• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.1-6
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• 2015

We investigate the propagation characteristics of a pulse laser in a time-of-flight laser range finder (TOF-LRF) system with variations in atmospheric conditions, such as temperature, pressure, relative humidity, and the concentration of $CO_2$. The measurement error of distance related with the group velocity change in the TOF-LRF system is analyzed by considering the refractive index of the standard atmosphere with variations in atmospheric conditions. The dependence of the pulse width broadening induced by chromatic dispersion of the standard atmosphere on the operating wavelength and the initial pulse width of the light sources is discussed. The transmission of air with variations in the relative humidity or the concentration of $CO_2$ is analyzed by using different values of absorption coefficients depending on the operation wavelength of the light source in the TOF-LRF system.

• Journal of the Korean Mathematical Society
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• v.47 no.2
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• pp.385-407
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• 2010

To study the relationship between the levels of chemical pollutants and the number of daily total hospital admissions for respiratory diseases and to find the effect of temperature/relative humidity on the admission number, Wong et al. [17] introduced the varying-coefficient single-index model (VCSIM). As pointed out, it is a popular multivariate nonparametric fitting technique. However, the tests of the model have not been very well developed. In this paper, based on the estimators obtained by the local linear technique, the average method and the one-step back-fitting technique in the VCSIM, the generalized likelihood ratio (GLR) tests for varying-coefficient parts on the VCSIM are established. Under the null hypotheses the new proposed GLR tests follow the $\chi^2$-distribution asymptotically with scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Simulations are conducted to evaluate the test procedure empirically. A real example is used to illustrate the performance of the testing approach.

• Journal of the Ergonomics Society of Korea
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• v.18 no.2
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• pp.25-34
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• 1999

The objective of this study is to evaluate the emotional change of a driver according to the change of temperature, humidity, $CO_2$ gas concentration and $C_4H_{10}$ gas concentration in the automobile by electroencephalogram(EEG) spectrum analysis. The experiment was performed in an automobile simulated shielding room with healthy volunteers(age : 18-31, male : 14, female : 7). The subject's emotion at every different condition was indexed 11-point scale(+5 : most pleasant, -5 : least pleasant). The emotion index at each condition resulted in as follows; in temperature $1.00(23.5^{\circ}C)$, $-2.33(30.5^{\circ}C)$, in humidity 1.50(45%), -1.50(65%), in $CO_2$ gas concentration 0.67(500ppm), -0.57(6,000ppm), in $C_4H_{10}$ gas concentration -0.25(0ppm), -2.75(1,200ppm). From EEG spectrum analysis, the average mean power frequency(MPF) value at each different condition was shown as follows; in temperature $5.48(23.5^{\circ}C)$, $4.06(30.5^{\circ}C)$, in humidity 11.03(45%), 3.03(65%), in $CO_2$ gas concentration 7.16(500ppm), 6.38(6,000ppm), in $C_4H_{10}$ gas concentration 10.21(0ppm), 2.87(1,200ppm). When the environment became unpleasant to the subject, all of the obtained MPF values were decreased. It was found that there is close agreement between subjective evaluation by subject's scaling and objective evaluation by EEG spectrum analysis at different environment. These results indicated that the EEG spectrum analysis is a proper method to assess emotional response of a driver in the changing automobile environment.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.129-136
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• 2022

The most important part of the smart livestock building system is to maintain a breeding environment so that livestock can grow to high quality despite changes in the internal and external atmospheric environment. Especially, it is very important to maintain the temperature and humidity in the livestock building because various diseases occur during the summer and winter. To manage the environment suitable for livestock, a smartfarm system for livestock building is applied, but it is very expensive. In this study, we propose a hardware design and control method for low cost system based on HMI and fuzzy control. To evaluate the performance of the proposed system, we did a simulation experiment in the atmospheric conditions of summer and winter. As a result, it showed the performance of minimizing the temperature and humidity stress of livestock. And when applied to the livestock building, the proposed system showed stable control performance even in the change of the external atmospheric environment. Therefore, as with these results, if proposed system in this study is applied to the smart farm system, it will be effective in managing the environment of livestock building.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.5
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• pp.85-91
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• 2020

In order to calculate the Crop Water Stress Index (CWSI), it is necessary to collect weather data (air temperature, humidity, wind speed and solar radiation) and canopy temperature. However, it is not always available to have necessary data sets for CWSI calculation. Therefore, this study was aimed to develop an easy and simple CWSI equation (CWSI_EE) using only two data, air and canopy temperatures. Infrared sensors and weather sensors were installed on apple and peach trees and nearby a study area and every ten-minute data were collected from June to October in 2018 and 2019, respectively. A relationship between air-canopy temperature difference and CWSI was statistically analyzed and used to develop CWSI_EE using the three dimensional Gaussian model. The performance of CWSI_EE against original CWSI showed R² and NSE to 0.780 and 0.710 for apple trees and R² and NSE to 0.884 and 0.866 for peach trees. This study found that the level of crop water stress could be easily calculated using CWSI_EE with only air and canopy temperature data.

• Korean journal of food and cookery science
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• v.11 no.5
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• pp.456-462
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• 1995

The work environment and 20 influencing variables in 20 conventional hospital foodservice systems were examined. Twenty hospitals with more than 500 beds in Seoul were surveyed to obtain data for study variables. The work environment index was measured by five objective measurements including noise (dB), light(Lux), temperature ($^{\circ}C$), humidity (％) and ventilation (mι/sec). Statistical methods used in this study were descriptive analysis and Pearson product moment correlation analysis. The number of beds, space of foodservice system, the proportion of dishwashing area space in foodservice system area, noise, humidity, and ventilation were significantly correlated to the work environment of the dishwashing area.

• Journal of Climate Change Research
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• v.3 no.2
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• pp.89-100
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• 2012

This study analyzes spatio-temporal variability of discomfort index for summer the during the past ten years(2001~2010) in the Korean Peninsula, and considers the application possibility of discomfort index as a preliminary data for various phenomenon of society based on the analysis. Discomfort index defined as daily representative value was estimated using hourly temperature and humidity data which are observed 60 weather stations managed by Korea Meteorological Administration. The result indicates that the discomfort index in summer keeps the level at which one feels unpleasant, and the level increased steadily as temperature is rising. And discomfort index in 3 pm and on August are the highest during the day and year. Gangwon-do have shown the lowest discomfort index among the provinces. Variability analysis of discomfort index due to climate changes can be used for making policies in various fields such as industry and public health field.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.3
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• pp.442-450
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• 2015

Climate temperature affects animal production. This study was conducted to evaluate whether climatic conditions affect beef carcass characteristics of Korean cattle steers. The monthly carcass characteristics of Korean cattle steers (n = 2,182,415) for 8 yr (2006 through 2013) were collected from the Korean Institute for Animal Products Quality Evaluation. Daily climate temperature (CT) and relative humidity (RH) data were collected from the Korean Meteorological Administration. Weather conditions in South Korea during summer were hot and humid, with a maximum temperature of $28.4^{\circ}C$ and a maximum RH of 91.4%. The temperature-humidity index (THI), calculated based on CT and RH, ranges from 73 to 80 during summer. Winter in South Korea was cold, with a minimum temperature of $-4.0^{\circ}C$ and a wind-chill temperature of $-6.2^{\circ}C$. Both marbling score (MS) and quality grade (QG) of Korean cattle steer carcasses were generally best (p<0.05) in autumn and worst in spring. A correlation analysis showed that MS and QG frequencies were not associated (p>0.05) with CT. Yield grade (YG) of Korean cattle steer carcasses was lowest (p<0.05) in winter (November to January) and highest in spring and summer (May to September). A correlation analysis revealed that YG frequency was strongly correlated ($r{\geq}0.71$; p<0.01) with CT and THI values. The rib eye area, a positive YG parameter, was not associated with CT. Backfat thickness (BT), a negative YG factor, was highest in winter (November and December). The BT was strongly negatively correlated ($r{\leq}-0.74$; p<0.01) with CTs. Therefore, the poor YG during winter is likely due in part to the high BT. In conclusion, YG in Korean cattle steer carcasses was worst in winter. QGs were not associated with winter or summer climatic conditions.

• Animal Bioscience
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• v.34 no.4
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• pp.567-574
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• 2021

Objective: In this study we investigated the effect of seasonal thermal stress on milk production and milk compositions between Holstein and Jersey dairy cows under the temperate-climate in Korea. Methods: A total of 9 Holstein lactating dairy cows (2.0±0.11 parity) which had a daily milk yield of 29.77±0.45 kg, and days in milk of 111.2±10.29 were selected similarly at the beginning of the experiments in each season. Also, a total of 9 Jersey lactating dairy cows (1.7±0.12 parity) which had a daily milk yield of 20.01±0.43 kg, and days in milk of 114.0±9.74 were selected similarly at the beginning of the experiments. Results: Results showed that the average ambient temperature (℃) and temperature-humidity index (THI) were higher in summer, and were lower in winter (p<0.05). The average relative humidity (RH, %) was higher in autumn than that of other seasons (p<0.05). Milk production was significantly decreased (Holstein 29.02 kg/d and Jersey 19.75 kg/d) in autumn than in other seasons (Holstein 30.14 kg/d and Jersey 20.96 kg/d). However, the milk production was negatively correlated in Holstein cows, and positively correlated in Jersey cows with THI values increased from 16 to 80. In addition, milk yield was increased by 15% in Holstein cows and decreased by 11% in Jersey cows with the THI values increased from 16 to 20. The fat and protein content percentage was significantly higher in Jersey milk than in Holstein milk, furthermore the fat and protein content yield was higher in Jersey cow milk than that of Holstein cow's milk with all THIs. Conclusion: From the study results, we concluded that Jersey cows might be less adaptable to low temperature of the winter, and this would have a negative impact on dairy farmer income since Korea's milk price estimation system places a higher value on milk yield than on milk compositions or sanitary grades.

• 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.