• The Journal of Engineering Geology
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• v.18 no.4
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• pp.381-391
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• 2008

The eigenvalue technique is introduced to overcome the problem of truncation errors caused by temporal discretization of numerical analysis. The eigenvalue technique is different from simulation in that only the space is discretized. The spatially discretized equation is diagonized and the linear dynamic system is then decoupled. The time integration can be done independently and continuously for any nodal point at any time. The results of eigenvalue technique are compared with the exact solution and FEM numerical solution. The eigenvalue technique is more efficient than the FEM to the computation time and the computer storage in the same conditions. This technique is applied to the solute transport analysis in nonuniform flow fields around underground storage caverns. This method can be very useful for time consuming simulations. So, a sensitivity analysis is carried out by using this method to analyze the safety of caverns from nearly located contaminant sources. According to the simulations, the reaching time from source to the nearest cavern may takes 50 years with longitudinal dispersivity of 50 m and transversal dispersivity of 5 m, respectively.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.261-273
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• 2004

Advances in information and communication technologies have been creating new classes of applications in the area of databases. For example, in moving object databases, which track positions of a lot of objects, or stream databases, which process data streams from a lot of sensors, data Processed in such database systems are usually changed very rapidly and continuously. However, traditional database systems have a problem in processing these rapidly and continuously changing data because they suppose that a data item stored in the database remains constant until It is explicitly modified. The problem becomes more serious in the R-tree, which is a typical index structure for multidimensional data, because modifying data in the R-tree can generate cascading node splits or merges. To process frequent updates more efficiently, we propose a novel update technique for the R-tree, which we call the leaf-update technique. If a new value of a data item lies within the leaf MBR that the data item belongs, the leaf-update technique changes the leaf node only, not whole of the tree. Using this leaf-update manner and the leaf-access hash table for direct access to leaf nodes, the proposed technique can reduce update cost greatly. In addition, the leaf-update technique can be adopted in diverse variants of the R-tree and various applications that use the R-tree since it is based on the R-tree and it guarantees the correctness of the R-tree. In this paper, we prove the effectiveness of the leaf-update techniques theoretically and present experimental results that show that our technique outperforms traditional one.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.687-701
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• 2014

Sea ice is generally accepted as an important factor to understand the process of earth climate changes and is the basis of earth system models for analysis and prediction of the climate changes. To continuously monitor sea ice changes at kilometer scale, it is demanded to create more accurate grid data from the current, limited sea ice data. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Sea Ice Concentration (SIC) from 10 km to 1 km resolution using a weighting scheme of sea ice days ratio derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice cover product that has a high correlation with the SIC. In a case study for Okhotsk Sea, the sea ice areas of both data (before and after downscaling) were identical, and the monthly means and standard deviations of SIC exhibited almost the same values. Also, Empirical Orthogonal Function (EOF) analyses showed that three kinds of SIC data (ERA-Interim, original AMSR2, and downscaled AMSR2) had very similar principal components for spatial and temporal variations. Our method can apply to downscaling of other continuous variables in the form of ratio such as percentage and can contribute to monitoring small-scale changes of sea ice by providing finer SIC data.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.3
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• pp.111-119
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• 1999

The purpose of this study is the simulation of discontinuous rockmass and identification of characteristics of discontinuity network as a branch of the study on characteristics of groundwater system in discontinuous rockmass for evaluation of safety on disposal site of radioactive waste. In this study the site for LPG underground storage was selected for the similarities of the conditions which were required for disposal site of radioactive waste. Through the identification of hydraulic properties. characteristics of discontinuities and selection of discontinuity model around LPG underground storage facility. the applications of discrete fracture network model were evaluated for the analysis of pathway. The orientation and spatial density of discontinuities are primarily important elements for the simulation of groundwater and solute transportation in discrete fracture network model. In this study three fracture sets identified and the spatial intensity (P$_{32}$) of discontinuities is revealed as 0.85 $m^2$/㎥. The conductive fracture intensity (P$_{32c}$) estimated for the simulation area around propane cavern (200${\times}$200${\times}$200) is 0.536 $m^2$/㎥. Truncated conductive fracture intensity (T-P$_{32c}$) is calculated as 0.26 $m^2$/㎥ by eliminating the fracture with the iowest transmissivity and based on this value the pathway from the water curtain to PC 2. PC 3 analyzed.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.550-563
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• 2006

Software product line engineering is a method that prepares for the future reuse and supports to seamless reuse in application development process. Commonality and variability play central roles in all product line development processes. Reusable assets will become core assets by explicitly representing C&V. Indeed, the variabilities that art identified at each phase of core assets development have different levels of abstraction. In the past, these variabilities have been handled in an implicit manner and without distinguishing the characteristics of each core assets. In addition, previous approaches have depended on the experience and intuition of a domain expert to recognize commonality and variability. In this paper, we suggest a 2-dimensional analyzing method that analyzes the variabilities of core assets in software product line. In horizontal analysis process, the variation types are analyzed in requirements, architecture, and component that are produced at each phase of development process. In vertical analysis process, variations are analyzed in different abstract levels, in which the region of commonality is identified and the variation points are refined. By this method, the traceability of variations between core assets will be possible and core assets can be reused seamlessly.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.466-466
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• 2017

지하공간의 개발과 지하공간의 굴착으로 인한 지표수 및 지하수 시스템의 변화나 굴착면 주위의 지하수 유동 체계의 변화는 터널내로의 지하수 유입, 지표수 고갈을 가져온다. 또한 터널 상부의 지반에서 현지응력의 변화로 인한 지하수 유출은 지표침하, 하천수 및 계곡수 고갈을 발생시킬 수 있다. 그러나, 터널설계 시 비용 및 시간, 현장의 진입조건 등의 제약으로 상세한 지반조사의 실시가 이루어지지 않을 때가 있다. 또한, 터널 공사가 진행되는 중에는 공사기간과 공사비 때문에 별도의 지반조사를 하지 않는다. 그 대신에 터널 막장에서 실시하는 Face Mapping을 토대로 공사를 진행하며, 대규모 위험요소가 발견되지 않는 이상 별도의 비용과 시간을 투입하여 추가 지질 및 지반 조사를 실시하는 경우는 매우 드물다. 연구지역의 지질은 경상분지내 백악기 하양층군의 퇴적암류, 이를 관입/분출한 불국사화강암류 및 제3기 화산암류, 전기 에오세 연일층군에 대비되는 퇴적암류로 구성되어 있다. 이들을 피복하는 제4기 충적 퇴적층은 주로 단층곡과 동측 지괴의 선상지 및 하천을 따라 분포한다. 연구지역에는 폭 100 m 이상의 대규모 단층대가 발달하였으며 제4기 단층운동으로 인한 단층파쇄대가 존재한다. 퇴적암 분포지역에서는 반복층서가 관찰되며 소규모 단층, 단열, 변형띠 등이 연속적으로 발달해 있다. 본 연구에서는 터널공사에 의한 지하수 변화를 확인하기 위하여 현장추적자 시험과 수질분석 및 지하수 모델링을 실시하였다. 현장 수질 분석에 의한 지표수와 지하수 간의 수질의 차이를 보면, 알칼리도를 제외한 대부분의 수질 항목이 서로 유사성을 보인다. 전기전도도(EC), TDS, 알칼리도의 경우 지표수의 수원지에서 터널 내부로 유입이 일어나고 있다. 이는 터널 공사의 영향으로 판단되며, 현장에서 실시한 추적자 시험에서는 추적자의 이동 시간이 매우 빨라 지표 수원지로부터 지표수가 터널내부로 빠른 속도(10시간 이내)로 유입된다고 판단된다. 지하수 모델링 결과, 정상류 상태에서는 지하수가 북동쪽의 높은 고도에서 서남쪽의 낮은 고도로 흐르는 것으로 확인되며, 가뭄시에도 지하수 함양으로 지하수가 고갈되지는 않는 것으로 나타났다. 부정류 상태 모델링 결과, 일일 평균 $32.49m^3$의 지하수가 터널 내부로 유입되는 것으로 산정되었다. 이 양은 터널 내부뿐만 아니라 터널 공사 현장 주위로도 지하수 유출이 일어나고 있음을 지시한다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.77-86
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• 2013

In this paper, we propose a fast video retargeting method which preserves the contents of a video and converts the image size. Since the conventional Seam Carving which is the well-known content-aware image retargeting technique uses the dynamic programming method, the repetitive update procedure of the accumulation energy is absolutely needed to obtain seam. The energy update procedure cannot avoid the processing time delay because of many operations by the image full-searching. By applying the proposed method, frames which have similar features in video are classified into a scene, and the first frame of a scene is resized by the modified Seam Carving where multiple seams are extracted from candidate seams to reduce the repetitive update procedure. After resizing the first frame of a scene, all continuous frames of the same scene are resized with reference to the seam information stored in the previous frame without the calculation of the accumulation energy. Therefore, although the fast processing is possible with reducing complexity and without analyzing all frames of scene, the quality of an image can be analogously maintained with an existing method. The experimental results show that the proposed method can preserve the contents of an image and can be practically applied to retarget the image on real time.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.59-66
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• 2005

The main purpose of this paper is to describe a highly efficient common mid-point (CMP) data acquisition method for ground-penetrating radar (GPR) surveying, which is intended to widen the application of GPR. The most important innovation to increase the efficiency of CMP data acquisition is continuous monitoring of the GPR antenna positions, using a real-time kinematic Global Positioning System (RTK-GPS). Survey time efficiency is improved because the automatic antenna locating system that we propose frees us from the most time-consuming process-deployment of the antenna at specified positions. Numerical experiments predicted that the data density and the CMP fold would be increased by the increased efficiency of data acquisition, which results in improved signal-to-noise ratios in the resulting data. A field experiment confirmed this hypothesis. The proposed method makes GPR surveys using CMP method more practical and popular. Furthermore, the method has the potential to supply detailed groundwater information. This is because we can convert the spatially dense dielectric constant distribution, obtained by using the CMP method we describe, into a dense physical value distribution that is closely related to such groundwater properties as water saturation.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.29-42
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• 2021

As the low fertility intensifies in Korea, this study investigated fundamental differences between the government's low fertility policy and public perception of it. To this end, we selected four times 'Aging Society and Population Policy' documents and news comments for two weeks immediately after announcement of the third and fourth Policy as analysis targets. Then we conducted word frequency analysis, co-occurrence analysis and CONCOR analysis. As a result of analyses, first, direct childcare support during the first and second periods, and a social structural approach during third and fourth periods were noticeable. Second, it was revealed that both policies and comments aim for the work-family compatibility in 'parenting'. Lastly it was showed public interest in environment of raising children and the critical mind to effectiveness of the policy. This study is meaningful in that it confirmed the public perception using big data analysis, and it will help improve the direction for the future low fertility policy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.