• KOREAN JOURNAL OF CROP SCIENCE
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• v.56 no.1
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• pp.44-49
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• 2011

The bio-degradable transplanting pot containing rice by-product (rice-hull and rice-bran) were developed, and tested their ability for agronomic use. Rice by-products were crosslinked with biodegradable aliphatic ally aromatic copolyesters or urea resin for making transplanting pot. Mechanical properties and degradability of these pots were measured and compared to those of the Jiffy pot (commercially used bio-degradable pot). Mechanical strength was higher than that of Jippy pot, and bio-degradability was excellent under the actual field condition. In addition, the pot could be degraded within 3 months under the ground. Our result indicated bio-degradable pot containing rice by-products has a great potential for such agronomic use.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.257-263
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• 2015

This study was conducted to assess the potential of using NIRS to accurately determine the chemical composition and fermentation parameters in fresh coarse sorghum and sudangrass silage. Near Infrared Spectroscopy (NIRS) has been increasingly used as a rapid and accurate method to analyze the quality of cereals and dried animal forage. However, silage analysis by NIRS has a limitation in analyzing dried and ground samples in farm-scale applications because the fermentative products are lost during the drying process. Fresh coarse silage samples were scanned at 1 nm intervals over the wavelength range of 680~2500 nm, and the optical data were obtained as log 1/Reflectance (log 1/R). The spectral data were regressed, using partial least squares (PLS) multivariate analysis in conjunction with first and second order derivatization, with a scatter correction procedure (standard normal variate and detrend (SNV&D)) to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV). The results of this study showed that NIRS predicted the chemical constituents with a high degree of accuracy (i.e. the correlation coefficient of cross validation ($R^2{_{cv}}$) ranged from 0.86~0.96), except for crude ash which had an $R^2{_{cv}}$ of 0.68. Comparison of the mathematical treatments for raw spectra showed that the second-order derivatization procedure produced the best result for all the treatments, except for neutral detergent fiber (NDF). The best mathematical treatment for moisture, acid detergent fiber (ADF), crude protein (CP) and pH was 2,16,16 respectively while the best mathematical treatment for crude ash, lactic acid and total acid was 2,8,8 respectively. The calibrations of fermentation products produced poorer calibrations (RPD < 2.5) with acetic and butyric acid. The pH, lactic acid and total acids were predicted with considerable accuracy at $R^2{_{cv}}$ 0.72~0.77. This study indicated that NIRS calibrations based on fresh coarse sorghum and sudangrass silage spectra have the capability of assessing the forage quality control

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Journal of The Korean Society of Grassland and Forage Science
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• v.24 no.2
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• pp.163-170
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• 2004

A new oil crop chufa(Cyperus esculentus var. sativus) was studied to evaluate the yield potential of tuber and productivity of leaf as a new forage crop resources. Response to nitrogen fertilizer was not clear, showing low yield over 10kg/l0a of nitrogen application. Tuber yield was higher at 50cm $\times$ 15cm and 50cm$\times$20cm of planting population of tuber. Planting at early May showed high tuber yield, and sprouting tuber planting could not increased the tuber yield. The plant height of Chufa is 126cm, and the number of tiller per $\m^2$ are 671. It is moderate to lodging, but susceptable according to the amount of field products. Fresh forage and dry matter yield of above ground of chufa were 2,135kg/10a, and 590kg/l0a, respectively. The contents of crude protein, ether extract, fiber, ash, and acid detergent fiber are 24.8%, 8.1%, 38%, 64.4%, 52.8%, and 55.9%, respectively. It was considered that the nutritive value of chufa leaf in maturing stage was so good as rice straw.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.2
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• pp.160-164
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• 1999

Subsurface environments, including the intermediate vadose zone and aquifers, may be contributing to increased atmospheric concentrations of $N_2$O. Denitrification appears to be the major source of $N_2$O in the subsurface environment. In the intermediate vadose zone, the level of denitrifying activity is dependent on the soil morphology, particularly stratified layers within the soil profile, which impede water and solute movement and create conditions favorable for denitrification. Movement of organic C from the soil surface appears to support denitrifying activity by providing an energy source and increasing the consumption of $O_2$. Denitrirication and $N_2$O production have been observed in aquifers but appear to be of greatest significance in shallow unconfined aquifers. The lack of organic C, N $O_2$, or anaerobiosis is often a limiting factor for activity but seems to be site specific. The presence of denitrifying bacteria does not appear to be a major limitation, based on published results, but the ubiquity of denitrifiers in subsurface environments needs to be confirmed. The fate of the $N_2$O produced in subsurface environments is unknown. Transport of $N_2$O by up ward diffusion, by outgassing at contacts with surface waters, and by ground water use need to be quantified to determine the contribution to atmospheric $N_2$O. Contamination of subsurface environment with N $O_3$$^{ }$ and organics has the potential for increasing the contribution to atmospheric $N_2$O by enhancing denitrification .

• Geotechnical Engineering
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• v.10 no.2
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• pp.121-140
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• 1994

This paper presents the probabilistic model to evaluate the three-dimensional stability of layered deposits and c-0 soil slopes. Rotational slides are assumed with a cylindroid control part terminated with plane ends. And the potential failure surfaces in this study are assumed with the logarithmic spiral curve refracted at boundary of layers. This model takes into consideration the spatial variabilities of soil properties and the uncertainties stemming from insufficient number of samples and the discrepancies between laboratory measured and in -situ values of shear strength parameters. From the probabilistic approxi mate method (FOSM and SOSM method), the mean and variance of safety factor are calculated, respectively. And the programs based on above models is developed and a case study is analysed in detail to study the sensitivity of results to variations in different parameters by using the programs developed in this study. On the basis of thin study the following conclusions could be stated : (1) The sensitivity analysis shown that the probability of failure is more sensitive to the uncertainty of the angle of internal friction than that of the cohesion, (2) The total 3-D proability of failure and the critical width of failure are significantly affected by total width of slope. It is found that the total 3-D probability of failure and the critical width of failure increase with increasing the slope width when seismic forces do not exist and the total 3-D probability of failure increases with increasing the slope width and the critical width of failure decreases when seismic intensity is relatively large, (3) A decrease in the safety factor (due to effect such as a rise in the mean ground water level, lower shear strength parameters, lower values for the correction factors, etc.) would result in reduction in the critical width of failure.

• Journal of the Korean Society for Railway
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• v.17 no.2
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• pp.94-99
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• 2014

Recently, trends in new transportation system development have been primarily focused on sustainable and ecofriendly mobility solutions. The personal rapid transit (PRT) system has been considered a promising candidate in this category; its competitiveness is being improved through convergence with cutting-edge electric vehicle (EV) technologies. However, battery-powered vehicles pose difficult technical challenges in attempts to achieve reliable and efficient operation. In this study, a design approach for a solar-power assisted PRT system is presented with small-scale demonstrations aimed at circumventing challenges facing its adoption, as well as helping speed the transition to electric-powered ground transportation. From the results, it is expected that flexible photovoltaic (PV) cells will be able to supply 11% of the power required by the service equipment installed in a prototype vehicle. In particular, flexible photovoltaic (PV) cells are advantageous in terms of cost, weight, and design considerations. Most importantly, the cells' flexibility and attach-ability are expected to give them great potential for extended application in various areas.

• Environmental and Resource Economics Review
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• v.19 no.3
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• pp.597-632
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• 2010

There is general agreement that global warming is occurring and that the main contributor to this probably is the buildup of green house gasses, GHG, in the atmosphere. Two main contributors are the utilization of fossil fuels and the deforestation of many regions of the world. The burning of fossil fuels increases atmospheric carbon while the burning of fuel-wood reducing fossil fuel consumption along with its forest source maintain an atmospheric carbon level. The standing timber in the forests is a carbon sink, as are wood buildings and structures, and fossil fuel in the ground. This paper is designed to examine a number of current issues related to mitigating the global warming problem through forestry. For this purpose, we develop a modeling approach by integrating timber market, fossil fuel market and carbon cycling model. We use discrete time optimal control theory to identify optimal time paths, the laws of motion, and stationary stats solutions of endogenous variables in the model. On the basis of these results, we identify the optimal amounts of subsidies to be provided or taxes to be imposed by the regulatory agency to mitigate atmospheric carbon accumulation. We also present a numerical example to help illustrate the characteristics of variables in the model when the social cost for atmospheric carbon incrementally shifts upward. A surprising result is that the social cost function for atmospheric carbon has a very smaller impact on the optimal rotation period than previous literature suggested.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.75-88
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• 2009

The main purpose of the current research is to introduce the alternative algorithm of the non-recursive batch filter based on the unscented transformation in which the linearization process is unnecessary. The presented algorithm is applied to the orbit determination of a low earth orbiting satellite and compared its results with those of the well-known Bayesian batch least squares estimation and the iterative UKF smoother (IUKS). The system dynamic equations consist of the Earth's geo-potential, the atmospheric drag, solar radiation pressure and the lunar/solar gravitational perturbations. The range, azimuth and elevation angles of the satellite measured from ground stations are used for orbit determination. The characteristics of the non recursive unscented batch filter are analyzed for various aspects, including accuracy of the determined orbit, sensitivity to the initial uncertainty, measurement noise and stability performance in a realistic dynamic system and measurement model. As a result, under large non-linear conditions, the presented non-recursive batch filter yields more accurate results than the other batch filters about 5% for initial uncertainty test and 12% for measurement noise test. Moreover, the presented filter exhibits better convergence reliability than the Bayesian least squares. Hence, it is concluded that the non-recursive batch filter based on the unscented transformation is effectively applicable for highly nonlinear batch estimation problems.

• Journal of the Korean Geosynthetics Society
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• v.12 no.2
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• pp.13-23
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• 2013

The Korean Peninsula is considered as a seasonal frozen area that is thawed in the spring and frozen in the winter. The influence of fines of the frost susceptibility of subgrade soils were established by laboratory freezing tests simulating closely the thermal conditions in the field. During the winter season, the climate is heavily influenced by the cold and dry continental high pressure. Because of siberian air mass, the temperature of January is $-6{\sim}-7^{\circ}C$ on average. This chilly weather generate the frost heaving by freezing the moisture of soil and damage potential of the geotechnical structure. In the freezing soil, the ice lenses increase the freeze portion of soil by absorbing the ground water with capillary action. However, the capillary characteristics differ from the sort of soil on the state of freezing condition. In this study, ten soil samples are prepared. The basic physical property tests were performed by following the Korean Industrial Standard and the soil specimens were classified by the Unified Soil Classification System (USCS). These classified soils are used to perform the laboratory opened systems freezing test in order to determine the frost heaving characteristics of soils such as unfrozen water content, heaving amount, and freezing depth.