• Geomechanics and Engineering
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• v.36 no.4
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• pp.381-390
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• 2024

The introduction of bio-based materials has been recommended in the geotechnical engineering field to reduce environmental pollutants such as heavy metals and greenhouse gases. However, bio-treated soil methods face limitations in field application due to short research periods and insufficient verification of engineering performance, especially when compared to conventional materials like cement. Therefore, this study aimed to develop a machine learning model for predicting the unconfined compressive strength, a representative soil property, of biopolymer-based soil treatment (BPST). Four machine learning algorithms were compared to determine a suitable model, including linear regression (LR), support vector regression (SVR), random forest (RF), and neural network (NN). Except for LR, the SVR, RF, and NN algorithms exhibited high predictive performance with an R² value of 0.98 or higher. The permutation feature importance technique was used to identify the main factors affecting the strength enhancement of BPST. The results indicated that the unconfined compressive strength of BPST is affected by mean particle size, followed by biopolymer content and water content. With a reliable prediction model, the proposed model can present guidelines prior to laboratory testing and field application, thereby saving a significant amount of time and money.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1874-1885
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• 2018

The customer side operation is getting more complex in a smart grid environment because of the adoption of renewable resources. In performing energy management planning or scheduling, it is essential to forecast non-controllable resources accurately and robustly. The PV system is one of the common renewable energy resources in customer side. Its output depends on weather and physical characteristics of the PV system. Thus, weather information is essential to predict the amount of PV system output. However, weather forecast usually does not include enough solar irradiation information. In this study, a PV system power output prediction model (PPM) under limited weather information is proposed. In the proposed model, meteorological radiation model (MRM) is used to improve cloud cover radiation model (CRM) to consider the seasonal effect of the target region. The results of the proposed model are compared to the result of the conventional CRM prediction method on the PV generation obtained from a field test site. With the PPM, root mean square error (RMSE), and mean absolute error (MAE) are improved by 23.43% and 33.76%, respectively, compared to CRM for all days; while in clear days, they are improved by 53.36% and 62.90%, respectively.

• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.30-35
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• 2008

The present study has been conducted to examine the effect of grid resolution on the predicted results for electric cable fire using pyrolysis model in FDS(Fire Dynamics Simulator, version 5). The grid independent test for different grid resolutions has been performed for a PE coating cable and the grid resolution is defined by the non-dimensional characteristic length of fire and mean grid size. The calculated maximum heat release rate and mean flame spread rate were almost constant for higher grid resolution of 20${\sim}$25 and the computing time for the grid resolution takes approximately 20hours to solve flame propagation with pyrolysis model. The geometrical simplification of a electric cable dose not greatly affect on the maximum heat release rate and flame spread rate and the rectangular approximation of cable shape gives acceptable result comparing with the round cable with stepwise grid.

• The korean journal of orthodontics
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• v.5 no.1
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• pp.51-56
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• 1975

In orthodontic field, the study on gnathostatic model is very important to the diagnosis and analysis of malocclusion. The purpose of this study is to observe that relation of orbital plane and upper canine in Koreans. We selected 230 cases with normal occlusion, 124 male and 106 female cases aged from 12 years to 25 years, to prepare 230 gnathostatic models, and measured the distance from midpoint of mesio-distal distance of upper canine to orbital plane in gnathostatic model. The results obtained were as follows: 1) The mean value of the distance from upper canine to orbital plane showed no significant change with age. 2) The mean value of the distance from the upper canine to orbital plane was -3.11mm in male and -3.84mm in female. 3) The orbital plane passed through the upper canine in normal occlusion of Koreans.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.54-60
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• 2001

In this research, we developed a computer code that designs a compressor impeller, which serves as an essential component of a vacuum cleaner, and predicted its performance. The TEIS model originally developed by Japikse(1985), and the mean line analysis m combined to design the centrifugal impeller optimally. In this program the inlet geometry is designed by using the mean line analysis, and with assumption of resonable exit blade angle, the optimal geometry is searched by means of TEIS model and iterative scheme. The performance of designed impeller was compared with experimental data, and the far-field noise by the rotating impeller is also predicted.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.132-138
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• 2000

Complex gear shifting and high speed-reduction ratio reduce the transmission efficiency in power driveline of agricultural tractors. According to a field test, the power transmission efficiency of a tractor in transporting operations was estimated about 70%. However, the actual efficiency was found by the experiment to fluctuate in a range of 56 to 87%. Therefore, the constant efficiency model commonly used for a simulation of power drivelines is not likely to simulate its performance more accurately. In order to predict power transmission efficiency more accurately, a new model was proposed and the new concepts of the maximum efficiency and sticking torque were introduced. The error mean between the measured and the predicted efficiencies was about 2.3% in mean. The new model reflecting the transmission characteristics in the power driveline of tractors could be used to analyze and predict the power transmission performance of tractors more accurately.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.247-256
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• 1996

In this paper, we applied bayesian hierarchical model to analyze the field mice example introduced by Demster et al.(1981). For this example, we use Gibbs sampler method to provide the posterior mean and compared it with LSE(Least Square Estimator) and MLR(Maximum Likelihood estimator with Random effect) via the EM algorithm.

• Journal of KSNVE
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• v.7 no.2
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• pp.301-310
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• 1997

This paper presents active noise control method to form the near-field quiet zone for passengers in an automobile. The actuator model including interior acoustic plant, speaker and amplifier is experimentally identified in forms of auto-regressive and moving average by means of least mean square algorithm, The digital controller is composed of the regulator and Kalman filter to be designed based on LQG (linear quadratic gaussian). If the actuator model is prefiltered with digital filter to be properly designed for concentrating control performance index on the frequency band of primary noise source, LQG design approach can be effectively applied for the design of headset controller. Experimental results demonstrate that near-field quiet zone showing about 10dB noise reduction at microphone position can be formed using the headset located at passenger seat.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.422-433
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• 2017

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we developed for estimating garlic growth at field scale model in major cultivation regions. We used the $NDVI_{UAV}$ that reflects the crop conditions, and seven meteorological elements for 3 major cultivation regions from 2015 to 2017. For this study, UAV imagery was taken at Taean, Changnyeong, and Hapcheon regions nine times from early February to late June during the garlic growing season. Four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.), and fresh weight (F.W.) were measured for twenty plants per plot for each field campaign. The multiple linear regression models were suggested by using backward elimination and stepwise selection in the extraction of independent variables. As a result, model of cold type explain 82.1%, 65.9%, 64.5%, and 61.7% of the P.H., F.W., L.N., P.D. with a root mean square error (RMSE) of 7.98 cm, 5.91 g, 1.05, and 3.43 cm. Especially, model of warm type explain 92.9%, 88.6%, 62.8%, 54.6% of the P.H., P.D., L.N., F.W. with a root mean square error (RMSE) of 16.41 cm, 9.08 cm, 1.12, 19.51 g. The spatial distribution map of garlic growth was in strong agreement with the field measurements in terms of field variation and relative numerical values when $NDVI_{UAV}$ was applied to multiple linear regression models. These results will also be useful for determining the UAV multi-spectral imagery necessary to estimate growth parameters of garlic.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.309-311
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• 1996

It is analysed the discrepancy about the coronal magnetic field between solar optic and solar radio using magnetic fibril concept with filling factor and fractal structure model. The magnetic field of $\~$ 100 G considered in solar optics is mean value in a large scale, and that of $\~$1000 G in solar should be the value of fine structures inside 'macro' loop.