• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.537-543
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• 2006

There have been many recent studies on the nonlinear rainfall-runoff modeling, where the use of neural networks is shown to be quite successful. Due to fundamental limitation of linear structures, employing linear models has often been considered inferior to the neural network approaches in this area. However, we believe that with an appropriate extension, the concept of linear impulse responses can be a viable tool since it enables us to understand underlying dynamics principles better. In this paper, we propose the use of multiple impulse responses for the problem of rainfall-runoff analysis. The proposed method is based on a simple and fixed strategy for switching among multiple linear impulse-response models, each of which satisfies the constraints of non-negativity and uni-modality. The computational analysis performed for a certain Korean hydrometeorologic data set showed that the proposed method can yield very meaningful results.

• International Area Studies Review
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• v.13 no.2
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• pp.66-88
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• 2009

This paper studies optimal discretionary monetary policy in the presence of uncertainty in the housing sector. In particular, we allow two possible regimes regarding the evolution of housing price inflation and the effects of housing price inflation on the aggregate demand. Estimation results with the US data confirm the presence of two distinctive regimes, one 'normal' and the other more akin to the housing price 'bubble' state. The optimal policy is 'asymmetric' in that the optimal responses in the 'normal' regime require the central bank to lean against the wind to inflationary pressure from CPI and housing inflation, while the central bank is recommended to accommodate it in the other regime.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.253-261
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• 2018

Korea Astronomy and Space Science Institute (KASI) has been developing the space optical and laser tracking (SOLT) system for space geodesy, space situational awareness, and Korean space missions. The SOLT system comprises satellite laser ranging (SLR), adaptive optics (AO), and debris laser tracking (DLT) systems, which share numerous subsystems, such as an optical telescope and tracking mount. It is designed to be capable of laser ranging up to geosynchronous Earth orbit satellites with a laser retro-reflector array, space objects imaging brighter than magnitude 10, and laser tracking low Earth orbit space debris of uncooperative targets. For the realization of multiple functions in a novel configuration, the SOLT system employs a switching mirror that is installed inside the telescope pedestal and feeds the beam path to each system. The SLR and AO systems have already been established at the Geochang station, whereas the DLT system is currently under development and the AO system is being prepared for testing. In this study, the design and development of the SOLT system are addressed and the SLR data quality is evaluated compared to the International Laser Ranging Service (ILRS) tracking stations in terms of single-shot ranging precision. The analysis results indicate that the SLR system has a good ranging performance, to a few millimeters precision. Therefore, it is expected that the SLR system will not only play an important role as a member of the ILRS tracking network, but also contribute to future Korean space missions.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.89-99
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• 2019

The project to utilize kenaf as thermal power plant fuel has a positive effect on the unused energy utilization, greenhouse gas reduction, and farm income. However, it is analyzed that it is difficult to secure economical efficiency because the fuel cost of kenaf is higher than that of power by thermal power plant and Renewable Energy Certification (REC). The project of power generation using kenaf is meet the government's major policies, while government support is essential for securing economical efficiency. As a result of the sensitivity analysis on the ratio of the government subsidies, to secure economical efficiency, the power generation prices using kenaf through the direct financial support of the government indicate that 47% and 76% of kenaf fuel cost are supported by government in case of the Saemangeum reclamation and Gangneung-si, respectively. In the case of the government indirect policy support, if kenaf is included as a renewable energy source of Renewable Energy Portfolio Standard and REC is granted, the economic efficiency of Saemangeum reclamation and Gangneung-si is obtained when REC secured at 1.05 or more and 2.43 or more, respectively. The results of this study are meaningful in that the direct and indirect effects of the government on the development of the herbaceous energy crop, kenaf, were evaluated economically. These results are to suggest the need for demonstration study, but economics analyze and evaluate are necessary based on operational data through the demonstration phase in the future.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.15-30
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• 2021

Purpose: Year of 2020, COVID-19 has been changing the people's everyday life to ways never been thought of before all over the world. The IT and electronic industry, the methods of supplying goods and services have been changed from contact to un-tact environments based on un-tact systems very rapidly. COVID-19 has been striking the tourism and the travel industry, especially the airline and hotel industry of which services are provided by human. For the passenger service of airliner, automation has been propelled and un-tact style of service has become mainstreams except cabin service since 2000's. For passenger transportation, due to traffic regulations and exclusions etc., switching to new ways is not easy. However, under the new environment made by COVID-19, kiosk check-in, web check-in and mobile check-in has become more important. In this study, the characteristics of airline customers using mobile goods are investigated to find ways to raise the rate of utilizing mobile check-in and to increase the efficiency of boarding process. Research design, data, and methodology: Considering the COVID-19 environment, survey was done by online research company. The research model is designed to integrate the user characteristics and usage/purchase motive and technology acceptance theory. Especially considering infectious diseases prevention, concern of safety is adopted as one of the usage motive variable. Results: Extraversion or conscientiousness characteristics prefers counter check-in(contact service), while openness characteristics prefers mobile check-in(un-tact service). Concern of safety for infectious disease shows strong non-preference on counter check-in. Conclusions: Regarding service type regardless of type of the industry, automation and un-tact have been mainstreams due to high costs of labor, efficiency and standardization issue, etc., and COVID-19 has given impetus to them. For airliner, un-tact service including boarding process service has been more and more important. To raise the rate of un-tact service use, the characteristics of the user should be analyzed first. The study results indicate that for extraversion or conscientiousness, some kinds of methods to induce them to use un-tact service more are needed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.722-728
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• 2020

Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.12-19
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• 2021

This paper presents a safety assessment method for FTA-based induction heating systems; the failures and causes of electrical fire are first analyzed for each part and module qualitatively, and methods to manage high probabilities of failure and electrical fire are considered, thereby improving the reliability of the induction heating system. The cumulative importance value (ACC) of the minimal cut set is drawn by setting failure as the top event, and STACK and SMPS are observed to account for about 70% of the induction heating system failures. Thus, intensively managing the basic events contained in the minimal cut set of failures for STACK and SMPS is expected to provide effective and stable operation of the induction heating system. When electrical fire is set as the top event, the STACK percentage is 90%. Accordingly, the current IGBT is changed to a FET to increase the applied voltage and prevent induction heating system failure, and a heat sink plane is installed to prevent FET heating caused by switching, thereby preventing an electrical fire. By classifying the parts and modules of the induction heating system in detail and by applying FTA based on actual failure rates and relevant data, more practical and reasonable results may be expected. Hence, continuous research must be conducted to ensure safety when using induction heating systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.431-433
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• 2022

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. Image denoising is one of the basic processes of image processing, and is used as a preprocessing step in many applications. Various studies have been conducted to remove noise, but various problems arise in the process of noise removal, such as image detail preservation, texture restoration, and special noise removal. In this paper, we propose a digital filter using an extended convolutional mask to preserve image detail during the impulse denoising process. The proposed algorithm uses an extended convolution mask as a filtering mask, and obtains the final output by switching the extension level according to the noise level. Simulation was conducted to evaluate the performance of the proposed algorithm, and the performance was analyzed compared to the existing method.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.85-100
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• 2023

The stochastic volatility (SV) model is one of the main methods of modeling time-varying volatility. In particular, SV model is actively used in estimation and prediction of financial market volatility and option pricing. This paper attempts to model the time-varying volatility of the bitcoin market price using SV model. Hidden Markov model (HMM) is combined with the SV model to capture characteristics of regime switching of the market. The HMM is useful for recognizing patterns of time series to divide the regime of market volatility. This study estimated the volatility of bitcoin by using data from Upbit, a cryptocurrency trading site, and analyzed it by dividing the volatility regime of the market to improve the performance of the SV model. The MCMC technique is used to estimate the parameters of the SV model, and the performance of the model is verified through evaluation criteria such as MAPE and MSE.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.141-156
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• 2008

Market structure analysis is a very useful tool to analyze the competition boundary of the brand or the company. But most of the studies in market structure analysis, the concern lies in nondurable goods such as candies, soft drink and etc. because of the their availability of the data. In the field of durable goods, the limitation of the data availability and the repurchase time period constrain the study. In the analysis of the automobile market, those of views might be more persuasive. The purpose of this study is to analyze the structure of automobile market based on some idea suggested by prior studies. Usually the buyers of the automobile tend to buy upper tier when they buy in the next time. That kind of behavior make it impossible to analyze the structure of automobile market under the level of automobile model. For that reason I tried to analyze the market structure in the brand or company level. In this study, consideration data was used for market structure analysis. The reasons why we used the consideration data are summarized as following. Firstly, as the repurchase time cycle is too long, brand switching data which is used for the market analysis of nondurable good is not avaliable. Secondly, as we mentioned, the buyers of the automobile tend to buy upper tier when they buy in the next time. We used survey data collected in the U.S.A. market in the year of 2005 through questionaire. The sample size was 8,291. The number of brand analyzed in this study was 9 among 37 which was being sold in U.S.A. market. Their market share was around 50%. The brands considered were BMW, Chevrolet, Chrysler, Dodge, Ford, Honda, Mercedes, and Toyota. �� ratio was derived from frequency of the consideration set. Actually the frequency is different from the brand switch concept. In this study to compute the �� ratio, the frequency of the consideration set was used like a frequency of brand switch for convenience. The study can be divided into 2 steps. The first step is to build hypothetical market structures. The second step is to choose the best structure based on the hypothetical market structures, Usually logit analysis is used for the choice best structure. In this study we built 3 hypothetical market structure. They are type-cost, cost-type, and unstructured. We classified the automobile into 5 types, sedan, SUV(Sport Utility Vehicle), Pickup, Mini Van, and Full-size Van. As for purchasing cost, we classified it 2 groups based on the median value. The median value was $28,800. To decide best structure among them, maximum likelihood test was used. Resulting from market structure analysis, we find that the automobile market of USA is hierarchically structured in the form of 'automobile type - purchasing cost'. That is, result showed that automobile buyers considered function or usage first and purchasing cost next. This study has some limitations in the analysis level and variable selection. First, in this study only type of the automobile and purchasing cost were as attributes considered for purchase. Considering other attributes is very needful. Because of the attributes considered, only 3 hypothetical structure could be analyzed. Second, due to the data, brand level analysis was tried. But model level analysis would be better because automobile buyers consider model not brand. To conduct model level study more cases should be obtained. That is for acquiring the better practical meaning, brand level analysis should be conducted when we consider the actual competition which occurred in the real market. Third, the variable selection for building nested logit model was very limited to some avaliable data. In spite of those limitations, the importance of this study lies in the trial of market structure analysis of durable good.