• Economic and Environmental Geology
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• v.30 no.5
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• pp.469-476
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• 1997

In the conventional velocity analysis, the peaks of a semblance panel are picked and the stacking velocities of the peaks are assumed as RMS velocities from which interval velocities are determined. This velocity analysis technique is correct only for horizontal homogeneous layes and incurs error in a layer whose velocity varies laterally. Tediousness of peak picking and error in velocity analysis can be reduced by automatic velocity analysis techniques. An automatic velocity analysis algorithm has been presented in order to improve these problems by considering the stacking velocity from the view point of interval velocity model and by relating the stacking velocity and the interval velocity with the traveltimes. In this paper, we apply the automatic velocity analysis method to simple models having lateral velocity anomaly to verify the effectivenesses and limits of this method. From the results of numerical experiments, we can determine the interval velocites without pickings of the stacking velocities in the one-dimensional velocity analysis and the general patterns of the laterally varying interval velocities appear in the two-dimensional case. However, the interval velocity and the depth of velocity anomaly determined by two-dimensional automatic velocity analysis are somewaht discrepant in those of the theoretical model.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.313-319
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• 2000

In this paper, we proposed the model of wireless communication for ACTS using DSRC and the DSRC system for T/C. The proposed wireless communication model is how to join with DSRC and other wireless communication in port. The DSRC system for T/C is the first application to the unit of port Facilities Automation on stacking area. The DSRC system is communicated between OBE and RSE using 5.8Hz ISM band frequency. The previous works of DSRC applications are gate automation. In these cases, the road trackers are difficult to obtain information of the port in the stacking area. So we used the DSRC for the wireless communication for the port Facilities Automation. Using DSRC, the load trackers obtain more information in the port and contacts to ITS on back-roads of port. The proposed communication system is serviced to reelection of port statistics.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.2
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• pp.222-235
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• 2017

In this study, finite element modeling was used to predict the material properties of tri-axially braided textile composite. The model was made based on an experimental test specimen which was also used to compare the final results. The full interlacing of tows was geometrically modelled, from which repeating parts that make up the whole braid called unit cells were identified based on the geometric and mechanical property periodicity. In order to simulate the repeating nature of the unit cell, periodic boundary conditions were applied. For validation of the method, a reference model was analyzed for which a very good agreement was obtained. Material property calculation was done by simulating uniaxial and pure shear tests on the unit cell. The comparison of these results with that of experimental test results showed an excellent agreement. Finally, parametric study on the effect of number of plies, stacking type (symmetric/anti-symmetric) and stacking phase shift was conducted.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.182-182
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• 2021

본 연구에서는 1일부터 최대 7일까지의 시간을 두고 남한 전체의 유출량에 대한 예측 모형을 제시하고자 한다. 이를 위하여 LSM (Land Surface Model) 모형을 사용하여 유출량을 모의하였고 이 과정에서 미 계측치에 대한 유출량을 예측하기 위하여 Xgboost (Extreme Gradient Boost)를 활용하여 매개변수를 지역화하였다. 이러한 지역화 기법을 통하여 남한 전체의 유출량에 대한 그리드화 된 유출값을 얻을 수 있었다. 또한 본 연구에서는 기상 예측자료를 유출량에 대한 예측으로 변환하기 위하여 Stacking 앙상블 기반의 수문학적 후처리 기법을 사용하였다. Stacking 앙상블 기법은 Base-learner와 Meta-learner의 조합으로 이루어 지는데 본 연구에서 새롭게 사용되는 패널티 기반의 분위회귀분석 방법론은 기존의 방법론과의 비교에 있어서 유용한 것으로 파악되었다. 결과적으로 본 연구에서는 총 7일의 앞선 시간의 예측에 있어서 한반도 전체의 유출량에서 비교적 짧은 시간에 대한 예측인 1일과 2일에서의 예측은 실질적으로 사용이 가능한 것으로 파악되었다.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.31-37
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• 2002

This paper demonstrates the analyses of the interlaminar shear stress of laminated composite plates subjected to transversely impact. For this purpose, a plate finite element model based on the higher order shear deformation plate theory in conjunction with static contact laws is developed. Test materials were CFRP with cross-ply laminate $[O_4/{\theta}_4]_S$, $[90_4/{\theta}_4]_S$ stacking sequences and angle-ply laminate $[{\theta}_4/-{\theta}_4]_S$, $[{\theta}_4/-{\theta}_4]_S$ stacking deguences with $2^t{\times}40^w{\times}100^l(mm)$ dimension. As a result, stacking seguence and fiber orientation were found to have a significant effect on the interlaminar stresses in composite laminates.

• Bulletin of the Korean Chemical Society
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• v.22 no.6
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• pp.575-580
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• 2001

Intramolecular ring-ring interactions in the model compounds, $8-methoxypsoralen-CH_2O(CH_2)n-adenine(MOPCH_2OCnAd$, n=2, 3, 5, and 6) in which 5' position of 8-methoxypsoralne (8-MOP) is linked by different polymethylene bridges to N9 of adenine, have been investigated by hypochromism measurements. Efficient ring-ring stacking interactions have been observed in $MOPCH_2CO2Ad$ (7) from the percent hypochromism(%H) and fluorescence spectra of the models and a reference molecule. The 8-methoxyposralen-adenine systems have shown stronger ring-ring stacking interaction than the psoralen-adenine system.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.279-289
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• 2024

Familial searching is a useful technique in a forensic investigation. Using genetic information, it is possible to identify individuals, determine familial relationships, and obtain racial/ethnic information. The total number of shared alleles (TNSA) and likelihood ratio (LR) methods have traditionally been used, and novel data-mining classification methods have recently been applied here as well. However, it is difficult to apply these methods to identify familial relationships above the third degree (e.g., uncle-nephew and first cousins). Therefore, we propose to apply a stacking ensemble machine learning algorithm to improve the accuracy of familial relationship identification. Using real data analysis, we obtain superior relationship identification results when applying meta-classifiers with a stacking algorithm rather than applying traditional TNSA or LR methods and data mining techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.97-102
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• 2010

The purpose of medical data mining for efficient algorithms and techniques throughout the various diseases is to increase the reliability of estimates to classify. Previous studies, an algorithm based on a single model, and even the existence of the model to better predict the classification accuracy of multi-model ensemble-based research techniques are being applied. In this paper, the higher the medical data to predict the reliability of the existing scope of the ensemble technique applied to the I-ENSEMBLE offers. Data for the diagnosis of hypothyroidism is the result of applying the experimental technique, a representative ensemble Bagging, Boosting, Stacking technique significantly improved accuracy compared to all existing, respectively. In addition, compared to traditional single-model techniques and ensemble techniques Multi modeling when applied to represent the effects were more pronounced.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.83-90
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• 2019

People constantly strive for better choices. For this reason, recommender system has been developed since the early 1990s. In particular, collaborative filtering technique has shown excellent performance in the field of recommender systems, and research of recommender system using machine learning has been actively conducted. This study constructs recommender system using collaborative filtering and machine learning based on stacking model which is one of ensemble methods. The results of this study confirm that the recommender system with the stacking model is useful in aspects of recommender performance. In the future, the model proposed in this study is expected to help individuals or firms to make better choices.