• Proceedings of the KSME Conference
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• 2002.08a
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• pp.185-188
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• 2002

The objective of present paper is to apply a stereoscopic PIV(Particle Image Velocimetry) techiique for measuring the 3 dimensional flow structure of turbulent wake behind a marine propeller with 5 blades. It is essential to measure 3-components velocity fields for the investigation of complicated near-wake behind the propeller. The out-of-plane velocity component was measured using the particle images captured by two CCD cameras in the angular displacement configuration.400 instantaneous velocity fields were measured for each of few different blade phases of $0^{\circ},\;18^{\circ},\;36^{\circ}\;and\;54^{\circ}$. They were ensemble averaged to investigate the spatial evolution of the propeller wake in the region ranged from the trailing edge to the region of one propeller diameter(D) downstream. The phase-averaged velocity fields show the viscous wake formed by the boundary layers developed along the blade surfaces. Tip vortices were formed periodically and the slipstream contraction occurs in the near-wake region. The out-of-plane velocity component has large values at the tip and trailing votices. With going downstream, the axial turbulence intensity and the strength of tip vortices were decreased due to the visous dissipation, turbulence diffusion and blade-to-blade interaction. The blade wake traveling at higher speed with respect to the tip vortex overtakes and interacts with tip vortices formed from the previous blade. Tip vortices are separated from the wake and show oscillating trajectory

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.5
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• pp.612-618
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• 2004

Stereoscopic PIV measurements were made in the wind tunnel with the actual size waterjet model. The main wind tunnel provides the vehicle velocity while the secondary wind tunnel adjusts the jet issuing velocity. Experiments were performed at the range of jet to vehicle velocity ratio (JVR), 3.75 to 8.0 and the Reynolds number of 220,000 based on the jet velocity and the hydraulic diameter of the waterjet intake duct. Wall pressure distributions were measured for various JVRs. Three dimensional velocity fields were obtained at the inlet and outlet of the intake duct. It is found that severe acceleration is occurred at the lip region while deceleration is noticeable at the ramp side. The detailed three dimensional velocity fields can be used as the accurate velocity input for the CFD simulation. It is interesting to note that there are many different types of vortices in the instantaneous velocity field. It can be considered that those vortices are generated by the corner of rectangular section of the intake and Gortler vortices due to the curved wall. However, typical secondary flow with a pair of counter rotating vortex pair is clearly seen in the ensemble averaged velocity field.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.207-218
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• 2019

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.17-24
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• 2023

Based on the problem of 'Tatanic - Machine Learning from Disaster', a representative competition of Kaggle that presents challenges related to data science and solves them, we want to see how data preprocessing and model construction affect prediction accuracy and score. We compare and analyze the features by selecting seven top-ranked solutions with high scores, except when using redundant models or ensemble techniques. It was confirmed that most of the pretreatment has unique and differentiated characteristics, and although the pretreatment process was almost the same, there were differences in scores depending on the type of model. The comparative analysis study in this paper is expected to help participants in the kaggle competition and data science beginners by understanding the characteristics and analysis flow of the preprocessing methods of the top score participants.

• Korean Journal of Materials Research
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• v.33 no.4
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• pp.164-174
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• 2023

The bandgap characteristics of semiconductor materials are an important factor when utilizing semiconductor materials for various applications. In this study, based on data provided by AFLOW (Automatic-FLOW for Materials Discovery), the bandgap of a semiconductor material was predicted using only the material's compositional features. The compositional features were generated using the python module of 'Pymatgen' and 'Matminer'. Pearson's correlation coefficients (PCC) between the compositional features were calculated and those with a correlation coefficient value larger than 0.95 were removed in order to avoid overfitting. The bandgap prediction performance was compared using the metrics of R² score and root-mean-squared error. By predicting the bandgap with randomforest and xgboost as representatives of the ensemble algorithm, it was found that xgboost gave better results after cross-validation and hyper-parameter tuning. To investigate the effect of compositional feature selection on the bandgap prediction of the machine learning model, the prediction performance was studied according to the number of features based on feature importance methods. It was found that there were no significant changes in prediction performance beyond the appropriate feature. Furthermore, artificial neural networks were employed to compare the prediction performance by adjusting the number of features guided by the PCC values, resulting in the best R² score of 0.811. By comparing and analyzing the bandgap distribution and prediction performance according to the material group containing specific elements (F, N, Yb, Eu, Zn, B, Si, Ge, Fe Al), various information for material design was obtained.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.181-181
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• 2021

유역 내의 물순환 평가를 위하여 적합한 강우-유출모형을 선정하고 적용하는 것은 수문학적 관점에서 주된 과제이다. 장기적인 관점의 수자원 관리를 위해서는 직접적인 계측을 통해 장기간의 유출자료를 취득하는 방법이 있으나, 국내의 주요지점을 제외한 대다수의 중소규모의 지점에 계측기를 설치하는 것은 현실적으로 어려우므로, 자료취득이 비교적 용이하고 신뢰성이 높은 장기간 강우 자료를 강우-유출모형의 입력자료로 활용하여 미계측 유역으로의 모형을 확장하는 방안이 적절하다는 평가를 받고 있다. 본 연구는 국내외 주요 연속강우-유출모형의 특성을 파악하기 위하여 비교적 신뢰성 있는 자료를 보유하고 있는 소양강댐 유역에 다수의 연속강우-유출모형을 적용하였다. 모델링 결과로 산출된 유황곡선(flow duration curve)을 소양강댐 유입량과 비교하여 각 모형의 특징을 파악하고 유량에 따른 적합성 평가를 진행하였다. 또한, 향후 미계측유역으로 모형을 확장하기 위하여 매개변수 개수 및 재현능력을 동시에 평가하였다. 다수의 모형 중 적합성이 높은 모형들을 선별하였으며, 선별된 모형들의 불확실성을 고려함과 동시에 계층적 베이지안 기법을 활용하여 최종적으로 앙상블모형을 제시하였다. 앙상블모형을 단일 모형과 비교한 결과 단일 모형보다 개선된 성능을 확인하였다.

• International Journal of Stem Cells
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• v.17 no.1
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• pp.30-37
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• 2024

The lung is a complex organ comprising a branched airway that connects the large airway and millions of terminal gas-exchange units. Traditional pulmonary biomedical research by using cell line model system have limitations such as lack of cellular heterogeneity, animal models also have limitations including ethical concern, race-to-race variations, and physiological differences found in vivo. Organoids and on-a-chip models offer viable solutions for these issues. Organoids are three-dimensional, self-organized construct composed of numerous cells derived from stem cells cultured with growth factors required for the maintenance of stem cells. On-a-chip models are biomimetic microsystems which are able to customize to use microfluidic systems to simulate blood flow in blood channels or vacuum to simulate human breathing. This review summarizes the key components and previous biomedical studies conducted on lung organoids and lung-on-a-chip models, and introduces potential future applications. Considering the importance and benefits of these model systems, we believe that the system will offer better platform to biomedical researchers on pulmonary diseases, such as emerging viral infection, progressive fibrotic pulmonary diseases, or primary or metastatic lung cancer.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.271-278
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• 1999

Soil filters are commonly used to protect the soil structures from eroding and piping. When filters are clogged by fine particles which are progressively accumulated, these may lead to buildup of excessive pore pressures also leading to instability in subsurface infrastructure. A filter in the backfill of a retaining wall, a filter adjacent to the lining of a tunnel, or a filter in the bottom of an earth dam can be clogged by transported fine particles. This causes reduction in the permeability, which in turn may lead to intolerable decreases in their drainage capacity. In this thesis, the extent of this reduction is addressed using results from both experimental and theoretical investigations. In the experimental phase, the permeability reduction of a filter is monitored when an influent of constant concentration flows into the filter (uncoupled test), and when the water flow through the soil-filter system to simulate an in-situ condition (coupled test), respectively. The results of coupled and uncoupled test are compared with among others. In the theoretical phase of the investigation, a representative elemental volume of the soil filter was modeled as an ensemble of capillary tubes and the permeability reduction due to physical clogging was simulated using basic principles of flow in cylindrical tubes. In general, it was found that the permeability was reduced by at least one order of magnitude, and that the results from the uncoupled test and theoretical investigations were in good agreement. It is observed that the amount of deposited particles of the coupled test matches fairly well with that of the uncoupled test, which indicates that the prediction of permeability reduction is possible by preforming the uncoupled test instead of the coupled test, and/or by utilizing the theoretical model.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.3
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• pp.211-217
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• 2014

This study analyzes the nonlinear interaction between two different vortex shedding frequencies from a cylinder with two diameters. In particular, two different vortex shedding frequencies are generated by preparing a cylinder having two diameters artificially. Flow velocity fluctuations behind the cylinder are measured three-dimensionally. Additionally, we fabricated a hole and placed a pressure transducer for measuring the pressure on the cylinder surface. The pressure signal from the pressure transducer is used as basic signal. A TSC(Trans Spectrum Coherence) is used for checking the strength of the nonlinear interaction between two different vortex shedding frequencies. As a result, the following are clarified: i) frequency distribution behind the cylinder, ii) three-dimensional flow state behind the cylinder through calculation of ensemble average, and iii) close relationship between the vertical vortex and change of low frequency by nonlinear interaction between two different vortex shedding frequencies from the cylinder with two diameters.

• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.31-44
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• 2014

In the present study, a few of recently developed geostatistical models are comparatively studied. The models are two-point statistics based sequential indicator simulation (SISIM) and generalized coupled Markov chain (GCMC), multi-point statistics single normal equation simulation (SNESIM), and object based model of FLUVSIM (fluvial simulation) that predicts structures of target object from the provided geometric information. Out of the models, SNESIM and FLUVSIM require additional information other than conditioning data such as training map and geometry, respectively, which generally claim demanding additional resources. For the comparative studies, three-dimensional fluvial reservoir model is developed considering the genetic information and the samples, as input data for the models, are acquired by mimicking realistic sampling (i.e. random sampling). For SNESIM and FLUVSIM, additional training map and the geometry data are synthesized based on the same information used for the objective model. For the comparisons of the predictabilities of the models, two different measures are employed. In the first measure, the ensemble probability maps of the models are developed from multiple realizations, which are compared in depth to the objective model. In the second measure, the developed realizations are converted to hydrogeologic properties and the groundwater flow simulation results are compared to that of the objective model. From the comparisons, it is found that the predictability of GCMC outperforms the other models in terms of the first measure. On the other hand, in terms of the second measure, the both predictabilities of GCMC and SNESIM are outstanding out of the considered models. The excellences of GCMC model in the comparisons may attribute to the incorporations of directional non-stationarity and the non-linear prediction structure. From the results, it is concluded that the various geostatistical models need to be comprehensively considered and comparatively analyzed for appropriate characterizations.