• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.5 no.1
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• pp.93-101
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• 1994

This study was performed to assess the amount of altered serotonergic responsivity in individuals with repeated aggressive behaviors compared with normal controls. Sixteen aggressive(delinquent criminals with repeated aggressive behaviors) and seventeen controls(medical college students) were selected and assessed their severity of aggression by several psychological instruments. The platelet $^3H$-imipramine binding sites which is known to correlate the serotonergic function of the central nervous system were measured. The results are as follows. 1) Mean scores of physical aggression in the aggressive subjects were found to be significantly higher than normal controls(p<.01). And impulsivity, hostility, psychoticism in the aggressives were found higher than controls, also. 2) In the paltelet $^3H$-imipramine binding, the aggressives had a tendency of reduced maximal binding sites(Bmax) comparing with controls(p=.0841). 3) There was no statistically significant differences between two groups in the binding coefficients(Kd) of platelet $^3H$ Imipramine binding. 4) The value of maximal binding sites(Bmax) showed significant inverse correlations with aggressive scale scores of PFAV(r=-.6311), and physical aggression scale scores of CTS(r=-.5377).

• Progress in Superconductivity and Cryogenics
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• v.21 no.4
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• pp.1-5
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• 2019

We investigated the effect of Fe₃O₄ addition on the critical temperature of (Bi, Pb)-2223 polycrystalline samples. Bi_1.6Pb_0.4Sr₂Ca₂Cu₃O_10+δ + x wt. % Fe₃O₄ (x = 0.0, 0.2, 0.4, 0.6, and 0.8) samples were prepared by using a solid-state reaction method. The analysis of X-ray diffraction data indicates that as Fe₃O₄ is added, dominant phase of the sample changes from Bi-2223 to Bi-2212 with an increasing Bi-2201 phase. The transition temperature of the samples drastically decreased with the Fe₃O₄ addition. The resistance data of samples with x = 0.2 and 0.4 showed a double transition indicating a coexistence of Bi-2223 and Bi-2212 phase while the samples with x = 0.6 and 0.8 showed a single transition with a semiconducting behavior. This phase transition may originate from changes in local structure of the Bi-2223 system by Fe₃O₄ addition. Analysis of the pair distribution function of the Cu-O pair in the CuO₂ plane calculated from extended X-ray absorption fine structure data revealed that the oxygen coordination of copper ion changes from CuO₄ planar type (x = 0.0 - 0.4) to CuO₅ pyramidal type (x = 0.6, 0.8). The correlated Debye-Waller factor, providing information on the atomic disorder within the CuO₂ plane, shows an inverse relation to the coordination number. These results indicate that addition of Fe₃O₄ changes the oxygen distribution around Cu in the CuO₂ plane, causing a phase transition from Bi-2223 to more stable Bi-2212/Bi-2201 phases.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.87-93
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• 2014

If one identifies the detailed distribution of pressure and axial velocity at a source plane, the position and strength of major noise sources can be known, and the propagation characteristics in axial direction can be well understood to be used for the low noise design. Conventional techniques are usually limited in considering the constant source characteristics specified on the whole source surface; then, the source activity cannot be known in detail. In this work, a method to estimate the pressure and velocity field distribution on the source surface with high spatial resolution is studied. The matrix formulation including the evanescent modes is given, and the nearfield measurement method is proposed. Validation experiment is conducted on a wide duct system, at which a part of the source plane is excited by an acoustic driver in the absence of airflow. Increasing the number of evanescent modes, the prediction of pressure spectrum becomes further precise, and it has less than -25 dB error with 26 converged evanescent modes within the Helmholtz number range of interest. By using the converged modal amplitudes, the source parameter distribution is restored, and the position of the driver is clearly identified at kR = 1. By applying the regularization technique to the restored result, the unphysical minor peaks at the source plane can be effectively suppressed with the filtering of the over-estimated pure radial modes.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.391-400
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• 2017

Italian ryegrass (IRG) is one of the fastest growing grasses available to farmers. It offers rapid establishment and starts growing early in the following spring and has fast regrowth after defoliation. So, IRG can be utilized as the dominant/single species of grass used in a farming system, or to play a role as a large producing pasture and sacrificial paddock. The objective of this study was to develop the use of unmanned aerial vehicle (UAV) for the evaluation of feed value of IRG. For this study, UAV imagery was taken on the Nonsan regions two times during the IRG growing season. We analyzed the relationships between $NDVI_{UAV}$ and feed value parameters such as fresh matter yield, dry matter yield, acid detergent fiber (ADF), neutral detergent fiber (NDF), total digestible nutrient (TDN) and crude protein at the season of harvest. Correlation analysis between $NDVI_{UAV}$ and feed value parameters of IRG revealed that $NDVI_{UAV}$ correlated well with crude protein (r = 0.745), and fresh matter yield (r = 0.655). According to the relationship, the variation of $NDVI_{UAV}$ was significant to interpret feed value parameters of IRG. Eight different regression models such as Linear, Logarithmic, Inverse, Quadratic, Cubic, Power, S, and Exponential model were used to estimate IRG feed value parameters. The S and exponential model provided more accurate results to predict fresh matter yield and crude protein than other models based on coefficient of determination, p- and F-value. The spatial distribution map of feed values in IRG plot was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to regression equation. These lead to the result that the characteristics of variations in feed value of IRG according to $NDVI_{UAV}$ were well reflected in the model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.257-266
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• 2007

The research on red tide is generally in progress through field work, such as the naked eye and sampling. It was difficult to forecast exactly the course, from appearance of red tide to disappearance. with the established ways of investigation and analysis. Accordingly it is need to analyze environmental factors in time and space, the appearance of red tide and the path of its migration by more objective and scientific methods. In this study, GIS is applied to analyse the space character of red tide and the interpolation of IDW(Inverse Distance Weight) is applied to assume the density distribution of red tide after gather data by using Arc/Info. After IDW interpolation, the sea area occurred over 1,000 cells/ml of red tide density is extracted with CON and SUM Function of Grid Module, and the density of the sea area is accumulated daily. As a result of this study, the distribution condition of red tide is found timely and spacially by applying GIS to the sea area of red tide, the results indicated that the spatial density and the cumulative frequency about the origin of red tide using GIS, the sea area demonstrated that the maximum density and the maximum frequency varied significantly over the Nammyun of Namhae-Is. with the maximum frequency being 49 times. accordingly if data about the areas of red tide will occur from the present are accumulated, the shifting route of red tide occurrence and extinction can be predicted.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.181-191
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• 2020

In order to produce accurate initial condition of soil moisture for global Numerical Weather Prediction (NWP), spin-up experiment is carried out using Noah Land Surface Model (LSM). The model is run repeatedly through 10 years, under the atmospheric forcing condition of 2008-2017 until climatological land surface state is achieved. Spin-up time for the equilibrium condition of soil moisture exhibited large variability across Koppen-Geiger climate classification zone and soil layer. Top soil layer took the longgest time to equilibrate in polar region. From the second layer to the fourth layer, arid region equilibrated slower (7 years) than other regions. This result means that LSM reached to equilibrium condition within 10 year loop. Also, spin-up time indicated inverse correlation with near surface temperature and precipitation amount. Initialized from the equilibrium state, LSM was spun up to obtain land surface state in 2018. After 6 months from restarted run, LSM simulates soil moisture, skin temperature and evaportranspiration being similar land surface state in 2018. Based on the results, proposed LSM spin-up system could be used to produce proper initial soil moisture condition despite updates of physics or ancillaries for LSM coupled with NWP.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.479-487
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• 2004

Biopotential signals have been used as command in systems using electrical stimulation of motor nerves to restore movement after an injury to the central nervous system (CNS). In order to use the voluntary EMG (electromyography) among the biopotentials as a control signal for the electrical stimulation of the same muscle for CNS injury patients, it is necessary to remove M-wave of having high magnitude from raw data. We designed an optimal filter for removing the M-wave and preserving the voluntary EMG and showed that the optimal filter is eigen filter. We also proved that the previous method using the prediction error filter(PEF) is a suboptimal filtering in the sense of preserving the voluntary EMG. On basis of the data obtained from a model for M-wave and voluntary EMG and from actual CNS injury patients, with false-positive rate analysis, the proposed adaptive filter showed a very promising performance in comparison with previous method.

• Analytical Science and Technology
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• v.25 no.2
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• pp.133-145
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• 2012

The quantitative composition of total suspended particulates (TSP) in the atmosphere is identified to consist mainly of ions, organic carbon (OC), element carbon (EC), and metals. In terms of environmental analysis, the rest of the TSP composition may be defined as unknown fraction (${\Sigma}X$) which is yet difficult to analyze both quantitatively and qualitatively. In this study, the major components of TSP were measured at an urban residential area (Gang Seo) in Seoul, Korea from February to December 2009. These TSP data were analyzed in various respects to explain the relationship between known and unknown constituents. During this study period, TSP was comprised mainly of unknown compounds (48.6%) followed by ions, OC, EC, and metals. The results of this study indicate that the distribution of ${\Sigma}X$ exhibits a strong similarity with ${\Sigma}Anions$, as they both increase with increasing TSP levels. However, if the concentrations of ${\Sigma}X$ and ${\Sigma}Anion$ are normalized against TSP, they exhibit a strong inverse correlation with each other due probably to larges differences in solubility. To establish a better strategy for air quality control in urban atmosphere, more efforts are needed to characterize unidentified proportion of particulate matters.

• Magazine of the Korean Society of Agricultural Engineers
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• v.27 no.2
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• pp.23-37
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• 1985

This studies were carried out to get characteristics of frequency distribution, probable flood flows according to the return periods, and the correlation between return periods and those length of records affect the Risk of failure in the annual maximum series of the main river systems in Korea. Especially, Risk analysis according to the levels were emphasized in relation to the design frequency factors for the different watersheds. Twelve watersheds along Han, Geum, Nak Dong, Yeong San and Seom Jin river basin were selected as studying basins. The results were analyzed and summarized as follows. 1. Type 1 extremal distribution was newly confirmed as a good fitted distribution at selected watersheds along Geum and Yeong San river basin. Three parameter lognormal Seom Jin river basin. Consequently, characteristics of frequency distribution for the extreme value series could be changed in connection with the watershed location even the same river system judging from the results so far obtained by author. 2. Evaluation of parameters for Type 1 extremal and three parameter lognormal distribution based on the method of moment by using an electronic computer. 3. Formulas for the probable flood flows were derived for the three parameter lognormal and Type 1 extremal distribution. 4. Equations for the risk to failure could be simplified as $\frac{n}{N+n}$ and $\frac{n}{T}$ under the condition of non-parametric method and the longer return period than the life of project, respectively. 5. Formulas for the return periods in relation to frequency factors were derived by the least square method for the three parameter lognormal and Type 1 extremal distribution. 6. The more the length of records, the lesser the risk of failure, and it was appeared that the risk of failure was increasing in propotion to the length of return periods even same length of records. 7. Empirical formulas for design frequency factors were derived from under the condition of the return periods identify with the life of Hydraulic structure in relation to the risk level. 8. Design frequency factor was appeared to be increased in propotion to the return periods while it is in inverse proportion to the levels of the risk of failure. 9. Derivation of design flood including the risk of failure could be accomplished by using of emprical formulas for the design frequency factor for each watershed.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.