• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.2
• /
• pp.1-16
• /
• 2017

This study was conducted to analyze the urban heat island(UHI) intensity of South Korea by using Moderate Resolution Imaging Spectroradiometer(MODIS) satellite imagery. For this purpose, the metropolitan area was spatially divided according to land cover classification into urban and non-urban land. From the analysis of land surface temperature(LST) in South Korea in the summer of 2009 which was calculated from MODIS satellite imagery it was determined that the highest temperature recorded nationwide was $36.0^{\circ}C$, lowest $16.2^{\circ}C$, and that the mean was $24.3^{\circ}C$, with a standard deviation of $2.4^{\circ}C$. In order to analyze UHI by cities and counties, UHI intensity was defined as the difference in average temperature between urban and non-urban land, and was calculated through RST1 and RST2. The RST1 calculation showed scattered distribution in areas of high UHI intensity, whereas the RST2 calculation showed that areas of high UHI intensity were concentrated around major cities. In order to find an effective method for analyzing UHI by cities and counties, analysis was conducted of the correlation between the urbanization ratio, number of tropical heat nights, and number of heat-wave days. Although UHI intensity derived through RST1 showed barely any correlation, that derived through RST2 showed significant correlation. The RST2 method is deemed as a more suitable analytical method for measuring the UHI of urban land in cities and counties across the country. In cities and counties with an urbanization ratio of < 20%, the rate of increase for UHI intensity in proportion to increases in urbanization ratio, was very high; whereas this rate gradually declined when the urbanization ratio was > 20%. With an increase of $1^{\circ}C$ in RST2 UHI intensity, the number of tropical heat nights and heat wave days was predicted to increase by approximately five and 0.5, respectively. These results can be used for reference when predicting the effects of increased urbanization on UHI intensity.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.1
• /
• pp.41-50
• /
• 2022

In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.1
• /
• pp.1-9
• /
• 2006

Regardless of the recent observed warmer winters in Korea, more freeze injuries and associated economic losses are reported in fruit industry than ever before. Existing freeze-frost forecasting systems employ only daily minimum temperature for judging the potential damage on dormant flowering buds but cannot accommodate potential biological responses such as short-term acclimation of plants to severe weather episodes as well as annual variation in climate. We introduce 'dormancy depth', in addition to daily minimum temperature, as a complementary criterion for judging the potential damage of freezing temperatures on dormant flowering buds of grape vines. Dormancy depth can be estimated by a phonology model driven by daily maximum and minimum temperature and is expected to make a reasonable proxy for physiological tolerance of buds to low temperature. Dormancy depth at a selected site was estimated for a climatological normal year by this model, and we found a close similarity in time course change pattern between the estimated dormancy depth and the known cold tolerance of fruit trees. Inter-annual and spatial variation in dormancy depth were identified by this method, showing the feasibility of using dormancy depth as a proxy indicator for tolerance to low temperature during the winter season. The model was applied to 10 vineyards which were recently damaged by a cold spell, and a temperature-dormancy depth-freeze injury relationship was formulated into an exponential-saturation model which can be used for judging freeze risk under a given set of temperature and dormancy depth. Based on this model and the expected lowest temperature with a 10-year recurrence interval, a freeze risk probability map was produced for Hwaseong County, Korea. The results seemed to explain why the vineyards in the warmer part of Hwaseong County have been hit by more freeBe damage than those in the cooler part of the county. A dormancy depth-minimum temperature dual engine freeze warning system was designed for vineyards in major production counties in Korea by combining the site-specific dormancy depth and minimum temperature forecasts with the freeze risk model. In this system, daily accumulation of thermal time since last fall leads to the dormancy state (depth) for today. The regional minimum temperature forecast for tomorrow by the Korea Meteorological Administration is converted to the site specific forecast at a 30m resolution. These data are input to the freeze risk model and the percent damage probability is calculated for each grid cell and mapped for the entire county. Similar approaches may be used to develop freeze warning systems for other deciduous fruit trees.

• Archives of design research
• /
• v.20 no.3 s.71
• /
• pp.299-314
• /
• 2007

For the past 20 years, the growth and development of university-design-educational institutes contributed to the industrial development of our country. Due to the technological fluctuation and changes in the industrial structure in the latter half of the 20th century, the enterprise is demanding professionally-oriented design manpower. The principle which appears from instances of the advanced nations is to accommodate the demands in social changes and apply them to educational design programs. In order to respond promptly to the industrial demand especially, the advanced nations adopted "multidisciplinary design education programs" to lead innovation in the area of design globally. The objective of the research consequently is to suggest an educational system and a program through which the designer can be educated to obtain complex knowledge and the technique demanded by the industry and enterprise. Nowadays in order to adapt to a new business environment, designers specially should have both the knowledge and techniques in engineering and business administration. We suggest that the IPDI, a multidisciplinary design educational system and program is made up of the coordinated operation of major classes, on-the-job training connection, educational system for research base creation, renovation design development program for the application and the synthesis of alternative proposals about the training facility joint ownership by connecting with the education of design, business administration and engineering.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.8 no.4
• /
• pp.853-860
• /
• 2007

In this modern era, human beings lead their life in complex environment where there are lots of parameters such as temperature, light, smell, sound, visual stimulus etc. that play important role for quality life. These parameters affect physical and mental behavior of a human being immensely. To ensure quality life the demand for quality products is always associated with human emotion and sensibility. Due to human sensibility and emotion involvement with quality life, the design stages of any kind of product must include some certain features related with emotion and sensibility. The cues for optimizing artificial environment are the physiological responses of human in that environment. The conventional approach of environmental physiology is to measure the relationship between environmental physical parameters and human psychological parameters under artificial conditions. Using that approach we tried to design an artificial environment for our daily lives and activities associated with both physiological and psychological behavior. We developed the technique to present the mock environment and software to measure and evaluate sensibility physiologically or psychologically and a simulator to measure and evaluate sensibility that can be utilized for large scale industrial production and design of environment. Simulator to measure and analyze human sensibility (SMAS) was constructed, which was utilized to estimate human sensibility and to simulate living and office environment.

• Restorative Dentistry and Endodontics
• /
• v.32 no.1
• /
• pp.19-27
• /
• 2007

The purpose of this study is to develope new dental color-space system. Twelve kinds of dental composites and one kind of dental porcelain were used in this study. Disk samples (15 mm in diameter, 4 mm in thickness) of used materials were made and sample's CIE $L^*a^*b^*$ value was measured by Spectrocolorimeter (MiniScan XE plus, Model 4000S, diffuse/$8^{\circ}$ viewing mode, 14.3 mm Port diameters, Hunter Lab USA) The range of measured color distribution was analyzed. All the data were applied in the form of T### which is expression unit in CNU Cons Dental Color Chart. The value of $L^*$ lies between 80.40 and 52.70. The value of $a^*$ are between 10.60 and 3.60 and $b^*$ are between 28.40 and 2.21. The average value of $L^*$ is 67.40, and median value is 67.30. The value of $a^*$ are 2.89 and 2.91 respectively. And for the $b^*$, 14.30 and 13.90 were obtained. The data were converted to T### that is the unit count system in CNU-Cons Dental Color Chart. The value of $L^*$ is converted in the first digit of the numbering system. Each unit is 2.0 measured values. The second digit is the value of $a^*$ and is converted new number by 1.0 measured value. For the third digit $b^*$ is replaced and it is 2.0 measured unit apart. T555 was set to the value of $L^*$ ranging from 66.0 to 68.0, value of $a^*$ ranging from 3 to 4 and $b^*$ value ranging from 14 to 16.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.2
• /
• pp.80-98
• /
• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.