• Journal of Korean Society on Water Environment
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• v.34 no.6
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• pp.579-590
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• 2018

The lakes' metabolism bears important information for the assessment of the carbon budget due to the accumulation or loss of carbon in the lake as well as the dynamics of the food webs through primary production. A lake-scale metabolism is evaluated by Gross Primary Production (GPP), Ecosystem Respiration (R), and Net Ecosystem Production (NEP), which is the difference between the first two values. Methods for estimating GPP and R are based on the levels carbon and oxygen. Estimation of carbon is expensive because of the use of radioactive materials which requires a high degree of proficiency. The purpose of this study was to estimate Lake Daecheong ecosystem metabolism using high frequency water temperature data and DO measurement sensor, widely utilized in the field of water quality monitoring, and to evaluate the possibility of using the application method. High frequency data was collected at intervals of 10 minutes from September to December 2017 by installing a thermistor chain and a DO sensor in downstream of Daechung Dam. The data was then used to estimate GPP, R and NEP using the R public program LakeMetabolizer, and other metabolism models (mle, ols, kalman, bookkeep). Calculations of gas exchange coefficient methods (cole, crusius, heiskanen, macIntyre, read, soloviev, vachon) were compared. According to the result, Lake Daecheong has some deviation based on the application method, but it was generally estimated that the NEP value is negative and acts as a source of atmospheric carbon in a heterotrophic system. Although the high frequency sensor data used in this study had negative and positive GPP and R values during the physical mixing process, they can be used to monitor real-time metabolic changes in the ecosystem if these problems are solved.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.384-391
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• 2005

Three dimensional finite difference elastic wave model was developed to estimate the feasibility of surface wave applications in geotechnical problems. The wave motions calculated by the developed program in this study shows good agreement with well known analytic solutions. The surface wave motions calculated from layered dam type structure can be interpreted as a infinite layer structure using dispersion curve but it is need a special source of which high energy in frequency band lower than 10 Hz to get information of physical properties in few tens meter deep. The source which has high energy in the low frequency band, however, can give defect on dam and this will make some limitation in real field applications. The dispersion curves calculated from the surface wave motion of homogeneous and center core type dam models will give rise to fatal errors if the conventional infinite layer structure used in their interpretation because the surrounding materials and boundaries of dam make some distortion in dispersion curve of surface wave. So it is strongly recommended to use three dimensional inversion model for correct interpretation and estimation of physical properties of dam materials.

• Journal of the Korean GEO-environmental Society
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• v.10 no.7
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• pp.135-141
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• 2009

For more reliable estimation of soil-structure interaction and seismic source and attenuation properties, site amplification function should be considered. This study use the Nakamura's method (1989) for estimating site amplification though various methods for the same purpose have been proposed. This method was originally applied to the surface waves of background noise and therefore there are some limitation for applications to general wave energy. However, recently this method has been extended and applied to the S wave energy successfully. This study applied the method to the coda wave energy which is equivalent to the backscattered S wave energy. We used more than 60 observed ground motions from 5 earthquakes which occurred recently, with magnitude range from 3.6 to 5.1 Each station showed characteristic site amplification property in low-, high- and resonance frequency ranges. In the case of comparing these results to those from S wave energy, lots of information to the site classification work can be gained. Moreover, removal of site amplification can give us more reliable seismic source parameters.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.65-73
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• 1998

One approach to improved image restoration methods has been the incorporation of additional source information via Gibbs priors that assume a source that is piecewise smooth. A natural Gibbs prior for expressing such constraints is an energy function defined on binary valued line processes as well as source intensities. However, the estimation of both continuous variables and binary variables is known to be a difficult problem. In this work, we consider the application of the deterministic annealing method. Unlike other methods, the deterministic annealing method offers a principled and efficient means of handling the problems associated with mixed continuous and binary variable objectives. The application of the deterministic annealing method results in a sequence of objective functions (defined only on the continuous variables) whose sequence of solutions approaches that of the original mixed variable objective function. The sequence is indexed by a control parameter (the temperature). The energy functions at high temperatures are smooth approximations of the energy functions at lower temperatures. Consequently, it is easier to minimize the energy functions at high temperatures and then track the minimum through the variation of the temperature. This is the essence of a continuation method. We show experimental results, which demonstrate the efficacy of the continuation method applied to a Bayesian restoration model.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1208-1215
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• 2017

Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.12
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• pp.1458-1467
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• 1999

VLSI 공정 기술이 발달하면서 이웃한 전선 간의 간격이 점점 더 가까워 지고 있으며, 그에 따라 인접 전선 간의 혼신 문제가 심각해지고 있다. 본 논문에서는 3층 그리드 채널 배선에 적용 가능한 혼신을 최소화시키는 배선층 할당 방법을 제안한다. 이 방법은 선형 의사 불린 최적화 기법에 맞도록 고안되었으며, 적절한 변수 선택 휴리스틱과 상한값 추정 방법을 통하여 최적의 결과를 짧은 시간 안에 찾아낸다. 실험 결과를 통하여, 일반적인 0/1 정수 선형 프로그래밍 기법과 비교하여 성능과 수행시간 면에서 우수함을 보인다. Abstract Current deep-submicron VLSI technology appears to cause crosstalk problem severe since it requires adjacent wires to be placed closer and closer. In this paper, we deal with a horizontal layer assignment problem for three layer HVH channel routing to minimize coupling capacitance, a main source of crosstalk. It is formulated in a 0/1 integer linear programming problem which is then solved by a linear pseudo boolean optimization technique. Experiments show that accurate upper bound estimation technique effectively reduces crosstalk in a reasonable amount of running times.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.14 no.1
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• pp.38-47
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• 2018

For safe operation of nuclear power plants, a loose-part monitoring system (LPMS) is used to detect and locate loose-parts within the reactor coolant system, and to estimate their mass and damage potential. There are several methods to estimate mass, such as the center frequency method based on the Hertz's impact theory, a frequency ratio method and so on, but it is known that these methods cannot provide accurate information on impact response for identifying the impact source. Thanks to increasing computing power, finite element analysis (FEA) method recently become an available option to calculate reliably impact response behavior. In this paper, a finite element analysis model to simulate the propagation behavior of the bending wave, generated by a metal ball impact, is validated by performing a series of impact tests and the corresponding finite element analyses for flat plate and shell structures. Also, a FEA-based metal sphere signal map is developed, and then blind tests are performed to verify the map. This study provides an accurate simulation method for predicting the metal impact behavior and for building a metal sphere signal map, which can be used to estimate the mass of loose-parts on site in nuclear power plants.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.1
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• pp.39-48
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• 2013

The solar radiation is the primary energy source that drives many of the earth's physical and biological processes and climate change. Understanding its importance to the solar radiation observation is a key to understanding a broad range of natural processes, agricultural, energy and human activities. The purpose of this study is to estimate solar radiation using sunshine duration, and to estimate distribution of solar radiation using a topography factor considering surface slope and aspect in complex terrain. The result of regression analysis between ratio of solar radiation and sunshine duration from 2001 to 2010 shows high $R^2$ value of 0.878. Regression analyses indicated that topographic attributes including elevation, slope and aspect had significant effects on solar radiation. The variation of topographic factor with aspect and slope for the summer and winter are considered. The highest month of daily mean solar radiation at Jeju island appears in April of 20.61 $MJ{\cdot}m^{-2}{\cdot}day^{-1}$, and the lowest month appears in December of 6.90 $MJ{\cdot}m^{-2}{\cdot}day^{-1}$. These results provided useful quantitative information about the influence of topography on solar radiation in the island region.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.4913-4916
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• 2016

Objective: As a source of information, medical data can feature hidden relationships. However, the high volume of datasets and complexity of decision-making in medicine introduce difficulties for analysis and interpretation and processing steps may be needed before the data can be used by clinicians in their work. This study focused on the use of Bayesian models with different numbers of nodes to aid clinicians in breast cancer risk estimation. Methods: Bayesian networks (BNs) with a retrospectively collected dataset including mammographic details, risk factor exposure, and clinical findings was assessed for prediction of the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: A network incorporating selected features performed better (AUC = 0.94) than that incorporating all the features (AUC = 0.93). The results revealed no significant difference among 3 models regarding performance indices at the 5% significance level. Conclusion: BNs could effectively discriminate malignant from benign abnormalities and accurately predict the risk of breast cancer in individuals. Moreover, the overall performance of the 9-node BN was better, and due to the lower number of nodes it might be more readily be applied in clinical settings.

• Proceedings of the KSRS Conference
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• v.1
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• pp.181-183
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• 2006

Digital topographic map in Korea contains layers of spatial and attribute data for 8 land features such as railroads, watercourses, roads, buildings and etc. Some of the layers such as building and forest don't include any information about height, which can be just prepared by interpretation of remote sensed data or field survey. LiDAR(Light Detection And Ranging) data using active pulse and digital camera provides data about height and form of land features. LiDAR data can be used not only to extract the outline of land features but also to estimate the height. This study presents technical availability for extraction and estimation of land feature's outline and height using LiDAR data which composes of natural and artificial land features, and digital aerial photograph which was taken simultaneously with the LiDAR. The estimated location, outline and height of land features were compared with the field survey data, and we could find that LiDAR data and digital aerial photograph can be a useful source for estimating the height of land features as well as extracting the outline.