• Korean Journal of Agricultural Science
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• v.3 no.2
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• pp.207-213
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• 1976

In order to obtain the prediction of the maximum dry density and the optimum moisture content of soil without soil moisture test, compaction test results from 157 different places either under construction or already completed were analyzed. The analyzed results were as follow The relationship between the maximum dry density and the optimum moisture content of the soil showing a correlation coefficient of 0.96 indicated that there was a high correlation between them. From the above relationship we obtained the equation, ${\gamma}_{dmax.}={\frac{1}{0.4193+0.00937W_{opt.}}$ Equation between the optimum moisture content and the maximum wet density of the soil was $W_{opt.}={\frac{0.4193{\gamma}_{tmax.}}{0.937_{\gamma}_{tmax.}-0.01}$, and the values of the optimum moisture content being predicted with the maximum wet density of the soil showed a little difference between those and tested values. The values of the maximum dry density being predicted with the moisture content estimated by the maximum wet density of the soil were within the range of ${\pm}5%$ of its tested values. The relationship between the dry density and the void ratio showed a high correlation between them (${\gamma}=0.9706$). From the above relationship, we obtained the equation, ${\gamma}_{dmax.}={\frac{1}{0.3938+0.3426e}}$.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1584-1588
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• 2018

During hyperthermia therapy, cancer cells are heated to a temperature in the range of $40{\sim}45^{\circ}C$ for a defined time period to damage these cells while keeping healthy tissues at safe temperatures. Prior to hyperthermia therapy, the amount of heat energy transferred to the cancer cells must be predicted. Among various non-invasive methods, the thermal prediction method using the specific absorption rate (SAR) is the most widely used method. The existing methods predict the thermal distribution by using a single constant for the mass density in one organ through assignment. However, because the SAR and the bio heat equation (BHE) vary with the mass density, the mass density of each organ must be accurately considered. In this study, the mass density distribution was calculated using the relationship between the Hounsfield unit and the mass density of tissues in preceding research. The SAR distribution was found using a quasi-static approximation to Maxwell's equation and was used to calculate the potential distribution and the energy distributions for capacitive RF heating. The thermal distribution during exposure to RF waves was determined by solving the BHE with consideration given to the considering contributions of heat conduction and external heating. Compared with reference data for the mass density, our results was within 1%. When the reconstructed temperature distribution was compared to the measured temperature distribution, the difference was within 3%. In this study, the density distribution and the thermal distribution were reconstructed for the agar phantom. Based on these data, we developed an algorithm that could be applied to patients.

• 한국데이터정보과학회:학술대회논문집
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• 2002.06a
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• pp.23-28
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• 2002

Support vector machine(SVM) has been very successful in classification, regression, time series prediction and density estimation. In this paper, we will propose SVM for fuzzy data classification.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.3
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• pp.86-102
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• 2003

Polynitrogen molecules are of great interest as potential high energy-density materials, and hence such structures of various isomers of nitrogen clusters have been calculated using molecular modeling techniques by the researchers from various sectors of scientific institutions. In this article, the predicted meta-stable structures of these hypothetical molecules have been thoroughly reviewed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.625-626
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• 2010

• Computers and Concrete
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• v.19 no.5
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• pp.555-566
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• 2017

Recently some efforts have been performed to combine the advantages of light-weight and self-compacting concrete in one package called Light-Weight Self-Compacting Concrete (LWSCC). Accurate prediction of hardened properties from fresh state characteristics is vital in design of concrete structures. Considering the lack of references in mixture design of LWSCC, investigating the proper mixture components and their effects on mechanical properties of LWSCC can lead to a reliable basis for its application in construction industry. This study utilizes wide range of existing data of LWSCC mixtures to study the individual and combined effects of the components on the compressive strength. From sensitivity of compressive strength to the proportions and interaction of the components, two equations are proposed to estimate the LWSCC compressive strength. Predicted values of the equations are in good agreement with the experimental data. Application of lightweight aggregate to reduce the density of LWSCC may bring some mixing problems like segregation. Reaching a higher strength by lowered density is a challenging problem that is investigated as well. The results show that, the compressive strength can be improved by increasing the of mixture density of LWSCC, especially in the range of density under $2000Kg/m^3$.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.188-195
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• 2000

This study was conducted to measure the moisture content of powdered food using RF impedance spectroscopic method. In frequency range of 1.0 to 30㎒, the impedance such as reactance and resistance of parallel plate type sample holder filled with wheat flour and red-pepper powder of which moisture content range were 5.93∼-17.07%w.b. and 10.87 ∼ 27.36%w.b., respectively, was characterized using by Q-meter (HP4342). The reactance was a better parameter than the resistance in estimating the moisture density defined as product of moisture content and bulk density which was used to eliminate the effect of bulk density on RF spectral data in this study. Multivariate data analyses such as principal component regression, partial least square regression and multiple linear regression were performed to develop one calibration model having moisture density and reactance spectral data as parameters for determination of moisture content of both wheat flour and red-pepper powder. The best regression model was one by the multiple linear regression model. Its performance for unknown data of powdered food was showed that the bias, standard error of prediction and determination coefficient are 0.179% moisture content, 1.679% moisture content and 0.8849, respectively.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.21-24
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• 2014

In this study, we have investigated the maximum smoke density and the initial stage smoke density in order to see the characteristics of smoke release of the architectural surface materials and the architectural adhesives, using smoke density chamber. As a result of the study, polyurethane foam showed the highest smoke density index, 206.55 within 10 min. In the case of the other samples, reinforced styrofoam was followed as 39.90, general styrofoam 33.73, and glass fiber 5.40, respectively. In the intial stage of a fire, it is forecasted actually to give hardship at the clear visibility. In the case of architectural adhesives, the highest ranking was those for windows and doors 509.64, stone 275.63, wood 232.25, tile 18.65, and styrofoam 6.44 were followed, respectively. This result is an early research to show characteristics of smoke release through experiment. However, it is meaningful that this study can be used as a basic for further study on architectural fire hazard prediction.

• Journal of Powder Materials
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• v.26 no.5
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• pp.369-374
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• 2019

The properties of powder metallurgy products are related to their densities. In the present work, we demonstrate a method to apply artificial neural networks (ANNs) trained on experimental data to predict the bulk density of barium titanates. The density is modeled as a function of pressure, press rate, heating rate, sintering temperature, and soaking time using the ANN method. The model predictions with the training and testing data result in a high coefficient of correlation (R2 = 0.95 and Pearson's r = 0.97) and low average error. Moreover, a graphical user interface for the model is developed on the basis of the transformed weights of the optimally trained model. It facilitates the prediction of an infinite combination of process parameters with reasonable accuracy. Sensitivity analysis performed on the ANN model aids the identification of the impact of process parameters on the density of barium titanates.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.2
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• pp.159-174
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• 2022

Flow prediction was carried out through observational survey and three dimensional multi-layered numerical diagnostic model experiment to clarify the time and spatial structure of tidal current and residual flow dominant in the sea exchange and material circulation of the waters around Geumo Islands in the southern waters of Korea. The horizontal variation of tidal current is so large that it causes asymmetric tidal mixing due to horizontal eddies and the topographical effect creating convergence and dispersion of flow direction and velocity. Due to strong tidal currents flowing northwest-southeast, counterclockwise and clockwise eddies are formed on the left and right sides of the south of Sori Island. These topographical eddies are created by horizontal turbulence and bottom friction causing nonlinear effects. Baroclinic density flows are less than 5 cm/s at coastal area in summer and the entire sea area in winter. The wind driven currents assuming summer and winter seasonal winds are also less than 5 cm/s and the current flow rate is high in winter. Density current in summer and wind driven current in winter have a relatively greater effect on the net residual flows (tidal residual current + density current + density driven current) around Geumo Islands Sea area.