• Journal of Navigation and Port Research
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• v.29 no.9
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• pp.777-782
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• 2005

Maritime transportation consists of various situations such as navigation in the ocean, ship handling at harbor entrances, cargo handling and mooring in harbors. Generally, ships are built for the purpose of currying people and materials upon the seas. In order to accomplish the mission, a ship must be built to withstand the rigors of heavy weather and waves. In particular, the safety of ship motions at the entering/departing harbor and mooring under the effects of waves is very important for ship operation from the viewpoint of marine engineering. Therefore, safety and efficiency during entrance, departure, and mooring are extremely important aspects in the evaluation of ship operations from viewpoints of ship motions. However, the ship motions near a harbor entrance are not observed or studied as much. In this paper, to evaluate the difficulty of ship operations, field observations were performed using a new observation system with high accuracy in typhoon seasons, and grasp was done concerning about the time series characteristic that ship motions change rapidly within a harbor. Namely, such observations enable the quantitative safety evaluation under the effects of waves during ships entering and departing harbors in heavy weather.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.93-102
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• 2023

Jeju International Airport is characterized by the occurrence of low-level windshear due to its location, surrounding terrain, and its weather characteristics. Especially the low-level windshear accompanied by tailwinds on both sides of the runway i.e., bidirectional tailwind, is a hazardous weather phenomenon with unique characteristics that are difficult to find at any other airports. This study focuses on bidirectional tailwind occurrence at Jeju International Airport in 2020-2021. As a result, characteristic pressure patterns of the types that cause bidirectional tailwind was identified as it was possible to categorize strong wind types such as 1) strong southwest wind, 2) strong east wind, and 3) strong northwest wind, which do not cause bidirectional tailwind, and wind direction variation types such as 4) bidirectional tailwind, and 5) south wind followed by southwest wind, which cause bidirectional tailwind. The results of this study are expected to contribute to improving aviation safety by enabling aviation operators to predict and take appropriate safety measures based on their understanding of the causes and characteristics of bidirectional tailwind.

• Atmosphere
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• v.29 no.5
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• pp.567-583
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• 2019

In this study, the high-resolution numerical simulations considering detailed anthropogenic heat, albedo, emission and roughness length are analyzed by using single layer Urban Canopy Model (UCM) in Weather Research Forecast (WRF). For this, improved urban parameter data for Seoul Metropolitan Area (SMA) was collected from global data. And then the parameters were applied to WRF-UCM model after it was processed into 2-dimensional topographical data. The 6 experiments were simulated by using the model with each parameter and verified against observation from Automated Weather Station (AWS) and flux tower for the temperature and sensible heat flux. The data for sensible heat flux of flux towers on Jungnang and Bucheon, the temperature of AWS on Jungnang, Gangnam, Bucheon and Neonggok were used as verification data. In the case of summer, the improvement of simulation by using detailed anthropogenic heat was higher than the other experiments in sensible flux simulation. The results of winter case show improved in all simulations using each advanced parameters in temperature and sensible heat flux simulation. Improvement of urban parameters in this study are possible to reflect the heat characteristics of urban area. Especially, detailed application of anthropogenic heat contributed to the enhancement of predicted value for sensible heat flux and temperature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.676-682
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• 2014

In this paper, precipitation echo(PRE) and non-precipitaion echo(N-PRE)(including ground echo and clear echo) through weather radar data are identified with the aid of neuro-fuzzy algorithm. The accuracy of the radar information is lowered because meteorological radar data is mixed with the PRE and N-PRE. So this problem is resolved by using RBFNN and judgement module. Structure expression of weather radar data are analyzed in order to classify PRE and N-PRE. Input variables such as Standard deviation of reflectivity(SDZ), Vertical gradient of reflectivity(VGZ), Spin change(SPN), Frequency(FR), cumulation reflectivity during 1 hour(1hDZ), and cumulation reflectivity during 2 hour(2hDZ) are made by using weather radar data and then each characteristic of input variable is analyzed. Input data is built up from the selected input variables among these input variables, which have a critical effect on the classification between PRE and N-PRE. Echo judgment module is developed to do echo classification between PRE and N-PRE by using testing dataset. Polynomial-based radial basis function neural networks(RBFNNs) are used as neuro-fuzzy algorithm, and the proposed neuro-fuzzy echo pattern classifier is designed by combining RBFNN with echo judgement module. Finally, the results of the proposed classifier are compared with both CZ and DZ, as well as QC data, and analyzed from the view point of output performance.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.319-327
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• 2016

This research attempts an analysis that fuses the big data concerning weather variation and health care from January 1, 2011 to December 31, 2014; it gives the weather factor as to what kind of influence there is for the incidence of food poisoning, and also endeavors to be helpful regarding national health prevention. By using R, the Logistic and Lasso Logistic Regression were analyzed. The main factor germ generating the food poisoning was classified and the incidence was confirmed for the germ of bacteria and virus. According to the result of the analysis of Logistic Regression, we found that the incidence of bacterial food poisoning was affected by the following influences: the average temperature, amount of sunshine deviation, and deviation of temperature. Furthermore, the weather factors, having an effect on the incidence of viral food poisoning, were: the minimum vapor pressure, amount of sunshine deviation and deviation of temperature. This study confirmed the correlation of meteorological factors and incidence of food poisoning. It was also found out that even if the incidence from two causes were influenced by the same weather factor, the incidence might be oppositely affected by the characteristic of the germs.

• Atmosphere
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• v.23 no.4
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• pp.401-412
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• 2013

East Asia experienced extremely cold weather in January 2011, while the previous December and the following February had normal winter temperature. In this study National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data are used to investigate the characteristic features observed in the meteorological fields such as temperature, sea-level pressure, geopotential height, and wind during this winter period. In January the planetary-wave pattern is dominated by stationary-wave form in the mid-to-high latitude region, while transient waves are significant in the previous month. To understand the planetary-wave features quantitatively, harmonic analyses have been done for the 500-hPa geopotential height field. In the climatological-mean geopotential heights the wave numbers 1, 2, and 3 are dominant during the whole winter. In January 2011 the waves of number 1, 2, and 3 are dominant and stationary as in the climatological-mean field. In December 2010 and February 2011, however, the waves of number 4, 5, and 6 play a major role and show a transient pattern. In addition to the distinctive features in each month the planetary-wave patterns dependent on the latitude are also discussed.

• Proceedings of the KIEE Conference
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• 2002.04a
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• pp.201-203
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• 2002

In recent years there has been a growing interest in renewable energy systems due to the environmental problem and the economic benefits of fuel savings. Such systems are usually connected to the existing power grid for "fuel displacement" purpose as well as of earning some "capacity credit". Wind power generation system(WPGS) is one of the most useful energy resource using natural environment. So far, it was very difficult to simulate the dispersed generation system including WPGS using EMTP or EMTDC because the source of the dispersed generation system has a particular wind power characteristic equation. In this paper, a novel simulation method of WPGS has proposed and a new wind turbine component for EMTDC is also developed. The wind power characteristic equation of wind turbine is used in order to realize the WPGS in EMTDC simulation. And the real field data of weather conditions is interfaced to EMTDC using Fortran program interface method. Consequently the simulation of WPGS using field data is realized in this paper and shows acceptable results.

• International Journal of Highway Engineering
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• v.19 no.2
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• pp.1-6
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• 2017

PURPOSES : Pavement textures can be categorized into four according to wavelength: microtexture, macrotexture, megatexture (roads), and roughness. Pavement surface texture influences a number of aspects of tire-pavement interaction such as wet-weather friction, tire-pavement noise, splash, spray, tire-wear, and rolling resistance. In particular, macrotexture is the pavement surface characteristic that considerably impacts tire-pavement noise. In general, it can be demonstrated that tire-pavement noise increases with the increase of texture depth and wavelength. Recently, mean profile depth (MPD) and wavelength have been used to evaluate tire-pavement noise. This study aimed to identify the relationship between mean profile depth and average wavelength for asphalt pavement based on the information obtained on a number of asphalt pavement sections. METHODS : Profile data were collected from a number of expressway sections in Korea. In addition, mean profile depth and average wavelength were calculated by using this profile data. Statistical analysis was performed to determine the correlationship between mean profile depth and average wavelength. RESULTS:This study demonstrates a linear relationship between mean profile depth and average wavelength for asphalt concrete pavement. CONCLUSIONS :The strong relationship between mean profile depth and average wavelength of asphalt pavement was determined in this study.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.3-11
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• 2013

Under the consumption of bad weather situation affects traffic flows, the study scope is focused on highway capacity and speed variations among other highway traffic flow characteristic changes according to snowfall density. Thus, this study carried out through the data collection and statistical analysis by focusing on capacity and speed changes. Traffic volume, speed and density were selected as factors to explain the property change of a traffic flow for analysis, and 7 basic sections such as 3 highways in Gyeonggi-do and 4 highways near the meteorological observatory were selected as survey points for data collection. Snowfall levels were classified into 3 steps(Light, Medium, Heavy Snow) to analyze the capacity change by snowfall levels. As a result of analysis, the change of capacity depending on snowfall levels decreased 13.2% in case of light snow compared to a good weather, 18.6% in case of medium snow and 32.0% in case of heavy snow, so the capacity reduction rate increased as the snowfall level increased. The worsening weather appeared to have a very big possibility to act as a factor to reduce the operational efficiency of a road, so a road design and operation method considering this should be presented in the future.

• Journal of the Mineralogical Society of Korea
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• v.32 no.4
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• pp.259-271
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• 2019

We evaluated mineralogical, physical property and accelerated weather resistance of cinnabar, realgar and orpiment used as cultural heritages and traditional paintings. JB and JS are sample names of cinnabar and JH and UH are sample names of orpiment and Realgar, respectively. As a result of mineralogical property evaluation, Jinsa was identified cinnabar (HgS) and there was no difference in chemical composition according to the grade. UH and JH were confirmed realgar (AsS) and orpiment (As₂S₃), respectively. The polarization characteristics such as shape and color indicate that pigments using our test were natural mineral pigment observed by polarization microscope. Especially, in the case of cinnabar, it is not easy to distinguish between natural mineral pigment and synthetic pigment. But the results of polarization microscope said that cinnabar is natural occurring mineral which have authentic mineral particle and unevenly fracture. As a result of thermal analysis, JH has a higher glass transition temperature and heat stability than UH. After accelerated weather test, cinnabar, realgar and orpiment were striking result in color change because of light degradation. Red color of cinnabar turn into black and the color of realgar and orpiment became brighter than before. JB (meta-cinnabar) is more photosensitivity and faster becoming dark than JB (cinnabar). Finally light transforms realgar (red, As₄S₄) in arsenolite (As₂O₃).