• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.159-166
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• 2013

In this paper, we propose a transmission rate compensation method to remove a haze of an image by using edge information of a haze image and image segmentation. With a hazed image, it is difficult not only to recognize objects in the image but also to use an image processing method. One of the famous defogging algorithm named 'Dark Channel Prior'(DCP) is used to predict fog transmission rate using dark area of an image, and eliminates fog from the image. But there is a big possibility to calculate a wrong transmission rate if the area of high RGB values is larger than the area of the reference area. Therefore we eliminate color distortion area to calculate transmission rate by using the propose method, and obtain a natural clean image from a hazed image.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.738-747
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• 2015

It is difficult to use a recognition algorithm of an image in a foggy environment because the color and edge information is removed. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)' which is used to predict for transmission rate using color information of an image and eliminates fog from the image. However, in case that the image has factors such as sunset or yellow dust, there is overemphasized problem on the color of certain channel after haze removal. Furthermore, in case that the image includes an object containing high RGB channel, the transmission related to this area causes a misestimated issue. In this paper, we purpose an enhanced fog elimination algorithm by using improved color normalization and haze rate revision which correct mis-estimation haze area on the basis of color information and edge information of an image. By eliminating the color distortion, we can obtain more natural clean image from the haze image.

• Journal of Korean Vacuum Science & Technology
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• v.6 no.2
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• pp.105-107
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• 2002

a-C:H films were coated on windows of mobile telephone by RF plasma chemical vapor deposition equipment made in our company. Thickness of the coatings is about 0.7 micrometers and they have high hardness, low friction coefficient, good adhesion, high optical transparency and chemical inertness. Knoop hardness of the diamond-like carbon films on glass substrate is 2328 kg/mm$^2$. The adherence between films and substrate is good and shows to be 69 N by scratching test. The optical performance is improved obviously owing to coat the film on it. The index of the coated windows is 2.5, transmission of visible light is larger than 90%, and transmission of ultraviolet light decreases by 30% and the ultraviolet light can be obstructed obviously. The coated glass also has self-clean effect and decontamination ability. The films have hydrophobic character and the soakage angle of water drop is larger than 90 degrees. The windows have fog-proof ability owing to eliminate the capillary phenomena in the inner surface. The physics and chemical properties of the coated windows are steady. Study indicates that the performance of a-C:H coated mobile phone windows are improved notably on wear-resistance, corrosion-proof and optical properties and it is excellent mobile windows protective coatings.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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• pp.6-9
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• 2001

In this research, a experiment was performed to evaluate the electrical properties of outdoor insulator with the pollution cycle method. Cycle test methods such as DCM of STRI, IEC 61109 compared with pollution cycle method. Using dimatic properties of Korea peninsula, we could get the optimal condition for the pollution cycle method. As the factor, clean and saline fog, voltage, rainfall and drying was chosen. The applied voltage is 13,2 kV, the salinity of salt solution was changed from 0.1 wt% to 1.5 wt% and one cycle is about 4 hours. To ensure the reproducibility and reliability, experiments repeated 4 times. The leakage current was measured with Lab VIEW and the ESDD was measured with brushwiping method. This experiment could ensure superiority of pollution cycle method which developed through the result of this experiment and we could know the relationship between ESDD, leakage current and relative humidity.

• Atmosphere
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• v.26 no.2
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• pp.243-256
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• 2016

Total number concentration of aerosols larger than 10 nm ($N_{CN10}$), 3 nm ($N_{CN3}$), and cloud condensation nuclei ($N_{CCN}$) were measured during four different ship cruises over the Yellow Sea. Average values of $N_{CN10}$ and $N_{CCN}$ at 0.6% supersaturation were 6914 and $3353cm^{-3}$, respectively, and the minimum value of $N_{CN10}$ was $2000cm^{-3}$, suggesting significant anthropogenic influence even at relatively clean marine environment. Although $N_{CN10}$ and $N_{CN3}$ increased near the coast due to anthropogenic influence, $N_{CCN}$ was relatively constant and therefore $N_{CCN}/N_{CN10}$ ratio tended to decrease, suggesting that coastal aerosols were relatively less hygroscopic. In general $N_{CN10}$, $N_{CN3}$, and $N_{CCN}$ during the cruises seemed to be significantly influenced by wet scavenging effects (e.g. fog) and boundary layer height variation. Only one new particle formation (NPF) event was observed during the measurement period. Interestingly, the NPF event occurred during a dust storm event and spatial scale of the NPF event was estimated to be larger than 100 km. These results demonstrate that aerosol and CCN concentration over the Yellow Sea can vary due to various different factors.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.45-54
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• 2022

Image depth estimation is a technology that is the basis of various image analysis. As analysis methods using deep learning models emerge, studies using deep learning in image depth estimation are being actively conducted. Currently, most deep learning-based depth estimation models are being trained with clean and ideal images. However, due to the lack of data on adverse conditions such as haze or fog, the depth estimation may not work well in such an environment. It is hard to sufficiently secure an image in these environments, and in particular, obtaining non-homogeneous haze data is a very difficult problem. In order to solve this problem, in this study, we propose a method of synthesizing non-homogeneous haze images and a learning method for a monocular depth estimation deep learning model using this method. Considering that haze mainly occurs outdoors, datasets mainly containing outdoor images are constructed. Experiment results show that the model with the proposed method is good at estimating depth in both synthesized and real haze data.

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.281-304
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• 2011

In the energy-climate era, pollution emissions from port activities have a significant issue in international shipping and port community. Thus international organization such as IMO and developed countries are seeking to develop various reduction strategies against air pollution. However Korea has recently conducted several studies concerning air pollution in port industry. The main purpose of the paper is to suggest emission reduction strategies for bulk terminal in Port of Incheon, which handles large amount bulk cargoes as a gateway for the metropolitan area. For this aim, the clean air strategies of the world major ports were considered and air pollution reduction strategies were suggested. The main findings of this paper are as follows. First, the emission reduction strategies for container terminal are should be integrated based on technologies changes, operational changes and market-based measures. Second, the emission reduction strategies for bulk terminal can be effective when use innovative measures during loading, unloading and storage process such as telescopic cascade trimming chute, snake sandwich equipment, dry fog system and dome structure. Finally, investigation on actual conditions of air pollution in Korean ports and development of environmental evaluation scheme for persisting monitoring should be conducted.