• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.51-60
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• 2010

To determine subglacial topography and internal features of the Fourcade Glacier on King George Island in Antarctica, helicopter-borne and ground-towed ground-penetrating radar (GPR) data were recorded along four profiles in November 2006. Signature deconvolution, f-k migration velocity analysis, and finite-difference depth migration applied to the mixed-phase, single-channel, ground-towed data, were effective in increasing vertical resolution, obtaining the velocity function, and yielding clear depth images, respectively. For the helicopter-borne GPR, migration velocities were obtained as root-mean-squared velocities in a two-layer model of air and ice. The radar sections show rugged subglacial topography, englacial sliding surfaces, and localised scattering noise. The maximum depth to the basement is over 79m in the subglacial valley adjacent to the south-eastern slope of the divide ridge between Fourcade and Moczydlowski Glaciers. In the ground-towed profile, we interpret a complicated conduit above possible basal water and other isolated cavities, which are a few metres wide. Near the terminus, the GPR profiles image sliding surfaces, fractures, and faults that will contribute to the tidewater calving mechanism forming icebergs in Potter Cove.

• ALGAE
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• v.30 no.2
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• pp.121-137
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• 2015

Studies on carbon flux in the oceans have been highlighted in recent years due to increasing awareness about climate change, but the coastal ecosystem remains one of the unexplored fields in this regard. In this study, the dynamics of carbon flux in a vegetative coastal ecosystem were examined by an evaluation of net and gross ecosystem production (NEP and GEP) and $CO_2$ exchange rates (net ecosystem exchange, NEE). To estimate NEP and GEP, community production and respiration were measured along different habitat types (eelgrass and macroalgal beds, shallow and deep sedimentary, and deep rocky shore) at Gwangyang Bay, Korea from 20 June to 20 July 2007. Vegetative areas showed significantly higher ecosystem production than the other habitat types. Specifically, eelgrass beds had the highest daily GEP ($6.97{\pm}0.02g\;C\;m^{-2}\;d^{-1}$), with a large amount of biomass and high productivity of eelgrass, whereas the outer macroalgal vegetation had the lowest GEP ($0.97{\pm}0.04g\;C\;m^{-2}\;d^{-1}$). In addition, macroalgal vegetation showed the highest daily NEP ($3.31{\pm}0.45g\;C\;m^{-2}\;d^{-1}$) due to its highest P : R ratio (2.33). Furthermore, the eelgrass beds acted as a $CO_2$ sink through the air-seawater interface according to NEE data, with a carbon sink rate of $0.63mg\;C\;m^{-2}\;d^{-1}$. Overall, ecosystem production was found to be extremely high in the vegetated systems (eelgrass and macroalgal beds), which occupy a relatively small area compared to the unvegetated systems according to our conceptual diagram of a carbon-flux box model. These results indicate that the vegetative ecosystems showed significantly high capturing efficiency of inorganic carbon through coastal primary production.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.5
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• pp.571-577
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• 2012

In this study, a small movable batch treatment system for dredging soil deposited in a rain water tube is proposed; further, a vacuum silo sorting separation device with a vacuum silo, first-stage sorting separator, and conveyor is designed. The vacuum silo sorting separation device also consists of a storage tank, transferring screw, vacuum gate, screen bar, screen bar cleaner, and vacuum discharging device. In view of the fact that the flow of drawn air in the storage tank is a major factor influencing the sorting separation performance, the optimum shape of the tank is determined by CFD flow analysis. In addition, by using CAE structure analysis, the safety of a storage tank made of boards is examined. The specifications of the vacuum silo sorting separation device are determined by conducting mechanical and dynamic simulations of the driving mechanism of the vacuum silo sorting separation device through 3D-CAD modeling. Following this study, we will design a drum-screen-type second sorter, a decanter-type dehydration device, and waste water tank and pump as a secondary device. Further, on the basis of this design, we will construct a prototype model and carry out a field test.

• Applied Chemistry for Engineering
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• v.8 no.6
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• pp.954-959
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• 1997

The solid solutions of the $Sr_{1-X}M_XFeO_{3-y}$ (x=0.1, 0.2, 0.3, 0.4, 0.5, M=Ca) system having perovskite structures were prepared in air by heat treatment at 1473 K for 18hr. X-ray diffraction assigns cubic system for all the samples and shows that the lattice volume of each system decreases with increasing x value until x=0.3, but increases abruptly from x=0.4. The mole fractions of $Fe^{4+}$ ion($\tau$ value), the amounts of oxygen vacancy (y value) and finally nonstoichiometric chemical formulas for each composition were determined from Mohr salt analysis. TG/DTA thermal analysis (temperature range: 300~1173K) exhibits that 3-y values of the samples having x=0.1 and 0.2, decrease with temperature and increase almost reversibly with decreasing temperature. The samples of $x{\geq}0.3$, however, didn't show the reversible weight change and the 3-y values of them were nearly 2.5 in cooling process. Conductivities of each sample were varied within the semiconductivity range at relatively low temperature. And the conductivity at constant temperature decreases steadily with x value. The conduction mechanism of this ferrite system may be proposed as a hopping model of conducting electrons between the mixed valence states. At high temperature semiconductivity of each sample changed into metallic property.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.11-19
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• 2020

In recent years, college students have emerged as the main players in Chinese innovation and start-ups. Based on the TPB theory, this paper introduced the start-up education variables and established the influence model of start-up education for university students in China on the motivation of start-up. In this paper, a questionnaire containing five variables, including behavior attitude, subjective norms, perceived behavior control, entrepreneurship education and entrepreneurial intention, was investigated for students from six universities in Jilin Province, China, and statistical analysis was carried out using SPSS23.0. The study found that the entrepreneurship education of college students had the greatest impact on entrepreneurial intentions compared to the three elements of planned behavioral theory: behavioral attitudes, subjective norms and perceived behavioral control. This paper has a guiding significance in strengthening start-up education in universities. This study was conducted only for students from six universities in Jilin Province, China, and the scope of the study needs to be expanded throughout China in order to generalize the research results.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.467-474
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• 2011

In an effort to investigate water pollution characteristics of Juam lake, water samples were collected from three sites (Sites A, B, and C) of Oenam stream which is a typical tributary of rural watershed in the lake and analyzed for N concentration and the corresponding isotope ratio (${\delta}^{15}N$) of ${NO_3}^-$. Concentrations of ${NO_3}^-$ were not dramatically different among the sites; $0.8{\pm}0.2mgNL^{-1}$ (range: $0.0{\sim}4.3mgNL^{-1}$) for Site A, $1.1{\pm}0.2mgNL^{-1}$ ($0.0{\sim}4.3mgNL^{-1}$) for Site B, and $1.1{\pm}0.1mgNL^{-1}$ ($0.1{\sim}2.6mgNL^{-1}$) for Site C. Meanwhile, ${\delta}^{15}N$ tended to decrease with river flow; it was highest for Site A ($45.5{\pm}5.3$‰) followed by Site B ($19.7{\pm}2.0$‰) and Site C ($8.7{\pm}1.5$‰). Such high ${\delta}^{15}N$ values of ${NO_3}^-$ in Site A suggested that ${NO_3}^-$ derived from livestock feedlot (specifically livestock excrete of which ${\delta}^{15}N$ is higher than 10‰) is the predominant pollution sources despite mountainous area occupied the most of land-use in the watershed. Using the two-sources isotope mixing model, it was estimated that the contribution of cropping activities (i.e. fertilization) became greater in down-stream area (Sites B and C) due to the higher agricultural land-use than the up-stream area (Site A). Particularly, during the active cropping season, the low contribution of organic pollution sources indicated that domestic sewage was not the predominant pollution source. Therefore, it was suggested that agricultural sources such as livestock farming and cropping rather than mountainous and residential are the dominant sources of water pollution in the study area. These results could be effectively utilized in elucidating water pollution sources in rural areas and selecting water management practices.

• Journal of Bio-Environment Control
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• v.10 no.2
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• pp.80-87
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• 2001

This study was conducted to provide basic data for the design of shading facility of greenhouse. The proper distance between external shading screen and roof surface, transmissivity of shading materials, and shading effects of external and internal shadings were analyzed. About a distance of 10 cm between inclined external shading screen and roof surface was enough to guarantee the external shading effect in the greenhouse without roof vent. The inside temperature of greenhouse installed with 85% internal shading screen was lower the maximum of 4$^{\circ}C$ and mean of 2$^{\circ}C$ than that with 55% internal shading screen in both natural ventilation and no ventilation condition. The difference of soil temperature between shading and no shading greenhouse was great, but the difference by shading rate or shading method was small. The performance of external shading for controlling inside temperature down was superior to that of the internal shading. The externally inclined shading screen parallel to the roof surface of greenhouse was more effective than the externally horizontal shading screen in controlling inside temperature of greenhouse without roof vent.

• 한국체육학회지인문사회과학편
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• v.57 no.6
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• pp.293-308
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• 2018

This study was carried out to investigate the current trends in skiing-related research from existing literature in the field of kinematics, measurement sensor and computer simulation. In the field of kinematics, research is being conducted on the mechanism of ski turn, posture analysis according to the grade and skill level of skiers, friction force of ski and snow, and air resistance. In the field of measurement sensor and computer simulation, researches are being conducted for researching and developing equipment using IMU sensor and GPS. The results of this study are as follows. First, beyond the limits of the existing kinematic analysis, it is necessary to develop measurement equipment that can analyze the entire skiing area and can be deployed with ease at the sports scene. Second, research on the accuracy of information obtained using measurement sensors and various analysis techniques based on these measures should be carried out continuously to provide data that can help the sports scene. Third, it is necessary to use computer simulation methods to clarify the injury mechanism and discover ways to prevent injuries related to skiing. Fourth, it is necessary to provide optimized ski trajectory algorithm by developing 3D ski model using computer simulation and comparing with actual skiing data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.