• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.327-332
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• 2016

This study is a leading research project to develop an automatic grade decision making algorithm of a 6-years-old fresh ginseng. For this work, we developed a Ginseng image acquiring instrument which can take 4-direction's images of a Ginseng at the same time and obtained 245 jingen images using the instrument. The 12 parameters were extracted for each image by a manual way. Lastly, 4 parameters were selected depending on a Ginseng grade classification criteria of KGC Ginseng research institute and a survey result which a distribution of averaging 12 parameters. A pattern recognition classifier was used as a support vector machine, designed to "k-class classifier" using the OpenCV library which is a open-source platform. We had been surveyed the algorithm performance(Correct Matching Ratio, False Acceptance Ratio, False Reject Ratio) when the training data number was controlled 10 to 20. The result of the correct matching ratio is 94% of the $1^{st}$ ginseng grade, 98% of the $2^{nd}$ ginseng grade, 90% of the $3^{rd}$ ginseng grade, overall, showed high recognition performance with all grades when the number of training data are 10.

• Composite Materials and Engineering
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• v.3 no.3
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• pp.201-220
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• 2021

In this study, potential of three machine learning techniques i.e., M5P, Support vector machines and Gaussian processes were evaluated to find the best algorithm for the prediction of flexural strength of concrete mix with steel fibre. The study comprises the comparison of results obtained from above-said techniques for given dataset. The dataset consists of 124 observations from past research studies and this dataset is randomly divided into two subsets namely training and testing datasets with (70-30)% proportion by weight. Cement, fine aggregates, coarse aggregates, water, super plasticizer/ high-range water reducer, steel fibre, fibre length and curing days were taken as input parameters whereas flexural strength of the concrete mix was taken as the output parameter. Performance of the techniques was checked by statistic evaluation parameters. Results show that the Gaussian process technique works better than other techniques with its minimum error bandwidth. Statistical analysis shows that the Gaussian process predicts better results with higher coefficient of correlation value (0.9138) and minimum mean absolute error (1.2954) and Root mean square error value (1.9672). Sensitivity analysis proves that steel fibre is the significant parameter among other parameters to predict the flexural strength of concrete mix. According to the shape of the fibre, the mixed type performs better for this data than the hooked shape of the steel fibre, which has a higher CC of 0.9649, which shows that the shape of fibers do effect the flexural strength of the concrete. However, the intricacy of the mixed fibres needs further investigations. For future mixes, the most favorable range for the increase in flexural strength of concrete mix found to be (1-3)%.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.239-244
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• 2022

In this study, the key parameters affecting the deterioration of each track type were derived based on field inspections and laboratory tests. The existing track deterioration model was limited to the ballasted tracks, and the deterioration evaluation of concrete tracks was insufficient. In this study, the laboratory test was performed to evaluate the performance and condition of track components to derive the deterioration factors reflecting the characteristics of various track structures. In addition, through analysis of track maintenance history data, parameters affecting track deterioration and maintenance were derived. The key parameters for presenting a track deterioration model based on the track performance of ballasted and concrete tracks through field inspection, track maintenance history data analysis, and performance test of track components using on-site specimens were identified as track support stiffness, Ballast gravel, track settlement and Resilience pad were presented.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.1
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• pp.1-10
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• 2020

Effective jamming in electronic warfare depends on proper jamming technique selection and jamming parameter estimation. For this purpose, this paper proposes a new method of estimating jamming parameters using Gaussian kernel function networks. In the proposed approach, a new method of determining the optimal structure and parameters of Gaussian kernel function networks is proposed. As a result, the proposed approach estimates the jamming parameters in a reliable manner and outperforms other methods such as the DNN(Deep Neural Network) and SVM(Support Vector Machine) estimation models.

• Environmental Analysis Health and Toxicology
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• v.24 no.2
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• pp.95-105
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• 2009

Chemical Ranking and Scoring (CRS) system is a useful tool to screen priority chemicals of large body of substances. The relative ranking of chemicals based on CRS system has served as a decision-making support tools. Exposure potential and toxicity are significant parameters in CRS system, and there are differences in evaluating those parameters in each CRS system. In this study, the parameters of exposure potential, human toxicity, and ecotoxicity were extensively compared. In addition the scoring methods in each parameter were analyzed. The CRS systems considered in this study include the CHEMS-1 (Chemical Hazard Evaluation for Management Strategies), SCRAM (Scoring and Ranking Assessment Model), EURAM (European Union Risk Ranking Method), ARET (Accelerated Reduction/Elimination of Toxics), and CRS-Korea. An comparative analysis of the several CRS systems is presented based on their assessment parameters and scoring methods.

• Journal of the Korean Society of Physical Medicine
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• v.2 no.2
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• pp.161-171
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• 2007

Purpose : The purpose of this study was to evaluate the effect of footwear on gait in older adults. Methods : The footwear consists of loafer with fixation and mule and slipper without fixation. Twenty one female older adults voluntarily participated in this study. Each participant walked on the gait system GAITRite and measured temporal-spatial gait parameters. And the participants wore loafer, mule, slipper randomly. We measured stance time, swing time, heel-to-heel BOS, double support time, velocity, cadence, FAP as temporal-spatial gait parameters. Results : Three gait parameters showed significant difference statistically among 7 gait parameters. The stance time increased as loafer, mule, barefoot, slipper orderly. And there was a significant difference statistically (p<.05). The swing time increased as slipper, barefoot, mule, loafer orderly. And there was a significant difference statistically(p<.05). And the heel-to-heel BOS increased as barefoot, loafer, mule, slipper orderly. And there was a significant difference statistically(p<.05) according to footwear type. Conclusion : The footwear type with high stability like loafer is considered better than footwear type with low stability like mule and slipper for the elderly.

• Journal of Environmental Science International
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• v.28 no.1
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• Wind and Structures
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• v.23 no.2
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• pp.157-169
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• 2016

The structural integrity of tube bundles represents a major concern when dealing with high risk industries, such as nuclear steam generators, where the rupture of a tube or tubes will lead to the undesired mixing of the primary and secondary fluids. Flow-induced vibration is one of the major concerns that could compromise the structural integrity. The vibration is caused by fluid flow excitation. While there are several excitation mechanisms that could contribute to these vibrations, fluidelastic instability is generally regarded as the most severe. When this mechanism prevails, it could cause serious damage to tube arrays in a very short period of time. The tubes are therefore stiffened by means of supports to avoid these vibrations. To accommodate the thermal expansion of the tube, as well as to facilitate the installation of these tube bundles, clearances are allowed between the tubes and their supports. Progressive tube wear and chemical cleaning gradually increases the clearances between the tubes and their supports, which can lead to more frequent and severe tube/support impact and rubbing. These increased impacts can lead to tube damage due to fatigue and/or wear at the support locations. This paper presents simulations of a loosely supported multi-span U-bend tube subjected to turbulence and fluidelastic instability forces. The mathematical model for the loosely-supported tubes and the fluidelastic instability model is presented. The model is then utilized to simulate the nonlinear response of a U-bend tube with flat bar supports subjected to cross-flow. The effect of the support clearance as well as the support offset are investigated. Special attention is given to the tube/support interaction parameters that affect wear, such as impact and normal work rate.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.203-212
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• 2019

The purpose of this study was to identify the effects of stress factors of student pilots on mental health, and to reduce the safe and efficient misconduct education and psychological disharmony by identifying the psychological buffering role of stress coping style and social support. In order to achieve the research purpose, a research model and hypothesis were presented based on previous studies, and regression analysis and mediation effect verification were conducted through a questionnaire survey of 202 student pilots. As a result of the analysis, factors such as flight stress, values stress, professor stress, and friend relationship stress have been shown to affect emotional conditions or psychological well-being. Also we found that the parameters of disengagement coping, family/friend support and organization Support had a mediating effect on the factors between student pilot stress and psychological health. Therefore, student pilots need to manage problems and negative emotions that may cause from flight training, value distractions, professor and friendships' relationship and it is suggested that organization support for training and safety related to emotional support and delinquency of family and friends.

• Geomechanics and Engineering
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• v.25 no.3
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• pp.233-243
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• 2021

Rib spalling is a major issue affecting the safety of steeply inclined coal seam. And the failure coal face and support system can be affected with each other to generate a vicious cycle along with inducing large-scale collapse of surrounding rock in steeply inclined coal seam. In order to analyze failure mechanism and propose the corresponding prominent control measures of steeply inclined coal working face, mechanical model based on coal face-support-roof system and mechanical model of coal face failure was established to reveal the disaster mechanism of rib spalling and the sensitive analysis of related factors was performed. Furthermore, taking 3402 working face of Chen-man-zhuang coal mine as engineering background, numerical model by using FLAC3D was built to illustrate the propagation of displacement and stress fields in steeply inclined coal seam and verify the theory analysis as mentioned in this study. The results show that the coal face slide body in steeply inclined working face can be observed as the failure height of upper layer smaller than that of lower layer exhibiting with an irregular quadrilateral pyramid shape. Moreover, the cracks were originated from the upper layer of sliding body and gradually developed to the lower layer causing the final rib spalling. The influence factors on the stability of coal face can be ranked as overlying strata pressure (P) > mechanical parameters of coal body (e.g., cohesion (c), internal fraction angle (φ)) > support strength (F) > the support force of protecting piece (F') > the false angle of working face (Θ). Moreover, the corresponding control measures to maintain the stability of the coal face in the steeply inclined working face were proposed.