• Journal of the Korean Society of Industry Convergence
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• v.26 no.4_2
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• pp.629-637
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• 2023

This study aimed to evaluate the effect of post-curing equipment and time on the flexural strength of 3D printing resins produced by a liquid crystal display(LCD) printer. The three 3D printing resins(DENTCA Denture Teeth, DT; C&B 5.0 hybrid, CH; C&B Permanent A2, CP) were divided into four groups according to post-curing time(10 min and 30 min) and equipment with or without vacuum treatment. For the three-point flexural strength test and biaxial strength test were prepared by method according to ISO 10477, ISO 6872, respectively. Flexural strength was measured with universal testing machine. Comparison between post-curing time of each post-curing equipment was analyzed by independent sample t-test and Mann-Whitney U test(α=.05), and comparison between groups according to each 3D printing resin was performed by Kruskal-Wallis test and post-hoc by Bonferroni-Dunn test(α=.05). The flexural strength of the resin post-curing under vacuum was higher than that of the resin post-curing in air. In the comparison according to the post-curing time, in the case of the post-curing equipment without vacuum, the 30 minute curing time showed significantly higher flexural strength than the 10 minute curing time, except for the biaxial flexural strength of CH(P<.05). In the post-curing equipment with vacuum, the three-point flexural strength of all 3D printing resins(DT, CH, and CP) showed a higher value at 30 minute curing time than at 10 minute curing time.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.212-212
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• 2023

비점오염원관리와 같이 장기적인 유역 관리 계획에서 유역 내 오염원 평가는 정말 중요하다. 유역 내 오염원 평가는 강우 유출에 의한 비점오염 발생원이 어디서 얼마나 발생시키는지에 대한 정량적인 조사가 필요하다. 유역 내의 오염원에 대한 정량적인 조사는 많은 비용과 시간이 필요하다. 이러한 비용과 시간을 줄이기 위해 유역단위 수리 수문 모델을 사용하고 있다. 유역단위 수리수문 모델은 HSPF (Hydrological Simulation Program in Fortran), SWAT (Soil and Water Assessment Tool), L-THIA ACN-WQ(The Long-term Hydrologic Impact Assessment Model with Asymptotic Curve Number Regression Equation and Water Quality model)등 다양한 모델이 사용되고 있다. 하지만 유역 모델을 통한 모의는 다양한 연산 과정을 진행하여 모의까지 많은 시간이 필요하다는 단점이 있다. 이에 따라 데이터 기반 모델링 기법(머신러닝/딥러닝)을 이용한 유출 및 수질 예측 연구가 많이 이루어지고 있다. 단순 머신러닝/딥러닝 기반 모델링 기법은 점(최종유출구)에서의 예측만 가능하여 최적관리 기법 적용 등과 같은 유역관리 방안을 적용하기 힘들다는 문제점이 있다. 따라서 본 연구에서 머신러닝/딥러닝을 통해 일부 수문 프로세스를 대체하고 소유역별 하도추적 기법을 연계하여 유량 및 수질 항목들의 모의가 가능한 하이브리드 모델을 개발하였다. 이는 머신러닝/딥러닝이 유역 모델의 일부 연산 과정을 대체하여 모의시간이 빠르며, 기존 머신러닝/딥러닝 예측 모델에서 평가가 어려웠던 유역 관리 방안 및 최적관리기법 적용 평가에도 활용이 가능할 것으로 판단이 된다.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.81-89
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• 2010

Biological data mining has been noticed as an issue as the volume of biological data is increasing extremely. Grid technology can share and utilize computing data and resources. In this paper, we propose a hybrid system that combines biological data mining with grid technology. Especially, we propose a decision range adjustment algorithm for processing efficiency of biological data mining. We obtain a reliable data mining recognition rate automatically and rapidly through this algorithm. And communication loads and resource allocation are key issues in grid environment because the resources are geographically distributed and interacted with themselves. Therefore, we propose a dynamic load balancing algorithm and apply it to the grid-based biological data mining method. For performance evaluation, we measure average processing time, average communication time, and average resource utilization. Experimental results show that this method provides many advantages in aspects of processing time and cost.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.11-22
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• 2009

For a wireless ad-hoc network, event routing algorithm of the publish/subscribe system is especially important for the performance of the system because of the dynamic characteristic and constraint network of its own. In this paper, we propose a new hybrid event routing algorithm. TopSim for efficient publish/subscribe system on the wireless ad-hoc network by extending the ShopParent algorithm by considering not only network overheads to choose a Parent of the publish/subscribe tree, but also topic similarity which is closeness of subscriptions. Our evaluation shows our proposed TopSim performs better for the case where a new joining node subscribed to the multiple topics and there is a node among Parent candidate nodes who subscribe to the ones in the list of multiple topics (related topics).

• Membrane and Water Treatment
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• v.14 no.2
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• pp.85-93
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• 2023

Membrane separation is widely used for several applications such as water treatment, membrane reactors and climate change. Cross-linked organic-inorganic hybrid polyvinylidene fluoride (PVDF) / Tetraethyl orthosilicate (TEOS) was adopted for the preparation of optimized hollow membrane (HFM) for membrane distillation or other low pressure separators for mechanical properties and permeability under varying pretreatment schemes. HFMs were prepared on semi-pilot membrane fabrication system. Novel adopted post-treatment schemes involved soaking in glycerol, magnesium sulphate (MgSO₄), sodium hypochlorite (NaOCl), and isopropanol for different durations. All fibers were characterized for morphology using a scanning electron microscope (SEM), surface roughness using atomic force microscope (AFM), elemental composition by examining Energy Dispersive Spectroscopy (EDS), water contact angle (CA°) and porosity. The performance of the fibers was evaluated for pure water permeation flux (PWF). Post-treatment with MgSO₄ gave the highest both tensile modulus and flux. Assessment of properties and performance revealed comparable results with other organic-inorganic separators, HF or flat. In spite of few reported data on post treatment using MgSO₄ in presence of TEOS, this proves the potential of low cost treatment without negative impact on other membrane properties. The flux is also comparable with hypochlorite which manifests substantial precaution requirements in actual industrial use.The relatively high values of flux/bar for sample treated with TEOS, post treated with MgSO₄ and hypochlorite are 88 and 82 LMH/bar respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.1-7
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• 2023

Durability was evaluated by performing a full-scale vertical load fatigue test and a wheel load performance test on the HRS, which reduces the replacement time of the existing expansion joint and improves serviceability to allow partial replacement by lane. As a result of the vertical load fatigue test, the maximum stress of the rail-type expansion joint is 170 MPa, which is about 47.8% of the yield strength of the HRS expansion joint rail 355 MPa. The vertical load fatigue test of the HRS expansion joint with improved serviceability set the size and load of the load plate according to the road bridge design standards, did not show any fracture behavior in the vertical load fatigue test and the wheel load performance test 2 million times, and its durability and safety were verified.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.307-307
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• 2022

최근 기후변화와 댐 상류 토지이용 변화 등과 같은 다양한 원인에 의해 댐 유입량의 변동성이 증가하면서 댐 관리 및 운영조작 의사 결정에 어려움이 발생하고 있다. 따라서 이러한 댐 유입량의 변동 특성을 반영하여 댐 유입량을 정확하고 효율적으로 예측할 수 있는 방안이 필요한 실정이다. 머신러닝 기술이 발전하면서 Auto-ML(Automated Machine Learning)이 다양한 분야에서 활용되고 있다. Auto-ML은 데이터 전처리, 최적 알고리즘 선택, 하이퍼파라미터 튜닝, 모델 학습 및 평가 등의 모든 과정을 자동화하는 기술이다. 그러나 아직까지 수문 분야에서 댐 유입량을 예측하기 위한 모델을 개발하는데 있어서 Auto-ML을 활용한 사례는 부족하고, 특히 댐 유입량의 예측 정확성을 확보하기 위해 High-inflow and low-inflow 의 변동 특성을 고려한 하이브리드 결합 방식을 통해 Auto-ML 기반 앙상블 모델을 개발하고 평가한 연구는 없다. 본 연구에서는 Auto-ML의 패키지 중 Auto-sklearn을 통해 홍수기, 비홍수기 유입량 변동 특성을 반영한 하이브리드 앙상블 댐 유입량 예측 모델을 개발하였다. 소양강댐을 대상으로 적용한 결과, 하이브리드 Auto-sklearn 앙상블 모델의 댐 유입량 예측 성능은 R² 0.868, RMSE 66.23 m³/s, MAE 16.45 m³/s로 단일 Auto-sklearn을 통해 구축 된 앙상블 모델보다 전반적으로 우수한 것으로 나타났다. 특히 FDC (Flow Duration Curve)의 저수기, 갈수기 구간에서 두 모델의 유입량 예측 경향은 큰 차이를 보였으며, 하이브리드 Auto-sklearn 모델의 예측 값이 관측 값과 더욱 유사한 것으로 나타났다. 이는 홍수기, 비홍수기 구간에 대한 앙상블 모델이 독립적으로 구축되는 과정에서 각 모델에 대한 하이퍼파라미터가 최적화되었기 때문이라 판단된다. 향후 본 연구의 방법론은 보다 정확한 댐 유입량 예측 자료를 생성하기 위한 방안 수립뿐만 아니라 다양한 분야의 불균형한 데이터셋을 이용한 앙상블 모델을 구축하는데도 유용하게 활용될 수 있을 것으로 사료된다.

• Design & Manufacturing
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• v.17 no.3
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• pp.55-60
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• 2023

The fiber-reinforced plastics and cellular injection molding process can be used to efficiently reduce the weight of battery housing components of mild hybrid electronic vehicles(MHEV) made of metal. However, the fiber orientation of fiber-reinforced plastics and the growth of foaming cells are intertwined during the injection molding process, so it is difficult to predict the mechanical properties of products in the design process. Therefore, it is necessary to evaluate the mechanical properties of the materials prior to the efficient stiffness design of the target product. In this study, a study was conducted to evaluated the mechanical properties of fiber reinforced cellular injection-molded specimens. Two types of fiber-reinforced plastics that can be used in the target product were evaluated for changes in tensile properties of cellular injection-molded specimens depending on the foaming ratio and position from the injection gate. The PP and PA66 specimens showed a decrease of tensile modulus and strength of approximately 30% and 17% depending on the foaming ratio, respectively. Also, the tensile strength decreased approximately 26% and 17% depending on the position from the injection gate, respectively. As a result, it was confirmed that the PP specimens have a significantly mechanical property degradation compared to the PA66 specimens depending on the foaming ratio and position.

• Journal of Oriental Neuropsychiatry
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• v.35 no.1
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• pp.1-13
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• 2024

Objectives: This study aims to develop an educational program based on a manual for disaster medical support using Korean medicine (KM) for disaster survivors. Methods: We conducted a literature review on another educational program, a focus group interviews with experts, a survey of the academic needs of Korean medicine (KM) doctors, educational competency development, and an expert Delphi survey. Results: This program was designed using a hybrid method combining online (4 h) and offline (8 h) elements; the total time of the program is 12 h. The offline course consists of theory (4 h) and practice (4 h) lectures. The theory lecture covers herbal medicine, acupuncture, stabilizing technique, emotional freedom technique, and self-management, and the practice lecture covers stabilizing technique, emotional freedom technique, and clinical performance evaluation. Meanwhile, the online course covers a manual for disaster medical support using KM and an introductory course from the National Center for Disaster and Trauma. Conclusions: The results of this study are expected to be useful for enhancing training for KM doctors in trauma care for disaster survivors as well as evaluating and validating the program's effectiveness.