• Atmosphere
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• v.12 no.4
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• pp.69-90
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• 2002

The infrared and microwave satellite observations have been used to derive the information of hydrometeors (i.e., cloud and precipitation) and atmospheric temperature. The observations were made by the Nimbus-4 Infrared Interferometer Spectrometer (IRIS) in 1970, and by the Microwave Sounding Unit (MSU) during the period 1980-99, which had channel 1~4 (Chl~4). The IRIS, which has a field of view of ~100 km, has been utilized to examine the cirrus and marine stratus clouds. The cirrus and stratus distributions were obtained, respectively, based on the spectral difference in the infrared window region, and the absorption of water vapor and $CO_2$ in the spectral region $870-980cm^{-1}$. The MSU Ch1 data has been used for low tropospheric temperature and hydrometeors, while the Ch2, Ch3 and Ch4, respectively, for the thermal state of midtroposphere, tropopause, and lower stratosphere. The climatic aspects of El Ni$\tilde{n}$o, Quasi-Biennial Oscillation (QBO) and temperature trends over the globe are discussed with the MSU data. This study suggests that the IRIS and MSU data are useful for monitoring the hydrometeors and atmospheric thermal state in climate system.

• Tribology and Lubricants
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• v.27 no.2
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• pp.109-114
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• 2011

The low temperature characteristics of automotive diesel have been legally regulated due to the fact that solid particle in diesel at low temperature can cause severe problems in the vehicle. The biodiesel is well known for eco-friendly fuel, which is one of the most popular alternative petrodiesel, but it is easy to solidified at low temperature than petrodiesel at low temperature. For that reason, in this study, we investigated the low temperature fuel characteristics of diesel-biodiesel blends which were prepared to mix 6 different kinds of biodiesel to winter diesel fuel, respectively. Also, we confirmed to improve low temperature fuel characteristics by pour point depressant.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1409-1416
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• 2015

The change of temperature influences on the various aspect, especially human health, plant and animal's growth, economics, industry, and culture of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly temperature data at the Suwon monitoring site in Korea. In the ARE model, five meteorological variables, four greenhouse gas variables and five pollution variables are used as the explanatory variables for the temperature data set. The five meteorological variables are wind speed, rainfall, radiation, amount of cloud, and relative humidity. The four greenhouse gas variables are carbon dioxide ($CO_2$), methane ($CH_4$), nitrous oxide ($N_2O$), and chlorofluorocarbon ($CFC_{11}$). And the five air pollution explanatory variables are particulate matter ($PM_{10}$), sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), ozone ($O_3$), and carbon monoxide (CO). Among five meteorological variables, radiation, amount of cloud, and wind speed are more influence on the temperature. The radiation influences during spring, summer and fall, whereas wind speed influences for the winter time. Also, among four greenhouse gas variables and five pollution variables, chlorofluorocarbon, methane, and ozone are more influence on the temperature. The monthly ARE model explained about 43-69% for describing the temperature.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.75-83
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• 2018

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.17-37
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• 1987

The purpose of this study is to establish more rational and practical planning theory for amusement park. It analyze and consider the fluctuation of people who come and use the Tong-Ch'on amusement park. The results drawn from this reserch work are as follows; 1. The main visitors of the Tong-Ch'on amusement park are students in their twenties and thirties, and people whose incomes are below 300,000 Won a month. The purpose of visit is for a rest rather than for amusement and user prefer summer, while the user is so rare in wintertime. Those phenomena observed are somewhat different from the real purpose of a amusement park which is on purpose to make profits by offering entertainments to the users. So planner should pay attention to the three points. They are varieties, seasonable diversification and fantastic character of facilties, in the amusement park. 2. The access time of the Tong-Ch'on amusement park was 41 minutes, the use frequency was 4 times a year and resident time was 164 minutes. The relationship of the three factors are as follows; log Y(F) =1.7832-0.0277(A.T) R$^2$=0.75 Y(R. F)=31.8885+3.3217(A.T) R$^2$=0.53 Y(R. T)=224.8959-87.8309 1og(F) R$^2$=0.38 F;Use frequency(time/year) A.T;Access Time(minute) R.T;Resident Time(minute) 3. In the choice of space, there were much differences according to tole user's age, job, degree of education, companion type and purpose of use. 4. There are considerable correlation between use fluctuation and some factors. The factors are season(summer, winter) as a time, temperature, cloud amount, duration of sunshine, weather(rainy-day) as a climate and a day of the week(weekday, holiday) as a social system. The important variables are temperature, cloud amount, duration of sunshine and a day of the week(weekday, holiday) to estimate the user of amusementpark. 5. 1 can reduce the following two types of regression models. 1) log$\sub$e/ Y1 = 6.9114 + 0.l135 TEM + 0.00002 SUN -0.4068W1 + 0.4316 W3 (R$^2$= 0.94) 2) log$\sub$e/ Y2 = 7.2069 + 0.l177 TEM - 0.0990 CLO + 0.4880 W3 (R$^2$=0.95) Y; Number of User TEM; Temperature CLO; Amount of cloud SUN; Duration of Sunshine W1; Weekday W3; Holiday Those model is in order to estimate the user for management of Tong-Ch'on amusement park and use on the computation of facility sloe for reconstruction. Besides the amusement park, city park and outdoor recreation area could estimate of user through this method. But, I am not sure about the regression models because I did not apply the regression models to the other amusement park, city Park or outdoor recreation area. Therefore, I think that this problem needs to be studied on in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.1
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• pp.86-98
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• 1998

In order to provide an information as input data of possible storm surges in advance, the typhoon center and maximum wind position analysis scheme must be developed for the initialization of pressure and wind field.This study proposes a semi-automatical and objective analysis method and a procedure on a real time basis using the satellite TBB data of the GMS IR1, NOAA satellite CH4 and CH5, and shows the result of an experimental analysis. It includes a simple method of determining the parameters of the typhoon using minimum top temperature of the convective cloud near the inner eyewall. The method analyzing the isotropic cross sectional variation of TBB gradient from center to environment was developed to determine the center of Rmax of typhoon. This position of intense eyewall from typhoon center can be considered as the position of maximum wind. The results of estimation of typhoon center show very good agreement to the results of synoptic analysis. It is found that the Rmax is approximately 50-200km. From the comparison of the GMS and NOAA IR TBB data, it is found that the Rmax from NOAA data tends to be longer than those from GMS data.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.291-296
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• 2003

This study estimated surface temperature by using split-window technique and NOAA/AVHRR data was used. For surface monitoring, cloud masking procedure was carried out using threshold algorithm. The daily maximum air temperature is estimated by multiple regression method using independent variables such as satellite-derived surface temperature, EDD, and latitude. When the EDD data added, the highest correlation shown. This indicates that EDD data is the necessary element for estimation of the daily maximum air temperature. We derived correlation and experience equation by three approaching method to estimate daily maximum air temperature. 1) non-considering landcover method as season, 2) considering landcover method as season, and 3) just method as landcover. The last approaching method shows the highest correlation. So cross-validation procedure was used in third method for validation of the estimated value. For all landcover type 5, the results using the cross-validation procedure show reasonable agreement with measured values(slope=0.97, intercept=-0.30, R$^2$=0.84, RMSE=4.24$^{\circ}C$). Also, for all landcover type 7, the results using the cross-validation procedure show reasonable agreement with measured values(slope=0.993, Intercept=0.062, R$^2$=0.84, RMSE=4.43$^{\circ}C$).

• Journal of the Korean Society of Safety
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• v.19 no.3 s.67
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• pp.65-69
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• 2004

This study was performed with Hartmann type dust explosion apparatus and Godbert-Greenwald furnace apparatus in order to research the effect of temperature and humidity affecting LEL, minimum ignition temperature of Hydroxy Propyl Methyl Cellulose. The experimental determinations in the range between $20^{\circ}C\;and\;60^{\circ}C$ of temperature was not affected $LEL(180g/m^3)$ but LEL showed $200g/m^3\;and\;250g/m^3\;at\;80^{|circ}C\;and\;100^{\circ}C$. As the change of humidity LEL was $180g/m^3\;for\;50\%,\;200g/m^3\;for\;60\%\;and\;250g/m^3\;for\;70\%$ but dust explosion didn't occur over $80\%$. The ignition temperature of HPMC dust clouds was increased as increasing of humidity. So, the minimum ignition temperatures at $50\%,\;60\%,\;70\%\;80\%$ of humidity was $363^{\circ}C,\;375^{\circ}C,\;397^{\circ}C,\;405^{\circ}C$.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.1-4
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• 2002

This article presents the unique characteristics of cavitation, those are very high pressure and very high temperature even in a very short time. Such the high-pressure causes the destruction of material, which sometimes brings a severe problem to fluid machinery. However, if we look the cavitation from the different direction, such the high pressure can be used to various applications. The author presents two examples of the utilization of cavitation recently done at the Toyo University. Those are 'dispersion of spilled oil' and 'killing planktons'.

• Atmosphere
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• v.20 no.4
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• pp.427-436
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• 2010

The single-scattering optical properties of ice crystals in cirrus clouds by the aircraft measurement data were investigated, and the radiative equilibrium temperatures and radiative fluxes were calculated and analyzed by radiative convective model with the variations of ice crystal habits and sizes in cirrus clouds. The homogeneous cloud is assumed to be in the layer 200~260 hPa with an ice crystal content of $10gm^{-2}$ for the flux calculation. The profiles of temperature, humidity, and ozone typical of mid-latitude summer are used. The surface albedo is assumed to be 0.2 for all spectral bands and the cosine of solar zenith angles is 0.5. The result of radiative equilibrium temperature at surface was less than surface temperature of the standard atmosphere data in case of smaller effective ice crystal size and larger optical thickness. The column, aggregation and plate in 6 ice crystal habits were the most effective in positive greenhouse effect and bullet-4 was the worst in it. At the surface, the maximum difference of equilibrium temperature by 6 kinds of ice crystal habits were about 3~15 K with 30 sample aircraft measurement data.