shaped nonlinear relationship between tax avoidance and corporate value. In the additional analysis using Ohlson (1995) firm valuation model for the robustness of the results of the empirical analysis, the same nonlinear value relationship between tax avoidance can be confirmed. Research implications or Originality - This study is considered to be meaningful in that it verifies the non-linear relationship of tax avoidance, which has not been attempted in previous studies. The meaning of the inverted U-shaped nonlinear relationship presented in this study is that corporate tax avoidance acts as a factor that increases corporate value up to a certain level, but rather becomes a factor that decreases corporate value when it exceeds a critical point. These results are expected to provide new perspectives and perspectives on tax avoidance to companies belonging to the Korean capital market.

• Journal of the Korean Geotechnical Society
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• v.36 no.11
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• pp.157-165
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• 2020

At present, there are no clearly stated criteria or theories in calculating additional vertical dynamic loads that occur at the machine foundation due to vibration and reflecting them in the design at home and abroad. According to the domestic standard, although it is not a serious vibration condition, the additional dynamic load due to vibration is considered up to 100% of the static load. This is an extremely conservative design. The purpose of this study is to propose a model test method for evaluating the quantitative magnitude of additional dynamic loads that are generated at certain static loads due to vertical mechanical vibrations. As preliminary basic tests for the model tests, the test for evaluating the effects of reflective wave that may occur within a limited size soil box and the test for estimating the natural frequency of the devised model soil-foundation system were carried out. From the analysis of results for basic tests, a method to minimize the influence of the reflected wave was prepared, and the effect of the resonance of the model system was minimized during the model tests. After the basic tests, the main model tests were conducted. Through the proposed main test, the quantitative magnitude of additional dynamic loads caused by machine vibration on a shallow foundation for machine on medium dense sand foundations were evaluated. From the results of the model test, the feasibility of design applied at home and abroad was reviewed.

• Korean Journal of Ichthyology
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• v.19 no.1
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• pp.1-7
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• 2007

The effect of water temperature (T) and body weight (W) on the oxygen consumption of the fasted black rockfish, Sebastes schlegeli was investigated to provide empirical data for the culture management and bioenergetic growth model of this species. The mean wet body weights of two fish groups used for the present experiment were $12.9{\pm}2.7g$ ($mean{\pm}SD$) and $351.1{\pm}9.2g$. The oxygen consumption rate (OCR) was measured under three water temperature regimes (15, 20 and $25^{\circ}C$) at an interval of 5 minutes for 24 hours using a continuous flow-through respirometer. In each treatment three replicates were set up and 45 fish in small size groups and 6 fish in large size groups were used. The OCRs increased with increasing water temperature in both size groups (p<0.001). Mean OCRs at 15, 20 and $25^{\circ}C$ were 414.2, 691.5 and $843.8mg\;O_2\;kg^{-1}h^{-1}$ in small size groups, and 182.0, 250.7 and $328.2mg\;O_2\;kg^{-1}h^{-1}$ in large size groups, respectively. The OCRs decreased with increasing body weights in three water temperature groups (p<0.001). The mass effect on metabolic rate can be expressed by the power of 0.69~0.75. The data are best described by the relationship: OCR=89.12+28.79T-1.17W. $Q_{10}$ values ranged 1.90~2.79 between 15 and $20^{\circ}C$, 1.49~1.71 between 20 and $25^{\circ}C$, and 1.80~2.03 over the full temperature range, respectively. The energy loss by metabolic cost increased with increasing water temperature and decreasing body weight (p<0.001). Mean energy loss rates by oxygen consumption at 15, 20 and $25^{\circ}C$ were 282.9, 472.3 and $576.3kJ\;kg^{-1}d^{-1}$ in small size groups and 124.3, 171.3 and $224.1kJ\;kg^{-1}d^{-1}$ in large size groups, respectively.