• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Korean Journal of Construction Engineering and Management
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• v.14 no.6
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• pp.22-29
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• 2013

As construction projects are getting larger, more complex and specialized, the size and scale of the structures are increasing and large-scale projects with multiple participants involved have continuously been ordered. Due to the nature of a large-scale construction project, when there are interferences and conflicts in process, schedule and area among project participants, the project requires more time and efforts to resolve the issues as it progresses further. This study suggests the interface management model that is time-saving and physically beneficial in solving interface issues based on case study. This study provides a practical management model including the organization of interface consultative group, checklist preparation, LIST management and PMIS application, which will be useful for the construction sites seeking effective know-how to manage design interferences and changes.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.529-532
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• 2005

In anomaly intrusion detection, how to model the normal behavior of activities performed by a user is an important issue. To extract the normal behavior as a profile, conventional data mining techniques are widely applied to a finite audit data set. However, these approaches can only model the static behavior of a user in the audit data set This drawback can be overcome by viewing the continuous activities of a user as an audit data stream. This paper proposes a new clustering algorithm which continuously models a data stream. A set of features is used to represent the characteristics of an activity. For each feature, the clusters of feature values corresponding to activities observed so far in an audit data stream are identified by the proposed clustering algorithm for data streams. As a result, without maintaining any historical activity of a user physically, new activities of the user can be continuously reflected to the on-going result of clustering.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.553-568
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• 2005

In order to integrate distributed biological information sources physically or virtually, it is necessary to overcome the heterogeneity of information sources and support a superior generality and adaptation in order to satisfy user's various demands. In this paper, we present a flexible and general XML query engine of a wrapper system in designing the middleware system to integrate data as well as application programs. Since this query engine applies user-defined XML view, it is possible to composite flexible integrated query. The query processing in a wrapper requires view composition, query translation into local sources, and generation of XML documents from local query results. We present a query processing model based on the view tree, where the n views and the XML queries are represented by the view tree. Moreover, to confirm the generality of our query processing model, we present a methodology of query processing for relational databases, web sources, and application programs whose return types of query results are relational tuples or XML documents.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.8
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• pp.553-561
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• 2017

The main motivation for this study was to establish a CFD-based procedure for the analysis of heating characteristics, particularly in industrial furnaces. As certain open-source software packages have gained popularity in dealing with complex industrial problems, the OpenFOAM framework was selected for further development of advanced physical models to meet industrial requirements. In this study, the newly developed comprehensive model was applied to simulate physical processes in the full-scale horizontal furnace of a continuous galvanizing line (CGL). The numerical results obtained indicate that the current approach predicts heating characteristics reasonably well. It was also found that radiative heat transfer plays a dominant role in heating the moving strip. To improve the predictability of our method, further work is required to model the turbulence-chemistry interaction realistically, as well as to impose a physically correct thermal wall boundary condition.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.281-281
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• 2015

Shallow landslide often occurs in areas of this topography where subsurface soil water flow paths give rise to excess pore-water pressures downslope. Recent hillslope hydrology studies have shown that subsurface topography has a strong impact in controlling the connectivity of saturated areas at the soil-bedrock interface. In this study, the physically based SHALSTAB model was used to evaluate the effects of three soil thicknesses (i.e. average soil layer, soil thickness to weathered soil and soil thickness to bedrock soil layer) and subsurface flow reflecting three soil thicknesses on shallow landslide prediction accuracy. Three digital elevation models (DEMs; i.e. ground surface, weathered surface and bedrock surface) and three soil thicknesses (average soil thickness, soil thickness to weathered rock and soil thickness to bedrock) at a small hillslope site in Jinbu, Kangwon Prefecture, eastern part of the Korean Peninsula, were considered. Each prediction result simulated with the SHALSTAB model was evaluated by receiver operating characteristic (ROC) analysis for modelling accuracy. The results of the ROC analysis for shallow landslide prediction using the ground surface DEM (GSTO), the weathered surface DEM and the bedrock surface DEM (BSTO) indicated that the prediction accuracy was higher using flow accumulation by the BSTO and weathered soil thickness compared to results. These results imply that 1) the effect of subsurface flow by BSTO on shallow landslide prediction especially could be larger than the effects of topography by GSTO, and 2) the effect of weathered soil thickness could be larger than the effects of average soil thickness and bedrock soil thickness on shallow landslide prediction. Therefore, we suggest that using BSTO dem and weathered soil layer can improve the accuracy of shallow landslide prediction, which should contribute to more accurately predicting shallow landslides.

• Journal of Soil and Groundwater Environment
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• v.13 no.1
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• pp.67-76
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• 2008

In this study, a combined model of a water-table fluctuation and a soil moisture content model is proposed for the estimation of groundwater recharge rate at a given location. To evaluate the model, groundwater level data from 4 monitoring wells (Pohang Yeonil, Pohang Kibuk, Suncheon Oeseo, Hongcheon Hongcheon) of National Groundwater Monitoring Network from 1996 to 2005 and precipitation data of corresponding years are used. From the proposed methodology, the groundwater recharge rates are estimated to be from 0.5 to 61.4% for Hongcheon Hongcheon, from 1.1 to 27.4% for Pohang Yeonil, from 5.1 to 41.4% for Pohang Kibuk, and from 1.1 to 8.3% for Suncheon Oeseo. The magnitude of variation of the estimated recharge rate depends on the soil type observed near the stations. The groundwater fluctuation model used in this study includes precipitation as a unique source of water-table perturbation and there may exist corollary limitations. To improve the applicability of the proposed method, a capillary-water content constitutive model for unsaturated fractured rock media may be considered. The proposed recharge rate delineation method is physically based and uses minimum numbers of assumptions. The method may be used as a better substitute for the previous tools for delineating recharge rate of a location using water-table fluctuation method and contribute to national groundwater management plan. Further research on the spatial interpolation of the method is under progress.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.682-691
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• 2005

We present a two-step evolution system that produces controllable virtual creatures in physically simulated 3D environment. Previous evolutionary methods for virtual creatures did not allow any user intervention during evolution process, because they generated a creature's shape, locomotion, and high-level behaviors such as target-following and obstacle avoidance simultaneously by one-time evolution process. In this work, we divide a single system into manageable two sub-systems, and this more likely allowsuser interaction. In the first stage, a body structure and low-level motor controllers of a creature for straight movement are generated by an evolutionary algorithm. Next, a high-level control to follow a given path is achieved by a neural network. The connection weights of the neural network are optimized by a genetic algorithm. The evolved controller could follow any given path fairly well. Moreover, users can choose or abort creatures according to their taste before the entire evolution process is finished. This paper also presents a new sinusoidal controller and a simplified hydrodynamics model for a capped-cylinder, which is the basic body primitive of a creature.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.706-716
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• 2016

Because of efficient space utilization and fast key search times, B-trees have been widely accepted for the use of indexes in HDD-based DBMSs. However, when the B-ree is stored in flash memory, its costly operations of node updates may impair the performance of a DBMS. This is because the random updates in B-tree's leaf nodes could tremendously enlarge I/O costs for the garbage collecting actions of flash storage. To solve the problem, we make all the parents of leaf nodes the virtual nodes, which are not stored physically. Rather than, those nodes are dynamically generated and buffered by referring to their child nodes, at their access times during key searching. By performing node updates and tree reconstruction within a single flash block, our proposed B-tree can reduce the I/O costs for garbage collection and update operations in flash. Moreover, our scheme provides the better performance of key searches, compared with earlier flash-based B-trees. Through a mathematical performance model, we verify the performance advantages of the proposed flash B-tree.