• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.891-905
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• 2011

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• Journal of Environmental Science International
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• v.25 no.9
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• pp.1269-1281
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• 2016

This study evaporative cooling system a heat wave climate change and reduction of the inside and outside thermal environment change research. Measurement items included micro meteorological phenomena and measured comfort indices. A micro meteorograph of temperature, relative humidity, surface temperature, and the comfort indices of WBGT, UTCI, and PMV were measured. The difference in inside and outside temperatures were compared for different land types, with the largest difference found in Type A ($4.81^{\circ}C$), followed by Type B ($4.40^{\circ}C$) and Type C ($3.12^{\circ}C$). Relative humidity was about 10.43% higher inside due to water injection by the evaporative cooling system. Surface temperature was inside about $6.60^{\circ}C$ higher than the outside all types. WBGT were Type A ($3.50^{\circ}C$) > Type B ($2.71^{\circ}C$) > Type C ($1.88^{\circ}C$). UTCI was low heat stress inside than outside all types. PMV was analysed Type C for inside predicted percentage of dissatisfied 75%, other types was percentage of dissatisfied 100% by inside and outside. Correlation analysis between land cover type and temperature, surface temperature, pmv, utci. T-test analysed inside and outside temperature difference was significant in all types of land.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.14-22
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• 2011

It is important for the strategy of service to provide the health information in the environment that the healthcare has been changed focusing on the preventive medicine. Recently, the various applications of u-healthcare have been presented by researchers. In this paper, we proposed the health information monitoring system using the context sensors based band. By wearing the proposed hand, the health status is gathered and vital signals are transmitted to the connected UMPC. It can be easily monitored according to the user locations in real time. To provide the health index according to the temperature, the air conditioning, the illumination, the humidity, and the ultraviolet rays, we use the various XML links extracted from RSS of the Korea Meteorological Administration. The health information is analyzed in terms of factors, such as, the asthma index, the stroke index, the skin disease index, the pulmonary disease index, the pollen concentration index, and the city high temperature index. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed system. Accordingly, the satisfaction and the quality of services will be improved the healthcare.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.357-364
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• 2016

Purpose: This study was performed to define the drying characteristics of sorghum by developing thin layer drying equations and evaluating various grain drying equations. Thin layer drying equations lay the foundation characteristics to establish the thick layer drying equations, which can be adopted to determine the design conditions for an agricultural dryer. Methods: The drying rate of sorghum was measured under three levels of drying temperature ($40^{\circ}C$, $50^{\circ}C$, and $60^{\circ}C$) and relative humidity (30%, 40%, and 50%) to analyze the drying process and investigate the drying conditions. The drying experiment was performed until the weight of sorghum became constant. The experimental constants of four thin layer drying models were determined by developing a non-linear regression model along with the drying experiment results. Result: The half response time (moisture ratio = 0.5) of drying, which is an index of the drying rate, was increased as the drying temperature was high and relative humidity was low. When the drying temperature was $40^{\circ}C$ at a relative humidity (RH) of 50%, the maximum half response time of drying was 2.8 h. Contrastingly, the maximum half response time of drying was 1.2 h when the drying temperature was $60^{\circ}C$ at 30% RH. The coefficient of determination for the Lewis model, simplified diffusion model, Page model, and Thompson model was respectively 0.9976, 0.9977, 0.9340, and 0.9783. The Lewis model and the simplified diffusion model satisfied the drying conditions by showing the average coefficient of determination of the experimental constants and predicted values of the model as 0.9976 and Root Mean Square Error (RMSE) of 0.0236. Conclusion: The simplified diffusion model was the most suitable for every drying condition of drying temperature and relative humidity, and the model for the thin layer drying is expected to be useful to develop the thick layer drying model.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.73-79
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• 2019

Continuous and tremendous data (canopy temperature and meteorological variables) are necessary to determine Crop Water Stress Index (CWSI). This study investigated the optimal monitoring time and interval of canopy temperature and meteorological variables (air temperature, relative humidity, solar radiation and wind speed) to determine CWSIs. The Nash-Sutcliffe model efficiency coefficient (NSE) was used to quantitatively describe the accuracy of sampling method depending upon various time intervals (t=5, 10, 15, 20, 30 and 60 minutes) and CWSIs per every minute were used as a reference. The NSE coefficient of wind speed was 0.516 at the sampling time of 60 minutes, while the ones of other meteorological variables and canopy temperature were greater than 0.8. The pattern of daily CWSIs increased from 8:00 am, reached the maximum value at 12:00 pm, then decreased after 2:00 pm. The statistical analysis showed that the data collection at 11:40 am produced the closest CWSI value to the daily average of CWSI, which indicates that just one time of measurement could be representative throughout the day. Overall, the findings of this study contributes to the economical and convenient method of quantifying CWSIs and irrigation management.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.5
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• pp.23-31
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• 2019

Crop response to weather and internal water pressure changes is more sensitive to crop water stress than soil water content. Recently, its implementation to optimal irrigation scheduling has been receiving much attention. This study was conducted to determine and compare the theoretical crop water stress index (CWSI) using meterological data and canopy temperature collected from three different irrigation treatments, which were Tr-1 plot (rainfed), Tr-2 plot (50% of daily evapotranspiration (ET) irrigated) and Tr-3 plot (75% of daily evapotranspiration (ET) irrigated). The readings of canopy temperature and CWSI were significantly different among irrigation treatment schemes. The average canopy temperatures and CWSIs of Tr-1 and Tr-3 plots were $34.6^{\circ}C$ and $32.6^{\circ}C$, 0.79 and 0.64, respectively. Solar radiation had the biggest correlation with CWSI (R=0.68) which was followed by wind speed, relative humidity and air temperature. Overall, the findings of this study indicated that canopy temperatures and CWSIs could be further used for irrigation scheduling for crop growth.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.6
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• pp.820-826
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• 2018

Objective: The purpose of this retrospective study was to investigate the relationship between temperature-humidity index (THI), season, and conception rate (CR) of Holstein cows in central Taiwan. Methods: The mean performance and number of observations were statistically evaluated for various parameters, including age at first service, number of days open, gestation length, CR, and calving interval for different parities. Results: The results indicate that the mean age at first service was 493.2 days; the gestation length was similar across all cows of different parities, ranging from 275.1 to 280.7 days. The overall CR of all inseminations was significantly lower in multiparous cows ($47.26%{\pm}0.22%$) than in heifers ($57.14%{\pm}0.11%$) (p<0.05). At THI>72 and during the hot season (from June to November), CRs for multiparous cows were significantly reduced compared to that for heifers, while the ratio remained unchanged among heifers for all seasons. Conclusion: To achieve a high CR, lactating cows should be bred in winter and spring (from December to May) from the start of the seasonal breeding program, whereas the heifer should be allowed to breed in summer and fall under the subtropical climate in Taiwan.

• Journal of Astronomy and Space Sciences
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• v.33 no.2
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• pp.137-146
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• 2016

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.243-252
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• 2014

Many researches about the effect on politics, economics and Sociocultural phenomenon using the social media are in progress. Authors utilized NAVER Trend most famous web browsing service in korea, NAVER Blog social media, NAVER Cafe service and Open Data(API) and also used temperature, humidity index data of Korea Meteorological Administration. This study analyzed a change of the public's emotion in korea using Cluster analysis of vocabulary of taste among its of feelings and senses. K-means clustering was followed by decision of the number of groups which was used Chi-square goodness of fit test and ward analysis. Eight groups was made and it represented sensitive vocabulary. By Discriminant analysis, eight groups decided by Cluster analysis has 98.9% accuracy. The change of the public's emotion has capability to predict people's activity so they can share sensibility and a bond of sympathy developed between them.