• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.435-442
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• 2017

The runway visual range affected by fog and so on is one of the important indicators to determine whether aircraft can take off and land at the airport or not. In the case of airports where transportation airplanes are operated, major weather forecasts including the runway visual range for local area have been released and provided to aviation workers for recognizing that. This paper proposes a runway visual range estimation model with a deep neural network applied recently to various fields such as image processing, speech recognition, natural language processing, etc. It is developed and implemented for estimating a runway visual range of local airport with a deep neural network. It utilizes the past actual weather observation data of the applied airfield for constituting the learning of the neural network. It can show comparatively the accurate estimation result when it compares the results with the existing observation data. The proposed model can be used to generate weather information on the airfield for which no other forecasting function is available.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.491-499
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• 2018

Runway visual range (RVR), one of the important indicators of aircraft takeoff and landing, is affected by meteorological conditions such as temperature, humidity, etc. It is important to estimate the RVR at the time of arrival in advance. This study estimated the RVR of the local airport after 1 hour by upgrading the RVR estimation model using the proposed deep learning network. To this end, the advancement of the estimation model was carried out by changing the time interval of the meteorological data (temperature, humidity, wind speed, RVR) as input value and the linear conversion of the results. The proposed method generates estimation model based on the past measured meteorological data and estimates the RVR after 1 hour and confirms its validity by comparing with measured RVR after 1 hour. The proposed estimation model could be used for the RVR after 1 hour as reference in small airports in regions which do not forecast the RVR.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.70-75
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• 2012

This paper is part of the research about the selection and justification of Jeju international airport as an aircraft category 'F' alternative airport, which is the results of an weather analysis based on meteorological statistics. As the results of the study, it has been only 1 day per year (58minutes) that weather conditions of Incheon and Jeju international airports, from January 2006 to June 2011, are below landing weather minimums of each airport at the same times. This means that these airports are not within the same meteorological region, which is against the current orthodoxy. In addition, it is very rare that weather conditions of Jeju international airports are below landing weather minimums when Incheon international airport is below landing weather minima. It shows that the meteorological characteristics of these regions differ widely and the designation of Jeju international airport as an alternative airport is scientifically reasonable.

• Journal of the Korean Home Economics Association
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• v.48 no.5
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• pp.17-24
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• 2010

Although design, color, and material are important elements in stage costumes, stage lightning also plays significant role in the presentation of stage costumes. Costumes color, material and perception can be significantly influenced by visual effects. Stage illumination can be arranged or managed so that colors are closely related to or enhanced or change the effects of costume colors on the runway or display at specific times. The results of this thesis are as follow; 1) Fabric tone, name, brightness, and chroma of colors were changed by the colors of stage lighting. 2) An achromatic color was changed to a chromatic color after being combined with colors of stage lighting. 3) Stage illuminations can make fabric, colors look similar to stage colors. 4) Plain satin silk fabric which reflects light shows high brightness and chroma after being influenced by stage lighting its shining effects and color changes were clear and apparent. 5) Velvet pile fabric which absorbs light shows low brightness and chroma after being influenced by stage lightning its shining effects and changes of colors were not clear and apparent. In conclusion, natural lights did not significantly influence fabric colors and perception, while artificial lights had wide range of effects on fabric colors and perception.