• Spatial Information Research
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• v.17 no.3
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• pp.341-350
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• 2009

As the power and scale of typhoons are growing due to global warming and socioeconomic damages induced by super-typhoons are increasing, it is important to estimate inundation damages and to prepare proper adaptation plans against an attack of the super-typhoon. In this paper, we estimated the inundation damages of urban area around Haeundae beach induced by super-typhoons which follow the route of Typhoon Maemi with the conditions of Typhoon Vera (Ise Bay in Japan, 1959), Typhoon Durian (Philippine, 2006) and Hurricane Katrina (New Oleans in U.S.A, 2005). The coastal area around the Haeundae beach (Busan and Gyeongnam province) is expectedly damaged by severe storm surges. In this study we calculated the rise of sea level height after harmonizing the different datum levels of land and ocean and estimated the inundation depth, inundation area and the amount of building damages by using airborne LiDAR data and GIS spatial analysis techniques more accurately and quantitatively. As many researchers are predicting that super-typhoon of overwhelming power will occur around the Korean peninsula in the near future, the results of this study are expected to contribute to producing coastal inundation map and evacuation planning.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.173-181
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• 2017

In this paper, we have studied tracking as a training stage of considering the position and the scale of a person given its previous position, scale, as well as next and forward image fraction. Unlike other learning methods, CNN is thereby learning combines both time and spatial features from the image for the two consecutive frames. We introduce multiple path ways in CNN to better fuse local and global information. A creative shift-variant CNN architecture is designed so as to alleviate the drift problem when the distracting objects are similar to the target in cluttered environment. Furthermore, we employ CNNs to estimate the scale through the accurate localization of some key points. These techniques are object-independent so that the proposed method can be applied to track other types of object. The capability of the tracker of handling complex situations is demonstrated in many testing sequences. The accuracy of the SVM classifier using the features learnt by the CNN is equivalent to the accuracy of the CNN. This fact confirms the importance of automatically optimized features. However, the computation time for the classification of a person using the convolutional neural network classifier is less than approximately 1/40 of the SVM computation time, regardless of the type of the used features.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.9-19
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• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• Journal of Korea Water Resources Association
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• v.48 no.2
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• pp.115-126
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• 2015

In recent years, debris flow disaster has occurred in multiple locations between high and low mountainous areas simultaneously with a flooding disaster in urban areas caused by heavy and torrential rainfall due to the changing global climate and environment. As a result, these disasters frequently lead to large-scale destruction of infrastructures or individual properties and cause psychological harm or human death. In order to mitigate these disasters more effectively, it is necessary to investigate what causes the damage with an integrated model of both disasters at once. The objectives of this study are to analyze the mechanism of debris flow for real basin, to determine the PMP and run-off discharge due to the DAD analysis, and to estimate the influence range of debris flow for fan area according to the scenario. To analyse the characteristics of debris flow at the real basin, the parameters such as the deposition pattern, deposit thickness, approaching velocity, occurrence of sediment volume and travel length are estimated from DAD analysis. As a results, the peak time precipitation is estimated by 135 mm/hr as torrential rainfall and maximum total amount of rainfall is estimated by 544 mm as typhoon related rainfall.

• Korean Journal of Construction Engineering and Management
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• v.15 no.3
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• pp.83-91
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• 2014

The problems of environmental pollutions and resources depletion have been growing issues in global construction recently. Efforts to reduce $CO_2$ emission have been also made in all sectors of construction industry these days. As one of the biggest industries that consume a huge amount of resources and generate complex construction wastes, the construction industry has significant impacts on environment issues. However, systematic approach to manage wastes has been rarely made, and most construction wastes from construction sites are being land-filled or incinerated. In this study, a system is proposed to predict the amount of wastes in visual formats, and to control the process of wastes management. The system's main functions include : (1) to estimate the amount of wastes to be generated in project schedule, (2) to categorize the types of wastes, (3) to determine the timing of taking out wastes from sites, and (4) to share information regarding wastes for recycling. A huge amount of wastes are generated in construction process, but most of the wastes have been discharged in forms of mixed wastes, which make them hardly reused. The system not only provide information on wastes to be generated, but also prevent mixing various wastes by classifying them by types and schedules. This features of the system, along with functions to share wastes information with other agencies outside the site, are expected to enhance the level of wastes recycling to a great extent. By saving construction materials through wastes recycling, the system also contributes in reducing $CO_2$ emission.

• KDI Journal of Economic Policy
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• v.36 no.2
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• pp.103-136
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• 2014

The covered interest rate parity condition (CIRP) has been widely used in open macroeconomic analysis, risk management, exchange rate forecasts, and so forth. Due to the recent global financial crises, there have been remarkable changes in the financial markets of the emerging markets. These changes possibly influenced the dynamics of the covered interest rate parity condition. In this paper, we investigate whether the CIRP dynamics has changed, and what is the nature of the regime changes. To do this, we propose and estimate multiple-state Markov regime switching models using a Bayesian MCMC method. Our estimation results indicate that the default risk or the deviation from the CIRP has been decreased after the crisis. It seems to be associated with the more active interaction between the short-term bond market and the short-term foreign exchange market than before. The tightened relation of these two financial markets is caused by the arbitrage transaction of foreign investors.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.527-556
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• 2019

In Korea, nearly 100 billion won is spent annually under the name of energy voucher on 600,000 households for the last five years, and this is a unique case and hard to monitor worldwide. Therefore, no studies have been conducted to assess impacts of the energy voucher on energy consumption and cost burden alleviation for beneficiaries. This paper aims to demonstrate the effectiveness of energy vouchers in terms of energy expense. The propensity score matching was conducted on samples of low-income households based on the Korea Welfare Panel. Then, simple Difference-In-Differences and Fixed-Effect Difference-In-Differences models were applied to estimate the effect of energy vouchers. In results, the beneficiaries of energy vouchers would spend an additional 4,371~4,870 won per month on energy consumption. The ratio is equivalent to 51.9~57.7 percent of the aid, which is also the highest when compared with 23~56 percent of U.S. Food Stamp. In terms of energy welfare, voucher payment could become one of the best management practices. However, identifying the blind spots as non-reciprocal households and expanding the differential support mechanism that reflects the energy consumption environment should be solved in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.489-492
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• 2006

Red tide occurred sporadically in early 90s. But It is happening extensively by global warming. So, Airline observation, Red tide buoy development, and Red tide alarm system research is progressing for monitor ring. However, study to early forecast red tide and red tide alarm system did not exist hard. This paper proposed development that design and implementation red tide database of using wireless sensor network. There are GPS, Water Temperature sensor, Oxygen sensor, and Turbidity sensor in each node. And data is stored to red tide database through Ad-hoc network. This data is integrated and analyzed. So, forecast red tide. And red tide database has red tide data that happen at past. This is utilized to comparative analysis data for red tide estimate. Main screen displays position of node and measured value in electron map. Much studies must be backed for this a study. But I think that contribute to analyze red tide data by red tide database construction.

• Fire Science and Engineering
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• v.26 no.4
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• pp.55-62
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• 2012

The suppression mechanisms of carbon dioxide ($CO_2$) as a representative fire suppression agent were revisited using a counterflow diffusion flame which could be applied the concept of a local application system. To end this, the low strain rate $CH_4$/air counterflow diffusions with $CO_2$ addition in either fuel or oxidizer stream were examined numerically using detailed-kinetic chemistry. Radiative heat loss due to radiating gas species including $CO_2$ added was considered by the optically thin model (OTM). As a result, the critical $CO_2$ volume fractions in the oxidizer stream required to extinguish the flame were in good agreement with the experimental data reported in the literature, while somewhat under-prediction was observed with $CO_2$ added in the fuel stream. The surrogate agents were adopted to estimate the quantitative contribution with changing in global strain rate ($a_g$) on the flame extinguishment among pure dilution effect, thermal effects including radiation heat loss and chemical effect due to the $CO_2$ fire suppression agent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.609-617
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• 2016

In general, Personal Navigation Systems (PNSs) can be defined systems to acquire pedestrian positional information. GPS is an example of PNS. However, GPS can only be used where the GPS signal can be received. Pedestrian Dead Reckoning (PDR) can estimate the positional information of pedestrians using Inertial Measurement Unit (IMU). Therefore, PDR can be used for GPS-disabled areas. This paper proposes a PDR scheme considering various movement types over GPS-disabled areas as combat environments. We propose a movement distance estimation scheme and movement direction estimation scheme as pedestrian's various movement types such as walking, running and crawling using IMU. Also, we propose a fusion algorithm between GPS and PDR to mitigate the lack of accuracy of positional information at the entrance to the building. The proposed algorithm has been tested in a real test bed. In the experimental results, the proposed algorithms exhibited an average position error distance of 5.64m and position error rate in goal point of 3.41% as a pedestrian traveled 0.6km.