• 한국멀티미디어학회논문지
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• 제23권12호
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• pp.1486-1495
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• 2020

The analysis of digital microscopy images plays a vital role in computer-aided diagnosis (CAD) and prognosis. The main purpose of this paper is to develop a machine learning technique to predict the histological grades in prostate biopsy. To perform a multiclass classification, an AI-based deep learning algorithm, a multichannel convolutional neural network (MCCNN) was developed by connecting layers with artificial neurons inspired by the human brain system. The histological grades that were used for the analysis are benign, grade 3, grade 4, and grade 5. The proposed approach aims to classify multiple patterns of images extracted from the whole slide image (WSI) of a prostate biopsy based on the Gleason grading system. The Multichannel Convolution Neural Network (MCCNN) model takes three input channels (Red, Green, and Blue) to extract the computational features from each channel and concatenate them for multiclass classification. Stain normalization was carried out for each histological grade to standardize the intensity and contrast level in the image. The proposed model has been trained, validated, and tested with the histopathological images and has achieved an average accuracy of 96.4%, 94.6%, and 95.1%, respectively.

• The Journal of Asian Finance, Economics and Business
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• 제9권7호
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• pp.53-62
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• 2022

Commercial banks have a significant impact on the economy of Vietnam because they provide the majority of transactional capital. Therefore, the operational efficiency of commercial banks is a viral topic for the study of the Vietnamese banking system. The research aims to examine the efficiency and inefficiency of joint-stock commercial banks in Vietnam from 2016 to 2020 and then classify them into the efficient group and inefficient group. The study employs the time series data of 29 joint-stock commercial banks during the period 2016-2020. Based on the data collected from the annual audited financial statements of 29 Vietnamese joint-stock commercial banks, the authors select input and output variables for the standard DEA models and anti-efficient DEA models. This research uses two stages, first, by applying the standard DEA model, we investigate the efficient banks; second, by employing the anti-efficient DEA model, we find out the inefficient banks. The results reveal that the average efficiency score of 29 joint-stock commercial banks tends to increase in the period 2016-2018 and decrease gradually in the period 2019-2020. The findings of this study suggest that several small and medium-sized banks in the Vietnamese banking sector have both promising and risky performances and the efficiency of state-owned commercial banks has also improved significantly during the study period.

• Advances in aircraft and spacecraft science
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• 제9권5호
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• pp.367-375
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• 2022

Modeling the properties of complex alloys such as nickel superalloys is an extremely challenging scientific and engineering task. The model should take into account a large number of uncorrelated factors, for many of which information may be missing or vague. The individual contribution of one or another chemical element out of a dozen possible ligants cannot be determined by traditional methods. Moreover, there are no general analytical models describing the influence of elements on the characteristics of alloys. Artificial neural networks are one of the few statistical modeling tools that can account for many implicit correlations and establish correspondences that cannot be identified by other more familiar mathematical methods. However, such networks require careful tuning to achieve high performance, which is time-consuming. Data preprocessing can make model training much easier and faster. This article focuses on combining physics-based deep network configuration and input data engineering to simulate the solvus temperature of nickel superalloys. The used deep artificial neural network shows good simulation results. Thus, this method of numerical simulation can be easily applied to such problems.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.337-345
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• 2017

The sponge city construction is being carried out in China, and how to reasonably determine the scale of the sponge city facilities is a key point that the planners and designers should seriously solve. In this paper, taking determination of the sponge city facilities in a residential building in Shenzhen as an example, the layout and scales of the rainwater tanks, raingardens, ecological roofs and permeable pavements are decided by using the volumetric method and stormwater management model (SWMM). The calculated results by the two methods are compared and analyzed. The results show that the scales of the sponge city facilities determined by the two methods are almost the same, and it means that any method can be used to determine the scale of sponge city facilities. The volumetric method is relatively simple, and it is suggested to use to determine the scale of sponge city facilities during planning stage. While SWMM is more complex and requires a lot of input conditions, but it can provide the reduction effects of the sponge city facilities for rainfalls with different recurrence periods. Therefore, SWMM is recommended to use the calculation of the hydrological process of the sponge city facilities during the design stage.

• 소성∙가공
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• 제33권2호
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• pp.96-102
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• 2024

This study addresses evaluation of performance of hardening model for a titanium alloy (Ti6Al4V) based on the artificial neural network (ANN) regarding the strain rate and the temperature. Uniaxial compression tests were carried out at different strain rates from 0.001 /s to 10 /s and temperatures from 575 ℃ To 975 ℃. Using the experimental data, ANN models were trained and tested with different hyperparameters, such as size of hidden layer and optimizer. The input features were determined with the equivalent plastic strain, strain rate, and temperature while the output value was set to the equivalent stress. When the number of data is sufficient with a smooth tendency, both the Bayesian regulation (BR) and the Levenberg-Marquardt (LM) show good performance to predict the flow behavior. However, only BR algorithm shows a predictability when the number of data is insufficient. Furthermore, a proper size of the hidden layer must be confirmed to describe the behavior with the limited number of the data.

• 한국환경보건학회지
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• 제45권5호
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• pp.497-510
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• 2019

Objectives: The aim of this study was to secure the reliability of using the CalTOX model when evaluating LADD (or ADD) and Risk (or HQ) among local residents for the emission of BTEX (Benzene, Toluene, Ethylbenzene, Xylene) and by closely examining the difference in the confidence interval of the assessment outcomes according to the difference in the probability density function of input variables. Methods: The assessment was made by dividing it according to the method ($I^{\dagger}$) of inputting the probability density function in meteorological variables of the model with log-normal distribution and the method of inputting ($II^{\ddagger}$) after grasping the optimal probability density function using @Risk. A T-test was carried out in order to analyze the difference in confidence interval of the two assessment results. Results: It was evaluated to be 1.46E-03 mg/kg-d in LADD of Benzene, 1.96E-04 mg/kg-d in ADD of Toluene, 8.15E-05 mg/kg-d in ADD of Ethylbenzene, and 2.30E-04 mg/kg-d in ADD of Xylene. As for the predicted confidence interval in LADD and ADD, there was a significant difference between the $I^{\dagger}$ and $II^{\ddagger}$ methods in $LADD_{Inhalation}$ for Benzene, and in $ADD_{Inhalation}$ and ADD for Toluene and Xylene. It appeared to be 3.58E-05 for risk in Benzene, 3.78E-03 for HQ in Toluene, 1.48E-03 for HQ in Ethylbenzene, and 3.77E-03 for HQ in Xylene. As a result of the HQ in Toluene and Xylene, the difference in confidence interval between the $I^{\dagger}$ and $II^{\ddagger}$ methods was shown to be significant. Conclusions: The human risk assessment for BTEX was made by dividing it into the method ($I^{\dagger}$) of inputting the probability density function of meteorological variables for the CalTOX model with log-normal distribution, and the method of inputting ($II^{\ddagger}$) after grasping the optimal probability density function using @Risk. As a result, it was identified that Risk (or HQ) is the same, but that there is a significant difference in the confidence interval of Risk (or HQ) between the $I^{\dagger}$ and $II^{\ddagger}$ methods.

• 방사성폐기물학회지
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• 제9권1호
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• pp.13-21
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• 2011

한국원자력연구원의 연구지역에서 고준위방사성폐기물처분을 위한 부지특성평가 기술 구축을 위해 지질특성조사가 1997년부터 지표기반 조사, 시추공 조사를 포함하여 수행되었다. 2006년에는 지하처분연구터널 (KURT, KAERI Underground Research Tunnel)을 준공하여 연구지역에 대한 심부지질환경 규명을 위해 노력하고 있다. 본 연구는 한국원자력연구원내 건설된 지하처분연구시설 주변 지역을 연구대상 지역으로 하여 지질모델에 대한 수리지질모델의 통합 구축을 목적으로 한다. 본 연구를 위해 연구지역에서 굴착된 9개의 시추공에 대한 현장 수리시험 자료를 이용하였으며, 지질모델에서 도출한 풍화대, 상부저경사단열대, 심부 영역에 존재하는 결정론적 단열대에 대한 수라지질특성을 분석하였다. 본 연구 결과 제시된 수리지질모델은 향후 지하수 유동모델링에 이용될 것이다.

• 환경영향평가
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• 제9권4호
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• pp.323-338
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• 2000

A Korean air dispersion modeling software, AirMaster, was developed on a basis of dispersion theories adopted in U.S. EPA's ISC3 (Industrial Source Complex - version 3) model to assess the air quality impact from the stacks. Key characteristics of AirMaster are as follows: 1) The building downwash effect can be easily simulated; 2) The screen, long term, and short term models can be run independently; 3) The input data to run the model such as meteorological and terrain data are supplied automatically from the databases in AirMaster; and 4) The modeling procedure is easy and simple under the GUI window environment. In order to validate AirMaster, comparisons with ISC3 model and Indianapolis tracer experiment were carried out. It was shown that AirMaster was identical to ISCST3 and ISCLT3 models in predicting the 1 hr to annual concentrations from the stack under various stack emission and meteorological conditions. The 1 hr concentrations predicted by AirMaster also showed a good agreement with the Indianapolis tracer measurements.

• 한국항공우주학회지
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• 제35권6호
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• pp.489-495
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• 2007

표준 동역학 모델의 피치 동안정미계수를 측정하기 위한 실험적 연구가 아음속 풍동에서 수행되었다. 모델은 트리거 신호가 주어지면 직류형 서보모터에 의하여 일정한 진폭과 주파수로 상, 하 피치운동을 시작하며, 동시에 25 사이클 동안의 데이터가 자료획득시스템에 저장된다. 동안정미계수 계산에 필요한 위상차는 기준입력 신호와 모델의 무게중심에 장착된 밸런스로부터 나오는 출력신호의 최대 정점과의 위상변화로부터 얻어졌다. 또한 Stabilator의 동안정미계수에 대한 영향은 조종면을 변위시키면서 측정하였다. 본 실험을 위해 독창적으로 제작된 모델의 구동장치 및 실험장치가 다른 연구와 다른데도 불구하고 실험결과는 받음각 변화에 따른 동안정미계수의 변화 경향성이 TPI, NAE, 그리고 FFA의 연구결과와 비교적 잘 일치함을 확인하였다.

• 한국농공학회논문집
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• 제60권6호
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• pp.1-12
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• 2018

The objectives of this study were to develop a system linking hydrologic and water quality models considering the mechanisms of agricultural reservoir and paddy cultivation and to evaluate whether the developed system simulates hydrologic and water quality processes better than a hydrologic model that do not consider the mechanisms. The system consisted of Hydrological Simulation Program-Fortran (HSPF) as a watershed model, Module-based hydrologic Analysis System for Agricultural watersheds (MASA) as reservoir water balance model, and Chemical, Runoff and Erosion from Agricultural Management System-Paddy (CREAMS-PADDY) as a hydrologic and water quality model for paddy fields. This study carried out on the Seolseong-Cheon watershed in Icheon, and the water level and water quality had been monitored for two years at the outlet of the watershed. According to the results of this study, the performance of the simulation using HSPF-MASA-CREAMS-PADDY system was better than others, but they did not show a statistically significant difference. This seemed to be due to the uncertainty of the farming data and the water quality data of the reservoir. Therefore, if accurate input data for the system is obtained, HSPF-MASA-CREAMS-PADDY system could be used to model an agricultural watershed to obtain more realistic results. The results of this study could be utilized to the modeling of agricultural watersheds in Korea where paddy rice cultivation is dominant.