• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.533-538
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• 2014

Power generator is one of the most important component of electricity generation system to convert mechanical energy to electrical energy. I t designed robustly to maintain high system reliability during operation time. But unexpected failure of the power generator could happen and it cause huge amount of economic and social loss. To keep it from unexpected failure, health prognostics should be carried out In this research, We developed a health prognostic method of stator windings in power generator with statistical data analysis and degradation modeling against water absorption. We divided whole 42 windings into two groups, absorption suspected group and normal group. We built a degradation model of absorption suspected winding using Fick's second law to predict upcoming absorption data. Through the analysis of data of normal group, we could figure out the distribution of data of normal windings. After that, we can properly predict absorption data of normal windings. With data prediction of two groups, we derived upcoming Directional Mahalanobis Distance (DMD) of absorption suspected winding and time vs DMD curve. Finally we drew the probability distribution of Remaining Useful Life of absorption suspected windings.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.318-326
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• 2013

Purpose: We developed a viability evaluation method for cucumber (Cucumis sativus) seed using hyperspectral reflectance imaging. Methods: Reflectance spectra of cucumber seeds in the 400 to 1000 nm range were collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares-discriminant analysis (PLS-DA) was developed to predict viable and non-viable seeds. Various ranges of spectra induced by four types of LEDs (Blue, Green, Red, and RGB) were investigated to develop the classification models. Results: PLS-DA models for spectra in the 600 to 700 nm range showed 98.5% discrimination accuracy for both viable and non-viable seeds. Using images based on the PLS-DA model, the discrimination accuracy for viable and non-viable seeds was 100% and 99%, respectively Conclusions: Hyperspectral reflectance images made using LED light can be used to select high quality cucumber seeds.

• Journal of Sasang Constitutional Medicine
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• v.32 no.2
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• pp.10-21
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• 2020

Objectives Genome-wide association studies(GWAS) is a useful method to identify genetic associations for various phenotypes. The purpose of this study was to develop predictive models for Sasang constitution types using genetic factors. Methods The genotypes of the 1,999 subjects was performed using Axiom Precision Medicine Research Array (PMRA) by Life Technologies. All participants were prescribed Sasang Constitution-specific herbal remedies for the treatment, and showed improvement of original symptoms as confirmed by Korean medicine doctor. The genotypes were imputed by using the IMPUTE program. Association analysis was conducted using a logistic regression model to discover Single Nucleotide Polymorphism (SNP), adjusting for age, sex, and BMI. Results & Conclusions We developed models to predict Korean medicine constitution types using identified genectic factors and sex, age, BMI using Random Forest (RF), Support Vector Machine (SVM), and Neural Network (NN). Each maximum Area Under the Curve (AUC) of Teaeum, Soeum, Soyang is 0.894, 0.868, 0.767, respectively. Each AUC of the models increased by 6~17% more than that of models except for genetic factors. By developing the predictive models, we confirmed usefulness of genetic factors related with types. It demonstrates a mechanism for more accurate prediction through genetic factors related with type.

• Journal of Ocean Engineering and Technology
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• v.2 no.2
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• pp.61-70
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• 1988

In order to consider the concept of the fitness for purpose'in fatigue design of offshore structure, fracture mechanics is applied to evaluate initial or weld defects. Generally, linear elastic fracture mechanics has been applied to tstimate initial fatigue crack propagation rate as well as long fatigue crack propagation rate. But, initial fatigue crack propagation rate in elasto-plastic notch field may not be characterized by application of stress intensity factor range .DELTA. K, because plastic effect due to stress concentration of notch may contribute to initial crack propagation. Therefore, to introduce the plastic effect into fatigue crack driving force, in this studty, the evaluating method of J-integral range .DELTA. J, was developed by willson was modified for application to notch field. In calculation of .DELTA. J obtained from the modified J-integral, stress gradient and crack closure behavior in the notch field were considered. The initial crack propagation rates in the notch fields of mild steels and high tensile strength steels were correlated to .DELTA. J. As the result, it was cleared that the present .DELTA. J is applicable to charachterize the fatigue crack propagation rates in both the elastic and elasto-plastic notch fields.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.333-342
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• 2004

Tensile and low cycle fatigue (LCF) tests on prior cold worked 316L stainless steel were carried out at various temperatures from room temperature to 650$^{\circ}C$. At all test temperatures, cold worked material showed the tendency of higher strength and lower ductility compared with those of solution treated material. The embrittlement of material occurred in the temperature region from 300$^{\circ}C$ to 600$^{\circ}C$ due to dynamic strain aging. Following initial cyclic hardening for a few cycles, cycling softening was observed to dominate until failure occurred during LCF deformation, and the cyclic softening behavior strongly depended on temperature and strain amplitude. Non-Masing behavior was observed at all test temperatures and hysteresis energy curve method was employed to describe the stress-strain hysteresis loops at half$.$life. The prediction shows a good agreement with the experimental results.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.49-60
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• 2021

BCSA (Bias-Correction and Stochastic Analog) is a statistical downscaling technique designed to effectively correct the systematic errors of GCM (General Circulation Model) output and reproduce basic statistics and spatial variability of the observed precipitation filed. In this study, the applicability of BCSA was evaluated using the ASOS observation data over South Korea, which belongs to the monsoon climatic zone with large spatial variability of rainfall and different rainfall characteristics. The results presented the reproducibility of temporal and spatial variability of daily precipitation in various manners. As a result of comparing the spatial correlation with the observation data, it was found that the reproducibility of various climate indices including the average spatial correlation (variability) of rainfall events in South Korea was superior to the raw GCM output. In addition, the needs of future related studies to improve BCSA, such as supplementing algorithms to reduce calculation time, enhancing reproducibility of temporal rainfall patterns, and evaluating applicability to other meteorological factors, were pointed out. The results of this study can be used as the logical background for applying BCSA for reproducing spatial details of the rainfall characteristic over the Korean Peninsula.

• Geomechanics and Engineering
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• v.18 no.5
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• pp.493-502
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• 2019

Internal stability is an important safety issue for levees, embankments, and other earthen structures. Since a large part of the world's population lives near oceans, lakes and rivers, floods resulting from breaching of dams can lead to devastating disasters with tremendous loss of life and property, especially in densely populated areas. There are some main factors that affect the internal stability of dams, levees and other earthen structures, such as the erodibility of the soil, the water velocity inside the soil mass and the geometry of the earthen structure, etc. Thus, the mechanism of internal erosion and stability of soils is very complicated and it is vital to investigate the assessment methods of internal stability of soils in embankment dams and their foundations. This paper presents an improved support vector machine (SVM) model to predict the internal stability of soils. The grid search algorithm (GSA) is employed to find the optimal parameters of SVM firstly, and then the cross - validation (CV) method is employed to estimate the classification accuracy of the GSA-SVM model. Two examples of internal stability of soils are presented to validate the predictive capability of the proposed GSA-SVM model. In addition to verify the effectiveness of the proposed GSA-SVM model, the predictions from the proposed GSA-SVM model were compared with those from the traditional back propagation neural network (BPNN) model. The results showed that the proposed GSA-SVM model is a feasible and efficient tool for assessing the internal stability of soils with high accuracy.

• Animal Bioscience
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• v.35 no.5
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• pp.659-669
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• 2022

Objective: Thoroughbred horses have been bred exclusively for racing in England for a long time. Additionally, because horse racing is a global sport, a healthy leisure activity for ordinary citizens, and a high-value business, systematic racehorse breeding at the population level is a requirement for continuous industrial development. Therefore, we established genomic evaluation system (using prize money as horse racing traits) to produce spirited, agile, and strong racing horse population Methods: We used phenotypic data from 25,061 Thoroughbred horses (all registered individuals in Korea) that competed in races between 1994 and 2019 at the Korea Racing Authority and constructed pedigree structures. We quantified the improvement in racehorse breeding output by year in Korea, and this aided in the establishment of a high-level horse-fill industry. Results: We found that pedigree-based best linear unbiased prediction method improved the racing performance of the Thoroughbred population with high accuracy, making it possible to construct an excellent Thoroughbred racehorse population in Korea. Conclusion: This study could be used to develop an efficient breeding program at the population level for Korean Thoroughbred racehorse populations as well as others.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.485-491
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• 2015

The technology review about risk of hypothermia of victim according to heat transfer characteristic of life raft and sea state can use accident correspondence of standing and sinking of ship. This study studied heat transfer characteristics required for the design of life raft and thermal insulation property analysis and evaluation methods. In addition, it is study for comprehend the risk of hypothermia and suggest analysis result that is experiment of thermal insulation property and body temperature property for decide of prediction the body temperature decline Thermal Analysis apply the finite element analysis method is comprehended the property of heat conductivity, convective effect of sea water and properties changes according to property of insulation material. it measure the heat flux with attach temperature sensor on body in order to comprehend the variation of body temperature with boarding a life raft experiment on a human body. This study validate results by comparing variation of temperature measured from experiment on a body with variation of temperature from finite element analysis model. Also, the criteria of hypothermia was discussed through result of finite element analysis.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.72-77
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• 2002

The development of a Pay Adjustment (PA) procedure for implementing Performance-related Specifications (PRS) is known to be a difficult task faced by most State Highway Agencies (SHAs) due to the difficulty in such areas as selecting pay factor items, modeling the relationship between stochastic variability of pay factor items and pavement performance, and determining an overall lot pay adjustment. This led to the need for an effective way of developing a scientific pay adjustment procedure by incorporating Life Cycle Cost Analysis (LCCA) embedded Monte Carlo approach. In this work, we propose a prototype system to determine a PA specifically using the data in the pavement management information systems at Wisconsin Department of Transportation (WisDOT) as an exemplary to other SHAs. It is believed that the PRS methodology demonstrated in this study can be used in real projects by incorporating the more accurate and reliable performance prediction models and LCC model.