• 한국물환경학회지
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• 제22권6호
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• pp.982-990
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• 2006

Generally CSOs (Combined Sewer Overflows) are regarded as one of the most serious nonpoint pollution source in the urban watershed, Particularly, the water quality of the Oncheon stream is seriously affected by CSOs because the capacity of interception sewer system connected to the Suyoung wastewater treatment plant is too small to intercept most storm water discharges. The objective of this study is to evaluate the effect of nonpoint source on an urban stream with regards to combined sewer system and separate sewer system using GIS (Geographic Information System) and SWMM (Storm Water Management Model), and to provide an insight for the management of urban stream water quality. In order to consider the effect of CSOs on the receiving water quality, the flow divider element in SWMM was applied. The model calibration and verification were performed by the measured data of quantity and quality on the Oncheon stream. The quantity data acquired from the Suyoung wastewater treatment plant were also used for this procedure. In case of separate sewer system, the modeling results showed the increased tendency in streamflow compared with the combined system in dry weather, In addition, the water quality is remarkably improved in rainfall events at the separate condition. The results imply that the construction of separate sewer system should be taken into first consideration to restore the quality and quantity of water in urban streams.

• Korean Journal of Radiology
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• 제22권3호
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• pp.476-488
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• 2021

Objective: We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images. Materials and Methods: Thin-section non-contrast chest CT images from 203 patients (115 males, 88 females; age range, 31-89 years) between January 2017 and May 2017 were included in the study, of which 150 cases had extensive lung parenchymal disease involving more than 40% of the parenchymal area. Parenchymal diseases included interstitial lung disease (ILD), emphysema, nontuberculous mycobacterial lung disease, tuberculous destroyed lung, pneumonia, lung cancer, and other diseases. Five experienced radiologists manually drew the margin of the lungs, slice by slice, on CT images. The dataset used to develop the network consisted of 157 cases for training, 20 cases for development, and 26 cases for internal validation. Two-dimensional (2D) U-Net and three-dimensional (3D) U-Net models were used for the task. The network was trained to segment the lung parenchyma as a whole and segment the right and left lung separately. The University Hospitals of Geneva ILD dataset, which contained high-resolution CT images of ILD, was used for external validation. Results: The Dice similarity coefficients for internal validation were 99.6 ± 0.3% (2D U-Net whole lung model), 99.5 ± 0.3% (2D U-Net separate lung model), 99.4 ± 0.5% (3D U-Net whole lung model), and 99.4 ± 0.5% (3D U-Net separate lung model). The Dice similarity coefficients for the external validation dataset were 98.4 ± 1.0% (2D U-Net whole lung model) and 98.4 ± 1.0% (2D U-Net separate lung model). In 31 cases, where the extent of ILD was larger than 75% of the lung parenchymal area, the Dice similarity coefficients were 97.9 ± 1.3% (2D U-Net whole lung model) and 98.0 ± 1.2% (2D U-Net separate lung model). Conclusion: The deep neural network achieved excellent performance in automatically delineating the boundaries of lung parenchyma with extensive pathological conditions on non-contrast chest CT images.

• 제어로봇시스템학회논문지
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• 제11권3호
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• pp.254-261
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• 2005

Time-optimal performances are analyzed in the sense of inner loop. A varying-time sharing thrusting logic is suggested as a new sequential paired thrusting logic for fast maneuvers of satellites with coupled thruster configuration. Its time-optimal maneuvering performance is compared with two conventional thrusting logics: separate thrusting logic and constant-time sharing sequential paired thrusting logic. It is found that the newly suggested varying-time sharing thrusting logic can be easily implemented by adjusting the conventional constant-time logic with its thrust on-time, while it can reduce the maneuvering time enormously as much as the separate thrusting logic. The performance of the logic is simulated on the agile maneuvering spacecraft model KOMPSAT-II.

• Structural Engineering and Mechanics
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• 제85권1호
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• pp.119-133
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• 2023

Impact event is the key factor influencing the operational state of the mechanical equipment. Additionally, nonlinear factors existing in the complex mechanical equipment which are currently attracting more and more attention. Therefore, this paper proposes a novel hybrid-separate identification strategy to solve the force identification problem of the nonlinear structure under impact excitation. The 'hybrid' means that the identification strategy contains both l1-norm (sparse) and l2-norm regularization methods. The 'separate' means that the nonlinear response part only generated by nonlinear force needs to be separated from measured response. First, the state-of-the-art two-step iterative shrinkage/thresholding (TwIST) algorithm and sparse representation with the cubic B-spline function are developed to solve established normalized sparse regularization model to identify the accurate impact force and accurate peak value of the nonlinear force. Then, the identified impact force is substituted into the nonlinear response separation equation to obtain the nonlinear response part. Finally, a reduced transfer equation is established and solved by the classical Tikhonove regularization method to obtain the wave profile (variation trend) of the nonlinear force. Numerical and experimental identification results demonstrate that the novel hybrid-separate strategy can accurately and efficiently obtain the nonlinear force and impact force for the nonlinear structure.

• Geosystem Engineering
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• 제21권5호
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• pp.262-272
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• 2018

The U-statistic method is one of the most important structural methods to separate the anomaly from background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, 3D U-statistic method has been applied for the first time through the three-dimensional (3D) modeling of an ore deposit. In order to achieve this purpose, 3D U-statistic is applied on the data (Fe grade) resulted from the drilling network in Baghak mine, central part of the Sangan iron mines (in Khorassan Razavi Province, Iran). Afterward, results from applying 3D U-statistic method are used for 3D modeling of the iron mineralization. Results show that the anomalous values are well separated from background so that the determined samples as anomalous are not dispersed and according to their positioning, denser areas of anomalous samples could be considered as anomaly areas. And also, final results (3D model of iron mineralization) show that output model using this method is compatible with designed model for mining operation. Moreover, seen that U-statistic method in addition for separating anomaly from background, could be very efficient for the 3D modeling of different ore type.

• 한국경영과학회지
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• 제19권3호
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• pp.169-186
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• 1994

This paper presents three mathematical programming approaches to solving transshipment problems with interval supply and demand requirements. A linear goal programming model was developed based on the data obtained from a nationwide retail firm. Three mathematical programming model results were compared and analyzed, and three separate hypotheses were examined by using the Wilcoxon signed-ranked test for the model applicability. The test results were analyzed and interpreted for decision making.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.313-316
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• 2004

Model selection is the process that sets up the regularization parameter in the support vector machine or regularization network by using the external methods such as general cross validation or L-curve criterion. This paper suggests that the regularization parameter can be obtained simultaneously within the learning process of neural networks without resort to separate selection methods. In this paper, extended kernel method is introduced. The relationship between regularization parameter and the bias term in the extended kernel is established. Experimental results show the effectiveness of the new model selection method.

• 설비공학논문집
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• 제18권8호
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• pp.641-648
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• 2006

In this study, a two-stage phase-separate cycle was investigated analytically to improve the performance of the $CO_2$ system in the cooling mode. The simulation results were verified with the measured data. The predictions using the simulation model were consistent with the measured data within ${\pm}20%$ deviations. The performance of the modified $CO_2$ system with the two-stage phase-separated cycle was analyzed with the variations of outdoor temperature and EEV opening. The cooling COP decreased with the increase of compressor frequency. The highest COP was 2.7 at compressor frequencies of 30 Hz and 30 Hz for the first and second compressors, respectively. In addition, the cooling COP increased by 9.3% with an application of optimum control of the first and second-stage EEV openings.

• 한국콘텐츠학회논문지
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• 제9권2호
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• pp.115-124
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• 2009

얼굴 인식 방법 중 인기 있는 고유얼굴 기반 얼굴 인식 방법은 훈련 얼굴 이미지 세트에 대해 PCA를 적용하여 얻어진 고유얼굴을 이용한다. 따라서 훈련 얼굴 이미지들의 조명들과 다른 조명의 환경들에서는 신뢰성 있는 성능을 얻기 어렵다. 본 논문에서는 조명의 영향을 배제한 조명분리 고유얼굴 기반 얼굴 인식 방법을 제안한다. 제안된 방법은 얼굴 모델 이미지 세트의 고유얼굴 공간을 구성된 얼굴 조명 부분공간에 대해 직교 분해하여 얻은 조명분리 고유얼굴들을 이용한다. 실험을 통해서 조명분리 고유얼굴에 기반하는 제안된 얼굴 인식 방법이 기존 고유얼굴 기반 얼굴 인식 방법보다 조명의 영향에 보다 강인함을 확인하였다.

• 한국지반공학회논문집
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• 제24권5호
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• pp.107-115
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• 2008

본 연구는 1차압밀 중의 크리프의 영향과 Yin이 제안한 탄-점-소성 모델에 대한 적용성을 검토하였다. 탄성모델을 이용한 일반적인 압밀이론은, 1차압밀 과정을 표현할 수 있으나 2차압밀을 표현할 수 없다. 이러한 결과는 2차압축을 표현할 수 있는 점성에 기인하며, 때로는 Ladd 등(1977)이 제안한 가정 A 및 B와 같은 스케일효과(실험실 공시체와 현장조건 사이의 점토층 두께의 차이)와 관련되어진다. 통상적으로 1차압밀 중의 크리프의 존재는 많은 연구자에 의해 확인되어졌으며, 가정 B가 잘 맞는 것으로 되어있다. 한편, 대형압밀시험을 통해 가정 A와 B의 중간적인 특성이 Aboshi(1973)에 의한 가정 C로써 제안되어졌다. 본 연구에서는 1차압밀 중의 침하-시간관계에 대한 크리프의 영향을 명백히 하기 위해, peat와 점토에 대해 분할형 압밀시험기를 이용하여 가정 B의 압밀시험을 행하였다. 그리고 Yin의 탄-점-소성 모델을 이용하여 실험결과를 해석하였다. 얻어진 결과는 다음과 같다. 1차압밀 종료시에 분할 공시체의 압축은 과잉간극수압 소산속도의 차이에 의해 동일하지 않았다. 또한 분할형 압밀시험기에 의해 측정된 평균변형률과 Yin의 EVP 모델을 이용한 해석치는 잘 일치하였다. 그러나 과잉간극수압의 소산에 대해서는 측정치가 Yin 모델에 비해 빨리 소산되었다.