• Asian-Australasian Journal of Animal Sciences
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• v.16 no.8
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• pp.1126-1130
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• 2003

The conditions of measurement for the determination of bulk density were evaluated to assess the bulkiness of 8 kinds of forage. The bulkiness of the forages was determined with 4 different sizes of forage samples with 7 different pressure application under air-dry and wet conditions. The dry bulk density (DBD) curvilinearly regressed with the pressure applied. The particle size of the samples and kinds of forage used in the present study did not affect changes in values of DBD determined under pressures over $20g/cm^2$ up to $200g/cm^2$. The values of the wet bulk density (WBD) increased as an increment of particle size, but were not always regressed on the particle size of the 8 kinds of forage. The DBD determined on 8 mm particles showed a higher correlation coefficient with neutral detergent fiber (NDF) contents. The DBD may be a useful tool for the assessment of NDF in forage, when it is determined under condition of a pressure of $100g/cm^2$ or over with a particle size of 8 mm. The WBD may not be utilized for the direct measurement of the physical characteristics of forage, but may be required a thorough consideration on water solubility of forages. Further studies are needed to clarify the DBD contribution to the prediction of forage intake by ruminants.

• Bulletin of the Korean Chemical Society
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• v.24 no.12
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• pp.1742-1750
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• 2003

In order to characterize the hydrophobic parameters of N-acetyl amino acid amides in 1-octanol/water, a theoretical calculation was carried out using a solvation free energy density model. The hydrophobicity parameters of the molecules are obtained with the consideration of the solvation free energy over the solvent volume surrounding the solute, using a grid model. Our method can account for the solvent accessible surface area of the molecules according to conformational variations. Through a comparison of the hydrophobicity of our calculation and that of other experimental/theoretical works, the solvation free energy density model is proven to be a useful tool for the evaluation of the hydrophobicity of amino acids and peptides. In order to evaluate the solvation free energy density model as a method of calculating the activity of drugs using the hydrophobicity of its building blocks, the contracture of Bradykinin potentiating pentapeptide was also predicted from the hydrophobicity of each residue. The solvation free energy density model can be used to employ descriptors for the prediction of peptide activities in drug discovery, as well as to calculate the hydrophobicity of amino acids.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.46.1-46.1
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• 2016

The formation process of a current sheet is important for solar flare from a viewpoint of a space weather prediction. We therefore derive the temporal development of the spatial and statistical distribution of electric current density distributed in a flare-producing active region to describe the formation of a current sheet. We derive time sequence distribution of electric current density by applying a nonlinear force-free approximation reconstruction to Active Region 12158 that produces an X1.6-class flare. The time sequence maps of photospheric vector magnetic field used for reconstruction are captured by a Helioseismic and Magnetic Imager (HMI) onboard Solar Dynamic Observatory (SDO) on 10th September, 2014. The spatial distribution of electric current density in NLFFF model well reproduce observed sigmoidal structure at the preflare phase, although a layer of high current density shrinks at the postflare phase. A double power-law profile of electric current density is found in statistical analysis. This may be expected to use an indicator of the occurrence of a solar flare.

• Journal of ILASS-Korea
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• v.13 no.3
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• pp.117-125
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• 2008

The correlations for the prediction of maximum liquid-phase penetration in diesel spray are reviewed in this study. The existing models developed for the prediction of maximum liquid-phase penetration can be categorized as the zero-dimensional (empirical) model, the multi-dimensional model and the other model. The existing zero-dimensional model can be classified into four groups and the existing multidimensional models can be classified into three groups. The other model includes holistic hydraulic and spray model. The maximum liquid-phase penetration is mainly affected by nozzle diameter, fuel volatility, injection pressure, ambient gas pressure, ambient gas density and fuel temperature. In the case of empirical correlations incorporated with spray angle, the predicted results will be different according to the selection of correlation for spray angle. The research for the effect of boiling point temperatures on maximum liquid-phase penetration is required. In the case of multidimensional model, there exist problems of the grid and spray sub-models dependency effects.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.448-451
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• 2005

This paper presents the methodology to analyze flow duration characteristics and performance prediction for small hydro power(SHP) plants and its application. The flow duration curvecan be decided by using monthly rainfall data at the most of the SHP sites with no useful hydrological data. It was proved that the monthly rainfall data can be characterized by using the cumulative density function of Weibull distribution and Thiessen method were adopted to decide flow duration curve at SHP plants. And, the performance prediction has been studied and development. One SHP plant was selected and performance characteristics was analyzed by using the developed technique. Primary design specfications such as design flowrate, plant capacity, operational rate and annual electricity production for the SHP plant were estimated. It was found that the methodology developed in this study can be a useful tool to predict the performance of SHP plants and candidate sites in Korea.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.28-34
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• 2007

Recently, with the rapid growth of industry, environmental condition became worse. In addition to outdoor insulators in seashore are polluted due to salty wind. Also this pollution causes the flashover and failure of electric equipments. Especially the salt contaminant is one of the most representative pollutants, and known as the main source of the accident by contamination. As well known, the pollution has a close relation with meteorological factors such as wind velocity, wind direction, temperature, relative humidity, precipitation and so on. In this paper we have statistically analyzed the correlation between the pollution and the meteorological factors. The multiple regression analysis was used for the statistical analysis; daily measured equivalent salt deposit density(dependent variable) and the weather condition data(independent variable) were used. Also we have developed an expert program to predict the pollution deposit. A new prediction system using this program called SPPP(salt pollution prediction program) has been used to model accurately the relationship between ESDD with the meteorological factors.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.42-48
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• 2015

This paper has its purpose on constructing a prediction model of the arrival sequencing strategy which reflects the actual sequencing patterns of air traffic controllers. As the first step, we analyzed a pair-wise sequencing of two aircraft entering TMA from different entering points. Based on the historical trajectory data, several traffic factors such as time, speed and traffic density were examined for the model. With statistically significant factors, we constructed a prediction model of arrival sequencing through a binary logistic regression analysis. With the estimated coefficients, the performance of the model was conducted through a cross validation.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.376-379
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• 2004

Operational orbit determination (OOD) depends on the capability of generating accurate prediction of spacecraft ephemeris in a short period. The predicted ephemeris is used in the operations such as instrument pointing and orbit maneuvers. In this study the orbit prediction problem consists of the estimating diverse arc length orbit using GPS navigation data, the predicted orbit for the next 48 hours, and the fitted 30-hour arc length orbits of double differenced GPS measurements for the predicted 48-hour period. For 24-hour orbit arc length, the predicted orbit difference from truth orbit was 205 meters due to the along-track error. The main error sources for the orbit prediction of the Low Earth Orbiter (LEO) satellite are solar pressure and atmosphere density.

• Wind and Structures
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• v.31 no.6
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• pp.549-560
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• 2020

Methods for stochastic simulation of non-Gaussian wind pressure have increasingly addressed the efficiency and accuracy contents to offer an accurate description of the extreme value estimation of the long-span and high-rise structures. This paper presents a linear prediction and z-transform (LPZ) based Cumulative distribution function (CDF) mapping algorithm for the simulation of multivariate non-Gaussian fluctuating wind pressure. The new algorithm generates realizations of non-Gaussian with prescribed marginal probability distribution function (PDF) and prescribed spectral density function (PSD). The inverse linear prediction and z-transform function (ILPZ) is deduced. LPZ is improved and applied to non-Gaussian wind pressure simulation for the first time. The new algorithm is demonstrated to be efficient, flexible, and more accurate in comparison with the FFT-based method and Hermite polynomial model method in two examples for transverse softening and longitudinal hardening non-Gaussian wind pressures.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.259-272
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• 2023

In this paper, we suggest a new method for the prediction of sharp changes in particulate matter (PM₁₀) using quantile mapping. To predict the current PM₁₀ density in Seoul, we consider PM₁₀ and precipitation in Baengnyeong and Ganghwa monitoring stations observed a few hours before. For the PM₁₀ distribution estimation, we use the extreme value mixture model, which is a combination of conventional probability distributions and the generalized Pareto distribution. Furthermore, we also consider a quantile generalized additive model (QGAM) for the relationship modeling between precipitation and PM₁₀. To prove the validity of our proposed model, we conducted a simulation study and showed that the proposed method gives lower mean absolute differences. Real data analysis shows that the proposed method could give a more accurate prediction when there are sharp changes in PM₁₀ in Seoul.