• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.54-56
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• 2006

Single-well-gas-sparging tests were developed and evaluated for assessing the feasibility of in-situ aerobic cometabolism of trichloroethylene (TCE), using propane as a growth substrate. To evaluate transport characteristics of dissolved solutes [sulfur hexafluoride (SF6) or bromide (non-reactive tracers), propane (a growth substrate), ethylene, propylene (nontoxic surrogates to probe for CAH transformation activity), and DO], push-pull transport tests were performed. Mass balance showed about 90% of the injected bromide and about 80% of the injected SF6 were recovered, and the recoveries of other solutes were comparable with bromide and slightly higher than SF6. A series of Gas-Sparging Biostimulation tests were performed by sparging propane/oxygen/argon/SF6 gas mixtures, and temporal ground water samples were obtained from the injection well under natural gradient 'drift' conditions. The decreased time for propane depletion and the longer time to deplete SF6 as a conservative tracer indicate the progress of biostimulation. Gas-Sparging Activity tests were performed. .Propane utilization, DO consumption, and ethylene and propylene cometabolism were well demonstrated. The stimulated propane-utilizers cometabolized ethylene and propylene to produce ethylene oxide and propylene oxide, as cometabolic by-products, respectively. Gas-Sparging Acetylene Blocking tests were performed by sparging gas mixtures including acetylene to demonstrate the involvement of monooxygenase enzymes. Gas substrate degradation was essentially completely Inhibited in the presence of acetylene, and no production of the corresponding oxides was also observed. The Gas-Sparging tests supports the evidences that the successive stimulation of propane-oxidizing microorganisms, cometabolic transformation of ethylene and propylene by the enzyme responsible for methane and propane degradation.

• Fire Science and Engineering
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• v.28 no.1
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• pp.31-36
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• 2014

Recently, the safety assessments with using the various evacuation programs are performed for improving the performance of fire and evacuation safety in the building. Generally, the evacuation programs can simulate the human behavior in fire situation by applying the variation of the movement speed and Fractional Effective Dose (FED) index in the smoke. However, if the simulation is performed without optional setting around the fire, the agents do not avoid the fire and they move through the fire. Therefore in this study, we define the radiative repulsion force which exists between the fire and the agents. Moreover, we modify the Helbing's movement model by adding the radiative repulsion force. As a result of the modified movement model, all agents move around the fire and they do not enter the upper bound area of radiative heat flux, $2.4kW/m^2$. From these results, we verified the reliability of the modified movement model.

• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2006.10a
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• pp.86-96
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• 2006

To provide some ecological informations for protection and management of mixed heronries, their distribution, breeding species and individuals, and site characteristics that may be important to heron ecology were investigated in Jeollanam-do during 2005 breeding season. During the study, 17 mixed heronries, containing a total of six ardeid species were found. Of them, Great Egret(Egretta alba) and Grey Heron(Ardea cinerea) bred in most sites(both 92%) and were most numerous(36.3%, 31.0% respectively). Many of heronries(53.3%) were located within the bamboo forest. Other site characteristics were as follows: the mean area of heronry was $2346m^2$ with range of $500-7,000m^2$, the mean distance between nearest two heronies was 18.1km with range of 5.6-40.4km, the mean distance to nearest village was 297m with range of 10-2,000m, the mean gradient of the topography was $18^{\circ}$ with range of $2^{\circ}{\sim}40^{\circ}$, and 40.0% of heronries were located in the eastern slope.

• Environmental Engineering Research
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• v.23 no.3
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• pp.294-300
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• 2018

Cometabolism technology was employed to degrade lignin wastewater in Sequencing Batch Biofilm Reactor. Cometabolic system (with glucose and lignin in inflow) and the control group (only lignin in inflow) were established to do a comparative study. In contrast with the control group, the average removal rates of lignin increased by 14.7% and total oarganic carbon increased by 32% in the cometabolic system with glucose as growth substrate, under the condition of 5 mg/L DO, $0.2kgCOD/(m^3{\cdot}d)$ lignin and glucose $1.0kgCOD/(m^3{\cdot}d)$. Functional groups of lignin are degraded effectively in cometabolic system proved by fourier transform infrared spectroscopy and Gas Chromatography-Mass Spectrometer, and the degradation products were amides (mainly including acetamide, N-ethylacetamide and N, N-diethylacetamide), alcohols (mainly including glycerol and ethylene glycol) and acids. Meanwhile, results of Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis showed great differences in microbial population richness between cometabolic system and the control group. The Margalef's richness index and Shannon-Wiener's diversity index of microorganism in cometabolic system were 3.075 and 2.61, respectively. The results showed that extra addition of glucose, with a concentration of 943 mg/L, was beneficial to lignin biodegradation in cometabolic system.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.619-627
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• 2022

In Korea, apples and pears are among the most important agricultural products to farmers who seek to earn money as income. Generally, farmers make decisions at various stages to maximize their income but they do not always know exactly which option will be the best one. Many previous studies were conducted to solve this problem by predicting farmers' income structure, but researchers are still exploring better approaches. Currently, machine learning technology is gaining attention as one of the new approaches for farmers' income prediction. The machine learning technique is a methodology using an algorithm that can learn independently through data. As the level of computer science develops, the performance of machine learning techniques is also improving. The purpose of this study is to predict the income structure of apples and pears using the automatic machine learning solution H2O.AI and to present some implications for apple and pear farmers. The automatic machine learning solution H2O.AI can save time and effort compared to the conventional machine learning techniques such as scikit-learn, because it works automatically to find the best solution. As a result of this research, the following findings are obtained. First, apple farmers should increase their gross income to maximize their income, instead of reducing the cost of growing apples. In particular, apple farmers mainly have to increase production in order to obtain more gross income. As a second-best option, apple farmers should decrease labor and other costs. Second, pear farmers also should increase their gross income to maximize their income but they have to increase the price of pears rather than increasing the production of pears. As a second-best option, pear farmers can decrease labor and other costs.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.537-542
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• 2001

In recent engineering, the designer has become more and more dependent on computer simulation. But defining exact model using computer simulation is too expensive and time consuming in the complicate systems. Thus, designers often use approximation models, which express the relation between design variables and response variables. These models are called metamodel. In this paper, we introduce one of the metamodel, named Kriging. This model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. This class of interpolating model has flexibility to model response data with multiple local extreme. By reason of this multi modality, we can't use any gradient-based optimization algorithm to find global extreme value of this model. Thus we have to introduce global optimization algorithm. To do this, we introduce DE(Differential Evolution). DE algorithm is developed by Ken Price and Rainer Storn, and it has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. This algorithm is similar to GA(Genetic Algorithm) in populating points, crossing over, and mutating. But it introduces vector concept in populating process. So it is very simple and easy to use. Finally, we show how we determine Kriging metamodel and find global extreme value through two mathematical examples.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.130-136
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• 1995

This paper is on the development of tools to generate pointillist representation-like images automatically by computer. Pointillist representation -like effects on the generated images are enforced by steps as follows. First, the position of brush stroke is determined from the gradient vector so that the brush touches look more natural. Second, pointillist representation-like coloring is endorsed by changing saturation and value using the RGB components of image. Our approach combines image processing techniques with computer graphics techniques for more faithful pointillist representation-like images and a couple of sample images are presented to show the effectiveness.

• Journal of Computing Science and Engineering
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• v.9 no.1
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• pp.29-38
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• 2015

Human action recognition has become an important research topic in computer vision area recently due to many applications in the real world, such as video surveillance, video retrieval, video analysis, and human-computer interaction. The goal of this paper is to evaluate descriptors which have recently been used in action recognition, namely Histogram of Oriented Gradient (HOG) and Histogram of Optical Flow (HOF). This paper also proposes new descriptors to represent the change of points within each part of a human body, caused by actions named as Histogram of Changing Points (HCP) and so-called Average Speed (AS) which measures the average speed of actions. The descriptors are combined to build a strong descriptor to represent human actions by modeling the information about appearance, local motion, and changes on each part of the body, as well as motion speed. The effectiveness of these new descriptors is evaluated in the experiments on KTH and Hollywood datasets.

• Atmosphere
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• v.23 no.1
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• pp.13-21
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• 2013

In this study, the effects of atmospheric stability and surface temperature on the microscale local airflow are investigated in a hydrological suburban area using a computational fluid dynamics (CFD) model. The model domain includes the river and industrial complex for analyzing the effect of water system and topography on local airflow. The surface boundary condition is constructed using a geographic information system (GIS) data in order to more accurately build topography and buildings. In the control experiment, it is shown that the topography and buildings mainly determine the microscale airflow (wind speed and wind direction). The sensitivity experiments of atmospheric stability (neutral, stable, and unstable conditions) represent the slight changes in wind speed with the increase in vertical temperature gradient. The differential heating of ground and water surfaces influences on the local meteorological factors such as air temperature, heat flow, and airflow. These results consequentially suggest that the meteorological impact assessment is accompanied by the changes of background land and atmospheric conditions. It is also demonstrated that the numerical experiments with very high spatial resolution can be useful for understanding microscale local meteorology.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.8
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• pp.11-16
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• 2008

In this paper, firstly we made of the rapid thermal processor equipment with the specifically useful structure to measure wafer stress. Secondly we made of the laser interferometry to inspect the wafer surface curvature based on the large deformation theory. And then the wafer surface fringe image was obtained by experiment, and the full field stress distribution of wafer surface comes into view by signal processing with thining and pitch mapping. After wafer was ground by 1mm and polished from the back side to get easily deformation, and it was heated by three to four times thermal treatments at about 1000 degree temperature. Finally the severe deformation between wafer before and after the heat treatment was shown.