• International Area Studies Review
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• v.12 no.3
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• pp.49-67
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• 2008

In this paper, we address the problem of optimal monetary policy rule in the presence of abrupt shifts in the structure of the economy. To do so, we first estimate a Markov switching model for the US housing price inflation, and find evidence supporting the presence of two distinct regimes for the US housing price inflation. One of the two regimes identified appears 'usual', in that housing price inflation negatively responds to higher real interest rate. The other regime is 'unusual', in that the housing price inflation is positively related with real interest rate. We then solve an optimal control problem of the FRB under the presence of the two regimes thus identified. The optimal policy is 'asymmetric' in that the optimal responses in the 'usual' regime require the FRB to lean against the wind to inflationary pressure, while the FRB is recommended to accommodate it in the unusual regime. It is also found that the optimal degree of responses is more conservative when the FRB acknowledges the uncertainty about future regime.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.23 no.4
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• pp.204-217
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• 2018

This study proposes a cost-effective method to monitor coastal environments using e-Navigation-implemented domestic and international ferries, and to analyze big data of records such as wind, temperature, salinity, waves, and currents that are gathered through e-Navigation system. First, we present the concept and architecture of e-Navigation operation system based on the General Information Center on Maritime Safety and Security. Then, the marine observation system that can be applied to ferries operating in our nation's territory is discussed. Analytical methods, such as spatio-temporal mixed effects model, ensemble method, and meshfree method, in handling real-time big data obtained by the e-Navigation observing system are then explained in detail. This study will support the implementation of the Korean e-Navigation project that focuses on the safety of small vessels such as coasters and fishing vessels.

• Atmosphere
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• v.28 no.4
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• pp.457-467
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• 2018

This study investigated the variability of spring (March-May) forest fire risk in Korea for the period 1991~2017 and analyzed its relationship with large-scale climate factors. The Forest Weather Index (FWI) representing the meteorological risk for forest fire occurrences calculated based on observational data and its relationship with large-scale climate factors were analyzed. We performed the empirical orthogonal function (EOF) analysis on the spring FWI. The leading EOF mode of FWI accounting for about 70% of total variability was found to be highly correlated with total number of forest fire occurrences in Korea. The high FWI, forest fire occurrence risk, in Korea, is associated with warmer atmosphere temperature in midwest Eurasia-China-Korea peninsula, cyclonic circulation anomaly in northeastern China-Korea peninsula-northwest pacific, westerly wind anomaly in central China-Korea peninsula, and low humidity in Korea. These are further related with warmer sea surface temperature and enhanced outgoing longwave radiation over Western Pacific, which represents a typical condition for a La $Ni\tilde{n}a$ episode. This suggests that large-scale climate factors over East Asia and ENSO could have a significant influence on the occurrence of spring forest fires in Korea.

• Steel and Composite Structures
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• v.31 no.1
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• pp.99-112
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• 2019

Semi-rigid joints have been widely studied in literature in recent decades because they affect greatly the structural response of frames. In literature, the behavior of semi-rigid joints is commonly assumed to be identical under positive and negative moments which are obviously incorrect in many cases where joint details such as bolt arrangement or placement of haunch are vertically asymmetrical. This paper evaluates two common types of steel frames with asymmetrical beam-to-column joints by Direct Analysis allowing for plasticity. A refined design method of steel frames using a proposed simple forth order curved-quartic element with an integrated joint model allowing for asymmetrical geometric joint properties is presented. Furthermore, the ultimate behavior of six types of asymmetrical end-plate connections under positive and negative moment is examined by the Finite Element Method (FEM). The FEM results are further applied to the proposed design method with the curved-quartic element for Direct Analysis of two types of steel frames under dominant gravity or wind load. The ultimate frame behavior under the two different scenarios are examined with respect to their failure modes and considerably different structural performances of the frames were observed when compared with the identical frames designed with the traditional method where symmetrical joints characteristics were assumed. The finding of this research contributes to the design of steel frames as their asymmetrical beam-to-column joints lead to different frame behavior when under positive and negative moment and this aspect should be incorporated in the design and analysis of steel frames. This consideration of asymmetrical joint behavior is recommended to be highlighted in future design codes.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.

• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.222-228
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• 2019

An extreme value analysis (EVA) is essential to obtain a design value for highly nonlinear variables such as long-term environmental data for wind and waves, and slamming or sloshing impact pressures. According to the extreme value theory (EVT), the extreme value distribution is derived by multiplying the initial cumulative distribution functions for independent and identically distributed (IID) random variables. However, in the position mooring of DNVGL, the sampled global maxima of the mooring line tension are assumed to be IID stochastic variables without checking their independence. The ITTC Recommended Procedures and Guidelines for Sloshing Model Tests never deal with the independence of the sampling data. Hence, a design value estimated without the IID check would be under- or over-estimated because of considering observations far away from a Weibull or generalized Pareto distribution (GPD) as outliers. In this study, the IID sampling data are first checked in an EVA. With no IID random variables, an automatic resampling scheme is recommended using the block maxima approach for a generalized extreme value (GEV) distribution and peaks-over-threshold (POT) approach for a GPD. A partial autocorrelation function (PACF) is used to check the IID variables. In this study, only one 5 h sample of sloshing test results was used for a feasibility study of the resampling IID variables approach. Based on this study, the resampling IID variables may reduce the number of outliers, and the statistically more appropriate design value could be achieved with independent samples.

• Wind and Structures
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• v.28 no.5
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• pp.285-298
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• 2019

For super long-span bridges, the aerodynamic forces induced by the flow passing the box girder should be considered carefully. And the Reynolds number sensitively of aerodynamic characteristics is one of considerable issue. In the study, a numerical study on the Reynolds number sensitivity of aerodynamic characteristic (flow pattern, pressure distribution and aerodynamic forces) of a twin-box girder were carried out using large eddy simulation (LES) with the dynamic Smagorinsky-Lilly subgrid model. The results show that the aerodynamic characteristics have strong correlation with the Reynolds number. At the leading edge, the flow experiences attachment, departure, and reattachment stages accompanying by the laminar transition into turbulence, causing pressure plateaus to form on the surface, and the pressure plateaus gradually shrinks. Around the gap, attributing that the flow experiences stages of laminar cavity flow, the wake with alternate shedding vortices, and turbulent cavity flow in sequence with an increase in the Reynolds number, the pressures around the gap vary greatly with the Reynold number. At the trailing edge, the pressure gradually recovers as the flow transits to turbulence (the flow undergoes wake instability, shear layer transition-reattachment station), In addition, at relative high Reynolds numbers, the drag force almost does not change, however, the lift force coefficient gradually decreases with an increase in Reynolds number.

• 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).

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1183-1194
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• 2021

Traditionally, electric power systems have been known as the centralized structures, which is organized into placing customers at the end of the supply chain. However, recent decades have witnessed the emergence of distributed energy resources(:DERs) such as rooftop solar, farming PV system, small wind turbines, battery energy storage systems and smart home appliances. With the emergence of distributed energy resources, the role of distributed system operators(:DSOs) will expand. The increasing penetration of DERs could lead to a less predictable and reverse flow of power in the system, which can affect the traditional planning and operation of distribution and transmission networks. This raises the need for a change in the role of the DSOs that have conventionally planned, maintained and managed networks and supply outages. The objective of this research is to designed the future distribution operation system with multi-DERs and the proposed distribution system model is implemented by hardware-in-the-loop simulation(HILS). The test results show the normal operation domain and reduction of distribution line loss.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.291-299
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• 2021

Recently, due to environmental problems caused by densification and high rise of urban areas, interests in air flow is increasing and appropriate shape and layout design of buildings is required. Therefore, in this study, we intend to propose an experimental method that can observe the air flow around a building using thermochromic pigment. Thermochromic pigments have limitations in observing precise temperature changes due to the characteristic that the color changes only with respect to a specific temperature, but they have the advantages of easy configuration of experimental equipment and short time required for experiments. In this study, the air flow tendencies around a building was examined by performing CFD analysis for a simple model and then compared with the thermochromic experiment results in order to review the usefulness of the proposed experimental method. As a result of the experiment, it was possible to observe the formation of separated flow and vortex region generated by buildings using the charateristics of thermochromic pigment and it was confirmed that the proposed method can be useful for buildings design and urban city planning.