• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.341-343
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• 2019

As the generation of high concentration particulate matter increases, much attention is focused on the prediction of particulate matter. Particulate matter refers to particulate matter less than $10{\mu}m$ diameter in the atmosphere and is affected by weather changes such as temperature, relative humidity and wind speed. Therefore, various studies have been conducted to analyze the correlation with weather information for particulate matter prediction. However, the nonlinear time series distribution of particulate matter increases the complexity of the prediction model and can lead to inaccurate predictions. In this paper, we try to mitigate the nonlinear characteristics of particulate matter by using cluster algorithm and classification algorithm of machine learning. The machine learning algorithms used are agglomerative clustering, density-based spatial clustering of applications with noise(DBSCAN).

• Geomechanics and Engineering
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• v.17 no.5
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• pp.485-496
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• 2019

Sealing of leakage in waterfront or water-retaining structures is one of the major issues in geotechnical engineering practices. With demands for biological methods as sustainable ground improvement techniques, bioclogging, defined as the reduction in hydraulic conductivity of soils caused by microbial activities, has been considered as an alternative to the chemical grout techniques for its economic advantages and eco-friendliness of microbial by-products. This study investigated the feasibility of bioaugmentation and biostimulation methods to induce fermentation-based bioclogging effect in coarse sands. In the bioaugmentation experiments, effects of various parameters and conditions, including grain size, pH, and biogenic gas generation, on hydraulic conductivity reduction were examined through a series of column experiments while Leuconostoc mesenteroides, which produce an insoluble biopolymer called dextran, was used as the model bacteria. The column test results demonstrate that the accumulation of bacterial biopolymer can readily reduce the hydraulic conductivity by three-to-four orders of magnitudes or by 99.9-99.99% in well-controlled environments. In the biostimulation experiments, two inoculums of indigenous soil bacteria sampled from waterfront embankments were prepared and their bioclogging efficiency was examined. With one inoculum containing species capable of fermentation and biopolymer production, the hydraulic conductivity reduction by two orders of magnitude was achieved, however, no clogging was found with the other inoculum. This implies that presence of indigenous species capable of biopolymer production and their population, if any, play a key role in causing bioclogging, because of competition with other indigenous bacteria. The presented results provide fundamental insights into the bacterial biopolymer formation mechanism, its effect on soil permeability, and potential of engineering bacterial clogging in subsurface.

• International journal of steel structures
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• v.18 no.4
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• pp.1191-1199
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• 2018

Concepts of submerged floating tunnels (SFTs) for land connection have been continuously suggested and developed by several researchers and institutes. To maintain their predefined positions under various dynamic environmental loading conditions, the submerged floating tunnels should be effectively moored by reasonable mooring systems. With rational mooring systems, the design of SFTs should be confirmed to satisfy the structural safety, fatigue, and operability design criteria related to tunnel motion, internal forces, structural stresses, and the fatigue life of the main structural members. This paper presents a feasibility study of a submerged floating tunnel moored by an inclined tendon system. The basic structural concept was developed based on the concept of conventional cable-stayed bridges to minimize the seabed excavation, penetration, and anchoring work by applying tower-inclined tendon systems instead of conventional tendons with individual seabed anchors. To evaluate the structural performance of the new type of SFT, a hydrodynamic analysis was performed in the time domain using the commercial nonlinear finite element code ABAQUS-AQUA. For the main dynamic environmental loading condition, an irregular wave load was examined. A JONSWAP wave spectrum was used to generate a time-series wave-induced hydrodynamic load considering the specific significant wave height and peak period for predetermined wave conditions. By performing a time-domain hydrodynamic analysis on the submerged floating structure under irregular waves, the motional characteristics, structural stresses, and fatigue damage of the floating tunnel and mooring members were analyzed to evaluate the structural safety and fatigue performance. According to the analytical study, the suggested conceptual model for SFTs shows very good hydrodynamic structural performance. It can be concluded that the concept can be considered as a reasonable structural type of SFT.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.311-318
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• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.

• Advances in nano research
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• v.10 no.5
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• pp.449-460
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• 2021

Flexoelectricity is an interesting materials' property that is more touchable in small scales. This property beside the sandwich structures placed in the center of scientists' attention due to their extraordinary effects on the mechanical properties. Furthermore, in the passage of decades, more elaborated sandwich structures took into consideration results from using honeycomb core. This kind of structure, inspiring from honeycomb core, provides more stiffness to weight ratio, which plays a crucial role in different industries. In this paper, based on the Love-Kirchhoff's hypothesis, Hamilton's principle, modified couple stress theory and Fourier series analytical method, equations of motion for a sandwich plate containing a honeycomb core integrated by two face-sheets have derived and solved analytically. The equations of both face sheets have derived by flexoelectricity consideration. Moreover, it should be noticed that the whole structure rests on the visco-Pasternak foundation. Conducting current research provided an acceptable and throughout study based on flexoelectricity to address the effect of materials' characteristics, length-scale parameter, aspect, and thickness ratios and boundary conditions on the natural frequency of honeycomb sandwich plates. Also, based on the presented figures and tables, there is a close agreement between previous studies and recent work. Due to the high ratio of strength to weight, current model analyzing is capable of taking into account for different vehicles' manufacturing in a high range of industries.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.697-710
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• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.255-269
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• 2020

Purpose - This paper analyzes the market efficiency focusing on the long memory properties of the domestic futures market. By decomposing futures prices into yield and volatility and looking at the long memory properties of the time series, this study aims to understand the futures market pricing and change behavior and risks, specifically and in detail. Design/methodology/approach - This study analyzes KOSPI 200 futures, KOSDAQ 150 futures, 3 and 10-year government bond futures, US dollar futures, yen futures, and euro futures, which are among the most actively traded on the Korea Exchange. To analyze the long memory and market efficiency, we used the Variance Ratio, Rescaled-Range(R/S), Geweke and Porter-Hudak(GPH) tests as semi- parametric methods, and ARFIMA-FIGARCH model as the parametric method. Findings - It was found that all seven futures supported the efficiency market hypothesis because the property of long memory turned out not to exist in their yield curves. On the other hand, in futures volatility, all 7 futures showed long memory properties in the analysis, which means that if new information is generated in the domestic futures market and the market volatility once expanded due to the impact, it does not decrease or shrink for a long period of time, but continues to affect the volatility. Research implications or Originality - The results of this paper suggest that it can be useful information for predicting changes and risks of volatility in the domestic futures market. In particular, it was found that the long memory properties would be further strengthened in the currency futures and bond rate futures markets after the global financial crisis if the regime changes of the domestic financial market are taken into account in the analysis.

• Journal of Society of Preventive Korean Medicine
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• v.24 no.3
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• pp.57-67
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• 2020

Background : The Life cycle Health Promotion Programs using Traditional Korean Medicine (the Life cycle HaPPs-TKM) are the on-going 3rd stage projects that have centered on the development and dissemination of the standard life cycle HaPPs-TKM in the local community. The purpose of the study was to introduce the development background of the standard life cycle HaPPs-TKM and to suggest its activation plan. Methods : Academic and government research reports on the life cycle HaPPs-TKM were analyzed to introduce the development process, development backgrounds and the details of KM-HPP for each life cycle, such as infants and toddlers, adolescents, pregnant women, adults and the elderly. Results : We reviewed the development process of the standard life cycle HaPP-TKM consisted of a series of diagnosis on community members' health problems, establishment of project purpose, research on the involvement of KM intervention in a project, and final development of the project model. And we rediscovered that in the development backgrounds of KM-HPP, there were beneficial goals to manage and promote public health conditions for each life cycle. Conclusion : To activate life cycle HaPPs-TKM, we would recommend that activation plan should include six factors through systematic analysis of research reports. These factors consist of diversified goals for each life-cycle, competency reinforcement of local project manager, diversified Korean Medicinal modalities to enhance Sasang Constitution and Qigong, development of standard Outcome Index, periodical holding of performance contest, and improved guidance of government and associated entities through whole process of HaPP-TKM.

• International Area Studies Review
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• v.12 no.2
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• pp.3-26
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• 2008

This article investigates the usefulness of the skewed Student-t distribution in modeling the long memory volatility property that might be present in the daily returns of two Australian financial series; the ASX200 stock index and AUD/USD exchange rate. For this purpose we assess the performance of FIGARCH and FIAPARCH Value-at-Risk (VaR) models based on the normal, Student-t, and skewed Student-t distribution innovations. Our results support the argument that the skewed Student-t distribution models produce more accurate VaR estimates of Australian financial markets than the normal and Student-t distribution models. Thus, consideration of skewness and excess kurtosis in asset return distributions provides appropriate criteria for model selection in the context of long memory volatility models in Australian stock and foreign exchange markets.

• (The)Study of the Eastern Classic
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• no.33
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• pp.7-29
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• 2008

Jang, Hyeon-Guang is one of the representative natural philosophers of Joseon Korea. This article aims to investigate the meaning of the factors of Xiangshuxue(象數學) contained in his cosmology. Xiangshuxue applies Image(Xiang), Numeral(Shu) and In-Yang to present the distinctions, inter-relations and time-series orders of things. Jang's cosmology, combined with Xiangshuxue, insisted that Li(Principle) is infinite in time and space, the cosmos is finite on the other side. This assures that the moral principle is absolute and eternal. Jang emphasized the book I-ching as the criterion and the model in understanding the nature. This restrained the objectivizm of Shaoyong and made his concept 'natural law' difficult to change itself as the experience and the knowledge expand. None the less, his cosmology is appraised in that it strengthened natural philosophical basis of neo-confucianism and preceded the cosmological investigations since mid-Joseon dynasty.